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ESCCdb: A comprehensive database and key regulator exploring platform based on cross dataset comparisons for esophageal squamous cell carcinoma
Esophageal cancer is the seventh most prevalent and the sixth most lethal cancer. Esophageal squamous cell carcinoma (ESCC) is one of the major esophageal cancer subtypes that accounts for 87 % of the total cases. However, its molecular mechanism remains unclear. Here, we present an integrated datab...
Autores principales: | , , , , , , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Research Network of Computational and Structural Biotechnology
2023
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10036886/ https://www.ncbi.nlm.nih.gov/pubmed/36968016 http://dx.doi.org/10.1016/j.csbj.2023.03.026 |
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author | Yang, Jian Bi, Liyun Wang, Chen Wang, Gang Gou, Yixiong Dong, Liting Wang, Maoxu Luo, Hong Wang, Kun Wang, Yu Huang, Yue Cai, Haoyang Xiao, Zhixiong |
author_facet | Yang, Jian Bi, Liyun Wang, Chen Wang, Gang Gou, Yixiong Dong, Liting Wang, Maoxu Luo, Hong Wang, Kun Wang, Yu Huang, Yue Cai, Haoyang Xiao, Zhixiong |
author_sort | Yang, Jian |
collection | PubMed |
description | Esophageal cancer is the seventh most prevalent and the sixth most lethal cancer. Esophageal squamous cell carcinoma (ESCC) is one of the major esophageal cancer subtypes that accounts for 87 % of the total cases. However, its molecular mechanism remains unclear. Here, we present an integrated database for ESCC called ESCCdb, which includes a total of 56 datasets and published studies from the GEO, Xena or SRA databases and related publications. It helps users to explore a particular gene with multiple graphical and interactive views with one click. The results comprise expression changes across 20 datasets, copy number alterations in 11 datasets, somatic mutations from 12 papers, related drugs derived from DGIdb, related pathways, and gene correlations. ESCCdb enables directly cross-dataset comparison of a gene’s mutations, expressions and copy number changes in multiple datasets. This allows users to easily assess the alterations in ESCC. Furthermore, survival analysis, drug-gene relationships, and results from whole-genome CRISPR/Cas9 screening can help users determine the clinical relevance, derive functional inferences, and identify potential drugs. Notably, ESCCdb also enables the exploration of the correlation structure and identification of potential key regulators for a process. Finally, we identified 789 consistently differential expressed genes; we summarized recurrently mutated genes and genes affected by significant copy number alterations. These genes may be stable biomarkers or important players during ESCC development. ESCCdb fills the gap between massive omics data and users’ needs for integrated analysis and can promote basic and clinical ESCC research. The database is freely accessible at http://cailab.labshare.cn/ESCCdb. |
format | Online Article Text |
id | pubmed-10036886 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2023 |
publisher | Research Network of Computational and Structural Biotechnology |
record_format | MEDLINE/PubMed |
spelling | pubmed-100368862023-03-25 ESCCdb: A comprehensive database and key regulator exploring platform based on cross dataset comparisons for esophageal squamous cell carcinoma Yang, Jian Bi, Liyun Wang, Chen Wang, Gang Gou, Yixiong Dong, Liting Wang, Maoxu Luo, Hong Wang, Kun Wang, Yu Huang, Yue Cai, Haoyang Xiao, Zhixiong Comput Struct Biotechnol J Database Article Esophageal cancer is the seventh most prevalent and the sixth most lethal cancer. Esophageal squamous cell carcinoma (ESCC) is one of the major esophageal cancer subtypes that accounts for 87 % of the total cases. However, its molecular mechanism remains unclear. Here, we present an integrated database for ESCC called ESCCdb, which includes a total of 56 datasets and published studies from the GEO, Xena or SRA databases and related publications. It helps users to explore a particular gene with multiple graphical and interactive views with one click. The results comprise expression changes across 20 datasets, copy number alterations in 11 datasets, somatic mutations from 12 papers, related drugs derived from DGIdb, related pathways, and gene correlations. ESCCdb enables directly cross-dataset comparison of a gene’s mutations, expressions and copy number changes in multiple datasets. This allows users to easily assess the alterations in ESCC. Furthermore, survival analysis, drug-gene relationships, and results from whole-genome CRISPR/Cas9 screening can help users determine the clinical relevance, derive functional inferences, and identify potential drugs. Notably, ESCCdb also enables the exploration of the correlation structure and identification of potential key regulators for a process. Finally, we identified 789 consistently differential expressed genes; we summarized recurrently mutated genes and genes affected by significant copy number alterations. These genes may be stable biomarkers or important players during ESCC development. ESCCdb fills the gap between massive omics data and users’ needs for integrated analysis and can promote basic and clinical ESCC research. The database is freely accessible at http://cailab.labshare.cn/ESCCdb. Research Network of Computational and Structural Biotechnology 2023-03-17 /pmc/articles/PMC10036886/ /pubmed/36968016 http://dx.doi.org/10.1016/j.csbj.2023.03.026 Text en © 2023 The Authors. Published by Elsevier B.V. on behalf of Research Network of Computational and Structural Biotechnology. 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 | Database Article Yang, Jian Bi, Liyun Wang, Chen Wang, Gang Gou, Yixiong Dong, Liting Wang, Maoxu Luo, Hong Wang, Kun Wang, Yu Huang, Yue Cai, Haoyang Xiao, Zhixiong ESCCdb: A comprehensive database and key regulator exploring platform based on cross dataset comparisons for esophageal squamous cell carcinoma |
title | ESCCdb: A comprehensive database and key regulator exploring platform based on cross dataset comparisons for esophageal squamous cell carcinoma |
title_full | ESCCdb: A comprehensive database and key regulator exploring platform based on cross dataset comparisons for esophageal squamous cell carcinoma |
title_fullStr | ESCCdb: A comprehensive database and key regulator exploring platform based on cross dataset comparisons for esophageal squamous cell carcinoma |
title_full_unstemmed | ESCCdb: A comprehensive database and key regulator exploring platform based on cross dataset comparisons for esophageal squamous cell carcinoma |
title_short | ESCCdb: A comprehensive database and key regulator exploring platform based on cross dataset comparisons for esophageal squamous cell carcinoma |
title_sort | esccdb: a comprehensive database and key regulator exploring platform based on cross dataset comparisons for esophageal squamous cell carcinoma |
topic | Database Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10036886/ https://www.ncbi.nlm.nih.gov/pubmed/36968016 http://dx.doi.org/10.1016/j.csbj.2023.03.026 |
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