Abstract
64 Background: At present, the clinical management of resected GC is only based on risk stratification according to the AJCC staging. This project evaluates molecular factors on formalin-fixed, paraffin-embedded (FFEP) specimens of the primary tumor radically resected in an omogeneous group patients considered at poor prognosis according by nodal involvement (pN3a/b AJCC 7th edition) and included in the ITACA-S trial. Methods: Matched pairs of tumor-normal GC FFPE specimens collected from 15 patients were subjected to whole-exome sequencing using TruSeq Exome technology and NextSeq500 (Illumina). Somatic mutations (single-nucleotide variants) were identified, filtered and then searched for recurrently mutated genes and pathways. Patients with recurrence (cases) were compared to an equally-sized sample of patients without recurrence (controls) with the same follow up time (60 months). Results: Clinical characteristics of 15 pts: median age 61 (41-71) yrs. Nodal involvement: pN3a( 5); pN3b (10). Histotype: Intestinal (4); diffuse (8); mixed (3). Primary site: gastroesophageal junction (1); gastric (14). Patients with GC relapse (8) and without relapse (7). Whole exome sequencing revealed the presence of an average of 553 somatic mutations (range: 197 - 1318) following removal of not exonic/silent variants and of variants with an alternative allele depth < 5. Among a list of 48 genes, reported as mutated in some GC studies, we found that CDH1, GNAS and DCC were mutated in 57% of patients, whereas CTNNB1, LRP1B, LRRK2, NOTCH1, and TRRAP were mutated in 42%. Furthermore RHOA, KRAS, FGFR2, PDGFRA and PRKDC showed mutation in 28% of cases. We are currently evaluating the presence of mutual exclusive relationships mechanisms, functions and molecular pathways in “cases” versus “controls”. Conclusions: Our findings confirm a relevant role of disregulation of cell adhesion pathway involving CDH1 and DCC in GC. However, a validation analysis with an independent and bigger cohort of GC patients is ongoing, in order to find outcome-related mutational patterns that could be relevant for the selection of treatment in GC.
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