DHX37 Impacts Prognosis of Hepatocellular Carcinoma and Lung Adenocarcinoma through Immune Infiltration

Potentials of ribosomopathy gene as pharmaceutical targets for cancer treatment

Ribosomopathies encompass a spectrum of disorders arising from impaired ribosome biogenesis and reduced functionality. Mutation or dysexpression of the genes that disturb any finely regulated steps of ribosome biogenesis can result in different types of ribosomopathies in clinic, collectively known as ribosomopathy genes. Emerging data suggest that ribosomopathy patients exhibit a significantly heightened susceptibility to cancer. Abnormal ribosome biogenesis and dysregulation of some ribosomopathy genes have also been found to be intimately associated with cancer development. The correlation between ribosome biogenesis or ribosomopathy and the development of malignancies has been well established. This work aims to review the recent advances in the research of ribosomopathy genes among human cancers and meanwhile, to excavate the potential role of these genes, which have not or rarely been reported in cancer, in the disease development across cancers. We plan to establish a theoretical framework between the ribosomopathy gene and cancer development, to further facilitate the potential of these genes as diagnostic biomarker as well as pharmaceutical targets for cancer treatment.

New insights into T-cell exhaustion in liver cancer: from mechanism to therapy

Liver cancer is one of the most common malignancies. T-cell exhaustion is associated with immunosuppression of tumor and chronic infection. Although immunotherapies that enhance the immune response by targeting programmed cell death-1(PD-1)/programmed cell death ligand 1 (PD-L1) have been applied to malignancies, these treatments have shown limited response rates. This suggested that additional inhibitory receptors (IRs) also contributed to T-cell exhaustion and tumor prognosis. Exhausted T-cells (Tex) in the tumor immune microenvironment (TME) are usually in a dysfunctional state of exhaustion, such as impaired activity and proliferative ability, increased apoptosis rate, and reduced production of effector cytokines. Tex cells participate in the negative regulation of tumor immunity mainly through IRs on the cell surface, changes in cytokines and immunomodulatory cell types, causing tumor immune escape. However, T-cell exhaustion is not irreversible and targeted immune checkpoint inhibitors (ICIs) can effectively reverse the exhaustion of T-cells and restore the anti-tumor immune response. Therefore, the research on the mechanism of T-cell exhaustion in liver cancer, aimed at maintaining or restoring the effector function of Tex cells, might provide a new method for the treatment of liver cancer. In this review, we summarized the basic characteristics of Tex cells (such as IRs and cytokines), discussed the mechanisms associated with T-cell exhaustion, and specifically discussed how these exhaustion characteristics were acquired and shaped by key factors within TME. Then new insights into the molecular mechanism of T-cell exhaustion suggested a potential way to improve the efficacy of cancer immunotherapy, namely to restore the effector function of Tex cells. In addition, we also reviewed the research progress of T-cell exhaustion in recent years and provided suggestions for further research.

Fungi composition in settled dust associated with fractional exhaled nitric oxide in school children with asthma

Fungi exposure has been significantly linked to respiratory illness. However, numerous fungi taxa that are potentially allergenic still undocumented and leave a barrier to establishing a clear connection between exposure and health risks. This study aimed to evaluate the association of fungi composition in settled dust with fractional exhaled nitric oxide (FeNO) levels among school children with doctor-diagnosed asthma. A cross-sectional study was undertaken among secondary school students in eight schools in the urban area of Hulu Langat, Selangor, Malaysia. A total of 470 school children (aged 14 years old) were randomly selected and their FeNO levels were measured and allergic skin prick tests were conducted. The settled dust samples were collected and analysed by using metagenomic technique to determine the fungi composition. The general linear regression with complex sampling was employed to determine the interrelationship. In total, 2645 fungal operational taxonomic units (OTUs) were characterised from the sequencing process which belongs to Ascomycota (60.7 %), Basidiomycota (36.4 %), Glomeromycota (2.9 %) and Chytridiomycota (0.04 %). The top five mostly abundance in all dust samples were Aspergillus clavatus (27.2 %), followed by Hyphoderma multicystidium (12.2 %), Verrucoconiothyrium prosopidis (9.4 %), Ganoderma tuberculosum (9.2 %), and Heterochaete shearii (7.2 %). The regression results indicated that A. clavatus, Brycekendrickomyces acaciae, Candida parapsilosis, Hazslinszkyomyces aloes, H. multicystidium, H. shearii, Starmerella meliponinorum, V. prosopidis were associated in increased of FeNO levels among the asthmatic group at 0.992 ppb (95 % CI = 0.34-1.68), 2.887 ppb (95 % CI = 2.09-3.76), 0.809 ppb (95 % CI = 0.14-1.49), 0.647 ppb (95 % CI = 0.36-0.94), 1.442 ppb (95 % CI = 0.29-2.61), 1.757 ppb (95 % CI = 0.59-2.87), 1.092 ppb (95 % CI = 0.43-1.75) and 1.088 ppb (95 % CI = 0.51-1.62), respectively. To our knowledge, this is a new finding. The findings pointed out that metagenomics profiling of fungi could enhance our understanding of a complex interrelation between rare and unculturable fungi with airway inflammation.

