2021年6⽉12⽇
第28回抗悪性腫瘍薬開発フォーラム

リキッドバイオプシーによるがんゲノム医療時代の幕開け
中村能章
国⽴がん研究センター東病院
臨床研究⽀援部⾨トランスレーショナルリサーチ推進部トランスレーショナルリサーチ⽀援室／消化管内科1

SCRUM-Japan Project Since 2015

Astellas

LC-SCRUM
Participating
Institutions
2

Astra
ZenecaDaiichiSankyo

BristolMyers

Taiho

Eisai

TakedaChugai

Participating
fees
Kyowa
Kirin

Ono

PfizerMSD

Novartis

Merck
SeronoEli Lilly

Submission of Clinical Samples

GI*-SCREENLC*-SCRUM

Annotated report

Analysis
Data

SCRUM-Japan Common Data Center & Administrative Office

Genomic &clinical data

Submission of Clinical Samples

Annotated reportComprehensive NGS (Next Generation Sequencing) test by central vendor

Janssen

Boehringer
Ingelheim

GI-SCREEN
Participating
Institutions

GOZILA Nationwide ctDNA Screening Project
From North to South
1. Hokkaido University Hospital
2. University of Tsukuba
3. National Cancer Center Hospital East
4. Chiba Cancer Center
5. Saitama Cancer Center
6. National Cancer Center Hospital
7. Keio University School of Medicine
8. Kyorin University Hospital
9. The Cancer Institute Hospital of JFCR
10. St.Marianna University School of Medicine
11. Kanagawa Cancer Center
12. Shizuoka Cancer Center
13. Kanazawa University
14. Aichi Cancer Center Hospital
15. Osaka University Graduate School of Medicine
16. Kindai University
17. Kansai Rosai Hospital
18. National Hospital Organization Shikoku Cancer Center
19. National Hospital Organization Kyushu Cancer Center
20. Kyushu University
21. National Hospital Organization Osaka National Hospital
22. Kagawa University
23. Saitama Medical University International Medical Center
24. Kobe City Medical Center General Hospital
25. Gifu University Hospital
26. Osaka Medical College Hospital
27. Shimane Prefectural Central Hospital
28. Kansai Medical University Hospital
29. Kyoto Katsura Hospital
30. Osaka International Cancer Institute
31. Osaka General Medical Center

3

Guardant Health

31 Core Centers from17 prefectures

1

Blood

5, 23

G360 analysis

25
13
29

17, 24

2
3,4

27
19,20

14

12

10,11

6,7,8,922
18

15,16,21,26,28,30,31

n Launched on Jan, 2018n All GI cancers
n Sample size: 5000
p 4069 pts enrolled by Apr 2021

ctDNA解析の利点
p Turnaround timeが短く患者の治療適応の判断が速やかに可能

p Heterogeneityを評価することが可能

4

ctDNA解析の利点
p Turnaround timeが短く患者の治療適応の判断が速やかに可能

p Heterogeneityを評価することが可能

5

ctDNA解析のゲノム医療に対する有⽤性
2015年2⽉に開始した腫瘍組織パネル検査のスクリーニングプロジェクト
5000名以上の患者さんが参加


GI-SCREEN-Japan

GI-SCREEN-Japanと
α



A



• 登録から結果到着までの期間
β

 $




B



GOZILAC

2018年1⽉に開始したctDNAパネル検査のスクリーニングプロジェクト
63000名以上の患者さんが参加• 治験に登録された患者さんの割合• 治験治療の効果

γ%"#&GOZILAで以下の項⽬を⽐較

対象（~2019年8⽉）
GI-SCREEN︓5743名
GOZILA︓1787名

QNS
.1%

TurnaroundTimeb
GI-SCREEN(tissue)n = 5,621cMedian19 daysMedian14 daysOthe
P < 0.0001

GOZILAMedian(ctDNA) 4 daysn = 1,687
0

7

P < 0.0001

Median
7 days5

Interval between enrollment and sample reception
Time from receiving samples to reporting results

10

15
20
Time (days)

e

25

30

35

Nakamura Y, et al. Nat Med 2020.

