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Integrative analysis of <i>KRAS</i>-wildtype pancreatic ductal adenocarcinoma reveals unique similarities to extrahepatic cholangiocarcinoma.

2022· article· en· W4206648200 on OpenAlexaff
Erica S. Tsang, James T. Topham, Joanna M. Karasinska, Steve E. Kalloger, Veronika Csizmók, Laura Williamson, Hui‐Li Wong, Grainne M. O’Kane, Jonathan M. Loree, Faiyaz Notta, Oliver F. Bathe, Patricia A. Tang, Rachel Goodwin, Jennifer J. Knox, Steven Gallinger, Janessa Laskin, Marco A. Marra, Steven J.M. Jones, David F. Schaeffer, Daniel J. Renouf

Bibliographic record

VenueJournal of Clinical Oncology · 2022
Typearticle
Languageen
FieldMedicine
TopicCholangiocarcinoma and Gallbladder Cancer Studies
Canadian institutionsBC Cancer AgencyPrincess Margaret Cancer CentreUniversity of CalgaryVancouver General HospitalUniversity of British ColumbiaToronto General HospitalOttawa HospitalUniversity Health NetworkOntario Institute for Cancer ResearchPancreas Centre (Canada)Canada's Michael Smith Genome Sciences CentreGenome British Columbia
Fundersnot available
KeywordsKRASMedicineMalignancyAdenocarcinomaOncologyInternal medicinePancreatic cancerCancer researchColorectal cancerCancer

Abstract

fetched live from OpenAlex

587 Background: Oncogenic driver mutations in KRAS represent a hallmark genomic event in approximately 90% of pancreatic adenocarcinoma (PDAC). For the remaining 10% of patients with KRAS wildtype (wt) PDAC, distinct driver mutations have been described, but their transcriptional landscape has not been reported. Here, we leverage sequencing data from the PanGen trial to provide a comprehensive characterization of advanced KRASwt PDAC. Methods: 63 patients with advanced PDAC received whole genome and transcriptome sequencing prior to treatment for metastatic disease as part of the PanGen trial (NCT02869802). Clinical features, somatic mutation data and gene expression patterns were compared between KRASwt and mutant groups. PDAC samples were contrasted with 77 other metastatic carcinoma (colorectal and cholangiocarcinoma) samples from the Personalized OncoGenomics trial (NCT0215562). KRAS wt-associated genes were further investigated using 3 additional PDAC cohorts (COMPASS NCT02750657, TCGA, and ICGC). Results: 9 of 63 (14%) samples were KRASwt, with an earlier median age at diagnosis (51.4 vs. 60.9 years; p=0.03). Clinical features, including diabetes, family history of malignancy, and location of primary tumor, were comparable. CA 19-9 at baseline was lower in the KRASwt group, with median 58 vs. 4900 U/mL in the KRAS-mutant group ( p=0.03). Patients with KRASwt PDAC showed increased overall survival in univariable ( p=0.0024) and multivariable ( p=0.0089) analyses. 6 of 9 (67%) KRASwt tumors had fusions involving NRG1 (n = 3), FGFR2 (n = 1), BRAF (n = 1) or NTRK2 (n = 1), while known actionable fusions were not observed in KRAS mutant patients. KRASwt tumors showed increased expression of genes associated with cholangiocytes and grouped with cholangiocarcinoma samples in unsupervised clustering analysis. Validation using three independent PDAC cohorts revealed a core set of 70 KRAS wt-associated genes that converge on keratinization, ion transport, and hormone metabolism pathways. Conclusions: Patients with KRASwt PDAC show potentially targetable molecular traits with actionable fusions. We also highlight novel mutation and expression-based similarities between KRASwt PDAC and cholangiocarcinoma samples. Recurrent dysregulation of genes involved in cellular structure and metastasis provide impetus for further investigation into the developmental trajectory and potential therapeutic vulnerabilities of KRASwt PDAC.

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 score0.004

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
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 head0.105
GPT teacher head0.435
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 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
Published2022
Admission routes1
Has abstractyes

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