Construction of a 13-microRNA-based signature and prognostic nomogram for predicting overall survival in patients with hepatocellular carcinoma

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.

Identification of N7-methylguanosine-related miRNAs as potential biomarkers for prognosis and drug response in breast cancer

Objectives

The impact of N7-methylguanosine (m7G) on tumor progression and the regulatory role of microRNAs (miRNAs) in immune function significantly influence breast cancer (BC) prognosis. Investigating the interplay between m7G modification and miRNAs provides novel insights for assessing prognostics and drug responses in BC.

Materials and methods

RNA sequences (miRNA and mRNA profiles) and clinical data for BC were acquired from the Cancer Genome Atlas (TCGA) database. A miRNA signature associated with 15 m7G in this cohort was identified using Cox regression and LASSO. The risk score model was evaluated using Kaplan-Meier and time-dependent ROC analysis, categorizing patients into high-risk and low-risk groups. Functional enrichment analyses were conducted to explore potential pathways. The immune system, including scores, cell infiltration, function, and drug sensitivity, was examined and compared between high-risk and low-risk groups. A nomogram that combines risk scores and clinical factors was developed and validated. Single-sample gene set enrichment analysis (ssGSEA) was employed to explore m7G-related miRNA signatures and immune cell relationships in the tumor microenvironment. Additionally, drug susceptibility was compared between risk groups.

Results

Fifteen m7G-related miRNAs were independently correlated with overall survival (OS) in BC patients. Time-dependent ROC analysis yielded area under the curve (AUC) values of 0.742, 0.726, and 0.712 for predicting 3-, 5-, and 10-year survival rates, respectively. The Kaplan-Meier analysis revealed a significant disparity in OS between the high-risk and low-risk groups (p = 1.3e-6). Multiple regression identified the risk score as a significant independent prognostic factor. An excellent calibration nomogram with a C-index of 0.785 (95 % CI: 0.728-0.843) was constructed. In immune analysis, low-risk patients exhibited heightened immune function and increased responsiveness to immunotherapy and chemotherapy compared to high-risk patients.

Conclusion

This study systematically analyzed m7G-related miRNAs and revealed their regulatory mechanisms concerning the tumor microenvironment (TME), pathology, and the prognosis of BC patient. Based on these miRNAs, a prognostic model and nomogram were developed for BC patients, facilitating prognostic assessments. These findings can also assist in predicting treatment responses and guiding medication selection.

Circulating extracellular vesicle-encapsulated microRNA-557 induces a proinflammatory immune response and serves as a diagnostic or relapse marker in autoimmune hepatitis

AIM

This study investigated serum microRNAs (miRNAs/miRs) in autoimmune hepatitis (AIH) and the relationship of these molecules with diagnostic and relapse markers.

METHODS

Initially, extracellular vesicle-encapsulated miRNAs (EV-miRNAs) in serum with altered expression in AIH relative to healthy control (HC) samples were identified using microarray analysis. To validate the microarray results, the expression levels of selected EV-miRNAs were determined.

RESULTS

Among the 2569 mature miRNAs evaluated in the microarray, EV-miR-557 discriminated patients with AIH from healthy controls (HCs). Validation by digital polymerase chain reaction indicated that serum EV-miR-557 levels were higher in patients with AIH (7.75 copies/μl) than in patients with non-alcoholic steatohepatitis (1.60 copies/μl; p < 0.001), patients with primary biliary cholangitis (2.16 copies/μl; p < 0.005), and HCs (1.86 copies/μl; p < 0.005). The area under the receiver operating characteristic curve values for the probability of AIH using serum EV-miR-557 between the AIH and non-alcoholic steatohepatitis, AIH and primary biliary cholangitis, and AIH and HC groups were 0.81, 0.78, and 0.79, respectively. In addition, serum EV-miR-557 levels >7.69 copies/μl were associated with a significantly higher risk of relapse in patients with AIH (7-year incidence rate: 11.1 vs. 35.4%, log-rank test, p < 0.05). Interestingly, gene expression analysis revealed that increased miR-557 expression following transient transfection of peripheral blood mononuclear cells with a miR-557 mimic resulted in enhanced expression of proinflammatory cytokine-related genes such as interleukin-6, interferon-γ, and tumor necrosis factor. Moreover, miR-557 induced significant tumor necrosis factor-α production (mean: 313.5 vs. 10 642.3 pg/ml, p < 0.05).

CONCLUSION

EV-miR-557 may play an important role as a potential biomarker of AIH and may be a promising therapeutic target for AIH.

