Genomic Correlates of DNA Damage in Breast Cancer Subtypes

SIMPLE SUMMARY: Breast cancer (BC) is the most common invasive tumor in women and the second leading cause of cancer-related death. Therefore, identification of druggable targets to improve current therapies and overcome resistance is a major goal. In this work, we performed an in silico analysis of transcriptomic datasets in breast cancer, and focused on those involved in DNA damage, as were clearly upregulated using gene set enrichment analyses (GSEA), particular the following pathways: ATM/ATR, BARD1 and Fanconi Anemia. BHLHE40, RFWD2, BRIP1, PRKDC, NBN, RNF8, FANCD2, RAD1, BLM, DCLRE1C, UBE2T, CSTF1, MCM7, RFC4, YWHAB, YWHAZ, CDC6, CCNE1, and FANCI genes were amplified/overexpressed in BC, and correlated with detrimental prognosis. Finally, we selected the best transcriptomic signature of genes within this function that associated with clinical outcome to identify functional genomic correlates of outcome. ABSTRACT: Among the described druggable vulnerabilities, acting on the DNA repair mechanism has gained momentum, with the approval of PARP inhibitors in several indications, including breast cancer. However, beyond the mere presence of BRCA1/BRCA2 mutations, the identification of additional biomarkers that would help to select tumors with an extreme dependence on DNA repair machinery would help to stratify therapeutic decisions. Gene set enrichment analyses (GSEA) using public datasets evaluating expression values between normal breast tissue and breast cancer identified a set of upregulated genes. Genes included in different pathways, such as ATM/ATR, BARD1, and Fanconi Anemia, which are involved in the DNA damage response, were selected and confirmed using molecular alterations data contained at cBioportal. Nineteen genes from these gene sets were identified to be amplified and upregulated in breast cancer but only five of them NBN, PRKDC, RFWD2, UBE2T, and YWHAZ meet criteria in all breast cancer molecular subtypes. Correlation of the selected genes with prognosis (relapse free survival, RFS, and overall survival, OS) was performed using the KM Plotter Online Tool. In last place, we selected the best signature of genes within this process whose upregulation can be indicative of a more aggressive phenotype and linked with worse outcome. In summary, we identify genomic correlates within DNA damage pathway associated with prognosis in breast cancer.