Genome-Wide Association Study of MKI67 Expression and its Clinical Implications in HBV-Related Hepatocellular Carcinoma in Southern China

Yang, Cheng Kun; Yu, Ting; Han, Chuang Ye; Qin, Wei; Liao, Xi Wen; Liu, Yu; Liu, Xiao Guang; Zhu, Guang Zhi; Su, Hao; Lu, Si Cong; Chen, Zhiwei; Liu, Zhen; Huang, Ke Tuan; Liu, Zheng Tao; Lan, Yu; Huang, Jian; Mo, Zengnan; Qin, Xue; Li, Le‐Qun; Xiao, Kai Yin; Peng, Min; Winkle, Cheryl Ann; O’Brien, Stephen J.; Peng, Tao

doi:10.1159/000478963

Cited by 29 publications

(26 citation statements)

References 52 publications

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“…In the present study, 10 cases of HCC patients in Nanjing Drum Tower Hospital were sequenced by whole-exome sequencing, and highly frequent mutant genes, such as MUC4, HYDIN, CDC27, TTN 26 , COL6A6, SYNE1, NEB, OBSCN, NEB, HSPG2, FLG, DNAH17, ASPM, AHNAK2 and XIRP2, were also detected in the TCGA database. OBSCN was associated with HCC tumor thrombectomy, while CDC27 was associated with recurrence.…”

Section: Discussionmentioning

confidence: 91%

Identification of a novel gene signature for the prediction of recurrence in HCC patients by machine learning of genome-wide databases

Shen

Liang

Zou

et al. 2020

Sci Rep

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Hepatocellular carcinoma (HCC) is a common malignant tumor in China. In the present study, we aimed to construct and verify a prediction model of recurrence in HCC patients using databases (TCGA, AMC and Inserm) and machine learning methods and obtain the gene signature that could predict early relapse of HCC. Statistical methods, such as feature selection, survival analysis and Chi-Square test in R software, were used to analyze and select mutant genes related to disease free survival (DFS), race and vascular invasion. In addition, whole-exome sequencing was performed on 10 HCC patients recruited from our center, and the sequencing results were compared with the databases. Using the databases and machine learning methods, the prediction model of recurrence was constructed and optimized, and the selected mutant genes were verified in the test group. The accuracy of prediction was 74.19%. Moreover, these 10 patients from our center were used to verify these mutant genes and the prediction model, and a success rate of 80% was achieved. Collectively, we discovered recurrence-related genes and established recurrence prediction model of recurrence for HCC patients, which could provide significant guidance for clinical prediction of recurrence. Hepatocellular carcinoma (HCC) is a common malignant tumor in China, which ranks the third in morbidity and the second in mortality. Its morbidity is usually associated with specific risk factors, including infections with HBV and HCV, high alcohol intake, obesity and consumption of aflatoxin-containing food 1. With the development of the second-generation sequencing techniques increasing research on HCC has been conducted on the molecular level. In 2014, Totoki et al. 2 have reported the whole-genome sequencing of 608 HCC patients from Asia and Europe. In 2015, Schulze et al. 3 have reported the whole-genome sequencing of 243 HCC patients from Europe and America. In 2016, Fujimoto et al. 4 have reported the whole-genome sequencing of 300 HCC patients from Japan. The molecular blueprint of HCC including somatic mutation, mRNA expression, methylation and miRNA regulation has been gradually outlined, which could be used for the diagnosis, treatment, and prediction of recurrence and survival of liver cancer patients. In 2017, TCGA working group 5 has systematically analyzed the sequencing results of the whole exome of more than 360 HCC patients in TCGA database and compared these data with other published HCC sequencing samples. Various statistical methods, related classification and clustering algorithms of machine learning have been used. TERT, TP53, CTNNB1, AXIN1, ARID1A, ARID2, RB1, ALB, APOB, PTEN, CDKN2A, DOCK2 6-15 and other somatic cells with significantly mutant genes (SMGs) and driver mutation have been identified. These findings have been rapidly applied as potential therapeutic targets and prognostic indicators in clinical practice. However, the high cost of whole-exome sequencing and whole-genome sequencing limits its use in clinical practice. Actually, patients often ...

