Construction of a ceRNA network and a genomic-clinicopathologic nomogram to predict survival for HBV-related HCC

Exposure of benzo[a]pyrene induces HCC exosome-circular RNA to activate lung fibroblasts and trigger organotropic metastasis

BACKGROUND

Benzo[a]pyrene (B[a]P), a carcinogen pollutant produced by combustion processes, is present in the western diet with grilled meats. Chronic exposure of B[a]P in hepatocellular carcinoma (HCC) cells promotes metastasis rather than primary proliferation, implying an unknown mechanism of B[a]P-induced malignancy. Given that exosomes carry bioactive molecules to distant sites, we investigated whether and how exosomes mediate cancer-stroma communications for a toxicologically associated microenvironment.

METHOD

Exosomes were isolated from B[a]P stimulated BEL7404 HCC cells (7404-100Bap Exo) at an environmental relevant dose (100 nmol/L). Lung pre-education animal model was prepared via injection of exosomes and cytokines. The inflammatory genes of educated lungs were evaluated using quantitative reverse transcription PCR array. HCC LM3 cells transfected with firefly luciferase were next injected to monitor tumor burdens and organotropic metastasis. Profile of B[a]P-exposed exosomes were determined by ceRNA microarray. Interactions between circular RNA (circRNA) and microRNAs (miRNAs) were detected using RNA pull-down in target lung fibroblasts. Fluorescence in situ hybridization and RNA immunoprecipitation assay was used to evaluate the "on-off" interaction of circRNA-miRNA pairs. We further developed an adeno-associated virus inhalation model to examine mRNA expression specific in lung, thereby exploring the mRNA targets of B[a]P induced circRNA-miRNA cascade.

RESULTS

Lung fibroblasts exert activation phenotypes, including focal adhesion and motility were altered by 7404-100Bap Exo. In the exosome-educated in vivo model, fibrosis factors and pro-inflammatory molecules of are up-regulated when injected with exosomes. Compared to non-exposed 7404 cells, circ_0011496 was up-regulated following B[a]P treatment and was mainly packaged into 7404-100Bap Exo. Exosomal circ_0011496 were delivered and competitively bound to miR-486-5p in recipient fibroblasts. The down-regulation of miR-486-5p converted fibroblast to cancer-associated fibroblast via regulating the downstream of Twinfilin-1 (TWF1) and matrix metalloproteinase-9 (MMP9) cascade. Additionally, increased TWF1, specifically in exosomal circ_0011496 educated lungs, could promote cancer-stroma crosstalk via activating vascular endothelial growth factor (VEGF). These modulated fibroblasts promoted endothelial cells angiogenesis and recruited primary HCC cells invasion, as a consequence of a pre-metastatic niche formation.

CONCLUSION

We demonstrated that B[a]P-induced tumor exosomes can deliver circ_0011496 to activate miR-486-5p/TWF1/MMP9 cascade in the lung fibroblasts, generating a feedback loop that promoted HCC metastasis.

Carcinogenic roles of MAFG-AS1 in human cancers

The MAF bZIP transcription factor G-antisense RNA 1 (MAFG-AS1) is located on chromosome 17. MAFG-AS1 was upregulated in 15 human cancers. MAFG-AS1 not only suppresses 16 miRNAs but also directly impacts 22 protein-coding genes' expression. Notably, abnormal MAFG-AS1 expression is connected to clinicopathological characteristics and a worse prognosis in a variety of cancers. Moreover, MAFG-AS1 takes its part in the tumorigenesis and progression of various human malignancies by suppressing apoptosis and promoting proliferation, migration, invasion, aerobic glycolysis, ferroptosis, angiogenesis, EMT, and metastasis. Besides, it can predict treatment effectiveness in ER + breast cancer, urothelial bladder carcinoma, and liver cancer by functioning as a trigger of resistance to tamoxifen, sorafenib, and cisplatin. This study systematically presents the functions of MAFG-AS1 in various cancers, as well as the findings of bioinformatics analyses of the MAFG-AS1, which should give clear advice for future research.

