ArticlePeerJ2018
Establishment of a 12-gene expression signature to predict colon cancer prognosis.
Article in PeerJ, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 22 papers.
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Who cites it
22 citing papers in PubMed.
- DNA ploidy combined with tumor stroma as a biomarker for predicting the prognosis of stage II colorectal cancer patients and identifying candidates for chemotherapy.World journal of surgical oncology · 2025Article
- Article
- Risk factors of recurrence in TNM stage I colorectal cancer.Annals of surgical treatment and research · 2023Article
- Vasoactive intestinal peptide blockade suppresses tumor growth by regulating macrophage polarization and function in CT26 tumor-bearing mice.Scientific reports · 2023Article
- 18F-FDG PET/CT Image Deep Learning Predicts Colon Cancer Survival.Contrast media & molecular imaging · 2023Article
- Molecular signature to predict quality of life and survival with glioblastoma using Multiview omics model.PloS one · 2023Article
- Based on Molecular Subtypes, Immune Characteristics and Genomic Variation to Constructing and Verifying Multi-Gene Prognostic Characteristics of Colorectal Cancer.Frontiers in cell and developmental biology · 2022Article
- An 11-gene signature for the prediction of systemic recurrences in colon adenocarcinoma.Gastroenterology report · 2021Article
- A Claudin-Based Molecular Signature Identifies High-Risk, Chemoresistant Colorectal Cancer Patients.Cells · 2021Article
- Identification and development of a novel invasion-related gene signature for prognosis prediction in colon adenocarcinoma.Cancer cell international · 2021Article
- Machine learning analysis of TCGA cancer data.PeerJ. Computer science · 2021Article
- Identification of a 5-Gene-Based Scoring System by WGCNA and LASSO to Predict Prognosis for Rectal Cancer Patients.Analytical cellular pathology (Amsterdam) · 2021Article
- The role of multiple metabolic genes in predicting the overall survival of colorectal cancer: A study based on TCGA and GEO databases.PloS one · 2021Article
- Prognostic Value of SLC4A4 and its Correlation with Immune Infiltration in Colon Adenocarcinoma.Medical science monitor : international medical journal of experimental and clinical research · 2020Article
- Gene signature and prognostic merit of M6a regulators in colorectal cancer.Experimental biology and medicine (Maywood, N.J.) · 2020Article
- Molecular docking and machine learning analysis of Abemaciclib in colon cancer.BMC molecular and cell biology · 2020Article
- Development of a prognostic index of colon adenocarcinoma based on immunogenomic landscape analysis.Annals of translational medicine · 2020Article
- IRF1 association with tumor immune microenvironment and use as a diagnostic biomarker for colorectal cancer recurrence.Oncology letters · 2020Article
- Prognostic Model of Colorectal Cancer Constructed by Eight Immune-Related Genes.Frontiers in molecular biosciences · 2020Article
- Analysis of factors potentially predicting prognosis of colorectal cancer.World journal of gastrointestinal oncology · 2019Article
Corrections and comments
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Authors and funding
8 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
A robust and accurate gene expression signature is essential to assist oncologists to determine which subset of patients at similar Tumor-Lymph Node-Metastasis (TNM) stage has high recurrence risk and could benefit from adjuvant therapies. Here we applied a two-step supervised machine-learning method and established a 12-gene expression signature to precisely predict colon adenocarcinoma (COAD) prognosis by using COAD RNA-seq transcriptome data from The Cancer Genome Atlas (TCGA). The predictive performance of the 12-gene signature was validated with two independent gene expression microarray datasets: GSE39582 includes 566 COAD cases for the development of six molecular subtypes with distinct clinical, molecular and survival characteristics; GSE17538 is a dataset containing 232 colon cancer patients for the generation of a metastasis gene expression profile to predict recurrence and death in COAD patients. The signature could effectively separate the poor prognosis patients from good prognosis group (disease specific survival (DSS): Kaplan Meier (KM) Log Rank
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