# Unveiling Novel Genetic Mutations and Prognostic Indicators in Breast Carcinoma: An Analysis of The Cancer Genome Atlas (TCGA) Data

## TL;DR

This study identifies new genetic mutations and prognostic indicators in breast cancer using TCGA data, highlighting potential targets for treatment.

## Contribution

The study reveals novel genes like SETDB1, ARMCX5, and SLCO6A1 with prognostic significance in breast carcinoma.

## Key findings

- SETDB1, USP37, NDUFS1, TRPM4, and MYO18A are associated with poor prognosis in breast cancer.
- ARMCX5 and SLCO6A1 are enriched in high-grade tumors.
- The findings suggest a role for metabolic and epigenetic genes in breast cancer progression.

## Abstract

Background

Breast carcinoma is one of the leading causes of cancer-associated mortality in women worldwide. Although several advances have been made in molecularly classifying breast cancers, treatment resistance continues to limit the overall survival. The Cancer Genome Atlas (TCGA) has unraveled diverse genomic alterations in breast carcinoma. However, some potential biomarkers still remain unexplored, like SETDB1, a histone methyltransferase involved in epigenetic silencing of tumor suppressor genes. ARMCX5 and SLCO6A1 are also some of the unexplored genes that could have a potential role in drug resistance.

Materials and methods

The Mutation Annotation Format (MAF) data set from the Cancer Genome Atlas Breast Cancer (TCGA-BRCA) cohort was analyzed using the Maftools, Survival, Mclust, and Survminer R packages. Oncodrive driver analysis and protein family (PFAM) domain mapping were performed. A total of 845 cases of breast carcinoma with complete survival data were retrieved, of which mutation data for 800 cases were available. Comprehensive mutation analysis was also done to unveil unexplored genes. Survival data of 845 cases were integrated for Kaplan-Meier and Cox proportional hazard analysis to ascertain the prognostic significance of an array of genes. Oncogenic signaling pathway mapping was done to determine the clinical enrichment of the genes associated with breast carcinoma. Genes associated with clinical enrichment, clustering of somatic mutations, and prognosis were subjected to further analysis.

Results

Besides the established molecular drivers like PIK3CA and TP53, we found several novel and understudied genes with potential prognostic and oncogenic significance. SETDB1 (p < 0.0001), USP37 (p < 0.0001), NDUFS1 (p = 0.025), TRPM4 (p < 0.0001), and MYO18A (p < 0.0001) were associated with poor prognosis. ARMCX5 (p < 0.0001) and SLCO6A1 (p < 0.0001) were enriched in high-grade tumors.

Conclusion

The TCGA-BRCA cohort analysis emphasizes a potential interplay of metabolic genes like NDUFS1, TRPM4, ARMCX5, SLCO6A1, and epigenetic axis genes like SETDB1 and USP37 in the oncogenesis and prognosis of breast carcinomas. These observations could open potential avenues for exploring novel therapeutics in aggressive breast carcinomas.