PTTG1 is involved in TNF‐α‐related hepatocellular carcinoma via the induction of c‐myc

Lin, Xiao; Yang, Yidong; Guo, Yi; Liu, Huiling; Jiang, Jie; Fang, Zheng; Wu, Bin

doi:10.1002/cam4.2473

Cited by 37 publications

(27 citation statements)

References 43 publications

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“…It should be noted that among these genes are those connected with viral infections as well as tumor progression. It proves that PTTG3P , PTTG1 and PTTG2 may function as oncogenes in HNSCC, similarly as was indicated in other cancers [ 17 , 30 , 31 , 34 , 36 , 37 , 38 , 39 , 40 ].…”

Section: Discussionsupporting

confidence: 76%

“…Similarly, the second member, PTTG1 , has been reported to promote migration and invasion in non-small cell lung cancer [ 11 ]. It has also been shown to play the role of an inflammation-related oncogene in hepatocellular carcinoma [ 31 ] Additionally, PTTG1 was found to induce epithelial–mesenchymal transition in colon carcinoma [ 32 ].…”

Section: Discussionmentioning

confidence: 99%

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The Oncogenic Roles of PTTG1 and PTTG2 Genes and Pseudogene PTTG3P in Head and Neck Squamous Cell Carcinomas

et al. 2020

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Background: Head and neck squamous cell carcinomas are a group of heterogeneous diseases that occur in the mouth, pharynx and larynx and are characterized by poor prognosis. A low overall survival rate leads to a need to develop biomarkers for early head and neck squamous cell carcinomas detection, accurate prognosis and appropriate selection of therapy. Therefore, in this paper, we investigate the biological role of the PTTG3P pseudogene and associated genes PTTG1 and PTTG2 and their potential use as biomarkers. Methods: Based on TCGA data and the UALCAN database, PTTG3P, PTTG1 and PTTG2 expression profiles and clinicopathological features with TP53 gene status as well as expression levels of correlated genes were analyzed in patients’ tissue samples. The selected genes were classified according to their biological function using the PANTHER tool. Gene Set Enrichment Analysis software was used for functional enrichment analysis. All statistical analyses were performed using GraphPad Prism 5. Results: In head and neck squamous cell carcinomas, significant up-regulation of the PTTG3P pseudogene, PTTG1 and PTTG2 genes’ expression between normal and cancer samples were observed. Moreover, the expression of PTTG3P, PTTG1 and PTTG2 depends on the type of mutation in TP53 gene, and they correlate with genes from p53 pathway. PTTG3P expression was significantly correlated with PTTG1 as well as PTTG2, as was PTTG1 expression with PTTG2. Significant differences between expression levels of PTTG3P, PTTG1 and PTTG2 in head and neck squamous cell carcinomas patients were also observed in clinicopathological contexts. The contexts taken into consideration included: T-stage for PTTG3P; grade for PTTG3, PTTG1 and PTTG2; perineural invasion and lymph node neck dissection for PTTG1 and HPV p16 status for PTTG3P, PTTG1 and PTTG2. A significantly longer disease-free survival for patients with low expressions of PTTG3P and PTTG2, as compared to high expression groups, was also observed. Gene Set Enrichment Analysis indicated that the PTTG3 high-expressing group of patients have the most deregulated genes connected with DNA repair, oxidative phosphorylation and peroxisome pathways. For PTTG1, altered genes are from DNA repair groups, Myc targets, E2F targets and oxidative phosphorylation pathways, while for PTTG2, changes in E2F targets, G2M checkpoints and oxidative phosphorylation pathways are indicated. Conclusions: PTTG3P and PTTG2 can be used as a prognostic biomarker in head and neck squamous cell carcinomas diagnostics. Moreover, patients with high expressions of PTTG3P, PTTG1 or PTTG2 have worse outcomes due to upregulation of oncogenic pathways and more aggressive phenotypes.

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Section: Discussionsupporting

confidence: 76%

Section: Discussionmentioning

confidence: 99%

The Oncogenic Roles of PTTG1 and PTTG2 Genes and Pseudogene PTTG3P in Head and Neck Squamous Cell Carcinomas

et al. 2020

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“…Enriched genes such as KIF18A [Luo et al 2018], MCM6 [Liu et al 2018], SKA1 [Xiao et al 2019] and ACTG2 [Wu et al 2017] were involved in invasion of hepatocellular carcinoma cells, but these genes may be associated with invasion of hepatoblastoma cells. Enriched genes such as PTTG1 [Lin et al 2019], CENPF (centromere protein F) [Li et al 2018], HJURP (Holliday junction recognition protein) [Chen et al 2018], MCM2 [Yang et al 2018], MCM7 [Qu et al 2017], RRM2 [Wang et al 2016], SGO1 [Wang et al 2015], NDC80 [Ju et al 2017], FOXM1 [Yu et al 2016], SKP2 [Wei et al 2018], TPX2 [Chen et al 2018], PLK4 [Bao et al 2018], NUF2 [Wang et al 2019], CENPK (centromere protein K) [Wang et al 2019], NCAPG (non-SMC condensin I complex subunit G) [Zhang et al 2018], BUB1 [Xu et al 2017], E2F5 [Sun et al 2016], RFC3 [Yao et al 2015], NCAPH (non-SMC condensin I complex subunit H) [Sun et al 2019], CCNB1 [Gu et al 2019], CDK1 [Gao et al 2018], CDC25C [Sun et al 2015], MAD2L1 [Li et al 2017], CDK6 [Zhu et al 2016], DKK1 [Zhang et al 2016], DKK4 [Chouhan et al 2016], DKK2 [Lin et al 2016] and LEF1 [Hu et al 2018] were important for proliferation of hepatocellular carcinoma cells, but these genes may be involved in proliferation of hepatoblastoma cells. High expression of enriched genes such as SPC25 [Chen et al 2018], MCM4 [Xie et al 2017], TYMS (thymidylatesynthetase) [Lee et al 2013], KNTC1 [Liu et al 2019] and CDH11 [Chen et al 2018] were responsible for advancement of various cancer types, but over expression these gene may be liable for progression of hepatoblastoma.…”

