ArticleBiomedicines2022
Impact of
Article in Biomedicines, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 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
7 citing papers in PubMed, 9 citations in OpenAlex.
- miR-1-3p downregulation drives tumor invasion in oral squamous cell carcinoma: insights from in vitro, in vivo, and ex vivo models.Molecular biology reports · 2026Article
- Integrated Analysis of the LncRNA-Mediated ceRNA Network Associated With Prognosis in Posttreatment Recurrent Nasopharyngeal Carcinoma.Journal of cellular and molecular medicine · 2025Article
- miR-429 suppresses progression and metastasis of salivary adenoid cystic carcinoma by targeting ZEB1.Journal of molecular histology · 2025Article
- Machine Learning-Driven Identification of Exosome-Related Genes in Head and Neck Squamous Cell Carcinoma for Prognostic Evaluation and Drug Response Prediction.Biomedicines · 2025Article
- Identification of Tumor-SuppressiveCancers · 2023Article
- Identification of AntitumorGenes · 2022Article
- Clinical and molecular evaluation of patients with ovarian cancer in the context of drug resistance to chemotherapy.Frontiers in oncology · 2022Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
10 authors at 2 institutions in 1 country.
Funding
Abstract
Based on our original RNA sequence-based microRNA (miRNA) signatures of head and neck squamous cell carcinoma (HNSCC), it was revealed that the expression levels of miR-1-3p, miR-206, miR-133a-3p, and miR-133b were significantly suppressed in cancer specimens. Seed sequences of miR-1-3p/miR-206 and miR-133a-3p/miR-133b are identical. Interestingly, miR-1-3p/miR-133a-3p and miR-206/miR-133b are clustered in the human genome. We hypothesized that the genes coordinately controlled by these miRNAs are closely involved in the malignant transformation of HNSCC. Our in silico analysis identified a total of 28 genes that had putative miR-1-3p/miR-133a-3p and miR-206/miR-133b binding sites. Moreover, their expression levels were upregulated in HNSCC tissues. Multivariate Cox regression analyses showed that expression of PFN2 and PSEN1 were independent prognostic factors for patients with HNSCC (p < 0.05). Notably, four miRNAs (i.e., miR-1-3p, miR-206, miR-133a-3p, and miR-133b) directly bound the 3′untranslated region of PFN2 and controlled expression of the gene in HNSCC cells. Overexpression of PFN2 was confirmed in clinical specimens, and its aberrant expression facilitated cancer cell migration and invasion abilities. Our miRNA-based strategy continues to uncover novel genes closely involved in the oncogenesis of HNSCC.
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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.