ArticleFrontiers in oncology2025
Novel mtDNA methylation-associated prognostic signatures in colorectal cancer.
Article in Frontiers in oncology, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.
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
3 citing papers in PubMed.
- The mitochondrial DNA-cGAS-STING axis in colorectal cancer: a focused review of context-dependent roles and therapeutic opportunities.Frontiers in molecular biosciences · 2026Review
- Colorectal Adenocarcinoma: A Comprehensive Narrative Review of Molecular Pathogenesis, Metabolic Vulnerabilities, and Therapeutic Potential of Sorghum Polyphenols.Analytical cellular pathology (Amsterdam) · 2026Review
- Commentary: Novel mtDNA methylation-associated prognostic signatures in colorectal cancer.Frontiers in oncology · 2026Article
Corrections and comments
- Commented on by
Authors and funding
6 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Background: Given the high morbidity and mortality of colorectal cancer (CRC), as well as its challenging treatment, the present study was conducted to identify reliable prognostic signatures for predicting clinical outcomes. Methods: This study identified key genes through differential expression analysis and cluster analysis on CRC transcriptomic data from public databases and mitochondrial DNA methylation-related genes (MDM-RGs) from previous literature. Cox analysis and machine learning were used to define prognostic genes and build a prognostic model, followed by the establishment of a nomogram to assess the risk score as a prognostic indicator. Furthermore, the impact of prognostic genes was explored by employing immune infiltration, antitumor immunoassay, medication sensitization assay, and prognostic gene dependency analysis. In addition, the expression of MDM-RGs in CRC was assessed by qPCR and Western blotting. Results: Consequently, this study identified three prognostic MDM-RGs (TINAG, EPHB2, and FCN3), and a risk model was constructed based on these three prognostic genes. A nomogram was created to predict CRC prognosis clinically. Significant differences in risk scores were observed across subgroups, particularly in stage and T stage groups. This study observed disparities in immune cells involving lymphocytes and memory cells, with the identification of 92 pharmaceuticals showing intergroup significant differences. Sorafenib, Salubrinal, and Roscovitine were positively correlated with the risk score, whereas WO2009093972 was negatively correlated. Additionally, this study identified several target genes such as FBXO25 with TINAG, CCDC28A with EPHB2, and SH2D6 with FCN3, with subsequent validation achieved through qPCR and western blotting. Conclusions: In conclusion, this study identifies three prognostic genes, providing new insights into CRC pathogenesis and potential therapeutic strategies.
Indexed as
Identifiers
What OpenQuestion 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 OpenQuestion graph.