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TRANSCRIPT
1/20/2016
1
Practical Molecular Diagnostics in
Lung Cancer: Beyond the NCCN
Guidelines
Lynette M. Sholl, M.D.
Department of Pathology
Brigham and Women’s Hospital
Harvard Medical School
Boston, MA
Disclosures
• Genentech: Scientific Advisory Board
Objectives
• Established and emerging molecular targets in
lung cancer
– Applying advanced technologies in clinical practice
• Role of pathology in current lung cancer
management
– Optimizing histologic diagnoses on small biopsies
– Application of predictive immunohistochemistry
– Accurate reporting of molecular results
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Trends in lung cancer histology
Histologic Diagnoses,
SEER data 2008-2012
Meza et al. PLOSOne 2015.
Small cell, 13.1
Squamous cell,
22.8
Adenocarcinoma,
43.2
Large Cell, 2.1
NSCLC, 10.6
Carcinoma,
NOS, 3.1
Other,
5.0
Sarcoma, 0.2
• Change in smoking habits
– Decline in tobacco use since
the 1960s
– Increased use of filters
requiring more vigorous
inhalation
Reasons for increased fraction of adenocarcinoma?
Trends in lung cancer outcomes
• 27% of all cancer deaths
in 2015
• Significant downward
trends in death rates
among both men and
women diagnosed with
lung cancer between
2000-2010
Edwards et al. Cancer 2014.
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Reasons for decreasing mortality
rates?
Improved detection:
Reasons for decreasing mortality
rates?
Improved therapy:
Kris et al. JAMA 2014.
TARGETED THERAPIES
Lung adenocarcinoma
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EGFR an attractive therapeutic target
• Important pro-growth signaling protein in normal and neoplastic tissues
• Commonly overexpressed in multiple tumor types, including lung cancer
• EGFR TKIs the new wonder drugs in lung cancer??– Poor outcomes from clinical
trials of erlotinib and gefitinib in unselected patients
– Occasional patients with exceptional response to therapy
EGFR mutation is key biomarker
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EGFR mutation
…vs. copy number?
What’s the relationship?
• In an EGFR-mutated tumor:
– Step 1: mutation
– Step 2: amplification and
protein overexpression
•Amplification/overexpression
may occur in the absence of
mutation.
ALK translocations in NSCLC:
3 years (!) from bench to bedside
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CAP/AMP/IASLC
Clinical Practice Guidelines
• Any advanced stage (IV) patient with ACA or patient with progressive disease should receive EGFR and ALK testing– Reflex testing may be appropriate
in certain environments
– This testing is not recommended for lung tumors lacking evidence of ACA differentiation
– Avoid the term “non small cell lung carcinoma” whenever possible
• Prioritize tissue for EGFR and ALK testing
ROS1 rearrangements in lung cancer
•Rare (1-2% of lung
ACA)
•More common in
never smokers
•Promising responses to
crizotinib therapy
Shaw AT et al. N Engl J Med 2014;371:1963-1971.
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RET rearrangements in lung cancer
• Rare (1% of lung ACA)
• Results from small intrachromosomalrearrangement
(inv (10)(p11.22q11.2)
• More common in never smokers
• Reported responses to:– cabozantinib
• (c-Met, VEGFR2 inhibitor)
– Vandetanib • (VEGFR, EGFR, RET inhibitor)
Takeuchi et al Nat Med 2012
67 year old woman with lung mass and
numerous subcutaneous metastases:
EGFR, ALK, ROS1 wild type
Sequencing reveals METex14 mutation &
MET amplification with Exon 14 skipping
Efficacy of crizotinib in MET ex 14 splice tumors
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• 64yo M, ~15 pack-year smoker, quit 1 year prior to diagnosis
• May 2014: diagnosed with stage IV lung adenocarcinoma
• Standard testing negative for EGFR, ALK, ROS1
• Started on first-line carboplatin/pemetrexed, with mixed response
• BRAF c.1799T>A (p.V600E) detected by sequencing
Dabrafenib (BRAF inhibitor) +
Trametinib (MEK inhibitor)*
October 2014 March 2015
*60% overall response rate in the phase 2 trial for patients with BRAF V600E mutations.
Planchard et al. J Clin Oncol 33, 2015 (suppl; abstr 8006)
KRAS
33.8
EGFR
19.1ALK
3.9
BRAF
3.8MET
3.0
PIK3CA
2.9
ERBB2
2.5NRAS
1.0
ROS1
1.1
RET
1.0
AKT1
0.6
MAP2K1
0.3
HRAS
0.1
No/unknown driver
29.9
Oncogenic drivers in
non-squamous NSCLC (%)
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Reality check.
