Evidence map›Paper›PMID 40654937›Full record

ArticlebioRxiv : the preprint server for biology2025

High-Sensitive Spatial Proteomics for Pancreatic Cancer Progression Analysis.

Jongmin Woo, Zhenyu Sun, Yingwei Hu, Trung Alvin Hoàng, Decapite Christine, Smith Katelyn, Singhi Aatur, Randall E Brand, Daniel W Chan, Qing Kay Li and 2 more

Abstract readPreprint
PubMed Full text at PMC Publisher
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

12 authors.

Jongmin WooDepartment of Pathology, The Sol Goldman Pancreatic Cancer Research Center, Johns Hopkins University School of Medicine, Baltimore, MD 21231.ORCID 0000-0001-5569-9304
Zhenyu SunDepartment of Pathology, The Sol Goldman Pancreatic Cancer Research Center, Johns Hopkins University School of Medicine, Baltimore, MD 21231.
Yingwei HuDepartment of Pathology, The Sol Goldman Pancreatic Cancer Research Center, Johns Hopkins University School of Medicine, Baltimore, MD 21231.
Trung Alvin HoàngDepartment of Pathology, The Sol Goldman Pancreatic Cancer Research Center, Johns Hopkins University School of Medicine, Baltimore, MD 21231.
Decapite ChristineDepartment of Pathology, University of Pittsburgh Medical Center, Pittsburgh, PA 15261.
Smith KatelynDepartment of Pathology, University of Pittsburgh Medical Center, Pittsburgh, PA 15261.
Singhi AaturDepartment of Pathology, University of Pittsburgh Medical Center, Pittsburgh, PA 15261.
Randall E BrandDepartment of Pathology, University of Pittsburgh Medical Center, Pittsburgh, PA 15261.
Daniel W ChanDepartment of Pathology, The Sol Goldman Pancreatic Cancer Research Center, Johns Hopkins University School of Medicine, Baltimore, MD 21231.
Qing Kay LiDepartment of Pathology, The Sol Goldman Pancreatic Cancer Research Center, Johns Hopkins University School of Medicine, Baltimore, MD 21231.
Ralph H HrubanDepartment of Pathology, The Sol Goldman Pancreatic Cancer Research Center, Johns Hopkins University School of Medicine, Baltimore, MD 21231.
Hui ZhangDepartment of Pathology, The Sol Goldman Pancreatic Cancer Research Center, Johns Hopkins University School of Medicine, Baltimore, MD 21231.

Funding

Proteogenomic Characterization of Tumor Tissues and Preclinical Models with High PrecisionU24CA271079 · NCI · JOHNS HOPKINS UNIVERSITY · PI DANIEL Wanyui CHAN, Hui Zhang · 2022 to 2026
$6.6M
Biomarker Reference LaboratoryU2CCA271895 · NCI · JOHNS HOPKINS UNIVERSITY · PI DANIEL Wanyui CHAN · 2023 to 2026
$4.6M
Development of a panel of multiplex biomarkers for the early detection of pancreatic ductal adenocarcinoma and high-risk lesionsU01CA274514 · NCI · JOHNS HOPKINS UNIVERSITY · PI Randall Brand, DANIEL Wanyui CHAN · 2023 to 2026
$3.2M
NCI NIH HHS U01 CA274514NCI NIH HHS U24 CA271079NCI NIH HHS U2C CA271895
6 · The paper itself

Abstract

Pancreatic cancer remains as one of the most challenging malignancies to diagnose and treat due to the late development of symptoms and limited early diagnostic options. Intraductal papillary mucinous neoplasms (IPMNs) are non-invasive precursors to invasive pancreatic ductal adenocarcinoma (PDAC)and an understanding of the changes in patterns of protein expression that accompany the progression from normal ductal (ND) cell, to IPMN to PDAC may provide avenues for improved earlier detection. In this study, we present an optimized spatial tissue proteomics workflow, termed SP-Max (Spatial Proteomics Optimized for Maximum Sensitivity and Reproducibility in Minimal Sample), designed to maximize protein recovery and quantification from limited laser micro dissected (LMD) samples. Our workflow enabled the identification of more than 6,000 proteins and the quantification of over 5,200 protein groups from FFPE tissue contours of pancreatic tissues. Comparative analyses across ND, IPMN, and PDAC revealed critical molecular differences in protein pathways and potential markers of progression. SP-Max provides a systematic, reproducible approach that significantly enhances our ability to study precancerous lesions and cancer progression in pancreatic tissues at unprecedented resolution.

Indexed as

FFPE TissueHigh-sensitivity Mass SpectrometryIntraductal Papillary Mucinous NeoplasmPancreatic Ductal AdenocarcinomaSpatial Proteomics

Identifiers

PMID40654937
PMCPMC12247709

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.