Pseudogene PLGLA exerts anti-tumor effects on hepatocellular carcinoma through modulating miR-324-3p/GLYATL1 axis

Identification and validation a novel kinase-related gene signature for predicting prognosis and responsiveness to immunotherapy in hepatocellular carcinoma

Liver cancer research highlights the kinome's critical role in disease initiation and progression. However, comprehensive data analysis on the kinome's impact on hepatocellular carcinoma (HCC) prognosis is limited. We used the TCGA-LIHC mRNA expression profiles, analyzing them with various R packages. Key methods included univariate Cox regression for prognostic gene identification, consensus clustering for subtype classification, Gene Set Enrichment Analysis (GSEA), and immune landscape evaluation. A prognostic model was developed using LASSO Cox regression, and chemotherapy drug sensitivity was assessed using the pRRophetic package. We identified 45 kinases-related differentially expressed genes (DEGs), with 27 linked to HCC prognosis. Cluster analysis divided these genes into two subtypes, with distinct prognoses. We discovered 157 DEGs between kinase-related subtypes, 120 of which were prognostically relevant. A kinase-related gene signature (KRS) was developed for prognostic prediction. The high-KRS group showed poorer survival in TCGA-LIHC and validation cohorts, with notable differences in immune cell infiltration and checkpoint gene expression. This group also showed varying sensitivity to common drugs and anti-PD-L1 treatment. In contrast, the low-KRS group might respond better to anti-PD-1 immunotherapy. Our study introduces a kinase-related gene signature as a novel tool for predicting HCC prognosis. This signature aids in tailoring personalized treatment strategies, potentially improving clinical outcomes in HCC patients.

Exploring non-coding RNA expression profiles of AKR1B10P1, RP11-465B22.3, WASH8P, and NPM1P25 as a predictive model for hepatocellular carcinoma patient survival

The primary aim of the study was to analyze novel long non-coding RNAs (lncRNAs) in hepatocellular carcinoma (HCC) to assess their roles as potential oncogenes and tumor suppressors and to develop a survival prediction model based on their expression levels. Data from The Cancer Genome Atlas, GSE135631, and GSE214846, were utilized to evaluate changes in lncRNA expression in HCC and their associations with patient prognosis. A risk model was created based on lncRNA expression to predict patient mortality. The co-expression network was employed to identify associated pathways, and the results were subsequently validated using the RT-qPCR method. The findings indicated that 14 lncRNAs were down-regulated in HCC, and their increased expression was associated with a favorable prognosis. Additionally, eight lncRNAs were overexpressed and correlated with poorer patient outcomes. The multivariate Cox regression analysis demonstrated that overexpression of AKR1B10P1, RP11-465B22.3, WASH8P, and the downregulation of NPM1P25 could independently predict patient survival, irrespective of clinical variables. The risk score model based on these lncRNAs effectively stratified patients by their mortality risk. Furthermore, the co-expression network analysis revealed that the identified lncRNAs might be involved in various pathways, including fatty acid metabolism, mTOR signaling, glycolysis, angiogenesis, Wnt-β-catenin pathway, and DNA repair. RT-qPCR results validated the significant increase in the expression level of WASH8P in cancer specimens compared to normal tissues. Our results unveiled that changes in the expression levels of AKR1B10P1, RP11-465B22.3, WASH8P, and NPM1P25 were significantly and independently associated with prognosis. Moreover, the patient mortality risk model constructed using these four lncRNAs exhibited a robust capacity to accurately predict patients' survival rates.

Downregulation of GLYAT correlates with tumour progression and poor prognosis in hepatocellular carcinoma

Glycine N-acyltransferase (GLYAT), known to influence glycine metabolism, has been implicated in the progression of various malignant tumours. However, its clinical relevance in hepatocellular carcinoma (HCC) remains unexplored. Here, GLYAT expression levels in HCC tissues were significantly reduced compared to normal liver tissues. Similarly, GLYAT expression levels in Huh 7, HepG2, PLC and SK-HEP1 were lower than those in LO2. Receiver operating characteristic curve analysis demonstrated that GLYAT exhibited good diagnostic performance for HCC. Kaplan-Meier analyses suggested that decreased GLYAT expression was correlated with poorer progress in HCC. Low GLYAT expression was significantly associated with gender and histologic grade. Multivariate Cox regression analysis identified low GLYAT expression and T stage as independent prognostic factors. Nomograms based on GLYAT mRNA expression and T stage showed good concordance with actual survival rates at 1, 2, 3 and 5 years. Moreover, GLYAT downregulation in the Huh 7 cell line enhanced cell proliferation, invasion and migration abilities, while GLYAT overexpression in the HepG2 cell line inhibited these abilities. HCC patients with low GLYAT expression exhibited a predisposition to immune escape and poor response to immunotherapy. This research revealed that GLYAT holds promise as both a prognostic biomarker and a potential therapeutic target in HCC.

miRNA Expression and HCC Occurrence in HCV Cirrhotic Patients Treated with Direct Acting Antivirals

