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Identification of Candidate Therapeutic Genes for More Precise Treatment of Esophageal Squamous Cell Carcinoma and Adenocarcinoma
The standard therapy administered to patients with advanced esophageal cancer remains uniform, despite its two main histological subtypes, namely esophageal squamous cell carcinoma (SCC) and esophageal adenocarcinoma (AC), are being increasingly considered to be different. The identification of pote...
Autores principales: | , , , , , , , , , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
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Frontiers Media S.A.
2022
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9161154/ https://www.ncbi.nlm.nih.gov/pubmed/35664298 http://dx.doi.org/10.3389/fgene.2022.844542 |
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author | Polewko-Klim, Aneta Zhu, Sibo Wu, Weicheng Xie, Yijing Cai, Ning Zhang, Kexun Zhu, Zhen Qing, Tao Yuan, Ziyu Xu, Kelin Zhang, Tiejun Lu, Ming Ye, Weimin Chen, Xingdong Suo, Chen Rudnicki, Witold R. |
author_facet | Polewko-Klim, Aneta Zhu, Sibo Wu, Weicheng Xie, Yijing Cai, Ning Zhang, Kexun Zhu, Zhen Qing, Tao Yuan, Ziyu Xu, Kelin Zhang, Tiejun Lu, Ming Ye, Weimin Chen, Xingdong Suo, Chen Rudnicki, Witold R. |
author_sort | Polewko-Klim, Aneta |
collection | PubMed |
description | The standard therapy administered to patients with advanced esophageal cancer remains uniform, despite its two main histological subtypes, namely esophageal squamous cell carcinoma (SCC) and esophageal adenocarcinoma (AC), are being increasingly considered to be different. The identification of potential drug target genes between SCC and AC is crucial for more effective treatment of these diseases, given the high toxicity of chemotherapy and resistance to administered medications. Herein we attempted to identify and rank differentially expressed genes (DEGs) in SCC vs. AC using ensemble feature selection methods. RNA-seq data from The Cancer Genome Atlas and the Fudan-Taizhou Institute of Health Sciences (China). Six feature filters algorithms were used to identify DEGs. We built robust predictive models for histological subtypes with the random forest (RF) classification algorithm. Pathway analysis also be performed to investigate the functional role of genes. 294 informative DEGs (87 of them are newly discovered) have been identified. The areas under receiver operator curve (AUC) were higher than 99.5% for all feature selection (FS) methods. Nine genes (i.e., ERBB3, ATP7B, ABCC3, GALNT14, CLDN18, GUCY2C, FGFR4, KCNQ5, and CACNA1B) may play a key role in the development of more directed anticancer therapy for SCC and AC patients. The first four of them are drug targets for chemotherapy and immunotherapy of esophageal cancer and involved in pharmacokinetics and pharmacodynamics pathways. Research identified novel DEGs in SCC and AC, and detected four potential drug targeted genes (ERBB3, ATP7B, ABCC3, and GALNT14) and five drug-related genes. |
format | Online Article Text |
id | pubmed-9161154 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2022 |
publisher | Frontiers Media S.A. |
record_format | MEDLINE/PubMed |
spelling | pubmed-91611542022-06-03 Identification of Candidate Therapeutic Genes for More Precise Treatment of Esophageal Squamous Cell Carcinoma and Adenocarcinoma Polewko-Klim, Aneta Zhu, Sibo Wu, Weicheng Xie, Yijing Cai, Ning Zhang, Kexun Zhu, Zhen Qing, Tao Yuan, Ziyu Xu, Kelin Zhang, Tiejun Lu, Ming Ye, Weimin Chen, Xingdong Suo, Chen Rudnicki, Witold R. Front Genet Genetics The standard therapy administered to patients with advanced esophageal cancer remains uniform, despite its two main histological subtypes, namely esophageal squamous cell carcinoma (SCC) and esophageal adenocarcinoma (AC), are being increasingly considered to be different. The identification of potential drug target genes between SCC and AC is crucial for more effective treatment of these diseases, given the high toxicity of chemotherapy and resistance to administered medications. Herein we attempted to identify and rank differentially expressed genes (DEGs) in SCC vs. AC using ensemble feature selection methods. RNA-seq data from The Cancer Genome Atlas and the Fudan-Taizhou Institute of Health Sciences (China). Six feature filters algorithms were used to identify DEGs. We built robust predictive models for histological subtypes with the random forest (RF) classification algorithm. Pathway analysis also be performed to investigate the functional role of genes. 294 informative DEGs (87 of them are newly discovered) have been identified. The areas under receiver operator curve (AUC) were higher than 99.5% for all feature selection (FS) methods. Nine genes (i.e., ERBB3, ATP7B, ABCC3, GALNT14, CLDN18, GUCY2C, FGFR4, KCNQ5, and CACNA1B) may play a key role in the development of more directed anticancer therapy for SCC and AC patients. The first four of them are drug targets for chemotherapy and immunotherapy of esophageal cancer and involved in pharmacokinetics and pharmacodynamics pathways. Research identified novel DEGs in SCC and AC, and detected four potential drug targeted genes (ERBB3, ATP7B, ABCC3, and GALNT14) and five drug-related genes. Frontiers Media S.A. 2022-05-19 /pmc/articles/PMC9161154/ /pubmed/35664298 http://dx.doi.org/10.3389/fgene.2022.844542 Text en Copyright © 2022 Polewko-Klim, Zhu, Wu, Xie, Cai, Zhang, Zhu, Qing, Yuan, Xu, Zhang, Lu, Ye, Chen, Suo and Rudnicki. https://creativecommons.org/licenses/by/4.0/This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms. |
spellingShingle | Genetics Polewko-Klim, Aneta Zhu, Sibo Wu, Weicheng Xie, Yijing Cai, Ning Zhang, Kexun Zhu, Zhen Qing, Tao Yuan, Ziyu Xu, Kelin Zhang, Tiejun Lu, Ming Ye, Weimin Chen, Xingdong Suo, Chen Rudnicki, Witold R. Identification of Candidate Therapeutic Genes for More Precise Treatment of Esophageal Squamous Cell Carcinoma and Adenocarcinoma |
title | Identification of Candidate Therapeutic Genes for More Precise Treatment of Esophageal Squamous Cell Carcinoma and Adenocarcinoma |
title_full | Identification of Candidate Therapeutic Genes for More Precise Treatment of Esophageal Squamous Cell Carcinoma and Adenocarcinoma |
title_fullStr | Identification of Candidate Therapeutic Genes for More Precise Treatment of Esophageal Squamous Cell Carcinoma and Adenocarcinoma |
title_full_unstemmed | Identification of Candidate Therapeutic Genes for More Precise Treatment of Esophageal Squamous Cell Carcinoma and Adenocarcinoma |
title_short | Identification of Candidate Therapeutic Genes for More Precise Treatment of Esophageal Squamous Cell Carcinoma and Adenocarcinoma |
title_sort | identification of candidate therapeutic genes for more precise treatment of esophageal squamous cell carcinoma and adenocarcinoma |
topic | Genetics |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9161154/ https://www.ncbi.nlm.nih.gov/pubmed/35664298 http://dx.doi.org/10.3389/fgene.2022.844542 |
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