Highly deregulated lncRNA LOC is associated with overall worse prognosis in Hepatocellular Carcinoma patients.
Ontology highlight
ABSTRACT:
SUBMITTER: Lim LJ
PROVIDER: S-EPMC8100808 | biostudies-literature |
REPOSITORIES: biostudies-literature
Similar Datasets
Project description:Background & aimsCancer cachexia is a wasting syndrome associated with functional impairment and reduced survival that impacts up to 50% of patients with gastrointestinal cancers. However, data are limited on the prevalence and clinical significance of cachexia in patients with hepatocellular carcinoma (HCC).MethodsWe performed a retrospective cohort study of patients diagnosed with HCC at 2 United States health systems between 2008 and 2018. Patient weights were recorded 6 months prior to and at time of HCC diagnosis. Cachexia was defined as >5% weight loss (or >2% weight loss if body mass index <20 kg/m2), and precachexia was defined as 2% to 5% weight loss. We used multivariable logistic regression models to identify correlates of cachexia and multivariable Cox proportional hazard models to identify factors associated with overall survival.ResultsOf 604 patients with HCC, 201 (33.3%) had precachexia and 143 (23.7%) had cachexia at diagnosis, including 19.0%, 23.5%, 34.7%, and 34.0% of patients with Barcelona Clinic Liver Cancer stages 0/A, B, C, and D, respectively. Patients with cachexia were less likely to receive HCC treatment (odds ratio, 0.38; 95% confidence interval, 0.21-0.71) and had worse survival than those with precachexia or stable weight (11.3 vs 20.4 vs 23.5 months, respectively; P < .001). Cachexia remained independently associated with worse survival (hazard ratio, 1.43; 95% confidence interval, 1.11-1.84) after adjusting for age, sex, race, ethnicity, Child Pugh class, alpha-fetoprotein, Barcelona Clinic Liver Cancer stage, and HCC treatment.ConclusionsNearly 1 in 4 patients with HCC present with cachexia, including many with compensated cirrhosis or early stage tumors. The presence of cancer-associated weight loss appears to be an early and independent predictor of worse outcomes in patients with HCC.
| S-EPMC8934317 | biostudies-literature
Project description:Hepatocellular carcinoma (HCC) is one of the most common and lethal cancers worldwide. Here, we present a novel strategy to identify key circRNA signatures of clinically relevant co-expressed circRNA-mRNA networks in pertinent cancer-pathways that modulate prognosis of HCC patients, by integrating clinic-pathological features, circRNA and mRNA expression profiles. Through further integration with miRNA expression profiles, clinically relevant competing-endogenous-RNA (ceRNA) networks of circRNA-miRNA-mRNAs were constructed. At least five clinically relevant nodal-circRNAs, co-expressed with numerous genes, were identified from the circRNA-mRNA networks. These nodal circRNAs upregulated proliferation (except circRaly) and transformation in cells. The most upregulated nodal-circRNA, circGPC3, associated with higher-grade tumors and co-expressed with 33 genes, competes with 11 mRNAs for two shared miRNAs. circGPC3 was experimentally demonstrated to upregulate cell-cycle and migration/invasion in both transformed and non-transformed liver cell-lines. circGPC3 was further shown to act as a sponge of miR-378a-3p to regulate APSM (Abnormal spindle-like microcephaly associated) expression and modulate cell transformation. This study identifies 5 key nodal master circRNAs in a clinically relevant circRNA-centric network that are significantly associated with poorer prognosis of HCC patients and promotes tumorigenesis in cell-lines. The identification and characterization of these key circRNAs in clinically relevant circRNA-mRNA and ceRNA networks may facilitate the design of novel strategies targeting these important regulators for better HCC prognosis.
