Massively Parallel Sequencing in NSCLC: Comparison to Traditional Hot Spot Analysis for Selection of Approved and Novel Targeted

Therapies

JS Ross, A Parker, M Jarosz, S Downing, R Yelensky, D Lipson, P Stephens, G Palmer,

M Cronin, CE Sheehan

Department of Pathology and Laboratory Medicine

Albany Medical CollegeAlbany, NY

Foundation Medicine, Inc.Cambridge, MA

Background (1)

• Next Generation DNA Sequencing (NGS) has recently been applied to FFPE cancer biopsies and major resections (Ross JS et al. J Clin Oncol 29: 2011)

• Current Hot-Spot Genotyping only detects:– Mutations restricted to specific exons and codons

• NGS detects:– Whole exome mutations in numerous cancer related genes– Insertions and deletions– Translocations and fusions– Copy number alterations (amplifications)

Background (2)• Recently, biomarker testing has emerged as a major driver of

the selection of therapy for non-small cell lung cancer (NSCLC)

• Currently, “hot-spot” DNA sequencing and FISH are used to select therapies for NSCLC:– EGFR genotyping for tyrosine kinase inhibitor (erlotinib)– EML4:ALK translocation testing for crizotinib

• The emergence of comprehensive genomic profiling by NGS has led investigators to question whether more thorough gene sequencing techniques could discover potential targets for the treatment of relapsed and metastatic NSCLC not currently searched for in current routine practice

Targeted Therapies for Cancer

Molecular profiling is driving many new targeted cancer therapeutics

Subset of analyzed targets listed; data from BioCentury Online Intelligence Database

• ~500 compounds hitting ~140 targets in development

• Growing number of newly identified potential targets

Design (1)

• DNA was extracted from 4 x 10 m FFPE sections from 49 primary NSCLC (28 female; 21 male; mean age 68 years; 24% Stage I; 13% Stage II; 5% Stage III; 16% Stage IV; 46% Stage unknown)

• The exons of 145 cancer-related genes were fully sequenced using the Illumina HiSeq 2000 (Illumina, San Diego, CA) and evaluated for point mutations, insertions/deletions (indels), specific genomic rearrangements and copy number alterations (CNA)

• A total of 606,676-bp content was sequenced and selected using solution phase hybridization, to an average coverage of 229×, with 84% of exons being sequenced at ≥100× coverage

• This assay captures and sequences 2,574 coding exons representing 145 cancer-relevant genes (genes that are associated with cancer-related pathways, targeted therapy or prognosis), plus 37 introns from 14 genes that are frequently rearranged in cancer

Design (2)

• To maximize mutation-detection sensitivity in heterogeneous NSCLC biopsies, the test was validated to detect base substitutions at a ≥10% mutant allele frequency with ≥99% sensitivity and to detect indels at a ≥20% mutant allele frequency with ≥95% sensitivity, with a false discovery rate of <1%

• Samples included 5% fluid cell blocks; 5% regional lymph nodes; 3% pericardial biopsy and 87% lung biopsies or resections

• There were 46 adenocarcinomas (34 acinar, 19 lepidic, 2 mucinous, 1 papillary), 1 large cell carcinoma, and 2 squamous cell carcinomas

• Results were compared with commercial laboratory allele-specific PCR genotyping on the same tissue blocks

Cancer Genome Profiling Workflow

<14-21 days

Increasing Coverage To 500x Allows For >99% Sensitivity To Detect Mutant Alleles >5%, With No False Positive Mutation Calls

Sensitivity vs Allele Frequency at 500X Coverage (1Mb panel)

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Allele Frequency

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Allele Frequency

80X 0% Error

80X 0.5% Error

500X 0.5% Error

Deep coverage is required for clinical grade samples

5% 10%

Lower Coverage Misses Relevant Mutations

Mutant Allele frequency spectrum of known mutations found in a series of clinical samples

Fraction of mutations <5%

Fraction of mutations <10%

Fraction of mutations <20%

Fraction of mutations <25%

Fraction of mutations <50%

Fraction of mutations <100%

11% 32% 55% 67% 93% 100%

0-5%6-10%

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16-20%

21-25%

26-30%

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Mutant Allele Frequency

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Genomic Alteration Categories

Highly Actionable“Page 1”

