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Search Results (291)

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17 pages, 1305 KiB  
Article
CT-Scan-Assessed Body Composition and Its Association with Tumor Protein Expression in Endometrial Cancer: The Role of Muscle and Adiposity Quantities
by Cuthbert Mario Mahenge, Rand Talal Akasheh, Ben Kinder, Xuan Viet Nguyen, Faiza Kalam and Ting-Yuan David Cheng
Cancers 2024, 16(24), 4222; https://doi.org/10.3390/cancers16244222 - 18 Dec 2024
Viewed by 614
Abstract
Background: Endometrial cancer is strongly associated with obesity, and tumors often harbor mutations in major cancer signaling pathways. To inform the integration of body composition into targeted therapy paradigms, this hypothesis-generating study explores the association between muscle mass, body fat, and tumor [...] Read more.
Background: Endometrial cancer is strongly associated with obesity, and tumors often harbor mutations in major cancer signaling pathways. To inform the integration of body composition into targeted therapy paradigms, this hypothesis-generating study explores the association between muscle mass, body fat, and tumor proteomics. Methods: We analyzed data from 113 patients in The Cancer Genome Atlas (TCGA) and Cancer Proteomic Tumor Analysis Consortium (CPTAC) cohorts and their corresponding abdominal CT scans. Among these patients, tumor proteomics data were available for 45 patients, and 133 proteins were analyzed. Adiposity and muscle components were assessed at the L3 vertebral level on the CT scans. Patients were stratified into tertiles of muscle and fat mass and categorized into three groups: high muscle/low adiposity, high muscle/high adiposity, and low muscle/all adiposities. Linear and Cox regression models were adjusted for study cohort, stage, histology type, age, race, and ethnicity. Results: Compared with the high-muscle/low-adiposity group, both the high-muscle/high-adiposity (HR = 4.3, 95% CI = 1.0–29.0) and low-muscle (HR = 4.4, 95% CI = 1.3–14.9) groups experienced higher mortality. Low muscle was associated with higher expression of phospho-4EBP1(T37 and S65), phospho-GYS(S641) and phospho-MAPK(T202/Y204) but lower expression of ARID1A, CHK2, SYK, LCK, EEF2, CYCLIN B1, and FOXO3A. High muscle/high adiposity was associated with higher expression of phospho-4EBP1 (T37), phospho-GYS (S641), CHK1, PEA15, SMAD3, BAX, DJ1, GYS, PKM2, COMPLEX II Subunit 30, and phospho-P70S6K (T389) but with lower expression of CHK2, CRAF, MSH6, TUBERIN, PR, ERK2, beta-CATENIN, AKT, and S6. Conclusions: These findings demonstrate an association between body composition and proteins involved in key cancer signaling pathways, notably the PI3K/AKT/MTOR, MAPK/ERK, cell cycle regulation, DNA damage response, and mismatch repair pathways. These findings warrant further validation and assessment in relation to prognosis and outcomes in these patients. Full article
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<p>Correlation between TSM (<b>A</b>) and TAT (<b>B</b>) with the BMI of the study participants.</p>
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<p>BMI distribution across the body composition groups of the study participants.</p>
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<p>Kaplan–Meier graph exploring the survival trend based on body composition group.</p>
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<p>Volcano plot of differential expression of protein tumors based on body composition groups with high muscle/low adiposity as a referent group.</p>
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13 pages, 699 KiB  
Review
The Influence of Diet and Obesity in Lynch Syndrome: What Do We Know So Far
by Cláudio Rodrigues, Susana Couto Irving, Paula Alves, Mário Dinis-Ribeiro, Catarina Brandão and Marta Correia
Nutrients 2024, 16(24), 4352; https://doi.org/10.3390/nu16244352 - 17 Dec 2024
Viewed by 692
Abstract
Of all new cases of colorectal cancer, Lynch syndrome (LS) accounts for approximately 3%. This syndrome is the most common hereditary cancer syndrome and is caused by pathogenic variants in the genes responsible for DNA mismatch repair. Although the relationship between colorectal cancer [...] Read more.
Of all new cases of colorectal cancer, Lynch syndrome (LS) accounts for approximately 3%. This syndrome is the most common hereditary cancer syndrome and is caused by pathogenic variants in the genes responsible for DNA mismatch repair. Although the relationship between colorectal cancer risk and diet is well established, little is known regarding the influence of diet and nutritional characteristics on LS’s clinical evolution. There is some evidence suggesting that individuals living with LS should follow general guidelines for diet and alcohol restriction/moderation, so as to achieve and maintain a favorable weight status and overall health and quality of life. However, more research is needed, preferentially from clinical studies of a prospective nature with robust designs, to better inform diet and behavioral patterns targeting cancer prevention in LS. Full article
(This article belongs to the Section Nutrition and Obesity)
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<p>Flow diagram demonstrating the literature search and eligibility.</p>
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34 pages, 1583 KiB  
Review
Proteins Associated with Neurodegenerative Diseases: Link to DNA Repair
by Svetlana N. Khodyreva, Nadezhda S. Dyrkheeva and Olga I. Lavrik
Biomedicines 2024, 12(12), 2808; https://doi.org/10.3390/biomedicines12122808 - 11 Dec 2024
Viewed by 896
Abstract
The nervous system is susceptible to DNA damage and DNA repair defects, and if DNA damage is not repaired, neuronal cells can die, causing neurodegenerative diseases in humans. The overall picture of what is known about DNA repair mechanisms in the nervous system [...] Read more.
The nervous system is susceptible to DNA damage and DNA repair defects, and if DNA damage is not repaired, neuronal cells can die, causing neurodegenerative diseases in humans. The overall picture of what is known about DNA repair mechanisms in the nervous system is still unclear. The current challenge is to use the accumulated knowledge of basic science on DNA repair to improve the treatment of neurodegenerative disorders. In this review, we summarize the current understanding of the function of DNA damage repair, in particular, the base excision repair and double-strand break repair pathways as being the most important in nervous system cells. We summarize recent data on the proteins involved in DNA repair associated with neurodegenerative diseases, with particular emphasis on PARP1 and ND-associated proteins, which are involved in DNA repair and have the ability to undergo liquid–liquid phase separation. Full article
(This article belongs to the Special Issue Cellular and Molecular Biology of Neurodegenerative Disorders)
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<p>DNA repair pathways and typical repaired lesions (italicized).</p>
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<p>Base excision repair (BER) mechanisms. Base excision repair is performed by short patch (SP-BER) or long patch (LP-BER). Damaged bases are removed by monofunctional (UNG, TDG, SMUG1, MBD4, MPG, MUTYH) and bifunctional (NTH1, OGG1, NEIL1, NEIL2, NEIL3) DNA glycosylases. AP (apurinic/apyrimidinic) sites remaining after the action of monofunctional glycosylases are incised by apurinic/apyrimidinic endonuclease 1 (APE1). dRP (5′ deoxyribose phosphate) is removed by the 5′dRP lyase activity of DNA polymerase β (Polβ), followed by Polβ-catalysed incorporation of a dNMP (SP-BER). The resulting nick is sealed by DNA ligase 3 (Lig3)-XRCC1. Oxidized DNA bases are processed by bifunctional DNA glycosylases, which remove the base and cut into the DNA backbone, creating the nick with 3′ α,β-4-hydroxypentene-2-al (PUA) or phosphate (P). The 3′ PUA residue and the 3′ P group are removed by APE1 and polynucleotide kinase phosphatase (PNKP), respectively. In LP-BER, a 2 to 13 nucleotide patch is synthesized by Polδ/ε (or Polβ) with the assistance of PCNA. A resulting 5′ flap is removed by flap endonuclease 1 (FEN1), and the final ligation step is performed by DNA ligase 1 (Lig1). Red arrow indicates the newly incorporated nucleotide(s); red and yellow ovals indicate the damaged base and AP site, respectively.</p>
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<p><b>Nonhomologous end-joining (NHEJ) mechanisms</b>. NHEJ occurs via classical (C-NHEJ) or alternative (Alt-NHEJ) pathways. Alt-NHEJ is subdivided into microhomology-mediated end-joining (MMEJ) and single-strand annealing (SSA) pathways. In C-NHEJ, DSB recognition is carried out by the Ku70/Ku80 protein, followed by recruitment of the catalytic subunit of DNA-dependent protein kinase (DNA-PKcs), PNKP, and nucleases (WRN or Artemis) or tyrosyl DNA phosphodiesterase 1 (TDP1) and DNA polymerases (Polμ or Polλ) to process the ends as required. DNA ligase 4 (Lig4) rejoins DNA ends in the presence of XRCC4, XLF/Cernunnos proteins. In MMEJ, PARP1 performs recognition and recruits MRN (Mre11/Rad50/Nbs1) and CtIP for short-end resection. After microhomology-mediated annealing of the DNA chains, ERCC1/XPF nuclease trims the gaps. Gaps are filled by Polθ or Polβ, and nicks are sealed by Lig1 or Lig3/XRCC1. In SSA, after long-end resection, RAD52-mediated annealing and ERCC1/XPF-mediated flap trimming followed by DNA synthesis (Polθ), Lig1 seals the nicks. Red arrows indicate unpaired regions of DNA strands.</p>
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10 pages, 2493 KiB  
Case Report
A Rare Case of a Malignant Proliferating Trichilemmal Tumor: A Molecular Study Harboring Potential Therapeutic Significance and a Review of Literature
by Mokhtar H. Abdelhammed, Hanna Siatecka, A. Hafeez Diwan, Christie J. Finch, Angela D. Haskins, David J. Hernandez and Ya Xu
Dermatopathology 2024, 11(4), 354-363; https://doi.org/10.3390/dermatopathology11040038 - 10 Dec 2024
Viewed by 812
Abstract
Malignant proliferating trichilemmal tumors (MPTTs), arising from the external root sheath of hair follicles, are exceptionally rare, with limited documentation of their genetic alterations. We present a case of a 64-year-old African American woman who initially presented with a gradually enlarging nodule on [...] Read more.
