Evidence map›Paper›PMID 25216700›Full record

ArticleJournal of cancer research and clinical oncology2015

Protein deep sequencing applied to biobank samples from patients with pancreatic cancer.

Daniel Ansari, Roland Andersson, Monika P Bauden, Bodil Andersson, Joanne B Connolly, Charlotte Welinder, Agata Sasor, György Marko-Varga

Open access · greenAbstract readComparative Study
In one paragraph

Article in Journal of cancer research and clinical oncology, 2015. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 28 papers.

0numbers the graph read from it
0cells of the map it votes in
28citing papers in PubMed
2.4field-weighted citation impact, top 10% 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

28 citing papers in PubMed, 40 citations in OpenAlex.

  1. Article
  2. Article
  3. Proteomics in pancreatic cancer.Biomarker research · 2025
    Review
  4. Article
  5. Potentially functional variants ofFrontiers in immunology · 2024
    Article
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  16. Sperm-Associated Antigen 5 Expression Is Increased in Hepatocellular Carcinoma and Indicates Poor Prognosis.Medical science monitor : international medical journal of experimental and clinical research · 2018
    Article
  17. Article
  18. Article
  19. Review
  20. Overexpression and biological function of MEF2D in human pancreatic cancer.American journal of translational research · 2017
    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

8 authors at 3 institutions in 2 countries.

Daniel AnsariDepartment of Surgery, Clinical Sciences Lund, Lund University, Skåne University Hospital, 221 85, Lund, Sweden.
Roland Andersson
Monika P Bauden
Bodil Andersson
Joanne B Connolly
Charlotte Welinder
Agata Sasor
György Marko-Varga
Lund University · SESkåne University Hospital · SEWaters (United Kingdom) · GB

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

purposePancreatic cancer is commonly detected at advanced stages when the tumor is no longer amenable to surgical resection. Therefore, finding biomarkers for early stage disease is urgent. Here, we show that high-definition mass spectrometry (HDMS(E)) can be used to identify serum protein alterations associated with early stage pancreatic cancer.

methodsWe analyzed serum samples from patients with resectable pancreatic cancer, benign pancreatic disease, and healthy controls. The SYNAPT G2-Si platform was used in a data-independent manner coupled with ion mobility. The dilution of the samples with yeast alcohol dehydrogenase tryptic digest of known concentration allowed the estimated amounts of each identified protein to be calculated (Silva et al. in Anal Chem 77:2187-2200, 2005; Silva et al. in Mol Cell Proteomics 5:144-156, 2006). A global protein expression comparison of the three study groups was made using label-free quantification and bioinformatic analyses.

resultsTwo-way unsupervised hierarchical clustering revealed 134 proteins that successfully classified pancreatic cancer patients from the controls, and identified 40 proteins that showed a significant up-regulation in the pancreatic cancer group. This discrimination reliability was further confirmed by principal component analysis. The differentially expressed candidates were aligned with protein network analyses and linked to biological pathways related to pancreatic tumorigenesis. Pancreatic disease link associations could be made for BAZ2A, CDK13, DAPK1, DST, EXOSC3, INHBE, KAT2B, KIF20B, SMC1B, and SPAG5, by pathway network linkages to p53, the most frequently altered tumor suppressor in pancreatic cancer.

conclusionThese pancreatic cancer study candidates may provide new avenues of research for a noninvasive blood-based diagnosis for pancreatic tumor stratification.

Indexed as

Biological Specimen BanksAgedBiomarkers, TumorBlood ProteinsCase-Control StudiesComputational BiologyFemaleHumansMaleMiddle AgedPancreasPancreatic NeoplasmsPrognosisProteomicsSpectrometry, Mass, Matrix-Assisted Laser Desorption-IonizationBiomarkers, TumorBlood Proteins

Identifiers

PMID25216700
PMCPMC11823806
OpenAlexW2076820746

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.