Evidence map›Paper›PMID 24007603›Full record

ArticleBMC cancer2013

Validation of four candidate pancreatic cancer serological biomarkers that improve the performance of CA19.9.

Shalini Makawita, Apostolos Dimitromanolakis, Antoninus Soosaipillai, Ireena Soleas, Alison Chan, Steven Gallinger, Randy S Haun, Ivan M Blasutig, Eleftherios P Diamandis

Open access · goldAbstract read
In one paragraph

Article in BMC cancer, 2013. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 35 papers.

0numbers the graph read from it
0cells of the map it votes in
35citing papers in PubMed
1.9field-weighted citation impact, top 14% 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

35 citing papers in PubMed, 54 citations in OpenAlex.

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  13. Current State of "Omics" Biomarkers in Pancreatic Cancer.Journal of personalized medicine · 2021
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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

9 authors at 3 institutions in 2 countries.

Shalini MakawitaDepartment of Laboratory Medicine and Pathobiology, University of Toronto, Toronto, ON, Canada. ediamandis@mtsinai.on.ca.
Apostolos Dimitromanolakis
Antoninus Soosaipillai
Ireena Soleas
Alison Chan
Steven Gallinger
Randy S Haun
Ivan M Blasutig
Eleftherios P Diamandis
Mount Sinai Hospital · CAUniversity of Toronto · CAUniversity of Arkansas for Medical Sciences · US

Funding

Early Detection of Pancreatic CancerR21CA118164 · NCI · UNIV OF ARKANSAS FOR MED SCIS · PI HAUN, RANDY S · 2006 to 2007
$290k
Role of serine protease KLK7 in pancreatic cancerI01BX000828 · VA · CENTRAL ARKANSAS VETERANS HLTHCARE SYS · PI HAUN, RANDY S. · 2011 to 2014
–
BLRD VA I01 BX000828NCI NIH HHS R21 CA118164NCI NIH HHS R21CA118164-01A1
6 · The paper itself

Abstract

backgroundThe identification of new serum biomarkers with high sensitivity and specificity is an important priority in pancreatic cancer research. Through an extensive proteomics analysis of pancreatic cancer cell lines and pancreatic juice, we previously generated a list of candidate pancreatic cancer biomarkers. The present study details further validation of four of our previously identified candidates: regenerating islet-derived 1 beta (REG1B), syncollin (SYCN), anterior gradient homolog 2 protein (AGR2), and lysyl oxidase-like 2 (LOXL2).

methodsThe candidate biomarkers were validated using enzyme-linked immunosorbent assays in two sample sets of serum/plasma comprising a total of 432 samples (Sample Set A: pancreatic ductal adenocarcinoma (PDAC, n = 100), healthy (n = 92); Sample Set B: PDAC (n = 82), benign (n = 41), disease-free (n = 47), other cancers (n = 70)). Biomarker performance in distinguishing PDAC from each control group was assessed individually in the two sample sets. Subsequently, multiparametric modeling was applied to assess the ability of all possible two and three marker panels in distinguishing PDAC from disease-free controls. The models were generated using sample set B, and then validated in Sample Set A.

resultsIndividually, all markers were significantly elevated in PDAC compared to healthy controls in at least one sample set (p ≤ 0.01). SYCN, REG1B and AGR2 were also significantly elevated in PDAC compared to benign controls (p ≤ 0.01), and AGR2 was significantly elevated in PDAC compared to other cancers (p < 0.01). CA19.9 was also assessed. Individually, CA19.9 showed the greatest area under the curve (AUC) in receiver operating characteristic (ROC) analysis when compared to the tested candidates; however when analyzed in combination, three panels (CA19.9 + REG1B (AUC of 0.88), CA19.9 + SYCN + REG1B (AUC of 0.87) and CA19.9 + AGR2 + REG1B (AUC of 0.87)) showed an AUC that was significantly greater (p < 0.05) than that of CA19.9 alone (AUC of 0.82). In a comparison of early-stage (Stage I-II) PDAC to disease free controls, the combination of SYCN + REG1B + CA19.9 showed the greatest AUC in both sample sets, (AUC of 0.87 and 0.92 in Sets A and B, respectively).

conclusionsAdditional serum biomarkers, particularly SYCN and REG1B, when combined with CA19.9, show promise as improved diagnostic indicators of pancreatic cancer, which therefore warrants further validation.

Indexed as

AdultAgedAge FactorsAmino Acid OxidoreductasesBiomarkers, TumorCA-19-9 AntigenCarrier ProteinsCase-Control StudiesFemaleHumansLithostathineMaleMembrane ProteinsMiddle AgedMucoproteinsNeoplasm StagingAGR2 protein, humanAmino Acid OxidoreductasesBiomarkers, TumorCA-19-9 AntigenCarrier ProteinsLithostathineLOXL2 protein, humanMembrane ProteinsMucoproteinsOncogene ProteinsProteinsREG1B protein, humanSycn protein, rat

Identifiers

PMID24007603
PMCPMC3847832
OpenAlexW2146571366

What OpenQuestion holds

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LicenceCC BY
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.