Malignant proliferating trichilemmal tumors (MPTTs), arising from the external root sheath of hair follicles, are exceptionally rare, with limited documentation of their genetic alterations. We present a case of a 64-year-old African American woman who initially presented with a gradually enlarging nodule on her posterior scalp. An initial biopsy at an outside hospital suggested metastatic adenocarcinoma or squamous cell carcinoma (SCC) of an uncertain origin. A subsequent wide local excision revealed a 2.0 cm tumor demonstrating characteristic trichilemmal keratinization, characterized by an abrupt transition from the nucleated epithelium to a laminated keratinized layer, confirming MPTT. Immunohistochemistry demonstrated diffuse p53 expression, patchy CD 34 expression, focal HER2 membranous expression, and patchy p16 staining (negative HPV ISH). A molecular analysis identified TP53 mutation and amplifications in the ERBB2 (HER2), BRD4, and TYMS. Additional gene mutations of uncertain significance included HSPH1, ATM, PDCD1 (PD-1), BARD1, MSH3, LRP1B, KMT2C (MLL3), GNA11, and RUNX1. Assessments for the homologous recombination deficiency, PD-L1 expression, gene rearrangement, altered splicing, and DNA mismatch repair gene expression were negative. The confirmation of ERBB2 (HER2) amplification in the MPTT through a molecular analysis suggests potential therapeutic avenues involving anti-HER2 monoclonal antibodies. The presence of the TP53 mutation, without the concurrent gene mutations typically observed in SCC, significantly aided in this differential diagnosis. Full article
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<p>Clinical presentation and histologic examination of malignant proliferating trichilemmal tumors (MPTT) on a hematoxylin and eosin stain (H and E). The tumor presented as a 2.0 cm mass on the left occipital scalp (<b>A</b>). Microscopically, a histological examination revealed a solid and cystic dermal neoplasm, with smaller cystic spaces (<b>B</b>) 20X and a larger cyst exhibiting infolding bands of tumor cells with calcification indicated by an arrow (<b>C</b>) 20X. The tumor displayed an abrupt transition from the nucleated epithelium to a densely laminated keratinized layer without an intermediate granular layer (<b>D</b>) higher magnification of the squared area in (<b>C</b>) 200X. There were areas with invasive irregular tumor nests in the desmoplastic stroma, composed of nonkeratinizing tumor cells (<b>E</b>) 40X, showing moderate nuclear pleomorphism, frequent mitoses (indicated by narrow arrows), and occasional necrosis (indicated by wide arrow) (<b>F</b>) higher magnification of the squared area in (<b>E</b>) 200X.</p>
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<p>Immunohistochemistry (IHC) of the malignant proliferating trichilemmal tumor. IHC revealed diffuse expression of CK17 (<b>A</b>) 40X and p53 (<b>C</b>) 100X in the tumor, along with patchy positivity for CD34 (<b>B</b>) 40X. The Ki-67 proliferative index was approximately 30% in the hottest spots (<b>D</b>) 100X. Focal HER2 overexpression with a complete membranous staining pattern was observed (<b>E</b>) 100X. Additionally, patchy p16 staining was noted (<b>F</b>) 40X, whereas high risk HPV RNA in situ hybridization was negative.</p>
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14 pages, 343 KiB  
Review
Gynecological Insights into Lynch Syndrome—A Comprehensive Review of Cancer Screening and Prevention
by Elena Chitoran, Roxana-Elena Bohiltea, Vlad Rotaru, Cristiana-Elena Durdu, Madalina-Nicoleta Mitroiu and Laurentiu Simion
Medicina 2024, 60(12), 2013; https://doi.org/10.3390/medicina60122013 - 6 Dec 2024
Viewed by 787
Abstract
Lynch syndrome, one of the most common genetic syndromes predisposing to cancer, is associated with a series of malignant conditions, among which the most frequent is colorectal cancer, but gynecologic cancers (especially endometrial) are also quite common. Despite the significant progress made in [...] Read more.
Lynch syndrome, one of the most common genetic syndromes predisposing to cancer, is associated with a series of malignant conditions, among which the most frequent is colorectal cancer, but gynecologic cancers (especially endometrial) are also quite common. Despite the significant progress made in understanding this condition over time, there are still aspects in managing this condition that have not demonstrated clear benefits. This article aims to summarize the recommendations of international societies and present the latest developments in managing Lynch syndrome, focusing on gynecologic cancer screening and possible prevention strategies. Advances in genetic testing procedures and discoveries related to the association between oncological pathology frequency and the affected pathogenic variant type will probably lead to personalized medicine focused on the individual patient in the coming years. Although various screening methods for gynecological cancers in patients with Lynch syndrome have been used over time, they have not shown significant survival benefits. This highlights the need for studying and implementing new screening and diagnostic methods, which have been under investigation in recent years and are mentioned in this article. Full article
15 pages, 1617 KiB  
Review
Action-At-A-Distance in DNA Mismatch Repair: Mechanistic Insights and Models for How DNA and Repair Proteins Facilitate Long-Range Communication
by Bryce W. Collingwood, Scott J. Witte and Carol M. Manhart
Biomolecules 2024, 14(11), 1442; https://doi.org/10.3390/biom14111442 - 13 Nov 2024
Viewed by 1301
Abstract
Many DNA metabolic pathways, including DNA repair, require the transmission of signals across long stretches of DNA or between DNA molecules. Solutions to this signaling challenge involve various mechanisms: protein factors can travel between these sites, loop DNA between sites, or form oligomers [...] Read more.
Many DNA metabolic pathways, including DNA repair, require the transmission of signals across long stretches of DNA or between DNA molecules. Solutions to this signaling challenge involve various mechanisms: protein factors can travel between these sites, loop DNA between sites, or form oligomers that bridge the spatial gaps. This review provides an overview of how these paradigms have been used to explain DNA mismatch repair, which involves several steps that require action-at-a-distance. Here, we describe these models in detail and how current data fit into these descriptions. We also outline regulation steps that remain unanswered in how the action is communicated across long distances along a DNA contour in DNA mismatch repair. Full article
(This article belongs to the Special Issue DNA Damage, Mutagenesis, and Repair Mechanisms)
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<p>In DNA repair, signals for repair can be widely spaced along the DNA contour, necessitating mechanisms to transmit recognition at one site (site 1) to action at a distant site (site 2). Several models illustrate how this action-at-a-distance can occur. For panels (<b>A</b>–<b>C</b>), a generic protein is depicted in blue. (<b>A</b>) The tracking or sliding model: a protein binds to a recognition site and then moves along the DNA to the site of action. (<b>B</b>) DNA looping models: a protein binds to its recognition site and translocates along the DNA, forming an extruded loop. Another variation (transactivation) involves one protein binding to the recognition site and another to the site of action; the dimerization of these two proteins facilitates interactions between the two sites, extruding a loop of DNA. (<b>C</b>) Oligomerization model: a protein binds to a recognition site and forms a large oligomeric complex with other copies of itself or additional factors along the DNA, extending to the site of action. (<b>D</b>) The model for DNA mismatch repair: action-at-a-distance is essential at several steps to initiate repair and remove mismatches. The repair pathway relies on an incision generated by the MutL<span class="html-italic">α</span> protein to excise the mismatch, which can be separated by hundreds of base pairs from the incision site, necessitating communication between the two sites. The mismatch is ultimately removed through excision or DNA synthesis, initiated at the MutL<span class="html-italic">α</span> incision site and terminating at a site beyond the mismatch.</p>
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<p>The directionality of mismatch repair systems in vitro and possibly in vivo is guided by pre-existing DNA nicks. (<b>A</b>) PCNA has two distinct faces: one that interacts with MutL<span class="html-italic">α</span> to stimulate its endonuclease activity and another that does not. (<b>B</b>) A model for how a 3′ pre-existing nick could direct an incision on the 5′ side of the mismatch. See the text for details.</p>
