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Protein expression-based classification of gastric cancer by immunohistochemistry of tissue microarray

Authors :
Dan Zang
Jie He
Yanlei Du
Hong Du
Yuqiang Nie
Yongjian Zhou
Zhiqiang Feng
Chong Zhao
Hongzhen He
Hongli Huang
Source :
PLoS ONE, PLoS ONE, Vol 15, Iss 10, p e0238836 (2020)
Publication Year :
2020
Publisher :
Public Library of Science, 2020.

Abstract

Recently, the Cancer Genome Atlas and Asian Cancer Research Group propose two new classifications system of gastric cancer by using multi-platforms of molecular analyses. However, these highly complicated and cost technologies have not yet been translated into full clinical utility. In addition, the clinicians are expected to gain more guidance of treatment for different molecular subtypes. In this study, we developed a panel of gastric cancer patients in population from Southern China using commercially accessible TMA and immunohistochemical technology. A cohort of 259 GC patients was classified into 4 subtypes on the basis of expression of mismatch repair proteins (PMS2, MLH1, MSH2, and MSH6), E-cadherin and p21 protein. We observed that the subtypes presented distinct prognosis. dMMR-like subtype was associated with the best prognosis, and E-cadherin-a subtype was associated with the worst prognosis. Patients with p21-High and p21-Ligh subtypes had intermediate overall survival. In multivariate analysis, the dMMR-like subtype remained an independent prediction power for overall survival in the model. We described a molecular classification of gastric cancers using clinically applicable assay. The biological relevance of the four subtypes was illustrated by significant differences in prognosis. Our molecular classification provided an effective and inexpensive screening tool for improving prognostic models. Nevertheless, our study should be considered preliminary and carries a limited predictive value as a single-center retrospective study.

Details

Language :
English
ISSN :
19326203
Volume :
15
Issue :
10
Database :
OpenAIRE
Journal :
PLoS ONE
Accession number :
edsair.doi.dedup.....a418825566013a459c73c6a0036b2236