2015년 4월 19일 대한척추통증학회 26차 학술대회에 초청되어 발표한 내용입니다.

1. 성균관대학교 휴먼ICT융합학부
Health-IT Convergence Evangelist
최윤섭, Ph.D.
Knocking on the clinic door of precision medicine
: Recent advances in precision oncology based on NGS

2. “It's in Apple's DNA that technology alone is not enough.
It's technology married with liberal arts.”

3. The Convergence of IT, BT and Medicine

5. Inevitable Tsunami of Change

6. Why Now?

8. 9,223,372,036,854,775,808

9. Moore’s Law
“The number of transistors in a dense integrated circuit
doubles approximately every two years.”
• Microprocessor price
• Memory capacity
• The number of pixels in digital camera

10. Moore’s Law

11. “2006년이 무어의 법칙에 따라 2배씩 증가한,
32번째 되는 해가 된다!
우리는 이미 체스판의 후반부에 접어들었다.”

12. ASCI RED (1997)

14. Playstation 3 (2006)

15. CRAY-2 (1985)

16. 1988.3.7. 매일경제

17. 한국과학기술정보연구원(KISTI)

18. iPad2 (2011)

20. What have been changed?

21. 2003 Human Genome Project 13 years (676 weeks) $2,700,000,000
2007 Dr. CraigVenter’s genome 4 years (208 weeks) $100,000,000
2008 Dr. James Watson’s genome 4 months (16 weeks) $1,000,000
2009 (Nature Biotechnology) 4 weeks $48,000
현재 1-2 weeks ~$5,000

22. 13 years 1 week
(676 weeks)
Over the last decade,

23. $2,700,000,000 ~$5,000
Over the last decade,

24. Ferrari 458 Spider
$398,000 40 cents
http://www.guardian.co.uk/science/2013/jun/08/genome-sequenced

25. The $1000 Genome is Already Here!

26. The $1000 Genome is Already Here!

27. A T G C
DNA = Biological Data = Digital Data

28. GTCCGGGCAGCCCCCGGCGCAGCGCGGCCGCAGCAGCCTCCGCCCCCCGCACGGTGTGAGCGCCCGACGCGGCCGAGGCGGCCGGAGTCCCGAGCTAGCCCCGGC
GGCCGCCGCCGCCCAGACCGGACGACAGGCCACCTCGTCGGCGTCCGCCCGAGTCCCCGCCTCGCCGCCAACGCCACAACCACCGCGCACGGCCCCCTGACTCCG
TCCAGTATTGATCGGGAGAGCCGGAGCGAGCTCTTCGGGGAGCAGCGATGCGACCCTCCGGGACGGCCGGGGCAGCGCTCTGGCGCTGCTGGCTGCGCTCTGCCC
GGCGAGTCGGGCTCTGGAGGAAAAGAAAGGTAAGGGCGTGTCTCGCCGGCTCCCGCGCCGCCCCCGGATCGCGCCCCGGACCCCGCAGCCCGCCCAACCGCGCAC
CGGCGCACCGGCTCGGCGCCCGCGCCCCCGCCCGTCCTTTCCTGTTTCCTTGAGATCAGCTGCGCCGCCGACCGGGACCGCGGGAGGAACGGGACGTTTCGTTCT
TCGGCCGGGAGAGTCTGGGGCGGGCGGAGGAGGAGACGCGTGGGACACCGGGCTGCAGGCCAGGCGGGGAACGGGTCCGGGCAGCCCCCGGCGCAGCGCGGCCGC
AGCAGCCTCCGCCCCCCGCACGGTGTGAGCGCCCGACGCGGCCGAGGCGGCCGGAGTCCCGAGCTAGCCCCGGCGGCCGCCGCCGCCCAGACCGGACGACAGGCC
ACCTCGTCGGCGTCCGCCCGAGTCCCCGCCTCGCCGCCAACGCCACAACCACCGCGCACGGCCCCCTGACTCCGTCCAGTATTGATCGGGAGAGCCGGAGCGAGC
TCTTCGGGGAGCAGCGATGCGACCCTCCGGGACGGCCGGGGCAGCGCTCTGGCGCTGCTGGCTGCGCTCTGCCCGGCGAGTCGGGCTCTGGAGGAAAAGAAAGGT
AAGGGCGTGTCTCGCCGGCTCCCGCGCCGCCCCCGGATCGCGCCCCGGACCCCGCAGCCCGCCCAACCGCGCACCGGCGCACCGGCTCGGCGCCCGCGCCCCCGC
CCGTCCTTTCCTGTTTCCTTGAGATCAGCTGCGCCGCCGACCGGGACCGCGGGAGGAACGGGACGTTTCGTTCTTCGGCCGGGAGAGTCTGGGGCGGGCGGAGGA
GGAGACGCGTGGGACACCGGGCTGCAGGCCAGGCGGGGAACGGGTCCGGGCAGCCCCCGGCGCAGCGCGGCCGCAGCAGCCTCCGCCCCCCGCACGGTGTGAGCG
CCCGACGCGGCCGAGGCGGCCGGAGTCCCGAGCTAGCCCCGGCGGCCGCCGCCGCCCAGACCGGACGACAGGCCACCTCGTCGGCGTCCGCCCGAGTCCCCGCCT
CGCCGCCAACGCCACAACCACCGCGCACGGCCCCCTGACTCCGTCCAGTATTGATCGGGAGAGCCGGAGCGAGCTCTTCGGGGAGCAGCGATGCGACCCTCCGGG
ACGGCCGGGGCAGCGCTCTGGCGCTGCTGGCTGCGCTCTGCCCGGCGAGTCGGGGAAAAGAAAGGTAAGGGCGTGTCTCGCCGGCTCCCGCGCCGCCCCCGGATC
GCGCCCCGGACCCCGCAGCCCGCCCAACCGCGCACCGGCGCACCGGCTCGGCGCCCGCGCCCCCGCCCGTCCTTTCCTGTTTCCTTGAGATCAGCTGCGCCGCCG
ACCGGGACCGCGGGAGGAACGGGACGTTTCGTTCTTCGGCCGGGAGAGTCTGGGGCGGGCGGAGGAGGAGACGCGTGGGACACCGGGCTGCAGGCCAGGCGGGGA
ACGGGTCCGGGCAGCCCCCGGCGCAGCGCGGCCGCAGCAGCCTCCGCCCCCCGCACGGTGTGAGCGCCCGACGCGGCCGAGGCGGCCGGAGTCCCGAGCTAGCCC
CGGCGGCCGCCGCCGCCCAGACCGGACGACAGGCCACCTCGTCGGCGTCCGCCCGAGTCCCCGCCTCGCCGCCAACGCCACAACCACCGCGCACGGCCCCCTGAC
TCCGTCCAGTATTGATCGGGAGAGCCGGAGCGAGCTCTTCGGGGAGCAGCGATGCGACCCTCCGGGACGGCCGGGGCAGCGCTCTGGCGCTGCTGGCTGCGCTCT
GCCCGGCGAGTCGGGCTCTGGAGGAAAAGAAAGGTAAGGGCGTGTCTCGCCGGCTCCCGCGCCGCCCCCGGATCGCGCCCCGGACCCCGCAGCCCGCCCAACCGC
GCACCGGCGCACCGGCTCGGCGCCCGCGCCCCCGCCCGTCCTTTCCTGTTTCCTTGAGATCAGCTGCGCCGCCGACCGGGACCGCGGGAGGAACGGGACGTTTCG
TTCTTCGGCCGGGAGAGTCTGGGGCGGGCGGAGGAGGAGACGCGTGGGACACCGGGCTGCAGGCCAGGCGGGGAACGGGTCCGGGCAGCCCCCGGCGCAGCGCGG
CCGCAGCAGCCTCCGCCCCCCGCACGGTGTGAGCGCCCGACGCGGCCGAGGCGGCCGGAGTCCCGAGCTAGCCCCGGCGGCCGCCGCCGCCCAGACCGGACGACA
GGCCACCTCGTCGGCGTCCGCCCGAGTCCCCGCCTCGCCGCCAACGCCACAACCACCGCGCACGGCCCCCTGACTCCGTCCAGTATTGATCGGGAGAGCCGGAGC
GAGCTCTTCGGGGAGCAGCGATGCGACCCTCCGGGACGGCCGGGGCAGCGCTCTGGCGCTGCTGGCTGCGCTCTGCCCGGCGAGTCGGGCTCTGGAGGAAAAGAA
AGGTAAGGGCGTGTCTCGCCGGCTCCCCCACCGCGCACGGCCCCCTGACTCCGTCCAGTATTGATCGGGAGAGCCGGAGCGAGCTCTTCGGGGAGCAGCGATGCG
ACCCTCCGGGACGGCCGGGGCAGCGCTCTGGCGCTGCTGGCTGCGCTCTGCCCGGCGAGTCGGGCTCTGGAGGAAAAGAAAGGTAAGGGCGTGTCTCGCCGGCTC
CCGCGCCGCCCCCGGATCGCGCCCCGGACCCCGCAGCCCGCCCAACCGCGCACCGGCGCACCGGCTCGGCGCCCGCGCCCCCGCCCGTCCTTTCCTGTTTCCTTG
AGATCAGCTGCGCCGCCGACCGGGACCGCGGGAGGAACGGGACGTTTCGTTCTTCGGCCGGGAGAGTCTGGGGCGGGCGGAGGAGGAGACGCGTGGGACACCGGG
CTGCAGGCCAGGCGGGGAACGGGTCCGGGCAGCCCCCGGCGCAGCGCGGCCGCAGCAGCCTCCGCCCCCCGCACGGTGTGAGCGCCCGACGCGGCCGAGGCGGCC
GGAGTCCCGAGCTAGCCCCGGCGGCCGCCGCCGCCCAGACCGGACGACAGGCCACCTCGTCGGCGTCCGCCCGAGTCCCCGCCTCGCCGCCAACGCCACAACCAC
CGCGCACGGCCCCCTGACTCCGTCCAGTATTGATCGGGAGAGCCGGAGCGAGCTCTTCGGGGAGCAGCGATGCGACCCTCCGGGACGGCCGGGGCAGCGCTCTGG
CGCTGCTGGCTGCGCTCTGCCCGGCGAGTCGGGCTCTGGAGGAAAAGAAAGGTAAGGGCGTGTCTCGCCGGCTCCCCCACCGCGCACGGCCCCCTGACTCCGTCC
AGTATTGATCGGGAGAGCCGGAGCGAGCTCTTCGGGGAGCAGCGATGCGACCCTCCGGGACGGCCGGGGCAGCGCTCTGGCGCTGCTGGCTGCGCTCTGCCCGGC
GAGTCGGGCTCTGGAGGAAAAGAAAGGTAAGGGCGTGTCTCGTCCGGGCAGCCCCCGGCGCAGCGCGGCCGCAGCAGCCTCCGCCCCCCGCACGGTGTGAGCGCC
CGACGCGGCCGAGGCGGCCGGAGTCCCGAGCTAGCCCCGGCGGCCGCCGCCGCCCAGACCGGACGACAGGCCACCTCGTCGGCGTCCGCCCGAGTCCCCGCCTCG
CCGCCAACGCCACAACCACCGCGCACGGCCCCCTGACTCCGTCCAGTATTGATCGGGAGAGCCGGAGCGAGCTCTTCGGGGAGCAGCGATGCGACCCTCCGGGAC
GGCCGGGGCAGCGCTCTGGCGCTGCTGGCTGCGCTCTGCCCGGCGAGTCGGGCTCTGGAGGAAAAGAAAGGTAAGGGCGTGTCTCGCCGGCTCCCGCGCCGCCCC
CGGATCGCGCCCCGGACCCCGCAGCCCGCCCAACCGCGCACCGGCGCACCGGCTCGGCGCCCGCGCCCCCGCCCGTCCTTTCCTGTTTCCTTGAGATCAGCTGCG
CCGCCGACCGGGACCGCGGGAGGAACGGGACGTTTCGTTCTTCGGCCGGGAGAGTCTGGGGCGGGCGGAGGAGGAGACGCGTGGGACACCGGGCTGCAGGCCAGG
CGGGGAACGGGTCCGGGCAGCCCCCGGCGCAGCGCGGCCGCAGCAGCCTCCGCCCCCCGCACGGTGTGAGCGCCCGACGCGGCCGAGGCGGCCGGAGTCCCGAGC
Big Data

29. Human Genome
= 3 billion base pair

30. Precision Medicine
정밀 의료

31. President Obama’s Precision Medicine Initiative
• $215 million investment in the President’s 2016 Budget (January 30, 2015)

32. Depression
Asthma
Diabetes
Arthritis
Alzheimer
Cancer
62%
60%
57%
50%
30%
25%
Source of data: Brian B. Spear, Margo Heath-Chiozzi, Jeffery Huff,
“ClinicalTrends in Molecular Medicine,”Volume 7, Issue 5, 1 May 2001, Pages 201-204.
PERCENTAGE OFTHE PATIENT
POPULATION FOR WHICH
A PARTICULAR DRUG IS EFFECTIVE

