Methylation of nucleolar and coiled-body phosphoprotein 1 is associated with the mechanism of tumorigenesis in hepatocellular carcinoma

Roles of NOLC1 in cancers and viral infection

BACKGROUND

The nucleolus is considered the center of metabolic control and an important organelle for the biogenesis of ribosomal RNA (rRNA). Nucleolar and coiled-body phosphoprotein 1(NOLC1), which was originally identified as a nuclear localization signal-binding protein is a nucleolar protein responsible for nucleolus construction and rRNA synthesis, as well as chaperone shuttling between the nucleolus and cytoplasm. NOLC1 plays an important role in a variety of cellular life activities, including ribosome biosynthesis, DNA replication, transcription regulation, RNA processing, cell cycle regulation, apoptosis, and cell regeneration.

PURPOSE

In this review, we introduce the structure and function of NOLC1. Then we elaborate its upstream post-translational modification and downstream regulation. Meanwhile, we describe its role in cancer development and viral infection which provide a direction for future clinical applications.

METHODS

The relevant literatures from PubMed have been reviewed for this article.

CONCLUSION

NOLC1 plays an important role in the progression of multiple cancers and viral infection. In-depth study of NOLC1 provides a new perspective for accurate diagnosis of patients and selection of therapeutic targets.

Association analysis of hepatocellular carcinoma-related hub proteins and hub genes

PURPOSE

Hepatocellular carcinoma (HCC) is one of the most common cancers worldwide. The occurrence and development of HCC are closely related to epigenetic modifications. Epigenetic modifications can regulate gene expression and related functions through DNA methylation. This paper presents an association analysis method of HCC-related hub proteins and hub genes.

EXPERIMENTAL DESIGN

Bioinformatics analysis of HCC-related DNA methylation data is carried out to clarify the molecular mechanism of HCC-related genes and to find hub genes (genes with more connections in the network) by constructing in the gene interaction network. This paper proposes an accurate prediction method of protein-protein interaction (PPI) based on deep learning model DeepSG2PPI. The trained DeepSG2PPI model predicts the interaction relationship between the synthetic proteins regulated by HCC-related genes.

RESULTS

This paper finds that four genes are the intersection of hub genes and hub proteins. The four genes are: FBL, CCNB2, ALDH18A1, and RPLP0. The association of RPLP0 gene with HCC is a new finding of this study. RPLP0 is expected to become a new biomarker for the treatment, diagnosis, and prognosis of HCC. The four proteins corresponding to the four genes are: ENSP00000221801, ENSP00000288207, ENSP00000360268, and ENSP00000449328.

CONCLUSIONS AND CLINICAL RELEVANCE

The association between the hub genes with the hub proteins is analyzed. The mutual verification of the hub genes and the hub proteins can obtain more credible HCC-related genes and proteins, which is helpful for the diagnosis, treatment, and drug development of HCC.

Comparative Proteomic Analysis of Drug Trichosanthin Addition to BeWo Cell Line

Trichosanthin (TCS) is a traditional Chinese herbal medicine used to treat some gynecological diseases. Its effective component has diverse biological functions, including antineoplastic activity. The human trophoblast cell line BeWo was chosen as an experimental model for in vitro testing of a drug screen for anticancer properties of TCS. The MTT method was used in this study to get a primary screen result. The result showed that 100 mM had the best IC₅₀ value. Proteomics analysis was then performed for further investigation of the drug effect of TCS on the BeWo cell line. In this differential proteomic expression analysis, the total proteins extracted from the BeWo cell line and their protein expression level after the drug treatment were compared by 2DE. Then, 24 unique three-fold differentially expressed proteins (DEPs) were successfully identified by MALDI-TOF/TOF MS. Label-free proteomics was run as a complemental method for the same experimental procedure. There are two proteins that were identified in both the 2DE and label-free methods. Among those identified proteins, bioinformatics analysis showed the importance of pathway and signal transduction and gives us the potential possibility for the disease treatment hypothesis.

