Evidence map›Paper›PMID 41709591›Full record

ArticleMolecular oncology2026

Identification of serum protein biomarkers for pre-cancerous lesions associated with pancreatic ductal adenocarcinoma.

Hannah Mearns, Jaclyn S Long, Sergio Lilla, Kelly Hodge, Marcus J G W Ladds, Colin Nixon, Paula Fernández-Palanca, Sara Zanivan, Pilar Acedo, Stephen P Pereira and 1 more

Abstract read
In one paragraph

Article in Molecular oncology, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

1 citing paper in PubMed.

  1. Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

11 authors.

Hannah MearnsCancer Research UK Scotland Institute, Glasgow, UK.
Jaclyn S LongCancer Research UK Scotland Institute, Glasgow, UK.
Sergio LillaCancer Research UK Scotland Institute, Glasgow, UK.
Kelly HodgeCancer Research UK Scotland Institute, Glasgow, UK.
Marcus J G W LaddsCancer Research UK Scotland Institute, Glasgow, UK.
Colin NixonCancer Research UK Scotland Institute, Glasgow, UK.
Paula Fernández-PalancaCancer Research UK Scotland Institute, Glasgow, UK.
Sara ZanivanCancer Research UK Scotland Institute, Glasgow, UK.
Pilar AcedoInstitute for Liver and Digestive Health, Royal Free Hospital Campus, University College London (UCL), UK.
Stephen P PereiraInstitute for Liver and Digestive Health, Royal Free Hospital Campus, University College London (UCL), UK.
Kevin M RyanCancer Research UK Scotland Institute, Glasgow, UK.ORCID 0000-0002-1059-9681

Funding

Cancer Research UK A22903Cancer Research UK A28686Cancer Research UK A29800Cancer Research UK A31287Cancer Research UK CanDetectEDDPGM-May22\100002Pancreatic Cancer UK 06/Q0512/106
6 · The paper itself

Abstract

Pancreatic ductal adenocarcinoma (PDAC) has poor prognosis as early-stage asymptomaticity leads to late-stage diagnoses. Strategies to detect PDAC earlier or identify high-risk individuals are therefore paramount. Here, we report results from genetically engineered mice and PDAC patients that identify serum proteins associated with pancreatic intraepithelial neoplasms (PanINs), the most common PDAC precursor, and early-stage PDAC. Initially, we screened previously described PanIN-abundant mice, harbouring pancreatic and duodenal homeobox 1 (Pdx1)-Cre, Lox-STOP-Lox-Kras

Indexed as

Biomarkers, TumorBlood ProteinsCarcinoma, Pancreatic DuctalPancreatic NeoplasmsPrecancerous ConditionsAnimalsFemaleHumansMaleMiceMice, TransgenicBiomarkers, TumorBlood Proteinsautophagybiomarkerearly detectionmicepancreatic ductal adenocarcinoma; pancreatic intraepithelial neoplasiaproteomicsserum

Identifiers

PMID41709591
PMCPMC13238842

What Socratic holds

Textmetadata
LicenceCC BY
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the Socratic graph.