DEAD-box Helicase 27 Promotes Hepatocellular Carcinoma Progression Through ERK Signaling

DDX27 regulates oral squamous cell carcinoma development through targeting CSE1L

THE HEADINGS AIMS

DEAD-box helicase 27 (DDX27), a member of the DEAD-Box nucleic acid helicase family, holds an elusive role in oral squamous cell carcinoma (OSCC). This study aims to unravel the regulatory functions of DDX27 in OSCC and explore its downstream targets.

MATERIALS AND METHODS

A commercial oral squamous cell carcinoma (OSCC) tissue microarray (TMA) was utilized. We analyzed differentially expressed genes in OSCC through the GEO database. Target gene silencing was achieved using the shRNA-mediated lentivirus method. Coexpedia analysis identified co-expressed genes associated with DDX27. Additionally, a Co-Immunoprecipitation (Co-IP) experiment confirmed the protein interaction between DDX27 and CSE1L. Xenograft tumor models were employed to evaluate DDX27's role in OSCC tumor formation.

KEY FINDINGS

Elevated DDX27 expression in OSCC correlated with a higher pathological grade. DDX27 knockdown resulted in decreased cell proliferation, increased apoptosis, inhibited cell migration, and induced G2/M phase cell cycle arrest, as well as impaired tumor outgrowth. Coexpedia analysis identified STAU1, NELFCD, and CSE1L as top co-expressed genes. Lentiviral vectors targeting STAU1, NELFCD, and CSE1L revealed that silencing CSE1L significantly impaired cell growth, indicating it as a downstream target of DDX27. Cell rescue experiments demonstrated that increased DDX27 levels ameliorated cell proliferation, attenuated apoptosis, and CSE1L depletion blocked cell development induced by DDX27 overexpression.

SIGNIFICANCES

This study highlighted DDX27 as a potential therapeutic target for OSCC treatment, shedding light on its crucial role in OSCC development. Targeting DDX27 or its downstream effector, CSE1L, holds promise for innovative OSCC therapies.

Role and therapeutic potential of DEAD-box RNA helicase family in colorectal cancer

Colorectal cancer (CRC) is the third most commonly diagnosed and the second cancer-related death worldwide, leading to more than 0.9 million deaths every year. Unfortunately, this disease is changing rapidly to a younger age, and in a more advanced stage when diagnosed. The DEAD-box RNA helicase proteins are the largest family of RNA helicases so far. They regulate almost every aspect of RNA physiological processes, including RNA transcription, editing, splicing and transport. Aberrant expression and critical roles of the DEAD-box RNA helicase proteins have been found in CRC. In this review, we first summarize the protein structure, cellular distribution, and diverse biological functions of DEAD-box RNA helicases. Then, we discuss the distinct roles of DEAD-box RNA helicase family in CRC and describe the cellular mechanism of actions based on recent studies, with an aim to provide future strategies for the treatment of CRC.

Synthetic lethal interactions of DEAD/H-box helicases as targets for cancer therapy

DEAD/H-box helicases are implicated in virtually every aspect of RNA metabolism, including transcription, pre-mRNA splicing, ribosomes biogenesis, nuclear export, translation initiation, RNA degradation, and mRNA editing. Most of these helicases are upregulated in various cancers and mutations in some of them are associated with several malignancies. Lately, synthetic lethality (SL) and synthetic dosage lethality (SDL) approaches, where genetic interactions of cancer-related genes are exploited as therapeutic targets, are emerging as a leading area of cancer research. Several DEAD/H-box helicases, including DDX3, DDX9 (Dbp9), DDX10 (Dbp4), DDX11 (ChlR1), and DDX41 (Sacy-1), have been subjected to SL analyses in humans and different model organisms. It remains to be explored whether SDL can be utilized to identity druggable targets in DEAD/H-box helicase overexpressing cancers. In this review, we analyze gene expression data of a subset of DEAD/H-box helicases in multiple cancer types and discuss how their SL/SDL interactions can be used for therapeutic purposes. We also summarize the latest developments in clinical applications, apart from discussing some of the challenges in drug discovery in the context of targeting DEAD/H-box helicases.

