Advances in RNA as Diagnostic Biomarkers

A special issue of Biomolecules (ISSN 2218-273X). This special issue belongs to the section "Molecular Biomarkers".

Deadline for manuscript submissions: closed (31 December 2023) | Viewed by 3649

Special Issue Editors

Center for RNA Medicine, Department of Clinical Medicine, Aalborg University, DK-2450 Copenhagen, Denmark
Interests: microRNA; liver; NASH; RNA; therapy
Center for RNA Medicine, Department of Clinical Medicine, Aalborg University, DK-2450 Copenhagen, Denmark
Interests: non-coding RNAs; stem cell biology; neuroscience
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Special Issue Information

Dear Colleagues,

It is now clear that most of the mammalian genome is transcribed as RNAs. Whether all of these RNAs are functional or not, their expression profiles are reflections of cellular activities. As such, the dysregulation of RNAs’ expressions has been recorded under various diseases. Due to the decreased costs of performing RNA sequencing (RNA-seq) experiments, the unbiased profiling of the transcriptome is frequently used in both basic and translational research.

The aim of this Special Issue is to highlight the usage of RNA as a potential diagnostic biomarker of various diseases. We encourage contributions on technical advancements in detecting various forms of RNA (e.g., non-coding RNAs, including microRNAs, long non-coding RNAs (lncRNAs), and circular RNAs (circRNAs)) and computational approaches to analyzing RNA-seq data.

Dr. Riccardo Panella
Prof. Dr. Shizuka Uchida
Dr. Mirolyuba Ilieva
Guest Editors

Manuscript Submission Information

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Keywords

  • biomarker
  • disease
  • RNA
  • ncRNA
  • lncRNA
  • circRNA

Published Papers (3 papers)

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Research

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15 pages, 3901 KiB  
Article
Using LLMs and Explainable ML to Analyze Biomarkers at Single-Cell Level for Improved Understanding of Diseases
Biomolecules 2023, 13(10), 1516; https://doi.org/10.3390/biom13101516 - 12 Oct 2023
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Abstract
Single-cell RNA sequencing (scRNA-seq) technology has significantly advanced our understanding of the diversity of cells and how this diversity is implicated in diseases. Yet, translating these findings across various scRNA-seq datasets poses challenges due to technical variability and dataset-specific biases. To overcome this, [...] Read more.
Single-cell RNA sequencing (scRNA-seq) technology has significantly advanced our understanding of the diversity of cells and how this diversity is implicated in diseases. Yet, translating these findings across various scRNA-seq datasets poses challenges due to technical variability and dataset-specific biases. To overcome this, we present a novel approach that employs both an LLM-based framework and explainable machine learning to facilitate generalization across single-cell datasets and identify gene signatures to capture disease-driven transcriptional changes. Our approach uses scBERT, which harnesses shared transcriptomic features among cell types to establish consistent cell-type annotations across multiple scRNA-seq datasets. Additionally, we employed a symbolic regression algorithm to pinpoint highly relevant, yet minimally redundant models and features for inferring a cell type’s disease state based on its transcriptomic profile. We ascertained the versatility of these cell-specific gene signatures across datasets, showcasing their resilience as molecular markers to pinpoint and characterize disease-associated cell types. The validation was carried out using four publicly available scRNA-seq datasets from both healthy individuals and those suffering from ulcerative colitis (UC). This demonstrates our approach’s efficacy in bridging disparities specific to different datasets, fostering comparative analyses. Notably, the simplicity and symbolic nature of the retrieved gene signatures facilitate their interpretability, allowing us to elucidate underlying molecular disease mechanisms using these models. Full article
(This article belongs to the Special Issue Advances in RNA as Diagnostic Biomarkers)
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Review

