ArticleInternational journal of genomics2025
Risk Prediction of Colon Cancer Metastasis and Bioinformatics Analysis of Aspirin Treatment.
Article in International journal of genomics, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
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.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
1 citing paper in PubMed.
- Risk Prediction of Colon Cancer Metastasis and Bioinformatics Analysis of Aspirin Treatment.International journal of genomics · 2025Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
5 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Background: Metastasis is a major adverse prognostic factors of colon cancer. Aspirin chemoprophylaxis may improve outcomes for metastatic colon cancer patients. This study aimed to determine the impact of metastasis-related molecular subtypes on prognosis and aspirin chemoprophylaxis benefit. Methods: We obtained differentially expressed metastasis-related genes in cancer and normal tissues. A weighted gene co-expression network (WGCNA) was constructed by differentially expressed genes. Lasso-Cox regression identified key prognostic genes within relevant modules, establishing a risk score model. Transcription factors regulating module genes were explored. Aspirin-interacting genes were identified using the Comparative Toxicogenomics Database (CTD) and validated via cellular experiments. Results: WGCNA analysis of 2062 metastasis-related genes revealed significant correlations between blue/yellow modules and colon cancer. A risk score model based on blue module genes predicted overall survival and 1-, 3-, and 5-year survival rates. Transcription factor analysis implicated the E2F family in blue module regulation and NF Conclusion: We developed a validated metastasis gene predictive model. Colon cancer patients with upregulated NOX4, CXCL8, CXCL5, GDF15, or MMP13 may not benefit from aspirin chemoprophylaxis. Conversely, patients showing aspirin-induced downregulation of E2F1, CCNE1, VEGFA, and MMP3 may derive chemoprophylactic benefit.
Indexed as
Identifiers
What Socratic holds
Registered trials
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 Socratic graph.