Paediatric Solid Tumour Biology and Therapeutics Group

Professor Louis Chesler’s group is investigating the genetic causes for the childhood cancers, neuroblastoma, medulloblastoma and rhabdomyosarcoma. 

Research, projects and publications in this group

Our group's aim is to improve the treatment and survival of children with neuroblastoma, medulloblastoma and rhabdomyosarcoma.

The goal of our laboratory is to improve the treatment and survival of children with neuroblastoma, medulloblastoma and rhabdomyosarcoma, three paediatric solid tumours in which high-risk patient cohorts can be defined by alterations in a single oncogene. We focus on the role of the MYCN oncogene, since aberrant expression of MYCNis very significantly associated with high-risk in all three diseases and implies that they may have a common cell-of-origin.

Elucidating the molecular signalling pathways that control expression of the MYCN oncoprotein and targeting these pathways with novel therapeutics is a major goal of the laboratory. We use a variety of innovative preclinical drug development platforms for this purpose.

Technologically, we focus on genetically engineered cancer models incorporating novel imaging (optical and fluorescent) modalities that can be used as markers to monitor disease progression and therapeutic response.

Our group has several key objectives:

  • Mechanistically dissect the role of the MYCN oncogene, and other key oncogenic driver genes in poor-outcome paediatric solid tumours (neuroblastoma, medulloblastoma, rhabdomyosarcoma).
  • Develop novel therapeutics targeting MYCN oncoproteins and other key oncogenic drivers
  • Develop improved genetic cancer models dually useful for studies of oncogenesis and preclinical development of novel therapeutics.
  • Use such models to develop and functionally validate optical imaging modalities useful as surrogate markers of tumour progression in paediatric cancer.

Professor Louis Chesler

Clinical Senior Lecturer/Group Leader:

Paediatric Solid Tumour Biology and Therapeutics Professor Louis Chesler (Profile pic)

Professor Louis Chesler is working to understand the biology of children’s cancers and use that information to discover and develop new personalised approaches to cancer treatment. His work focuses on improving the understanding of the role of the MYCN oncogene.

Researchers in this group

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Email: [email protected]

Location: Sutton

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Phone: +44 20 3437 6124

Email: [email protected]

Location: Sutton

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Phone: +44 20 3437 3617

Email: [email protected]

Location: Sutton

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Phone: +44 20 8722 4186

Email: [email protected]

Location: Sutton

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Phone: +44 20 3437 3501

Email: [email protected]

Location: Sutton

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Email: [email protected]

Location: Sutton

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Phone: +44 20 8722 4361

Email: [email protected]

Location: Sutton

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Email: [email protected]

Location: Sutton

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Phone: +44 20 3437 6118

Email: [email protected]

Location: Sutton

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Phone: +44 20 3437 6021

Email: [email protected]

Location: Sutton

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Phone: +44 20 3437 6196

Email: [email protected]

Location: Sutton

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Phone: +44 20 3437 6258

Email: [email protected]

Location: Sutton

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Email: [email protected]

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Email: [email protected]

Location: Sutton

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Phone: +44 20 8722 4527

Email: [email protected]

Location: Sutton

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OrcID: 0000-0003-3977-7020

Phone: +44 20 3437 6109

Email: [email protected]

Location: Sutton

I obtained an MSci in Biochemistry from the University of Glasgow in 2018. In October 2018 I joined the labs of Dr Michael Hubank and Professor Andrea Sottoriva to investigate the use of liquid biopsy to monitor clonal frequency and emergence of resistance mutations in paediatric cancers.

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Email: [email protected]

Location: Sutton

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Email: [email protected]

Location: Sutton

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Email: [email protected]

Location: Sutton

Professor Louis Chesler's group have written 113 publications

Most recent new publication 4/2025

See all their publications

Vacancies in this group

Working in this group

Postdoctoral Training Fellow

  • Chelsea
  • Structural Biology
  • Salary Range: £45,600 - £55,000 per annum
  • Fixed term

