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Integrative molecular profiling and response to chemotherapy on the COMPASS trial.

2019· article· en· W2913218375 on OpenAlexaff
Grainne M. O’Kane, Sandra E. Fischer, Rob Denroche, Gun Ho Jang, Amy Zhang, Anna Dodd, Robert C. Grant, Barbara T. Grünwald, Mehdi Masoomian, Shari Moura, Elena Elimova, Rebecca M. Prince, George Zogopoulos, Faiyaz Notta, Julie M. Wilson, Steven Gallinger, Jennifer J. Knox

Bibliographic record

VenueJournal of Clinical Oncology · 2019
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicCancer Genomics and Diagnostics
Canadian institutionsMcGill University Health CentreUniversity Health NetworkToronto General HospitalUniversity of TorontoOntario Institute for Cancer ResearchPrincess Margaret Cancer Centre
Fundersnot available
KeywordsMedicineInternal medicineChemotherapyOncologyPopulationCohortBiopsyPathology

Abstract

fetched live from OpenAlex

188 Background: Predictive mutational and transcriptional features in advanced PDAC are needed for improved patient stratification and treatment selection. Methods: Patients (pts) on the COMPASS trial with advanced PDAC are prospectively recruited prior to first-line chemotherapy for WGS and RNAseq. Tumor tissue undergoes enrichment by laser capture microdissection with genomic analyses available within eight wks. Tumor responses and clinical outcomes in this maturing cohort were correlated with molecular characteristics. Results: 157 pts underwent a tumor biopsy between Dec 2015 and Jul 2018 with over 95% success in achieving results. 141 genomes have been reported in pts planned to receive chemotherapy; the median time from biopsy to report was 35.5 days. In the ITT population,118 pts are summarised for first-line response. The median age was 63 yrs (29-81), 55% were male, and 16% had locally advanced disease. 66 (56%) received modified FFX as first-line treatment. 25 (21%) tumors displayed the Moffitt basal-like RNA signature which associated with chemotherapy resistance, with tumor shrinkage mainly observed in the classical RNA subtype (p = 0.002). GATA6 expression (log10 scale) clearly separated Moffitt subgroups with classical tumors exhibiting high expression (p < 0.0001). GATA6 in situ hybridization strongly correlated with RNAseq, (r = 0.89, p < 0.001) with strong correlation also seen with GATA6 IHC. The median overall survival (OS) in the classical group was 8.5 mths vs. 6.6 mths in the basal-like group (HR 0.53, 95% CI 0.32-0.89 p = 0.015). In those treated with mFFX, median OS was 10.1mths in classical versus 6.6mths in the basal-like subtypes, (HR 0.32, 95% CI 0.16-0.63, p=0.001). 30% of pts had potentially actionable genetic alterations including BRAF variants (n = 4) and an NTRK3-EML4 fusion in KRAS WT tumors (8%). Signatures of homologous recombination deficiency (HRD) were found in seven pts; two additional pts with BRCA germline variants did not exhibit somatic HRD hallmarks. Conclusions: Subsets of pts with advanced PDAC have actionable variants including those with HRD signatures and patients with KRAS WT tumors. GATA6 is a putative predictive biomarker of transcriptomic subgroups which should be incorporated in clinical trials. Clinical trial information: NCT02750657.

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)0.001
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 score0.005
Threshold uncertainty score0.016

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0010.000
Open science0.0000.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0050.001

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 head0.051
GPT teacher head0.425
Teacher spread0.374 · 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

Citations15
Published2019
Admission routes1
Has abstractyes

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