Identification of diagnostic long non‑coding RNA biomarkers in patients with hepatocellular carcinoma

Roles of peroxisome proliferator-activated receptors in hepatocellular carcinoma

Hepatocellular carcinoma (HCC), the main pathological type of liver cancer, is linked to risk factors such as viral hepatitis, alcohol intake and non-alcoholic fatty liver disease (NAFLD). Recent advances have greatly improved our understanding that NAFLD is playing a major risk factor for HCC. Peroxisome proliferator-activated receptors (PPARs) are a class of transcription factors divided into three subtypes: PPARα (PPARA), PPARδ/β (PPARD) and PPARγ (PPARG). As important nuclear receptors, PPARs are involved in many physiological processes, and PPARs can improve NAFLD by regulating lipid metabolism, accelerating fatty acid oxidation and inhibiting inflammation. In recent years, some studies have shown that PPARs can participate in the occurrence and development of HCC by regulating metabolic pathways. In addition, PPAR modulators have been reported to inhibit the proliferation and metastasis of HCC cells and can enhance the curative effect of conventional treatments. This article reviews the role of PPARs in the occurrence and development of HCC, as well as its value in the diagnosis, treatment and prognosis of HCC, in order to provide directions for future research.

Molecular regulation of hypoxia through the lenses of noncoding RNAs and epitranscriptome

Cells maintain homeostasis in response to environmental stress through specific cell stress responses. Hypoxic stress, well known to be associated with diverse solid tumors, is one of the main reasons for cancer-related mortality. Although cells can balance themselves well during hypoxic stress, the underlying molecular mechanisms are not well understood. The enhanced appreciation of diverse roles played by noncoding transcriptome and epigenome in recent years has brought to light the involvement of noncoding RNAs and epigenetic modifiers in hypoxic regulation. The emergence of techniques like deep sequencing has facilitated the identification of large numbers of long noncoding RNAs (lncRNAs) that are differentially regulated in various cancers. Similarly, proteomic studies have identified diverse epigenetic modifiers such as HATs, HDACs, DNMTs, polycomb groups of proteins, and their possible roles in the regulation of hypoxia. The crosstalk between lncRNAs and epigenetic modifiers play a pivotal role in hypoxia-induced cancer initiation and progression. Besides the lncRNAs, several other noncoding RNAs like circular RNAs, miRNAs, and so forth are also expressed during hypoxic conditions. Hypoxia has a profound effect on the expression of noncoding RNAs and epigenetic modifiers. Conversely, noncoding RNAs/epigenetic modifies can regulate the hypoxia signaling axis by modulating the stability of the hypoxia-inducible factors (HIFs). The focus of this review is to illustrate the molecular orchestration underlying hypoxia biology, especially in cancers, which can help in identifying promising therapeutic targets in hypoxia-induced cancers. This article is categorized under: RNA Turnover and Surveillance > Regulation of RNA Stability RNA in Disease and Development > RNA in Disease RNA Structure and Dynamics > RNA Structure, Dynamics and Chemistry.

Function of the Long Noncoding RNAs in Hepatocellular Carcinoma: Classification, Molecular Mechanisms, and Significant Therapeutic Potentials

Hepatocellular carcinoma (HCC) is the most common and serious type of primary liver cancer. HCC patients have a high death rate and poor prognosis due to the lack of clear signs and inadequate treatment interventions. However, the molecular pathways that underpin HCC pathogenesis remain unclear. Long non-coding RNAs (lncRNAs), a new type of RNAs, have been found to play important roles in HCC. LncRNAs have the ability to influence gene expression and protein activity. Dysregulation of lncRNAs has been linked to a growing number of liver disorders, including HCC. As a result, improved understanding of lncRNAs could lead to new insights into HCC etiology, as well as new approaches for the early detection and treatment of HCC. The latest results with respect to the role of lncRNAs in controlling multiple pathways of HCC were summarized in this study. The processes by which lncRNAs influence HCC advancement by interacting with chromatin, RNAs, and proteins at the epigenetic, transcriptional, and post-transcriptional levels were examined. This critical review also highlights recent breakthroughs in lncRNA signaling pathways in HCC progression, shedding light on the potential applications of lncRNAs for HCC diagnosis and therapy.