Proportion of Actionable Alterationc

GI-SCREEN(tissue)n = 5,621

GOZILA(ctDNA)n = 1,687

Level 1 (2.9%)
Level 2 (3.1%)
Other (45.7%)
0.0001

Level 3a (0.04%)

ctDNA not Level 1 (4.0%)
Level 2 (3.9%)
detected (8.8%)
Level 3a (0.06%)
ctDNA fraction<3× LoD(12.3%)

eptionsults
Level 3b (48.3%)
Level 1~3b: 54.3%
8

ctDNA fraction
Level 3b (49.3%)≥3× LoD(21.8%)
Level 1~3b: 57.2%
Nakamura Y, et al. Nat Med 2020.

GI-SCREEN(tissue)n = 5,621

GOZILA(ctDNA)n = 1,687

0

5

10

15
20
Time (days)

Clinical Trial Enrollment Rate
60/632 (9.5%)

9
8
7
6
5
4

126/3,055 (4.1%)

3
2
1
0

GI-SCREEN(tissue)

GOZILA(ctDNA)

160
140

30

Total
Tissue on

120
100
80
60
40
20
0
Feb 15
Apr 15
Jun 15
Aug 15
Oct 15

Patients enrolled in a trial (%)

10

9

e

P < 0.0001

Number of patients enrolled in a triald25

Nakamura Y, et al. Nat Med 2020.

Interval between Screening and Trial Enrollment

10

Nakamura Y, et al. Nat Med 2020.

P = 0.69

10
8
6
4
2
0

Objective response rate (%)

21/126 (16.7%)
21/126 (16.7%)

18
16
14
12
10

8
6
4
2
0
GI-SCREEN
GOZILA
GI-SCREEN(tissue)(ctDNA)(tissue)N

Apr 18Jun 18Aug 18
Oct 18Dec 18
Feb 19Apr 19g

g

P = 0.69
12/60 (20.0%)

18

Date

Date

12/60 (20.0%)

20

12

GOZILA(ctDNA)GOZILA(ctDNA)

0

80
60
40
20
0

GOZILA(ctDNA)100

100

Progression-free survival (%)

GI-SCREEN

GI-SCREEN(tissue)(tissue)

20

14

0

Efficacy of Clinical Trials
0

f

16

20

Feb 15
Apr 15
Jun 15
Aug 15
Oct 15Dec
1515
Feb
Feb 16
Apr 15
Apr 16
Jun 15
Jun 16
Aug
Aug
1615
Oct
Oct
1615
Dec
Dec
1615
Feb
Feb
1716
Apr
Apr
1716
Jun
Jun
1716
Aug
1716
Aug
Oct
1716
Oct
Dec
1716
Dec
Feb
1817
Feb
Apr
1817
Apr
Jun 18Jun 17
Aug 18Aug 17
Oct 18
Oct
Dec
1817
Dec
Feb
1917
Feb
Apr
1918

0

Num

1

1

Progression-free survival (%)

20Median PFSn
(months)n

80

GI-SCREEN
GOZILA

60

GI-SCREEN
126
2.8 12660
GOZILA 2.4

60

MedianHR PFS(months)(95%
CI)

P (95% CI)

HR

2.8
1.07
(0.77–1.47)
2.4

0.70

1.07
(0.77–1.47

40
20
0
3

0

6

3

9

6

Time (months)

12

9

15

Time (months)

12

18

15

genotyping versus tissue genotyping in screening for targeted therapy trials. a, Sequencing success rates for tissue anDNAtissuegenotyping
in screening
for targeted
trials.
Sequencing
successratNakamuraY, et al. Nat
Med 2020.
ty 11
not genotyping
sufficient. b, versus
Turnaroundtime
for both genotyping
studies.
Two-sidedtherapy
P!value isbaseda,on
the Mann–WhitneytesctDNA解析の利点
p Turnaround timeが短く患者の治療適応の判断が速やかに可能

p Heterogeneityを評価することが可能

12

Heterogeneity by ctDNA Analysis

13

Nakamura Y, et al. Nat Rev Clin Oncol 2021.

