Download Germline Predisposition to Cancer Sharon Plon, Baylor College of

Germline Susceptibility to Cancer
Sharon E. Plon, MD, PhD, FACMG
Texas Children’s Cancer Center
Baylor College of Medicine
Texas Children’s Hospital
Disclosures – Sharon E. Plon, MD, PhD
• I have the following financial relationships to
disclose:
– I am a employee of Baylor College of Medicine (BCM) which
derives revenue from genetic testing, including whole
exome sequencing.
– BCM and Miraca Holdings Inc. have entered into a joint
venture, Baylor Genetics with shared ownership and
governance of the clinical genetics diagnostic laboratories
– I am a member of the BG Scientific Advisory Board
• I will not discuss off label use and/or
investigational use in my presentation.
Dept of Molecular
and Human Genetics
Baylor College of
Medicine
Launch October 2011
February 2015
Whole Genome Laboratory at
Baylor (April 2011)
• Issues that needed to be addressed for clinical
quality NGS analysis of the Exome
– Capture platform (VCrome)
– Base calling algorithms
– Quality scores
– Depth of coverage
– Analysis pipeline, annotation of variants
– Hand-off to clinical reporting team
– Decisions on what to include in the report
– Sign-out
Whole Exome Sequencing
Workflow
Sample Intake (1500)
1500 (WES) + 6644 (SNP Array)
Financial evaluation
DNA Extraction, SNP-Array
√ QC: sample quantity and quality
Library Preparation
√ QC: at multiple steps for product size
Target Enrichment
√ QC: qPCR for folder of enrichment at
Illumina Sequencing
distribution, quality and quantity
selected loci and quantification of library
√ QC: Criteria from real time analysis
(RTA) on the machine
√ QC:
Data analysis
Clinical Report
1)Mapping: <4% error rate, >90% unique reads
2)Data analysis>10 Gb data, >95% target
bases >20X, >85% target bases >40X, mean
coverage >100X
3)SNP concordance to genotype array:
>99.8%
VCRome2.1 capture reagent
• Coding Exons from: Vega, CCDS, RefSeq,
• Predicted coding exons from: Contrast and GenScan.
• 197K targets, 42Mb genomic region; NimbleGen Rebalanced x2
• Clinical Sequencing: Single Capture
% 20X Coverage
100%
95%
90%
Whole Exome Sequencing
85%
Total samples: 5100; Avg: 96.6% at ≥20X Coverage
80%
0
500
1000
1500
2000
Clinical Exome Sequencing Timeline
2014
2011
2013
Clinical
exome
sequencing
2013
ACMG IF
guidelines
NEJM
250
Cases
JAMA 2000
and 800
cases; GIM
500 cases
2015
ACMG/AMP
Variant
Guidelines
Yaping Yang
2012
2015
2015
NHGRI
CSER
U01
Exom
e
relate
d CPT
codes
Critica
l and
prenat
al
exom
e
Christine Eng
Diversity of germline results returned to all
patients
FOCUSED GERMLINEREPORT
Gene
Mutation
Example
Related to
Patient’s Phenotype
Other
Medically
Actionable
Pathogenic
Pathogenic Pathogenic
ARID1A
VUS
Rare MECP2
missense
SCN5A
mut
mtDNA
MELAS
mut
PCG
Genes
Recessive
Carrier
Genes
FDA
Indication
Pathogenic
CYP2A
mut
CFTR
DF508
Opt-In
Yang et al., JAMA, 2014 – Description of 2000
WES clinical cases
• 1780 (89%) are pediatric
patients (< 18 yr)
• 1440 (72%) have intellectual
disability, seizure disorder or
autism
• Also: skeletal disorders,
gastrointestinal, cardiovascular
disease, syndromic disorders
• Variety of referral sources –
academic medical centers,
national, international
• Now completed over 8000
clinical cases
Molecular Diagnosis Rate 25%:
Varies for Different Phenotypic Groups
Overall (n=2000)
Non-neurologic (n=244)
Neurologic plus (n=1147)
Neurologic only (n=526)
Specific Neurologic (n=83)
0%
10%
20%
30%
40%
50%
Diagnostic rate (+/- 95% CI)
Yang, et al., JAMA, 2014
Mutations in Positive WES Cases
1.1% 0.8%
0.7% 0.1%
0.1%
0.1%
missense
frameshift
8.1%
nonsense
splice
18.9%
48.9%
in-frame
large deletions
start codon