Identification of key interferon-stimulated genes for indicating the condition of patients with systemic lupus erythematosus

Systemic lupus erythematosus (SLE) is a chronic autoimmune disease with highly heterogeneous clinical symptoms and severity. There is complex pathogenesis of SLE, one of which is IFNs overproduction and downstream IFN-stimulated genes (ISGs) upregulation. Identifying the key ISGs differentially expressed in peripheral blood mononuclear cells (PBMCs) of patients with SLE and healthy people could help to further understand the role of the IFN pathway in SLE and discover potential diagnostic biomarkers.

The differentially expressed ISGs (DEISG) in PBMCs of SLE patients and healthy persons were screened from two datasets of the Gene Expression Omnibus (GEO) database. A total of 67 DEISGs, including 6 long noncoding RNAs (lncRNAs) and 61 messenger RNAs (mRNAs) were identified by the “DESeq2” R package. According to Gene Ontology (GO) enrichment analysis and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analysis, those DEISGs were mainly concentrated in the response to virus and immune system processes. Protein-protein interaction (PPI) network showed that most of these DEISGs could interact strongly with each other. Then, IFIT1, RSAD2, IFIT3, USP18, ISG15, OASL, MX1, OAS2, OAS3, and IFI44 were considered to be hub ISGs in SLE by “MCODE” and “Cytohubba” plugins of Cytoscape, Moreover, the results of expression correlation suggested that 3 lncRNAs (NRIR, FAM225A, and LY6E-DT) were closely related to the IFN pathway.

The lncRNA NRIR and mRNAs (RSAD2, USP18, IFI44, and ISG15) were selected as candidate ISGs for verification. RT-qPCR results showed that PBMCs from SLE patients had substantially higher expression levels of 5 ISGs compared to healthy controls (HCs). Additionally, statistical analyses revealed that the expression levels of these ISGs were strongly associated to various clinical symptoms, including thrombocytopenia and facial erythema, as well as laboratory indications, including the white blood cell (WBC) count and levels of autoantibodies. The Receiver Operating Characteristic (ROC) curve demonstrated that the IFI44, USP18, RSAD2, and IFN score had good diagnostic capabilities of SLE.

According to our study, SLE was associated with ISGs including NRIR, RSAD2, USP18, IFI44, and ISG15, which may contribute to the future diagnosis and new personalized targeted therapies.

DNA Methylation Regulates a Set of Long Non-Coding RNAs Compromising Hepatic Identity during Hepatocarcinogenesis

Simple Summary

Hepatocarcinogenesis is a long process which implies the loss of hepatic functions. Our effort is to understand the mechanisms implicated in this pathological process in order to contribute to the development of new diagnostic markers and therapeutic targets. In this study we have identified a set of lncRNAs significantly downregulated in hepatocellular carcinoma (HCC) in correlation with the grade of tumor dedifferentiation and patients’ worse prognosis. Mechanistically, our results show that they are related with hepatic differentiation and at least a subset of those lncRNAs are essential to ensure the expression of other hepato-specific genes required for liver function. Moreover, we demonstrate that the expression of these lncRNAs in HCC is silenced by DNA methylation. All in all, we uncover connected epigenetic alterations involved in the progression of liver cancer and identify potential new biomarkers.

