Integrated bioinformatic analysis of RNA binding proteins in hepatocellular carcinoma

Integration of single-cell RNA-seq and bulk RNA-seq to construct liver hepatocellular carcinoma stem cell signatures to explore their impact on patient prognosis and treatment

BACKGROUND

Liver hepatocellular carcinoma (LIHC) is a prevalent form of primary liver cancer. Research has demonstrated the contribution of tumor stem cells in facilitating tumor recurrence, metastasis, and treatment resistance. Despite this, there remains a lack of established cancer stem cells (CSCs)-associated genes signatures for effectively predicting the prognosis and guiding the treatment strategies for patients diagnosed with LIHC.

METHODS

The single-cell RNA sequencing (scRNA-seq) and bulk RNA transcriptome data were obtained based on public datasets and computerized firstly using CytoTRACE package and One Class Linear Regression (OCLR) algorithm to evaluate stemness level, respectively. Then, we explored the association of stemness indicators (CytoTRACE score and stemness index, mRNAsi) with survival outcomes and clinical characteristics by combining clinical information and survival analyses. Subsequently, weighted co-expression network analysis (WGCNA) and Cox were applied to assess mRNAsi-related genes in bulk LIHC data and construct a prognostic model for LIHC patients. Single-sample gene-set enrichment analysis (ssGSEA), Cell-type Identification By Estimating Relative Subsets Of RNA Transcripts (CIBERSORT) and Tumor Immune Estimation Resource (TIMER) analysis were employed for immune infiltration assessment. Finally, the potential immunotherapeutic response was predicted by the Tumor Immune Dysfunction and Exclusion (TIDE), and the tumor mutation burden (TMB). Additionally, pRRophetic package was applied to evaluate the sensitivity of high and low-risk groups to common chemotherapeutic drugs.

RESULTS

A total of four genes (including STIP1, H2AFZ, BRIX1, and TUBB) associated with stemness score (CytoTRACE score and mRNAsi) were identified and constructed a risk model that could predict prognosis in LIHC patients. It was observed that high stemness cells occurred predominantly in the late stages of LIHC and that poor overall survival in LIHC patients was also associated with high mRNAsi scores. In addition, pathway analysis confirmed the biological uniqueness of the two risk groups. Personalized treatment predictions suggest that patients with a low risk benefited more from immunotherapy, while those with a high risk group may be conducive to chemotherapeutic drugs.

CONCLUSION

The current study developed a novel prognostic risk signature with genes related to CSCs, which provides novel ideas for the diagnosis, prognosis and treatment of LIHC.

miR-460b-5p promotes proliferation and differentiation of chicken myoblasts and targets RBM19 gene

The meat production of broilers is crucial to economic benefits of broiler industries, while the slaughter performance of broilers is directly determined by skeletal muscle development. Hence, the broiler breeding for growth traits shows a great importance. As a kind of small noncoding RNA, microRNA (miRNA) can regulate the expression of multiple genes and perform a wide range of regulation in organisms. Currently, more and more studies have confirmed that miRNAs are closely associated with skeletal muscle development of chickens. Based on our previous miR-seq analysis (accession number: PRJNA668199), miR-460b-5p was screened as one of the key miRNAs probably involved in the growth regulation of chickens. However, the regulatory effect of miR-460b-5p on the development of chicken skeletal muscles is still unclear. Therefore, miR-460b-5p was further used for functional validation at the cellular level in this study. The expression pattern of miR-460b-5p was investigated in proliferation and differentiation stages of chicken primary myoblasts. It was showed that the expression level of miR-460b-5p gradually decreased from the proliferation stage (GM 50%) to the lowest at 24 h of differentiation. As differentiation proceeded, miR-460b-5p expression increased significantly, reaching the highest and stabilizing at 72 h and 96 h of differentiation. Through mRNA quantitative analysis of proliferation marker genes, CCK-8 and Edu assays, miR-460b-5p was found to significantly facilitate the transition of myoblasts from G1 to S phase and promote chicken myoblast proliferation. mRNA and protein quantitative analysis of differentiation marker genes, as well as the indirect immunofluorescence results of myotubes, revealed that miR-460b-5p significantly stimulated myotube development and promote chicken myoblast differentiation. In addition, the target relationship was validated for miR-460b-5p according to the dual-luciferase reporter assay and mRNA quantitative analysis, which indicates that miR-460b-5p was able to regulate RBM19 expression by specifically binding to the 3' UTR of RBM19. In summary, miR-460b-5p has positive regulatory effects on the proliferation and differentiation of chicken myoblasts, and RBM19 is a target gene of miR-460b-5p.