| S-EPMC8199648 | biostudies-literature
Project description:The aim of this study was to identify novel prognostic mRNA and microRNA (miRNA) biomarkers for hepatocellular carcinoma (HCC) using methods in systems biology. Differentially expressed mRNAs, miRNAs, and long non-coding RNAs (lncRNAs) were compared between HCC tumor tissues and normal liver tissues in The Cancer Genome Atlas (TCGA) database. Subsequently, a prognosis-associated mRNA co-expression network, an mRNA-miRNA regulatory network, and an mRNA-miRNA-lncRNA regulatory network were constructed to identify prognostic biomarkers for HCC through Cox survival analysis. Seven prognosis-associated mRNA co-expression modules were obtained by analyzing these differentially expressed mRNAs. An expression module including 120 mRNAs was significantly correlated with HCC patient survival. Combined with patient survival data, several mRNAs and miRNAs, including CHST4, SLC22A8, STC2, hsa-miR-326, and hsa-miR-21 were identified from the network to predict HCC patient prognosis. Clinical significance was investigated using tissue microarray analysis of samples from 258 patients with HCC. Functional annotation of hsa-miR-326 and hsa-miR-21-5p indicated specific associations with several cancer-related pathways. The present study provides a bioinformatics method for biomarker screening, leading to the identification of an integrated mRNA-miRNA-lncRNA regulatory network and their co-expression patterns in relation to predicting HCC patient survival.
| S-EPMC9402792 | biostudies-literature
Project description:Pyroptosis is an inflammatory form of programmed cell death that is involved in various cancers, including hepatocellular carcinoma (HCC). Long non-coding RNAs (lncRNAs) were recently verified as crucial mediators in the regulation of pyroptosis. However, the role of pyroptosis-related lncRNAs in HCC and their associations with prognosis have not been reported. In this study, we constructed a prognostic signature based on pyroptosis-related differentially expressed lncRNAs in HCC. A co-expression network of pyroptosis-related mRNAs-lncRNAs was constructed based on HCC data from The Cancer Genome Atlas. Cox regression analyses were performed to construct a pyroptosis-related lncRNA signature (PRlncSig) in a training cohort, which was subsequently validated in a testing cohort and a combination of the two cohorts. Kaplan-Meier analyses revealed that patients in the high-risk group had poorer survival times. Receiver operating characteristic curve and principal component analyses further verified the accuracy of the PRlncSig model. Besides, the external cohort validation confirmed the robustness of PRlncSig. Furthermore, a nomogram based on the PRlncSig score and clinical characteristics was established and shown to have robust prediction ability. In addition, gene set enrichment analysis revealed that the RNA degradation, the cell cycle, the WNT signaling pathway, and numerous immune processes were significantly enriched in the high-risk group compared to the low-risk group. Moreover, the immune cell subpopulations, the expression of immune checkpoint genes, and response to chemotherapy and immunotherapy differed significantly between the high- and low-risk groups. Finally, the expression levels of the five lncRNAs in the signature were validated by quantitative real-time PCR. In summary, our PRlncSig model shows significant predictive value with respect to prognosis of HCC patients and could provide clinical guidance for individualized immunotherapy.
| S-EPMC8927701 | biostudies-literature
Project description:Hepatocellular carcinoma (HCC) cells often invade the portal venous system and subsequently develop into portal vein tumour thrombosis (PVTT). Long noncoding RNAs (lncRNAs) have been associated with HCC, but a comprehensive analysis of their specific association with HCC metastasis has not been conducted. Here, by analysing 60 clinical samples' RNA-seq data from 20 HCC patients, we have identified and characterized 8,603 candidate lncRNAs. The expression patterns of 917 recurrently deregulated lncRNAs are correlated with clinical data in a TCGA cohort and published liver cancer data. Matched array data from the 60 samples show that copy number variations (CNVs) and alterations in DNA methylation contribute to the observed recurrent deregulation of 235 lncRNAs. Many recurrently deregulated lncRNAs are enriched in co-expressed clusters of genes related to cell adhesion, immune response and metabolic processes. Candidate lncRNAs related to metastasis, such as HAND2-AS1, were further validated using RNAi-based loss-of-function assays. Thus, we provide a valuable resource of functional lncRNAs and biomarkers associated with HCC tumorigenesis and metastasis.
