Abstract

e16279 Background: To date, few targetable mutations have been found to enhance PDAC treatment. Next-generation sequencing (NGS) of somatic mutation profiles may help tailor cytotoxic chemotherapy selection and guide translational research. Methods: We analyzed NGS data from a retrospective cohort of 142 patients with unresectable biopsy-proven PDAC from August 2009 to December 2022. Individual mutations were grouped into 14 distinct signaling pathways: cell cycle, DNA damage repair, KIT, ErbB2, TP53, MAPK-RAS, PIK3, TGF-beta, NOTCH, ALK, FLT3, FGFR, and WNT. Treatment selection, duration of response, and survival were recorded. We stratified patients based on their first-line therapy, either FOLFIRINOX (FFX) or gemcitabine/nab-paclitaxel (GA). We present median time-to-first progression (PFS1) and overall survival (OS) based on the presence or absence of mutations in these pathways. The time-to-event endpoint was estimated by the Kaplan-Meier method. Results: Of 142 samples, 131 were analyzed for PFS1; 57 received FFX, and 60 received GA. In the FFX group, no pathway predicted PFS1 with statistical significance. In the GA group, KIT pathway mutations (n = 10) showed improved PFS1 vs. non-KIT mutated tumors (10.3 mos vs. 6.2 mos, p = 0.02). Similar improvement in PFS1 was seen for mutations in the PIK3 pathway (n = 25, 6.6 vs. 5.7, p = 0.02) and FLT3 pathway (n = 4, 13.1 vs. 6.2, p = 0.02). 125 samples were analyzed for OS. KIT pathway mutations (n = 21) showed a better OS vs. non-KIT mutated samples (21.3 mos vs. 12.2 mos, p = 0.04), as did NOTCH mutated samples (n = 44, 15 vs. 12.3, p < 0.01). FLT3 pathway mutations showed a trend toward improved OS (23.6 vs. 13, p = 0.3). PIK3 mutated tumors had no difference in OS. 8 samples were KRAS WT; removing these from the analysis did not change the results. Conclusions: In this sample, KIT, FLT3, and PIK3 pathway mutated tumors had improved PFS1 with GA (but not FFX) treatment. Tumors with KIT and NOTCH pathway mutations had an improved OS. This and similar analyses could help identify potential drivers of treatment response for unresectable pancreatic tumors. [Table: see text]

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