ArticleVaccines2022
Integration of Bulk and Single-Cell RNA-Seq Data to Construct a Prognostic Model of Membrane Tension-Related Genes for Colon Cancer.
Article in Vaccines, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers.
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Who cites it
6 citing papers in PubMed, 6 citations in OpenAlex.
- A tumor-intrinsic WNT-inhibitory NOTUM program drives immune resistance in microsatellite stable colorectal cancer.Cell reports. Medicine · 2026Article
- Integrative multi-omics analysis reveals a membrane tension signature associated with tumor-stroma crosstalk in hepatocellular carcinoma.Frontiers in immunology · 2026Article
- Sidedness matters: single-cell perspectives on left- and right-sided colorectal cancer.Frontiers in cell and developmental biology · 2025Review
- Article
- Membrane tension-mediated stiff and soft tumor subtypes closely associated with prognosis for prostate cancer patients.European journal of medical research · 2023Article
- Integrative analysis reveals a four-gene signature for predicting survival and immunotherapy response in colon cancer patients using bulk and single-cell RNA-seq data.Frontiers in oncology · 2023Article
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Authors and funding
4 authors at 1 institution in 1 country.
Funding
Abstract
backgroundThe plasma membrane provides a highly dynamic barrier for cancer cells to interact with their surrounding microenvironment. Membrane tension, a pivotal physical property of the plasma membrane, has attracted widespread attention since it plays a role in the progression of various cancers. This study aimed to identify a prognostic signature in colon cancer from membrane tension-related genes (MTRGs) and explore its implications for the disease.
methodsBulk RNA-seq data were obtained from The Cancer Genome Atlas (TCGA) database, and then applied to the differentially expressed gene analysis. By implementing a univariate Cox regression and a LASSO-Cox regression, we developed a prognostic model based on four MTRGs. The prognostic efficacy of this model was evaluated in combination with a Kaplan-Meier analysis and receiver operating characteristic (ROC) curve analysis. Moreover, the relationships between the signature and immune cell infiltration, immune status, and somatic mutation were further explored. Lastly, by utilizing single-cell RNA-seq data, cell type annotation, pseudo-time analysis, drug sensitivity, and molecular docking were implemented.
resultsWe constructed a 4-MTRG signature. The risk score derived from the model was further validated as an independent variable for survival prediction. Two risk groups were divided based on the risk score calculated by the 4-MTRG signature. In addition, we observed a significant difference in immune cell infiltration, such as subsets of CD4 T cells and macrophages, between the high- and low-risk groups. Moreover, in the pseudo-time analysis, TIMP1 was found to be more highly expressed with the progression of time. Finally, three small molecule drugs, elesclomol, shikonin, and bryostatin-1, exhibited a binding potential to TIMP-1.
conclusionsThe novel 4-MTRG signature is a promising biomarker in predicting clinical outcomes for colon cancer patients, and TIMP1, a member of the signature, may be a sensitive regulator of the progression of colon cancer.
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