High-throughput sequencing approach for the identification of lncRNA biomarkers in hepatocellular carcinoma and revealing the effect of ZFAS1/miR-150-5p on hepatocellular carcinoma progression

Expression of ALG8 in hepatocellular carcinoma and its diagnostic and prognostic significance

BACKGROUND

Alpha-1,3-glucosyltransferase (ALG8), a key enzyme in protein glycosylation, is implicated in the oncogenesis and progression of several human malignancies. This study aimed to define the role of ALG8 in hepatocellular carcinoma (HCC) and uncover its mechanisms of action.

METHODS

ALG8 expression in HCC and normal tissues was analyzed using the TCGA and GEO databases, validated by RT-qPCR and western blot. Survival outcomes were evaluated via Cox analyses, and ALG8's impact on HCC behavior was examined through functional assays. GO, KEGG, and GSEA identified ALG8-related pathways, validated by biochemical assays.

RESULTS

In bioinformatics analyses, ALG8 was overexpressed in HCC tissues (p < 0.05 for all comparisons) and correlated with poorer survival (p = 0.006 and p = 0.025, respectively), establishing its role as an independent prognostic factor. In vitro experiments showed that knockdown of ALG8 reduced HCC cell proliferation, migration, and invasion. Using the STRING platform and TCGA-LIHC dataset, we identified ALG8-interacting genes and their associated differentially expressed genes (DEGs). GO and KEGG analyses further linked ALG8 to genes involved in glycosylation, signal release, and other processes, as well as pathways including neuroactive ligand-receptor interaction and N-Glycan biosynthesis. GSEA, corroborated by western blot and immunofluorescence, points to the Wnt/β-catenin signaling cascade as a probable mechanistic pathway through which ALG8 may modulate HCC progression.

CONCLUSION

Elevated ALG8 expression in HCC is linked to worse outcomes and increased tumor aggressiveness, with silencing ALG8 reducing Wnt/β-catenin signaling, highlighting ALG8 as a potential therapeutic target.

Deciphering the nexus between long non-coding RNAs and endoplasmic reticulum stress in hepatocellular carcinoma: biomarker discovery and therapeutic horizons

Hepatocellular carcinoma (HCC) remains a significant global health challenge with few effective treatment options. The dysregulation of endoplasmic reticulum (ER) stress responses has emerged as a pivotal factor in HCC progression and therapy resistance. Long non-coding RNAs (lncRNAs) play a crucial role as key epigenetic modifiers in this process. Recent research has explored how lncRNAs influence ER stress which in turn affects lncRNAs activity in HCC. We systematically analyze the current literature to highlight the regulatory roles of lncRNAs in modulating ER stress and vice versa in HCC. Our scrutinization highlights how dysregulated lncRNAs contribute to various facets of HCC, including apoptosis resistance, enhanced proliferation, invasion, and metastasis, all driven by ER stress. Moreover, we delve into the emerging paradigm of the lncRNA-miRNA-mRNA axis, elucidating it as the promising avenue for developing novel biomarkers and paving the way for more personalized treatment options in HCC. Nevertheless, we acknowledge the challenges and future directions in translating these insights into clinical practice. In conclusion, our review provides insights into the complex regulatory mechanisms governing ER stress modulation by lncRNAs in HCC.

LncRNA ZFAS1 regulates ATIC transcription and promotes the proliferation and migration of hepatocellular carcinoma through the PI3K/AKT signaling pathway

PURPOSE

Long noncoding RNAs (lncRNAs) exert a significant influence on various cancer-related processes through their intricate interactions with RNAs. Among these, lncRNA ZFAS1 has been implicated in oncogenic roles in multiple cancer types. Nevertheless, the intricate biological significance and underlying mechanism of ZFAS1 in the initiation and progression of hepatocellular carcinoma (HCC) remain largely unexplored.

