Evidence map›Paper›PMID 18547137›Full record

ArticlePLoS medicine2008

A mouse to human search for plasma proteome changes associated with pancreatic tumor development.

Vitor M Faca, Kenneth S Song, Hong Wang, Qing Zhang, Alexei L Krasnoselsky, Lisa F Newcomb, Ruben R Plentz, Sushma Gurumurthy, Mark S Redston, Sharon J Pitteri and 18 more

Open access · goldAbstract read
In one paragraph

Article in PLoS medicine, 2008. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 118 papers.

0numbers the graph read from it
0cells of the map it votes in
118citing papers in PubMed
17.6field-weighted citation impact, top 1% of its field
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

118 citing papers in PubMed, 260 citations in OpenAlex.

  1. Article
  2. Article
  3. Article
  4. Functional and Clinical Proteomic Exploration of Pancreatic Cancer.Molecular & cellular proteomics : MCP · 2023
    Review
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  6. Article
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  14. ImmunoPET/NIRF/Cerenkov multimodality imaging of ICAM-1 in pancreatic ductal adenocarcinoma.European journal of nuclear medicine and molecular imaging · 2021
    Article
  15. Review
  16. Review
  17. Review
  18. Biomarkers and Strategy to Detect Preinvasive and Early Pancreatic Cancer: State of the Field and the Impact of the EDRN.Cancer epidemiology, biomarkers & prevention : a publication of the American Association for Cancer Research, cosponsored by the American Society of Preventive Oncology · 2020
    Article
  19. Article
  20. Article

58 more citing papers are in PubMed but not listed here.

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

28 authors at 7 institutions in 1 country.

Vitor M FacaFred Hutchinson Cancer Research Center, Seattle, Washington, United States of America.
Kenneth S Song
Hong Wang
Qing Zhang
Alexei L Krasnoselsky
Lisa F Newcomb
Ruben R Plentz
Sushma Gurumurthy
Mark S Redston
Sharon J Pitteri
Sandra R Pereira-Faca
Renee C Ireton
Hiroyuki Katayama
Veronika Glukhova
Douglas Phanstiel
Dean E Brenner
Michelle A Anderson
David Misek
Nathalie Scholler
Nicole D Urban
Matt J Barnett
Cim Edelstein
Gary E Goodman
Mark D Thornquist
Martin W McIntosh
Ronald A DePinho
Nabeel Bardeesy
Samir M Hanash
Fred Hutch Cancer Center · USMassachusetts General Hospital · USMichigan Center for Translational Pathology · USBrigham and Women's Hospital · USDana-Farber Cancer Institute · USHarvard University · USMichigan United · US

Funding

The RAS and P13K Pathways in Pancreatic AdenocarcinomaP01CA117969 · NCI · UNIVERSITY OF TX MD ANDERSON CAN CTR · PI DEPINHO, RONALD ANTHONY · 2006 to 2025
$41.7M
CHILDRENS CANCER STUDY GROUPU10CA011796 · NCI · CHILDREN'S HOSPITAL OF PHILADELPHIA · PI LANGE, BEVERLY J · 1985 to 2002
$1.2M
Mouse Model of Pancreatic Cancer Progression-MaintenanceK01CA104647 · NCI · MASSACHUSETTS GENERAL HOSPITAL · PI EL-BARDEESY, NABEEL · 2005 to 2009
$783k
NCI NIH HHS 5K01CA104647NCI NIH HHS 5P01CA117969-02NCI NIH HHS K01 CA104647NCI NIH HHS P01 CA117969
6 · The paper itself

Abstract

backgroundThe complexity and heterogeneity of the human plasma proteome have presented significant challenges in the identification of protein changes associated with tumor development. Refined genetically engineered mouse (GEM) models of human cancer have been shown to faithfully recapitulate the molecular, biological, and clinical features of human disease. Here, we sought to exploit the merits of a well-characterized GEM model of pancreatic cancer to determine whether proteomics technologies allow identification of protein changes associated with tumor development and whether such changes are relevant to human pancreatic cancer. METHODS AND

findingsPlasma was sampled from mice at early and advanced stages of tumor development and from matched controls. Using a proteomic approach based on extensive protein fractionation, we confidently identified 1,442 proteins that were distributed across seven orders of magnitude of abundance in plasma. Analysis of proteins chosen on the basis of increased levels in plasma from tumor-bearing mice and corroborating protein or RNA expression in tissue documented concordance in the blood from 30 newly diagnosed patients with pancreatic cancer relative to 30 control specimens. A panel of five proteins selected on the basis of their increased level at an early stage of tumor development in the mouse was tested in a blinded study in 26 humans from the CARET (Carotene and Retinol Efficacy Trial) cohort. The panel discriminated pancreatic cancer cases from matched controls in blood specimens obtained between 7 and 13 mo prior to the development of symptoms and clinical diagnosis of pancreatic cancer.

conclusionsOur findings indicate that GEM models of cancer, in combination with in-depth proteomic analysis, provide a useful strategy to identify candidate markers applicable to human cancer with potential utility for early detection.

Indexed as

AnimalsBiomarkers, TumorHumansMass SpectrometryMicePancreatic NeoplasmsProteomeProteomicsRNA, MessengerBiomarkers, TumorProteomeRNA, Messenger

Identifiers

PMID18547137
PMCPMC2504036
OpenAlexW2156250197

What OpenQuestion holds

Textmetadata
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 OpenQuestion graph.