Correlative Assessment of p53 Immunostaining Patterns and TP53 Mutation Status by Next-Generation Sequencing in High-Grade Endometrial Carcinomas
Bibliographic record
Abstract
TP53 mutations are frequently identified in the copy number-high molecular subgroup of endometrial carcinomas (ECs). P53 immunohistochemistry (IHC) is a widely used surrogate marker reflecting the mutational status of TP53 , and recent reports have shown ~95% concordance between the two methods in ECs. While these results are promising, studies evaluating the correlation between different p53 IHC staining patterns and comprehensive next-generation sequencing results are still limited. We compared the p53 IHC staining patterns, scored as wild-type, diffuse nuclear overexpression, null/complete absence, and cytoplasmic, to next-generation sequencing results reported by FoundationOneCDx in 43 high-grade ECs: 20 serous ECs, 9 mixed ECs with a serous component, 4 carcinosarcomas with a serous component, and 10 grade 3 endometrioid ECs. The concordance of p53 IHC and TP53 mutation status was 100% (43/43) overall, including 100% (33/33) concordance in tumors with a serous component and 100% (10/10) in endometrioid ECs. Among the 35 tumors with aberrant p53 expression the most commonly observed pattern was diffuse nuclear overexpression seen in 69% (24/35), followed by cytoplasmic staining in 17% (6/35), and complete absence of staining (null) in 14% (5/35) of tumors. Of the 6 tumors with cytoplasmic staining, 4 corresponded to missense mutations within the DNA binding domain (V157F in 2 tumors, and S127P and R280S, in 2 tumor each), while 2 corresponded to nonsense mutations in the tetramerization domain (p.E339*). Our results further support that p53 IHC can serve as an accurate predictor of TP53 alterations in ECs to aid the molecular-based tumor classification and the distinction between tumor histotypes, both of which play an important role in the assessment of clinical prognosis and therapeutic decision making. In addition, our data suggest, that the type and position of TP53 mutation may not directly correlate with the observed p53 IHC pattern in all tumors, and that there may be alternative mechanisms for cytoplasmic localization (other than mutations involving the nuclear localization domain), possibly due to conformational changes or posttranslational modifications of the aberrant p53 protein.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 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 | 0.001 |
| 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".