Progress in Molecular Biology and Translational Science最新文献

RNA therapeutics are a class of drugs that use RNA molecules to treat diseases, including cancer. RNA therapeutics work by targeting specific genes or proteins involved in the disease process, with the aim of blocking or altering their activity to ultimately halt or reverse the disease progression. The use of RNA therapeutics in cancer treatment has shown great potential, as they offer the ability to specifically target cancer cells while leaving healthy cells intact. This is in contrast to traditional chemotherapy and radiation treatments, which can damage healthy cells and cause unpleasant side effects. The field of RNA therapeutics is rapidly advancing, with several types of RNA molecules being developed for cancer treatment, including small interfering RNA, microRNA, mRNA, and RNA aptamers. Each type of RNA molecule has unique properties and mechanisms of action, allowing for targeted and personalized cancer treatments. In this chapter, we will explore the different types of RNA therapeutics used in cancer treatment, their mechanisms of action, and their potential applications in treating different types of cancer. We will also discuss the challenges and opportunities in the development and research of RNA therapeutics for cancer, as well as the future outlook for this promising field.

The excretory system is responsible for removing wastes from the human body, which plays a crucial role in our lives. Current treatments for diseases related to this system have shown several limitations; therefore, there is a rising need for novel methods. In this circumstance, RNA-based therapeutics have rapidly emerged as new and promising candidates. In fact, to date, a handful of potential drugs have passed the development step and entered the clinical pipeline. Among them, one drug received FDA approval to enter the global market, which is Oxlumo (Lumasiran) for the treatment of primary hyperoxaluria type 1. For other excretory diseases, such as paroxysmal nocturnal hemoglobinuria, urothelial cancer or renal cancer, RNA-based candidates are also being tested under clinical trials. Currently, the most potential types of RNA therapeutics to treat disorders of the excretory system are those based on small interfering RNA (siRNA), antisense oligonucleotides (ASO) and messenger RNA (mRNA), Among them, siRNA therapeutics seem to be the most promising, including Oxlumo and two other developing drug candidates. This chapter will provide a general overview on the application of RNA therapeutics in disorders of the excretory system.

RNA therapy is one of the new treatments using small RNA molecules to target and regulate gene expression. It involves the application of synthetic or modified RNA molecules to inhibit the expression of disease-causing genes specifically. In other words, it silences genes and suppresses the transcription process. The main theory behind RNA therapy is that RNA molecules can prevent the translation into proteins by binding to specific messenger RNA (mRNA) molecules. By targeting disease-related mRNA molecules, RNA therapy can effectively silence or reduce the development of harmful proteins. There are different types of RNA molecules used in therapy, including small interfering RNAs (siRNAs), microRNAs (miRNAs), aptamer, ribozyme, and antisense oligonucleotides (ASOs). These molecules are designed to complement specific mRNA sequences, allowing them to bind and degrade the targeted mRNA or prevent its translation into protein. Nanotechnology is also highlighted to increase the efficacy of RNA-based drugs. In this chapter, while examining various methods of RNA therapy, we discuss the advantages and challenges of each.

The drug discovery and development (DDD) process greatly relies on the data available in various forms to generate hypotheses for novel drug design. The complex and heterogeneous nature of biological data makes it difficult to utilize or gather meaningful information as such. Computational biology techniques have provided us with opportunities to better understand biological systems through refining and organizing large amounts of data into actionable and systematic purviews. The drug repurposing approach has been utilized to overcome the expansive time periods and costs associated with traditional drug development. It deals with discovering new uses of already approved drugs that have an established safety and efficacy profile, thereby, requiring them to go through fewer development phases. Thus, drug repurposing through computational biology provides a systematic approach to drug development and overcomes the constraints of traditional processes. The current chapter covers the basics, approaches and tools of computational biology that can be employed to effectively develop repurposing profile of already approved drug molecules.

Drug repurposing has emerged as a promising approach in the drug discovery and development process as it offers safe and effective therapeutic options in a time effective manner. Though the issues related to pre-clinical and clinical aspects of drug development process are greatly addressed during drug repurposing yet regulatory perspectives gain even more However, like traditional drug development the repurposed drugs face multiple challenges. Such challenges range from the patenting rights, novelty of repurposing, data and market exclusivity to affordability and equitable access to the patient population. In order to optimize the market access of repurposed drugs, regulatory organizations throughout the world have developed accelerated approval procedures. The regulatory bodies have recognized the importance of repurposing approaches and repurposed drugs. Regulatory bodies can encourage the development of repurposed drugs by providing incentives to pharmaceutical companies and more accessible and affordable repurposed agents for the general population. This chapter summarizes the regulatory and ethical considerations pertaining to the repurposed drugs and highlights a few cases of intellectual property rights for repurposed drugs that have helped improve patient's access to safe, efficacious and cost-effective therapeutic options.

