ArticleAnnals of translational medicine2023
The lncRNA XIST/miR-29b-3p/COL3A1 axis regulates central carbon metabolism in head and neck squamous cell carcinoma and is associated with poor tumor prognosis.
Article in Annals of translational medicine, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. It has been retracted, and should not be counted. 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, 4 citations in OpenAlex.
- PFKP in malignant tumors: bridging metabolic reprogramming, post-translational modifications, and the immunosuppressive microenvironment.Frontiers in cell and developmental biology · 2026Review
- Utilization of TEP miRNAs in tumor proliferation, diagnostic evaluation, therapeutic intervention, and prognostic assessment.Molecular biology reports · 2025Review
- Retraction: The lncRNA XIST/miR-29b-3p/COL3A1 axis regulates central carbon metabolism in head and neck squamous cell carcinoma and is associated with poor tumor prognosis.Annals of translational medicine · 2024Article
Corrections and comments
- Retraction · 2023-12-13Notice - Limited or No Information ·
- Retracted
Authors and funding
6 authors at 3 institutions in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Background: Recent evidence shows that COL3A1 promotes the progression of many types of cancer. The purpose of our study is to explore the correlation between COL3A1 and the prognosis of patients with head and neck squamous cell carcinoma (HNSCC) and its potential mechanism. Methods: We initially screened the differentially expressed gene COL3A1 in The Cancer Genome Atlas (TCGA) database, and the association between the expression level of COL3A1, prognosis, and the clinical parameters of HNSCC patients was verified. A nomogram was constructed according to the multivariate analysis results. Next, a heatmap of COL3A1 co-expressed genes was constructed in TCGA database. The TargetScan database is used to explore the microRNAs (miRNA) related to COL3A1. The starBase database was used to explore and predict the long non-coding RNAs (lncRNAs) that the candidate miRNAs might bind to. Finally, the potential mechanism of action was investigated using Gene Set Enrichment Analysis (GSEA). Results: COL3A1 expression is elevated in HNSCC tumor tissues, and HNSCC patients with high COL3A1 expression have worse prognostic factors. COL3A1 was positively correlated with the central carbon metabolism-related proteins: epidermal growth factor receptor (EGFR), phosphoglycerate mutase 1 (PGAM1), hexokinase 3 (HK3), and phosphofructokinase, platelet (PFKP). The TargetScan database showed that the best candidate miRNA for binding to the three prime untranslated region (3'UTR) end of COL3A1 mRNA was Conclusions: Low COL3A1 expression can be employed as a new HNSCC predictive biomarker, and the prognosis of HNSCC patients with lower COL3A1 expression can be greatly improved. At the same time, we found that the lncRNA XIST/
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.