ArticleMolecular & cellular proteomics : MCP2016
Identification of Serum Biomarkers for Gastric Cancer Diagnosis Using a Human Proteome Microarray.
Article in Molecular & cellular proteomics : MCP, 2016. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 59 papers.
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.
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.
Who cites it
59 citing papers in PubMed.
- Systematic evaluation of IgG responses to SARS-CoV-2 spike protein-derived peptides for monitoring COVID-19 patients.Cellular & molecular immunology · 2021Trial
- Mapping Autoantibodies in Children With Acute Rheumatic Fever.Frontiers in immunology · 2021Trial
- Autoantibody-Based Models for the Diagnosis and Activity Assessment of Takayasu Arteritis.Journal of cardiovascular translational research · 2026Article
- Advances in protein microarray-based proteomics for gastric cancer applications in biomarker discovery, molecular subtyping, and precision oncology.Frontiers in oncology · 2026Review
- Immunoproteomics: The Evolution from Classical Methods to Emerging Techniques.Methods in molecular biology (Clifton, N.J.) · 2026Review
- Article
- Unraveling the causal relationship and underlying mechanisms between cathepsins on liver cancer: findings from mendelian randomization and bioinformatics analysis.Discover oncology · 2025Article
- Screening of Cancer-Specific Biomarkers for Hepatitis B-Related Hepatocellular Carcinoma Based on a Proteome Microarray.Molecular & cellular proteomics : MCP · 2024Article
- Review
- ZPR1 is an immunodiagnostic biomarker and promotes tumor progression in esophageal squamous cell carcinoma.Cancer science · 2024Article
- PhIP-Seq: methods, applications and challenges.Frontiers in bioinformatics · 2024Review
- Circulating Proteins as Diagnostic Markers in Gastric Cancer.International journal of molecular sciences · 2023Review
- Hydrophobicity and molecular mass-based separation method for autoantibody discovery from mammalian total cellular proteins.Protein science : a publication of the Protein Society · 2023Article
- Discovery of potential biomarkers for lung cancer classification based on human proteome microarrays using Stochastic Gradient Boosting approach.Journal of cancer research and clinical oncology · 2023Article
- Human Proteome Microarray identifies autoantibodies to tumor-associated antigens as serological biomarkers for the diagnosis of hepatocellular carcinoma.Molecular oncology · 2023Article
- Identification of novel serological autoantibodies in Chinese prostate cancer patients using high-throughput protein arrays.Cancer immunology, immunotherapy : CII · 2023Article
- Screening of autoantibodies as biomarkers in the serum of renal cancer patients based on human proteome microarray.Acta biochimica et biophysica Sinica · 2022Article
- Evaluation of CSTB and DMBT1 expression in saliva of gastric cancer patients and controls.BMC cancer · 2022Article
- Temporal reproducibility of IgG and IgM autoantibodies in serum from healthy women.Scientific reports · 2022Article
- Hsa_circ_0007967 promotes gastric cancer proliferation through the miR-411-5p/MAML3 axis.Cell death discovery · 2022Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
17 authors.
Funding
Abstract
We aimed to globally discover serum biomarkers for diagnosis of gastric cancer (GC). GC serum autoantibodies were discovered and validated using serum samples from independent patient cohorts encompassing 1,401 participants divided into three groups, i.e. healthy, GC patients, and GC-related disease group. To discover biomarkers for GC, the human proteome microarray was first applied to screen specific autoantibodies in a total of 87 serum samples from GC patients and healthy controls. Potential biomarkers were identified via a statistical analysis protocol. Targeted protein microarrays with only the potential biomarkers were constructed and used to validate the candidate biomarkers using 914 samples. To provide further validation, the abundance of autoantibodies specific to the biomarker candidates was analyzed using enzyme-linked immunosorbent assays. Receiver operating characteristic curves were generated to evaluate the diagnostic accuracy of the serum biomarkers. Finally, the efficacy of prognosis efficacy of the final four biomarkers was evaluated by analyzing the clinical records. The final panel of biomarkers consisting of COPS2, CTSF, NT5E, and TERF1 provides high diagnostic power, with 95% sensitivity and 92% specificity to differentiate GC patients from healthy individuals. Prognosis analysis showed that the panel could also serve as independent predictors of the overall GC patient survival. The panel of four serum biomarkers (COPS2, CTSF, NT5E, and TERF1) could serve as a noninvasive diagnostic index for GC, and the combination of them could potentially be used as a predictor of the overall GC survival rate.
Indexed as
Identifiers
What OpenQuestion holds
Registered trials
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.