LncRNA MAFG-AS1 is involved in human cancer progression

Long noncoding RNAs (lncRNAs) refer to a type of non-protein-coding transcript of more than 200 nucleotides. LncRNAs play fundamental roles in disease development and progression, and lncRNAs are dysregulated in many pathophysiological processes. Thus, lncRNAs may have potential value in clinical applications. The lncRNA, MAF BZIP Transcription Factor G (MAFG)-AS1, is dysregulated in several cancer, including breast cancer, lung cancer, liver cancer, bladder cancer, colorectal cancer, gastric cancer, esophagus cancer, prostate cancer, pancreatic cancer, ovarian cancer, and glioma. Altered MAFG-AS1 levels are also associated with diverse clinical characteristics and patient outcomes. Mechanistically, MAFG-AS1 mediates a variety of cellular processes via the regulation of target gene expression. Therefore, the diagnostic, prognostic, and therapeutic aspects of MAFG-AS1 have been widely explored. In this review, we discuss the expression, major roles, and molecular mechanisms of MAFG-AS1, the relationship between MAFG-AS1 and clinical features of diseases, and the clinical applications of MAFG-AS1.

Construction of a ceRNA network to reveal a vascular invasion associated prognostic model in hepatocellular carcinoma

The aim of this study is to explore the prognostic value of vascular invasion (VI) in hepatocellular carcinoma (HCC) by searching for competing endogenous RNAs (ceRNA) network and constructing a new prognostic model for HCC. The differentially expressed genes (DEGs) between HCC and normal tissues were identified from GEO and TCGA. StarBase and miRanda prediction tools were applied to construct a circRNA-miRNA-mRNA network. The DEGs between HCC with and without VI were also identified. Then, the hub genes were screened to build a prognostic risk score model through the method of least absolute shrinkage and selection operator. The prognostic ability of the model was assessed using the Kaplan-Meier method and Cox regression analysis. In result, there were 221 up-regulated and 47 down-regulated differentially expressed circRNAs (DEcircRNAs) in HCC compared with normal tissue. A circRNA-related ceRNA network was established, containing 11 DEcircRNAs, 12 DEmiRNAs, and 161 DEmRNAs. Meanwhile, another DEG analysis revealed 625 up-regulated and 123 down-regulated DEGs between HCC with and without VI, and then a protein-protein interaction (PPI) network was built based on 122 VI-related DEGs. From the intersection of DEGs within the PPI and ceRNA networks, we obtained seven hub genes to build a novel prognostic risk score model. HCC patients with high-risk scores had shorter survival time and presented more advanced T/N/M stages as well as VI occurrence. In conclusion a novel prognostic model based on seven VI-associated DEGs within a circRNA-related ceRNA network was constructed in this study, with great ability to predict the outcome of HCC patients.

Decoding hepatocarcinogenesis from a noncoding RNAs perspective

Being a leading lethal malignancy worldwide, the pathophysiology of hepatocellular carcinoma (HCC) has gained a lot of interest. Yet, underlying mechanistic basis of the liver tumorigenesis is poorly understood. The role of some coding genes and their respective translated proteins, then later on, some noncoding RNAs (ncRNAs) such as microRNAs have been extensively studied in context of HCC pathophysiology; however, the implication of long noncoding RNAs (lncRNAs) and circular RNAs (circRNAs) in HCC is indeed less investigated. As a subclass of the ncRNAs which has been elusive for long time ago, lncRNAs was found to be involved in plentiful cellular functions such as DNA, RNA, and proteins regulation. Hence, it is undisputed that lncRNAs dysregulation profoundly contributes to HCC via diverse etiologies. Accordingly, lncRNAs represent a hot research topic that requires prime focus in HCC. In this review, the authors discuss breakthrough discoveries involving lncRNAs and circRNAs dysregulation that have contributed to the contemporary concepts of HCC pathophysiology and how these concepts could be leveraged as potential novel diagnostic and prognostic HCC biomarkers. Further, this review article sheds light on future trends, thereby discussing the pathological roles of lncRNAs and circRNAs in HCC proliferation, migration, and epithelial-to-mesenchymal transition. Along this line of reasoning, future recommendations of how these targets could be exploited to achieve effective HCC-related drug development is highlighted.

