Skip to main page content
U.S. flag

An official website of the United States government

Dot gov

The .gov means it’s official.
Federal government websites often end in .gov or .mil. Before sharing sensitive information, make sure you’re on a federal government site.

Https

The site is secure.
The https:// ensures that you are connecting to the official website and that any information you provide is encrypted and transmitted securely.

Access keys NCBI Homepage MyNCBI Homepage Main Content Main Navigation
. 2021 Feb 23:9:e10943.
doi: 10.7717/peerj.10943. eCollection 2021.

Identification of the hub gene BUB1B in hepatocellular carcinoma via bioinformatic analysis and in vitro experiments

Jie Fu  1   2 , Xiao Zhang  1   2 , Likun Yan  1   2 , Yaoli Shao  1   2 , Xinxu Liu  1   2 , Yuan Chu  1   2 , Ge Xu  1   2 , Xundi Xu  1   2
Affiliations

Identification of the hub gene BUB1B in hepatocellular carcinoma via bioinformatic analysis and in vitro experiments

Jie Fu et al. PeerJ. .

Abstract

Background: Hepatocellular carcinoma (HCC) is one of the most commonly diagnosed cancers and the fourth leading cause of cancer-related deaths in the world. Although the treatment of HCC has made great progress in recent years, the therapeutic effects on HCC are still unsatisfactory due to difficulty in early diagnosis, chemoresistance and high recurrence rate post-surgery.

Methods: In this study, we identified differentially expressed genes (DEGs) based on four Gene Expression Omnibus (GEO) datasets (GSE45267, GSE98383, GSE101685 and GSE112790) between HCC and normal hepatic tissues. A protein-protein interaction (PPI) network was established to identify the central nodes associated with HCC. Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) analysis of the central nodes were conducted to find the hub genes. The expression levels of the hub genes were validated based on the ONCOMINE and Gene Expression Profiling Interactive Analysis (GEPIA) databases. Additionally, the genetic alterations of the hub genes were evaluated by cBioPortal. The role of the hub genes on the overall survival (OS) and relapse survival (RFS) of HCC patients was evaluated by Kaplan-Meier plotter. At last, the mechanistic role of the hub genes was illustrated by in vitro experiments.

Results: We found the following seven hub genes: BUB1B, CCNB1, CCNB2, CDC20, CDK1, MAD2L1 and RRM2 using integrated bioinformatics analysis. All of the hub genes were significantly upregulated in HCC tissues. And the seven hub genes were associated with the OS and RFS of HCC patients. Finally, in vitro experiments indicated that BUB1B played roles in HCC cell proliferation, migration, invasion, apoptosis and cell cycle by partially affecting mitochondrial functions.

Conclusions: In summary, we identified seven hub genes that were associated with the expression and prognosis of HCC. The mechanistic oncogenic role of BUB1B in HCC was first illustrated. BUB1B might play an important role in HCC and could be potential therapeutic targets for HCC.

Keywords: BUB1B; Bioinformatic analysis; Hepatocellular carcinoma; Hub genes; In vitro.

PubMed Disclaimer

Conflict of interest statement

The authors declare there are no competing interests.

