Garnett Group

Translational Cancer Genomics

We investigate how abnormalities in the DNA of cells contribute to cancer and impact on patient responses to therapy. This provides fundamental insights into disease mechanisms with implications for the development of improved therapies.

Research foci

There are currently four complementary research focuses in my laboratory:

  • The genomics of drug sensitivity. High-throughput drug screens in human cancer cell cultures to identify genetic features of cancer cells that are predictive of drug sensitivity.
  • Mapping synthetic-lethal dependencies in cancer cells. Genome-wide CRISPR-Cas9 synthetic-lethal screens in cancer cell lines to identify potential new oncology drug targets.
  • A new generation of organoid cancer models. Methods for the derivation, characterisation and use of a new set of cancer organoid in vitro cell culture models.
  • Tumour-immune cell interactions. The use of patient-derived in vitro co-cultures to understand mediators of tumour and immune cell interactions.

These studies are intergrated into our Cancer Dependency Map initiative, which aims to identify all dependencies in cancer cells to help guide future precision cancer medicines.


Cancer is a genetic disease caused by the accumulation of changes within the DNA of cells that confers a growth and survival advantage. Cancer is not just one disease, but many different diseases, each with a different spectrum of underlying genetic causes. The functional consequence of these genetic changes in the genes of healthy and cancer cells is often poorly understood, and how they contribute to disease is often unclear. Furthermore, these genetic changes can impact on patient responses to therapy and consequently can be used to select patients most likely to benefit from a specific treatment.

The Translational Cancer Genomics team investigates how genetic alterations in cancer contribute to disease and impact on response to therapy. Our research is at the interface of cancer genomics, cell biology and cancer therapeutics and employs high-throughput biology approaches together with detailed mechanistic studies.

The team have state-of-the-art facilities to perform their research including extensive robotics, acoustic dispensing, high-content microscopy, CRISPR and chemical libraries, and access to core Sanger IT and genomics infrastructure.

Seminars and talks from the team, as well as tutorials for our public databases, are available to view on Twitter.

The genomics of drug sensitivity

Heatmap of IC50s of 83 Compounds against a Panel of Colon Cancer Organoids

The team uses high-throughput drug sensitivity screens in highly annotated human cancer cell cultures to identify genetic features of cancer cells that are predictive of drug response.

The collection of cancer cell models to study drug response includes >1000 human cancer cell lines, organoids, and engineered mouse and human cells. Cell culture models are highly annotated at the level of the genome (DNA sequencing), transcriptome (gene expression and RNAseq), epigenome (DNA methylation), and proteome. The team perform single-drug and combination screens with hundreds of anti-cancer compounds across their large collection of cell culture models to detect drug sensitivity in specific tissue and genetic sub-types.

The results from these screens are used to improve the design of clinical trials through the identification of patient populations most likely to respond to a therapy.

This research is performed in partnership with the laboratory’s of Ultan McDermott and Mike Stratton within the Cancer Genome Project at the Sanger Institute. The results of this work are available from the Genomics of Drug Sensitivity in Cancer database.

Mapping synthetic-lethal dependencies in cancer cells

Mathew’s group are performing genome-wide CRISPR-Cas9 synthetic-lethal screens in cancer cells to identify potential new oncology drug targets in defined genetic backgrounds.

The complexity and diversity of cancer genomes represents a significant challenge when developing new cancer therapies. Specifically, identifying cellular signalling nodes and processes whose perturbation selectively kills cancer cells while sparing normal cells remains acutely difficult. This is because our understanding of which proteins are necessary for cancer cell survival is incomplete. Furthermore, our understanding of cellular networks and processes is relatively poor in normal cells, let alone in the context of cancer cells with their myriad of molecular alterations. Thus, systematic and unbiased approaches to identify critical dependencies in cancer cells could significantly expand the repertoire of new drug targets for future development.