Actionable in Principle“Page 2”

Prognostic“Page 3”

Biologically Significant“Page 4”

Category A: Approved / standard alterations that predict sensitivity or resistance to approved / standard therapiesCategory B: Alterations that are inclusion or exclusion criteria for specific experimental therapies

Category C: Alterations with limited evidence that predict sensitivity or resistance to standard or experimental therapies

Category D: Alterations with prognostic or diagnostic utility

Category E: Alterations with clear biological significance in cancer (i.e. driver mutations) without clear clinical implications

Initial Cohort Results (1)• For EGFR status, the NGS result was concordant with commercial

laboratory genotyping in 23/23 (100%) cases

• In 22/23 (96%) NSCLC samples, NGS revealed 53 total genomic alterations, including :– 14 (64%) base substitutions– 2 (9%) INDELs– 6 (27%) CNA– 0 (0%) rearrangements

• Genomic alterations associated with sensitivity or resistance to targeted therapies for NSCLC were found in 16/22 (73%) of cases including: 10 KRAS 4 STK11 3 JAK2 2 PIK3CA11 BRAF 2 EGFR 1 NF1 1 TSC11 TSC2 1 CCNE1 1 PTCH 1 CDK41 CCND1 1 BRCA2 1 CDKN2A 1 ATM

•

Initial Cohort Results (2)• In comparison with the COSMIC database,

NGS results were similar for most genes except for– a lower rate of EGFR mutations (9% vs. 21%)– a higher rate of KRAS mutations (41% vs. 16%) – an unprecedented rate of JAK2 mutations (14% vs.

0%)• 7/22 (32%) of the NSCLC had 2 or more

potentially actionable alterations after NGS

NSCLC: Actionable Genomic AlterationsKR

AS

TP53

EGFR

STK1

1

LRP1

B

PIK3

CA

CTNN

B1 NF1

MDM

2

JAK2

DNM

T3A

CDKN

2A

ATM

TSC1

CCNE

1

BRAF

SMAR

CA4

SMAD

4

RUNX

1

RB1

PTPR

D

NOTC

H1

MYC

MSH

6

MAP

2K1

MLH

1

MCL

1

GNAS

FGFR

2

CDKN

2B

CDK4

BRCA

1

APC

0%

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60%

Tumor Type

Perc

enta

ge o

f Cas

es w

ith M

utati

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Cetuximab/Panitum resist.

Tubulin

s.

Vemuraf

enib se

ns./Cetu

ximab

resis

t.

CDK inhibito

rs

MEK in

hibitors

(sens.

and re

sist.)

/Vem

urafen

ib resis

t.

Nutlins

MEK/E

RK inhibito

rs

CDK4/6 in

hibitors

mTOR in

hibitors

Dasati

nib

DNMT inhibito

rs

FGFR

inhib

PARP in

hibitors

Gefitinib, E

rlotinib, o

thers

PI3 kinas

e, mTO

R inhibito

rsJA

K2 inhibito

rs

mTOR in

hibitors

Notch in

hibitors

CDK4/6 in

hibitors

PARP in

hib

Genes with Actionable AlterationsGenes with Alterations, Actionability Unknown

Multiple ‘Potentially Actionable Alterations in a Single Sample

NSCLC sample SM92

BRAF c.1397G>T p.G466V

PIK3CA c.1035T>A p.N345K

CDK4 Gene amplification

MDM2 Gene amplification

JAK2 c.1849G>T p.V617F

NSCLC sample SM87

EGFR Gene amplification

MDM2 Gene amplification

NSCLC sample SM51

BRAF c.1397G>C p.G466A

STK11 c. 493G>T p.E165*

KRAS c.34G>T p.G12C

Expanded Cohort Results: Initial Gene Rearrangement Detected

RETKIF5B

ATG

ATG

32,316,377 bps 43,611,118 bps

KIF5B-RETRET-KIF5B

ATG

ATG

Break Break

ATG

Translation

KIF5B (exons 1—15) RET (exons 12—20)

Kinesin Coiled coil Tyrosine kinase

KIF5B-RET

Novel RET:KIF 5B Rearrangement in NSCLC (11.3Mb Pericentric Inversion)

Lipson et al. Nature Med, Feb, 2012

Novel gene fusion joining exons 1-15 of KIF5B to exons 12-20 of RET in lung adenocarcinoma

