Background: Pancreatic cancer (PC) represents an aggressive disease with median overall survival (OS) of less than 1 year in the front-line setting. FOLFIRINOX and gemcitabine and paclitaxel (GP) are standard of care options for these patients; however, optimal selection of therapy is challenging.

Methods: Comprehensive genomic profiling was performed on 8358 PC patients. Outcomes were available for 1149 metastatic PC patients treated with 1L FOLFIRINOX or GP. A scar-based measure of HRD was called using a machine learning-based algorithm incorporating copy number and indel features.

Results: A scar-based HRD signature (HRDsig) was identified in 9% of patients. HRDsig significantly co-occurred with biallelic alterations in BRCA1/2, PALB2, BARD1, and RAD51C/D, but encompassed a larger population than that defined by BRCA1/BRCA2/PALB2 (9% vs. 6%). HRDsig was predictive of 1L FOLFIRNOX chemotherapy benefit with doubled OS relative to gemcitabine and paclitaxel (GP) (rwOS aHR 0.37 [0.22-0.62]), including 25% of the population with long-term (2 year+) survival in a real-world cohort of patients. Less benefit from FOLFIRINOX was observed in the HRDsig(-) population. Predictive value was seen in both the BRCA1/2/PALB2 mutant and wildtype populations, suggesting additional value to mutational profiling.

Conclusion: A scar-based HRD biomarker was identified in a significant fraction of PC patients and is predictive of FOLFIRINOX benefit. Incorporating a biomarker like HRDsig could identify the right patients for platinum chemotherapy and potentially reduce FOLFIRINOX use by over 40%, minimizing toxicities with similar survival outcomes. Confirmatory studies should be performed.

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Source
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC10400136PMC
http://dx.doi.org/10.1093/oncolo/oyad178DOI Listing

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