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<p>Models for action-at-a-distance between the mismatch and the MutL<span class="html-italic">α</span> incision used for mismatch removal. Following the recognition of mismatch by the MutS<span class="html-italic">α</span>/<span class="html-italic">β</span> complex, MutS<span class="html-italic">α</span>/<span class="html-italic">β</span> undergoes an exchange of ADP for ATP, enabling an interaction with MutL<span class="html-italic">α</span>. (<b>A</b>) It has been proposed that upon ATP binding, MutS<span class="html-italic">α</span> can function as a sliding clamp, migrating along the DNA to a distant position where it recruits or interacts with MutL<span class="html-italic">α</span> to facilitate incision. (<b>B</b>) Alternatively, the ATP-bound form of MutS<span class="html-italic">α</span> may translocate to extrude a mismatch-containing (heteroduplex) loop, engaging with MutL<span class="html-italic">α</span> at a remote site. In another scenario, MutS<span class="html-italic">α</span> could remain stationary at the mismatch while forming a complex with MutL<span class="html-italic">α</span> bound to the distant site, resulting in the extrusion of a homoduplex loop. (<b>C</b>) MutS<span class="html-italic">α</span> may also remain associated with the mismatch and interact with an oligomer of MutL<span class="html-italic">α</span>, effectively bridging the spatial gap between the mismatch and the MutL<span class="html-italic">α</span> incision site. This oligomerization of MutL<span class="html-italic">α</span> may induce conformational changes in the DNA structure, facilitating the necessary interactions. Refer to the text for further details.</p>
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<p>The incision generated by MutL<span class="html-italic">α</span> serves as the initiation point for the exonuclease EXO1 or DNA polymerase <span class="html-italic">δ</span> to remove the mismatch. The mechanisms by which these proteins are recruited to MutL<span class="html-italic">α</span>-generated incisions and regulated to terminate nascent strand removal beyond the mismatch are not fully characterized. (<b>A</b>) In the EXO1-dependent mismatch removal pathway, EXO1 is recruited to the incision created by MutL<span class="html-italic">α</span>, potentially by repair factors involved in earlier steps, and begins excising DNA in a 5′ to 3′ direction. The activity of EXO1 may be regulated or terminated by factors such as MutL<span class="html-italic">α</span> or RPA. (<b>B</b>) After the removal of the mismatch-containing nascent strand, DNA polymerase <span class="html-italic">δ</span> or <span class="html-italic">ε</span> fills in the resulting gap. Gap filling may be regulated beyond the mismatch by collisions with the duplex region, the loss of interaction with PCNA, or the creation of a single-stranded DNA tail through strand displacement, which can reduce polymerase processivity. (<b>C</b>) In the EXO1-independent mismatch removal pathway, DNA polymerase <span class="html-italic">δ</span>, in conjunction with FEN1 (Rad27), can access the incision made by MutL<span class="html-italic">α</span> and begin displacing the error-containing nascent strand. As strand displacement occurs, the polymerase resynthesizes the DNA, correcting the nucleotide mispairing. The termination signal for this process is likely similar to that regulating the gap filling described in panel (<b>B</b>).</p>
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11 pages, 1504 KiB  
Article
A Comparative Study of Methyl-BEAMing and Droplet Digital PCR for MGMT Gene Promoter Hypermethylation Detection
by Marco Macagno, Valeria Pessei, Noemi Congiusta, Luca Lazzari, Sara Erika Bellomo, Fariha Idrees, Alessandro Cavaliere, Filippo Pietrantonio, Alessandra Raimondi, Eleonora Gusmaroli, Maria Giulia Zampino, Lorenzo Gervaso, Davide Ciardiello, Giuseppe Mondello, Armando Santoro, Nicola Personeni, Emanuela Bonoldi, Maria Costanza Aquilano, Emanuele Valtorta, Salvatore Siena, Andrea Sartore-Bianchi, Alessio Amatu, Erica Francesca Bonazzina, Katia Bruna Bencardino, Guido Serini, Silvia Marsoni, Ludovic Barault, Federica Di Nicolantonio and Federica Maioneadd Show full author list remove Hide full author list
Diagnostics 2024, 14(22), 2467; https://doi.org/10.3390/diagnostics14222467 - 5 Nov 2024
Viewed by 854
Abstract
Background: O-6-methylguanine-DNA methyltransferase is responsible for the direct repair of O6-methylguanine lesions induced by alkylating agents, including temozolomide. O-6-methylguanine-DNA methyltransferase promoter hypermethylation is a well-established biomarker for temozolomide response in glioblastoma patients, also correlated with therapeutic response in colorectal cancer. Objectives: The ARETHUSA [...] Read more.
Background: O-6-methylguanine-DNA methyltransferase is responsible for the direct repair of O6-methylguanine lesions induced by alkylating agents, including temozolomide. O-6-methylguanine-DNA methyltransferase promoter hypermethylation is a well-established biomarker for temozolomide response in glioblastoma patients, also correlated with therapeutic response in colorectal cancer. Objectives: The ARETHUSA clinical trial aims to stratify colorectal cancer patients based on their mismatch repair status. Mismatch repair-deficient patients are eligible for treatment with immune checkpoint inhibitors (anti-PDL-1), whereas mismatch repair-proficient samples are screened for O-6-methylguanine-DNA methyltransferase promoter methylation to identify those suitable for temozolomide treatment. Methods: In this context, a subset of ARETHUSA metastatic colorectal cancer samples was used to compare two different techniques for assessing O-6-methylguanine-DNA methyltransferase hypermethylation: Methyl-BEAMing, a highly sensitive digital PCR approach that combines emulsion PCR and flow cytometry, and droplet digital PCR, a more automated procedure that enables the rapid, operator-independent analysis of a large number of samples. Results: Our study clearly demonstrates that the results obtained using Methyl-BEAMing and droplet digital PCR are comparable, with both techniques showing similar accuracy, sensitivity, and reproducibility. Conclusions: Digital droplet PCR proved to be an efficient method for detecting gene promoter methylation. However, the Methyl-BEAMing method has proved more sensitive for detecting low quantities of DNA. Full article
(This article belongs to the Section Pathology and Molecular Diagnostics)
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<p>Representative plots of the gate strategy used for the flow cytometric analysis. (<b>A</b>) ARETHUSA samples analyzed through the Methyl-BEAMing technique were first grouped based on their complexity events. (<b>B</b>) Gate R2 (46.6%) includes unmethylated events, whereas R3 (4.1%) contains methylated ones. (<b>C</b>) The value of 61.7% referred to gate R3 is representative of a methylated sample. (<b>D</b>) Unmethylated sample control (R3 0%). (<b>E</b>) Methylated sample control (R3 83%). (<b>F</b>) The 50% control, obtained by mixing the unmethylated control with the methylated one (R3 34.1%) (<b>G</b>) Methylation profiling of CRC tissue samples assessed by Methyl-BEAMing.</p>
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<p>Assessment of <span class="html-italic">MGMT</span> gene promoter hypermethylation using the ddPCR technique. (<b>A</b>) Scheme of ddPCR: DNA amplification occurs independently in thousands of drops through a water-in-oil emulsion. Droplets are classified as positive or negative based on the emitted fluorescence wavelength. (<b>B</b>) Linearity of quantification of ultramer oligonucleotide mixture assessed by ddPCR. (<b>C</b>) Methylation analysis by ddPCR using three independent bisulfite treatments in nine different mCRC samples. (<b>D</b>) <span class="html-italic">MGMT</span> methylation profiling of CRC tissue samples obtained by ddPCR.</p>
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<p>Evaluation of the concordance between results obtained using Methyl-BEAMing and those obtained using ddPCR. (<b>A</b>) Contingency table was carried out to qualitatively compare the number of methylated samples evaluated by either Methyl-BEAMing or ddPCR analysis. (<b>B</b>) Bland–Altman plot shows the agreement between the results of both techniques used. (<b>C</b>) Correlation and linear regression between Methyl-BEAMing and droplet digital PCR results. (<b>D</b>) The table reports differences between Methyl-BEAMing and ddPCR, including the time of execution, number of amplification steps, automation grade, and sensitivity.</p>
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<p>Analysis of the incidence of MGMT gene promoter methylation in a cohort of mCRC patients. (<b>A</b>) Clinical features collected for 148 mCRC patients. (<b>B</b>) This Table shows a non-statistically significant trend of increased <span class="html-italic">MGMT</span> methylation frequency in older women compared to younger ones (Fisher’s exact probability test one-tailed <span class="html-italic">p</span>-value = 0.4963).</p>
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Article
Influence of Genetic Polymorphisms on the Age at Cancer Diagnosis in a Homogenous Lynch Syndrome Cohort of Individuals Carrying the MLH1:c.1528C>T South African Founder Variant
by Lutricia Ndou, Ramadhani Chambuso, Ursula Algar, Paul Goldberg, Adam Boutall and Raj Ramesar
Biomedicines 2024, 12(10), 2201; https://doi.org/10.3390/biomedicines12102201 - 27 Sep 2024
Cited by 1 | Viewed by 1091
Abstract
Background: High variability in the age at cancer diagnosis in Lynch syndrome (LS) patients is widely observed, even among relatives with the same germline pathogenic variant (PV) in the mismatch repair (MMR) genes. Genetic polymorphisms and lifestyle factors are thought to contribute to [...] Read more.
