Using multi-omic data for neuroendocrine cancer diagnostics and metastatic predictions

Lead Supervisor
Professor Rebecca Oakey
Professor
Medical & Molecular Genetics, BMBS, FoLSM, King’s College London
rebecca.oakey@kcl.ac.uk

Co-supervisors
Dr Cynthia Andoniadou (Senior Lecturer, FoDOCS, King’s College London)
Louise Izatt (Clinical Partner GSTT)

Project Details

Background:

Pheochromocytomas and paragangliomas (PCCs/PGLs) are rare neuroendocrine tumours of the adrenal medulla (PCCs) and the sympathetic and parasympathetic paraganglia (PGLs). Many PCCs/PGLs are characterised by excessive production of catecholamines, leading to hypertension, arrhythmia and stroke. Patients with metastatic disease have an estimated 5-year survival rate of 50%. A third of PCCs/PGLs are associated with inherited cancer susceptibility genes, the highest rate among all tumour types. Germline SDHB mutations (encoding succinate dehydrogenase B) are present in 6-8% of tumours and 34-70% of mutation carriers develop metastatic disease, for which at present, there are no predictors. Methylome analyses have identified a hypermethylation phenotype in SDH-deficient tumours and this project seeks to stratify malignant versus benign tumours using their epigenetic and transcriptomic profiles.

Rationale:

This project is designed to identify commonly methylated target genes in malignant PCC/PGL tumours and develop diagnostic tools that can predict the malignant course of PCCs/PGLs, for which there is an unmet need.

Preliminary data:

DNA methylomes, whole genome sequences and transcriptomic data have been generated in partnership with detailed clinical records for patients with SDHB mutations from the Cancer Genome Atlas (TCGA) consortium and from the GSTT and KCH Hospital Trusts. Analysis of the DNA methylome provides evidence that DNA methylation status is a predictor of metastatic propensity and these characteristics will be utilised to develop a predictor of the malignant phenotype in PCCs/PGLs.

Project design:

Our large cohorts of patients with deep clinical data alongside precisely-characterised epigenomes will be correlated with transcriptomic data to understand the role of epigenomic marks in modifying gene expression. This is essential to understanding why some tumours, particularly those carrying SDHB mutations, behave aggressively. There are currently no robust predictors of malignancy for PCCs/PGLs for SDHB-related tumourigenesis. This project will provide mechanistic understanding of the disease, enable the development of diagnostic tools, and provide novel therapeutic targets which are desperately needed for treating these aggressive tumours using big-omics data and longitudinal deep phenotyping.

Datasets

PPGLs from the Cancer Genome Atlas (TCGA) consortium- whole genome sequencing  (public domain) transcrptomic data (Prof K Nathanson, U.Penn collaborator) and methylomes (our group, unpublished). Transcriptomes, exomes/whole genomes constitutional & tumour and methylomes (our group unpublished). Ethics: South West – Cornwall & Plymouth Research Ethics Committee REC reference 17/SW/0018.

Keywords

Pheochromocytomas & paragangliomas; inherited mutation; epigenomics; genomics; transcriptomics;  metastatic cancer