ORACLE diagnostic for cancer prognosis

• A novel signature and method to address Genomic ITH (Intra-Tumour Heterogeneity) and CIN (Chromosome Instability) which are common features across cancer types
• The team developed the Outcome Risk Associated Clonal Lung Expression (ORACLE) gene signature, comprised of genes robust to sampling bias
• This is a new diagnostic approach/genetic test that will aid early clinical decision making for lung cancer, combining machine learning approaches with an understanding of cancer evolution to distinguish between high- and low-risk tumours
• The underlying ORACLE methodology has also broader applicability in identifying biomarker signatures for prognostication in other cancer types and predicting response to therapy (targeted or immuno-oncology drugs)
• Developed by Professor Charles Swanton and his team as part of the TRACERx study https://www.nature.com/collections/haffgaicaf
• Published and featured on the front cover of Nature Medicine https://www.nature.com/articles/d42473-020-00213-w  
• Strong patent application PCT/GB2020/050221 filed in major territories with National Phase entry in August/September 2021 in US, CA, EU, CN, JP and AU

ORACLE is a new genetic test that combines machine learning with our understanding of tumour evolution to distinguish high- and low-risk lung tumours; it is also applicable to other tumours. This technology was developed by Cancer Research UK-funded scientists as part of the TRACERx study and was featured on the front cover of Nature Medicine. The underlying ORACLE methodology also has broader applicability for identifying biomarker signatures for prognostication in other cancer types and predicting response to therapy (both targeted and immuno-oncology drugs). 

Genomic intra-tumour heterogeneity (ITH) and chromosome instability (CIN) are common features across cancer types. This results in a diagnostic challenge for molecular biomarkers termed 'sampling bias': sampling biopsies from different parts of the same tumour can yield completely different results.

To address this well-established problem, the investigators have analysed multi-region, multi-omic data from patients with Non-Small Cell Lung Cancer (NSCLC) recruited within the TRACERx study (TRAcking Cancer Evolution through therapy). This led to the development of the Outcome Risk Associated Clonal Lung Expression (ORACLE) gene signature, which is comprised of genes significantly less vulnerable to sampling bias. This new approach robustly predicted which early-stage lung cancer patients were at higher mortality risk, including those missed by existing clinical criteria.

Professor Charles Swanton FRS, Cancer Research UK's Chief Clinician, leads the research team between the Francis Crick Institute and UCL Cancer Institute. Professor Swanton is a global leader in cancer evolution, publishing extensively on the mechanisms and clinical impact of ITH in journals including the New England Journal of Medicine, Science, Nature, and Cell. He leads the TRACERx study, which represents the single largest investment by CRUK into NSCLC research (£12M). Over the last five years he has also attracted >£100M in commercial funding from pharmaceutical and biotechnical companies.

Dr Dhruva Biswas - a post-doctoral fellow in Professor Swanton’s group - is the first author on the Nature Medicine paper describing the development of ORACLE. He is also the principal investigator on two grants supporting its clinical validation.

One patent application has been filed: Publication Number WO/2020/157508; Publication Date: 6 Aug 2020; International Application Number PCT/GB2020/050221; International Filing Date: 30 Jan 2020.

• Click here to see this opportunity's associated publications and GitHub page.
• Click here to learn more about how TRACERx is providing new insights into the forces that shape how tumours change over time, and how they interact with the body’s immune system. 
• Read the latest publication on this technology.