The Pan Cancer GeCIP Domain will focus on the analysis of all types of cancer, using data from all tumour types in the 100,000 Genomes Project. There are complex patterns of genetic changes specific to tumour types, but also patterns of genetic changes that are seen across tumour types. Analyses of this type are very important and need thousands of samples to accurately detect the effects of genetic changes.
Below are the current subdomains for this domain. You can find the full details of the research proposed by this domain in the Pan–Cancer Detailed Research Plan.
|SUBDOMAIN||SUBDOMAIN LEAD/S||RESEARCH DESCRIPTION|
|Pan-cancer analysis||Dr Peter Campbell||Genomics England will sequence ~40,000 whole cancer genomes and matched germline DNA over the next 2-‐3 years. This represents a considerably larger collection of whole cancer genomes than any that currently exist, and will be of similar magnitude to efforts planned elsewhere in the world in the same time frame, including from the NCI and ICGC-‐2. There will be a GeCIP domain for each tumour type analysed by Genomics England, focusing on the genomic and clinical aspects of their particular cancer. We propose to establish a GeCIP with an aim to understand patterns of germline and somatic variation in cancer genomes across tumour types. We believe such a GeCIP would be exploring fundamentally different questions to individual tumour type domains, and would produce data that would assist the individual domains in their interpretation of the genomic data.|
|Cross-cancer analytics||Francesca D. Ciccarelli||The idea of an analytical subdomain specifically focused on the detection of rare and noncoding drivers comes from the observation that at present ~20% of sequenced cancer genomes have no somatic alterations in known cancer genes. We thus expect that the driver events of a considerable fraction of cancer samples sequenced in the context of the 100k Genome Project will remain undetected. The complete map of cancer driver mutations requires dedicated efforts towards the development of analytical approaches for the detection of rare and noncoding events.
The subdomain will bring together computational cancer biologists, mathematicians and statisticians with different and complementary skills from three leading UK Institutions, namely King’s College London, CRUK London Research Institute, and University of Oxford.
|Pan-cancer drug therapy toxicity||Dr. Jean E Abraham and Professor Paul Pharoah||The aim of the Pan-Cancer Drug Therapy Toxicity Genomics England Clinical Interpretation Partnership (GeCIP) Consortium is to create a collaborative environment in which consortium members with an existing interest in cancer drug therapy related toxicities can work together to utilise the national resource that the 100,000 Genomes Project will provide. The consortium has representation from many Genomic Medicine Centres, and the NRCI Clinical Study Groups.|
|HOX gene clusters in cancer||Prof Richard Morgan||The HOX genes are a family of transcription factors characterized by highly conserved DNA- and co-factor binding domains. This conservation has been driven by their roles in some of the most fundamental patterning events that underlie early development. Most notable of these is the patterning of the anterior to posterior axis, for which a precise spatial and temporal order in the expression of HOX genes is required. This is achieved in part through a chromosomal arrangement whereby HOX genes are present in closely linked clusters allowing the sharing of common enhancer regions. In mammals there are four such clusters (A-D), containing a total of 39 HOX genes. The relative position of each HOX gene 3’ to 5’ within the cluster is reflected in a number of key attributes, including the spatial and temporal order of expression, whereby the 3’ most genes are expressed earlier than their 5’ neighbors. The nomenclature of the HOX genes reflects this precise chromosomal ordering, with members of each cluster being numbered with respect to the 3’ end, thus for example, the 3’ most member of cluster B is HOXB1.|
|Radiogenomics (genomics of normal tissue toxicity from radiotherapy)||Prof Neil Burnet||There are ~2 million cancer survivors in the UK, a figure predicted to rise by >3% per year. Nearly half have undergone radiotherapy (RT). RT is used to treat >100,000 patients with curative intent in the UK each year, including many with four of the solid malignancies covered by the 100K Genomes project: lung, breast, prostate and colorectal. Many patients suffer with moderate or serious long-term side effects. For example, about a third of prostate cancer patients can experience diarrhoea, urgency, rectal bleeding or urinary incontinence. A smaller proportion suffers severe toxicity. Toxicity is not recorded well in routine clinical practice, so that a simple review of treated patients is not sufficient to define a RT toxicity phenotype.|
|Cancer symptomology||Dr Ollie Minton PhD FRCP FHEA||The subdomain proposes to study broadly cancer symptomology with a specific focus on:
1) Fatigue & rehabilitation in patients successfully treated for cancer: Survivorship.
2) Symptom burden on adjuvant (or curative intent) cancer treatment – including fatigue, pain, breathlessness etc.: Supportive care in cancer.
Symptom burden in patients who have metastatic cancer and a poor prognosis (less than a year on average): Palliative care in cancer.
|Cancer Prevention||Prof Dion Morton||This GeCIP will undertake multidisciplinary integrated cancer-prevention research and will work collaboratively with cancer-specific domains to ensure prevention is central to research endeavour. Further added value is envisaged through interaction with cardiovascular and metabolism GeCIPs to interrogate shared risk factors and develop novel stratified prevention strategies which will have benefits beyond cancer prevention. This presents an exceptional opportunity to interrogate real-time genomic, transcriptomic, metabolomic and phenotypic data and dissect cancer susceptibility and therapeutic interventions in translational research from in-vivo organoid modelling to human intervention trials.|