Improved LOD Increases Detection of Clonal Hematopoiesis Variants• NEJM 2014 study (Genovese 2014) identified 217 unique candidate drivers in WES.

- Disruptive (nonsense, frameshift, splice-site) mutations in DNMT3A, TET2, ASXL1 and PPM1D; missense in DNMT3A. - Recurrent (≥ 7 patients) in hematopoietic and lymphoid cancers in COSMIC.

• 212 of 217 previously identified drivers are covered by cfDNA panel.• 37 unique drivers (77 events) were detected in quality filtered WBC variants (total = 1072) among 198 subjects.

Blood(Streck BCT)

Plasma/Buffy CoatSeparation

Optimized single-tube library prepUnique Molecular Identifiers for error suppression

Error suppressionVariant callingAnnotationFiltering

508-gene cancer panel (2.1 Mb)

>60,000x raw target coverage for both cfDNA and gDNA

High-intensity Sequencing

DNA Extraction Library Prep Target Capture Sequencing Analysis

cfDNA assayPlasma cfDNA

WBC gDNA

20

40

60

80

Healthy Breast Lung Prostate

Age

0

5

10

15

20

Healthy Breast Lung ProstateCohort

Num

ber o

f var

iant

s pe

r sub

ject

Unique Variants per GeneProportion of Subjects

with Variants

RANBP2DNMT3B

NF1EGFR

GRIN2ACBL

ASXL1FAT1

PTPRTATM

CHEK2TP53

PPM1DTET2

DNMT3A

0.0 0.2 0.4 0.6RANBP2DNMT3B

NF1EGFR

GRIN2ACBL

ASXL1FAT1

PTPRTATM

CHEK2TP53

PPM1DTET2

DNMT3A

0.0 0.2 0.4 0.6RANBP2DNMT3B

NF1EGFR

GRIN2ACBL

ASXL1FAT1

PTPRTATM

CHEK2TP53

PPM1DTET2

DNMT3A

0.0 0.2 0.4 0.6

N 47 48 49 54Cohort

Variants per Gene

TotalPercent in Top 15

1072 99649% 46%

Total VariantsNumber of Subjects

683 195114 37

19447

Cancer: Prior Therapy Cancer: No Prior Therapy Healthy

Previously Implicated Genes

DNMT3BGRIN2A

EGFRCBL

FAT1NF1

ASXL1KMT2CPTPRT

ATMCHEK2

TP53PPM1D

TET2DNMT3A

0 50 100 150 200DNMT3BGRIN2A

EGFRCBL

FAT1NF1

ASXL1KMT2CPTPRT

ATMCHEK2

TP53PPM1D

TET2DNMT3A

0 50 100 150 200DNMT3BGRIN2A

EGFRCBL

FAT1NF1

ASXL1KMT2CPTPRT

ATMCHEK2

TP53PPM1D

TET2DNMT3A

0.0 0.2 0.4

0

2

4

6

8

DN

MT3

A R

882C

DN

MT3

A R

882H

DN

MT3

A R

736H

DN

MT3

A W

860R

DN

MT3

A Y

735C

DN

MT3

A F

755S

DN

MT3

A P

904L

PP

M1D

R57

2*JA

K2

V61

7FD

NM

T3A

R32

6CD

NM

T3A

R73

6CD

NM

T3A

R77

1*D

NM

T3A

V65

7MA

SX

L1 R

634f

sA

SX

L1 Y

591f

sC

BL

R42

0QD

NM

T3A

G54

3CD

NM

T3A

G55

0RD

NM

T3A

I780

TD

NM

T3A

L34

4PD

NM

T3A

M76

1VD

NM

T3A

M88

0VD

NM

T3A

P77

7RD

NM

T3A

Q81

6*D

NM

T3A

R32

0*D

NM

T3A

R59

8*D

NM

T3A

R68

8HD

