ArticleCancer cell international2023
Identification and validation of a novel prognosis model based on m5C-related long non-coding RNAs in colorectal cancer.
Article in Cancer cell international, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 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
5 citing papers in PubMed, 7 citations in OpenAlex.
- Identification of an m7G-Related lncRNA Signature for Prognostic Prediction and Immune Landscape Characterization in Early Gastric Cancer.OncoTargets and therapy · 2026Article
- m5C RNA modification in colorectal cancer: mechanisms and therapeutic targets.Journal of translational medicine · 2025Review
- Long non-coding RNAs promote colorectal cancer development through other epigenetic modifications.Gastroenterology report · 2025Review
- Development of a novel prognostic prediction model using mitochondrial-related genes and single-cell sequencing data for colorectal carcinoma.Translational gastroenterology and hepatology · 2025Article
- m5C methylation modification may be an accomplice in colorectal cancer escaping from anti-tumor effects of innate immunity-type I/III interferon.Frontiers in immunology · 2024Review
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
9 authors at 3 institutions in 1 country.
Funding
Abstract
backgroundThe prognosis of tumor patients can be assessed by measuring the levels of lncRNAs (long non-coding RNAs), which play a role in controlling the methylation of the RNA. Prognosis in individuals with colorectal adenocarcinoma (CRC) is strongly linked to lncRNA expression, making it imperative to find lncRNAs that are associated with RNA methylation with strong prognostic value.
methodsIn this study, by analyzing TCGA dataset, we were able to develop a risk model for lncRNAs that are associated with m5C with prognostic significance by employing LASSO regression and univariate Cox proportional analysis. There were a number of methods employed to ensure the model was accurate, including multivariate and univariate Cox regression analysis, Kaplan analysis, and receiver operating characteristic curve analysis. The principal component analysis, GSEA and GSVA analysis were used for risk model analysis. The CIBERSORT instrument and the TIMER database were used to evaluate the link between the immune cells that infiltrate tumors and the risk model. In vitro experiments were also performed to validate the predicted m5C-related significant lncRNAs.
resultsThe m5c regulators were differentially expressed in colorectal cancer and normal tissue. Based on the screening criteria and LASSO regression, 11 m5c-related lncRNAs were identified for developing the prognostic risk model. Multivariate and univariate Cox regression analysis showed the risk score is a crucial prognostic factor in CRC patients. The 1-year, 3-year, and 5-year AUC curves showed the risk score was higher than those identified for other clinicopathological characteristics. A nomogram using the risk score as a quantitative tool was developed for predicting patients' outcomes in clinical settings. In addition, the risk profile of m5C-associated lncRNAs can discriminate between tumor immune cells' characteristics in CRC. Mutation patterns and chemotherapy were analyzed between high- and low- risk groups of CRC patients. Moreover, TNFRSF10A-AS1 was chosen for the in vitro verification of the m5C-connected lncRNA to demonstrate impressive effects on the proliferation, migration and invasion of CRC cells.
conclusionA risk model including the prognostic value of 11 m5C-associated lncRNAs proves to be a useful prognostic tool for CRC and improves the care of patients suffering from CRC based on these findings.
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.