Overexpression of TMEM79 combined with SMG5 is related to prognosis, tumor immune infiltration and drug sensitivity in hepatocellular carcinoma

BACKGROUND

Hepatocellular carcinoma (HCC) is a primary liver malignancy that is now relatively common worldwide. TMEM79 has been reported to play diagnostic and prognostic markers in a variety of cancers and was found to be closely associated with immune infiltration. SMG5 is associated with immune cell infiltration in HCC. Multiple nonsense-mediated mRNA processes require the involvement of SMG5. TMEM79 and SMG5 complexes may be prognostic markers for prostate cancer. However, the relationship between TMEM79 expression in HCC and prognosis, its role and mechanism of action, and its relationship with SMG5 have not been studied. This article focuses on not only the prognostic role of TMEM79 and its biological significance, including immuno-infiltration, tumor mutations and drug sensitivity, but also the interaction with SMG5 in HCC.

METHODS

Differential expression analysis and the multiCox proportional hazards regression analyses of TMEM79 and SMG5 were performed by multiple databases. Then, use IHC to verify our results. Subsequently, we used R software to analyze the clinical phenotype of both: analysis of clinicopathological features, enrichment analysis, analysis of immune infiltration, analysis of immune checkpoints, analysis of drug sensitivity, and immunotherapy.

RESULTS

Both the database studies and the results of our research group showed that TMEM79 and SMG5 were differentially expressed in HCC and normal tissues. Validation of immunohistochemistry showed that differential expression of TMEM79 and SMG5, which influenced the prognosis of patients with HCC, could be an independent prognostic factor. Results of the TCGA database study showed that TMEM79 and SMG5 were correlated with immune infiltration, immune checkpoints, drug sensitivity, and immunotherapy. We typed TMEM79-related molecules in HCC according to R software. Two types of TMEM79 correlated with clinical features, survival of patients with HCC, and immune infiltration.

CONCLUSION

TMEM79 are highly expressed in HCC and play an important role in the prognosis of patients with HCC. TMEM79 and SMG5 are positively correlated and may both associated with immune infiltration, and closely linked to immune checkpoints, drug sensitivity, and immunotherapy in HCC.

Key protein identification by integrating protein complex information and multi-biological features

Identifying key proteins based on protein-protein interaction networks has emerged as a prominent area of research in bioinformatics. However, current methods exhibit certain limitations, such as the omission of subcellular localization information and the disregard for the impact of topological structure noise on the reliability of key protein identification. Moreover, the influence of proteins outside a complex but interacting with proteins inside the complex on complex participation tends to be overlooked. Addressing these shortcomings, this paper presents a novel method for key protein identification that integrates protein complex information with multiple biological features. This approach offers a comprehensive evaluation of protein importance by considering subcellular localization centrality, topological centrality weighted by gene ontology (GO) similarity and complex participation centrality. Experimental results, including traditional statistical metrics, jackknife methodology metric and key protein overlap or difference, demonstrate that the proposed method not only achieves higher accuracy in identifying key proteins compared to nine classical methods but also exhibits robustness across diverse protein-protein interaction networks.

Pan-Cancer Analysis of the Prognostic and Immunological Role of SMG5: A Biomarker for Cancers

INTRODUCTION

SMG5 is involved in tumor cell development and viewed as a potential target for immunotherapy. The purpose of this study was to systematically analyze the expression level, function, and prognostic value of SMG5 in pan-cancers.

METHODS

Differential expression of SMG5 in normal and tumor tissues was analyzed using The Cancer Genome Atlas (TCGA) and the Genotype-Tissue Expression Database (GTEx) data. Survival analysis was performed by Kaplan-Meier method and Cox risk regression. The relationship between SMG5 expression and lymphocyte abundance, tumor cell immune infiltration level, molecular and immune subtypes as well as immune checkpoints was analyzed by tumor-immune system interactions database (TISIDB), Tumor Immune Estimation Resource (TIMER), and Sangerbox databases. The correlation between SMG5 and immune scores was studied using the Estimation of Stromal and Immune Cells in Malignant Tumours using Expression (ESTIMATE) data algorithm. Further, drug sensitivity analysis of SMG5 with low-grade glioma (LGG) was conducted using the CellMiner database.