“Non small cell lung carcinoma”
Adenocarcinoma Squamous cell carcinoma
Most common subtype in
nonsmokers
Unique chemosensitivity
profile (pemetrexed)
~60% have a defined oncogenic
driver
-“Targetable”
Smokers
Use of antiangiogenic agents
associated with massive
pulmonary hemorrhage
Minority with defined
oncogenic driver
-Limited targetability
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IASLC algorithm for Small Biopsies
Subclassification of morphologic
NSCLC-NOS
IASLC classification of small biopsies,
take home points:
• Distinguish ACA and SQC whenever possible
• The molecular profile of an ACA will dictate
targeted therapy
• Judicious use of IHC is critical
– Two first-line markers:
• TTF1 and p63 or p40
• Less established/less specific markers (napsin, mucin,
CK7, CK5/6) should be considered second line
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Make a diagnosis
+
EGFR, KRAS, HER2, BRAF, PIK3CA,
ALK, ROS1, RET, MET, etc. mutations,
copy number alterations, translocations
EGFR mutation-specific
antibodies
(clones 43B2 and 6B6)
Study L858REx19del
Sensitivity Specificity Sensitivity Specificity
Yu et al.92%
(24 of 26)99%
(193 of 195)86%
(23 of 26)100%
(196 of 196)
Kawahara et al.
83%(19 of 23)
100%(16 of 16)
62%(13 of 21)
100%(16 of 16)
Kato et al. 75%
(9 of 12)97%
(56 of 58)50%
(9 of 18)100%
(52 of 52)
Brevet et al.95%
(20 of 21)99%
(171 of 173)74%
(23 of 31)99%
(161 of 163)
Fan et al.93%
(40 of 43)100%
(126 of 126)74%
(17 of 23)99%
(145 of 146)
Bondgaard et al.
80%(8 of 10)
98%(152 of 155)
63%(12 of 19)
99%(153 of 155)
Excellent specificity, limited sensitivity
Informative if positive- may be useful in
scant specimens
Cutz et al. JTO 2014
ALK IHC
93-100% sensitive and specific as compared to FISH
Ventana ALK (D5F3) CDx assay approved as a companion diagnostic for crizotinib
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ROS1 IHC
(D4D6 antibody)Ideal screening tool:
Excellent sensitivity,
good specificity
Reference N Sensitivity Specificity Notes
Sholl et al. 2013 210 100 92 Focal expression in a KRAS-
mutated tumor
Strong expression in a FISH
negative tumor
Mescam-Mancini
et al. 2014
221 100 96.9 Expressed in two HER2-
mutated tumors
Cha et al. 2014 330 100 72.6-93.4* ROS1 expression seen in ROS1
WT tumors from ever-smokers
Boyle et al. 2014 33 100 100 As compared to FISH or RT-PCR
Sholl et al. AJSP 2013.
Reference Clone IHC pattern vs.RET
N
WT
NSensitivity Specificity
Tsuta et al.
2014EPR2871 Any
FISH or
RTPCR21 1774 66.7 86.1
Lee et al. 2014 ab134100 Any
Transcript
profiling or
FISH
15 79 100 87.3
Sasaki et al.
2014
3F8 Any RTPCR 3 154 100 70.3
EPR2871 Any RTPCR 3 75 100 33.3
EPR2871Mod to
strong onlyRTPCR 3 75 66.7 77.3
RET IHC• Variable antibody
performance
• Current evidence doesn’t
support routine clinical useTsuta et al. Br. J. Cancer 2014
How has next gen sequencing (NGS)
changed the game?