stoploss
21.0%
promoter region
mitochondrial
708 Mutant Alleles in the 504 Positives, 409 (58%) novel at
time of reporting
Most Mutant Alleles Arose de Novo
(AD: 74%; XL: 62%)
X-LINKED, 13%
Mito, 0.2%
de novo,
74%
AD, 53%
AR, 36%
unknown, 14%
inherited, 11%
Diagnostic rate heavily dependent on newly
discovered disease genes
100
88
80
70
60
50
40
30
25
24
19
20
8
2
1991
10
2
39
36
35
1988
1
11
26
24
17
13
34
24
19 18
15
13
8
3
Year in which a gene was first reported as disease causing
2013
2012
2011
2010
2009
2008
2007
2006
2005
2004
2003
2002
2001
2000
1999
1998
1997
1996
1995
1994
1993
0
1992
Number of molecular diagnoses
90
Discovery of new disease genes is the greatest
contributor to improved diagnostic rate
Exome “Spike-in” design content
Spike-in PKv1
1,977 Genes (0.220 Mbp)
GeneTest
21 Clinical Panels
PKV1 PKV2
Spike-in PKv2
3,643 Genes (2.5 Mbp)
VCRome 2.1
Exome
42 Mbp
PKv1 design
OMIM
Selected Cancer Genes
Solved Clinical Cases
Spike-in reagents target gene regions < 20X coverage
Donna Muzny, Yaping
Yang, Yan Ding, Harsha
Doddapaneni, Jianhong
Hu and Kimberly Walker
Critical Trio Example
• Clinical presentation:
• 4-day-old male; IUGR, admitted to NICU due to
respiratory distress, pale skin, petechiae and
bruising on chest and back
• Initial lab work revealed pancytopenia
• Critical trio WES (TAT 10d):
• FANCA, c.154C>T (p.R52X), c.2852G>A, p.R951Q,
both pathogenic, compound heterozygous
• Fanconi anemia, complementation group A
[MIM: 227650] –
o
o
Only a few case reports of newborn presentation
of FA
Average age of bone marrow failure – 6 years
Summary of non-cancer WES Experience
• The majority of patients referred for WES have
neurodevelopmental phenotypes.
– Growing interest in WES in different clinical scenarios
• The diagnostic rate is approximately 25% which is
increased further by doing parent/child trios.
– There is a balance of autosomal dominant, autosomal
recessive and X-linked underlying diagnoses.
– ~5% of of diagnosed patients have more than one
Mendelian disorder underlying phenotype.
– De novo mutations are a major feature of diagnoses.
• Non-diagnostic cases can be studied further/solved
through several research mechanisms
3
BASIC
Baylor College of Medicine Advancing Sequencing Into Childhood Cancer Care
PATIENTS
280 children newly diagnosed
CNS and non-CNS
solid tumors
SEQUENCING
Blood
Tumor
SAMPLES
CLIA-certified
whole exome
sequencing
RETURN OF RESULTS
FOLLOW-UP
Germline
EMR
GCs
Relapse
Somatic
MDs
Family
No relapse
MUTATION
REPORTS
Study objectives:
• To integrate information from CLIA-certified germline
and tumor exome sequencing into the care of newly
diagnosed solid and brain tumor patients at Texas
Will Parsons
Children’s Cancer Center
Pediatric Oncology
• To perform parallel evaluation of the impact of tumor
and germline exomes on families and physicians
CLIA cancer whole exome sequencing
• Using 1 ug of DNA isolated from frozen tissue and
paired blood sample
• Illumina Sequencing Platform
– Capture exome on Roche-Nimblegen VCRome 2.1 from BCM
HGSC
– One paired tumor/blood sample per HiSeq lane
• Analysis using platform developed by BCM-HGSC
informatics team with separate germline and tumor
reports issued
Total Gb Unique
– see Yang et al,
2013 for details
platform
perNEJM,aligned
Meanof germline
Bases 20X
Bases 40X
WES sample sample
Gb
coverage coverage coverage
Germline
18.8
17.5
272
97.5%
95.7%
Tumor
18.8
17.6
276
97.3%
95.1%
Enrollment and Consent Status
• Paper on informed consent process. Scollon et al.,
Genomic Medicine, 2014
No (17%)
Overwhelmed (10%)
Yes
(83%)
Privacy risks (3%)
Genetic anxiety (2.5%)
Blood draw (2%)
Current Enrollment Numbers: Steady Enrollment of
