Endocrine Abstracts

Background: Tumour heterogeneity and evolution present significant challenges in advanced thyroid cancers, contributing to treatment resistance and disease progression. NOMINATE (NCT05837260) is a multicentre, prospective biological sampling study which aims to investigate the genomic diversity of thyroid cancers and assess the utility of circulating tumour DNA (ctDNA) for delineating evolutionary forces driving treatment failure and resistance. We present our latest progress in trial recruitment and preliminary data of a pilot study of a patient with medullary thyroid cancer to illustrate our methodology of DNA analyses using state-of-the-art sequencing and computational methods.

Methods: NOMINATE (NCT05837260) is multicentre, prospective study aiming to collect clinical samples from 120 patients with advanced thyroid cancers (iodine-refractory, medullary and anaplastic) and is open for recruitment. Blood samples for ctDNA extraction are collected at regular intervals over a 2-year period, in addition to fresh or formalin-fixed tumour samples. For the pilot study, comprehensive whole-exome sequencing (WES) was performed on Illumina sequencing platforms following standardised protocols. ichorCNA was used to estimate tumour fraction in plasma cell-free DNA (cfDNA). State-of-the-art computational methods including Mutect2, VarScan2, CNVkit and TitanCNA were utilised for DNA variant analyses. Subclonal reconstruction was performed using Pyclone and ClonEvol to map the evolutionary histories and trajectories of these cancers.

Results: As of March 2024, we have recruited 46 patients on the NOMINATE clinical trial. We present a pilot study of a patient with sporadic, RET -mutated metastatic MTC and showed that low-coverage whole-genome sequencing (WGS) (~1x) as a screening method for tumour purity estimation in plasma cfDNA was possible. WES revealed shared and distinct mutations between primary tumour, lymph node metastasis and plasma ctDNA. Subclonal populations identified using Pyclone and ClonEvol showed unique clustering of mutations for phylogeny and clonal ordering.

Conclusions: Our findings demonstrate a robust and feasible approach in unravelling the molecular landscape of advanced thyroid cancers and interrogates the role of tumour heterogeneity in disease progression and treatment resistance. We aim to develop the value of using ctDNA as a non-invasive biomarker in capturing tumour dynamics and heterogeneity in informing personalised therapy.

Keywords: Advanced thyroid cancer, tumour heterogeneity, multiregion sampling, circulating tumour DNA, subclonal reconstruction, cancer evolution.