NM

T3A

R72

9WD

NM

T3A

R79

2HD

NM

T3A

W30

6*D

NM

T3A

W79

5RP

PM

1D C

478f

sP

PM

1D R

458*

SF3

B1

E62

2DS

F3B

1 K

700E

TET2

R55

0*TP

53 R

248Q

# of

Sub

ject

s w

ith D

river

s

ASXL1CBLDNMT3AJAK2PPM1DSF3B1TET2TP53

0

10

20

30

40

50

<50 >50 and <60 >60 and <70 >70

% o

f Sub

ject

s w

ith D

river

s

Drivers inNEJM, at least 10%GRAIL, at least 10%GRAIL, at least 1%GRAIL, at least 0.1%

Pro

porti

on o

f Sub

ject

s w

ith V

aria

nts

20

40

60

80

Healthy Breast Lung Prostate

Age

0

5

10

15

20

Healthy Breast Lung ProstateCohort

Num

ber o

f var

iant

s pe

r sub

ject

Unique Variants per GeneProportion of Subjects

with Variants

RANBP2DNMT3B

NF1EGFR

GRIN2ACBL

ASXL1FAT1

PTPRTATM

CHEK2TP53

PPM1DTET2

DNMT3A

0.0 0.2 0.4 0.6RANBP2DNMT3B

NF1EGFR

GRIN2ACBL

ASXL1FAT1

PTPRTATM

CHEK2TP53

PPM1DTET2

DNMT3A

0.0 0.2 0.4 0.6RANBP2DNMT3B

NF1EGFR

GRIN2ACBL

ASXL1FAT1

PTPRTATM

CHEK2TP53

PPM1DTET2

DNMT3A

0.0 0.2 0.4 0.6

N 47 48 49 54Cohort

Variants per Gene

TotalPercent in Top 15

1072 99649% 46%

Total VariantsNumber of Subjects

683 195114 37

19447

Cancer: Prior Therapy Cancer: No Prior Therapy Healthy

Previously Implicated Genes

DNMT3BGRIN2A

EGFRCBL

FAT1NF1

ASXL1KMT2CPTPRT

ATMCHEK2

TP53PPM1D

TET2DNMT3A

0 50 100 150 200DNMT3BGRIN2A

EGFRCBL

FAT1NF1

ASXL1KMT2CPTPRT

ATMCHEK2

TP53PPM1D

TET2DNMT3A

0 50 100 150 200DNMT3BGRIN2A

EGFRCBL

FAT1NF1

ASXL1KMT2CPTPRT

ATMCHEK2

TP53PPM1D

TET2DNMT3A

0.0 0.2 0.4

0

2

4

6

8

DN

MT3

A R

882C

DN

MT3

A R

882H

DN

MT3

A R

736H

DN

MT3

A W

860R

DN

MT3

A Y

735C

DN

MT3

A F

755S

DN

MT3

A P

904L

PP

M1D

R57

2*JA

K2

V61

7FD

NM

T3A

R32

6CD

NM

T3A

R73

6CD

NM

T3A

R77

1*D

NM

T3A

V65

7MA

SX

L1 R

634f

sA

SX

L1 Y

591f

sC

BL

R42

0QD

NM

T3A

G54

3CD

NM

T3A

G55

0RD

NM

T3A

I780

TD

NM

T3A

L34

4PD

NM

T3A

M76

1VD

NM

T3A

M88

0VD

NM

T3A

P77

7RD

NM

T3A

Q81

6*D

NM

T3A

R32

0*D

NM

T3A

R59

8*D

NM

T3A

R68

8HD

NM

T3A

R72

9WD

NM

T3A

R79

2HD

NM

T3A

W30

6*D

NM

T3A

W79

5RP

PM

1D C

478f

sP

PM

1D R

458*

SF3

B1

E62

2DS

F3B

1 K

700E

TET2

R55

0*TP

53 R

248Q

# of

Sub

ject

s w

ith D

river

s

ASXL1CBLDNMT3AJAK2PPM1DSF3B1TET2TP53

0

10

20

30

40

50

<50 >50 and <60 >60 and <70 >70

% o

f Sub

ject

s w

ith D

river

s

Drivers inNEJM, at least 10%GRAIL, at least 10%GRAIL, at least 1%GRAIL, at least 0.1%

