MicroRNAs: Role in Cancer Progression, Diagnostics and Therapy

Name: MicroRNAs: Role in Cancer Progression, Diagnostics and Therapy
Brand: Springer Nature Switzerland
SKU: 9783032088239
Price: 197.99 USD
Availability: InStock

Pathak, Surajit; Banerjee, Antara

This book describes microRNAs as relevant tools that form a new bridge in modern oncological progress between molecular insights and clinical practice. It also highlights the therapeutic applications, emphasizing their utility in personalized medicine and targeted therapies.

MicroRNAs (miRNAs) are short, non-coding RNAs that play a crucial role in regulating gene expression. Their importance in cancer biology has grown significantly in recent years, as they have been found to influence various aspects of cancer development and progression. This book provides a comprehensive overview of the diverse roles of miRNAs in several cancers, from their biogenesis and functions to their potential as therapeutic targets and biomarkers. This book further looks into the critical role of the miRNAs in the tumor microenvironment (TME) and their influence on processes such as epithelial-to-mesenchymal transition, immune modulation, and angiogenesis. The chapters focus on their diagnostic and therapeutic importance in several cancer types, such as colorectal, cervical, lung, and breast cancers, with particular emphasis on cancers that exhibits unusual metastatic patterns such as breast and prostate cancer metastasis to bones. The chapters will additionally address the process by which miRNA-mediated pathways contribute to the development of brain and gynaecological tumors, as well as explores the potential of exosomal miRNAs as non-invasive biomarkers for cancer detection through mechanisms that trigger intracellular signaling within the TME.

The development of AI and bioinformatics has transformed miRNA research, enabling a deeper understanding of miRNA function and facilitating the development of innovative diagnostic and therapeutic strategies. By incorporating them into high-throughput sequencing with machine learning approaches, several models have been developed that have favoured the identification, classification, and prediction of the target functions of miRNAs and their targets, particularly in cancer biology.