ebi industry programme tcga warren kibbe november 2013

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NCI CBIIT Re-engaged Warren Kibbe [email protected] 240-276-7300 The views expressed are my own and not a reflection of DHHS or NCI policy

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Presentation to the EBI Industry Programme to highlight the TCGA project at the NCI

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Page 1: EBI Industry programme TCGA Warren KIbbe November 2013

NCI CBIIT Re-engaged Warren Kibbe

[email protected] 240-276-7300

The views expressed are my own and not a reflection of DHHS or NCI policy

Page 2: EBI Industry programme TCGA Warren KIbbe November 2013

General strategic objectives •  Reduce cancer risk •  Improve cancer outcomes •  Education and dissemination of

information •  Provide informative data and powerful

examples

Page 3: EBI Industry programme TCGA Warren KIbbe November 2013

Broad strategic activities •  Understand social media as a mechanism

for communication, education, and improving lifestyle choices

•  Work productively with patient advocates •  Understand risk factors leading to cancer •  Model cancer initiation and progression •  Enable precision oncology •  Help build learning healthcare systems

Page 4: EBI Industry programme TCGA Warren KIbbe November 2013

Informatics strategic objectives •  Lower barriers to data access, analysis

and modeling •  Promote agility, flexibility, data liquidity •  Promote Open Access, Open Data, Open

Source, Open Science •  Promote semantic interoperability,

standards, CDEs and Case Report Forms

Page 5: EBI Industry programme TCGA Warren KIbbe November 2013

Informatics strategic objectives •  Promote mobile and BYOD for patient

reported outcomes, education, surveillance, eligibility …

•  Use informatics to improve and lower barriers to clinical trials accrual

•  Use informatics to blur the distinction between care and research – support clinical standards in research

•  Identify and disseminate innovations and practices that make research more efficient and effective

Page 6: EBI Industry programme TCGA Warren KIbbe November 2013

A few specific activities •  Genomic Data Commons •  Cloud Pilot •  EVS, NCI Thesaurus, NCI Metathesaurus •  CDEs, Case Report Forms •  MPACT, MATCH, Exceptional Responders •  Integrated informatics for the cooperative

groups •  FDA Clinical Trials Repository

–  Janus – Collaboration between the FDA and NCI

•  RAS Initiative – hub at NCI Frederick

Page 7: EBI Industry programme TCGA Warren KIbbe November 2013

TCGA history •  Initiated in 2005 •  Collaboration of NHGRI and NCI to

examine GBM, Lung and Ovarian cancer using genomic techniques in 2006.

•  Expanded to 20+ tumor types.

Page 8: EBI Industry programme TCGA Warren KIbbe November 2013

TCGA snapshot •  Data collection will complete in Q3 2014 •  As of October 2013, 700TB of data has

been collated and integrated. •  Anticipates 2.5 PB of data as of the end of

Q3 2014 •  Some tumor types are complete, others

nearly complete, and still others are just getting to the point of submission

Page 9: EBI Industry programme TCGA Warren KIbbe November 2013

TCGA snapshot •  Today there is a standardized analysis

pipeline with standardized protocols •  Today there is standardized consent and

consenting process •  Today there is a standardized data access

policy

Page 10: EBI Industry programme TCGA Warren KIbbe November 2013

TCGA drivers •  Providing high quality reference sets for

20+ tissue types •  Providing a platform for systems biology

and hypothesis generation •  Providing a test bed for understanding the

real world implications of consent and data access policies on genomic and clinical data.

Page 11: EBI Industry programme TCGA Warren KIbbe November 2013

Focus on the TCGA •  The TCGA consortium slides

Page 12: EBI Industry programme TCGA Warren KIbbe November 2013

TCGA – Lessons fromstructural genomics#

Jean Claude Zenklusen, Ph.D. Director TCGA Program Office National Cancer Institute

Page 13: EBI Industry programme TCGA Warren KIbbe November 2013

13

Tumor Project Progress

Manuscript submitted or published

Analysis underway

Sample acquisition phase

Rare tumor project

0

200

400

600

800

1000

1200

®

® ® ® ® ® ® ® ®

Accepting AA cases only Goal of 500 reached

Page 14: EBI Industry programme TCGA Warren KIbbe November 2013

The Mutational Burden of Human Cancer#

Mike Lawrence and Gaddy Getz

Increasing genomic#complexity#

Childhood#cancers#

Carcinogens#

Page 15: EBI Industry programme TCGA Warren KIbbe November 2013
Page 16: EBI Industry programme TCGA Warren KIbbe November 2013

Response of RCC#To Everolimus#

Everolimus#Placebo#

mTOR mutations#Progression-free survival#

(months)#

PI(3)K aberrations (28% of cases)#

Frequent Activation of the PI(3)K Pathway in#Clear Cell Renal Carcinoma#

Motzer et al Lancet 372:449 (2008)#Hakimi et al Nat Gen 45:849 (2013)#Sato et al Nat Gen 45:860 (2013)#TCGA Nature 499:45 (2013)#