Clonal Evolution Captured by ctDNA Analysis
Mutated alleles (%) or
CEA (ng/ml)

160
140
120

8

100

6

80
60

4

40

2

20
Baseline

1st CT scan
Irinotecan+Cetux

25-JUN-2009

1.0
0.8

alleles (%)

180

0.6

1st-line PD

Baselinere-challenge
Tomox

1st CT scan

2nd-line PD

0

Cetux

30-SEP-2009
16-FEB-2010 27-DEC-2010 3-MAR-2011
14-JUL-2011
CT scan: PR Last administration of
CT scan: PR Last administration
anti-EGFR retreatmentof anti-EGFR

Tumor load
KRAS p.G12V
KRAS p.G13D
CEA

120
100
80
60

Tumor load (% oor CEA (n

14

10

0

b

acid,
inic
,

Tumor load
KRAS p.G12V
CEA

12

Tumor load (% of baseline)

ile
cs
es
CGach
ars
red
ed
ated
nt
es
ed
utationatingstars
ed bluemab;aSiravegna G, et al. Nat Med 2015.

GOZILA IITs
Nationwide Genome
Screening Project

臓器縦断的なアプローチ

SCRUM-Japan GI-SCREEN

⼤腸がん
⼤腸がん以外の消化器がん
消化器がん以外の固形がん

ctDNA解析(Guardant360)

臓器横断的
アプローチ
ctDNA解析(Guardant360)

全固形がん
15

NEW!!

HER2 amplification

Trastuzumab + Pertuzumab(TRIUMPH)

BRAF V600E MT

Eribulin (BRAVERY)

BRAF non-V600E MT

Encorafenib + Binimetinib+ Cetuximab(BIG BANG)

MET amplification

Cabozantinib + Panitumumab(METBEIGE)

RAS WT

Re-challenge with anti-EGFR
mAb (PURSUIT)HER2 amplification

DS-8201a (HERB)bTMB-High

Nivolumab (bTMB-H basket)

Any FGFR alteration

TAS-120 (TiFFFANY)HER2 amplification

DS-8201a (HERALD)ROS1 fusion

Brigatinib (Barossa)

BRCA mutation

Niraparib (NIR-B)

NFE2L2 mutation

Sapanisertib

MONSTAR-SCREENF1L CDx

Systemic therapy

Solid tumors
Microbiome

Assess temporal changes in cancer biomarkers thorough systemic therapy
Next stage MONSTAR-SCREEN will be launched soon with whole-exome
transcriptome analysis of circulating tumor nucleic acids
16

Tissue/ctDNA Genotyping
31%

44%

Head and neck cancer Gastrointestinal cancer

33%

Genitourinary cancer

21%

Melanoma

31%
35%

13.5
%

BC

F1L Only
F1L+F1T

Hepatobiliaryand Pancreatic Cancer

Breast cancer

Gynecologic cancer

F1Lで検出された変異全体の21%〜44%がF1Lのみでしか検出されなかった。
17

Ogata D, et al.; Yamanaka T, et al.; Watanabe K, et al.; Kadowaki S, et al.; Chiyoda T, et al.; Masuishi T, et al.; and Nonomua N, et al. JSMO 2021.

ctDNA解析の⽋点
p エビデンスが少ない
p ctDNAの滲出量が少ない症例では遺伝⼦異常の評価が困難
p Subclonal遺伝⼦異常の治療標的としての意義が不明
p クローン造⾎（Clonal hematopoiesis: CHIP）の区別が不可能

18

ctDNA解析の⽋点
p エビデンスが少ない
p ctDNAの滲出量が少ない症例では遺伝⼦異常の評価が困難
p Subclonal遺伝⼦異常の治療標的としての意義が不明
p クローン造⾎（Clonal hematopoiesis: CHIP）の区別が不可能