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25 pages, 1465 KiB  
Review
Extracellular Vesicles as Delivery Vehicles for Non-Coding RNAs: Potential Biomarkers for Chronic Liver Diseases
Biomolecules 2024, 14(3), 277; https://doi.org/10.3390/biom14030277 - 26 Feb 2024
Viewed by 308
Abstract
In recent years, EVs have emerged as promising vehicles for coding and non-coding RNAs (ncRNAs), which have demonstrated remarkable potential as biomarkers for various diseases, including chronic liver diseases (CLDs). EVs are small, membrane-bound particles released by cells, carrying an arsenal of ncRNAs, [...] Read more.
In recent years, EVs have emerged as promising vehicles for coding and non-coding RNAs (ncRNAs), which have demonstrated remarkable potential as biomarkers for various diseases, including chronic liver diseases (CLDs). EVs are small, membrane-bound particles released by cells, carrying an arsenal of ncRNAs, including microRNAs (miRNAs), long non-coding RNAs (lncRNAs), and other ncRNA species, such as piRNAs, circRNAs, and tsRNAs. These ncRNAs act as key regulators of gene expression, splicing, and translation, providing a comprehensive molecular snapshot of the cells of origin. The non-invasive nature of EV sampling, typically via blood or serum collection, makes them highly attractive candidates for clinical biomarker applications. Moreover, EV-encapsulated ncRNAs offer unique advantages over traditional cell-free ncRNAs due to their enhanced stability within the EVs, hence allowing for their detection in circulation for extended periods and enabling more sensitive and reliable biomarker measurements. Numerous studies have investigated the potential of EV-enclosed ncRNAs as biomarkers for CLD. MiRNAs, in particular, have gained significant attention due to their ability to rapidly respond to changes in cellular stress and inflammation, hallmarks of CLD pathogenesis. Elevated levels of specific miRNAs have been consistently associated with various CLD subtypes, including metabolic dysfunction-associated steatotic liver disease (MASLD), metabolic dysfunction-associated steatohepatitis (MASH), and chronic hepatitis B and C. LncRNAs have also emerged as promising biomarkers for CLD. These transcripts are involved in a wide range of cellular processes, including liver regeneration, fibrosis, and cancer progression. Studies have shown that lncRNA expression profiles can distinguish between different CLD subtypes, providing valuable insights into disease progression and therapeutic response. Promising EV-enclosed ncRNA biomarkers for CLD included miR-122 (elevated levels of miR-122 are associated with MASLD progression and liver fibrosis), miR-21 (increased expression of miR-21 is linked to liver inflammation and fibrosis in CLD patients), miR-192 (elevated levels of miR-192 are associated with more advanced stages of CLD, including cirrhosis and HCC), LncRNA HOTAIR (increased HOTAIR expression is associated with MASLD progression and MASH development), and LncRNA H19 (dysregulation of H19 expression is linked to liver fibrosis and HCC progression). In the present review, we focus on the EV-enclosed ncRNAs as promising tools for the diagnosis and monitoring of CLD of various etiologies. Full article
(This article belongs to the Special Issue Advances in RNA as Diagnostic Biomarkers)
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24 pages, 4759 KiB  
Review
Infection Meets Inflammation: N6-Methyladenosine, an Internal Messenger RNA Modification as a Tool for Pharmacological Regulation of Host–Pathogen Interactions
Biomolecules 2023, 13(7), 1060; https://doi.org/10.3390/biom13071060 - 29 Jun 2023
Viewed by 1323
Abstract
The significance of internal mRNA modifications for the modulation of transcript stability, for regulation of nuclear export and translation efficiency, and their role in suppressing innate immunity is well documented. Over the years, the molecular complexes involved in the dynamic regulation of the [...] Read more.
The significance of internal mRNA modifications for the modulation of transcript stability, for regulation of nuclear export and translation efficiency, and their role in suppressing innate immunity is well documented. Over the years, the molecular complexes involved in the dynamic regulation of the most prevalent modifications have been characterized—we have a growing understanding of how each modification is set and erased, where it is placed, and in response to what cues. Remarkably, internal mRNA modifications, such as methylation, are emerging as an additional layer of regulation of immune cell homeostasis, differentiation, and function. A fascinating recent development is the investigation into the internal modifications of host/pathogen RNA, specifically N6-methyladenosine (m6A), its abundance and distribution during infection, and its role in disease pathogenesis and in shaping host immune responses. Low molecular weight compounds that target RNA-modifying enzymes have shown promising results in vitro and in animal models of different cancers and are expanding the tool-box in immuno-oncology. Excitingly, such modulators of host mRNA methyltransferase or demethylase activity hold profound implications for the development of new broad-spectrum therapeutic agents for infectious diseases as well. This review describes the newly uncovered role of internal mRNA modification in infection and in shaping the function of the immune system in response to invading pathogens. We will also discuss its potential as a therapeutic target and identify pitfalls that need to be overcome if it is to be effectively leveraged against infectious agents. Full article
(This article belongs to the Special Issue Advances in RNA as Diagnostic Biomarkers)
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