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Resolving the impact of genomic instability and error prone DNA repair on radiation resistance through phylogenetic analysis in NSCLC

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  • Full or part time
    Dr N McGranahan
    Dr C Hiley
  • Application Deadline
    No more applications being accepted
  • Competition Funded PhD Project (European/UK Students Only)
    Competition Funded PhD Project (European/UK Students Only)

Project Description

Lung cancer is the most common cause of cancer death in the UK. In patients with stage III non-small cell lung cancer (NSCLC) chemoradiotherapy is the most common treatment. However only 32% of patient treated with concurrent chemoradiotherapy are alive 5 years after treatment [1]. Despite advances in precision medicine for NSCLC, where targeted therapies can be matched with sensitising mutations, we have limited understanding of what cell intrinsic factors are responsible for sensitivity or resistance to radiotherapy. Genomic instability is the increase of mutations, copy number changes and structural variants in a cell lineage and is responsible for carcinogenesis and resistance to cancer treatment [2]. Radiation has been shown to induce genomic and chromosomal instability but the impact of this on treatment response is not well elucidated.

Quantification of chromosomal instability through next generation sequencing analysis of bulk cancer tissue samples is prognostic in surgically resected NSCLC [3]. However even deep whole exome sequencing has limited resolution due to stromal contamination hindering the deconvolution of mutational signatures and copy number variants. We are establishing the DLP+ single cell sequencing (scSeq) technology that permits scSeq at an affordable scale. Amplification free ultra-low pass whole genome sequencing using DLP+ permits identification of clonal phylogenies therefore allowing the combination of single cell data to give clone specific single nucleotide resolution [4]. This technological advancement will allow high fidelity assessment of mutational signatures and aneuploidy in radiation resistant NSCLC.


Targeted therapies have been shown to generate reactive oxygen species which results in an adaptive upregulation of error prone DNA polymerases which generates genomic diversity and permits the development of resistance [5]. Error prone repair can be detected by mutational signature analysis but in the context of radiation induced DNA damage is likely to be clustered and need the greater resolution for detection permitted by DLP+ scSeq. We propose to obtain fresh tissue from patients with radiation resistant NSCLC through prospective tissue collection studies and perform scSeq to investigate the role of chromosomal instability and error prone DNA repair in radiation resistance. The project will compare data from irradiated and non-irradiated sites within the same patient and with patients who are radiation naive to answer the following questions:

• Is chromosomal instability greater in patients who have received prior radiotherapy?
• Is there evidence of evolutionary bottlenecking and a restriction in clonal diversity following radiotherapy?
• Is there greater evidence of immune evasion following radiotherapy to supress the pro-inflammatory signals from radiation induced micro-nuclei formation?
• Are mutational signatures of error prone DNA polymerase evident in the repair of clustered DNA damage from radiation?
• Is error prone DNA repair implicated in resistance to radiation?
• What is the effect of mutations in driver genes commonly mutated in NSCLC e.g. KEAP1, ATM, UBR5, MLH1 on mutational signatures and chromosomal instability of patients treated with radiation therapy?

Candidates will ideally have a background in cancer biology and some computational skills but will be supported to develop the required data science skills during this training fellowship.

For further details on how to apply please visit the CRUK CoL Centre RadNet studentships page: https://www.colcc.ac.uk/radnet-training-programme/


Potential research placements

1. Experience of sample setup in the Crick Advanced Sequencing Facility. Analysis and QC of DLP+ scSeq data. Dr Emelia Lim, Senior Post-doctoral fellow in the Charles Swanton lab, The Francis Crick Institute.

2. Bioinformatics training in the study of cancer evolution. Dr Nicky McGranahan, UCL Cancer Institute.

3. Bioinformatics training in cancer evolution, Dr Peter Van Loo, The Francis Crick Institute.

Funding Notes

Due to funding restrictions only UK / EU candidates are eligible to apply

References

1. Bradley, J.D. et al. Long-Term Results of NRG Oncology RTOG 0617: Standard- Versus High-Dose Chemoradiotherapy With or Without Cetuximab for Unresectable Stage III Non-Small-Cell Lung Cancer. J Clin Oncol. 2019; Dec 16: JCO1901162.

2. Burrell, R.A. et al.The causes and consequences of genetic heterogeneity in cancer evolution. Nature. 2013; Sep 19;501(7467):338-45.

3. Jamal-Hanjani, M. et al.; TRACERx Consortium. Tracking the Evolution of Non-Small-Cell Lung Cancer. N Engl J Med. 2017; Jun 1;376(22):2109-2121.

4. Laks, E. et al. Resource: Scalable whole genome sequencing of 40,000 single cells identifies stochastic aneuploidies, genome replication states and clonal repertoires. bioRxiv 411058; doi: https://doi.org/10.1101/411058

5. Russo M, et al. Adaptive mutability of colorectal cancers in response to targeted therapies. Science. 2019; Dec 20;366(6472):1473-1480.



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