Abstract:
Introduction and Objective: Radiation therapy plays a central role in cancer management; however, its success is often limited by tumour radio resistance and the risk of late treatment-related toxicities, even with advanced technologies and across various forms of radiation and ion therapy. Understanding the genomic alterations induced by radiation and their impact on tumour evolution is crucial for optimizing therapeutic strategies and predicting patient outcomes for personalized treatments. These abstract outlines a framework for the clinical interpretation of whole genomic sequencing (WGS) data of pre radiation treatments and to be obtained from tumours of post-radiation treatment, with the primary objective of elucidating the effects of radiation on the tumour genome.
Materials and Methods: We have done more than 240 patients WGS data including 40 cancer patients. Analysis done on Pre and post Radiation samples to identify diverse genomic changes, including single nucleotide variants (SNVs), small insertions/deletions (indels), copy number variations (CNVs), and structural variants (SVs), as well as their intronic and intergenic variants within the tumour. Radiation dose distribution, imaging biomarkers, and clinical follow-up data were studied which can be integrated using bioinformatics and radio genomic modeling. The findings were interpreted in a clinical context to explore their potential to refine treatment planning and predict radiation sensitivity or resistance.
Results and Discussions: Genetic variants, its types and evidence were observed. Single nucleotide variation, small indels, slice variants structural variants intronic and intergenic variants were studied. Distinct genomic patterns were observed among responders and non-responders. Mutations in DNA damage response genes (e.g., ATM, BRCA1/2, TP53) and specific mutational signatures can be correlated with higher radiosensitivity and favourable tumour control. Our WGS germ line testing report identified heterozygous variants, 57 clinically actionable pharmacogenomic variants, and location of heterozygous variants which is associated with adverse drug reactions etc. Some studies already proved that Integration of WGS data into treatment planning enables identification of patient subgroups who might benefit from dose escalation, dose de-escalation, or targeted radiosensitizers. This may lead to early clinical validation which can improve treatment outcomes compared to conventional clinical-radiological parameters alone. Clinical Interpretation of WGS was done which is the goal of this study.
Conclusion: Whole genome sequencing provides valuable insights into the molecular determinants which is useful to study radiation response and toxicity. Genome-guided radiation therapy holds promise for tailoring treatment intensity, improving tumour control, and minimizing normal tissue damage. Translating these genomic findings into clinical decision support systems could advance precision radiation oncology and enable truly personalized cancer care.
