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Updated: Jun 13, 2026

Live Imaging to Quantify Cellular Radiosensitivity in Patient-Derived Tumor Organoids

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Published on: April 5, 2024

From Cellular Radiosensitivity to Precision Radiotherapy: Integrating Functional Assays, Genomics, and Clinical

Angeliki Gkikoudi^1,2, Sotiria Triantopoulou², Eygenia Markellou¹

¹DNA Damage Laboratory, Physics Department, School of Applied Mathematical and Physical Sciences, National Technical University of Athens (NTUA), Zografou Campus, 15780 Athens, Greece.

|June 12, 2026

Summary

This summary is machine-generated.

Predicting radiotherapy response requires assessing radiosensitivity using multiple methods. Integrating functional assays with genomic and clinical data offers a promising path toward personalized radiotherapy and improved patient outcomes.

Keywords:

DNA damage response RILA chromosomal radiosensitivity functional radiosensitivity assays micronucleus assay organoids personalized radiotherapy radiosensitivity radiotherapy toxicity γ-H2AX

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Irradiator Commissioning and Dosimetry for Assessment of LQ α and β Parameters, Radiation Dosing Schema, and in vivo Dose Deposition

Irradiator Commissioning and Dosimetry for Assessment of LQ α and β Parameters, Radiation Dosing Schema, and in vivo Dose Deposition

Published on: March 11, 2021

Area of Science:

Oncology
Radiation Oncology
Genomics

Background:

Radiotherapy success depends on balancing tumor control and normal tissue toxicity, with significant patient variability.
Current radiogenomic and molecular predictors of radiosensitivity have limited standalone predictive power.

Purpose of the Study:

To review and synthesize functional assays, genomic biomarkers, and integrative models for assessing radiosensitivity.
To highlight the potential of multi-dimensional approaches for improving radiotherapy outcomes.

Main Methods:

Comprehensive review of functional assays: radiation-induced lymphocyte apoptosis (RILA), chromosomal radiosensitivity assays, micronucleus formation, γ-H2AX foci kinetics, comet assays, clonogenic survival, and patient-derived organoids.
Inclusion of genomic and molecular predictors: hypoxia signatures and gene expression-based models (RSI, GARD).
Synthesis of integrative models combining functional, genomic, and clinical data.

Main Results:

Functional assays directly assess radiation response phenotypes (DNA repair, chromosomal stability, apoptosis) and correlate with normal tissue toxicity.
Tumor radiosensitivity is influenced by intrinsic factors and microenvironmental conditions like hypoxia and genomic instability.
Integrative approaches demonstrate enhanced potential for predictive accuracy in radiosensitivity.

Conclusions:

Radiosensitivity is a complex, systems-level phenotype necessitating multi-dimensional assessment.
Integrating functional assays with genomic and clinical data frameworks advances personalized radiotherapy.
Unified modeling approaches for tumor and normal tissue responses promise clinically actionable precision radiotherapy.