Nucleolar and Coiled-Body Phosphoprotein 1 Is Associated With Stemness and Represents a Potential Therapeutic Target in Triple-Negative Breast Cancer

Triple-negative breast cancer (TNBC) is the most aggressive subtype of breast cancer and lacks approved specific targeted therapies. One of the major reasons why TNBC is difficult to treat is the high proportion of cancer stem cells within the tumor tissue. Nucleolus is the location of ribosome biogenesis which is frequently overactivated in cancer cells and overactivation of ribosome biogenesis frequently drives the malignant transformation of cancer. Nucleolar and coiled-body phosphoprotein 1 (NOLC1) is a nucleolar protein responsible for nucleolus organization and rRNA synthesis and plays an important role in ribosome biogenesis. However, the correlation of NOLC1 expression with patient prognosis and its value as a therapeutic target have not been evaluated in TNBC. In the current study, based on bioinformatics analysis of the online databases, we found that the expression of NOLC1 was higher in breast cancer tissues than normal tissues, and NOLC1 was expressed at a higher level in TNBC than other subtypes of breast cancer. GSEA analysis revealed that stemness-related pathways were significantly enriched in breast cancer with high NOLC1 gene expression. Further analyses using gene expression profiling interactive analysis 2 (GEPIA2), tumor immune estimation resource (TIMER) and search tool for retrieval of interacting genes/proteins (STRING) demonstrated that NOLC1 was significantly associated with stemness in both all breast cancer and basal-like breast cancer/TNBC patients at both gene and protein levels. Knockdown of NOLC1 by siRNA decreased the protein level of the key stemness regulators MYC and ALDH and inhibited the sphere-forming capacity in TNBC cell line MDA-MB-231. Univariate and multivariate Cox regression analyses demonstrated that NOLC1 was an independent risk factor for overall survival in breast cancer. PrognoScan and Kaplan-Meier plotter analyses revealed that high expression of NOLC1 was associated with poor prognosis in both all breast cancer and TNBC patients. Further immunohistochemical analysis of breast cancer patient samples revealed that TNBC cells had a lower level of NOLC1 in the nucleus compared with non-TNBC cells. These findings suggest that NOLC1 is closely associated with the stemness properties of TNBC and represents a potential therapeutic target for TNBC.

Knockdown of NOLC1 Inhibits PI3K-AKT Pathway to Improve the Poor Prognosis of Esophageal Carcinoma

Objective

Esophageal carcinoma (ESCA) is a common malignant gastrointestinal tumor. The abnormal expression of NOLC1 is involved in the tumorigenesis of various human tumors, whereas the function and mechanism of NOLC1 in ESCA remain unclear. In this study, we explored the relationship between NOLC1 and poor prognosis of ESCA, and its role and mechanism in the occurrence of ESCA.

Methods

The NOLC1 expression in ESCA tissues and cell lines was determined by qRT-PCR, immunohistochemistry, or western blot. The Kaplan–Meier method was conducted to estimate the overall survival. Cox regression analysis was carried out to examine the association between patient characteristics and prognosis. A recombined lentiviral vector containing NOLC1 was applied for transfecting ESCA cells (Eca109 and TE-13) and established a stable cell line with low NOLC1 expression or high NOLC1 expression, in the absence or presence of PI3K inhibitor (LY294002) treatment. Cell proliferation, apoptosis rate, invasion ability, migration ability, and PI3K/AKT pathway were detected by CCK8 assay, flow cytometry, Transwell assay, wound-healing assay, and western blot.

