LncRNA LINC00924 upregulates NDRG2 to inhibit epithelial-mesenchymal transition via sponging miR-6755-5p in hepatitis B virus-related hepatocellular carcinoma

NDRG2 acts as a negative regulator of the progression of small-cell lung cancer through the modulation of the PTEN-AKT-mTOR signalling cascade

N-myc downstream-regulated gene 2 (NDRG2) has been recognised as a negative regulator of the progression of numerous tumours, yet its specific role in small-cell lung carcinoma (SCLC) is not fully understood. The purpose of the current study was to investigate the biological role and mechanism of NDRG2 in SCLC. Initial investigation using the Gene Expression Omnibus (GEO) dataset revealed marked downregulation of NDRG2 transcripts in SCLC. The decreased abundance of NDRG2 in SCLC was verified by examining clinical specimens. Increasing NDRG2 expression in SCLC cell lines caused significant changes in cell proliferation, cell cycle progression, colony formation, and chemosensitivity. NDRG2 overexpression decreased the levels of phosphorylated PTEN, AKT and mTOR. In PTEN-depleted SCLC cells, the upregulation of NDRG2 did not result in any noticeable impact on AKT or mTOR activation. Additionally, the reactivation of AKT reversed the antitumour effects of NDRG2 in SCLC cells. Notably, increasing NDRG2 expression retarded the growth of SCLC cell-derived xenografts in vivo. In conclusion, NDRG2 serves as an inhibitor of SCLC, and its cancer-inhibiting effects are achieved through the suppression of AKT/mTOR via the activation of PTEN. This work suggests that NDRG2 is a potential druggable target for SCLC treatment.

The Prognostic Value and Potential Immune Mechanisms of lncRNAs Related to Immunogenic Cell Death in Papillary Thyroid Carcinoma

Background

Long non-coding RNAs (lncRNAs) associated with immunogenic cell death (ICD) play a pivotal role in tumorigenesis and offer prognostic insights for papillary thyroid carcinoma (PTC) patients. This study delves into the impact of ICD-related lncRNAs on the prognosis of PTC.

Methods

PTC samples were accessed from The Cancer Genome Atlas-Thyroid carcinoma database (TCGA-THCA) and consensus cluster analysis to elucidate the influence of ICD-related lncRNA expression. To gauge the prognostic significance of these lncRNAs, we developed a prognostic model. Additionally, we conducted GO and KEGG enrichment analyses, assessed immune cell infiltration (ICI) using CIBERSORT and ssGSEA, examined immune checkpoint expression, tumor mutation burden (TMB), tumor microenvironment (TME), T-cell dysfunction and exclusion (TIDE), TCIA, and drug sensitivity across various groups. A comprehensive suite of in vitro experiments, encompassing EdU labeling, wound scratch assays, Transwell assays, and flow cytometry, were conducted to elucidate the regulatory role of LINC00924 in two PTC cell lines, BCPAP and TPC1, transfected with LINC00924 overexpression plasmids.

Results

Two distinct clusters demonstrated varying TME, BRAF, NRAS, and ICI characteristics, suggesting potential immune mechanisms in PTC. Our prognostic model identified seven lncRNAs: SRRM2-AS1, AC008556.1, BHLHE40-AS1, EGOT, AL39066.1, LINC00924, and PICART1. The expression of ICD-related lncRNAs correlated with progression-free interval (PFI) in PTC patients. Overexpression of LINC00924 significantly reduced cell proliferation, migration, and invasion, while augmenting apoptosis in PTC cells.

Conclusion

Our findings highlight the potential of ICD-related lncRNAs as prognostic biomarkers for PFI in PTC. In vitro experiments suggest a protective role of LINC00924 in PTC progression.

Sequence pre-training-based graph neural network for predicting lncRNA-miRNA associations

MicroRNAs (miRNAs) silence genes by binding to messenger RNAs, whereas long non-coding RNAs (lncRNAs) act as competitive endogenous RNAs (ceRNAs) that can relieve miRNA silencing effects and upregulate target gene expression. The ceRNA association between lncRNAs and miRNAs has been a research hotspot due to its medical importance, but it is challenging to verify experimentally. In this paper, we propose a novel deep learning scheme, i.e. sequence pre-training-based graph neural network (SPGNN), that combines pre-training and fine-tuning stages to predict lncRNA-miRNA associations from RNA sequences and the existing interactions represented as a graph. First, we utilize a sequence-to-vector technique to generate pre-trained embeddings based on the sequences of all RNAs during the pre-training stage. In the fine-tuning stage, we use Graph Neural Network to learn node representations from the heterogeneous graph constructed using lncRNA-miRNA association information. We evaluate our proposed scheme SPGNN on our newly collected animal lncRNA-miRNA association dataset and demonstrate that combining the $k$-mer technique and Doc2vec model for pre-training with the Simple Graph Convolution Network for fine-tuning is effective in predicting lncRNA-miRNA associations. Our approach outperforms state-of-the-art baselines across various evaluation metrics. We also conduct an ablation study and hyperparameter analysis to verify the effectiveness of each component and parameter of our scheme. The complete code and dataset are available on GitHub: https://github.com/zixwang/SPGNN.

