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11 pages, 975 KiB

Open AccessArticle

In Patients Treated by Selective Internal Radiotherapy, Cellular In Vitro Immune Function Is Predictive of Survival

by Aglaia Domouchtsidou, Ferdinand Beckmann, Beate Marenbach, Stefan P. Mueller, Jan Best, Ken Herrmann, Peter A. Horn, Vahé Barsegian and Monika Lindemann

Cancers 2023, 15(16), 4055; https://doi.org/10.3390/cancers15164055 - 11 Aug 2023

Viewed by 1376

Abstract

In patients with liver malignancies, the cellular immune function was impaired in vitro after selective internal radiotherapy (SIRT). Because immunosuppression varied substantially, in the current study, we investigated in 25 SIRT patients followed up for ten years whether the lymphocyte function was correlated [...] Read more.

In patients with liver malignancies, the cellular immune function was impaired in vitro after selective internal radiotherapy (SIRT). Because immunosuppression varied substantially, in the current study, we investigated in 25 SIRT patients followed up for ten years whether the lymphocyte function was correlated with survival. Peripheral blood mononuclear cells were stimulated with four microbial antigens (tuberculin, tetanus toxoid, Candida albicans and CMV) before therapy and at four time points thereafter, and lymphocyte proliferation was determined by H3-thymidine uptake. The median sum of the responses to these four antigens decreased from 39,464 counts per minute (CPM) increment (range 1080–204,512) before therapy to a minimum of 700 CPM increment on day 7 after therapy (0–93,187, p < 0.0001). At all five time points, the median survival in patients with weaker responses was 2- to 3.5-fold shorter (p < 0.05). On day 7, the median survival in patients with responses below and above the cutoff of a 2 CPM increment was 185 and 523 days, respectively (χ² = 9.4, p = 0.002). In conclusion, lymphocyte function could be a new predictor of treatment outcome after SIRT. Full article

(This article belongs to the Special Issue Tumor Microenvironment and Molecular Aberrations Convey Immune Evasion)

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Figure 1
Cellular response towards four microbial antigens in 25 patients treated by selective internal radiotherapy (SIRT). Panel (a) shows individual data prior to SIRT and one hour and on day 2, 7 and 28 thereafter, together with median and interquartile range. Red dots indicate values for patients with a short survival (<median of 369 days), and green dots those for patients with a long survival (≥median). Data were compared by 1-way ANOVA, and the comparison of data from all test points yielded a p value of <0.0001. p values in panel (a) indicate the significance of pairwise comparisons, corrected for multiple comparisons. Panel (b–f) indicate the results of a receiver operating characteristic (ROC) curve analysis of the cellular response towards four microbial antigens and of survival (<median vs. ≥median). Each of these panels provides information on area under the curve (AUC), cutoff, sensitivity, specificity and likelihood ratio. On day 7 (panel (e)), we considered two different cutoffs for the cumulative (cum.) antigen response, as we observed two maxima for the likelihood ratio. CPM incr., counts-per-minute increment, i.e., antigen-specific response minus the negative control. Full article ">Figure 2
Impact of the cumulative antigen response on the survival of 25 patients treated by selective internal radiotherapy (SIRT). Panel (a) shows the survival curves with respect to the cumulative (cum.) antigen response (towards four microbial antigens) prior to SIRT, and panel (b–f) show curves after SIRT. Please note that the analysis on day 7 after SIRT was performed with two different cutoff values, as explained in the legend to <a href="#cancers-15-04055-f001" class="html-fig">Figure 1</a>e. Survival curves were compared by the Log Rank (Mantel–Cox) test. CPM increment, counts-per-minute increment, i.e., antigen-specific response minus the negative control. Full article ">

17 pages, 2321 KiB

Open AccessArticle

Nigericin Boosts Anti-Tumor Immune Response via Inducing Pyroptosis in Triple-Negative Breast Cancer

by Lisha Wu, Shoumin Bai, Jing Huang, Guohui Cui, Qingjian Li, Jingshu Wang, Xin Du, Wenkui Fu, Chuping Li, Wei Wei, Huan Lin and Man-Li Luo

Cancers 2023, 15(12), 3221; https://doi.org/10.3390/cancers15123221 - 16 Jun 2023

Cited by 7 | Viewed by 3114

Abstract

Although immune checkpoint inhibitors improved the clinical outcomes of advanced triple negative breast cancer (TBNC) patients, the response rate remains relatively low. Nigericin is an antibiotic derived from Streptomyces hydrophobicus. We found that nigericin caused cell death in TNBC cell lines MDA-MB-231 [...] Read more.