Background: The risk of hepatocarcinoma in HCV cirrhotic patient responders after treatment with DAAs decrease, but HCC still occurs. A correlation between specific miRNAs and the development of hepatocarcinoma have been highlighted. Aim: To investigate miRNA expression in HCV-infected cirrhotic patients treated with DAAs, regarding whether or not they developed HCC at follow-up. Methods: A total of 73 outpatients with HCV-related cirrhosis treated with DAAs were enrolled, 28 of which had HCC. Samples were collected at the start and at the end of treatment. In the screening phase, 172 miRNAs were analyzed at baseline. Differentially expressed miRNAs were validated in the entire cohort. Results: In the validation phase, at baseline and in patients treated for 12 weeks, miR-28-5p was confirmed to be more highly expressed in the HCC group compared to the non-HCC group. In all of the patients treated for 12 weeks, at end of the treatment we found a significant downregulation in miR-132-3p, miR-133b-3p, miR-221-3p and miR-324-3p. In the HCC group, miR-28-5p was significantly downregulated after DAA therapy as well as in HCC patients treated for 24 weeks. Conclusion: In the HCC group, miR28-5p was differently expressed both at baseline and at the end of therapy with DAAs. This difference in expression should suggest its involvement in HCC development.

The role of competing endogenous RNA network in the development of hepatocellular carcinoma: potential therapeutic targets

The current situation of hepatocellular carcinoma (HCC) management is challenging due to its high incidence, mortality, recurrence and metastasis. Recent advances in gene genetic and expression regulation have unveiled the significant role of non-coding RNA (ncRNA) in various cancers. This led to the formulation of the competing endogenous RNA (ceRNA) hypothesis, which posits that both coding RNA and ncRNA, containing miRNA response elements (MRE), can share the same miRNA sequence. This results in a competitive network between ncRNAs, such as lncRNA and mRNA, allowing them to regulate each other. Extensive research has highlighted the crucial role of the ceRNA network in HCC development, impacting various cellular processes including proliferation, metastasis, cell death, angiogenesis, tumor microenvironment, organismal immunity, and chemotherapy resistance. Additionally, the ceRNA network, mediated by lncRNA or circRNA, offers potential in early diagnosis and prevention of HCC. Consequently, ceRNAs are emerging as therapeutic targets for HCC. The complexity of these gene networks aligns with the multi-target approach of traditional Chinese medicine (TCM), presenting a novel perspective for TCM in combating HCC. Research is beginning to show that TCM compounds and prescriptions can affect HCC progression through the ceRNA network, inhibiting proliferation and metastasis, and inducing apoptosis. Currently, the lncRNAs TUG1, NEAT1, and CCAT1, along with their associated ceRNA networks, are among the most promising ncRNAs for HCC research. However, this field is still in its infancy, necessitating advanced technology and extensive basic research to fully understand the ceRNA network mechanisms of TCM in HCC treatment.

A prognostic exosome-related long non-coding RNAs risk model related to the immune microenvironment and therapeutic responses for patients with liver hepatocellular carcinoma

Background

Liver hepatocellular carcinoma (LIHC) is the third largest cause of cancer mortality. Exosomes are vital regulators in the development of cancer. However, the mechanisms regarding the association of exosome-related long non-coding RNAs (lncRNAs) in LIHC are not clear.

Methods

LIHC RNA sequences and exosome-associated genes were collected according to The Cancer Genome Atlas (TCGA), Hepatocellular Carcinoma Cell DataBase (HCCDB) and ExoBCD databases, and exosome-related lncRNAs with prognostic differential expression were screened as candidate lncRNAs using Spearman's method and univariate Cox regression analysis. Candidate lncRNAs were then used to construct a prognostic model and mRNA-lncRNA co-expression network. Differentially expressed genes (DEGs) in low- and high-risk groups were identified and enrichment analysis was performed for up- and down-regulated DEGs, respectively. The expression of immune checkpoint-related genes, immune escape potential and microsatellite instability among different risk groups were further analyzed. Quantitative real-time polymerase chain reaction (qRT-PCR) and transwell assay were applied for detecting gene expression levels and invasion and migration ability.

Results

Based on 17 prognostical exosome-associated lncRNAs, four hub lncRNAs (BACE1_AS, DSTNP2, PLGLA, and SNHG3) were selected for constructing a prognostic model, which was demonstrated to be an independent prognostic variable for LIHC. High risk score was indicative of poorer overall survival, lower anti-tumor immune cells, higher genomic instability, higher immune escape potential, and less benefit for immunotherapy. The qRT-PCR test verified the expression level of the lncRNAs in LIHC cells, and the inhibitory effect of BACE1_AS on immune checkpoint genes levels. BACE1_AS silence also depressed the ability of migration and invasion of LIHC cells.

Conclusion

The Risk model constructed by exosome-associated lncRNAs could well predict immunotherapy response and prognostic outcomes for LIHC patients. We comprehensively reveal the clinical features of prognostical exosome-related lncRNAs and their potential ability to predict immunotherapeutic response of patients with LIHC and their prognosis.

