Abstract A063: What can we learn from a retrospective evaluation of HER2, P53 and P16INK4A protein expression in rare ovarian tumors?
Bibliographic record
Abstract
Abstract In this retrospective study, we examined the incidence and prevalence of HER2, P53, and P16INK4A protein accumulation patterns in patients diagnosed with rare ovarian cancer. The population-based study included a total of thirteen patients diagnosed at the Saskatoon Cancer Centre during the years 1983-1995. Immunohistochemistry for evaluation of HER2, P53 and P16INK4A protein expression and ploidy status in paraffin-embedded tissue (PET) specimens were correlated with clinicopathologic variables. Immunoexpression studies were with the following rabbit monoclonal antibodies: Erb-B2, 485 and P16INK4A, G175-405, 13251A, except for P53, mouse monoclonal antibody, D07. DNA status was assessed by flow-cytometric analysis. The most prevalent histologic subtype was sex-cord stromal, followed by three germ-cell, while the remaining two tumors were malignant Brenner. The patients’ ages ranged between (15-77 years). The data on stage was unavailable in five patients, two patients had undifferentiated tumor, one had grade 2-3, and data on grade was unavailable in the remaining six cases. Two of the 13 patients died: one patient in stage IV, grade 3, granulosa-theca, P53 immunonegative and near-tetraploid DNA status; the other patient with malignant Brenner histologic subtype, P53 overexpression, and diploid DNA status. Tumor tissues were available in nine of 13 randomly selected patients. Except for one case with P53 overexpression, the remaining 89% tumor specimens had low to zero P53, P16INK4A, and Erb-B2 expression. The nonsignificance of the immunoexpression studies and preclusion from prognostic prediction is likely due to the restricted sample size. Thus, immunoexpression of P53, P16INK4A, and Erb-B2 have not been associated with rare ovarian tumors. Moreover, the observation that malignant Brenner had P53 overexpression and diploid DNA status in one of the patients is a significant finding of this retrospective study. Additionally, these findings argue for routine use of P53 protein expression and ploidy status in the assessment of malignant Brenner tumors. The vast majority of tumors with P53 mutations progress rapidly. Therefore, the subset of patients with malignant Brenner tumors that have P53 protein disruption will likely benefit from therapy using PARP inhibitors. A. Geissel and J. L. Griffin, “Preparation of nuclei for flow cytometry,” in AFIP Advances in Laboratory methods in Histology and Pathology, ed. Mikel UV (Washington DC: American Registry of Pathology, 1944), 111-121. Citation Format: Kavitha M. Advikolanu-Rao, Anthony M. Magliocco, Andrew W. Maksymiuk. What can we learn from a retrospective evaluation of HER2, P53 and P16INK4A protein expression in rare ovarian tumors? [abstract]. In: Proceedings of the AACR Special Conference on Ovarian Cancer; 2023 Oct 5-7; Boston, Massachusetts. Philadelphia (PA): AACR; Cancer Res 2024;84(5 Suppl_2):Abstract nr A063.
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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 | 0.005 | 0.018 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".