Use tumor suppressor genes as biomarkers for diagnosis of non-small cell lung cancer

Abstract Lung cancer is the leading cause of death worldwide. Especially, non-small cell lung cancer (NSCLC) has higher mortality rate than the other cancers. The high mortality rate is partially due to lack of efficient biomarkers for detection, diagnosis and prognosis. To find high efficient bioma...

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Autores principales:	Chuantao Zhang, Man Jiang, Na Zhou, Helei Hou, Tianjun Li, Hongsheng Yu, Yuan-De Tan, Xiaochun Zhang
Formato:	article
Lenguaje:	EN
Publicado:	Nature Portfolio 2021
Materias:	Medicine R Science Q
Acceso en línea:	https://doaj.org/article/9c2605b63a07471c93a57ed7106aa4f2
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spelling	oai:doaj.org-article:9c2605b63a07471c93a57ed7106aa4f22021-12-02T13:30:34ZUse tumor suppressor genes as biomarkers for diagnosis of non-small cell lung cancer10.1038/s41598-020-80735-x2045-2322https://doaj.org/article/9c2605b63a07471c93a57ed7106aa4f22021-02-01T00:00:00Zhttps://doi.org/10.1038/s41598-020-80735-xhttps://doaj.org/toc/2045-2322Abstract Lung cancer is the leading cause of death worldwide. Especially, non-small cell lung cancer (NSCLC) has higher mortality rate than the other cancers. The high mortality rate is partially due to lack of efficient biomarkers for detection, diagnosis and prognosis. To find high efficient biomarkers for clinical diagnosis of NSCLC patients, we used gene differential expression and gene ontology (GO) to define a set of 26 tumor suppressor (TS) genes. The 26 TS genes were down-expressed in tumor samples in cohorts GSE18842, GSE40419, and GSE21933 and at stages 2 and 3 in GSE19804, and 15 TS genes were significantly down-expressed in tumor samples of stage 1. We used S-scores and N-scores defined in correlation networks to evaluate positive and negative influences of these 26 TS genes on expression of other functional genes in the four independent cohorts and found that SASH1, STARD13, CBFA2T3 and RECK were strong TS genes that have strong accordant/discordant effects and network effects globally impacting the other genes in expression and hence can be used as specific biomarkers for diagnosis of NSCLC cancer. Weak TS genes EXT1, PTCH1, KLK10 and APC that are associated with a few genes in function or work in a special pathway were not detected to be differentially expressed and had very small S-scores and N-scores in all collected datasets and can be used as sensitive biomarkers for diagnosis of early cancer. Our findings are well consistent with functions of these TS genes. GSEA analysis found that these 26 TS genes as a gene set had high enrichment scores at stages 1, 2, 3 and all stages.Chuantao ZhangMan JiangNa ZhouHelei HouTianjun LiHongsheng YuYuan-De TanXiaochun ZhangNature PortfolioarticleMedicineRScienceQENScientific Reports, Vol 11, Iss 1, Pp 1-13 (2021)
institution	DOAJ
collection	DOAJ
language	EN
topic	Medicine R Science Q
spellingShingle	Medicine R Science Q Chuantao Zhang Man Jiang Na Zhou Helei Hou Tianjun Li Hongsheng Yu Yuan-De Tan Xiaochun Zhang Use tumor suppressor genes as biomarkers for diagnosis of non-small cell lung cancer
description	Abstract Lung cancer is the leading cause of death worldwide. Especially, non-small cell lung cancer (NSCLC) has higher mortality rate than the other cancers. The high mortality rate is partially due to lack of efficient biomarkers for detection, diagnosis and prognosis. To find high efficient biomarkers for clinical diagnosis of NSCLC patients, we used gene differential expression and gene ontology (GO) to define a set of 26 tumor suppressor (TS) genes. The 26 TS genes were down-expressed in tumor samples in cohorts GSE18842, GSE40419, and GSE21933 and at stages 2 and 3 in GSE19804, and 15 TS genes were significantly down-expressed in tumor samples of stage 1. We used S-scores and N-scores defined in correlation networks to evaluate positive and negative influences of these 26 TS genes on expression of other functional genes in the four independent cohorts and found that SASH1, STARD13, CBFA2T3 and RECK were strong TS genes that have strong accordant/discordant effects and network effects globally impacting the other genes in expression and hence can be used as specific biomarkers for diagnosis of NSCLC cancer. Weak TS genes EXT1, PTCH1, KLK10 and APC that are associated with a few genes in function or work in a special pathway were not detected to be differentially expressed and had very small S-scores and N-scores in all collected datasets and can be used as sensitive biomarkers for diagnosis of early cancer. Our findings are well consistent with functions of these TS genes. GSEA analysis found that these 26 TS genes as a gene set had high enrichment scores at stages 1, 2, 3 and all stages.
format	article
author	Chuantao Zhang Man Jiang Na Zhou Helei Hou Tianjun Li Hongsheng Yu Yuan-De Tan Xiaochun Zhang
author_facet	Chuantao Zhang Man Jiang Na Zhou Helei Hou Tianjun Li Hongsheng Yu Yuan-De Tan Xiaochun Zhang
author_sort	Chuantao Zhang
title	Use tumor suppressor genes as biomarkers for diagnosis of non-small cell lung cancer
title_short	Use tumor suppressor genes as biomarkers for diagnosis of non-small cell lung cancer
title_full	Use tumor suppressor genes as biomarkers for diagnosis of non-small cell lung cancer
title_fullStr	Use tumor suppressor genes as biomarkers for diagnosis of non-small cell lung cancer
title_full_unstemmed	Use tumor suppressor genes as biomarkers for diagnosis of non-small cell lung cancer
title_sort	use tumor suppressor genes as biomarkers for diagnosis of non-small cell lung cancer
publisher	Nature Portfolio
publishDate	2021
url	https://doaj.org/article/9c2605b63a07471c93a57ed7106aa4f2
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Use tumor suppressor genes as biomarkers for diagnosis of non-small cell lung cancer

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