Abstract

Background: Long noncoding RNAs (lncRNAs) are emerging as key players in cancer, including hepatocellular carcinoma (HCC). Here we identify the mechanism implicated in the HCC inhibition of a set of lncRNAs, and their contribution to the process of hepatocarcinogenesis. Methods and Results: The top-ranked 35 lncRNAs downregulated in HCC (Top35 LNDH) were validated in several human HCC cohorts. We demonstrate that their inhibition is associated with promoter hypermethylation in HCC compared to control tissue, and in HCC human cell lines compared to primary hepatocytes. Moreover, demethylating treatment of HCC human cell lines induced the expression of these lncRNAs. The Top35 LNDH were preferentially expressed in the adult healthy liver compared to other tissues and fetal liver and were induced in well-differentiated HepaRG cells. Remarkably, their knockdown compromised the expression of other hepato-specific genes. Finally, the expression of the Top35 LNDH positively correlates with the grade of tumor differentiation and, more importantly, with a better patient prognosis. Conclusions: Our results demonstrate that the selected Top35 LNDH are not only part of the genes that compose the hepatic differentiated signature but participate in its establishment. Moreover, their downregulation through DNA methylation occurs during the process of hepatocarcinogenesis compromising hepatocellular differentiation and HCC patients’ prognosis.

Role of three-dimensional printing and artificial intelligence in the management of hepatocellular carcinoma: Challenges and opportunities

Hepatocellular carcinoma (HCC) constitutes the fifth most frequent malignancy worldwide and the third most frequent cause of cancer-related deaths. Currently, treatment selection is based on the stage of the disease. Emerging fields such as three-dimensional (3D) printing, 3D bioprinting, artificial intelligence (AI), and machine learning (ML) could lead to evidence-based, individualized management of HCC. In this review, we comprehensively report the current applications of 3D printing, 3D bioprinting, and AI/ML-based models in HCC management; we outline the significant challenges to the broad use of these novel technologies in the clinical setting with the goal of identifying means to overcome them, and finally, we discuss the opportunities that arise from these applications. Notably, regarding 3D printing and bioprinting-related challenges, we elaborate on cost and cost-effectiveness, cell sourcing, cell viability, safety, accessibility, regulation, and legal and ethical concerns. Similarly, regarding AI/ML-related challenges, we elaborate on intellectual property, liability, intrinsic biases, data protection, cybersecurity, ethical challenges, and transparency. Our findings show that AI and 3D printing applications in HCC management and healthcare, in general, are steadily expanding; thus, these technologies will be integrated into the clinical setting sooner or later. Therefore, we believe that physicians need to become familiar with these technologies and prepare to engage with them constructively.

lncRNA ST8SIA6-AS1 facilitates proliferation and invasion in liver cancer by regulating miR-142-3p

Long non-coding RNA ST8 α-N-acetyl-neuraminide α-2,8-sialyltransferase 6 antisense 1 (ST8SIA6-AS1) has been identified as a novel oncogene in breast cancer. However, its involvement in liver cancer has remained elusive. In the present study, the expression of ST8SIA6-AS1 and microRNA (miR)-142-3p in liver cancer tissues and cell lines was detected by reverse transcription-quantitative PCR. Tumor cell proliferation, migration and invasion assays were performed to determine the biological functions of ST8SIA6-AS1. The targeting interaction between ST8SIA6-AS1 and miR-142-3p predicted by bioinformatics was verified by a luciferase reporter assay and a biotin pulldown assay. The results indicated that ST8SIA6-AS1 was highly expressed in liver cancer tissues and cell lines, and the high expression of ST8SIA6-AS1 in liver cancer tissues was associated with poor prognosis. Knockdown of ST8SIA6-AS1 inhibited the proliferation, metastasis and invasion of liver cancer cells. Mechanistic investigation revealed that ST8SIA6-AS1 sequesters miR-142-3p and negatively regulates miR-142-3p expression in liver cancer cells. Further investigation indicated that the tumor-inhibitory effect of ST8SIA6-AS1 silencing was reversed by miR-142-3p depletion. In conclusion, ST8SIA6-AS1 was indicated to exert an oncogenic function in liver cancer by competitively sponging miR-142-3p.