33. Tumor Heterogeneity
Meric-Bernstam F, Mills GB. Nat Rev Clin Oncol. 2012 Sep;9(9):542-8.

34. in the understanding of tumour heterogeneity; second,
the role of surgery as a therapeutic modality in the era of
targeted therapy; third, the use of personalized therapy
in the perioperative period and, finally, the possibilities
of personalization of surgical procedures according to
lung cancer subtypes.
VATS lobectomy showed that intraoperative blood loss
was significantly reduced in the VATS group compared
with open lobectomy in nine studies; however, no differ-
ence was observed in five studies and the values were not
reported in seven studies.12
Hospital stay was also signifi-
cantly shorter in VATS group in five studies. Park et al.,13
Heterogeneity in patients
with adenocarcinoma
of the lung according
to driver oncogenes
Heterogeneity within
patients with
EGFR mutation
Heterogeneity in
resistance mechanisms
in one patient
HER2
3%
EGFR
~40% in Asians
~15% in Caucasians
ALK
~5%
KRAS
~15% in Asians
~30% in Caucasians
RET
~1%
ROS1
~1%
BRAF
~1%
PIK3CA
~1%
NRAS
~1%
MET
<5%
Others?
Exon 19del
~50%
L858R
~40%
Sensitive
Inherent resistance
CRKL
~3%
BIM
20–40%
IκB
~30%
Inherent T790M
~2% by sequencing
~30% by sensitive
method
Further
heterogeneity
EGFR-TKI
Drug X
T790M
MET
a cb
T790M
Heterogeneity in patients
with adenocarcinoma
of the lung according
to driver oncogenes
Heterogeneity within
patients with
EGFR mutation
Heterogeneity
resistance mecha
in one patien
HER2
3%
EGFR
~40% in Asians
~15% in Caucasians
ALK
~5%
KRAS
~15% in Asians
~30% in Caucasians
RET
~1%
ROS1
~1%
BRAF
~1%
PIK3CA
~1%
NRAS
~1%
MET
<5%
Others?
Exon 19del
~50%
L858R
~40%
Sensitive
Inherent resistance
CRKL
~3%
BIM
20–40%
IκB
~30%
Inherent T790M
~2% by sequencing
~30% by sensitive
method
Further
heterogeneity
EGFR-TKI
Drug
T790M
ME
a cb
T790M
Figure 1 | Various classes of tumour heterogeneity in adenocarcinoma of the lung. a | Heterogeneity in patients with
adenocarcinoma of the lung according to driver oncogenes that are crucial for selecting targeted drugs for treatment.2,76
Number of people reflects approximate incidence.2,76
b | Heterogeneity in patients with EGFR mutations, resulting in
MitsudomiT, Suda K,YatabeY. Nat Rev Clin Oncol. 2013 Apr;10(4):235-44.
Heterogeneity in Lung Adenocarcinoma

35. Percent
20
15
10
5
0
BRCA
1/2
PIK3CA
am
pPTEN
delA
KT
am
pN
F1
del
KRA
S
CD
KN
2A
del
CCN
D
1
am
p
CCN
E1
am
pRB1
del
Percent
80
60
40
20
0
EG
FR
ERBB2PD
G
FRA
M
ET
N
F1
RA
S
PTEN
PI3KCD
KN
2A
CD
K4/6
RB1
ID
H
1/2
emrofitluMamotsalboilGrecnaCnairavO
KRAS
EGFR
ALK
BRAF
PIK3CA
MET
ERBB2
MEK1
NRAS
ROS
RET
Other?
Lung Adenocarcinoma
EGFR
ERBB2/3
FGFR
PI3K
MAPK
TOR
Other?
Lung Squamous Cancer
ERBB2
PIK3CA
AKT
FGFR1
amp
PTEN
Other?
Breast Cancer
KRAS
PTEN
PIK3CA
KRAS+
PIK3CAERBB2/3
BRAF
NRAS
Other?
Colorectal Cancer
BRAF
NRAS
NF1
KIT
Other?
Melanoma
CDKN2A
CCND1
PTEN
PIK3CA
HRAS
EGFR,
ERBB2
Other?
Head and Neck Squamous Cancer
(PTEN and CDKN2A are
frequently inactivated)
CBA
D
E
HG
F
Levi A. Garraway
Garraway LA. J Clin Oncol. 2013 May 20;31(15):1806-14.
Genomic alterations in common solid tumors.
Expanding catalogs of cancer mutations dispel the notion
that cancer mutations are tissue-specific
Roychowdhury S et al. SciTransl Med. 2011 Nov 30;3(111):111ra121.

36. Although the number of actionable alterations in any individual cancer patient’s sample
was low (average, 1.57), a wide variety of alter- ations was observed across all samples,
with 1,579 unique alterations reported.
Actionable Genomic Alterations Were Identified in a Large Number of Genes
assay, highlighting the broad applicability of the approach.
Given that matched normal specimens are not routinely collected
in clinical practice, reporting focused on known sites of somatic
mutation39, truncations or homozygous deletions of known tumor
suppressor genes40, as well as known amplifications of oncogenes
and gene fusions in genes known to be rearranged in solid tumors.
Alterations were reported in 174/189 (92%) of tested genes, with an
surprising to observe that current clinical testing paradigms compris-
ing only mutation hotspots10,11,43 capture less than one-third of total
actionable results (Fig. 6c).
The therapeutic implications of the long tail were particularly notable
for proven targets of therapy, as exemplified by ERBB2. Although ERBB2
is currently clinically validated only as an amplified or overexpressed
drug target in breast and gastro-esophageal cancer, we observed ERBB2
ab
Head & neck 4%
Soft tissue, 6%
Unknown, 9%
Gene amplification, 33%
Sub/indel, 8%
Gene deletion, 8%
Mutation hotspots,
31%
Lung, 18%
Rearrangement, 3%
Truncation, 17%
Breast, 14%
Colon, 7%Pancreas, 5%
Ovary, 5%
Skin, 3%
Liver, 3%
Uterus, 3%
Others, 26%
Patientsamples(%)
c
40
45
35
30
25
20
15
10
5
0
TP53KR
AS
APCM
C
L1
R
B
1
N
F1
B
R
C
A2
AU
R
KAN
KX2_1
KIT
ESR
1
IG
F1R
R
ET
TSC
2
M
SH
6
ALK
EW
SR
1
PD
G
FR
A
R
U
N
X1
VH
L
FG
FR
2
M
AP2K4
TET2
C
C
N
D
2
M
ET
C
D
K6
N
F2
C
C
N
D
3
FG
FR
3
PIK3R
1
AKT1
B
AP1
R
PTO
R
C
D
H
1
ID
H
1
AKT2
SM
AR
C
A4
SO
X2
KD
M
6A
D
N
M
T3A
N
O
TC
H
1
N
R
AS
LR
P1B
R
IC
TO
R
B
R
C
A1
C
TN
N
B
1
ATM
FB
XW
7
C
C
N
E1
PTPR
D
STK11
SM
AD
4
B
R
AF
C
D
K4
FG
FR
1
ER
B
B
2
M
D
M
2
EG
FR
C
C
N
D
1
AR
ID
1A
PTEN
C
D
KN
2B
PIK3C
AM
YC
C
D
KN
2A
amples(%)
d
30
25
20
15
e Lung (17)
Unknown (2)
Stomach (1)
Pancreas (1)
Ovary (1)
Bladder (1)
Duodenum (1)ERBB2
Furin-Like TM Tyrosine_KinaseFurin-Like
R678Q(4) L755S(4)
D769Y(3)
V842I(4)
Receptor_L Receptor_L
Colon (2)
Uterus (4)
Breast (8)
ollected
somatic
n tumor
cogenes
tumors.
with an
ing only mutation hotspots10,11,43 capture less than one-third of total
actionable results (Fig. 6c).
The therapeutic implications of the long tail were particularly notable
for proven targets of therapy, as exemplified by ERBB2. Although ERBB2
is currently clinically validated only as an amplified or overexpressed
drug target in breast and gastro-esophageal cancer, we observed ERBB2
nknown, 9%
Gene amplification, 33%
Sub/indel, 8%
Gene deletion, 8%
Mutation hotspots,
31%
18%
Rearrangement, 3%
Truncation, 17%
Breast, 14%
%
c
AU
R
KAN
KX2_1
KIT
ESR
1
IG
F1R
R
ET
TSC
2
M
SH
6
ALK
EW
SR
1
PD
G
FR
A
R
U
N
X1
VH
L
FG
FR
2
M
AP2K4
TET2
C
C
N
D
2
M
ET
C
D
K6
N
F2
C
C
N
D
3
FG
FR
3
PIK3R
1
AKT1
B
AP1
R
PTO
R
C
D
H
1
ID
H
1
AKT2
SM
AR
C
A4
SO
X2
KD
M
6A
D
N
M
T3A
N
O
TC
H
1
N
R
AS
LR
P1B
R
IC
TO
R
R
C
A1
1
Lung (17)
Unknown (2)
Stomach (1)
Pancreas (1)
Ovary (1)
Bladder (1)
Duodenum (1)
Furin-Like TM Tyrosine_Kinase
R678Q(4) L755S(4)
D769Y(3)
P780_Y781insGSP(4)
V842I(4)
Receptor_L
Colon (2)
Uterus (4)
Breast (8)
Nat Biotechnol. 2013 Nov;31(11):1023-31.

37. Implementing Personalize Oncology
the case of Foundation Medicine

38. Analyzed cancer genome in 2011
spending $100,000 at Broad Institute

39. • 암환자의 FFPE 시료를 이용, 315 개의 암 관련 ‘actionable gene’ 변이를 한 번에 분석
• 이를 기반으로, 환자의 유전자 변이를 표적으로 하는 치료제 정보를 의사에게 제공
• Broad Institute 에서 spin-off , GoogleVentures와 빌게이츠 투자
• 2012년에 서비스를 시작, 2013년 9월에 나스닥 IPO
• 분석 가격: $5,800
• 2014년 3사 분기: 6,428 회 분석 (149% 성장), 2014년 22,000-25,000 회 분석 예상
http://www.foundationmedicine.com/

40. ©2013NatureAmerica,Inc.Allrig
sensitivity, specificity, accuracy and precision across the reportable
range of the assay, in line with guidelines established by the Next
Generation Sequencing: Standardization of Clinical Testing work-
group25. Relevant sample types were represented, including FFPE.
Base substitutions, indels, focal gene amplifications and homozygous
gene deletions were tested. We report our experience with the first
2,221 patient tumor FFPE specimens submitted to our Clinical
Laboratory Improvement Amendments (CLIA)-certified and College
In contrast to diagnostic assays for a limited number of genomic sites,
analytical validation of an NGS-based genomic profiling test assaying
~1.5 Mb of target sequence is a complex challenge. A single tumor spec-
imen can harbor multiple types of genomic alterations, at any position
in the tested region, at a wide range of mutant allele frequencies (MAF)
or copy number levels. Reference specimens containing all possible
somatic alterations in all cancer-related genes do not exist. We therefore
developed a representative validation approach with reference samples
a b c dFFPE tumor sample
Sequencing library
preparation
Analysis pipeline Clinical report
OR
Genomic DNA
Sequencing library
Biotinylated
DNA baits
Hybridization
capture
DNA
Extraction Sequencing
Base substitutions
Bayesian algorithm
Short insertions/deletions
Local assembly
Copy number alterations
Comparison with process-
matched normal control
Gene fusions
Analysis of chimeric read pairs
Analysis &
interpretation
Sample requirements
Surface area: ≥25 mm2
Sample volume: ≥1 mm3
Nucleated cellularity: ≥80%
or ≥30,000 cells
Tumor content: ≥20%
Fraction of patients with tissue
insufficient for analysis: 10–15%
Laboratory process highlights
Requires ≥50 ng of dsDNA
(quantified by PicoGreen)
Fragmentation by sonication
(Covaris) and ‘with-bead’
library construction
Hybridization capture with
biotinylated DNA
oligonucleotides
49 × 49 paired-end sequencing
on the Illumina HiSeq
platform to >500× average
unique coverage, with >100×
at >99% of exons
Analysis methods highlights
Sensitivity to variants present
at any mutant allele
frequency
Detection of long (1–40 bp)
indel variants using de Bruijn
graph–based local assembly
CGH-like analysis of read-
depth for CNAs assessment
Reporting approach
Interpretation without a
matched normal
Germline variants from 1000
Genomes Project (dbSNP135)
removed
Known driver alterations
(COSMIC v62) highlighted as
biologically significant
A concise summary of the
biomedical literature and
current clinical trials is provided
for each highlighted alteration
Figure 1 NGS-based cancer genomic profiling test workflow. (a) DNA is extracted from routine FFPE biopsy or surgical specimens. (b) 50–200 ng
of DNA undergoes whole-genome shotgun library construction and hybridization-based capture of 4,557 exons of 287 cancer-related genes and 47
introns of 19 genes frequently rearranged in solid tumors. Hybrid-capture libraries are sequenced to high depth using the Illumina HiSeq2000 platform.
(c) Sequence data are processed using a customized analysis pipeline designed to accurately detect multiple classes of genomic alterations: base
substitutions, short insertions/deletions, copy-number alterations and selected gene fusions. (d) Detected mutations are annotated according to clinical
significance and reported.
Nat Biotechnol. 2013 Nov;31(11):1023-31.
NGS-based cancer genomic profiling test workflow

41. 315 cancer related genes
& introns from 28 genes often rearranged or altered in cancer
Current as of
August 4, 2014
th high accuracy. The test simultaneously sequences
anged or altered in cancer to a typical median depth of
ter than 500X. Each covered read represents a unique
tions that occur at low frequencies due to tumor
w tumor purity and small tissue samples. FoundationOne
s of genomic alterations, including base substitutions,
letions (indels), copy number alterations (CNAs) and
using a small, routine FFPE sample (including core or
rovided in an interpretive report, both in hard copy and
4
ation is found in any one of the genes on the current
ort will identify the gene and alteration and will provide an
on the front page of the report are found to have one or
evant alterations. All other genes are not found to have
vant alterations. In some cases, pertinent negatives
the front of the report; these are genes that have no
ancer, EGFR in lung cancer). The complete list of genes
ppears in the “Current Gene List” table to the right, in the
ation is detected in one of the genes included on
in the report so that they may be acted upon in the
clinical evidence emerge.
of the estimated tumor DNA.
One Includes Genes That Are Commonly
n All Solid Tumors
l classes of actionable alterations, including those in
One report often reveals alterations that may lead to
ent options for physicians and their patients to consider.
*As measured from the date the Foundation Medicine laboratory receives a sample that meets requirements.
Current Gene List4
clinical literature.
CURRENT GENE LIST
FANCC GATA3 MITF STAT4
GATA4 JAK3 PDGFRA RET STK11
CIC FANCE GATA6 JUN MPL RICTOR SUFU
AKT1 FANCF
GID4
(C17orf39)
KAT6A
(MYST3)
MRE11A PDK1 RNF43 SYK
CRKL FANCG GLI1 KDM5A ROS1 TAF1
AKT3 FANCL GNA11 KDM5C PIK3CA RPTOR
ALK CSF1R FAS GNA13 KDM6A MTOR RUNX1 TERC
AMER1 C11orf30
(EMSY)
CTCF FAT1 GNAQ KDR PIK3CG RUNX1T1
TERT
(promoter only)
APC CARD11 CTNNA1 GNAS KEAP1 MYC PIK3R1
AR FGF10 KEL
MYCL
(MYCL1)
ARAF CUL3 FGF14 KIT MYCN TNFAIP3
ARFRP1 CCND1 CYLD FGF19 GRM3 TNFRSF14
ARID1A DAXX (MLL) NF1 POLD1 TOP1
CCND3 FGF3
(MLL3)
POLE
CCNE1 DICER1 FGF4 TP53
ASXL1 DNMT3A FGF6 KRAS PRDM1 TSC1
ATM CD79A DOT1L FGFR1 LMO1 SMAD3
ATR EGFR PRKAR1A SMAD4
ATRX CDC73 EP300 FGFR3 LYN PRKCI SMARCA4
AURKA FGFR4 LZTR1 PRKDC VEGFA
NPM1 SMO
AXIN1 CDK4 FLCN IGF1R NRAS SNCAIP
AXL CDK6 FLT1 NSD1 PTEN SOCS1
FLT3 NTRK1 PTPN11 SOX10 XPO1
CDKN1A FLT4 IKZF1 MAP3K1 QKI
IL7R MCL1 NTRK3 RAC1 SOX9
ERG FOXP1 NUP93 RAD50 SPEN ZNF703
ERRFI1 MDM4 PAK3 RAD51 SPOP
ESR1 RAF1 SPTA1
IRF4 SRC
FAM46C GATA1 MEN1 PAX5 RARA
FANCA JAK1 MET STAT3
SELECT REARRANGEMENTS
ALK ETV4 FGFR1 KIT MYC RARA
EGFR ETV5 PDGFRA RET
ETV1 ETV6 FGFR3 NTRK1 RAF1 ROS1
1
and established the performance
-
ndationOne. This updated version of FoundationOne met these performance
-