RESULTS

SMG5 was highly expressed in 23 tumors and only had a significant impact on the prognosis of patients with LGG only. In addition, in tumor microenvironment and tumor immune analysis, we found that the level of immune infiltration, tumor mutational load, microsatellite instability, and immune checkpoints of LGG were significantly correlated with SMG5 expression. Furthermore, SMG5 was significantly associated with immune scores, stromal scores, and sensitivity of some drugs in LGG.

CONCLUSION

SMG5 is differentially expressed in several cancers and is significantly associated with prognosis, immune microenvironment, and immune checkpoints in LGG patients. Therefore, SMG5 could be a potential pan-cancer biomarker and an immunotherapeutic target for LGG.

Diverse targets of SMN2-directed splicing-modulating small molecule therapeutics for spinal muscular atrophy

Designing an RNA-interacting molecule that displays high therapeutic efficacy while retaining specificity within a broad concentration range remains a challenging task. Risdiplam is an FDA-approved small molecule for the treatment of spinal muscular atrophy (SMA), the leading genetic cause of infant mortality. Branaplam is another small molecule which has undergone clinical trials. The therapeutic merit of both compounds is based on their ability to restore body-wide inclusion of Survival Motor Neuron 2 (SMN2) exon 7 upon oral administration. Here we compare the transcriptome-wide off-target effects of these compounds in SMA patient cells. We captured concentration-dependent compound-specific changes, including aberrant expression of genes associated with DNA replication, cell cycle, RNA metabolism, cell signaling and metabolic pathways. Both compounds triggered massive perturbations of splicing events, inducing off-target exon inclusion, exon skipping, intron retention, intron removal and alternative splice site usage. Our results of minigenes expressed in HeLa cells provide mechanistic insights into how these molecules targeted towards a single gene produce different off-target effects. We show the advantages of combined treatments with low doses of risdiplam and branaplam. Our findings are instructive for devising better dosing regimens as well as for developing the next generation of small molecule therapeutics aimed at splicing modulation.

Spliceosomal profiling identifies EIF4A3 as a novel oncogene in hepatocellular carcinoma acting through the modulation of FGFR4 splicing

INTRODUCTION

Altered splicing landscape is an emerging cancer hallmark; however, the dysregulation and implication of the cellular machinery controlling this process (spliceosome components and splicing factors) in hepatocellular carcinoma (HCC) is poorly known. This study aimed to comprehensively characterize the spliceosomal profile and explore its role in HCC.

METHODS

Expression levels of 70 selected spliceosome components and splicing factors and clinical implications were evaluated in two retrospective and six in silico HCC cohorts. Functional, molecular and mechanistic studies were implemented in three cell lines (HepG2, Hep3B and SNU-387) and preclinical Hep3B-induced xenograft tumours.

RESULTS

Spliceosomal dysregulations were consistently found in retrospective and in silico cohorts. EIF4A3, RBM3, ESRP2 and SRPK1 were the most dysregulated spliceosome elements in HCC. EIF4A3 expression was associated with decreased survival and greater recurrence. Plasma EIF4A3 levels were significantly elevated in HCC patients. In vitro EIF4A3-silencing (or pharmacological inhibition) resulted in reduced aggressiveness, and hindered xenograft-tumours growth in vivo, whereas EIF4A3 overexpression increased tumour aggressiveness. EIF4A3-silencing altered the expression and splicing of key HCC-related genes, specially FGFR4. EIF4A3-silencing blocked the cellular response to the natural ligand of FGFR4, FGF19. Functional consequences of EIF4A3-silencing were mediated by FGFR4 splicing as the restoration of non-spliced FGFR4 full-length version blunted these effects, and FGFR4 inhibition did not exert further effects in EIF4A3-silenced cells.

CONCLUSIONS

Splicing machinery is strongly dysregulated in HCC, providing a source of new diagnostic, prognostic and therapeutic options in HCC. EIF4A3 is consistently elevated in HCC patients and associated with tumour aggressiveness and mortality, through the modulation of FGFR4 splicing.