Identifying novel transcript biomarkers for hepatocellular carcinoma (HCC) using RNA-Seq datasets and machine learning

BACKGROUND

Hepatocellular carcinoma (HCC) is one of the leading causes of cancer death in the world owing to limitations in its prognosis. The current prognosis approaches include radiological examination and detection of serum biomarkers, however, both have limited efficiency and are ineffective in early prognosis. Due to such limitations, we propose to use RNA-Seq data for evaluating putative higher accuracy biomarkers at the transcript level that could help in early prognosis.

METHODS

To identify such potential transcript biomarkers, RNA-Seq data for healthy liver and various HCC cell models were subjected to five different machine learning algorithms: random forest, K-nearest neighbor, Naïve Bayes, support vector machine, and neural networks. Various metrics, namely sensitivity, specificity, MCC, informedness, and AUC-ROC (except for support vector machine) were evaluated. The algorithms that produced the highest values for all metrics were chosen to extract the top features that were subjected to recursive feature elimination. Through recursive feature elimination, the least number of features were obtained to differentiate between the healthy and HCC cell models.

RESULTS

From the metrics used, it is demonstrated that the efficiency of the known protein biomarkers for HCC is comparatively lower than complete transcriptomics data. Among the different machine learning algorithms, random forest and support vector machine demonstrated the best performance. Using recursive feature elimination on top features of random forest and support vector machine three transcripts were selected that had an accuracy of 0.97 and kappa of 0.93. Of the three transcripts, two were protein coding (PARP2-202 and SPON2-203) and one was a non-coding transcript (CYREN-211). Lastly, we demonstrated that these three selected transcripts outperformed randomly taken three transcripts (15,000 combinations), hence were not chance findings, and could then be an interesting candidate for new HCC biomarker development.

CONCLUSION

Using RNA-Seq data combined with machine learning approaches can aid in finding novel transcript biomarkers. The three biomarkers identified: PARP2-202, SPON2-203, and CYREN-211, presented the highest accuracy among all other transcripts in differentiating the healthy and HCC cell models. The machine learning pipeline developed in this study can be used for any RNA-Seq dataset to find novel transcript biomarkers. Code: www.github.com/rajinder4489/ML_biomarkers.

The lncRNAs in HBV-Related HCCs: Targeting Chromatin Dynamics and Beyond

Simple Summary

Hepatocellular carcinoma (HCC), a common and fast rising cause of cancer, is responsible for over 800,000 deaths/year. Chronic hepatitis B virus (HBV) infection accounts for >50% of the cases worldwide. Long non-coding RNAs (lncRNAs), untranslated transcripts longer than 200 nucleotides, by acting both in the nuclear and cytoplasmic compartments, regulate gene expression both at the transcriptional and post-transcriptional levels. The lncRNAs have been involved in the development and progression of many cancers, including HCC. In this review, we describe the role of lncRNAs in HBV infection and HBV-related liver carcinogenesis and discuss the potential of lncRNAs as predictive or diagnostic biomarkers.

Abstract

Hepatocellular carcinoma (HCC) represents the fourth leading and fastest rising cause of cancer death (841,000 new cases and 782,000 deaths annually), and hepatitis B (HBV), with 250 million people chronically infected at risk of developing HCC, accounts for >50% of the cases worldwide. Long non-coding RNAs (lncRNAs), untranslated transcripts longer than 200 nucleotides, are implicated in gene regulation at the transcriptional and post-transcriptional levels, exerting their activities both in the nuclear and cytoplasmic compartments. Thanks to high-throughput sequencing techniques, several lncRNAs have been shown to favor the establishment of chronic HBV infection, to change the host transcriptome to establish a pro-carcinogenic environment, and to directly participate in HCC development and progression. In this review, we summarize current knowledge on the role of lncRNAs in HBV infection and HBV-related liver carcinogenesis and discuss the potential of lncRNAs as predictive or diagnostic biomarkers.

