Cellular senescence-related long noncoding ribonucleic acids: Predicting prognosis in hepatocellular carcinoma

BACKGROUND

Due to their inherent role in cell function, long non-coding ribonucleic acids (lncRNAs) mediate changes in the microenvironment, and thereby participate in the development of cellular senescence.

AIMS

This study aimed to identify cellular senescence-related lncRNAs that could predict the prognosis of liver cancer.

METHODS AND RESULTS

Gene expression and clinical data were downloaded from the UCSC Xena platform, ICGC, and TCGA databases. Cox regression and LASSO regression were used to establish a cellular senescence-related lncRNA model. ROC curves and Kaplan-Meier survival curves were then constructed to predict patient prognosis. Cox regression analysis and clinical characteristics were used to evaluate the capability of the model. Tumor mutational burden and tumor-infiltrating immune cell analyses were subsequently performed in the risk subgroups and the samples in the entire cohort were reclustered. Finally, potential small molecule immune-targeted drugs were identified based on the model. The cellular senescence-related prognostic model that was constructed based on AGAP11 and FAM182B. Along with the results of Cox regression and Lasso regression, the risk score was found to be an independent factor for predicting overall survival in cohorts. In the subgroup analysis, the prognosis of the low-risk group in each cohort was significantly higher than that of the high-risk group; the area under temporal ROC curves and clinical ROC curves were all greater than 0.65, respectively. C-index shows that the risk scores are greater than 0.6, showing the stability of the model. The high-risk group demonstrated lower tumor microenvironment and higher tumor mutational burden scores, further verifying the reliability of the model grouping results. Analysis of tumor-infiltrating immune cells indicated that CD8+ and γδ T cells were more abundant among patients in the low-risk group; cluster reorganization indicated that the two groups had different prognoses and proportions of immune cells. The p value of potential drugs predicted based on the expression of model lncRNAs were all less than .05, demonstrating the potential of model lncRNAs as therapeutic targets to some extent.

CONCLUSION

A prognostic model based on cellular senescence-associated lncRNAs was established and this may be used as a potential biomarker for the prognosis assessment of liver cancer patients.

Identification and Validation of a Novel Immune-Related lncRNA Signature for Bladder Cancer

Purpose

We aimed to construct an immune-related long noncoding ribonucleic acids (irlncRNA) signature to evaluate the prognosis of patients without specific expression level of these irlncRNA.

Methods

The raw transcriptome data were downloaded from The Cancer Genome Atlas (TCGA), irlncRNAs were filtered out using an online immune related gene database and coexpression analysis, differently expressed irlncRNA (DEirlncRNA) pairs were identified by univariate analysis. The areas under curve (AUC) were compared and the Akaike information criterion (AIC) values of receiver operating curve (ROC) was counted, the most optimal model was constructed to divide bladder cancer patients into high- and low-risk groups usingõ the cut-off point of ROC. Then, we evaluated them from multiple perspectives, such as survival time, clinic-pathological characteristics, immune-related cells infiltrating, chemotherapeutics efficacy and immune checkpoint inhibitors.

Results

14 DEirlncRNA pairs were included in this signature. Patients in high-risk groups demonstrated apparent shorter survival time, more aggressive clinic-pathological characteristics, different immune-related cells infiltrating status, lower chemotherapeutics efficacy.

Conclusion

The irlncRNA signature demonstrated a promising prediction value for bladder cancer patients and was important in guiding clinical treatment.

Long Noncoding Ribonucleic Acid SNHG18 Promotes Glioma Cell Motility via Disruption of α-Enolase Nucleocytoplasmic Transport

Glioma is a common malignancy with poor prognosis. Recent evidence suggests that the pathogenesis and progression of glioma involve long noncoding RNAs (lncRNAs). Previously, we showed that glioma cell radioresistance was enhanced by lncRNA SNHG18 in vitro and in vivo. In the present study, we showed that SNHG18 promoted the invasion and migration of glioma cells. SNHG18 was demonstrated to regulate the progression of epithelial-mesenchymal transition and cytoskeleton remodeling, thereby affecting cell motility. Furthermore, the promotion of invasion evoked by SNHG18 overexpression could be rescued by α-enolase (ENO1) deletion. Moreover, rather than altering ENO1 expression, SNHG18 suppressed its nucleocytoplasmic transport by directly combining with ENO1 in glioma cells. The results suggested that SNHG18 inhibited the nucleocytoplasmic transport of ENO1 to promote cell motility. The results reveal the mechanism by which this lncRNA affects tumorigenesis and metastasis, forming the basis for further research that will lead to novel strategies to treat glioma.

Beyond adiponectin and leptin: adipose tissue-derived mediators of inter-organ communication

The breakthrough discoveries of leptin and adiponectin more than two decades ago led to a widespread recognition of adipose tissue as an endocrine organ. Many more adipose tissue-secreted signaling mediators (adipokines) have been identified since then, and much has been learned about how adipose tissue communicates with other organs of the body to maintain systemic homeostasis. Beyond proteins, additional factors, such as lipids, metabolites, noncoding RNAs, and extracellular vesicles (EVs), released by adipose tissue participate in this process. Here, we review the diverse signaling mediators and mechanisms adipose tissue utilizes to relay information to other organs. We discuss recently identified adipokines (proteins, lipids, and metabolites) and briefly outline the contributions of noncoding RNAs and EVs to the ever-increasing complexities of adipose tissue inter-organ communication. We conclude by reflecting on central aspects of adipokine biology, namely, the contribution of distinct adipose tissue depots and cell types to adipokine secretion, the phenomenon of adipokine resistance, and the capacity of adipose tissue to act both as a source and sink of signaling mediators.