Although immune checkpoint inhibitors improved the clinical outcomes of advanced triple negative breast cancer (TBNC) patients, the response rate remains relatively low. Nigericin is an antibiotic derived from Streptomyces hydrophobicus. We found that nigericin caused cell death in TNBC cell lines MDA-MB-231 and 4T1 by inducing concurrent pyroptosis and apoptosis. As nigericin facilitated cellular potassium efflux, we discovered that it caused mitochondrial dysfunction, leading to mitochondrial ROS production, as well as activation of Caspase-1/GSDMD-mediated pyroptosis and Caspase-3-mediated apoptosis in TNBC cells. Notably, nigericin-induced pyroptosis could amplify the anti-tumor immune response by enhancing the infiltration and anti-tumor effect of CD4+ and CD8+ T cells. Moreover, nigericin showed a synergistic therapeutic effect when combined with anti-PD-1 antibody in TNBC treatment. Our study reveals that nigericin may be a promising anti-tumor agent, especially in combination with immune checkpoint inhibitors for advanced TNBC treatment. Full article

(This article belongs to the Special Issue Tumor Microenvironment and Molecular Aberrations Convey Immune Evasion)

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Figure 1
Nigericin-treated TNBC cells exhibit both pyroptotic and apoptotic features. (A) Human TNBC cell line MDA-MB-231 and mouse TNBC cell line 4T1 were exposed to increasing concentrations of nigericin (0, 0.25, 0.5, 1, 2, 5, 10 and 20 μg/mL) for 24 h. Cell viability was measured using MTS assays, and IC50 value was calculated based on cell viability curve. Displayed are mean ± SD relative to control. (B) Flow cytometry analysis of PI and Annexin V stained TNBC cells before and after nigericin treatment (nigericin 2 μg/mL for 12 h, Annexin V+PI−: early apoptotic cells, Annexin V+PI+: late apoptotic/necrotic cells). Right panel shows cell percentages in left flow cytometry plots. Data are shown as mean ± SD (t-test, * p < 0.05, ** p < 0.01, *** p < 0.001). (C) LDH released from TNBC cells upon nigericin treatment (2 μg/mL) at different time points was detected using the LDH release assay. Each bar represents mean ± SD of experimental triplicates (one-way ANOVA, *** p < 0.001). (D) IL-1β released from TNBC cells upon nigericin treatment (2 μg/mL for 24 h) was detected with the IL-1β ELISA. Each bar represents mean ± SD of experimental triplicates (t-test, *** p < 0.001). Level of cleaved Caspase-1 or cleaved Caspase-3 was detected via western blots. (E) Nigericin treatment induced the cleavage of Caspase-1 and Caspase-3, as detected by western blots. (F) Representative SEM pictures of MDA-MB-231 treated with nigericin (2 μg/mL for 24 h). White arrows indicate membrane pores. Black arrows indicate pyroptotic bubbles. Yellow arrows indicate apoptotic bodies. TNBC, triple-negative breast cancer; PI, propidium iodide; LDH, lactate dehydrogenase; IL, interleukin; SEM, scanning electron microscope. Full article ">Figure 2
Nigericin-induced TNBC pyroptosis is GSDMD-dependent. (A) Western blots detected GSDMD or GSDME in TNBC cells upon nigericin treatment (2 μg/mL or 4 μg/mL for 12 h). (B) Confocal microscopy detected the N-terminal GSDMD migration from cytoplasm to membrane in MDA-MB-231 cells upon nigericin treatment (2 μg/mL for 12 h). (C) Flow cytometry detected PI- and Annexin V-stained TNBC cells with and without GSDMD knockdown, which occurred upon nigericin treatment (nigericin 2 μg/mL for 12 h, Annexin V+PI−: early apoptotic cells; Annexin V+PI+: late apoptotic/necrotic cells). (D) LDH released from TNBC cells with or without GSDMD knockdown, treated with nigericin (2 μg/mL for 12 h). Bar graphs represent mean ± SD of experimental triplicates (t-test, ** p < 0.01). (E) Western blots detected supernatant HMGB1 and cytoplasm GSDMD in control and GSDMD knockdown TNBC cells treated with nigericin (2 μg/mL for 12 h). (F) Representative phase-contrast images of control and GSDMD knockdown TNBC cells treated with nigericin (2 μg/mL for 24 h). Red arrows indicate pyroptotic cells, and yellow arrows indicate apoptotic cells. TNBC, triple-negative breast cancer; FL-GSDMD, full-length gasdermin-D; N-GSDMD, N-terminal fragments of gasdermin-D; FL-GSDME, full-length gasdermin-E; N-GSDME, N-terminal fragments of gasdermin-E; DAPI, 4′,6-diamidino-2-phenylindole; PI, propidium iodide; LDH, lactate dehydrogenase; HMGB1, high mobility group box-1. Full article ">Figure 3