• Increased target coverage with decreased
tissue requirements
ABL1 BMPR1A CDKN1B EP300 FAS HRAS MDM2 NFKBIZ PRAME RPL26 STAG2
AKT1 BRAF CDKN1C EPHA3 FBXW7 ID3 MDM4 NKX2-1 PRDM1 RUNX1 STAT3
AKT2 BRCA1 CDKN2A EPHA5 FGFR1 IDH1 MECOM NOTCH1 PRF1 SBDS STAT6
AKT3 BRCA2 CDKN2B EPHA7 FGFR2 IDH2 MEF2B NOTCH2 PRKAR1A SDHA STK11
ALK BRD4 CDKN2C ERBB2 FGFR3 IGF1R MEN1 NPM1 PRKCI SDHAF2 SUFU
ALOX12B BRIP1 CEBPA ERBB3 FGFR4 IKZF1 MET NPRL2 PRKCZ SDHB SUZ12
APC BUB1B CHEK2 ERBB4 FH IKZF3 MITF NPRL3 PRKDC SDHC SYK
AR CADM2 CIITA ERCC2 FKBP9 INSIG1 MLH1 NRAS PRPF40B SDHD TCF3
ARAF CARD11 CREBBP ERCC3 FLCN JAK2 MLL NTRK1 PRPF8 SETBP1 TCF7L1
ARID1A CBL CRKL ERCC4 FLT1 JAK3 MLL2 NTRK2 PSMD13 SETD2 TCF7L2
ARID1B CBLB CRLF2 ERCC5 FLT3 KCNIP1 MPL NTRK3 PTCH1 SF1 TERC
ARID2 CCND1 CRTC1 ESR1 FLT4 KDM5C MSH2 PALB2 PTEN SF3B1 TERT
ASXL1 CCND2 CRTC2 ETV1 FUS KDM6A MSH6 PARK2 PTK2 SH2B3 TET2
ATM CCND3 CSF1R ETV4 GATA3 KDM6B MTOR PAX5 PTPN11 SLITRK6 TLR4
ATRX CCNE1 CSF3R ETV5 GATA4 KDR MUTYH PBRM1 PTPRD SMAD2 TNFAIP3
AURKA CD274 CTNNB1 ETV6 GATA6 KEAP1 MYB PDCD1LG2 QKI SMAD4 TP53
AURKB CD58 CUX1 EWSR1 GLI1 KIT MYBL1 PDGFRA RAD21 SMARCA4 TSC1
AXL CD79B CYLD EXT1 GLI2 KRAS MYC PDGFRB RAF1 SMARCB1 TSC2
B2M CDC73 DDB2 EXT2 GLI3 LINC00894 MYCL1 PHF6 RARA SMC1A U2AF1
BAP1 CDH1 DDR2 EZH2 GNA11 LMO1 MYCN PHOX2B RB1 SMC3 VHL
BCL2 CDK1 DEPDC5 FAM46C GNAQ LMO2 MYD88 PIK3C2B RBL2 SMO WRN
BCL2L1 CDK2 DICER1 FANCA GNAS LMO3 NBN PIK3CA RECQL4 SOCS1 WT1
BCL2L12 CDK4 DIS3 FANCC GNB2L1 MAP2K1 NEGR1 PIK3R1 REL SOX2 XPA
BCL6 CDK5 DMD FANCD2 GPC3 MAP2K4 NF1 PIM1 RET SOX9 XPC
BCOR CDK6 DNMT3A FANCE GSTM5 MAP3K1 NF2 PMS1 RFWD2 SQSTM1 XPO1
BCORL1 CDK9 EED FANCF H3F3A MAPK1 NFE2L2 PMS2 RHEB SRC ZNF217
BLM CDKN1A EGFR FANCG HNF1A MCL1 NFKBIA PNRC1 RHPN2 SRSF2 ZNF708
ROS1 STAG1 ZRSR2
POPv2 GENE LIST
SNV, INDELS, COPY NUMBER ALTERATIONS
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How has next gen sequencing (NGS)
changed the game?• Increased target coverage with
decreased tissue requirements
• Less biased genomic analysis– Detect novel variants in known
oncogenes
– Detect variants outside of coding regions
– Detect variants in genes not typically included on clinical test menus
– Detect common variants in known oncogenes in unusual contexts
NGS vs. IHC vs. FISH for
ALK translocation detection
ALK translocations in Lung Adenocarcinoma
Clinical FISH and/or IHC
ALK + ALK -
Oncopanel
ALK
Fusion + 25 0 Sensitivity
96%
Specificity
100% ALK
Fusion - 1* 190
Total 26 190
* 20% tumor in this specimen
NGS as an arbiter in discrepant cases:
ALK IHC (5A4 clone)
FISH negative IHC positive
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Fused Green onlyRed only
NGS showed: CLIP4-ALK fusion AND EML4-ALK fusion
From Vysis ALK FISH probe product insert
CLIP4
FISH cannot detect cryptic EML4-ALK fusions.
Unusual FISH results are considered “negative” but should be followed up.
MET in tumorigenesis
Lai AZ, et al, Trends in Cell Bio, 2009
• Exon 14 deletion removes the juxtamembranedomain of MET
• Tyr1003 phosphorylation site necessary for Cbl binding
• Decreased ubiquitination and impaired downregulation of the activated receptor
Identification of tumor-specific, intronic mutations in Met leading to exon 14 splicing.
