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Cancers, Volume 14, Issue 24 (December-2 2022) – 251 articles

Cover Story (view full-size image): Androgen deprivation therapy (ADT) is the principal therapy for advanced prostate cancer. ADT controls tumor growth by rapidly altering the prostate tumor microenvironment and subsequently inducing cancer cell death. ADT induces vascular damage and thereby reduces intratumoral blood flow, but the mechanism has long been elusive. This work, for the first time, functionally defines TNF as the mediator of castration-induced vascular damage in prostate tumors. This pathological response to androgen deprivation—beginning with endothelial cell apoptosis and increased vessel permeability and culminating in hypoxia—indirectly contributes to prostate cancer regression. Since TNF is also a critical death receptor ligand for prostate epithelial cells, we propose that TNF is a multi-purpose, comprehensive signal that mediates prostate cancer regression following androgen deprivation. View this paper
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11 pages, 1409 KiB  
Review
Best Supportive Care of the Patient with Oesophageal Cancer
by Rita Carrilho Pichel, Alexandra Araújo, Vital Da Silva Domingues, Jorge Nunes Santos, Elga Freire, Ana Sofia Mendes, Raquel Romão and António Araújo
Cancers 2022, 14(24), 6268; https://doi.org/10.3390/cancers14246268 - 19 Dec 2022
Cited by 3 | Viewed by 2671
Abstract
Background: Oesophageal cancer patients have poor survival, and most are unfit for curative or systemic palliative treatment. This article aims to review the best supportive care for oesophageal cancer, focusing on the management of its most frequent or distinctive symptoms and complications. Methods: [...] Read more.
Background: Oesophageal cancer patients have poor survival, and most are unfit for curative or systemic palliative treatment. This article aims to review the best supportive care for oesophageal cancer, focusing on the management of its most frequent or distinctive symptoms and complications. Methods: Evidence-based review on palliative supportive care of oesophageal cancer, based on Pubmed search for relevant clinical practice guidelines, reviews and original articles, with additional records collected from related articles suggestions, references and societies recommendations. Results: We identified 1075 records, from which we screened 138 records that were related to oesophageal cancer supportive care, complemented with 48 additional records, finally including 60 records. This review summarizes the management of oesophageal cancer-related main problems, including dysphagia, malnutrition, pain, nausea and vomiting, fistula and bleeding. In recent years, several treatments have been developed, while optimal management is not yet standardized. Conclusion: This review contributes toward improving supportive care and decision making for oesophageal cancer patients, presenting updated summary recommendations for each of their main symptoms. A robust body of evidence is still lacking, and the best supportive care decisions should be individualized and shared. Full article
(This article belongs to the Special Issue Quality of Life and Side Effects Management in Cancer Treatment)
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<p>Flowchart of selection of relevant evidence-based information on palliative supportive care of oesophageal cancer. * PubMed search heading: ((supportive care) OR (palliative)) AND ((oesophag *) OR (esophag *)) AND ((cancer) OR (carcinoma)), last executed on 25 August 2022.</p>
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<p>Oesophageal fistula. (<b>a</b>) Tracheo-oesophageal fistula (arrow) associated with pneumonia and lung abscess (*) (<b>b</b>) Squamous carcinoma of cervical oesophagus complicated with pneumomediastinum (arrow).</p>
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18 pages, 1231 KiB  
Review
Lipid Metabolism Heterogeneity and Crosstalk with Mitochondria Functions Drive Breast Cancer Progression and Drug Resistance
by Aurelien Azam and Nor Eddine Sounni
Cancers 2022, 14(24), 6267; https://doi.org/10.3390/cancers14246267 - 19 Dec 2022
Cited by 11 | Viewed by 3565
Abstract
Breast cancer (BC) is a heterogeneous disease that can be triggered by genetic alterations in mammary epithelial cells, leading to diverse disease outcomes in individual patients. The metabolic heterogeneity of BC enhances its ability to adapt to changes in the tumor microenvironment and [...] Read more.
Breast cancer (BC) is a heterogeneous disease that can be triggered by genetic alterations in mammary epithelial cells, leading to diverse disease outcomes in individual patients. The metabolic heterogeneity of BC enhances its ability to adapt to changes in the tumor microenvironment and metabolic stress, but unfavorably affects the patient’s therapy response, prognosis and clinical effect. Extrinsic factors from the tumor microenvironment and the intrinsic parameters of cancer cells influence their mitochondrial functions, which consequently alter their lipid metabolism and their ability to proliferate, migrate and survive in a harsh environment. The balanced interplay between mitochondria and fatty acid synthesis or fatty acid oxidation has been attributed to a combination of environmental factors and to the genetic makeup, oncogenic signaling and activities of different transcription factors. Hence, understanding the mechanisms underlying lipid metabolic heterogeneity and alterations in BC is gaining interest as a major target for drug resistance. Here we review the major recent reports on lipid metabolism heterogeneity and bring to light knowledge on the functional contribution of diverse lipid metabolic pathways to breast tumorigenesis and therapy resistance. Full article
(This article belongs to the Special Issue Mitochondrial Functions in Cancer)
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<p>Different scales and factors of heterogeneity in breast cancer. Heterogeneity in breast cancer might be dependent on individuals, the environment and cell types within the tumor microenvironment. For each scale, main factors of heterogeneity (time, genetics and environment) may vary in their impacts and approach. For example, a single genetic mutation can be common to two unrelated women but differentially expressed within their respective tumors.</p>
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<p>Known lipid metabolism adaptations in BC cells. Breast cancer cells can develop and undergo adaptation of their diverse lipid metabolic pathways to cover their high needs for energy and biomass synthesis. Main proteins responsible for these metabolic changes are depicted here and are deciphered as intrinsic proteins (in purple) or derived from the TME (in orange). Major effects of lipid metabolic pathways on BC progression are indicated by green arrows. Metabolic stress includes nutrient deprivation, hypoxia and endoplasmic reticulum stress. Upregulated and downregulated pathways described above illustrate an inherent large heterogeneity of lipid metabolism in BC. ACLY: ATP-citrate lyase, ACSL4: long-chain acyl-coenzyme A synthetase 4, ACSS2: acyl-coenzyme A synthetase 2, CAA: cancer-associated adipocytes, CAF: cancer-associated fibroblasts, BC: breast cancer, CD36: fatty acid-translocase, CPT1: carnitine palmitoyltransferase 1, FAPBs: fatty acid-binding proteins, FASN: fatty acid synthase, LPCATs: lysophospholipid acyltransferases, MUFA: monounsaturated fatty acids, p53: tumor protein 53, PUFA: polyunsaturated fatty acids, SCD1: stearoyl-CoA desaturase 1, SFA: saturated fatty acids.</p>
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16 pages, 1322 KiB  
Article
Development and Psychometric Evaluation of Healthcare Access Measures among Women with Ovarian Cancer
by Tomi Akinyemiju, Ashwini Joshi, April Deveaux, Lauren E. Wilson, Dandan Chen, Clare Meernik, Malcolm Bevel, Jen Gathings, Laura Fish, Nadine Barrett, Valarie Worthy, Xiomara Boyce, Keshia Martin, Corre Robinson, Maria Pisu, Margaret Liang, Arnold Potosky, Bin Huang, Kevin Ward, Maria J. Schymura, Andrew Berchuck and Bryce B. Reeveadd Show full author list remove Hide full author list
Cancers 2022, 14(24), 6266; https://doi.org/10.3390/cancers14246266 - 19 Dec 2022
Cited by 2 | Viewed by 2294
Abstract
Several proposed theoretical frameworks have defined the complex nature of healthcare access (HCA) [...] Full article
(This article belongs to the Section Cancer Epidemiology and Prevention)
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<p>Steps to develop HCA Accommodation and Acceptability Measures for diverse cancer survivors.</p>
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<p>A Two-Factor Model of Accommodation Dimension.</p>
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<p>A Five-Factor Higher-Order Model of Acceptability Dimension.</p>
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10 pages, 583 KiB  
Review
Surgical Aspects of Intrahepatic Cholangiocarcinoma
by Amram Kupietzky and Arie Ariche
Cancers 2022, 14(24), 6265; https://doi.org/10.3390/cancers14246265 - 19 Dec 2022
Cited by 7 | Viewed by 1987
Abstract
Intrahepatic cholangiocarcinoma (ICC) is a rare and aggressive malignancy. It originates from the bile ducts and is the second most common primary cancer of the liver. Surgery is considered the only curative treatment of ICC, offering the best chance for long-term survival. The [...] Read more.
Intrahepatic cholangiocarcinoma (ICC) is a rare and aggressive malignancy. It originates from the bile ducts and is the second most common primary cancer of the liver. Surgery is considered the only curative treatment of ICC, offering the best chance for long-term survival. The purpose of this article is to review the available literature on ICC, with a focus on the various aspects of the surgical care in this potentially lethal malignancy. Full article
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<p>Lymph node locations for ICC lymphadenectomy.</p>
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21 pages, 4416 KiB  
Review
A Multi-Disciplinary Approach to Diagnosis and Treatment of Radionecrosis in Malignant Gliomas and Cerebral Metastases
by Julian Mangesius, Stephanie Mangesius, Matthias Demetz, Christian Uprimny, Gianpaolo Di Santo, Malik Galijasevic, Danijela Minasch, Elke R. Gizewski, Ute Ganswindt, Irene Virgolini, Claudius Thomé, Christian F. Freyschlag and Johannes Kerschbaumer
Cancers 2022, 14(24), 6264; https://doi.org/10.3390/cancers14246264 - 19 Dec 2022
Cited by 9 | Viewed by 2395
Abstract
Radiation necrosis represents a potentially devastating complication after radiation therapy in brain tumors. The establishment of the diagnosis and especially the differentiation from progression and pseudoprogression with its therapeutic implications requires interdisciplinary consent and monitoring. Herein, we want to provide an overview of [...] Read more.
Radiation necrosis represents a potentially devastating complication after radiation therapy in brain tumors. The establishment of the diagnosis and especially the differentiation from progression and pseudoprogression with its therapeutic implications requires interdisciplinary consent and monitoring. Herein, we want to provide an overview of the diagnostic modalities, therapeutic possibilities and an outlook on future developments to tackle this challenging topic. The aim of this report is to provide an overview of the current morphological, functional, metabolic and evolving imaging tools described in the literature in order to (I) identify the best criteria to distinguish radionecrosis from tumor recurrence after the radio-oncological treatment of malignant gliomas and cerebral metastases, (II) analyze the therapeutic possibilities and (III) give an outlook on future developments to tackle this challenging topic. Additionally, we provide the experience of a tertiary tumor center with this important issue in neuro-oncology and provide an institutional pathway dealing with this problem. Full article
(This article belongs to the Special Issue Novel Therapeutic Strategies for Neuro-Oncology)
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<p>Diagnostic and therapeutic algorithm for suspected tumor recurrence or radiation necrosis. In cases of tumor enlargement on MRI or neurologic symptoms suggestive of tumor progression, a short-term MRI scan is performed using advanced new techniques. If the results are inconclusive, a dynamic <sup>18</sup>F-FET PET scan or, in selected cases, a biopsy or surgical resection may be performed. All results are discussed in an interdisciplinary tumor board (with specialists in neurology, neurosurgery, neuroradiology, nuclear medicine and radiation oncology), where a final decision is made regarding the differential diagnosis of radiation necrosis and/or progression and the assignment of further diagnostic and therapeutic steps. Radiation necrosis not responsive to corticosteroids can be treated with bevacizumab or surgical resection in rare cases. Abbreviations: diffusion-weighted images (DWI), T2-turbo spin echo (T2-TSE; T<sub>2</sub>w), fluid-attenuated inversion recovery (FLAIR), 3D T1-Magnetization-Prepared Rapid Gradient-Echo (MPRAGE; 3D-T<sub>1</sub>w), without and after (−/+), contrast agent (CA), T1-sampling perfection with application-optimized contrast using different flip angle evolutions (T1-SPACE; in case of metastases), susceptibility-weighted imaging (SWI), perfusion-weighted imaging (PWI; in case of glioblastoma) and Hydrogen 1 magnetic resonance spectroscopy (1H-MRS).</p>
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<p>Example of radionecrosis in the parietal lobe of the left hemisphere after radiosurgery of a metastasis from non-small-cell lung cancer with 20 Gy on the 80% PTV marginal isodose: no diffusion restriction on diffusion-weighted images, the mean ADC in radionecrosis is not significantly different between the enhancing area and the neighboring area (<b>A</b>,<b>B</b>), non-correlation between the boundaries of the lesion seen on enhanced T1-weighted and T2-weighted imaging (“T1/T2 mismatch”) (<b>C</b>), non-specific morphological appearances of contrast enhancement in post-contrast T1-weighted images (<b>D</b>), which increases diffusely after 80 min in the delayed contrast extravasation MRI (<b>E</b>), as the contrast agent accumulates over time in necrotic tissue, color-coded in red in the treatment response assessment map (TRAM) (<b>F</b>), decreased rCBV as a result of occlusive vasculopathy leading to ischemia (<b>G</b>) and low tracer uptake in in the <sup>18</sup>F-FET-PET examination (<b>H</b>). The lesion is located within the high dose area of the radiation therapy (<b>I</b>).</p>
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<p>Assessment of treatment effect in (1H) Magnetic Resonance Spectroscopy. (<b>A</b>): True progression in a case of glioblastoma: reduced NAA, increased Cho. Cho/NAA ratio over cut-off, with a mean of 2.72. (<b>B</b>): Radionecrosis after radiosurgical treatment of a metastasis: Cho/NAA ratio with a mean of 1.46. (<b>C</b>): Pseudoprogression (glioblastoma): Cho/NAA ratio under 1.47–2.11 and Cho/Cr ration under 0.82–2.25. (<b>D</b>): Mixed image between pseudoprogression and true progression in a glioblastoma case.</p>
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<p>Example of both radiation necrosis and tumor progression in a case of glioblastoma after radiochemotherapy. (<b>A</b>): structural MRI, (<b>B</b>): FET-PET, (<b>C</b>): perfusion-weighted MRI, (<b>D</b>): delayed contrast MRI.</p>
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<p>(<b>A</b>): Typical appearance of an RN in a patient treated due to progressive CE mass after resection and focal radiotherapy for a melanoma BM. Necrotic areas and shadows of vessels without tumor cells. HE staining 20×. (<b>B</b>): Necrotic tissue adjacent to vital tumor cells with eosinophilic cytoplasm in a patient with NSCLC. Tumor cell nuclei are variable in size. HE staining.</p>
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16 pages, 1882 KiB  
Article
Comparing Genetic Risk and Clinical Risk Classification in Luminal-like Breast Cancer Patients Using a 23-Gene Classifier
by Chi-Cheng Huang, Ting-Hao Chen, Liang-Chih Liu, Chiun-Sheng Huang, Ji-An Liang, Yu-Chen Hsu, Chia-Ming Hsieh, Sean-Lin Huang, Kuan-Hui Shih and Ling-Ming Tseng
Cancers 2022, 14(24), 6263; https://doi.org/10.3390/cancers14246263 - 19 Dec 2022
Viewed by 2325
Abstract
Background: A 23-gene classifier has been developed based on gene expression profiles of Taiwanese luminal-like breast cancer. We aim to stratify risk of relapse and identify patients who may benefit from adjuvant chemotherapy based on genetic model among distinct clinical risk groups. Methods: [...] Read more.