Diverse Population N=239; 50 Spanish speaking
Table 2. Characteristics of patients enrolled and not enrolled on study - updated
Characteristic - no. (%)
Ethnicity
Hispanic
Non-Hispanic
Not reported
Race
White
Black or African American
Asian
American Indian or Alaska Native
Multiple
Not reported
Enrolled
(n=239)
Declined
(n=103)
P Value
0.54
111 (46%)
119 (50%)
10 (4%)
41 (40%)
52 (50%)
10 (10%)
0.11
141 (59%)
25 (10%)
7 (3%)
10 (4%)
14 (6%)
42 (18%)
74 (72%)
12 (12%)
4 (4%)
2 (2%)
---
BASIC3 DIVERSE PEDIATRIC TUMOR DIAGNOSES
NON-CNS
CNS
81/94 (86%)
40/56 (71%)
Tumor available for WES
Diversity of germline results returned
TUMOR
REPORT
GERMLINE
REPORT
Cancer or Other
Patient Phenotype
Other
Medically
Actionable
PCG
Genes
Recessive
Carrier
Genes
All
Gene
All
Somatic
Mutation
Pathogenic
VUS
Pathogenic
FDA
Indication
Pathogenic
BRAF
V600E
Example
DICER1
nonsense
Rare WT1
missense
SCN5A
mut
CYP2A
mut
CFTR
DF508
Opt-In
Scollon et al., Genome Medicine, 2014
BASIC3 germline results related to phenotype (10%)
Mechanism
n=150
Autosomal dominant
13
Genes
Genes known to be
associated w/ specific
childhood cancer
8
Examples include DICER1, VHL, MSH2,
WT1, TP53
Genes not previously
associated w/ specific
cancer
5
Examples include BRCA1, BRCA2,
SMARCA4
Autosomal recessive
diagnosis
1
TJP2 homozygous LOF mutation –
progressive cholestatic liver & HCC
Diagnostic for other
medical problems
1
For example CLCN5-mutation in child
with unexplained renal disease
Update with 256 WES – still 9% cancer diagnoses
Inheritance pattern of diagnostic mutations
• Parental DNA available for 20 patients.
• In 16 of 20 (80%) patients the pathogenic variant
was inherited:
– Family history often consistent with the genetic
diagnosis
– Only exceptions were: somatic Mosaic WT1 and De novo
mutation in KRAS
• All at-risk siblings have undergone testing for the
diagnostic mutation independent of ethnicity
• Of the VUS in cancer susceptibility genes reported
(median of 3/subject) almost none are de novo.
Single pathogenic recessive mutation
Gene
association
Associated
with the cancer
Gene not
known to be
associated with
the specific
childhood
cancer
Tumor diagnosis and other
history
LOH in tumor
DIS3L2
Wilms tumor
Present
BUB1B
Glioma
No
FANCC
Wilms tumor
No
FANCL
Kaposiform
hemangioendothelioma
No
FANCL
Ganglioneuroblastoma
No
FANCL
Ependymoma
No
MUTYH
Anaplastic ganglioglioma
ND
RAD50
Malignant mixed germ cell
tumor
No
SBDS
Pilocytic astrocytoma
ND
No. Gene
1
9
WRAP53 Medulloblastoma
No
Single recessive alleles
• We compared the 150 BASIC3 WES data with the
JAMA 2000 pediatric non-cancer cohort.
• Overall frequency of truncating mutations in any
Fanconi gene was not over-represented in pediatric
cancer patients.
• However, 3 of the BASIC3 patients had same
frameshift allele seen in 0.5% of JAMA cohort (p=)
– No LOH at the Fanconi allele in the tumor and very
diverse tumor types
– Subsequently had two additional patients with this
variant – haploinsufficiency may have some impact on
cancer risk.
VUS REPORTED in CANCER SUSCEPTIBILTY GENES
(n = 215 germline exome reports)
FREQUENCY
50
median of 3 VUS
(range from 0 to 10)
40
-
30
20
No difference in
Hispanic
African-Americans
median of 5
10
0
0
1
2
3
4
5
VUS #
6
7
8
9
10
Scollon et al, ACMG 2016
Tumor WES results
Somatic mutation categories:
Gene
Mutation
All
All
Somatic
I
Mutations known to be diagnostic, prognostic and/or
predictive of treatment in the specific tumor type
tested. Example: ALK p.F1174L in neuroblastoma.
II
Mutations in members of targetable cancer pathways,
gene families, or functional groups, regardless of tumor
type. Example: TSC2 frameshift in osteosarcoma.
