ArticleComputational and mathematical methods in medicine2022
m6A-Related Genes Contribute to Poor Prognosis of Hepatocellular Carcinoma.
Article in Computational and mathematical methods in medicine, 2022. 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.
- WTAP-mediated m6A regulation in digestive system cancers: from molecular mechanisms to therapeutic strategies.American journal of cancer research · 2025Review
- Liver-specific Mettl14 deletion induces nuclear heterotypia and dysregulates RNA export machinery.bioRxiv : the preprint server for biology · 2024Article
- Detecting the Tumor Prognostic Factors From the YTH Domain Family Through Integrative Pan-Cancer Analysis.Cancer informatics · 2024Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
4 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Background: Hepatocellular carcinoma (HCC) is one of the most common and lethal digestive system cancers worldwide. N6-methyladenosine (m6A) modification plays an essential role in diverse critical biological processes and may participate in the development and progression of HCC. Methods: We downloaded transcriptome data and clinical data from TCGA as the training set. COX and LASSO screened prognostic m6A genes. ROC and Kaplan-Meier curve analysis evaluated the effectiveness of the model. ICGC and our center data were used as verification sets. Results: We include the "writer (METTL3, METTL14, WTAP, KIAA1429, RBM15, ZC3H13)," the "reader (YTHDC1, YTHDC2, YTHDF1, YTHDF2, HNRNPC)," and the "eraser (FTO, ALKBH5)" in the study. We obtained YTHDF2, YTHDF1, METTL3, and KIAA1429 through differential analysis, survival analysis, and LASSO regression analysis. The prediction model was established based on the expression of these 4 molecules. HCC patients were divided into "high-risk" and "low-risk" groups to compare survival differences. The model suggested a poor prognosis in the validation sets. Conclusion: The four-m6A-related-gene combination model was an independent prognostic factor of HCC and could improve the prediction of the prognosis of HCC.
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.