lncRNAs In Hepatocellular Carcinoma Research Articles

Identification of biomarkers of hepatocellular carcinoma gene prognosis based on the immune-related lncRNA signature of transcriptome data

Long non-coding RNAs (lncRNAs) are well established to have an important role in cancer. The goal of this research was to investigate the prognostic usefulness of putative immune-related lncRNAs in hepatocellular carcinoma (HCC). The developed lncRNA signature was validated using 343 HCC patients from The Cancer Genome Atlas (TCGA) and 81 samples from Gene Expression Omnibus (GEO). Cox regression and Least Absolute Shrinkage and Selection Operator (LASSO) analysis were used to analyze immune-related lncRNAs for HCC prognosis. Patients in the low-risk group survived substantially longer than those in the high-risk group (P < 0.05). The discovered signal might be a useful prognostic factor for predicting patient survival. Overall survival predicted some clinical net improvements, according to the nomogram. Numerous enrichment approaches (including gene set enrichment analysis) were utilized to investigate the underlying mechanisms. Drug metabolism, mTOR, and p53 signaling pathways were associated with high-risk groups. When the expression of lncRNA PRRT3-AS1 was silenced in HepG2 cells, the proliferation, migration, and invasion abilities of HepG2 cells were decreased, and apoptosis was enhanced. In the supernatant from HepG2 cells with PRRT3-AS1 knockdown, the anti-inflammatory factors IL-10 and TGF-1 were induced, whereas the pro-inflammatory factors IL-1β, TNF-α, and IL-6 were reduced (P < 0.05). After PRRT3-AS1 knockdown, the protein expression of CD24, THY1, LYN, CD47, and TRAF2 in HepG2 cells was attenuated (P < 0.05). The discovery of five immune-related lncRNA signatures has significant therapeutic significance for predicting patient prognosis and directing personalized treatment for patients with HCC, which requires additional prospective confirmation.

Identification of a cuproptosis and copper metabolism gene-related lncRNAs prognostic signature associated with clinical and immunological characteristics of hepatocellular carcinoma.

The relationship between cuproptosis and HCC is still in the exploratory stage. Long noncoding RNAs (lncRNAs) have recently been linked to the progression of hepatocellular carcinoma (HCC). However, the clinical significance of lncRNAs associated with cuproptosis remains unclear. Based on The Cancer Genome Atlas (TCGA) liver hepatocellular carcinoma (LIHC) dataset, we identified characteristic prognostic lncRNAs by univariate, LASSO, and multifactorial regression analysis, and constructed a prognostic signature of cuproptosis-related lncRNAs in HCC. The role of lncRNAs were identified through CCK-8, clone formation in Huh-7 cells with high expression of FDX1. Prognostic potential of the characteristic lncRNAs was evaluated in each of the two cohorts created by randomly dividing the TCGA cohort into a training cohort and a test cohort in a 1:1 ratio. Immune profiles in defined subgroups of cuproptosis-related lncRNA features as well as drug sensitivity were analyzed. We constructed a multigene signature based on four characteristic prognostic lncRNAs (AL590705.3, LINC02870, KDM4A-AS1, MKLN1-AS). These four lncRNAs participated in the development of cuproptosis. HCC patients were classified into high-risk and low-risk groups based on the median value of the risk score. The receiver operating characteristic curve area under the curve values for 1-, 3-, and 5-year survival were 0.773, 0.728, and 0.647, respectively, for the training cohort, and 0.764, 0.671, and 0.662, respectively, for the test cohort. Univariate and multifactorial regression analyses indicated that this prognostic feature was an independent prognostic factor for HCC. Principal component analysis plots clearly distinguished between low- and high-risk patients in terms of their probability of survival. Furthermore, gene set enrichment analysis showed that a variety of processes associated with tumor proliferation and progression were enriched in the high-risk group compared with the low-risk group. Moreover, there were significant differences in the expression of immune cell subpopulations, immune checkpoint genes, and potential drug screening, which provided distinct therapeutic recommendations for individuals with various risks. We constructed a novel cuproptosis-associated lncRNA signature with a significant predictive value for the prognosis of patients with HCC. Cuproptosis-associated lncRNAs are associated with the tumor immune microenvironment of HCC and even the efficacy of tumor immunotherapy.

