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Evaluation of RNA-sequencing (RNA-seq) signatures with pembrolizumab (pembro) in patients (pts) with renal cell carcinoma (RCC) from KEYNOTE-427 cohort A.

2020· article· en· W3007846944 on OpenAlexaff
David F. McDermott, Jae‐Lyun Lee, Georg A. Bjarnason, James Larkin, Rustem Gafanov, Mark D. Kochenderfer, Jahangeer Malik, Alexandr Poprach, Scott S. Tykodi, Sabina Signoretti, Rodolfo F. Perini, Jared Lunceford, Raluca Predoiu, Andrey Loboda, Qing Zhao, Alexandra Snyder, Charles Schloss, Michael B. Atkins

Bibliographic record

VenueJournal of Clinical Oncology · 2020
Typearticle
Languageen
FieldMedicine
TopicRenal cell carcinoma treatment
Canadian institutionsHealth Sciences CentreSunnybrook Health Science Centre
Fundersnot available
KeywordsMedicineCohortOncologyAngiogenesisStromal cellProportional hazards modelRNA-SeqInternal medicineRenal cell carcinomaCancer researchGene expressionTranscriptomeGeneBiologyGenetics

Abstract

fetched live from OpenAlex

729 Background: We evaluated the association (assoc) of baseline RNA-seq–based signatures with response/resistance to pembro from the phase 2 KEYNOTE-427 study (NCT02853344) in pts with advanced clear cell RCC enrolled in cohort A (n = 110). Methods: In pembro-treated pts with RNA-seq and clinical data (N = 78), we analyzed the assoc of signatures (18-gene tumor T-cell–inflamed GEP; 10 non–T-cell–inflamed GEP canonical signatures [angiogenesis, gMDSC, glycolysis, hypoxia, mMDSC, MYC, proliferation, RAS, stromal/EMT/TGFβ, WNT]) quantifying the TME with clinical outcomes. Canonical signatures were derived from 2 databases (TCGA, Moffit) using an algorithm that included genes based on their correlation to reference signatures in the literature. Signature definitions were finalized before linking to the clinical data, and significance was prespecified at 0.10 given the potential for limited power. Canonical signatures were also analyzed through regression testing of response and the residuals of consensus signatures after adjusting for T-cell–inflamed GEP and IMDC scores in the model. P values were adjusted for multiplicity. Database cutoff date for clinical data: March 12, 2019. Results: Pt characteristics for this analysis were similar to those of the overall cohort A population. T-cell–inflamed GEP was statistically significantly assoc with ORR ( P = 0.021) but not PFS ( P = 0.116). When adjusting for PD-L1 expression (CPS by IHC) and IMDC scores, T-cell–inflamed GEP remained statistically significantly assoc with ORR ( P = 0.059). The angiogenesis signature was not assoc with response. PD-L2 RNA-seq expression was not assoc with response with multiplicity-adjusted P values. Like PD-L1 IHC, PD-L2 RNA-seq expression moderately correlated with T-cell–inflamed GEP and did not show independent predictive value when adjusted for T-cell–inflamed GEP and IMDC scores. Conclusions: RNA-seq–based, T-cell–inflamed GEP was assoc with ORR in pts with clear cell RCC receiving first-line pembro monotherapy; no canonical signatures showed statistical significance. Future directions for these data include whole exome sequencing analysis. Clinical trial information: NCT02853344.

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

Direct model labels (unvalidated)

Per-model category and study-design labels from the labeling rounds. They are machine output, unvalidated, and the disagreement between models ships as data. No study design here is MEDLINE-validated yet.

Model armCategoriesStudy designConfidence
gemmano category
Domain: not available · Genre: Empirical
About the Canadian research system: no · About a Canadian topic: no
Observationallow
gptno category
Domain: not available · Genre: Empirical
About the Canadian research system: no · About a Canadian topic: no
Observationallow
models agreeAgreement compares identical category sets and study designs across arms.

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)0.001
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 score0.002
Threshold uncertainty score0.006

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0010.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0020.000

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 head0.114
GPT teacher head0.376
Teacher spread0.262 · 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

Labeled directly by 2 models reading the full record.

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 routes1
Has abstractyes

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