Evidence map›Paper›PMID 33490271›Full record

ArticleBioMed research international2021

COL1A1 Is a Potential Prognostic Biomarker and Correlated with Immune Infiltration in Mesothelioma.

Cangang Zhang, Shanshan Liu, Xin Wang, Haiyan Liu, Xiaobo Zhou, Haibo Liu

Open access · hybridAbstract read
In one paragraph

Article in BioMed research international, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 25 papers.

0numbers the graph read from it
0cells of the map it votes in
25citing papers in PubMed
3.8field-weighted citation impact, top 6% 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

25 citing papers in PubMed, 32 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

6 authors at 2 institutions in 1 country.

Cangang ZhangDepartment of Pathogenic Microbiology and Immunology, School of Basic Medical Sciences, Xi'an Jiaotong University, Xi'an, 710061 Shaanxi, China.ORCID https://orcid.org/0000-0001-6443-7023
Shanshan LiuHealth Science Center, Xi'an Jiaotong University, Xi'an, 710061 Shaanxi, China.
Xin WangDepartment of Pathogenic Microbiology and Immunology, School of Basic Medical Sciences, Xi'an Jiaotong University, Xi'an, 710061 Shaanxi, China.
Haiyan LiuDepartment of Pathogenic Microbiology and Immunology, School of Basic Medical Sciences, Xi'an Jiaotong University, Xi'an, 710061 Shaanxi, China.
Xiaobo ZhouDepartment of Pathogenic Microbiology and Immunology, School of Basic Medical Sciences, Xi'an Jiaotong University, Xi'an, 710061 Shaanxi, China.ORCID https://orcid.org/0000-0002-2305-2255
Haibo LiuDepartment of Hematology, The First Affiliated Hospital of Xi'an Jiaotong University, Xi'an, 710061 Shaanxi, China.ORCID https://orcid.org/0000-0003-3091-8798
First Affiliated Hospital of Xi'an Jiaotong University · CNXi'an Jiaotong University · CN

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

objectiveMesothelioma (MESO) is a rare tumor derived from mesothelium cells. The aim of this study was to explore key candidate genes and potential molecular mechanisms for mesothelioma through bioinformatics analysis.

methodsThe MESO expression profiles came from the Gene Expression Omnibus (GEO) and The Cancer Genome Atlas (TCGA) databases. The differences in the infiltration levels of immune cells between MESO and normal tissues were assessed using CIBERSORT. Differentially expressed genes (DEGs) were identified by comprehensive analysis of multiple datasets. A protein-protein interaction (PPI) network was constructed, and a hub gene COL1A1 was selected for MESO. The expression and mutation of COL1A1 in MESO were analyzed in the cBioPortal database. The correlation between COL1A1 expression and immune cell infiltration was evaluated using the TIMER database. Gene Set Enrichment Analysis (GSEA) of COL1A1 was then performed. Finally, Kaplan-Meier survival analysis was presented to predict the survival times between high and low COL1A1 expression groups for MESO patients.

resultsThere were distinct differences in the infiltration levels of immune cells between MESO and normal tissues. A total of 118 DEGs were identified by comprehensively analyzing three expression profile datasets. COL1A1, a hub gene, was identified to be highly expressed in MESO compared to normal tissues. COL1A1 genetic mutation occurred in 9% of MESO samples, and amplification was the most common type of mutation. COL1A1 expression was significantly correlated to the infiltration levels of CD4+ T cells, macrophages, and neutrophils. GSEA results indicated that COL1A1 could be involved in key biological processes and pathways like extracellular matrix and PI3K-Akt pathway. Patients with high COL1A1 expression usually experienced shorten overall survival time than those with its low expression.

conclusionOur findings revealed that COL1A1 could become a potential prognostic biomarker for MESO, which was significantly related to immune cell infiltration.

Indexed as

MesotheliomaBiomarkers, TumorCollagen Type ICollagen Type I, alpha 1 ChainComputational BiologyFemaleHumansMaleMutationPrognosisProtein Interaction MapsTranscriptomeBiomarkers, TumorCollagen Type ICollagen Type I, alpha 1 Chain

Identifiers

PMID33490271
PMCPMC7803428
OpenAlexW3120997854

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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.