Integrated Analysis of N1-Methyladenosine Methylation Regulators-Related lncRNAs in Hepatocellular Carcinoma

N1-methyladenosine (m1A) and long non-coding RNAs (lncRNAs) play significant roles in tumor progression in hepatocellular carcinoma (HCC). However, their association with HCC is still unclear. In this study, lncRNAs related to m1A were extracted from the mRNA expression matrix in The Cancer Genome Atlas (TCGA) database. Five m1A-related lncRNAs (AL031985.3, NRAV, WAC-AS1, AC026412.3, and AC099850.4) were identified based on lasso Cox regression and they generated a prognostic signature of HCC. The prognostic signature was identified as an independent prognosis factor in HCC patients. Moreover, the prognostic signature achieved better performance than TP53 mutation status or tumor mutational burden (TMB) scores in the stratification of patient survival. The immune landscape indicated that most immune checkpoint genes and immune cells were distributed differently between both risk groups. A higher IC50 of chemotherapeutics (sorafenib, nilotinib, sunitinib, and gefitinib) was observed in the high-risk group, and a lower IC50 of gemcitabine in the low-risk group, suggesting the potential of the prognostic signature in chemosensitivity. In addition, fifty-five potential small molecular drugs were found based on drug sensitivity and NRAV expression. Together, five m1A-related lncRNAs generated a prognostic signature that could be a promising prognostic prediction approach and therapeutic response assessment tool for HCC patients.

Epigenetic inhibition of lncRNA GMDS-AS1 by methyltransferase ESET promoted cell viability and metastasis of hepatocellular carcinoma.

Long noncoding RNA (lncRNAs) GMDS-AS1 has been reported as a tumor regulator in tumor growth and metastasis, but its effect in hepatocellular carcinoma (HCC) remains unclear. ESET, a histone H3K9 methyl-transferase, is involved in epigenomic regulation of tumor progression in multiple cancers. However, the correlation between ESET and lncRNA in HCC is less reported. Quantitative real-time PCR (qRT-PCR) was taken to determine the expression of ESET and GMDS-AS1. Western blot was taken to determine the target protein levels of ESET and GMDS-AS1. Online database and bioinformatics analysis were used to screen abnormally expressed genes. Luciferase assay was performed to confirm the binding of GMDS-AS1 and PSMB1. Ki67 and Edu were used for evaluated the proliferation of tumor cells. ChIP assay was performed to verify the relationship between H3K9me1 and lncRNA GMDS-AS1 promoter. Transwell was taken to determine the migration and invasion ability of tumor cells. CCK-8 was used for determining the viability of tumor cells. Flow cytometry was performed to detect the cell cycle of tumor cells. The expression of GMDS-AS1 was decreased and the expression of ESET was increased in HCC. GMDS-AS1 inhibition contributed to tumor development, and this effect was closely related to epigenetic inhibition of GMDS-AS1 by ESET. PSMB1, a downstream target of GMDS-AS1, promoted the tumor proliferation and was negatively regulated by GMDS-AS1. Our result demonstrates anti-tumorigenic traits of lncRNA GMDS-AS1 in HCC and explains its pattern of regulation mediated by ESET. Our work unmasked an essential role of GMDS-AS1 in HCC progression and detected a novel pathway for ESET to promote HCC.

Construction a prognostic signature of hepatocellular carcinoma based on 5 necroptosis-related lncRNAs

Background: Hepatocellular carcinoma (HCC) is one of the most common malignant tumors of the digestive tract with a poor prognosis. Necroptosis is a kind of death receptor-mediated regulated programmed death, which has the dual characteristics of necrosis and apoptosis. Long non-coding RNAs (lncRNAs) are considered to be key regulators of the development of HCC. However, the expression of necroptosis-related lncRNAs in HCC and their relationship with prognosis have rarely been evaluated.

