Molecular and Genomic
Pathology at UNC
Molecular and Genomic
Pathology at UNC
David A. Eberhard, MD, PhD
Dept. of Pathology and Laboratory Medicine
Director, Preclinical Genomic Pathology Lab
Lineberger Comprehensive Cancer Center
University of North Carolina – Chapel Hill
ADASP Annual Meeting
March 2, 2013
Notice of Faculty Disclosure
In accordance with ACCME guidelines, any individual in a
position to influence and/or control the content of this ASCP
CME activity has disclosed all relevant financial relationships
within the past 12 months with commercial interests that
provide products and/or services related to the content of this
CME activity.
The individual below has responded that he/she has no relevant
financial relationship(s) with commercial interest(s) to disclose:
David A. Eberhard, MD, PhD
World Rank of NGS Centers
180
160
140
120
100
80
60
40
20
0
From http://topsequence500.org/
Different NGS Platforms
Have Different Capabilities
Sequence alterations
Text
DNA and RNA
RNA expression
profiles
DNA copy number
variations
DNA
rearrangements
RNA splicing variants
A single method is suitable for
some of these, but not others –
must consider cost, specimen type,
& application
Methylation
NGS Applications in Cancer
Human Genome Project: reference
genome and large-scale compilation of
tumor variants from various sources
(http://cancercommons.org,
www.icgc.org,
http://cancergenome.nih.gov/,
http://www.sanger.ac.uk/genetics/CGP/
cosmic/
• Mutation Panels (Genotyping or resequencing)
• Exome or transcriptome screening
• Genome sequencing (compare to normal or
reference sample)
Genome Res. 2012 Nov;22(11):2101-8
Erlotinib
(2004)
Crizotinib
(2011)
Text
Vandetinib
Vemurafinib
Resistance to Erlotinib?
Headline
8
NGS For Cancer Diagnostics
• Potentially improve Economy, Efficiency, Sensitivity
• No one size fits all: must consider desired end use
• Considerations for technical platform:
– Broad vs Deep: More genes vs more sensitivity
– Turnaround time & cost: single samples vs multiplex batches
– PCR vs non-PCR libraries: implications for sample amount, false
positives
– Sample preanalytical variables (FFPE, amount, etc)
– References (T/N), standards
– What results does it provide? What results do we report?
Making NGS Accessible
NGS In Clinical Cancer Diagnostics
How much do you need?
Broad coverage =
more complexity and cost;
more unknown variants;
overkill for clinical care?
What do you need to find?
Large indels,
rearrangements with
variable breakpoints are
difficult
Deep Coverage Improves
Mutation Detection
Small Sample Size and Low Tumor
Content May Result In False Negatives
WT
WT
Mu
----
WT
Mu
Detection
Limit
-------------------------------Mu
NGS Mutation Detection Issues
NGS platformdependent false
positives
FFPE background
noise
Variable % tumor cells
and variable % tumor
cells with secondary
mutation
Mutation confirmation
Usually by Sanger sequencingwill platform evolution eliminate?
May overlap with NGS
false positive rate and
background noise
Low level mutations- not easily
confirmed by Sanger sequencing
(higher detection threshold ≈ 15-20%)
May need more sensitive method –
DGGE, dHPLC, pyrosequencing or
mutation enrichment- i.e. COLD PCR
What to Test?
•
Quality and quantity are key determinants
•
•
•
Primary vs. metastasis
•
•
•
A cellular FNA is better than a necrotic resection
Decal; Bouin’s etc degrade quality
May be changes during interval therapy
If metastasis after initial response, then test metastasis
Multiple primaries
•
•
•
If histologies differ, then test BOTH/ALL
Patients benefit even if 1 of multiple tumors responds
Testing multiple areas in a tumor is unnecessary
N Engl J Med.
2012 Mar
8;366(10):883-92
Minimum Tumor Content
•
•
•
•
Absolute and relative amounts of tumor
Each lab must determine during validation
Pathologist must review each section
Enrichment: Macrodissection is recommended
•
Laser capture, WGA are error-prone
Tumor Sample Heterogeneity
• Clinical sample characteristics: size/amount, matrix,
preservation
– Blood: whole, buffy coat, Ficoll, FACS, CTCs
– Tissue: fresh, fixed (FFPE), decal bone, biopsies, resections
– Cytology: aspirates (FNA), buccal swabs, smears
• Clinical sample composition: Various cell and tissue types
– tumor cells, stromal cells, vascular cells, immune/inflammatory
cells, normal tissue
– Viable tissue (dense, fatty), necrosis, mucin, hemorrhage
• Tumor genotypic and phenotypic composition
– Mono- vs Polyclonality; tumor evolution; variable differentiation,
EMT, stem cells
Bioinformatics
NGS diagnostics is highly
dependent on data
analysis and management
Requires bioinformatics
and statistical expertise
and computational
hardware
Unprecedented amounts of
data and processing
algorithms necessitate
adequate tools
(Alignment and assembly QC of
image processing,
base calling, filtering, variant
calling, SNP finding, archiving)
Clinical Issues:
Evaluation of the variant
positions “called” involves
queries of all known
relevant databases
Lack of databases curated
to accept clinical standards
is significant challenge in
managing and reporting
genome sequencing data
EHR considerations – test
ordering, archiving of NGS
reports, patient consent,
data (reinterpretation?)
Clinical Utility - Challenges
Which variants are
clinically actionable?
NGS yields many
variants of unknown
significance
How to establish significance
(Structural, functional, preclinical, clinical)?