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Section: Discussionmentioning

confidence: 91%

Identification of a novel gene signature for the prediction of recurrence in HCC patients by machine learning of genome-wide databases

Shen

Liang

Zou

et al. 2020

Sci Rep

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“… 16 , 21 , 30 In addition, ENO1 expression was positively correlated with that of MKI67, PCNA, CDK4, CDK2, and MELK, which were involved in cell cycle and DNA replication, and associated with the malignant phenotype of HCC. 31 , 32 …”

Section: Discussionmentioning

confidence: 99%

Enolase-1 serves as a biomarker of diagnosis and prognosis in hepatocellular carcinoma patients

Zhu¹,

Li²,

Yu³

et al. 2018

CMAR

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BackgroundHepatocellular carcinoma (HCC) is an aggressive malignancy with high incidence rate and poor prognosis. Enolase-1 (ENO1), a key glycolytic enzyme, has been implicated in the tumorigenesis of various cancers. However, its diagnostic value and clinical significance in HCC are unclear.MethodsData of 374 HCC tissues and 50 nontumor tissues were retrieved from The Cancer Genome Atlas database, and the expression level of ENO1 mRNA in HCC was evaluated. In addition, a meta-analysis of 12 HCC cohorts deposited in the Gene Expression Omnibus database was conducted to determine ENO1 expression levels. The diagnostic power of ENO1 in distinguishing HCC tissues from non-HCC tissues was confirmed by receiver operating characteristic (ROC) curve analysis. A tissue microarray comprising 93 HCC specimens and 87 adjacent normal specimens was used to validate ENO1 expression, and its prognostic value in HCC was ascertained by Kaplan–Meier analysis and Cox regression models. In addition, the gene set enrichment analysis was performed to predict the molecular mechanism of ENO1 action in HCC.ResultsENO1 was overexpressed in HCC tissues and associated with worse outcomes in terms of overall survival (OS) (P<0.01) and disease-free survival (P<0.01). ENO1 expression (P<0.01) was an independent prognostic variable for the OS of HCC patients. Moreover, as per the ROC curve analysis, it had good diagnostic power as well. In addition, elevated expression of ENO1 was significantly correlated with the cell cycle and DNA replication pathway, consistent with its association with pro-proliferative genes such as MKI67, PCNA, CDK4, CDK2, and MELK.ConclusionENO1 was markedly upregulated and was an oncogene-associated protein in HCC. It is a promising prognostic and diagnostic biomarker for HCC.

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“…p53, a known tumor suppressor, participates in various critical biological processes [23]. The p53 mutation plays crucial roles in HCC development.…”

Section: Discussionmentioning

confidence: 99%

Upregulated TRIM11 Exerts its Oncogenic Effects in Hepatocellular Carcinoma Through Inhibition of P53

Liu

Rao

Lou

et al. 2017

Cell Physiol Biochem

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Background/Aims: The tripartite motif containing (TRIM) family plays crucial roles in tumor development and progression. However, little is known about the function and mechanism of TRIM11 in hepatocellular carcinoma (HCC). Methods: The expression levels of TRIM11 were examined by real-time PCR, Western blot and Immunohistochemical (IHC) staining. TRIM11 knockdown cells were produced by lentivirus infection, and functional assays, such as MTT, colony formation assay, migration and invasion assays and a xenograft tumor model were used to investigate the role of TRIM11 in HCC. We also determined the effect of TRIM11 on p53 signaling and its downstream molecules. Results: We found that TRIM11 mRNA and protein levels were significantly increased in HCC tissues as compared with normal tissues; increased levels correlated with poor patient survival. By loss-and gain-of-function investigations, knockdown of TRIM11 suppressed cell proliferation, migration, invasion in vitro and tumor growth in vivo. Moreover, TRIM11 negatively regulated p53 expression. Knockdown of p53 abrogated the in vitro and in vivo biological functions of TRIM11 shRNA in HCC cells. Conclusions: These data show that TRIM11 exerts its oncogenic effect in HCC by downregulating p53 both in vitro and in vivo. Our data provide new insights into the pathogenesis of HCC and indicate that TRIM11 may serve as a new therapeutic target for HCC treatment.

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Genome-Wide Association Study of MKI67 Expression and its Clinical Implications in HBV-Related Hepatocellular Carcinoma in Southern China

Cited by 29 publications

References 52 publications

Identification of a novel gene signature for the prediction of recurrence in HCC patients by machine learning of genome-wide databases

Identification of a novel gene signature for the prediction of recurrence in HCC patients by machine learning of genome-wide databases

Enolase-1 serves as a biomarker of diagnosis and prognosis in hepatocellular carcinoma patients

Upregulated TRIM11 Exerts its Oncogenic Effects in Hepatocellular Carcinoma Through Inhibition of P53

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