42. e anatomic
Increasingly,
c alterations,
ns, cancer
pes of
us drivers
equences
an depth of
s a unique
mor
undationOne
stitutions,
Technical Information
Base
Substitutions1 Indels1
Copy Number
Alterations1 Rearrangements
Sensitivity
>99%
MAF 5%
>97%
MAF 10%
>95%
CN 8 or 0
30% tumor nuclei
2
>99% for ALK fusion3
20% tumor nuclei
>99% >99% >99% >99%
(each covered read is of a unique DNA
fragment to enable detection of alterations
at low frequency)
5001
14 day average*
*As measured from the date the Foundation Medicine laboratory receives a sample that meets requirements.
Technical Information
and Test Overview
Current Gene List4
Technical Information of FoundationOne

43. Number of Samples 441
Number of failed samples 4% (16)
Number of samples analyzed 96% (425)
Number of samples analyzed with at
least one actionable alteration
77% (325)
Number of samples analyzed with
at least one actionable alteration not
detectable by hotspot tests1
59% (251)
Number of alterations per analyzed
sample
2.74 (range 0-9)
Number of actionable alterations per
analyzed sample
1.40 (range 0-5)
Actionability for Cancer Samples
• At least one actionable alteration was found from 77% of samples.
• On average,1.4 actionable alterations was found from one sample.

44. Lung Breast Colorectal
Number of
samples
82 70 44
Number of failed
samples
5% (4) 4% (3) 0% (0)
Number of
samples analyzed
95% (78) 86% (67) 100% (44)
Samples with
at least one
actionable
alteration
86% (67) 85% (57) 86% (38)
Alterations per
sample
2.7 (range
0-6)
2.9 (range
0-7)
3.8 (range
1-7)
Actionable
alterations per
sample
1.6 (range
0-5)
1.6 (range
0-4)
1.5 (range
0-3)
Actionability for Lung, Colon, and Breast Cancers was High
The three major tumor subtypes, lung, breast, and colorectal, accounted for 196 out of the 441 samples (44%).
The percentage of samples with at least one actionable alteration was 86%, 85%, and 86% respectively.

45. Patient Name
Lee, Cheol
Report Date
26 February 2013
Diagnosis
Soft tissue
sarcoma (NOS)
Electronically Signed by Jeffrey S. Ross M.D., Medical Director | CLIA Number: 22D2027531 | 26 February 2013
Foundation Medicine, Inc., One Kendall Square Ste B3501, Cambridge MA | 1.888.988.3639 page 1 of 11
Date of Birth 09 August 1948 Client ASAN Medical Center Specimen Received 04 February 2013
Gender Male Ordering Physician Kim, Kyu-pyo Specimen Site Lymph Node
FMI Case # TRF007878 Additional Recipient C. Anthony Blau Date of Collection 04 January 2013
Medical Record # Not Given FMI Client # 200535 Specimen Type Slide
Specimen ID S-13-132 A Pathologist Sejin Jang
ABOUT THE TEST:
FoundationOne™ is a next-generation sequencing (NGS) based assay which identifies genomic alterations within hundreds of cancer-related genes.
PATIENT RESULTS TUMOR TYPE: SOFT TISSUE SARCOMA (NOS)
7 genomic alterations Genomic Alterations Identified†
NF2 W74*
CCND2 amplification
KRAS G13D, amplification
TP53 R282W
FGF23 amplification
FGF6 amplification
3 therapies associated with potential clinical benefit
0 therapies associated with lack of response
6 clinical trials
†
For a complete list of the genes assayed, please refer to the Appendix
THERAPEUTIC IMPLICATIONS
Genomic Alterations
Detected
FDA Approved Therapies
(in patient’s tumor type)
FDA Approved Therapies
(in another tumor type)
Potential Clinical Trials
NF2
W74*
None Everolimus
Lapatinib
Temsirolimus
Yes, see clinical trials
section
CCND2
amplification
None None Yes, see clinical trials
section
KRAS
G13D, amplification
None None Yes, see clinical trials
section
TP53
R282W
None None None
FGF23
amplification
None None None
FGF6
amplification
None None None
Note: Genomic alterations detected may be associated with activity of certain FDA approved drugs; however, the agents listed in this report may have
varied clinical evidence in the patient’s tumor type. Neither the therapeutic agents nor the trials identified are ranked in order of potential or predicted
efficacy for this patient, nor are they ranked in order of level of evidence for this patient’s tumor type.
Patient Name
Lee, Cheol
Report Date
26 February 2013
Diagnosis
Soft tissue
sarcoma (NOS)
Electronically Signed by Jeffrey S. Ross M.D., Medical Director | CLIA Number: 22D2027531 | 26 February 2013
Foundation Medicine, Inc., One Kendall Square Ste B3501, Cambridge MA | 1.888.988.3639 page 2 of 11
GENOMIC ALTERATIONS
GENE
ALTERATION
INTERPRETATION
NF2
W74*
Merlin, encoded by NF2, functions by coordinating signaling of receptor tyrosine kinases (RTKs) such as
the epidermal growth factor receptor (Egfr) with cell contact (Curto and McClatchey, 2008; 17971776).
The inactivation of Merlin in cancer disrupts this mechanism and leads to unrestrained RTK signaling
despite cell contact (Curto and McClatchey, 2008; 17971776). NF2 W74* results in the premature
termination of the 595 amino acid merlin protein, truncating the majority of the protein, and is therefore
predicted to be inactivating. Loss of NF2 has not been reported in a collection of 207 sarcoma samples
reported in the cBio Cancer Genomics Portal (cbioportal.org, Feb 2013). However, loss of heterozygosity
for chromosome 22q (where the NF2 gene resides) has been reported in 6/10 epithelioid sarcomas
(Quezado et al., 1998; 9635681). Additionally, NF2 mutations have been reported in 41% (271/669) of all
soft tissue tumors analyzed in the COSMIC database (COSMIC, Dec 2012). The majority of those
analyzed were schwannoma, which had an NF2 mutation rate of 43% (COSMIC, Dec 2012). At present
there are no approved therapies that directly target NF2 loss. However, preclinical studies in models of
NF2 loss have suggested that the TKI lapatinib and mTOR inhibitors may be a relevant approach
(Ammoun et al., 2010; 20511180, López-Lago et al., 2009; 19451229, James et al., 2009; 19451225).
Lapatinib and the mTOR inhibitors everolimus and temsirolimus have received FDA approval in other
cancer types and are under clinical investigation in solid tumors. Clinical studies of lapatinib in NF2
patients with progressive vestibular schwannoma reported efficacy (Karajannis et al., 2012; 22844108).
CCND2
amplification
CCND2 encodes the protein cyclin D2, which binds and regulates the cyclin-dependent kinases that
control cell cycle progression, and is a downstream target of cancer signaling pathways including
hedgehog and PI-3-kinase (Katoh and Katoh, 2009; 19860666, White et al., 2006; 16301994). CCND2
amplification has been reported in 2.4% of sarcomas (The cBio Cancer Genomics Portal,
http://www.cbioportal.org/, Feb 2013) (Höglund et al., 1996; 8547659). CCND2 alterations have not been
reported in soft tissue sarcomas in the literature (PubMed, Feb 2013). Overexpression of Cyclin D2 has
been reported in several types of sarcomas, including endometrial stromal sarcoma and
rhabdomyosarcoma (Davidson et al., 2013; 23178314, Li et al., 2012; 22330340). Loss of expression of
Cyclin D2 in stage III NSCLC, but not stage II or IV, has been associated with decreased recurrence free
survival (Ko et al., 2012; 22534667). CCND2 expression has been associated with decreased metastasis
in one study of 13 metastatic and 18 non-metastatic neuroendocrine tumors (Lee et al., 2012; 22485171).
There are no approved therapies that specifically target CCND2 amplification; however, several
preclinical studies suggest that cyclin D2 may associate with Cdk4 in cancer cells, and that Cyclin D2-
overexpressing cells may be sensitive to Cdk4/6 inhibitors (Decker et al., 2002; 11896535, Cole et al.,
2010; 20736363). Clinical trials of Cdk4/6 inhibitors are currently underway in multiple tumor types.
KRAS
G13D,
amplification
The KRAS gene is one of the most commonly mutated genes in human malignancies (Farber et al., 2011;
22016105, Feldmann et al., 2007; 17520196, Han et al., 2011; 22011285). Activating mutations in RAS
genes can cause uncontrolled cell proliferation and tumor formation (Pylayeva-Gupta et al., 2011;
21993244, Kahn et al., 1987; 3310850). The G13D mutation lies within the first "G box" domain of the
KRAS protein, one of several conserved regions (Colicelli, 2004; 15367757). Disruption of this region
creates a protein that is defective for GTP hydrolysis and therefore constitutively active. KRAS alterations
have been reported variously from 0-44% in soft tissue sarcoma (COSMIC, The cBio Cancer Genomics
Portal, http://www.cbioportal.org, Feb 2013), perhaps dependent on country of origin (Yoo et al., 1999;
10463479, Yoo and Robinson, 1999; 10391564, Barretina et al., 2010; 20601955, Jin et al., 2010;
20150643). KRAS amplification has been reported in 4/207 (2%) soft tissue sarcomas in the Sarcoma
Genome Project dataset (The cBio Cancer Genomics Portal, http://www.cbioportal.org, Feb 2013).
Constitutive activation of KRAS leads to activation of the RAF/MEK/ERK pathway, leading to
tumorigenesis (Pylayeva-Gupta et al., 2011; 21993244). Therefore, tumors with activating mutations in
KRAS may be sensitive to inhibitors of this pathway. Both the KRAS-targeting reovirus Reolysin and
specific MEK inhibitors are under investigation for tumors bearing KRAS mutations. Activating mutations
in KRAS have been associated with resistance to Egfr inhibitors in colorectal carcinoma; however, this
relationship has not been a significant subject of study in soft tissue sarcoma (Lièvre et al., 2006;
16618717, De Roock et al., 2011; 21163703).
Patient Name
Lee, Cheol
Report Date
26 February 2013
Diagnosis
Soft tissue
sarcoma (NOS)
Electronically Signed by Jeffrey S. Ross M.D., Medical Director | CLIA Number: 22D2027531 | 26 February 2013
Foundation Medicine, Inc., One Kendall Square Ste B3501, Cambridge MA | 1.888.988.3639 page 4 of 11
THERAPIES
There are no therapies FDA approved in this patient's tumor type that are specific to the reported genomic alterations.
ADDITIONAL THERAPIES – FDA APPROVED IN OTHER TUMOR TYPES
THERAPY RATIONALE
Everolimus
Everolimus is an orally available mTOR inhibitor that has been approved for use in renal cell carcinoma,
pancreatic neuroendocrine tumors, subependymal giant cell astrocytoma associated with TSC, and
hormone receptor positive, HER2 negative advanced breast cancer. Preclinical data suggests that NF2
loss may be associated with sensitivity to rapamycin, which is similar in mechanism of action to
everolimus (Lopez-Lago et al., 2009; 19451229, James et al., 2009; 19451225). Everolimus is currently
being tested in clinical trials in several tumor types. A Phase 1 trial of everolimus and figitumumab, an
IGF-1R inhibitor, in sarcomas and other solid tumors showed that the combination was safe and well-
tolerated, with a partial response in 1/18 patients and stable disease in 15/18 patients (Quek et al., 2011;
21177764).
Lapatinib
Lapatinib is a dual tyrosine kinase inhibitor, targeting both Egfr and Her2 (Erbb2). It has been approved
for use in metastatic breast cancer. Mutation of NF2 may lead to Egfr and/or Erbb2 activation; lapatinib
inhibits Egfr and Erbb2 and has shown preclinical activity in NF2 deficient vestibular schwannoma
(Ammoun et al., 2010; 20511180). Lapatinib is currently in clinical trials in multiple solid tumor types.
Temsirolimus
Temsirolimus is an intravenous mTOR inhibitor that has been approved for use in advanced renal cell
carcinoma. Preclinical data suggests that NF2 loss may be associated with sensitivity to rapamycin,
which is similar in mechanism of action to temsirolimus (Lopez-Lago et al., 2009; 19451229, James et al.,
2009; 19451225). Temsirolimus is currently being tested in clinical trials in several tumor types. A Phase
2 trial of temsirolimus as single agent in soft tissue sarcoma reported limited efficacy and moderate
toxicity, with a partial response exhibited in 2 of 40 evaluable patients (Okuno et al., 2011; 21287536). A
Phase 1 trial of temsirolimus combined with liposomal doxorubicin in recurrent and refractory bone and
soft tissue sarcoma patients reported that the combination treatment is safe and demonstrates sufficient
preliminary efficacy to pursue the Phase 2 portion of the study (Thornton et al., 2013; 23382028).
Genomic alterations detected may be associated with activity of certain FDA approved drugs, however the agents listed in this report may have little or
no evidence in the patient’s tumor type
Patient Name
Lee, Cheol
Report Date
26 February 2013
Diagnosis
Soft tissue
sarcoma (NOS)
Electronically Signed by Jeffrey S. Ross M.D., Medical Director | CLIA Number: 22D2027531 | 26 February 2013
Foundation Medicine, Inc., One Kendall Square Ste B3501, Cambridge MA | 1.888.988.3639 page 5 of 11
CLINICAL TRIALS TO CONSIDER
IMPORTANT: While every effort is made to ensure the accuracy of the information contained below, the information available in the
public domain is continuously updated and should be investigated by the physician or research staff. This is not meant to be a
complete list of available trials. In order to conduct a more thorough search, please go to www.clinicaltrials.gov and use the search
terms provided below. For more information about a specific clinical trial, type the NCT ID of the trial indicated below into the search
bar.
GENE RATIONALE FOR POTENTIAL CLINICAL TRIALS
NF2
W74*
Mutation or loss of NF2 results in the dysregulation of RTK and mTOR signaling. Therefore, RTK or mTOR
inhibitors may be relevant for patients with NF2 mutations.
A search of the trial website clinicaltrials.gov, using terms such as “NF2”, "lapatinib", "mTOR" and/or "solid
tumor" retrieves more than 10 trials that may be relevant for this patient's tumor.
Examples of these trials are shown below.
TITLE PHASE TARGETS LOCATIONS NCT ID
An Open-label, Multi-center Phase I Dose-
finding Study of RAD001 (Everolimus, Afinitor®)
in Combination With BEZ235 in Patients With
Advanced Solid Tumors
Phase 1 MTOR, PI3K Missouri, Auckland (New
Zealand), Barcelona (Spain),
Bordeaux Cedex (France),
Montpellier Cedex 5 (France),
Newcastle Upon Tyne (United
Kingdom), Seoul (Korea,
Republic of), Verona (Italy),
Wilrijk (Belgium)
NCT01482156
A Phase I Study of the HER1, HER2 Dual
Kinase Inhibitor, Lapatinib Plus the
Proteosomal Inhibitor Bortezomib in Patients
With Advanced Malignancies
Phase 1 EGFR,
Her2/neu,
proteasome
District of Columbia NCT01497626