Nigericin treatment leads to mitochondrial dysfunction. (A) Changes in intracellular potassium level in TNBC cells before and after nigericin treatment (2 μg/mL for 6 h), as detected via ICP-MS. Bar graphs stand for mean ± SD of experimental triplicates (t-test, * p < 0.05). (B) Mitochondrial membrane potential changes in TNBC cells (nigericin 2 μg/mL for 6 h), as detected via JC-1 probes. At high mitochondrial membrane potential, JC-1 aggregated and yielded red-colored emission (590 nm). At low mitochondrial membrane potential, JC-1 was predominantly a monomer that yielded green-colored emission (530 nm). (C) Metabolites screened via mass spectrometry in 4T1 cells with or without nigericin treatment. Metabolic pathway enrichment of differential metabolites was performed based on Metaboanalyst (<a href="https://www.metaboanalyst.ca" target="_blank">https://www.metaboanalyst.ca</a> (accessed on 31 October 2020)). (D,E) Nigericin significantly impacted mitochondrial metabolism. (D) Metabolites of TCA cycle and (E) oxidative phosphorylation upon nigericin treatment detected via mass spectrometry. Bar graphs stand for mean ± SD of experimental quadruplicates (t-test, * p < 0.05, ** p < 0.01, *** p < 0.001). TNBC, triple-negative breast cancer; JC-1, tetraethylbenzimidazolylcarbocyanine iodide; ICP-MS, inductively coupled plasma mass spectrometry; TCA cycle, tricarboxylic acid cycle; FADH2, flavin adenine dinucleotide; NADH, nicotinamide adenine dinucleotide. Full article ">Figure 4
Nigericin-mediated mitochondria dysfunction leads to Caspase-1-induced pyroptosis. (A) Changes in ROS level in TNBC cells treated with indicated reagents, as detected via flow cytometry. (B,C) Western blots detected expression of Caspase-1 and GSDMD in TNBC cells treated with indicated reagents. (D) LDH released from TNBC cells treated in indicated reagents was assessed using LDH assay kits. Bar graphs are shown as mean ± SD of experimental triplicates (one-way ANOVA, *** p < 0.001). TNBC, triple-negative breast cancer; ROS, reactive oxygen species; Nig, nigericin; NAC, N-acetylcysteine; GSDMD, gasdermin-D; LDH, lactate dehydrogenase. Full article ">Figure 5
Nigericin-mediated mitochondria dysfunction leads to Caspase-3 dependent apoptosis. (A–C) Changes in Parp-1 and Caspase-3 in TNBC cells treated with indicated reagents, as analyzed via western blots. (D) LDH released from TNBC cells treated with indicated reagents was assessed using LDH assay kits. Each bar represent means± SD of experimental triplicates (one-way ANOVA, *** p < 0.001). TNBC, triple-negative breast cancer; NAC, N-acetylcysteine; Nig, nigericin; GSDMD, gasdermin-D; LDH, lactate dehydrogenase. Full article ">Figure 6
Nigericin combined with anti-PD-1 is an effective anti-tumor strategy. (A) Flow cytometry analysis of TNF-α secreted by CD4+ and CD8+ T cells from human PBMCs co-cultured with MDA-MB-231 and treated with indicated reagents. Each bar represents mean ± SD (one-way ANOVA, *** p < 0.001). (B) 4T1 cells were injected orthotopically into left inguinal mammary fat pad of BALB/c mice, which were treated with either nigericin (subcutaneous) or anti-PD-1 antibody (intraperitoneal) alone or together. Tumor volumes were monitored every 3–4 days. Displayed are means ± SD of different groups (two-way ANOVA, *** p < 0.001). (C,D) Representative image (C) and tumor weights (D) of 4T1 xenografts. Each bar represents mean ± SD (one-way ANOVA, *** p < 0.001). (E) Proportions of infiltrated CD4 and CD8 in tumors were detected via flow cytometry. Each bar represents mean ± SD (one-way ANOVA, * p < 0.05, ** p < 0.01). (F) Flow cytometry analysis of IFN-γ or TNF-α secreted by CD4+ and CD8+ T cells. Displayed are means ± SD of different groups (one-way ANOVA, * p < 0.001). (G) Expression of cleaved Caspase-1 or cleaved Caspase-3 of tumors from each group, as detected via IHC. Each bar represents mean ± SD (one-way ANOVA, ** p < 0.01, *** p < 0.001). PD-1, programmed death-1; Nig, nigericin; PBMCs, human peripheral blood mononuclear cells; TNF, tumor necrosis factor; IHC, immuno-histochemistry. Full article ">Figure 7
Schematic summary of mechanism of Nigericin in inducing anti-tumor immune response. Nigericin caused cellular potassium efflux and mitochondrial dysfunction, leading to mitochondrial ROS accumulation, as well as activation of Caspase-1/GSDMD-mediated pyroptosis and Caspase-3-dependent apoptosis in TNBC cells. Finally, nigericin-induced pyroptosis could amplify anti-tumor immune response by enhancing infiltration and anti-tumor effects of CD4+ and CD8+ T cells. Full article ">

