PhD studentship: Investigating metastatic migration patterns in lung cancer patients

A computational project composed of three main parts: identification of somatic alterations, design of algorithms for tumour evolution, and statistical analysis of recurrent mutations

• Primary supervisor Dr Simone Zaccaria
• Secondary supervisor Dr Mariam Jamal-Hanjani

APPLICATIONS CLOSED (Monday 11 January 2021 17:00 (GMT)

Project

Full title: Computational methods for investigating metastatic migration patterns through large genomic alterations in lung cancer patients

Metastasis results from the dissemination of cancer cells from a primary tumour to other anatomical sites and is the most common cause of death for lung cancer patients. Thus, elucidating genetic changes which engender metastatic potential could have a critical clinical impact. Recent studies have demonstrated that multi-site DNA sequencing allows us to investigate this process and reconstruct metastatic migration patterns by analysing somatic single-nucleotide mutations. However, large genetic alterations are pervasive in cancer and may play an important role in the metastatic process. Using available computational methods and developing novel specific algorithms, we propose to use large genomic alterations for analysing metastatic migration patterns in up to 50 lung cancer patients enrolled in the national research autopsy study PEACE, for which an unprecedented number of metastatic samples is available. This cohort of patients will also include samples obtained from the national TRACERx lung study, providing a unique opportunity to study these genetic changes throughout the disease course, from diagnosis to death. 

The project is fully computational and composed of three main parts in which the skills of the student will be developed: identification of somatic alterations, design of algorithms for tumour evolution, and statistical analysis of recurrent mutations. Firstly, the student will learn to apply standard and existing computational methods to identify different types of somatic genetic alterations (e.g. SNVs, CNAs, etc.) from DNA sequencing data. In particular, these methods will be applied in parallel to the large PEACE and TRACERx datasets by using high-performance computing. Secondly, the student will design new algorithms through combinatorial and probabilistic techniques to reconstruct metastatic migration patterns from the identified genetic alterations. Lastly, the student will use statistical techniques to identify site-specific recurrent alterations from the inferred metastatic migration patterns to reveal putative alterations engendering metastatic potential. These results will also be validated large cohorts of datasets from international cancer consortia (TCGA, ICGC, PCAWG, etc.). 

More detailed information about the research project is available on request from s.zaccaria@ucl.ac.uk.

Person specification

Essential 

• Minimum upper second class Honours Degree in an associated discipline, or an overseas qualification of an equivalent standard. 
• Knowledge of data science, algorithm development, and statistical analysis. 
• Basic knowledge of genomics, cancer genomics, discrete math, and statistical inference. 
• Preliminary knowledge of research techniques. 
• Evidence of motivation for and understanding of the proposed area of study. 
• Ability to develop understanding of complex problems and apply in-depth knowledge to address them. 
• Potential to develop expertise in new areas of the subject. 
• Potential for innovation and initiative, and evidence of an ability to work independently. 
• Effective communication skills in both written and spoken English. 

Desirable 

• Relevant laboratory research experience. 
• Experience in designing, developing, and using bioinformatics pipelines. 
• Experience in using, implementing, or developing phylogenetics algorithms. 
• Experience in using, implementing, or developing techniques of statistical inference and hypothesis testing. 
• Experience with sequencing data. 

Students will also need to qualify as UK/EU fee payers and meet UCL general admissions criteria. 

Duties and responsibilities

Research 

• To apply highly specialist scientific skills and expertise to lead in the delivery of high quality research and the preparation of high-impact research publications. 
• To keep abreast of current developments in this research area. 
• To report research progress to the supervisory team, the Cancer Institute, and at scientific conferences and meetings. 
• To work with other Scientists within the team as necessary. 
• To work safely by adhering to all University policies and practices, including preparing and following laboratory risk assessments, and complying with Health and Safety policies, ethical approval processes and Human Tissue Act guidelines. 

Analytical and Judgement Skills 

• To demonstrate a high-level of technical and analytical skill to resolve highly complex scenarios, requiring analysis, interpretation and expert judgement to find the most appropriate solutions. 
• To identify, interpret and integrate information from a wide variety of sources, and critically evaluate the quality and assumptions of these data. 
• To show initiative and the ability to make decisions in areas where no previous work has been undertaken. 
• To show awareness of your own developmental needs and undertake appropriate training where appropriate. 
• To comply with professional codes of conduct. 

Research environment

The UCL Cancer Institute is a state-of-the-art institute to consolidate cancer research at UCL and promote links with our partner teaching hospitals, in order to support excellence in basic and translational studies. The Institute draws together talented scientists who are working together to translate research discoveries into developing kinder, more effective therapies for cancer patients. It is a Cancer Research UK and Experimental Cancer Medicine Centre, and contains approximately 580 staff, including 80 PhD and MD (Res) students and 30-40 MSc students. Core facilities within the Institute include: Genomics Facility (gene expression microarrays); Proteomics Facility; Imaging and Cell Sorting (confocal, time-lapsed microscopy, MoFlo FACS); Pathology Suite (laser capture microdissection, tissue arrays); Experimental Imaging (with UCL Institute of Child Health); and Transgenesis. 

Application

APPLICATIONS CLOSED (Monday 11 January 2021 17:00 (GMT)

Students will need to qualify as UK/EU fee payers and meet UCL general admissions criteria. This studentship is subject to confirmation of funding from CRUK

To apply for this studentship, you must submit only three documents. 

1. Your full CV including a short summary (<500 words) detailing how your experience and ability matches the project and the person specification. 
2. A single PDF file containing scans of two academic references, and the transcripts of your university degree(s) showing your unit/module marks
3. An equal opportunities monitoring form (Word download). This form will be separated from your application before it is forwarded to shortlisters. By submitting this form you are giving us consent to use the data contained for quality and monitoring purposes. Data will be anonymised.  . 

These three documents should then be emailed to ci.scholarships@ucl.ac.uk. Please write 'CRUK 2004 Zaccaria' in the subject line of the email. 

APPLICATIONS CLOSED (Monday 11 January 2021 17:00 (GMT)