ArticleOxidative medicine and cellular longevity2021
Identification of a Tumor Microenvironment-Related Gene Signature Indicative of Disease Prognosis and Treatment Response in Colon Cancer.
Article in Oxidative medicine and cellular longevity, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 32 papers.
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Who cites it
32 citing papers in PubMed, 40 citations in OpenAlex.
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- Identifying colorectal cancer subtypes and establishing a prognostic model using metabolic plasticity and ferroptosis genes.Scientific reports · 2024Article
- PDE1B, a potential biomarker associated with tumor microenvironment and clinical prognostic significance in osteosarcoma.Scientific reports · 2024Article
- To explore the prognostic characteristics of colon cancer based on tertiary lymphoid structure-related genes and reveal the characteristics of tumor microenvironment and drug prediction.Scientific reports · 2024Article
- Downstream STING pathways IRF3 and NF-κB differentially regulate CCL22 in response to cytosolic dsDNA.Cancer gene therapy · 2024Article
- Propensity score matching as an effective strategy for biomarker cohort design and omics data analysis.PloS one · 2024Article
- GNG4, as a potential predictor of prognosis, is correlated with immune infiltrates in colon adenocarcinoma.Journal of cellular and molecular medicine · 2023Article
- Clinical plasma cells-related genes to aid therapy in colon cancer.BMC genomics · 2023Article
- Extracellular Matrix- and Integrin Adhesion Complexes-Related Genes in the Prognosis of Prostate Cancer Patients' Progression-Free Survival.Biomedicines · 2023Article
- CLEC5A regulates the proliferation and migration of colon cancer via the AKT/mTOR signaling pathway.Journal of gastrointestinal oncology · 2023Article
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- Homophilic interaction of cell adhesion molecule 3 coordinates retina neuroepithelial cell proliferation.The Journal of cell biology · 2023Article
- Exploring the prognostic function of TMB-related prognostic signature in patients with colon cancer.BMC medical genomics · 2023Article
- Anti-IgLON5 disease: a novel topic beyond neuroimmunology.Neural regeneration research · 2023Review
- Machine learning algorithm to construct cuproptosis- and immune-related prognosis prediction model for colon cancer.World journal of gastrointestinal oncology · 2023Review
- Anti-IgLON5 disease complicated with rectal adenocarcinoma: a case report.BMC neurology · 2023Article
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Authors and funding
9 authors at 1 institution in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
backgroundThe tumor microenvironment (TME) is associated with disease outcomes and treatment response in colon cancer. Here, we constructed a TME-related gene signature that is prognosis of disease survival and may predict response to immunotherapy in colon cancer.
methodsWe calculated immune and stromal scores for 385 colon cancer samples from The Cancer Genome Atlas (TCGA) database using the ESTIMATE algorithm. We identified nine TME-related prognostic genes using Cox regression analysis. We evaluated associations between protein expression, extent of immune cell infiltrate, and patient survival. We calculated risk scores and built a clinical predictive model for the TME-related gene signature. Receiver operating characteristic (ROC) curves were generated to assess the predictive power of the signature. We estimated the half-maximal inhibitory concentration (IC50) of chemotherapeutic drugs in patients using the pRRophetic algorithm. The expression of immune checkpoint genes was evaluated.
resultsHigh immune and stromal scores are significantly associated with poor overall survival (
conclusionsWe identified a novel prognostic TME-related gene expression signature in colon cancer. Stratification of patients based on this gene signature could be used to improve outcomes and guide better therapy for colon cancer patients.
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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.