Beyond BRCA: The Emerging Significance of DNA Damage Response and Personalized Treatment in Pancreatic and Prostate Cancer Patients

The BRCA1/2 germline and/or somatic pathogenic variants (PVs) are key players in the hereditary predisposition and therapeutic response for breast, ovarian and, more recently, pancreatic and prostate cancers. Aberrations in other genes involved in homologous recombination and DNA damage response (DDR) pathways are being investigated as promising targets in ongoing clinical trials. However, DDR genes are not routinely tested worldwide. Due to heterogeneity in cohort selection and dissimilar sequencing approaches across studies, neither the burden of PVs in DDR genes nor the prevalence of PVs in genes in common among pancreatic and prostate cancer can be easily quantified. We aim to contextualize these genes, altered in both pancreatic and prostate cancers, in the DDR process, to summarize their hereditary and somatic burden in different studies and harness their deficiency for cancer treatments in the context of currently ongoing clinical trials. We conclude that the inclusion of DDR genes, other than BRCA1/2, shared by both cancers considerably increases the detection rate of potentially actionable variants, which are triplicated in pancreatic and almost doubled in prostate cancer. Thus, DDR alterations are suitable targets for drug development and to improve the outcome in both pancreatic and prostate cancer patients. Importantly, this will increase the detection of germline pathogenic variants, thereby patient referral to genetic counseling.

Automated summary

The BRCA1/2 genes play a crucial role in breast, ovarian, pancreatic and prostate cancers. Other genes involved in homologous recombination and DNA damage response are being studied as potential targets for treatment. However, these genes are not routinely tested worldwide. This study summarizes the genetic and cellular burden of these genes and suggests that including DDR genes shared by both pancreatic and prostate cancers can lead to better detection of actionable variants.