Prognostic and immunological role of sulfatide-related lncRNAs in hepatocellular carcinoma.

Hepatocellular carcinoma (HCC) is the most common primary malignancy of the liver. Long non-coding RNAs (lncRNAs) play important roles in the occurrence and development of HCC through multiple pathways. Our previous study reported the specific molecular mechanism for sulfatide regulation of integrin αV expression and cell adhesion in HCC cells through lncRNA AY927503. Next, it is necessary to identify more sulfatide-related lncRNAs, explore their clinical signifcance, and determine new targeted treatment strategies. Microarrays were used to screen a complete set of lncRNAs with different expression profiles in sulfatide-treated cells. Sulfatide-related lncRNAs expression data and corresponding HCC patient survival information were obtained from the The Cancer Genome Atlas (TCGA) database, and the prognosis prediction model was constructed based on Cox regression analysis. Methylated RNA immunoprecipitation with next generation sequencing (MeRIP-seq) was used to detemine the effect of sulfatide on lncRNAs m6A modification. Tumor Immune Estimation Resource (TIMER) and Gene set nnrichment analysis (GSEA) were utilized to enrich the immune and functional pathways of sulfatide-related lncRNAs. A total of 85 differentially expressed lncRNAs (|Fold Change (FC)|>2, P<0.05) were screened in sulfatide-treated HCC cells. As a result, 24 sulfatide-related lncRNAs were highly expressed in HCC tissues, six of which were associated with poor prognosis in HCC patients. Based on thses data, a sulfatide-related lncRNAs prognosis assessment model for HCC was constructed. According to this risk score analysis, the overall survival (OS) curve showed that the OS of high-risk patients was significantly lower than that of low-risk patients (P<0.05). Notably, the expression difference in sulfatide-related lncRNA NRSN2-AS1 may be related to sulfatide-induced RNA m6A methylation. In addition, the expression level of NRSN2-AS1 was significantly positively correlated with immune cell infiltration in HCC and participated in the peroxisome and Peroxisome proliferator-activated receptor (PPAR) signaling pathways. In conclusion, sulfatide-related lncRNAs might be promising prognostic and therapeutic targets for HCC.

E2F1 combined with LINC01004 super-enhancer to promote hepatocellular carcinoma cell proliferation and metastasis

IntroductionSuper-enhancer-associated lncRNAs play important roles in the occurrence and development of malignant tumors, including hepatocellular carcinoma (HCC).ObjectivesThe current work aimed to identify and characterize super-enhancer-associated lncRNAs in the pathogenesis of HCC.MethodsH3K27ac ChIP-seq data from HepG2 cell line and two HCC tissues were used to identify super-enhancer-associated lncRNAs in HCC. JQ-1 treatment and CRISPR-dCas9 system were performed to confirm super-enhancer activity. Quantitative real-time PCR (qPCR), ChIP-qPCR, and dual-luciferase reporter system assay demonstrated the regulation of E2F1 on super-enhancer. Functional loss experiment was used to identify the function of LINC01004.ResultsIn this study, we identified and characterized LINC01004, a novel super-enhancer-associated lncRNA, as a crucial oncogene in HCC. LINC01004 was upregulated in liver cancer tissues and was associated with poor patient prognosis. Moreover, LINC01004 promoted cell proliferation and metastasis of HCC. The binding of E2F1 to the super-enhancer could promote the transcription of LINC01004, while the inhibition of super-enhancer activity decreased LINC01004 expression.ConclusionThis finding might provide mechanistic insights into the molecular mechanisms underlying hepatocarcinogenesis and the biological function of super-enhancer. LINC01004 can serve as a potential therapeutic target for HCC patient.Graphical abstract

Identification of a CD4+ conventional T cells-related lncRNAs signature associated with hepatocellular carcinoma prognosis, therapy, and tumor microenvironment.

