DDX41 regulates the expression and alternative splicing of genes involved in tumorigenesis and immune response

DDX41: exploring the roles of a versatile helicase

DDX41 is a DEAD-box helicase and is conserved across species. Mutations in DDX41 have been associated with myeloid neoplasms, including myelodysplastic syndrome and acute myeloid leukemia. Though its pathogenesis is not completely known, DDX41 has been shown to have many cellular roles, including in pre-mRNA splicing, innate immune sensing, ribosome biogenesis, translational regulation, and R-loop metabolism. In this review, we will summarize the latest understandings regarding the various roles of DDX41, as well as highlight challenges associated with drug development to target DDX41. Overall, understanding the molecular and cellular mechanisms of DDX41 could help develop novel therapeutic options for DDX41 mutation-related hematologic malignancies.

R-Loops in Genome Instability and Cancer

R-loops are unique, three-stranded nucleic acid structures that primarily form when an RNA molecule displaces one DNA strand and anneals to the complementary DNA strand in a double-stranded DNA molecule. R-loop formation can occur during natural processes, such as transcription, in which the nascent RNA molecule remains hybridized with the template DNA strand, while the non-template DNA strand is displaced. However, R-loops can also arise due to many non-natural processes, including DNA damage, dysregulation of RNA degradation pathways, and defects in RNA processing. Despite their prevalence throughout the whole genome, R-loops are predominantly found in actively transcribed gene regions, enabling R-loops to serve seemingly controversial roles. On one hand, the pathological accumulation of R-loops contributes to genome instability, a hallmark of cancer development that plays a role in tumorigenesis, cancer progression, and therapeutic resistance. On the other hand, R-loops play critical roles in regulating essential processes, such as gene expression, chromatin organization, class-switch recombination, mitochondrial DNA replication, and DNA repair. In this review, we summarize discoveries related to the formation, suppression, and removal of R-loops and their influence on genome instability, DNA repair, and oncogenic events. We have also discussed therapeutical opportunities by targeting pathological R-loops.

Germline and somatic drivers in inherited hematologic malignancies

Inherited hematologic malignancies are linked to a heterogenous group of genes, knowledge of which is rapidly expanding using panel-based next-generation sequencing (NGS) or whole-exome/whole-genome sequencing. Importantly, the penetrance for these syndromes is incomplete, and disease development, progression or transformation has critical clinical implications. With the earlier detection of healthy carriers and sequential monitoring of these patients, clonal hematopoiesis and somatic driver variants become significant factors in determining disease transformation/progression and timing of (preemptive) hematopoietic stem cell transplant in these patients. In this review, we shed light on the detection of probable germline predisposition alleles based on diagnostic/prognostic 'somatic' NGS panels. A multi-tier approach including variant allele frequency, bi-allelic inactivation, persistence of a variant upon clinical remission and mutational burden can indicate variants with high pre-test probability. We also discuss the shared underlying biology and frequency of germline and somatic variants affecting the same gene, specifically focusing on variants in DDX41, ETV6, GATA2 and RUNX1. Germline variants in these genes are associated with a (specific) pattern or over-/underrepresentation of somatic molecular or cytogenetic alterations that may help identify the underlying germline syndrome and predict the course of disease in these individuals. This review is based on the current knowledge about somatic drivers in these four syndromes by integrating data from all published patients, thereby providing clinicians with valuable and concise information.

Chromatin-Accessible miRNA Regulons Driving Thyroid Tumorigenesis and Progression

BACKGROUND

Although papillary thyroid cancer can remain indolent, associated lymph node metastases and recurrence rates are approximately 50% and 20%, respectively. Omics-based medicine has led to the discovery of predictive biomarkers that can be used to predict tumor progression and clinical outcomes. We aimed to develop a noninvasive omics-driven blood test to allow accurate risk stratification and help tailor individual patient treatment plans.

STUDY DESIGN

RNA sequencing (seq) and microRNA analysis of The Cancer Genome Atlas and Gene Expression Omnibus datasets were employed to identify an epigenetic prognostic panel. Integrated bulk assay for transposase-accessible chromatin-seq and RNA-seq experiments confirmed the results. Sixty-two paired tumor and adjacent control thyroid tissues and 67 blood samples (62 papillary thyroid cancer and 5 controls) were analyzed for validation using sequencing and real-time polymerase chain reaction and correlated to clinical outcomes. A liposome-exosome fusion clustered regularly interspaced short palindromic repeats (CRISPR)-fluorescent detection system miRNA assay was developed. A predictive risk nomogram was generated and tested for performance.

