Nottley, Steven William George; (2025) Determining the molecular and pathological responses of neoadjuvant radiotherapy on soft tissue sarcomas. Doctoral thesis (Ph.D), UCL (University College London).

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Abstract

Soft tissue sarcomas (STS) are a heterogeneous group of mesenchymal malignancies, often treated with neoadjuvant radiotherapy (RT) to improve local control. However, the genomic impact of RT on STS remains poorly understood. This thesis investigates the mutational and transcriptomic responses of STS to RT using whole-exome sequencing (WES), RNA sequencing (RNAseq), and the highly sensitive NanoSeq technology. Initial WES analyses of pre- and post-RT tumour samples revealed a low tumour mutational burden (TMB) with no significant increase in single nucleotide variants (SNVs) or small insertions and deletions (indels) post-treatment. Given the known role of RT in inducing DNA damage, I hypothesised that conventional WES might lack the sensitivity to detect low-frequency mutations. To address this, I employed NanoSeq, a duplex sequencing approach capable of detecting rare mutations with unprecedented accuracy. Analysis of paired pre- and post-RT samples using NanoSeq demonstrated a significant increase in indels and a shift toward microhomology-mediated end joining, suggesting a mutational footprint of RT previously undetectable with standard sequencing. Transcriptomic analysis revealed differentially expressed genes and pathways when comparing pre- and post-RT samples, shedding light on the molecular response to RT and identifying potential biomarkers of disease. A machine learning model trained on gene expression data successfully distinguished patients with favourable vs. poor post-RT outcomes. These findings provide novel insights into the genomic and transcriptomic effects of RT on STS. By leveraging high-resolution sequencing technologies, this work enhances our understanding of RT-induced mutagenesis and lays the foundation for improved patient stratification based on molecular response. This research identifies potential biomarkers of disease progression and therapeutic targets, which, with further research and validation, could inform both post-RT surveillance strategies and the development of adjuvant treatment approaches in clinical practice.

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