De Novo Profiling of Long Non-Coding RNAs Involved in MC-LR-Induced Liver Injury in Whitefish: Discovery and Perspectives

Microcystin-LR (MC-LR) is a potent hepatotoxin for which a substantial gap in knowledge persists regarding the underlying molecular mechanisms of liver toxicity and injury. Although long non-coding RNAs (lncRNAs) have been extensively studied in model organisms, our knowledge concerning the role of lncRNAs in liver injury is limited. Given that lncRNAs show low levels of sequence conservation, their role becomes even more unclear in non-model organisms without an annotated genome, like whitefish (Coregonus lavaretus). The objective of this study was to discover and profile aberrantly expressed polyadenylated lncRNAs that are involved in MC-LR-induced liver injury in whitefish. Using RNA sequencing (RNA-Seq) data, we de novo assembled a high-quality whitefish liver transcriptome. This enabled us to find 94 differentially expressed (DE) putative evolutionary conserved lncRNAs, such as MALAT1, HOTTIP, HOTAIR or HULC, and 4429 DE putative novel whitefish lncRNAs, which differed from annotated protein-coding transcripts (PCTs) in terms of minimum free energy, guanine-cytosine (GC) base-pair content and length. Additionally, we identified DE non-coding transcripts that might be 3′ autonomous untranslated regions (3′UTRs) of mRNAs. We found both evolutionary conserved lncRNAs as well as novel whitefish lncRNAs that could serve as biomarkers of liver injury.

GFI1-Mediated Upregulation of LINC00675 as a ceRNA Restrains Hepatocellular Carcinoma Metastasis by Sponging miR-942-5p

Hepatocellular carcinoma (HCC) is a common malignant liver tumor worldwide. Tumor recurrence and metastasis contribute to the bad clinical outcome of HCC patients. Substantial studies have displayed lncRNAs modulate various tumorigenic processes of many cancers. Our current work was aimed to investigate the function of LINC00675 in HCC and to recognize the potential interactions between lncRNAs and microRNAs. GFI1 can exhibit a significant role in the progression of human malignant tumors. Firstly, GFI1 was identified using real-time PCR in HCC tissues and cells. In this work, we indicated GFI1 was remarkably reduced in HCC tissues and cells. Meanwhile, GFI1 specifically interacted with the promoter of LINC00675. Up-regulation of LINC00675 obviously repressed the migration and invasion capacity of SMCC-7721 and QGY-7703 cells in vitro. Moreover, decrease of LINC00675 competitively bound to miR-942-5p that contributed to the miRNA-mediated degradation of GFI1, thus facilitated HCC metastasis. The ceRNA function of LINC00675 in HCC cells was assessed and confirmed using RNA immunoprecipitation assay and RNA pull-down assays in our work. Additionally, we proved overexpression of miR-942-5p promoted HCC progression, which was reversed by the up-regulation of GFI1. In summary, LINC00675 might act as a prognostic marker for HCC, which can inhibit HCC development via regulating miR-942-5p and GFI1.

Long Non-Coding RNA Associated with Cholesterol Homeostasis and Its Involvement in Metabolic Diseases

Cholesterol is an essential cell component that functions to create and maintain all kinds of cell membranes and lipoprotein particles. It is crucial to maintain the proper amount of cholesterol at both the cellular and systemic level. Recently, the importance of cholesterol has been reported not only in various cell development processes but also in the development of diseases. Furthermore, the involvement of long non-coding RNAs (lncRNAs), which are regarded as important epigenetic regulators in gene expression, has also been reported in cholesterol homeostasis. It is thus necessary to summarize the research on lncRNAs related to cholesterol with increased interest. This review organized the role of lncRNAs according to the major issues in cholesterol homeostasis: efflux, metabolism and synthesis, and disease process.

Epigenetic Associations between lncRNA/circRNA and miRNA in Hepatocellular Carcinoma

Simple Summary

Non-coding RNAs such as microRNAs, long non-coding RNAs, and circular RNAs contribute to the development and progression of hepatocellular carcinoma through epigenetic association. Long non-coding RNAs and circular RNAs act as competing endogenous RNAs that contain binding sites for miRNAs and thus compete with the miRNAs, which results in promotion of miRNA target gene expression, thereby leading to proliferation and metastasis of hepatocellular carcinoma. Competing endogenous RNAs have the potential to become diagnostic biomarkers and therapeutic targets for treatment of hepatocellular carcinoma.

