ArticleInnovation (Cambridge (Mass.))2024
Integrated analysis of public datasets for the discovery and validation of survival-associated genes in solid tumors.
Article in Innovation (Cambridge (Mass.)), 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 535 papers.
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Who cites it
535 citing papers in PubMed.
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- Allele-Specific MicroRNA-Binding Variants at Colorectal Cancer Risk Loci in a Hispanic/Latino Population: An Integrative GWAS, All of Us, and Epigenomic Analysis.medRxiv : the preprint server for health sciences · 2026Article
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- Inhibiting CXCR2 Remodels the Tumor Microenvironment and Blunts Tumor Progression and Dissemination of High-Grade Serous Carcinoma.Cancer research communications · 2026Article
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- CCL26-Mediated Modulation of Endothelial Secretome by Hypoxia-Induced Tumor-Derived Exosomes Enhances Metastatic Progression in Head and Neck Cancer.Head & neck · 2026Article
- In vivo CRISPR screening links NFKB1 to endocrine resistance in ER+ breast cancer.Endocrine-related cancer · 2026Article
- Subtype-Specific Alterations in Copper Trafficking Associated with KRAS Mutations in Isogenic Colorectal Cancer Cell Lines.Biological trace element research · 2026Article
- N-Acetyltransferase 10 (NAT10) at the crossroads of metabolism, immunology, and cancer biology.Cancer metastasis reviews · 2026Review
475 more citing papers are in PubMed but not listed here.
Corrections and comments
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Authors and funding
1 author.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Identifying genes with prognostic significance that can act as biomarkers in solid tumors can help stratify patients and uncover novel therapy targets. Here, our goal was to expand our previous ranking analysis of survival-associated genes in various solid tumors to include colon cancer specimens with available transcriptomic and clinical data. A Gene Expression Omnibus search was performed to identify available datasets with clinical data and raw gene expression measurements. A combined database was set up and integrated into our Kaplan-Meier plotter, making it possible to identify genes with expression changes linked to altered survival. As a demonstration of the utility of the platform, the most powerful genes linked to overall survival in colon cancer were identified using uni- and multivariate Cox regression analysis. The combined colon cancer database includes 2,137 tumor samples from 17 independent cohorts. The most significant genes associated with relapse-free survival with a false discovery rate below 1% in colon cancer carcinoma were
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Registered trials
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