26 pages, 60053 KiB

Open AccessArticle

Pan-Cancer Landscape of NEIL3 in Tumor Microenvironment: A Promising Predictor for Chemotherapy and Immunotherapy

by Weixin Liao, Shaozhuo Huang, Lin Li, Jialiang Wang, Jing Li, Yongjian Chen, Lubiao Chen, Yifan Lian and Yuehua Huang

Cancers 2023, 15(1), 109; https://doi.org/10.3390/cancers15010109 - 24 Dec 2022

Cited by 1 | Viewed by 1949

Abstract

With the aim of enhancing the understanding of NEIL3 in prognosis prediction and therapy administration, we conducted a pan-cancer landscape analysis on NEIL3. The mutation characteristics, survival patterns, and immune features of NEIL3 across cancers were analyzed. Western blotting, qPCR, and immunohistochemistry were [...] Read more.

With the aim of enhancing the understanding of NEIL3 in prognosis prediction and therapy administration, we conducted a pan-cancer landscape analysis on NEIL3. The mutation characteristics, survival patterns, and immune features of NEIL3 across cancers were analyzed. Western blotting, qPCR, and immunohistochemistry were conducted to validate the bioinformatics results. The correlation between NEIL3 and chemotherapeutic drugs, as well as immunotherapies, was estimated. NEIL3 was identified as an oncogene with prognostic value in predicting clinical outcomes in multiple cancers. Combined with the neoantigen, tumor mutational burden (TMB), and microsatellite instability (MSI) results, a strong relationship between NEIL3 and the TME was observed. NEIL3 was demonstrated to be closely associated with multiple immune parameters, including infiltrating immunocytes and pro-inflammatory chemokines, which was verified by experiments. More importantly, patients with a higher expression of NEIL3 were revealed to be more sensitive to chemotherapeutic regimens and immune checkpoint inhibitors in selected cancers, implying that NEIL3 may be an indicator for therapeutic administration. Our study indicated NEIL3 has a strong association with the immune microenvironment and phenotypic changes in certain types of cancers, which facilitated the improved understanding of NEIL3 across cancers and highlighted the potential for clinical application of NEIL3 in precision medical stratification. Full article

(This article belongs to the Special Issue Tumor Microenvironment and Molecular Aberrations Convey Immune Evasion)

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25 pages, 9862 KiB

Open AccessArticle

ACAP1 Deficiency Predicts Inferior Immunotherapy Response in Solid Tumors

by Qiyi Yi, Youguang Pu, Fengmei Chao, Po Bian and Lei Lv

Cancers 2022, 14(23), 5951; https://doi.org/10.3390/cancers14235951 - 1 Dec 2022

Cited by 6 | Viewed by 2492

Abstract

Background: ACAP1 plays a key role in endocytic recycling, which is essential for the normal function of lymphocytes. However, the expression and function of ACAP1 in lymphocytes have rarely been studied. Methods: Large-scale genomic data, including multiple bulk RNA-sequencing datasets, single-cell sequencing datasets, [...] Read more.