Comprehensive analysis and identification of the circ_0084615/miR-451a/MEF2D axis in benzo(a)pyrene exposed tumor cells in hepato-carcinogenesis

Hepatocellular carcinoma (HCC) is caused by genetic and epigenetic alterations, as well as abnormal lifestyle and dietary habits, including contaminated food intake. Benzo(a)pyrene (B[a]P), derived from deep-fried meats, is regarded as the main dietary factor for tumorigenesis in epidemiological investigations. Although various studies have illustrated the adverse effects of B[a]P in malignancy through cell and animal models, the correlation between B[a]P exposure and clinical data remain to be explored. In the present study, we analyzed and identified novel B[a]P-associated circular RNA (circRNA) from microarray databases of liver tumor cells and HCC patient samples. Considering that circRNA regulates mRNA as a miRNA sponge, molecular circRNA-miRNA-mRNA interactions based on the stimulation of B[a]P exposure were predicted and established. Furthermore, up-regulated circ_0084615 in B[a]P-treated tumor cells was verified as a miRNA sponge via fluorescence in situ hybridization (FISH) assays, and the repression between circ_0084615 and target miR-451a exhibited a contrasting effect on hepatocarcinogenesis. Therefore, we performed integrated bioinformatics analysis and molecular experiments to establish the circ_0084615/miR-451a/MEF2D pathway, which provided a better understanding of the adverse effects of fried food preference on human health.

Molecular subtypes and a prognostic model for hepatocellular carcinoma based on immune- and immunogenic cell death-related lncRNAs

Background

Accumulating evidence shows that immunogenic cell death (ICD) enhances immunotherapy effectiveness. In this study, we aimed to develop a prognostic model combining ICD, immunity, and long non-coding RNA biomarkers for predicting hepatocellular carcinoma (HCC) outcomes.

Methods

Immune- and immunogenic cell death-related lncRNAs (IICDLs) were identified from The Cancer Genome Atlas and Ensembl databases. IICDLs were extracted based on the results of differential expression and univariate Cox analyses and used to generate molecular subtypes using ConsensusClusterPlus. We created a prognostic signature based on IICDLs and a nomogram based on risk scores. Clinical characteristics, immune landscapes, immune checkpoint blocking (ICB) responses, stemness, and chemotherapy responses were also analyzed for different molecular subtypes and risk groups.

Result

A total of 81 IICDLs were identified, 20 of which were significantly associated with overall survival (OS) in patients with HCC. Cluster analysis divided patients with HCC into two distinct molecular subtypes (C1 and C2), with patients in C1 having a shorter survival time than those in C2. Four IICDLs (TMEM220-AS1, LINC02362, LINC01554, and LINC02499) were selected to develop a prognostic model that was an independent prognostic factor of HCC outcomes. C1 and the high-risk group had worse OS (hazard ratio > 1.5, p < 0.01), higher T stage (p < 0.05), higher clinical stage (p < 0.05), higher pathological grade (p < 0.05), low immune cell infiltration (CD4⁺ T cells, B cells, macrophages, neutrophils, and myeloid dendritic cells), low immune checkpoint gene expression, poor response to ICB therapy, and high stemness. Different molecular subtypes and risk groups showed significantly different responses to several chemotherapy drugs, such as doxorubicin (p < 0.001), 5-fluorouracil (p < 0.001), gemcitabine (p < 0.001), and sorafenib (p < 0.01).

Conclusion

Our study identified molecular subtypes and a prognostic signature based on IICDLs that could help predict the clinical prognosis and treatment response in patients with HCC.

Comprehensive analysis of the endoplasmic reticulum stress-related long non-coding RNA in bladder cancer

Background

Bladder cancer is ranked the second most frequent tumor among urological malignancies. The research strived to establish a prognostic model based on endoplasmic reticulum stress (ERS)-related long non-coding RNA (lncRNA) in bladder cancer.

Methods

We extracted the ERS-related genes from the published research and bladder cancer data from the Cancer Genome Atlas database. ERS-related lncRNAs with prognostic significance were screened by univariate Cox regression, least absolute shrinkage and selection operator regression analysis and Kaplan-Meier method. Multivariate Cox analysis was leveraged to establish the risk score model. Moreover, an independent dataset, GSE31684, was used to validate the model’s efficacy. The nomogram was constructed based on the risk score and clinical variables. Furthermore, the biological functions, gene mutations, and immune landscape were investigated to uncover the underlying mechanisms of the ERS-related signature. Finally, we employed external datasets (GSE55433 and GSE89006) and qRT-PCR to investigate the expression profile of these lncRNAs in bladder cancer tissues and cells.