Background: A 23-gene classifier has been developed based on gene expression profiles of Taiwanese luminal-like breast cancer. We aim to stratify risk of relapse and identify patients who may benefit from adjuvant chemotherapy based on genetic model among distinct clinical risk groups. Methods: There were 248 luminal (hormone receptor-positive and human epidermal growth factor receptor II-negative) breast cancer patients with 23-gene classifier results. Using the modified Adjuvant! Online definition, clinical high/low-risk groups were tabulated with the genetic model. The primary endpoint was a recurrence-free interval (RFI) at 5 years. Results: There was a significant difference between the high/low-risk groups defined by the 23-gene classifier for the 5-year prognosis of recurrence (16 recurrences in high-risk and 3 recurrences in low-risk; log-rank test: p < 0.0001). Among the clinically high-risk group, the 5-year RFI of high risk defined by the 23-gene classifier was significantly higher than that of the low-risk group (15 recurrences in high-risk and 2 recurrences in low-risk; log-rank test: p < 0.0001). Conclusion: This study showed that 23-gene classifier can be used to stratify clinically high-risk patients into distinct survival patterns based on genomic risks and displays the potentiality to guide adjuvant chemotherapy. The 23-gene classifier can provide a better estimation of breast cancer prognosis which can help physicians make a better treatment decision. Full article
(This article belongs to the Special Issue Genomics and Bioinformatics Based Analysis of Cancer)
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Graphical abstract

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<p>Consolidated standard of reporting trials (CONSORT) for this study to perform the workflow of this study.</p>
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<p>The boxplot for the visualization of 23-gene expression divided by recurrence status. Red: recurrence; blue: no recurrence; x-axis: 23 genes; y-axis: gene expression.</p>
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<p>Kaplan–Meier plot for RFI within 5 years to compare the partition of 23-gene classifier. Blue: genetic low-risk group; red: genetic high-risk group.</p>
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<p>Kaplan–Meier plot for RFI within 5 years to compare the partition of clinical risk. Blue: clinically low-risk group; red: clinically high-risk group.</p>
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<p>Kaplan–Meier plot for RFI within 5 years in clinically high-risk group to compare the partition of 23-gene classifier. Blue: genetic low-risk group; red: genetic high-risk group.</p>
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<p>Kaplan–Meier plot for RFI within 5 years in clinically low-risk group to compare the partition of 23-gene classifier. Blue: genetic low-risk group; red: genetic high-risk group.</p>
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<p>Kaplan–Meier plot for the RFI among patients without chemotherapy within 5 years to compare the partition of clinical risk. Blue: clinically low-risk group; red: clinically high-risk group.</p>
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<p>Kaplan–Meier plot for the RFI among patients without chemotherapy within 5 years to compare the partition of 23-gene classifier. Blue: genetic low-risk group; red: genetic high-risk group.</p>
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21 pages, 5134 KiB  
Article
A Label-Free Proteomic Approach for the Identification of Biomarkers in the Exosome of Endometrial Cancer Serum
by Eduardo Sommella, Valeria Capaci, Michelangelo Aloisio, Emanuela Salviati, Pietro Campiglia, Giuseppe Molinario, Danilo Licastro, Giovanni Di Lorenzo, Federico Romano, Giuseppe Ricci, Lorenzo Monasta and Blendi Ura
Cancers 2022, 14(24), 6262; https://doi.org/10.3390/cancers14246262 - 19 Dec 2022
Cited by 14 | Viewed by 3194
Abstract
Endometrial cancers (ECs) are mostly adenocarcinomas arising from the inner part of the uterus. The identification of serum biomarkers, either soluble or carried in the exosome, may be useful in making an early diagnosis. We used label-free quantification mass spectrometry (LFQ-MS)-based proteomics to [...] Read more.
Endometrial cancers (ECs) are mostly adenocarcinomas arising from the inner part of the uterus. The identification of serum biomarkers, either soluble or carried in the exosome, may be useful in making an early diagnosis. We used label-free quantification mass spectrometry (LFQ-MS)-based proteomics to investigate the proteome of exosomes in the albumin-depleted serum from 12 patients with EC, as compared to 12 healthy controls. After quantification and statistical analysis, we found significant changes in the abundance (p < 0.05) of 33 proteins in EC vs. control samples, with a fold change of ≥1.5 or ≤0.6. Validation using Western blotting analysis in 36 patients with EC as compared to 36 healthy individuals confirmed the upregulation of APOA1, HBB, CA1, HBD, LPA, SAA4, PF4V1, and APOE. A multivariate logistic regression model based on the abundance of these proteins was able to separate the controls from the EC patients with excellent sensitivity levels, particularly for stage 1 ECs. The results show that using LFQ-MS to explore the specific proteome of serum exosomes allows for the identification of biomarkers in EC. These observations suggest that PF4V1, CA1, HBD, and APOE represent biomarkers that are able to reach the clinical stage, after a validation phase. Full article
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<p>CD 63 and CD9 common exosome markers. Western blotting in exosome of three C (control) and three EC (endometrial cancers).</p>
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<p>(<b>A</b>–<b>H</b>) Western blotting analyses of exosomes for eight proteins APOA1, HBB, CA1, HBD, LPA, SAA4, PF4V1, and APOE in controls (C) and endometrial cancer (EC) patients. The intensity of immunostained bands was normalized against the total protein intensities measured from the same blot stained with Red Ponceau. The graph shows the relative abundance of the proteins in control and endometrial cancer exosomes. Results are shown as a histogram (<span class="html-italic">p</span> &lt; 0.05), with each bar representing mean ± standard deviation.</p>
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<p>(<b>A</b>–<b>H</b>) Western blotting analyses of exosomes for eight proteins APOA1, HBB, CA1, HBD, LPA, SAA4, PF4V1, and APOE in controls (C) and endometrial cancer (EC) patients. The intensity of immunostained bands was normalized against the total protein intensities measured from the same blot stained with Red Ponceau. The graph shows the relative abundance of the proteins in control and endometrial cancer exosomes. Results are shown as a histogram (<span class="html-italic">p</span> &lt; 0.05), with each bar representing mean ± standard deviation.</p>
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<p>(<b>A</b>–<b>H</b>) Western blotting analyses of exosomes for eight proteins APOA1, HBB, CA1, HBD, LPA, SAA4, PF4V1, and APOE in controls (C) and endometrial cancer (EC) patients. The intensity of immunostained bands was normalized against the total protein intensities measured from the same blot stained with Red Ponceau. The graph shows the relative abundance of the proteins in control and endometrial cancer exosomes. Results are shown as a histogram (<span class="html-italic">p</span> &lt; 0.05), with each bar representing mean ± standard deviation.</p>
Full article ">Figure 2 Cont.
<p>(<b>A</b>–<b>H</b>) Western blotting analyses of exosomes for eight proteins APOA1, HBB, CA1, HBD, LPA, SAA4, PF4V1, and APOE in controls (C) and endometrial cancer (EC) patients. The intensity of immunostained bands was normalized against the total protein intensities measured from the same blot stained with Red Ponceau. The graph shows the relative abundance of the proteins in control and endometrial cancer exosomes. Results are shown as a histogram (<span class="html-italic">p</span> &lt; 0.05), with each bar representing mean ± standard deviation.</p>
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<p>Western blotting of proteins APOA1, APOE, CA1, HBB, HBD, LPA, PF4V1, and SAA4 present in EC.</p>
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<p>Sensitivity and specificity plot of the final model with the outcome EC patients vs. controls.</p>
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<p>Receiver operating characteristics curve of the final model with the outcome EC patients vs. controls.</p>
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<p>Sensitivity and specificity plot of the final model with the outcome Stage 1 EC patients vs. controls.</p>
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<p>Receiver operating characteristics curve of the final model with the outcome Stage 1 EC patients vs. controls.</p>
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<p>Sensitivity and specificity plot of the final model with the outcome Advanced Stage EC patients vs. controls.</p>
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<p>Receiver operating characteristics curve of the final model with the outcome Advanced Stage EC patients vs. controls.</p>
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<p>gProfiler classification of proteins in the EC serum exosomes according to their molecular function, biological processes, and cellular component.</p>
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<p>Network build-up from one of the most significant bio-functions: (1) activation of phagocytosis; (2) binding of antigen-presenting cells; (3) cell movement of leukocytes; (4) migration of cells.</p>
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13 pages, 1797 KiB  
Article
Integration of Clinical and CT-Based Radiomic Features for Pretreatment Prediction of Pathologic Complete Response to Neoadjuvant Systemic Therapy in Breast Cancer
by Huei-Yi Tsai, Tsung-Yu Tsai, Chia-Hui Wu, Wei-Shiuan Chung, Jo-Ching Wang, Jui-Sheng Hsu, Ming-Feng Hou and Ming-Chung Chou
Cancers 2022, 14(24), 6261; https://doi.org/10.3390/cancers14246261 - 19 Dec 2022
Cited by 6 | Viewed by 2354
Abstract
The purpose of the present study was to examine the potential of a machine learning model with integrated clinical and CT-based radiomics features in predicting pathologic complete response (pCR) to neoadjuvant systemic therapy (NST) in breast cancer. Contrast-enhanced CT was performed in 329 [...] Read more.
The purpose of the present study was to examine the potential of a machine learning model with integrated clinical and CT-based radiomics features in predicting pathologic complete response (pCR) to neoadjuvant systemic therapy (NST) in breast cancer. Contrast-enhanced CT was performed in 329 patients with breast tumors (n = 331) before NST. Pyradiomics was used for feature extraction, and 107 features of seven classes were extracted. Feature selection was performed on the basis of the intraclass correlation coefficient (ICC), and six ICC thresholds (0.7–0.95) were examined to identify the feature set resulting in optimal model performance. Clinical factors, such as age, clinical stage, cancer cell type, and cell surface receptors, were used for prediction. We tried six machine learning algorithms, and clinical, radiomics, and clinical–radiomics models were trained for each algorithm. Radiomics and clinical–radiomics models with gray level co-occurrence matrix (GLCM) features only were also built for comparison. The linear support vector machine (SVM) regression model trained with radiomics features of ICC ≥0.85 in combination with clinical factors performed the best (AUC = 0.87). The performance of the clinical and radiomics linear SVM models showed statistically significant difference after correction for multiple comparisons (AUC = 0.69 vs. 0.78; p < 0.001). The AUC of the radiomics model trained with GLCM features was significantly lower than that of the radiomics model trained with all seven classes of radiomics features (AUC = 0.85 vs. 0.87; p = 0.011). Integration of clinical and CT-based radiomics features was helpful in the pretreatment prediction of pCR to NST in breast cancer. Full article
(This article belongs to the Special Issue Recent Advances in Oncology Imaging)
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<p>Flowchart of data collection and partition. Data partition was performed using a semi-random selection. The whole dataset was firstly separated into the pCR (+) and pCR (−) groups, followed by random selection of 15% data from the two groups. pCR: pathologic complete response; CECT: contrast-enhanced computed tomography; CT: computed tomography; FOV: field of view.</p>
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<p>An example of image segmentation. Contrast-enhanced axial (<b>A</b>) and coronal (<b>C</b>) images show an enhanced tumor in the right breast. Tumor segmentation was performed using the GrowCut semi-automatic segmentation method of 3D-Slicer software (<b>B</b>,<b>D</b>). The 3D contour of the tumor is shown in (<b>E</b>).</p>
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<p>Linear SVM model performance of different radiomic feature sets selected on the basis of different ICC thresholds. ICC = intraclass correlation coefficient; AUC: area under the ROC curve.</p>
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<p>Radiomic features with intraclass correlation coefficient ≥0.85: 11 shape-based, 10 first-order, 12 GLCM, seven GLDM, eight GLRLM, four GLSZM, and one NGTDM features.</p>
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<p>Receiver operating characteristic curves of the clinical, radiomics (GLCM), radiomics (all classes of features), and clinical–radiomics (all classes of features) linear SVM models in the training and testing sets. In the testing set, the AUC values were 0.69, 0.77, 0.78, and 0.87 for clinical, radiomics (GLCM), radiomics (all), and clinical–radiomics (all), respectively.</p>
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<p>Top 10 important features of the integration linear SVM model, consisting of three clinical (red) and seven radiomics features (blue). ER: estrogen receptor; HER2: human epidermal growth factor receptor 2; PR: progesterone receptor.</p>
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19 pages, 4310 KiB  
Article
Therapeutic Target Identification and Inhibitor Screening against Riboflavin Synthase of Colorectal Cancer Associated Fusobacterium nucleatum
by Norah A. Alturki, Mutaib M. Mashraqi, Khurshid Jalal, Kanwal Khan, Zarrin Basharat and Ahmad Alzamami
Cancers 2022, 14(24), 6260; https://doi.org/10.3390/cancers14246260 - 19 Dec 2022
Cited by 11 | Viewed by 2935
Abstract
Colorectal cancer (CRC) ranks third among all cancers in terms of prevalence. There is growing evidence that gut microbiota has a role in the development of colorectal cancer. Fusobacterium nucleatum is overrepresented in the gastrointestinal tract and tumor microenvironment of patients with CRC. [...] Read more.
Colorectal cancer (CRC) ranks third among all cancers in terms of prevalence. There is growing evidence that gut microbiota has a role in the development of colorectal cancer. Fusobacterium nucleatum is overrepresented in the gastrointestinal tract and tumor microenvironment of patients with CRC. This suggests the role of F. nucleatum as a potential risk factor in the development of CRC. Hence, we aimed to explore whole genomes of F. nucleatum strains related to CRC to predict potential therapeutic markers through a pan-genome integrated subtractive genomics approach. In the current study, we identified 538 proteins as essential for F. nucleatum survival, 209 non-homologous to a human host, and 12 as drug targets. Eventually, riboflavin synthase (RiS) was selected as a therapeutic target for further processing. Three different inhibitor libraries of lead-like natural products, i.e., cyanobactins (n = 237), streptomycins (n = 607), and marine bacterial secondary metabolites (n = 1226) were screened against it. After the structure-based study, three compounds, i.e., CMNPD3609 (−7.63) > Malyngamide V (−7.03) > ZINC06804365 (−7.01) were prioritized as potential inhibitors of F. nucleatum. Additionally, the stability and flexibility of these compounds bound to RiS were determined via a molecular dynamics simulation of 50 ns. Results revealed the stability of these compounds within the binding pocket, after 5 ns. ADMET profiling showed compounds as drug-like, non-permeable to the blood brain barrier, non-toxic, and HIA permeable. Pan-genomics mediated drug target identification and the virtual screening of inhibitors is the preliminary step towards inhibition of this pathogenic oncobacterium and we suggest mouse model experiments to validate our findings. Full article
(This article belongs to the Special Issue Bacterial, Viral and Parasitic Pathogens and Colorectal Cancer)
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<p>Pan-genome analysis of 14 <span class="html-italic">F. nucleatum</span> strains related to CRC.</p>
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<p>Phylogenetic tree depicting (<b>A</b>) Pan-genome phylogeny of 14 CRC related <span class="html-italic">F. nucleatum</span> strains used in this study (<b>B</b>) Core genome phylogeny of studied <span class="html-italic">F. nucleatum</span> strains. 1 = <span class="html-italic">F. nucleatum</span> CC53; 2 = <span class="html-italic">F. nucleatum</span> Fn10-CTX3; 3 = <span class="html-italic">F. nucleatum</span> Fn146CP; 4 = <span class="html-italic">F. nucleatum</span> Fn173CP; 5 = <span class="html-italic">F. nucleatum</span> Fn3760T; 6 = <span class="html-italic">F. nucleatum</span> FnS0431; 7 = <span class="html-italic">F. nucleatum</span> subsp. animalis strain P2_CP; 8 = <span class="html-italic">F. nucleatum</span> subsp. animalis strain P2_LM; 9 = <span class="html-italic">F. nucleatum</span> subsp. animalis strain THCT5A4; 10 = <span class="html-italic">F. nucleatum</span> subsp. animalis strain THCT6B3; 11 = <span class="html-italic">F. nucleatum</span> subsp. animalis strain THCT7A2; 12 = <span class="html-italic">F. nucleatum</span> subsp. polymorphum strain THCT7E2; 13 = <span class="html-italic">F. nucleatum</span> subsp. polymorphum strain THCT15E1; 14 = <span class="html-italic">F. nucleatum</span> subsp. vincentii strain THCT14A3.</p>
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<p>Functional enrichment analysis of identified genome of <span class="html-italic">F. nucleatum</span> strains.</p>
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<p>Representation of the selected drug target as a solo protein and part of its network (<b>A</b>) 3D structure of RiS retrieved from AlphaFold (<b>B</b>) PPI analysis of RiS.</p>
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<p>Molecular docking analysis of (<b>A</b>) RiS-CMNPD3609, (<b>B</b>) RiS-Malyngamide V, (<b>C</b>) RiS-ZINC06804365, and (<b>D</b>) RiS-control.</p>
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<p>MD simulation for shortlisted compounds, depicting (<b>A</b>) RMSD (<b>B</b>) RMSF (<b>C</b>) Radius of gyration and (<b>D</b>) Hydrogen bonds.</p>
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13 pages, 1014 KiB  
Article
Impact of Mobilization Strategies on Peripheral Blood Stem Cell Collection Efficiency and Product Quality: A Retrospective Single-Center Study
by Patricija Rajsp, Manuela Branka, Nelly Besson, Andreas Tanzmann and Nina Worel
Cancers 2022, 14(24), 6259; https://doi.org/10.3390/cancers14246259 - 19 Dec 2022
Cited by 4 | Viewed by 3244
Abstract
Autologous stem cell transplantation is routinely used in the management of several hematological diseases, solid tumors, and immune disorders. Peripheral blood stem cell (PBSC) collection performed by apheresis is the preferred source of stem cells. In this study, the potential impact of mobilization [...] Read more.