19

ctDNA解析の前向きエビデンス

20

Phase

Drug

ctDNA Assay

Cancer

Alteration

Trial

3

Alpelisib

Therascreen
PIK3CA RGQBreast cancer

PIK3CA mutation

SOLAR-1

3

Buparlisib

Inostics BEAMing

Breast cancer

PIK3CA mutation

BELLE-3

3

Osimertinib*

Cobas EGFR
Guardant360

Non-small-cell lung cancer

EGFR mutation

FLAURA,
AURA3

2

Pertuzumab +trastuzumab

Guardant360

Colorectal cancer

HER2 amplification

TRIUMPH2

Bemarituzumab

Not disclosed

Gastric cancer

FGFR2 amplification

FIGHT

2

Tepotinib

Guardant360

Non-small-cell lung cancer

MET ex14 skipping

VISION

2

Rucaparib*

F1L CDx

Prostate cancer

BRCA1/2 alteration

TRITON2*検体採取は前向き、解析は後ろ向き

Prospective Evidence of ctDNA Analysis
Key eligibility criterial Metastatic CRC
l ECOG PS of 0 or 1l Refractory or intolerant to standard therapy that
included anti-EGFR monoclonal antibodyl RAS wild-type by tissue analysis
l HER2 positive by tissue analysis: IHC 3+ or FISH
positive (HER2/CEP17 ratio ≥ 2.0)
or
ERBB2-amplified and RAS wild-type identified by
ctDNA analysis (NGS-based assay, Guardant360)

Meet
eligibility
criteria

Trastuzumab
8 mg/kg load then 6 mg/kg+
Pertuzumab
840 mg load then 420 mg
Q3W until PD

Primary endpoint:l Confirmed objective response rate (ORR) in ERBB2 amp group confirmed by tissue analysis
l Confirmed ORR in ERBB2 amp group confirmed by ctDNA analysis
Sample size and statistical plan: 25 with one-sided 𝛼 = 2.5%, 𝛽 = 10%, H0 = 5% ORR, and H1 = 30% ORR
for each tissue and ctDNA positive group, ≥ 5 responses needed to reject H0.
21

Nakamura Y, et al. ESMO 2019.

Prospective Evidence of ctDNA Analysis

22

ORR N (% [95% CI])DCR N (% [95% CI])

Tissue positive group (N = 17)All

6 (35.3 [14.2-61.7])

11 (64.7 [38.3-85.8])

Tumor site
Right-sided (N = 1)
Left-sided (N = 16)

1 (100.0 [2.5-100.0])
5 (31.3 [11.0-58.7])

1 (100.0 [2.5-100])
10 (62.5 [35.4-84.8])

ctDNA RAS/BRAF/PIK3CA/ERBB2*WT (N = 11)
MT (N = 5)

6 (54.5 [23.4-83.3])
0 (0.0 [0.0-52.2])

10 (90.9 [58.7-99.8])
0 (0.0 [0-52.2])

ctDNA positive group (N = 15)All

5 (33.3 [11.8-61.6])

9 (60.0 [32.3-83.7])

Tumor site
Right-sided (N = 2)
Left-sided (N = 13)

1 (50.0 [13.0-98.7])
4 (30.8 [9.1-68.4])

1 (50.0 [1.3-98.7])
8 (61.5 [31.6-86.1])

ctDNA RAS/BRAF/PIK3CA/ERBB2
WT (N = 11)
MT (N = 4)

5 (45.5 [16.7-76.6])
0 (0.0 [0.0-60.2])

9 (81.8 [48.2-97.7])
0 (0.0 [0.0-60.2])
Nakamura Y, et al. ESMO 2019.

Prospective Evidence of ctDNA Analysis
Tepotinib for MET+ NSCLC

Bemarituzumab for FGFR2+ gastric cancer

23

Paik PK, et al. N Engl J Med 2020.
Catenacci D, et al. ASCO 2021.

ctDNA解析の⽋点
p エビデンスが少ない
p ctDNAの滲出量が少ない症例では遺伝⼦異常の評価が困難
p Subclonal遺伝⼦異常の治療標的としての意義が不明
p クローン造⾎（Clonal hematopoiesis: CHIP）の区別が不可能

24

ctDNA滲出に影響を与えうる因⼦
p 採⾎⼿順p 患者因⼦ー⽇内変動、喫煙、妊娠、運動、合併症（炎症性疾患、貧⾎、⼼疾患、代謝性疾患、⾃⼰免疫性疾患など）、輸⾎、⾻髄移植、臓器移植

p 腫瘍因⼦ーがん種、腫瘍量、転移臓器個数、転移臓器部位など

25

Nakamura Y, et al. ESMO Open 2020.