Dysregulated microRNAs as a biomarker for diagnosis and prognosis of hepatitis B virus-associated hepatocellular carcinoma

Hepatocellular carcinoma (HCC) is a malignancy with a high incidence and fatality rate worldwide. Hepatitis B virus (HBV) infection is one of the most important risk factors for its occurrence and development. Early detection of HBV-associated HCC (HBV-HCC) can improve clinical decision-making and patient outcomes. Biomarkers are extremely helpful, not only for early diagnosis, but also for the development of therapeutics. MicroRNAs (miRNAs), a subset of non-coding RNAs approximately 22 nucleotides in length, have increasingly attracted scientists' attention due to their potential utility as biomarkers for cancer detection and therapy. HBV profoundly impacts the expression of miRNAs potentially involved in the development of hepatocarcinogenesis. In this review, we summarize the current progress on the role of miRNAs in the diagnosis and treatment of HBV-HCC. From a molecular standpoint, we discuss the mechanism by which HBV regulates miRNAs and investigate the exact effect of miRNAs on the promotion of HCC. In the near future, miRNA-based diagnostic, prognostic, and therapeutic applications will make their way into the clinical routine.

MALAT1 binds to miR-188-3p to regulate ALOX5 activity in the lung inflammatory response of neonatal bronchopulmonary dysplasia

Bronchopulmonary dysplasia (BPD) causes high morbidity and mortality in infants, but no effective preventive or therapeutic agents have been developed to combat BPD. In this study, we assessed the expression of MALAT1 and ALOX5 in peripheral blood mononuclear cells from BPD neonates, hyperoxia-induced rat models and lung epithelial cell lines. Interestingly, we found upregulated expression of MALAT1 and ALOX5 in the experimental groups, along with upregulated expression of proinflammatory cytokines. According to bioinformatics prediction, MALAT1 and ALOX5 simultaneously bind to miR-188-3p, which was downregulated in the experimental groups above. Silencing MALAT1 or ALOX5 and overexpressing miR-188-3p inhibited apoptosis and promoted the proliferation of hyperoxia-treated A549 cells. Suppressing MALAT1 or overexpressing miR-188-3p increased the expression levels of miR-188-3p but decreased the expression levels of ALOX5. Moreover, RNA immunoprecipitation (RIP) and luciferase assays showed that MALAT1 directly targeted miR-188-3p to regulate ALOX5 expression in BPD neonates. Collectively, our study demonstrates that MALAT1 regulates ALOX5 expression by binding to miR-188-3p, providing novel insights into potential therapeutics for BPD treatment.

LINC00924-induced fatty acid metabolic reprogramming facilitates gastric cancer peritoneal metastasis via hnRNPC-regulated alternative splicing of Mnk2

The molecular mechanism underlying gastric cancer (GC) peritoneal metastasis (PM) remains unclear. Here, we identified LINC00924 as a GC PM-related lncRNA through Microarray sequencing. LINC00924 was highly expressed in GC, and its high expression is associated with a broad range of PM. Via RNA sequencing, RNA pulldown assay, mass spectrometry, Seahorse, Lipidomics, spheroid formation and cell viability assays, we found that LINC00924 promoted fatty acid (FA) oxidation (FAO) and FA uptake, which was essential for matrix-detached GC cell survival and spheroid formation. Regarding the mechanism, LINC00924 regulated the alternative splicing (AS) of Mnk2 pre-mRNA by binding to hnRNPC. Specifically, LINC00924 enhanced the binding of hnRNPC to Mnk2 pre-mRNA at e14a, thus downregulating Mnk2a splicing and regulating the p38 MAPK/PPARα signaling pathway. Collectively, our results demonstrate that LINC00924 plays a role in promoting GC PM and could serve as a drug target.

CORRIGENDUM

LncRNA LINC00924 upregulates NDRG2 to inhibit epithelial-mesenchymal transition via sponging miR-6755-5p in hepatitis B virus-related hepatocellular carcinoma This article is protected by copyright. All rights reserved.

Application and progress of the detection technologies in hepatocellular carcinoma

Hepatocellular carcinoma (HCC) has a very high incidence and fatality rate, and in most cases, it is already at an advanced stage when diagnosed. Therefore, early prevention and detection of HCC are two of the most effective strategies. However, the methods recommended in the practice guidelines for the detection of HCC cannot guarantee high sensitivity and specificity except for the liver biopsy, which is known as the "gold standard". In this review, we divided the detection of HCC into pre-treatment diagnosis and post-treatment monitoring, and found that in addition to the traditional imaging detection and liver biopsy, alpha fetoprotein (AFP), lens culinaris-agglutinin-reactive fraction of AFP (AFP-L3), protein induced by vitamin K absence or antagonist-II (PIVKA-II) and other biomarkers are excellent biomarkers for HCC, especially when they are combined together. Most notably, the emerging liquid biopsy shows great promise in detecting HCC. In addition, lactic dehydrogenase (LDH), suppressor of cytokine signaling (SOCS) and other relevant biomarkers may become promising biomarkers for HCC post-treatment monitoring. Through the detailed introduction of the diagnostic technology of HCC, we can have a detailed understanding of its development process and then obtain some enlightenment from the diagnosis, to improve the diagnostic rate of HCC and reduce its mortality.