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Receptor tyrosine kinase amplified gastric cancer: Clinicopathologic characteristics and proposed screening algorithm

Authors
 Cheol Keun Park  ;  Ji Soo Park  ;  Hyo Song Kim  ;  Sun Young Rha  ;  Woo Jin Hyung  ;  Jae-Ho Cheong  ;  Sung Hoon Noh  ;  Sang Kil Lee  ;  Yong Chan Lee  ;  Yong-min Huh  ;  Hyunki Kim 
Citation
 Oncotarget, Vol.7(44) : 72099-72112, 2016 
Journal Title
 Oncotarget 
Issue Date
2016
Abstract
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.
Files in This Item:
T201605785.pdf Download
DOI
10.18632/oncotarget.12291
Appears in Collections:
1. College of Medicine (의과대학) > Dept. of Pathology (병리학교실) > 1. Journal Papers
1. College of Medicine (의과대학) > Dept. of Internal Medicine (내과학교실) > 1. Journal Papers
1. College of Medicine (의과대학) > Dept. of Surgery (외과학교실) > 1. Journal Papers
1. College of Medicine (의과대학) > Dept. of Radiology (영상의학교실) > 1. Journal Papers
Yonsei Authors
김현기(Kim, Hyunki) ORCID logo https://orcid.org/0000-0003-2292-5584
김효송(Kim, Hyo Song) ORCID logo https://orcid.org/0000-0002-0625-9828
노성훈(Noh, Sung Hoon) ORCID logo https://orcid.org/0000-0003-4386-6886
라선영(Rha, Sun Young) ORCID logo https://orcid.org/0000-0002-2512-4531
박지수(Park, Ji Soo) ORCID logo https://orcid.org/0000-0002-0023-7740
이상길(Lee, Sang Kil) ORCID logo https://orcid.org/0000-0002-0721-0364
이용찬(Lee, Yong Chan)
정재호(Cheong, Jae Ho) ORCID logo https://orcid.org/0000-0002-1703-1781
허용민(Huh, Yong Min) ORCID logo https://orcid.org/0000-0002-9831-4475
형우진(Hyung, Woo Jin) ORCID logo https://orcid.org/0000-0002-8593-9214
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URI
https://ir.ymlib.yonsei.ac.kr/handle/22282913/152941
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