A miR‐194/PTBP1/CCND3 axis regulates tumor growth in human hepatocellular carcinoma

Kang, Hyeran; Heo, Sungeun; Shin, Jung Jae; Ji, Eunbyul; Tak, Hyosun; Ahn, Sojin; Lee, Kyung Jin; Lee, Eun Kyung; Kim, Wook

doi:10.1002/path.5325

Cited by 40 publications

(38 citation statements)

References 48 publications

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“…IGF2 mRNA-binding proteins (IGF2BPs) can specifically bind to the lncRNA HULC (Highly Up-regulated in Liver Cancer) HULC, thereby controlling its expression [ 23 ]. Polypyrimidine tract-binding protein 1 (PTBP1) is highly expressed in hepatocellular carcinoma and promotes the translation of cyclin D3 (CCND3) via interacting with the 5′-untranslated region (5′-UTR) of its mRNA, thereby playing a role in the development of hepatocellular carcinoma [ 24 ].RBPs are capable of specifically binding to conserved 3′-UTR sequences in target mRNAs, thereby modulating their stability and subsequent translation [ 25 , 26 ]. Appropriate regulation of DNA modification is essential to ensure that chromosomes replicate correctly, and that genes are expressed or silenced in a context-appropriate manner [ 27 ].…”

Section: Discussionmentioning

confidence: 99%

Development and validation of an RNA binding protein-associated prognostic model for hepatocellular carcinoma

et al. 2020

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Background Hepatocellular carcinoma (HCC) is among the deadliest forms of cancer. While RNA-binding proteins (RBPs) have been shown to be key regulators of oncogenesis and tumor progression, their dysregulation in the context of HCC remains to be fully characterized. Methods Data from the Cancer Genome Atlas - liver HCC (TCGA-LIHC) database were downloaded and analyzed in order to identify RBPs that were differentially expressed in HCC tumors relative to healthy normal tissues. Functional enrichment analyses of these RBPs were then conducted using the GO and KEGG databases to understand their mechanistic roles. Central hub RBPs associated with HCC patient prognosis were then detected through Cox regression analyses, and were incorporated into a prognostic model. The prognostic value of this model was then assessed through the use of Kaplan-Meier curves, time-related ROC analyses, univariate and multivariate Cox regression analyses, and nomograms. Lastly, the relationship between individual hub RBPs and HCC patient overall survival (OS) was evaluated using Kaplan-Meier curves. Finally, find protein-coding genes (PCGs) related to hub RBPs were used to construct a hub RBP-PCG co-expression network. Results In total, we identified 81 RBPs that were differentially expressed in HCC tumors relative to healthy tissues (54 upregulated, 27 downregulated). Seven prognostically-relevant hub RBPs (SMG5, BOP1, LIN28B, RNF17, ANG, LARP1B, and NR0B1) were then used to generate a prognostic model, after which HCC patients were separated into high- and low-risk groups based upon resultant risk score values. In both the training and test datasets, we found that high-risk HCC patients exhibited decreased OS relative to low-risk patients, with time-dependent area under the ROC curve values of 0.801 and 0.676, respectively. This model thus exhibited good prognostic performance. We additionally generated a prognostic nomogram based upon these seven hub RBPs and found that four other genes were significantly correlated with OS. Conclusion We herein identified a seven RBP signature that can reliably be used to predict HCC patient OS, underscoring the prognostic relevance of these genes.

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Section: Discussionmentioning

confidence: 99%

Development and validation of an RNA binding protein-associated prognostic model for hepatocellular carcinoma

et al. 2020

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“…Thus, these miRNAs are abundantly expressed in normal liver [27] and seven of them (miR-122, let-7a, miR-22, -125b, -143, -194 and -24) are within the first 20 liver-specific miRNAs called "atlas liver" [30]. The expression levels of miR-122, let-7a, miR-22, -125b, -143, -194 and -199a have been described to be downregulated in liver cancer cells and function as tumor suppressor miRNAs, as these miRNAs are involved in inhibiting proliferation, cell cycle progression, epithelial-mesenchymal transition and activating apoptosis and autophagy [22,[31][32][33][34][35][36][37][38]. On the contrary, miR-21, -24, -210 and -224 have been reported to be upregulated in HCC and function as oncomiRs, promoting proliferation, cell cycle progression, biliary tumor growth, angiogenesis and aggressiveness [31,[39][40][41][42].…”

Section: Discussionmentioning

confidence: 99%

The Effect of Methylselenocysteine and Sodium Selenite Treatment on microRNA Expression in Liver Cancer Cell Lines

Lendvai

Szekerczés

Kontsek

et al. 2020

Pathol. Oncol. Res.

