Non-invasive classification of pancreatic cancer using imaging signatures

Supervisors: David Lewis (CRUK Beatson Institute), David Chang (University of Glasgow)

Pancreatic cancer has a very poor prognosis and although there are occasional responders to novel treatment there is no effective method to identify these patients prior to commencing therapy. To address this pancreatic cancer has been classified into 4 subtypes with distinct transcriptional and phenotypic signatures. This classification provides an opportunity to stratify patients and to develop subtype-specific cancer therapy. Genomic and phenotypic stratification is performed on resected tumour samples or biopsies, however due to sampling bias, classification based on a single sample may not accurately reflect tumour heterogeneity. Compared with biopsy, non-invasive imaging with PET/MRI enables molecular classification in the primary tumour and metastases, providing an opportunity to identify intra-patient heterogeneity and monitor tumour evolution during the course of treatment.

This project will examine whether molecular subtypes of pancreatic cancer have distinct imaging signatures determined by non-invasive PET/MR imaging and whether these signatures can act as surrogates for identification of tumour heterogeneity and tumour evolution. This will involve collaboration within a multidisciplinary team of clinicians, chemists, physicists, bioinformaticians and cancer biologists. You will gain experience of a range of molecular profiling and imaging technologies with opportunities to design innovative biomarker driven clinical trials to improve patient selection for more effective therapy.

Keywords: Pancreatic cancer; imaging; genomics biomarker; stratification

Recent Publications:

Neves, A.A., et al. Rapid Imaging of Tumor Cell Death In Vivo Using the C2A Domain of Synaptotagmin-I. Journal of nuclear medicine. 58, 881-887 (2017).

Brindle, K.M., Izquierdo-Garcia, J.L., Lewis, D.Y., Mair, R.J. & Wright, A.J. Brain Tumor Imaging. Journal of clinical oncology. 35, 2432-2438 (2017).

Serrao, E.M., et al. MRI with hyperpolarised [1-13C]pyruvate detects advanced pancreatic preneoplasia prior to invasive disease in a mouse model. Gut 65, 465-475 (2016).

Heinzmann, K., et al. The relationship between endogenous thymidine concentrations and [18F]FLT uptake in a range of preclinical tumour models. EJNMMI research 6, 63 (2016).

Lewis, D.Y., Soloviev, D. & Brindle, K.M. Imaging tumor metabolism using positron emission tomography. Cancer journal 21, 129-136 (2015).

Vallejo, A., et al. An integrative approach unveils FOSL1 as an oncogene vulnerability in KRAS-driven lung and pancreatic cancer. Nature communications 8, 14294 (2017).

Scarpa, A., et al. Whole-genome landscape of pancreatic neuroendocrine tumours. Nature 543, 65-71 (2017).

Humphris, J.L., et al. Hypermutation In Pancreatic Cancer. Gastroenterology 152, 68-74 e62 (2017).

Dreyer, S.B., Chang, D.K., Bailey, P. & Biankin, A.V. Pancreatic Cancer Genomes: Implications for Clinical Management and Therapeutic Development. Clinical cancer research : an official journal of the American Association for Cancer Research 23, 1638-1646 (2017).

Bailey, P., et al. Genomic analyses identify molecular subtypes of pancreatic cancer. Nature 531, 47-52 (2016).

 

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