Background: ACAP1 plays a key role in endocytic recycling, which is essential for the normal function of lymphocytes. However, the expression and function of ACAP1 in lymphocytes have rarely been studied. Methods: Large-scale genomic data, including multiple bulk RNA-sequencing datasets, single-cell sequencing datasets, and immunotherapy cohorts, were exploited to comprehensively characterize ACAP1 expression, regulation, and function. Gene set enrichment analysis (GSEA) was used to uncover the pathways associated with ACAP1 expression. Eight algorithms, including TIMER, CIBERSORT, CIBERSORT-ABS, QUANTISEQ, xCELL, MCPCOUNTER, EPIC, and TIDE, were applied to estimate the infiltrating level of immune cells. Western blotting, qPCR, and ChIP-PCR were used to validate the findings from bioinformatic analyses. A T-cell co-culture killing assay was used to investigate the function of ACAP1 in lymphocytes. Results: ACAP1 was highly expressed in immune-related tissues and cells and minimally in other tissues. Moreover, single-cell sequencing analysis in tumor samples revealed that ACAP1 is expressed primarily in tumor-infiltrating lymphocytes (TILs), including T, B, and NK cells. ACAP1 expression is negatively regulated by promoter DNA methylation, with its promoter hypo-methylated in immune cells but hyper-methylated in other cells. Furthermore, SPI1 binds to the ACAP1 promoter and positively regulates its expression in immune cells. ACAP1 levels positively correlate with the infiltrating levels of TILs, especially CD8+ T cells, across a broad range of solid cancer types. ACAP1 deficiency is associated with poor prognosis and immunotherapeutic response in multiple cancer types treated with checkpoint blockade therapy (ICT). Functionally, the depletion of ACAP1 by RNA interference significantly impairs the T cell-mediated killing of tumor cells. Conclusions: Our study demonstrates that ACAP1 is essential for the normal function of TILs, and its deficiency indicates an immunologically “cold” status of tumors that are resistant to ICT. Full article

(This article belongs to the Special Issue Tumor Microenvironment and Molecular Aberrations Convey Immune Evasion)

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Review

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28 pages, 1578 KiB

Open AccessReview

Polarization of Cancer-Associated Macrophages Maneuver Neoplastic Attributes of Pancreatic Ductal Adenocarcinoma

by Huey-Jen Lin, Yingguang Liu, Kailey Caroland and Jiayuh Lin

Cancers 2023, 15(13), 3507; https://doi.org/10.3390/cancers15133507 - 5 Jul 2023

Cited by 4 | Viewed by 3121

Abstract

Mounting evidence links the phenomenon of enhanced recruitment of tumor-associated macrophages towards cancer bulks to neoplastic growth, invasion, metastasis, immune escape, matrix remodeling, and therapeutic resistance. In the context of cancer progression, naïve macrophages are polarized into M1 or M2 subtypes according to [...] Read more.

Mounting evidence links the phenomenon of enhanced recruitment of tumor-associated macrophages towards cancer bulks to neoplastic growth, invasion, metastasis, immune escape, matrix remodeling, and therapeutic resistance. In the context of cancer progression, naïve macrophages are polarized into M1 or M2 subtypes according to their differentiation status, gene signatures, and functional roles. While the former render proinflammatory and anticancer effects, the latter subpopulation elicits an opposite impact on pancreatic ductal adenocarcinoma. M2 macrophages have gained increasing attention as they are largely responsible for molding an immune-suppressive landscape. Through positive feedback circuits involving a paracrine manner, M2 macrophages can be amplified by and synergized with neighboring neoplastic cells, fibroblasts, endothelial cells, and non-cell autonomous constituents in the microenvironmental niche to promote an advanced disease state. This review delineates the molecular cues expanding M2 populations that subsequently convey notorious clinical outcomes. Future therapeutic regimens shall comprise protocols attempting to abolish environmental niches favoring M2 polarization; weaken cancer growth typically assisted by M2; promote the recruitment of tumoricidal CD8⁺ T lymphocytes and dendritic cells; and boost susceptibility towards gemcitabine as well as other chemotherapeutic agents. Full article

(This article belongs to the Special Issue Tumor Microenvironment and Molecular Aberrations Convey Immune Evasion)