Hepatocellular carcinoma (HCC) is the second leading cause of cancer-related death worldwide, and CD4+ T lymphocytes can inhibit hepatocarcinogenesis and mediate tumor regression. However, few studies have focused on the prognostic power of CD4+ Tconv-related lncRNAs in HCC patients. We obtained data from TCGA and GEO databases and identified CD4+Tconv-related lncRNAs in HCC. The risk score was constructed using lasso regression and the model was validated using two validation cohorts. The RS was also assessed in different clinical subgroups, and a nomogram was established to further predict the patients' outcomes. Furthermore, we estimated the immune cell infiltration and cancer-associated fibroblasts (CAFs) through TIMER databases and assessed the role of RS in immune checkpoint inhibitors response. We constructed a CD4+ Tconv-related lncRNAs risk score, including six lncRNAs (AC012073.1, AL031985.3, LINC01060, MKLN1-AS, MSC-AS1, and TMCC1-AS1), and the RS had good predictive ability in validation cohorts and most clinical subgroups. The RS and the T stage were included in the nomogram with optimum prediction and the model had comparable OS prediction power compared to the AJCC. Patients in the high-risk group had a poor immune response phenotype, with high infiltrations of macrophages, CAFs, and low infiltrations of NK cells. Immunotherapy and chemotherapy response analysis indicated that low-risk group patients had good reactions to immune checkpoint inhibitors. We constructed and validated a novel CD4+ Tconv-related lncRNAs RS, with the potential predictive value of HCC patients' survival and immunotherapy response.

Identification and development of TP53 mutation-associated Long non-coding RNAs signature for optimized prognosis assessment and treatment selection in hepatocellular carcinoma.

The TP53 gene is estimated to be mutated in over 50% of tumors, with the majority of tumors exhibiting abnormal TP53 signaling pathways. However, the exploration of TP53 mutation-related LncRNAs in Hepatocellular carcinoma (HCC) remains incomplete. This study aims to identify such LncRNAs and enhance the prognostic accuracy for Hepatoma patients. Differential gene expression was identified using the "limma" package in R. Prognosis-related LncRNAs were identified via univariate Cox regression analysis, while a prognostic model was crafted using multivariate Cox regression analysis. Survival analysis was conducted using Kaplan-Meier curves. The precision of the prognostic model was assessed through ROC analysis. Subsequently, the Tumor Immune Dysfunction and Exclusion (TIDE) algorithm were executed on the TCGA dataset via the TIDE database. Fractions of 24 types of immune cell infiltration were obtained from NCI Cancer Research Data Commons using deconvolution techniques. The protein expression levels encoded by specific genes were obtained through the TPCA database. In this research, we have identified 85 LncRNAs associated with TP53 mutations and developed a corresponding signature referred to as TP53MLncSig. Kaplan-Meier analysis revealed a lower 3-year survival rate in high-risk patients (46.9%) compared to low-risk patients (74.2%). The accuracy of the prognostic TP53MLncSig was further evaluated by calculating the area under the ROC curve. The analysis yielded a 5-year ROC score of 0.793, confirming its effectiveness. Furthermore, a higher score for TP53MLncSig was found to be associated with an increased response rate to immune checkpoint blocker (ICB) therapy (p = .005). Patients possessing high-risk classification exhibited lower levels of P53 protein expression and higher levels of genomic instability. The present study aimed to identify and validate LncRNAs associated with TP53 mutations. We constructed a prognostic model that can predict chemosensitivity and response to ICB therapy in HCC patients. This novel approach sheds light on the role of LncRNAs in TP53 mutation and provides valuable resources for analyzing patient prognosis and treatment selection.

The Prognostic Value of a lncRNA Risk Model Consists of 9 m6A Regulator-Related lncRNAs in Hepatocellular Carcinoma (HCC).