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The unique character of selenium compounds, including sodium selenite and Se-methylselenocysteine (MSC), is that they exert cytotoxic effects on neoplastic cells, providing a great potential for treating cancer cells being highly resistant to cytostatic drugs. However, selenium treatment may affect microRNA (miRNA) expression as the pattern of circulating miRNAs changed in a placebo-controlled selenium supplement study. This necessitates exploring possible changes in the expression profiles of miRNAs. For this, miRNAs being critical for liver function were selected and their expression was measured in hepatocellular carcinoma (HLE and HLF) and cholangiocarcinoma cell lines (TFK-1 and HuH-28) using individual TaqMan MicroRNA Assays following selenite or MSC treatments. For establishing tolerable concentrations, IC 50 values were determined by performing SRB proliferation assays. The results revealed much lower IC 50 values for selenite (from 2.7 to 11.3 μM) compared to MSC (from 79.5 to 322.6 μM). The treatments resulted in cell line-dependent miRNA expression patterns, with all miRNAs found to show fold change differences; however, only a few of these changes were statistically different in treated cells compared to untreated cells below IC 50. Namely, miR-199a in HLF, miR-143 in TFK-1 upon MSC treatment, miR-210 in HLF and TFK-1, miR-22,-24,-122, −143 in HLF upon selenite treatment. Fold change differences revealed that miR-122 with both selenium compounds, miR-199a with MSC and miR-22 with selenite were affected. The miRNAs showing minimal alterations included miR-125b and miR-194. In conclusion, our results revealed moderately altered miRNA expression in the cell lines (less alterations following MSC treatment), being miR-122, −199a the most affected and miR-125b,-194 the least altered miRNAs upon selenium treatment.

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“…Polypyrimidine tract-binding protein 1 (PTBP1) is highly expressed in hepatocellular carcinoma and promotes the translation of cyclin D3 (CCND3) via interacting with the 5'untranslated region (5'-UTR) of its mRNA, thereby playing a role in the development of hepatocellular carcinoma [24].RBPs are capable of specifically binding to conserved 3'-UTR sequences in target mRNAs, thereby modulating their stability and subsequent translation [25,26]. Appropriate regulation of DNA modification is essential to ensure that chromosomes replicate correctly, and that genes are expressed or silenced in a context-appropriate manner [27].…”

Section: Discussionmentioning

confidence: 99%

Development and Validation of an Rna Binding Protein-associated Prognostic Model for Hepatocellular Carcinoma

Wang

Huang

Chen

et al. 2020

Preprint

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Abstract Background: Hepatocellular carcinoma (HCC) is among the deadliest forms of cancer. While RNA-binding proteins (RBPs) have been shown to be key regulators of oncogenesis and tumor progression, their dysregulation in the context of HCC remains to be fully characterized. Methods: Data from the Cancer Genome Atlas - liver HCC (TCGA-LIHC) database were downloaded and analyzed in order to identify RBPs that were differentially expressed in HCC tumors relative to healthy normal tissues. Functional enrichment analyses of these RBPs were then conducted using the GO and KEGG databases to understand their mechanistic roles. Central hub RBPs associated with HCC patient prognosis were then detected through Cox regression analyses, and were incorporated into a prognostic model. The prognostic value of this model was then assessed through the use of Kaplan-Meier curves, time-related ROC analyses, univariate and multivariate Cox regression analyses, and nomograms. Lastly, the relationship between individual hub RBPs and HCC patient overall survival (OS) was evaluated using Kaplan-Meier curves. Results: In total, we identified 81 RBPs that were differentially expressed in HCC tumors relative to healthy tissues (54 upregulated, 27 downregulated). Seven prognostically-relevant hub RBPs (SMG5, BOP1, LIN28B, RNF17, ANG, LARP1B, and NR0B1) were then used to generate a prognostic model, after which HCC patients were separated into high- and low-risk groups based upon resultant risk score values. In both the training and test datasets, we found that high-risk HCC patients exhibited decreased OS relative to low-risk patients, with time-dependent area under the ROC curve values of 0.801 and 0.676, respectively. This model thus exhibited good prognostic performance. We additionally generated a prognostic nomogram based upon these seven hub RBPs and found that four other genes were significantly correlated with OS. Conclusion: We herein identified a seven RBP signature that can reliably be used to predict HCC patient OS, underscoring the prognostic relevance of these genes.

show abstract

A miR‐194/PTBP1/CCND3 axis regulates tumor growth in human hepatocellular carcinoma

Cited by 40 publications

References 48 publications

Development and validation of an RNA binding protein-associated prognostic model for hepatocellular carcinoma

Development and validation of an RNA binding protein-associated prognostic model for hepatocellular carcinoma

The Effect of Methylselenocysteine and Sodium Selenite Treatment on microRNA Expression in Liver Cancer Cell Lines

Development and Validation of an Rna Binding Protein-associated Prognostic Model for Hepatocellular Carcinoma

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