Long Noncoding RNA SNHG1 Regulates LMNB2 Expression by Sponging miR-326 and Promotes Cancer Growth in Hepatocellular Carcinoma

SNHG1: Redefining the Landscape of Hepatocellular Carcinoma through Long Noncoding RNAs

Hepatocellular carcinoma (HCC) represents a global health concern, ranking as the sixth most common malignancy worldwide and the third leading cause of cancer-related mortality. Despite advances in research, the diagnosis and prognosis of such malignancy remain challenging. Alpha-fetoprotein, the current serum biomarker used in the management of HCC, has limited sensitivity and specificity, making early detection and effective management more difficult. Thus, new management approaches in diagnosis and prognosis are needed to improve the outcome and survival of HCC patients. SNHG1 is a long noncoding RNA mainly expressed in the cell and cytoplasm of cells and is consistently upregulated in tissues and cell lines of HCC, where it acts as an important regulator of various processes: modulation of p53 activity, sponging of microRNAs with consequent upregulation of their target mRNAs, regulation of fatty acid, iron and glucose metabolism, and interaction with immune cells. The deregulation of these processes results in abnormal cell division, angiogenesis, and apoptosis, thus promoting various aspects of tumorigenesis, including proliferation, invasion, and migration of cells. Clinically, a higher expression of SNHG1 predicts poorer clinical outcomes by significantly correlating with bigger, less differentiated, and more aggressive tumors, more advanced disease stages, and lower overall survival in HCC patients. This article comprehensively summarizes the current understanding of the multifaceted roles of SNHG1 in the pathogenesis of HCC, while also highlighting its clinicopathological correlations, therefore concluding that it has potential as a biomarker in HCC diagnosis and prognosis.

Comprehensive analysis of LMNB2 in pan-cancer and identification of its biological role in sarcoma

BACKGROUNDS

Sarcoma (SARC) is a mesenchymal tumor which often responds poorly to systemic therapy. It is therefore important to look for possible biological markers that could tell the prognosis and the progression of SARC.

METHODS

A combined evaluation of the Cancer Genome Atlas (TCGA) and genotypic tissue expression (GTEx) portal was used to analyzeLMNB2 expression level in different types of cancer. Kaplan-Meier survival analysis was performed to examine LMNB2 predictive value in over-all survival rate and disease-free survival rate. The association among LMNB2 expression level and immune cell infiltration, microsatellite instability (MSI) and tumor mutational burden (TMB) were analyzed. GO and KEGG enrichment analysis were performed to predicate LMNB2 biological functions. The biological function of LMNB2 was estimated by MTT and flow cytometry assay. Additionally, western blot assay was used to examine protein expression levels.

RESULTS

Increased LMNB2 expression was related with worsened cancer type-dependent survival. A relation between LMNB2 expression levels and immune cell infiltration was found. GO and KEGG enrichment analysis indicated that LMNB2 was involved in a series of pathways. Biology function assays revealed that down-regulation of LMNB2 impaired proliferation and cell cycle distribution. At the mechanical level, LMNB2 acts as a regulator of cyclinD1 and cyclinE1.

CONCLUSIONS

Altogether, these data suggest that LMNB2 may serve as a tumor promoter and could be a possible target for cancer therapy.

LncRNA SNHG1: role in tumorigenesis of multiple human cancers

Small nucleolar RNA host gene 1 (SNHG1) is an important member of the SNHG family. This family is composed of a group of host genes that can be processed into small nucleolar RNAs and play important biological functions. In an oncogenic role, the SNHG1 expression is increased in various cancers, which has immense application prospects in the diagnosis, treatment, and prognosis of malignant tumors. In this review, we have summarized the role and molecular mechanism of SNHG1 in the development of various cancers. In addition, we have emphasized the clinical significance of SNHG1 in cancers in our article. This molecule is expected to be a new marker for potential usage in the diagnosis, prognosis, and treatment of cancer.

The role of Lamin B2 in human diseases

Lamin B2 (LMNB2), on the inner side of the nuclear envelope, constitutes the nuclear skeleton by connecting with other nuclear proteins. LMNB2 is involved in a wide range of nuclear functions, including DNA replication and stability, regulation of chromatin, and nuclear stiffness. Moreover, LMNB2 regulates several cellular processes, such as tissue development, cell cycle, cellular proliferation and apoptosis, chromatin localization and stability, and DNA methylation. Besides, the influence of abnormal expression and mutations of LMNB2 has been gradually discovered in cancers and laminopathies. Therefore, this review summarizes the recent advances of LMNB2-associated biological roles in physiological or pathological conditions, with a particular emphasis on cancers and laminopathies, as well as the potential mechanism of LMNB2 in related cancers.