Results

NOLC1 overexpression was observed in ESCA tissues and ESCA cell lines (EC9706, Eca109, TE-13, Kyse170, T.TN) compared with adjacent normal tissues and normal esophageal cell line HEEC. NOLC1 overexpression was markedly associated with bigger tumor size, lymph node metastasis, and advanced TNM stage. Patients with NOLC1 overexpression have shorter overall survival than that of those with low NOLC1 expression. NOLC1 overexpression was considered to be an independent poor prognostic factor affecting overall survival. NOLC1 knockdown inhibited proliferation, migration, invasion, and cyclin B1 expression and promoted the apoptosis and cleaved-caspase-3 expression of Eca109 and TE-13 cells. NOLC1 overexpression accelerated proliferation, migration, invasion, and cyclin B1 expression and inhibited the apoptosis and cleaved-caspase-3 expression of ESCA cells via activating PI3K/AKT pathway. Rescue experiments showed that PI3K inhibitor (LY294002) could reverse the phenomenon caused by NOLC1 overexpression.

Conclusion

NOLC1 may be a marker for poor prognosis. It can participate in the occurrence and development of ESCA via the PI3K/AKT pathway.

Circular RNA CircNOLC1, Upregulated by NF-KappaB, Promotes the Progression of Prostate Cancer via miR-647/PAQR4 Axis

Background

CircRNAs recently have shown critical roles in tumor biology. However, their roles in prostate cancer (PCa) remains largely unclear.

Methods

CircRNA microarrays were performed in immortal prostate cell line RWPE1 and PCa cell lines as DU145, PC3, LNCaP, C4-2, and 22RV1. Combined with upregulated circRNAs in PCa tissues, circNOLC1 expression was validated in PCa cells and tissues via qRT-PCR and FISH. Sanger sequencing, actinomycin D, gDNA, and cDNA, RNase R assays were used to assess the circular characteristics of circNOLC1. CCK-8, colony formation, transwell migration assays, and mice xenograft models were conducted to evaluate the functions of PCa cells after circNOLC1 knockdown and overexpression. RNA pulldown, luciferase reporter assay, FISH (fluorescence in situ hybridization), and CHIP were utilized to illustrate the further mechanisms of circNOLC1.

Results

Our research indicated that circNOLC1 was overexpressed in PCa cells and tissues, and circNOLC1 was more stable than linear NOLC1 mRNA. CircNOLC1 promoted PCa cells proliferation and migration in vitro and vivo. Additionally, we found that circNOLC1 could upregulate PAQR4 expression by sponging miR-647, leading to the activation of PI3K/Akt pathway. Moreover, NF-kappaB was identified to bind to the NOLC1 promoter sites and upregulated both NOLC1 and circNOLC1 expression.

Conclusion

CircNOLC1, elevated by transcription factor NF-kappaB, promotes PCa progression via a miR-647/PAQR4 axis, and circNOLC1 is a potential biomarker and target for PCa treatment.

Identification of Novel Prognosis and Prediction Markers in Advanced Prostate Cancer Tissues Based on Quantitative Proteomics

BACKGROUND/AIM

Prostate cancer (PCa) is the most frequent cancer found in males worldwide, and its mortality rate is increasing every year. However, there are no known molecular markers for advanced or aggressive PCa, and there is an urgent clinical need for biomarkers that can be used for prognosis and prediction of PCa.

MATERIALS AND METHODS

Mass spectrometry-based proteomics was used to identify new biomarkers in tissues obtained from patients with PCa who were diagnosed with T2, T3, or metastatic PCa in regional lymph nodes.

RESULTS

Among 1,904 proteins identified in the prostate tissues, 344 differentially expressed proteins were defined, of which 124 were up-regulated and 216 were down-regulated. Subsequently, based on the results of partial least squares discriminant analysis and Gene Ontology and Kyoto Encyclopedia of Genes and Genomes enrichment analyses, we proposed that spermidine synthase (SRM), nucleolar and coiled-body phosphoprotein 1 (NOLC1), and prostacyclin synthase (PTGIS) represent new protein biomarkers for diagnosis of advanced PCa. These proteomics results were verified by immunoblot assays in metastatic PCa cell lines and by indirect enzyme-linked immunosorbent assay in prostate specimens.

CONCLUSION

SRM was significantly increased depending on the cancer stage, confirming the possibility of using SRM as a biomarker for prognosis and prediction of advanced PCa.