Monica Kong-Beltran et al. Cancer Res 2006;66:283-289
©2006 by American Association for Cancer Research
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MET: Diverse Deletions & Point Mutations
Awad et al. J Clin Oncol, 2016.
MET juxtamembrane splice mutations:
not uncommon in lung adenocarcinomas
and predict response to MET inhibitors
• 2.4% in Kong-Beltran et al. Cancer Res, 2006
• 3.3% in Onazato et al. J Thor Oncol, 2009
• ~4.5% in TCGA Nature, 2014
• 3% in Frampton et al. Cancer Discovery, 2015
• 4% in Paik et al. Cancer Discovery, 2015
• 3% in Awad et al. J Clin Oncol, 2016
Clinical CharacteristicsClinical Characteristic
MET ex14
(N = 28)
EGFR
(N = 99)
KRAS
(N = 169)
Median age (range), years 72.5 (59-84) 61 (30-93) 65 (42-93)
Sex, N (%)
Male
Female
9 (32%)
19 (68%)
30 (30%)
69 (70%)
62 (37%)
107 (63%)
Smoking history, N (%)‡
Never-smoker
≤10 pack-years
>10 pack-years
10 (36%)
3 (11%)
15 (53%)
57 (58%)
10 (10%)
28 (28%)
6 (4%)
11 (7%)
152 (90%)
Race, N (%)
White, non-Hispanic
Asian
Black
White, Hispanic
Unknown
28 (100%)
0 (0%)
0 (0%)
0 (0%)
0 (0%)
79 (80%)
15 (15%)
1 (1%)
3 (3%)
1 (1%)
157 (93%)
0 (0%)
5 (3%)
3 (2%)
4 (2%)
Histology, N (%)
Adenocarcinoma
Pleomorphic w/ adenocarcinoma component
NSCLC, poorly-differentiated
Squamous
Adenosquamous
18 (64%)
4 (14%)
5 (18%)
0 (0%)
1 (4%)
92 (93%)
0 (0%)
4 (4%)
2 (2%)
1 (1%)
150 (89%)
3 (2%)
10 (6%)
5 (3%)
1 (1%)
Stage at diagnosis, N (%)
I
II
III
IV
13 (46%)
2 (7%)
4 (14%)
9 (32%)
9 (9%)
3 (3%)
9 (9%)
78 (79%)
12 (7%)
12 (7%)
44 (26%)
101 (60%)
Awad et al. J Clin Oncol 2016.
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Pulmonary sarcomatoid carcinoma
• Sarcomatoid carcinoma– Pleomorphic carcinoma
• Giant cells or spindled cells comprise ≥ 10% of tumor
• Admixed adenocarcinoma, squamous, or undifferentiated carcinoma
– Carcinosarcoma• Carcinoma + sarcoma with
heterologous elements
– Pulmonary blastoma• Fetal adenocarcinoma+
mesenchymal stroma
• 2-3% of lung cancers
• Predominantly smokers
MET mutations in pulmonary
pleomorphic/sarcomatoid carcinoma
• Lui et al, JCO 2015:
• MET exon 14 splice
mutations in 8/36 (22%)
of pulmonary
sarcomatoid carcinomas
undergoing WES and
targeted MET analysis
• BWH/DFCI:
• MET exon 14 splice
mutations in 4/15 (27%)
pulmonary pleomorphic
carcinoma sequenced by
NGS
• Other alterations include:
– KRAS (13%)
– NRAS (7%)
– no known driver (53%).
Potential for NGS in diagnosis
• Distinguishing multiple primary lung tumors
from metastases
• Defining site of origin for poorly differentiated
carcinomas
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RUL
RLL
EGFR c.2573T>G (p.L858R), in 2.8% of 285 reads
KRAS c.35G>A (p.G12D), in 15% of 438 reads
MET c.3028+2T>C (p.D1010_splice) - in 34% of 449 reads
74 year old woman, former smoker,
incidental RUL mass and multiple GGOs
Breast vs. Lung?
• 58 year old woman, h/o
well differentiated
T1aN0 invasive ductal
carcinoma (ER+, PR+,
HER2-) 5 years prior
• Now with lung left
upper lobe mass and
diaphragmatic implants Lung tumor: CK7+, TTF1-, GATA3 weak,
ER weak, mammoglobin -
“The carcinoma in the lung is poorly differentiated with high grade nuclei, abundant
cytoplasm, mucin production, and necrosis. The carcinoma does not resemble the
breast carcinoma in the excision from 2010. The possibility that the patient has a
different breast primary carcinoma should be considered.”
