The Road toPersonalized Medicine is

Paved with Data and InformationJohn Quackenbush

NCI Second Generation Sequencing

May 3, 2012

Disease Progression and Personalized Care

TreatmentOptions

QualityOf Life

GeneticRisk

EarlyDetection

Patient Stratification

DiseaseStaging

Outcomes

Natural History of Disease Clinical Care

Environment + Lifestyle

Birth Treatment Death

Biomarkers

Turning the vision into a reality• Assure access to samples and rational consent

• Develop a technology platform

• Make information integration as a central mission

• Conduct research as a vital component

• Present data and information to the local community

• Enable research beyond your own

• Engage corporate partners

• Communicating the mission to the community.

Assure Access to Samples

Access, Research, Security• Patients want to be part of the process of curing disease

• Informed consent needs to be structured to allow patients to be partners in the research process

• HIPPA requires both informed consent and that we assure patient confidentiality

• But “identifiability” is a moving target in a genomic age

• With the <$1000 genome, in the age of Facebook, what this means remains unclear

• The new Genomics is a disruptive technology.

Develop aTechnology Platform

The cost decreases exponentially with time

7

Illumina GAIIABI SOLiD

The $1000 Genome:October 2012

Continuing the Regression:Genomes for $100 in February 2014

2010: Enabling a New Era in Genome Analysis

Illumina HiSeq

100Gb (~30X genome coverage)

150bp reads

Two samples/week

<$10,000 per genome

Just Announced: The Life TechnologiesIon Torrent Proton

The Promise from LTI

A Genome in ~24 hours for $1000

Promised in Q3 2012

The USB sequencer

Let the games begin!The Oxford Nanopore MiniON

The Challenge New technologies inspired by the Human

Genome Project are transforming biomedical research from a laboratory science to an information science

We need new approaches to making sense of the data we generate

The winners in the race to understand disease are going to be those best able to collect, manage, analyze, and interpret the data.

Make information integration as a central mission

ClinicalData Metabolomics

ProteomicsTranscriptomics

Cytogenomics

Epigenomics

Genomics

PublishedDatasets

DrugBank

TheHapMap

TheGenome

DiseaseDatabases

(OMIM)

PubMed

ClinicalTrials

ChemicalBiology

Etc.

CentralWarehouse

Improved DiagnosticsIndividualized Therapies

More Effective Agents

Beating Information Overload

Conduct research as a vital component

Data Generation Illumina partnered with us to generate comprehensive

mRNA, microRNA, and methylation, and copy number variation (CNV) profiles on these FFPE ovarian cancer samples

Renee Rubio and Kristina Holton developed protocols for efficient extraction of mRNA/microRNA and genomic DNA from FFPE cores

Quality was validated using BioAnalyzer and hybridizations to Illumina DASL arrays

mRNA/microRNA and DNA were extracted from 132 samples and profiled in collaboration with Illumina on a prototype 12k DASL array

Data were normalized and analyzed using the ISIS class discovery algorithm.

Identifying modules using ISIS*

Module:Set of genes supporting a bi-partition

ISIS searches for stratifications of samples into two groups that maximize a DLD score.

*ISIS: Identifying splits of clear separation (von Heydebreck et al., Bioinformatics 2001)

Module 2 (gene expression)

Module 2Gene set enrichment analysis

Survival and Validation

1606 published ovarian tumors

1090 high grade, late stage serous tumors

Present data and information to the local community

LGRC Research Portal

LGRC Data Download

• Data download

• Browse by basic metadata

• Browse by clinical / phenotype attributes

• Download ‘raw’ data

• Secure transfer via single use ‘tickets’ . Enables authorized users access to the specified result basket for a single session.

LGRC Research Portal

PAGE DETAILS

Search-Facets-Search within results-Keyword prompts-Search history

Table:-Paged results-Sortable columns

Actions:-Go to Gene detail page-Add genes to ‘gene set’

Gene Expression Summary

RNASeq

Annotation Summary

PAGE DETAILS

Annotation summary & summary view for each assay/data type:

Accordion style sections

GEXP – expression profile across major Dx categoriesRNASeq – Exon structure of the geneSNPs – Table of SNPs in region of gene, highlighting association with major Dx group- Methylation – Methylation profile in region around geneGenomic alterations – table of CNVs & alterations observed w/ freq in region around gene

Actions:- Click through to assay detail pageAdd gene to set

LGRC Research Portal

LGRC Research Portal

PAGE DETAILS

- View aggregate statistics-View cohort details-Build cohort sets-Build composite phenotypes

Actions:

-Go to data download for selected cohort -Go to assay detail for selected cohort-Go to cohort manager

LGRC Research Portal

Engage corporate partners

We need to find the best tools We received an $1M Oracle Commitment grant to create

our integrated clinical/research data warehouse

We’ve partnered with IDBS to create data portals

We are working with Illumina on a variety of projects

We are forging relationships with Thomson-Reuters to link genomic profiling data to drug, trial, and patent information

We are building partnerships with Roche, Genomatix, NEB, and others interested in entering the personal genomics space.

Enable research beyondyour own

John Quackenbush, DirectorMick Correll, Associate Director

The MissionThe mission of the CCCB is to provide broad-based support for the analysis and interpretation of ‘omic data and in doing so to further basic, clinical and translational research. CCCB also will conduct research that opens new ways of understanding cancer.

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Consulting

CCCB Collaborative Consulting Model

1. Initial meeting to understand project scope and objectives

2. Development of an analysis plan and time/cost estimate

3. During project execution, data and results are exchanged through a secure, password-protected collaboration portal

4. Available as ad-hoc service, or larger scale support agreements

Communicate the mission to the community.

The LGRC

Why Patient Involvement is Essential

Patients want to be our partners in curing disease

The incentive structure in medical research is skewed away from success We all say, “We want to cure disease.” We mean, “We want to cure disease, but only if I am

the one to cure disease.”

The only way to break the logjam is to have patients involved in the process.

Genomics is here to stay

<johnq@jimmy.harvard.edu>

http://compbio.dfci.harvard.edu

AcknowledgmentsThe Gene Index TeamCorina AntonescuValentin AntonescuFenglong LiuGeo PerteaRazvan SultanaJohn Quackenbush

Array Software Hit TeamKatie FranklinEleanor HoweJohn QuackenbushDan SchlauchRaktim SinhaJoseph White

Eskitis InstituteChristine WellsAlan Mackay-Sim

Center for CancerComputational BiologyMick CorrellVictor ChistyakovHowie GoodellLan HuiLev KuznetsovNiall O'ConnorJerry PapenhausenYaoyu WangJohn Quackenbushhttp://cccb.dfci.harvard.edu

Gene Expression Team Fieda AbderazzaqStefan BentinkAedin CulhaneKathleen Fleming Benjamin Haibe-KainsJessica MarMelissa MerrittMegha PadiRenee Rubio

(Former) Stellar StudentsMartin AryeeKaveh Maghsoudi Jess Mar

Systems SupportStas Alekseev, Sys AdminPriya Karanam, DBA

Administrative SupportJoan CoraccioJulianna Coraccio

http://compbio.dfci.harvard.edu