DDX24 regulates the chemosensitivity of hepatocellular carcinoma to sorafenib via mediating the expression of SNORA18

Sorafenib (SFN) is a multi-kinase inhibitor drug for the treatment of advanced hepatocellular carcinoma (HCC), but its limited efficacy is a major obstacle to the clinical outcomes of patients with HCC. We aimed to explore a novel molecular mechanism underlying the chemosensitivity of HCC to SFN, and to identify a promising therapeutic target for HCC treatment. In this study, bioinformatic analysis revealed that DDX24 was associated with poor survival in HCC cases, and significantly related to the pathways modulating tumor development. DDX24 regulated HCC cell proliferation and migration potentials. Moreover, reduction of DDX24 promoted the sorafenib-mediated inhibition of HCC cell growth and migration, the elevation of sorafenib-induced HCC cell apoptosis. DDX24 overexpression suppressed the inhibitory effect of SFN on cell proliferation and migration and reduced the apoptosis induced by SFN. Further, DDX24, combined with SFN treatment, presented a synergistic enhancement of the sensitivity of SFN to the growth and migration of HCC cells via AKT/ERK and the epithelial-mesenchymal transition (EMT) pathways, and that it modulated apoptosis via the caspase/PARP pathway. Mechanistically, SNORA18 served as a target gene for DDX24, regulating the chemosensitivity of sorafenib-treated HCC cells. Furthermore, SNORA18 knockdown or overexpression could partially reverse the inhibition or elevation of cell viability, colony formation and migration induced by DDX24 in sorafenib-treated HCC cells, respectively. Collectively, our results suggest that DDX24 regulates the chemosensitivity of HCC to SFN by mediating the expression of SNORA18, which may act as an effective therapeutic target for improving SFN efficiency in HCC treatment.

Integration of three machine learning algorithms identifies characteristic RNA binding proteins linked with diagnosis, immunity and pyroptosis of IgA nephropathy

Objective: RNA-binding proteins (RBPs) are essential for most post-transcriptional regulatory events, which exert critical roles in nearly all aspects of cell biology. Here, characteristic RBPs of IgA nephropathy were determined with multiple machine learning algorithms.

Methods: Our study included three gene expression datasets of IgA nephropathy (GSE37460, GSE73953, GSE93798). Differential expression of RBPs between IgA nephropathy and normal samples was analyzed via limma, and hub RBPs were determined through MCODE. Afterwards, three machine learning algorithms (LASSO, SVM-RFE, random forest) were integrated to determine characteristic RBPs, which were verified in the Nephroseq database. Immune cell infiltrations were estimated through CIBERSORT. Utilizing ConsensusClusterPlus, IgA nephropathy were classified based on hub RBPs. The potential upstream miRNAs were predicted.

Results: Among 388 RBPs with differential expression, 43 hub RBPs were determined. After integration of three machine learning algorithms, three characteristic RBPs were finally identified (DDX27, RCL1, and TFB2M). All of them were down-regulated in IgA nephropathy than normal specimens, with the excellent diagnostic efficacy. Additionally, they were significantly linked to immune cell infiltrations, immune checkpoints, and pyroptosis-relevant genes. Based on hub RBPs, IgA nephropathy was stably classified as two subtypes (cluster 1 and 2). Cluster 1 exhibited the relatively high expression of pyroptosis-relevant genes and characteristic RBPs. MiR-501-3p, miR-760, miR-502-3p, miR-1224-5p, and miR-107 were potential upstream miRNAs of hub RBPs.

Conclusion: Collectively, our findings determine three characteristic RBPs in IgA nephropathy and two RBPs-based subtypes, and thus provide a certain basis for further research on the diagnosis and pathogenesis of IgA nephropathy.