Long non-coding RNA BACE1-AS plays an oncogenic role in hepatocellular carcinoma cells through miR-214-3p/APLN axis

Combinatorial Gene Expression Profiling of Serum HULC, HOTAIR, and UCA1 lncRNAs to Differentiate Hepatocellular Carcinoma from Liver Diseases: A Systematic Review and Meta-Analysis

Hepatocellular carcinoma (HCC) presents a significant global health challenge due to limited early detection methods, primarily relying on conventional approaches like imaging and alpha-fetoprotein (AFP). Although non-coding RNAs (ncRNAs) show promise as potential biomarkers in HCC, their true utility remains uncertain. We conducted a comprehensive review of 76 articles, analyzing 88 circulating lncRNAs in 6426 HCC patients. However, the lack of a standardized workflow protocol has hampered holistic comparisons across the literature. Consequently, we herein confined our meta-analysis to only a subset of these lncRNAs. The combined analysis of serum highly upregulated in liver cancer (HULC) gene expression with homeobox transcript antisense intergenic RNA (HOTAIR) and urothelial carcinoma-associated 1 (UCA1) demonstrated markedly enhanced sensitivity and specificity in diagnostic capability compared to traditional biomarkers or other ncRNAs. These findings could have substantial implications for the early diagnosis and tailored treatment of HCC.

m6A modified BACE1-AS contributes to liver metastasis and stemness-like properties in colorectal cancer through TUFT1 dependent activation of Wnt signaling

BACKGROUND

Liver metastasis is one of the most important reasons for high mortality of colorectal cancer (CRC). Growing evidence illustrates that lncRNAs play a critical role in CRC liver metastasis. Here we described a novel function and mechanisms of BACE1-AS promoting CRC liver metastasis.

METHODS

qRT-PCR and in situ hybridization were performed to examine the BACE1-AS level in CRC. IGF2BP2 binding to m6A motifs in BACE1-AS was determined by RIP assay and S1m-tagged immunoprecipitation. Transwell assay and liver metastasis mice model experiments were performed to examine the metastasis capabilities of BACE1-AS knockout cells. Stemness-like properties was examined by tumor sphere assay and the expression of stemness biomarkers. Microarray data were acquired to analyze the signaling pathways involved in BACE1-AS promoting CRC metastasis.

RESULTS

BACE1-AS is the most up-regulated in metastatic CRC associated with unfavorable prognosis. Sequence blast revealed two m6A motifs in BACE1-AS. IGF2BP2 binding to these two m6A motifs is required for BACE1-AS boost in metastatic CRC. m6A modified BACE1-AS drives CRC cells migration and invasion and liver metastasis both in vitro and in vivo. Moreover, BACE1-AS maintains the stemness-like properties of CRC cells. Mechanically, BACE1-AS promoted TUFT1 expression by ceRNA network through miR-214-3p. CRC patients with such ceRNA network suffer poorer prognosis than ceRNA-negative patients. Depletion of TUFT1 mimics BACE1-AS loss. BACE1-AS activated Wnt signaling pathway in a TUFT1 dependent manner. BACE1-AS/miR-214-3p/TUFT1/Wnt signaling regulatory axis is essential for CRC liver metastasis. Pharmacologic inhibition of Wnt signaling pathway repressed liver metastasis and stemness-like features in BACE1-AS over-expressed CRC cells.

CONCLUSION

Our study demonstrated BACE1-AS as a novel target of IGF2BP2 through m6A modification. m6A modified BACE1-AS promotes CRC liver metastasis through TUFT1 dependent activation of Wnt signaling pathway. Thus, targeting BACE1-AS and its downstream Wnt signaling pathways may provide a new opportunity for metastatic CRC intervention and treatment.

Making Sense of Antisense lncRNAs in Hepatocellular Carcinoma

Transcriptome complexity is emerging as an unprecedented and fascinating domain, especially by high-throughput sequencing technologies that have unveiled a plethora of new non-coding RNA biotypes. This review covers antisense long non-coding RNAs, i.e., lncRNAs transcribed from the opposite strand of other known genes, and their role in hepatocellular carcinoma (HCC). Several sense-antisense transcript pairs have been recently annotated, especially from mammalian genomes, and an understanding of their evolutionary sense and functional role for human health and diseases is only beginning. Antisense lncRNAs dysregulation is significantly involved in hepatocarcinogenesis, where they can act as oncogenes or oncosuppressors, thus playing a key role in tumor onset, progression, and chemoradiotherapy response, as deduced from many studies discussed here. Mechanistically, antisense lncRNAs regulate gene expression by exploiting various molecular mechanisms shared with other ncRNA molecules, and exploit special mechanisms on their corresponding sense gene due to sequence complementarity, thus exerting epigenetic, transcriptional, post-transcriptional, and translational controls. The next challenges will be piecing together the complex RNA regulatory networks driven by antisense lncRNAs and, ultimately, assigning them a function in physiological and pathological contexts, in addition to defining prospective novel therapeutic targets and innovative diagnostic tools.