Classification of early and late stage liver hepatocellular carcinoma patients from their genomics and epigenomics profiles

Background

Liver Hepatocellular Carcinoma (LIHC) is one of the major cancers worldwide, responsible for millions of premature deaths every year. Prediction of clinical staging is vital to implement optimal therapeutic strategy and prognostic prediction in cancer patients. However, to date, no method has been developed for predicting the stage of LIHC from the genomic profile of samples.

Methods

The Cancer Genome Atlas (TCGA) dataset of 173 early stage (stage-I), 177 late stage (stage-II, Stage-III and stage-IV) and 50 adjacent normal tissue samples for 60,483 RNA transcripts and 485,577 methylation CpG sites, was extensively analyzed to identify the key transcriptomic expression and methylation-based features using different feature selection techniques. Further, different classification models were developed based on selected key features to categorize different classes of samples implementing different machine learning algorithms.

Results

In the current study, in silico models have been developed for classifying LIHC patients in the early vs. late stage and cancerous vs. normal samples using RNA expression and DNA methylation data. TCGA datasets were extensively analyzed to identify differentially expressed RNA transcripts and methylated CpG sites that can discriminate early vs. late stages and cancer vs. normal samples of LIHC with high precision. Naive Bayes model developed using 51 features that combine 21 CpG methylation sites and 30 RNA transcripts achieved maximum MCC (Matthew’s correlation coefficient) 0.58 with an accuracy of 78.87% on the validation dataset in discrimination of early and late stage. Additionally, the prediction models developed based on 5 RNA transcripts and 5 CpG sites classify LIHC and normal samples with an accuracy of 96–98% and AUC (Area Under the Receiver Operating Characteristic curve) 0.99. Besides, multiclass models also developed for classifying samples in the normal, early and late stage of cancer and achieved an accuracy of 76.54% and AUC of 0.86.

Conclusion

Our study reveals stage prediction of LIHC samples with high accuracy based on the genomics and epigenomics profiling is a challenging task in comparison to the classification of cancerous and normal samples. Comprehensive analysis, differentially expressed RNA transcripts, methylated CpG sites in LIHC samples and prediction models are available from CancerLSP (http://webs.iiitd.edu.in/raghava/cancerlsp/).

NS5ATP13 Promotes Liver Fibrogenesis Via Activation of Hepatic Stellate Cells

Liver fibrosis is a reversible wound-healing response to any etiology of chronic hepatic injuries. Activation of hepatic stellate cells (HSCs) is the key event in liver fibrogenesis. Generally, persistent activation and proliferation of HSCs results in liver fibrosis progression, while primary mechanisms of liver fibrosis resolution are apoptosis and reversion to a quiescent phenotype of activated HSCs. NS5ATP13 (HCV NS5A-transactivated protein 13) is involved in nucleologenesis and tumorigenesis, but its role in liver fibrosis and HSC activation remains unclear. This study found that NS5ATP13 was upregulated in both fibrotic liver tissues and activated human HSCs induced by TGF-β1. Moreover, NS5ATP13 enhanced extracellular matrix (ECM) production and HSC activation, with or without TGF-β1 treatment, likely involving the TGF-β1/Smad3 signaling pathway. Additionally, NS5ATP13 boosted HSC proliferation by inhibiting cell apoptosis. Furthermore, HCV NS5A promoted the profibrogenic effect of NS5ATP13 partly through TGF-β1 and NF-κB p65 (RelA) upregulation. Meanwhile, NS5ATP13 was required for the pro-fibrogenic effect of NF-κB. Moreover, NS5ATP13 and NF-κB phosphorylation as well as HSC activation were reduced by CX-4945, a CK2 specific inhibitor. These findings indicated that NS5ATP13 acts as a profibrogenic factor, providing a potential target for antifibrotic therapies. J. Cell. Biochem. 118: 2463-2473, 2017. © 2017 Wiley Periodicals, Inc.