46. Patient Name
Lee, Cheol
Report Date
26 February 2013
Diagnosis
Soft tissue
sarcoma (NOS)
Electronically Signed by Jeffrey S. Ross M.D., Medical Director | CLIA Number: 22D2027531 | 26 February 2013
Foundation Medicine, Inc., One Kendall Square Ste B3501, Cambridge MA | 1.888.988.3639 page 1 of 11
Date of Birth 09 August 1948 Client ASAN Medical Center Specimen Received 04 February 2013
Gender Male Ordering Physician Kim, Kyu-pyo Specimen Site Lymph Node
FMI Case # TRF007878 Additional Recipient C. Anthony Blau Date of Collection 04 January 2013
Medical Record # Not Given FMI Client # 200535 Specimen Type Slide
Specimen ID S-13-132 A Pathologist Sejin Jang
ABOUT THE TEST:
FoundationOne™ is a next-generation sequencing (NGS) based assay which identifies genomic alterations within hundreds of cancer-related genes.
PATIENT RESULTS TUMOR TYPE: SOFT TISSUE SARCOMA (NOS)
7 genomic alterations Genomic Alterations Identified†
NF2 W74*
CCND2 amplification
KRAS G13D, amplification
TP53 R282W
FGF23 amplification
FGF6 amplification
3 therapies associated with potential clinical benefit
0 therapies associated with lack of response
6 clinical trials
†
For a complete list of the genes assayed, please refer to the Appendix
THERAPEUTIC IMPLICATIONS
Genomic Alterations
Detected
FDA Approved Therapies
(in patient’s tumor type)
FDA Approved Therapies
(in another tumor type)
Potential Clinical Trials
NF2
W74*
None Everolimus
Lapatinib
Temsirolimus
Yes, see clinical trials
section
CCND2
amplification
None None Yes, see clinical trials
section
KRAS
G13D, amplification
None None Yes, see clinical trials
section
TP53
R282W
None None None
FGF23
amplification
None None None
FGF6
amplification
None None None
Note: Genomic alterations detected may be associated with activity of certain FDA approved drugs; however, the agents listed in this report may have
varied clinical evidence in the patient’s tumor type. Neither the therapeutic agents nor the trials identified are ranked in order of potential or predicted
efficacy for this patient, nor are they ranked in order of level of evidence for this patient’s tumor type.

47. Patient Name
Lee, Cheol
Report Date
26 February 2013
Diagnosis
Soft tissue
sarcoma (NOS)
Electronically Signed by Jeffrey S. Ross M.D., Medical Director | CLIA Number: 22D2027531 | 26 February 2013
Foundation Medicine, Inc., One Kendall Square Ste B3501, Cambridge MA | 1.888.988.3639 page 2 of 11
GENOMIC ALTERATIONS
GENE
ALTERATION
INTERPRETATION
NF2
W74*
Merlin, encoded by NF2, functions by coordinating signaling of receptor tyrosine kinases (RTKs) such as
the epidermal growth factor receptor (Egfr) with cell contact (Curto and McClatchey, 2008; 17971776).
The inactivation of Merlin in cancer disrupts this mechanism and leads to unrestrained RTK signaling
despite cell contact (Curto and McClatchey, 2008; 17971776). NF2 W74* results in the premature
termination of the 595 amino acid merlin protein, truncating the majority of the protein, and is therefore
predicted to be inactivating. Loss of NF2 has not been reported in a collection of 207 sarcoma samples
reported in the cBio Cancer Genomics Portal (cbioportal.org, Feb 2013). However, loss of heterozygosity
for chromosome 22q (where the NF2 gene resides) has been reported in 6/10 epithelioid sarcomas
(Quezado et al., 1998; 9635681). Additionally, NF2 mutations have been reported in 41% (271/669) of all
soft tissue tumors analyzed in the COSMIC database (COSMIC, Dec 2012). The majority of those
analyzed were schwannoma, which had an NF2 mutation rate of 43% (COSMIC, Dec 2012). At present
there are no approved therapies that directly target NF2 loss. However, preclinical studies in models of
NF2 loss have suggested that the TKI lapatinib and mTOR inhibitors may be a relevant approach
(Ammoun et al., 2010; 20511180, López-Lago et al., 2009; 19451229, James et al., 2009; 19451225).
Lapatinib and the mTOR inhibitors everolimus and temsirolimus have received FDA approval in other
cancer types and are under clinical investigation in solid tumors. Clinical studies of lapatinib in NF2
patients with progressive vestibular schwannoma reported efficacy (Karajannis et al., 2012; 22844108).
CCND2
amplification
CCND2 encodes the protein cyclin D2, which binds and regulates the cyclin-dependent kinases that
control cell cycle progression, and is a downstream target of cancer signaling pathways including
hedgehog and PI-3-kinase (Katoh and Katoh, 2009; 19860666, White et al., 2006; 16301994). CCND2
amplification has been reported in 2.4% of sarcomas (The cBio Cancer Genomics Portal,
http://www.cbioportal.org/, Feb 2013) (Höglund et al., 1996; 8547659). CCND2 alterations have not been
reported in soft tissue sarcomas in the literature (PubMed, Feb 2013). Overexpression of Cyclin D2 has
been reported in several types of sarcomas, including endometrial stromal sarcoma and
rhabdomyosarcoma (Davidson et al., 2013; 23178314, Li et al., 2012; 22330340). Loss of expression of
Cyclin D2 in stage III NSCLC, but not stage II or IV, has been associated with decreased recurrence free
survival (Ko et al., 2012; 22534667). CCND2 expression has been associated with decreased metastasis
in one study of 13 metastatic and 18 non-metastatic neuroendocrine tumors (Lee et al., 2012; 22485171).
There are no approved therapies that specifically target CCND2 amplification; however, several
preclinical studies suggest that cyclin D2 may associate with Cdk4 in cancer cells, and that Cyclin D2-
overexpressing cells may be sensitive to Cdk4/6 inhibitors (Decker et al., 2002; 11896535, Cole et al.,
2010; 20736363). Clinical trials of Cdk4/6 inhibitors are currently underway in multiple tumor types.
KRAS
G13D,
amplification
The KRAS gene is one of the most commonly mutated genes in human malignancies (Farber et al., 2011;
22016105, Feldmann et al., 2007; 17520196, Han et al., 2011; 22011285). Activating mutations in RAS
genes can cause uncontrolled cell proliferation and tumor formation (Pylayeva-Gupta et al., 2011;
21993244, Kahn et al., 1987; 3310850). The G13D mutation lies within the first "G box" domain of the
KRAS protein, one of several conserved regions (Colicelli, 2004; 15367757). Disruption of this region
creates a protein that is defective for GTP hydrolysis and therefore constitutively active. KRAS alterations
have been reported variously from 0-44% in soft tissue sarcoma (COSMIC, The cBio Cancer Genomics
Portal, http://www.cbioportal.org, Feb 2013), perhaps dependent on country of origin (Yoo et al., 1999;
10463479, Yoo and Robinson, 1999; 10391564, Barretina et al., 2010; 20601955, Jin et al., 2010;
20150643). KRAS amplification has been reported in 4/207 (2%) soft tissue sarcomas in the Sarcoma
Genome Project dataset (The cBio Cancer Genomics Portal, http://www.cbioportal.org, Feb 2013).
Constitutive activation of KRAS leads to activation of the RAF/MEK/ERK pathway, leading to
tumorigenesis (Pylayeva-Gupta et al., 2011; 21993244). Therefore, tumors with activating mutations in
KRAS may be sensitive to inhibitors of this pathway. Both the KRAS-targeting reovirus Reolysin and
specific MEK inhibitors are under investigation for tumors bearing KRAS mutations. Activating mutations
in KRAS have been associated with resistance to Egfr inhibitors in colorectal carcinoma; however, this
relationship has not been a significant subject of study in soft tissue sarcoma (Lièvre et al., 2006;
16618717, De Roock et al., 2011; 21163703).

48. Patient Name
Lee, Cheol
Report Date
26 February 2013
Diagnosis
Soft tissue
sarcoma (NOS)
GENOMIC ALTERATIONS
GENE
ALTERATION
INTERPRETATION
NF2
W74*
Merlin, encoded by NF2, functions by coordinating signaling of receptor tyrosine kinases (RTKs) such as
the epidermal growth factor receptor (Egfr) with cell contact (Curto and McClatchey, 2008; 17971776).
The inactivation of Merlin in cancer disrupts this mechanism and leads to unrestrained RTK signaling
despite cell contact (Curto and McClatchey, 2008; 17971776). NF2 W74* results in the premature
termination of the 595 amino acid merlin protein, truncating the majority of the protein, and is therefore
predicted to be inactivating. Loss of NF2 has not been reported in a collection of 207 sarcoma samples
reported in the cBio Cancer Genomics Portal (cbioportal.org, Feb 2013). However, loss of heterozygosity
for chromosome 22q (where the NF2 gene resides) has been reported in 6/10 epithelioid sarcomas
(Quezado et al., 1998; 9635681). Additionally, NF2 mutations have been reported in 41% (271/669) of all
soft tissue tumors analyzed in the COSMIC database (COSMIC, Dec 2012). The majority of those
analyzed were schwannoma, which had an NF2 mutation rate of 43% (COSMIC, Dec 2012). At present
there are no approved therapies that directly target NF2 loss. However, preclinical studies in models of
NF2 loss have suggested that the TKI lapatinib and mTOR inhibitors may be a relevant approach
(Ammoun et al., 2010; 20511180, López-Lago et al., 2009; 19451229, James et al., 2009; 19451225).
Lapatinib and the mTOR inhibitors everolimus and temsirolimus have received FDA approval in other
cancer types and are under clinical investigation in solid tumors. Clinical studies of lapatinib in NF2
patients with progressive vestibular schwannoma reported efficacy (Karajannis et al., 2012; 22844108).
CCND2
amplification
CCND2 encodes the protein cyclin D2, which binds and regulates the cyclin-dependent kinases that
control cell cycle progression, and is a downstream target of cancer signaling pathways including
hedgehog and PI-3-kinase (Katoh and Katoh, 2009; 19860666, White et al., 2006; 16301994). CCND2
amplification has been reported in 2.4% of sarcomas (The cBio Cancer Genomics Portal,
http://www.cbioportal.org/, Feb 2013) (Höglund et al., 1996; 8547659). CCND2 alterations have not been
reported in soft tissue sarcomas in the literature (PubMed, Feb 2013). Overexpression of Cyclin D2 has
been reported in several types of sarcomas, including endometrial stromal sarcoma and
rhabdomyosarcoma (Davidson et al., 2013; 23178314, Li et al., 2012; 22330340). Loss of expression of
Cyclin D2 in stage III NSCLC, but not stage II or IV, has been associated with decreased recurrence free
survival (Ko et al., 2012; 22534667). CCND2 expression has been associated with decreased metastasis
in one study of 13 metastatic and 18 non-metastatic neuroendocrine tumors (Lee et al., 2012; 22485171).
There are no approved therapies that specifically target CCND2 amplification; however, several
preclinical studies suggest that cyclin D2 may associate with Cdk4 in cancer cells, and that Cyclin D2-
overexpressing cells may be sensitive to Cdk4/6 inhibitors (Decker et al., 2002; 11896535, Cole et al.,
2010; 20736363). Clinical trials of Cdk4/6 inhibitors are currently underway in multiple tumor types.
The KRAS gene is one of the most commonly mutated genes in human malignancies (Farber et al., 2011;
• 유전자(단백질)의 기능 및 암 발병에서 메커니즘 소개
• NF2 유전자에서 나오는 Merlin은 EGFR과 같은 RTKs를 조절하는 기능을 가짐
• Merlin의 비활성화는 이런 메커니즘을 망가뜨려, RTKs 신호를 조절하지 못하게 됨
• 유전 변이가 단백질/메커니즘에 어떠한 영향을 미치는지 설명
• NF2 의 W74*는 Merlin의 premature termination을 통해 단백질의 비활성화를 야기함
• 유전 변이가 해당 암종에 대해 DB/논문에 어떻게 보고 되어 있는지 설명
• cBio Cancer Genomics Portal: 207개의 sarcoma 샘플에는 NF2 loss 데이터는 없음
• Quezado et al.: Epithelial sarcoma 에서 NF2가 위치한 염색체의 loss of heterozygosity 가 보고된 바 있음
• COSMIC: NF2의 변이(W74* ?)가 41%의 soft tissue tumor 에서 보고된 바 있으며, 샘플의 대부분은 schwannoma
• 유전 변이에 효과가 있는 약물 (승인/임상)에 대한 간략한 소개
• NF2 loss 변이를 직접 표적으로 하는 승인 받은 약은 없음
• 전임상 결과에 따르면 TKI lapatinib과 mTOR 저해제가 효과 있을 수도 있음
• Lapatinib과 mTOR 저해제는 다른 암종에 대해서 승인 받았으며, solid tumor에 대하여 임상 중임
• Lapatinib은 NF2 변이 vestibular schwannoma 환자에 대한 임상에서 효능을 보임