Background: High variability in the age at cancer diagnosis in Lynch syndrome (LS) patients is widely observed, even among relatives with the same germline pathogenic variant (PV) in the mismatch repair (MMR) genes. Genetic polymorphisms and lifestyle factors are thought to contribute to this variability. We investigated the influence of previously reported genetic polymorphisms on the age at cancer diagnosis in a homogenous LS cohort with a South African founder germline PV c.1528C>T in the MLH1 gene. Methods: A total of 359 LS variant heterozygotes (LSVH) from 60 different families were genotyped for specific genetic polymorphisms in GSTM1, GSTT1, CYP1A1, CYP17, PPP2R2B, KIF20A, TGFB1, XRCC5, TNF, BCL2, CHFR, CDC25C, ATM, TTC28, CDC25C, HFE, and hTERT genes using Multiplex Polymerase Chain Reaction and MassArray methods. Kaplan–Meier survival analysis, univariate and multivariate Cox proportional hazards gamma shared frailty models adjusted for sex were used to estimate the association between age at cancer diagnosis and polymorphism genotypes. A p-value < 0.05 after correcting for multiple testing using the Benjamini–Hochberg method was considered significant at a 95% confidence interval. Results: We identified three genotypes in the cell-cycle regulation, DNA repair, and xenobiotic-metabolism genes significantly associated with age at cancer diagnosis in this cohort. The CYP1A1 rs4646903 risk (GG) and CDC25C rs3734166 polymorphic (GA+AA) genotypes were significantly associated with an increased risk of a younger age at cancer diagnosis (Adj HR: 2.03 [1.01–4.08], p = 0.034 and Adj HR: 1.53 [1.09–2.14], p = 0.015, respectively). LSVH who were heterozygous for the XRCC5 rs1051685 SNP showed significant protection against younger age at cancer diagnosis (Adj HR: 0.69 [CI, 0.48–0.99], p = 0.043). The risk of a younger age at any cancer diagnosis was significantly high in LS carriers of one to two risk genotypes (Adj HR: 1.49 [CI: 1.06–2.09], corrected p = 0.030), while having one to two protective genotypes significantly reduced the risk of developing any cancer and CRC at a younger age (Adj HR: 0.52 [CI: 0.37–0.73], and Adj HR: 0.51 [CI: 0.36–0.74], both corrected p < 0.001). Conclusions: Polymorphism genotypes in the cell-cycle regulation, DNA repair, and xenobiotic metabolizing genes may influence the age at cancer diagnosis in a homogenous LS cohort with a South African founder germline PV c.1528C>T in the MLH1 gene. Full article
(This article belongs to the Section Molecular Genetics and Genetic Diseases)
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<p>A flowchart summarizing the study methodology.</p>
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<p>Age distribution of the LSVH in our study cohort, stratified by sex and health status (affected, unaffected, deceased).</p>
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<p>Kaplan–Meier survival plots by sex in the total cohort (i.e., the affected and unaffected LSVH). The curve shows the effect sex has on age at cancer (i.e., either CRC or extra-colonic cancer) diagnosis in LSVH. A significant difference in the age of cancer diagnosis can be seen between males (median age at diagnosis = 45 years) and females (median age at diagnosis = 51 years).</p>
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13 pages, 275 KiB  
Review
Targeted Therapies in Pancreatic Cancer: A New Era of Precision Medicine
by Bingyu Li, Qiong Zhang, Claire Castaneda and Shelly Cook
Biomedicines 2024, 12(10), 2175; https://doi.org/10.3390/biomedicines12102175 - 25 Sep 2024
Viewed by 3380
Abstract
Pancreatic ductal adenocarcinoma (PDAC), a leading cause of cancer mortality in the United States, presents significant treatment challenges due to its late diagnosis and poor prognosis. Despite advances, the five-year survival rates remain dismally low, with only a fraction of patients eligible for [...] Read more.
Pancreatic ductal adenocarcinoma (PDAC), a leading cause of cancer mortality in the United States, presents significant treatment challenges due to its late diagnosis and poor prognosis. Despite advances, the five-year survival rates remain dismally low, with only a fraction of patients eligible for potentially curative surgical interventions. This review aims to comprehensively examine the current landscape of targeted therapies in PDAC, focusing on recent developments in precision medicine approaches. We explore various molecular targets, including KRAS mutations, DNA damage repair deficiencies, mismatch repair pathway alterations, and rare genetic fusions. The review discusses emerging therapies, such as PARP inhibitors, immune checkpoint inhibitors, and novel targeted agents, like RET and NTRK inhibitors. We analyze the results of key clinical trials and highlight the potential of these targeted approaches in specific patient subgroups. Recent developments in PDAC research have emphasized precision oncology, facilitated by next-generation sequencing and the identification of genetic and epigenetic alterations. This approach tailors treatments to individual genetic profiles, improving outcomes and reducing side effects. Significant strides have been made in classifying PDAC into various subtypes, enhancing therapeutic precision. The identification of specific mutations in genes like KRAS, along with advancements in targeted therapies, including small molecule inhibitors, offers new hope. Furthermore, emerging therapies targeting DNA repair pathways and immunotherapeutic strategies also show promising results. As research evolves, integrating these targeted therapies with conventional treatments might improve survival rates and quality of life for PDAC patients, underscoring the shift towards a more personalized treatment paradigm. Full article
(This article belongs to the Special Issue Targeted Therapies for Cancers)
11 pages, 499 KiB  
Article
Differences in Prevalence of Colorectal Carcinoma by Gender and Marital Status and Expression of DNA Mismatch Repair Proteins
by Peilin Zhang, Omid Bakhtar, Chris Wixom, Brian Cox, John Lee, Saha Sadeghi, Aidan Clement, Lana Kabakibi and Madeleine Schwab
Int. J. Transl. Med. 2024, 4(3), 584-594; https://doi.org/10.3390/ijtm4030040 - 23 Sep 2024
Viewed by 1026
Abstract
Background: The effect of gender dimorphism and marital status on colorectal cancer mortality have been previously documented, but the relationship between these factors and DNA mismatch repair protein (MMRP) expression status is unknown. Methods: Colectomy specimens were reviewed retrospectively for patients between 2018 [...] Read more.
Background: The effect of gender dimorphism and marital status on colorectal cancer mortality have been previously documented, but the relationship between these factors and DNA mismatch repair protein (MMRP) expression status is unknown. Methods: Colectomy specimens were reviewed retrospectively for patients between 2018 and 2023, with demographics including race/ethnicity, gender, marital status, faith, body mass index, pathologic staging, and MMRP expression status. Statistical analyses were performed by using baseline characteristics tables and various programs in the R package. Results: A total 1018 colectomies were reviewed, and the tumor stages were significantly higher in the right colon (stage 3 and 4) than in the left colon and rectosigmoid colon (p < 0.01). Marital status was significantly associated with patients’ gender, age, tumor size, and tumor stages (all p < 0.01). MMRP status was available in 775 cases, with 139 (17.9%) MMRP-deficient and 636 (82%) MMRP-proficient. MMRP deficiency was significantly associated with older female patients, larger tumor sizes, higher tumor stages, higher histologic grades, and was more common in the right colon (all p < 0.01). In addition, MMRP deficiency was statistically associated with a higher percentage of divorced and widowed patients (p < 0.01). Multivariate linear regression analysis revealed a persistent association of MMRP deficiency with tumor size, tumor grade, tumor stage, and nodal metastasis, but the associations with gender and marital status no longer existed. Conclusions: The differences in prevalence of CRC by gender and marital status and tumor MMRP status illustrate the importance of these factors on tumor stages and nodal metastasis but these associations are more complex with other confounding factors. Full article
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<p>Distribution of CRC based on the anatomic site. Left panel shows the percentage of CRC at each anatomic location. The right panel shows the distribution of CRC in the right colon, transverse colon, left colon, and rectosigmoid colon.</p>
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<p>Multivariate linear regression model of MMRP status in CRC patients. <span class="html-italic">p</span> &lt; 0.05 is considered statistically significant (*).</p>
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31 pages, 1385 KiB  
Review
Predictive Biomarkers and Resistance Mechanisms of Checkpoint Inhibitors in Malignant Solid Tumors
by Luciana Alexandra Pavelescu, Robert Mihai Enache, Oana Alexandra Roşu, Monica Profir, Sanda Maria Creţoiu and Bogdan Severus Gaspar
Int. J. Mol. Sci. 2024, 25(17), 9659; https://doi.org/10.3390/ijms25179659 - 6 Sep 2024
Cited by 1 | Viewed by 4043
Abstract
Predictive biomarkers for immune checkpoint inhibitors (ICIs) in solid tumors such as melanoma, hepatocellular carcinoma (HCC), colorectal cancer (CRC), non-small cell lung cancer (NSCLC), endometrial carcinoma, renal cell carcinoma (RCC), or urothelial carcinoma (UC) include programmed cell death ligand 1 (PD-L1) expression, tumor [...] Read more.
