Intra-Tumoral Heterogeneity of HER2, FGFR2, cMET and ATM in Gastric Cancer: Optimizing Personalized Healthcare through Innovative Pathological and Statistical Analysis.

Abstract

Current drug development efforts on gastric cancer are directed against several molecular targets driving the growth of this neoplasm. Intra-tumoral biomarker heterogeneity however, commonly observed in gastric cancer, could lead to biased selection of patients. MET, ATM, FGFR2, and HER2 were profiled on gastric cancer biopsy samples. An innovative pathological assessment was performed through scoring of individual biopsies against whole biopsies from a single patient to enable heterogeneity evaluation. Following this, false negative risks for each biomarker were estimated in silico. 166 gastric cancer cases with multiple biopsies from single patients were collected from Shanghai Renji Hospital. Following pre-set criteria, 56 ~ 78% cases showed low, 15 ~ 35% showed medium and 0 ~ 11% showed high heterogeneity within the biomarkers profiled. If 3 biopsies were collected from a single patient, the false negative risk for detection of the biomarkers was close to 5% (exception for FGFR2: 12.2%). When 6 biopsies were collected, the false negative risk approached 0%. Our study demonstrates the benefit of multiple biopsy sampling when considering personalized healthcare biomarker strategy, and provides an example to address the challenge of intra-tumoral biomarker heterogeneity using alternative pathological assessment and statistical methods.