Hepatocellular carcinoma (HCC) is the most common primary malignancy of the liver. Although the RNA modification N6-methyladenine (m6A) has been reported to be involved in HCC carcinogenesis, early diagnostic markers and promising personalized therapeutic targets are still lacking. In this study, we identified that 19 m6A regulators and 34 co-expressed lncRNAs were significantly upregulated in HCC samples; based on these factors, we established a prognostic signal of HCC associated with 9 lncRNAs and 19 m6A regulators using LASSO Cox regression analysis. Kaplan-Meier survival estimate revealed correlations between the risk scores and patients' OS in the training and validation dataset. The ROC curve demonstrated that the risk score-based curve has satisfactory prediction efficiency for both training and validation datasets. Multivariate Cox's proportional hazard regression analysis indicated that the risk score was an independent risk factor within the training and validation dataset. In addition, the risk score could distinguish HCC patients from normal non-cancerous samples and HCC samples of different pathological grades. Eventually, 232 mRNAs were co-expressed with these 9 lncRNAs according to GSE101685 and GSE112790; these mRNAs were enriched in cell cycle and cell metabolic activities, drug metabolism, liver disease-related pathways, and some important cancer related pathways such as p53, MAPK, Wnt, RAS and so forth. The expression of the 9 lncRNAs was significantly higher in HCC samples than that in the neighboring non-cancerous samples. Altogether, by using the Consensus Clustering, PCA, ESTIMATE algorithm, LASSO regression model, Kaplan-Meier survival assessment, ROC curve analysis, and multivariate Cox's proportional hazard regression model analysis, we established a prognostic marker consisting of 9 m6A regulator-related lncRNAs that markers may have prognostic and diagnostic potential for HCC.

LINC01608 activated by YY1 facilitate hepatocellular carcinoma progression by modulating the EGFR/ERK axis.

Long non-coding RNAs (LncRNAs) have been demonstrated to associate with a variety of cancers. However, the mechanisms of LncRNAs in hepatocellular carcinoma (HCC) progression are still not fully clarified. LINC01608 expression level in HCC and adjacent normal tissues was detected by real-time-quantitively PCR (RT-qPCR) in clinical samples and in situ hybridization (ISH) in tissue microarray. Several functional assays were performed to determine the biological effects of LINC01608 in HCC cells in vitro, while subcutaneous xenograft models and lung metastasis models in nude mice and immunohistochemistry (IHC) results showed the role of LINC01608 in HCC progression in vivo. The combination of LINC01608 with miR-875-5p and target genes was elucidated by dual-luciferase report assays, RNA immunoprecipitation (RIP) assays and fluorescence in situ hybridization (FISH) assays. Finally, bioinformatics analysis and chromatin immunoprecipitation (CHIP) were performed to investigate the mechanism of Yin Yang-1 (YY1) regulating LINC01608 transcription. LINC01608 was overexpressed in HCC tissues, and high LINC01608 expression predicted poor overall survival (OS) and disease-free survival (DFS) in HCC patients. LINC01608 could promote HCC cell proliferation, migration, invasion and epithelial-mesenchymal transition (EMT) in vitro and in vivo. Furthermore, we demonstrated that LINC01608 could sponge to miR-875-5p and activate the EGFR/ERK pathway. Moreover, we identified transcriptional factor YY1 could bind to the promoter of LINC01608 and induce its transcription. LINC01608 could serve as a promising prognostic biomarker of HCC. YY1-activated LINC01608 could promote HCC progression by associating with miR-875-5p to induce the EGFR/ERK signalling pathway. This discovery might provide therapeutic strategies for HCC.

The roles of lncRNA functions and regulatory mechanisms in the diagnosis and treatment of hepatocellular carcinoma.

Hepatocellular carcinoma (HCC) is the most frequent and deadly type of liver cancer. While the underlying molecular mechanisms are poorly understood, it is documented that lncRNAs may play key roles. Many HCC-associated lncRNAs have been linked to HBV and HCV infection, mediating gene expression, cell growth, development, and death. Studying the regulatory mechanisms and biological functions of HCC-related lncRNAs will assist our understanding of HCC pathogenesis as well as its diagnosis and management. Here, we address the potential of dysregulated lncRNAs in HCC as diagnostic and therapeutic biomarkers, and we evaluate the oncogenic or tumor-suppressive properties of these lncRNAs.

