Sequencing of Candidate Chromosome Instability Genes in Endometrial Cancers Reveals Somatic Mutations in ESCO1, CHTF18, and MRE11A
Bibliographic record
Abstract
Most endometrial cancers can be classified histologically as endometrioid, serous, or clear cell. Non-endometrioid endometrial cancers (NEECs; serous and clear cell) are the most clinically aggressive of the three major histotypes and are characterized by aneuploidy, a feature of chromosome instability. The genetic alterations that underlie chromosome instability in endometrial cancer are poorly understood. In the present study, we used Sanger sequencing to search for nucleotide variants in the coding exons and splice junctions of 21 candidate chromosome instability genes, including 19 genes implicated in sister chromatid cohesion, from 24 primary, microsatellite-stable NEECs. Somatic mutations were verified by sequencing matched normal DNAs. We subsequently resequenced mutated genes from 41 additional NEECs as well as 42 endometrioid ECs (EECs). We uncovered nonsynonymous somatic mutations in ESCO1, CHTF18, and MRE11A in, respectively, 3.7% (4 of 107), 1.9% (2 of 107), and 1.9% (2 of 107) of endometrial tumors. Overall, 7.7% (5 of 65) of NEECs and 2.4% (1 of 42) of EECs had somatically mutated one or more of the three genes. A subset of mutations are predicted to impact protein function. The co-occurrence of somatic mutations in ESCO1 and CHTF18 was statistically significant (P = 0.0011, two-tailed Fisher's exact test). This is the first report of somatic mutations within ESCO1 and CHTF18 in endometrial tumors and of MRE11A mutations in microsatellite-stable endometrial tumors. Our findings warrant future studies to determine whether these mutations are driver events that contribute to the pathogenesis of endometrial cancer.
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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 | 0.000 | 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 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".