Caris Life Sciences, Phoenix, AZ
Sherri Z. Millis , Brian L. Abbott , Erin H Baker , Ryan Bender , Jeffrey Swensen , Zoran Gatalica , Sandeep K. Reddy , Alexander Rosemurgy , David A Iannitti
Background: Pancreas adenocarcinoma (PAC) is a challenging disease with overall single digit 5-year survivorship. BRCA1 and BRCA2 germline mutations are associated with increased risk of PC. Recent retrospective studies have described response of BRCA patients to platinum agents and PARP inhibitors. Additionally, immune therapies targeting the programmed cell death pathway in other cancers have shown promise; evaluating the incidence of aberrations of these markers in PAC impact therapeutic decisions. Methods: 450 PAC’s were evaluated at a commercial CLIA laboratory using a combination of sequencing (Sanger or next generation sequencing (NGS)) and protein expression (immunohistochemistry). BRCA1/2 mutations that could be germline or somatic, co-incidence with other mutations identified in the tissue, and expression levels of PD-L1 and PD-1 tumor infiltrating lymphocytes (TIL’s) were evaluated. Results: Mutations (MT) in BRCA1 and BRCA2 were identified in 5 and 17% percent of tissues, respectively. BRCA1 and BRCA2 MT had different rates of concurrence with other gene alterations, which was also different from the general PC population (table). Overexpression of PD-L1 and PD-1 TIL’s were also identified in 7% and 37% of PAC cases, respectively. BRCA1 MT cases had a higher incidence of PD-1 TIL’s, while BRCA2 MT cases had a higher percent of overexpressed PD-L1 than the overall population. Conclusions: The different frequencies of KRAS, TP53, PIK3CA and SMAD4 MT between the overall PAC population and BRCA MT populations may inform driver differences and may help select drugs and refine treatment decision making for certain patients. Evaluating the profiles of the BRCA MT populations with clinical outcomes will provide valuable insight into the clinical behavior in genomically defined subsets and may facilitate in developing rational combinations of targeted agents in PAC.
Biomarker MT | BRCA1 MT | BRCA2 MT | Overall PC Population |
---|---|---|---|
% Coincidence | |||
APC | 14 | 0 | 3 |
BRAF | 0 | 0 | 1 |
KRAS | 71 | 77 | 85 |
PIK3CA | 14 | 0 | 3 |
SMAD4 | 0 | 10 | 16 |
TP53 | 43 | 60 | 59 |
PD-1 | 38 | 50 | 37 |
PD-L1 | 13 | 8 | 7 |
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