Chemotherapy Response In Cancer Research Articles

Discovery of a proliferation essential gene signature and actin-like 6A as potential biomarkers for predicting prognosis and neoadjuvant chemotherapy response in triple-positive breast cancer.

Patients with triple-positive breast cancer (TPBC) have a higher risk of recurrence and lower survival rates than patients with other luminal breast cancers. However, there are few studies on the predictive biomarkers of prognosis and treatment responses in TPBC. Proliferation essential genes (PEGs) were acquired from clustered regularly interspaced short palindromic repeats-associated protein 9 (CRISPR-Cas9) technology, and cohorts of patients with TPBC were obtained from public databases and our cohort. To develop a TPBC-PEG signature, Cox regression and least absolute shrinkage and selection operator regression analyses were applied. Functional analyses were performed with gene set enrichment analysis. The relationship between candidate genes and neoadjuvant chemotherapy (NACT) sensitivity was explored via real-time quantitative polymerase chain reaction (RT-qPCR) and immunohistochemistry (IHC) on the basis of clinical samples. Among 900 TPBC-PEGs, 437 showed significant differential expression between TPBC and normal tissues. Three prognostic PEGs (actin-like 6A [ACTL6A], chaperonin containing TCP1 subunit 2 [CCT2], and threonyl-TRNA synthetase [TARS]) were identified and used to construct the PEG signature. Patients with high PEG signature scores exhibited a worse overall survival and lower sensitivity to NACT than patients with low PEG signature scores. RT-qPCR results indicated that ACTL6A and CCT2 expression were significantly upregulated in patients who lacked sensitivity to NACT. IHC results showed that the ACTL6A protein was highly expressed in patients with NACT resistance and nonpathological complete responses. This efficient PEG signature prognostic model can predict the outcomes of TPBC. Furthermore, ACTL6A expression level was associated with the response to NACT, and could serve as an important factor in predicting prognosis and drug sensitivity of patients with TPBC.

RhoB expression associated with chemotherapy response and prognosis in colorectal cancer

PurposeTo examine the role of RhoB expression in relation to chemotherapy response, clinical outcomes and associated signaling pathways in colorectal cancer patients.Materials and methodsThe study included 5 colon cancer cell lines, zebrafish embryos and 260 colorectal cancer patients treated with 5-fluorouracil (5-FU) and oxaliplatin (OXL). The methods consisted of CRISPR/Cas9, reactive oxygen species (ROS), caspase-3 activity, autophagy flux, in-silico RNA sequencing and immunohistochemistry. Gene expression analysis and pathway analysis were conducted using RNA-seq data.ResultsAll cancer lines tested, including SW480, SW480-KO13 (RhoB knockout), SW480-KO55 (RhoB knockout), HCT116 and HCT116-OE (RhoB overexpressed), exhibited cytotoxicity to 5-FU and OXL. RhoB knockout cell lines demonstrated significantly reduced migration compared to the control cell lines. Furthermore, RhoB played a role in caspase-3-dependent apoptosis, regulation of ROS production and autophagic flux. The mRNA sequencing data indicated lower expression levels of oncogenes in RhoB knockout cell lines. The zebrafish model bearing SW480-KO showed a light trend toward tumor regression. RhoB expression by immunohistochemistry in patients was increased from normal mucosa to tumor samples. In patients who received chemotherapy, high RhoB expression was related to worse survival compared to low RhoB expression. Furthermore, the molecular docking analysis revealed that OXL had a higher binding affinity for RhoB than 5-FU, with a binding affinity of -7.8 kcal/mol and HADDOCK predicted molecular interactions between RhoB and caspase 3 protein. Gene-set enrichment analysis supported these findings, showing that enrichment of DNA damage response pathway and p53 signaling in RhoB overexpression treatment group, while the RhoB knockout treatment group exhibited enrichment in the negative regulation pathway of cell migration.ConclusionRhoB was negatively associated with chemotherapy response and survival in colorectal cancers. Therefore, RhoB inhibition may enhance chemotherapeutic responses and patient survival.

Machine learning constructs a T cell-related signature for predicting prognosis and drug sensitivity in ovarian cancer.

