Bibliographic record
Abstract
Background: Squamous carcinomas of the uterine cervix often carry mutations of the gene encoding for the catalytic sub-unit of kinase PI3K, PIK3CA. The locus of this gene at chromosome 3q26 and neighboring loci are also commonly amplified. The landscape of 3q26-amplified cases have not been previously characterized in detail in cervical cancer. Methods: Published genomic data and associated clinical data from TCGA cervical cancer cohort were analyzed at cBioportal for amplifications in genes at 3q26. The clinical and molecular characteristics of the group of patients with 3q26 amplifications was compared with the group without 3q26 amplifications. Comparative prevalence of amplification and expression of genes at 3q26 in amplified squamous cervical cancer cases were surveyed as well as 3q26 amplifications in cervical cancer cell line databases. Results: Amplification of 3q26 locus is a prevalent molecular lesion in cervical squamous cell carcinomas encountered in about 15% of cases in TCGA cohort of 247 patients. Cancer-related genes commonly amplified from 3q26 include PIK3CA, TBL1XR1, DCUN1D1, SOX2, MECOM, PRKCI, and TERC. Amplified cases do not completely overlap with PIK3CA mutant cases. Differences exist between 3q26-amplified and non-amplified carcinomas in the frequency of mutations and frequency of other amplifications. Most commonly over-expressed genes in 3q26 amplified cases include PIK3CA, TBL1XR1, DCUN1D1, and less commonly SOX2 and PRKCI. Conclusion: The subset of squamous cervical carcinomas with 3q26 amplifications is not overlapping with cancers carrying PIK3CA mutations and contains, besides PIK3CA, other cancer-associated genes that are over-expressed at the mRNA level, including TBL1XR1 and DCUN1D1. DCUN1D1, a regulator of SCF ubiquitin ligase activity, may be a relevant pathogenic player given the importance of ubiquitination and the proteasome in the disease. These observations could form the basis for therapeutic exploitation in this subset of squamous cervical carcinomas.
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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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.003 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.004 | 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".