| S-EPMC5316832 | biostudies-literature
Project description:Recent studies indicated that long noncoding RNAs (lncRNAs) played important regulatory roles in carcinogenesis and cancer progression. However, the contribution of small nucleolar RNA host gene 20 (SNHG20) to cancer development remains largely unknown. The aim of the study is to investigate the expression of SNHG20 and its clinical significance in hepatocellular carcinoma (HCC). Our results showed that the expression of SNHG20 was remarkably up-regulated in HCC tissues compared with adjacent non-tumor liver tissues from 49 fresh HCC samples (cohort 1) detected by quantitative reverse-transcription polymerase chain reaction (qRT-PCR, P = 0.004). The results were confirmed in 144 formalin-fixed, paraffin-embedded HCC tissues (cohort 2) by in situ hybridization (ISH). Meanwhile, the expression of SNHG20 was associated with tumor size (P = 0.027 for cohort 1 and P = 0.046 for cohort 2) and clinical stage (P = 0.027 for cohort 1 and P = 0.028 for cohort 2). Importantly, patients with high expression of SNHG20 had a shorter overall survival (OS, P < 0.001) and disease-free survival (DFS, P < 0.001) than those with low expression of SNHG20. Univatiate and multivariate analysis showed that SNHG20 was a significant and independent prognostic predictor for OS of HCC patients (hazard ratio = 3.985, 95% CI = 1.981-8.017, P < 0.001). In addition, a total of 331 HCC patients' data from the Caner Genome Atlas project (TCGA) were used to validate our findings. Consistently, the results from TCGA HCC cohort demonstrated that SNHG20 were overexpressed in HCC tissues compared with non-tumor liver tissues (P < 0.001). Patients with higher expression levels of SNHG20 had poorer OS (P = 0.021) and DFS (P < 0.001). Functionally, knockdown of SNHG20 in SK-Hep-1 cells significantly inhibited cellular proliferation, migration, and invasion. In conclusion, SNHG20, up-regulated in patients with HCC, may serve as an independent prognostic predictor for HCC patients.
| S-EPMC4820738 | biostudies-literature
Project description:Objective: The purpose of this study was to establish an N6-methylandenosine (m6A)-related long non-coding RNA (lncRNA) signature to predict the prognosis of hepatocellular carcinoma (HCC). Methods: Pearson correlation analysis was used to identify m6A-related lncRNAs. We then performed univariate Cox regression analysis and least absolute shrinkage and selection operator (LASSO) Cox regression analysis to construct an m6A-related lncRNA signature. Based on the cutoff value of the risk score determined by the X-title software, we divided the HCC patients into high -and low-risk groups. A time-dependent ROC curve was used to evaluate the predictive value of the model. Finally, we constructed a nomogram based on the m6A-related lncRNA signature. Results: ZEB1-AS1, MIR210HG, BACE1-AS, and SNHG3 were identified to comprise an m6A-related lncRNA signature. These four lncRNAs were upregulated in HCC tissues compared to normal tissues. The prognosis of patients with HCC in the low-risk group was significantly longer than that in the high-risk group. The M6A-related lncRNA signature was significantly associated with clinicopathological features and was established as a risk factor for the prognosis of patients with HCC. The nomogram based on the m6A-related lncRNA signature had a good distinguishing ability and consistency. Conclusion: We identified an m6A-related lncRNA signature and constructed a nomogram model to evaluate the prognosis of patients with HCC.