RESULTS

Our miRNA panel (miR-146b-5p and miR-221-3p) from tissue and blood was associated with aggressive features and was located within accessible chromatin regions. The miRNA risk score and prognostic nomogram showed higher accuracy in predicting lymph node metastases (miR-146b: area under the curve [AUC] 0.816, sensitivity 76.9%; miR-221: AUC 0.740, sensitivity 79.5%) and recurrence (miR-146b: AUC 0.921, sensitivity 75.0%; miR-221: AUC 0.756, sensitivity 70.0%; p < 0.001) than staging and American Thyroid Association risk stratification. CRISPR-based miRNA assays showed upregulation in the blood of cancer cohorts.

CONCLUSIONS

CRISPR-based detection of miR-146b and miR-221 in the blood of thyroid cancer patients is a reliable and noninvasive tool for real-time assessment and prognostication that has great potential to provide a direct impact on the care of these patients.

Investigating genes associated with heart failure, atrial fibrillation, and other cardiovascular diseases, and predicting disease using machine learning techniques for translational research and precision medicine

Cardiovascular disease (CVD) is the leading cause of mortality and loss of disability adjusted life years (DALYs) globally. CVDs like Heart Failure (HF) and Atrial Fibrillation (AF) are associated with physical effects on the heart muscles. As a result of the complex nature, progression, inherent genetic makeup, and heterogeneity of CVDs, personalized treatments are believed to be critical. Rightful application of artificial intelligence (AI) and machine learning (ML) approaches can lead to new insights into CVDs for providing better personalized treatments with predictive analysis and deep phenotyping. In this study we focused on implementing AI/ML techniques on RNA-seq driven gene-expression data to investigate genes associated with HF, AF, and other CVDs, and predict disease with high accuracy. The study involved generating RNA-seq data derived from the serum of consented CVD patients. Next, we processed the sequenced data using our RNA-seq pipeline and applied GVViZ for gene-disease data annotation and expression analysis. To achieve our research objectives, we developed a new Findable, Accessible, Intelligent, and Reproducible (FAIR) approach that includes a five-level biostatistical evaluation, primarily based on the Random Forest (RF) algorithm. During our AI/ML analysis, we have fitted, trained, and implemented our model to classify and distinguish high-risk CVD patients based on their age, gender, and race. With the successful execution of our model, we predicted the association of highly significant HF, AF, and other CVDs genes with demographic variables.

A study of the prognostic value of long non-coding RNA CASC15 in human solid tumors utilizing The Cancer Genome Atlas (TCGA) datasets and a meta-analysis

BACKGROUND AND AIMS

Several malignant solid tumors have been reported to have an abnormal expression of the long non-coding RNA CASC15 (lncRNA CASC15). However, the clinicopathologic and prognostic importance of CASC15 in solid tumors are unknown. As a result, we examined the interrelationship between CASC15, overall survival length, and clinicopathological attributes of cancers affecting humans by analyzing various studies and The Cancer Genome Atlas (TCGA) data related to CASC15 expression.

METHODS

Web of Science, PubMed, Cochrane Library, Embase, Chinese WanFang, and Chinese CNKI databases were used to conduct a literature search. Hazard ratios (HRs) and Pooled odds ratios (ORs) were calculated taking 95% confidence intervals (CIs). The results of the current meta-analysis were further validated using TCGA datasets.

RESULTS

A total of 12 eligible studies enrolling 767 patients were included in this meta-analysis. Findings of the analysis showed that CASC15 expression had a significant relation to the metastasis of lymph node (OR = 3.30, 95%CI = 1.88-5.81, p < 0.001), distant metastasis (OR = 2.64, 95%CI = 1.24-5.63, p = 0.012), and high TNM/clinical stage (OR = 2.67, 95%CI = 1.34-5.32, p = 0.005). Additionally, we found that a poor outcome for overall survival (OS) was predicted by an elevation in CASC15 expression (HR = 2.01, 95%CI = 1.71-2.36, p < 0.001). Further investigation of the TCGA dataset revealed that CASC15 had abnormal expression in many cancers, which at least partially validated the findings of the current meta-analysis.

CONCLUSIONS

According to the latest meta-analysis and systematic review, high expression levels of CASC15 are associated with poor survival outcomes for solid tumor patients, and the use of CASC15 as a solid tumor prognostic predictor has a solid theoretical foundation.

A miRNA-Based Prognostic Model to Trace Thyroid Cancer Recurrence

Simple Summary

Some thyroid tumors elected for surveillance remain indolent, while others progress. The mechanism responsible for this difference is poorly understood, making it challenging to devise patient surveillance plans. Early prediction is important for tailoring treatment and follow-up in high-risk patients. The aim of our study was to identify predictive markers for progression. We leveraged a highly sensitive test that accurately predicts which thyroid nodules are more likely to develop lymph node metastasis, thereby improving care and outcomes for cancer patients.

