Although targeted therapy for receptor tyrosine kinases (RTKs) of advanced gastric cancers (AGCs) has been in the spotlight, guidelines for the identification of RTK-amplified gastric cancers (RA-GCs) have not been established. In this study, we investigate clinicopathologic characteristics of RA-GCs and propose a screening algorithm for their identification. We performed immunohistochemistry (IHC) for MLH1, MSH2, PMS2, MSH6, key RTKs (EGFR, HER2, MET), and p53, in situ hybridization for Epstein-Barr virus encoding RNA, and silver in situ hybridization (SISH) for EGFR, HER2, and MET using tissue microarrays of 993 AGCs. On IHC, 157 (15.8%) 61, (6.15%), and 85 (8.56%) out of 993 cases scored 2+ or 3+ for EGFR, HER2, and MET, respectively. On SISH, 31.2% (49/157), 80.3% (49/61), and 30.6% (26/85) of 2+ or 3+ cases on IHC showed amplification of the corresponding genes. Of the 993 cases, 104 were classified as RA-GCs. RA-GC status correlated with older age (P < 0.001), differentiated histology (P = 0.001), intestinal or mixed type by Lauren classification (P < 0.001), lymphovascular invasion (P = 0.026), and mutant-pattern of p53 (P < 0.001). The cases were divided into four subgroups using two classification systems, putative molecular classification and histologic-molecular classification, based on Lauren classification, IHC, and SISH results. The histologic-molecular classification showed higher sensitivity for identification of RA-GCs and predicted patient prognosis better than the putative molecular classification. In conclusion, RA-GCs show unique clinicopathologic features. The proposed algorithm based on histologic-molecular classification can be applied to select candidates for genetic examination and targeted therapy.
Bibliographical noteFunding Information:
This research was supported by the Basic Science Research Program through the National Research Foundation of Korea (NRF) and was funded by the Ministry of Science, ICT and Future Planning (Hyunki Kim; 2012R1A1A1004403) and the Bio & Medical Technology Development Program of the NRF funded by the Ministry of Science, ICT & Future Planning (Yong-min Huh; NRF-2015M3A9D7029878).
All Science Journal Classification (ASJC) codes