This is an early access version, the complete PDF, HTML, and XML versions will be available soon.
From Cellular Radiosensitivity to Precision Radiotherapy: Integrating Functional Assays, Genomics, and Clinical Modeling
by
, , , , , and
Angeliki Gkikoudi
1,2
,
Sotiria Triantopoulou
2,
Eygenia Markellou
1,
Vasiliki Xynou
2,
Spyridon N. Vasilopoulos
1,
Marios Myronakis
3,
Evagelia C. Laiakis
4,5,6
,
Kiki Theodorou
3,7
,
Georgia I. Terzoudi
2 and
Alexandros G. Georgakilas
1,*
1
DNA Damage Laboratory, Physics Department, School of Applied Mathematical and Physical Sciences, National Technical University of Athens (NTUA), Zografou Campus, 15780 Athens, Greece
2
Laboratory of Health Physics, Radiobiology & Cytogenetics, Institute of Nuclear & Radiological Sciences & Technology, Energy & Safety, National Centre for Scientific Research “Demokritos”, 15341 Agia Paraskevi, Greece
3
Department of Medical Physics, Faculty of Medicine, University of Thessaly, 41500 Larissa, Greece
4
Department of Radiation Medicine, Georgetown University Medical Center, Washington, DC 20057, USA
5
Department of Oncology, Lombardi Comprehensive Cancer Center, Georgetown University Medical Center, Washington, DC 20057, USA
6
Department of Biochemistry and Molecular & Cellular Biology, Georgetown University Medical Center, Washington, DC 20057, USA
7
Innovation and Research, King Faisal Specialist Hospital & Research Centre, Riyadh 11211, Saudi Arabia
*
Author to whom correspondence should be addressed.
Cancers 2026, 18(11), 1823; https://doi.org/10.3390/cancers18111823
Submission received: 22 April 2026
/
Revised: 19 May 2026
/
Accepted: 27 May 2026
/
Published: 2 June 2026
(This article belongs to the Special Issue Radiosensitivity and Radiotoxicity in Cancer)
Simple Summary
Radiotherapy response varies among patients due to differences in tumor and normal tissue radiosensitivity. This review outlines key biological factors influencing this variability, including DNA repair capacity, genetic background, and the tumor microenvironment. It summarizes functional assays used to assess radiation response and highlights genomic approaches such as gene expression models and hypoxia-related markers. The importance of integrating biological, molecular, and clinical data is emphasized to improve prediction of treatment outcomes.
Abstract
Background: Radiotherapy outcomes are determined by the balance between tumor control and normal tissue toxicity, both of which exhibit significant interpatient variability. While radiogenomic and molecular approaches have identified determinants of radiosensitivity, their predictive performance remains limited when used in isolation. Methods: This review provides a comprehensive synthesis of functional assays, genomic biomarkers, and integrative models used to assess radiosensitivity, including radiation-induced lymphocyte apoptosis (RILA), chromosomal radiosensitivity assays, micronucleus formation, γ-H2AX foci kinetics, comet assays, clonogenic survival, and patient-derived organoids, alongside genomic and molecular predictors of tumor response such as hypoxia signatures and gene expression-based models (e.g., RSI and GARD). Results: Functional assays provide direct phenotypic assessment of radiation response, capturing DNA repair capacity, chromosomal stability, apoptosis, and tissue regenerative potential, and have shown associations in several studies with normal tissue toxicity across clinical settings. Tumor radiosensitivity is influenced by intrinsic cellular factors and microenvironmental conditions, including hypoxia and genomic instability. Integrative approaches combining functional, genomic, and clinical data show increasing potential for improving predictive accuracy. Conclusions: Radiosensitivity should be considered a systems-level phenotype requiring multi-dimensional assessment. Conceptual frameworks that integrate tumor and normal tissue responses within a unified modeling approach, supported by measurable biological and clinical parameters, represent a promising direction for clinically actionable precision radiotherapy. The integration of functional assays with genomic and clinical modeling frameworks represents a promising strategy for advancing personalized radiotherapy and improving therapeutic outcomes.