III
Mutations in other consensus cancer genes, not
currently considered targetable.
Example: MED12 p.G44D in Wilms tumor.
IV
All other mutations.
Tumor WES results
• Genes mutated in only one tumor:
– ALK, MET, JAK2, JAK3, FGFR1, FGFR3, NTRK2,
FBXW7, NF2, DICER1, NOTCH3, BRCA1, BRCA2,
PTPN11…
Tumor WES results
Total
(n=121)
BCOR:c.5267G>T:p.X1756L
Putative somatic BCOR stop-loss mutation
N
T
DNA (WES)
BCOR:c.5267G>T:p.X1756L
Putative somatic BCOR stop-loss mutation
N
T
DNA (WES)
RNA (RNA-seq)
Recurrent BCOR ITDs
• ITD detected in 11/14 CCSK in initial cohort
 8/10 males; 3/4 females; median age 1.6 yr (0.6-3.5 yr)
 Confirmed in 12/13 CCSK cases in TARGET cohort
• ITD absent in:
o Patient-matched blood (n=1) or adjacent normal kidney (n=7)
o Wilms tumors (n=18), CMN (n=9), sarcomas (n=10)
• Identical ITDs detected in 2 metastatic relapsed CCSKs
Roy et al. Nat Comm 2015
Recurrent BCOR ITDs
ITD lengths:





Type I – 96 bp
Type II – 93 bp
Type III – 90 bp
Type IV – 87 bp (+3)
Type V – 114 bp
Roy et al. Nat Comm 2015
Germline and/or somatic mutations with potential
clinical relevance found in 40% of cases
Parsons et al., JAMA Oncology, 2016
Germline results can have an impact on
multiple family members
• 14 yo girl with glioblastoma
– Mother aware of cancer family history
but not in electronic medical record
– Sequencing revealed c.1697delA
frameshift mutation in MSH2
transmitted from her mother.
• MSH2 mutation associated with
Lynch syndrome and glioma.
– Cancer screening recommendations
made for siblings, mother and other
MSH2 positive family members
GBM
Patient can also be mosaic for a cancer
susceptibility mutation
Ian Campbell (BCM) creative
commons copyright
• Mosaicism – postfertilization event so only a
portion of cells carry the
mutation.
• Siblings not at risk but can
still pass it onto future
children
• With advent of clinical next
generation sequencing – we
have many more reports of
mosaicism
Example of unexpected finding of mosaic WT1
mutation in patient with Wilms tumor
• Subject 223202 – 9 mo male
with Stage III Wilms tumor.
• No FH of cancer, no congenital
anomalies and no genetic
testing recommended.
– WES revealed mosaicism for
frameshift in WT1.
– Complete loss of
heterozygosity in tumor.
– Finding of WT1 mutation
resulted in long-term renal
function assessment and more
frequent contralateral kidney
surveillance.
Tumor
Normal
Angshumoy Roy
Newly described TSG with unexpected tumor:
SMARCA4 LOF w/ neuroblastoma tumor
Expected gene with expected tumor – still
clinically useful
• 11 year old female seen in endocrine clinic: headache,
nausea/vomiting, abdominal pain with bp: 160/90
• Abdominal imaging revealed an almost 5 cm right
adrenal mass (MIBG avid) and plasma
normetanephrine 35.3 nmol/L (ULN:
Tumor0.89)
• Adrenalectomy performed - pheochromocytoma
• BASIC3 germline result revealed a heterozygous
c.499C>T (p.R167W) mutation (previously described
in another unrelated BASIC3 patient with
pheochromocytoma
• Patient now undergoing routine VHL surveillance
Impact on family – asymptomatic 8 year old brother
undergoes testing (+VHL), imaging revealed bilateral
pheochromocytomas and elevated plasma metanephrines
63yrs
A/W
d.69yrs
Lung ca
d.33yrs
HIV
47yrs
A/W
27yrs
A/W
65yrs
70yrs
43yrs
VHL+
44yrs
VHL-
High Cholesterol
2
A/W
A/W
Unilateral pheo Bilateral pheo
dx. 11yrs
dx. 8yrs
VHL+
VHL+
25yrs
A/W
20yrs
A/W
36yrs
4
33yrs
2
Zhang J et al. N Engl J Med 2015. DOI: 10.1056/NEJMoa1508054
Frequency of Pediatric Cancer
Types among Patients Younger
than 20 Years of Age.
