Evidence map›Paper›PMID 33346593›Full record

Observational studyClinical and translational gastroenterology2020

Discovery and Validation of Serum Autoantibodies Against Tumor-Associated Antigens as Biomarkers in Gastric Adenocarcinoma Based on the Focused Protein Arrays.

Qian Yang, Jiejie Qin, Guiying Sun, Cuipeng Qiu, Di Jiang, Hua Ye, Xiao Wang, Liping Dai, Jicun Zhu, Peng Wang and 1 more

Open access · goldAbstract readObservational StudyValidation Study
In one paragraph

Observational study in Clinical and translational gastroenterology, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 12 papers.

0numbers the graph read from it
0cells of the map it votes in
12citing papers in PubMed
1.3field-weighted citation impact, top 16% 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

12 citing papers in PubMed, 31 citations in OpenAlex.

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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

11 authors at 1 institution in 1 country.

Qian YangDepartment of Epidemiology and Statistics, College of Public Health, Zhengzhou University, Zhengzhou, Henan Province, China.
Jiejie QinDepartment of Epidemiology and Statistics, College of Public Health, Zhengzhou University, Zhengzhou, Henan Province, China.
Guiying SunDepartment of Epidemiology and Statistics, College of Public Health, Zhengzhou University, Zhengzhou, Henan Province, China.
Cuipeng QiuDepartment of Epidemiology and Statistics, College of Public Health, Zhengzhou University, Zhengzhou, Henan Province, China.
Di JiangDepartment of Epidemiology and Statistics, College of Public Health, Zhengzhou University, Zhengzhou, Henan Province, China.
Hua YeDepartment of Epidemiology and Statistics, College of Public Health, Zhengzhou University, Zhengzhou, Henan Province, China.
Xiao WangHenan Institute of Medical and Pharmaceutical Sciences, Zhengzhou University, Zhengzhou, Henan Province, China.
Liping DaiHenan Institute of Medical and Pharmaceutical Sciences, Zhengzhou University, Zhengzhou, Henan Province, China.
Jicun ZhuDepartment of Epidemiology and Statistics, College of Public Health, Zhengzhou University, Zhengzhou, Henan Province, China.
Peng WangDepartment of Epidemiology and Statistics, College of Public Health, Zhengzhou University, Zhengzhou, Henan Province, China.
Jianying ZhangDepartment of Epidemiology and Statistics, College of Public Health, Zhengzhou University, Zhengzhou, Henan Province, China.
Zhengzhou University · CN

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

introductionPrevious studies have demonstrated that autoantibodies against tumor-associated antigens (TAAs) in patients with cancer can be used as sensitive immunodiagnostic biomarkers for the detection of cancer. Most of these TAAs are involved in the tumorigenesis pathway. Cancer driver genes with intragenic mutations can promote tumorigenesis. This study aims to identify autoantibodies against TAAs encoded by cancer driver genes in sera as potential immunodiagnostic biomarkers for gastric adenocarcinoma (GAC).

methodsProtein arrays based on cancer driver genes were customized for screening candidate TAAs in 100 GAC sera and 50 normal control (NC) sera. Autoantibodies against candidate TAAs were assessed by enzyme-linked immunosorbent assay in both training group (205 GAC sera and 205 NC sera) and independent validation group (126 GAC sera and 126 NC sera). Moreover, the immunodiagnostic models were respectively established and validated in the training group and validation group.

resultsA panel with 5 autoantibodies including anti-TP53, anti-COPB1, anti-GNAS, anti-serine/arginine-rich splicing factor 2, and anti-SMARCB1 was selected by the Fisher linear discriminant analysis model with an areas under receiver operating characteristic curve (AUC) of 0.928 (95% confidence interval [CI]: 0.888-0.967) in the training cohort and an AUC of 0.885 (95% CI: 0.852-0.918) in the validation cohort. Besides, the panel with 5 autoantibodies including anti-TP53, anti-COPB1, anti-GNAS, anti-PBRM1, and anti-ACVR1B which were selected by the binary logistic regression model showed an AUC of 0.885 (95% CI: 0.852-0.919) in the training cohort and 0.884 (95% CI: 0.842-0.925) in the validation cohort. DISCUSSION: Two panels which were selected in this study could boost the detection of anti-TAA autoantibodies in sera as biomarkers for the detection of GAC.

Indexed as

AdenocarcinomaAdultAgedAged, 80 and overAntigens, NeoplasmAutoantibodiesBiomarkers, TumorCohort StudiesEnzyme-Linked Immunosorbent AssayFemaleGastric MucosaHumansMaleMiddle AgedProtein Array AnalysisROC CurveAntigens, NeoplasmAutoantibodiesBiomarkers, Tumor

Identifiers

PMID33346593
PMCPMC7752677
OpenAlexW3116084849

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC-ND
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.