Autologous stem cell transplantation is routinely used in the management of several hematological diseases, solid tumors, and immune disorders. Peripheral blood stem cell (PBSC) collection performed by apheresis is the preferred source of stem cells. In this study, the potential impact of mobilization regimens on the performance of the Spectra Optia® continuous mononuclear cell collection system was evaluated. We performed a retrospective data analysis for patients undergoing autologous PBSC collection at the Medical University Vienna, Vienna General Hospital between September 2016 and June 2018. Collections were divided into two main groups according to the mobilization regimen received: without (210 collections) or with (99 collections) plerixafor. Assessed variables included product characteristics and collection efficiency (CE). Overall, product characteristics were similar between the groups. Median CD34+ CE2 was 50.1% versus 53.0%, and CE1 was 66.9% versus 69.9% following mobilization without and with plerixafor, respectively; the difference was not statistically significant. Simple linear regression showed a very weak positive correlation between the mobilization method and CE1 or CE2 (mobilization with plerixafor increased CE2 by 4.106%). In conclusion, the Spectra Optia® apheresis system led to high CE and a good quality of PBSC products when mobilization regimens with or without plerixafor were used. Full article
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<p>Correlations between pre-apheresis CD34+ cell count and CD34+ cells collected per liter of blood processed (<b>a</b>) overall and (<b>b</b>) by mobilization regimen. G-CSF, granulocyte colony-stimulating factor; CT, chemotherapy.</p>
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<p>Distribution of individual CE1 (<b>a</b>,<b>c</b>) and CE2 (<b>b</b>,<b>d</b>) values by mobilization regimen (<b>a</b>,<b>b</b>) and subgroup (<b>c</b>,<b>d</b>). CE, collection efficiency; Q1, first quartile; Q3, third quartile; G-CSF, granulocyte colony-stimulating factor; CT, chemotherapy. Notes: Error bars represent 95% confidence intervals. Outliers (◦) are defined as values lower than Q1-1.5*interquartile range or higher than Q3 + 1.5*interquartile range. Extreme outliers (*) are defined as values lower than Q1-3*interquartile range or higher than Q3 + 3*interquartile range.</p>
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16 pages, 822 KiB  
Review
Natural Blockers of PD-1/PD-L1 Interaction for the Immunotherapy of Triple-Negative Breast Cancer-Brain Metastasis
by Maryam Nakhjavani and Sarah Shigdar
Cancers 2022, 14(24), 6258; https://doi.org/10.3390/cancers14246258 - 19 Dec 2022
Cited by 6 | Viewed by 4246
Abstract
The limited treatment options for triple-negative breast cancer with brain metastasis (TNBC-BM) have left the door of further drug development for these patients wide open. Although immunotherapy via monoclonal antibodies has shown some promising results in several cancers including TNBC, it cannot be [...] Read more.
The limited treatment options for triple-negative breast cancer with brain metastasis (TNBC-BM) have left the door of further drug development for these patients wide open. Although immunotherapy via monoclonal antibodies has shown some promising results in several cancers including TNBC, it cannot be considered the most effective treatment for brain metastasis. This is due to the protective role of the blood–brain barrier (BBB) which limits the entrance of most drugs, especially the bulky ones such as antibodies, to the brain. For a drug to traverse the BBB via passive diffusion, various physicochemical properties should be considered. Since natural medicine has been a key inspiration for the development of the majority of current medicines, in this paper, we review several naturally-derived molecules which have the potential for immunotherapy via blocking the interaction of programmed cell death protein-1 (PD-1) and its ligand, PD-L1. The mechanism of action, physicochemical properties and pharmacokinetics of these molecules and their theoretical potential to be used for the treatment of TNBC-BM are discussed. Full article
(This article belongs to the Special Issue Immunotherapy of Triple-Negative Breast Cancer)
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<p>Chemical structure of: (<b>a</b>) apigenin (API) and cosmosiin (COS); (<b>b</b>) kaempferol (KMF) and kaempferol 7-O-rhamnoside (KFR); (<b>c</b>) quercetin (QUE); (<b>d</b>) eriodictyol (ERI) and fisetin (FIS); (<b>e</b>) 1-caffeoylquinic acid (1-CQA), 3-caffeoylquinic acid (3-CQA), 4-caffeoylquinic acid (4-CQA), and 5-caffeoylquinic acid (5-CQA); (<b>f</b>) glyasperin C (GC); (<b>g</b>) ellagic acid (EA); (<b>h</b>) gramicidin S (GS); and (<b>i</b>) rifabutin (RIF).</p>
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33 pages, 1170 KiB  
Review
Kinase Inhibitors in the Treatment of Ovarian Cancer: Current State and Future Promises
by Aikaterini Skorda, Marie Lund Bay, Sampsa Hautaniemi, Alexandra Lahtinen and Tuula Kallunki
Cancers 2022, 14(24), 6257; https://doi.org/10.3390/cancers14246257 - 19 Dec 2022
Cited by 13 | Viewed by 4606
Abstract
Ovarian cancer is the deadliest gynecological cancer, the high-grade serous ovarian carcinoma (HGSC) being its most common and most aggressive form. Despite the latest therapeutical advancements following the introduction of vascular endothelial growth factor receptor (VEGFR) targeting angiogenesis inhibitors and poly-ADP-ribose-polymerase (PARP) inhibitors [...] Read more.
Ovarian cancer is the deadliest gynecological cancer, the high-grade serous ovarian carcinoma (HGSC) being its most common and most aggressive form. Despite the latest therapeutical advancements following the introduction of vascular endothelial growth factor receptor (VEGFR) targeting angiogenesis inhibitors and poly-ADP-ribose-polymerase (PARP) inhibitors to supplement the standard platinum- and taxane-based chemotherapy, the expected overall survival of HGSC patients has not improved significantly from the five-year rate of 42%. This calls for the development and testing of more efficient treatment options. Many oncogenic kinase-signaling pathways are dysregulated in HGSC. Since small-molecule kinase inhibitors have revolutionized the treatment of many solid cancers due to the generality of the increased activation of protein kinases in carcinomas, it is reasonable to evaluate their potential against HGSC. Here, we present the latest concluded and on-going clinical trials on kinase inhibitors in HGSC, as well as the recent work concerning ovarian cancer patient organoids and xenograft models. We discuss the potential of kinase inhibitors as personalized treatments, which would require comprehensive assessment of the biological mechanisms underlying tumor spread and chemoresistance in individual patients, and their connection to tumor genome and transcriptome to establish identifiable subgroups of patients who are most likely to benefit from a given therapy. Full article
(This article belongs to the Special Issue Kinase Signaling in Cancer)
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<p>Kinase inhibitors and their targets discussed in this review. Inhibitors highlighted with red color are currently (November 2022) under clinical trials. The colors of the frames around the inhibitors represent the colors used for the kinases they inhibit. Created with BioRender.com.</p>
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26 pages, 5787 KiB  
Article
Population-Based Temporal Trends and Ethnic Disparity in Cervical Cancer Mortality in South Africa (1999–2018): A Join Point and Age–Period–Cohort Regression Analyses
by Gbenga Olorunfemi, Elena Libhaber, Oliver Chukwujekwu Ezechi and Eustasius Musenge
Cancers 2022, 14(24), 6256; https://doi.org/10.3390/cancers14246256 - 19 Dec 2022
Cited by 5 | Viewed by 2923
Abstract
Cervical cancer is one of the leading causes of cancer deaths among women in low- and middle-income countries such as South Africa. The current impact of national cervical cancer control and sexual and reproductive health interventions in South Africa reduce its burden. The [...] Read more.
Cervical cancer is one of the leading causes of cancer deaths among women in low- and middle-income countries such as South Africa. The current impact of national cervical cancer control and sexual and reproductive health interventions in South Africa reduce its burden. The aim of this study was to assess the trends in cervical cancer mortality and its relation to breast and gynaecological cancers in South Africa from 1999 to 2018. We conducted joinpoint regression analyses of the trends in crude and age-standardised mortality rates (ASMR) for cervical cancer mortality in South Africa from 1999 to 2018. An age–period–cohort regression analysis was also conducted to determine the impact of age, period, and cohort on cervical cancer mortality trends. Analyses were stratified by ethnicity. Cervical cancer (n = 59,190, 43.92%, 95% CI: 43.65–44.18%) was responsible for about 43.9% of breast and gynecological cancer deaths. The mortality rate of cervical cancer (from 11.7 to 14.08 per 100,000) increased at about 0.9% per annum (Average Annual Percent Change (AAPC): 0.9% (AAPC: 0.9%, p-value < 0.001)), and young women aged 25 to 49 years (AAPC: 1.2–3.5%, p-value < 0.001) had increased rates. The risk of cervical cancer mortality increased among successive birth cohorts. In 2018, cervical cancer mortality rate among Blacks (16.74 per 100,000 women) was about twice the rates among Coloureds (8.53 deaths per 100,000 women) and approximately four-fold among Indians/Asians (4.16 deaths per 100,000 women), and Whites (3.06 deaths per 100,000 women). Cervical cancer control efforts should be enhanced in South Africa and targeted at ethnic difference, age, period, and cohort effects. Full article
(This article belongs to the Special Issue Incidence, Mortality, Trend, and Survival of Cancer)
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<p>A. Overall age-specific death rates in 2018 in South Africa from (<b>A</b>) breast and cervical cancer. National and ethnic annual deaths: (<b>A</b>), age-standardised mortality rates; (<b>B</b>) crude mortality rates; (<b>C</b>) age-specific mortality rates; (<b>D</b>) Comparison of age-specific death rates for cervical cancer, breast cancer, and ovarian cancer in South Africa, 2018; and (<b>E</b>) rates of cervical cancer in South Africa (1999–2018).</p>
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<p>Joinpoint regression trends of the annual age-standardised mortality rate for cervical cancer in South Africa (1999–2018) for: (<b>A</b>) overall; (<b>B</b>) Indians/Asians; (<b>C</b>) Blacks; (<b>D</b>) Whites; and (<b>E</b>) Coloured ethnic groups.</p>
Full article ">Figure 2 Cont.
<p>Joinpoint regression trends of the annual age-standardised mortality rate for cervical cancer in South Africa (1999–2018) for: (<b>A</b>) overall; (<b>B</b>) Indians/Asians; (<b>C</b>) Blacks; (<b>D</b>) Whites; and (<b>E</b>) Coloured ethnic groups.</p>
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<p>Joinpoint trends of age-specific death rates of cervical cancer in South Africa, 1999–2018. (<b>A</b>) 15–19 years (<b>B</b>) 20–24 years (<b>C</b>) 25–29 years (<b>D</b>) 30–34 years (<b>E</b>) 35–39 years (<b>F</b>) 40–44 years (<b>G</b>) 45–49 years (<b>H</b>) 50–54 years (<b>I</b>) 55–59 years (<b>J</b>) 60–64 years (<b>K</b>) 65–69 years (<b>L</b>)70–74 years (<b>M</b>) 75 years and above.</p>
Full article ">Figure 3 Cont.
<p>Joinpoint trends of age-specific death rates of cervical cancer in South Africa, 1999–2018. (<b>A</b>) 15–19 years (<b>B</b>) 20–24 years (<b>C</b>) 25–29 years (<b>D</b>) 30–34 years (<b>E</b>) 35–39 years (<b>F</b>) 40–44 years (<b>G</b>) 45–49 years (<b>H</b>) 50–54 years (<b>I</b>) 55–59 years (<b>J</b>) 60–64 years (<b>K</b>) 65–69 years (<b>L</b>)70–74 years (<b>M</b>) 75 years and above.</p>
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<p>Joinpoint trends of age-specific death rates of cervical cancer in South Africa, 1999–2018. (<b>A</b>) 15–19 years (<b>B</b>) 20–24 years (<b>C</b>) 25–29 years (<b>D</b>) 30–34 years (<b>E</b>) 35–39 years (<b>F</b>) 40–44 years (<b>G</b>) 45–49 years (<b>H</b>) 50–54 years (<b>I</b>) 55–59 years (<b>J</b>) 60–64 years (<b>K</b>) 65–69 years (<b>L</b>)70–74 years (<b>M</b>) 75 years and above.</p>
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<p>Joinpoint trends of age-specific death rates of cervical cancer in South Africa, 1999–2018. (<b>A</b>) 15–19 years (<b>B</b>) 20–24 years (<b>C</b>) 25–29 years (<b>D</b>) 30–34 years (<b>E</b>) 35–39 years (<b>F</b>) 40–44 years (<b>G</b>) 45–49 years (<b>H</b>) 50–54 years (<b>I</b>) 55–59 years (<b>J</b>) 60–64 years (<b>K</b>) 65–69 years (<b>L</b>)70–74 years (<b>M</b>) 75 years and above.</p>
Full article ">Figure 3 Cont.
<p>Joinpoint trends of age-specific death rates of cervical cancer in South Africa, 1999–2018. (<b>A</b>) 15–19 years (<b>B</b>) 20–24 years (<b>C</b>) 25–29 years (<b>D</b>) 30–34 years (<b>E</b>) 35–39 years (<b>F</b>) 40–44 years (<b>G</b>) 45–49 years (<b>H</b>) 50–54 years (<b>I</b>) 55–59 years (<b>J</b>) 60–64 years (<b>K</b>) 65–69 years (<b>L</b>)70–74 years (<b>M</b>) 75 years and above.</p>
Full article ">Figure 3 Cont.
<p>Joinpoint trends of age-specific death rates of cervical cancer in South Africa, 1999–2018. (<b>A</b>) 15–19 years (<b>B</b>) 20–24 years (<b>C</b>) 25–29 years (<b>D</b>) 30–34 years (<b>E</b>) 35–39 years (<b>F</b>) 40–44 years (<b>G</b>) 45–49 years (<b>H</b>) 50–54 years (<b>I</b>) 55–59 years (<b>J</b>) 60–64 years (<b>K</b>) 65–69 years (<b>L</b>)70–74 years (<b>M</b>) 75 years and above.</p>
Full article ">Figure 3 Cont.
<p>Joinpoint trends of age-specific death rates of cervical cancer in South Africa, 1999–2018. (<b>A</b>) 15–19 years (<b>B</b>) 20–24 years (<b>C</b>) 25–29 years (<b>D</b>) 30–34 years (<b>E</b>) 35–39 years (<b>F</b>) 40–44 years (<b>G</b>) 45–49 years (<b>H</b>) 50–54 years (<b>I</b>) 55–59 years (<b>J</b>) 60–64 years (<b>K</b>) 65–69 years (<b>L</b>)70–74 years (<b>M</b>) 75 years and above.</p>
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<p>Net (<b>A</b>) and local drift (<b>B</b>) of cervical cancer mortality in South Africa (1999–2018). (National and ethnic trends).</p>
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<p>Age effect (Risk ratio) of the National and ethnic cervical cancer mortality in South Africa (1999–2018).</p>
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<p>Period Risk ratio of the National and ethnic cervical cancer mortality trends in South Africa (1999–2018).</p>
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<p>Cohort Risk ratio of the National and ethnic cervical cancer mortality trends in South Africa (1999–2018).</p>
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20 pages, 953 KiB  
Review
An Immunocompetent Environment Unravels the Proto-Oncogenic Role of miR-22
by Maria Laura Centomo, Marianna Vitiello, Laura Poliseno and Pier Paolo Pandolfi
Cancers 2022, 14(24), 6255; https://doi.org/10.3390/cancers14246255 - 19 Dec 2022
Cited by 7 | Viewed by 2561
Abstract
MiR-22 was first identified as a proto-oncogenic microRNA (miRNA) due to its ability to post-transcriptionally suppress the expression of the potent PTEN (Phosphatase And Tensin Homolog) tumor suppressor gene. miR-22 tumorigenic role in cancer was subsequently supported by its ability to positively trigger [...] Read more.
