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Quantification of tumour heterogeneity during cancer evolution and inresponse to therapy

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  • Full or part time
    Dr F Ciccarelli
  • Application Deadline
    No more applications being accepted
  • Funded PhD Project (European/UK Students Only)
    Funded PhD Project (European/UK Students Only)

Project Description

This 4-year PhD studentship is offered in Dr Francesca Ciccarelli’s Group based at the Francis Crick Institute (the Crick).

Cancer cells acquire somatic alterations in their genome throughout the life of a tumour. This enables the tumour to evolve in time and space, adapting to the stimuli from the external environment and contributing to actively shape the internal microenvironment. Cancer genome instability leads to inter- and intra-tumour heterogeneity that poses major challenges not only to the basic understanding of cancer biology but also to patient treatment. The genomic landscape of tumours influences the response to therapy and, in turn, pharmacological treatments profoundly change the genomic landscape of tumours. Therefore, understanding how the genome of a tumour changes in time and space is important to better understand the disease and eventually improve treatment outcome.

Our group and others have developed methods to quantify inter- and intra-tumour heterogeneity and to reveal the clone composition of a tumour, which is a measure of how heterogeneous the tumour is. These methods are also useful to rebuild the temporal acquisition of clonal and subclonal cancer driver events during the development of the disease. This is important to then identify genetic modifications that are actionable in therapy.

The successful student will apply available methods and develop new ones to study tumour heterogeneity in time and space and in response to cancer therapy. They will work in collaboration with computational and wet-lab scientists to analyse high quality high-throughput molecular data (i.e. genomic, transcriptomic, epigenomic data) and matched clinical annotations of a large, prospective cohort of oesophageal cancers from two major genomic and patient stratification initiatives (ICGC and OCCAMS). A range of projects related to the study of inter- and intra-tumour heterogeneity of this sample cohort are available and the precise project will be decided on consultation with the supervisor. The position is suitable for a computational biologist, mathematician or physicist interested in cancer biology or for a cancer biologist with an interest and some background in computational biology. Although the main focus of the project will be on computational approaches, the possibility of a wet-lab component can be envisaged, depending on the preference and background of the candidate.

Talented and motivated students passionate about doing research are invited to apply for this PhD position. The successful applicant will join the Crick PhD Programme in September 2019 and will register for their PhD at one of the Crick partner universities (Imperial College London, King’s College London or UCL).

Applicants should hold or expect to gain a first/upper second-class honours degree or equivalent in a relevant subject and have appropriate research experience as part of, or outside of, a university degree course and/or a Masters degree in a relevant subject.


Funding Notes

This position is funded by Cancer Research UK. The successful candidate will join the Crick PhD Programme on the same studentship terms and conditions as all other Crick PhD students.

Non-EU candidates are not eligible for the funding for this position.

Successful applicants will be awarded a non-taxable annual stipend of £22,000 plus payment of university tuition fees.


1. Mourikis, T., Benedetti, L., Foxall, E., Perner, J., Cereda, M., Lagergren, J., Howell, M., Yau, C., Fitzgerald, R., Scaffidi, P. and Ciccarelli, F. D. (2018)
Preprint: Patient-specific detection of cancer genes reveals recurrently perturbed processes in esophageal adenocarcinoma.
Available at: BioRxiv.
2. Kuppili Venkata, S., Repana, D., Nulsen, J., Dressler, L., Bortolomeazzi, M., Tourna, A., Yakovleva, A., Palmieri, T. and Ciccarelli, F. D. (2018)
Preprint: The Network of Cancer Genes (NCG): a comprehensive catalogue of known and candidate cancer genes from cancer sequencing screens.
Available at: BioRxiv.
3. Cereda, M., Gambardella, G., Benedetti, L., Iannelli, F., Patel, D., Basso, G., Guerra, R. F., Mourikis, T. P., Puccio, I., Sinha, S., Laghi, L., Spencer, J., Rodriguez-Justo, M. and Ciccarelli, F. D. (2016)
Patients with genetically heterogeneous synchronous colorectal cancer carry rare damaging germline mutations in immune-related genes.
Nature Communications 7: 12072. PubMed abstract
4. Gambardella, G., Cereda, M., Benedetti, L. and Ciccarelli, F. D. (2017)
MEGA-V: detection of variant gene sets in patient cohorts.
Bioinformatics 33: 1248-1249. PubMed abstract

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