Abstract

The three major members of non-coding RNAs (ncRNAs), named microRNAs (miRNAs), long non-coding RNAs (lncRNAs), and circular RNAs (circRNAs), play an important role in hepatocellular carcinoma (HCC) development. Recently, the competing endogenous RNA (ceRNA) regulation model described lncRNA/circRNA as a sponge for miRNAs to indirectly regulate miRNA downstream target genes. Accumulating evidence has indicated that ceRNA regulatory networks are associated with biological processes in HCC, including cancer cell growth, epithelial to mesenchymal transition (EMT), metastasis, and chemoresistance. In this review, we summarize recent discoveries, which are specific ceRNA regulatory networks (lncRNA/circRNA-miRNA-mRNA) in HCC and discuss their clinical significance.

Non-Coding RNAs in Multiple Myeloma Bone Disease Pathophysiology

Bone remodeling is uncoupled in the multiple myeloma (MM) bone marrow niche, resulting in enhanced osteoclastogenesis responsible of MM-related bone disease (MMBD). Several studies have disclosed the mechanisms underlying increased osteoclast formation and activity triggered by the various cellular components of the MM bone marrow microenvironment, leading to the identification of novel targets for therapeutic intervention. In this regard, recent attention has been given to non-coding RNA (ncRNA) molecules, that finely tune gene expression programs involved in bone homeostasis both in physiological and pathological settings. In this review, we will analyze major signaling pathways involved in MMBD pathophysiology, and report emerging evidence of their regulation by different classes of ncRNAs.

Our emerging understanding of the roles of long non-coding RNAs in normal liver function, disease, and malignancy

Long non-coding RNAs (lncRNAs) are important biological mediators that regulate numerous cellular processes. New experimental evidence suggests that lncRNAs play essential roles in liver development, normal liver physiology, fibrosis, and malignancy, including hepatocellular carcinoma and cholangiocarcinoma. In this review, we summarise our current understanding of the function of lncRNAs in the liver in both health and disease, as well as discuss approaches that could be used to target these non-coding transcripts for therapeutic purposes.

The Effect of m6A Methylation Regulatory Factors on the Malignant Progression and Clinical Prognosis of Hepatocellular Carcinoma

The modification level of the transcript N⁶-methyladenosine (m6A), dynamically regulated by methyltransferases, binding proteins and demethylases, is closely related to the occurrence, and progression of tumors. Here, 13 differentially expressed m6A methylation regulators were confirmed in 374 hepatocellular carcinoma (HCC) patients, among which RBM15, YTHDC1, YTHDF1, and YTHDF2 were significantly variant in different stages and grades. Further consensus clustering analysis identified two HCC subtypes (cluster1/2) in this cohort, finding an active role of the m6A methylation regulators in the malignant progression of HCC. Furthermore, GESA enrichment analysis showed that PPAR signaling pathway, and the pathways involved in retinol metabolism and peroxisome were related to tumor progression. Additionally, a 4-gene risk model (ROC = 0.729) that can be used as a prognostic marker and a predictor for clinicopathological characteristics of HCC was constructed via univariate and multivariate Cox regression analyses. Analysis on overall survival and disease-free survival demonstrated that METTL3 and YTHDF1 out of the four genes in the model could serve as independent prognostic factors for HCC. Overall, this study systematically investigated the effect of m6A methylation regulators on the malignant progression of HCC and proposed a 4-gene risk prediction model, laying a theoretical foundation for the further research on HCC prognosis.

