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Combining Immune-Related Genes For Delineating the Extracellular Matrix and Predicting Hormone Therapy and Neoadjuvant Chemotherapy Benefits In Breast Cancer

ABSTRACT: Breast cancer (BC) is the most prevalent cancer in women worldwide. A systematic approach to BC treatment, comprising adjuvant and neoadjuvant chemotherapy (NAC), as well as hormone therapy, forms the foundation of the disease’s therapeutic strategy. The extracellular matrix (ECM) is a dynamic network that exerts a robust biological effect on the tumor microenvironment (TME), and it is highly regulated by several immunological components, such as chemokines and cytokines. It has been established that the ECM promotes the development of an immunosuppressive TME. Therefore, while analyzing the ECM of BC, immune-related genes must be considered. In this study, we used bioinformatic approaches to identify the most valuable ECM-related immune genes. We used weighted gene co-expression network analysis to identify the immune-related genes that potentially regulate the ECM and then combined them with the original ECM-related gene set for further analysis. Least absolute shrinkage and selection operator (LASSO) regression and SurvivalRandomForest were used to narrow our ECM-related gene list and establish an ECM index (ECMI) to better delineate the ECM signature. We stratified BC patients into ECMI high and low groups and evaluated their clinical, biological, and genomic characteristics. We found that the ECMI is highly correlated with long-term BC survival. In terms of the biological process, this index is positively associated with the cell cycle, DNA damage repair, and homologous recombination but negatively with processes involved in angiogenesis and epithelial–mesenchymal transition. Furthermore, the tumor mutational burden, copy number variation, and DNA methylation levels were found to be related to the ECMI. In the Metabric cohort, we demonstrated that hormone therapy is more effective in patients with a low ECMI. Additionally, differentially expressed genes from the ECM-related gene list were extracted from patients with a pathologic complete response (pCR) to NAC and with residual disease (RD) to construct a neural network model for predicting the chance of achieving pCR individually. Finally, we performed qRT-PCR to validate our findings and demonstrate the important role of the gene OGN in predicting the pCR rate. In conclusion, delineation of the ECM signature with immune-related genes is anticipated to aid in the prediction of the prognosis of patients with BC and the benefits of hormone therapy and NAC in BC patients.

SUBMITTER: Liu J

PROVIDER: S-EPMC9331652 | biostudies-literature |

REPOSITORIES: biostudies-literature

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Project description:PurposeTo develop a scoring system for hormone receptor-positive (HR+) breast cancer patients who are expected to achieve axillary pathological complete response (pCR) after neoadjuvant chemotherapy (NAC). To confirm the correlation between axillary status and survival rate in HR+ breast cancer after NAC.MethodsWomen from the Shanghai Jiao Tong University Breast Cancer Database (SJTU-BCDB) who underwent NAC for cT1-4N1-3M0 primary HR+ breast cancer between 2009 and 2018 were included in the study. In this case, patient follow up was performed until 2022 for those with complete data before and after NAC. The main outcome measures were the axillary pCR rate, overall survival (OS), and disease-free survival (DFS). The patients were randomly assigned to a test set (n = 175) and a validation set (n = 68) in a 7 : 3 ratio. A prediction risk score was then developed based on the odds ratios from the multivariate analysis of the test set (n = 175) before being validated in the validation set (n = 68). Finally, the Kaplan-Meier curves were used to explore the survival on this score system.ResultsFrom the database, 243 women were included, and the median follow-up period was 47.5 months (95% confidence interval: 41.9-53.1). The axillary pCR rate was 18.9% (46 of 243), with the independent predictors of residual positive axillary lymph nodes (LNs) being lymphovascular invasion (LVI), breast conserving surgery (BCS), Ki67 < 14%, HER2 negativity, positive lymph nodes in ultrasound (US) before surgery, and stage III histological grade (All, P < 0.05). Using the above predictors of the model, the receiver operating characteristic (ROC) curve was used for calibration and inspection, with values for the test and validation sets being 0.847 (P < 0.001; 95% CI: 0.769, 0.925) and 0.813 (P < 0.001; 95% CI: 0.741, 0.885), respectively. The total risk score ranged from 0 to 6 for the multivariate analysis, and from this range, a risk score of 0-2 was defined as a low-risk group, while scores of 3-6 were defined as the high-risk one. By constructing the survival curve, it was found that the 5-year OS rates for the low-risk and high-risk groups were 89.0% and 84.2% (P = 0.236). Similarly, the 5-year DFS rates for the low-risk and high-risk groups were 80% and 68.5% (P = 0.048), respectively. In addition, axillary pathological stages were significantly correlated with the overall survival (OS) and disease-free survival (DFS) (All, P < 0.05).ConclusionThe prediction model showed good performance for HR + breast cancer. LVI, BCS, low Ki-67, HER2 negativity, suspected positive LNs before surgery, and stage III histological grade were all risk factors for residual positive axillary LNs. However, unlike pathological stages, achieving pCR in the axillary LNs does not affect the survival status.

