Evidence map›Paper›PMID 27217769›Full record

ArticleOncoTargets and therapy2016

Serum biomarker panels for diagnosis of gastric cancer.

Weihua Tong, Fei Ye, Liang He, Lifeng Cui, Miao Cui, Yuan Hu, Wei Li, Jing Jiang, David Y Zhang, Jian Suo

Open access · goldAbstract read
In one paragraph

Article in OncoTargets and therapy, 2016. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 33 papers.

0numbers the graph read from it
0cells of the map it votes in
33citing papers in PubMed
3.0field-weighted citation impact, top 9% 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

33 citing papers in PubMed, 53 citations in OpenAlex.

  1. Research progress of machine learning applications in gastric cancer diagnosis and therapy.Clinical & translational oncology : official publication of the Federation of Spanish Oncology Societies and of the National Cancer Institute of Mexico · 2026
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  15. Circulating Proteins as Diagnostic Markers in Gastric Cancer.International journal of molecular sciences · 2023
    Review
  16. Article
  17. Article
  18. High-throughput proteomics: a methodological mini-review.Laboratory investigation; a journal of technical methods and pathology · 2022
    Review
  19. Expression and the Prognostic Value of Biglycan in Gastric Cancer.Computational and mathematical methods in medicine · 2022
    Article
  20. 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

10 authors at 1 institution in 1 country.

Weihua TongDepartment of Gastrointestinal Surgery, The First Hospital, Jilin University, Changchun, Jilin, People's Republic of China.
Fei YeDepartment of Pathology, Icahn School of Medicine at Mount Sinai, New York, NY, USA.
Liang HeDepartment of Gastrointestinal Surgery, The First Hospital, Jilin University, Changchun, Jilin, People's Republic of China.
Lifeng CuiDepartment of Gastrointestinal Surgery, The First Hospital, Jilin University, Changchun, Jilin, People's Republic of China.
Miao CuiDepartment of Pathology, Icahn School of Medicine at Mount Sinai, New York, NY, USA.
Yuan HuDepartment of Pathology, Icahn School of Medicine at Mount Sinai, New York, NY, USA.
Wei LiDepartment of Gastrointestinal Surgery, The First Hospital, Jilin University, Changchun, Jilin, People's Republic of China.
Jing JiangDivision of Clinical Epidemiology, The First Hospital, Jilin University, Changchun, Jilin, People's Republic of China.
David Y ZhangDepartment of Pathology, Icahn School of Medicine at Mount Sinai, New York, NY, USA.
Jian SuoDepartment of Gastrointestinal Surgery, The First Hospital, Jilin University, Changchun, Jilin, People's Republic of China.
Icahn School of Medicine at Mount Sinai · US

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

purposeCurrently, serum biomarkers that are sufficiently sensitive and specific for early detection and risk classification of gastric adenocarcinomas are not known. In this study, ten serum markers were assessed using the Luminex system and enzyme-linked immunosorbent assay for the diagnosis of gastric cancer and analysis of the relation between prognosis and metastases. PATIENTS AND

methodsA training set consisting of 228 gastric adenocarcinoma and 190 control samples was examined. A Luminex multiplex panel with nine biomarkers, consisting of three proteins discovered through our previous studies and six proteins previously reported to be cancer-associated, was constructed. One additional biomarker was detected using a commercial kit containing EDTA. Logistic regression, random forest (RF), and support vector machine (SVM) were used to identify the panel of discriminatory biomarkers in the training set. After selecting five proteins as candidate biomarkers, multivariate classification analyses were used to identify algorithms for diagnostic biomarker combinations. These algorithms were independently validated using a set of 57 gastric adenocarcinoma and 48 control samples.

resultsSerum pepsinogen I, serum pepsinogen II, A Disintegrin And Metalloproteinase domain-containing protein 8 (ADAM8), vascular endothelial growth factor (VEGF), and serum IgG to Helicobacter pylori were selected as classifiers in the three algorithms. These algorithms differentiated between the majority of gastric adenocarcinoma and control serum samples in the training/test set with high accuracy (RF 79.0%, SVM 83.8%, logistic regression 76.2%). These algorithms also differentiated the samples in the validation set (accuracy: RF 82.5%, SVM 86.1%, logistic regression 78.7%).

conclusionA panel of combinatorial biomarkers comprising VEGF, ADAM8, IgG to H. pylori, serum pepsinogen I, and pepsinogen II were developed. The use of biomarkers is a less invasive method for the diagnosis of gastric adenocarcinoma. They may supplement clinical gastroscopic evaluation of symptomatic gastric cancer patients and enhance the diagnostic accuracy.

Indexed as

cancer diagnosiscancer screeninggastric adenocarcinomaLuminex

Identifiers

PMID27217769
PMCPMC4853138
OpenAlexW2344041952

What OpenQuestion holds

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LicenceCC BY-NC
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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.