Page 17: EBI Industry programme TCGA Warren KIbbe November 2013
Page 18: EBI Industry programme TCGA Warren KIbbe November 2013

TCGA Nature 497:67 (2013)#

Four Molecular Subgroups of Endometrial Cancer#Defined by Integrative Analysis#

POLE#(ultra-#

mutated)#MSI#

(hypermutated)#Copy-number low#

(endometriod)#Copy-number high#

(serous-like)#

Histology#

Mutations#Per Mb#

PolE#MSI / MSH2#

Copy ##PTEN#

p53#

Page 19: EBI Industry programme TCGA Warren KIbbe November 2013

TCGA Nature 497:67 (2013)#

Molecular Subgroups Refine Histological Diagnosis#Of Endometrial Carcinoma#

POLE#(ultra-#

mutated)#MSI#

(hypermutated)#Copy-number low#

(endometriod)#Copy-number high#

(serous-like)#

Histology#

Mutations#Per Mb#

PolE#MSI / MSH2#

Copy ##PTEN#

p53#

Serous#misdiagnosed#

as endometrioid?#Endometrioid#Serous#

Histology#

Page 20: EBI Industry programme TCGA Warren KIbbe November 2013

TCGA Nature 497:67 (2013)#

Molecular Diagnosis of Endometrial Cancer May#Influence Choice of Therapy#

POLE#(ultra-#

mutated)#MSI#

(hypermutated)#Copy-number low#

(endometriod)#Copy-number high#

(serous-like)#

Histology#

Mutations#Per Mb#

PolE#MSI / MSH2#

Copy ##PTEN#

p53#

Adjuvant#chemotherapy?#

Adjuvant#radiotherapy?#

Surgery only?#

Page 21: EBI Industry programme TCGA Warren KIbbe November 2013

GDC!

NCI Cancer Genomics Data Commons Functionality#

NCI Genomics#Data Commons#

Genomic +#clinical data#

. . .

Page 22: EBI Industry programme TCGA Warren KIbbe November 2013

GDC!

NCI Genomics#Data Commons#

Genomic +#clinical data#

. . .

Cancer#information#

donor#

NCI Cancer Genomics Data Commons Functionality#

Page 23: EBI Industry programme TCGA Warren KIbbe November 2013

DACO

ICGC

dbGaP

EGA

TCGA

BAM

Open

Open

ERA

BAM

Germ���Line

+ EGA id

BAM BAM

Page 24: EBI Industry programme TCGA Warren KIbbe November 2013

ICGC BAM/FASTQ

TCGA BAM/FASTQ

ICGC Open Data

(includes ���TCGA ���

Open Data)

COSMIC Open Data

Page 25: EBI Industry programme TCGA Warren KIbbe November 2013

GDC!

Relationship of the Cancer Genomics Data Commonsand NCI Clouds #

NCI Cloud Computational Centers#

Periodic  Data  Freezes  

Search  /  retrieve  

Analysis  NCI Genomics#Data Commons#

Page 26: EBI Industry programme TCGA Warren KIbbe November 2013

Cancer Genomics Cloud Pilots

Page 27: EBI Industry programme TCGA Warren KIbbe November 2013

Essential Functions of a Genomics Data Commons#v  Perform data quality control#v  Harmonize primary data across studies

=> realign all primary sequence data to the reference genome#v  Provide “gold standard” derived data:

=> mutations / copy number / digital gene expression #

Page 28: EBI Industry programme TCGA Warren KIbbe November 2013

Jones et al. Genome Biol. 2010;11(8):R82.

Copy # gain#Copy # loss#

Overexpressed#Under expressed#

Mutated#Cancer

Genome Diagnostic

Report

Essential Functions of a Genomics Data Commons#v  Perform data quality control#v  Harmonize primary data across studies

=> realign all primary sequence data to the reference genome#v  Provide “gold standard” derived data:

=> mutations / copy number / digital gene expression #v  Permit integrative analysis across data types#

Page 29: EBI Industry programme TCGA Warren KIbbe November 2013

Essential Functions of a Genomics Data Commons#v  Perform data quality control#v  Harmonize primary data across studies

=> realign all primary sequence data to the reference genome#v  Provide “gold standard” derived data:

=> mutations / copy number / digital gene expression #v  Permit integrative analysis across data types#v  Enable integrative analysis across all cancer samples#

TCGA PanCan Working Group#Giovanni Ciriello#Nikloaus Schultz#Chris Sander#

Page 30: EBI Industry programme TCGA Warren KIbbe November 2013

GDC!

Utility of a Cancer Knowledge Base#

Identify#low-frequency#cancer drivers#

Define genomic#determinants of response#

to therapy#

Compose clinical trial#cohorts sharing#

Targeted genetic lesions#

Cancer#information#

donor#