49. Patient Name
Lee, Cheol
Report Date
26 February 2013
Diagnosis
Soft tissue
sarcoma (NOS)
Electronically Signed by Jeffrey S. Ross M.D., Medical Director | CLIA Number: 22D2027531 | 26 February 2013
Foundation Medicine, Inc., One Kendall Square Ste B3501, Cambridge MA | 1.888.988.3639 page 4 of 11
THERAPIES
There are no therapies FDA approved in this patient's tumor type that are specific to the reported genomic alterations.
ADDITIONAL THERAPIES – FDA APPROVED IN OTHER TUMOR TYPES
THERAPY RATIONALE
Everolimus
Everolimus is an orally available mTOR inhibitor that has been approved for use in renal cell carcinoma,
pancreatic neuroendocrine tumors, subependymal giant cell astrocytoma associated with TSC, and
hormone receptor positive, HER2 negative advanced breast cancer. Preclinical data suggests that NF2
loss may be associated with sensitivity to rapamycin, which is similar in mechanism of action to
everolimus (Lopez-Lago et al., 2009; 19451229, James et al., 2009; 19451225). Everolimus is currently
being tested in clinical trials in several tumor types. A Phase 1 trial of everolimus and figitumumab, an
IGF-1R inhibitor, in sarcomas and other solid tumors showed that the combination was safe and well-
tolerated, with a partial response in 1/18 patients and stable disease in 15/18 patients (Quek et al., 2011;
21177764).
Lapatinib
Lapatinib is a dual tyrosine kinase inhibitor, targeting both Egfr and Her2 (Erbb2). It has been approved
for use in metastatic breast cancer. Mutation of NF2 may lead to Egfr and/or Erbb2 activation; lapatinib
inhibits Egfr and Erbb2 and has shown preclinical activity in NF2 deficient vestibular schwannoma
(Ammoun et al., 2010; 20511180). Lapatinib is currently in clinical trials in multiple solid tumor types.
Temsirolimus
Temsirolimus is an intravenous mTOR inhibitor that has been approved for use in advanced renal cell
carcinoma. Preclinical data suggests that NF2 loss may be associated with sensitivity to rapamycin,
which is similar in mechanism of action to temsirolimus (Lopez-Lago et al., 2009; 19451229, James et al.,
2009; 19451225). Temsirolimus is currently being tested in clinical trials in several tumor types. A Phase
2 trial of temsirolimus as single agent in soft tissue sarcoma reported limited efficacy and moderate
toxicity, with a partial response exhibited in 2 of 40 evaluable patients (Okuno et al., 2011; 21287536). A
Phase 1 trial of temsirolimus combined with liposomal doxorubicin in recurrent and refractory bone and
soft tissue sarcoma patients reported that the combination treatment is safe and demonstrates sufficient
preliminary efficacy to pursue the Phase 2 portion of the study (Thornton et al., 2013; 23382028).
Genomic alterations detected may be associated with activity of certain FDA approved drugs, however the agents listed in this report may have little or
no evidence in the patient’s tumor type

50. • 약의 유형 및 표적 소개
• Erlotinib 은 저분자 화합물 (small molecule) 약으로
• EGFR의 타이로신 활성효소 억제제 (tyrosine kinase inhibitor)임
• 약의 FDA 승인 적응증
• NSCLC (비세포성 폐암) 및 췌장암에 승인 되었음
• 해당 유전 변이에 대한 약의 효과 설명
• EGFR 활성화 유전변이가 있는 환자들에게서, erlotinib 의 투여는 암의 진행 속도를 늦추는 효과를 나타냄 (ref)
• (폐암에 대한) 약의 임상 시험 과정 및 결과
• NSCLC에 대한 erlotinib의 승인은 무작위 임상 3상에서 표준항암치료에 비해 생존기간(OS)의 연장에 근거하였음 (ref)
• 몇번의 무작위 임상 3상에서 EGFR 양성 환자들에 대하여, 무진행 생존률(PFS)이 표준치료에 비해 유의미하게 연장됨 (ref)
• 해당 유전 변이의 약에 대한 저항성 설명
• 다른 EGFR 활성화 변이와는 달리, 어떤 exon 20 변이는 (전)임상 시험에서 EGFR 타이로신 활성효소 억제제에 대한 저항성을 보였다.
• Exon 20 insertion 변이의 경우 어떤 환자들에게서는 EGFR 저해제를 투여했을 경우 질병이 더 진행되지 않았다.

51. • (폐암에 대한) 약의 임상 시험 과정 및 결과
• 처음 임상시험에서는 무작위 NSCLC 환자에 대하여 위약 대비 생존율에 대한 유의미한 효과를 보이지 못하여, 임상 실패
• 하지만, 추우에 EGFR 변이 환자들에게 항암요법과 병용투여하였을 경우 생존율에 유의미한 차이를 보인 결과 (승인 받음)

52. Patient Name
Lee, Cheol
Report Date
26 February 2013
Diagnosis
Soft tissue
sarcoma (NOS)
Electronically Signed by Jeffrey S. Ross M.D., Medical Director | CLIA Number: 22D2027531 | 26 February 2013
Foundation Medicine, Inc., One Kendall Square Ste B3501, Cambridge MA | 1.888.988.3639 page 5 of 11
CLINICAL TRIALS TO CONSIDER
IMPORTANT: While every effort is made to ensure the accuracy of the information contained below, the information available in the
public domain is continuously updated and should be investigated by the physician or research staff. This is not meant to be a
complete list of available trials. In order to conduct a more thorough search, please go to www.clinicaltrials.gov and use the search
terms provided below. For more information about a specific clinical trial, type the NCT ID of the trial indicated below into the search
bar.
GENE RATIONALE FOR POTENTIAL CLINICAL TRIALS
NF2
W74*
Mutation or loss of NF2 results in the dysregulation of RTK and mTOR signaling. Therefore, RTK or mTOR
inhibitors may be relevant for patients with NF2 mutations.
A search of the trial website clinicaltrials.gov, using terms such as “NF2”, "lapatinib", "mTOR" and/or "solid
tumor" retrieves more than 10 trials that may be relevant for this patient's tumor.
Examples of these trials are shown below.
TITLE PHASE TARGETS LOCATIONS NCT ID
An Open-label, Multi-center Phase I Dose-
finding Study of RAD001 (Everolimus, Afinitor®)
in Combination With BEZ235 in Patients With
Advanced Solid Tumors
Phase 1 MTOR, PI3K Missouri, Auckland (New
Zealand), Barcelona (Spain),
Bordeaux Cedex (France),
Montpellier Cedex 5 (France),
Newcastle Upon Tyne (United
Kingdom), Seoul (Korea,
Republic of), Verona (Italy),
Wilrijk (Belgium)
NCT01482156
A Phase I Study of the HER1, HER2 Dual
Kinase Inhibitor, Lapatinib Plus the
Proteosomal Inhibitor Bortezomib in Patients
With Advanced Malignancies
Phase 1 EGFR,
Her2/neu,
proteasome
District of Columbia NCT01497626

53. Patient Name
Lee, Cheol
Report Date
26 February 2013
Diagnosis
Soft tissue
sarcoma (NOS)
CLINICAL TRIALS TO CONSIDER (CONT.)
GENE RATIONALE FOR POTENTIAL CLINICAL TRIALS
KRAS
G13D, amplification
Activating mutations in KRAS may result in activation of downstream pathways, including the MAPK
pathway. Therefore, inhibitors of MAPK pathway components, including the protein MEK, may be of use in a
tumor with a KRAS activating mutation. Additionally, the engineered reovirus Reolysin is under investigation
in clinical trials for its ability to specifically target cells bearing activated KRAS.
A search of the trial website clinicaltrials.gov, using terms such as "KRAS", "MEK", "sarcoma", and/or "solid
tumor", retrieves more than 10 trials that may be relevant for this patient’s tumor.
Examples of these trials are shown below.
TITLE PHASE TARGETS LOCATIONS NCT ID
A Phase Ib, Open-Label, Dose-Escalation
Study Evaluating the Safety, Tolerability and
Pharmacokinetics of GDC-0973 in Combination
With GDC-0941 When Administered in Patients
With Locally Advanced or Metastatic Solid
Tumors
Phase 1 MEK, PI3K Massachusetts, Michigan,
Tennessee
NCT00996892
A Phase Ib, Open-label, Multi-center, Dose-
escalation and Expansion Study of an Orally
Administered Combination of BEZ235 Plus
MEK162 in Adult Patients With Selected
Advanced Solid Tumors
Phase 1 MEK, MTOR,
PI3K
Massachusetts, Texas,
Wisconsin, Ontario (Canada),
Barcelona (Spain), Cologne
(Germany), Essen (Germany),
Victoria (Australia), Villejuif
(France)
NCT01337765
• 이 임상시험들이 권장되는 이유
• KRAS의 활성화 변이는 MAPK pathway 등의 downstream pathway를 활성화시킨다.
• 그러므로 MEK를 포함한 MAPK pathway 의 구성요소들을 저해하는 약은 KRAS 활성화 변이에 대해 사용될 수 있다.
• 또한, 임상시험 중인 reovirus Reolysin 은 활성화된 KRAS 를 가지고 있는 세포만을 저해하는 기능으로 연구되고 있다.
• Clinialtrial.gov 에는 KRAS, MEK, sarcoma, solid tumor 등으로 10개가 넘는 임상시험을 찾을 수 있다.

54. Promising Cases of
Personalized Cancer Medicine

55. • He developed Acute Lymphoblastic Leukemia, which he studied himself.
• Recurred, 5 years after the bone-marrow transplant
• Whole genome sequencing +Transcriptome analysis
• Overexpression of FLT3 was found (FLT3: cell growth, proliferation)
• Sutent (sunitinib), which was approved for Kidney cancer, inhibits FLT3
• ALL was successfully treated by Sutent, the Kidney cancer drug.
Dr. Lukas Wartman
http://www.nytimes.com/2012/07/08/health/in-gene-sequencing-treatment-for-leukemia-glimpses-of-the-future.html?pagewanted=all&_r=0

56. ‹›
• June, 2010: 53 y.o. female diagnosed with metastatic
inflammatory breast cancer (IBC) involving liver and bone
• Initial therapies: docetaxel, carboplatin and trastuzumab –
achieved some improvement
• Disease progression within 12 months
• April - November, 2011: Numerous additional drug
regimens attempted
• November, 2011: Rapid progression of disease
24
Case Presentation 2: FMI vs ‘Limited’ Testing
Foundation Medicine,“Next Generation Sequencing in the Clinic - The First 2200+ Cases Lessons Learned”

57. ‹›
FoundationOne® Report – Profiling the Genome
25
Foundation Medicine,“Next Generation Sequencing in the Clinic - The First 2200+ Cases Lessons Learned”

58. ‹›“Common” Mutation Identified
• EGFR Exon 21 L858R point mutation identified
– Associated with unprecedented sensitivity to EGFR-TKIs
such as gefitinib (Iressa) and erlotinib (Tarceva)
• Present in 10% of lung adenocarcinomas
• NOT reported with reproducible frequency in other
tumor types → NO clinical testing done
• Broad based, highly sensitive NGS test
(FoundationOne) identifies a transforming lesion in
this advanced IBC
26
Foundation Medicine,“Next Generation Sequencing in the Clinic - The First 2200+ Cases Lessons Learned”

59. Cell cycle
enome integrity
RTK signalling
RB1
CDKN2A
FGFR3
KIT
FGFR2
EPHB6
PDGFRA
ERBB4
EPHA3
FLT3
EGFR
ERCC2
RAD21
CHEK2
SMC3
SMC1A
BRCA1
BAP1
STAG2
ATR
BRCA2
ATRX
ATM
TP53
14.3 1.8 0.5 8.3 3.0 0.2 0.0 5.3 6.9 1.9 3.9 3.2
4.1 0.0 0.5 0.7 21.3 1.0 0.0 6.6 14.9 0.0 0.4 3.6
8.2 0.1 0.5 1.4 1.7 1.4 0.0 0.4 2.3 0.3 0.4 1.0
1.0 0.5 1.0 1.0 1.0 0.7 4.0 1.8 3.5 1.9 2.2 1.4
2.0 0.9 0.0 0.3 0.7 0.2 0.0 3.1 2.3 0.0 10.4 1.5
3.1 0.4 0.0 1.4 1.3 1.2 0.0 9.7 3.5 0.3 1.7 1.6
6.1 0.4 1.0 3.8 1.0 1.4 0.5 6.6 4.0 1.0 1.3 1.9
2.0 0.8 3.6 0.3 4.3 1.4 0.0 7.5 5.2 0.0 2.6 2.1
1.0 0.5 3.1 1.0 3.7 0.5 0.5 8.8 6.3 1.0 2.2 2.1
2.0 0.4 0.0 1.7 0.7 0.5 26.5 4.0 4.0 1.0 0.9 2.7
1.0 0.7 1.6 26.6 4.7 1.7 1.0 11.4 2.9 1.9 1.3 4.6
12.2 0.1 0.5 0.0 0.3 0.2 0.0 1.3 0.0 0.3 0.4 0.7
2.0 0.5 1.0 0.3 1.0 0.0 2.5 2.6 1.2 0.3 0.9 0.9
2.0 0.4 0.0 1.7 2.3 0.7 0.0 0.9 1.2 0.3 1.3 0.9
1.0 0.4 0.0 1.4 1.7 1.2 3.5 2.6 2.3 0.3 0.4 1.2
3.1 0.8 1.6 1.7 1.0 0.5 3.5 1.3 0.6 1.3 4.4 1.5
4.1 1.6 0.0 1.0 2.7 1.0 0.0 3.5 5.2 3.5 0.9 1.9
4.1 0.3 0.0 0.7 1.0 10.1 0.0 1.3 0.6 0.6 2.2 2.0
10.2 0.9 1.0 4.1 0.7 1.7 3.0 2.6 3.5 1.0 3.9 2.2
4.1 0.8 2.1 1.4 5.3 1.2 0.0 5.7 4.0 0.6 7.0 2.4
6.1 1.7 1.6 1.4 3.7 1.9 0.0 5.7 5.8 3.2 4.4 2.7
8.2 1.2 1.0 5.5 4.3 1.9 0.0 6.1 5.8 0.6 3.0 2.8
11.2 2.1 5.7 1.4 2.7 2.9 0.0 7.9 4.0 1.3 6.5 3.3
50.0 32.9 58.6 28.3 69.8 2.2 7.5 51.8 79.3 94.6 27.8 42.0
Transcription
factor/regulator
BLCA
BRCA
COAD/READ
GBM
HNSC
KIRC
AML
LUAD
LUSC
OV
UCEC
Pan−Cancer
SIN3A
TBX3
MECOM
RUNX1
TSHZ2
TAF1
CTCF
EP300
TSHZ3
GATA3
VHL
1.0 0.5 0.5 0.7 0.7 0.5 0.0 1.8 2.9 0.6 5.2 1.1
3.1 2.4 1.0 0.0 0.7 0.0 0.0 4.4 2.9 1.0 1.3 1.4
5.1 0.5 1.0 1.4 1.7 1.0 0.0 3.5 4.6 0.6 3.0 1.5
1.0 3.3 1.0 0.0 0.7 0.0 9.0 0.4 0.0 0.0 1.3 1.6
4.1 0.9 3.1 2.4 1.3 0.7 0.0 6.6 3.5 1.0 1.7 1.8
2.0 1.1 1.6 1.4 2.3 1.2 0.0 4.0 6.9 1.6 8.7 2.3
2.0 2.4 1.6 0.0 3.3 0.5 0.5 1.3 0.0 0.3 16.5 2.4
17.4 0.8 2.1 0.3 8.0 1.4 0.0 0.9 4.6 0.3 5.2 2.5
2.0 0.7 3.1 0.7 1.3 1.2 0.5 14.9 6.3 1.0 3.9 2.6
1.0 10.6 1.0 0.0 2.0 0.0 0.0 2.6 2.9 0.3 0.4 3.2
0.0 0.0 0.0 0.0 0.0 52.3 0.0 0.0 0.6 0.0 0.9 6.9
Nature. 2013 Oct 17;502(7471):333-9. Mutational landscape and significance across 12 major cancer types. Kandoth C et. al.