Targeting Non-Coding RNAs for the Development of Novel Hepatocellular Carcinoma Therapeutic Approaches

Hepatocellular carcinoma (HCC) remains a global health challenge, representing the third leading cause of cancer deaths worldwide. Although therapeutic advances have been made in the few last years, the prognosis remains poor. Thus, there is a dire need to develop novel therapeutic strategies. In this regard, two approaches can be considered: (1) the identification of tumor-targeted delivery systems and (2) the targeting of molecule(s) whose aberrant expression is confined to tumor cells. In this work, we focused on the second approach. Among the different kinds of possible target molecules, we discuss the potential therapeutic value of targeting non-coding RNAs (ncRNAs), which include micro interfering RNAs (miRNAs), long non-coding RNAs (lncRNAs) and circular RNAs (circRNAs). These molecules represent the most significant RNA transcripts in cells and can regulate many HCC features, including proliferation, apoptosis, invasion and metastasis. In the first part of the review, the main characteristics of HCC and ncRNAs are described. The involvement of ncRNAs in HCC is then presented over five sections: (a) miRNAs, (b) lncRNAs, (c) circRNAs, (d) ncRNAs and drug resistance and (e) ncRNAs and liver fibrosis. Overall, this work provides the reader with the most recent state-of-the-art approaches in this field, highlighting key trends and opportunities for more advanced and efficacious HCC treatments.

Long non-coding RNAs (lncRNAs) in hepatocellular carcinoma progression: Biological functions and new therapeutic targets

Liver is an important organ in body that performs vital functions such as detoxification. Liver is susceptible to development of cancers, and hepatocellular carcinoma (HCC) is among them. 75-85% of liver cancer cases are related to HCC. Therefore, much attention has been directed towards understanding factors mediating HCC progression. LncRNAs are epigenetic factors with more than 200 nucleotides in length located in both nucleus and cytoplasm and they are promising candidates in cancer therapy. Directing studies towards understanding function of lncRNAs in HCC is of importance. LncRNAs regulate cell cycle progression and growth of HCC cells, and they can also induce/inhibit apoptosis in tumor cells. LncRNAs affect invasion and metastasis in HCC mainly by epithelial-mesenchymal transition (EMT) mechanism. Revealing the association between lncRNAs and downstream signaling pathways in HCC is discussed in the current manuscript. Infectious diseases can affect lncRNA expression in mediating HCC development and then, altered expression level of lncRNA is associated with drug resistance and radio-resistance. Biomarker application of lncRNAs and their role in prognosis and diagnosis of HCC are also discussed to pave the way for treatment of HCC patients.

Dysregulation of miR-204-5p/APLN axis affects malignant progression and cell stemness of esophageal cancer

OBJECTIVE

This study attempted to investigate the mechanism of miR-204-5p and its downstream gene in regulating bio-functions of esophageal cancer (EC).

METHODS

Bioinformatics analysis was performed to select the mature miRNAs, mRNAs, and clinical data of EC. The miRNA-mRNA regulatory axis was predicted through bioinformatics and used Dual-luciferase analysis to verify the interaction between miR-204-5p and APLN. qRT-PCR was applied to analyze expression of miR-204-5p and APLN mRNA. Western blot was utilized to detect APLN protein expression. Functional assays like CCK-8, wound healing, Transwell, and stem cell sphere formation assays were launched to confirm proliferative, migratory, invasive and stemness of cells in different treatment groups.

RESULTS

MiR-204-5p was lowly expressed while its target gene APLN was highly expressed in tumor tissues. Besides, miR-204-5p overexpression hindered proliferation, invasion, migration, and stemness of EC cells. Additionally, dual-luciferase assay verified the interaction of miR-204-5p and APLN. MiR-204-5p could downregulate APLN level and its overexpression reduced the effect of APLN on EC cell functions.

CONCLUSION

Dysregulation of miR-204-5p/APLN axis was linked with malignant progression of EC. MiR-204-5p/APLN may be an underlying candidate for the design of anticarcinogens.

Identification and Validation of Necroptosis-Related LncRNA Signature in Hepatocellular Carcinoma for Prognosis Estimation and Microenvironment Status

Background: Hepatocellular carcinoma (HCC) is among malignancies with the highest fatality toll globally and minimal therapeutic options. Necroptosis is a programmed form of necrosis or inflammatory cell death, which can affect prognosis and microenvironmental status of HCC. Therefore, we aimed to explore the prognostic value of necroptosis-related lncRNAs (NRLs) in HCC and the role of the tumor microenvironment (TME) in immunotherapy. Methods: The RNA-sequencing data and clinical information were downloaded from The Cancer Genome Atlas (TCGA) and the International Cancer Genome Consortium (ICGC). NRLs were identified by Pearson correlation analysis. The signature was constructed using the LASSO-Cox regression analysis and evaluated using the receiver operating characteristic curve (ROC) and the area under the Kaplan-Meier curve. The nomogram was built based on clinical information and risk score. Gene set enrichment analysis (GSEA), immunoassay, half-maximum inhibitory concentration (IC₅₀) analysis of the risk group, and the HCC subtype identification based on NRLs were also carried out. Finally, we detected the expression of lncRNAs in HCC tissues and cell lines in vitro. Results: A total of 508 NRLs were screened out, and seven NRLs were constructed as a risk stratification system to classify patients into distinct low- and high-risk groups. Patients in the high-risk group had a significantly lower overall survival (OS) than those in the low-risk group. Using multivariate Cox regression analysis, we found that the risk score was an independent predictor of OS. Functional analysis showed that the immune status of different patients was different. The IC₅₀ analysis of chemotherapy demonstrated that patients in the high-risk group were more sensitive to commonly prescribed drugs. qRT-PCR showed that three high-risk lncRNAs were upregulated in drug-resistant cells, and the expression in HCC tissues was higher than that in adjacent tissues. Conclusion: The prediction signature developed in this study can be used to assess the prognosis and microenvironment of HCC patients, and serve as a new benchmark for HCC treatment selection.

