Noncoding RNA-chromatin association: Functions and mechanisms

Targeting Regulatory Noncoding RNAs in Human Cancer: The State of the Art in Clinical Trials

Noncoding RNAs (ncRNAs) are a heterogeneous group of RNA molecules whose classification is mainly based on arbitrary criteria such as the molecule length, secondary structures, and cellular functions. A large fraction of these ncRNAs play a regulatory role regarding messenger RNAs (mRNAs) or other ncRNAs, creating an intracellular network of cross-interactions that allow the fine and complex regulation of gene expression. Altering the balance between these interactions may be sufficient to cause a transition from health to disease and vice versa. This leads to the possibility of intervening in these mechanisms to re-establish health in patients. The regulatory role of ncRNAs is associated with all cancer hallmarks, such as proliferation, apoptosis, invasion, metastasis, and genomic instability. Based on the function performed in carcinogenesis, ncRNAs may behave either as oncogenes or tumor suppressors. However, this distinction is not rigid; some ncRNAs can fall into both classes depending on the tissue considered or the target molecule. Furthermore, some of them are also involved in regulating the response to traditional cancer-therapeutic approaches. In general, the regulation of molecular mechanisms by ncRNAs is very complex and still largely unclear, but it has enormous potential both for the development of new therapies, especially in cases where traditional methods fail, and for their use as novel and more efficient biomarkers. Overall, this review will provide a brief overview of ncRNAs in human cancer biology, with a specific focus on describing the most recent ongoing clinical trials (CT) in which ncRNAs have been tested for their potential as therapeutic agents or evaluated as biomarkers.

Exploring the roles of RNAs in chromatin architecture using deep learning

Recent studies have highlighted the impact of both transcription and transcripts on 3D genome organization, particularly its dynamics. Here, we propose a deep learning framework, called AkitaR, that leverages both genome sequences and genome-wide RNA-DNA interactions to investigate the roles of chromatin-associated RNAs (caRNAs) on genome folding in HFFc6 cells. In order to disentangle the cis- and trans-regulatory roles of caRNAs, we have compared models with nascent transcripts, trans-located caRNAs, open chromatin data, or DNA sequence alone. Both nascent transcripts and trans-located caRNAs improve the models' predictions, especially at cell-type-specific genomic regions. Analyses of feature importance scores reveal the contribution of caRNAs at TAD boundaries, chromatin loops and nuclear sub-structures such as nuclear speckles and nucleoli to the models' predictions. Furthermore, we identify non-coding RNAs (ncRNAs) known to regulate chromatin structures, such as MALAT1 and NEAT1, as well as several new RNAs, RNY5, RPPH1, POLG-DT and THBS1-IT1, that might modulate chromatin architecture through trans-interactions in HFFc6. Our modeling also suggests that transcripts from Alus and other repetitive elements may facilitate chromatin interactions through trans R-loop formation. Our findings provide insights and generate testable hypotheses about the roles of caRNAs in shaping chromatin organization.

Exploring the Therapeutic Significance of microRNAs and lncRNAs in Kidney Diseases

MicroRNAs (miRNAs) and long non-coding RNAs (lncRNAs) are two crucial classes of transcripts that belong to the major group of non-coding RNAs (ncRNAs). These RNA molecules have significant influence over diverse molecular processes due to their crucial role as regulators of gene expression. However, the dysregulated expression of these ncRNAs constitutes a fundamental factor in the etiology and progression of a wide variety of multifaceted human diseases, including kidney diseases. In this context, over the past years, compelling evidence has shown that miRNAs and lncRNAs could be prospective targets for the development of next-generation drugs against kidney diseases as they participate in a number of disease-associated processes, such as podocyte and nephron death, renal fibrosis, inflammation, transition from acute kidney injury to chronic kidney disease, renal vascular changes, sepsis, pyroptosis, and apoptosis. Hence, in this current review, we critically analyze the recent findings concerning the therapeutic inferences of miRNAs and lncRNAs in the pathophysiological context of kidney diseases. Additionally, with the aim of driving advances in the formulation of ncRNA-based drugs tailored for the management of kidney diseases, we discuss some of the key challenges and future prospects that should be addressed in forthcoming investigations.

Exploring the Roles of RNAs in Chromatin Architecture Using Deep Learning

Recent studies have highlighted the impact of both transcription and transcripts on 3D genome organization, particularly its dynamics. Here, we propose a deep learning framework, called AkitaR, that leverages both genome sequences and genome-wide RNA-DNA interactions to investigate the roles of chromatin-associated RNAs (caRNAs) on genome folding in HFFc6 cells. In order to disentangle the cis- and trans-regulatory roles of caRNAs, we compared models with nascent transcripts, trans-located caRNAs, open chromatin data, or DNA sequence alone. Both nascent transcripts and trans-located caRNAs improved the models' predictions, especially at cell-type-specific genomic regions. Analyses of feature importance scores revealed the contribution of caRNAs at TAD boundaries, chromatin loops and nuclear sub-structures such as nuclear speckles and nucleoli to the models' predictions. Furthermore, we identified non-coding RNAs (ncRNAs) known to regulate chromatin structures, such as MALAT1 and NEAT1, as well as several novel RNAs, RNY5, RPPH1, POLG-DT and THBS1-IT, that might modulate chromatin architecture through trans-interactions in HFFc6. Our modeling also suggests that transcripts from Alus and other repetitive elements may facilitate chromatin interactions through trans R-loop formation. Our findings provide new insights and generate testable hypotheses about the roles of caRNAs in shaping chromatin organization.