A genome-wide association scan of biological processes involved in oral lichen planus and oral squamous cell carcinoma
Bibliographic record
Abstract
BACKGROUND: In this study, the molecular mechanisms underlying malignant transformation from oral lichen planus (OLP) to oral squamous cell carcinoma (OSCC) were examined. METHODS: High-throughput sequencing of long noncoding RNAs (lncRNAs) and mRNAs of normal subjects and patients with OLP and OSCC was conducted. RNA-seq reads were mapped, lncRNA and mRNA transcripts were assembled, and expression levels were estimated. The targets of lncRNAs were predicted. Finally, Gene Ontology (GO) and pathway enrichment analyses of differentially expressed genes (DEGs) and lncRNA targets were performed. RESULTS: High-quality sequence data were generated and the mapping ratios for OSCC, normal, and OLP samples were high. In total, 820, 656, and 582 DEGs were obtained from OPL vs. normal, OSCC vs. normal, and OSCC vs. OPL, respectively. A total of 1721 known lncRNAs and 133 predicted lncRNAs and targets were obtained. Keratinization was significantly enriched by OSCC-related DEGs, but not OPL-related DEGs. The pathway of olfactory transduction was enriched by OPL- and OSCC-related DEGs. Defense response to virus and viral carcinogenesis were enriched by DEGs and lncRNA targets in all comparisons. GO term related to the metabolic process was enriched by lncRNA targets in the OPL vs normal comparison, and antigen processing and presentation via MHC class I was significantly enriched by lncRNA targets in the other 2 comparisons. CONCLUSION: Keratinization and MHC class I antigen processing and presentation were activated during the malignant transformation from OLP to OSCC. Additionally, the olfactory transduction pathway may be important for OSCC.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".