Hepatocellular carcinoma risk variant modulates lncRNA HLA-DQB1-AS1 expression via a long-range enhancer-promoter interaction

Functional SNPs in SYISL promoter significantly affect muscle fiber density and muscle traits in pigs

Our previous studies showed that SYISL is a negative regulator of muscle growth and regeneration in mice, pigs and humans. SYISL knockout resulted in an increase in the density of muscle fibers and muscle growth. However, it is unclear whether there are natural mutations in pig SYNPO2 intron sense-overlapping lncRNA (pSYISL) that affect the expression of pSYISL and muscle growth traits. In this study, three SNPs in exons and six SNPs within the promoter of pSYISL were identified. Association analysis showed that the two SNPs in exons are significantly associated with loin muscle area (p < 0.05); the six SNPs in the promoter that show complete linkage are significantly associated with live backfat thickness and live loin muscle area in American Large White pigs. Bioinformatics and luciferase reporter assays as well as in vitro binding experiments indicated that the mutation of SNP rs702045770 (g.539G>A) leads to the loss of YY1 binding to the promoter, thus affecting the expression level of pSYISL, and we found that Jiangshan Black pigs with genotype GG have a higher expression level of pSYISL than genotype AA individuals, but the muscle fiber density was significantly lower than in genotype AA individuals. Furthermore, the association analysis showed that the carcass backfat thickness of genotype GG of SNP rs702045770 was significantly higher than that of other genotypes in (Pietrain × Duroc) × (Landrace × Yorkshire) crossbred pigs (p < 0.05). The glycolytic potential of genotype GG was significantly higher than that of other genotypes (p < 0.05). These results provide novel insight into the identification of functional SNPs in non-coding genomic regions.

Noncoding RNA mutations in cancer

Cancer is driven by both germline and somatic genetic changes. Efforts have been devoted to characterizing essential genetic variations in cancer initiation and development. Most attention has been given to mutations in protein-coding genes and associated regulatory elements such as promoters and enhancers. The development of sequencing technologies and in silico and experimental methods has allowed further exploration of cancer predisposition variants and important somatic mutations in noncoding RNAs, mainly for long noncoding RNAs and microRNAs. Association studies including GWAS have revealed hereditary variations including SNPs and indels in lncRNA or miRNA genes and regulatory regions. These mutations altered RNA secondary structures, expression levels, and target recognition and then conferred cancer predisposition to carriers. Whole-exome/genome sequencing comparing cancer and normal tissues has revealed important somatic mutations in noncoding RNA genes. Mutation hotspots and somatic copy number alterations have been identified in various tumor-associated noncoding RNAs. Increasing focus and effort have been devoted to studying the noncoding region of the genome. The complex genetic network of cancer initiation is being unveiled. This article is categorized under: RNA in Disease and Development > RNA in Disease.

Long non-coding RNA-targeting therapeutics: discovery and development update

INTRODUCTION

lncRNAs are major players in regulatory networks orchestrating multiple cellular functions, such as 3D chromosomal interactions, epigenetic modifications, gene expression and others. Due to progress in the development of nucleic acid-based therapeutics, lncRNAs potentially represent easily accessible therapeutic targets.

AREAS COVERED

Currently, significant efforts are directed at studies that can tap the enormous therapeutic potential of lncRNAs. This review describes recent developments in this field, particularly focusing on clinical applications.

EXPERT OPINION

Extensive druggable target range of lncRNA combined with high specificity and accelerated development process of nucleic acid-based therapeutics open new prospects for treatment in areas of extreme unmet medical need, such as genetic diseases, aggressive cancers, protein deficiencies, and subsets of common diseases caused by known mutations. Although currently wide acceptance of lncRNA-targeting nucleic acid-based therapeutics is impeded by the need for parenteral or direct-to-CNS administration, development of less invasive techniques and orally available/BBB-penetrant nucleic acid-based therapeutics is showing early successes. Recently, mRNA-based COVID-19 vaccines have demonstrated clinical safety of all aspects of nucleic acid-based therapeutic technology, including multiple chemical modifications of nucleic acids and nanoparticle delivery. These trends position lncRNA-targeting drugs as significant players in the future of drug development, especially in the area of personalized medicine.

Pyroptosis-related lncRNA prognostic signatures for cutaneous melanoma and tumor microenvironment status

Aims: To explore whether the expression of pyroptosis-related lncRNAs makes a difference in the prognosis and antitumor immunity of cutaneous melanoma (CM) patients. Methods: A series of analyses were conducted to establish a prognostic risk model and validate its accuracy. Immune-related analyses were performed to further assess the associations among immune status, tumor microenvironment and the prognostic risk model. Results: Eight pyroptosis-related lncRNAs relevant to prognosis were ascertained and applied to establish the prognostic risk model. The low-risk group had a higher overall survival rate. Conclusion: The established prognostic risk model presents better prediction ability for the prognosis of CM patients and provides new possible therapeutic targets for CM.

SNP-Target Genes Interaction Perturbing the Cancer Risk in the Post-GWAS

Cancer ranks as the second leading cause of death worldwide, and, being a genetic disease, it is highly heritable. Over the past few decades, genome-wide association studies (GWAS) have identified many risk-associated loci harboring hundreds of single nucleotide polymorphisms (SNPs). Some of these cancer-associated SNPs have been revealed as causal, and the functional characterization of the mechanisms underlying the cancer risk association has been illuminated in some instances. In this review, based on the different positions of SNPs and their modes of action, we discuss the mechanisms underlying how SNPs regulate the expression of target genes to consequently affect tumorigenesis and the development of cancer.