Knockdown of the long noncoding RNA PURPL induces apoptosis and sensitizes liver cancer cells to doxorubicin

Hepatocellular carcinoma (HCC) is the most common type of primary liver cancer with increasing incidence in western countries. Most HCC patients have advanced cancer at the time of diagnosis due to the asymptomatic nature of early-stage HCC and do not qualify for potentially curative surgical treatment, thus, highlighting the need for new therapeutic strategies. Long noncoding RNAs (lncRNAs) comprise a large and heterogeneous group of non-protein coding transcripts that play important regulatory roles in numerous biological processes in cancer. In this study, we performed RNA sequencing of liver biopsies from ten HCC, ten hepatitis C virus-associated HCC, and four normal livers to identify dysregulated lncRNAs in HCC. We show that the lncRNA p53-upregulated-regulator-of-p53-levels (PURPL) is upregulated in HCC biopsies and that its expression is p53-dependent in liver cancer cell lines. In addition, antisense oligonucleotide-mediated knockdown of PURPL inhibited cell proliferation, induced apoptosis, and sensitized HepG2 human HCC cells to treatment with the chemotherapeutic agent doxorubicin. In summary, our findings suggest that PURPL could serve as a new therapeutic target for reversing doxorubicin resistance in HCC.

Exploring a four-gene risk model based on doxorubicin resistance-associated lncRNAs in hepatocellular carcinoma.

Background: Liver cancer is a lethal cancer type among which hepatocellular carcinoma (HCC) is the most common manifestation globally. Drug resistance is a central problem impeding the efficiency of HCC treatment. Long non-coding RNAs reportedly result in drug resistance. This study aimed to identify key lncRNAs associated with doxorubicin resistance and HCC prognosis. Materials and Methods: HCC samples with gene expression profiles and clinical data were accessed from public databases. We applied differential analysis to identify key lncRNAs that differed between HCC and normal samples and between drug-fast and control samples. We also used univariate Cox regression analysis to screen lncRNAs or genes associated with HCC prognosis. The least absolute shrinkage and selection operator (LASSO) was used to identify the key prognostic genes. Finally, we used receiver operating characteristic analysis to validate the effectiveness of the risk model. Results: The results of this study revealed RNF157-AS1 as a key lncRNA associated with both doxorubicin resistance and HCC prognosis. Metabolic pathways such as fatty acid metabolism and oxidative phosphorylation were enriched in RNF157-AS1-related genes. LASSO identified four protein-coding genes-CENPP, TSGA10, MRPL53, and BFSP1-to construct a risk model. The four-gene risk model effectively classified HCC samples into two risk groups with different overall survival. Finally, we established a nomogram, which showed superior performance in predicting the long-term prognosis of HCC. Conclusion: RNF157-AS1 may be involved in doxorubicin resistance and may serve as a potential therapeutic target. The four-gene risk model showed potential for the prediction of HCC prognosis.

N6 -methyladenosine-modified lncRNA ARHGAP5-AS1 stabilises CSDE1 and coordinates oncogenic RNA regulons in hepatocellular carcinoma.

Hepatocellular carcinoma (HCC) ranks fourth among the malignancies leading to cancer-related deaths all around the world. It is increasingly evident that long non-coding RNAs (lncRNAs) are a key mode of hepatocarcinogenesis. As the most prevalent mRNA modification form, N6 -methyladenosine (m6 A) regulates gene expression by impacting multiple aspects of mRNA metabolism. However, there are still no reports on genome-wide screening and functional annotation of m6 A-methylated lncRNAs in HCC. The m6 A modification and biologic functions of ARHGAP5-AS1 in HCC were investigated through a series of biochemical assays. Clinical implications of ARHGAP5-AS1 were examined in tissues from HCC patients. After systematically analysing the m6 A-seq data of HCC cells, we identified 22 candidate lncRNAs with evidently dysregulated m6 A levels. Among these lncRNAs, we found that ARHGAP5-AS1 is the lncRNA with the highest levels of m6 A modification and significantly increased expression in HCC specimens. METTL14 acts as the m6 A writer of ARHGAP5-AS1 and IGF2BP2 stabilises the lncRNA as its m6 A reader. ARHGAP5-AS1 remarkably promotes malignant behaviours of HCC cells ex vivo and in vivo. We identified oncoprotein CSDE1 working as the interacting protein of the lncRNA and TRIM28 as the E3 ligase of CSDE1 in HCC. Interestingly, ARHGAP5-AS1 could attenuate interactions between CSDE1 and TRIM28, which prevents the degradation of CSDE1 via the ubiquitin-proteasome pathway. Elevated levels of CSDE1 coordinate oncogenic RNA regulons, promote translation of VIM and RAC1 and activate the ERK pathway, which contributes to HCC prognosis. Our study reveals a new paradigm in m6 A-modified lncRNAs controlling CSDE1-mediated oncogenic RNA regulons and highlights lncRNAs as potential targets for future therapeutics against HCC.