SF3B4 Depletion Retards the Growth of A549 Non-Small Cell Lung Cancer Cells via UBE4B-Mediated Regulation of p53/p21 and p27 Expression

Splicing factor B subunit 4 (SF3B4), a component of the U2-pre-mRNA spliceosomal complex, contributes to tumorigenesis in several types of tumors. However, the oncogenic potential of SF3B4 in lung cancer has not yet been determined. The in vivo expression profiles of SF3B4 in non-small cell lung cancer (NSCLC) from publicly available data revealed a significant increase in SF3B4 expression in tumor tissues compared to that in normal tissues. The impact of SF3B4 deletion on the growth of NSCLC cells was determined using a siRNA strategy in A549 lung adenocarcinoma cells. SF3B4 silencing resulted in marked retardation of the A549 cell proliferation, accompanied by the accumulation of cells at the G0/G1 phase and increased expression of p27, p21, and p53. Double knockdown of SF3B4 and p53 resulted in the restoration of p21 expression and partial recovery of cell proliferation, indicating that the p53/p21 axis is involved, at least in part, in the SF3B4-mediated regulation of A549 cell proliferation. We also provided ubiquitination factor E4B (UBE4B) is essential for p53 accumulation after SF3B4 depletion based on followings. First, co-immunoprecipitation showed that SF3B4 interacts with UBE4B. Furthermore, UBE4B levels were decreased by SF3B4 depletion. UBE4B depletion, in turn, reproduced the outcome of SF3B4 depletion, including reduction of polyubiquitinated p53 levels, subsequent induction of p53/p21 and p27, and proliferation retardation. Collectively, our findings indicate the important role of SF3B4 in the regulation of A549 cell proliferation through the UBE4B/p53/p21 axis and p27, implicating the therapeutic strategies for NSCLC targeting SF3B4 and UBE4B.

The Systematic Analyses of RING Finger Gene Signature for Predicting the Prognosis of Patients with Hepatocellular Carcinoma

RING finger (RNF) proteins are frequently dysregulated in human malignancies and are tightly associated with tumorigenesis. However, the expression profiles of RNF genes in hepatocellular carcinoma (HCC) and their relations with prognosis remain undetermined. Here, we aimed at constructing a prognostic model according to RNF genes for forecasting the outcomes of HCC patients using the data from The Cancer Genome Atlas (TCGA) program. We collected HCC datasets to validate the values of our model in predicting prognosis of HCC patients from International Cancer Genome Consortium (ICGC) platform. Then, functional experiments were carried out to explore the roles of the representative RNF in HCC progression. A total of 107 differentially expressed RNFs were obtained between TCGA-HCC tumor and normal tissues. After comprehensive evaluation, a prognostic signature composed of 11 RNFs (RNF220, RNF25, TRIM25, BMI1, RNF216P1, RNF115, RNF2, TRAIP, RNF157, RNF145, and RNF19B) was constructed based on TCGA cohort. Then, the Kaplan-Meier (KM) curves and the receiver operating characteristic curve (ROC) were employed to evaluate predictive power of the prognostic model in testing cohort (TCGA) and validation cohort (ICGC). The KM and ROC curves illustrated the good predictive power in testing and validation cohort. The areas under the ROC curve are 0.77 and 0.76 in these two cohorts, respectively. Among the prognostic signature genes, BMI1 was selected as a representative for functional study. We found that BMI1 protein level was significantly upregulated in HCC tissues. Moreover, the inhibitor of BMI1, PTC-209, displayed an excellent anti-HCC effect in vitro. Enrichment analysis of BMI1 downstream targets showed that BMI1 might be involved in tumor immunotherapy. Together, our overall analyses revealed that the 11-RNFs prognostic signature might provide us latent chances for evaluating HCC prognosis and developing novel HCC therapy.