Machine Learning Screens Potential Drugs Targeting a Prognostic Gene Signature Associated With Proliferation in Hepatocellular Carcinoma

Background: This study aimed to screen potential drugs targeting a new prognostic gene signature associated with proliferation in hepatocellular carcinoma (HCC). Methods: CRISPR Library and TCGA datasets were used to explore differentially expressed genes (DEGs) related to the proliferation of HCC cells. Differential gene expression analysis, univariate COX regression analysis, random forest algorithm and multiple combinatorial screening were used to construct a prognostic gene signature. Then the predictive power of the gene signature was validated in the TCGA and ICGC datasets. Furthermore, potential drugs targeting this gene signature were screened. Results: A total of 640 DEGs related to HCC proliferation were identified. Using univariate Cox analysis and random forest algorithm, 10 hub genes were screened. Subsequently, using multiplex combinatorial screening, five hub genes (FARSB, NOP58, CCT4, DHX37 and YARS) were identified. Taking the median risk score as a cutoff value, HCC patients were divided into high- and low-risk groups. Kaplan-Meier analysis performed in the training set showed that the overall survival of the high-risk group was worse than that of the low-risk group (p < 0.001). The ROC curve showed a good predictive efficiency of the risk score (AUC > 0.699). The risk score was related to gene mutation, cancer cell stemness and immune function changes. Prediction of immunotherapy suggetsted the IC50s of immune checkpoint inhibitors including A-443654, ABT-888, AG-014699, ATRA, AUY-922, and AZ-628 in the high-risk group were lower than those in the low-risk group, while the IC50s of AMG-706, A-770041, AICAR, AKT inhibitor VIII, Axitinib, and AZD-0530 in the high-risk group were higher than those in the low-risk group. Drug sensitivity analysis indicated that FARSB was positively correlated with Hydroxyurea, Vorinostat, Nelarabine, and Lomustine, while negatively correlated with JNJ-42756493. DHX37 was positively correlated with Raltitrexed, Cytarabine, Cisplatin, Tiotepa, and Triethylene Melamine. YARS was positively correlated with Axitinib, Fluphenazine and Megestrol acetate. NOP58 was positively correlated with Vorinostat and 6-thioguanine. CCT4 was positively correlated with Nerabine. Conclusion: The five-gene signature associated with proliferation can be used for survival prediction and risk stratification for HCC patients. Potential drugs targeting this gene signature deserve further attention in the treatment of HCC.

RNA Helicase DHX37 Facilitates Liver Cancer Progression by Cooperating with PLRG1 to Drive Superenhancer-Mediated Transcription of Cyclin D1

RNA helicases are dysregulated in tumors. Here, we identified DHX37 as one of the top RNA helicase genes with upregulated expression in hepatocellular carcinoma (HCC). DHX37 promoted proliferation of liver cancer cells in vitro and in vivo. Epigenomic profiling of DHX37-knockdown and control HCC cells revealed that DHX37 is associated with superenhancer activity. Mechanistically, DHX37 interacted with pleiotropic regulator 1 (PLRG1) to transcriptionally activate cyclin D1 (CCND1) expression via co-occupation of its promoter and superenhancer elements. DHX37 and PLRG1 promoted liver cancer cell proliferation and contributed to the poor prognosis of patients with HCC. Importantly, CCND1 inhibitors were effective as antiproliferative agents for liver cancer. These results together demonstrate a cooperative mechanistic interaction between DHX37 and PLRG1 that regulates CCND1 expression and promotes liver cancer progression, advancing our understanding of the epigenetic and transcriptional dysregulations mediated by RNA helicases and superenhancers in HCC.

SIGNIFICANCE

This work characterizes a novel mechanism of superenhancer-driven cyclin D1 upregulation by DHX37 and PLRG1, implicating this pathway as a potential therapeutic target in hepatocellular carcinoma.