Natural antisense transcripts as drug targets

The recent discovery of vast non-coding RNA-based regulatory networks that can be easily modulated by nucleic acid-based drugs has opened numerous new therapeutic possibilities. Long non-coding RNA, and natural antisense transcripts (NATs) in particular, play a significant role in networks that involve a wide variety of disease-relevant biological mechanisms such as transcription, splicing, translation, mRNA degradation and others. Currently, significant efforts are dedicated to harnessing these newly emerging NAT-mediated biological mechanisms for therapeutic purposes. This review will highlight the recent clinical and pre-clinical developments in this field and survey the advances in nucleic acid-based drug technologies that make these developments possible.

A hypoxia-related lncRNA model for prediction of head and neck squamous cell carcinoma prognosis

BACKGROUND

Head and neck squamous cell carcinoma (HNSCC) is one of the most common and highly heterogeneous malignancies worldwide. Increasing studies have proven that hypoxia and related long non-coding RNA (lncRNA) are involved in the occurrence and prognosis of HNSCC. The goal of this work is to construct a risk assessment model using hypoxia-related lncRNAs (hrlncRNAs) for HNSCC prognosis prediction and personalized treatment.

METHODS

Transcriptome expression matrix, clinical follow-up data, and somatic mutation data of HNSCC patients were obtained from The Cancer Genome Atlas (TCGA). We used co-expression analysis to identify hrlncRNAs, then screened for differentially expressed lncRNAs (DEhrlncRNAs), and paired these DEhrlncRNAs. The risk model was established through univariate, least absolute shrinkage and selection operator (LASSO), and stepwise multivariate Cox regression. Finally, we assessed the model from multiple perspectives of tumor mutation burden (TMB), tumor immune infiltration, chemotherapeutic sensitivity, immune checkpoint inhibitor (ICI), and functional enrichment.

RESULTS

The risk assessment model included 14 hrlncRNA pairs. The risk score was observed to be a reliable prognostic factor. The high-risk patients had an unfavorable prognosis and significant differences from the low-risk group in TMB and tumor immune infiltration. In the high-risk patients, the common immune checkpoints were down-regulated, including CTLA4 and PDCD1, and the sensibility to paclitaxel and docetaxel was higher. The functional enrichment analysis suggested that the low-risk group was accompanied by activated immune function.

CONCLUSIONS

The risk assessment model of 14-hrlncRNA-pairs demonstrated a promising prognostic prediction for HNSCC patients and can guide personalized clinical treatment.

HLA-DQB1-AS1 Promotes Cell Proliferation, Inhibits Apoptosis, and Binds with ZRANB2 Protein in Hepatocellular Carcinoma

Major histocompatibility complex, class II, DQ beta 1 antisense RNA 1 (HLA-DQB1-AS1) conferred the susceptibility to hepatocellular carcinoma. Sustaining cell growth and resisting apoptosis are two hallmarks of hepatocellular carcinoma. The present study explored the role of HLA-DQB1-AS1 in the proliferation and apoptosis of hepatocellular carcinoma cells and investigated its downstream pathway. Colony formation assay was performed to assess cell proliferation. Cell apoptosis was assessed with the TdT-mediated dUTP nick end labeling method. HLA-DQB1-AS1 deficiency exerts antiproliferative and proapoptotic effects on hepatocellular carcinoma cells. Moreover, based on bioinformatic analysis combined with the results of RNA immunoprecipitation assay, HLA-DQB1-AS1 was revealed to bind with zinc finger RANBP2-type containing 2 (ZRANB2) protein. ZRANB2 was upregulated in hepatocellular carcinoma at a clinical and cellular level. HLA-DQB1-AS1 caused no significant effects on ZRANB2 mRNA and protein expression. ZRANB2 knockdown suppressed cell proliferation and enhanced cell apoptosis of hepatocellular carcinoma. Moreover, ZRANB2 overexpression rescued the anticancer effect of silenced HLA-DQB1-AS1 in hepatocellular carcinoma cells. In conclusion, HLA-DQB1-AS1 promotes cell proliferation and inhibits apoptosis in hepatocellular carcinoma by the interaction with ZRANB2 protein.

A Novel Risk Model Based on Autophagy-Related LncRNAs Predicts Prognosis and Indicates Immune Infiltration Landscape of Patients With Cutaneous Melanoma

Cutaneous melanoma (CM) is a malignant tumor with a high incidence rate and poor prognosis. Autophagy plays an essential role in the development of CM; however, the role of autophagy-related long noncoding RNAs (lncRNAs) in this process remains unknown. Human autophagy-related genes were extracted from the Human Autophagy Gene Database and screened for autophagy-related lncRNAs using Pearson correlation. Multivariate Cox regression analysis was implemented to identify ten autophagy-related lncRNAs associated with prognosis, and a risk model was constructed. The Kaplan-Meier survival curve showed that the survival probability of the high-risk group was lower than that of the low-risk group. A novel predictive model was constructed to investigate the independent prognostic value of the risk model. The nomogram results showed that the risk score was an independent prognostic signature that distinguished it from other clinical characteristics. The immune infiltration landscape of the low-risk and high-risk groups was further investigated. The low-risk groups displayed higher immune, stromal, and ESTIMATE scores and lower tumor purity. The CIBERSORT and single sample gene set enrichment analysis (ssGSEA) algorithms indicated a notable gap in immune cells between the low- and high-risk groups. Ten autophagy-related lncRNAs were significantly correlated with immune cells. Finally, Gene Set Enrichment Analysis (GSEA) and Gene Set Variation Analysis (GSVA) results demonstrated that autophagy-related lncRNA-mediated and immune-related signaling pathways are crucial factors in regulating CM. Altogether, these data suggest that constructing a risk model based on ten autophagy-related lncRNAs can accurately predict prognosis and indicate the tumor microenvironment of patients with CM. Thus, our study provides a new perspective for the future clinical treatment of CM.