Evidence map›Paper›PMID 41164825›Full record

ArticleFrontiers in molecular biosciences2025

ITRAQ and PRM-based quantitative saliva proteomics in gastric cancer: biomarker discovery.

Zhanyan Liu, Jieren Liu, Zaid Chachar, Jimao Mo, Haoran Chi, Runtao Wen, Kaixin Luo, Lei Huang, Guanlin Li, Chenhao Zhang and 4 more

Abstract read
PubMed Full text at PMC Publisher
In one paragraph

Article in Frontiers in molecular biosciences, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing papers in PubMed
–field-weighted citation impact
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

1 citing paper in PubMed.

  1. 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

14 authors.

Zhanyan Liu *The First Affiliated Hospital of Shenzhen University, Shenzhen Second People's Hospital, Medical Innovation Technology Transformation Center of Shenzhen Second People's Hospital, Shenzhen University, Shenzhen Translational Medicine Institute, Shenzhen, China.
Jieren Liu *School of Big Data and Internet, Shenzhen Technology University, Shenzhen, China.
Zaid Chachar *School of Data Science, The Chinese University of Hong Kong, Shenzhen, China.
Jimao MoSchool of Big Data and Internet, Shenzhen Technology University, Shenzhen, China.
Haoran ChiSchool of Big Data and Internet, Shenzhen Technology University, Shenzhen, China.
Runtao WenSchool of Big Data and Internet, Shenzhen Technology University, Shenzhen, China.
Kaixin LuoSchool of Big Data and Internet, Shenzhen Technology University, Shenzhen, China.
Lei HuangSchool of Big Data and Internet, Shenzhen Technology University, Shenzhen, China.
Guanlin LiThe First Affiliated Hospital of Shenzhen University, Shenzhen Second People's Hospital, Medical Innovation Technology Transformation Center of Shenzhen Second People's Hospital, Shenzhen University, Shenzhen Translational Medicine Institute, Shenzhen, China.
Chenhao ZhangSchool of Big Data and Internet, Shenzhen Technology University, Shenzhen, China.
Yuanru MaoSchool of Big Data and Internet, Shenzhen Technology University, Shenzhen, China.
Yuanzhe CaiSchool of Big Data and Internet, Shenzhen Technology University, Shenzhen, China.
Zhengzhi WuThe First Affiliated Hospital of Shenzhen University, Shenzhen Second People's Hospital, Medical Innovation Technology Transformation Center of Shenzhen Second People's Hospital, Shenzhen University, Shenzhen Translational Medicine Institute, Shenzhen, China.
Feijuan HuangThe First Affiliated Hospital of Shenzhen University, Shenzhen Second People's Hospital, Medical Innovation Technology Transformation Center of Shenzhen Second People's Hospital, Shenzhen University, Shenzhen Translational Medicine Institute, Shenzhen, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Background: Salivary proteomics is a non-invasive, low-cost, and real-time diagnostic approach increasingly applied in cancer research. Salivary biomarkers hold particular promise for the early identification of gastric cancer (GC). This study aimed to detect salivary proteins altered in GC and evaluate their potential as novel non-invasive biomarkers. Methods: We analyzed salivary proteomes from GC patients (group 1: Results: A total of 671 proteins with unique peptide segments were identified. Among them, 124 and 102 proteins were significantly differentially expressed in GC groups 1 and 2, respectively, compared with controls. Fifty-six overlapping DEPs were detected between the two GC groups, including 24 upregulated and 32 downregulated proteins. Functional enrichment and PRM validation highlighted four key proteins (S100A8, S100A9, CST4, CST5) with consistent differential expression. Interestingly, CST4 and CST5 were downregulated in saliva but upregulated in GC tissue and blood. Conclusion: Our findings demonstrate that salivary proteins, particularly S100A8, S100A9, CST4, and CST5, hold significant potential as non-invasive biomarkers for gastric cancer detection. These results provide new insights into saliva-based diagnostics and highlight the importance of cross-comparison with tissue and blood expression profiles.

Indexed as

biomarkersgastric canceriTRAQPRMproteomicsaliva

Identifiers

PMID41164825
PMCPMC12559802

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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.