Under the leadership of Claudio Alfieri, we are seeking to appoint a Postdoctoral Training Fellow to join the Molecular Mechanisms of Cell Cycle Regulation Group at the Chester Beatty Laboratories, Fulham Road in London. This project aims to investigate the molecular mechanisms of cell cycle regulation by macromolecular complexes involved in cell proliferation decisions, by combining genome engineering, proteomics and in situ structural biology. For general information on Post Doc's at The ICR can be found here. Key Requirements The successful candidate must have a PhD in cellular biochemistry and experience in Cryo-EM and CLEM is desirable. The ICR has a workforce agreement stating that Postdoctoral Training Fellows can only be employed for up to 7 years as PDTF at the ICR, providing total postdoctoral experience (including previous employment at this level elsewhere) does not exceed 7 years Department/Directorate Information: The candidate will work in the Molecular Mechanisms of Cell Cycle Regulation Group within the ICR Division of Structural Biology headed by Prof. Laurence Pearl and Prof. Sebastian Guettler. The division has state-of-the-art facilities for protein expression and biophysics/x-ray crystallography, in particular the Electron Microscopy Facility is equipped with a Glacios 200kV with Falcon 4i detector with Selectris energy filter and the ICR has access to Krios microscopes via eBIC and the LonCEM consortium. We encourage all applicants to access the job pack attached for more detailed information regarding this role. For an informal discussion regarding the role, please contact Claudio Alfieri via Email on [email protected]

Research Group Leader, ICR Clinical Trials and Statistics Unit (ICR-CTSU)

  • Sutton
  • Clinical Trials and Statistics Unit
  • Salary: From £66,092 pa
  • Permanent

Role Summary The Group Leader will lead a component of ICR-CTSU’s portfolio of clinical trials research. The post holder will further develop and grow the portfolio in line with ICR-CTSU’s overall strategy and take responsibility for a number of ongoing trials as well as the development of new trials. We seek an experienced biostatistician with a strong research interest in clinical trials methodology and a passion for direct involvement in the oversight and leadership of academic clinical trials. The successful candidate will work closely with the Director of ICR-CTSU to further enhance the Unit’s internationally recognised strength in clinical trial design, conduct and analysis. The post holder will be expected to make a substantial independent intellectual contribution to clinical trials projects and be proactive in leading and contributing to broad initiatives that enhance the overall effectiveness of ICR-CTSU. The appointee will contribute to the overall scientific life of the ICR including the newly established ICR/Royal Marsden Hospital’s Centre for Trials and Population Data Science, by providing mentorship to more junior colleagues and acting as an academic leader. We seek an individual who will work closely and collaboratively with other faculty/Group Leaders at ICR and with international/national key opinion leaders to extend the breadth and depth of ICR-CTSU’s biologically rich clinical trials portfolio. In partnership with clinical opinion leaders, s/he will generate research funds to conduct and deliver clinical trials research at the international forefront. Presentation at national and international conferences, production of top-quality research outputs and substantial professional contribution to wider clinical trial network bodies are expected. Enthusiasm for team-based science in a collaborative interdisciplinary environment is essential. The appointment will be based on track record and the ability and willingness to engage in team science. The successful appointee will have access to ICR’s successful PhD training programme and core facilities. Key Requirements Higher degree (MSc or PhD) in medical statistics/biostatistics or an allied field (e.g. public health, epidemiology, data science) with relevant work experience Significant experience as a clinical trials, medical or bio-statistician within the academic or commercial sector A desire to apply existing and novel statistical methods to the requirements of a diverse range of statistical problems A broad understanding of cancer research Ability to lead a Clinical Trials Unit based research group As part of your online application, you will be required to upload your full CV which will pre-populate your application form, you will also be asked to attach the following documents and failure to do so will mean your application cannot be considered on this occasion: Lists of major publications, achievements, research grants and distinctions. A PDF of a maximum of five key publications, or other research outputs (e.g. patents) that best demonstrate previous productivity or a single document giving hyperlinks to these outputs. You must also complete the personal statement section of the application form in the format of a cover letter including the names and contact details of three academic referees Department/Directorate Information: Division of Clinical Studies Clinical Trials and Statistics Unit (ICR-CTSU) The ICR-CTSU is a Cancer Research UK-funded, internationally recognised methodologist led clinical trials unit, providing cancer-focused clinical trial research expertise. We lead pioneering, efficient, high-quality, and impactful trials across the phases. Our expertise ranges from experimental medicine early phase studies exploring biological efficacy to trials which may deliver widespread change to routine practice, underpinned by applied methodology to drive forward clinical trial innovation. See our clinical trials Joining as a group leader, you will be given outstanding support to help you to continue to develop in your career. Along with a start-up package of funding, you will also have access to resources to establish your group, including support for recruiting key group members, such as PhD students and postdoctoral researchers. We encourage all applicants to access the job pack attached for more detailed information regarding this role. For an informal discussion regarding the role, please contact Professor Emma Hall ([email protected])

Industrial partnership opportunities with this group

Opportunity: A novel test for predicting future cancer risk in patients with inflammatory bowel disease

Commissioner: Professor Trevor Graham

Recent discoveries from this group

20/03/25

Scientists have developed a revolutionary AI ‘fingerprint’ technology that can accurately show how cancer cells respond to new drugs, by simply observing changes to their shape.