The field of drug repurposing is gaining attention as a way to introduce pharmaceutical agents with established safety profiles to new patient populations. This approach involves finding new applications for existing drugs through observations or deliberate efforts to understand their mechanisms of action. Recent advancements in bioinformatics and pharmacology, along with the availability of extensive data repositories and analytical techniques, have fueled the demand for novel methodologies in pharmaceutical research and development. To facilitate systematic drug repurposing, various computational methodologies have emerged, combining experimental techniques and in silico approaches. These methods have revolutionized the field of drug discovery by enabling the efficient repurposing of screens. However, establishing an ideal drug repurposing pipeline requires the integration of molecular data accessibility, analytical proficiency, experimental design expertise, and a comprehensive understanding of clinical development processes. This chapter explores the key methodologies used in systematic drug repurposing and discusses the stakeholders involved in this field. It emphasizes the importance of strategic alliances to enhance the success of repurposing existing compounds for new indications. Additionally, the chapter highlights the current benefits, considerations, and challenges faced in the repurposing process, which is pursued by both biotechnology and pharmaceutical companies. Overall, drug repurposing holds great promise in expanding the use of existing drugs and bringing them to new patient populations. With the advancements in computational methodologies and the collaboration of various stakeholders, this approach has the potential to accelerate drug development and improve patient outcomes.

Synthetic biology, precision medicine, and nanobiotechnology are the three main emerging areas that drive translational innovation toward commercialization. There are several strategies used in precision medicine and drug repurposing is one of the key approaches as it addresses the challenges in drug discovery (high cost and time). Here, we provide a perspective on various new approaches to drug repurposing for cancer precision medicine. We report here our optimized wound healing methodology that can be used to validate drug sensitivity and drug repurposing. Using HeLa as our benchmark, we demonstrated that the assay can be applied to identify drugs that limit cell proliferation. From a future perspective, this assay can be expanded to ex vivo culturing of solid tumors in 2D culture and leukemia in 3D culture.

The conventional theory linking a single gene with a particular disease and a specific drug contributes to the dwindling success rates of traditional drug discovery. This requires a substantial shift focussing on contemporary drug design or drug repurposing, which entails linking multiple genes to diverse physiological or pathological pathways and drugs. Lately, drug repurposing, the art of discovering new/unlabelled indications for existing drugs or candidates in clinical trials, is gaining attention owing to its success rates. The rate-limiting phase of this strategy lies in target identification, which is generally driven through disease-centric and/or drug-centric approaches. The disease-centric approach is based on exploration of crucial biomolecules such as genes or proteins underlying pathological cascades of the disease of interest. Investigating these pathological interplays aids in the identification of potential drug targets that can be leveraged for novel therapeutic interventions. The drug-centric approach involves various strategies such as exploring the mechanism of adverse drug reactions that can unearth potential targets, as these untoward reactions might be considered desirable therapeutic actions in other disease conditions. Currently, artificial intelligence is an emerging robust tool that can be used to translate the aforementioned intricate biological networks to render interpretable data for extracting precise molecular targets. Integration of multiple approaches, big data analytics, and clinical corroboration are essential for successful target mining. This chapter highlights the contemporary strategies steering target identification and diverse frameworks for drug repurposing. These strategies are illustrated through case studies curated from recent drug repurposing research inclined towards neurodegenerative diseases, cancer, infections, immunological, and cardiovascular disorders.

Nowadays, information technology (IT) has been holding a significant role in daily life worldwide. The trajectory of data science and bioinformatics promises pioneering personalized therapies, reshaping medical landscapes and patient care. For RNA therapy to reach more patients, a comprehensive understanding of the application of data science and bioinformatics to this therapy is essential. Thus, this chapter has summarized the application of data science and bioinformatics in RNA therapeutics. Data science applications in RNA therapy, such as data integration and analytics, machine learning, and drug development, have been discussed. In addition, aspects of bioinformatics such as RNA design and evaluation, drug delivery system simulation, and databases for personalized medicine have also been covered in this chapter. These insights have shed light on existing evidence and opened potential future directions. From there, scientists can elevate RNA-based therapeutics into an era of tailored treatments and revolutionary healthcare.

The study of small RNAs is a field that is expanding quickly. Other functional short RNA molecules other than microRNAs, and gene expression regulators, have been found in animals and plants. MicroRNAs play a significant role in host-microbe interactions, and parasite microRNAs may affect the host's innate immunity. Furthermore, short RNAs are intriguing non-invasive biomarker possibilities because they can be found in physiological fluids. These trends suggest that for many researchers, quick and simple techniques for expression profiling and subsequent downstream analysis of miRNA-seq data are crucial. We selected sRNAtoolbox to make integrated sRNA research easier. Each tool can be used separately or to explore and analyze sRNAbench results in further depth. A special focus was placed on the tools' usability. We review available miRNA research tools to have an overview of the evaluation of the tools. Mainly we evaluate the tool sRNAtoolbox.