MiR-22 was first identified as a proto-oncogenic microRNA (miRNA) due to its ability to post-transcriptionally suppress the expression of the potent PTEN (Phosphatase And Tensin Homolog) tumor suppressor gene. miR-22 tumorigenic role in cancer was subsequently supported by its ability to positively trigger lipogenesis, anabolic metabolism, and epithelial-mesenchymal transition (EMT) towards the metastatic spread. However, during the following years, the picture was complicated by the identification of targets that support a tumor-suppressive role in certain tissues or cell types. Indeed, many papers have been published where in vitro cellular assays and in vivo immunodeficient or immunosuppressed xenograft models are used. However, here we show that all the studies performed in vivo, in immunocompetent transgenic and knock-out animal models, unanimously support a proto-oncogenic role for miR-22. Since miR-22 is actively secreted from and readily exchanged between normal and tumoral cells, a functional immune dimension at play could well represent the divider that allows reconciling these contradictory findings. In addition to a critical review of this vast literature, here we provide further proof of the oncogenic role of miR-22 through the analysis of its genomic locus vis a vis the genetic landscape of human cancer. Full article
(This article belongs to the Collection miRNAs: New Insights in Tumor Biology)
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<p>Schematic representation of miR-22 genomic locus on chromosome 17.</p>
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<p>Mir-22 oncogenic role in cancer. Scheme of miR-22 functional mechanisms in promoting tumorigenesis of cutaneous squamous cell carcinoma (cSCC), breast cancer (BRCA), prostate cancer (PC), and Leukemia in immunocompetent (<b>a</b>–<b>d</b>) and xenograft (<b>e</b>) mouse models. (<b>a</b>) miR-22 promotes cSCC initiation and progression, repressing Wnt/β-catenin signaling by targeting Fosb and PAD2. (<b>b</b>) Epigenetic inactivation of miR-200 through miR-22 targeting the TET family in breast cancer triggers EMT and increases mammary tumorigenesis and metastasis. (<b>c</b>) miR-22 promotes tumor invasion in prostate cancer targeting E-Cadherin. (<b>d</b>) miR-22 decreases the level of 5-hmC by negatively regulating TET2 leading to MDS and MDS-derived leukemia. (<b>e</b>) Increased levels of miR-22 directly target PTEN, which results in PI3K/AKT signaling pathway upregulation and cancer progression in Breast and Prostate in vivo mouse models.</p>
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<p>Alterations in miR-22 expression level, genomic location, and sequence. (<b>a</b>) Differential expression profile of miR-22-3p (miR-22), miR-132-3p (miR-132), and miR-212-3p (miR-212), in breast cancer, according to dbDEMC 3.0 database. (<b>b</b>) The number of breast cancer studies where miR-22 expression has been found up-regulated (black) or down-regulated (grey), according to dbDEMC. (<b>c</b>) Breast cancer samples available at TCGA (OncoLnc analysis) were divided at the median expression levels of hsa-miR-22-3p. The survival curve was then calculated for high (above the median, red) and low (below the median, blue) expression. (<b>d</b>) The ratio of the number of amplifications (+) and deletions (−) reported on cBioportal database for the indicated microRNAs in all tumors and in breast cancer (BRCA), hepatocellular carcinoma (HCC) and prostate cancer (PC). (<b>e</b>) The number of amplifications (+) and deletions (−) of miR-22, miR-132, and miR-212 in BRCA patients reported in the cBioportal database. (<b>f</b>) The number of amplifications (left) and deletions (right) reported on the cBioportal database for <span class="html-italic">CRK</span>, <span class="html-italic">PITPNA-AS1,</span> and <span class="html-italic">HIC1</span> in 205 studies. See the text for details about the cases highlighted by the black and red arrows. (<b>g</b>) Base pair variations in miRNA sequences reported in GenomAD browser. Red: mature miRNA sequence; blue: base pair variation; black: pre-miRNA sequence.</p>
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26 pages, 5704 KiB  
Article
High-Frequency Nanosecond Bleomycin Electrochemotherapy and its Effects on Changes in the Immune System and Survival
by Austėja Balevičiūtė, Eivina Radzevičiūtė, Augustinas Želvys, Veronika Malyško-Ptašinskė, Jurij Novickij, Auksė Zinkevičienė, Vytautas Kašėta, Vitalij Novickij and Irutė Girkontaitė
Cancers 2022, 14(24), 6254; https://doi.org/10.3390/cancers14246254 - 19 Dec 2022
Cited by 8 | Viewed by 2454
Abstract
In this work, a time-dependent and time-independent study on bleomycin-based high-frequency nsECT (3.5 kV/cm × 200 pulses) for the elimination of LLC1 tumours in C57BL/6J mice is performed. We show the efficiency of nsECT (200 ns and 700 ns delivered at 1 kHz [...] Read more.
In this work, a time-dependent and time-independent study on bleomycin-based high-frequency nsECT (3.5 kV/cm × 200 pulses) for the elimination of LLC1 tumours in C57BL/6J mice is performed. We show the efficiency of nsECT (200 ns and 700 ns delivered at 1 kHz and 1 MHz) for the elimination of tumours in mice and increase of their survival. The dynamics of the immunomodulatory effects were observed after electrochemotherapy by investigating immune cell populations and antitumour antibodies at different timepoints after the treatment. ECT treatment resulted in an increased percentage of CD4+ T, splenic memory B and tumour-associated dendritic cell subsets. Moreover, increased levels of antitumour IgG antibodies after ECT treatment were detected. Based on the time-dependent study results, nsECT treatment upregulated PD 1 expression on splenic CD4+ Tr1 cells, increased the expansion of splenic CD8+ T, CD4+CD8+ T, plasma cells and the proportion of tumour-associated pro inflammatory macrophages. The Lin population of immune cells that was increased in the spleens and tumour after nsECT was identified. It was shown that nsECT prolonged survival of the treated mice and induced significant changes in the immune system, which shows a promising alliance of nanosecond electrochemotherapy and immunotherapy. Full article
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<p>Schematic overview of the time-dependent and time independent studies.</p>
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<p>(<b>A</b>) Mice survival curves. (<b>B</b>) Median survival days. Mantel–Cox test was used for the statistical evaluation of mice survival. (<b>C</b>) Bioluminescence imaging of untreated, microsecond and nanosecond ECT treated tumours in tumour-bearing mice. (<b>D</b>) Tumour luminescence % before (Day 0), after ECT and 11 days after the treatment. The imaging in (<b>C</b>,<b>D</b>) was done with a IVIS Spectrum device and Living Image software. The Mann-Whitney test was used for the comparison of tumour luminescence data. Statistically significant (** <span class="html-italic">p</span> &lt; 0.005; *** <span class="html-italic">p</span> &lt; 0.0005) differences compared to the untreated group. Significant differences (●● <span class="html-italic">p</span> &lt; 0.005) compared to the μsECT group.</p>
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<p>Time-dependent study. Lymphocyte (<b>A</b>–<b>D</b>), myeloid cells (<b>E</b>,<b>F</b>) and “Negative” (Lin<sup>−</sup>) population (<b>G</b>) in mice spleens. Cytometry was performed with BD FACSAria III cytometer. Statistically significant (* <span class="html-italic">p</span> &lt; 0.05; ** <span class="html-italic">p</span> &lt; 0.005) differences and tendencies (+ <span class="html-italic">p</span> = 0.05–0.1) compared to the untreated group. Significant differences (● <span class="html-italic">p</span> &lt; 0.05; ●● <span class="html-italic">p</span> &lt; 0.005) and tendencies (???? <span class="html-italic">p</span> = 0.05–0.1) compared to the μsECT group.</p>
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<p>Time-independent study. Lymphocytes (<b>A</b>–<b>F</b>), myeloid cells (<b>G</b>,<b>H</b>), “Negative” (Lin<sup>−</sup>) population (<b>I</b>) and erythrocytes (<b>J</b>) in mice spleens. Cytometry was performed with BD FACSAria III cytometer. Statistically significant (* <span class="html-italic">p</span> &lt; 0.05; ** <span class="html-italic">p</span> &lt; 0.005; *** <span class="html-italic">p</span> &lt; 0.0005) differences and tendencies (+ <span class="html-italic">p</span> = 0.05–0.1) compared to the untreated group.</p>
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<p>Time-dependent study. Lymphocyte (<b>A</b>–<b>D</b>), myeloid cells (<b>E</b>,<b>F</b>) and “Negative” (Lin<sup>−</sup>) population (<b>G</b>) in mice tumours. Cytometry was performed with BD FACSAria III cytometer. Statistically significant (* <span class="html-italic">p</span> &lt; 0.05; ** <span class="html-italic">p</span> &lt; 0.005) differences and tendencies (+ <span class="html-italic">p</span> = 0.05–0.1) compared to the untreated group. Significant differences (● <span class="html-italic">p</span> &lt; 0.05; ●● <span class="html-italic">p</span> &lt; 0.005) and tendencies (<b>????</b> <span class="html-italic">p</span> = 0.05–0.1) compared to the μsECT group.</p>
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<p>Time-independent study. Lymphocytes (<b>A</b>–<b>C</b>), myeloid cells (<b>D</b>,<b>E</b>) and “Negative” (Lin<sup>−</sup>) population (<b>F</b>) in mice tumours. Cytometry was performed with BD FACSAria III cytometer. Statistically significant (* <span class="html-italic">p</span> &lt; 0.05; ** <span class="html-italic">p</span> &lt; 0.005; *** <span class="html-italic">p</span> &lt; 0.0005) differences and tendencies (+ <span class="html-italic">p</span> = 0.05–0.1) compared to the untreated group.</p>
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<p>Time-independent study. Lymphocytes (<b>A</b>–<b>E</b>), myeloid cells (<b>F</b>,<b>G</b>) and “Negative” (Lin<sup>−</sup>) population (<b>H</b>) in murine lymph nodes. Cytometry was performed with BD FACSAria III cytometer. Statistically significant (* <span class="html-italic">p</span> &lt; 0.05; ** <span class="html-italic">p</span> &lt; 0.005; *** <span class="html-italic">p</span> &lt; 0.0005) differences and tendencies (+ <span class="html-italic">p</span> = 0.05–0.1) compared to the untreated group.</p>
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<p>The relative percent of anti-LLC1 IgG antibodies in time-dependent (<b>A</b>) and time-independent (<b>B</b>) study. Data was normalized according to (<span class="html-italic">n</span> = 7) untreated tumour-bearing (<b>A</b>) and (<span class="html-italic">n</span> = 6) healthy mice (<b>B</b>). Statistically significant (* <span class="html-italic">p</span> &lt; 0.05; ** <span class="html-italic">p</span> &lt; 0.005) differences compared to untreated group; significant differences (● <span class="html-italic">p</span> &lt; 0.05) compared to the μsECT group. Flow cytometry was performed with Amnis FlowSight.</p>
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13 pages, 6082 KiB  
Article
Real-Time Split-Dose PET/CT-Guided Ablation Improves Colorectal Liver Metastasis Detection and Ablation Zone Margin Assessments without the Need for Repeated Contrast Injection
by Mahdi Zirakchian Zadeh, Randy Yeh, Henry S. Kunin, Assen S. Kirov, Elena N. Petre, Mithat Gönen, Mikhail Silk, Francois H. Cornelis, Kevin C. Soares, Etay Ziv, Stephen B. Solomon, Vlasios S. Sotirchos and Constantinos T. Sofocleous
Cancers 2022, 14(24), 6253; https://doi.org/10.3390/cancers14246253 - 19 Dec 2022
Cited by 14 | Viewed by 2967
Abstract
Background: Real-time split-dose PET can identify the targeted colorectal liver metastasis (CLM) and eliminate the need for repeated contrast administration before and during thermal ablation (TA). This study aimed to assess the added value of pre-ablation real-time split-dose PET when combined with non-contract [...] Read more.
Background: Real-time split-dose PET can identify the targeted colorectal liver metastasis (CLM) and eliminate the need for repeated contrast administration before and during thermal ablation (TA). This study aimed to assess the added value of pre-ablation real-time split-dose PET when combined with non-contract CT in the detection of CLM for ablation and the evaluation of the ablation zone and margins. Methods: A total of 190 CLMs/125 participants from two IRB-approved prospective clinical trials using PET/CT-guided TA were analyzed. Based on detection on pre-TA imaging, CLMs were categorized as detectable, non-detectable, and of poor conspicuity on CT alone, and detectable, non-detectable, and low FDG-avidity on PET/CT after the initial dose. Ablation margins around the targeted CLM were evaluated using a 3D volumetric approach. Results: We found that 129/190 (67.9%) CLMs were detectable on CT alone, and 61/190 CLMs (32.1%) were undetectable or of poor conspicuity, not allowing accurate depiction and targeting by CT alone. Thus, the theoretical 5- and 10-mm margins could not be defined in these tumors (32.1%) using CT alone. When TA intraprocedural PET/CT images are obtained and inspected (fused PET/CT), only 4 CLM (2.1%) remained undetectable or had a low FDG avidity. Conclusions: The addition of PET to non-contrast CT improved CLM detection for ablation targeting, margin assessments, and continuous depiction of the FDG avid CLMs during the ablation without the need for multiple intravenous contrast injections pre- and intra-procedurally. Full article
(This article belongs to the Special Issue Management of Colorectal Cancer Metastatic Disease)
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<p>Study Flowchart.</p>
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<p>CLM detection and margin assessment on pre-ablation imaging.</p>
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<p>Steps in assessment of intraprocedural PET/CT guided ablation. (<b>A</b>) Accurate detection of tumor on pre-ablation imaging modalities is the first step (here, the tumor was detectable on PET and PET/CT—shown with blue arrows—but not on CT alone). (<b>B</b>) Segmentation of tumor (red circle) and margins (5−mm margin depicted with yellow circle and 10−mm depicted with green circle) on pre-ablation PET. (<b>C</b>) Registration of pre-ablation non-contrast CT (C1) and post-ablation portal venous CT (C2) (registration is shown in C3). The ablation zone is shown with an orange arrow on the portal venous phase of the post-ablation contrast-enhanced CT (C2). (<b>D</b>) The tumor (red circle), 5−mm (yellow circle), and 10−mm (green circle) margins transferred from pre-ablation PET to the registered post-ablation portal venous CT for assessment of the tumor and tumor margins that are not covered within ablation zone AZ (AZ is depicted with blue here; the margins that are not covered by the AZ are filled with green).</p>
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<p>Pie charts showing the colorectal liver metastasis detection rate for CT and PET/CT.</p>
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<p>An example of a CLM with low-FDG avidity and 5− and 10−mm margins assessment for the target CLM.</p>
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<p>Real-time PET provides the benefit of continuous depiction of the FDG avid CLMs during the ablation and eliminates the need for multiple contrast injections. The location of the tumor and the ablation electrode is depicted with blue arrows in three consecutive PET/CT slices.</p>
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<p>Importance of accurate tumor and margins detection for preventing local tumor progression. A patient with colorectal liver metastasis in segment8. (<b>A</b>) Pre-ablation anatomical imaging (CT) and PET and fused PET/CT. The CLM was detected on PET and PET/CT but not easily detectable on CT alone. Insufficient coverage of margins (5 mm margin filled with yellow (<b>B</b>) and 10 mm margin filled with green (<b>C</b>)) led to tumor progression (<b>D</b>) in less than 6 months after thermal ablation in the area where the tumor was not sufficiently covered.</p>
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23 pages, 1195 KiB  
Review
The Normal, the Radiosensitive, and the Ataxic in the Era of Precision Radiotherapy: A Narrative Review
by Sandrine Pereira, Ester Orlandi, Sophie Deneuve, Amelia Barcellini, Agnieszka Chalaszczyk, Isabelle Behm-Ansmant, Liza Hettal, Tiziana Rancati, Guillaume Vogin and Juliette Thariat
Cancers 2022, 14(24), 6252; https://doi.org/10.3390/cancers14246252 - 19 Dec 2022
Cited by 13 | Viewed by 3170
Abstract
(1) Background: radiotherapy is a cornerstone of cancer treatment. When delivering a tumoricidal dose, the risk of severe late toxicities is usually kept below 5% using dose-volume constraints. However, individual radiation sensitivity (iRS) is responsible (with other technical factors) for unexpected toxicities after [...] Read more.
(1) Background: radiotherapy is a cornerstone of cancer treatment. When delivering a tumoricidal dose, the risk of severe late toxicities is usually kept below 5% using dose-volume constraints. However, individual radiation sensitivity (iRS) is responsible (with other technical factors) for unexpected toxicities after exposure to a dose that induces no toxicity in the general population. Diagnosing iRS before radiotherapy could avoid unnecessary toxicities in patients with a grossly normal phenotype. Thus, we reviewed iRS diagnostic data and their impact on decision-making processes and the RT workflow; (2) Methods: following a description of radiation toxicities, we conducted a critical review of the current state of the knowledge on individual determinants of cellular/tissue radiation; (3) Results: tremendous advances in technology now allow minimally-invasive genomic, epigenetic and functional testing and a better understanding of iRS. Ongoing large translational studies implement various tests and enriched NTCP models designed to improve the prediction of toxicities. iRS testing could better support informed radiotherapy decisions for individuals with a normal phenotype who experience unusual toxicities. Ethics of medical decisions with an accurate prediction of personalized radiotherapy’s risk/benefits and its health economics impact are at stake; (4) Conclusions: iRS testing represents a critical unmet need to design personalized radiotherapy protocols relying on extended NTCP models integrating iRS. Full article
(This article belongs to the Special Issue Personalized Radiation Therapy for Oncology)
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<p>Main pathways involved in molecular toxicities and predictive assays.</p>
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<p>Practical consequences of knowing patients’ iRS of a patient before starting treatment.</p>
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19 pages, 1039 KiB  
Systematic Review
Current Knowledge on Spinal Meningiomas Epidemiology, Tumor Characteristics and Non-Surgical Treatment Options: A Systematic Review and Pooled Analysis (Part 1)
by Victor Gabriel El-Hajj, Jenny Pettersson-Segerlind, Alexander Fletcher-Sandersjöö, Erik Edström and Adrian Elmi-Terander
Cancers 2022, 14(24), 6251; https://doi.org/10.3390/cancers14246251 - 19 Dec 2022
Cited by 19 | Viewed by 2295
Abstract
Background: Spinal meningiomas are the most common primary intradural spinal tumors. Although they are a separate entity, a large portion of the knowledge on spinal meningiomas is based on findings in intracranial meningiomas. Therefore, a comprehensive review of all the literature on spinal [...] Read more.
