GeCIP Research Registry

Members of the GeCIP and Discovery Forum are asked to register all of the projects they are currently working on. Each project is required to have a lay summary on registration which would be made publicly available. If you believe that some of these are not written in lay speak and you would like to help rewrite these and discuss the project with the project lead please give us an email to [email protected] containing the name and registry ID of the project and we will help to coordinate with you and the researchers.

293 Results

Minimal mapping of 12p amplification in TGCT

Testicular germ cell tumours (TGCTs) are highly aneuploid, with large-scale copy number variations frequently observed. Gain of chromosomal material at 12p is observed in almost all tumours and is thought to be a critical event in the development of TGCT. To date, efforts to identify the critical gene(s) targeted by this event through minimal mapping of 12p amplifications have proven inconclusive, in part due to the low resolution of the technologies used. We propose to use TGCT whole genome sequencing data to delineate these events with a much higher degree of precision than previously achieved, with the aim of identifying the associated critical driver(s).

Project lead: Clare Turnbull
Domain: Testicular cancer


Characterising predisposition to rhabdomyosarcomas and other DICER1-related childhood tumours

Childhood cancers are believed to be more strongly linked to inherited gene alterations compared to adult cancers, where family background explains only a small proportion of patient cases. We will use genomic data available from Genomics England to examine the genetic variations that predispose these children to cancer. This work will help to better understand the causes of cancer in childhood, aid the earlier diagnosis, therapy and possibly even pave the way to a cure for children at the initial stages of developing these cancers.

Project lead: Mae Goldgraben; Marc Tischkowitz;
Domain: Childhood solid cancers; Inherited cancer predisposition


Hyper/ultramutation in colorectal and endometrial cancer

Between one sixth and one third of bowel and womb cancers carry a much higher than average number of errors in their DNA. We know that in some settings, this is associated with better prognosis and benefit from particular therapies, but the explanations for this are only partially understood. We propose to address this by analysis of the substantial number of these cancers in the Genomics England 100,000 Genomes Project.

Project lead: David Church; Ian Tomlinson;
Domain: Colorectal cancer; Ovarian cancer


A Convolutional Filtering Approach for Mutation Signature Discovery

Mutation signatures in cancer describe certain patterns of DNA aberrations that tend to recur in cancers and are potentially due to the property of a specific DNA-damaging mechanism. At present, these signatures are typically limited to looking at small sequence fragments of 3- or 5-base pairs but it is possible that signatures may exist on larger scales. Unfortunately current mutation signature discovery techniques do not scale well to longer sequence fragments. We have developed a new approach using ideas from the machine learning field of “Deep Learning” to enable us to discover long-range mutation signatures.

Project lead: Christopher Yau
Domain: Pan-cancer; Quantitative methods, machine learning and functional genomics


Pseudotemporal modelling for cancer progression

The majority of cancer patients in the 100,000 Genomes Project will have a single tumour biopsy sequenced limiting our ability to learn from any individual how their tumour has evolved and how it might evolve. The purpose of this project is to develop a “pseudotemporal” machine learning algorithm that is able consider a cohort of patients, each having a single tumor biopsy sequenced, and to use all the information across patients together to identify common cancer progression trajectories. The identification of these trajectories will allow us to understand how cancers develop and the potential molecular prognosis for patients. It will allow us to understand core mutational processes that drive cancer development but also factors that lead certain cancers to develop specific characteristics.

Project lead: Christopher Yau
Domain: Pan-cancer; Quantitative methods, machine learning and functional genomics


Genetic Predisposition to Multiple Primary Cancers

Individuals affected by multiple different cancers may have underlying genetic factors contributing to their disease. Identifying these potential risk factors, both known and new, will aid the clinical management of these patients.

Project lead: Clare Turnbull
Domain: Inherited cancer predisposition


Landscape of Pathogenic Germline Variants in Cancer

Deciphering the inherited genetic basis of cancer has three key clinical benefits: (i) prevention of cancer by identifying and managing genetically high-risk individuals; (ii) identification of new targets for anticancer therapy and prophylaxis; and (iii) providing a route to better understanding of cancer at a fundamental level.

Project lead: Ian Tomlinson; Richard Houlston;
Domain: Inherited cancer predisposition


Identification and characterisation of endometrial cancer susceptibility variants and genes

Womb cancer is the most common gynaecological malignancy in the Western world, affecting 100,000 women a year in Europe alone. Identifying rare and common genetic variants which predispose women to this disease will enable doctors to target screening and prevention measures towards the women at the highest risk, whilst avoiding unnecessary interventions in those at lowest risk. It may also be possible to identify patients at risk of toxic side-effects from treatment or who might be suitable for intensive therapies. We will compare the genotypes of women with and without womb cancer in the Genomics England 100,000 Genomes Project in order to find genetic variants which are associated with risk of this disease.

Project lead: Deborah Thompson
Domain: Ovarian cancer


Identification of early driver somatic mutations to predict cancer

We will identify and validate early mutations leading to cancer that can be used for new diagnostic and prognostic tests for cancer prevention.

Project lead: King Wai Lau
Domain: Pan-cancer


Identification of genetic variants associated with primary immunodeficiency

The human immune system has evolved to protect us from a bewildering array of germs, a job it usually performs unnoticed. We can think of the immune system as a network of armed forces that cooperate to defend us. When one element of these defences is weakened, it can leave us critically exposed to certain threats. It stands to reason that the same weapons also pose a threat if mistakenly targetted to our own tissues, so the healthy immune system is actively held in check. Severe and unusual infections, and/or self-directed, autoimmune diseases, can reflect an underlying problem in the genetic blueprint for the immune system. By analysing the DNA of affected individuals, and comparing its sequence with that of healthy family members, the current research aims to uncover the genetic origins of immune disorders. This knowledge may assist doctors and patients/families in making clinical decisions, and will add to scientific understanding of the healthy immune system.

Project lead: Sophie Hambleton
Domain: Immune disorders


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