Pro

porti

on o

f Sub

ject

s w

ith V

aria

nts

Many cell-free DNA (cfDNA) mutations are derived from clonal hematopoiesis: Implications for interpretation of liquid biopsy tests Pedram Razavi1, Bob T. Li1, Chenlu Hou7, Ronglai Shen2, Oliver Venn7, Raymond S. Lim4, Earl Hubbell7, Ino De Bruijn4, Qinwen Liu7, Ravi Vijaya Satya7, Hui Xu7, Ling Shen7, Amy Sehnert7, Tara Maddala7, Michael F. Berger1, 4, 5, Alex Aravanis7, Jorge S. Reis-Filho4, Mark Lee7, Howard Scher1, 6, David B. Solit1, 3, 5, Jose Baselga1, 3

1. Department of Medicine, Memorial Sloan Kettering Cancer Center (MSKCC), 1275 York Avenue, New York, NY, USA. 2. Department of Epidemiology and Biostatistics, Memorial Sloan Kettering Cancer Center. 3. Human Oncology and Pathogenesis Program, Memorial Sloan Kettering Cancer Center. 4. Department of Pathology, Memorial Sloan Kettering Cancer Center. 5. Marie-Josée and Henry R. Kravis Center for Molecular Oncology, Memorial Sloan Kettering Cancer Center. 6. Genitourinary Oncology Service, Department of Medicine, Memorial Sloan Kettering Cancer Center. 7. GRAIL, Menlo Park, CA 94402 USA.

Background• A large fraction of cell-free DNA (cfDNA) fragments are

known to be derived from hematopoietic cells (Lui 2002).• Sequencing of genomic DNA (gDNA) from white blood

cells (WBC) in circulation has revealed an age-dependent presence of clones carrying somatic variants—a phenomenon now termed clonal hematopoiesis (Genovese 2014).

• Somatic alterations in cfDNA can be tumor-derived but also could represent somatic changes associated with clonal hematopoiesis.

• We applied a high-intensity sequencing approach (ultra-deep sequencing with broad genomic coverage) to characterize both cfDNA and WBC gDNA from cancer and non-cancer subjects.

Objective• To evaluate the contribution of clonal hematopoiesis to

the variants observed in cfDNA through high-intensity sequencing of both plasma cfDNA and matched WBC gDNA.

Methods: Patient PopulationsCancer Patient Population:• Metastatic breast, lung, or prostate cancer, either de novo

or with progressive disease on current therapy.• All patients have provided written informed consent to

an MSK institutional protocol (NCT01775072) allowing research of cfDNA and clinical tumor sequencing.

• Two tubes of blood collected in Streck Cell-Free DNA BCT.

Healthy Donor Population:• Enrolled through San Diego Blood Bank. • Self reported as non-smokers and cancer-free.• Two tubes of blood collected in Streck Cell-Free DNA BCT.

Methods: AnalysiscfDNA and WBC gDNA variant calling pipeline• The variant calling pipeline includes the following steps:

- Read alignment, error correction (consisting of read collapsing and stitching of mate pairs), de novo assembly, variant calling, and variant filtering.

- Variants are filtered using two approaches (1) heuristics applied based on the surrounding sequence context and type and quality of reads supporting the variant and (2) empirical noise levels observed in a set of healthy samples:

• Blood samples from an independent cohort of 24 non-cancer (self-reported) individuals (vendor sourced), were used for noise modeling for the 151 cancer patients in this study.

• The 47 healthy subjects were processed with a slightly different assay protocol and UMI set and therefore had 20 additional non-cancer subjects used to establish a noise model for that assay protocol.

- Variants are further filtered based on dbSNP presence and restricted to protein coding variants.

