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Comprehensive genomic analysis in metastatic pancreatic ductal adenocarcinoma (PDAC).

2016· article· en· W2591529322 on OpenAlexaff
Hui‐Li Wong, Martin Jones, Peter Eirew, Joanna M. Karasinska, Kasmintan A. Schrader, Howard J. Lim, Yaoqing Shen, Steven J.M. Jones, Stephen Yip, Janessa Laskin, Marco A. Marra, David F. Schaeffer, Daniel J. Renouf

Bibliographic record

VenueJournal of Clinical Oncology · 2016
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicCancer Genomics and Diagnostics
Canadian institutionsVancouver General HospitalUniversity of British ColumbiaPancreas Centre (Canada)BC Cancer Agency
Fundersnot available
KeywordsKRASCDKN2AMedicineTranscriptomeCancerSubtypingOncologyCancer researchBiopsyInternal medicineGenePathologyGene expressionColorectal cancerBiologyGenetics

Abstract

fetched live from OpenAlex

285 Background: In the absence of defined tumor molecular subtypes and validated predictive markers, PDAC has been largely treated as a single disease. Recent studies of molecular subtyping in PDAC reveal a complex mutational landscape with data suggesting the presence of genomic and gene expression signatures that may have prognostic and therapeutic significance. These studies predominantly focused on resected PDAC and lack data on metastatic tumors. We aim to explore the clinical utility of whole genome sequencing (WGS) and transcriptome analysis from metastatic biopsy samples in patients (pts) with advanced PDAC. Methods: Pts with incurable advanced cancers undergo tumor biopsy for in-depth WGS and RNA sequencing (RNASeq) as part of an ongoing prospective study (NCT02155621). Comprehensive bioinformatics analysis is performed to identify somatic cancer aberrations, gene expression changes and cellular pathway abnormalities. Here we describe clinical and molecular data on the subset of pts with advanced PDAC. Results: Sixteen PDAC pts have been enrolled; median age 59 years, 8 males (50%), 10 with de novo metastases (63%). Full WGS and RNASeq were completed in 11 pts (1 failed biopsy, 4 had insufficient tumor). KRAS codon 12 and TP53 mutations were present in all but one pt. CDKN2A and SMAD4 were also frequently altered (7 and 4 pts respectively). Gene expression analysis for classical and basal subtypes similar to those recently described (PMID 26343385) identified 3 and 6 pts with classical and basal expression patterns respectively, and 2 pts with mixed expression. Overall survival (OS) was significantly worse for the basal subtype vs all others (median OS 7 vs. 13.9 months (ms), p = 0.017). When separated into 3 subtypes a significant difference was still noted (median OS 7 ms in basal, 19.2 ms in classical and 11.8 ms in mixed subtype, p = 0.032). Conclusions: WGS analysis demonstrated a similar mutation pattern to that described in resectable PDAC, with no novel actionable mutations identified. Gene expression analysis demonstrated the presence of distinct gene expression signatures significantly associated with outcome, despite small pt numbers. These results need to be validated prospectively in larger cohorts. Clinical trial information: NCT02155621.

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)0.000
metaresearch head score (Gemma)0.000
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: Empirical
Teacher disagreement score0.001
Threshold uncertainty score0.003

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
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 head0.071
GPT teacher head0.404
Teacher spread0.333 · 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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Citations1
Published2016
Admission routes1
Has abstractyes

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