Screening prognostic markers for hepatocellular carcinoma based on pyroptosis-related lncRNA pairs.

Pyroptosis is closely related to cancer prognosis. In this study, we tried to construct an individualized prognostic risk model for hepatocellular carcinoma (HCC) based on within-sample relative expression orderings (REOs) of pyroptosis-related lncRNAs (PRlncRNAs). RNA-seq data of 343 HCC samples derived from The Cancer Genome Atlas (TCGA) database were analyzed. PRlncRNAs were detected based on differentially expressed lncRNAs between sample groups clustered by 40 reported pyroptosis-related genes (PRGs). Univariate Cox regression was used to screen out prognosis-related PRlncRNA pairs. Then, based on REOs of prognosis-related PRlncRNA pairs, a risk model for HCC was constructed by combining LASSO and stepwise multivariate Cox regression analysis. Finally, a prognosis-related competing endogenous RNA (ceRNA) network was built based on information about lncRNA-miRNA-mRNA interactions derived from the miRNet and TargetScan databases. Hierarchical clustering of HCC patients according to the 40 PRGs identified two groups with a significant survival difference (Kaplan-Meier log-rank, p = 0.026). Between the two groups, 104 differentially expressed lncRNAs were identified (|log2(FC)|> 1 and FDR < 5%). Among them, 83 PRlncRNA pairs showed significant associations between their REOs within HCC samples and overall survival (Univariate Cox regression, p < 0.005). An optimal 11-PRlncRNA-pair prognostic risk model was constructed for HCC. The areas under the curves (AUCs) of time-dependent receiver operating characteristic (ROC) curves of the risk model for 1-, 3-, and 5-year survival were 0.737, 0.705, and 0.797 in the validation set, respectively. Gene Set Enrichment Analysis showed that inflammation-related interleukin signaling pathways were upregulated in the predicted high-risk group (p < 0.05). Tumor immune infiltration analysis revealed a higher abundance of regulatory T cells (Tregs) and M2 macrophages and a lower abundance of CD8 + T cells in the high-risk group, indicating that excessive pyroptosis might occur in high-risk patients. Finally, eleven lncRNA-miRNA-mRNA regulatory axes associated with pyroptosis were established. Our risk model allowed us to determine the robustness of the REO-based PRlncRNA prognostic biomarkers in the stratification of HCC patients at high and low risk. The model is also helpful for understanding the molecular mechanisms between pyroptosis and HCC prognosis. High-risk patients may have excessive pyroptosis and thus be less sensitive to immune therapy.

Wu T ，Li N ，Luo F ，Chen Z ，Ma L ，Hu T ，Hong G ，Li H ... -  《BMC BIOINFORMATICS》

Screening Prognosis-Related lncRNAs Based on WGCNA to Establish a New Risk Score for Predicting Prognosis in Patients with Hepatocellular Carcinoma.

Hepatocellular carcinoma (HCC) remains an important cause of cancer death. The molecular mechanism of hepatocarcinogenesis and prognostic factors of HCC have not been completely uncovered. In this study, we screened out differentially expressed lncRNAs (DE lncRNAs), miRNAs (DE miRNAs), and mRNAs (DE mRNAs) by comparing the gene expression of HCC and normal tissue in The Cancer Genome Atlas (TCGA) database. DE mRNAs were used to perform Gene Ontology (GO), Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway analysis. Then, the miRNA and lncRNA/mRNA modules that were most closely related to the survival time of patients with HCC were screened to construct a competitive endogenous RNA (ceRNA) network by weighted gene coexpression network analysis (WGCNA). Moreover, univariable Cox regression and Kaplan-Meier curve analyses of DE lncRNAs and DE mRNAs were conducted. Finally, the lasso-penalized Cox regression analysis and nomogram model were used to establish a new risk scoring system and predict the prognosis of patients with liver cancer. The expression of survival-related DE lncRNAs was verified by qRT-PCR. A total of 1896 DEmRNAs, 330 DElncRNAs, and 76 DEmiRNAs were identified in HCC and normal tissue samples. Then, the turquoise miRNA and turquoise lncRNA/mRNA modules that were most closely related to the survival time of patients with HCC were screened to construct a ceRNA network by WGCNA. In this ceRNA network, there were 566 lncRNA-miRNA-mRNA regulatory pairs, including 30 upregulated lncRNAs, 16 downregulated miRNAs, and 75 upregulated mRNAs. Moreover, we screened out 19 lncRNAs and 14 hub mRNAs related to prognosis from this ceRNA network by univariable Cox regression and Kaplan-Meier curve analyses. Finally, a new risk scoring system was established by selecting the optimal risk lncRNAs from the 19 prognosis-related lncRNAs through lasso-penalized Cox regression analysis. In addition, we established a nomogram model consisting of independent prognostic factors to predict the survival rate of HCC patients. Finally, the correlation between the risk score and immune cell infiltration and gene set enrichment analysis were determined. In conclusion, the results may provide potential biomarkers or therapeutic targets for HCC and the establishment of the new risk scoring system and nomogram model provides the new perspective for predicting the prognosis of HCC.

Zhou X ，Dou M ，Liu Z ，Jiao D ，Li Z ，Chen J ，Li J ，Yao Y ，Li L ，Li Y ，Han X ... -  《-》

A Cuproptosis-Related LncRNA Risk Model for Predicting Prognosis and Immunotherapeutic Efficacy in Patients with Hepatocellular Carcinoma.