Genome-editing technologies such as CRISPR-Cas9 (clustered regularly interspaced short palindromic repeats) are a powerful tool for studying gene function in normal and diseased cells. This approach uses a single guide RNA (sgRNA) to recruit the Cas9 endonuclease to a desired genomic loci to create double strand breaks, which are repaired through an error prone process resulting in targeted gene inactivation. Taking advantage of the programmable nature of the sgRNA, it is now possible to use a library of sgRNAs to perform genome-wide functional genetic screens across a diverse array of cellular models and systems.

Mathew’s group, in collaboration with the laboratory of Kosuke Yusa, are exploiting CRISPR-Cas9 genome-editing technology to systematically identify new drug targets using genome-wide ‘synthetic lethal’ screens in cancer cell lines. The identification of acute sensitivities, which occurs within specific molecular/genetic sub-types, could provide novel opportunities for genetically targeted therapeutic intervention.  The results of our CRISPR screens and target prioritisation are available through the Project Score database.

A new generation of organoid cancer models

Approximately 1,000 human cancer cell lines are available to scientists worldwide and this has been a useful resource for cancer research. However as we enter the era of precision medicine, poor representation of some cancer types, insufficient numbers to capture the genetic diversity of cancer, lack of clinical outcome data and lack of comparison to normal reference sample limit their use.

Novel cell culturing methods such as organoid derivation have revolutionised our ability to derive cell line models from both healthy and diseased tissue, and have the potential to overcome these limitations.

We are generating and characterising new patient-derived cancer cell line models from different tumour types as experimental tools. These cell lines are being characterised at the level of the genome and transcriptome, profiled for differential sensitivity to anti-cancer therapies, and are being made available to the research community.  These models are being generated as part of an international collaboration called the Human Cancer Model Initiative, led by the Sanger Institute, the U.S. National Cancer Institute, and Hubrecht Organoid Foundation.

Organoid models generated by Sanger are for sale through American Type Culture Collection.

Our Cell Model Passports database hosts cell model genetic and functional datasets.

We anticipate that this highly annotated resource will have broad applications and serve to catalyse a new wave of discovery in fundamental cancer biology and therapeutics.

Tumour-immune cell interactions

Immunotherapies against PD1 and CTLA-4 are effective for the treatment of multiple tumour types and lead to durable responses for some patients.  However, these therapies – referred to as checkpoint blockade – are not effective for all cancer types and the duration of responses remains poorly understood.  The pre-clinical development of new immunotherapies is difficult because of a lack of human models systems that effectively mimic the interaction of the tumour and immune system.

We are developing new in vitro co-cultures models of patient-derived organoids together with immune cells to study the cellular factors that mediate immune cell mediated tumour cell killing.

The development of these models, and their use for the study of tumour-immune cell interactions, could lead to a deeper understanding of factors influencing patients responses to checkpoint blockade and new therapuetic hypotheses.