Quality filtering on cfDNA and WBC gDNA variant calls• Analyses focus on matched variants in cfDNA and WBC

gDNA meeting the following criteria: - Non-synonymous. - Allele frequency (AF) >= 0.1% and a minimum of 3 supporting reads.

- In order to exclude germline, AF < 15% in cfDNA. - In order to exclude germline, AF < 35% in WBC gDNA. - Indels not in homopolymer >= 3. - Variants must be found in <=10 samples to avoid recurrent artifacts.

- Unique coverage >=500 to exclude low coverage regions.

Statistical analysis of variants by age• A Poisson regression model was used for analysis of the

association between age, cohort, and mutation count (dependent variable).

Patient Disposition

Distribution of Age by CohortHealthy subjects and breast cancer patients tend to be younger than lung cancer and prostate cancer patients

WBC Variants Contain Previously Identified Drivers• Matched variants in cfDNA and WBC contain 77 driver variants (37 unique variants).

- Drivers supported by a median of 12 unique reads in WBC gDNA (3 - 533 ). - Drivers supported by a median of 18 unique reads in cfDNA (3 - 617).

Summary and Conclusions• This high-intensity sequencing approach applied

to both plasma cfDNA and WBC gDNA reveals that many cfDNA variants arise from clonal hematopoiesis:

- The most common variants matched between cfDNA and WBC gDNA are in genes previously implicated in clonal hematopoiesis, including DNMT3A, TET2, PPM1D, and TP53. - As with previous WBC gDNA sequencing studies, the number of cfDNA variants attributable to clonal hematopoiesis increases with age.

• The limit of detection of our sequencing approach suggests that clonal hematopoiesis variants may be present at low allele frequencies and possibly prevalent in more patients than previously reported. This hypothesis will require further evaluation.

• Accurate interpretation of cell-free DNA assays for detection of circulating tumor DNA must account for the confounding signals arising from clonal hematopoiesis, and may require deep sequencing of WBC gDNA (Abstract #11528, Poster #228, Razavi et al).

References

Lui, Y.Y., Chik, K.W., Chiu, R.W., Ho, C.Y., Lam, C.W., Lo, Y.M. (2002). Predominant hematopoietic origin of cell-free DNA in plasma and serum after sex-mismatched bone marrow transplantation. Clin Chem, 48, 421-7.

Genovese, G., Kahler, AK., Handsaker, R.E., Lindberg, J., Rose, S.A., Bakoum, S.F., Chambert, K., Mick, E., Neale, B.M, … McCarroll, S.A. (2014). Clonal Hematopoiesis and Blood-Cancer Risk Inferred from Blood DNA Sequence. NEnglJMed, 371, 2477-87. https://doi.org/10.1056/NEJMoa1409405

Matched Variants in cfDNA and WBC Are Associated with Age• Positive association with age: p-val <0.0001. • The association of number of matched variants with age does not appear to be different between healthy subjects and those with breast/lung/prostate

cancer in this cohort. Interaction of age with cancer not significant: p = 0.08.

Patient Characteristics

Sample Workflows and Assays

Patient Characteristics (Cancer Characteristics)

Analysis

EnrollmentAssigned pt ID (N = 282)

Breast80

Lung82

Prostate70

EligibleEligibleClinically Eligible and Lab Evaluable (N = 161)

NBreast

53

Lung

53

Prostate

55

EligibleClinically Eligible and Lab Evaluable (N = 211)

Breast53

Lung53

Prostate55

cfDNA Assay Evaluable (N = 198)

Breast48

Lung49

Prostate54

Excluded subjects (N = 71)

Clinical exclusion* Lab exclusions for insufficient sampleTissue or cfDNA assay unevaluable

