Abstract
747 Background: Pancreatic ductal adenocarcinoma (PDAC) is the third leading cause of cancer deaths. KRAS is a primary oncogenic driver in the majority of PDAC patients. KRAS wild-type (wt) PDAC (~10%) is a molecularly heterogeneous subgroup that may harbor alternate drivers and targetable alterations. In this study, we sought to characterize the circulating tumor DNA (ctDNA) landscape of alterations in PDAC patients harboring KRAS mutations ( KRAS mut) compared to KRAS wt. Methods: We analyzed ctDNA samples from 2000 patients ( N= 1000 each for KRAS mut and KRAS wt) collected prospectively between 2019-2022 using a 74-83 gene next generation sequencing panel (Guardant360). KRAS mutation not detected was used as a proxy for KRAS wt. To limit bias from low tumor shed, samples were excluded if they did not have maximum variant allele fraction (VAF) > 0.34% and if the only maximum VAF > 0.34% was within putative germline range (40-60%). Statistical analyses were performed using Fisher’s exact test or t-test. Results: No significant gender differences were noted between KRAS wt and KRAS mut patients. Median age was 72yo in KRAS wt and 69yo in KRAS mut patients. Overall, KRAS wt patients had higher frequency of alterations in ATM, BRAF, ERBB2, FGFR2, JAK3, MET and NOTCH1 compared to KRAS mut (all p < 0.05). Meanwhile, KRAS wt patients had lower frequency of alterations in CDKN2A, SMAD4, CDK6, ARID1A, and TP53 compared to KRAS mut (all p < 0.05). The most frequently mutated gene in KRAS wt PDAC was TP53 (46%), followed by ATM (26%) and EGFR (11%). The most common currently targetable alterations identified in KRAS wt patients were ATM (26%), BRCA1/2 (12%), EGFR (11%; 70% mutations, 30% amplifications), FGFR1/2 (9%), BRAF (8%; 91% mutations, 9% amplifications), PIK3CA (7%), MET (7%; 80% mutations, 20% amplifications) and ERBB2 (5.8%; 79% mutations, 21% amplifications) among others. Median tumor mutational burden for KRAS wt patients was higher than KRAS mut (10.0 vs. 7.77 mut/Mb, p = 0.035). There were no significant differences in rates of MSI-H between KRAS wt and KRAS mut patients (1.9% vs. 1.3%, p = 0.37). KRAS wt patients harbored higher number of oncogenic gene fusions compared to KRAS mut (1.6% vs 0.2%, p = 0.0013). The most common fusion partners among KRAS wt patients included FGFR2 (0.4%), BRAF (0.4%), ALK (0.2%), NTRK (0.2%), RET (0.2%), FGFR3 (0.1%) and EGFR (0.1%). Potential germline variants (pathogenic/likely pathogenic) were detected in both KRAS wt and mut patients, most commonly in the DNA-damage repair genes, including ATM (3.5%), BRCA2 (1.8%) and BRCA1 (0.6%). Conclusions: Targetable alterations and oncogenic rearrangements are enriched in KRAS wt PDAC compared to KRAS mut. These analyses provide additional therapeutic options and may improve outcomes for KRAS wt patients, warranting blood-based ctDNA genomic profiling in PDAC, especially when a tissue biopsy is not feasible or sufficient for comprehensive genomic profiling.
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