UCL Cancer Institute


Cancer Genome Evolution Research Group

Our lab focuses on using computational methods to explore the cancer genome and anti-tumour immunity within an evolutionary framework. We are based within the CRUK-UCL Lung Cancer Centre of Excellence, located in the UCL Cancer Institute.

Group Leader: Dr Nicholas McGranahan 

A new position has become available to join McGranahan Lab. We are seeking a collaborative
 and self-motivated bioinformatician Research Fellow/ Senior Research Fellow to work on cancer evolution and deciphering the impact of treatment on the acquisition of somatic alterations and the immune microenvironment.
Apply by: Friday 23 September 2022

Details and apply


The cancer genome contains within it an archaeological record about its past, with each genomic event representing a scar from the mutational processes that have been active during a tumour’s life history. 

The advent of next-generation sequencing, coupled with its exponential cost decrease, has led to the sequencing of exomes and entire cancer genomes at a large-scale. Indeed, consortia such as TCGA (the Cancer Genome Atlas) and ICGC (the International Cancer Genome Consortium) have made thousands of sequenced cancer genomes and exomes publicly available. 

To date, this data has been used to reveal many of the key genomic events involved in cancer, distinguishing key driver and passenger mutations (Lawrence et al., 2014), as well as shedding light on some of the key mutational processes shaping cancer evolution (Alexandrov et al., 2013). However, we have learned less than initially anticipated from these sequencing projects, and targeted therapies that have focused on established driver events have not appreciably improved cancer patients’ overall survival times. 

Tumour heterogeneity

A primary obstacle to success of personalized medicine is intra-tumour heterogeneity (McGranahan and Swanton (2015)). Recent work from us and others have demonstrated not only that the genomic landscape of each tumour is unique but also even different regions of the same tumour can be vastly divergent (Burrell et al., 2013). This intra-tumour heterogeneity is likely a key cause of drug resistance and therapeutic failure. 

While intra-tumour heterogeneity may confound treatment success, it can also serve to illuminate the evolutionary history of tumours (Greaves, 2015; McGranahan and Swanton, 2015).


We utilize state-of-the-art bioinformatics and evolutionary methods to decipher cancer genome evolution and to explore patterns of tumour growth and development across cancers, focussing on lung cancer. Ultimately, we aim to gain a deeper understanding of the rules that govern tumour evolution and anti-tumour immunity to improve patient treatment.  

We recently developed a novel tool to enable exploration of T cell content in DNA sequencing data.

Another example of a bioinformatics tool we have recently developed to understand immune escape, is LOHHLA, Loss OHeterozygosity in Human Leukocyte Antigen.

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LOHHLA is available at bitbucket.org/mcgranahanlab/lohhla

Selected publications