Abstract

Papillary thyroid carcinomas (PTCs) account for most endocrine tumors; however, screening and diagnosing the recurrence of PTC remains a clinical challenge. Using microRNA sequencing (miR-seq) to explore miRNA expression profiles in PTC tissues and adjacent normal tissues, we aimed to determine which miRNAs may be associated with PTC recurrence and metastasis. Public databases such as TCGA and GEO were utilized for data sourcing and external validation, respectively, and miR-seq results were validated using quantitative real-time PCR (qRT-PCR). We found miR-145 to be significantly downregulated in tumor tissues and blood. Deregulation was significantly related to clinicopathological features of PTC patients including tumor size, lymph node metastasis, TNM stage, and recurrence. In silico data analysis showed that miR-145 can negatively regulate multiple genes in the TC signaling pathway and was associated with cell apoptosis, proliferation, stem cell differentiation, angiogenesis, and metastasis. Taken together, the current study suggests that miR-145 may be a biomarker for PTC recurrence. Further mechanistic studies are required to uncover its cellular roles in this regard.

Walking a tightrope: The complex balancing act of R-loops in genome stability

Although transcription is an essential cellular process, it is paradoxically also a well-recognized cause of genomic instability. R-loops, non-B DNA structures formed when nascent RNA hybridizes to DNA to displace the non-template strand as single-stranded DNA (ssDNA), are partially responsible for this instability. Yet, recent work has begun to elucidate regulatory roles for R-loops in maintaining the genome. In this review, we discuss the cellular contexts in which R-loops contribute to genomic instability, particularly during DNA replication and double-strand break (DSB) repair. We also summarize the evidence that R-loops participate as an intermediate during repair and may influence pathway choice to preserve genomic integrity. Finally, we discuss the immunogenic potential of R-loops and highlight their links to disease should they become pathogenic.

DDX41 is needed for pre- and postnatal hematopoietic stem cell differentiation in mice

DDX41 is a tumor suppressor frequently mutated in human myeloid neoplasms, but whether it affects hematopoiesis is unknown. Using a knockout mouse, we demonstrate that DDX41 is required for mouse hematopoietic stem and progenitor cell (HSPC) survival and differentiation, particularly of myeloid lineage cells. Transplantation of Ddx41 knockout fetal liver and adult bone marrow (BM) cells was unable to rescue mice from lethal irradiation, and knockout stem cells were also defective in colony formation assays. RNA-seq analysis of Lin-/cKit+/Sca1+Ddx41 knockout cells from fetal liver demonstrated that the expression of many genes associated with hematopoietic differentiation were altered. Furthermore, differential splicing of genes involved in key biological processes was observed. Our data reveal a critical role for DDX41 in HSPC differentiation and myeloid progenitor development, likely through regulating gene expression programs and splicing.

HSPA6 is Correlated With the Malignant Progression and Immune Microenvironment of Gliomas

Gliomas are primary intracranial space lesions with a high mortality rate. Current treatments for glioma are very limited. Recently, immunotargeted therapy of the glioma microenvironment has been developed. Members of the 70 kDa heat shock protein (HSP70) family are involved in the development of many tumors and immunity. HSPA6 protein belongs to the HSP70 family; However, the biological function of this protein in gliomas has yet to be evaluated. In the present study, a range of analyses, involving protein networks, survival, clinical correlation, and function, revealed that the expression of HSPA6 was negatively correlated with clinical prognosis and closely associated with immunity, invasion, and angiogenesis. Quantitative protein analysis confirmed that HSPA6 was expressed at high levels in patients with glioblastoma. Vitro experiments further verified that HSPA6 enhanced the malignant progression of glioma cells by promoting proliferation, invasion and anti-apoptosis. We also found that HSPA6 was closely correlated with genomic variations and tumor microenvironment. Collectively, we demonstrated that HSPA6 may represent a new therapeutic target to improve the prognosis of patients with gliomas.

Identification of an Innate Immune-Related Prognostic Signature in Early-Stage Lung Squamous Cell Carcinoma

Background

Early-stage lung squamous cell carcinoma (LUSC) progression is accompanied by changes in immune microenvironments and the expression of immune-related genes (IRGs). Identifying innate IRGs associated with prognosis may improve treatment and reveal new immunotherapeutic targets.