Computational Characterizing Necroptosis Reveals Implications for Immune Infiltration and Immunotherapy of Hepatocellular Carcinoma

Necroptosis is a programmed form of necrotic cell death in regulating cancer ontogenesis, progression, and tumor microenvironment (TME) and could drive tumor-infiltrating cells to release pro-inflammatory cytokines, incurring strong immune responses. Nowadays, there are few identified biomarkers applied in clinical immunotherapy, and it is increasingly recognized that high levels of tumor necroptosis could enhance the response to immunotherapy. However, comprehensive characterization of necroptosis associated with TME and immunotherapy in Hepatocellular carcinoma (HCC) remains unexplored. Here, we computationally characterized necroptosis landscape in HCC samples from TCGA and ICGA cohorts and stratified them into two necroptosis clusters (A or B) with significantly different characteristics in clinical prognosis, immune cell function, and TME-landscapes. Additionally, to further evaluate the necroptosis levels of each sample, we established a novel necroptosis-related gene score (NRGscore). We further investigated the TME, tumor mutational burden (TMB), clinical response to immunotherapy, and chemotherapeutic drug sensitivity of HCC subgroups stratified by the necroptosis landscapes. The NRGscore is robust and highly predictive of HCC clinical outcomes. Further analysis indicated that the high NRGscore group resembles the immune-inflamed phenotype while the low score group is analogous to the immune-exclusion or metabolism phenotype. Additionally, the high NRGscore group is more sensitive to immune checkpoint blockade-based immunotherapy, which was further validated using an external HCC cohort, metastatic melanoma cohort, and advanced urothelial cancer cohort. Besides, the NRGscore was demonstrated as a potential biomarker for chemotherapy, wherein the high NRGscore patients with more tumor stem cell composition could be more sensitive to Cisplatin, Doxorubicin, Paclitaxel-based chemotherapy, and Sorafenib therapy. Collectively, a comprehensive characterization of the necroptosis in HCC suggested its implications for predicting immune infiltration and response to immunotherapy of HCC, providing promising strategies for treatment.

A Prognosis Marker Dynein Cytoplasmic 1 Heavy Chain 1 Correlates with EMT and Immune Signature in Liver Hepatocellular Carcinoma by Bioinformatics and Experimental Analysis

Background

Liver hepatocellular carcinoma (LIHC) has had a continuous increase in incidence and mortality rates over the last 40 years. Dynein Cytoplasmic 1 Heavy Chain 1 (DYNC1H1) is a protein coding gene which encodes the cytoplasmic dynein heavy chain family. This is the first investigation into the expression of DYNC1H1 and its mechanisms of action in LIHC patients.

Methods

Based on the DYNC1H1 expression data from the TCGA database, we performed the DYNC1H1 expression, clinicopathological data, gene enrichment, and immune infiltration analysis. TIMER and CIBERSORT were used to assess immune responses of DYNC1H1 in LIHC. GEPIA, K-M survival analysis, and immunohistochemical staining pictures from the THPA were used to validate the results. In order to evaluate the diagnostic value of DYNC1H1, GEO datasets were analyzed by using ROC analysis. And quantitative real-time polymerase chain reaction was also carried out to evaluate the expression of DYNC1H1.

Results

DYNC1H1 expression levels were associated with T classification, pathologic stage, histologic grade, and serum AFP levels. DYNC1H1 is an independent factor for a poor prognosis in patients with LIHC. Further study showed that high expression of DYNC1H1 was enriched in epithelial–mesenchymal transition (EMT) and the TGF β signaling pathway by GSEA analysis enrichment, indicating that DYNC1H1 might play a key role in the progression of CRC through EMT and immune response, which also had been validated by the experimental assays.

Conclusions

DYNC1H1 will provide a novel and important perspective for the mechanisms of LIHC by regulating EMT. This gene will be able to act as an efficacious tool for the early diagnosis and effective intervention of LIHC.

The role of RNA binding proteins in hepatocellular carcinoma

Hepatocellular carcinoma (HCC) is one of the leading causes of overall cancer deaths worldwide with limited therapeutic options. Due to the heterogeneity of HCC pathogenesis, the molecular mechanisms underlying HCC development are not fully understood. Emerging evidence indicates that RNA-binding proteins (RBPs) play a vital role throughout hepatocarcinogenesis. Thus, a deeper understanding of how RBPs contribute to HCC progression will provide new tools for early diagnosis and prognosis of this devastating disease. In this review, we summarize the tumor suppressive and oncogenic roles of RBPs and their roles in hepatocarcinogenesis. The diagnostic and therapeutic potential of RBPs in HCC, including their limitations, are also discussed.

