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Towards controlling cell-state switching of neural crest differentiation states in melanoma evolution

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Manchester, United Kingdom

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Towards controlling cell-state switching of neural crest differentiation states in melanoma evolution

About the Project

Melanoma, a deadly skin cancer, exhibits remarkable adaptability, enabling metastasis, therapy resistance, and immune evasion. Central to this adaptability is the ability of melanoma cells to transition between distinct functional states, a process rooted in mechanisms of cell fate choice. These transitions are driven by dynamic interactions between transcription factors, such as Sox10, Zeb1 and Mitf, which define tumour cell phenotypes and influence therapy response. Understanding how these factors coordinate cell fate decisions is essential for identifying novel therapeutic vulnerabilities.

This PhD project will unravel how intrinsic gene regulatory networks and extrinsic signalling cues drive cell fate choice in melanoma plasticity. This PhD project will focus on exploring the transcriptional dynamics of Sox10, Zeb1 and Mitf during melanoma cell-state transitions. Using cutting-edge CRISPR-mediated fluorescent reporter models, advanced imaging, and transcriptomic analyses, the candidate will:

  1. Investigate Sox10, Zeb1 and Mitf expression dynamics and regulation under diverse environmental and genetic conditions.
  2. Uncover molecular mechanisms and regulatory networks driving melanoma cell-state transitions.

The successful candidate will be part of an interdisciplinary team, collaborating with mathematicians and employing state-of-the-art techniques such as high-resolution imaging, siRNA screening, and ‘Omics analyses to understand and perturb mechanisms of multipotency and plastic adaptation in melanoma. This work will generate critical insights into cancer biology, with the goal of identifying novel therapeutic strategies.

We seek a highly motivated candidate with a strong academic background in cancer biology, molecular biology, life sciences or related fields. We will accept self-funded applicants to this post. Applicants with Master’s-level research experience or equivalent lab-based experience are particularly encouraged to apply.

Candidates are expected to hold (or be about to obtain) a minimum 2:1 Bachelors Degree with Honours (or equivalent) in a related area/subject. We would be particularly happy to receive applications from individuals with a strong academic track record and Masters-level and/or other laboratory research experience in cancer biology or life sciences. Additional computational or maths training would be viewed favourable (although not essential).

Eligibility

Applicants must have obtained or be about to obtain a minimum Upper Second class UK honours degree, or the equivalent qualifications gained outside the UK, in a relevant discipline.

Before you Apply

Applicants must make direct contact with preferred supervisors before applying. It is your responsibility to make arrangements to meet with potential supervisors, prior to submitting a formal online application.

How to Apply

To be considered for this project you MUST submit a formal online application form – on the application form select PhD Cancer Sciences Programme. Full details on how to apply can be found on the Website: How to apply for postgraduate research at The University of Manchester

If you have any queries regarding making an application please contact our admissions team FBMH.doctoralacademy.admissions@manchester.ac.uk

Equality, Diversity and Inclusion

Equality, diversity and inclusion is fundamental to the success of The University of Manchester, and is at the heart of all of our activities. The full Equality, diversity and inclusion statement can be found on the website: Equality, diversity and inclusion (EDI | Postgraduate Research | Biology, Medicine and Health | University of Manchester)

Funding Notes

Applications are invited from self-funded students. This project has a Band Standard fee. Details of our different fee bands can be found on our website View Website

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