Long non-coding RNA COX7C-5 promotes hepatocellular carcinoma progression via miR-581/ZEB2 axis

Long non-coding RNAs (lncRNA) play crucial roles in hepatocellular carcinoma (HCC) progression. However, the functional roles of lncRNAs in HCC still remain largely unknown. Our study aimed to investigate the biological function and potential molecular mechanism of lnc-COX7C-5 in HCC. Here, we show that Lnc-COX7C-5 was significantly upregulated in HCC tissues, which was correlated with poor prognosis in HCC patients. Lnc-COX7C-5 positively regulated proliferation, migration, and invasion of HCC cells. Mechanistically, lnc-COX7C-5 function as a competing endogenous RNA (ceRNA) for miR-581 in HCC cells. Over-expression or knockdown of miR-581 could alter cell phenotypes caused by Lnc-COX7C-5 in HCC. Further investigations indicated that ZEB2 was demonstrated as a downstream target of miR-581. In mouse model, over-expression of Lnc-COX7C-5 facilitate lung metastasis of HCC. Collectively, Lnc-COX7C-5 promote HCC tumorigenesis and progression by targeting the miR-581/ZEB2 axis. Lnc-COX7C-5 may be a potential therapeutic target for HCC.

The Expressions and Functions of lncRNA Related to m6A in Hepatocellular Carcinoma from a Bioinformatics Analysis.

Hepatocellular carcinoma (HCC) is one of the most common cancer in these days. Besides, N6-methyladenosine (m6A) plays an important role in the occurrence and development of hepatocellular carcinoma. Meanwhile, it is known to us that long noncoding RNAs (lncRNA) have the capability to control the expression of genes which means some lncRNA can adjust the expression of some m6A.Thus, it is indispensable to dig the m6A-related lncRNA in hepatocellular carcinoma about its potential regulatory mechanism and immune analysis as well as its potential drugs. In this experiment, expression profile and clinical information of lncRNA are obtained by downloading the liver cancer data set from The Cancer Genome Atlas (TCGA) database. GO enrichment analysis is used to predict potential regulatory mechanism of lncRNA. Correlation analysis of clinical parameters are calculated via chisq.test. The Cox regression model is used in univariate and multivariate analysis, and the difference is statistically significant when P < 0.05. The results show that many kinds of lncRNA have influence on the prognosis of patients with HCC, and enrichment analysis discloses some pathways that can be used to evaluate mechanism underlying in HCC. The screening of targeted drugs can provide new clues for further experiments and clinical treatment.

Identification and validation of a prognostic model of necroptosis-related lncRNAs in hepatocellular carcinoma.