The leading cause of death related to gynecologic cancer is ovarian cancer, which typically has a poor prognosis. T cells are referred to as key mediators of immunosurveillance and tumor eradication, and unbalanced regulation or lack of T cells in tumors result in immunotherapy resistance. The identification of T cell related markers depended on single-cell RNA-seq analysis. Using data from multiple datasets, including TCGA, GSE14764, GSE26193, GSE26712, and GSE140082, we constructed a prognostic signature called TRS (T cell-related signature) using 10 different machine learning algorithms. The correlation between TRS and drug sensitivity were analyzed using the data from GSE91061 and IMvigor210 dataset. PlsRcox method based TRS was as a risk factor for the clinical outcome of ovarian cancer patients. In comparison with stage, grade and many prognostic signatures, the performance of our TRS in evaluating the clinical outcome was better in ovarian cancer. TRS-based risk score showed distinct association with the level of ESTIMATE score, immune-related function score and immune cells. Moreover, TRS could be used to predict the immunotherapy response and chemotherapy response in ovarian cancer. In conclusion, we constructed a powerful TRS in ovarian cancer, which could accurately predict the clinical outcome of patients and be used to predict the immunotherapy response and chemotherapy response.

Ki-67 Change in Anthracyline-containing Neoadjuvant Chemotherapy Response in Breast Cancer.

Anthracycline-containing regimens are irreplaceable in neoadjuvant chemotherapy (NAC) for breast cancer (BC) at present. However, 30% of early breast cancer (EBC) patients are resistant to anthracycline-containing chemotherapy, leading to poor prognosis and higher mortality. Ki-67 is associated with the prognosis and response to therapy, and it changes after NAC. A total of 105 BC patients who received anthracycline-containing NAC were enrolled. Then, the optimal model of Ki-67 was selected, and its predictive efficacy was analyzed. Immunohistochemistry (IHC) was used to determine the estrogen receptor (ER), progesterone receptor (PR), and human epidermal growth factor receptor 2 (HER-2) status and Ki-67 level. Fluorescent in situ hybridization (FISH) was used to verify the HER-2 when the IHC score was 2+. The post-NAC Ki67 level after treatment with anthracycline drugs was lower than pre-NAC Ki-67 (19.6%±23.3% vs. 45.6%±23.1%, P<0.001). Furthermore, patients with the Ki-67 decrease had a border line higher pathological complete response (pCR) rate (17.2% vs. 0.0%, P=0.068), and a higher overall response rate (ORR) (73.6% vs. 27.8%, P<0.001), when compared to patients without the Ki-67 decrease. The ΔKi-67 and ΔKi-67% were valuable markers for the prediction of both the pCR rate and ORR. The area under the curve (AUC) for ΔKi-67 on pCR and ORR was 0.809 (0.698-0.921) and 0.755 (0.655-0.855), respectively, while the AUC for ΔKi-67% on pCR and ORR was 0.857 (0.742-0.972) and 0.720 (0.618-0.822), respectively. Multivariate logistic regression model 1 revealed that ΔKi-67 was an independent predictor for both pCR [odds ratio (OR)=61.030, 95% confidence interval (CI)=4.709-790.965; P=0.002] and ORR (OR=10.001, 95% CI: 3.044-32.858; P<0.001). Multivariate logistic regression model 2 revealed that ΔKi-67% was also an independent predictor for both pCR (OR=408.922, 95% CI=8.908-18771.224; P=0.002) and ORR (OR=5.419, 95% CI=1.842-15.943; P=0.002). The present study results suggest that ΔKi67 and ΔKi67% are candidate predictors for anthracycline-containing NAC response, and that they may provide various information for further systematic therapy after surgery in clinical practice.