Predictive biomarkers for immune checkpoint inhibitors (ICIs) in solid tumors such as melanoma, hepatocellular carcinoma (HCC), colorectal cancer (CRC), non-small cell lung cancer (NSCLC), endometrial carcinoma, renal cell carcinoma (RCC), or urothelial carcinoma (UC) include programmed cell death ligand 1 (PD-L1) expression, tumor mutational burden (TMB), defective deoxyribonucleic acid (DNA) mismatch repair (dMMR), microsatellite instability (MSI), and the tumor microenvironment (TME). Over the past decade, several types of ICIs, including cytotoxic T-lymphocyte-associated protein 4 (CTLA-4) inhibitors, anti-programmed cell death 1 (PD-1) antibodies, anti-programmed cell death ligand 1 (PD-L1) antibodies, and anti-lymphocyte activation gene-3 (LAG-3) antibodies have been studied and approved by the Food and Drug Administration (FDA), with ongoing research on others. Recent studies highlight the critical role of the gut microbiome in influencing a positive therapeutic response to ICIs, emphasizing the importance of modeling factors that can maintain a healthy microbiome. However, resistance mechanisms can emerge, such as increased expression of alternative immune checkpoints, T-cell immunoglobulin (Ig), mucin domain-containing protein 3 (TIM-3), LAG-3, impaired antigen presentation, and alterations in the TME. This review aims to synthesize the data regarding the interactions between microbiota and immunotherapy (IT). Understanding these mechanisms is essential for optimizing ICI therapy and developing effective combination strategies. Full article
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<p>Inhibition of PD-L1/PD-1 checkpoint. (<b>A</b>)<b>. T-cell-Inhibited Activation.</b> T Cell: This immune cell is essential for locating and eliminating cancer cells. Tumor Cell: A malignant cell that uses inhibitory pathways to avoid detection by the immune system. MHC-TCR Complex: The tumor cell’s major histocompatibility complex (MHC) binds an antigen to the TCR. For T cells to identify the tumor cell, this contact is necessary. When activated, a T-cell receptor known as PD-1 transmits an inhibitory signal that lessens the T cell’s capacity to assault the tumor. PD-L1 is a ligand expressed on the surface of tumor cells and attaches itself to T-cell PD-1. By blocking T-cell activation, this interaction enables the tumor cell to avoid immune recognition and elimination. Since the tumor cell, in this instance, expresses PD-L1, which binds to the T cell’s PD-1 receptor, the tumor cell’s capacity to attack the T cell is hindered. The T cell receives a “stop” signal from this contact, which stops it from destroying the tumor cell. (<b>B</b>)<b>. ICI Blockade.</b> T cells that have been fully activated can mount an immunological response. Anti-PD-1/PD-L1 Antibodies: These antibodies prevent the interaction between the tumor cell’s PD-L1 and the T cell’s PD-1. The inhibitory signal is stopped by obstructing this contact, which keeps the T cell activated. Tumor Cell Death and Immune Attack: As a result of the antibodies blocking the inhibitory signals, the T cell releases cytokines and other cytotoxic chemicals, which ultimately cause the tumor cell to be destroyed. Anti-PD-1 or anti-PD-L1 antibodies, which are ICIs, in this case, block the interaction that would typically inhibit the T cell. As a result, the tumor cell is successfully attacked and killed by the T cell, which still functions. Created with <a href="http://BioRender.com" target="_blank">BioRender.com</a> (accessed on 18 August 2024).</p>
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<p>CTLA-4 checkpoint inhibition mechanism. Dendritic cell (DC): The APC type plays a crucial role in activating naive T cells. MHC: The MHC on the DC presents an antigen to the TCR on the naive T cell. This interaction is essential for T-cell activation. B7 molecules (CD80/CD86): These molecules on the DC surface bind to receptors on the T cell to either provide activation signals or engage in inhibitory signaling. Naive T cell: This T cell has not yet encountered its specific antigen. TCR: This receptor recognizes the antigen the MHC presents on the DC, initiating activation. CD28: A costimulatory receptor on the T cell that binds to B7 molecules (CD80/CD86) on the DC. When CD28 binds to B7, it provides a necessary costimulatory signal for T-cell activation, enhancing its response. CTLA-4: This receptor is also on the T cell and competes with CD28 for binding to B7. However, when CTLA-4 binds to B7, it sends an inhibitory signal, dampening the T cell’s activation to prevent excessive immune responses. Anti-CTLA-4 antibody: The figure shows an anti-CTLA-4 antibody blocking the CTLA-4 receptor. This prevents CTLA-4 from binding to B7 molecules, thereby blocking the inhibitory signal normally downregulating T-cell activation. By blocking CTLA-4, the antibody enhances the activation signal from the CD28-B7 interaction, promoting a stronger immune response. Created with <a href="http://BioRender.com" target="_blank">BioRender.com</a> (accessed on 10 August 2024).</p>
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<p>The influence of intestinal microbiota in ICI treatment. DCs in the gut microbiome identify non-self-material and present it to T cells in the lymph nodes, activating memory T cells (TCMs). These TCMs differentiate into effector T cells and proliferate, increasing levels of human IL-2 and IFN-γ. Through their primary mechanisms, IL-2 and IFN-γ enhance the effectiveness of the therapeutic response to ICIs. Created with <a href="http://BioRender.com" target="_blank">BioRender.com</a> (accessed on 10 August 2024).</p>
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16 pages, 6041 KiB  
Article
Identification of TAT as a Biomarker Involved in Cell Cycle and DNA Repair in Breast Cancer
by Fei Xie, Saiwei Hua, Yajuan Guo, Taoyuan Wang, Changliang Shan, Lianwen Zhang and Tao He
Biomolecules 2024, 14(9), 1088; https://doi.org/10.3390/biom14091088 - 30 Aug 2024
Viewed by 1077
Abstract
Breast cancer (BC) is the most frequently diagnosed cancer and the primary cause of cancer-related mortality in women. Treatment of triple-negative breast cancer (TNBC) remains particularly challenging due to its resistance to chemotherapy and poor prognosis. Extensive research efforts in BC screening and [...] Read more.
Breast cancer (BC) is the most frequently diagnosed cancer and the primary cause of cancer-related mortality in women. Treatment of triple-negative breast cancer (TNBC) remains particularly challenging due to its resistance to chemotherapy and poor prognosis. Extensive research efforts in BC screening and therapy have improved clinical outcomes for BC patients. Therefore, identifying reliable biomarkers for TNBC is of great clinical importance. Here, we found that tyrosine aminotransferase (TAT) expression was significantly reduced in BC and strongly correlated with the poor prognosis of BC patients, which distinguished BC patients from normal individuals, indicating that TAT is a valuable biomarker for early BC diagnosis. Mechanistically, we uncovered that methylation of the TAT promoter was significantly increased by DNA methyltransferase 3 (DNMT3A/3B). In addition, reduced TAT contributes to DNA replication and cell cycle activation by regulating homologous recombination repair and mismatch repair to ensure genomic stability, which may be one of the reasons for TNBC resistance to chemotherapy. Furthermore, we demonstrated that Diazinon increases TAT expression as an inhibitor of DNMT3A/3B and inhibits the growth of BC by blocking downstream pathways. Taken together, we revealed that TAT is silenced by DNMT3A/3B in BC, especially in TNBC, which promotes the proliferation of tumor cells by supporting DNA replication, activating cell cycle, and enhancing DNA damage repair. These results provide fresh insights and a theoretical foundation for the clinical diagnosis and treatment of BC. Full article
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<p>TAT is down-regulated and associated with poor prognosis in BC. (<b>A</b>,<b>B</b>) Tyrosine-metabolizing enzymes (TAT, HPD, HGD, GSTZ1, and FAH) and mRNA and protein expression levels between tumor and normal tissues in patients with BC in TCGA database. (<b>C</b>) ROC curve analysis for diagnostic value of tyrosine-metabolizing enzymes (TAT, HPD, HGD, GSTZ1, and FAH) in BC. AUC—area under curve. (<b>D</b>) Overall survival of patients with BC grouped by tyrosine-metabolizing enzyme expression through the Kaplan-Meier plotter online analysis tool. All error bars, mean values ± SD, and <span class="html-italic">p</span> values were determined by unpaired two-tailed Student’s <span class="html-italic">t</span> test or one way ANOVA of <span class="html-italic">n</span> = 3 independent biological experiments.</p>
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<p><span class="html-italic">TAT</span> promoter is methylated by DNMT3A and DNMT3B. (<b>A</b>) Methylation level of <span class="html-italic">TAT</span> promoter between tumor and normal tissues in patients with BC in TCGA database. (<b>B</b>) DNA methyltransferases (DNMT1, DNMT3A, and DNMT3B) and mRNA and protein expression levels between tumor and normal tissues in patients with BC in TCGA database. (<b>C</b>) Representative IHC staining of DNMT1, DNMT3A, and DNMT3B in BC from HPA database. (<b>D</b>) Expression correlation between DNMT3A/B and TAT in BC patients. Each black circle represents the level of two proteins in each sample. The red lines represent the linear relationship between the two proteins in these samples. (<b>E</b>) Overall survival of patients with BC grouped by DNMT1/DNMT3A/DNMT3B expression through the Kaplan–Meier plotter online analysis tool. All error bars, mean values ± SD, and <span class="html-italic">p</span> values were determined by unpaired two-tailed Student’s <span class="html-italic">t</span> test or one way ANOVA of <span class="html-italic">n</span> = 3 independent biological experiments. *** <span class="html-italic">p</span> &lt; 0.001.</p>
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<p>Expression of TAT and DAMT3A/3B was negatively correlated in TNBC. (<b>A</b>) mRNA level of <span class="html-italic">TAT</span> between tumor and normal tissues in patients with BC in TCGA database. (<b>B</b>) ROC curve analysis for diagnostic value of TAT in GSE93601. (<b>C</b>) mRNA level of <span class="html-italic">DNMT3A/3B</span> between tumor and normal tissues in patients with BC in TCGA database. (<b>D</b>) Expression correlation between DNMT3A/B and TAT. Each black circle represents the level of two proteins in each sample. The red lines represent the linear relationship between the two proteins in these samples. (<b>E</b>) Expression of TAT, DNMT3A, and NDMT3B in the paired tumor-adjacent normal breast tissues (N) and human BC tissues (T) by WB. (<b>F</b>) Levels of TAT, DNMT3A, and DNMT3B were analyzed in clinical normal breast tissues and BC tissues. (<b>G</b>) The correlation between TAT and DNMT3A/DNMT3B protein expression in clinical samples were analyzed. Each black circle represents the level of two proteins in each sample. The red lines represent the linear relationship between the two proteins in these samples. All error bars, mean values ± SD, and <span class="html-italic">p</span> values were determined by unpaired two-tailed Student’s <span class="html-italic">t</span> test or one way ANOVA of <span class="html-italic">n</span> = 3 independent biological experiments. * <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. Original images of (<b>E</b>) can be found in <a href="#app1-biomolecules-14-01088" class="html-app">Supplementary Materials</a>.</p>