Background: The study focused on establishing a prognostic survival model with six necroptosis-related lncRNAs to predict overall survival (OS) in patients with hepatocellular carcinoma (HCC). Methods: The data of gene expression and clinical information of HCC patients were obtained from The Cancer Genome Atlas (TCGA). Cox regression with LASSO was used for constructing a necroptosis-related lncRNA survival model, which we further validated with qRT-PCR in vitro. The relative bioinformatics analysis and consensus cluster analysis were performed based on six differentially expressed lncRNAs. Results: The survival prognostic model was constructed by using data from TCGA. Receiver operating characteristic (ROC) curves showed a good survival prediction by this model. GSEA showed that several signaling pathways were related to HCC progression. Immune-related functional analysis showed that aDCs, macrophages, Th2 cells, and Tregs have stronger correlation with the high-risk group. The consensus cluster analysis further validated the 6-lncRNA prognostic model. Conclusion: A novel 6-lncRNA (AL606489.1, NRAV, LINC02870, DUXAP8, “ZFPM2-AS1,” and AL031985.3) prognostic model had an accurately predictive power in HCC prognosis, which might be worthy of clinical application.

Cuproptosis-related lncRNAs predict the clinical outcome and immune characteristics of hepatocellular carcinoma.

Cuproptosis, as a novel copper-dependent and non-apoptotic form of cell death, is induced by aggregation of lipoylated mitochondrial proteins and the instability of Fe-S cluster proteins. However, the role of cuproptosis-related long noncoding RNAs (CRLncRNAs) in hepatocellular carcinoma (HCC) has not been clearly elucidated. In this study, we identified and characterized cuproptosis-related lncRNAs in HCC. 343 HCC cases from The Cancer Genome Atlas (TCGA) with gene transcriptome data and clinical data were obtained for analysis after the screening. Univariate and multivariate Cox proportional hazards analyses were performed to establish a prognostic cuproptosis-related lncRNA signature (CRlncSig). We established a prognosis-related model consisting of nine cuproptosis-related lncRNAs: GSEC, AL158166.1, AC005479.2, AL365361.1, AC026412.3, AL031985.3, LINC00426, AC009974.2, AC245060.7, which was validated in the internal cohort. High-risk group stratified by the CRlncSig was significantly related to poor prognosis (p < 0.001). The area under the receiver operating characteristic curve (AUC) of 1 year, 3 years, and 5 years of survival were 0.813, 0.789, and 0.752, respectively. Furthermore, a prognostic nomogram including CRlncSig with clinicopathologic factors was built with favorable predictive power. In addition, GO and KEGG enrichment analysis suggested that CRlncSig was involved in many carcinogenesis and immune-related pathways. Additionally, we found that tumor microenvironment, immune infiltration, immune function, and drug response were significantly different between the high-risk and low-risk groups based on the risk model. These results highlight the value of cuproptosis-related lncRNAs on prognosis for HCC patients and provide insight into molecular and immune features underlying cuproptosis-related lncRNAs, which might play an important role in patient management and immunotherapy.

Expression and prognostic signatures of m6A-related lncRNAs in hepatocellular carcinoma.

N6-methyladenosine (m6A) is a common modification and plays an important role in various biological processes, but m6A-related lncRNA functions in hepatocellular carcinoma (HCC) have not been systematically clarified. The clinical data and RNA-seq transcriptome of 375 cases of HCC and 50 cases of normal tissues were obtained from the Cancer Gene Atlas database. Co-expression analysis was used to obtain m6A-related lncRNA. The independent prognostic factors were identified by univariate and multivariate Cox regression models. Kaplan-Meier method was used in survival analysis. The core gene of the mRNA-mRNA interaction network is related to m6A-related lncRNAs obtained by the CytoHubba plugin of Cytoscape. Gene ontology and Kyoto Gene Encyclopedia were analyzed to find out the potential mechanism. CIBERSORT algorithm was used to calculate the relative proportion of immune infiltrating cells. We identified two subgroups (cluster 1 and cluster 2) according to the expression level. The survival analysis curve and receiver operating characteristic curve proved that this model could predict the prognosis of HCC patients. The univariate and multivariate Cox regression analyses showed the independent prognostic value. UBE2C was screened as the pivotal gene. The expression level of m6A-related lncRNAs causes changes in the tumor immune microenvironment. The expression levels of m6A-related lncRNAs were significantly different and the prognostic value of m6A-related lncRNAs was confirmed. The m6A-related lncRNAs are expected to be prognostic signatures in HCC.