ArticleiScience2021
Integrative omics analysis reveals effective stratification and potential prognosis markers of pan-gastrointestinal cancers.
Article in iScience, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
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Who cites it
4 citing papers in PubMed.
- Decoding disease and therapy through multiomics integration and systems analysis.Briefings in bioinformatics · 2026Review
- Article
- Artificial intelligence-enabled multi-omics biomarkers for immune checkpoint blockade: mechanisms, predictive modeling, and clinical translation.Frontiers in immunology · 2026Review
- Integration of small RNAs from plasma and cerebrospinal fluid for classification of multiple sclerosis.Frontiers in genetics · 2022Article
Corrections and comments
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Authors and funding
8 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Gastrointestinal (GI) tract cancers are the most common malignant cancers with high mortality rate. Pan-cancer multi-omics data fusion provides a powerful strategy to examine commonalities and differences among various cancer types and benefits for the identification of pan-cancer drug targets. Herein, we conducted an integrative omics analysis on The Cancer Genome Atlas pan-GI samples including six carcinomas and stratified into 9 clusters, i.e. 5 single-type-dominant clusters and 4 mixed clusters, the clustering reveals the molecular features of different subtypes, other than the organ and cell-of-origin classifications. Especially the mixed clusters revealed the homogeneity of pan-GI cancers. We demonstrated that the prognosis differences among pan-GI subtypes based on multi-omics integration are more significant than clustering by single-omics. The potential prognostic markers for pan-GI stratification were identified by proportional hazards model, such as
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Registered trials
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