About the Program

Identifying individuals with inherited genetic cancer susceptibility prevents cancer and saves lives through effective targeting of resource for enhanced screening and/or prevention to those at highest risk.

 

Recent advances in sequencing technology have catalysed dramatic expansion in genetic cancer susceptibility testing, with roll-out of population-level screening for cancer susceptibility likely imminent. 

Split into six interlinked work-packages, CanGene-CanVar aims to create an interface between NHS and research settings that will underpin future expansions in genetic testing access aimed at population risk stratification. 

  1. Collection, linkage and analyses of nationally-collected genomic and cancer data

  2. Data Clinical Laboratory Resources for Genomic Cancer Variant Interpretation

  3. Dynamic Evidence-based Clinical Guidance

  4. Patient-facing decision-making tools

  5. Medical Education

  6. Ethics, Governance and Policy

Through the research infrastructure for centralised data linkage, we will generate for tomorrow better evidence regarding cancer genetic risk. In concert, through clinical-facing resources, tools and education we shall ensure the best evidence available today is applied effectively and consistently across our national NHS clinical-laboratory system.

Our vision is to catalyse UK research and infrastructure development for cancer genetic risk estimation to improve clinical translation.

 

This will ensure coordinated, safe, and effective delivery of clinical cancer susceptibility genetics, enabling best outcomes for patients, optimum impact from resources used for saving lives from cancer through screening/prevention, and avoidance of harm and litigation through misinterpretation and over-diagnosis. 

Work Package 2

Data Clinical Laboratory Resources for Genomic Cancer Variant Interpretation

Work Package Investigators

  • Prof. Clare Turnbull

  • Prof. Richard Houlston

Through Work-Package 2 we shall leverage the

collapsed total variant counts from Work-Package 1

and integrate them with multiple available datasets,

in-silico variant predictions, selected datasets from

the literature and multiple functional datasets made

available from collaborators.

Clinical decision trees using ACMG (American College of Medical Genetics) criteria and
machine learning approaches will be applied.

The constituent data and derived interpretations will be made available to the NHS laboratories through CanVar-UK, an interactive interface, to be co-developed with NHS England.

Work Package 1

Collection, linkage and analyses of nationally-collected genomic and cancer data

Work Package Investigators

  • Dr Jem Rashbass (1a lead)

  • Dr Steven Hardy

  • Prof. Eva Morris (1b lead)

  • Prof. Antonis Antoniou (1c lead)

  • Prof. Paul Pharoah

  • Dr Marc Tischkowitz

Through Work-Package 1 we shall kick-start utilisation of the new national Public Health England datasets of variants in cancer susceptibility genes.

We shall undertake data linkages to routine cancer and non-cancer datasets and facilitate release of these datasets through Public Health England Office for Data Release and Leeds Institute for Data Analytics.

We shall evaluate these linked datasets against overlapping prospectively collected cohorts and undertake analyses on risk and outcomes, leveraging the value from this dataset of mutation-carriers who have accumulated several years of follow-up information and information on cancer diagnoses, surgery, pathology, cancer treatment, recurrence and death

 
 

Work Package 3

Dynamic Evidence-based Clinical Guidance

Work Package Investigators

  • Dr Marc Tischkowitz

  • Prof. Gareth Evans

  • Dr Emma Woodward

  • Dr Helen Hanson

  • Dr Fiona Lalloo

Through Work-Package 3, we shall evolve a mini-NICE (National Institute for Health and Care Excellence) model to deliver rapid turn-around, highly focused guidance for the clinical community. Leveraging the best interpretation of the best data available today.

This will be achieved through juxtaposing 

(i) partnership with NHSE,

(ii) input from expert genetic epidemiologists, translational academic clinicians and clinicians with expertise in guideline development,

(iii) support with resource for systematic review and for data analysis.


We shall establish priorities through consultation with expert clinical groups, with strong focus guidance relating to differential cancer risk varying by context of ascertainment.

Recent Outputs:


Germline-Focused Analysis of Tumour-Only Sequencing: Recommendations from the ESMO Precision Medicine Working Group. 

Mandelker D, Donoghue MTA, Talukdar S, Bandlamudi C, Srinivasan P, Vivek M, Jezdic S, Hanson H, Snape K, Kulkarni A, L, Douillard JY, Wallace SE, Rial-Sebbag E, Meric-Bersntam F, George A, Chubb D, Loveday C, Ladanyi M, Berger MF, Taylor BS, Turnbull C. Ann Oncol. 2019 May 3.


Structural Aberrations with Secondary Implications (SASIs): consensus recommendations for reporting of cancer susceptibility genes identified during analysis of Copy Number Variants (CNVs). 

Talukdar S, Hawkes L, Hanson H, Kulkarni A, Brady AF, McMullan DJ, Ahn JW, Woodward E, Turnbull C; UK Association for Clinical Genomic Science and UK Cancer Genetics Group.J Med Genet. 2019 Apr 24.

 

Work Package 5

Medical Education

Work Package Investigators

  • Prof. Kate Tatton-Brown

  • Dr Katie Snape

  • Dr Katherine Joekes

Work-Package 5 comprises development of a sustainable

infrastructure for the delivery of effective and clinically

relevant educational resources around risk and cancer

susceptibility genetics for different areas of the medical

workforce.

Approaches will be mindful of ease of accessibility, time pressures of busy front facing clinicians, and clinical need.

Specifically we shall develop a mixture of proactive and reactive learning resources including:

 

  • resources for tertiary clinical cancer geneticists to adjust previously held paradigms regarding cancer risks and management in well-established cancer predisposition genes, alongside an understanding of polygenic risk management,

  • resources to upskill the oncology healthcare professionals in the interpretation and clinical actionability of genomic data from laboratory reports to ensure safe, and evidence based clinical management and screening and

  • training of secondary and primary care healthcare professionals in risk estimation, requirements for referral of at risk patients, and risk communication.

Work Package 4

Patient-facing tools for decision-making

Work-Package 4 will collate and evaluate current information resources in collaboration with patients and clinicians.

We shall build on this to create patient facing tools that provide accessible information to support informed decision-making about whether or not to have a genetic test and how to interpret and act on genetic test results.

Existing resources will be assessed, elements deemed valuable (to patients) identified, adapted and further developed.

The patient facing tools developed will support people to understand what the genetic test involves; what the possible outcomes of the test are; what the result means for risk management, concerns about cancer risk, and implications for other family members.

Work Package Investigators

  • Prof. Claire Foster

  • Prof. Diana Eccles

 
 
 

Work Package 6

Ethics, Governance and Policy

Work Package Investigators

  • Prof. Nina Hallowell

  • Dr Ingrid Slade

Work-Package 6 will focus on ensuring that all aspects of the programme have a firm ethical grounding and that ethical issues emerging from the research activities are identified and described.

There will be particular focus on ethical issues around release of nationally collected data, involving consultation with the PPI group.

Work-Package 6 will aim to address the new ethical, legal and governance questions that arise at the intersection of population health and genomics both within CanGene-CanVar and within cancer genetics more broadly.

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