Breast

27

Lung

29

Prostate

15

** Includes 2 pseudoprogressionsHealthy

50

Healthy50

Healthy

0

9 20* 7 010 8 0 08 1 8 0

Healthy47

cfDNA assay unevaluable (N = 13)Breast

5Lung

4Prostate

1Healthy

3

* Clinical exclusion includes new systemic therapy, disease progression not confirmed on review, etc)

Patient Characteristics Breast (n=48)

Lung (n=49)

Prostate (n=54)

Healthy (n=47)

Age at enrollment

Mean (SD) 57.0 (10.76) 66.1 (10.86) 67.6 (9.55) 57.8 (16.03)

Median 60 67 68 61

Range 30, 79 33, 86 46, 87 20, 78

Gender, N (%)

Female 48 (100.0%) 32 (65.3%) N/A 24 (51.1%)

# of lines of therapy, N (%)

0 22 (45.8%) 28 (57.1%) 18 (33.3%)

1 2 (4.2%) 12 (24.5%) 15 (27.8%)

2 5 (10.4%) 4 (8.2%) 9 (16.7%)

>=3 19 (39.6%) 5 (10.2%) 12 (22.2%)

Receptor Status, N (%)

HR+/HER2+ 3 (6.3%) N/A N/A

HR+/HER2- 34 (70.8%) N/A N/A

HR-/HER2+ 3 (6.3%) N/A N/A

Triple Negative 8 (16.7%) N/A N/A

Histology N (%)

Metastatic Breast Cancer (n=48)

Breast Invasive Ductal Carcinoma 40 (83.3%)

Breast Invasive Lobular Carcinoma 3 (6.3%)

Breast Mixed Ductal and Lobular Carcinoma 5 (10.4%)

Metastatic Lung Cancer (n=49)

Lung Adenocarcinoma 46 (93.9%)

Lung Non-adenocarcinoma 3 (6.1%)

Metastatic Prostate Cancer (n=54)

Prostate Adenocarcinoma 49 (90.7%)

Prostate Neuroendocrine 5 (9.3%)

