Abstract 1535: Immunohistochemistry predicts presence and type of TP53 mutation in high-grade serous carcinoma
Bibliographic record
Abstract
Abstract TP53 mutations are ubiquitous to ovarian high-grade serous carcinomas (HGSC) but uncommon in other types such as endometrioid carcinomas. Despite the advances in direct sequencing, this technology is not widely available for routine diagnostics. Significant improvements in standardization of immunohistochemistry (IHC) have dramatically improved sensitivity. We hypothesized that the pattern of p53 expression by IHC can predict the presence and group of TP53 mutations: complete absence indicating null mutations versus overexpression indicating missense mutation. DNA extracted from 91 fresh frozen HGSC samples obtained from the Canadian Ovarian Experimental Unified Resource (COEUR) and from 66 formalin fixed paraffin embedded HGSC samples obtained from Calgary Laboratory Services were sequenced using TAmSeq methods for NGS. Additional Sanger sequencing was performed for confirmation or for identification of indel mutations. Accompanying tissue microarrays with 0.6 mm cores were constructed and immunohistochemistry for p53 was performed on a Leica Bond MAX platform using the DO-7 monoclonal antibody. The expression of p53 was scored in a 3-tier system: complete absence, wild type (any staining from 1-70%), overexpression (>70% strong nuclear staining). Cytoplasmic localization was noted separately. TP53 mutations were detected in 147/157 HGSC (94%). The type of mutation in descending order were missense 104/147 (71%), frameshift 17/147 (12%), stopgain 13/147 (9%), and splice site 13/147 (13%). 101/104 cases with TP53 missense mutations showed p53 overexpression (98% concordance) while 12/17 cases with frameshift, 11/13 cases with stopgain, and 7/13 with splicing (combined 70% concordance) showed the expected complete absence of p53 expression. The overall sensitivity of p53 IHC to predict the group of mutation was 89% (131/147). Only 6/147 (4%) cases with TP53 mutations showed a p53 wild type pattern, four those were splice site mutations, hence the sensitivity of p53 IHC to predict the presence of mutation is 94%. Interestingly, 7/10 cases with TP53 wild type or synonymous silent mutations showed aberrant p53 expression as either complete absence or overexpression, suggesting alternative abnormalities in the p53 pathway. The three cases with TP53 wild type and p53 wild type expression may not be HGSC. We conclude that contemporary p53 immunohistochemistry is a useful, widely accessible, inexpensive complimentary test for direct TP53 sequencing. Citation Format: Martin Köbel, Anna Piskorz, Shuhong Liu, James D. Brenton. Immunohistochemistry predicts presence and type of TP53 mutation in high-grade serous carcinoma. [abstract]. In: Proceedings of the 105th Annual Meeting of the American Association for Cancer Research; 2014 Apr 5-9; San Diego, CA. Philadelphia (PA): AACR; Cancer Res 2014;74(19 Suppl):Abstract nr 1535. doi:10.1158/1538-7445.AM2014-1535
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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) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| 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) | 0.005 | 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".