(N – 1120)
Zhang J et al. N Engl J Med 2015. DOI: 10.1056/NEJMoa1508054
Distribution of Germline
Mutations in Different Gene
Categories and Cancer Subtypes
• 8.5% had pathogenic dominant
mutations (entire cohort)
• 5.6% if hypodiploid ALL and
ACT excluded
• Single recessive diagnosis (AT)
• 8.5% prevalence of single
recessive pathogenic mutations
• 2/3 demonstrated LOH
Zhang J et al. N Engl J Med 2015. DOI:
10.1056/NEJMoa1508054
Contrasting WES results in pediatric cancer
and neurodevelopmental cohorts
Pediatric Cancer
• Diagnostic rate of ~9%
• Autosomal dominant
disorders predominate
• Small numbers but ~85%
inherited from parent
• Results frequently impact
screening & surveillance
recommendations
• Tumor data can be used to
aid interpretation of
germline genome
Neurodevelopmental
• Diagnostic rate of 25%
• More equal mixture of AD,
AR and XLR
• De novo mutations (~70%)
predominate (multiple DNM)
• Results used for diagnosis
and refining recurrence risk
for parents
Baylor College of Medicine Germline and
Cancer Exome Key Team Members
Richard
Gibbs
Will Parsons
Pediatric Oncology
Christine Eng
Molecular Diagnostics
Yaping Yang
Molecular Diagnostics
Angshumoy Roy
Molecular Pathology
David Wheeler
Cancer Informatics
Donna Muzny
Operations
Marilyn
Li
A Clinical Sequencing Exploratory Research (CSER) project
Supported by NHGRI/NCI 1U01HG006485
BASIC3 Project 1 (clinical)
• Sharon Plon, MD, PhD (Project PI)
• Will Parsons, MD, PhD (Project PI)
• Murali Chintagumpala, MD (co-I)
• Stacey Berg, MD (co-I,)
• Susan Hilsenbeck, PhD (co-I)
• Tao Wang, PhD (co-I)
BASIC3 Clinical Project Team
• TXCCC pediatric oncologists
• Robin Kerstein, MT, CCRA
• Sarah Scollon, MS, CGC
• Katie Bergstrom, MS, CGC
• Stephanie Gutierrez (Data manager)
• Ryan Zabriskie (Laboratory manager)
TCH/BCM Pathology
• Angshumoy Roy, MD, PhD
• Dolores López-Terrada, MD, PhD
• Adekunle Adesina, MD, PhD
TCH Surgery and Neurosurgery
BCM/TCH leadership
• David Poplack, MD
• Susan Blaney, MD
• Arthur Beaudet, MD
• James Versalovic, MD, PhD
• Jed Nuchtern, MD
BASIC3 Project 2 (sequencing and reporting)
• Richard Gibbs, PhD (co-PI)
• Christine Eng, MD (co-PI)
• Yaping Yang, PhD (co-I)
• Angshumoy Roy, MD, PhD (co-I)
• David Wheeler, PhD (Co-I)
• Donna Muzny, MS
BASIC3 Project 3 (ELSI)
• Laurence McCullough, PhD (co-PI)
• Richard Street, Jr., PhD (co-PI)
• Amy McGuire, JD, PhD (co-I)
• Melody Slashinski, PhD (co-I)
ClinGen - www.clinicalgenome.org
The Clinical Genome Resource
Purpose: Create authoritative central resource that defines the clinical
relevance of genes and variants for use in precision medicine and research.
Rehm et al. ClinGen - The Clinical Genome Resource. N Engl J Med 2015; 372:2235-2242
www.clinicalgenome.org
www.ncbi.nlm.nih.gov/clinvar
Aggregating Variant Interpretations in ClinVar
Sharing Clinical
Reports Project
Clinical Labs
Researcher
s
Expert
Groups
Unpublished
or
Literature
Citations
Genome Connect and
Free-the-Data
Patient
s
Clinics
Patient Registries
Linked Databases
ClinVar
Variant-level Data
OMIM
CFTR2
InSiGHT
BIC
PharmGKB
Current Largest Submitters to ClinVar Across
All Genes
Submitter
Variants Submitted Total
w/ interpretations Genes
Last updated
OMIM; Johns Hopkins University 26656
3991
Apr 29, 2016
GeneDx
22391
653
Mar 25, 2016
Emory Genetics Laboratory
15982
1299
Jun 09, 2015
Invitae
8473
344
Mar 17, 2016
Laboratory for Molecular
Medicine; Partners Healthcare
12207
405
Aug 18, 2015
10413
818
Sep 15, 2015
10175
317
Apr 08, 2016
Genetics Services Laboratory;
University of Chicago
Ambry Genetics
ClinVar Variant View
ClinVar Review Levels
ClinVar uses a
rating system to
help users assess
the quality and
consistency of
submitted variant
assertions
Practice
Guideline
Expert Panel
Multi-Source Consistency
Single Submitter – Criteria Provided
Single Submitter – No Criteria Provided
No Assertion
No stars
Not applicable
58
Key Features of Expert Panels
• Multi-institutional membership (often international in
nature):
– Multiple types of expertise represented in the committee:
clinical, laboratory, bioinformatic
• Panel focuses on a limited set of genes/diseases:
– Thoughtful and experienced analysis of a few genes is
preferred over large sets of genes.