Identification of potential diagnostic gene biomarkers in patients with osteoarthritis

The current study was aimed to identify diagnostic gene signature for osteoarthritis (OA). The differentially expressed genes (DEGs) in synovial membrane samples and blood samples were respectively identified from the GEO dataset. The intersection DEGs between synovial membrane and blood were further screened out, followed by the functional annotation of these common DEGs. The optimal intersection gene biomarkers for OA diagnostics were determined. The GSE51588 dataset of articular cartilage was used for expression validation and further diagnostic analysis validation of identified gene biomarkers for OA diagnostics. There were 379 intersection DEGs were obtained between the synovial membrane and blood samples of OA. 22 DEGs had a diagnostic value for OA. After further screening, a total of 9 DEGs including TLR7, RTP4, CRIP1, ZNF688, TOP1, EIF1AY, RAB2A, ZNF281 and UIMC1 were identified for OA diagnostic. The identified DEGs could be considered as potential diagnostic biomarkers for OA.

Long Noncoding RNAs and Circular RNAs in Autoimmune Diseases

Immune responses are essential for the clearance of pathogens and the repair of injured tissues; however, if these responses are not properly controlled, autoimmune diseases can occur. Autoimmune diseases (ADs) are a family of disorders characterized by the body's immune response being directed against its own tissues, with consequent chronic inflammation and tissue damage. Despite enormous efforts to identify new drug targets and develop new therapies to prevent and ameliorate AD symptoms, no definitive solutions are available today. Additionally, while substantial progress has been made in drug development for some ADs, most treatments only ameliorate symptoms and, in general, ADs are still incurable. Hundreds of genetic loci have been identified and associated with ADs by genome-wide association studies. However, the whole list of molecular factors that contribute to AD pathogenesis is still unknown. Noncoding (nc)RNAs, such as microRNAs, circular (circ)RNAs, and long noncoding (lnc)RNAs, regulate gene expression at different levels in various diseases, including ADs, and serve as potential drug targets as well as biomarkers for disease progression and response to therapy. In this review, we will focus on the potential roles and genetic regulation of ncRNA in four autoimmune diseases-systemic lupus erythematosus, rheumatoid arthritis, multiple sclerosis, and type 1 diabetes mellitus.

Comprehensive biological function analysis of lncRNAs in hepatocellular carcinoma

Thousands of long non-coding RNAs (lncRNAs) have been discovered in human genomes by gene chip, next-generation sequencing, and/or other methods in recent years, which represent a significant subset of the universal genes involved in a wide range of biological functions. An abnormal expression of lncRNAs is associated with the growth, invasion, and metastasis of various types of human cancers, including hepatocellular carcinoma (HCC), which is an aggressive, highly malignant, and invasive tumor, and a poor prognosis in China. With a more in-depth understanding of lncRNA research for HCC and the emergence of new molecular-targeted therapies, the diagnosis, treatment, and prognosis of HCC will be considerably improved. Therefore, this review is expected to provide recommendations and directions for future lncRNA research for HCC.

Weighted Gene Co-Expression Network Analysis Identifies Critical Genes in the Development of Heart Failure After Acute Myocardial Infarction

Background: The development of heart failure (HF) remains a common complication following an acute myocardial infarction (AMI), and is associated with substantial adverse outcomes. However, the specific predictive biomarkers and candidate therapeutic targets for post-infarction HF have not been fully established. We sought to perform a weighted gene co-expression network analysis (WGCNA) to identify key modules, hub genes, and possible regulatory targets involved in the development of HF following AMI.

Methods: Genes exhibiting the most (top 50%) variation in expression levels across samples in a GSE59867 dataset were imported to the WGCNA. Gene Ontology and pathway enrichment analyses were performed on genes identified in the key module by Metascape. Gene regulatory networks were constructed using the microarray probe reannotation and bioinformatics database. Hub genes were screened out from the key module and validated using other datasets.

Results: A total of 10,265 most varied genes and six modules were identified between AMI patients who developed HF within 6 months of follow-up and those who did not. Specifically, the blue module was found to be the most significantly related to the development of post-infarction HF. Functional enrichment analysis revealed that the blue module was primarily associated with the inflammatory response, immune system, and apoptosis. Seven transcriptional factors, including SPI1, ZBTB7A, IRF8, PPARG, P65, KLF4, and Fos, were identified as potential regulators of the expression of genes identified in the blue module. Further, non-coding RNAs, including miR-142-3p and LINC00537, were identified as having close interactions with genes from the blue module. A total of six hub genes (BCL3, HCK, PPIF, S100A9, SERPINA1, and TBC1D9B) were identified and validated for their predictive value in identifying future HFs.