Digital image analysis and machine learning-assisted prediction of neoadjuvant chemotherapy response in triple-negative breast cancer

BackgroundPathological complete response (pCR) is associated with favorable prognosis in patients with triple-negative breast cancer (TNBC). However, only 30–40% of TNBC patients treated with neoadjuvant chemotherapy (NAC) show pCR, while the remaining 60–70% show residual disease (RD). The role of the tumor microenvironment in NAC response in patients with TNBC remains unclear. In this study, we developed a machine learning-based two-step pipeline to distinguish between various histological components in hematoxylin and eosin (H&E)-stained whole slide images (WSIs) of TNBC tissue biopsies and to identify histological features that can predict NAC response.MethodsH&E-stained WSIs of treatment-naïve biopsies from 85 patients (51 with pCR and 34 with RD) of the model development cohort and 79 patients (41 with pCR and 38 with RD) of the validation cohort were separated through a stratified eightfold cross-validation strategy for the first step and leave-one-out cross-validation strategy for the second step. A tile-level histology label prediction pipeline and four machine-learning classifiers were used to analyze 468,043 tiles of WSIs. The best-trained classifier used 55 texture features from each tile to produce a probability profile during testing. The predicted histology classes were used to generate a histology classification map of the spatial distributions of different tissue regions. A patient-level NAC response prediction pipeline was trained with features derived from paired histology classification maps. The top graph-based features capturing the relevant spatial information across the different histological classes were provided to the radial basis function kernel support vector machine (rbfSVM) classifier for NAC treatment response prediction.ResultsThe tile-level prediction pipeline achieved 86.72% accuracy for histology class classification, while the patient-level pipeline achieved 83.53% NAC response (pCR vs. RD) prediction accuracy of the model development cohort. The model was validated with an independent cohort with tile histology validation accuracy of 83.59% and NAC prediction accuracy of 81.01%. The histological class pairs with the strongest NAC response predictive ability were tumor and tumor tumor-infiltrating lymphocytes for pCR and microvessel density and polyploid giant cancer cells for RD.ConclusionOur machine learning pipeline can robustly identify clinically relevant histological classes that predict NAC response in TNBC patients and may help guide patient selection for NAC treatment.

Intra‐tumoral tumor infiltrating Lymphocyte‐T CD8+ and chemotherapy response in colorectal cancer: A prospective observational study

Background: The immunotherapy approach to colorectal cancer is becoming one of the key approaches to colorectal cancer treatment. One of the components of immune responses is tumor‐infiltrating lymphocyte CD8+ cells (TILs CD8+). While chemotherapy is one of the main treatments for colorectal cancer, we need to consider immunotherapy for advanced colorectal cancer. Thus, this study is aimed at finding the association between TIL CD8+ expression and chemotherapy response. Methods: This is a prospective cohort study with colorectal cancer patients in the Digestive Surgery division of a tertiary general hospital in West Java, Indonesia. An immunohistochemistry examination was used to evaluate the expression of TIL CD8+. The response evaluation criteria in solid tumors (RECIST) were used for the evaluation of chemotherapy response. Results: There were 53 research subjects included. There were 20 (37.7%) subjects with high expression of TILs CD8+; there were 30 (56.6%) subjects in stage III, followed by stage IV (17.32%) and stage II (6.11%). There were 18 subjects (34%) who showed progressive disease, 17 subjects (32.1%) showed partial response, and 16 subjects (30.2%) with high expression of TILs CD8+ showed partial chemotherapy response. The TILs CD8+ expression showed no significant relationship with age, sex, subtype, grade, or tumor location, but showed a significant relationship with stage and chemotherapy response (P &lt; 0.05). Conclusion: High TILs CD8+ expression show a relationship with better chemotherapy response and a better prognosis based on disease stage in colorectal cancer patients.

Establishment of a SUMO pathway related gene signature for predicting prognosis, chemotherapy response and investigating the role of EGR2 in bladder cancer.