• Details of the variant classification procedures must be
available on the web or by publication
• Applications reviewed by ClinGen Steering Committee
• ENIGMA has Expert Panel status and has deposited 1030
BRCA1/2 variants to date.
59
Variant Curation Interface
NM_007294.3(BRCA1):c.5559C>A (p.Tyr1853Ter)
Header
always
present
Tabs for
different
evidence
categorie
s
Variant Specific Information
ClinVar VariationID: 55629
Canonical Allele ID: CA000234
dbSNP ID: rs80357336
Variant type: single nucleotide polymorphism
Interpretation Transcript: [Add]
Gene-specific Information
Associated gene: BRCA1
Uniprot: P38398 (BRCA1_HUMAN)
BRCA1 Associated disease: breastovarian cancer, familial, 1 [OMIM:
604370]
Record-specific Information
Creator: Curator1
Last edited: 2016-02-13
Other interpretations:
Curator 2: Provisional: pathogenic. date
Curator 3: In process; last edited: date
Interpret
Basic
Information
Population
Computationa
l
Functional
Segregation
Genomic
NC_000017.11:g.43045711G>T (GRCh38)
NC_000017.10:g.41197728G>T (GRCh37)
ClinVar
NM_007294.3:c.5559C>A
NM_007299.3:c.*73C>A
NR_027676.1:n.5695C>A
nonsense SO:0001587
3 prime UTR variant SO:0001624
non-coding transcript variant
SO:0001619
RefSeq
NM_007294.3:c.5559C>A
NP_009225.1:p.Tyr1853Ter
stop gained SO:0001587 +
Ensembl
ENST00000357654.7:c.5559C>A
ENSP00000350283.3:p.Tyr1853Ter
stop gained SO:0001587 +
Associate
breast-ovarian cancer, familial, 1
RCV000049051.2 (Unknown)
Case
Gene-specific
Ability to
interpret
based on
evidence
Shared
information
Selina Dwight - Stanford Univer
ClinGen Acknowledgements
ClinGen Steering Committee
Jonathan Berg, UNC
Lisa Brooks, NHGRI
Carlos Bustamante, Stanford
Mike Cherry, Stanford
James Evans, UNC
Andy Faucett, Geisinger
Katrina Goddard, Kaiser Permanente
Danuta Krotoski, NICHD
Melissa Landrum, NCBI
David Ledbetter, Geisinger
Christa Lese Martin, Geisinger
Aleks Milosavljevic, Baylor
Robert Nussbaum, UCSF
Kelly Ormond, Stanford
Sharon Plon, Baylor
Erin Ramos, NHGRI
Heidi Rehm, Harvard
Sheri Schully, NCI
Steve Sherry, NCBI
Michael Watson, ACMG
Kirk Wilhelmsen, UNC
Marc Williams, Geisinger
Program Coordinators:
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Chairs: Christa Martin,
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and Data Submission
WG
Chair: Karen Eilbeck,
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Hereditary Cancer:
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Offit, Sharon Plon
Somatic Cancer: Shashi
Kulkarni, Subha
Madhavan
Chairs: Jonathan Berg,
Christa Martin
Chairs: Andy Faucett,
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Actionability WG
Sequence Variant
Interpretation WG
Data Model WG
Chairs: Les Beisecker,
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Chairs: Larry Babb,
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Cardiovascular: Euan
Ashley, Birgit Funke, Ray
Hershberger
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Metabolic: Rong Mao,
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Craigen
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Disclosure
Recommendations
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Chair: Carlos
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Engagement, Access
WG
Chairs: Jim Evans,
Katrina Goddard
EHR WG
Chair: Marc Williams