Long noncoding RNA BACE1-antisense transcript plays a critical role in Parkinson's disease via microRNA-214-3p/Cell death-inducing p53-target protein 1 axis

This study aimed to analyze the function and latent mechanism of long noncoding RNA BACE1-antisense transcript (lncRNA BACE1-AS) in MPP⁺-induced SH-SY5Y cells. SH-SY5Y cells were cultivated in 1 mM MPP⁺ for 24 h to establish Parkinson’s disease (PD) model in vitro. TargetScan and luciferase reporter assay were conducted to predict and verify the interaction between microRNA (miR)-214-3p and CDIP1 (Cell death-inducing p53-target protein 1). Cell viability, lactate dehydrogenase (LDH) release, and cell apoptosis were evaluated by 3-(4,5-dimethylthiazol-2-yl)-2,5-diphenyl-2 H-tetrazolium bromide (MTT), LDH, and flow cytometer. The secretion of inflammatory factors and representative biomarkers of oxidative stress, including reactive oxygen species (ROS) and superoxide dismutase (SOD) were assessed using enzyme-linked immunosorbent assay (ELISA) and specific assay kits. Results suggested that lncRNA BACE1-AS was over-expressed and miR-214-3p was under-expressed in MPP⁺-stimulated SH-SY5Y cells. Further analyses revealed that MPP⁺ inhibited cell viability; enhanced cell apoptosis, Cleaved Caspase-3 expression and Cleaved Caspase-3/GAPDH ratio; induced oxidative stress and inflammation in SH-SY5Y cells were inhibited by lncRNA BACE1-AS-siRNA transfection; and all these inhibitions were reversed by miR-214-3p inhibitor. In addition, we found that CDIP1 was directly targeted by miR-214-3p and up-regulated in MPP⁺-stimulated SH-SY5Y cells. Further functional assays suggested that CDIP1-plasmid reversed the effects of miR-214-3p mimic on MPP⁺-stimulated SH-SY5Y cells. In conclusion, lncRNA BACE1-AS regulates SH-SY5Y cell proliferation, apoptosis, inflammatory response, and oxidative stress through direct regulation of miR-214-3p/CDIP1 signaling axis, and could be a potential candidate associated with the diagnosis and treatment of PD.

Development and Validation of a Prognostic Signature Associated With Tumor Microenvironment Based on Autophagy-Related lncRNA Analysis in Hepatocellular Carcinoma

Objective: The present study aimed to establish a prognostic signature based on the autophagy-related long non-coding RNAs (lncRNAs) analysis in patients with hepatocellular carcinoma (HCC).

Methods: Patients with HCC from The Cancer Genome Atlas (TCGA) were taken as the training cohort, and patients from the International Cancer Genome Consortium (ICGC) were treated as the validation cohort. Autophagy-related lncRNAs were obtained via a co-expression network analysis. According to univariate and multivariate analyses, a multigene prognostic signature was constructed in the training cohort. The predictive power of the signature was confirmed in both cohorts. The detailed functions were investigated using functional analysis. The single-sample gene set enrichment analysis (ssGSEA) score was used to evaluate the tumor microenvironment. The expression levels of immunotherapy and targeted therapy targets between the two risk groups were compared. Finally, a nomogram was constructed by integrating clinicopathological parameters with independently predictive value and the risk score.

Results: Four autophagy-related lncRNAs were identified to establish a prognostic signature, which separated patients into high- and low-risk groups. Survival analysis showed that patients in the high-risk group had a shorter survival time in both cohorts. A time-independent receiver-operating characteristic (ROC) curve and principal component analysis (PCA) confirmed that the prognostic signature had a robust predictive power and reliability in both cohorts. Functional analysis indicated that the expressed genes in the high-risk group are mainly enriched in autophagy- and cancer-related pathways. ssGSEA revealed that the different risk groups were associated with the tumor microenvironment. Moreover, the different risk groups had positive correlations with the expressions of specific mutant genes. Multivariate analysis showed that the risk score also exhibited excellent predictive power irrespective of clinicopathological characteristics in both cohorts. A nomogram was established. The nomogram showed good discrimination, with Harrell's concordance index (C-index) of 0.739 and good calibration.

Conclusion: The four autophagy-related lncRNAs could be used as biological biomarkers and therapeutic targets. The prognostic signature and nomogram might aid clinicians in individual treatment optimization and clinical decision-making for patients with HCC.