Background: Bladder cancer is a prevalent malignancy with significant clinical implications. Small Ubiquitin-like Modifier (SUMO) pathway related genes (SPRG) have been implicated in the development and progression of cancer. Methods: In this study, we conducted a comprehensive analysis of SPRG in bladder cancer. We analyzed gene expression and prognostic value of SPRG and developed a SPRG signature (SPRGS) prognostic model based on four genes (HDAC4, TRIM27, EGR2, and UBE2I) in bladder cancer. Furthermore, we investigated the relationship between SPRGS and genomic alterations, tumor microenvironment, chemotherapy response, and immunotherapy. Additionally, we identified EGR2 as a key SPRG in bladder cancer. The expression of EGR2 in bladder cancer was detected by immunohistochemistry, and the cell function experiment clarified the effect of knocking down EGR2 on the proliferation, invasion, and migration of bladder cancer cells. Results: Our findings suggest that SPRGS hold promise as prognostic markers and predictive biomarkers for chemotherapy response and immunotherapy efficacy in bladder cancer. The SPRGS prognostic model exhibited high predictive accuracy for bladder cancer patient survival. We also observed correlations between SPRG and genomic alterations, tumor microenvironment, and response to chemotherapy. Immunohistochemical results showed that EGR2 was highly expressed in bladder cancer tissues, and its overexpression was associated with poor prognosis. Knockdown of EGR2 inhibited bladder cancer cell proliferation, invasion, and migration. Conclusion: This study provides valuable insights into the landscape of SPRGS in bladder cancer and their potential implications for personalized treatment strategies. The identification of EGR2 as a key SPRG and its functional impact on bladder cancer cells further highlights its significance in bladder cancer development and progression. Overall, SPRGS may serve as important prognostic markers and predictive biomarkers for bladder cancer patients, guiding treatment decisions and improving patient outcomes.

A Novel Machine Learning Approach for Predicting Neoadjuvant Chemotherapy Response in Breast Cancer: Integration of Multimodal Radiomics With Clinical and Molecular Subtype Markers

A Novel Machine Learning Approach for Predicting Neoadjuvant Chemotherapy Response in Breast Cancer: Integration of Multimodal Radiomics With Clinical and Molecular Subtype Markers

Correlation of Mitotic Index (MI) and Tumor Infiltrating Lymphocytes (TILs) to Chemotherapy Response in Triple Negative Breast Cancer (TNBC) at Haji Adam Malik General Hospital Medan

Correlation of Mitotic Index (MI) and Tumor Infiltrating Lymphocytes (TILs) to Chemotherapy Response in Triple Negative Breast Cancer (TNBC) at Haji Adam Malik General Hospital Medan

Immune activity score to assess the prognosis, immunotherapy and chemotherapy response in gastric cancer and experimental validation.

Gastric cancer (GC) is an extremely heterogeneous malignancy with a complex tumor microenvironment (TME) that contributes to unsatisfactory prognosis. The overall activity score for assessing the immune activity of GC patients was developed based on cancer immune cycle activity index in the Tracking Tumor Immunophenotype (TIP). Genes potentially affected by the overall activity score were screened using weighted gene co-expression network analysis (WGCNA). Based on the expression profile data of GC in The Cancer Genome Atlas (TCGA) database, COX analysis was applied to create an immune activity score (IAS). Differences in TME activity in the IAS groups were analyzed. We also evaluated the value of IAS in estimating immunotherapy and chemotherapy response based on immunotherapy cohort. Gene expression in IAS model and cell viability were determined by real-time reverse transcriptase-polymerase chain reaction (RT-qPCR) and Cell Counting Kit-8 (CCK-8) assay, respectively. WGCAN analysis screened 629 overall activity score-related genes, which were mainly associated with T cell response and B cell response. COX analysis identified AKAP5, CTLA4, LRRC8C, AOAH-IT1, NPC2, RGS1 and SLC2A3 as critical genes affecting the prognosis of GC, based on which the IAS was developed. Further RT-qPCR analysis data showed that the expression of AKAP5 and CTLA4 was downregulated, while that of LRRC8C, AOAH-IT1, NPC2, RGS1 and SLC2A3 was significantly elevated in GC cell lines. Inhibition of AKAP5 increased cell viability but siAOAH-IT1 promoted viability of GC cells. IAS demonstrated excellent robustness in predicting immunotherapy outcome and GC prognosis, with low-IAS patients having better prognosis and immunotherapy. In addition, resistance to Erlotinib, Rapamycin, MG-132, Cyclopamine, AZ628, and Sorafenib was reduced in patients with low IAS. IAS was a reliable prognostic indicator. For GC patients, IAS showed excellent robustness in predicting GC prognosis, immune activity status, immunotherapy response, and chemotherapeutic drug resistance. Our study provided novel insights into the prognostic assessment in GC.

