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Dynamic gene screening enabled identification of a 10-gene panel for early detection and progression assessment of gastric cancer
Early diagnosis and progression assessment are critical for the timely detection and treatment of gastric cancer (GC) patients. Identification of diagnostic biomarkers for early detection of GC represents an unmet clinical need, and how these markers further influence GC progression is explored rare...
Autores principales: | , , , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Research Network of Computational and Structural Biotechnology
2022
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9826902/ https://www.ncbi.nlm.nih.gov/pubmed/36659923 http://dx.doi.org/10.1016/j.csbj.2022.12.036 |
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author | Long, Fei Li, Shuo Xu, Yaqi Liu, Min Zhang, Xuan Zhou, Junting Chen, Yiyi Rong, Yuan Meng, Xiangyu Wang, Fubing |
author_facet | Long, Fei Li, Shuo Xu, Yaqi Liu, Min Zhang, Xuan Zhou, Junting Chen, Yiyi Rong, Yuan Meng, Xiangyu Wang, Fubing |
author_sort | Long, Fei |
collection | PubMed |
description | Early diagnosis and progression assessment are critical for the timely detection and treatment of gastric cancer (GC) patients. Identification of diagnostic biomarkers for early detection of GC represents an unmet clinical need, and how these markers further influence GC progression is explored rarely. We performed dynamic gene screening based on high-throughput data analysis from patients with precancerous lesions and early gastric cancer (EGC) and identified a 10-gene panel by the lasso regression model. This panel demonstrated good diagnostic performance in TCGA (AUC = 0.95, sensitivity = 86.67 %, specificity = 90.63 %) and GEO (AUC = 0.84, sensitivity = 91.67 %, specificity = 78.13 %) cohorts. Moreover, three GC subtypes were clustered based on this panel, in which cluster 2 (C2) demonstrated the highest tumor progression level with a high expression of 10 genes, showing a decreased tumor mutation burden, significantly enriched epithelial-mesenchymal transition hallmark and increased immune exclusion/exhausted features. Finally, the cell localization of these panel genes was explored in scRNA-seq data based on more than 40,000 cells. The 10-gene panel is expected to be a new clinical early detection signature for GC and may aid in progression assessment and personalized treatment of patients. |
format | Online Article Text |
id | pubmed-9826902 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2022 |
publisher | Research Network of Computational and Structural Biotechnology |
record_format | MEDLINE/PubMed |
spelling | pubmed-98269022023-01-18 Dynamic gene screening enabled identification of a 10-gene panel for early detection and progression assessment of gastric cancer Long, Fei Li, Shuo Xu, Yaqi Liu, Min Zhang, Xuan Zhou, Junting Chen, Yiyi Rong, Yuan Meng, Xiangyu Wang, Fubing Comput Struct Biotechnol J Research Article Early diagnosis and progression assessment are critical for the timely detection and treatment of gastric cancer (GC) patients. Identification of diagnostic biomarkers for early detection of GC represents an unmet clinical need, and how these markers further influence GC progression is explored rarely. We performed dynamic gene screening based on high-throughput data analysis from patients with precancerous lesions and early gastric cancer (EGC) and identified a 10-gene panel by the lasso regression model. This panel demonstrated good diagnostic performance in TCGA (AUC = 0.95, sensitivity = 86.67 %, specificity = 90.63 %) and GEO (AUC = 0.84, sensitivity = 91.67 %, specificity = 78.13 %) cohorts. Moreover, three GC subtypes were clustered based on this panel, in which cluster 2 (C2) demonstrated the highest tumor progression level with a high expression of 10 genes, showing a decreased tumor mutation burden, significantly enriched epithelial-mesenchymal transition hallmark and increased immune exclusion/exhausted features. Finally, the cell localization of these panel genes was explored in scRNA-seq data based on more than 40,000 cells. The 10-gene panel is expected to be a new clinical early detection signature for GC and may aid in progression assessment and personalized treatment of patients. Research Network of Computational and Structural Biotechnology 2022-12-22 /pmc/articles/PMC9826902/ /pubmed/36659923 http://dx.doi.org/10.1016/j.csbj.2022.12.036 Text en © 2022 The Authors https://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 Long, Fei Li, Shuo Xu, Yaqi Liu, Min Zhang, Xuan Zhou, Junting Chen, Yiyi Rong, Yuan Meng, Xiangyu Wang, Fubing Dynamic gene screening enabled identification of a 10-gene panel for early detection and progression assessment of gastric cancer |
title | Dynamic gene screening enabled identification of a 10-gene panel for early detection and progression assessment of gastric cancer |
title_full | Dynamic gene screening enabled identification of a 10-gene panel for early detection and progression assessment of gastric cancer |
title_fullStr | Dynamic gene screening enabled identification of a 10-gene panel for early detection and progression assessment of gastric cancer |
title_full_unstemmed | Dynamic gene screening enabled identification of a 10-gene panel for early detection and progression assessment of gastric cancer |
title_short | Dynamic gene screening enabled identification of a 10-gene panel for early detection and progression assessment of gastric cancer |
title_sort | dynamic gene screening enabled identification of a 10-gene panel for early detection and progression assessment of gastric cancer |
topic | Research Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9826902/ https://www.ncbi.nlm.nih.gov/pubmed/36659923 http://dx.doi.org/10.1016/j.csbj.2022.12.036 |
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