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Protein expression-based classification of gastric cancer by immunohistochemistry of tissue microarray
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...
Autores principales: | , , , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Public Library of Science
2020
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7584200/ https://www.ncbi.nlm.nih.gov/pubmed/33095797 http://dx.doi.org/10.1371/journal.pone.0238836 |
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author | Zhao, Chong Feng, Zhiqiang He, Hongzhen Zang, Dan Du, Hong Huang, Hongli Du, Yanlei He, Jie Zhou, Yongjian Nie, Yuqiang |
author_facet | Zhao, Chong Feng, Zhiqiang He, Hongzhen Zang, Dan Du, Hong Huang, Hongli Du, Yanlei He, Jie Zhou, Yongjian Nie, Yuqiang |
author_sort | Zhao, Chong |
collection | PubMed |
description | 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. |
format | Online Article Text |
id | pubmed-7584200 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2020 |
publisher | Public Library of Science |
record_format | MEDLINE/PubMed |
spelling | pubmed-75842002020-10-28 Protein expression-based classification of gastric cancer by immunohistochemistry of tissue microarray Zhao, Chong Feng, Zhiqiang He, Hongzhen Zang, Dan Du, Hong Huang, Hongli Du, Yanlei He, Jie Zhou, Yongjian Nie, Yuqiang PLoS One Research Article 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. Public Library of Science 2020-10-23 /pmc/articles/PMC7584200/ /pubmed/33095797 http://dx.doi.org/10.1371/journal.pone.0238836 Text en © 2020 Zhao et al http://creativecommons.org/licenses/by/4.0/ This is an open access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0/) , which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited. |
spellingShingle | Research Article Zhao, Chong Feng, Zhiqiang He, Hongzhen Zang, Dan Du, Hong Huang, Hongli Du, Yanlei He, Jie Zhou, Yongjian Nie, Yuqiang Protein expression-based classification of gastric cancer by immunohistochemistry of tissue microarray |
title | Protein expression-based classification of gastric cancer by immunohistochemistry of tissue microarray |
title_full | Protein expression-based classification of gastric cancer by immunohistochemistry of tissue microarray |
title_fullStr | Protein expression-based classification of gastric cancer by immunohistochemistry of tissue microarray |
title_full_unstemmed | Protein expression-based classification of gastric cancer by immunohistochemistry of tissue microarray |
title_short | Protein expression-based classification of gastric cancer by immunohistochemistry of tissue microarray |
title_sort | protein expression-based classification of gastric cancer by immunohistochemistry of tissue microarray |
topic | Research Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7584200/ https://www.ncbi.nlm.nih.gov/pubmed/33095797 http://dx.doi.org/10.1371/journal.pone.0238836 |
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