20

40

60

80

Healthy Breast Lung Prostate

Age

0

5

10

15

20

Healthy Breast Lung ProstateCohort

Num

ber o

f var

iant

s pe

r sub

ject

Unique Variants per GeneProportion of Subjects

with Variants

RANBP2DNMT3B

NF1EGFR

GRIN2ACBL

ASXL1FAT1

PTPRTATM

CHEK2TP53

PPM1DTET2

DNMT3A

0.0 0.2 0.4 0.6RANBP2DNMT3B

NF1EGFR

GRIN2ACBL

ASXL1FAT1

PTPRTATM

CHEK2TP53

PPM1DTET2

DNMT3A

0.0 0.2 0.4 0.6RANBP2DNMT3B

NF1EGFR

GRIN2ACBL

ASXL1FAT1

PTPRTATM

CHEK2TP53

PPM1DTET2

DNMT3A

0.0 0.2 0.4 0.6

N 47 48 49 54Cohort

Variants per Gene

TotalPercent in Top 15

1072 99649% 46%

Total VariantsNumber of Subjects

683 195114 37

19447

Cancer: Prior Therapy Cancer: No Prior Therapy Healthy

Previously Implicated Genes

DNMT3BGRIN2A

EGFRCBL

FAT1NF1

ASXL1KMT2CPTPRT

ATMCHEK2

TP53PPM1D

TET2DNMT3A

0 50 100 150 200DNMT3BGRIN2A

EGFRCBL

FAT1NF1

ASXL1KMT2CPTPRT

ATMCHEK2

TP53PPM1D

TET2DNMT3A

0 50 100 150 200DNMT3BGRIN2A

EGFRCBL

FAT1NF1

ASXL1KMT2CPTPRT

ATMCHEK2

TP53PPM1D

TET2DNMT3A

0.0 0.2 0.4

0

2

4

6

8

DN

MT3

A R

882C

DN

MT3

A R

882H

DN

MT3

A R

736H

DN

MT3

A W

860R

DN

MT3

A Y

735C

DN

MT3

A F

755S

DN

MT3

A P

904L

PP

M1D

R57

2*JA

K2

V61

7FD

NM

T3A

R32

6CD

NM

T3A

R73

6CD

NM

T3A

R77

1*D

NM

T3A

V65

7MA

SX

L1 R

634f

sA

SX

L1 Y

591f

sC

BL

R42

0QD

NM

T3A

G54

3CD

NM

T3A

G55

0RD

NM

T3A

I780

TD

NM

T3A

L34

4PD

NM

T3A

M76

1VD

NM

T3A

M88

0VD

NM

T3A

P77

7RD

NM

T3A

Q81

6*D

NM

T3A

R32

0*D

NM

T3A

R59

8*D

NM

T3A

R68

8HD

NM

T3A

R72

9WD

NM

T3A

R79

2HD

NM

T3A

W30

6*D

NM

T3A

W79

5RP

PM

1D C

478f

sP

PM

1D R

458*

SF3

B1

E62

2DS

F3B

1 K

700E

TET2

R55

0*TP

53 R

248Q

# of

Sub

ject

s w

ith D

river

s

ASXL1CBLDNMT3AJAK2PPM1DSF3B1TET2TP53

0

10

20

30

40

50

<50 >50 and <60 >60 and <70 >70

% o

f Sub

ject

s w

ith D

river

s

Drivers inNEJM, at least 10%GRAIL, at least 10%GRAIL, at least 1%GRAIL, at least 0.1%

Pro

porti

on o

f Sub

ject

s w

ith V

aria

nts

Matched Variants in cfDNA and WBC Per Subject(after Quality Filter)