What are necessary levels of evidence?
Risk of over interpretation
unnecessary medical action
unwarranted psychological stress
Headline
Specimen
Issues
Assay
Issues
Predictive
Model
Development,
Specification,
and
Preliminary
Performance
Evaluation
Clinical Trial
Design
Ethical, Legal
and Regulatory
Issues
LCCC 1108: Development of a Tumor Molecular
Analyses Program and Its Use to Support Treatment
Decisions (UNCseqTM)
• Primary Objectives of LCCC1108
– To provide a mechanism for association of known
molecular alterations with clinical outcome in oncology via
genetic profiling of patient specimens
– To support treatment decisions by providing rapid genetic
profiling of patient specimens and sharing reportable
results with treating physicians
• Prospective patients are consented such that biopsied tissue
may be used for both research and clinical purposes
• Executive, Technology, Clinical, and Pathology committees
formed to cover all aspects of the study protocol
LCCC 1108 (UNCseqTM) Process
Targeted Exome Sequencing
Normal
DNA
Tumor
Libraries
UNCseq 6.0:
247 cancer genes, 10 viruses
pool
barcode
Illumina HiSeq or MiSeq
Computational
processing to call
somatic mutations
Sequence Alignment
Read
ATGCCATTACACAGCGA
Human Genome (hg19)
… CGATCTAACGTAGCTAGCTAGCTAGCTAGCATGCCATTACACAGCGAACAGGGAGCTTAGGCGC…
GTAGCTAGCTAGCTAGC
CTAGCTAGCTAGCTAGC
CGATCTAACGTAGCTAGC
GAACAGGGAGCTAAGG
ACAGGGAGCTAAGGCGC
ATTACACAGCGAACAGG
Tumor Somatic Mutation Calling
526 reads of ‘T’
416 reads of ‘T’
98 reads of ‘C’
Normal
Tumor
Glioblastoma: Tx resection, chemoradiation.
Progressed with transformation to gliosarcoma
Headline
Approved drug linked to gene,
SOC (1) or Non-SOC (2A)
Potential clinical action,
e.g. drug in clinical trials
Trametinib: nearing approval (BRAF+ melanoma)
CDKN2A (p16Ink4A): 9p21
Glioblastoma: Tx resection, chemoradiation.
Progressed with transformation to gliosarcoma
Headline
Approved drug linked to gene,
SOC (1) or Non-SOC (2A)
Potential clinical action,
e.g. drug in clinical trials
Headline
UNCseq Gliosarcoma: PTEN IHC
Glioma component
Sarcoma component
Did PTEN mutation accompany evolution to sarcoma?
Mol/Genomic Path Education: UNC
– Molecular Diagnostics course for residents and fellows
includes 3.5 hrs on NGS
– 2 Mol Path fellows with focus on genomics: 1 on UNCseq
(oncology), 1 on NCGenes (germline)
– LabCorp / UNC interactions provides reference lab exposure
for Mol Path fellows (diagnostics and clinical trials)
– Translational Pathology course for PhD and MD/PhD
students includes sections on Mol Path, Genomics and
Translational Pathology Ex-Academia
Mol/Genomic Path Education:
Pharma and Dx Industry
• Molecular Pathology and Cancer Genomics integrates with
targeted drug development – provides tremendous opportunity
for cooperation between pathology centers and industry
– Providing clinical-grade assays and laboratories to support trials and highquality research
– Providing expertise to integrate practical pathology with cutting-edge
science
– Expanding educational and career opportunities for pathologists
UNCseqTM Team
Investigators
•
Shelley Earp
•
Juneko Grilley-Olson
•
Neil Hayes
•
Ned Sharpless
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Ben Calvo
•
Matthew Ewend
•
Matthew Nielson
•
Linda Van Le
•
Robert Esther
•
Nirmal Veeramachaneni
•
Cary Anders
•
Peter Voorhees
•
Keith Amos
•
Robert Dixon
•
Stergios Moschos
•
Young Whang
•
David Eberhard
Operations Group
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Juneko Grilley-Olson
•
Claire Dees
•
Lisa Carey
•
Ned Sharpless
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David Eberhard
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Ian Davis
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Jeanne Noe
•
Wasi Khan
Research Team
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Bes Baldwin
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Ashley Salazar
•
Michele Hayward
•
Todd Hoffert
Technical Group
•
Neil Hayes
•
Ned Sharpless
•
David Eberhard
•
Joel Parker
•
Xiaoying Yin
•
Will Jeck
•
Piotr Mieczkowski
•
Todd Auman
•
Billy Kim
•
Chuck Perou
•
Gary Rosson
•
Bryan Yonish
Pathology Group
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David Eberhard
•
Karen Weck-Taylor
•
Nirali Patel
•
Yuri Fedoriw
•
Ryan Miller
•
Yuri Trembath
•
Bill Funkhouser
CCGR
•
Claire Dees
•
Lisa Carey
•
Jim Evans
•
Jonathan Berg
•
Bert O’Neill
•
Billy Kim
•
Vicky Bae-Jump
•
Carol Shores
•
Kristy Richards
•
Carrie Lee
•
Jing Wu
•
Andrew Want
•
HJ Kim
•
David Ollila
Marketing
•
Ellen de Graffenreid
Bioinformatics/Computing
•
Joel Parker
•
Alan Hoyle
•
Lisle Mose
•
Stuart Jeffries
•
Sai Balu
•
Matthew Soloway
•
Janae Simons
•
Jeff Roach
•
Vonn Walter