Core team

Photo of Mrs Angham Al Saedi

Mrs Angham Al Saedi

Advanced Research Assistant

Photo of Syd Barthorpe

Syd Barthorpe

Senior Scientific Manager

Photo of Alexandra Beck

Alexandra Beck

Project Manager

Photo of Sophie Bell

Sophie Bell

Research Assistant

Photo of Mr Shriram G Bhosle

Mr Shriram G Bhosle

Principal Software Developer

Photo of Dr Matthew Coelho

Dr Matthew Coelho

Cancer Research UK Career Development Fellow 

Photo of Cansu Dincer

Cansu Dincer

PhD Student

Photo of Maria Garcia-Casado

Maria Garcia-Casado

Research Assistant

Photo of Dr Frederik Gibson

Dr Frederik Gibson

Cellular screening specialist

Photo of Mr James Gilbert

Mr James Gilbert

Senior Software Developer

Photo of Dr Carmen Herranz-Ors

Dr Carmen Herranz-Ors

Postdoctoral Fellow

Photo of Dr Liliya Kopanitsa

Dr Liliya Kopanitsa

Advanced Research Assistant

Photo of Dr Howard Lightfoot

Dr Howard Lightfoot

Principal Bioinformatician

Photo of Dr Katrina McCarten

Dr Katrina McCarten

Postdoctoral Fellow

Photo of Dr Clare Pacini

Dr Clare Pacini

Principal Bioinformatician

Photo of Dr Saroor Patel

Dr Saroor Patel

Senior Staff Scientist

Photo of Gabriele Picco

Gabriele Picco

Postdoctoral Fellow

Photo of Mamta Sharma

Mamta Sharma

Senior Technical Specialist

Photo of Rebecca Shepherd

Rebecca Shepherd

Senior Bioinformatician

Photo of Tzen Szen Toh

Tzen Szen Toh

Wellcome Trust Clinical PhD Fellow 

Photo of Samantha Walker

Samantha Walker

Research Assistant

Photo of Mr Alex Watterson

Mr Alex Watterson

Advanced Research Assistant

Photo of Wendy Yang

Wendy Yang

Senior Web Developer

Previous team members

Photo of Rizwan Ansari

Rizwan Ansari

Advanced Research Assistant

Photo of Dr Fiona Behan

Dr Fiona Behan

Postdoctoral Fellow

Photo of Graham Bignell

Graham Bignell

Senior Staff Scientist

Photo of Sophie Brocklesby

Sophie Brocklesby

Research Assistant

Photo of Jessica Cantwell

Jessica Cantwell

Research Assistant

Photo of Dr Thomas Cokelaer

Dr Thomas Cokelaer

Senior Bioinformatician

Photo of Dr Lisa Dwane

Dr Lisa Dwane

Postdoctoral Fellow

Photo of Luke Farrow

Luke Farrow

Research Assistant

Photo of Hayley Francies

Hayley Francies

Senior Staff Scientist

Photo of Emma Goffin

Emma Goffin

Former Advanced Research Assistant at the Sanger Institute

Photo of Emanuel Gonçalves

Emanuel Gonçalves

Postdoctoral Researcher

Photo of Caitlin Hall

Caitlin Hall

Research Assistant

Photo of Dr Patricia Jaaks

Dr Patricia Jaaks

Staff Scientist

Photo of Maciej Jablonski

Maciej Jablonski

Research Assistant

Photo of Megan Jukes

Megan Jukes

Research Assistant

Photo of Genevieve Leyden

Genevieve Leyden

Research Assistant

Photo of Ermira Lleshi

Ermira Lleshi

Research Assistant

Photo of Mr Iman Mali

Mr Iman Mali

Research Assistant

Photo of Emily Mallett

Emily Mallett

Research Assistant

Photo of Mr Kieron May

Mr Kieron May

Research Assistant

Photo of Ms Anne Maria McLaren-Douglas

Ms Anne Maria McLaren-Douglas

Senior Research Assistant

Photo of Tatiana Mironenko

Tatiana Mironenko

Senior Research Assistant

Photo of James Morris

James Morris

Research Assistant

Photo of Riccardo Panero

Riccardo Panero

Postdoctoral Fellow

Photo of Rachel Pooley

Rachel Pooley

Research Assistant

Photo of Stacey Price-Weight

Stacey Price-Weight

Head of Technical Development - DNAP

Photo of Mrs Laura Richardson

Mrs Laura Richardson

Advanced Research Assistant

Photo of Mr Gabriel Robert-Tissot

Mr Gabriel Robert-Tissot

Research Assistant

Photo of Dr Marie Shamseddin

Dr Marie Shamseddin

Postdoctoral Fellow

Photo of Ms Fran Thomas

Ms Fran Thomas

Research Assistant

Photo of Charlotte Tolley

Charlotte Tolley

Advanced Research Assistant

Photo of Dr Sara Valentini

Dr Sara Valentini

Genomic Surveillance Business Analyst and Continuous Improvement Lead

Photo of Sara Vieira

Sara Vieira

Advanced Research Assistant

Related groups


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