ctDNA Level across Cancer Types
Figure 1. Maximum MAF Distribution by Cancer Type26

G360CDx Technical Information

ctDNA解析の⽋点
p エビデンスが少ない
p ctDNAの滲出量が少ない症例では遺伝⼦異常の評価が困難
p Subclonal遺伝⼦異常の治療標的としての意義が不明
p クローン造⾎（Clonal hematopoiesis: CHIP）の区別が不可能

27

腫瘍組織解析とctDNA解析の使い分け（私⾒）
がん種

ctDNA滲出量が少ない（脳腫瘍、腎細胞がん、悪性⿊⾊腫、etc.）

ctDNA滲出量が多い（消化器がん、乳がん、膀胱がん、etc. ）組織が⼊⼿しにくい、古い（胆道がん、膵がん、前⽴腺がんetc. ）

腫瘍量

腫瘍量が少ない、肺転移単独

腫瘍量が多い、肝転移

治療ライン

治療中、病勢がstable

1st line前、治療変更時、標的治療後、腫瘍組織に治療修飾が⼊っている

バイオマーカー TMB-H、LOHを期待、Tissueベースの治験
腫瘍組織解析Favor
ü 豊富なエビデンス
ü 腫瘍量と関係なく評価可能
ü Clonalな遺伝⼦異常のみ評価
ü CHIPの懸念が少ない
28

ctDNA解析Favor
ü TATが短い
ü Heterogeneityを評価可能

Patient JourneyにおけるctDNA NGS

早期発⾒ü 症状出現前のスクリーニング29

予後予測

残存腫瘍の検出 治療モニタリング
ü MRD確認による再発リスク評価薬剤選択ü 遺伝⼦異常に応じた標的治療の選択Wan JCM, et al. Nat Rev Cancer 2017.

Assessment of MRD by ctDNA Analysis
Tumor DNA
Detection

Curative
Intent Treatment(e.g. primary removal)

30

Normal DNA

Minimal Residual
Disease (MRD)=
Recurrence ++No MRD=
Low Recurrence

Yoshino T, et al. ESMO2019.

ent in both the primary tumor and the metastatic recurrence in this pactDNA-negative blood sample
tient. dPCR demonstrated that
the RB1 mutation was a late event, only first
ctDNA-positive blood sample
Radiologic
relapsedetectable in a plasma sample
taken
16.1 months after surgery, then
ACT
No
ctDNAindetected
at serial
MRD
landmark
expandingfrequency on
sampling
at relapse (Fig. 7C). This sugChemotherapy
Surgicalintervention
B Day 30ctDNA
recurrence
gests thatgenetic
diversity
develops
in(CAPP-seq)
expanding micrometastatic disdetectedat MRDlandmark
LungcancerClinical follow-up
ease before relapse and that mutation tracking may have the potential to130
100
A 1.00identify MRD at a point
before genetic diversity develops. Pre-op. ctDNA Status

Post-operative ctDNA and Recurrencen = 291.0

100

P = 0.35

Not detected

0

6

0.8

12
18
24
Months post-surgery

30

36

ctDNA negative (day 30)

Freedom fromprogression (%)

0

Recurrence-Free Survival

500

80

Early-relapse

Disease-free

62
33

80

Negative
Borderline & positive
Censored
Censored

Recurrence

Patient No.

Fraction recurrence-freeFig. 3. Early relapse is not predicted by analysis of baseline ctDNA. 30
(A)
60
60
Disease-freesurvival according to the detection of ctDNA in the baseline
P < 0.001
P < 0.001
DISCUSSION
0.6
119
plasma sample. P value determined by log-rank test. (B) Mutant copies per
0.50
Here, we show that ctDNA
mutation tracking can detect MRD non124
40
40
milliliter of plasma at baseline in patients
who(HR, 7.2; 95%
CI,relapsed
2.7-19.0; P early< .001)and who did
0.4
invasively and identify earlier which patients are at risk of cancer re85
not relapse during follow-up. P value determined by Mann-Whitney U test.
20 pipeline that uses
currence. We devised an
assay
baseline
19 mos (95%
CI 12–27) vs. 8 primarymos (95% CI 6–10)
Data in (A) and (B) are from the same n = 4220
patients. ctDNA associations
82
0.25
P < 0.001
0.2
with other clinicopathological characteristics are in table S2.
tumor mutations to develop personalized dPCR assays to track
79
0.75

ctDNA positive (day 30)