METHODS

Analysis of The Cancer Genome Atlas Program (TCGA) database revealed a notable upregulation of lncRNA ZFAS1 in HCC tissues. To explore its function, we investigated colony formation and performed CCK-8 assays to gauge cellular proliferation and wound healing, Transwell assays to assess cellular migration, and an in vivo study employing a nude mouse model to scrutinize tumor growth and metastasis. Luciferase reporter assay was used to confirm the implicated interactions. Rescue experiments were conducted to unravel the plausible mechanism underlying the activation of the PI3K/AKT pathway by lncRNAs ZFAS1 and ATIC.

RESULTS

ZFAS1 and ATIC were significantly upregulated in the HCC tissues and cells. ZFAS1 knockdown inhibited cell proliferation and migration. We observed a direct interaction between the lncRNA ZFAS1 and ATIC. ATIC knockdown also suppressed cell proliferation and migration. SC79, an activator of AKT, partially restores the effects of lncRNA ZFAS1/ATIC knockdown on cell proliferation and migration. Knockdown of lncRNA ZFAS1/ATIC inhibited tumor growth and lung metastasis in vivo.

CONCLUSION

Overall, lncRNA ZFAS1 regulates ATIC transcription and contributes to the growth and migration of HCC cells through the PI3K/AKT signaling pathway.

Identification of important modules and biomarkers in tuberculosis based on WGCNA

Background

Tuberculosis (TB) is a significant public health concern, particularly in China. Long noncoding RNAs (lncRNAs) can provide abundant pathological information regarding etiology and could include candidate biomarkers for diagnosis of TB. However, data regarding lncRNA expression profiles and specific lncRNAs associated with TB are limited.

Methods

We performed ceRNA-microarray analysis to determine the expression profile of lncRNAs in peripheral blood mononuclear cells (PBMCs). Weighted gene co-expression network analysis (WGCNA) was then conducted to identify the critical module and genes associated with TB. Other bioinformatics analyses, including Kyoto Encyclopedia of Genes and Genomes (KEGG), Gene Ontology (GO), and co-expression networks, were conducted to explore the function of the critical module. Finally, real-time quantitative polymerase chain reaction (qPCR) was used to validate the candidate biomarkers, and receiver operating characteristic analysis was used to assess the diagnostic performance of the candidate biomarkers.

Results

Based on 8 TB patients and 9 healthy controls (HCs), a total of 1,372 differentially expressed lncRNAs were identified, including 738 upregulated lncRNAs and 634 downregulated lncRNAs. Among all lncRNAs and mRNAs in the microarray, the top 25% lncRNAs (3729) and top 25% mRNAs (2824), which exhibited higher median expression values, were incorporated into the WGCNA. The analysis generated 16 co-expression modules, among which the blue module was highly correlated with TB. GO and KEGG analyses showed that the blue module was significantly enriched in infection and immunity. Subsequently, considering module membership values (>0.85), gene significance values (>0.90) and fold-change value (>2 or < 0.5) as selection criteria, the top 10 upregulated lncRNAs and top 10 downregulated lncRNAs in the blue module were considered as potential biomarkers. The candidates were then validated in an independent validation sample set (31 TB patients and 32 HCs). The expression levels of 8 candidates differed significantly between TB patients and HCs. The lncRNAs ABHD17B (area under the curve [AUC] = 1.000) and ENST00000607464.1 (AUC = 1.000) were the best lncRNAs in distinguishing TB patients from HCs.

Conclusion

This study characterized the lncRNA profiles of TB patients and identified a significant module associated with TB as well as novel potential biomarkers for TB diagnosis.

Expression profile of microRNAs in patients with decompensated cirrhosis by small RNA deep sequencing

INTRODUCTION AND OBJECTIVE

Decompensated cirrhosis (DCC) is a more advanced stage of liver cirrhosis (LC). It is important to identify biomarkers to predict DCC progression. The aim of this study was to analyze microRNA (miRNA) profiles of whole blood involved in the DCC process to gain a better understanding of the molecular mechanisms underlying its development.

MATERIALS AND METHODS

RNA-Seq analysis of blood samples from a discovery set, including four DCC patients and four LC individuals, was performed to identify differentially expressed miRNAs. The selected differentially expressed miRNAs were validated by using an independent validation set.

