CHAPTER 5: Big Data and Its Emerging Role in Precision Medicine and Therapeutic Response

Nusrat J. Epsi, Sukanya Panja, Antonina Mitrofanova*

*Corresponding author for this work

Research output: Chapter in Book/Report/Conference proceedingChapterpeer-review

Abstract

High-throughput molecular profiling has revolutionized our understanding of molecular mechanisms involved in disease progression and treatment response. As more information from patients' high-throughput molecular and clinical profiles (i.e., Big Data) becomes accessible, there is a significant shift in personalized and precision-based patient-centric approaches, allowing for an individualized therapeutic planning and more accurate prediction of therapeutic success or failure. Here, we discuss the most commonly utilized Big Data types (touching on most recent advances), including genome, DNA methylome, and transcriptome (i.e., RNA abundance and alternative splicing), alongside computational methods for their effective analysis. Further, we discuss how Big Data integration helps in unveiling complex molecular relationships involved in treatment response in oncology, including identification of biological pathways as markers of treatment resistance, and how its utilization builds a foundation for improved clinical decision making and precision medicine.

Original languageEnglish
Title of host publicationDetection Methods in Precision Medicine
EditorsMengsu Yang, Michael Thompson
PublisherRoyal Society of Chemistry
Pages88-116
Number of pages29
Edition18
DOIs
StatePublished - 2021
Externally publishedYes

Publication series

NameRSC Detection Science
Number18
Volume2021-January
ISSN (Print)2052-3068
ISSN (Electronic)2052-3076

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