Screening of DNA Damage Repair Genes Involved in the Prognosis of Triple-Negative Breast Cancer Patients Based on Bioinformatics

An EMT-Related Gene Signature to Predict the Prognosis of Triple-Negative Breast Cancer

INTRODUCTION

Epithelial-mesenchymal transition (EMT) is an important biological process in tumor invasion and metastasis, and thus a potential indicator of the progression and drug resistance of breast cancer. This study comprehensively analyzed EMT-related genes in triple-negative breast cancer (TNBC) to develop an EMT-related prognostic gene signature.

METHODS

With the application of The Cancer Genome Atlas (TCGA) database, Molecular Taxonomy of Breast Cancer International Consortium (METABRIC), and the Genotype-Tissue Expression (GTEx) database, we identified EMT-related signature genes (EMGs) by Cox univariate regression and LASSO regression analysis. Risk scores were calculated and used to divide patients with TNBC into high-risk group and low-risk groups by the median value. Kaplan-Meier (K-M) and receiver operating characteristic (ROC) curve analyses were applied for model validation. Independent prognostic predictors were used to develop nomograms. Then, we assessed the risk model in terms of the immune microenvironment, genetic alteration and DNA methylation effects on prognosis, the probability of response to immunotherapy and chemotherapy, and small molecule drugs predicted by The Connectivity Map (Cmap) database.

RESULTS

Thirteen EMT-related genes with independent prognostic value were identified and used to stratify the patients with TNBC into high- and low-risk groups. The survival analysis revealed that patients in the high-risk group had significantly poorer overall survival than patients in the low-risk group. Populations of immune cells, including CD4 memory resting T cells, CD4 memory activated T cells, and activated dendritic cells, significantly differed between the high- and low-risk groups. Moreover, some therapeutic drugs to which the high-risk group might show sensitivity were identified.

CONCLUSIONS

Our research identified the significant impact of EMGs on prognosis in TNBC, providing new strategies for personalizing TNBC treatment and improving clinical outcomes.

Risk stratification based on DNA damage-repair-related signature reflects the microenvironmental feature, metabolic status and therapeutic response of breast cancer

DNA damage-repair machinery participates in maintaining genomic integrity and affects tumorigenesis. Molecular signatures based on DNA damage-repair-related genes (DRGs) capable of comprehensively indicating the prognosis, tumor immunometabolic profile and therapeutic responsiveness of breast cancer (BRCA) patients are still lacking. Integrating public datasets and bioinformatics algorithms, we developed a robust prognostic signature based on 27 DRGs. Multiple patient cohorts identified significant differences in various types of survival between high- and low-risk patients stratified by the signature. The signature correlated well with clinicopathological factors and could serve as an independent prognostic indicator for BRCA patients. Furthermore, low-risk tumors were characterized by more infiltrated CD8⁺ T cells, follicular helper T cells, M1 macrophages, activated NK cells and resting dendritic cells, and fewer M0 and M2 macrophages. The favorable immune infiltration patterns of low-risk tumors were also accompanied by specific metabolic profiles, decreased DNA replication, and enhanced antitumor immunity. Low-risk patients may respond better to immunotherapy, and experience improved outcomes with conventional chemotherapy or targeted medicine. Real-world immunotherapy and chemotherapy cohorts verified the predictive results. Additionally, four small molecule compounds promising to target high-risk tumors were predicted. In vitro experiments confirmed the high expression of GNPNAT1 and MORF4L2 in BRCA tissues and their association with immune cells, and the knockdown of these two DRGs suppressed the proliferation of human BRCA cells. In summary, this DNA damage-repair-related signature performed well in predicting patient prognosis, immunometabolic profiles and therapeutic sensitivity, hopefully contributing to precision medicine and new target discovery of BRCA.

Identification of Five Cytotoxicity-Related Genes Involved in the Progression of Triple-Negative Breast Cancer

Background: Breast cancer is one of the deadly tumors in women, and its incidence continues to increase. This study aimed to identify novel therapeutic molecules using RNA sequencing (RNA-seq) data of breast cancer from our hospital. Methods: 30 pairs of human breast cancer tissue and matched normal tissue were collected and RNA sequenced in our hospital. Differentially expressed genes (DEGs) were calculated with raw data by the R package "edgeR", and functionally annotated using R package "clusterProfiler". Tumor-infiltrating immune cells (TIICs) were estimated using a website tool TIMER 2.0. Effects of key genes on therapeutic efficacy were analyzed using RNA-seq data and drug sensitivity data from two databases: the Cancer Cell Line Encyclopedia (CCLE) and the Cancer Therapeutics Response Portal (CTRP). Results: There were 2,953 DEGs between cancerous and matched normal tissue, as well as 975 DEGs between primary breast cancer and metastatic breast cancer. These genes were primarily enriched in PI3K-Akt signaling pathway, calcium signaling pathway, cAMP signaling pathway, and cell cycle. Notably, CD8⁺ T cell, M0 macrophage, M1 macrophage, regulatory T cell and follicular helper T cell were significantly elevated in cancerous tissue as compared with matched normal tissue. Eventually, we found five genes (GALNTL5, MLIP, HMCN2, LRRN4CL, and DUOX2) were markedly corelated with CD8⁺ T cell infiltration and cytotoxicity, and associated with therapeutic response. Conclusion: We found five key genes associated with tumor progression, CD8⁺ T cell and therapeutic efficacy. The findings would provide potential molecular targets for the treatment of breast cancer.