Background: Spinal meningiomas are the most common primary intradural spinal tumors. Although they are a separate entity, a large portion of the knowledge on spinal meningiomas is based on findings in intracranial meningiomas. Therefore, a comprehensive review of all the literature on spinal meningiomas was performed. Methods: Electronic databases were searched for all studies on spinal meningiomas dating from 2000 and onward. Findings of matching studies were pooled to strengthen the current body of evidence. Results: A total of 104 studies were included. The majority of patients were female (72.83%), elderly (peak decade: seventh), and had a world health organization (WHO) grade 1 tumor (95.7%). Interestingly, the minority of pediatric patients had a male overrepresentation (62.0% vs. 27.17%) and higher-grade tumors (33.3% vs. 4.3%). Sensory and motor dysfunction and pain were the most common presenting symptoms. Despite a handful of studies reporting promising findings associated with the use of non-surgical treatment options, the literature still suffers from contradictory results and limitations of study designs. Conclusions: Elderly females with WHO grade 1 tumors constituted the stereotypical type of patient. Compared to surgical alternatives, the evidence for the use of non-surgical treatments is still relatively weak. Full article
(This article belongs to the Special Issue Meningioma Surgery and Functional Outcome)
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<p>PRISMA flow chart illustrating the study selection process.</p>
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<p>Distribution of the four most common meningioma subtypes as reported by the studies.</p>
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17 pages, 4210 KiB  
Article
Attempting to Identify Bacterial Allies in Immunotherapy of NSCLC Patients
by Anna Grenda, Ewelina Iwan, Paweł Krawczyk, Małgorzata Frąk, Izabela Chmielewska, Arkadiusz Bomba, Aleksandra Giza, Anna Rolska-Kopińska, Michał Szczyrek, Robert Kieszko, Tomasz Kucharczyk, Bożena Jarosz, Dariusz Wasyl and Janusz Milanowski
Cancers 2022, 14(24), 6250; https://doi.org/10.3390/cancers14246250 - 19 Dec 2022
Cited by 16 | Viewed by 2785
Abstract
Introduction: Factors other than PD-L1 (Programmed Death Ligand 1) are being sought as predictors for cancer immuno- or chemoimmunotherapy in ongoing studies and long-term observations. Despite high PD-L1 expression on tumor cells, some patients do not benefit from immunotherapy, while others, without the [...] Read more.
Introduction: Factors other than PD-L1 (Programmed Death Ligand 1) are being sought as predictors for cancer immuno- or chemoimmunotherapy in ongoing studies and long-term observations. Despite high PD-L1 expression on tumor cells, some patients do not benefit from immunotherapy, while others, without the expression of this molecule, respond to immunotherapy. Attention has been paid to the composition of the gut microbiome as a potential predictive factor for immunotherapy effectiveness. Materials and Methods: Our study enrolled 47 Caucasian patients with stage IIIB or IV non-small cell lung cancer (NSCLC). They were eligible for treatment with first- or second-line immunotherapy or chemoimmunotherapy. We collected stool samples before the administration of immunotherapy. We performed next-generation sequencing (NGS) on DNA isolated from the stool sample and analyzed bacterial V3 and V4 of the 16S rRNA gene. Results: We found that bacteria from the families Barnesiellaceae, Ruminococcaceae, Tannerellaceae, and Clostridiaceae could modulate immunotherapy effectiveness. A high abundance of Bacteroidaaceae, Barnesiellaceae, and Tannerellaceae could extend progression-free survival (PFS). Moreover, the risk of death was significantly higher in patients with a high content of Ruminococcaceae family (HR = 6.3, 95% CI: 2.6 to 15.3, p < 0.0001) and in patients with a low abundance of Clostridia UCG-014 (HR = 3.8, 95% CI: 1.5 to 9.8, p = 0.005) regardless of the immunotherapy line. Conclusions: The Clostridia class in gut microbiota could affect the effectiveness of immunotherapy, as well as the length of survival of NSCLC patients who received this method of treatment. Full article
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<p>(<b>a</b>) Plot showing the relative frequency of bacterial phylum based on 16S rRNA of 47 stool samples from NSCLC patients treated or not treated with antibiotics; (<b>b</b>) boxplot showing <span class="html-italic">Bacteroidota</span> content depending on antibiotic therapy up to 4 weeks before immunotherapy.</p>
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<p>Boxplots showing the content of (<b>a</b>) <span class="html-italic">Bifidobacteriaceae</span>, (<b>b</b>) <span class="html-italic">Clostridia UCG-014</span>, (<b>c</b>) <span class="html-italic">Rikenellaceae</span> depending on the application of antibiotic treatment, and (<b>d</b>) <span class="html-italic">Butiriciococcaceae</span> depending on the line of immunotherapy.</p>
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<p>Boxplots showing the content of (<b>a</b>) <span class="html-italic">Butiriciococcaceae</span> depending on the line of immunotherapy; (<b>b</b>) <span class="html-italic">Clostridia UCG-014</span> depending on immunotherapy toxicity; (<b>c</b>) <span class="html-italic">Prevotellaceae</span> depending on the histopathological diagnosis; (<b>d</b>) <span class="html-italic">Peptostreptococcaceae</span> depending on the histopathological diagnosis in patients who received first-line immunotherapy. All results concern the patients untreated with antibiotics before immunotherapy.</p>
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<p>Boxplots showing the content of (<b>a</b>) <span class="html-italic">Barnesiellaceae</span>, (<b>b</b>) <span class="html-italic">Tannerellaceae</span>, (<b>c</b>) <span class="html-italic">Clostridiaceae,</span> and (<b>d</b>) <span class="html-italic">Ruminococcaceae</span> in the group of patients with the disease control (SD + PR) and progression disease (PD) during first-line immunotherapy. All results concern the patients untreated with antibiotics before immunotherapy.</p>
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<p>Boxplot showing Verrucomicrobiota content in patients with different responses to immunotherapy.</p>
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<p>Differences in the abundance of individual bacteria in patients with PFS shorter and longer than 6 months. Boxplots showing the content of (<b>a</b>) <span class="html-italic">Bacteroidaaceae</span>, (<b>b</b>) <span class="html-italic">Barnesiellaceae,</span> and (<b>c</b>) <span class="html-italic">Tannerellaceae</span> in the group of patients treated with first-line immunotherapy.</p>
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<p>Boxplot showing Firmicutes content in patients with PFS above or below 6 months from the start of immunotherapy.</p>
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<p>Differences in the abundance of individual bacteria in patients with OS shorter and longer than 12 months. Boxplots showing the content of (<b>a</b>) <span class="html-italic">Enterobacteriaceae</span> regardless of immunotherapy line; (<b>b</b>) <span class="html-italic">Clostridia UCG-014</span> in first-line immunotherapy group; (<b>c</b>) <span class="html-italic">Ruminococcaceae</span> in first-line immunotherapy group; (<b>d</b>) <span class="html-italic">Enterobacteriaceae</span> in second-line immunotherapy group; (<b>e</b>) <span class="html-italic">Lachnospiracea</span> in second-line immunotherapy group; (<b>f</b>) <span class="html-italic">Bacteroidaceae</span> in first-line immunotherapy group; (<b>g</b>) <span class="html-italic">Christensenellaceae</span> in first-line immunotherapy group. Boxplots (<b>a</b>–<b>e</b>) show groups untreated with antibiotics before immunotherapy, while boxplots (<b>f</b>,<b>g</b>) concern patients treated and untreated with antibiotics.</p>
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<p>Analysis of overall survival in patients who received Immunotherapy depending on the content of (<b>a</b>) <span class="html-italic">Ruminococcaceae</span>), (<b>b</b>) <span class="html-italic">Christensenalceae</span>, and (<b>c</b>) <span class="html-italic">Clostridia UCG-014</span> regardless of immunotherapy line in the group untreated with antibiotics up to 4 weeks before immunotherapy.</p>
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11 pages, 1528 KiB  
Article
Central Nervous System Metastasis in Neuroblastoma: From Three Decades Clinical Experience to New Considerations in the Immunotherapy Era
by Angela Mastronuzzi, Giovanna Stefania Colafati, Andrea Carai, Maria D’Egidio, Francesco Fabozzi, Francesca Del Bufalo, Maria Felicia Villani, Giada Del Baldo, Sabina Vennarini, Costanza Canino, Angela Di Giannatale, Paolo Tomà, Maria Carmen Garganese and Maria Antonietta De Ioris
Cancers 2022, 14(24), 6249; https://doi.org/10.3390/cancers14246249 - 19 Dec 2022
Cited by 3 | Viewed by 2700
Abstract
Central nervous system (CNS) metastatic spread in neuroblastoma (NB) is rare and occurs more often at relapse/progression. We report on CNS involvement in high risk (HR) NB over 25 years. For this retrospective study, we reviewed the CNS imaging of all the patients [...] Read more.
Central nervous system (CNS) metastatic spread in neuroblastoma (NB) is rare and occurs more often at relapse/progression. We report on CNS involvement in high risk (HR) NB over 25 years. For this retrospective study, we reviewed the CNS imaging of all the patients treated at Bambino Gesù Children Hospital from 1 July 1996 to 30 June 2022. A total of 128 patients with HR NB were diagnosed over 26 years. Out of 128 patients, CNS metastatic spread occurred in 6 patients: 3 patients presented a metastatic spread at diagnosis, while in 3 patients, CNS was involved at relapse. Overall, the rate of occurrence of CNS spread is 4.7% with the same distribution at diagnosis and at relapse, namely 2.3%. Interestingly, CNS spread at diagnosis was observed only before 2012, whereas CNS was observed at relapse only after 2012, in the immunotherapy era. CNS metastases presented similar imaging features at diagnosis and at relapse, with a peculiar hemorrhagic aspect and mainly hemispheric localization in patients with bone skull involvement at the time of diagnosis. The outcome is dismal, and 3 out of 6 patients died for progressive disease. Full article
(This article belongs to the Section Pediatric Oncology)
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<p>Patient #1 (<b>a</b>–<b>c</b>) and Patient #3 (<b>c</b>–<b>e</b>) imaging features. Axial T2w images of Patient #1 (<b>a</b>) and Patient #3 (<b>d</b>) shows a single bulky parenchymal lesion associated with mild surrounding vasogenic edema. Susceptibility-weighted imaging sequences in Patient #1 (<b>b</b>) and Patient #3 (<b>e</b>) show blooming within each lesion consistent with hemorrhage. Axial T1w image of Patient #1 (<b>c</b>) shows a solid-cystic appearance of the lesion with multiloculated blood-fluid levels in the most anterior portion and a solid hemorrhagic posterior component. Axial non contrast brain computed tomography (CT) of Patient #3 (<b>f</b>) shows lesion hyperdensity consistent with hemorrhage.</p>
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<p>Patient #2 imaging features. Axial non contrast brain computed tomography (CT) (<b>a</b>) showed a bulky central nervous system (CNS) hyperdense lesion within the right cerebellopontine angle, with inhomogeneous signal in axial T2w image (<b>b</b>), but with restricted diffusion in diffusion weighted imaging (DWI) (<b>c</b>). Post-contrast sagittal T1w image of the brain (<b>d</b>) and post-contrast sagittal T1w (<b>e</b>) and T2w (<b>f</b>) images of the spine showed numerous other brain and spine leptomeningeal lesions. MRI of the spine demonstrated thickened leptomeninges with multiple extra medullary enhancing nodular lesions (<b>e</b>); the nodular enhancing foci within the conus and along the nerve roots of the cauda equine (<b>f</b>) had an inhomogeneous low signal intensity on sagittal T2w images indicating a hemorrhagic component within them.</p>
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<p>Patient #4 imaging features. Axial T2w image (<b>a</b>) shows a single lesion in the right frontal lobe, hyperdense on axial non contrast brain computed tomography (CT) (<b>b</b>), without hemorrhagic components in susceptibility weighted imaging (SWI) (<b>c</b>), but with restricted diffusion in diffusion weighted imaging (DWI) (<b>d</b>). The cerebral blood volume map from dynamic susceptibility contrast (DSC) perfusion images (<b>e</b>) shows elevated relative cerebral blood volume (rCBV) within the lesion consistent with angiogenesis/vascular proliferation. Post-contrast sagittal T1w image with maximum intensity projection (MIP) reconstruction (<b>f</b>) shows tortuous vessels within and around the lesion.</p>
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14 pages, 3123 KiB  
Article
High-Dose-Rate Brachytherapy as an Organ-Sparing Treatment for Early Penile Cancer
by Denisa Pohanková, Igor Sirák, Milan Vošmik, Linda Kašaová, Jakub Grepl, Petr Paluska, Lukáš Holub, Jiří Špaček, Miroslav Hodek, Martin Kopeček and Jiří Petera
Cancers 2022, 14(24), 6248; https://doi.org/10.3390/cancers14246248 - 19 Dec 2022
Cited by 5 | Viewed by 5041
Abstract
Background: Low-dose-rate brachytherapy is an effective organ-sparing treatment for patients with early-stage penile cancer. However, only limited data are available on the role of high-dose-rate brachytherapy (HDR-BT) in this clinical setting. Methods: Between 2002 and 2020, 31 patients with early penile cancer were [...] Read more.
Background: Low-dose-rate brachytherapy is an effective organ-sparing treatment for patients with early-stage penile cancer. However, only limited data are available on the role of high-dose-rate brachytherapy (HDR-BT) in this clinical setting. Methods: Between 2002 and 2020, 31 patients with early penile cancer were treated at our center with interstitial HDR BT at a dose of 18 × 3 Gy twice daily. A breast brachytherapy template was used for the fixation of stainless hollow needles. Results: The median follow-up was 117.5 months (range, 5–210). Eight patients (25.8%) developed a recurrence; of these, seven were salvaged by partial amputation. Six patients died of internal comorbidities or a second cancer. The probability of local control at 5 and 10 years was 80.7% (95% CI: 63.7–97.7%) and 68.3% (95% CI: 44.0–92.6%), respectively. Cause-specific survival was 100%. Only one case of radiation-induced necrosis was observed. The probability of penile sparing at 5 and 10 years was 80.6% (95% CI: 63.45–97.7%) and 62.1% (95% CI: 34.8–89.4%), respectively. Conclusions: These results show that HDR-BT for penile cancer can achieve results comparable to LDR-BT with organ sparing. Despite the relatively large patient cohort—the second largest reported to date in this clinical setting—prospective data from larger samples are needed to confirm the role of HDR-BT in penile cancer. Full article
(This article belongs to the Special Issue Advances in Brachytherapy in the Treatment of Tumors)
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<p>Implantation technique.</p>
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<p>Dose distribution. The simple geometrical 3D model was created in the BrachyVision planning system (Varian Medical Systems, Palo Alto, CA, USA) by measuring the distance between both plates, between each needle tip and plate, and between plates and the musoca entry and exit point for each needle. The urethra was modeled as a straight tube. The width of the plates was 1 cm, and the needle separation was 10 mm in square grid geometry. Purple contour = GTV; ochre contour = CTV; yellow contour = penis surface; violet contour = urethra; violet-filled structures = plastic template.</p>
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<p>Scheme of treatment schedule. Red arrows indicate brachytherapy fractions.</p>
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<p>Competing risk analysis of deaths from other cancers.</p>
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<p>Result at 5 years.</p>
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<p>Local control recurrence-free interval after HDR-BT.</p>
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<p>Penectomy-free interval outcomes.</p>
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<p>Template for CT-compatible brachytherapy.</p>
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18 pages, 5021 KiB  
Article
Targeting IRS-1/2 in Uveal Melanoma Inhibits In Vitro Cell Growth, Survival and Migration, and In Vivo Tumor Growth
by Chandrani Chattopadhyay, Rajat Bhattacharya, Jason Roszik, Fatima S. Khan, Gabrielle A. Wells, Hugo Villanueva, Yong Qin, Rishav Bhattacharya, Sapna P. Patel and Elizabeth A. Grimm
Cancers 2022, 14(24), 6247; https://doi.org/10.3390/cancers14246247 - 19 Dec 2022
Cited by 6 | Viewed by 2484
Abstract
Uveal melanoma originating in the eye and metastasizing to the liver is associated with poor prognosis and has only one approved therapeutic option. We hypothesized that liver-borne growth factors may contribute to UM growth. Therefore, we investigated the role of IGF-1/IGF-1R signaling in [...] Read more.