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<p>DNMT3A and DNMT3B methylate the promoter resulting in decreased TAT expression in TNBC. (<b>A</b>) Overall survival of BC patients with different receptor expression levels grouped by TAT expression using the Kaplan–Meier plotter online analysis tool. (<b>B</b>) <span class="html-italic">TAT</span> mRNA expression level between different subclasses of tumor and normal tissues in patients with BC in TCGA database. (<b>C</b>) <span class="html-italic">TAT</span> promoter methylation level between different subclasses of tumor and normal tissues in patients with BC in TCGA database. (<b>D</b>) <span class="html-italic">DNMT3A/3B</span> mRNA and protein expression levels between different subclasses of tumor and normal tissues in patients with BC in TCGA database. (<b>E</b>) mRNA level of <span class="html-italic">DNMT3A/3B</span> and <span class="html-italic">TAT</span> between TNBC tumor and non-TNBC tumor tissues in patients with BC in GEO database. (<b>F</b>) mRNA level of <span class="html-italic">DNMT3A/3B</span> and <span class="html-italic">TAT</span> in the tumor tissues of BC patients with different malignant degrees in GEO database. All error bars, mean values ± SD, and <span class="html-italic">p</span> values were determined by unpaired two-tailed Student’s <span class="html-italic">t</span> test or one way ANOVA of <span class="html-italic">n</span> = 3 independent biological experiments. * <span class="html-italic">p</span> &lt; 0.05; *** <span class="html-italic">p</span> &lt; 0.001.</p>
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<p>Decreased TAT promotes activation of the cell cycle and promotes DNA repair. (<b>A</b>) GSEA pathway enrichment analyses of TAT signature in patients with BC from the TCGA datasets. (<b>B</b>) Overlapping analysis for related genes of sister chromatid segregation, DNA-dependent DNA replication, and cell cycle. (<b>C</b>) <span class="html-italic">CDC6</span> mRNA expression levels between tumor and normal tissues in patients with BC in the TCGA database. (<b>D</b>) Overall survival of patients with BC grouped by <span class="html-italic">CDC6</span> expression through the Kaplan–Meier plotter online analysis tool. (<b>E</b>) GSEA pathway enrichment analyses of TAT signature in patients with BC from the TCGA datasets. (<b>F</b>) Overlapping analysis for related genes of DNA repair, homologous recombination, and mismatch repair. (<b>G</b>) <span class="html-italic">RPA3</span>, <span class="html-italic">POLD1</span>, and <span class="html-italic">POLD2</span> mRNA expression levels between tumor and normal tissues in patients with BC in the TCGA database. All error bars, mean values ± SD, and <span class="html-italic">p</span> values were determined by unpaired two-tailed Student’s <span class="html-italic">t</span> test or one way ANOVA of <span class="html-italic">n</span> = 3 independent biological experiments.</p>
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<p>Targeting DNMT3A/3B inhibits growth and proliferation of breast cancer cells. (<b>A</b>) Molecular models of Diazinon binding to DNMT3A/DNMT3B. (<b>B</b>) Expression of <span class="html-italic">TAT</span>, <span class="html-italic">RPA3</span>, <span class="html-italic">POLD1</span>, and <span class="html-italic">POLD2</span> in MCF7 and MDA-MB-231 cells with the treatment of Diazinon by qPCR. (<b>C</b>) The protein levels of γH2Ax, CyclinD1, and CDK4 in MDA-MB-231 cells with the treatment of Diazinon by qPCR. (<b>D</b>) Colony formation of MCF7 cells with the treatment of Diazinon. (<b>E</b>) Proliferation of MCF7 cells with the treatment of Diazinon. (<b>F</b>) Colony formation of MDA-MB-231 cells with the treatment of Diazinon. (<b>G</b>) Proliferation of MDA-MB-231 cells with the treatment of Diazinon. All error bars, mean values ± SD, and <span class="html-italic">p</span> values were determined by unpaired two-tailed Student’s <span class="html-italic">t</span> test or one way ANOVA of <span class="html-italic">n</span> = 3 independent biological experiments. * <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. Original images of (<b>C</b>) can be found in <a href="#app1-biomolecules-14-01088" class="html-app">Supplementary Materials</a>.</p>
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21 pages, 4352 KiB  
Article
PDCD10 Is a Key Player in TMZ-Resistance and Tumor Cell Regrowth: Insights into Its Underlying Mechanism in Glioblastoma Cells
by Yuan Zhu, Su Na Kim, Zhong-Rong Chen, Rainer Will, Rong-De Zhong, Philipp Dammann and Ulrich Sure
Cells 2024, 13(17), 1442; https://doi.org/10.3390/cells13171442 - 28 Aug 2024
Viewed by 1076
Abstract
Overcoming temozolomide (TMZ)-resistance is a major challenge in glioblastoma therapy. Therefore, identifying the key molecular player in chemo-resistance becomes urgent. We previously reported the downregulation of PDCD10 in primary glioblastoma patients and its tumor suppressor-like function in glioblastoma cells. Here, we demonstrate that [...] Read more.
Overcoming temozolomide (TMZ)-resistance is a major challenge in glioblastoma therapy. Therefore, identifying the key molecular player in chemo-resistance becomes urgent. We previously reported the downregulation of PDCD10 in primary glioblastoma patients and its tumor suppressor-like function in glioblastoma cells. Here, we demonstrate that the loss of PDCD10 causes a significant TMZ-resistance during treatment and promotes a rapid regrowth of tumor cells after treatment. PDCD10 knockdown upregulated MGMT, a key enzyme mediating chemo-resistance in glioblastoma, accompanied by increased expression of DNA mismatch repair genes, and enabled tumor cells to evade TMZ-induced cell-cycle arrest. These findings were confirmed in independent models of PDCD10 overexpressing cells. Furthermore, PDCD10 downregulation led to the dedifferentiation of glioblastoma cells, as evidenced by increased clonogenic growth, the upregulation of glioblastoma stem cell (GSC) markers, and enhanced neurosphere formation capacity. GSCs derived from PDCD10 knockdown cells displayed stronger TMZ-resistance and regrowth potency, compared to their parental counterparts, indicating that PDCD10-induced stemness may independently contribute to tumor malignancy. These data provide evidence for a dual role of PDCD10 in tumor suppression by controlling both chemo-resistance and dedifferentiation, and highlight PDCD10 as a potential prognostic marker and target for combination therapy with TMZ in glioblastoma. Full article
(This article belongs to the Special Issue Molecular and Cellular Mechanisms of Cancers: Glioblastoma III)
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<p>Knockdown of PDCD10 confers TMZ-resistance on GBM cells. (<b>A</b>) Confirmation of PDCD10 knockdown in lentiviral transduced U87 and T98g cells by RT<sup>2</sup>-PCR (<b>a</b>), western blot (<b>b</b>), and semi-quantitation of the blots (<b>c</b>). ev and sh: empty vector- and PDCD10 shRNA-transduced cells, respectively. IOD: integrated optical density. *, <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, compared with ev. (<b>B</b>) Knockdown of PDCD10 in GBM cells leads to a resistance to TMZ-induced cell death. U87 and T98g cells received the treatment with 150 µM (<b>a</b>) and 300 µM (<b>b</b>) of TMZ, respectively, for 72 h. Thereafter, TMZ was washed-out. Remaining viable cells were cultured in the TMZ-free medium for 3 d, which is defined as the post-treatment phase. Control cells (C) were treated with vehicle DMSO (0.1% and 0.2% for U87 and T98g, respectively). MTT assay was performed to determine the viability of cells at 72 h after TMZ treatment (treatment phase) and 3 d after washing-out of TMZ (post-treatment phase). *, <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, compared with ev; ##, <span class="html-italic">p</span> &lt; 0.01; ###, <span class="html-italic">p</span> &lt; 0.0001, compared with evC in the same phase; +++, <span class="html-italic">p</span> &lt; 0.001, compared with corresponding group in treatment phase.</p>
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<p>Knockdown of PDCD10 enhances cell viability after rechallenge with TMZ in regrown cells (RG) generated from the established acquired TMZ-resistant model. (<b>A</b>) Confirmation of PDCD10 knockdown in shU87-RG and shT98g-RG cells by RT<sup>2</sup>-PCR (<b>a</b>) and by FACS of respective transduced cells that expressed red-fluorescence protein (RFP) and green-fluorescence protein (GFP) (<b>b</b>). *, <span class="html-italic">p</span> &lt; 0.05, compared with ev. (<b>B</b>) MTT assay in RG cells in treatment phase and post-treatment phase. MTT assay was performed with ev/shU87 and ev/shT98g cells that received the treatment with 150 µM (<b>a</b>) and 300 µM (<b>b</b>) of TMZ, respectively, for 72 h (treatment phase) and 2 d and 4 d after washing-out TMZ (post-treatment phase, without reseeding). Control cells (C) received vehicle DMSO (0.1% and 0.2% for U87 and T98g, respectively). *, <span class="html-italic">p</span> &lt; 0.05; ***, <span class="html-italic">p</span> &lt; 0.001, compared with evRG C (72 h); ###, <span class="html-italic">p</span> &lt; 0.001, compared with evRG-TMZ (72 h). (<b>C</b>) MTT assay in RG cells in a second post-treatment model with reseeding. ev/shU87-RG and ev/shT98g-RG cells received the treatment with 150 µM (<b>a</b>) and 300 µM (<b>b</b>) of TMZ, respectively, for 72 h. Thereafter, TMZ–containing media and dead cells were washed-out, and the viable cells were harvested and reseeded at the same density, followed by 2, 4, and 6 d of culture in drug-free medium. A significantly more rapid regrowth was observed in both TMZ-treated shU87-RG and shT98g-RG cells, compared with the corresponding evRG cells after reseeding and culturing in drug-free media. *, <span class="html-italic">p</span> &lt; 0.05; ***, <span class="html-italic">p</span> &lt; 0.001, compared with corresponding evRG.</p>
