ArticleFrontiers in bioinformatics2025
Mutational insights and
Article in Frontiers in bioinformatics, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
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
0 citing papers in PubMed.
No citing paper in PubMed yet.
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
15 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Introduction: Oral squamous cell carcinoma (OSCC) is a prevalent malignancy characterized by aggressive behavior, poor prognosis, and limited therapeutic options. Mutations in the NIMA-related kinase (NEK) family are increasingly implicated in tumorigenesis across various cancers. However, their contributions to OSCC pathogenesis remain largely unexplored. Methods: Here, we employed whole-exome sequencing (WES) of formalin-fixed paraffin-embedded (FFPE) tissue blocks from 31 OSCC tumors and 9 adjacent paired normal samples derived from patients of Khyber Pakhtunkhwa (KP), Pakistan, to systematically profile Results: We identified 46 mutations overall (78.3% (36/46) somatic, 21.7% (10/46) germline), consisting of 82.6% (38/46) non-synonymous single-nucleotide variants (SNVs), 10.9% (5/46) frameshift deletions, 2.2% (1/26) non-frameshift deletions, and 4.3% (2/46) stop-gain mutations; notably, 10.9% (5/46) represented novel variants (not reported previously). NEK1 displayed the highest mutation frequency, followed by Conclusion: Collectively, these findings suggest
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.