Evidence map›Paper›PMID 40166305›Full record

ArticlebioRxiv : the preprint server for biology2025

Spatial analysis of IPMNs defines a paradoxical KRT17-positive, low-grade epithelial population harboring malignant features.

Jay Li, Justin Macchia, Ahmed M Elhossiny, Nandini Arya, Padma Kadiyala, Georgina Branch, Nicole Peterson, Jianhua Liu, Richard Kwon, Jorge D Machicado and 12 more

Abstract readPreprint
In one paragraph

Article in bioRxiv : the preprint server for biology, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing 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

0 citing papers in PubMed.

No citing paper in PubMed yet.

4 · The record

Corrections and comments

5 · Who and what money

Authors and funding

22 authors.

Jay Li
Justin Macchia
Ahmed M Elhossiny
Nandini Arya
Padma Kadiyala
Georgina Branch
Nicole Peterson
Jianhua Liu
Richard Kwon
Jorge D Machicado
Erik-Jan Wamsteker
Allison Schulman
George Philips
Stacy Menees
Aatur D Singhi
Vaibhav Sahai
Jiayun M Fang
Timothy L Frankel
Filip Bednar
Marina Pasca di Magliano
Jiaqi Shi
Eileen S CarpenterORCID 0000-0001-6775-6943

Funding

Training Program in Tumor MicroenvironmentT32CA009676 · NCI · UNIVERSITY OF MICHIGAN AT ANN ARBOR · PI Maria G Castro, Analisa Virginia DiFeo · 1992 to 2026
$7.3M
BLRD VA IK2 BX005875NCI NIH HHS T32 CA009676
6 · The paper itself

Abstract

Background & Aims: Intraductal papillary mucinous neoplasms (IPMNs) are pancreatic cysts that represent one of the few radiologically identifiable precursors to pancreatic ductal adenocarcinoma (PDAC).Though the IPMN-bearing patient population represents a unique opportunity for early detection and interception, current guidelines provide insufficient accuracy in determining which patients should undergo resection versus surveillance, resulting in a sizable fraction of resected IPMNs only harboring low-grade dysplasia, suggesting that there may be overtreatment of this clinical entity. Methods: To investigate the transcriptional changes that occur during IPMN progression, we performed spatial transcriptomics using the Nanostring GeoMx on patient samples containing the entire spectrum of IPMN disease including low-grade dysplasia, high-grade dysplasia, and IPMN-derived carcinoma. Single cell RNA sequencing was performed on side branch and main duct IPMN biospecimens. Results: We identified a subpopulation of histologically low-grade IPMN epithelial cells that express malignant transcriptional features including Conclusions: Our study demonstrates that KRT17 marks a distinct transcriptional signature in a subpopulation of epithelial cells within histologically low-grade IPMN. This population of cells likely represents a transitional state of histologically low-grade epithelial cells undergoing progression to a higher grade of dysplasia and thus may represent a higher risk of progression to carcinoma. Graphical abstract:

Identifiers

PMID40166305
PMCPMC11957041

What OpenQuestion holds

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Registered trials

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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 OpenQuestion graph.