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<p>Overexpression of PDCD10 sensitizes GBM cells to TMZ treatment. (<b>A</b>) Confirmation of overexpression of PDCD10 in lentiviral transduced U87 and T98g cells by RT<sup>2</sup>-PCR (<b>a</b>) and western blot (<b>b</b>) and semi-quantitation of the blots (<b>c</b>). Western blotting with anti-V5 antibody distinguishes between the expression of transgenic C-terminal V5-tagged PDCD10 protein and endogenous protein. ev and ox: empty vector-transduced and PDCD10-overexpressing cells, respectively. IOD: integrated optical density. *, <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, compared with ev. (<b>B</b>) Overexpression of PDCD10 significantly reduces cell viability in a concentration-dependent manner after 72 h of TMZ treatment in both oxU87 (<b>a</b>) and oxT98g (<b>b</b>) cells. Control cells (C) were treated with vehicle DMSO (0.1% and 0.2% for U87 and T98g, respectively). *, <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, compared with corresponding ev groups. (<b>C</b>) Overexpression of PDCD10 sensitizes GBM cells to TMZ treatment 72 h after TMZ treatment (treatment phase) and 3 d after washing-out TMZ (post-treatment phase). ev/oxU87 and ev/oxT98g cells received the treatment with 150 µM (<b>a</b>) and 300 µM (<b>b</b>) of TMZ for 72 h, respectively. Thereafter, TMZ-containing medium and dead cells were washed-out and the viable cells were further cultured in drug-free medium for 3 d followed by MTT assay. Control cells (C) were treated with vehicle DMSO (0.1% and 0.2% for U87 and T98g, respectively). *, <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, compared with corresponding ev groups; +++, <span class="html-italic">p</span> &lt; 0.001, compared with corresponding evC in the treatment phase; #, <span class="html-italic">p</span> &lt; 0.05, ###, <span class="html-italic">p</span> &lt; 0.001, compared with corresponding evC in the same phase.</p>
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<p>DNA replication in response to TMZ treatment is dependent on PDCD10 expression. DNA replication was detected by EdU incorporation followed by FACS at 72 h of TMZ treatment (treatment phase) and at 3 d after TMZ-washing-out and -culturing in drug-washout media (post-treatment phase). ev/shT98g-RG and ev/oxT98g cells received 500 and 300 µM TMZ, respectively. (<b>A</b>,<b>C</b>) Histograms of EdU-positive (EdU+) and -negative (EdU−) cell populations in ev/shT98g-RG and ev/oxT98g cells, respectively. (<b>B</b>,<b>D</b>) Bar graphs of EdU+/− populations based on the corresponding histograms in (<b>A</b>,<b>C</b>). Knockdown of PDCD10 leads to an increase in DNA replication in both the treatment and post-treatment phases of T98g-RG cells, whereas overexpression of PDCD10 suppresses DNA replication in response to TMZ treatment. The data are representative of at least three independent experiments.</p>
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<p>Alteration in cell cycle checkpoints in response to TMZ treatment is dependent on PDCD10 expression. Cell cycle assay was performed by FACS after 72 h of TMZ treatment (treatment phase) and at 3 d after TMZ-washing-out and -culturing in drug-washout media (post-treatment phase). ev/shT98g-RG and ev/oxT98g cells received 500 and 300 µM TMZ, respectively. (<b>A</b>,<b>C</b>) are representative of cell cycle histograms in ev/shT98g-RG and ev/oxT98g cells, respectively. DNA content-based cell cycle distributions were defined using FlowJo with the Dean–Jett–Fox algorithm and presented in histograms. Each cell cycle phase is shown in different colors: G0/G1- (blue), S- (yellow), and G2/M-phase (green). (<b>B</b>,<b>D</b>) Stacked bar graphs of the distribution of the cell population in the cell cycle based on the corresponding histograms in (<b>A</b>,<b>C</b>). Knockdown of PDCD10 leads to the escape of cells from G2/M arrest and increases the population in the S phase (DNA replication phase) in both the treatment and post-treatment phases, whereas overexpression does the opposite. The data are representative of at least three independent experiments.</p>
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<p>Knockdown of PDCD10 in T98g-RG cells leads to deregulation of DNA damage response (DDR) genes. ev/shT98g-RG and ev/oxT98g cells received 300 µM of TMZ or vehicle (0.2% DMSO) treatment (no TMZ treatment). Cells were harvested for PCR detection of DDR genes after 72 h of TMZ treatment (treatment phase) and at 3 d after TMZ-washing-out and culturing in drug-free media (post-treatment phase). (<b>A</b>) Expression of MGMT in T98g-RG (<b>a</b>) cells and ev/oxT98g (<b>b</b>) cells in the no treatment, treatment (300 µM, 72 h), and post-treatment (3 d after washing out) phases. (<b>B</b>) Western blot (<b>a</b>) and semi-quantitation of the blots (<b>b</b>) of the MGMT protein expression in ev/shT98g-RG and ev/oxT98g cells. (<b>C</b>) Expression of DDR genes (<span class="html-italic">MSH2</span>, <span class="html-italic">MSH6,</span> and <span class="html-italic">PMS2</span>) in T98g-RG cells in the no treatment (<b>a</b>), treatment (<b>b</b>), and post-treatment phases (<b>c</b>), respectively. (<b>D</b>) Expression of DDR genes in ev/oxT98g cells in the no treatment (<b>a</b>), treatment (<b>b</b>), and post-treatment phases (<b>c</b>), respectively. *, <span class="html-italic">p</span> &lt; 0.05; **, <span class="html-italic">p</span> &lt; 0.01 and ***, <span class="html-italic">p</span> &lt; 0.001, compared with corresponding ev.</p>
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<p>PDCD10 expression determines the colony formation capacity of GBM cells. ev/shT98g-RG (<b>A</b>) and ev/oxT98g (<b>B</b>) cells received 300 µM of TMZ or vehicle (0.2% DMSO) treatment. Cells were harvested for colony formation assay in a 12-well plate in triplicate after 72 h of TMZ treatment (treatment phase) and at 3 d after TMZ-washing-out and culturing in drug-free media (post-treatment phase). The number of colonies was quantified after staining with 0.5% crystal violet using the ImageJ software (version 1.54j). Representative images of colony formation in ev/shT98g-RG and ev/oxT98g are shown in (<b>Aa</b>) and (<b>Ba</b>), respectively. Quantitative analysis of the colony numbers is presented in (<b>Ab</b>) and (<b>Bb</b>) for ev/shT98g-RG and ev/oxT98g cells, respectively. ***, <span class="html-italic">p</span> &lt; 0.001, compared with ev; ##, <span class="html-italic">p</span> &lt; 0.01 and ###, <span class="html-italic">p</span> &lt; 0.001, compared with corresponding C; +++, <span class="html-italic">p</span> &lt; 0.001, compared with corresponding group in the treatment phase.</p>
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<p>Knockdown of PDCD10 enhances the self-renewal capacity of U87-RG cells and GSCs generated from the parental cell line U87-RG (U87-RG-GSCs), and increases the expression of stem cell markers in RG-GSCs. (<b>A</b>) Representative images of neurospheres derived from U87-RG cells and U87-RG-GSCs. Scale bar: 100 µm. (<b>B</b>) Quantitative analysis of neurospheres formation efficiency (SFE). ***, <span class="html-italic">p</span> &lt; 0.001, compared with corresponding ev; ###, <span class="html-italic">p</span> &lt; 0.001, compared with corresponding parental cells. (<b>C</b>) Knockdown of PDCD10 increases the mRNA expression of stemness genes in RG-GSCs. The expression of stem cell markers <span class="html-italic">Nestin</span> and <span class="html-italic">KLF4</span> was detected by RT<sup>2</sup>-PCR in untreated U87-RG-GSCs, and in shU87-RG-GSCs treated with TMZ (150 µM) for 72 h. *, <span class="html-italic">p</span> &lt; 0.05; ***, <span class="html-italic">p</span> &lt; 0.001, compared with corresponding ev; #, <span class="html-italic">p</span> &lt; 0.05; ###, <span class="html-italic">p</span> &lt; 0.001, compared with evC; +, <span class="html-italic">p</span> &lt; 0.05, compared with corresponding C. (<b>D</b>) Knockdown of PDCD10 enhances the viability of parental U87-RG cells and their GSC variants. U87-RG cells (left) and U87-RG-GSCs (right) received TMZ (150 M) or vehicle DMSO (0.1%) treatment for 72 h. Cell viability was detected after 72 h of treatment. *, <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, compared with corresponding ev; #, <span class="html-italic">p</span> &lt; 0.05; ##, <span class="html-italic">p</span> &lt; 0.01, compared with evC; +, <span class="html-italic">p</span> &lt; 0.05, ++, <span class="html-italic">p</span> &lt; 0.01, compared with corresponding parental cells. (<b>E</b>) Knockdown of PDCD10 reduces the mRNA expression of MMR genes (<span class="html-italic">MSH2</span>, <span class="html-italic">MSH6</span>, and <span class="html-italic">PMS2</span>) in U87-RG-GSCs. U87-RG-GSCs received treatment of 150 µM TMZ or vehicle (0.1% DMSO; no treatment). Cells were harvested for PCR detection of MMR genes after 72 h of treatment. Expression of MMR genes in non-treated (<b>Ea</b>) and TMZ-treated U87-RG-GSCs (<b>Eb</b>). *, <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, compared with ev.</p>
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<p>Schematic summary of the role and mechanism of PDCD10 in acquired TMZ-resistance. Knockdown of PDCD10 (shPDCD10) in GBM cells significantly increased cell survival in response to TMZ treatment, and strongly promoted tumor cell regrowth in the post-treatment phase, which collectively accounted for acquired TMZ-resistance. Mechanism studies revealed that the loss of PDCD10 modulated the expression of DNA damage response genes (i.e., upregulating MGMT and downregulating MMR genes <span class="html-italic">MSH2</span>, <span class="html-italic">MSH6</span>, and <span class="html-italic">PMS2</span>), and altered the cell cycle process, as evidenced by the evasion of tumor cells from arrest at the G2/M phase, and the increase in tumor cells in the proliferating S phase. In addition, shPDCD10-GBM cells exhibited higher cell plasticity, as demonstrated by an increased capacity for colony formation and transformation of shPDCD10-GBM cells into GSC-like cells that expressed higher levels of the stem cell markers Nestin and KLF4. In support of these findings, overexpression of PDCD10 (oxPDCD10) induced contrary changes in the molecular and cell behaviors observed in shPDCD10-GBM cells, increasing the sensitivity of oxPDCD10-GBM cells to TMZ treatment and suppressing tumor cell regrowth after TMZ treatment. Our results indicate that PDCD10 plays a pivotal role in acquired TMZ-resistance and thus represents a promising target for perturbing TMZ-resistance and tumor recurrence.</p>
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13 pages, 1408 KiB  
Review
Mutational Signatures in Colorectal Cancer: Translational Insights, Clinical Applications, and Limitations
by Giovanni Crisafulli
Cancers 2024, 16(17), 2956; https://doi.org/10.3390/cancers16172956 - 24 Aug 2024
Viewed by 1839
Abstract
A multitude of exogenous and endogenous processes have the potential to result in DNA damage. While the repair mechanisms are typically capable of correcting this damage, errors in the repair process can result in mutations. The findings of research conducted in 2012 indicate [...] Read more.