Project description:BackgroundThe extracellular matrix (ECM) plays a vital role in progression, expansion, and prognosis of malignancies. In this study, we aimed to explore a novel ECM-based prognostic model for patients with colon cancer (CC).MethodsECM-related genes were obtained from Molecular Signatures database. Differential expression analysis was performed using the CC dataset from The Cancer Genome Atlas (TCGA) database. Four ECM-related genes related to overall survival were identified using the Cox regression and LASSO analysis. Then an ECM-related signature was developed and verified in three independent CC cohorts (GSE33882, GSE39582 and GSE29621) from the Gene Expression Omnibus (GEO). A prognostic nomogram was developed incorporating the ECM-related gene signature with clinical risk factors. CIBERSORT was used to explore the immune cell infiltration level. Human Protein Atlas (HPA) database was utilized to validate the expression levels of identified prognostic ECM genes.ResultsFour ECM-related genes (CXCL13, CXCL14, SFRP5 and THBS4) were identified to develop an ECM-based gene signature and demarcated CC patients into the high- and low-risk groups. In training and validation datasets, patients in the low-risk group had better overall survival outcomes than those in the high-risk group (log-rank P<0.001). In addition, ECM-related signature was significantly associated with consensus molecular subtype 4 (CMS4) as well as other known clinical risk factors such as a higher Tumor, Nodal Involvement, Metastasis (TNM) stage. Moreover, the risk score derived from the ECM-based gene signature could be utilized as an independent prognostic factor for CC patients. A nomogram including the ECM-related gene signature, age and stage was developed to serve clinical practice. CIBERSORT analysis showed immune cell infiltration was different between high- and low-risk groups. The immunohistochemical results derived from HPA indicated differential expression of prognosis-related ECM genes in CC and normal tissues.ConclusionsIn the present study, a novel risk model based on ECM-signature could effectively reflect individual risk classification and provide potential therapeutic targets for CC patients. Moreover, the prognostic nomogram may help predict individualized survival.

Project description:Introduction: Neoadjuvant chemoradiotherapy (nCRT) was the foundation treatment for locally advanced rectal cancer (LARC). The nCRT can improve the efficacy of immunotherapy on account of its in-situ vaccine effect. Objective: The aim is to identify stable and reliable transcriptome signatures to predict the efficacy of immune checkpoint blockade (ICB) in patients with LARC. Methods: Immunophenotyping was established by using xCell immune cell infiltration abundance and consistent clustering in GSE39582 and verified in several data sets. The effects of immunophenotyping, follicular regulatory T cells, tumor associated fibroblasts (CAF) and tertiary lymphoid structures (TLS) signatures on the efficacy of ICB were analyzed by using IMvigor210, GSE91061 and an independent Daping Hospital (DPH) cohort. Results: There are four stable and repeatable immune subtypes in rectal cancer, among which C1 is low immune infiltration type, C2 is high interstitial infiltration type, C3 is high immune infiltration type and C4 is ion channel type. C2 is mainly characterized by high infiltration CAF, C3 is characterized by high infiltration of cytotoxic T lymphocytes, high expression of PD-L1 and TLS. In rectal cancer patients receiving nCRT, immunophenotyping was not significantly associated with pathological remission rate, but immunophenotyping was an independent prognostic factor of RFS. In IMvigor210 patients treatment with atezolizumab, the pathological remission rates of C1, C2, C3 and C4 were 23.86%, 10.94%, 33.33% and 23.08% respectively (χ2 = 8.981, P = 0.029), which were 11.76%, 50.00%, 42.86% and 0.0% respectively in the GSE91061 patients treatment with nivolumab (Fisher's exact probability, P = 0.018). Both follicular regulatory T cells and CAF showed a further impact on the ICB therapeutic efficacy of C2 and C3 subtype. In addition, both GSE91404 and DPH cohorts showed that nCRT treatment induced a significant increase in the expression of TNFRSF9 and abundance of macrophages in C3 subtype. Conclusion: Our data suggest that there are four immune types of rectal cancer, which are related to the prognosis of patients. Among them, C3 and some C2 subtypes represents the patients who may benefit from ICB after nCRT treatment.

Project description:IntroductionNeoadjuvant chemoradiotherapy (nCRT) is the foundation treatment for locally advanced rectal cancer (LARC). The nCRT can improve the efficacy of immunotherapy because of its in situ vaccine effect.ObjectiveThe aim is to identify stable and reliable transcriptome signatures to predict the efficacy of immune checkpoint blockade (ICB) in patients with LARC.MethodsImmunophenotyping was established using xCell immune cell infiltration abundance and consistent clustering in GSE39582 and verified in several data sets. The effects of immunophenotyping, follicular regulatory T cells, tumor-associated fibroblasts (CAFs), and tertiary lymphoid structure (TLS) signatures on the efficacy of ICB were analyzed using IMvigor210, GSE91061, and an independent Daping Hospital (DPH) cohort.ResultsThere are four stable and repeatable immune subtypes in rectal cancer, among which C1 is a low immune infiltration type, C2 is a high interstitial infiltration type, C3 is a high immune infiltration type, and C4 is an ion channel type. C2 is mainly characterized by high infiltration of CAF. C3 is characterized by high infiltration of cytotoxic T lymphocytes, high expression of PD-L1 and TLS. In rectal cancer patients receiving nCRT, immunophenotyping was not significantly associated with pathological remission rate, but immunophenotyping was an independent prognostic factor of RFS. In IMvigor210 patients treated with atezolizumab, the pathological remission rates of C1, C2, C3, and C4 were 23.86%, 10.94%, 33.33%, and 23.08% respectively (χ2 = 8.981, P = 0.029), which were 11.76%, 50.00%, 42.86%, and 0.0% respectively in the GSE91061 patient treatment with nivolumab (Fisher's exact probability, P = 0.018). Both follicular regulatory T cells and CAF showed a further impact on the ICB therapeutic efficacy of C2 and C3 subtypes. Additionally, both the GSE91404 and DPH cohorts showed that nCRT treatment induced a significant increase in the expression of TNFRSF9 and the abundance of macrophages in the C3 subtype.ConclusionOur data suggest that there are four immune types of rectal cancer, which are related to the prognosis of patients. Among them, C3 and some C2 subtypes represent the patients who may benefit from ICB after nCRT treatment.

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Combining Immune-Related Genes For Delineating the Extracellular Matrix and Predicting Hormone Therapy and Neoadjuvant Chemotherapy Benefits In Breast Cancer

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