Targeted Molecular and Immunohistochemical Analyses of Endometrial Clear Cell Carcinoma Show that POLE Mutations and DNA Mismatch Repair Protein Deficiencies Are Uncommon
Bibliographic record
Abstract
Endometrial clear cell carcinoma (ECCC) is an uncommon histotype without unique identified molecular alterations. Recently, The Cancer Genome Atlas molecular subtypes have been reported in ECCC. ECCC cases were collected from 11 institutions with diagnoses confirmed by morphologic review and immunohistochemistry. DNA mismatch repair (MMR) proteins, p53 expression, and ARID1A expression was assessed by immunohistochemistry on tissue microarrays. Targeted next-generation sequencing was completed for POLE, TP53, KRAS, and PIK3CA. Pathogenicity of mutations was determined using MutationTaster and PolyPhen databases. For p53, immunohistochemistry and sequencing were complimentarily used to assess the p53 status. Of 57 cases, 46 were considered prototypical ECCC by morphology and immunohistochemical profile (Napsin A-positive and ER-negative). Three cases were excluded because of insufficient sample for complete immunohistochemical analysis, and 6 had failed sequencing, resulting in 37 cases. Of the 37 remaining cases, 6/37 (16%) had predicted pathogenic mutations in the exonuclease domain of POLE with an allelic frequency >10%; however, no hot-spot mutations were identified. No cases were MMR-deficient. The gene most commonly affected was TP53 (59%, 22/37), followed by KRAS (13%, 2/15) and PIK3CA (13%, 2/15). The current study is the largest molecular analysis of pure ECCC reported to date. When strict classification criteria are applied, MMR-deficient and POLE mutated subtypes are not represented. Further consensus on what represents a deleterious POLE mutations is needed. The findings support separately studying histologically/immunohistochemically defined ECCC to identify characteristic molecular alterations in future studies.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| 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) | 0.001 | 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".