Predictive Significance of Systemic Immune-Inflammation Index in Patients with Breast Cancer: A Retrospective Cohort Study.

Peripheral blood inflammation indices, including the neutrophil-to-lymphocyte ratio (NLR), platelet-to-lymphocyte ratio (PLR), and systemic immune-inflammation index (SII), have become research hotspots in the diagnosis, treatment, and prognosis prediction of breast cancer, whereas existing research findings remain controversial. Data pertaining to 1808 breast cancer patients were collected retrospectively to analyze the predictive value of NLR/PLR/SII for breast cancer clinicopathological characteristics, chemotherapy response, and relapse. 1489, 258, and 53 eligible breast cancer patients entered into the three analyses, respectively. Logistic regression analyses were used to assess the correlation between these indices and poor response to chemotherapy. A predictive scoring model was established to predict chemotherapeutic responses based upon the odds ratio values of significant variables identified in logistic regression analyses. Higher pretherapeutic NLR/PLR/SII values were significantly correlated with higher tumor stage, triple-negative breast cancer, premenopausal status, and younger age. Logistic regression analyses indicated that pretherapeutic high SII (as a continuous variable or with a cut-off value of 586.40) and HER2-negative status were independent predictors of poor response to neoadjuvant chemotherapy. A first-in-class SII-based predictive scoring model well distinguished patients who might not benefit from neoadjuvant chemotherapy, with an area under the curve of 0.751. In HR-positive cancers, SII was more strongly associated with clinicopathological features and chemotherapy response. In addition, a receiver operating characteristic curve analysis indicated that the specificity of follow-up SII in identifying cancer relapse was greater than 98.0% at a cut-off value of 900. As a predictor of breast cancer, especially in the HR-positive subtype, SII may eclipse NLR/PLR. SII-high patients are more likely to have a worse chemotherapy response and a higher risk of recurrence.

MiR-203a-A multifaceted regulator modulating cancer hallmarks and therapy response.

MicroRNAs (miRNAs) are a class of noncoding RNAs of about 19-25 nucleotides, which serve as critical modulators of various cellular and biological processes by target gene regulation. Dysregulated expression of miRNAs modulates the pathophysiology of various human diseases, including cancer. Among miRNAs, miR-203a is one of the most extensively researched dysregulated miRNAs in different cancers. Our review investigated the roles of miR-203a in the hallmarks of cancer modulating different pathways through target gene regulations, chemoresistance, its crosstalk with other ncRNAs or genes in terms of ceRNAs impacting oncogenesis, and its potential applications in the diagnosis, prognosis, and chemotherapeutic responses in different cancer types. miR-203a impacts cancer cell behavior by regulating these exclusive hallmarks- sustaining proliferation, cell growth, invasion and metastasis, cell death, and angiogenesis. Besides, miR-203a is found in human circulating biofluids like plasma or serum of colorectal cancer, cervical cancer, and hepatocellular carcinoma, hinting at its potential as a biomarker. Further, miR-203a is involved in enhancing the chemosensitivity of cisplatin, docetaxel, paclitaxel, doxorubicin, and 5-fluorouracil in a variety of malignancies through their cognate target genes. These results suggest that miR-203a is a crucial multifaceted miRNA that controls cancer cell proliferation, metastasis, and chemotherapy response, shedding new light on its possible application.

Glutathione dynamics is a potential predictive and therapeutic trait for neoadjuvant chemotherapy response in bladder cancer

Radical cystectomy with preoperative cisplatin-based neoadjuvant chemotherapy (NAC) is the standard care for muscle-invasive bladder cancers (MIBCs). However, the complete response rate to this modality remains relatively low, and current clinicopathologic and molecular classifications are inadequate to predict NAC response in patients with MIBC. Here, we demonstrate that dysregulation of the glutathione (GSH) pathway is fundamental for MIBC NAC resistance. Comprehensive analysis of the multicohort transcriptomes reveals that GSH metabolism and immune-response genes are enriched in NAC-resistant and NAC-sensitive MIBCs, respectively. A machine-learning-based tumor/stroma classifier is applied for high-throughput digitalized immunohistochemistry analysis, finding that GSH dynamics proteins, including glutaminase-1, are associated with NAC resistance. GSH dynamics is activated in cisplatin-resistant MIBC cells, and combination treatment with a GSH dynamics modulator and cisplatin significantly suppresses tumor growth in an orthotopic xenograft animal model. Collectively, these findings demonstrate the predictive and therapeutic values of GSH dynamics in determining the NAC response in MIBCs.