RESULTS

In this study, a total of 1,036 miRNAs were identified in whole blood samples. Forty differentially expressed miRNAs were identified, including 24 upregulated and 16 downregulated miRNAs. The expression levels of three upregulated miRNAs (hsa-miR-20b-5p, hsa-miR-421, and hsa-miR-1307-3p) and two downregulated miRNAs (hsa-miR-139-5p and hsa-miR-150-5p) were validated by quantitative reverse transcriptase polymerase chain reaction. The receiver operator characteristic curve for the logistic regression model based on hsa-miR-20b-5p, hsa-miR-421, and hsa-miR-150-5p could distinguish DCC patients with excellent diagnostic accuracy (area under the curve: 0.981, p < 0.01).

CONCLUSION

The miRNA expression profiles in patients with DCC and LC controls suggested that miR-20b-5p, miR-421, and miR-150-5p could be potential biomarkers and therapeutic targets for this condition.

Diagnostic role and immune correlates of programmed cell death-related genes in hepatocellular carcinoma

Programmed cell death (PCD) is thought to have multiple roles in tumors. Here, the roles of PCD-related genes were comprehensively analyzed to evaluate their values in hepatocellular carcinoma (HCC) diagnosis and prognosis. Gene expression and single-cell data of HCC patients, and PCD-related genes were collected from public databases. The diagnostic and prognostic roles of differentially expressed PCD-related genes in HCC were explored by univariate and multivariate Cox regression analyses. Single-cell data were further analyzed for the immune cells and expression of feature genes. Finally, we evaluated the expression of genes by quantitative real-time polymerase chain reaction and Western blot, and the proportion of immune cells was detected by flow cytometry in HCC samples. We obtained 52 differentially expressed PCD-related genes in HCC, based on which the consensus clustering analysis cluster 2 was found to have a worse prognosis than cluster 1. Then 10 feature genes were identified using LASSO analysis, and programmed cell death index (PCDI) was calculated to divided HCC patients into high-PCDI and low-PCDI groups. Worse prognosis was observed in high-PCDI group. Cox regression analysis showed that PCDI is an independent prognostic risk factor for HCC patients. Additionally, SERPINE1 and G6PD of feature genes significantly affect patient survival. Macrophages and Tregs were significantly positively correlated with PCDI. G6PD mainly expressed in macrophages, SERPINE1 mainly expressed in fibroblast. The experimental results confirmed the high expression of SERPINE1 and G6PD in HCC compared with the control, and the infiltration level of macrophages and Treg in HCC was also obviously elevated. PCDI may be a new predictor for the diagnosis of patients with HCC. The association of SERPINE1 and G6PD with the immune environment will provide new clues for HCC therapy.

[Mechanism Research of lncRNA miR143HG on Regulating the Biological Behavior of Lung Squamous Cell Carcinoma H520 Cells]

BACKGROUND

There is a high morbidity, mortality, and poor clinical prognosis of lung squamous cell carcinoma (LUSC). However, there is currently no effective targeted treatment plan for LUSC. As a long non-coding RNA (lncRNA), lncRNA miR143HG has been proven to play an important role in the occurrence and development of various tumors. However, the biological role played by lncRNA miR143HG in LUSC cells is still unclear. Therefore, this study aimed to investigate the mechanism of lncRNA miR143HG on regulating the biological behavior of LUSC H520 cells.

METHODS

Pan-cancer analysis and differential expression analysis of lncRNA miR143HG were performed based on The Cancer Genome Atlas (TCGA) database. The predictive effect of lncRNA miR143HG on the diagnosis and prognosis of LUSC was evaluated by adopting the receiver operating characteristic (ROC) curve and timeROC curve. The enrichment degree of each pathway to lncRNA miR143HG was determined. The expression of lncRNA miR143HG and miR-155 in BEAS-2B cells and H520 cells was detected using quantitative real-time polymerase chain reaction (qRT-PCR). H520 cells were randomly divided into blank control group (without any treatment), negative control group (transfected with lncRNA-NC), lncRNA miR143HG group (transfected with lncRNA miR143HG), and lncRNA miR143HG+miR-155 group (co-transfected with lncRNA miR143HG and miR-155). The approaches of CCK-8, wound healing test, Transwell assay, flow cytometry, qRT-PCR, and Western blot were respectively employed to detect the cell proliferation ability, cell migration ability, cell invasion ability, cell apoptosis rate, and expression level of related genes and proteins of the Wnt/β-Catenin pathway.