KIF5B-RET Transformed Cells are sensitive to Multi-Targeted Kinase Inhibitors

• KIF5B-RET expression in Ba/F3 cells led to oncogenic transformation

• Cells were sensitive to sunitinib, sorafenib, and vandetanib

• Not sensitive to gefitinib

• Sunitinib, but not gefitinib inhibited RET phosphorylation

Hypothesis: RET kinase inhibitors should be tested in prospective trials for therapeutic benefit in NSCLC patients with KIF5B-RET rearrangements

Expanded Cohort NSCLC Gene Rearrangements Identified by NGS

• EML4:ALK– In FISH + tumors– In FISH – tumors

• RET:KIF5B

Percentage Of Samples With Actionable Alterations Across Major Tissue Types (224 Total Cases)

N=94 N=76 N=31 N=29 N=24

Colorectal Lung(NSCLC) Prostate Breast Melanoma0%

10%

20%

30%

40%

50%

60%

70%

80%

90%

100%

No Mutations FoundUnknown ActionabilityActionable Mutations

Tumor Type

Perc

ent o

f Cas

es

71% cases carried ≥1 plausibly actionable alterations32 % cases carried ≥2 plausibly actionable alterations

N = 111

INDELs; 13%

Copy Number Al-

terations (CNAs),

28%

Re-arrange-

ments, 3%

Substitu-tions; 28%

Covered by available targeted panels; 29%

Only Detected by NGS

Comparison of NGS with Traditional Hot-Spot Genotyping in NSCLC, CRC, Breast Cancer and Melanoma

Also Detected by Hot-Spot Genotyping

Novel Genomic Alterations* Discovered in NSCLC by NGS in an Expanded Cohort

Total Number of Sequenced NSCLC

Total Number of Novel Alterations

Types of Novel Alterations

249 6 (2%) - Chromosomal Inversions (2)- Chromosomal Rearrangements (2)- Gene Substitutions (2)

* Novel alterations discovered in tumor cell (somatic) sequence only as determined by comparison with the COSMIC database. Gene variants of undetermined significance which may represent germline variants are not included in this list.

NSCLC EGFR Activating Mutation

• Sample: SM58• Mutation: EGFR_c.2573T>G_p.L858R• Freq=32%, depth=53• 79 year old white female non-smoker• FNA of lung mass: NSCLC

• FNA sample cytocentrifuged and converted to an FFPE section• Very small numbers of viable tumor cells• Extensive tumor cell necrosis• Genotyping by allele-specific PCR showed identical activating EGFR mutation

Acquired Resistance to EGFR-TKI

By NGS, the resistance clone was seen in 6% of cells and the

sensitizing mutation in 25%

Sensitivity to gefitinib and erlotinib

Resistance to gefitinib and erlotinib

Nutlins

NSCLC: JAK2 Mutation Detected by NGS

• Sample: SM86• Mutation: JAK2_c.1849G>T_p.V617F• Freq=4%, depth=205• 77 year old white female• Lung adenocarcinoma diagnosed by pleural biopsy• Patient diagnosed with polycythemia vera

Low power of pleural biopsy positive for adenocarcinoma

High power view shows adenocarcinoma of the lung. Rare capillaries not blood filled. No nucleated RBC or blasts seen.

G T A T G T G T C T G T G G A

Val Cys Val Cys Gly

c.1849G>T p.V617F

Multiple CNAs in Adenosquamous Carcinoma• Sample: SM92• Mutation: CDK4 amp (6.6x), MDM2 amp (3.3x)• 77 year-old white male• Left lower lobe• Adenosquamous Carcinoma (composite tumor)• pT2 pN0 pMx

CDK4MDM2

Low power view of lobectomy

specimenHigh power view of tumor with adenocarcinoma glands to the left and squamous carcinoma

to the right

Conclusions• Deep sequencing (NGS) of clinical NSCLC samples is

completely concordant with traditional hot-spot genotyping

• NGS uncovers an unexpected number of genomic alterations that could influence therapy selection for NSCLC

• Broad-based, deep sequencing of cancer-related genes results in sensitive detection of all classes of genomic alterations in NSCLC and can reveal actionable genomic abnormalities that inform treatment decisions