Cuproptosis is a novel programmed cell death pathway that is initiated by direct binding of copper to lipoylated tricarboxylic acid (TCA) cycle proteins. Recent studies have demonstrated that cuproptosis-related genes regulate tumorigenesis. However, the potential role and clinical significance of cuproptosis-related long noncoding RNAs (lncRNAs) in hepatocellular carcinoma (HCC) have not been established. We performed a bioinformatics analyses of RNA-sequencing data of HCC patients extracted from The Cancer Genome Atlas (TCGA) dataset to identify and validate a cuproptosis-related lncRNA prognostic signature. Furthermore, we analyzed the clinical significance of the prognostic signature of cuproptosis-related lncRNA in predicting the immunotherapeutic efficacy and the status of the tumor immune microenvironment. The RNA-sequencing data, genomic mutations, and clinical information were downloaded for 374 HCC samples and 50 normal liver samples from TCGA-Liver Hepatocellular Carcinoma (TCGA-LIHC) dataset. Co-expression analysis of Gene-lncRNA pairs with 49 known cuproptosis-related prognostic genes was used to define cuproptosis-related prognostic lncRNAs. We performed the LASSO algorithm and univariate and multivariate Cox regression analysis, respectively, to gradually identify the prognostic risk models of cuproptosis-related lncRNA based on the TCGA-LIHC dataset. Subsequently, the predictive performance of the model was evaluated using receiver operation characteristic (ROC) curves, Kaplan-Meier survival curves, and prognostic nomogram. The analysis of gene-lncRNA co-expression with 49 known cuproptosis-related genes identified 1359 cuproptosis-related lncRNAs in the TCGA-LIHC data set. A prognostic model was constructed with nine cuproptosis-related prognostic lncRNAs (AC007998.3, AC003086.1, AC009974.2, IQCH-AS1, LINC0256 1, AC105345.1, ZFPM2-AS1, AL353708.1 and WAC-AS1) using LASSO regression and Cox regression analyses. Risk scores were calculated for all HCC patient samples based on the four cuproptosis-related lncRNA prognostic models. All HCC patients were divided into high-risk and low-risk subgroups according to a 1:1 ratio column. The Kaplan-Meier survival curve analysis showed that the overall survival rate (OS) of the high-risk group patients was significantly lower than that of the low-risk group. The principal component analysis (PCA) confirmed that the prognostic lncRNA model accurately distinguished between high- and low-risk HCC patients. Furthermore, regression analysis as well as ROC curves confirmed the prognostic value of the risk score. A nomogram with risk scores and other clinicopathological characteristics was constructed. The nomogram accurately predicted the probability of 1-, 3-, and 5-year OS in HCC patients. Tumor mutation burden (TMB) scores were higher for high-risk patients than for low-risk patients. HCC patients in the low-risk group showed lower TIDE scores and greater sensitivity to antitumor drugs than those in the high-risk group. Tumor immune responses and tumor immune cell infiltration were significantly different between the high-risk and low-risk groups of patients with HCC. Our study identified a 9-cuproptosis-related lncRNA signature that accurately predicted prognosis, immunotherapeutic efficacy, and the status of the tumor immune microenvironment in HCC patients. Therefore, this cuproptosis-related lncRNA risk model is a potential prognostic biometric feature in HCC and shows high clinical value in identifying HCC patients who are potentially responsive to immunotherapy.

Wang S ，Bai H ，Fei S ，Miao B ... -  《-》

Genome-Wide Analysis of Prognostic lncRNAs, miRNAs, and mRNAs Forming a Competing Endogenous RNA Network in Hepatocellular Carcinoma.

Hepatocellular carcinoma (HCC) is the most prevalent subtype of primary liver tumor worldwide. Growing evidence has led to a consensus that long non-coding RNAs (lncRNAs) have considerable influence on tumorigenesis and tumor progression of HCC via the mechanism of competing endogenous RNAs (ceRNAs). Here, we systematically investigated the expression landscape and clinical prognostic value of lncRNAs, micorRNAs (miRNAs), and mRNAs from The Cancer Genome Atlas. Differentially expressed RNAs were submitted to Cox regression analysis and the construction of prognostic indexes. A lncRNA-miRNA-mRNA regulatory network was then constructed based on interaction information derived from miRcode, TargetScan, miRTarBase, and miRDB. Gene Ontology and Kyoto Encyclopedia of Genes and Genomes analyses were performed to reveal and determine the functional roles of the ceRNA network in the prognosis of HCC. We detected 77 differentially expressed lncRNAs, 29 differentially expressed miRNAs, and 1014 differentially expressed mRNAs in HCC, which were significantly associated with the overall survival of patients with HCC. We developed three prognostic prediction models that showed moderate predicting prognosis performance and were highly correlated with tumor burden, histological grade and pathological stage. Additionally, 10 survival-related lncRNAs, 6 survival-related miRNAs, and 31 survival-related mRNAs were included to develop a ceRNA network. Further functional enrichment analysis suggested that the ceRNA network was associated with a dismal prognosis for patients with HCC by disturbing the homeostasis of the cell cycle. Together, our study highlights the significant roles of lncRNAs in the development and implementation of monitoring surveillance and prognosis of HCC and provides a deeper understanding of the lncRNA-related ceRNA regulatory mechanism in the pathogenesis of HCC.

Lin P ，Wen DY ，Li Q ，He Y ，Yang H ，Chen G ... -  《-》

Six-long non-coding RNA signature predicts recurrence-free survival in hepatocellular carcinoma.

Gu JX ，Zhang X ，Miao RC ，Xiang XH ，Fu YN ，Zhang JY ，Liu C ，Qu K ... -  《-》