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pmid:33083480

Identification of the Sixth Complement Component as Potential Key Genes in Hepatocellular Carcinoma via Bioinformatics Analysis.

Di Mu · Feng Qin · Baoshan Li · Qian Zhou

BioMed research international · 2020 doi:10.1155/2020/7042124

Paper

complete

Experiment

partial

Data

partial

Analysis

partial

Execution

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title
Identification of the Sixth Complement Component as Potential Key Genes in Hepatocellular Carcinoma via Bioinformatics Analysis.
doi
10.1155/2020/7042124
pmid
33083480
authors array · 4 items
[0]
Di Mu
[1]
Feng Qin
[2]
Baoshan Li
[3]
Qian Zhou
journal
BioMed research international
year
2020
abstract
The present study is designed to determine potential target genes involved in hepatocellular carcinoma (HCC) and provide possible underlying mechanisms of action. Several studies (GSE112790, GSE87630, and GSE56140) from the GEO database looking at molecular characteristics in HCC were screened and analyzed by GEO2R, which led to the identification of a total of 93 differentially expressed genes (DEGs). From the protein-protein interaction (PPI) network, we selected 13 key genes with high degree of variability in expression in HCC. Expression of three key genes (NQO1, CYP2C9, and C6) presented with poor overall survival (OS) in HCC patients by UALCAN. C6, which is a complement component, was found by ONCOMINE and TIMER to have low expression in many solid cancers including HCC. Besides, Kaplan-Meier plotter and UALCAN database analysis to access diseases prognosis suggested that low expression of C6 is significantly related to worse OS in LIHC patients, especially in advanced HCC patients. Finally, the TIMER analysis suggested that the C6 expression showed significant negative correlation with infiltrating levels of six immune cells. The somatic copy number alterations (SCNAs) of C6 were associated with CD4+ T cell infiltration in HCC. Taken together, these results together identified C6 as a potential key gene in the diagnosis and prognosis of HCC.
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DEGs between the HCC groups and the nontumor groups in the three datasets were determined by the online tool GEO2R, using following cutoff criteria: adjusted P value should be less than 0.01, and the absolute value of log FC (fold change) should be above 1.5.
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sections[3] "2.1. Microarray Data and Identification of DEGs" paragraph 3
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DEGs between the HCC groups and the nontumor groups in the three datasets were determined by the online tool GEO2R, using following cutoff criteria: adjusted P value should be less than 0.01, and the absolute value of log FC (fold change) should be above 1.5.
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sections[20] "Data Availability" paragraph 2
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Comprehensive molecular characterization of liver cancer and inheritance of the phenotypic traits during tumor recurrence [tissue]
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Integrated analysis of genomic and epigenomic regulation of transcriptome identifies molecular subtypes of liver cancer (gene expression)
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3.1. Identification, Function Enrichment Analysis of DEGs, and Selection of Key Genes
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The correlation of the C6 mRNA expression and overall survival in other four cancer types with UALCAN database.
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3.3. The C6 Expression Level and Prognostic Potential across Various Cancer
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The correlation of the C6 mRNA expression and overall survival in other four cancer types with UALCAN database.
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DEGs between the HCC groups and the nontumor groups in the three datasets were determined by the online tool GEO2R, using following cutoff criteria: adjusted P value should be less than 0.01, and the absolute value of log FC (fold change) should be above 1.5.
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The open available data sources or tools are as following: (1) http://www.ncbi.nlm.nih.gov/geo/, (2) http://bioinformatics.psb.ugent.be/webtools/Venn/, (3) https://david.ncifcrf.gov/, (4) http://gepia.cancer-pku.cn/index.html, (5) https://www.oncomine.org/resource/login.html, (6) https://cistrome.shinyapps.io/timer/, and (7) http://ualcan.path.uab.edu/.
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{"sci_version": "1.2", "schema": "https://corpus.bntrg.co.uk/sci/1.0/sci.schema.json", "id": "pmid:33083480", "kind": "science-record", "revision": 7, "content_hash": "sha256:2b97455e3640e0efb3206e30bd2c61425c75ce118ff7057fedf1fe6271e2e3fb", "created_at": "2026-11-01T15:41:13Z", "updated_at": "2026-11-01T22:02:22Z", "generator": {"name": "corpus-assay-engine", "run_id": "reading-sci-2026-11-01"}, "paper": {"state": "complete", "title": "Identification of the Sixth Complement Component as Potential Key Genes in Hepatocellular Carcinoma via Bioinformatics Analysis.", "doi": "10.1155/2020/7042124", "pmid": "33083480", "authors": ["Di Mu", "Feng Qin", "Baoshan Li", "Qian Zhou"], "journal": "BioMed research international", "year": 2020, "abstract": "The present study is designed to determine potential target genes involved in hepatocellular carcinoma (HCC) and provide possible underlying mechanisms of action. Several studies (GSE112790, GSE87630, and GSE56140) from the GEO database looking at molecular characteristics in HCC were screened and analyzed by GEO2R, which led to the identification of a total of 93 differentially expressed genes (DEGs). From the protein-protein interaction (PPI) network, we selected 13 key genes with high degree of variability in expression in HCC. Expression of three key genes (NQO1, CYP2C9, and C6) presented with poor overall survival (OS) in HCC patients by UALCAN. C6, which is a complement component, was found by ONCOMINE and TIMER to have low expression in many solid cancers including HCC. Besides, Kaplan-Meier plotter and UALCAN database analysis to access diseases prognosis suggested that low expression of C6 is significantly related to worse OS in LIHC patients, especially in advanced HCC patients. Finally, the TIMER analysis suggested that the C6 expression showed significant negative correlation with infiltrating levels of six immune cells. The somatic copy number alterations (SCNAs) of C6 were associated with CD4+ T cell infiltration in HCC. Taken together, these results together identified C6 as a potential key gene in the diagnosis and prognosis of HCC.", "claims": [{"id": "claim-method", "statement": "DEGs between the HCC groups and the nontumor groups in the three datasets were determined by the online tool GEO2R, using following cutoff criteria: adjusted P value should be less than 0.01, and the absolute value of log FC (fold change) should be above 1.5.", "kind": "methodological", "target": null, "evidence": [{"asset": "source:pmid:33083480", "locator": "sections[3] \"2.1. 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