Figures

Figure 1
Figure 1. Identification of common DEGs from the GSE45267, GSE98383, GSE101685 and GSE112790 datasets.
Venn diagram of (A) upregulated and (B) downregulated DEGs between HCC tissues and normal hepatic tissues based on the four GEO datasets. The intersecting areas represent the commonly altered DEGs. DEGs, differentially expressed genes; HCC, hepatocellular carcinoma; GEO, Gene Expression Omnibus.
Figure 2
Figure 2. PPI network construction and module analysis.
(A) A PPI network was constructed based on all 81 DEGs using the STRING database. Module analysis of the PPI network was performed by the MCODE plugin of Cytoscape. (B) Twenty-nine central nodes were identified. PPI, protein–protein interaction; DEGs, differentially expressed genes; STRING, Search Tool for the Retrieval of Interacting Genes.
Figure 3
Figure 3. Meta-analysis of the mRNA expression levels of (A) BUB1B, (B) CCNB1, (C) CCNB2, (D) CDC20, (E) CDK1, (F) MAD2L1 and (G) RRM2 in HCC tissues compared with normal hepatic tissues using the ONCOMINE database.
The colored squares represent the median rank of these genes across five datasets in ONCOMINE. P < 0.05 was regarded as statistically significant. HCC, hepatocellular carcinoma. The expression level is described by Z-score.
Figure 4
Figure 4. Validation of the mRNA expression levels of (A) BUB1B, (B) CCNB1, (C) CCNB2, (D) CDC20, (E) CDK1, (F) MAD2L1 and (G) RRM2 in LIHC tissues compared with normal hepatic tissues using the GEPIA online tool.
These box plots are based on 369 hepatocellular carcinoma samples (red) and 160 normal liver samples (gray). *P < 0.05 was considered statistically significant. LIHC, liver hepatocellular carcinoma. The expression level is described by log2(TPM + 1).
Figure 5
Figure 5. Genetic alterations and prognostic values of the seven hub genes.
(A, B) The frequencies of genetic alterations of the seven hub genes in HCC tissues were identified by cBioPortal. The specific mutation information for (C) BUB1B, (D) CCNB1, (E) CCNB2, (F) CDC20, (G) CDK1, (H) MAD2L1 and (I) RRM2 is displayed individually. (J, K) HCC cases with altered hub gene expression exhibited significantly worse OS and DFS compared to those with unaltered hub gene expression. HCC, hepatocellular carcinoma. OS, overall survival; DFS, disease-free survival.
Figure 6
Figure 6. OS of the seven hub genes (A) BUB1B, (B) CCNB1, (C) CCNB2, (D) CDC20, (E) CDK1, (F) MAD2L1 and (G) RRM2 in patients with HCC were analyzed by Kaplan–Meier plotter.
The data are presented as the hazard ratios with 95% confidence intervals. Log–rank P < 0.01 was regarded as statistically significant. OS, overall survival; HCC, hepatocellular carcinoma.
Figure 7
Figure 7. RFS of the seven hub genes (A) BUB1B, (B) CCNB1, (C) CCNB2, (D) CDC20, (E) CDK1, (F) MAD2L1 and (G) RRM2 in patients with HCC were analyzed by Kaplan–Meier plotter.
The data are presented as hazard ratios with 95% confidence intervals. Log–rank P < 0.01 was regarded as statistically significant. RFS, relapse-free survival; HCC, hepatocellular carcinoma.
Figure 8
Figure 8. Correlations between BUB1B and (A) CCNB1, (B) CCNB2, (C) CDC20, (D) CDK1, (E) MAD2L1 and (F) RRM2 were analyzed by GEPIA.
GEPIA, gene expression profiling interactive analysis.
Figure 9
Figure 9. Decreased BUB1B expression inhibited the proliferation, migration, and invasion, promoted the apoptosis and blocked cell cycle of HCC cells.
(A) The mRNA expression levels of BUB1B were detected in HCC cells and normal hepatic cells. (B) qRT-PCR was used to confirm the knockdown efficiency of the siRNAs against BUB1B. (C–G) CCK-8 assays and colony formation assays were performed to evaluate the proliferation of the HCC cell lines. (H–M) The effects of BUB1B knockdown on cell migration and invasion were determined by Transwell assays. (N–S) The cell apoptosis rate and cell cycle were analyzed by flow cytometry in HCC cells. HCC, hepatocellular carcinoma; CCK-8, Cell Counting Cit-8. ∗P < 0.05, ∗∗P < 0.01, ∗∗∗P < 0.001.
Figure 10
Figure 10. BUB1B plays a role in mitochondrial function.
Total ATP production was detected in different treatment groups (A). Mitochondrial membrane potential was analyzed by JC-1 staining (B, C). The basal OCR of HCC cells were measured using an XF-24 analyzer (D). OCR, oxygen consumption rate; HCC, hepatocellular carcinoma. ∗P < 0.05, ∗∗P < 0.01, ∗∗∗P < 0.001.
See this image and copyright information in PMC

References

    1. Abal M, Obrador-Hevia A, Janssen KP, Casadome L, Menendez M, Carpentier S, Barillot E, Wagner M, Ansorge W, Moeslein G, Fsihi H, Bezrookove V, Reventos J, Louvard D, Capella G, Robine S. APC inactivation associates with abnormal mitosis completion and concomitant BUB1B/MAD2L1 up-regulation. Gastroenterology. 2007;132:2448–2458. doi: 10.1053/j.gastro.2007.03.027. - DOI - PubMed
    1. Barrett T, Suzek TO, Troup DB, Wilhite SE, Ngau WC, Ledoux P, Rudnev D, Lash AE, Fujibuchi W, Edgar R. NCBI GEO: mining millions of expression profiles–database and tools. Nucleic Acids Research. 2005;33:D562–D566. doi: 10.1093/nar/gki022. - DOI - PMC - PubMed
    1. Buisson R, Langenbucher A, Bowen D, Kwan EE, Benes CH, Zou L, Lawrence MS. Passenger hotspot mutations in cancer driven by APOBEC3A and mesoscale genomic features. Science. 2019;364(6447):eaaw2872. doi: 10.1126/science.aaw2872. - DOI - PMC - PubMed
    1. Cancer Genome Atlas Research. Weinstein JN, Collisson EA, Mills GB, Shaw KR, Ozenberger BA, Ellrott K, Shmulevich I, Sander C, Stuart JM. The Cancer Genome Atlas Pan-Cancer analysis project. Nature Genetics. 2013;45:1113–1120. doi: 10.1038/ng.2764. - DOI - PMC - PubMed
    1. Davis RT, Blake K, Ma D, Gabra MBI, Hernandez GA, Phung AT, Yang Y, Maurer D, Lefebvre A, Alshetaiwi H, Xiao Z, Liu J, Locasale JW, Digman MA, Mjolsness E, Kong M, Werb Z, Lawson DA. Transcriptional diversity and bioenergetic shift in human breast cancer metastasis revealed by single-cell RNA sequencing. Nature Cell Biology. 2020;22:310–320. doi: 10.1038/s41556-020-0477-0. - DOI - PubMed

LinkOut - more resources