148P Identification of potential predictive biomarkers for ovarian cancer chemotherapy response

148P Identification of potential predictive biomarkers for ovarian cancer chemotherapy response

Early changes of platelet‑lymphocyte ratio correlate with neoadjuvant chemotherapy response and predict pathological complete response in breast cancer.

Markers with inflammatory properties, such as the ratio of neutrophils to lymphocytes and the platelet-to-lymphocyte ratio (PLR), have been documented as potential indicators for predicting pathologic complete response (pCR) following neoadjuvant chemotherapy (NACT) in cases of breast cancer. However, whether early changes of PLR (ΔPLR) during NACT can predict pCR has not been reported. A total of 257 breast cancer patients who underwent NACT were retrospectively analyzed. PLR was calculated by evaluating the complete blood cell counts prior to NACT and following two cycles of NACT. The analysis focused on the association between changes in PLR and the response to chemotherapy, as well as the association with pCR. Patients who stayed in or changed to the low PLR level subgroup after two cycles of NACT exhibited a superior response to chemotherapy, in contrast to those who stayed in or changed to the high PLR level subgroup. Of the 257 patients, 75 (29.1%) achieved a pCR after NACT. In the multivariate analysis, there was a significant association between ΔPLR and pCR, whereas pre-treatment and post-treatment PLR did not show any significant association. In multivariate analysis, patients who had a ΔPLR <0 had a notably higher rate of pCR compared with patients with a ΔPLR ≥0. It was concluded that ΔPLR, rather than pre-treatment or post-treatment PLR, is associated with pCR. This suggested that the early changes of PLR after two cycles of NACT might serve as a more accurate predictor for chemotherapy response and pCR in breast cancer.

Value of spectral CT parameters in predicting the efficacy of neoadjuvant chemotherapy for gastric cancer

To investigate the value of pre-chemotherapy spectral computed tomography (CT) parameters in predicting neoadjuvant chemotherapy (NAC) response in gastric cancer (GC). Sixty patients with GC who received NAC and underwent spectral CT examination before chemotherapy were enrolled retrospectively and divided into a responsive group and a non-responsive group according to the postoperative pathological tumour regression grade. Clinical characteristics were collected. The iodine concentration (IC), water concentration (WC), and effective atomic number (Eff-Z) of the portal venous phases were measured before chemotherapy, and IC was normalised to that of the aorta to provide the normalised IC (NIC). An independent samples t-test, Mann-Whitney U-test, or chi-square test was used to analyse the differences between the two groups, and the receiver operating curve (ROC) was used to evaluate the predictive performance of different variables. The neutrophil-to-lymphocyte ratio (NLR) was lower in the responsive group than in the non-responsive group (p<0.05). IC, NIC, and Eff-Z values were significantly higher in the responsive group than in the non-responsive group (p<0.01). The areas under the ROC curves for the NLR, IC, NIC, and Eff-Z were 0.694, 0.688, 0.799, and 0.690, respectively. The combination of NIC, Eff-Z, and NLR values showed good diagnostic performance in predicting response to NAC in GC, with an area under the ROC curve of 0.857, 76.92% sensitivity, 80% accuracy, and 85.71% specificity. Spectral CT parameters may serve as non-invasive tools for predicting the response to NAC in patients with GC.