Uveal melanoma originating in the eye and metastasizing to the liver is associated with poor prognosis and has only one approved therapeutic option. We hypothesized that liver-borne growth factors may contribute to UM growth. Therefore, we investigated the role of IGF-1/IGF-1R signaling in UM. Here, we found that IRS-1, the insulin receptor substrate, is overexpressed in both UM cells and tumors. Since we previously observed that IGF-1R antibody therapy was not clinically effective in UM, we investigated the potential of NT157, a small molecule inhibitor of IRS-1/2, in blocking this pathway in UM. NT157 treatment of multiple UM cell lines resulted in reduced cell growth and migration and increased apoptosis. This treatment also significantly inhibited UM tumor growth in vivo, in the chicken egg chorioallantoic membrane (CAM) and subcutaneous mouse models, validating the in vitro effect. Mechanistically, through reverse phase protein array (RPPA), we identified significant proteomic changes in the PI3K/AKT pathway, a downstream mediator of IGF-1 signaling, with NT157 treatment. Together, these results suggest that NT157 inhibits cell growth, survival, and migration in vitro, and tumor growth in vivo via inhibiting IGF-1 signaling in UM. Full article
(This article belongs to the Special Issue Tumor Microenvironment and Treatment in Uveal Melanoma)
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<p><b>Expression of IGF-1R in UM tumors and cell lines.</b> (<b>A</b>) The IGF-1R mRNA expression levels in tumor and normal tissues were compared in 33 cancer (red dots) and corresponding normal (green dots) tissues through TCGA database analysis. The expression in UM is indicated by an arrow. (<b>B</b>) RT-PCR analyses showing IGF-1R mRNA levels in 10 different UM cell lines. (<b>C</b>) Western blot analysis showing IGF-1R activation/induction in UM cell lines with 75 ng/mL of IGF-1 treatment for 10 min. (<b>D</b>) Western blot analysis for IGF-1R levels using IGF-1R antibody shows higher expression of IGF-1R protein in UM cell lines (92.1 and Mel270) vs. non-cancerous melanocytes, keratinocytes and fibroblasts. (<b>E</b>) FACS histogram plots showing cell surface expression of IGF-1R in the UM cell lines (Mel285, Mel202, 92.1, OMM2.3, OMM1, MEL20-06-039, MEL20-07-070 and MEL20-09-196) stained with IGF-1R antibody (red lines). The isotype control is represented by the black lines in the FACS histograms, and these experiments were repeated twice.</p>
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<p><b>Expression of IGF-1R in UM tumors and cell lines.</b> (<b>A</b>) The IGF-1R mRNA expression levels in tumor and normal tissues were compared in 33 cancer (red dots) and corresponding normal (green dots) tissues through TCGA database analysis. The expression in UM is indicated by an arrow. (<b>B</b>) RT-PCR analyses showing IGF-1R mRNA levels in 10 different UM cell lines. (<b>C</b>) Western blot analysis showing IGF-1R activation/induction in UM cell lines with 75 ng/mL of IGF-1 treatment for 10 min. (<b>D</b>) Western blot analysis for IGF-1R levels using IGF-1R antibody shows higher expression of IGF-1R protein in UM cell lines (92.1 and Mel270) vs. non-cancerous melanocytes, keratinocytes and fibroblasts. (<b>E</b>) FACS histogram plots showing cell surface expression of IGF-1R in the UM cell lines (Mel285, Mel202, 92.1, OMM2.3, OMM1, MEL20-06-039, MEL20-07-070 and MEL20-09-196) stained with IGF-1R antibody (red lines). The isotype control is represented by the black lines in the FACS histograms, and these experiments were repeated twice.</p>
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<p><b>NT157 treatment reduces IRS-1 levels leading to a reduction of cell viability, migration, and induction of apoptosis in UM cell lines.</b> (<b>A</b>) TCGA database analysis shows high expression of IRS-1 mRNA in UM tumors (indicated by an arrow) among 33 cancer (red dots) and corresponding normal (green dots) tissues. (<b>B</b>) Immunohistochemical staining of matched primary (eye) and metastatic (liver) UM tumor tissues using IRS-1 antibody detects IRS-1 expression (purple) in both eye and liver (both 2× and 20× magnifications are shown). (<b>C</b>) Western blot analysis of cell extracts from UM cell lines (92.1, OMM2.5, OMM1, MEL20-06-039, MP65) treated with NT157 (1 µM) and probed with anti-IRS-1 antibody shows IRS-1 protein levels decrease in UM cell lines with NT157 treatment for 48 h. (<b>D</b>) Quantification of percent cell survival using MTT-based assays in UM cell lines (MP46, MM28, MEL202, 92.1, MP65, and MP41) with (0.05, 0.1, 0.25, 0.5, 1.0, 2.5 µM) or without NT157 treatment (72 h) shows NT157 dose-dependent decrease in cell survival. The bar graphs represent a percentage of cell survival and are a mean ± SD of three independent experiments. p-values were calculated by comparing untreated controls with NT157 treatment doses (<span class="html-italic">* p</span> &lt; 0.05; <span class="html-italic">** p</span> &lt; 0.01; <span class="html-italic">*** p</span> &lt; 0.001). (<b>E</b>) Colony formation assay: Representative images of crystal violet staining shows fewer colonies formed by UM cell lines (MP46, MM28, MEL202, 92.1, MP65, and MP41) with NT157 treatment (1 and 2.5 µM for seven days) compared to untreated controls. (<b>F</b>) Representative FACS histograms of DNA content detected by propidium iodide staining to detect cell cycle status in UM cell lines (MP46, MM28 and MEL20-06-039, and MP65) show a dose-dependent increase in the number of cells in G0/G1 phase with NT157 treatment (1 and 2.5 µM for 72 h) vs. no treatment. (<b>G</b>) Western blot analysis of total cell extracts shows NT157 dose-dependent (1 and 2.5 µM for 72 h) increase in cleaved PARP and decrease in caspase 3 levels detected by respective antibodies in UM cell lines (MEL202, MEL270, 92.1, and MEL20-06-039) compared to untreated controls. (<b>H</b>) Quantification of cell migration in UM cell lines (OMM1, 92.1, MEL202, MP65, and MM28) shows a reduction in migration of cells treated with NT157 (2.5 µM) compared to untreated controls. An average of five fields of cells/filter were counted under a microscope with 40× magnification. The average number of cells counted/field were obtained in two independent experiments and the mean ± SD of these average cell counts/field were plotted as bar graphs. <span class="html-italic">p</span>-values were calculated by comparing untreated vs. NT157 treated cells (<span class="html-italic">* p</span> &lt; 0.05; <span class="html-italic">** p</span> &lt; 0.01; <span class="html-italic">*** p</span> &lt; 0.001).</p>
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<p><b>NT157 treatment reduces IRS-1 levels leading to a reduction of cell viability, migration, and induction of apoptosis in UM cell lines.</b> (<b>A</b>) TCGA database analysis shows high expression of IRS-1 mRNA in UM tumors (indicated by an arrow) among 33 cancer (red dots) and corresponding normal (green dots) tissues. (<b>B</b>) Immunohistochemical staining of matched primary (eye) and metastatic (liver) UM tumor tissues using IRS-1 antibody detects IRS-1 expression (purple) in both eye and liver (both 2× and 20× magnifications are shown). (<b>C</b>) Western blot analysis of cell extracts from UM cell lines (92.1, OMM2.5, OMM1, MEL20-06-039, MP65) treated with NT157 (1 µM) and probed with anti-IRS-1 antibody shows IRS-1 protein levels decrease in UM cell lines with NT157 treatment for 48 h. (<b>D</b>) Quantification of percent cell survival using MTT-based assays in UM cell lines (MP46, MM28, MEL202, 92.1, MP65, and MP41) with (0.05, 0.1, 0.25, 0.5, 1.0, 2.5 µM) or without NT157 treatment (72 h) shows NT157 dose-dependent decrease in cell survival. The bar graphs represent a percentage of cell survival and are a mean ± SD of three independent experiments. p-values were calculated by comparing untreated controls with NT157 treatment doses (<span class="html-italic">* p</span> &lt; 0.05; <span class="html-italic">** p</span> &lt; 0.01; <span class="html-italic">*** p</span> &lt; 0.001). (<b>E</b>) Colony formation assay: Representative images of crystal violet staining shows fewer colonies formed by UM cell lines (MP46, MM28, MEL202, 92.1, MP65, and MP41) with NT157 treatment (1 and 2.5 µM for seven days) compared to untreated controls. (<b>F</b>) Representative FACS histograms of DNA content detected by propidium iodide staining to detect cell cycle status in UM cell lines (MP46, MM28 and MEL20-06-039, and MP65) show a dose-dependent increase in the number of cells in G0/G1 phase with NT157 treatment (1 and 2.5 µM for 72 h) vs. no treatment. (<b>G</b>) Western blot analysis of total cell extracts shows NT157 dose-dependent (1 and 2.5 µM for 72 h) increase in cleaved PARP and decrease in caspase 3 levels detected by respective antibodies in UM cell lines (MEL202, MEL270, 92.1, and MEL20-06-039) compared to untreated controls. (<b>H</b>) Quantification of cell migration in UM cell lines (OMM1, 92.1, MEL202, MP65, and MM28) shows a reduction in migration of cells treated with NT157 (2.5 µM) compared to untreated controls. An average of five fields of cells/filter were counted under a microscope with 40× magnification. The average number of cells counted/field were obtained in two independent experiments and the mean ± SD of these average cell counts/field were plotted as bar graphs. <span class="html-italic">p</span>-values were calculated by comparing untreated vs. NT157 treated cells (<span class="html-italic">* p</span> &lt; 0.05; <span class="html-italic">** p</span> &lt; 0.01; <span class="html-italic">*** p</span> &lt; 0.001).</p>
Full article ">Figure 2 Cont.
<p><b>NT157 treatment reduces IRS-1 levels leading to a reduction of cell viability, migration, and induction of apoptosis in UM cell lines.</b> (<b>A</b>) TCGA database analysis shows high expression of IRS-1 mRNA in UM tumors (indicated by an arrow) among 33 cancer (red dots) and corresponding normal (green dots) tissues. (<b>B</b>) Immunohistochemical staining of matched primary (eye) and metastatic (liver) UM tumor tissues using IRS-1 antibody detects IRS-1 expression (purple) in both eye and liver (both 2× and 20× magnifications are shown). (<b>C</b>) Western blot analysis of cell extracts from UM cell lines (92.1, OMM2.5, OMM1, MEL20-06-039, MP65) treated with NT157 (1 µM) and probed with anti-IRS-1 antibody shows IRS-1 protein levels decrease in UM cell lines with NT157 treatment for 48 h. (<b>D</b>) Quantification of percent cell survival using MTT-based assays in UM cell lines (MP46, MM28, MEL202, 92.1, MP65, and MP41) with (0.05, 0.1, 0.25, 0.5, 1.0, 2.5 µM) or without NT157 treatment (72 h) shows NT157 dose-dependent decrease in cell survival. The bar graphs represent a percentage of cell survival and are a mean ± SD of three independent experiments. p-values were calculated by comparing untreated controls with NT157 treatment doses (<span class="html-italic">* p</span> &lt; 0.05; <span class="html-italic">** p</span> &lt; 0.01; <span class="html-italic">*** p</span> &lt; 0.001). (<b>E</b>) Colony formation assay: Representative images of crystal violet staining shows fewer colonies formed by UM cell lines (MP46, MM28, MEL202, 92.1, MP65, and MP41) with NT157 treatment (1 and 2.5 µM for seven days) compared to untreated controls. (<b>F</b>) Representative FACS histograms of DNA content detected by propidium iodide staining to detect cell cycle status in UM cell lines (MP46, MM28 and MEL20-06-039, and MP65) show a dose-dependent increase in the number of cells in G0/G1 phase with NT157 treatment (1 and 2.5 µM for 72 h) vs. no treatment. (<b>G</b>) Western blot analysis of total cell extracts shows NT157 dose-dependent (1 and 2.5 µM for 72 h) increase in cleaved PARP and decrease in caspase 3 levels detected by respective antibodies in UM cell lines (MEL202, MEL270, 92.1, and MEL20-06-039) compared to untreated controls. (<b>H</b>) Quantification of cell migration in UM cell lines (OMM1, 92.1, MEL202, MP65, and MM28) shows a reduction in migration of cells treated with NT157 (2.5 µM) compared to untreated controls. An average of five fields of cells/filter were counted under a microscope with 40× magnification. The average number of cells counted/field were obtained in two independent experiments and the mean ± SD of these average cell counts/field were plotted as bar graphs. <span class="html-italic">p</span>-values were calculated by comparing untreated vs. NT157 treated cells (<span class="html-italic">* p</span> &lt; 0.05; <span class="html-italic">** p</span> &lt; 0.01; <span class="html-italic">*** p</span> &lt; 0.001).</p>
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<p><b>Significant changes in cell signaling proteins detected post-NT157 treatment.</b> (<b>A</b>) RPPA protein profiling of four UM cell lines (MEL270, MM28, MEL-20-06-039, and 92.1; represented by each dot). The RPPA expression values are displayed on the y-axis for antibodies that show a significant difference (<span class="html-italic">p</span> &lt; 0.05) compared to the control sample. Cells were treated either for 24 or 48 h with a 1 or 2.5 µM concentration of NT157. Green dots represent untreated cells; orange and red dots represent cells treated with 1 and 2.5 µM of NT157, respectively for 24 and 48 h. (<b>B</b>) Western blot analyses to validate some of the significant changes observed in RPPA using antibodies against hexokinase-II, phospho-AKT, total AKT, and JNK2 show treatment and time-dependent (1 and 2.5 µM for 24 and 48 h) upregulation of hexokinase-II and downregulation of phospho-AKT.</p>
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<p><b>NT157 treatment reduces UM tumor growth in the chicken CAM model.</b> (<b>A</b>) H&amp;E (left) and pan melanoma cocktail (anti- HMB1, Tyrosinase, and S100 antibodies; right) staining of UM tumor tissues from 92.1 cells grown in chicken CAM model show the presence of melanoma cells. Representative (20×) and high magnification (inlay 2×) images shown as described. (<b>B</b>) Brightfield images of vehicle-treated (upper panel) and NT157-treated (1 µM; lower panel) representative tumors (two representative images per treatment) show a reduction of tumor size with NT157 treatment for four days. (<b>C</b>) Representative bioluminescence images of chicken eggs bearing luciferase-tagged UM cells (92.1) treated with vehicle controls (left panel) or NT157 (1 µM for four days) (right panel). (<b>D</b>) Tumor size of the implants was calculated as the total flux (photons per second) from the images in (<b>C</b>), which shows a reduction in tumor size with NT157 treatment; mean ± SD of three independent experiments was plotted as a graph; <span class="html-italic">* p</span> = 0.022. A student <span class="html-italic">t</span>-test was used for statistical analysis.</p>
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<p><b>NT157 treatment inhibits UM tumor growth in a subQ mouse model</b>. Subcutaneous tumors grown in NSG mice with 0.5 million UM cells 92.1 (top) and MM28 (bottom) were treated intraperitoneally with NT157 (50 mg/kg body weight), three times per week after tumors reached ~100 mm size. Tumor volume was measured twice weekly with slide calipers. When more than two tumors reached 1000 mm<sup>3</sup> volume in any one group, the experiment was ended, and tumors were harvested. (<b>A</b>) Shows harvested tumors from untreated and NT157-treated groups at the endpoint. (<b>B</b>) Shows a reduction in collective tumor weight at the endpoint and (<b>C</b>) A time-dependent reduction in tumor volume with NT157 treatment (1 µM) vs. untreated controls. Student <span class="html-italic">t</span>-test was used for statistical analysis and the data points marked ** and * show <span class="html-italic">p</span> &lt; 0.01 and &lt;0.05, respectively.</p>
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28 pages, 1880 KiB  
Review
Mechanisms of Drug Resistance in Ovarian Cancer and Associated Gene Targets
by Kharimat Lora Alatise, Samantha Gardner and Angela Alexander-Bryant
Cancers 2022, 14(24), 6246; https://doi.org/10.3390/cancers14246246 - 18 Dec 2022
Cited by 39 | Viewed by 4465
Abstract
In the United States, over 100,000 women are diagnosed with a gynecologic malignancy every year, with ovarian cancer being the most lethal. One of the hallmark characteristics of ovarian cancer is the development of resistance to chemotherapeutics. While the exact mechanisms of chemoresistance [...] Read more.
