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Feasibility of a platform trial based on molecular analysis in rare gynecologic cancers.

2019· article· en· W2947454850 on OpenAlexaff
Jubilee Brown, John Farley, Thomas J. Herzog, Erin K. Crane, Al Covens, David Arguello, Pilar Ramos, Wangjuh Chen, Adam C. ElNaggar

Bibliographic record

VenueJournal of Clinical Oncology · 2019
Typearticle
Languageen
FieldMedicine
TopicOvarian cancer diagnosis and treatment
Canadian institutionsHealth Sciences CentreSunnybrook Health Science Centre
Fundersnot available
KeywordsMedicineKRASPTENSerous fluidCDKN2AClear cellCarcinosarcomaARID1AOncologyEndometrial cancerInternal medicineGerm cell tumorsCancer researchCancerPI3K/AKT/mTOR pathwayCarcinomaChemotherapyColorectal cancerBiology

Abstract

fetched live from OpenAlex

e14585 Background: Challenges in patient accrual limit successful conduct of clinical trials in rare gynecologic malignancies. A platform trial using molecular analysis to guide therapy choice would optimize enrollment but would require actionable mutations (AM) to be feasible. Therefore, we sought to determine if enough AMs exist in rare gynecologic cancers (CA) to justify the design of a platform trial. Methods: We compiled all molecular profiling data performed at Caris Life Sciences through February 2019. Non-epithelial ovarian cancer (OC), rare epithelial OC, non-endometrioid uterine, neuroendocrine gynecologic, and vulvar CA were compiled. AMs were identified. Results: Among 280 cases of non-epithelial OC, 228 malignant stromal tumors and 52 germ cell tumors were identified. AMs in stromal tumors included KMT2D (9.8%), PIK3CA (7.8%), and 16 other AMs ( < 1% each). AMs in germ cell tumors included PIK3CA (20%), KIT (10%), PTEN (10%), TMB (8.2%), CDKN2A (8%), ARID1A (6%), and 16 other AMs ( < 6% each). Among 702 rare epithelial OCs, 132 mucinous CAs, 91 low-grade serous/endometrioid, 367 clear cell, and 112 carcinosarcoma (CS) cases were identified. AMs in mucinous CAs included KRAS (61.8%), CDKN2A (15.3%), PIK3CA (12.7%), ARID1A (9.9%), GNAS (6.9%), and 20 other AMs ( < 5% each). AMs in low-grade serous/endometrioid included KRAS (28.9%), ARID1A (13.3%), PTEN (8.9%), PIK3CA (7.8%), MSI (6.2%), and 15 other AMs ( < 6% each). AMs in clear cell OCs included ARID1A (53.4%), PIK3CA (47.5%), KRAS (11.6%), PTEN (6.8%), and 36 other AMs ( < 6% each). AMs in ovarian CSs included PIK3CA (7.2%), ARID1A (6.2%), and 22 other AMs ( < 5% each). Among 4864 rare uterine CA, 4670 sarcomas, 173 serous CAs, and 21 clear cell CAs were identified. AMs in uterine sarcomas included PTEN (40.1%), PIK3CA (37.1%), ARID1A (31.6%), MSI (20.7%), KRAS (16.8%), TMB (14%), PIK3R1 (10%), and 41 other AMs ( < 10% each). Among 102 gynecologic neuroendocrine tumors, AMs included ARID1A (29.2%), PIK3CA (18%), PTEN (18%), MSI (6.5%), TMB (6%), and 4 other AMs ( < 6% each). Among 59 vulvar CAs, AMs included CDKN2A (28.7%), PIK3CA (17.8%), NOTCH1 (9.6%), TMB (6.8%), and 24 other AMs ( < 5% each). Conclusions: A variety of actionable mutations are present in every type of rare gynecologic cancer evaluated, but mutations specific to individual histologies are not reliably present. This supports the use of molecular profiling to identify potential targets and supports a platform trial strategy to study rare gynecologic cancers.

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)0.019
metaresearch head score (Gemma)0.020
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Simulation or modeling · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.019
Threshold uncertainty score0.099

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0190.020
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.002
Bibliometrics0.0010.001
Science and technology studies0.0000.001
Scholarly communication0.0010.002
Open science0.0010.001
Research integrity0.0020.002
Insufficient payload (model declined to judge)0.0090.001

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.

Opus teacher head0.155
GPT teacher head0.486
Teacher spread0.330 · 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 designSimulation or modeling
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
Published2019
Admission routes1
Has abstractyes

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