Correlation of an immune-related 8-gene panel with pathologic response to neoadjuvant chemotherapy in patients with primary breast cancers

Neoadjuvant chemotherapy (NACT)-induced pathologic complete response (pCR) is associated with a favorable prognosis for breast cancer. Prior research links tumor-infiltrating lymphocytes with breast cancer chemotherapy response, suggesting the tumor-immune microenvironment's role. The aim of this study was to evaluate the immune-related genes that exhibit associations with the response to NACT. In this study, we analyzed a total of 37 patients (aged 27–67) who received NACT as the first-line treatment for primary breast cancer, followed by surgery. This group consisted of nine patients (24.3 %) with estrogen receptor (ER)-positive/HER2-negative status, ten patients (27.0 %) with ER-positive/HER2-positive status, five patients (13.5 %) with ER-negative/HER2-positive status, and thirteen patients (35.1 %) with triple-negative breast cancer (TNBC). Among these patients, twelve (32.4 %) achieved a pCR, with eight (66.6 %) having HER2-positive tumors, and the remaining four having TNBC. To identify immune-related genes linked with pCR in subjects with breast cancer prior to NACT, we collected fresh tissues for next-generation sequencing. Patients with pCR had higher expressions of eight genes, KLRK1, IGJ, CD69, CD40LG, MS4A1, CD1C, KLRB1, and CA4, compared to non-pCR patients. The 8-gene signature was associated with good prognosis and linked to better relapse-free survival in patients receiving chemotherapy. The expression of these genes was involved in better drug response, displaying a positive correlation with the infiltration of immune cells. In conclusion, we have identified eight immune-related genes that are associated with a favorable prognosis and positive responses to drugs. This 8-gene signature could potentially provide prognostic insights for breast cancer patients undergoing NACT.

ERCC1 and MGMT Methylation as a Predictive Marker of Relapse and FOLFOX Response in Colorectal Cancer Patients from South Tunisia.

Genetic and epigenetic modifications present a major cause of relapse and treatment failure in colorectal cancer. This study aims to appreciate the prognostic and predictive value of ERRC1 and MGMT methylation. We also studied the prognostic impact of the ERCC1 rs11615 polymorphism as well as its expression. Methylation profiles of ERCC1 and MGMT were tested by methylation-specific PCR. A polymorphism of ERCC1 was studied using PCR-RFLP and its expression was examined by immunohistochemistry. ERCC1 was methylated in 44.6% of colorectal adenocarcinoma while MGMT was methylated in 69% of cases. MGMT methylation was strongly associated with lymph node metastasis, lymph invasion, venous invasion, perineural invasion, distant metastasis and relapse. Patients with methylation of both genes were more likely to have a poor prognosis and display chemoresistance. IHC analysis revealed that ERCC1 staining was noted in 52.8% of colorectal adenocarcinoma and inversely related to distant metastasis and cancer recurrence. Kaplan Meier analysis revealed that the worst overall survival was significantly associated with ERCC1 and MGMT methylation while decreased ERCC1 expression and T/T genotype exhibited the best overall survival. The methylation of MGMT, alone or combined with ERCC1, is predictive for poor prognosis, short overall survival and chemotherapy response in colorectal cancer.

Flashback Foreword: Multigene Predictor for Chemotherapy Response in Breast Cancer

Flashback Foreword: Multigene Predictor for Chemotherapy Response in Breast Cancer

ATM-ESCO2-SMC3 axis promotes 53BP1 recruitment in response to DNA damage and safeguards genome integrity by stabilizing cohesin complex.

53BP1 is primarily known as a key regulator in DNA double-strand break (DSB) repair. However, the mechanism of DSB-triggered cohesin modification-modulated chromatin structure on the recruitment of 53BP1 remains largely elusive. Here, we identified acetyltransferase ESCO2 as a regulator for DSB-induced cohesin-dependent chromatin structure dynamics, which promotes 53BP1 recruitment. Mechanistically, in response to DNA damage, ATM phosphorylates ESCO2 S196 and T233. MDC1 recognizes phosphorylated ESCO2 and recruits ESCO2 to DSB sites. ESCO2-mediated acetylation of SMC3 stabilizes cohesin complex conformation and regulates the chromatin structure at DSB breaks, which is essential for the recruitment of 53BP1 and the formation of 53BP1 microdomains. Furthermore, depletion of ESCO2 in both colorectal cancer cells and xenografted nude mice sensitizes cancer cells to chemotherapeutic drugs. Collectively, our results reveal a molecular mechanism for the ATM-ESCO2-SMC3 axis in DSB repair and genome integrity maintenance with a vital role in chemotherapy response in colorectal cancer.