Browsing Over 167 Presentations
Digital pathology: Emerging technologies in the field
- Julien Adam, Villejuif, France, Institut Gustave Roussy
How to analyse data from digital pathology
- Trevor Graham, London, United Kingdom, Barts Cancer Institute-Queen Mary University of London
Mass cytometry: Principles and applications
- Sandra Tietscher, Zurich, Switzerland, UZH - University of Zurich - Irchel Campus
Coffee break
Basics of single cell sequencing
- Florent Ginhoux, Singapore, Singapore, A*STAR - Singapore Immunology Network (SIgN)
Bioinformatics and mathematics to analyse single cell data
- Charlotte K. Ng, Bern, Switzerland, University of Bern
Welcome to MAP 2019
- Charles Swanton, London, United Kingdom, The Francis Crick Institute
1O - 100,000 genomes project: Integrating whole genome sequencing (WGS) data into clinical practice
- Alona Sosinsky, London, United Kingdom, QMUL
Abstract
Background
The 100,000 Genomes Project aims to improve cancer care for NHS patients in the UK through personalised medicine. Our target is to return WGS results to clinicians in a clinically meaningful timescale to facilitate diagnosis and treatment choices for patients, and in parallel to provide a research platform of genomic data linked to longitudinal clinical data.
Methods
We present here an overview of clinical utility for reported outcomes. To date, bioinformatics reports for WGS, with links to potentially relevant therapies and UK clinical trials, have been produced for more than 14,000 cancer patients in the UK Currently our bioinformatics analysis of WGS includes clinical interpretation of somatic small variants, somatic structural and copy number variants (SV/CNV), germline pertinent findings, mutational burden and signatures. To iteratively develop a high-quality bioinformatics pipeline and to monitor clinical utility of returned results, we are collecting feedback via the 100,000 Genomes Project Interpretation Portal from NHS Molecular Tumour Boards. These data suggest that WGS has the potential to affect patient management. Future applications will include the utilisation of pan-genomic markers to better stratify patients within the context of a clinical study.
Results
WGS has the ability to replace multiple standard of care tests as it has the potential to detect all types of variants (SV/CNV/SNV/indels) as well as emerging pan-genome biomarkers in a single test. In this study we use samples submitted as part of the 100,000 Genomes Project to investigate the feasibility of WGS as an alternative to conventional testing. Overall comparison of WGS with the results of NGS panels (96 patients, 156 clinically-relevant SNVs), high-depth exome sequencing (10 patients, 3150 SNVs, 140 indels), cytogenetic FISH tests (70 patients, 259 SVs, 100 CNVs), immunohistochemistry tests for Mismatch Repair Deficiency (265 patients) and HER2 status (154 patients) demonstrated Positive Percentage Agreement > 90% and False Positive Rate < 5%.
Conclusions
Further work is required to validate fully all aspects of the WGS analysis pipeline but these results indicate that WGS can reliably detect clinically relevant biomarkers in the genomes of cancer patients.
Legal entity responsible for the study
Genomics England.
Funding
Genomics England.
Disclosure
All authors have declared no conflicts of interest.
2O - Pan-genome cfDNA methylation analysis of metastatic prostate cancer
- Anjui Wu, Taipei City, Taiwan, National Taiwan University College of Medicine
Abstract
Background
Tumour DNA circulates in the plasma of cancer patients admixed with DNA from non-cancerous cells. The genomic landscape of plasma tumour DNA has been characterised in metastatic castration-resistant prostate cancer (mCRPC) but the plasma methylome in mCRPC has not been extensively explored.
Methods
mCRPC plasma samples collected from three different centres were concurrently subject to targeted genomic and pan-genome methylation profiling. The treatment courses and outcomes were also obtained. Tumour fraction of each plasma sample was estimated based on heterogyzous SNPs located in two truncal genomic deletions (8q21 and 21q22). Targeted methylome was performed using pre-designed capture panel followed by deep sequencing. We integrated genomic information with methylation data to extract methylation signatures associated with genomically-determined tumour fraction or private to individual’s tumour.
Results
Principal component analysis on the mCRPC plasma methylome indicated that the main contributor to methylation variance (principal component one, or PC1) was strongly correlated with genomically-determined tumour fraction (r=-0.96; P < 10-9), characterised by hypermethylation of targets of the polycomb repressor complex 2 components. Further deconvolution of the top PC1 correlated segments revealed that these segments comprised of methylation patterns specific to either prostate cancer or prostate normal epithelium. To extract information specific to an individual’s cancer, we then focused on an orthogonal methylation signature which revealed enrichment for androgen receptor (AR) binding sequences and where hypomethylation of these segments associated with AR copy number gain. Individuals harbouring this methylation pattern had a more aggressive clinical course, including a significantly shorter overall survival (HR = 8.18, 95% CI = 1.93–34.76, P = 0.0044).
Conclusions
Plasma methylome analysis can accurately quantitate tumour fraction and identify distinct biologically-relevant mCRPC phenotypes associated with worse clinical outcome.
Clinical trial identification
Istituto Scientifico Romagnolo per lo Studio e la Cura dei Tumori (IRST), Meldola, Italy (REC 2192/2013) Royal Marsden, London, UK (REC 04/Q0801/6) PREMIERE trial (EudraCT: 2014-003192-28, NCT02288936).
Legal entity responsible for the study
The authors.
Funding
Cancer Research UK (CRUK), Prostate Cancer Foundation (PCF).
Disclosure
V. Conteduca: Honoraria (self), Advisory / Consultancy: Bayer; Honoraria (self), Advisory / Consultancy: Astellas; Honoraria (self), Advisory / Consultancy: Janssen-Cilag; Honoraria (self), Advisory / Consultancy: Sanofi-Aventis. E. Gonzalez-Billalebeita: Honoraria (self): Astellas; Honoraria (self): Janssen-Cilag; Honoraria (self): Sanofi-Aventis. U.D. Giorgi: Honoraria (self), Advisory / Consultancy: Bayer; Honoraria (self), Advisory / Consultancy: Astellas; Honoraria (self), Advisory / Consultancy: Janssen-Cilag,; Honoraria (self), Advisory / Consultancy: Sanofi-Aventis. G. Attard: Honoraria (self): Institute of Cancer Research; Honoraria (self), Advisory / Consultancy: Astellas; Honoraria (self), Advisory / Consultancy: Medivation; Honoraria (self), Advisory / Consultancy: Janssen; Honoraria (self), Advisory / Consultancy: AstraZeneca; Honoraria (self), Advisory / Consultancy: Arno. All other authors have declared no conflicts of interest.
Pancreatic cancer
- Andrew Biankin, Bearsden, United Kingdom, University of Glasgow - Wolfson Wohl Cancer Research Centre - Institute of Cancer Sciences
Glioblastomas
- Roel G. Verhaak, Farmington, United States of America, Jackson Laboratory for Genomic Medicine
Biliary tract cancer
- Lipika Goyal, Boston, United States of America, Massachusetts General Hospital, Harvard Medical School