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Record W3083639628 · doi:10.1158/1538-7445.am2020-3537

Abstract 3537: Evaluation of genomic instability using microsatellite instability, ploidy status, and p53 expression in archival paraffin embedded tissue from primary ovarian cancer specimens

2020· article· en· W3083639628 on OpenAlexaffabout
Kavitha Advikolanu Rao, Anthony Magliocco, Andrew W. Maksymiuk

Bibliographic record

VenueCancer Research · 2020
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicCancer Genomics and Diagnostics
Canadian institutionsCancerCare Manitoba
Fundersnot available
KeywordsMicrosatellite instabilityLoss of heterozygosityGenome instabilityBiologyCancerOvarian cancerImmunohistochemistryPloidyPathologyAneuploidyCancer researchMicrosatelliteMedicineDNAGeneticsGeneDNA damageChromosome

Abstract

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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.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.001
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.001
Threshold uncertainty score0.004

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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.

Opus teacher head0.098
GPT teacher head0.392
Teacher spread0.295 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

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".

Quick stats

Citations0
Published2020
Admission routes2
Has abstractyes

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