60. ‹›
Left Supraclavicular Lesion: PET-CT
Sept, 2012 Nov, 2012
Response Assessment After Starting Erlotinib
27
Foundation Medicine,“Next Generation Sequencing in the Clinic - The First 2200+ Cases Lessons Learned”

61. Ready for the Next Step?

62. “Food and Drug Administration (FDA) has granted
marketing authorization for the first high-throughput
(next-generation) genomic sequencer, Illumina's
MiSeqDx, which will allow the development and use
of innumerable new genome-based tests.”
(November 19, 2013)

64. NCCN Guidelines Index
NSCLC Table of Contents
Discussion
Version 4.2014, 06/05/14 © National Comprehensive Cancer Network, Inc. 2014, All rights reserved. The NCCN Guidelines®
and this illustration may not be reproduced in any form without the express written permission of NCCN®
. UPDATES
NCCN Guidelines Version 4.2014 Updates
Non-Small Cell Lung Cancer
Updates in the 1.2014 version of the Guidelines for Non-Small Cell Lung Cancer from the 2.2013 version include:
NSCL-6
•
• Surgery as initial treatment, margins positive:
R1 resection separated out with the following recommendations: resection + chemotherapy or chemoradiation (sequential or concurrent).
R2 resection separated out with the following recommendations: resection + chemotherapy or concurrent chemoradiation.
NSCL-8
• T1-3, N0-1: unresectable changed to medically inoperable.
• Surgery as initial treatment, margins positive:
R1 resection separated out with the following recommendations: chemoradiation (sequential or concurrent).
R2 resection separated out with the following recommendations: concurrent chemoradiation.
• Footnote “s” is new to the page: Patients likely to receive adjuvant chemotherapy may be treated with induction chemotherapy as an
alternative.
NSCL-9
• Surgery as initial treatment, margins positive:
R1 resection separated out with the following recommendations: chemoradiation (sequential or concurrent).
R2 resection separated out with the following recommendations: concurrent chemoradiation.
NSCL-10
• (eg, small subsolid nodules with slow growth).
However, if the lesion(s) becomes symptomatic or becomes high risk for producing symptoms (eg, subsolid nodules with accelerating
growth or increasing solid component or increasing FDG uptake, even while small), treatment should be considered.
NSCL-13
• T1-2, N0-1; T3, N0: SABR of the lung lesion added as a treatment option after chemotherapy.
NSCL-14
• H&P and chest CT recommendations in surveillance changed from a category 2B to a category 2A.
NSCL-15
• Mediastinal lymph node recurrence: treatment recommendations listed according to prior treatment with RT. If patients received prior RT, the
recommendation of systemic chemotherapy added.
NSCL-16
• Establish histologic subtype with adequate tissue for molecular testing: “consider rebiopsy if appropriate” added.
• “Integrate palliative care” added with footnote “b”. A link to the NCCN Guidelines for Palliative Care added.
• Adenocarcinoma, large cell, NSCLC NOS; the following added:
Category 1 added to ALK testing.
EGFR ± ALK testing should be conducted as part of a multiplex/next-generation sequencing.
•
Consider EGFR mutation and ALK testing are not routinely recommended except especially in never smokers and or small biopsy
specimens, or mixed histology.
EGFR ± ALK testing should be conducted as part of a multiplex/next-generation sequencing.
• Footnote “cc” added with direction to a new page, Targeted Agents for Patients with Other Genetic Alterations (NSCL-H).
• EGFR mutation and ALK negative: “or unknown” added.
Printed by yoon sup choi on 6/19/2014 8:23:15 PM. For personal use only. Not approved for distribution. Copyright © 2014 National Comprehensive Cancer Network, Inc., All Rights Reserved.

65. NCCN Guidelines Version 4.2014
Non-Small Cell Lung Cancer
NCCN Guidelines Index
NSCLC Table of Contents
Discussion
Version 4.2014, 06/05/14 © National Comprehensive Cancer Network, Inc. 2014, All rights reserved. The NCCN Guidelines®
and this illustration may not be reproduced in any form without the express written permission of NCCN®
.
Note: All recommendations are category 2A unless otherwise indicated.
Clinical Trials: NCCN believes that the best management of any cancer patient is in a clinical trial. Participation in clinical trials is especially encouraged.
NSCL-16
aSee Principles of Pathologic Review (NSCL-A).
bTemel JS, Greer JA, Muzikansky A, et al. Early palliative care for patients with metastatic non-small-cell lung cancer. N Engl J Med 2010;363:733-742.
ccSee Targeted Agents for Patients with Other Genetic Alterations (NSCL-H).
ddIn patients with squamous cell carcinoma, the observed incidence of EGFR mutations is 2.7% with a confidence that the true incidence of mutations is less than 3.6%.
This frequency of EGFR mutations does not justify routine testing of all tumor specimens. Forbes SA, Bharma G, Bamford S, et al. The catalogue of somatic mutations
in cancer (COSMIS). Curr Protoc Hum Genet 2008;chapter 10:unit 10.11.
eePaik PK, Varghese AM, Sima CS, et al. Response to erlotinib in patients with EGFR mutant advanced non-small cell lung cancers with a squamous or squamous-like
component. Mol Cancer Ther 2012;11:2535-2540.
ffConsider ROS1 testing; if positive, may treat with crizotinib. Bergethon K, Shaw AT, Ou SH, et al. ROS1 rearrangements define a unique molecular class of lung
cancers. J Clin Oncol 2012;30:863-870.
SYSTEMIC THERAPY FOR
METASTATIC DISEASE
HISTOLOGIC SUBTYPE
Metastatic
Disease
• Establish histologic
subtypea with
adequate tissue for
molecular testing
(consider rebiopsy
if appropriate)
• Smoking cessation
counseling
• Integrate palliative
careb (See NCCN
Guidelines for
Palliative Care)
• Adenocarcinoma
• Large Cell
• NSCLC not
otherwise
Squamous cell
carcinoma
• EGFR mutation testinga
(category 1)a
• ALK testing (category 1)a
• EGFR ± ALK testing should
be conducted as part of
multiplex/next-generation
sequencingcc
• Consider EGFR mutation and ALK
testingdd especially in never
smokers or small biopsy
specimens, or mixed histologyee
• EGFR ± ALK testing should be
conducted as part of multiplex/next-
generation sequencingcc
Sensitizing
EGFR mutation
positive
ALK positive
Sensitizing EGFR
mutation and
ALK negative or
unknownff
See First-Line
Therapy (NSCL-17)
See First-Line
Therapy (NSCL-18)
See First-Line
Therapy (NSCL-19)
See First-Line
Therapy (NSCL-20)
Printed by yoon sup choi on 6/19/2014 8:23:15 PM. For personal use only. Not approved for distribution. Copyright © 2014 National Comprehensive Cancer Network, Inc., All Rights Reserved.

66. Oct 16, 2014
“Priority Health has begun coverage
of Foundation Medicine's genomic
profiling services for cancer, making
the health plan the first in the
country to provide such coverage”

67. Nov 5, 2014
“Google will soon start covering the cost
of Foundation Medicine's DNA tests for
employees and their family-members
suffering from cancer, as part of its
health benefits portfolio.”

68. The pharmaceutical giant Roche
plans to spend $1 billion to acquire
majority control of Foundation
Medicine, a five-year old company
that developed an innovative DNA
test to match patients to specific
cancer drugs. (January 12, 2015)

69. President Obama’s Precision Medicine Initiative

70. Precision Medicine Initiative
• 2016년까지 $215m 을 투자
• NIH ($130m): development of a voluntary national research cohort
of a million or more volunteers
• NCI ($70m): scale up efforts to identify genomic drivers in cancer
• FDA ($10m)
• acquire additional expertise
• to advance innovation and protect public health.
• ONC ($5m): the development of interoperability standards

71. Objectives of
the Precision Medicine Initiative
• More and better treatments for cancer
• Creation of a voluntary national research cohort
• “Participants will be involved in the design of the Initiative and will have
the opportunity to contribute diverse sources of data”
• Commitment to protecting privacy
• Regulatory modernization
• “FDA will develop a new approach for evaluating NGS technologies”
• Public-private partnerships

73. Current Limitations
to Implement Precision Oncology
• NGS analysis methodology
• Identification of driver genes
• Policy for VUS (variant of unknown significance)
• Lack of actionable mutations
• Tumor heterogeneity

74. Limitation 1.
Technical Limitations
of NGS Analysis

75. S I S
r ascertain whether the platform-
Vs might be located in functionally
egions, we examined whether the
were present in the Varimed data-
ich contains variants catalogued
ome-wide association studies and
c linkage studies. We found that
- and 3 CG-specific SNVs were
arimed, from which we were able
associations between diseases
m-specific SNPs (Supplementary
ne of these, rs2672598, was called
MCs and saliva by the Illumina
ut not called in either PBMCs or
e CG platform. This SNP is at the
TRA1 and known to increase the
related macular degeneration by
P = 3.39 × 10−11)18,19. Another
he A202T allele in the TERT gene
omerase. This allele has been associated with aplastic ane-
was only detected by the Illumina platform. Thus, some
had a stronger association with L1, simple repeat and low-complexity
repeat. Overall, these results indicate that many platform-specific
Complete Genomics specific
99,578
Illumina specific
345,100
CG no-call
230,119; 67%
CG
Sub & other
77,196; 22%
CG ref.
37,785; 11%
IL no-call
74,556; 75%
IL ref. 25,022;
25%
CG+IL
Illumina
Union
Blood
3,570,658 3,528,194
Merge
Saliva
Complete Genomics
Blood
Merge
Union
2.7% 9.2%
3,295,023
Concordant SNPs
88.1%
Sensitivity: 99.34%
Total
Ti/Tv
Specific
Ti/Tv
Known
Novel
Sanger
Validated
Total
Ti/Tv
Specific
Ti/Tv
Known
Novel
Sanger
Validated
Total
Ti/Tv
Sensitivity
Concordant
Ti/Tv
Known
Novel
Sanger
Validated
3,394,601
2.13
99,578 (3.0%)
1.68
72,735 (73.0%)
26,843 (27.0%)
94.4% (17/18)
61.9%
3,640,123
2.05
345,100 (10.5%)
1.40
260,108 (75.4%)
84,992 (24.6%)
13.3% (2/15)
64.3%
3,739,701
2.04
99.5%
3,295,023
2.14
3,160,905 (95.9%)
134,118 (4.1%)
100% (20/20)
92.7%
Overall
Intersect Intersect
3,277,339 3,286,645
Saliva
a
b
V detection and intersection.
ected from the PBMC and saliva
ach platform were combined.
f SNVs in each platform were
ted. Sensitivity was measured
lumina Omni array. Ti/Tv is the
transversion ratio. The known
unts were based on dbSNP.
‘validated’ represent validation by
encing and Illumina sequencing
target enrichment capture),
(b) Comparing platform-specific
SNV calls in another platform. IL,
, Complete Genomics.
Lam HY et al. Nat Biotechnol. 2011 Dec 18;30(1):78-82.
Performance comparison of whole-genome sequencing platforms
: SNV (Single NucleotideVariation) detection

