Gatza_TCGAlobular_5.13.2014.FINAL

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Genomic Characterization of
Invasive Lobular Breast Carcinoma
Michael L. Gatza, Ph.D.
TCGA Breast Cancer AWG
Invasive Breast Carcinoma
Invasive Ductal Carcinoma (IDC)
50-80%
Ductal
Mixed IDC.ILC
4-5%
webmd.com
Lobular
2
Invasive Lobular Carcinoma (ILC)
10-15%
Summary of Data Freeze
Pathology centrally re-reviewed
(Andy Beck, Harvard)
817
490
127
88
112
3
Identification of differentially expressed genes
Ductal
LumA
Ductal
N=663 genes
2 Class SAM FDR=0
Lobular
LumA
Lobular Normal
ATM network
Immune signaling (multiple)
MAPK signaling
MYC targets (multiple)
E-cadherin stabilization
Low
4
Mike Gatza, UNC
High
mRNA Expression
CDH1
Development of Integrated MAF
DNA Exome sequencing
Integrated MAF
UNCeqR (mRNAseq / DNAseq)
Integrated MAF
Integrated MAF
ABRA (CDH1, TP53, GATA3, PTEN, RB1)
DNA-based MAF
Matt Wilkerson (UNC), Lisle Mose (UNC)
Giovanni Ciriello (MSKCC), Cyriac Kandoth (MSKCC)
5
Mike McLellan (Wash U)
DNA-based MAF
Comparison of significant alterations: IDC vs. ILC
6
Giovanni Ciriello, MSKCC
Identifying IDC LumA and ILC LumA-specific alterations
IDC
ILC
GATA3 (p=0.0002)
Low
High
Protein Expression
7
Giovanni Ciriello, MSKCC
PARADIGM analysis identifies IDC and ILCassociated signaling pathways
Blue: ILC DOWN
Red: ILC UP
CDH1
IDC
ILC
IDC
Low
ILC
mRNA
p53/DNA Damage Response
MYC
Protein
High
mRNA Expression
Low
High
Protein Expression
XBP1
Immune Related
8
Christina Yau, Buck Institute
Development of mRNA-based ILC classes
2
3
Centroid classifier (90genes)
1
ConsensusClusterPlus to ID 3 ILC classes
Identified samples with positive sil. width
ClaNC developed centroid predictor
TCGA ILC LumA (n=106)
TCGA ILC LumA (n=89)
TCGA ILC LumA (n=89)
9
Mike Gatza, UNC
2 Class SAM identifies differentially expressed
genes in ILC classes
988 genes (FDR=0)
Class1
C2
C3
N= 722 genes
EGFR
MET
GLI1
FGF17
WNT6
AREG
KIT
KRT 14, 15, 17, 32, 81
KRK 1, 6-8
CLDN 8,10,11, 19
PTCH2
TP63
VIT
ID4
N= 268 genes
Immune-related genes: >100
Low
High
mRNA Expression
10
Mike Gatza, UNC
LCK
IFNG
ILC class mRNA / miRNA expression patterns
correspond with IDC and Adjacent Normal
IDC
Norm
988 genes (FDR=0)
miRNA (SAMseq FDR<0.05)
ILC
Low
ILC
IDC
High
Normal
mRNA Expression
Class 1
61
49
94
Class 2
39
167
0
Low
High
miRNA Expression
Class 3
11
27
Mike Gatza, UNC
274
P<0.0001
0
Reanne Bowlby, BC Cancer Agency
ILC Class1 corresponds with RPPA Reactive Subtype
ILC Class (n=127)
Class1
Class2
Class3
Reactive
Non-reactive
Missing data
P<0.0001
RPPA Subtype (n=70)
RPPA
Annexin1
Caveolin1
Collagen IV
Myh11
RMB15
Low
High
Protein Expression
Mike Gatza, UNC
12
Gordon Mills, MDACC
ILC Class1 tumors exhibit altered PDGFR/
STAT3 and FoxM1 signaling
PARAGIGM
FOXM1 sub-network
PDGFR
FoxM1
RPPA
pSRC Y527
pSTAT3 Y705
FoxM1
Low
High
Protein Expression
Christina Yau, Buck Institute
13
Mike Gatza, UNC
ILC class 2 defined by high immune signaling
and proliferation
Class1
Class2
Class3
B-cell
BCR
B-cell (CS)
CD8
CD8 (CS)
T-cell (CS)
LCK
T-cell (TNBC)
NK
T-cell (Teschendo)
MΦ TH1 (CS)
MΦ CSF1
TCR
TCGA ILC (n=127)
Low
High
Proliferation Score (PAM50)
Signature Score
14
Mike Gatza, UNC
P=1.39e-10
Class 1
Class 2 Class 3
PARADIGM analysis identifies IFNG and FOXM1 as
key pathways in ILC class 2 tumors
15
Christina Yau, Buck Institute
Summary
•
Developed unique integrated MAF utilizing both DNA exome and mRNA
sequencing
•
ILC vs. IDC
–
–
–
–
•
FOXA1, CDH1 mutations associated with ILC
GATA3 mutation associated with IDC
Altered signaling: CDH1, Myc, p53/DNA damage, immune signaling
Identified differentially expressed miRNA and methylation
ILC classes
– Class 1 associated with Reactive subtype
– Class 2 immune component and highly proliferative
16
TCGA Breast Cancer Analysis Working Group
Baylor College of Medicine
Chad Creighton
Xiaosong Wang
British Columbia Cancer
Agency
Andy Chu
Elizabeth Chun
Andy Mungall
Gordon Robertson
Dominik Stoll
Broad Institute
Andrew Cherniack
Greater Poland Cancer Center
Maciej Wiznerowicz
Harvard Medical School
Terrence Wu
Yonghong Xiao
Institute for Systems Biology
Sheila Reynolds
Ilya Shmulevich
Lawrence Berkeley National
Laboratory
Paul Spellman
Mayo Clinic
Jim Ingle
17
The University of Texas
MD Anderson Cancer Center
Roel Verhaak
Rehan Akbani
Nancy Shih
Gordon Mills
Memorial Sloan-Kettering
Cancer Center
Giovanni Ciriello
Niki Schultz
Ethan Cerami
Arthur Goldberg
Caitlin Byrne
Anders Jacobsen
Tari King
Chris Sander
Nationwide Children’s
Hospital
Jay Bowen
Julie Gastier-Foster
National Cancer Institute
Chunhua Yan
John Demchok
Laura Dillon
Margi Sheth
Peter Good
Jacqueline Palchik
Heidi Sofia
Kenna Shaw
University of California
Santa Cruz
Buck Institute
Chris Benz
David Haussler
Christina Yau
Sam Ng
Ted Goldstein
Kyle Ellrott
Charlie Vaske
Josh Stuart
Jing Zhu
University of California,
San Francisco
Fred Waldman
University of Southern
California
Peter Laird
Swapna Mahurkar
Simeen Malik
Dan Weisenberger
Windber Research
Institute
Hai Hu
Richard Mural
University of North
Carolina
Chuck Perou (co-chair)
Katie Hoadley
Mike Gatza
Joel Parker
Xiaping He
Michael Iglesia
Grace Silva
Wei Zhao
The Genome Institute
at Washington University
Matthew Ellis (co-chair)
Li Ding
Lucinda Fulton
Daniel Koboldt
Elaine Mardis
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