0

0

0

12

A

No. at risk
Negative 84
Positive 10

24Time Since Surgery, mo
Neoadjuvant
Chemotheraphy

Post-surgery
78
9

0
S
u
r
g
e
r
y

6

0

104

12

18

35.5

0

24

30

Time from landmark
(mo)
B

36
12

13

B
1
Breast cancer (ddPCR)

Standard follow-up

9
1

0

24

Time Since Surgery, mo

Mutation tracking
Reinert T, et al. JAMA Oncol 2019.
PostSurgery

0

0.00

6
6

30
29

12

36.0 18

18

24
24

26
21

30

Time from landmark (mo)Recurrence-free survival (months)

No at. risk
Neoadjuvant
Chemotheraphy

12

S
u
r
g
e
r
y

PostSurgery

18
6

10
1

C

B

36

1.0

Likelihood of detecting
ctDNA at MRD landmark

Day 30 RFS
Colorectal
cancer (Signatera)
50

Fraction alive

1000

RecurrencefreeAn = 13

P = 0.067

Disease-specificsurvival (%)

Mutant copies/ml

Disease-free survival

1500

ctDNA not detected100

A

ciencemag.org/ at NATIONAL CANCER CENTER on February 3, 2021

RESEARCH BRIEF
ctDNA detected

1.00

0.75

0.5

0.50

0.25

0.0

0.00
0

12

CAPP
seq

Overall survival (monNo at. risk

Chaudhuri
AA, et al. Cancer
2017.
4
30 Discov
23Standard follow-up

0

Pancreatic cancer (ddPCR)

29

19

Fraction alive

Fraction recurrence-freeDisease-free survival

Recurrence-Free Survival

Disease-free survival

Recurrence-Free Survival

tDNA MRD detected

D
C
LUP236
1.00
1.00
Death
100
Post-op.
ctDNA
StatusD Longitudinal RFS
n = 30
LUP280ctDNA detected
Negative
Borderline & positive
Alive at last follow-upCensored
ctDNA negative (longitudinal)
LUP397
ctDNA not detected
1.0
1.0
Censored
ctDNA negative (after ACT)ctDNA detected
0.75
0.75
Progression
LUP284not detected
LUP248n = 30
15 mos (95% CI 8–22) vs. 5 mos (95% CI 3–8)
NoctDNA
progression
0.8
0.8
P < 0.001
50
50
LUP117(HR, 0.50
43.5; 95% CI, 9.8-193.5; P < .001)
0.50
LUP235n = 130.6
0.6
LUP020
P < 0.0001
n=7
P < 0.0001
0.25
0.25
ctDNA positive
HR,25.1(CI,
4.08-130.5)
HR,(longitudinal)
12.0 (CI, 3.36-43.07)
LUP2410.4
0.4
00
LUP0140
6
1224CI, 5.4-56.5;
30 P < .001)
36
0
6
12
18
24
30
36
(HR,1817.5; 95%
0.00
0.00
LUP2830.2
0.2
Months post-surgery
Months post-surgery
6
12
0
18
24
12
0
LUP240 I, et al. Sci Transl Med 2015.
31
Recurrence-free survival (months)
Overallsurvival (mGarcia-Murillas
Groot
VP,
et
al.
Clin
CancerRes
2019.
Fig. 4. Mutation tracking in serial
plasmasamplespredicts
earlyDisease-freesurvivalaccordingtothedetection
of
ctDNA
in
serialfollowctDNA positive (after ACT)100
C Post-ACT RFS