76. ©2012Natu
NATURE BIOTECHNOLOGY VOLUME 30 NUMBER 1 JANUARY 2012 81
390,060 (48.1%) and 206,461 (25.4%) were Illumina- and CG-specific,
respectively (Fig. 4a). Owing to the complexity of indels compared
to SNVs, the number of concordant indels was much lower than
the number of concordant SNVs. We also observed that the indels
detected by both platforms were similar in their size distribution
and type (Fig. 4b), though it is noteworthy that the Illumina data
showed a slight enrichment of 1-bp insertions, whereas the CG data
showed a slight enrichment of 1-bp deletions.
7
8
9
10
11
12
13 5
25
0
125
100
75
50
25
0
125
100
75
50
25
0
125
100
75
50
25
0
0125150
0
25
50
75
100
125
150
0
25
75
100
125
0
25
50
100
75
125
50
(c) Repetitive elements: centromere, telomere, tRNA
and rRNA. (d) Repetitive elements: L1, Alu, simple
repeat and low-complexity repeat. (e) SNV frequency
at different chromosomal locations. Tracks from outer
to inner: SNV frequency for Illumina (IL), Complete
Genomics (CG), concordant, IL-specific and CG-
specific calls. Outermost: chromosome ideogram.
Complete Genomics
Blood
361,783 341,172
Merge
Union
Intersect
Total
Total 811,903
215,382Concordant
Specific 206,461 (48.0%)
430,258
Saliva Blood
523,445 555,770
Merge
Union
Total
Specific 390,060 (63.8%)
Intersect
611,110
Saliva
206,461
CG-specific
(25.4%)
215,382
Concordant indels
(26.5%)
Overall
CG+IL
390,060
IL-specific
(48.1%)
Illumina
a Complete Genomics
Illumina
160,000
140,000
120,000
100,000
80,000
60,000
40,000
–72–68–64–60–56–52–48–44–40–36–32–28–24–20–16–12
–8
–4
0
0
Indel size
4
8
12
16
20
24
28
32
36
40
44
48
20,000
b
Figure 4 Indel detection and intersection. (a) Indels detected from the PBMC and saliva samples in each platform were combined. The unions of
indels in each platform were then intersected. Note: 5,668 IL and 8,415 CG indels were removed after 5b-window merging. (b) Indel size distribution.
Negative size represents deletion and positive size represents insertion.
Lam HY et al. Nat Biotechnol. 2011 Dec 18;30(1):78-82.
: indel detection
Performance comparison of whole-genome sequencing platforms

77. and may be deployed for clinical use once the appropriate platform
is chosen.32,47,48
Molecular Annotation of Variants
The somatic events observed with analysis tools are typically
represented in computer files as genomic coordinates with allele
changes or segments of copy number gain or loss. To proceed with
effectiveclinicalinterpretationoftheseevents,translationofthesedata
for human use with effective molecular annotation is necessary. Pub-
lically available annotation tools exist to convert these data into for-
mats that use gene names and protein changes based on established
public resources.49-54
Salient sequencing data metrics may include
alternative transcripts expressed from query loci, locus-specific cover-
age and the variant allelic fraction (defined as the number of alternate
reads at the site divided by the total number of reads at that site).
Additional resources may link genetic alterations to other databases
that can aid downstream clinical interpretation, including the pre-
dictedeffectofthevariantontheprotein52,55,56
orthefrequencyofthis
event in published cancer genomics research studies.57
At the present
time, these annotations are typically focused on research-oriented
pursuits,andnewdatabaseswillbeneededtoframeclinicallyoriented
molecular annotation.
THE PROCESS OF CLINICAL INTERPRETATION OF
TUMOR VARIANTS
Once all tumor variants in a patient’s genome have been identified,
clinical interpretation of each variant is needed to identify the subset
that may affect medical decision making. The process of clinical inter-
pretation includes classification of the effect of the variant, reporting
theresultstoclinicians,andenablingthephysiciantomakeamanage-
ment decision based on the genomic information integrated with
other clinical features.
BowTie
BWA
mrFAST
msFAST
Novoalign
SHRiMP
SNAP
SOAPv2
Stampy
Clinical interpretation
Molecular annotation
Alignment
Mutations Insertion/deletions Copy number
CapSeg
CNVnator
CoNAn-SNV
CoNIFER
SegSeq
Univ. of Michigan
VarScan 2
XHMM
BreakDancer
Dindel
Indelocator
Pindel
SOAPindel
SplazerS
GeneInsight
PHIAL
Mutation Taster
MutationAssessor
Oncotator
SeattleSeq
SNPeff (Ensembl)
wANNOVAR
Atlas2
JointSNVMix
MuTect
SomaticSniper
Strelka
UnifiedGenotyper
VarScan 2
A
B
C
D
Fig 2. A representative set of tools for the analysis and interpretation of genome
sequencing data. These include (A) a listing of representative algorithms for
sequencing alignment, (B) variant identification, (C) variant annotation, and (D)
clinical interpretation. Boldfaced entries are those specifically geared toward
tumor versus normal analysis.
Clinical Analysis and Interpretation of Cancer Genome Data
Which Analysis Tool to Choose?
J Clin Oncol. 2013
Review of bioinformatics analysis of whole exome sequ
Post-alignment processing:
3) Base quality score recalibration
GATK-BaseRecalibrator ReQON
Post-alignment processing:
1) Remove read duplicates
Picard SAMtools DupRecover
Map to reference genome
BWA Bowtie2 Novoalign GMAP
Filter and prioritize variants
VAAST2 CADD VarSifer KGGseq
PLINK/SEQ SPRING gNOME
Annotate variants
MAF, exonic function, deleterious
prediction
ANNOVAR SeattleSeq SnpEff
Post-alignment processing:
2) InDel realignment
GATK-InDelRealigner SRMA
InDel-realigned read alignment
BAM
List of Disease-Related Variants
4.Post-alignmentprocessing
5-3Variantprioritization5-2.Variantannotation5-1.Variantcalling
3.Alignment2.Preprocessing1.Qualitycontrol
Signaling pathways
Family history
Clinical data
Dedupped read alignment
BAM
Read alignment
BAM
Annotated variant calls
TAB
Public Databases
1000G, ESP6500, CADD,
ClinVar, COSMIC
Processed reads
FASTQ
Raw reads
FASTQ
Recalibrated read alignment
BAM
Variant calls (SNPs and InDels)
VCF
Germline
variants
Somatic
variants
Pass QC
Preprocessing
Cutadapt Trimmomatic PRINSEQ
Raw reads Qc
FastQC PRINSEQ QC3
Variant calling
GATK SAMtools Freebayes Atlas2
Strelka virmid SomaticSniper
Figure 1. A general framework of WES data analysis. Five major steps are shown: raw reads QC, preprocessing, alignment, post-­processing, and
analysis (variant calling, annotation, and prioritization).
Notes: FASTQ, BAM, variant call format (VCF), and TAB (tab-­delimited) refer to the standard file format of raw data, alignment, variant calls, and
annotated variants, respectively. A selection of tools supporting each analysis step is shown in italic.
Cancer Inform. 2014

78. ed BMC Bioinformatics 2013, 14:189 Page 3 of 16
biomedcentral.com/1471-2105/14/189
equently used in variant calling analyses. For
utation-calling, the tumor and its matched nor-
e are considered together. Therefore, a variant is
d by the joint status in tumor-normal sequence
atic’ (the variant allele is found in the tumor
t not in the normal), ‘germline’ (variant allele
both the tumor and the normal sample), and
(no variant allele found in either the tumor or
l sample). In our manuscript, a mutation or
e’ refers to a position only for the particular
rying the variant.
ies observed in the benchmark data
aset From each caller’s raw mutation-calling
CF), we extracted a final set of somatic muta-
have a broad picture, we gathered all such
from all 16 LUSC patients. An immediate
am summary reveals substantial discrepancies
mutations from the four callers (Figure 1A).
le, 491 and 427 mutations were detected by
nly and Caller D only, while 1,667 mutations
vered by all four callers. There are many muta-
were missed by a single caller. For example, 716
were detected by all but Caller B, and 104 were
y all but Caller C. We also categorized muta-
d on the degree of agreement (Figure 1B). In
0 mutations were called by one or more callers,
28%, 16%, and 25% of those were detected by
wo, and a single caller(s). A similar categoriza-
mutations detected by each caller suggests that
stringent, since it detected a relatively small
mutations, most of which were detected by
callers. Callers A, C, and D reported a simi-
r of mutations, a good proportion of which are
ific.
491
59 375
427
14
293
164
78
74
244
208
104716
466
1667
Caller A
Caller B Caller C
Caller D
0100020003000400050006000
3657
2670
4047
3862
5380
Caller A Caller B Caller C Caller D Union
Detected by single caller
Detected by two callers
Detected by three callers
Detected by all callers
A
B
Figure 1 Counts of the mutations detected by four callers in the
16 LUSC tumor-normal exome-seq pairs. A. Venn Diagram of the
mutations. B. Mutations detected by each caller or by any caller
(‘Union’) are classified based on the number of callers detecting the
mutations.
Kim SY, Speed TP. BMC Bioinformatics. 2013 Jun 10;14:189.
Comparing four somatic mutation-callers
Counts of the mutations detected by four different callers
in the 16 LUSC tumor-normal exome-seq pairs.

79. Kim and Speed BMC Bioinformatics 2013, 14:189 Page 4 of 16
http://www.biomedcentral.com/1471-2105/14/189
Caller A only
050100150200250
[0x,5x)
[5x,10x)
[10x,20x)
[20x,40x)
[40x,100x)
[100x,200x)
[200x,1519x]
[50%,100%]
[30%,50%)
[20%,30%)
[10%,20%)
[0%,10%)
Caller B only
050100150200250
[0x,5x)
[5x,10x)
[10x,20x)
[20x,40x)
[40x,100x)
[100x,200x)
[200x,1008x]
[50%,100%]
[30%,50%)
[20%,30%)
[10%,20%)
[0%,10%)
Caller C only
050100150200250
[0x,5x)
[5x,10x)
[10x,20x)
[20x,40x)
[40x,100x)
[100x,200x)
[200x,1702x]
[50%,100%]
[30%,50%)
[20%,30%)
[10%,20%)
[0%,10%)
Caller D only
050100150200250
[0x,5x)
[5x,10x)
[10x,20x)
[20x,40x)
[40x,100x)
[100x,200x)
[200x,501x]
[50%,100%]
[30%,50%)
[20%,30%)
[10%,20%)
[0%,10%)
All but Caller A
050100150200250
[0x,5x)
[5x,10x)
[10x,20x)
[20x,40x)
[40x,100x)
[100x,200x)
[200x,397x]
[50%,100%]
[30%,50%)
[20%,30%)
[10%,20%)
[0%,10%)
All but Caller B
050100150200250
[0x,5x)
[5x,10x)
[10x,20x)
[20x,40x)
[40x,100x)
[100x,200x)
[200x,423x]
[50%,100%]
[30%,50%)
[20%,30%)
[10%,20%)
[0%,10%)
All but Caller C
050100150200250
[0x,5x)
[5x,10x)
[10x,20x)
[20x,40x)
[40x,100x)
[100x,200x)
[200x,407x]
[50%,100%]
[30%,50%)
[20%,30%)
[10%,20%)
[0%,10%)
All but Caller D
050100150200250
[0x,5x)
[5x,10x)
[10x,20x)
[20x,40x)
[40x,100x)
[100x,200x)
[200x,1923x]
[50%,100%]
[30%,50%)
[20%,30%)
[10%,20%)
[0%,10%)
Figure 2 Distribution of the coverage (horizontal) and the variant allele fraction (vertical) in the tumor exome-seqs. Among the mutations
detected by four callers using 16 LUSC tumor-normal exome-seq pairs, mutations detected by a single caller (upper row) or missed by a single caller
(lower row) are used. Each column corresponds to a caller that uniquely detects the mutations or uniquely misses the mutations.
caller employed a certain filter that was different from are reported in the file, and then find the reasons for
Comparing four somatic mutation-callers
Distribution of the coverage (horizontal) and the variant allele fraction (vertical) in the tumor exome-seqs.
Kim SY, Speed TP. BMC Bioinformatics. 2013 Jun 10;14:189.

80. et al. [5] in the 20 samples included in our study. Also in
this case, all the comparison analyses took into account
all the discovered CNVs and rare and common variants
separately. Using microarray techniques, McCarroll et al.
[7] detected 100 CNV events (96 common CNVs and 4
rare CNVs) overlapping coding regions (with at least three
exons) on chromosomes 1 and 4 of these 20 samples, while
Conrad et al. [5] detected 120 events (116 common and
ratio between the number of correctly detected events
(the intersection between the tool calls and the validation
set calls) and the total number of events detected by a tool.
The recall was calculated as the ratio between the num-
ber of correctly detected events and the total number of
events in the validation set.
The results obtained by the four methods for the all
variants (Figure 3e) and common variants (Figure 3f)
Overlap(%)
03070
All Common Rare
a
Overlap(%)
03070
All Common Rare
b
Overlap(%)
03070
All Common Rare
c
Overlap(%)
03070
All Common Rare
d
EXCAVATOR XHMM CoNIFER ExomeCNV
0.0 0.2 0.4 0.6 0.8 1.0
0.00.20.40.60.81.0
Precision
Recall
f=0.1
f=0.2
f=0.3
f=0.4
f=0.5
f=0.6
f=0.7
f=0.8
f=0.9
e
0.0 0.2 0.4 0.6 0.8 1.0
0.00.20.40.60.81.0
Precision
Recall
f=0.1
f=0.2
f=0.3
f=0.4
f=0.5
f=0.7
f=0.8
f=0.9
f
0.0 0.2 0.4 0.6 0.8 1.0
0.00.20.40.60.81.0
Precision
Recall
f=0.1
f=0.2
f=0.3
f=0.4
f=0.5
f=0.6
f=0.7
f=0.8
f=0.9
g
f=0.6
Conrad
McCarroll
Conrad
McCarroll
Conrad
McCarroll
Figure 3 Summary of the results obtained by EXCAVATOR on the 1000 Genomes Project samples. (a), (b), (c), (d) Overlap between the set of
CNVs detected by the four methods and the CNVs annotated in the DGV (a, b) and in the NCBI dbVar (c, d) with the two overlapping criteria: 10%
(a, c) and 50% (b, d). (e), (f), (g) Precision-recall plots of the comparison between the CNV events detected by the four methods included in this
comparison and the CNVs previously reported by McCarroll et al. [7] and Conrad et al. [5]. Light grey curves represent F-measure levels (harmonic
mean of precision and recall). (e) Results for all variants. (f) Results for common CNVs. (g) Results for rare CNVs.
Comparing four CNV analysis tools
Summary of the results obtained by four different CNV analysis tools on the 1000 Genome Project samples.

