Evidence map›Paper›PMID 19582723›Full record

ArticleElectrophoresis2009

The identification of phosphoglycerate kinase-1 and histone H4 autoantibodies in pancreatic cancer patient serum using a natural protein microarray.

Tasneem H Patwa, Chen Li, Laila M Poisson, Hye-Yeung Kim, Manoj Pal, Debashis Ghosh, Diane M Simeone, David M Lubman

Open access · greenAbstract read
In one paragraph

Article in Electrophoresis, 2009. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 15 papers, 2 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
15citing papers in PubMed, 2 pooled it
2.2field-weighted citation impact, top 13% 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

15 citing papers in PubMed, 2 syntheses or guidelines pooled it, 36 citations in OpenAlex.

  1. Glucose metabolic phenotype of pancreatic cancer.World journal of gastroenterology · 2016
    Pooled it
  2. Pooled it
  3. Article
  4. Review
  5. Review
  6. Review
  7. Article
  8. Article
  9. Pancreatic Cancer: a Challenge to Cure.The Indian journal of surgery · 2015
    Article
  10. Review
  11. Proteomics in pancreatic cancer research.International journal of proteomics · 2011
    Article
  12. Article
  13. Article
  14. Seromic profiling of ovarian and pancreatic cancer.Proceedings of the National Academy of Sciences of the United States of America · 2010
    Article
  15. Review
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

8 authors at 2 institutions in 1 country.

Tasneem H PatwaDepartment of Chemistry, University of Michigan, Ann Arbor, MI 48109-0656, USA.
Chen Li
Laila M Poisson
Hye-Yeung Kim
Manoj Pal
Debashis Ghosh
Diane M Simeone
David M Lubman
University of Michigan–Ann Arbor · USPennsylvania State University · US

Funding

Biostatistics Training Program in Cancer ResearchT32CA083654 · NCI · UNIVERSITY OF MICHIGAN AT ANN ARBOR · PI Veerabhadran Baladandayuthapani, Kelley McLain Kidwell · 2002 to 2026
$4.3M
Microsequencing in an Ion Trap/reTOF DeviceR01GM049500 · NIGMS · UNIVERSITY OF MICHIGAN AT ANN ARBOR · PI LUBMAN, DAVID M. · 1994 to 2016
$3.0M
Protein Microarrays for the Humoral Response in CancerR01CA106402 · NCI · UNIVERSITY OF MICHIGAN AT ANN ARBOR · PI LUBMAN, DAVID M. · 2004 to 2008
$1.4M
Statistical Methods for the Analysis of Microarray DataR01GM072007 · NIGMS · UNIVERSITY OF MICHIGAN AT ANN ARBOR · PI GHOSH, DEBASHIS · 2004 to 2008
$1.1M
NCI NIH HHS R01 CA106402NCI NIH HHS R01CA106402NCI NIH HHS T32 CA083654NIGMS NIH HHS R01 GM049500NIGMS NIH HHS R01 GM072007NIGMS NIH HHS R01GM49500NIGMS NIH HHS R01GM72007
6 · The paper itself

Abstract

Protein microarrays have been used to explore whether a humoral response to pancreatic cancer-specific tumor antigens has utility as a biomarker of pancreatic cancer. To determine if such arrays can be used to identify novel autoantibodies in the sera from pancreatic cancer patients, proteins from a pancreatic adenocarcinoma cell line (MIAPACA) were resolved by 2-D liquid-based separations, and then arrayed on nitrocellulose slides. The slides were probed with serum from a set of patients diagnosed with pancreatic cancer and compared with age- and sex-matched normal subjects. To account for patient-to-patient variability, we used a rank-based non-parametric statistical testing approach in which proteins eliciting significant differences in the humoral response in cancer compared with control samples were identified. The prediction analysis for microarrays classification algorithm was used to explore the classification power of the proteins found to be differentially expressed in cancer and control sera. The generalization error of the classification analysis was estimated using leave-one-out cross-validation. A serum diagnosis of pancreatic cancer in this set was predicted with 86.7% accuracy, with a sensitivity and specificity of 93.3 and 80%, respectively. Candidate autoantibody biomarkers identified using this approach were studied for their classification power by performing a humoral response experiment on recombinant proteins using an independent sample set of 238 serum samples. Phosphoglycerate kinase-1 and histone H4 were noted to elicit a significant differential humoral response in cancer sera compared with age- and sex-matched sera from normal patients and patients with chronic pancreatitis and diabetes. This work demonstrates the use of natural protein arrays to study the humoral response as a means to search for the potential markers of cancer in serum.

Indexed as

Area Under CurveAutoantibodiesBiomarkers, TumorCell Line, TumorChromatography, LiquidCluster AnalysisElectrophoresisHistonesHumansPancreatic NeoplasmsPhosphoglycerate KinaseProtein Array AnalysisProteomicsRecombinant ProteinsReproducibility of ResultsROC CurveAutoantibodiesBiomarkers, TumorHistonesPhosphoglycerate KinaseRecombinant Proteins

Identifiers

PMID19582723
PMCPMC2794663
OpenAlexW2135244948

What OpenQuestion holds

Textmetadata
LicenceTDM
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.