CIRCULATE-Japan Project Since May 2020
ctDNA negative
ctDNA positive

N=2500Stock Pre-Op
Samples

R0/1
resection
cStage II/III
colon
cancercStage II/III
rectalcancerResectable
M1

WES

Post-Ope
ctDNA
Negative

N=1240 Experimental arm

No chemo

Control arm
CAPOX 3 months

1 mo

Post-Ope
ctDNA
Positive

32

VEGA
trial

ALTAIR

3 mo

N=240

CAPOX
4 cycles
ALTAIR

ctDNA monitoring

F/U
for 7
years

ALTAIRR

R

GALAXYstudy

Up to 24 moExperimental arm
FTD/TPI
6 cyclesControl arm
Placebo
6 cycles

F/U
for 5
years

ALTAIRtrial

In case of performed NAC

Yukami H, et al. ESMO-GI 2020.

5CORNGEQNNGEVKQPCPFGZVTCEVKQPOGVJ[NCVKQPRTQȮNKPI

Liquid Biopsy Early Cancer Detection
Conceptually, the sensitivity of any cfDNA approach depends on thenumber of alterations examined as well as the technical and biologicallimitations of detecting such changes. As a typical blood sample con/GVJ[NCVKQPRTQȮNGtains approximately 2,000 genome equivalents of cfDNA per millilitreof Methylome
plasmacfDNA
Plasmaofplasma5, the theoretical limit of detectionof a single
alteration can
be no better than one in a few thousand mutant to wild-type molecules. We hypothesized that the detection of a larger number of alterations in the genome may be more sensitive for detecting cancer in

cfMeDIP-seq

Fragmentome

AGTCAG Noninvasive cancer screening (DELFI)

Urine

White-blood-cell-derived cfDNA
r Healthy

in the blood provides a non-invasive diagnostic
ents with cancer1. However, characteristics ofmolecular features of cell-free DNA are poorly
Here we developed an approach to evaluate
Genomepatterns of cell-free DNA
across the genome, andiles of healthy individuals reflected nucleosomal
te blood cells, whereas patients with cancer had
ntation profiles. We used this method to analyseon profiles of 236 patients with breast, colorectal,
pancreatic, gastric or bile duct cancer and 245
uals. A machine learning model that incorporated
agmentation features had sensitivities of detection% to more than 99% among the seven cancer types
ty, with an overall area
under the curve value ofProteome
ation profiles could be used to identify the tissue
cancers to a limited number of sites in 75% ofng our approach with mutation-based cell-freedetected 91% of patients with cancer. The resultss highlight important properties of cell-free DNA
roof-of-principle approach for the screening, early
onitoring of human cancer.
morbidity and mortality of human cancers worldm late diagnosis when therapeutic intervention is lessortunately, clinically proven biomarkers that can be
diagnose and treat patients are not widely availa33
yses
of circulating cell-free DNA (cfDNA) suggest

Tumour-derived cfDNA

COSMOS Project

Liver

Pre-op phase34

Pancreas

Surgery

Colorectum

StomachGIST
Post-op phase

MelanomaSummaryp ctDNA解析はがんゲノム医療において従来の組織ベースの遺伝⼦パネル
検査を上回る有⽤性が⽰唆されており、進⾏⼤腸がんにおいてはがんゲノ
ムプロファイリングやclonal evolutionの評価としての使⽤が増えてくることが予想される。
p さらに、ctDNA解析は腫瘍が無い状況のMRDや早期がんの同定に役⽴つ可能性があり、あらゆるがん種・あらゆるステージでの応⽤が期待されている。
35

Acknowledgement
Patients and families
SCRUM-Japan MONSTAR SCREEN
National Cancer Center Hospital East (NCCHE)• A Ohtsu (Director of hospital)• Dpt. of Gastrointestinal Oncology
NCCHE TR Support Section• Izumi Miki
• Yasutoshi Sakamoto• Hiroko Ichiki• Masayuki Hata
• Kana Kitajima• Naomi Kuramoto• Hiroki Sokuoka• Hiroshi Uchigata• Satoshi Horasawa• Mihoko Yuasa• Tamami Nakamura

36

NCCHE Division of Clinical Research Support• Makoto Fukui• Miki Fukutani• Seiko Matsuda• Shogo Nomura• Akihiro Sato

Thank You For Kind Attention!!

yoshinak@east.ncc.go.jp37