Breast cancer is one of the leading cancer deaths around the world. Targeted drugs have greatly increased the survival rate of breast cancer patients in recent years. But in some patients, the current regimen is still ineffective. Therefore, more therapeutic targets for treating breast cancer are demanding. The core heterochromatin-related genes of breast cancer were identified by utilizing prognostic survival analysis and multivariate Cox hazard proportional regression analysis. Both breast cancer and adjacent normal tissue were collected and analyzed with western blot and immunohistochemistry. Colony formation assay, CCK8 assay, and EdU assay were used to measure the effect of CBX3 on breast cancer cell growth, wound-healing assay and Transwell assay were used to analyze the effect of CBX3 on breast cancer cell migration and invasion. Flow cytometry assay and western blot were used to study the molecular mechanism of CBX3 in breast cancer. High expression of heterochromatin-related proteins CBX3, H2AFY, and SULF1 showed a poor prognosis in patients in both TCGA dataset and GEO datasets. Western blot demonstrated that the expression level of CBX3 was significantly higher in breast cancer than that in adjacent normal tissues. Colony formation assay, CCK8 assay, and EdU assay showed that the knockdown of CBX3 could significantly inhibit breast cancer cell growth, and the overexpression of CBX3 could promote the growth of breast cancer cells. Transwell assay and wound healing assay showed that knockdown of CBX3 inhibited breast cancer cell migration and invasion, and the overexpression of CBX3 promoted breast cancer cell migration and invasion. Western blot showed that CBX3 might promote breast cancer cell proliferation, invasion, and migration in breast cancer by modulating the ERK1/2 signaling pathway and epithelial-mesenchymal transition (EMT)-related genes. CBX3 was a biomarker of poor prognosis in breast cancer patients. CBX3 promoted the proliferation of breast cancer cells through the ERK signaling pathway, and migration and invasion of breast cancer cells through EMT-related genes. The CBX3/p-ERK1/2 signaling axis might provide a new therapeutic method against breast cancer.
Background: Tumor antigenicity and efficiency of antigen presentation jointly influence tumor immunogenicity, which largely determines the effectiveness of immune checkpoint blockade (ICB). However, the role of altered antigen processing and presentation machinery (APM) in breast cancer (BRCA) has not been fully elucidated. Methods: A series of bioinformatic analyses and machine learning strategies were performed to construct APM-related gene signatures to guide personalized treatment for BRCA patients. A single-sample gene set enrichment analysis (ssGSEA) algorithm and weighted gene co-expression network analysis (WGCNA) were combined to screen for BRCA-specific APM-related genes. The non-negative matrix factorization (NMF) algorithm was used to divide the cohort into different clusters and the fgsea algorithm was applied to investigate the altered signaling pathways. Random survival forest (RSF) and the least absolute shrinkage and selection operator (Lasso) Cox regression analysis were combined to construct an APM-related risk score (APMrs) signature to predict overall survival. Furthermore, a nomogram and decision tree were generated to improve predictive accuracy and risk stratification for individual patients. Based on Tumor Immune Dysfunction and Exclusion (TIDE) method, random forest (RF) and Lasso logistic regression model were combined to establish an APM-related immunotherapeutic response score (APMis). Finally, immune infiltration, immunomodulators, mutational patterns, and potentially applicable drugs were comprehensively analyzed in different APM-related risk groups. Results: In this study, APMrs and APMis showed favorable performances in risk stratification and therapeutic prediction for BRCA patients. APMrs exhibited more powerful prognostic capacity and accurate survival prediction compared to conventional clinicopathological features. APMrs was closely associated with distinct mutational patterns, immune cell infiltration and immunomodulators expression. Furthermore, the two APM-related gene signatures were independently validated in external cohorts with prognosis or immunotherapeutic responses. Potential applicable drugs and targets were further mined in the APMrs-high group. Conclusion: The APM-related gene signatures established in our study could improve the personalized assessment of survival risk and guide ICB decision-making for BRCA patients.
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.
hi@scite.ai
10624 S. Eastern Ave., Ste. A-614
Henderson, NV 89052, USA
Copyright © 2024 scite LLC. All rights reserved.
Made with 💙 for researchers
Part of the Research Solutions Family.