Comprehensive Genomic Review of TCGA Head and Neck Squamous Cell Carcinomas (HNSCC)
Bibliographic record
Abstract
The aim of this present study was to comprehensively describe somatic DNA alterations and transcriptional alterations in the last extension of the HNSCC subsets in TCGA, encompassing a total of 528 tumours. In order to achieve this goal, transcriptional analysis, functional enrichment assays, survival analysis, somatic copy number alteration analysis and somatic alteration analysis were carried out. A total of 3491 deregulated genes were found in HNSCC patients, and the functional analysis carried out determined that tissue development and cell differentiation were the most relevant signalling pathways in upregulated and downregulated genes, respectively. Somatic copy number alteration analysis showed a “top five” altered HNSCC genes: CDKN2A (deleted in 32.03% of patients), CDKN2B (deleted in 28.34% of patients), PPFIA1 (amplified in 26.02% of patients), FADD (amplified in 25.63% of patients) and ANO1 (amplified in 25.44% of patients). Somatic mutations analysis revealed TP53 mutation in 72% of the tumour samples followed by TTN (39%), FAT1 (23%) and MUC16 (19%). Another interesting result is the mutual exclusivity pattern that was discovered between the TP53 and PIK3CA mutations, and the co-occurrence of CDKN2A with the TP53 and FAT1 alterations. On analysis to relate differential expression genes and somatic copy number alterations, some genes were overexpressed and amplified, for example, FOXL2, but other deleted genes also showed overexpression, such as CDKN2A. Survival analysis revealed that overexpression of some oncogenes, such as EGFR, CDK6 or CDK4 were associated with poorer prognosis tumours. These new findings help us to develop new therapies and programs for the prevention of HNSCC.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.005 | 0.005 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 0.001 |
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 source (direct Gemma or distilled Codex), 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".