81. Limitation 2.
Identification of driver genes
What if the patient have no known mutations?

82. Level of Evidence
그렇다면, 어느 변이부터 먼저 봐야 하나?
근거 수준에 따라 유전 변이의 우선 순위 구분

83. •Level 0: 식약처/FDA에 의해 승인된 유전자/유전변이-표적항암제 용법
•Level 1: 실험적인 근거가 확실하여, biologically 암 발병 원인으로 의심 가능한 변이
• Oncogene의 경우
! Protein function이 증가하는 결과를 가져오는 mutation
• Tumor Suppressor의 경우
! Protein function이 낮아지는/없어지는 결과를 가져오는 mutation
•Level 2: 실험적 근거는 불확실하나, 암 관련 보고가 있는 usual suspects
• COSMIC database에 포함된 mutation은 전부
• Uniprot 에서 ‘found in xxx cancer’,‘somatic mutation’ 이라 annotation된 경우
•Level 3: 나머지 somatic mutation
• 이 환자에게는 somatic 이긴 하지만, cancer와 관련된 기존 보고는 없는 경우

84. ©2014NatureAmerica,Inc.Allrightsreserved.
T E C H N I CA L R E P O RT S
Translating whole-exome sequencing (WES) for prospective
clinical use may have an impact on the care of patients with
cancer; however, multiple innovations are necessary for clinical
implementation. These include rapid and robust WES of DNA
derived from formalin-fixed, paraffin-embedded tumor tissue,
analytical output similar to data from frozen samples and
clinical interpretation of WES data for prospective use. Here,
we describe a prospective clinical WES platform for archival
formalin-fixed, paraffin-embedded tumor samples. The platform
employs computational methods for effective clinical analysis
and interpretation of WES data. When applied retrospectively to
511 exomes, the interpretative framework revealed a ‘long tail’
of somatic alterations in clinically important genes. Prospective
application of this approach identified clinically relevant
alterations in 15 out of 16 patients. In one patient, previously
undetected findings guided clinical trial enrollment, leading to an
objective clinical response. Overall, this methodology may inform
the widespread implementation of precision cancer medicine.
Massively parallel sequencing approaches such as WES have elu-
cidated the landscape of genetic alterations in many tumor types
and revealed biological insights relevant to clinical contexts1. The
increased practical availability and decreased cost of tumor genomic
profiling has generated opportunities to test the ‘precision medicine’
genes using either fresh frozen or formalin-fixed, paraffin-embedded
(FFPE) tissue7–9. Pilot studies that apply research-grade massively
parallel sequencing technology in focused clinical settings have
also been reported7,10–12, although production-scale efforts have
not been demonstrated. Multiple challenges to widespread clinical
WES implementation remain. One challenge involves rapidly gener-
ating high-quality WES data from archival FFPE tumor material13.
Another involves clinically interpreting WES data for prospective use
that maximizes clinical and biological exploration. A third involves
developing a system to interrogate plausibly actionable variants of
uncertain significance. Overcoming these challenges should allow
rigorous assessment of the value of WES to guide clinical decision
making and inform selected experimental follow-up.
Here, we describe an approach to generate high-quality WES data
from archival tumor material and validate WES data from FFPE tumor
samples with corresponding WES data from frozen samples. We also
present a heuristic algorithm that interprets the resulting data for clinical
oncologists and establish the clinical applicability of this interpretation
algorithm in a retrospective cohort of 511 cases. Prospective application
of this platform in patients with a range of tumor types indicates that
this approach can be used for both biological discovery and clinical trial
enrollment. This approach may therefore facilitate widespread applica-
tion of WES for precision cancer medicine studies.
Whole-exome sequencing and clinical interpretation of
formalin-fixed, paraffin-embedded tumor samples to
guide precision cancer medicine
Eliezer M Van Allen1,2,8, Nikhil Wagle1,2,8, Petar Stojanov1,2, Danielle L Perrin2, Kristian Cibulskis2,
Sara Marlow1,2, Judit Jane-Valbuena1,2, Dennis C Friedrich2, Gregory Kryukov2, Scott L Carter2,
Aaron McKenna2,3, Andrey Sivachenko2, Mara Rosenberg2, Adam Kiezun2, Douglas Voet2, Michael Lawrence2,
Lee T Lichtenstein2, Jeff G Gentry2, Franklin W Huang1,2, Jennifer Fostel2, Deborah Farlow2, David Barbie1,
Leena Gandhi1, Eric S Lander2, Stacy W Gray1, Steven Joffe1,4, Pasi Janne1, Judy Garber1, Laura MacConaill1,5,
Neal Lindeman1,5, Barrett Rollins1, Philip Kantoff1, Sheila A Fisher2, Stacey Gabriel2,9, Gad Getz2,6,7,9 &
Levi A Garraway1,2,9
Nat Med. 2014 Jun;20(6):682-8.

85. ©2014NatureAmerica,Inc.Allrightsreserved.
DISCUSSION
This study demonstrates that rapid WES can be applied to FFPE
clinical samples and that robust WES analysis and interpretation can
prospectively inform clinical trial enrollment. This approach incorpo-
rates new algorithms to identify clinically relevant alterations among
numerous somatic events. Furthermore, real-time curation of nomi-
nated alterations assigns levels of evidence to the corresponding clini-
cal actions for that alteration in that tumor type. In a proof-of-concept
application, we identified at least one clinically relevant alteration in
15 of 16 patients and showed how such findings can lead to clinical
trial enrollment and biological discovery.
Targeted sequencing of clinically relevant gene panels (contain-
ing hundreds of genes) have recently become possible from FFPE
tumor samples7 and are increasingly used clinically. However, there
are numerous advantages to clinical WES over targeted sequencing.
First, as the spectrum of clinically actionable alterations grows2,
targeted sequencing of particular genes is likely to be incomplete:
be mined to inform TARGET entries. We recognize that the pace
of cancer discovery will necessitate continual TARGET updates to
ensure its relevance, and we encourage input from the clinical and sci-
entific community to expand and update its content for all to benefit.
Methods to aggregate such data in a systems biology approach37 are
being developed to foster functional and clinical follow-up38,39.
There are ways to improve upon the framework. Efforts to further
minimize the input DNA requirement and predict which samples
yield successful WES will improve production-level sequencing. This
process will be enhanced by pathology review of clinical samples to
enrich tumor DNA selection. Improvements in exome-derived copy
number algorithms will better distinguish homozygous from hetero-
zygous deletions in stromally admixed tumor samples. Integration of
additional profiling technologies (for example, transcriptome profil-
ing) will provide increasingly complex views of an individual’s cancer
and incorporate other changes (for example, epigenetic) that may
have clinical relevance. In parallel, efforts to demonstrate the utility of
R870
Y981
Tofacitinib
a b c
e f
d
KRAS
ATM STK11
Lung adenocarcinoma
JAK3
MET
Prostate cancer
Baseline After 2 cycles
0 1 2 3 cm 0 1 2 3 cm
Time after complete IL-3 depletion (d)
Ba/F3
Ba/F3 + IL-3
JAK3 WT
JAK3 A572V
JAK3 R870W
Cumulativepopulationdoublings
0
50
40
30
20
10
0
5 201510 25 30
Carboplatin
Paclitaxel
Bevacizumab
CDK4
inhibitor
Vinorelbine
Time to progression (weeks)
0 5 10 15 20
SD
PD
Figure 5 Clinical sequencing informs clinical trial
enrollment and experimental discovery. (a) The PHIAL
output and treatment course for a patient with metastatic
lung adenocarcinoma is shown, with the integration of
clinical WES occurring during the patient’s first-line
therapy allowing subsequent clinical trial enrollment.
(b) The patient’s time-to-relapse data for the three
treatment regimens received. (c) Computed tomography
radiographic imaging of a representative metastatic
focus for the patient on the CDK4 inhibitor trial after
two cycles of therapy (measurement is 1.7 × 1.5 cm for
baseline mass and 1.3 × 1.3 cm for 2-month interval
scan of the same mass). Per RECIST criteria, overall
tumor reduction was 7.9%. (d) For another patient,
PHIAL nominated a JAK3 missense mutation, and given
its location in the kinase domain near alterations
previously defined as activating, was considered to have
inferential evidence (level E) for being clinically actionable.
(e) The crystal structure of JAK3 highlighting the arginine at residue 870 which directly coordinates the phosphate group of the primary activating
tyrosine phosphorylation site. (f) Experimental follow-up of this alteration was performed in a Ba/F3 system compared to wild-type or a known activating
JAK3 mutation (A572V).
Nat Med. 2014 Jun;20(6):682-8.
• Implementation of a procedure to generate experimental evidence
for selected level E (inferential association) alterations.
• R870W missense mutation in JAK3 gene
• JAK3R870W
• JAK3 wild type
• JAK3A572V (known activating mutation)

86. What if there’s no druggable mutations?
•clinical trial enrollment
•investigator-initiated trial (IIT)
•off-label prescription
• 미국: 허용
• 국내: 비급여로 삭감

87. Limitation 3.
Heterogeneity

88. Tumor Heterogeneity
Meric-Bernstam F, Mills GB. Nat Rev Clin Oncol. 2012 Sep;9(9):542-8.

89. Intratumor Heterogeneity Revealed by multiregion Sequencing
B Regional Distribution of Mutations
C Phylogenetic Relationships of Tumor Regions D Ploidy Profiling
A Biopsy Sites
R2 R4
R9 R8
R5
R1
R3
R2
PreP
PreM
R1
R2
R3
R5
R8
R9
R4
M1
M2a
M2b
C2orf85
WDR7
SUPT6H
CDH19
LAMA3
DIXDC1
HPS5
NRAP
KIAA1524
SETD2
PLCL1
BCL11A
IFNAR1
DAMTS10
C3
KIAA1267
RT4
CD44
ANKRD26
TM7SF4
SLC2A1
DACH2
MMAB
ZNF521
HMG20A
DNMT3A
RLF
MAMLD1
MAP3K6
HDAC6
PHF21B
FAM129B
RPS8
CIB2
RAB27A
SLC2A12
DUSP12
ADAMTSL4
NAP1L3
USP51
KDM5C
SBF1
TOM1
MYH8
WDR24
ITIH5
AKAP9
FBXO1
LIAS
TNIK
SETD2
C3orf20
MR1
PIAS3
DIO1
ERCC5
KL
ALKBH8
DAPK1
DDX58
SPATA21
ZNF493
NGEF
DIRAS3
LATS2
ITGB3
FLNA
SATL1
KDM5C
KDM5C
RBFOX2
NPHS1
SOX9
CENPN
PSMD7
RIMBP2
GALNT11
ABHD11
UGT2A1
MTOR
PPP6R2
ZNF780A
WSCD2
CDKN1B
PPFIA1
TH
SSNA1
CASP2
PLRG1
SETD2
CCBL2
SESN2
MAGEB16
NLRP7
IGLON5
KLK4
WDR62
KIAA0355
CYP4F3
AKAP8
ZNF519
DDX52
ZC3H18
TCF12
NUSAP1
X4
KDM2B
MRPL51
C11orf68
ANO5
EIF4G2
MSRB2
RALGDS
EXT1
ZC3HC1
PTPRZ1
INTS1
CCR6
DOPEY1
ATXN1
WHSC1
CLCN2
SSR3
KLHL18
SGOL1
VHL
C2orf21
ALS2CR12
PLB1
FCAMR
IFI16
BCAS2
IL12RB2
PrivateUbiquitous Shared primary Shared metastasis
Ubiquitous
Lung
metastases
Chest-wall
metastasis
Perinephric
metastasis
M1
10 cm
R7 (G4)
R5 (G4)
R9
R3 (G4)
R1 (G3) R2 (G3)
R4 (G1)
R6 (G1)
Hilum
R8 (G4)
Primary
tumor
Shared primary
Shared metastasis
M2b
M2a
Intratumor Heterogeneity Revealed
by Multiregion Sequencing
Gerlinger M et al. N Engl J Med. 2012 Mar 8;366(10):883-92

90. Nat Genet. 2014 Feb 26;46(3):214-5.
Intratumoral heterogeneity in kidney cancer

91. Nat Genet. 2014 Mar;46(3):225-33.
E S
226 VOLUME 46 | NUMBER 3 | MARCH 2014 NATURE G
Figure 1 Regional distribution of nonsynonymous mutations in ten ccRCC tumors. Mutations that failed validation were not included. Heat map
indicate the presence of a mutation (yellow) or its absence (blue) in each region. Category 1 high-confidence driver mutations and category 2 p
driver mutations are highlighted in magenta. The table shows the number of nonsynonymous mutations and the ratio of heterogeneous mutation
tumor. An asterisk indicates where VHL methylation was included in the analysis.
226 VOLUME 46 | NUMBER 3 | MARCH 2014 NATURE G
Figure 1 Regional distribution of nonsynonymous mutations in ten ccRCC tumors. Mutations that failed validation were not included. Heat ma
indicate the presence of a mutation (yellow) or its absence (blue) in each region. Category 1 high-confidence driver mutations and category 2 p
driver mutations are highlighted in magenta. The table shows the number of nonsynonymous mutations and the ratio of heterogeneous mutatio
tumor. An asterisk indicates where VHL methylation was included in the analysis.
Figure 1 Regional distribution of nonsynonymous mutations in ten ccRCC tumors. Mutations that failed validation were not included. Heat map
indicate the presence of a mutation (yellow) or its absence (blue) in each region. Category 1 high-confidence driver mutations and category 2 p
driver mutations are highlighted in magenta. The table shows the number of nonsynonymous mutations and the ratio of heterogeneous mutation
tumor. An asterisk indicates where VHL methylation was included in the analysis.
226 VOLUME 46 | NUMBER 3 | MARCH 2014 NATURE G
Figure 1 Regional distribution of nonsynonymous mutations in ten ccRCC tumors. Mutations that failed validation were not included. Heat ma
indicate the presence of a mutation (yellow) or its absence (blue) in each region. Category 1 high-confidence driver mutations and category 2 p
driver mutations are highlighted in magenta. The table shows the number of nonsynonymous mutations and the ratio of heterogeneous mutatio
tumor. An asterisk indicates where VHL methylation was included in the analysis.
226 VOLUME 46 | NUMBER 3 | MARCH 2014 NATURE
Figure 1 Regional distribution of nonsynonymous mutations in ten ccRCC tumors. Mutations that failed validation were not included. Heat m
indicate the presence of a mutation (yellow) or its absence (blue) in each region. Category 1 high-confidence driver mutations and category 2
driver mutations are highlighted in magenta. The table shows the number of nonsynonymous mutations and the ratio of heterogeneous mutati
tumor. An asterisk indicates where VHL methylation was included in the analysis.
Regional distribution of nonsynonymous mutations
in ten ccRCC tumors
Heat maps indicate the presence of a mutation (yellow) or its absence (blue) in each region.
Category 1 high-confidence driver mutations and category 2 probable driver mutations are highlighted in magenta.