Conclusions: By using the WGCNA, we provide new insights into the underlying molecular mechanism and molecular markers correlated with HF development following an AMI, which may serve to improve risk stratification, therapeutic decisions, and prognosis prediction in AMI patients.

PITPNA-AS1 abrogates the inhibition of miR-876-5p on WNT5A to facilitate hepatocellular carcinoma progression

LncRNA PITPNA-AS1 was a newly identified lncRNA which has never been studied in cancers. Whether PITPNA-AS1 participated in the development of hepatocellular carcinoma (HCC) is obscure. Given the coaction of lncRNAs and miRNAs to carcinogenesis, the purpose of the present research is to inquire how PITPNA-AS1 affects HCC progression. Firstly, PITPNA-AS1 was observed to be heightened in HCC tissues. Then function assays proved that overexpressing or silencing PITPNA-AS1 could manipulate the proliferation and motility of HCC cells. Besides, PITPNA-AS1 was located in the cytoplasm. Among the candidate miRNAs of PITPNA-AS1, miR-876-5p was an obvious target. Moreover, mechanism experiments validated that PITPNA-AS1 modulated WNT5A expression by targeting miR-876-5p. Rescue experiments affirmed that WNT5A silencing rescued the miR-876-5p suppression-induced cellular processes in PITPNA-AS1-silenced Hep3B cells. And in vivo experiments determined that PITPNA-AS1 regulated HCC progression in vivo via miR-876-5p/WNT5A pathway. In conclusion, this work shed lights on the modulatory mechanism of PITPNA-AS1/miR-876-5p/WNT5A axis in HCC, which might be pivotal for exploring effective diagnostic biomarkers and treatment strategies for HCC patients.

Low expression of long noncoding RNA CTC-297N7.9 predicts poor prognosis in patients with hepatocellular carcinoma

BACKGROUND

Long noncoding RNAs (lncRNAs) are reported to play important roles in tumorigenesis of various malignant tumors. However, the clinical significance of aberrant lncRNA expression in hepatocellular carcinoma (HCC) is still elusive.

METHODS

Firstly, a differentially expressed lncRNA CTC-297N7.9 in HCC was detected by analyzing the data from The Cancer Genome Atlas (TCGA). Secondly, the expression level of CTC-297N7.9 was examined in four HCC cell lines and 60 pairs of HCC tissues by polymerase chain reaction (PCR) assay at our center. Thirdly, receiver operating characteristic (ROC) analysis was performed to evaluate the diagnostic value of CTC-297N7.9 for HCC. Correlation and survival analysis of HCC patients from the TCGA and our center were also carried out to assess the predictive value of CTC-297N7.9. Finally, survival prognostic models were established combining lncRNA expression and other clinical parameters.

RESULTS

The expression of CTC-297N7.9 was downregulated in HCC cell lines and HCC tissues. ROC curve revealed its significant diagnostic value in HCC. CTC-297N7.9 expression correlated with serum alpha-fetal protein (AFP), tumor stage, and tumor differentiation. Survival analysis indicated that overall survival (OS) and disease-free survival (DFS) are all positively associated with CTC-297N7.9 expression, especially in patients without viral hepatitis or cirrhosis. Cox regression analysis showed that CTC-297N7.9 expression level is an independent prognostic factor for both OS and DFS in HCC patients. Based on the model, CTC-297N7.9 was observed to be negatively correlated to risk score, indicating its role as a protective factor for HCC.

CONCLUSION

Our study demonstrated that the low expression of CTC-297N7.9 is associated with poor prognosis in HCC patients, suggesting its possible role as a potential prognostic marker for HCC.