594 Background: Given the heterogeneity of gastrointestinal cancers (GICs), molecular profiling is becoming part of the standard of care for many solid tumors. The aim of this study was to evaluate the molecular profile of patients (pts) with GICs using a multiplatform profiling tool and to assess how the pattern of detected molecular alterations could guide clinical decision-making in these tumors. Methods: We retrospectively analyzed samples of 85 pts with GICs via a multiplatform profiling service (Caris Life Sciences, Phoenix, AZ) in order to evaluate clinically relevant genomic alterations (CRGAs) and clinically relevant biomarker expression (CRBs) in GICs. Results: A total of 85 pts with GICs were analyzed. 45 (53 %) were males and 40 (47%) were females. Tumors were colorectal 43 (51%), pancreatic 11 (13%) esophageal 11 (13%) gastric 8 (9%), hepatobiliary 8 (11%), anal canal 3 (4%), and small intestine 1 (1%). 80 cases (94%) had adequate sample for profiling. CRGAs were identified in 71 cases (89%) with a median of 3 CRGAs in the cohort. The most commonly detected CRGAs were TP53 45 (56%), APC 35 (44%), KRAS 32 (40%), ATM 14 (18%) and PTEN 5 (6%). The median number of CRBs was 9 and high expression levels were seen of mismatch repair biomarkers (MLH1, MSH2, MSH6, PMS2) in 45 (56%), TOPO1 in 44 (55%), PTEN in 27 (34%), TOP2A in 20 (25%), ERCC1 in 19 (24%), and both TS and TUBB3 in 17 (21%). Based on actionable CRGAs and CRBs, 94% of pts matched at least one FDA approved treatment with proven clinical benefit, with a median of 4 available therapies per pt. In addition, there was a median of 189 chemotherapy and 64 targeted therapy clinical trial opportunities available for these pts given the molecular blueprint of their GICs. Conclusions: Multiplatform molecular profiling identified a high frequency of actionable CRGAs and CRBs in GIC pts. This approach has the potential to aid in clinical decision-making by providing a stratification of beneficial therapeutic alternatives individualized to the molecular framework of tumor. Larger prospective studies are warranted to further investigate the impact of profiling guided treatment decisions on patient outcomes.
Molecular Profiling of Thyroid Nodules: Current Role for the Afirma Gene Expression Classifier on Clinical Decision Making