Back of the envelope:
Gene Frequency
in breast
Frequency
in Lung
PPV
KRAS
mutation
1% 25% 98%
(for lung)
EGFR
mutation
0 13% 100%
(for lung)
ERBB2
amp
16% 0.5% 91%
(for breast)
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Breast vs. Lung?
KRAS c.34G>T (p.G12C), exon 1
STK11 c.206C>A (p.S69*), exon 1
TP53 c.499_501CAG>G (p.Q167fs), exon 5
KEAP1 c.1016T>C (p.L339P), exon 3
KEAP1 c.382A>T (p.I128F), exon 2
JAK2 c.3214C>T (p.Q1072*), exon 24
BRIP1 c.434C>G (p.S145C), exon 5
CDC73 c.26G>T (p.R9L), exon 1
CHEK2 c.349A>G (p.R117G), exon 3
DMD c.10567G>A (p.E3523K), exon 75
JAK2 c.3214C>T (p.Q1072*), exon 24
SMARCA4 c.2439_splice (p.S813_splice)
TCF3 c.136G>A (p.G46R), exon 3
Dogan et al. Clin Cancer Res, 2012.
Calles et al. Clin Cancer Res, 2015.
Genomic evidence supports a lung primary.
NGS to explore new targets
KRAS
33.8
EGFR
19.1ALK
3.9
BRAF
3.8MET
3.0
PIK3CA
2.9
ERBB2
2.5
NRAS
1.0
ROS1
1.1
RET
1.0
AKT1
0.6
MAP2K1
0.3
HRAS
0.1
No/unknown
driver
29.9
Jamie Wyeth
“Targeted therapy is dead.”
-Anonymous
PD-1/PD-L1 inhibitors
• Applicable across most
tumor types
• 20-30% response rate on
average
• 18 month response
durability
Mutation-targeted inhibitors
• Applicable to few tumors
(lung, melanoma, GIST)
• 50-70% response rate
• Response durability 7-12
months
From a population standpoint, immune checkpoint blockade outperforms
mutation-targeted therapies.
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PD-L1 IHC in practice
nivolumab
pembrolizumab
tremelimumab
atezolizumab
E1L3N
??
Dako 28-8
22C3 pharmDx
Roche SP263
Roche SP142
PD-L1 IHC: mass confusion.
Perhaps other biomarkers will be better…
Characteristics of immune infiltrate?
Expression of other checkpoint inhibitors?
Mutational load?
Mutational signature?
Drug Company FDA approval mAb/Platform Scoring criteria Comment
Pembroluzimab
(Keytruda)
Merck FDA approved for
NSCLC
22C3 (DAKO
pharmDx)/
Link 48 Autostainer
≥50% tumor cells Companion
diagnostic1(as of
Oct 2015)
Nivolumab
(Opdivo)
Bristol- Myers
Squibb
FDA approved for
squamous and non
squamous NSCLC
28-8 (DAKO
pharmDx)/
Link 48 Autostainer
≥1% tumor cells Complementary
diagnostic (as of
Oct 2015)
Predictive only in
non-squamous
carcinomas
Atezolizumab
(MPDL3280)
Roche Expected in 2016 SP142 (Ventana) Tumor cells and/or
tumor infiltrating
immune cells
In development
Durvalumab
(MEDI4736)
Astra Zeneca Expected in 2016 SP263 (Ventana) ≥25% tumor cells In development
Biomarker reporting
• http://www.cap.org/web/home/resources/cancer-
reporting-tools/cancer-protocol-templates
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Biomarker reporting
• Optional reporting template
• Available as CAP electronic cancer checklist (eCC)
• Focused on targets with accepted clinical significance– Alteration type
– Methodology
• Updated version available in 2016 covers:– EGFR
– KRAS
– BRAF
– ERBB2
– ALK
– RET
– ROS1
– MET
Important topics given short shrift:
• Tumor types beyond adenocarcinoma
• Mechanisms and significance of acquired resistance in patients receiving EGFR TKIs, MET/ALK/ROS1 inhibitors
• “Liquid biopsy” in solid tumor clinical management
Sequist et al. Sci Trans Med. 2011
Mechanisms of EGFR TKI resistance
Thanks… Questions?
Acknowledgements:
Mark Awad, DFCI
Phil Cagle
Pasi Janne, DFCI
Neal Lindeman, BWH
Geoff Oxnard, DFCI
Members of the
Pulmonary Pathology
Society