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Updated: May 15, 2025

Identification of Circular RNAs using RNA Sequencing
Published on: November 14, 2019
Unveiling Pharmacogenomics Insights into Circular RNAs: Toward Precision Medicine in Cancer Therapy
Saud Alqahtani1, Taha Alqahtani1, Krishnaraju Venkatesan1
1Department of Pharmacology, College of Pharmacy, King Khalid University, Abha 62521, Saudi Arabia.
Abstract:
Pharmacogenomics is revolutionizing precision medicine by enabling tailored therapeutic strategies based on an individual genetic and molecular profile. Circular RNAs (circRNAs), a distinct subclass of endogenous non-coding RNAs, have recently emerged as key regulators of drug resistance, tumor progression, and therapeutic responses. Their covalently closed circular structure provides exceptional stability and resistance to exonuclease degradation, positioning them as reliable biomarkers and novel therapeutic targets in cancer management. This review provides a comprehensive analysis of the interplay between circRNAs and pharmacogenomics, focusing on their role in modulating drug metabolism, therapeutic efficacy, and toxicity profiles. We examine how circRNA-mediated regulatory networks influence chemotherapy resistance, alter targeted therapy responses, and impact immunotherapy outcomes. Additionally, we discuss emerging experimental tools and bioinformatics techniques for studying circRNAs, including multi-omics integration, machine learning-driven biomarker discovery, and high-throughput sequencing technologies. Beyond their diagnostic potential, circRNAs are being actively explored as therapeutic agents and drug delivery vehicles. Recent advancements in circRNA-based vaccines, engineered CAR-T cells, and synthetic circRNA therapeutics highlight their transformative potential in oncology. Furthermore, we address the challenges of standardization, reproducibility, and clinical translation, emphasizing the need for rigorous biomarker validation and regulatory frameworks to facilitate their integration into clinical practice. By incorporating circRNA profiling into pharmacogenomic strategies, this review underscores a paradigm shift toward highly personalized cancer therapies. circRNAs hold immense potential to overcome drug resistance, enhance treatment efficacy, and optimize patient outcomes, marking a significant advancement in precision oncology.
Insights
Circular RNAs (circRNAs) are key to pharmacogenomics, offering stable biomarkers for personalized cancer therapy. They help overcome drug resistance and improve treatment outcomes in precision oncology.
Area of Science:
- Oncology
- Genomics
- Molecular Biology
Background:
- Pharmacogenomics enables personalized medicine through genetic profiling.
- Circular RNAs (circRNAs) are stable non-coding RNAs regulating drug resistance and cancer progression.
- circRNAs' unique structure makes them promising biomarkers and therapeutic targets.
Purpose of the Study:
- To review the role of circRNAs in pharmacogenomics for cancer therapy.
- To analyze circRNA influence on drug metabolism, efficacy, and toxicity.
- To discuss circRNAs as biomarkers and therapeutic agents in precision oncology.
Main Methods:
- Comprehensive literature review of circRNAs in pharmacogenomics.
- Analysis of circRNA regulatory networks in chemotherapy, targeted therapy, and immunotherapy.
- Examination of experimental and bioinformatics tools for circRNA study.
- Review of circRNA-based therapeutics and delivery systems.
Main Results:
- circRNAs significantly modulate chemotherapy resistance, targeted therapy response, and immunotherapy outcomes.
- Multi-omics integration and machine learning aid circRNA biomarker discovery.
- circRNAs show potential as vaccines, drug delivery vehicles, and synthetic therapeutics.
- Standardization and validation are crucial for clinical translation of circRNA biomarkers.
Conclusions:
- Integrating circRNA profiling into pharmacogenomics represents a paradigm shift in personalized cancer therapy.
- circRNAs offer potential to overcome drug resistance and enhance treatment efficacy.
- circRNAs are pivotal for optimizing patient outcomes in precision oncology.
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