Advances in Multi-Omics Applications in HBV-Associated Hepatocellular Carcinoma

Hepatitis B virus (HBV) specifically infects liver cells, leading to progressive liver cirrhosis and significantly increasing the risk of hepatocellular carcinoma (HCC). The maturity of sequencing technology, improvement in bioinformatics data analysis and progress of omics technologies had improved research efficiency. The occurrence and progression of HCC are affected by multisystem and multilevel pathological changes. With the application of single-omics technologies, including genomics, transcriptomics, metabolomics and proteomics in tissue and body fluid samples, and even the novel development of multi-omics analysis on a single-cell platform, HBV-associated HCC changes can be better analyzed. The review summarizes the application of single omics and combined analysis of multi-omics data in HBV-associated HCC and proposes the importance of multi-omics analysis in the type of HCC, which provide the possibility for the precise diagnosis and therapy of HBV-associated HCC.

Upregulation of GTPBP4 Promotes the Proliferation of Liver Cancer Cells

RESULTS

The GTPBP4 has upregulated expression in liver cancer patients (P < 0.01), but there was no difference in its expression in patients with different clinicopathological stages. The expression of GTPBP4 increased with the increase of cancer metastasis in lymph nodes (P < 0.01). Liver cancer patients with upregulated expression of GTPBP4 showed a shorter overall survival rate (P=0.02). GTPBP4 is closely related to genes such as NIFK, WDR12, and RPF2, and these genes are involved in life processes such as GTP binding and rRNA processing. The upregulated expression of GTPBP4 promotes the proliferation of liver cancer cells and promotes the growth of tumors in mice, while the downregulated expression of GTPBP4 inhibits the proliferation of liver cancer cells and inhibits the growth of tumors in mice.

CONCLUSION

The expression of GTPBP4 is upregulated in liver cancer patients and affects the overall survival rate of patients. The upregulated expression of GTPBP4 promotes the proliferation of liver cancer cells and the growth of tumors.

The Emerging Factors and Treatment Options for NAFLD-Related Hepatocellular Carcinoma

Simple Summary

Nonalcoholic fatty liver disease (NAFLD) is the most common chronic liver disease, and it is an increasing factor in the cause of hepatocellular carcinoma (HCC). The incidence of NAFLD has increased in recent decades, accompanied by an increase in the prevalence of other metabolic diseases, such as obesity and type 2 diabetes. However, current treatment options are limited. Both genetic factors and non-genetic factors impact the initiation and progression of NAFLD-related HCC. The early diagnosis of liver cancer predicts curative treatment and longer survival. Some key molecules play pivotal roles in the initiation and progression of NAFLD-related HCC, which can be targeted to impede HCC development. In this review, we summarize some key factors and important molecules in NAFLD-related HCC development, the latest progress in HCC diagnosis and treatment options, and some current clinical trials for NAFLD treatment.

Abstract

Hepatocellular carcinoma (HCC) is the most common type of primary liver cancer, followed by cholangiocarcinoma (CCA). HCC is the third most common cause of cancer death worldwide, and its incidence is rising, associated with an increased prevalence of obesity and nonalcoholic fatty liver disease (NAFLD). However, current treatment options are limited. Genetic factors and epigenetic factors, influenced by age and environment, significantly impact the initiation and progression of NAFLD-related HCC. In addition, both transcriptional factors and post-transcriptional modification are critically important for the development of HCC in the fatty liver under inflammatory and fibrotic conditions. The early diagnosis of liver cancer predicts curative treatment and longer survival. However, clinical HCC cases are commonly found in a very late stage due to the asymptomatic nature of the early stage of NAFLD-related HCC. The development of diagnostic methods and novel biomarkers, as well as the combined evaluation algorithm and artificial intelligence, support the early and precise diagnosis of NAFLD-related HCC, and timely monitoring during its progression. Treatment options for HCC and NAFLD-related HCC include immunotherapy, CAR T cell therapy, peptide treatment, bariatric surgery, anti-fibrotic treatment, and so on. Overall, the incidence of NAFLD-related HCC is increasing, and a better understanding of the underlying mechanism implicated in the progression of NAFLD-related HCC is essential for improving treatment and prognosis.