Methods

Gene expression profiles and clinical data of early-stage LUSC patients were obtained from the Gene Expression Omnibus and The Cancer Genome Atlas databases and IRGs from the InnateDB database. Univariate and multivariate Cox regression and LASSO regression analyses were performed to identify an innate IRG signature model prognostic in patients with early-stage LUSC. The predictive ability of this model was assessed by time-dependent receiver operator characteristic curve analysis, with the independence of the model-determined risk score assessed by univariate and multivariate Cox regression analyses. Overall survival (OS) in early-stage LUSC patients was assessed using a nomogram and decision curve analysis (DCA). Functional and biological pathways were determined by gene set enrichment analysis, and differences in biological functions and immune microenvironments between the high- and low-risk groups were assessed by ESTIMATE and the CIBERSORT algorithm.

Results

A signature involving six IRGs (SREBF2, GP2, BMX, NR1H4, DDX41, and GOPC) was prognostic of OS. Samples were divided into high- and low-risk groups based on median risk scores. OS was significantly shorter in the high-risk than in the low-risk group in the training (P < 0.001), GEO validation (P = 0.00021) and TCGA validation (P = 0.034) cohorts. Multivariate Cox regression analysis showed that risk score was an independent risk factor for OS, with the combination of risk score and T stage being optimally predictive of clinical benefit. GSEA, ESTIMATE, and the CIBERSORT algorithm showed that immune cell infiltration was higher and immune-related pathways were more strongly expressed in the low-risk group.

Conclusion

A signature that includes these six innate IRGs may predict prognosis in patients with early-stage LUSC.

Relationship between HSPA1A-regulated gene expression and alternative splicing in mouse cardiomyocytes and cardiac hypertrophy

Background

Cardiac hypertrophy may be classified as either physiological or pathological. Pathological hypertrophy has a complex etiology and is genetically regulated. In this study, we used a mouse model of cardiac hypertrophy to explore the mechanisms of gene regulation, in particular, modulation of the expression of target genes through transcription factor activity, regulation of immune and inflammation-associated genes and regulation of the alternative splicing of transcription factors.

Methods

Mouse models of pathological cardiac hypertrophy were established by transverse aortic constriction (TAC). We overexpressed HSPA1A in mouse cardiac HL-1 cells. GO and KEGG pathway annotation database was used to analyze all DEGs.

Results

The expression of HSPA1A differed significantly between TAC + dantrolene vs. sham + dantrolene (Sham was the non-TAC group, and DMSO was the contrast agent), and TAC + DMSO vs. sham + DMSO. The RNA-binding protein Zfp36 was found to be differentially expressed between both TAC + dantrolene vs. sham + dantrolene and TAC + DMSO vs. sham + DMSO. The expression of mki67 and gm5619 was significantly different between TAC + dantrolene and TAC + DMSO. HSPA1A was found to selectively regulate the expression of non-coding RNAs related to cardiac hypertrophy, including Rn7sk and RMRP. The downregulated genes were mainly related to inflammation and the immune response. HSPA1A negatively regulated alternative splicing of Asxl2 and positively regulated alternative splicing of Runx1.

Conclusions

HSPA1A was closely related to cardiac hypertrophy. Zfp36 was also related to cardiac hypertrophy. Dantrolene may delay cardiac hypertrophy and ventricular remodeling by regulating the expression of the RNA-binding protein genes mki67 and gm5619. HSPA1A positively regulated the expression of the non-coding RNAs RN7SK and RMRP while negatively regulating the expression of inflammation- and immune response-related genes. HSPA1A can play a role in cardiac hypertrophy by regulating the alternative splicing of asxl2 and runx1.

Childhood Obesity-Related Mechanisms: MicroRNome and Transcriptome Changes in a Nested Case-Control Study

Childhood obesity could contribute to adulthood obesity, leading to adverse health outcomes in adults. However, the mechanisms for how obesity is developed are still unclear. To determine the epigenome-wide and genome-wide expression changes related with childhood obesity, we compared microRNome and transcriptome levels as well as leptin protein levels in whole bloods of 12 obese and 24 normal children aged 6 years. miR-328-3p, miR-1301-3p, miR-4685-3p, and miR-6803-3p were negatively associated with all obesity indicators. The four miRNAs were also associated with 3948 mRNAs, and separate 475 mRNAs (185 among 3948 mRNAs) were associated with all obesity indicators. The 2533 mRNAs (64.2%) among the 3948 mRNAs and 286 mRNAs (60.2%) among the 475 mRNAs were confirmed as targets of the four miRNAs in public databases through miRWalk 2.0. Leptin protein was associated with miR-6803-3p negatively and all obesity indicators positively. Using DAVID bioinformatics resources 6.8, top three pathways for obesity-related gene set were metabolic pathways, pathways in cancer, and PI3K-Akt signaling pathway. The top three obesity-related disease classes were metabolic, cardiovascular, and chemdependency. Our results support that childhood obesity could be developed through miRNAs-related epigenetic mechanism and, further, these obesity-related epigenetic changes could control the pathways related with the development of various diseases.