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Figure 1
Pancreatic ductal adenocarcinoma cells synergize with the tumor microenvironment to provoke polarization of M2 macrophages. Arrows with pointed or with blocked ends indicate activation or inhibition between regulators, respectively, while a fading effect at the start of arrows represents secretion of modulators. Plain straight lines depict interaction between ligands and receptors. Cell surface proteins are noted in rectangular boxes on cell membranes. The circular lipid bilayer depicts an extracellular vesicle. Abbreviations used include aryl hydrocarbon receptor (AhR), protein kinases B (AKT), Bcl-2-associated athanogene 3 (BAG3), cancer-associated fibroblast (CAF), CC-chemokine ligand (CCL), cluster of differentiated (CD), CXC chemokine ligand (CXCL), colony-stimulating factor (CSF) and receptor (CSF1R), dendritic cell (DC), double cortin-like kinase 1 (Dclk1), endothelial cell (Endo), epidermal growth factor receptor (EGFR), epithelial cell (Epi), ezrin (EZR), galectin (gal), granulocyte-macrophage colony-stimulating factor (GM-CSF), hypoxia-inducible factor (HIF), interleukin (IL), insulin-like growth factor binding protein 2 (IGFBP2), interferon-induced transmembrane protein 2 (IFITM-2), interferon regulatory factor 4 (Irf4), Kirsten rat sarcoma (KRAS), mammalian target of rapamycin (mTOR), microRNA (miR), monocyte (M), nucleotide-binding and leucine-rich repeat receptor containing pyrin domain 3 (NLRP3), pancreatic ductal adenocarcinoma (PDAC), phosphatidylinositol 3-kinase (PI3K), reactive oxygen species (ROS), regenerating gene family member 4 (REG4), sialic-acid-binding immunoglobulin-like lectin 15 (SIGLEC15), signal transducer and activator of transcription (STAT), spleen tyrosine kinase (SYK), suppression of tumorigenicity 2 (ST2), tumor-associated macrophage (TAM), transforming growth factor β (TGF-β), and T helper-2 (TH2). Full article ">Figure 2
M2 macrophage promotes a plethora of neoplastic features of pancreatic ductal adenocarcinoma and suppresses tumoricidal effects exerted from cytotoxic T lymphocyte. Arrows and straight plain lines, as well as overlapping abbreviations used in both figures, are described in the legend of <a href="#cancers-15-03507-f001" class="html-fig">Figure 1</a>. Additional abbreviations that are used in <a href="#cancers-15-03507-f002" class="html-fig">Figure 2</a> include apolipoprotein E (ApoE), arginine (Arg), adenylyl cyclase-associated protein 1 (CAP-1), CC-chemokine ligand (CCL), CC-chemokine receptor (CCR), cytidine deaminase (CDA), chitinase 3-like-1 (CHI3L1), CXC chemokine ligand (CXCL), endothelial cell (EC), epithelial–mesenchymal transition (EMT), extracellular signal-regulated kinase (ERK), fibronectin-1 (FN1), gemcitabine (GEM), hypoxia-inducible factor 1α (HIF-1α), interferon (IFN), insulin-like growth factor (IGF) and receptor (IGFR), IFN-stimulated gene 15 (ISG15), immunomodulatory cationic antimicrobial peptide 18/LL-37 (hCAP-18/LL-37), low-density-lipoprotein receptor (LDLR), lysyl oxidase-like protein 2 (LOXL2), macrophage inflammatory protein-3α(MIP3α), microRNA (miR), matrix metalloproteinase 9 (MMP-9), nuclear factor κ-light-chain-enhancer of activated B cells (NF-κB), oncostatin M (OSM), pancreatic cancer stem-like cells (PCSCs), programmed death receptor-1 (PD-1) and ligand (PD-L1), pyruvate kinase isoform M2 (PKM2), Toll-like receptor 4 (TLR4), tryptophan (Trp), tumor necrosis factor α (TNF-α), vascular cell adhesion molecule 1 (VCAM-1), vascular endothelial growth factor (VEGF) and receptor (VEGFR), and YWHAZ/14-3-3 protein zeta/delta (14-3-3ζ). Full article ">

22 pages, 1413 KiB

Open AccessFeature PaperReview

The Monocyte, a Maestro in the Tumor Microenvironment (TME) of Breast Cancer

by Hoda T. Amer, Ulrike Stein and Hend M. El Tayebi

Cancers 2022, 14(21), 5460; https://doi.org/10.3390/cancers14215460 - 7 Nov 2022

Cited by 21 | Viewed by 4707

Abstract

Breast cancer (BC) is well-known for being a leading cause of death worldwide. It is classified molecularly into luminal A, luminal B HER2−, luminal B HER2+, HER2+, and triple-negative breast cancer (TNBC). These subtypes differ in their prognosis; thus, understanding the tumor microenvironment [...] Read more.

