Systems Biology and Multi-omic Integration for Radiation Sensitization

About this Research Topic

Background

Radiation therapy (RT) in oncology is intricately connected to the individual biology of tumors and surrounding tissues. Overcoming intrinsic and acquired resistance mechanisms is crucial for therapeutic success. Traditional efforts focused on singular molecular pathways often fall short in the complex biological context of cancer, which functions as a dynamic system of interconnected networks. Therefore, a comprehensive, integrative approach—encompassing genomics, epigenomics, transcriptomics, proteomics, metabolomics, radiomics, and immunomics—offers the potential to unravel resistance mechanisms, discover new targets for radiation sensitization, and drive forward personalized oncology.

Systems biology, harnessing computational models with multi-omic data integration, is pivotal in understanding the complex interactions that dictate tumor responses to radiation. By concurrently assessing genomic alterations, transcriptomic signatures, DNA damage responses, metabolic shifts, immune milieu, and histologic organization, researchers are progressively equipped to predict radiation sensitivity and resistance with precision. This approach promises to fine-tune therapeutic strategies by tailoring them to the individual's tumor biology.

This Research Topic aims to explore systems biology and multi-omic approaches specifically crafted for enhancing radiation sensitization. It questions how molecular and cellular networks influence sensitivity or resistance and seeks to guide precision radiotherapy through innovative modeling.

To gather further insights into the integration of multi-omics in radiation sensitivity enhancement, we welcome articles addressing, but not limited to, the following themes:
• Application of multi-omics approaches to translational radiation oncology research, focusing on sensitization or resistance pathways.
• Development of computational frameworks and AI-based algorithms leveraging multi-omic datasets to predict radiation response.
• Systems-level evaluations revealing novel radiation-induced cellular adaptation or immune modulation mechanisms.
• Multi-omic analyses that bridge preclinical model discoveries with clinical patient datasets for personalized radiotherapy.
• Validation of network-based biomarkers predictive of tumor radiosensitivity and radiotherapy-associated toxicities.

This Research Topic prioritizes advances in multi-dimensional systems biology and computational methods that target radiation sensitization. Emphasis is placed on submissions demonstrating robust validation, clinical translation potential, and readiness for real-world implementation. We invite contributions across Original Research, Reviews, Methods Articles, Case Studies, and Perspectives.

Please note: manuscripts consisting solely of bioinformatics, computational analysis, or predictions of public databases which are not accompanied by validation (independent clinical or patient cohort, or biological validation in vitro or in vivo, which are not based on public databases) are not suitable for publication in this journal.

Article types and fees

This Research Topic accepts the following article types, unless otherwise specified in the Research Topic description:

• Brief Research Report
• Case Report
• Clinical Trial
• Editorial
• General Commentary
• Hypothesis and Theory
• Methods
• Mini Review
• Opinion
• ... View all formats

Articles that are accepted for publication by our external editors following rigorous peer review incur a publishing fee charged to Authors, institutions, or funders.

Article types

This Research Topic accepts the following article types, unless otherwise specified in the Research Topic description:

• Brief Research Report
• Case Report
• Clinical Trial
• Editorial
• General Commentary
• Hypothesis and Theory
• Methods
• Mini Review
• Opinion
• Original Research
• Perspective
• Review
• Systematic Review
• Technology and Code

Keywords: Systems Biology, Multi-omics Integration, Radiation Sensitization, Radiosensitivity Biomarkers, Radiation Resistance, Computational Modeling, Network Approaches, Personalized Radiotherapy, Precision Oncology, Integrative Radiomics

Important note: All contributions to this Research Topic must be within the scope of the section and journal to which they are submitted, as defined in their mission statements. Frontiers reserves the right to guide an out-of-scope manuscript to a more suitable section or journal at any stage of peer review.

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