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Abstract PR-2: Investigation of mismatch repair deficiency in ovarian cancers

2008· article· en· W2328839624 on OpenAlexaff
Tuya Pal, Domenico Coppola, Santo V. Nicosia, Shiyu Zhang, Ji‐Hyun Lee, Jenny Permuth Wey, Rebecca Sutphen, Joellen Schildkraut, Steven A. Narod, Thomas A. Sellers

Bibliographic record

VenueCancer Prevention Research · 2008
Typearticle
Languageen
FieldMedicine
TopicGenetic factors in colorectal cancer
Canadian institutionsWomen's College Hospital
Fundersnot available
KeywordsMicrosatellite instabilityMSH2MLH1MSH6Tissue microarrayLynch syndromeDNA mismatch repairOvarian cancerOncologyImmunohistochemistryColorectal cancerCancerMedicinePMS2PopulationInternal medicineCancer researchBiologyPathologyGeneticsMicrosatellite

Abstract

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Abstract PR-2 Background Defects in the mismatch repair (MMR) pathway are believed to be etiologically important in a reasonable proportion of epithelial ovarian cancers. Various laboratory methods can be used to identify MMR-deficient ovarian cancers, including microsatellite instability (MSI) analysis and immunohistochemistry (IHC). Specifically, in colorectal cancers (CRC), tumor characteristics previously shown to be useful in identifying MMR-deficient tumors include MSI-high (MSI-H) phenotype and loss of MMR protein expression on IHC analyses. Similar findings have been demonstrated in ovarian cancer, however the sample sizes of those studies have been limited. Objectives/Methods We sought to investigate tumor characteristics including: (1) MSI-high status, (2) Expression of 3 MMR proteins (MLH1, MSH2, and MSH6) through IHC studies, and (3) The concordance between MSI and IHC results. The tumors analyzed came from women between the ages of 18 and 80 years with newly-diagnosed epithelial ovarian cancer ascertained between December 13, 2000 and September 30, 2003in a population-based study covering a 2-county region of west central Florida. MSI-H was defined by instability in 2 or more of the 5 NCI-standardized microsatellite markers (ie: BAT25, BAT26, D2S123, D17D250, D5S346). Tissue microarrays were created to evaluate the loss of MMR protein expression on IHC based on a scoring system of 0-9 to evaluate both stain and intensity, and take the product of these 2 numbers; loss of expression of protein expression was defined as <3). These interim results are part of a larger multicenter study, currently underway, to investigate the clinical relevance of the MMR pathway in a population-based sample of ovarian cancers, including MSI analysis, IHC studies, MLH1 promoter hypermethylation, and germline mutation analysis of the MMR genes. Results Of the 232 who agreed to participation, tumor samples were collected on 219 (94%). The distribution of by race and ethnicity of study participants was similar to the distribution of cancer cases in the catchment area, with ~90% of participants being non-Hispanic Whites. The distribution of histologic subtypes, stage and median age at diagnosis was also similar to that seen in the general population. Of the 219 cases, all had IHC analysis and 201 had MSI analysis. The frequency of MSI-H was 29%. The frequency of loss of expression on IHC was 17%. The numbers of tumors which were concordant for MSI and IHC results was 141 (including 16 cases with MSI-H and loss of MMR protein expression and 125 cases with no MSI-H and presence of MMR protein expression). Conversely, there were 60 discordant cases (including 42 cases which were MSI-H, but MMR protein expression was present; and 18 cases which were not MSI-H, with loss of MMR protein expression). Conclusions In contrast to previous studies of CRC, our results indicate limited concordance between MSI-H status and loss of MMR protein expression. Thus, MSI analysis and IHC studies for MMR protein expression may be of limited utility in the identification of ovarian tumors with MMR deficiency. Citation Information: Cancer Prev Res 2008;1(7 Suppl):PR-2.

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How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.121
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
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 head0.156
GPT teacher head0.421
Teacher spread0.265 · 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 teacher head, not a consensus.

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".

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Citations0
Published2008
Admission routes1
Has abstractyes

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