Identification of microRNA-96-5p as a postoperative, prognostic microRNA predictor in nonviral hepatocellular carcinoma

AIM

The microRNA (miR) clusters miR-183/96/182 and miR-217/216a/216b are significantly upregulated in nonviral hepatocellular carcinoma (NBNC-HCC). Here, we investigate the impact of each member of these clusters on the clinical outcome of NBNC-HCC and analyze the antitumor effects of miR-96-5p.

METHODS

The association between recurrence-free survival of 111 NBNC-HCC patients and the levels of miR-183-5p, miR-96-5p, miR-182-5p, miR-217-5p, miR-216a-5p, and miR-216b-5p in tumor and adjacent tissues was investigated. The impact of miR-96-5p on apoptosis and invasion of a hepatoma cell line, HepG2, was investigated by cell counting, Transwell assay, and flow cytometry, respectively.

RESULTS

MicroRNA-183-5p, miR-96-5p, miR-182-5p, miR-217-5p, and miR-216b-5p were significantly upregulated in tumor tissues compared to the adjacent tissues (p = 0.0005, p = 0.0030, p = 0.0002, p = 0.0011, and p = 0.0288, respectively). By multivariate Cox regression analysis, high tumor/adjacent ratios of miR-182-5p (p = 0.007) and miR-217-5p (p = 0.008) were associated with poor recurrence-free survival. In contrast, a low tumor/adjacent ratio of miR-96-5p (p < 0.001) was associated with poor recurrence-free survival. It suggested that further upregulation of miR-96-5p in tumors might have an inhibitory effect on recurrence. Transfection of miR-96-5p mimic significantly induced apoptosis of HepG2 cells, in association with downregulation of Nucleophosmin 1 (NPM1) and a decrease of phosphorylated AKT protein. Interestingly, simultaneous knockdown of the NPM1 and AKT genes induced apoptosis. MicroRNA-96-5p also suppressed proliferation and invasion, which inhibited epithelial-to-mesenchymal transition of HCC cells.

CONCLUSION

MicroRNA-96-5p as a tumor suppressor would be valuable to stratify NBNC-HCC patients at high risk of recurrence.

A dual immune signature of CD8+ T cells and MMP9 improves the survival of patients with hepatocellular carcinoma

The 5-year survival of hepatocellular carcinoma (HCC) is difficult due to the high recurrence rate and metastasis. Tumor infiltrating immune cells (TICs) and immune-related genes (IRGs) bring hope to improve survival and treatment of HCC patients. However, there are problems in predicting immune signatures and identifying novel therapeutic targets. In the study, the CIBERSORT algorithm was used to evaluate 22 immune cell infiltration patterns in gene expression omnibus (GEO) and the cancer genome atlas (TCGA) data. Eight immune cells were found to have significant infiltration differences between the tumor and normal groups. The CD8+ T cells immune signature was constructed by least absolute shrinkage and selection operator (LASSO) algorithm. The high infiltration level of CD8+ T cells could significantly improve survival of patients. The weighted gene co-expression network analysis (WGCNA) algorithm identified MMP9 was closely related to the overall survival of HCC patients. K-M survival and tROC analysis confirmed that MMP9 had an excellent prognostic prediction. Cox regression showed that a dual immune signature of CD8+ T cells and MMP9 was independent survival factor in HCC. Therefore, a dual prognostic immune signature could improve the survival of patient and may provide a new strategy for the immunotherapy of HCC.

Systematic Construction and Validation of an RNA-Binding Protein-Associated Model for Prognosis Prediction in Hepatocellular Carcinoma

BACKGROUND

Evidence from prevailing studies show that hepatocellular carcinoma (HCC) is among the top cancers with high mortality globally. Gene regulation at post-transcriptional level orchestrated by RNA-binding proteins (RBPs) is an important mechanism that modifies various biological behaviors of HCC. Currently, it is not fully understood how RBPs affects the prognosis of HCC. In this study, we aimed to construct and validate an RBP-related model to predict the prognosis of HCC patients.

METHODS

Differently expressed RBPs were identified in HCC patients based on the GSE54236 dataset from the Gene Expression Omnibus (GEO) database. Integrative bioinformatics analyses were performed to select hub genes. Gene expression patterns were validated in The Cancer Genome Atlas (TCGA) database, after which univariate and multivariate Cox regression analyses, as well as Kaplan-Meier analysis were performed to develop a prognostic model. Then, the performance of the prognostic model was assessed using receiver operating characteristic (ROC) curves and clinicopathological correlation analysis. Moreover, data from the International Cancer Genome Consortium (ICGC) database were used for external validation. Finally, a nomogram combining clinicopathological parameters and prognostic model was established for the individual prediction of survival probability.