Results

Six ERS-related lncRNAs were identified to be closely coupled with patients’ prognosis. On this foundation, a risk score model was created to generate the risk score for each patient. The ERS-related risk score was shown to be an independent prognostic factor. And the results of GSE31684 dataset also supported this conclusion. Then, a nomogram was constructed based on risk scores and clinical characteristics, and proven to have excellent predictive value. Moreover, the gene function analysis demonstrated that ERS-related lncRNAs were closely linked to fatty extracellular matrix, cytokines, cell adhesion, and tumor pathways. Further analysis revealed the association of the 6-lncRNAs signature with gene mutations and immunity in bladder cancer. Finally, the external datasets and qRT-PCR verified high expressions of the ERS-related lncRNAs in bladder cancer tissues and cells.

Conclusions

Overall, our findings indicated that ERS-related lncRNAs, which may affect tumor pathogenesis in a number of ways, might be exploited to assess the prognosis of bladder cancer patients.

Long Non-Coding RNA MAFG-AS1 as a Potential Biomarker for Hepatocellular Carcinoma: Linkage with Tumor Features, Markers, Liver Functions, and Survival Profile

Purpose

Long non-coding RNAs musculoaponeurotic fibrosarcoma oncogene family, protein G antisense 1 (lnc-MAFG-AS1) regulates hepatocellular carcinoma (HCC) progression and treatment resistance in multiple ways, while its engagement in HCC clinical management remains obscure. The current study aims to explore the relationship of lnc-MAFG-AS1 with tumor features, liver function indexes, tumor markers, and prognosis in HCC patients.

Methods

One hundred and fifty-two surgical HCC patients who underwent tumor resection were retrospectively analyzed. Their tumor and adjacent tissues were acquired and then proposed to reverse transcription-quantitative polymerase chain reaction to detect lnc-MAFG-AS1 expression.

Results

Lnc-MAFG-AS1 expression was increased in HCC tumor tissue than in adjacent tissue [median (interquartile range): 2.730 (1.685–4.198) vs. 0.990 (0.703–1.468), p < 0.001], with a high area under the curve [0.889, 95% confidence interval (CI): 0.854–0.924] to distinguish them via receiver operating characteristic curve analysis. Tumor lnc-MAFG-AS1 was linked with multifocal nodules (p < 0.001), increased Barcelona Clinic Liver Cancer (BCLC) stage (p = 0.018), and elevated China Liver Cancer (CNLC) stage (p = 0.008), which also correlated with an abnormal alpha-fetoprotein (AFP) level (p = 0.004), However, lnc-MAFG-AS1 was not linked with other disease conditions, tumor properties, liver function indexes, or tumor markers (all ps > 0.05). In addition, patients with a high expression of lnc-MAFG-AS1 exhibited worse overall survival than those with a low expression of lnc-MAFG-AS1 [median (95% CI): 34.0 (24.5–43.5) vs. 48.0 (41.5–54.5) months] (p = 0.011), which was further validated by univariate Cox’s analysis [hazard ratio (HR) = 1.827, p = 0.013] and multivariate Cox’s analysis (HR = 1.697, p = 0.040).

Conclusion

Lnc-MAFG-AS1 relates to multifocal nodules, increased BCLC stage, elevated CNLC stage, and abnormal AFP level and predicts pejorative prognosis in HCC patients.

Diversity of Dysregulated Long Non-Coding RNAs in HBV-Related Hepatocellular Carcinoma

Infection with the hepatitis B virus (HBV) continues to pose a major threat to public health as approximately 292 million people worldwide are currently living with the chronic form of the disease, for which treatment is non-curative. Chronic HBV infections often progress to hepatocellular carcinoma (HCC) which is one of the world’s leading causes of cancer-related deaths. Although the process of hepatocarcinogenesis is multifaceted and has yet to be fully elucidated, several studies have implicated numerous long non-coding RNAs (lncRNAs) as contributors to the development of HCC. These host-derived lncRNAs, which are often dysregulated as a consequence of viral infection, have been shown to function as signals, decoys, guides, or scaffolds, to modulate gene expression at epigenetic, transcriptional, post-transcriptional and even post-translational levels. These lncRNAs mainly function to promote HBV replication and oncogene expression or downregulate tumor suppressors. Very few lncRNAs are known to suppress tumorigenesis and these are often downregulated in HCC. In this review, we describe the mechanisms by which lncRNA dysregulation in HBV-related HCC promotes tumorigenesis and cancer progression.