Lnc-SNHG5 Promoted Hepatocellular Carcinoma Progression Through the RPS3-NFκB Pathway

Background

We planned to explore the underlying mechanism and clinical significance of lnc-SNHG5 and RPS3 in hepatocellular carcinoma in this current study.

Methods

The expression of Lnc-SNHG5 and RPS3 in HCC tissues and several cell lines were affirmed, respectively, using UALCAN, TIMER, TCGA and RT-qPCR assay. Cell proliferation ability was detected by colony formation assay and CCK8 assay. Cell apoptosis was monitored by flow cytometry assay. Next, the RPS3 expression levels and the related proteins in NFκB pathway were examined using Western blot analysis. The role of lnc-SNHG5 and RPS3 in vivo was identified by subcutaneous tumor bearing experiment.

Results

Lnc-SNHG5 was significantly increased in hepatocellular carcinoma tissues and in hepatocellular carcinoma cells. Further investigation showed that up-regulated lnc-SNHG5 promoted cell viability and cell proliferation ability of SMMC-7721 cells by regulating the cell apoptosis, while down-regulation of lnc-SNHG5 revealed opposite results in QGY-7703 cells. In terms of mechanism, we found that lnc-SNHG5 interacted with RPS3. Lnc-SNHG5 regulated the NFκB pathway through RPS3 in vitro and in vivo.

Conclusion

This study suggested that lnc-SNHG5 expression was signally up-regulated in hepatocellular carcinoma, and lnc-SNHG5 promoted the malignant phenotypes in vitro and in vivo via directly regulating RPS3-NFκB pathway. Lnc-SNHG5 might be a target for molecular targeted therapy, a potential and novel diagnostic marker for HCC patients.

Identification of tumor immunophenotypes associated with immunotherapy response in bladder cancer

OBJECTIVES

This study aims to reveal immunophenotypes associated with immunotherapy response in bladder cancer, identify the signature genes of immune subtypes, and provide new molecular targets for improving immunotherapy response.

METHODS

Bladder cancer immunophenotypes were characterized in the bulk RNA sequencing dataset GSE32894 and Imvigor210, and gene expression signatures were established to identify the immunophenotypes. Expression of gene signatures were validated in single-cell RNA sequencing dataset GSE145140 and human proteins expression data source. Investigation of Immunotherapy Response was performed in IMvigor210 dataset. Prognosis of tumor immunophenotypes was further analyzed.

RESULTS

Inflamed and immune-excluded immunophenotypes were characterized based on the tumor immune cell scores. Risk score models that were established rely on RNA sequencing profiles and overall survival of bladder cancer cohorts. The inflamed tumors had lower risk scores, and the low-risk tumors were more likely to respond to atezolizumab, receiving complete response/partial response (CR/PR). Patients who responded to atezolizumab had higher SRRM4 and lower NPHS1 and TMEM72 expression than the non-responders. SRRM4 expression was a protective factor for bladder cancer prognosis, while the NPHS1 and TMEM72 showed the opposite pattern.

CONCLUSION

This study provided a novel classification method for tumor immunophenotypes. Bladder cancer immunophenotypes can predict the response to immune checkpoint blockade. The immunophenotypes can be identified by the expression of signature genes.

Establishing a prognostic model of chromatin modulators and identifying potential drug candidates in renal clear cell patients

BACKGROUND

Renal carcinoma is a common malignant tumor of the urinary system. Advanced renal carcinoma has a low 5-year survival rate and a poor prognosis. More and more studies have confirmed that chromatin regulators (CRs) can regulate the occurrence and development of cancer. This article investigates the functional and prognostic value of CRs in renal carcinoma patients.

METHODS

mRNA expression and clinical information were obtained from The Cancer Genome Atlas database. Univariate Cox regression analysis and LASSO regression analysis were used to select prognostic chromatin-regulated genes and use them to construct a risk model for predicting the prognosis of renal cancer. Differences in prognosis between high-risk and low-risk groups were compared using Kaplan-Meier analysis. In addition, we analyzed the relationship between chromatin regulators and tumor immune infiltration, and explored differences in drug sensitivity between risk groups.

RESULTS

We constructed a model consisting of 11 CRs to predict the prognosis of renal cancer patients. We not only successfully validated its feasibility, but also found that the 11 CR-based model was an independent prognostic factor. Functional analysis showed that CRs were mainly enriched in cancer development-related signalling pathways. We also found through the TIMER database that CR-based models were also associated with immune cell infiltration and immune checkpoints. At the same time, the genomics of drug sensitivity in cancer database was used to analyze the commonly used drugs of renal clear cell carcinoma patients. It was found that patients in the low-risk group were sensitive to medicines such as axitinib, pazopanib, sorafenib, and gemcitabine. In contrast, those in the high-risk group may be sensitive to sunitinib.

CONCLUSION

The chromatin regulator-related prognostic model we constructed can be used to assess the prognostic risk of patients with clear cell renal cell carcinoma. The results of this study can bring new ideas for targeted therapy of clear cell renal carcinoma, helping doctors to take corresponding measures in advance for patients with different risks.