RESULTS

The prognostic risk model was finally constructed based on two RBPs (BOP1 and EZH2), facilitating risk-stratification of HCC patients. Survival was markedly higher in the low-risk group relative to the high-risk group. Moreover, higher risk score was associated with advanced pathological grade and late clinical stage. Besides, the risk score was found to be an independent prognosis factor based on multivariate analysis. Nomogram including the risk score and clinical stage proved to perform better in predicting patient prognosis.

CONCLUSIONS

The RBP-related prognostic model established in this study may function as a prognostic indicator for HCC, which could provide evidence for clinical decision making.

Construction of an 11-microRNA-based signature and a prognostic nomogram to predict the overall survival of head and neck squamous cell carcinoma patients

Background

Head and neck squamous cell carcinoma (HNSCC) is a fatal malignancy owing to the lack of effective tools to predict overall survival (OS). MicroRNAs (miRNAs) play an important role in HNSCC occurrence, development, invasion and metastasis, significantly affecting the OS of patients. Thus, the construction of miRNA-based risk signatures and nomograms is desirable to predict the OS of patients with HNSCC. Accordingly, in the present study, miRNA sequencing data of 71 HNSCC and 13 normal samples downloaded from The Cancer Genome Atlas (TCGA) were screened to identify differentially expressed miRNAs (DEMs) between HNSCC patients and normal controls. Based on the exclusion criteria, the clinical information and miRNA sequencing data of 67 HNSCC samples were selected and used to establish a miRNA-based signature and a prognostic nomogram. Forty-three HNSCC samples were assigned to an internal validation cohort for verifying the credibility and accuracy of the primary cohort. Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) analyses were performed to explore the functions of 11 miRNA target genes.

Results

In total, 11 DEMs were successfully identified. An 11-miRNA risk signature and a prognostic nomogram were constructed based on the expression levels of these 11 DEMs and clinical information. The signature and nomogram were further validated by calculating the C-index, area under the curve (AUC) in receiver-operating characteristic curve analysis, and calibration curves, which revealed their promising performance. The results of the internal validation cohort shown the reliable predictive accuracy both of the miRNA-based signature and the prognostic nomogram. GO and KEGG analyses revealed that a mass of signal pathways participated in HNSCC proliferation and metastasis.

Conclusion

Overall, we constructed an 11-miRNA-based signature and a prognostic nomogram with excellent accuracy for predicting the OS of patients with HNSCC.

Inhibitory Effect of a Human MicroRNA, miR-6133-5p, on the Fibrotic Activity of Hepatic Stellate Cells in Culture

BACKGROUND

We recently identified 39 human microRNAs, which effectively suppress hepatitis B virus (HBV) replication in hepatocytes. Chronic HBV infection often results in active, hepatitis-related liver fibrosis; hence, we assessed whether any of these microRNAs have anti-fibrotic potential and predicted that miR-6133-5p may target several fibrosis-related genes.

METHODS

The hepatic stellate cell line LX-2 was transfected with an miR-6133-5p mimic and subsequently treated with Transforming growth factor (TGF)-β. The mRNA and protein products of the COL1A1 gene, encoding collagen, and the ACTA2 gene, an activation marker of hepatic stellate cells, were quantified.

RESULTS

The expression of COL1A1 and ACTA2 was markedly reduced in LX-2 cells treated with miR-6133-5p. Interestingly, phosphorylation of c-Jun N-terminal kinase (JNK) was also significantly decreased by miR-6133-5p treatment. The expression of several predicted target genes of miR-6133-5p, including TGFBR2 (which encodes Transforming Growth Factor Beta Receptor 2) and FGFR1 (which encodes Fibroblast Growth Factor Receptor 1), was also reduced in miR-6133-5p-treated cells. The knockdown of TGFBR2 by the corresponding small interfering RNA greatly suppressed the expression of COL1A1 and ACTA2. Treatment with the JNK inhibitor, SP600125, also suppressed COL1A1 and ACTA2 expression, indicating that TGFBR2 and JNK mediate the anti-fibrotic effect of miR-6133-5p. The downregulation of FGFR1 may result in a decrease of phosphorylated Akt, ERK (extracellular signal-regulated kinase), and JNK.

CONCLUSION

miR-6133-5p has a strong anti-fibrotic effect, mediated by inactivation of TGFBR2, Akt, and JNK.