A multitude of exogenous and endogenous processes have the potential to result in DNA damage. While the repair mechanisms are typically capable of correcting this damage, errors in the repair process can result in mutations. The findings of research conducted in 2012 indicate that mutations do not occur randomly but rather follow specific patterns that can be attributed to known or inferred mutational processes. The process of mutational signature analysis allows for the inference of the predominant mutational process for a given cancer sample, with significant potential for clinical applications. A deeper comprehension of these mutational signatures in CRC could facilitate enhanced prevention strategies, facilitate the comprehension of genotoxic drug activity, predict responses to personalized treatments, and, in the future, inform the development of targeted therapies in the context of precision oncology. The efforts of numerous researchers have led to the identification of several mutational signatures, which can be categorized into different mutational signature references. In CRC, distinct mutational signatures are identified as correlating with mismatch repair deficiency, polymerase mutations, and chemotherapy treatment. In this context, a mutational signature analysis offers considerable potential for enhancing minimal residual disease (MRD) tests in stage II (high-risk) and stage III CRC post-surgery, stratifying CRC based on the impacts of genetic and epigenetic alterations for precision oncology, identifying potential therapeutic vulnerabilities, and evaluating drug efficacy and guiding therapy, as illustrated in a proof-of-concept clinical trial. Full article
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Figure 1
<p>Scheme of mutation and mutational signature profile; the six substitution subtypes (C&gt;A, C&gt;G, C&gt;T, T&gt;A, T&gt;C, and T&gt;G) are collectively referred to as pyrimidine substitutions, which are used to build the profile of each signature: each of the substitutions is examined by incorporating information on the bases immediately 5′ and 3′ to each mutated base, generating 96 possible mutation types (6 types of substitution × 4 types of 5′ base × 4 types of 3′ base) for each strand.</p>
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<p>Scheme of the specific enrichment in single-base substitutions (SBSs) for MSI/MMRd, MSS/MMRp, <span class="html-italic">POLE</span>-Mutant, and <span class="html-italic">POLE</span> wt MSS/MMRp CRCs and other SBSs identified in CRCs that are not specific to each (sub)class but are linked to treatments.</p>
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<p>This figure illustrates the specific single-base substitution (SBS) patterns that are typically identified in colorectal cancer (CRC) samples and reported as artifacts. It also depicts the differences in the CRC signal when using high-quality data (mutations filtered by matched normal or using a metanormal) and data obtained without this filter.</p>
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8 pages, 508 KiB  
Review
Accidental Encounter of Repair Intermediates in Alkylated DNA May Lead to Double-Strand Breaks in Resting Cells
by Shingo Fujii and Robert P. Fuchs
Int. J. Mol. Sci. 2024, 25(15), 8192; https://doi.org/10.3390/ijms25158192 - 26 Jul 2024
Viewed by 1065
Abstract
In clinics, chemotherapy is often combined with surgery and radiation to increase the chances of curing cancers. In the case of glioblastoma (GBM), patients are treated with a combination of radiotherapy and TMZ over several weeks. Despite its common use, the mechanism of [...] Read more.
In clinics, chemotherapy is often combined with surgery and radiation to increase the chances of curing cancers. In the case of glioblastoma (GBM), patients are treated with a combination of radiotherapy and TMZ over several weeks. Despite its common use, the mechanism of action of the alkylating agent TMZ has not been well understood when it comes to its cytotoxic effects in tumor cells that are mostly non-dividing. The cellular response to alkylating DNA damage is operated by an intricate protein network involving multiple DNA repair pathways and numerous checkpoint proteins that are dependent on the type of DNA lesion, the cell type, and the cellular proliferation state. Among the various alkylating damages, researchers have placed a special on O6-methylguanine (O6-mG). Indeed, this lesion is efficiently removed via direct reversal by O6-methylguanine-DNA methyltransferase (MGMT). As the level of MGMT expression was found to be directly correlated with TMZ efficiency, O6-mG was identified as the critical lesion for TMZ mode of action. Initially, the mode of action of TMZ was proposed as follows: when left on the genome, O6-mG lesions form O6-mG: T mispairs during replication as T is preferentially mis-inserted across O6-mG. These O6-mG: T mispairs are recognized and tentatively repaired by a post-replicative mismatched DNA correction system (i.e., the MMR system). There are two models (futile cycle and direct signaling models) to account for the cytotoxic effects of the O6-mG lesions, both depending upon the functional MMR system in replicating cells. Alternatively, to explain the cytotoxic effects of alkylating agents in non-replicating cells, we have proposed a “repair accident model” whose molecular mechanism is dependent upon crosstalk between the MMR and the base excision repair (BER) systems. The accidental encounter between these two repair systems will cause the formation of cytotoxic DNA double-strand breaks (DSBs). In this review, we summarize these non-exclusive models to explain the cytotoxic effects of alkylating agents and discuss potential strategies to improve the clinical use of alkylating agents. Full article
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Figure 1
<p>The MMR-mediated futile cycle model is driven by the persistent presence of the O<sup>6</sup>-mG lesion on the genomic DNA. Alkylating agents such as temozolomide (TMZ). Widely used in the clinic to treat glioblastomas, alkylating agents induce a broad spectrum of adducts (lesions) on genomic DNA. In the MMR-mediated futile cycle model, the O<sup>6</sup>-mG lesion among alkylating agent-induced DNA damages is exclusively focused as the only source related to alkylating agent-induced cell death phenomenon. During DNA replication, thymine is preferentially incorporated opposite the O<sup>6</sup>-mG, forming the O<sup>6</sup>-mG: T mispair (left panel). This mismatch activates the MMR system. However, the O<sup>6</sup>-mG lesion remains persistently present in the parental strand, resulting in a novel MMR attempt that is futile by nature (right panel). Such iterative rounds of the MMR repair process could ultimately lead to cell cycle arrest and apoptosis.</p>
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<p>The Repair Accident Model. In the case of treatment with an alkylating agent such as TMZ during chemotherapy, a variety of DNA damages appear and are repaired by multiple DNA repair pathways. Indeed, distinct DNA repair systems work independently depending upon their substrate specificities. The BER system mainly acts at the N7-mG or the N3-mA lesion, while the core MMR proteins recognize not only the O<sup>6</sup>-mG: T base pair but also the O<sup>6</sup>-mG: C base pair as shown by our work [<a href="#B11-ijms-25-08192" class="html-bibr">11</a>]. Therefore, even in non-dividing or quiescent cells treated by alkylating agents; when an N7-mG or an N3-mA lesion is closely located with the O<sup>6</sup>-mG lesion (e.g., within several hundred nucleotides), the accidental encounter of BER and MMR derived repair intermediates were shown to lead to DSB when they occur within the same time frame. In non-dividing cells treated by an alkylating agent, the “repair accident model” scenario is as follows: when the MMR system recognizes the O<sup>6</sup>-mG: C base pair, the mechanism of initiation of the MMR reaction is presently unknown. It is likely that the strand discrimination signal is provided by a BER-mediated nick equally likely to occur in either strand. This is in contrast to the situation that occurs during replication where MMR is directed toward the excision of the nascent strand. In any case, Exo1-mediated strand degradation or helicase unwinding assists the DNA gap formation. If, within the same timeframe, the MMR-mediated gap formation process encounters, in the opposite strand, a nick resulting from an intermediate, independent BER repair, a DSB will result. Red square indicates a DNA lesion that is repaired by the BER system. Green arrow shows degradation of a strand by an exonuclease.</p>
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