In the United States, over 100,000 women are diagnosed with a gynecologic malignancy every year, with ovarian cancer being the most lethal. One of the hallmark characteristics of ovarian cancer is the development of resistance to chemotherapeutics. While the exact mechanisms of chemoresistance are poorly understood, it is known that changes at the cellular and molecular level make chemoresistance challenging to treat. Improved therapeutic options are needed to target these changes at the molecular level. Using a precision medicine approach, such as gene therapy, genes can be specifically exploited to resensitize tumors to therapeutics. This review highlights traditional and novel gene targets that can be used to develop new and improved targeted therapies, from drug efflux proteins to ovarian cancer stem cells. The review also addresses the clinical relevance and landscape of the discussed gene targets. Full article
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<p>Generic scheme of drug efflux proteins. The adenosine triphosphate (ATP) Binding Cassette (ABC) family of membrane proteins enables the efflux of therapeutics. ABC transporters (light purple) use ATP to pump chemotherapeutics (dark purple) out of the cell.</p>
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<p>The intrinsic and extrinsic apoptosis pathways. The extrinsic apoptosis pathway is initiated through ligand–receptor interactions. The intrinsic pathway is mediated by the release of <span class="html-italic">Smac</span> and cytochrome C from mitochondria (green). Inhibitory proteins (dark purple) can interrupt the caspase cascade (pink), ultimately preventing apoptosis.</p>
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<p>(<b>A</b>) Increased expression of DNA damage and repair proteins can cause resistance to platinum-based chemotherapeutics in ovarian cancer. (<b>B</b>) DNA damage by chemotherapeutics results in the activation of four DNA repair pathways. Increased expression of proteins within these pathways (green) can reverse this damage through repair mechanisms.</p>
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<p>Scheme of cancer stem cells (CSCs) depicting the role of CSCs in ovarian cancer recurrence. CSCs are inherently resistant to chemotherapy and radiation and remain in the tumor tissue after treatment, causing tumor cell production and tumor recurrence. Tumor cells (red), CSCs (yellow).</p>
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20 pages, 2653 KiB  
Review
Resistance to Antiangiogenic Therapy in Hepatocellular Carcinoma: From Molecular Mechanisms to Clinical Impact
by Piera Federico, Emilio Francesco Giunta, Andrea Tufo, Francesco Tovoli, Angelica Petrillo and Bruno Daniele
Cancers 2022, 14(24), 6245; https://doi.org/10.3390/cancers14246245 - 18 Dec 2022
Cited by 1 | Viewed by 2865
Abstract
Antiangiogenic drugs were the only mainstay of advanced hepatocellular carcinoma (HCC) treatment from 2007 to 2017. However, primary or secondary resistance hampered their efficacy. Primary resistance could be due to different molecular and/or genetic characteristics of HCC and their knowledge would clarify the [...] Read more.
Antiangiogenic drugs were the only mainstay of advanced hepatocellular carcinoma (HCC) treatment from 2007 to 2017. However, primary or secondary resistance hampered their efficacy. Primary resistance could be due to different molecular and/or genetic characteristics of HCC and their knowledge would clarify the optimal treatment approach in each patient. Several molecular mechanisms responsible for secondary resistance have been discovered over the last few years; they represent potential targets for new specific drugs. In this light, the advent of checkpoint inhibitors (ICIs) has been a new opportunity; however, their use has highlighted other issues: the vascular normalization compared to a vessel pruning to promote the delivery of an active cancer immunotherapy and the development of resistance to immunotherapy which leads to a better selection of patients as candidates for ICIs. Nevertheless, the combination of antiangiogenic therapy plus ICIs represents an intriguing approach with high potential to improve the survival of these patients. Waiting for results from ongoing clinical trials, this review depicts the current knowledge about the resistance to antiangiogenic drugs in HCC. It could also provide updated information to clinicians focusing on the most effective combinations or sequential approaches in this regard, based on molecular mechanisms. Full article
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<p>Main mechanisms of anti-angiogenic drug resistance in HCC. In this figure, the main mechanisms of resistance are summarized, represented at three levels: intranuclear, intracytoplasmic and tumor microenvironment.</p>
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<p>Liver tumor display vascular abnormalities. Liver tumor vessels have abnormal blood flow and are excessively leaky. This results in hypoxia and acidosis which contribute to immunosuppression in the TME: expansion of immunosuppressive regulatory T (Treg) cells and of myeloid-derived suppressor cells (MDSC); decrease in the infiltration of the CD8+ T cells; reprogramming of tumor-associated macrophages (TAMs) from an anticancer M1-like phenotype towards the pro-tumor M2 phenotype. The normalization process is transient and its onset provides an immune-supportive microenvironment, an efficient infiltration of immune cells and the delivery of anticancer therapy including immunotherapy. A judicious application of antiangiogenic therapy, neither too high nor too low, allows for the normalization window and the related benefits to be obtained.</p>
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<p>The IMbrave150 trial and further updates.</p>
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<p>How to overcome the resistance: an overview. This schematic representation underlines the open questions about resistance to antiangiogenic therapy and immunotherapy and the possibilities of overcoming them as well as the importance of stratifying patients into different subtypes to achieve higher response rates. Abbreviations: c-MET, c-mesenchymal-epithelial transition receptor; PI3K/Akt, phosphatidylinositol-3-kinase/Akt; mTOR, mammalian target of rapamycin; ADAs, anti-drug antibodies; EGFR, epidermal growth factor receptor; PD-1, programmed cell death; CXCR4, CXC chemokine receptor type 4; TKI, tyrosine kinase inhibitor; ICIs, immune checkpoint inhibitors; Gd-EOB-DTPA enhanced MRE, gadolinium-ethoxybenzyl-diethylenetriamine-enhanced magnetic resonance; FDG-PET/CT, fluoro-2-deoxy-D-glucose-PET/CT.</p>
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11 pages, 1273 KiB  
Article
Clinical and Cytogenetic Characterization of Early and Late Relapses in Patients Allografted for Myeloid Neoplasms with a Myelodysplastic Component
by Victoria Platte, Anika Bergmann, Barbara Hildebrandt, Dagmar Wieczorek, Esther Schuler, Ulrich Germing, Jennifer Kaivers, Rainer Haas, Guido Kobbe, Thomas Schroeder and Christina Rautenberg
Cancers 2022, 14(24), 6244; https://doi.org/10.3390/cancers14246244 - 18 Dec 2022
Cited by 2 | Viewed by 1752
Abstract
An improved understanding of relapse kinetics is required to optimize detection and treatment strategies for the post-transplant relapse of myeloid neoplasms. Therefore, we retrospectively analyzed data from 91 patients allografted for MDS (n = 54), AML-MRC (n = 29) and chronic [...] Read more.
An improved understanding of relapse kinetics is required to optimize detection and treatment strategies for the post-transplant relapse of myeloid neoplasms. Therefore, we retrospectively analyzed data from 91 patients allografted for MDS (n = 54), AML-MRC (n = 29) and chronic myelomonocytic leukemia (CMML, n = 8), who relapsed after transplant. Patients with early (<12 months, n = 56) and late relapse (>12 months, n = 35) were compared regarding patient-, disease- and transplant-related factors, including karyotype analyses at diagnosis and relapse. After a median follow-up of 17.4 months after relapse, late relapses showed improved outcomes compared with early relapses (2-yr OS 67% vs. 32%, p = 0.0048). Comparing frequency of distinct patient-, disease- and transplant-related factors among early and late relapses, complex karyotype (p = 0.0004) and unfavorable disease risk at diagnosis (p = 0.0008) as well as clonal evolution at relapse (p = 0.03) were more common in early than in late relapses. Furthermore, patients receiving transplant without prior cytoreduction or in complete remission were more frequently present in the group of late relapses. These data suggest that cytogenetics rather than disease burden at diagnosis and transplant-related factors determine the timepoint of post-transplant relapse and that upfront transplantation may be favored in order to delay relapse. Full article
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<p>Timepoint of post-transplant relapses. Median time from allo-SCT to relapse was 5.5 months (range 0.5 to 109.8 months), and 30%, 55%, 62%, 80% and 100% relapsed within 3, 6, 12, 24 and &gt;24 months, respectively. No., number.</p>
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<p>Outcome after post-transplant relapse. (<b>a</b>) Overall survival of the whole cohort (<span class="html-italic">n</span> = 91), median OS of the whole cohort was 14.1 months (range 0.8–129.3 months) corresponding to a 2-yr OS of 44% [95% CI 32–56%] after relapse. (<b>b</b>) Outcome of patients with early and late relapses, patients with late (green line, <span class="html-italic">n</span> = 35) relapse showed a significantly improved outcome compared with patients with early (red line, <span class="html-italic">n</span> = 56) relapse (2-yr OS 66.5% vs. 31.7%, <span class="html-italic">p</span> = 0.0048). Accordingly, the hazard to die after a late relapse was significantly lower than that after an early relapse (HR 0.36 [95%CI 0.19–0.67], <span class="html-italic">p</span> = 0.0048). Allo-SCT, allogeneic hematopietic stem-cell transplantation; HR, hazard ratio; CI, cumulative incidence; OS, overall survival; yr, year.</p>
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<p>Comparative karyotype analyses prior to allo-SCT and at the time of early relapse (<b>a</b>) or late relapse (<b>b</b>): (<b>a</b>) relapse ≤12 months post allo-SCT, (<b>b</b>) relapse &gt;12 months post allo-SCT. Karyotype changes more frequently occurred in the subgroup of patients with early (<span class="html-italic">n</span> = 28/37, 76%) than those with late (<span class="html-italic">n</span> = 13/27, 48%) relapse (<span class="html-italic">p</span> = 0.03). The proportion of patients showing a different karyotype in a relapse sample compared with a sample of prior-to allo-SCT was depicted in dark brown (=change), while the proportion of patients whose karyotype did not change at relapse compared with a pretransplant sample was illustrated in dark green (=no change). Karyotype changes were further described as either clonal evolution (appearance of new clonal alterations in addition to those documented at diagnosis), appearance of a new clone or a loss of an abnormal clone and were depicted in different shades of brown. In total, four patients developed two karyotype changes and therefore appeared twice in the descriptive subgroups. Within the early relapses, one patient harbored a combination of a new clone/clonal evolution and another patient a clonal evolution/loss of abnormal clone. Within the late relapses, two patients developed both a new clone/loss of abnormal clone. Patients without karyotype changes were further subdivided into those exposing a normal or an abnormal karyotype, which were illustrated in different shades of green; allo-SCT, allogeneic hematopoietic stem-cell transplantation.</p>
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15 pages, 307 KiB  
Article
Anastomotic Leakage after Colorectal Surgery in Ovarian Cancer: Drainage, Stoma Utility and Risk Factors
by Liliana Mereu, Francesca Dalprà, Valeria Berlanda, Riccardo Pertile, Daniela Coser, Basilio Pecorino, Maria Gabriella D’Agate, Francesco Ciarleglio, Alberto Brolese and Saverio Tateo
Cancers 2022, 14(24), 6243; https://doi.org/10.3390/cancers14246243 - 18 Dec 2022
Cited by 4 | Viewed by 2109
Abstract
Objective: to evaluate the incidence of anastomotic leakage (AL), risk factors and utility of drainage and stoma in patients undergoing intestinal surgery for ovarian cancer in a single institution and in a review of the literature. Methods: retrospective study that includes consecutive patients [...] Read more.
Objective: to evaluate the incidence of anastomotic leakage (AL), risk factors and utility of drainage and stoma in patients undergoing intestinal surgery for ovarian cancer in a single institution and in a review of the literature. Methods: retrospective study that includes consecutive patients undergoing debulking surgery with en bloc pelvic resection with rectosigmoid colectomy for ovarian cancer between 1 November 2011 and 31 December 2021. Data regarding patient and tumour characteristics, surgical procedure, hospitalisation, complications and follow-up were recorded and analysed. The PubMed database was explored for recent publications on this topic. Results: Seventy-five patients were enrolled in the study. All anastomoses were performed at a distance of >6 cm from the anal margin, with negative leak tests and tension-free anastomosis. Diverting stoma were performed in just three patients (4%). At least one perianastomotic pelvic drain was positioned in 71 patients (94.7%) and was removed on average on postoperative day 7. Four patients (5.3%) experienced AL. In all cases, the drain content was not the only sign of complication, as the clinical signs were also highly suggestive. Just one patient received conservative treatment. Average postoperative hospitalisation was 14.6 days (SD: ±9.7). There were no deaths at 30 and 60 days after surgery. Between the AL and non-AL groups, statistically significant differences were observed for age, Charlson Comorbidity Index, length of the intestinal resection and fitness for chemotherapy at 30 days. In ovarian cancer, rectosigmoid resection is a standardised procedure with comparable results for AL, and risk factors for AL are discretely homogeneous. What is neither homogeneous nor standardised according to the literature is the use of stomas and/or drains. Conclusion: use in the future of protective stoma and/or intra-abdominal drains is to be explored in selected and standardised situations to verify their preventive role. Full article
11 pages, 821 KiB  
Article
Predictive Value of 18F-Fluorodeoxyglucose Positron-Emission Tomography Metabolic and Volumetric Parameters for Systemic Metastasis in Tonsillar Cancer
by Jooin Bang, Hye Lim Park, Ie Ryung Yoo, Hyun-Il Shin, Geun-Jeon Kim, Dong-Il Sun and Sang-Yeon Kim
Cancers 2022, 14(24), 6242; https://doi.org/10.3390/cancers14246242 - 18 Dec 2022
Cited by 1 | Viewed by 1791
Abstract
Although the prognosis of tonsillar cancer (human papillomavirus-positive oropharyngeal squamous cell carcinoma) is improving, disease control failure (distant metastasis) still occurs in some cases. We explored whether several 18F-fluorodeoxyglucose (FDG) positron-emission tomography (PET) parameters can predict metastasis. We retrospectively reviewed the medical [...] Read more.
Although the prognosis of tonsillar cancer (human papillomavirus-positive oropharyngeal squamous cell carcinoma) is improving, disease control failure (distant metastasis) still occurs in some cases. We explored whether several 18F-fluorodeoxyglucose (FDG) positron-emission tomography (PET) parameters can predict metastasis. We retrospectively reviewed the medical records of 55 patients with tonsil squamous cell carcinoma who underwent pretreatment 18F-FDG positron-emission tomography/computed tomography (PET/CT) followed by primary surgery. During the follow-up period, systemic metastases were found in 7 of the 55 patients. The most common sites were the lungs (33%), bone (22%), brain/skull base (22%), small bowel (11%), and liver (11%). Pathologically, P53 mutation was less common in patients with systemic metastasis (41.7% vs. 14.3%, p = 0.054) than without systemic metastasis. In terms of PET parameters, the metabolic tumor volume (MTV2.5) and total lesion glycolysis (TLG2.5) values were lower in the primary tumor, and higher in the metastatic lymph nodes, of human papillomavirus (HPV)-positive compared to HPV-negative patients (all p < 0.05). The MTV2.5, TLG2.5, and tumor–to–liver uptake ratio were 36.07 ± 54.24 cm3, 183.46 ± 298.62, and 4.90 ± 2.77, respectively, in the systemic metastasis group, respectively; all of these values were higher than those of the patients without systemic metastasis (all p < 0.05). The MTV2.5 value was significantly different between the groups even when the values for the primary tumor and metastatic lymph nodes were summed (53.53 ± 57.78 cm3, p = 0.036). The cut-off value, area under the curve (95% confidence interval), sensitivity, and specificity of MTV2.5 for predicting systemic metastasis were 11.250 cm3, 0.584 (0.036–0.832), 0.571, and 0.565, respectively. The MTV2.5 of metastatic lymph nodes and summed MTV2.5 values of the primary tumor and metastatic lymph nodes were significantly higher in tonsillar cancer patients with than without systemic metastases. We suggest PET/CT scanning for pre-treatment cancer work-up and post-treatment surveillance to consider additional systemic therapy in patients with a high risk of disease control failure. Full article
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<p>Type of surgery.</p>
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<p>Comparison of overall survival according to HPV status.</p>
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<p>ROC curve analysis for searching the valuable parameters to predict systemic metastasis.</p>
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14 pages, 1817 KiB  
Article
Lung-Heart Outcomes and Mortality through the 2020 COVID-19 Pandemic in a Prospective Cohort of Breast Cancer Radiotherapy Patients
by Vincent Vinh-Hung, Olena Gorobets, Nele Adriaenssens, Hilde Van Parijs, Guy Storme, Dirk Verellen, Nam P. Nguyen, Nicolas Magne and Mark De Ridder
Cancers 2022, 14(24), 6241; https://doi.org/10.3390/cancers14246241 - 18 Dec 2022
Cited by 2 | Viewed by 1966
Abstract
We investigated lung-heart toxicity and mortality in 123 women with stage I-II breast cancer enrolled in 2007–2011 in a prospective trial of adjuvant radiotherapy (TomoBreast). We were concerned whether the COVID-19 pandemic affected the outcomes. All patients were analyzed as a single cohort. [...] Read more.