The new technology, which has been developed by a team at The Institute of Cancer Research, London, will allow researchers to quickly assess the ability of new drugs to reach their intended target, slashing years off the drug development process – allowing new drugs to reach patients faster.

The scientists believe their approach could also save millions of pounds by reducing investment and effort in projects that go on to fail.

Using 3D imaging of cells

Crucially, the tech helps scientists match the right drugs to the right patients, by enabling them to design clinical trials for specific cancer sub-types at a much earlier stage – thereby avoiding costly clinical trial failures.

The team from The Institute of Cancer Research (ICR), trained the AI technology using almost 100,000 3D images of melanoma skin cancer cells – taken with cutting-edge microscopy – and geometric deep learning to analyse the information about the shape of the cells.

Previous technologies have only been trained on flat, 2D images of cells on a microscope slide – which don’t take into account the 3D shape of a cell, as it appears in the body.

99.3% accuracy

In research published in the journal Cell Systems, the team treated the cells with a variety of drugs and used their newly created AI tool to learn which shape changes were caused by each drug.

They showed that the tool could predict which drug was being used on the cells with up to 99.3 per cent accuracy and it could even distinguish between the shape changes caused by drugs which, although they target different proteins, ultimately have very similar effects on the cell.

The researchers showed that the AI technology was accurately learning the underlying biochemical changes occurring when melanoma cells were treated with certain drugs. It was able to identify important proteins that the team are now exploring as potential targets to develop new drugs.

Cutting out stages in the drug development process

The team also showed their AI tool worked for other cell types – including red blood cells, cells in brain vessels, and stem cells – indicating that other diseases could benefit from this technology.

Developing a new drug usually takes 10 to 12 years. However, the ICR team believe that using their AI technology early in this process could cut out numerous steps in the preclinical phase – slashing it from three years to three months – and reduce the time taken to trial new drugs by up to six years, as patients most likely to benefit could be determined earlier, and side effects could be predicted.

The AI tool outperformed other similar algorithms as it is the first to use 3D information on a cell’s shape – the full picture of the cell, as it would appear in a body – instead of only 2D information on a microscope slide. The tool was also trained to take into account the variability in a population of cells, while other algorithms look either at single cells or take an average of cell shape across the population.

Implementing the tool into the ICR's drug discovery research

This research was funded by the ICR itself, which is both a research institute and a charity, and which has a strong track record of drug discovery – the ICR has discovered more cancer drugs than any other academic institute in the world.

The researchers will work with teams within the ICR’s Centre for Cancer Drug Discovery to implement their AI technology into the process of discovering targeted protein degraders – a new type of drug that co-opts a cell’s natural waste disposal system to remove the offending protein.

This research was also funded by Cancer Research UK and the Terry Fox Run UK. The research team has patented their tool and set up a spinout company, Sentinal4D, to take the innovation into the next phase and implement it into the drug discovery and development pathway.

Sentinal4D is the latest spinout company to be announced by the ICR and follows recent spinout successes including the foundation of Monte Rosa Therapeutics, which is now listed on New York’s NASDAQ stock exchange.

'The tool is so powerful that we will be able to streamline the drug discovery process'

Professor Chris Bakal, Professor of Cancer Morphodynamics at The Institute of Cancer Research, London, said:

“3D cell shape is like a fingerprint of cellular state and function – it’s a previously untapped reservoir of information. Using AI, we can decode this fingerprint and reveal how cells respond to drugs. The tool that we’ve created is so powerful that we will be able to streamline the years-long drug discovery process, saving both time and money. Patients with cancer need new treatment options as quickly as possible, so speeding up this process will be hugely valuable.”

Dr Matt De Vries, co-founder and Chief Technology Officer of Sentinal4D, said:

“With the AI tool we’ve created, it will be possible to predict how effective a drug will be and if there are likely to be any side effects. The tool could work for a range of diseases, as we’ve shown that it will pick up the changes in shape for a number of different cell types and drugs. Our new company, Sentinal4D, aims to use this tool to eliminate the guesswork and increase the chances of success in the subsequent phases of drug development – to bring treatments to patients sooner.”

Professor Kristian Helin, Chief Executive of The Institute of Cancer Research, London, said:

“The ICR is dedicated to discovering new drugs to meet the challenges of cancer evolution and drug resistance, so cancer patients have more treatment options – extending and saving lives. This latest technology builds on years of work at the ICR to understand cancer cell shape and to use artificial intelligence to analyse data. I look forward to seeing this technology being used to develop new medicines that have a real impact for people with cancer."