| S-EPMC9006777 | biostudies-literature
Project description:PurposeTP53 mutation is the most common genetic variation type in Hepatocellular carcinoma (HCC). We aim to illustrate the landscape of genomic alterations and TP53 mutation related and directly regulated lncRNA prognosis markers.Materials and methodsUtilizing the clinical and transcriptome data from The Cancer Genome Atlas (TCGA) website, we present the landscape of genomic alterations and RNA differential expression profiles. By analyzing the ENCODE TP53 ChIP-seq data, we get the TP53 chromatin binding profiles. By Kaplan-Meier (KM) survival analysis and ROC analysis, we identify lncRNA prognosis markers.ResultsTP53 ranks the highest mutation frequency gene and the maximum mutation type of TP53 is Missense Mutation (> 2.5×104). TP53 mutation showed poor clinical outcome among the pathological Stage II and Stage III HCC patients. By differential expression analysis of the TP53 wild type and mutation HCC, we find thousands of misregulated genes, including 699 differential expression lncRNAs (p <0.05, |log2FC| ≥1). Functional enrichment analysis of the misregulated genes shows that TP53 mutation events mainly alter DNA replication, cell cycle and immune response signaling pathways. By estimation of tumor-infiltrating immune cells through CIBERSORT, we find that the TP53 mutation events are significantly correlated with the different proportions of nine immune cells. We then integratively analyze the differential expression lncRNAs in TP53 wild type and mutation groups and the TP53 ChIP-seq binding lncRNAs, and get 112 overlap lncRNAs. By Kaplan-Meier survival analysis and ROC analysis, we identify two lncRNAs (RP4-736L20.3 and SNRK-AS1) that show significant prognosis value. Using the collected HCC samples, we validate the misregulated expression of RP4-736L20.3 and SNRK-AS1.ConclusionThe work presents the landscape of genomic variations and two TP53 mutation related and directly regulated lncRNA prognosis markers of HCC.
| S-EPMC8364375 | biostudies-literature
Project description:Increased intracellular toxicity due to an imbalance in copper homeostasis caused by copper ion accumulation could regulate the rate of cancer cell growth and proliferation. The goal of this study was to create a novel Cuproptosis-related lncRNA signature that may be utilized to predict survival and immunotherapy in HCC patients. Cuproptosis-associated lncRNAs and differentially expressed lncRNAs between HCC tumor tissue and normal tissue were discovered first. By LASSO-Cox analysis, the overlapping lncRNAs were then utilized to build a Cuproptosis-associated lncRNA signature, which might be used to predict patient prognosis and responsiveness to immune checkpoint blockade (ICB) therapy. Differences in the infiltration of immune cell subpopulations between high and low-risk score subgroups were also analyzed. Moreover, a nomogram based on the Cuproptosis-associated lncRNA signature and clinical features was developed and demonstrated to have good predictive potential. Finally, qRT-PCR was performed in HerpG2 and MHCC-97H cell lines to explore whether these lncRNAs were indeed involved in the process of Cuproptosis. In summary, we created a prognostic lncRNA profile linked to Cuproptosis to forecast response to immunotherapy, which may provide a new potential non-apoptotic therapeutic perspective for HCC patients.
| S-EPMC9256635 | biostudies-literature
Project description:Long noncoding RNAs (lncRNAs) have been substantially reported to have critical roles in regulating tumorigenesis in recent years. However, the expression pattern and biological function of SNHG17 in hepatocellular carcinoma (HCC) remain unclear. Bioinformatics analysis and qRT-PCR were performed to detect the expression pattern of SNHG17 in HCC tissues, adjacent nontumorous tissues, and cell lines. The effect of SNHG17 on proliferation, migration, and apoptosis of HCC was investigated by knockdown and overexpressing SNHG17 in HCC cell lines. RNA sequencing was utilized to explore the underlying mechanism. Utilizing publicly available TCGA-LIHC, GSE102079 HCC datasets, and qRT-PCR, we found SNHG17 was significantly upregulated in HCC tissues and cell lines and was notably associated with larger tumor size, poorly differentiation, presence of vascular invasion, and advanced TNM stage. Furthermore, gain- and loss-of-function studies demonstrated that SNHG17 promoted cell proliferation and migration and inhibited apoptosis of HCC. By employing RNA sequencing, we found knockdown of SNHG17 caused 1037 differentially expressed genes, highly enriched in several pathways, including metabolic, PI3K-Akt, cell adhesion, regulation of cell proliferation, and apoptotic pathway; among them, 92 were overlapped with SNHG17-related genes in the TCGA-LIHC dataset. Furthermore, ERH, TBCA, TDO2, and PDK4 were successfully validated and found significantly dysregulated in HCC tissues. Moreover, HCC patients with higher SNHG17 expression had a relatively poor overall survival and disease-free survival, and ERH and PDK4 also played a marked role in the prognosis of HCC. Broadly, our findings illustrate that SNHG17 acts as a noncoding oncogene in HCC progression, suggesting its potential value as a novel target for HCC therapy.
| S-EPMC8455207 | biostudies-literature