ATIC facilitates cell growth and migration by upregulating Myc expression in lung adenocarcinoma

5-Aminoimidazole-4-carboxamide ribonucleotide formyltransferase/IMP cyclohydrolase (ATIC), a catalysing enzyme in the de novo purine biosynthetic pathway, has been previously reported to be upregulated and to participate in myeloma and hepatocellular carcinoma progression. In the present study, by using bioinformatics technology, a higher ATIC expression was identified in lung adenocarcinoma (LUAD) tissues than in normal tissues, and ATIC expression was found to be positively associated with Myc expression in LUAD tissues. In addition, the role of ATIC in modulating the growth and migration of LUAD cells was explored and the involvement of Myc was revealed. ATIC expression in 56 paired LUAD and tumour adjacent non-cancerous tissues was assessed using reverse transcription-quantitative PCR and western blot analysis. Pearson's correlation analysis was applied to evaluate the correlation between ATIC and Myc expression levels in LUAD tissues. A rescue experiment was performed to explore the role of ATIC/Myc in regulating the growth, migration and invasion of HCC827 and NCI-H1435 cells. It was demonstrated that ATIC was overexpressed in LUAD tissues, particularly in advanced-stage LUAD, and was predicted to be associated with an advanced TNM stage, a higher lymph node metastasis rate, poor tissue differentiation and a lower overall survival rate. ATIC overexpression promoted cell growth, migratory and invasive capacities, whereas this effect was abrogated by Myc knockdown in the HCC827 and NCI-H1435 cells. On the whole, the present study demonstrates that ATIC promotes LUAD cell growth and migration by increasing Myc expression.

Construction of an immune-related lncRNA signature as a novel prognosis biomarker for LUAD

The tumor immune microenvironment of lung cancer is associated with prognosis and immunotherapy efficacy. Long noncoding RNAs are identified as prognostic biomarkers associated with immune functions. We constructed a signature comprising differentially expressed immune-related lncRNAs to predict the prognosis of patients with lung adenocarcinoma. We established the immune-related lncRNA signature by pairing immune-related lncRNAs regardless of expression level and lung adenocarcinoma patients were divided into high- and low-risk groups. The prognosis of patients in the two groups was significantly different; The immune-related lncRNA signature could serve as an independent lung adenocarcinoma prognostic indicator. The signature correlated negatively with B cell, CD4+ T cell, M2 macrophage, neutrophil, and monocyte immune infiltration. Patients with low risk scores had a higher abundance of immune cells and stromal cells around the tumor. Gene set enrichment analysis showed that samples from low-risk group were more active in the IgA production in intestinal immune network and the T and B cell receptor signaling pathway. High-risk groups had significant involvement of the cell cycle, DNA replication, adherens junction, actin cytoskeleton regulation, pathways in cancer, and TGF-β signaling pathways. High risk scores correlated significantly negatively with high CTLA-4 and HAVCR2 expression and higher median inhibitory concentration of common anti-tumor chemotherapeutics (e.g., cisplatin, paclitaxel, gemcitabine) and targeted therapy (e.g., erlotinib and gefitinib). We identified a reliable immune-related lncRNA lung adenocarcinoma prognosis model, and the immune-related lncRNA signature showed promising clinical prediction value.

Identification of P2RY13 as an immune-related prognostic biomarker in lung adenocarcinoma: A public database-based retrospective study

Background

Lung adenocarcinoma (LUAD) is the leading histological subtype of non-small cell lung cancer (NSCLC).

Methods

In the present study, the gene matrixes of LUAD were downloaded from The Cancer Genome Atlas to infer immune and stromal scores with the ‘Estimation of Stromal and Immune cells in Malignant Tumor tissues using Expression data’ (ESTIMATE) algorithm and identified immune-related differentially expressed genes (DEGs) between the high- and low-stromal/immune score groups. Next, all DEGs were subjected to univariate Cox regression and survival analyses to screen out prognostic biomarkers in the tumor microenvironment (TME), and were validated in the Gene Expression Omnibus database. Single-sample gene set enrichment analysis (ssGSEA) was performed to assess the level of tumor-infiltrating immune cells (TIICs) and immune functions, and GSEA was used to identified pathways altered by prognostic biomarkers.

Results

Survival analysis showed that LUAD in the high-immune and stromal score group had a better clinical prognosis. A total of 303 immune-related DEGs were detected. Univariate Cox regression and survival analyses revealed that P2Y purinoceptor 13 (P2RY13) was a favorable factor for the prognosis of LUAD. ssGSEA and Spearman correlation analysis demonstrated that P2RY13 was highly correlated with various TIICs and immune functions. Several immune-associated pathways were enriched between the high- and low-expression P2RY13 groups.

Conclusion

P2RY13 may be a potential prognostic indicator and is highly associated with the TME in LUAD. However, further experimental studies are required to validate the present findings.