Downregulation of ZC3H14 driven by chromosome 14q31 deletion promotes hepatocellular carcinoma progression by activating integrin signaling

Nucleotide-level prediction of CircRNA-protein binding based on fully convolutional neural network

Introduction: CircRNA-protein binding plays a critical role in complex biological activity and disease. Various deep learning-based algorithms have been proposed to identify CircRNA-protein binding sites. These methods predict whether the CircRNA sequence includes protein binding sites from the sequence level, and primarily concentrate on analysing the sequence specificity of CircRNA-protein binding. For model performance, these methods are unsatisfactory in accurately predicting motif sites that have special functions in gene expression. Methods: In this study, based on the deep learning models that implement pixel-level binary classification prediction in computer vision, we viewed the CircRNA-protein binding sites prediction as a nucleotide-level binary classification task, and use a fully convolutional neural networks to identify CircRNA-protein binding motif sites (CPBFCN). Results: CPBFCN provides a new path to predict CircRNA motifs. Based on the MEME tool, the existing CircRNA-related and protein-related database, we analysed the motif functions discovered by CPBFCN. We also investigated the correlation between CircRNA sponge and motif distribution. Furthermore, by comparing the motif distribution with different input sequence lengths, we found that some motifs in the flanking sequences of CircRNA-protein binding region may contribute to CircRNA-protein binding. Conclusion: This study contributes to identify circRNA-protein binding and provides help in understanding the role of circRNA-protein binding in gene expression regulation.

Down-regulation of MYH10 driven by chromosome 17p13.1 deletion promotes hepatocellular carcinoma metastasis through activation of the EGFR pathway

Somatic copy number alterations (CNAs) are a genomic hallmark of cancers. Among them, the chromosome 17p13.1 deletions are recurrent in hepatocellular carcinoma (HCC). Here, utilizing an integrative omics analysis, we screened out a novel tumour suppressor gene within 17p13.1, myosin heavy chain 10 (MYH10). We observed frequent deletions (~38%) and significant down‐regulation of MYH10 in primary HCC tissues. Deletion or decreased expression of MYH10 was a potential indicator of poor outcomes in HCC patients. Knockdown of MYH10 significantly promotes HCC cell migration and invasion in vitro, and overexpression of MYH10 exhibits opposite effects. Further, inhibition of MYH10 markedly potentiates HCC metastasis in vivo. We preliminarily elucidated the mechanism by which loss of MYH10 promotes HCC metastasis by facilitating EGFR pathway activation. In conclusion, our study suggests that MYH10, a candidate target gene for 17p13 deletion, acts as a tumour suppressor and may serve as a potential prognostic indicator for HCC patients.

Genomic gain of RRS1 promotes hepatocellular carcinoma through reducing the RPL11-MDM2-p53 signaling

Hepatocellular carcinomas (HCCs) are characterized by frequent somatic genomic copy number alterations (CNAs), with most of them biologically unexplored. Here, we performed integrative analyses combining CNAs with the transcriptomic data to reveal the cis- and trans-effects of CNAs in HCC. We identified recurrent genomic gains of chromosome 8q, which exhibit strong trans-effects and are broadly associated with ribosome biogenesis activity. Furthermore, 8q gain-driven overexpression of ribosome biogenesis regulator (RRS1) promotes growth of HCC cells in vitro and in vivo. Mechanistically, RRS1 attenuates ribosomal stress through retaining RPL11 in the nucleolus, which, in turn, potentiates MDM2-mediated ubiquitination and degradation of p53. Clinically, higher RRS1 expression levels predict poor clinical outcomes for patients with HCC, especially in those with intact p53 Our findings established that the chromosome 8q oncogene RRS1 promotes HCC development through attenuating the RPL11-MDM2-p53 pathway and provided new potential targets for treatment of this malignancy.