Section: Discussionmentioning

confidence: 99%

Identification of potential core genes in hepatoblastoma via bioinformatics analysis

Vastrad¹,

Vastrad²,

Kotturshetti³

2020

Preprint

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Hepatoblastoma is the childhood liver cancer. Profound efforts have been made to illuminate the pathology, but the molecular mechanisms of hepatoblastoma are still not well understood. To identify the candidate genes in the carcinogenesis and progression of hepatoblastoma, microarray dataset GSE131329 was downloaded from Gene Expression Omnibus (GEO) database. The differentially expressed genes (DEGs) were identified, and pathway and Gene Ontology (GO) enrichment analysis were performed. The protein-protein interaction network (PPI), module analysis, target gene - miRNA regulatory network and target gene - TF regulatory network were constructed and analyzed. A total of 996 DEGs were identified, consisting of 499 up regulated genes and 497 down regulated genes. The pathway and Gene Ontology (GO) enrichment analysis of the DEGs include proline biosynthesis, superpathway of tryptophan utilization, chromosome organization and organic acid metabolic process. Twenty-four hub genes were identified and biological process analysis revealed that these genes were mainly enriched in cell cycle, chromosome organization, lipid metabolic process and oxidation-reduction process. Validation of hub genes showed that TP53, PLK1, AURKA, CDK1, ANLN, ESR1, FGB, ACAT1, GOT1 and ALAS1 may be involved in the carcinogenesis, invasion or recurrence of hepatoblastoma. In conclusion, DEGs and hub genes identified in the present study help us understand the molecular mechanisms underlying the carcinogenesis and progression of hepatoblastoma, and provide candidate targets for diagnosis and treatment of hepatoblastoma.

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“…In the present study, twenty genes were identified as hub genes. Unsurprisingly, some have been associated with HCC, such as CD20 [13], PTTG1 [14], CDCA5 [15], HSP90AB1 [16], CCT3 [17], SF3B4 [16], SETDB1 [17], VPS45 [18], RACGAP1 [19], USP21 [20, 21], and KIF20A [22]. In addition, we also found that MED24, FOXD2 and ZNF282 are associated with the progression from cirrhosis to HCC.…”

Section: Discussionmentioning

confidence: 99%

A twenty gene-based gene set variation score reflects the pathological progression from cirrhosis to hepatocellular carcinoma

Lin

Liang

et al. 2019

Aging

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The molecular mechanism of the pathological progression from cirrhosis to hepatocellular carcinoma (HCC) remains elusive. In the present study, tissue samples from normal liver, cirrhosis and HCC were subjected to differentially gene expression analysis, weighted gene correlation network analysis to identify the twenty hub genes (TOP2A, CDC20, PTTG1, CDCA5, CCNB2, PRC1, KIF20A, SF3B4, HSP90AB1, FOXD2, PLOD3, CCT3, SETDB1, VPS45, SPDL1, RACGAP1, MED24, KIAA0101, ZNF282, and USP21) in the pathological progression from cirrhosis to HCC. Each sample was calculated a hub gene set variation analysis (HGSVA) score using Gene Set Variation Analysis, The HGSVA score significantly increased with progression from cirrhosis to HCC, and this result was validated in two independent data sets. Moreover, this score may be used as a blood-based marker for HCC and is an independent prognostic factor of recurrence-free survival (RFS) and overall survival (OS). High expression of the hub genes may be driven by hypomethylation. The twenty gene-based gene set variation score may reflect the pathological progression from cirrhosis to HCC and is an independent prognostic factor for both OS and RFS.

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PTTG1 is involved in TNF‐α‐related hepatocellular carcinoma via the induction of c‐myc

Cited by 37 publications

References 43 publications

The Oncogenic Roles of PTTG1 and PTTG2 Genes and Pseudogene PTTG3P in Head and Neck Squamous Cell Carcinomas

The Oncogenic Roles of PTTG1 and PTTG2 Genes and Pseudogene PTTG3P in Head and Neck Squamous Cell Carcinomas

Identification of potential core genes in hepatoblastoma via bioinformatics analysis

A twenty gene-based gene set variation score reflects the pathological progression from cirrhosis to hepatocellular carcinoma

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