Functional Genomics and Functional Genomics and Computational Biology in Computational Biology in

Cancer ResearchCancer Research

John QuackenbushJohn Quackenbush

February 4, 2009February 4, 2009

February 2001: Completion of the Draft Human GenomeFebruary 2001: Completion of the Draft Human Genome

Public HGPPublic HGP Celera GenomicsCelera GenomicsMay 2006: The “complete” human genomeMay 2006: The “complete” human genome

sequence is announcedsequence is announced

The Genome Project has provided a The Genome Project has provided a “parts list” for a human cell“parts list” for a human cell

Different cell types express different sets of genes

Neuron

Thyroid Cell

Lung Cell

Cardiac Muscle

Pancreatic Cell

Kidney Cell

Skeletal Muscle

Skin Cell

2006: State of the Art Sequencing 2006: State of the Art Sequencing

74x Capillary Sequencers10 FTEs15-40 runs per day1-2Mb per instrument per day120Mb total capacity per day

SEQUENCING

Rooms of equipmentSubcloning > picking > prepping 35 FTEs3-4 weeks

PRODUCTION

Sequencing the genome took ~15 years and $3B

2008: Enabling a New Era in Genome 2008: Enabling a New Era in Genome Analysis Analysis

1x Cluster Station1 FTE1 day

PRODUCTION

1x Genome AnalyzerSame FTE as above1 run per 3 days1Gb per instrument per run>300Mb per day

SEQUENCING

We can now re-sequence the genome in a ~2 weeks

Why Computational Biology?Why Computational Biology?New technologies inspired by the Human New technologies inspired by the Human Genome Project are transforming Genome Project are transforming biomedical biomedical research research from a laboratory science to an from a laboratory science to an information scienceinformation science

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

The best way to develop new methods is to The best way to develop new methods is to address real problems address real problems

In many ways, we are like the early telescope In many ways, we are like the early telescope makers – we build tools that also enable makers – we build tools that also enable research beyond our own.research beyond our own.

ClinicalClinicalDataData MetabolomicsMetabolomics

ProteomicsProteomicsTranscriptomicsTranscriptomics

CytogenomicsCytogenomics

EpigenomicsEpigenomics

GenomicsGenomics

PublishedPublishedDatasetsDatasets

DrugDrugBankBank

TheTheHapMapHapMap

TheTheGenomeGenome

DiseaseDiseaseDatabasesDatabases

(OMIM)(OMIM)

PubMedPubMed

ClinicalClinicalTrialsTrials

ChemicalChemicalBiologyBiology

Etc.Etc.

Beating Information OverloadBeating Information Overload

CentralCentralWarehouseWarehouse

Improved DiagnosticsImproved DiagnosticsIndividualized TherapiesIndividualized Therapies

More Effective AgentsMore Effective Agents

Like “Google” Like “Google” for Medicalfor Medical

and Biological Dataand Biological Data

2004 Estimated US 2004 Estimated US Cancer Deaths*Cancer Deaths*

ONS=Other nervous system.Source: American Cancer Society, 2004.

Men290,890

Women272,810

25% Lung & bronchus

15% Breast

10% Colon & rectum

6% Ovary

6% Pancreas

4% Leukemia

3% Non-Hodgkin lymphoma

3% Uterine corpus

2% Multiple myeloma

2% Brain/ONS

24% All other sites

Lung & bronchus 32%

Prostate 10%

Colon & rectum 10%

Pancreas 5%

Leukemia 5%

Non-Hodgkin 4%lymphoma

Esophagus 4%

Liver & intrahepatic 3%bile duct

Urinary bladder 3%

Kidney 3%

All other sites 21%

Early Detection of Breast CancerEarly Detection of Breast Cancer

Can we look in the Can we look in the tissue surrounding a tissue surrounding a breast tumor to find a breast tumor to find a

gene expression gene expression “signature” indicating “signature” indicating

its presence?its presence?

NORMAL TISSUENORMAL TISSUE CANCER TISSUECANCER TISSUE

Aedin Culhane, Timothy Yeatman

Breast Cancer Subtypes SurvivalBreast Cancer Subtypes Survival

Different subtypes have different survival profiles

Aedin Culhane, Timothy Yeatman

Ten Genes in Adjacent Tissue Ten Genes in Adjacent Tissue Distinguish Breast Cancer SubtypesDistinguish Breast Cancer Subtypes

histologically normal tissue

SubtypeSubtypeLuminal ABasal

1212

Aedin Culhane, Timothy Yeatman

2004 Estimated US 2004 Estimated US Cancer Deaths*Cancer Deaths*

ONS=Other nervous system.Source: American Cancer Society, 2004.

Men290,890

Women272,810

25% Lung & bronchus

15% Breast

10% Colon & rectum

6% Ovary

6% Pancreas

4% Leukemia

3% Non-Hodgkin lymphoma

3% Uterine corpus

2% Multiple myeloma

2% Brain/ONS

24% All other sites

Lung & bronchus 32%

Prostate 10%

Colon & rectum 10%

Pancreas 5%

Leukemia 5%

Non-Hodgkin 4%lymphoma

Esophagus 4%

Liver & intrahepatic 3%bile duct

Urinary bladder 3%

Kidney 3%

All other sites 21%

Cancer Death Rates per 100,000Cancer Death Rates per 100,000

*Age-adjusted to the 2000 US standard population.Source: US Mortality Public Use Data Tapes 1960-2000, US Mortality Volumes 1930-1959,National Center for Health Statistics, Centers for Disease Control and Prevention, 2003.

Ovarian Cancer is one of the few with an increasing death rate

Gene Expression: A First LookGene Expression: A First LookHierarchical clustering of the data shows three Hierarchical clustering of the data shows three distinct sample subgroups that do not correlate distinct sample subgroups that do not correlate with platinum resistant or platinum sensitive with platinum resistant or platinum sensitive statusstatus

A variety of statistical tests have failed to identify A variety of statistical tests have failed to identify a strong separation between response groups.a strong separation between response groups.

Why Dana-Farber?Why Dana-Farber?This is This is thethe premier Cancer Research Institute premier Cancer Research Institutein the world.in the world.

The most important resource we have for The most important resource we have for understanding the causes of cancer are the patients understanding the causes of cancer are the patients themselves.themselves.

There is no place that I have seen where there is a There is no place that I have seen where there is a greater sense of community involvement.greater sense of community involvement.

The patients and the staff realize that beating cancer The patients and the staff realize that beating cancer requires a partnership, a commitment,requires a partnership, a commitment,and an investment.and an investment.

There is a understanding that There is a understanding that developingdeveloping research research requires requires enablingenabling research. research.