Identification of Potential Biomarkers From Hepatocellular Carcinoma With MT1 Deletion

Background: Hepatocellular carcinoma (HCC) is one of the deadliest cancers worldwide. Metallothioneins (MTs) are metal-binding proteins involved in multiple biological processes such as metal homeostasis and detoxification, as well as in oncogenesis. Copy number variation (CNV) plays a vital role in pathogenesis and carcinogenesis. Nevertheless, there is no study on the role of MT1 CNV in HCC. Methods: Array-based Comparative Genomic Hybridization (aCGH) analysis was performed to obtain the CNV data of 79 Guangxi HCC patients. The prognostic effect of MT1-deletion was analyzed by univariate and multivariate Cox regression analysis. The differentially expressed genes (DEGs) were screened based on The Gene Expression Omnibus database (GEO) and the Liver Hepatocellular Carcinoma of The Cancer Genome Atlas (TCGA-LIHC). Then function and pathway enrichment analysis, protein-protein interaction (PPI) and hub gene selection were applied on the DEGs. Lastly, the hub genes were validated by immunohistochemistry, tissue expression and prognostic analysis. Results: The MT1-deletion was demonstrated to affect the prognosis of HCC and can act as an independent prognostic factor. 147 common DEGs were screened. The most significant cluster of DEGs identified by Molecular Complex Detection (MCODE) indicated that the expression of four MT1s were down-regulated. MT1X and other five hub genes (TTK, BUB1, CYP3A4, NR1I2, CYP8B1) were associated with the prognosis of HCC. TTK, could affect the prognosis of HCC with MT1-deletion and non-deletion. NR1I2, CYP8B1, and BUB1 were associated with the prognosis of HCC with MT1-deletion. Conclusions: In the current study, we demonstrated that MT1-deletion can be an independent prognostic factor in HCC. We identified TTK, BUB1, NR1I2, CYP8B1 by processing microarray data, for the first time revealed the underlying function of MT1 deletion in HCC, MT1-deletion may influence the gene expression in HCC, which may be the potential biomarkers for HCC with MT1 deletion.

Pan-cancer driver copy number alterations identified by joint expression/CNA data analysis

Analysis of large gene expression datasets from biopsies of cancer patients can identify co-expression signatures representing particular biomolecular events in cancer. Some of these signatures involve genomically co-localized genes resulting from the presence of copy number alterations (CNAs), for which analysis of the expression of the underlying genes provides valuable information about their combined role as oncogenes or tumor suppressor genes. Here we focus on the discovery and interpretation of such signatures that are present in multiple cancer types due to driver amplifications and deletions in particular regions of the genome after doing a comprehensive analysis combining both gene expression and CNA data from The Cancer Genome Atlas.

M2 polarization of tumor-associated macrophages is dependent on integrin β3 via peroxisome proliferator-activated receptor-γ up-regulation in breast cancer

Macrophages are particularly abundant and play an important role throughout the tumor progression process, namely, tumor-associated macrophages (TAM) in the tumor microenvironment. TAM can be polarized to disparate functional phenotypes, the M1 and M2 macrophages. M1-like type macrophages are defined as pro-inflammatory cells involved in killing cancer cells, while M2-like type cells can specially promote tumor growth and metastasis, tissue remodeling and immunosuppression. In this study, we first found that integrin β3 was highly expressed on the surface of TAM, both in vivo and in vitro, that displayed the M2-like characteristics. Under intervention of CYC or triptolide, the integrin β3 inhibitors, the M2 polarization of TAM could be inhibited. Moreover, in the cell model of M2 polarization, either blockade or knockout/knockdown of integrin β3 could also suppress macrophage M2 polarization, which suggested that the M2 polarization was dependent on integrin β3. Using knockdown of peroxisome proliferator-activated receptor-γ (PPARγ), an M2 regulator, we found that expression and activation of PPARγ participated in M2 polarization that was mediated by integrin β3. Finally, to verify the activity of integrin β3 inhibitors on TAM in vivo, 4T1 tumor-bearing mice were treated with CYC or triptolide; in response, the M1/M2 ratio of TAM was up-regulated, while the infiltration of total lymphocytes into tumor tissue was not altered. In general, our study found a connection between integrin β3 and macrophage polarization, which provides a strategy for facilitating M2 to M1 repolarization and reconstructing the tumor immune microenvironment.