We investigated lung-heart toxicity and mortality in 123 women with stage I-II breast cancer enrolled in 2007–2011 in a prospective trial of adjuvant radiotherapy (TomoBreast). We were concerned whether the COVID-19 pandemic affected the outcomes. All patients were analyzed as a single cohort. Lung-heart status was reverse-scored as freedom from adverse-events (fAE) on a 1–5 scale. Left ventricular ejection fraction (LVEF) and pulmonary function tests were untransformed. Statistical analyses applied least-square regression to calendar-year aggregated data. The significance of outliers was determined using the Dixon and the Grubbs corrected tests. At 12.0 years median follow-up, 103 patients remained alive; 10-years overall survival was 87.8%. In 2007–2019, 15 patients died, of whom 11 were cancer-related deaths. In 2020, five patients died, none of whom from cancer. fAE and lung-heart function declined gradually over a decade through 2019, but deteriorated markedly in 2020: fAE dipped significantly from 4.6–4.6 to 4.3–4.2; LVEF dipped to 58.4% versus the expected 60.3% (PDixon = 0.021, PGrubbs = 0.054); forced vital capacity dipped to 2.4 L vs. 2.6 L (PDixon = 0.043, PGrubbs = 0.181); carbon-monoxide diffusing capacity dipped to 12.6 mL/min/mmHg vs. 15.2 (PDixon = 0.008, PGrubbs = 0.006). In conclusion, excess non-cancer mortality was observed in 2020. Deaths in that year totaled one-third of the deaths in the previous decade, and revealed observable lung-heart deterioration. Full article
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<p>Rates of heart and lung toxicity grades over the calendar years. G0, no toxicity. G1–G4, toxicity Grade 1–4. Open circle: rate averaged on all patients observed in the year. Filled circle: rate observed in 2020, year of the COVID pandemic. Line: ordinary least squares fitted on years 2009–2021 excluding 2020. Grey band: 95% confidence interval of the least squares fit.</p>
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<p>The effect by year on heart and lung toxicity-free scores. Continuous toxicity-free score scaled from 1 (worst, no freedom from toxicity) to 5 (best, fully free of toxicity), where score = (5—Grade). Open circle: score averaged on all patients observed in the year. Filled circle: score observed in 2020, year of the COVID pandemic. Line: ordinary least squares fitted on years 2009–2021 excluding 2020. Grey band: 95% confidence interval of the least squares fit.</p>
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<p>The effect by year on heart and lung function. Open circle: value of the function averaged on all patients observed in the year. Filled circle: value observed in 2020, year of the COVID pandemic. Line: ordinary least squares fitted on years 2009–2021 excluding 2020. Grey band: 95% confidence interval of the least squares fit. The slopes per year are: Left ventricular ejection fraction (%) −0.29; Forced vital capacity (L) −0.063 (=63 mL); Residual volume (L) +0.052 (=52 mL); carbon-monoxide (CO) diffusing capacity (ml/min/mmHg) −0.29.</p>
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<p>Overall survival and breast cancer specific survival of the study population.</p>
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16 pages, 14000 KiB  
Article
Ex Vivo Drug Sensitivity Correlates with Clinical Response and Supports Personalized Therapy in Pediatric AML
by Debbie C. Strachan, Christine J. Gu, Ryosuke Kita, Erica K. Anderson, Michelle A. Richardson, George Yam, Graham Pimm, Jordan Roselli, Alyssa Schweickert, Maci Terrell, Raushan Rashid, Alan K. Gonzalez, Hailey H. Oviedo, Michelle C. Alozie, Tamilini Ilangovan, Andrea N. Marcogliese, Hiroomi Tada, Marianne T. Santaguida and Alexandra M. Stevens
Cancers 2022, 14(24), 6240; https://doi.org/10.3390/cancers14246240 - 18 Dec 2022
Cited by 5 | Viewed by 3135
Abstract
Acute myeloid leukemia (AML) is a heterogeneous disease that accounts for ~20% of all childhood leukemias, and more than 40% of children with AML relapse within three years of diagnosis. Although recent efforts have focused on developing a precise medicine-based approach towards treating [...] Read more.
Acute myeloid leukemia (AML) is a heterogeneous disease that accounts for ~20% of all childhood leukemias, and more than 40% of children with AML relapse within three years of diagnosis. Although recent efforts have focused on developing a precise medicine-based approach towards treating AML in adults, there remains a critical gap in therapies designed specifically for children. Here, we present ex vivo drug sensitivity profiles for children with de novo AML using an automated flow cytometry platform. Fresh diagnostic blood or bone marrow aspirate samples were screened for sensitivity in response to 78 dose conditions by measuring the reduction in leukemic blasts relative to the control. In pediatric patients treated with conventional chemotherapy, comprising cytarabine, daunorubicin and etoposide (ADE), ex vivo drug sensitivity results correlated with minimal residual disease (r = 0.63) and one year relapse-free survival (r = 0.70; AUROC = 0.94). In the de novo ADE analysis cohort of 13 patients, AML cells showed greater sensitivity to bortezomib/panobinostat compared with ADE, and comparable sensitivity between venetoclax/azacitidine and ADE ex vivo. Two patients showed a differential response between ADE and bortezomib/panobinostat, thus supporting the incorporation of ex vivo drug sensitivity testing in clinical trials to further evaluate the predictive utility of this platform in children with AML. Full article
(This article belongs to the Special Issue Advances in Pediatric Acute Myeloid Leukemia)
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<p>Ex vivo drug sensitivity profiling for 31 pediatric AML patients. (<b>A</b>) Fresh blood or bone marrow aspirate samples were collected for this study prior to treatment on day 0, and/or at the end of induction (EOI), from 31 pediatric AML patients diagnosed at Texas Children’s Hospital. Twenty-seven patients received cytarabine, daunorubicin, and etoposide (ADE) as backbone chemotherapy, and four patients did not receive an ADE backbone. (<b>B</b>) Patients were stratified by induction chemotherapy, disease status, pre-treatment sample collection, and matching ex vivo data. R/R, relapsed or refractory. (<b>C</b>) Ex vivo drug sensitivity was profiled using an automated flow cytometry-based platform. RBC, red blood cell. (<b>D</b>) Heat map of ex vivo drug sensitivity results that passed the data quality control, including 48 total samples from 27 pediatric AML patients (columns) in response to 78 dose conditions (rows). Patients were clustered based on differential ex vivo drug sensitivity using hierarchical clustering (Euclidean distance metric, Ward linkage criterion). Cell color indicates normalized blast counts &lt;1 (red; reduction in blasts) or normalized blast counts &gt;= 1 (blue; no or low reduction in blasts). Rows above the heat map indicate selected clinical and biologic variables. UPN, unique patient number; F, female; M, male; R/R, relapse/refractory; A, alive; DD, died of disease; TRM, treatment related mortality; CNS, central nervous system; FAB, French–American–British; BM, bone marrow; PB, peripheral blood; PDX, patient-derived xenograft mouse model; MRD, minimal residual disease; CPX, CPX-351; BMT, bone marrow transplant; Day, readout day for ex vivo drug sensitivity; * status for CPX, ADE, BMT; nan, not reported.</p>
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<p>Ex vivo drug sensitivity profiling for 31 pediatric AML patients. (<b>A</b>) Fresh blood or bone marrow aspirate samples were collected for this study prior to treatment on day 0, and/or at the end of induction (EOI), from 31 pediatric AML patients diagnosed at Texas Children’s Hospital. Twenty-seven patients received cytarabine, daunorubicin, and etoposide (ADE) as backbone chemotherapy, and four patients did not receive an ADE backbone. (<b>B</b>) Patients were stratified by induction chemotherapy, disease status, pre-treatment sample collection, and matching ex vivo data. R/R, relapsed or refractory. (<b>C</b>) Ex vivo drug sensitivity was profiled using an automated flow cytometry-based platform. RBC, red blood cell. (<b>D</b>) Heat map of ex vivo drug sensitivity results that passed the data quality control, including 48 total samples from 27 pediatric AML patients (columns) in response to 78 dose conditions (rows). Patients were clustered based on differential ex vivo drug sensitivity using hierarchical clustering (Euclidean distance metric, Ward linkage criterion). Cell color indicates normalized blast counts &lt;1 (red; reduction in blasts) or normalized blast counts &gt;= 1 (blue; no or low reduction in blasts). Rows above the heat map indicate selected clinical and biologic variables. UPN, unique patient number; F, female; M, male; R/R, relapse/refractory; A, alive; DD, died of disease; TRM, treatment related mortality; CNS, central nervous system; FAB, French–American–British; BM, bone marrow; PB, peripheral blood; PDX, patient-derived xenograft mouse model; MRD, minimal residual disease; CPX, CPX-351; BMT, bone marrow transplant; Day, readout day for ex vivo drug sensitivity; * status for CPX, ADE, BMT; nan, not reported.</p>
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<p>Ex vivo drug sensitivity to ADE correlates with clinical response. Diagnostic samples from 13 de novo pediatric AML patients that received ADE were screened for ADE sensitivity ex vivo. Violin plots to measure the correlation between normalized blast counts in the DSP and (<b>A</b>) minimal residual disease and (<b>B</b>) one year relapse-free survival. Lower dashed line at y = 0 indicates no blasts remaining following treatment with the drug. Upper dashed line at 1.0 indicates blast counts were comparable to the DMSO control. AUROC, Area Under the Receiver Operating Characteristic curve. (<b>C</b>) Log odds ratio comparing MRD &gt; 1% with a single mutational or clinical attribute (rows). Black boxes indicate the log odds ratio on a log scale, with the size of the box being proportional to the number of patient samples. (<b>D</b>) Relapse-free survival curves and (<b>E</b>) incidence of relapse following induction for 12 patients treated with ADE. One patient died from treatment-related mortality and is excluded from this analysis cohort. Patients were stratified into two DSP groups based on high sensitivity to ADE ex vivo (DSP &lt; 0.7; red) and low sensitivity to ADE ex vivo (DSP &gt;= 0.7; blue). <span class="html-italic">p</span>-values were determined using the Log-rank (Mantel-Cox) test.</p>
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<p>Patients pAML3 and pAML8 show distinct ex vivo drug sensitivity profiles. (<b>A</b>) Disease course and treatment timelines for patients pAML3 and pAML8. (<b>B</b>) Scatterplot comparing normalized blast counts for patients pAML3 (x-axis) and pAML8 (y-axis) in response to 29 matched drug conditions assayed ex vivo. Shaded region indicates conditions that showed sensitivity for patient pAML8 and not for patient pAML3. B/P = bortezomib/panobinostat. Normalized blast counts &gt; 1.4 are shown as 1.4. (<b>C</b>) Violin plot comparing the distribution of normalized blast counts for 13 patients in response to the indicated conditions. “Other” is the mean of the remaining 30 treatment conditions included in the DSP. Patient pAML3 is indicated in blue; patient pAML8 is indicated in red. Lower dashed line at y = 0 indicates no blasts remained following incubation with drug. Upper dashed line at 1.0 indicates no change in blast counts relative to DMSO control. Normalized blast counts &gt; 1.5 are shown as 1.5.</p>
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<p>Bortezomib in combination with panobinostat shows greater sensitivity than ADE ex vivo. (<b>A</b>) Median normalized blast counts for 13 patients in response to 37 conditions assayed ex vivo. Conditions are ordered from most to least sensitive starting from the left. Green bars highlight the 11 most sensitive conditions in the DSP. The others indicate the following conditions from left to right: enasidenib, gilteritinib, quizartinib, sunitinib, crenolanib, dexamethasone, dexamethasone/calcitrol, and midostaurin. Gray boxes indicate lower drug concentrations. (<b>B</b>) Box plot of the top 11 treatments. Normalized blast counts &gt; 1.4 are shown as 1.4. B/P, bortezomib/panobinostat; ADE, cytarabine/daunorubicin/etoposide. (<b>C</b>) Percentage of variation in the DSP explained by principal component (PC). (<b>D</b>) PC1 vs. PC2 principal component analysis plot to identify clustering of conditions that account for variance in ex vivo drug sensitivity. B/P is shaded in green. Conditions including cytarabine are shaded in blue.</p>
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<p>Differential response to ADE and Bortezomib/Panobinostat is observed ex vivo. (<b>A</b>) Comparison of normalized blast counts between ADE and bortezomib/panobinostat (B/P) in 13 diagnostic samples from patients with de novo AML. Dashed lines indicate cutoffs for high sensitivity (DSP &lt; 1.0 for B/P; DSP &lt; 0.7 for ADE). DSP values &gt; 1.4 are shown at 1.4. (<b>B</b>) Normalized blast counts for B/P, ADE, VEN/AZA (venetoclax/azacitidine), and VEN/DAC (venetoclax/decitabine) on a graded color-scale for high sensitivity (red) and low sensitivity (blue). Grey boxes indicate no data. Patients pAML3 (blue), pAML4 (purple), pAML6 (orange), and pAML8 (red) are labeled in the indicated colors.</p>
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13 pages, 1077 KiB  
Article
Different Oncologic Outcomes in Early-Onset and Late-Onset Sporadic Colorectal Cancer: A Regression Analysis on 2073 Patients
by Caterina Foppa, Annalisa Maroli, Sara Lauricella, Antonio Luberto, Carlotta La Raja, Francesca Bunino, Michele Carvello, Matteo Sacchi, Francesca De Lucia, Giuseppe Clerico, Marco Montorsi and Antonino Spinelli
Cancers 2022, 14(24), 6239; https://doi.org/10.3390/cancers14246239 - 18 Dec 2022
Cited by 13 | Viewed by 2652
Abstract
The incidence of colorectal cancer (CRC) is increasing in the population aged ≤ 49 (early-onset CRC-EOCRC). Recent studies highlighted the biological and clinical differences between EOCRC and late-onset CRC (LOCRC-age ≥ 50), while comparative results about long-term survival are still debated. This study [...] Read more.
The incidence of colorectal cancer (CRC) is increasing in the population aged ≤ 49 (early-onset CRC-EOCRC). Recent studies highlighted the biological and clinical differences between EOCRC and late-onset CRC (LOCRC-age ≥ 50), while comparative results about long-term survival are still debated. This study aimed to investigate whether age of onset may impact on oncologic outcomes in a surgical population of sporadic CRC patients. Patients operated on for sporadic CRC from January 2010 to January 2022 were allocated to the EOCRC and LOCRC groups. The primary endpoint was the recurrence/progression-free survival (R/PFS). A total of 423 EOCRC and 1650 LOCRC was included. EOCRC had a worse R/PFS (p < 0.0001) and cancer specific survival (p < 0.0001) compared with LOCRC. At Cox regression analysis, age of onset, tumoral stage, signet ring cells, extramural/lymphovascular/perineural veins invasion, and neoadjuvant therapy were independent risk factors for R/P. The analysis by tumoral stage showed an increased incidence of recurrence in stage I EOCRC (p = 0.014), and early age of onset was an independent predictor for recurrence (p = 0.035). Early age of onset was an independent predictor for worse prognosis, this effect was stronger in stage I patients suggesting a potentially—and still unknown—more aggressive tumoral phenotype in EOCRC. Full article
(This article belongs to the Special Issue Early Onset Colorectal Cancer: Epidemiology and Etiology)
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<p>R/PFS (recurrence/progression-free survival) of EOCRC (early-onset colorectal cancer) (red line) and LOCRC (late-onset colorectal cancer) (black line) patients. Data were compared with Kaplan–Meier analysis and log-rank (Mantel–Cox) test (HR = 1.89; 95% CI: 1.72–2.75; <span class="html-italic">p</span> &lt; 0.0001).</p>
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<p>R/PFS (recurrence/progression-free survival) of EOCRC (early-onset colorectal cancer) and LOCRC (late onset colorectal cancer) patients according to the postoperative tumoral stage: (<b>A</b>) RFS of EOCRC (red line) and LOCRC (black line) patients diagnosed with tumoral stage I were compared with Kaplan–Meier analysis and log-rank (Mantel–Cox) test (HR = 2.68; 95% CI: 1.07–6.72; <span class="html-italic">p</span> = 0.035). (<b>B</b>) RFS of EOCRC (red line) and LOCRC (black line) patients diagnosed with tumoral stage II were compared with Kaplan–Meier analysis and log-rank (Mantel˜Cox) test (HR = 0.98; 95% CI: 0.53–1.83; <span class="html-italic">p</span> = 0.955). (<b>C</b>) RFS of EOCRC (red line) and LOCRC (black line) patients diagnosed with tumoral stage III were compared with Kaplan˜Meier analysis and log-rank (Mantel˜Cox) test (HR = 1.43; 95% CI: 0.92–2.20; <span class="html-italic">p</span> = 0.108). (<b>D</b>) R/PFS of EOCRC (red line) and LOCRC (black line) patients diagnosed with tumoral stage IV were compared with Kaplan–Meier analysis and log-rank (Mantel–Cox) test (HR = 1.25; 95% CI: 0.93–1.67; <span class="html-italic">p</span> = 0.103).</p>
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