Identification and validation of a fatty acid metabolism-related lncRNA signature as a predictor for prognosis and immunotherapy in patients with liver cancer

Background

Fatty acid (FA) metabolism is considered the emerging cause of tumor development and metastasis, driving poor prognosis. Long non-coding RNAs (lncRNAs) are closely related to cancer progression and play important roles in FA metabolism. Thus, the discovery of FA metabolism-related lncRNA signatures to predict outcome and immunotherapy response is critical in improving the survival of patients with hepatocellular carcinoma (HCC).

Methods

FA metabolism scores and a FA metabolism-related lncRNA signature were constructed using a single-sample gene set enrichment analysis based on The Cancer Genome Atlas (TCGA) and Gene Expression Omnibus (GEO) databases. “ConsensusClusterPlus” was used to screen molecular subtypes. Chi-squared test and Fisher’s exact test were applied to explore the relationship between clinical, genomic mutation characteristics and subtypes. Transcription factor (TF) activity scores, cellular distributions, immune cell infiltration, and immunotherapy response were employed to investigate the functions of FA metabolism-related lncRNA signatures. FA metabolism microarray and western blot were performed to detect the biological function of candidate lncRNAs.

Results

A total of 70 lncRNAs that highly correlated with FA metabolism scores in two cohorts were used to construct two distinct clusters. Patients in cluster 2 had lower FA metabolism scores and worse survival than those in cluster 1. Patients in cluster 2 exhibited a high frequency of DNA damage, gene mutations, oncogenic signaling such as epithelial-to-mesenchymal transition, and a high degree of immune cell infiltration. Moreover, the lncRNA signature could predict the effects of immunotherapy in patients with HCC. Furthermore, three lncRNAs (SNHG1, LINC00261, and SNHG7) were identified that were highly correlated with FA metabolism. Additionally, SNHG1 and SNHG7 were found to regulate various FA metabolism-related genes and ferroptosis-related genes in vitro experiments. GSEA analysis revealed that SNHG1 and SNHG7 promote fatty acid beta-oxidation. SNHG1 and SNHG7 silencing dramatically reduced lipid droplets in HCC cells. Many immune-infiltration genes and TFs were overexpressed in HCC tissues with SNHG1 and SNHG7 high expression.

Conclusions

A novel molecular model of FA metabolism-related lncRNAs was developed, which has significantly prognostic potential in HCC diagnosis and aids in clinical decision making.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12885-022-10122-4.

Long Non-Coding RNAs as Novel Biomarkers in the Clinical Management of Papillary Renal Cell Carcinoma Patients: A Promise or a Pledge?

Papillary renal cell carcinoma (pRCC) represents the second most common subtype of renal cell carcinoma, following clear cell carcinoma and accounting for 10-15% of cases. For around 20 years, pRCCs have been classified according to their mere histopathologic appearance, unsupported by genetic and molecular evidence, with an unmet need for clinically relevant classification. Moreover, patients with non-clear cell renal cell carcinomas have been seldom included in large clinical trials; therefore, the therapeutic landscape is less defined than in the clear cell subtype. However, in the last decades, the evolving comprehension of pRCC molecular features has led to a growing use of target therapy and to better oncological outcomes. Nonetheless, a reliable molecular biomarker able to detect the aggressiveness of pRCC is not yet available in clinical practice. As a result, the pRCC correct prognosis remains cumbersome, and new biomarkers able to stratify patients upon risk of recurrence are strongly needed. Non-coding RNAs (ncRNAs) are functional elements which play critical roles in gene expression, at the epigenetic, transcriptional, and post-transcriptional levels. In the last decade, ncRNAs have gained importance as possible biomarkers for several types of diseases, especially in the cancer universe. In this review, we analyzed the role of long non-coding RNAs (lncRNAs) in the prognosis of pRCC, with a particular focus on their networking. In fact, in the competing endogenous RNA hypothesis, lncRNAs can bind miRNAs, resulting in the modulation of the mRNA levels targeted by the sponged miRNA, leading to additional regulation of the target gene expression and increasing complexity in the biological processes.