RESULTS

The results of pan-cancer analysis and differential analysis collectively showed that except for renal clear cell carcinoma, the expression of lncRNA miR143HG in other cancer tissues was higher than that in healthy tissues, and the differences were significant in LUSC. The evaluation results of the ROC curve and timeROC curve suggested that lncRNA miR143HG was of great significance in the prediction of diagnosis and prognosis of LUSC. The pathways enriched in high expression of lncRNA miR143HG mainly included focal adhesion, vascular smooth muscle contraction, calcium signaling pathways, and so on; the pathways enriched in the low expression of lncRNA miR143HG embraced oxidative phosphorylation, cell cycle, basic transcription factors, etc. The qRT-PCR results showed that lncRNA miR143HG was low expressed but miR-155 was highly expressed in H520 cells when compared to BEAS-2B cells (P<0.05). Compared with the negative control group, the expression levels of the gene of lncRNA miR143HG, the gene and protein of Wnt, as well as the gene and protein of β-Catenin were significantly increased, while the gene expression of miR-155, the ability of cell proliferation, cell migration, and cell invasion were significantly reduced, but the cell apoptosis rate was dominantly elevated in cells of lncRNA miR143HG group (P<0.05). In addition, compared with the lncRNA miR143HG group, overexpression of miR-155 could reverse the biological behavior mediated by lncRNA miR143HG, and the difference was statistically significant (P<0.05).

CONCLUSIONS

LncRNA miR143HG was of great significance for the biological behavior of H520 cells. LncRNA miR143HG inhibited the ability of proliferation, migration, and invasion, as well as enhanced the apoptosis of H520 cells by downregulating miR-155 expression, which may be related to the Wnt/β-Catenin pathway.
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Identification of subclusters and prognostic genes based on glycolysis/gluconeogenesis in hepatocellular carcinoma

Background

This study aimed to examine glycolysis/gluconeogenesis-related genes in hepatocellular carcinoma (HCC) and evaluate their potential roles in HCC progression and immunotherapy response.

Methods

Data analyzed in this study were collected from GSE14520, GSE76427, GSE174570, The Cancer Genome Atlas (TCGA), PXD006512, and GSE149614 datasets, metabolic pathways were collected from MSigDB database. Differentially expressed genes (DEGs) were identified between HCC and controls. Differentially expressed glycolysis/gluconeogenesis-related genes (candidate genes) were obtained and consensus clustering was performed based on the expression of candidate genes. Bioinformatics analysis was used to evaluate candidate genes and screen prognostic genes. Finally, the key results were tested in HCC patients.

Results

Thirteen differentially expressed glycolysis/gluconeogenesis-related genes were validated in additional datasets. Consensus clustering analysis identified two distinct patient clusters (C1 and C2) with different prognoses and immune microenvironments. Immune score and tumor purity were significantly higher in C1 than in C2, and CD4+ memory activated T cell, Tfh, Tregs, and macrophage M0 were higher infiltrated in HCC and C1 group. The study also identified five intersecting DEGs from candidate genes in TCGA, GSE14520, and GSE141198 as prognostic genes, which had a protective role in HCC patient prognosis. Compared with the control group, the prognostic genes all showed decreased expression in HCC patients in RT-qPCR and Western blot analyses. Flow cytometry verified the abnormal infiltration level of immune cells in HCC patients.

Conclusion

Results showed that glycolysis/gluconeogenesis-related genes were associated with patient prognosis, immune microenvironment, and response to immunotherapy in HCC. It suggests that the model based on five prognostic genes may valuable for predicting the prognosis and immunotherapy response of HCC patients.