Abstract 3537: Evaluation of genomic instability using microsatellite instability, ploidy status, and p53 expression in archival paraffin embedded tissue from primary ovarian cancer specimens
Bibliographic record
Abstract
Abstract A retrospective study of a subset of ovarian cancer cases was evaluated to assess the role of microsatellite instability (MSI) and ploidy status. P53 function is important in the regulation of genomic stability and its expression was examined by immuno-histochemical staining. Genomic instability is also considered a possible indicator of immuno-therapy responsive tumors. Ovarian cancer patients diagnosed between 1983 to 1987 at Saskatoon Cancer Center, Canada, were evaluated for genomic stability. Nearly 400 Epithelial Ovarian Cancer (EOC) cases were reviewed, and Paraffin Embedded Tissue (PET) blocks from 112 cases were retrieved from hospitals in the region. PET blocks containing over 70% neoplastic tissue were chosen for the study. P53 expression was determined in eighteen cases using the mouse monoclonal antibody D07. An assessment of MSI and LOH was performed using the PCR mixes from Perkin Elmer (PE) AB. The replication error repair (RER)/Loss of Heterozygosity (LOH) assays were performed at nine loci using the primers obtained from PE. Fourteen out of eighteen cases were evaluated for ploidy status using a method described in literature[1]. Statistical analyses were performed to determine the significance of MSI/LOH, ploidy status, and p53 expression. In this study, 34 (30%) of 112 EOC cases were found to be aneuploid. Fourteen EOC cases had ploidy status that could be evaluated. Of the eighteen patients analyzed for MSI, at least nine patients showed instability at one or more loci. Of these nine, there were two RER positive phenotypes with aneuploid DNA content which were also p53 immuno-negative. Of the seven (78%) RER negative tumors, 57% (4/7) p53 negative, and the remaining three cases overexpressed p53. In five EOC cases, with an RER negative phenotype, 60% (3/5) were aneuploid and 40% (2/5) were diploid. Furthermore, LOH was a common event at the nine loci. The three events: MSI, lack of p53 overexpression, and aneuploidy, may be characteristics of a subset of ovarian cancer cases. Secondly, the study suggests that RER positivity occurs in ovarian cancer pathogenesis. We conclude that the data indicates general genomic instability due to MSI and DNA ploidy status. [1] 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, 1994), 111-121. Citation Format: Kavitha Advikolanu Rao, Anthony M. Magliocco, Andrew W. Maksymiuk. Evaluation of genomic instability using microsatellite instability, ploidy status, and p53 expression in archival paraffin embedded tissue from primary ovarian cancer specimens [abstract]. In: Proceedings of the Annual Meeting of the American Association for Cancer Research 2020; 2020 Apr 27-28 and Jun 22-24. Philadelphia (PA): AACR; Cancer Res 2020;80(16 Suppl):Abstract nr 3537.
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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 | 0.001 | 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) | 0.001 | 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".