Breast cancer (BC) is well-known for being a leading cause of death worldwide. It is classified molecularly into luminal A, luminal B HER2−, luminal B HER2+, HER2+, and triple-negative breast cancer (TNBC). These subtypes differ in their prognosis; thus, understanding the tumor microenvironment (TME) makes new treatment strategies possible. The TME contains populations that exhibit anti-tumorigenic actions such as tumor-associated eosinophils. Moreover, it contains pro-tumorigenic populations such as tumor-associated neutrophils (TANs), or monocyte-derived populations. The monocyte-derived populations are tumor-associated macrophages (TAMs) and MDSCs. Thus, a monocyte can be considered a maestro within the TME. Moreover, the expansion of monocytes in the TME depends on many factors such as the BC stage, the presence of macrophage colony-stimulating factor (M-CSF), and the presence of some chemoattractants. After expansion, monocytes can differentiate into pro-inflammatory populations such as M1 macrophages or anti-inflammatory populations such as M2 macrophages according to the nature of cytokines present in the TME. Differentiation to TAMs depends on various factors such as the BC subtype, the presence of anti-inflammatory cytokines, and epigenetic factors. Furthermore, TAMs and MDSCs not only have a role in tumor progression but also are key players in metastasis. Thus, understanding the monocytes further can introduce new target therapies. Full article

(This article belongs to the Special Issue Tumor Microenvironment and Molecular Aberrations Convey Immune Evasion)

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25 pages, 1213 KiB

Open AccessReview

by Yoshiaki Yura and Masakazu Hamada

Cancers 2022, 14(3), 792; https://doi.org/10.3390/cancers14030792 - 4 Feb 2022

Cited by 17 | Viewed by 3291

Abstract

Conventional chemotherapy and targeted therapies have limited efficacy against advanced head and neck squamous cell carcinoma (HNSCC). The immune checkpoint inhibitors (ICIs) such as antibodies against CTLA-4, PD-1, and PD-L1 interrupt the co-inhibitory pathway of T cells and enhance the ability of CD8 [...] Read more.

Conventional chemotherapy and targeted therapies have limited efficacy against advanced head and neck squamous cell carcinoma (HNSCC). The immune checkpoint inhibitors (ICIs) such as antibodies against CTLA-4, PD-1, and PD-L1 interrupt the co-inhibitory pathway of T cells and enhance the ability of CD8⁺ T cells to destroy tumors. Even in advanced HNSCC patients with recurrent diseases and distant metastasis, ICI therapy shows efficiency and become an effective alternative to conventional chemotherapy. However, as this therapy releases the immune tolerance state, cytotoxic CD8⁺ T cells can also attack organs and tissues expressing self-antigens that cross-react with tumor antigens and induce immune-related adverse events (irAEs). When patients with HNSCC are treated with ICIs, autoimmune diseases occur in multiple organs including the skin, digestive tract, endocrine system, liver, and respiratory tract. Treatment of various malignancies, including HNSCC, with ICIs may result in the appearance of oral irAEs. In the oral cavity, an oral lichenoid reaction (OLR) and pemphigoid develop. Sicca syndrome also occurs in association with ICIs, affecting the salivary glands to induce xerostomia. It is necessary to elucidate the pathogenic mechanisms of these intractable diseases that are not seen with conventional therapy. Early diagnosis and appropriate approaches to irAEs are needed for efficient treatment of advanced HNSCC by ICIs. Full article

(This article belongs to the Special Issue Tumor Microenvironment and Molecular Aberrations Convey Immune Evasion)

