ArticleOncoTargets and therapy2021
Identification of Metabolic-Associated Genes for the Prediction of Colon and Rectal Adenocarcinoma.
Article in OncoTargets and therapy, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 10 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
10 citing papers in PubMed, 18 citations in OpenAlex.
- GAMT facilitates tumor progression via inhibiting p53 in clear cell renal cell carcinoma.Biology direct · 2025Article
- Review
- Identification of EARS2 as a Potential Biomarker with Diagnostic, Prognostic, and Therapeutic Implications in Colorectal Cancer.ImmunoTargets and therapy · 2025Article
- Identification of anoikis-related genes to develop a risk model and predict the prognosis and tumor microenvironment in rectal adenocarcinoma.Frontiers in genetics · 2025Article
- Longitudinal Risk Analysis of Second Primary Cancer after Curative Treatment in Patients with Rectal Cancer.Diagnostics (Basel, Switzerland) · 2024Article
- Proteomic-based stratification of intermediate-risk prostate cancer patients.Life science alliance · 2024Article
- Bioinformatics analysis of markers based on m6A related to prognosis combined with immune invasion of rectal adenocarcinoma.Cancer biomarkers : section A of Disease markers · 2024Article
- GPX3 expression was down-regulated but positively correlated with poor outcome in human cancers.Frontiers in oncology · 2023Article
- EARS2 significantly coexpresses with PALB2 in breast and pancreatic cancer.Cancer treatment and research communications · 2022Article
- Development of an exosome-related and immune microenvironment prognostic signature in colon adenocarcinoma.Frontiers in genetics · 2022Article
Corrections and comments
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Authors and funding
6 authors at 1 institution in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
BACKGROUND AND
aimUncontrolled proliferation is the most prominent biological feature of tumors. In order to rapidly proliferate, tumor cells regulate their metabolic behavior by controlling the expression of metabolism-related genes (MRGs) to maximize the utilization of available nutrients. In this study, we aimed to construct prognosis models for colorectal adenocarcinoma (COAD) and rectum adenocarcinoma (READ) using MRGs to predict the prognoses of patients.
methodsWe first acquired the gene expression profiles of COAD and READ from the TCGA database, and then utilized univariate Cox analysis, Lasso regression, and multivariable Cox analysis to identify the MRGs for risk models.
resultsEight genes (
conclusionIn this study, 14 MRGs were identified as potential prognostic biomarkers and therapeutic targets for colorectal cancer.
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