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Identification of potential biomarkers for lung adenocarcinoma
Lung adenocarcinoma (LUAD) is the most predominant subtype of lung cancers and is one of the leading causes of cancer related mortality worldwide. Despite the advancements in the field of cancer diagnostics and therapeutics, detection at an early stage using reliable biomarkers is an unmet clinical...
Autores principales: | , , , , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Elsevier
2020
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7677689/ https://www.ncbi.nlm.nih.gov/pubmed/33251353 http://dx.doi.org/10.1016/j.heliyon.2020.e05452 |
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author | Sayeeram, Deepak Katte, Teesta V. Bhatia, Saloni Jai Kumar, Anushree Kumar, Avinesh Jayashree, G. Rachana, D.S. Nalla Reddy, Harsha Vardhan Arvind Rasalkar, Avinash Malempati, Rajya Lakshmi Reddy S, Divijendra Natha |
author_facet | Sayeeram, Deepak Katte, Teesta V. Bhatia, Saloni Jai Kumar, Anushree Kumar, Avinesh Jayashree, G. Rachana, D.S. Nalla Reddy, Harsha Vardhan Arvind Rasalkar, Avinash Malempati, Rajya Lakshmi Reddy S, Divijendra Natha |
author_sort | Sayeeram, Deepak |
collection | PubMed |
description | Lung adenocarcinoma (LUAD) is the most predominant subtype of lung cancers and is one of the leading causes of cancer related mortality worldwide. Despite the advancements in the field of cancer diagnostics and therapeutics, detection at an early stage using reliable biomarkers is an unmet clinical need for a plethora of cancers, including LUAD, thus attributing to poor prognosis. In view of this, to identify potential biomarkers and therapeutic candidate genes, the expression of all known human genes was screened in the publicly available ‘The Cancer Genome Atlas’ (TCGA) samples of LUAD patients which resulted in the identification of overexpressed genes. Further analysis of these genes across various patient sample datasets revealed that ZNF687, ODR4, PBXIP1, PYGO2, METTL3, PIGM and RAD1 are consistently more highly expressed in LUAD. Higher expression of these genes either alone or in combination is correlated with poor survival of LUAD patients. Hence, in this study we propose that these identified genes could serve as potential candidates as gene signatures or biomarkers for LUAD that require further investigation in large cohorts of LUAD samples. |
format | Online Article Text |
id | pubmed-7677689 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2020 |
publisher | Elsevier |
record_format | MEDLINE/PubMed |
spelling | pubmed-76776892020-11-27 Identification of potential biomarkers for lung adenocarcinoma Sayeeram, Deepak Katte, Teesta V. Bhatia, Saloni Jai Kumar, Anushree Kumar, Avinesh Jayashree, G. Rachana, D.S. Nalla Reddy, Harsha Vardhan Arvind Rasalkar, Avinash Malempati, Rajya Lakshmi Reddy S, Divijendra Natha Heliyon Research Article Lung adenocarcinoma (LUAD) is the most predominant subtype of lung cancers and is one of the leading causes of cancer related mortality worldwide. Despite the advancements in the field of cancer diagnostics and therapeutics, detection at an early stage using reliable biomarkers is an unmet clinical need for a plethora of cancers, including LUAD, thus attributing to poor prognosis. In view of this, to identify potential biomarkers and therapeutic candidate genes, the expression of all known human genes was screened in the publicly available ‘The Cancer Genome Atlas’ (TCGA) samples of LUAD patients which resulted in the identification of overexpressed genes. Further analysis of these genes across various patient sample datasets revealed that ZNF687, ODR4, PBXIP1, PYGO2, METTL3, PIGM and RAD1 are consistently more highly expressed in LUAD. Higher expression of these genes either alone or in combination is correlated with poor survival of LUAD patients. Hence, in this study we propose that these identified genes could serve as potential candidates as gene signatures or biomarkers for LUAD that require further investigation in large cohorts of LUAD samples. Elsevier 2020-11-13 /pmc/articles/PMC7677689/ /pubmed/33251353 http://dx.doi.org/10.1016/j.heliyon.2020.e05452 Text en © 2020 Published by Elsevier Ltd. http://creativecommons.org/licenses/by-nc-nd/4.0/ This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/). |
spellingShingle | Research Article Sayeeram, Deepak Katte, Teesta V. Bhatia, Saloni Jai Kumar, Anushree Kumar, Avinesh Jayashree, G. Rachana, D.S. Nalla Reddy, Harsha Vardhan Arvind Rasalkar, Avinash Malempati, Rajya Lakshmi Reddy S, Divijendra Natha Identification of potential biomarkers for lung adenocarcinoma |
title | Identification of potential biomarkers for lung adenocarcinoma |
title_full | Identification of potential biomarkers for lung adenocarcinoma |
title_fullStr | Identification of potential biomarkers for lung adenocarcinoma |
title_full_unstemmed | Identification of potential biomarkers for lung adenocarcinoma |
title_short | Identification of potential biomarkers for lung adenocarcinoma |
title_sort | identification of potential biomarkers for lung adenocarcinoma |
topic | Research Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7677689/ https://www.ncbi.nlm.nih.gov/pubmed/33251353 http://dx.doi.org/10.1016/j.heliyon.2020.e05452 |
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