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RNA biomarkers in cancer therapeutics: The promise of personalized oncology
Hector Katifelis1, Maria Gazouli1
1Laboratory of Biology, Medical School, National and Kapodistrian University of Athens, Athens, Greece.
Abstract:
Cancer therapy is a rapidly evolving and constantly expanding field. Current approaches include surgery, conventional chemotherapy and novel biologic agents as in immunotherapy, that together compose a wide armamentarium. The plethora of choices can, however, be clinically challenging in prescribing the most suitable treatment for any given patient. Fortunately, biomarkers can greatly facilitate the most appropriate selection. In recent years, RNA-based biomarkers have proven most promising. These molecules that range from small noncoding RNAs to protein coding gene transcripts can be valuable in cancer management and especially in cancer therapeutics. Compared to their DNA counterparts which are stable throughout treatment, RNA-biomarkers are dynamic. This allows prediction of success prior to treatment start and can identify alterations in expression that could reflect response. Moreover, improved nucleic acid technology allows RNA to be extracted from practically every biofluid/matrix and evaluated with exceedingly high analytic sensitivity. In addition, samples are largely obtained by minimally invasive procedures and as such can be used serially to assess treatment response real-time. This chapter provides the reader insight on currently known RNA biomarkers, the latest research employing Artificial Intelligence in the identification of such molecules and in clinical decisions driving forward the era of personalized oncology.
Insights
RNA biomarkers offer dynamic insights for personalized cancer therapy, enabling real-time treatment response assessment. Artificial intelligence aids in identifying these RNA molecules for improved clinical decisions in oncology.
Area of Science:
- Oncology
- Molecular Biology
- Biomarker Discovery
Background:
- Cancer treatment involves surgery, chemotherapy, and immunotherapy, presenting complex choices for clinicians.
- Biomarkers are crucial for selecting optimal cancer therapies, with RNA-based biomarkers showing significant promise.
- RNA biomarkers are dynamic, unlike stable DNA, offering predictive and responsive insights during treatment.
Purpose of the Study:
- To provide an overview of current RNA biomarkers in cancer.
- To highlight the role of Artificial Intelligence in identifying novel RNA biomarkers.
- To discuss the application of RNA biomarkers in personalized oncology and clinical decision-making.
Main Methods:
- Review of current literature on RNA biomarkers in cancer therapy.
- Exploration of Artificial Intelligence applications in RNA biomarker identification.
- Discussion of minimally invasive procedures for serial sample collection and analysis.
Main Results:
- RNA biomarkers, including noncoding RNAs and gene transcripts, are valuable in cancer management and therapeutics.
- Dynamic RNA expression patterns can predict treatment success and reflect patient response.
- Advanced nucleic acid technology enables sensitive RNA analysis from various biofluids via minimally invasive methods.
Conclusions:
- RNA biomarkers are powerful tools for personalized cancer therapy, facilitating treatment selection and real-time response monitoring.
- The integration of Artificial Intelligence is advancing the discovery and application of RNA biomarkers.
- RNA biomarkers are pivotal in driving the future of personalized oncology.
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