Evidence map›Paper›PMID 33974527›Full record

ArticleBosnian journal of basic medical sciences2021

Integrated profiling identifies ITGB3BP as prognostic biomarker for hepatocellular carcinoma.

Qiuli Liang, Chao Tan, Feifei Xiao, Fuqiang Yin, Meiliang Liu, Lei Lei, Liuyu Wu, Yu Yang, Hui Juan Jennifer Tan, Shun Liu and 1 more

Open access · goldAbstract read
In one paragraph

Article in Bosnian journal of basic medical sciences, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers.

0numbers the graph read from it
0cells of the map it votes in
6citing papers in PubMed
0.4field-weighted citation impact, top 43% 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

6 citing papers in PubMed, 4 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 2 institutions in 2 countries.

Qiuli LiangDepartment of Epidemiology and Statistics, School of Public Health, Guangxi Medical University, Nanning, China.
Chao TanDepartment of Epidemiology and Statistics, School of Public Health, Guangxi Medical University, Nanning, China; Department of Epidemiology and Statistics, School of Public Health, Guilin Medical University, Guilin, China.
Feifei XiaoDepartment of Epidemiology and Biostatistics, University of South Carolina, Columbia, SC, United States.
Fuqiang YinLife Sciences Institute, Guangxi Medical University, Nanning, China; Key Laboratory of High-Incidence-Tumor Prevention and Treatment, Guangxi Medical University, Ministry of Education, Nanning, China.
Meiliang LiuDepartment of Epidemiology and Statistics, School of Public Health, Guangxi Medical University, Nanning, China.
Lei LeiDepartment of Epidemiology and Statistics, School of Public Health, Guangxi Medical University, Nanning, China.
Liuyu WuHospital Infection Management Department, Liuzhou Workers' hospital, Liuzhou, China.
Yu YangDepartment of Epidemiology and Statistics, School of Public Health, Guangxi Medical University, Nanning, China.
Hui Juan Jennifer TanLife Sciences Institute, Guangxi Medical University, Nanning, China.
Shun LiuDepartment of Epidemiology and Statistics, School of Public Health, Guangxi Medical University, Nanning, China.
Xiaoyun ZengDepartment of Epidemiology and Statistics, School of Public Health, Guangxi Medical University, Nanning, China; Key Laboratory of High-Incidence-Tumor Prevention and Treatment, Guangxi Medical University, Ministry of Education, Nanning, China.
Guangxi Medical University · CNUniversity of South Carolina · US

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Hepatocellular carcinoma (HCC) is a highly malignant tumor. In this study, we sought to identify a novel biomarker for HCC by analyzing transcriptome and clinical data. The R software was used to analyze the differentially expressed genes (DEGs) in the datasets GSE74656 and GSE84598 downloaded from the Gene Expression Omnibus database, followed by a functional annotation. A total of 138 shared DEGs were screened from two datasets. They were mainly enriched in the "Metabolic pathways" pathway (Padj = 8.21E-08) and involved in the carboxylic acid metabolic process (Padj = 0.0004). The top 10 hub genes were found by protein-protein interaction analysis and were upregulated in HCC tissues compared to normal tissues in The Cancer Genome Atlas database. Survival analysis distinguished 8 hub genes CENPE, SPDL1, Hyaluronan-mediated motility receptor, Rac GTPase activating protein 1, Thyroid hormone receptor interactor 13, cytoskeleton-associated protein (CKAP) 2, CKAP5, and Integrin subunit beta 3 binding protein (ITGB3BP) were considered as prognostic hub genes. Multivariate cox regression analysis indicated that all the prognostic hub genes were independent prognostic factors for HCC. Furthermore, the receiver operating characteristic curve revealed that the 8-hub genes model had better prediction performance for overall survival compared to the T stage (p = 0.008) and significantly improved the prediction value of the T stage (p = 0.002). The Human Protein Atlas showed that the protein expression of ITGB3BP was upregulated in HCC, so the expression of ITGB3BP was further verified in our cohort. The results showed that ITGB3BP was upregulated in HCC tissues and was significantly associated with lymph node metastasis.

Indexed as

Gene Expression ProfilingBiomarkers, TumorCarcinoma, HepatocellularFemaleGene Expression Regulation, NeoplasticHumansLiver NeoplasmsMaleMiddle AgedNuclear ProteinsPrognosisSoftwareUp-RegulationBiomarkers, TumorITGB3BP protein, humanNuclear Proteins

Identifiers

PMID33974527
PMCPMC8554696
OpenAlexW3152519253

What OpenQuestion holds

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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.