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Figure 1
CTLA-4 and PD-1/PD-L1 in cellular (A) and humoral (B) tumor immunity. (A) In the CD8+ T cell-based pathway, when tumor antigens are released into the tumor microenvironment from dying tumor cells, DCs take up the protein antigens and decomposes them to peptide antigens. In regional lymph nodes, the peptide antigens are cross-presented via MHC class I on the cell surface and recognized by the TCR of CD8+ T cells. In addition, the co-stimulatory binding of CD80/86 of DCs with CD28 of T cells is required for naïve CD8+ T cells to differentiate into cytotoxic CD8+ T cells. Activated CD8+ T cells express the co-inhibitory molecule CTLA-4 to prevent excess activation of CD8+ T cells. CD8+ T cells move to a peripheral tumor site and recognize tumor peptide antigens presented via MHC class I and exert antitumor activity. However, PD-I on CD8+ T cells binds PD-L1 on tumor cells and suppresses the activity of CD8+ T cells. Treg cells locally suppress the activity of CD8+ T cells and CD4+ helper cells. (B) The germinal center (GC) plays an important role in the proliferation and differentiation of B cells. Tfh cells physically bind to GC B cells by co-stimulatory/co-inhibitory pairs such as CD28–CD80/86, CD40L–CD40, ICOS–ICOSL, PD-1, and PD-L1. BCR expressed on B cells detects the protein antigens, and take them into the cells. Peptide antigens processed in B cells are then presented via MHC class II and recognized by Tfh cells. Interaction between Tfh and B cells promotes the differentiation of GC B cells into plasma cells and memory B cells. Tfr cells suppress Tfh and B cells. LN, lymph node; Treg, regulatory T; TCR, T cell receptor; irAEs, immune-related adverse events; GC, germinal center; Tfh, T follicular helper; Tfr, T follicular regulatory; PC, plasma cell; BCR, B cell receptor. Full article ">Figure 2
Characteristics of 76 previously reported patients with ICI-induced Sicca syndrome. (A) Sex. (B) Types of underlying malignancies. (C) Time to onset, months. (D) Prevalence of Sicca syndrome-related serum autoantibodies. (E) Other irAEs. (F) Degree of improvement of irAEs. Full article ">

25 pages, 861 KiB

Open AccessReview

Breast Cancer Tumor Microenvironment and Molecular Aberrations Hijack Tumoricidal Immunity

by Huey-Jen Lin, Yingguang Liu, Denene Lofland and Jiayuh Lin

Cancers 2022, 14(2), 285; https://doi.org/10.3390/cancers14020285 - 7 Jan 2022

Cited by 16 | Viewed by 4362

Abstract

Breast cancer is the most common malignancy among females in western countries, where women have an overall lifetime risk of >10% for developing invasive breast carcinomas. It is not a single disease but is composed of distinct subtypes associated with different clinical outcomes [...] Read more.

Breast cancer is the most common malignancy among females in western countries, where women have an overall lifetime risk of >10% for developing invasive breast carcinomas. It is not a single disease but is composed of distinct subtypes associated with different clinical outcomes and is highly heterogeneous in both the molecular and clinical aspects. Although tumor initiation is largely driven by acquired genetic alterations, recent data suggest microenvironment-mediated immune evasion may play an important role in neoplastic progression. Beyond surgical resection, radiation, and chemotherapy, additional therapeutic options include hormonal deactivation, targeted-signaling pathway treatment, DNA repair inhibition, and aberrant epigenetic reversion. Yet, the fatality rate of metastatic breast cancer remains unacceptably high, largely due to treatment resistance and metastases to brain, lung, or bone marrow where tumor bed penetration of therapeutic agents is limited. Recent studies indicate the development of immune-oncological therapy could potentially eradicate this devastating malignancy. Evidence suggests tumors express immunogenic neoantigens but the immunity towards these antigens is frequently muted. Established tumors exhibit immunological tolerance. This tolerance reflects a process of immune suppression elicited by the tumor, and it represents a critical obstacle towards successful antitumor immunotherapy. In general, immune evasive mechanisms adapted by breast cancer encompasses down-regulation of antigen presentations or recognition, lack of immune effector cells, obstruction of anti-tumor immune cell maturation, accumulation of immunosuppressive cells, production of inhibitory cytokines, chemokines or ligands/receptors, and up-regulation of immune checkpoint modulators. Together with altered metabolism and hypoxic conditions, they constitute a permissive tumor microenvironment. This article intends to discern representative incidents and to provide potential innovative therapeutic regimens to reinstate tumoricidal immunity. Full article

(This article belongs to the Special Issue Tumor Microenvironment and Molecular Aberrations Convey Immune Evasion)

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