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Molecular-based classification algorithm for endometrial carcinoma to categorize ovarian endometrioid carcinoma into prognostically significant groups.

2017· article· en· W2890234755 on OpenAlexaff
Carlos Parra‐Herran, Jordan Lerner‐Ellis, Bin Xu, Dina Bassiouny, Matthew Cesari, Nadia Ismiil, Sharon Nofech‐Mozes

Bibliographic record

VenueJournal of Clinical Oncology · 2017
Typearticle
Languageen
FieldMedicine
TopicEndometrial and Cervical Cancer Treatments
Canadian institutionsHealth Sciences CentreUniversity of TorontoMount Sinai HospitalSunnybrook Health Science Centre
Fundersnot available
KeywordsMedicineCarcinomaOncologyMSH2Endometrial cancerMSH6Serous carcinomaInternal medicineMLH1Ovarian cancerOvarian carcinomaSerous fluidImmunohistochemistryPathologyCancerDNA mismatch repairColorectal cancer

Abstract

fetched live from OpenAlex

e17081 Background: The Cancer Genome Atlas classification divides endometrial carcinoma in biologically distinct groups, and testing for p53, mismatch repair proteins (MMR) and polymerase ɛ (POLE) exonuclease domain mutations has been shown to predict the molecular subgroup and clinical outcome. While abnormalities in these markers have been described in ovarian endometrioid carcinoma (OEC), their role in predicting its molecular profile and prognosis is still not fully explored. Methods: OECs resected in a 14 year period were retrieved. Only tumors with confirmed endometrioid histology and negative WT1 were included. POLE mutational analysis and immunohistochemistry for p53, MLH1, MSH2, MSH6 and PMS2 was performed in formalin-fixed, paraffin-embedded tissue. Following the molecular classifier proposed for endometrial carcinoma ( B J Cancer 2015;113:299-310), cases were classified as: POLE mutated, MMR abnormal, p53 abnormal and p53 wild type. Clinicopathologic information was recorded including patient outcome. Results: 73 tumors were successfully reviewed and tested. Of these, 8 (11%) were POLE mutated, 6 (8%) were MMR abnormal and 17 (23%) were p53 abnormal; the remaining 42 cases (58%) were p53 wild type (no POLE, p53 or MMR abnormalities). Mean follow-up period was 69 months (median 62, range 1-179). The molecular classification was an independent predictor for disease free and overall survival on multivariate analysis (p = 0.005 and 0.045 respectively, Cox proportional hazard model). POLE mutated and MMR abnormal groups had 100% 5 year DFS and OS. p53 wild type cases had intermediate survival rates (86% DFS and OS). Conversely, the p53 abnormal group had worse outcomes with 42% DFS and 76% OS at 5 years. Conclusions: OEC can be classified into prognostically distinct subgroups by testing for molecular surrogates, akin to endometrial cancer. MMR and POLE alterations seem to identify a subset of ovarian endometrioid carcinomas with excellent outcome; conversely, abnormal p53 expression carries a worse prognosis. In the era of personalized medicine, the use of these markers in the routine evaluation of ovarian endometrioid tumors should be considered.

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)0.002
metaresearch head score (Gemma)0.006
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: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.007
Threshold uncertainty score0.024

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.006
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0060.002
Science and technology studies0.0010.000
Scholarly communication0.0020.001
Open science0.0010.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0070.003

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 head0.148
GPT teacher head0.450
Teacher spread0.301 · 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".

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Citations0
Published2017
Admission routes1
Has abstractyes

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