ArticleOncotarget2016
Assessing the clinical utility of genomic expression data across human cancers.
Article in Oncotarget, 2016. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 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
5 citing papers in PubMed.
- Potential relationship between the selenoproteome and cancer.Molecular and clinical oncology · 2020Article
- Integrating Somatic Mutations for Breast Cancer Survival Prediction Using Machine Learning Methods.Frontiers in genetics · 2020Article
- Stratification of Breast Cancer by Integrating Gene Expression Data and Clinical Variables.Molecules (Basel, Switzerland) · 2019Article
- Comprehensive analysis of the tumor immune micro-environment in non-small cell lung cancer for efficacy of checkpoint inhibitor.Scientific reports · 2018Article
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Authors and funding
6 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Cancer molecular profiling provides better understanding of tumor mechanisms and helps to improve the existing cancer management. Here we present the gene expression signatures from ~9000 human tumors with clinical information across 32 malignancies from The Cancer Genome Atlas project (TCGA). Major predictors from the RNA sequencing data that were significantly correlated with cancer survival were identified. The expression level of these prognostic genes revealed significant genomic pathways that were clinically relevant to survival outcomes across human cancers. Furthermore, it is shown that in most cancer types, combinations of these genomic signatures with clinical information might yield improved predictions. Thus, with respect to clinical utility, our study reveals the promising values of genomic data from the pan-cancer perspective.
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