functional genomics and computational biology in cancer research
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Functional Genomics and Computational Biology in Cancer Research. John Quackenbush February 4, 2009. Public HGP. Celera Genomics. February 2001: Completion of the Draft Human Genome. May 2006: The “complete” human genome sequence is announced. - PowerPoint PPT PresentationTRANSCRIPT
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.