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Record W4408135698 · doi:10.1038/s41698-025-00843-7

Whole-genome analysis of an aggressive metastatic pancreatic solid pseudopapillary neoplasm

2025· article· en· W4408135698 on OpenAlexaff
Phoebe T. M. Cheng, James T. Topham, Ayman Aldeheshi, J. Paul Taylor, Erin Pleasance, Melissa K. McConechy, Jessica Nelson, David F. Schaeffer, Steven J.M. Jones, Marco A. Marra, Janessa Laskin, Daniel J. Renouf

Bibliographic record

Venuenpj Precision Oncology · 2025
Typearticle
Languageen
FieldMedicine
TopicPancreatic and Hepatic Oncology Research
Canadian institutionsUniversity of British ColumbiaPancreas Centre (Canada)Canada's Michael Smith Genome Sciences CentreBC Cancer Agency
Fundersnot available
KeywordsNeoplasmMedicineOncologyPathology

Abstract

fetched live from OpenAlex

Pancreatic solid pseudopapillary neoplasms (SPNs) are uncommon tumors that rarely exhibit aggressive behavior. Given disease rarity, comprehensive studies to understand tumor biology, clinical course, and optimal management are limited. We describe an unusual case of a 55-year-old man with metastatic pancreatic SPN, where whole-genome and transcriptome analyses of the primary tumor and a metastatic liver lesion revealed a shared homozygous non-canonical mutation in APC. The patient received upfront modified FOLFIRINOX (infusional 5-fluorouracil, irinotecan, and oxaliplatin) chemotherapy due to rapidly progressive symptoms, demonstrating an early and sustained treatment response. Therefore, we identified potential genetic determinants of tumorigenesis and progression in a pathologically and clinically aggressive SPN, which may have important prognostic and treatment implications.

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 score0.002

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 head0.034
GPT teacher head0.411
Teacher spread0.377 · 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

Citations5
Published2025
Admission routes1
Has abstractyes

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