20

40

60

80

Healthy Breast Lung Prostate

Age

0

5

10

15

20

Healthy Breast Lung ProstateCohort

Num

ber o

f var

iant

s pe

r sub

ject

Unique Variants per GeneProportion of Subjects

with Variants

RANBP2DNMT3B

NF1EGFR

GRIN2ACBL

ASXL1FAT1

PTPRTATM

CHEK2TP53

PPM1DTET2

DNMT3A

0.0 0.2 0.4 0.6RANBP2DNMT3B

NF1EGFR

GRIN2ACBL

ASXL1FAT1

PTPRTATM

CHEK2TP53

PPM1DTET2

DNMT3A

0.0 0.2 0.4 0.6RANBP2DNMT3B

NF1EGFR

GRIN2ACBL

ASXL1FAT1

PTPRTATM

CHEK2TP53

PPM1DTET2

DNMT3A

0.0 0.2 0.4 0.6

N 47 48 49 54Cohort

Variants per Gene

TotalPercent in Top 15

1072 99649% 46%

Total VariantsNumber of Subjects

683 195114 37

19447

Cancer: Prior Therapy Cancer: No Prior Therapy Healthy

Previously Implicated Genes

DNMT3BGRIN2A

EGFRCBL

FAT1NF1

ASXL1KMT2CPTPRT

ATMCHEK2

TP53PPM1D

TET2DNMT3A

0 50 100 150 200DNMT3BGRIN2A

EGFRCBL

FAT1NF1

ASXL1KMT2CPTPRT

ATMCHEK2

TP53PPM1D

TET2DNMT3A

0 50 100 150 200DNMT3BGRIN2A

EGFRCBL

FAT1NF1

ASXL1KMT2CPTPRT

ATMCHEK2

TP53PPM1D

TET2DNMT3A

0.0 0.2 0.4

0

2

4

6

8

DN

MT3

A R

882C

DN

MT3

A R

882H

DN

MT3

A R

736H

DN

MT3

A W

860R

DN

MT3

A Y

735C

DN

MT3

A F

755S

DN

MT3

A P

904L

PP

M1D

R57

2*JA

K2

V61

7FD

NM

T3A

R32

6CD

NM

T3A

R73

6CD

NM

T3A

R77

1*D

NM

T3A

V65

7MA

SX

L1 R

634f

sA

SX

L1 Y

591f

sC

BL

R42

0QD

NM

T3A

G54

3CD

NM

T3A

G55

0RD

NM

T3A

I780

TD

NM

T3A

L34

4PD

NM

T3A

M76

1VD

NM

T3A

M88

0VD

NM

T3A

P77

7RD

NM

T3A

Q81

6*D

NM

T3A

R32

0*D

NM

T3A

R59

8*D

NM

T3A

R68

8HD

NM

T3A

R72

9WD

NM

T3A

R79

2HD

NM

T3A

W30

6*D

NM

T3A

W79

5RP

PM

1D C

478f

sP

PM

1D R

458*

SF3

B1

E62

2DS

F3B

1 K

700E

TET2

R55

0*TP

53 R

248Q

# of

Sub

ject

s w

ith D

river

s

ASXL1CBLDNMT3AJAK2PPM1DSF3B1TET2TP53

0

10

20

30

40

50

<50 >50 and <60 >60 and <70 >70

% o

f Sub

ject

s w

ith D

river

s

Drivers inNEJM, at least 10%GRAIL, at least 10%GRAIL, at least 1%GRAIL, at least 0.1%

Pro

porti

on o

f Sub

ject

s w

ith V

aria

nts

DNMT3A and TET2 Variants are Most Common in Both Healthy Subjects and Cancer Patients

20

40

60

80

Healthy Breast Lung Prostate

Age

0

5

10

15

20

Healthy Breast Lung ProstateCohort

Num

ber o

f var

iant

s pe

r sub

ject

Unique Variants per GeneProportion of Subjects

with Variants

RANBP2DNMT3B

NF1EGFR

GRIN2ACBL

ASXL1FAT1

PTPRTATM

CHEK2TP53

PPM1DTET2

DNMT3A

0.0 0.2 0.4 0.6RANBP2DNMT3B

NF1EGFR

GRIN2ACBL

ASXL1FAT1

PTPRTATM

CHEK2TP53

PPM1DTET2

DNMT3A

0.0 0.2 0.4 0.6RANBP2DNMT3B

NF1EGFR

GRIN2ACBL

ASXL1FAT1

PTPRTATM

CHEK2TP53

PPM1DTET2

DNMT3A

0.0 0.2 0.4 0.6

N 47 48 49 54Cohort

Variants per Gene

TotalPercent in Top 15

1072 99649% 46%

Total VariantsNumber of Subjects

683 195114 37

19447

Cancer: Prior Therapy Cancer: No Prior Therapy Healthy

Previously Implicated Genes

DNMT3BGRIN2A

EGFRCBL

FAT1NF1

ASXL1KMT2CPTPRT

ATMCHEK2

TP53PPM1D

TET2DNMT3A

0 50 100 150 200DNMT3BGRIN2A

EGFRCBL

FAT1NF1

ASXL1KMT2CPTPRT

ATMCHEK2

TP53PPM1D

TET2DNMT3A

0 50 100 150 200DNMT3BGRIN2A

EGFRCBL

FAT1NF1

ASXL1KMT2CPTPRT

ATMCHEK2

TP53PPM1D

TET2DNMT3A

0.0 0.2 0.4

0

2

4

6

8

DN

MT3

A R

882C

DN

MT3

A R

882H

DN

MT3

A R

736H

DN

MT3

A W

860R

DN

MT3

A Y

735C

DN

MT3

A F

755S

DN

MT3

A P

904L

PP

M1D

R57

2*JA

K2

V61

7FD

NM

T3A

R32

6CD

NM

T3A

R73

6CD

NM

T3A

R77

1*D

NM

T3A

V65

7MA

SX

L1 R

634f

sA

SX

L1 Y

591f

sC

BL

R42

0QD

NM

T3A

G54

3CD

NM

T3A

G55

0RD

NM

T3A

I780

TD

NM

T3A

L34

4PD

NM

T3A

M76

1VD

NM

T3A

M88

0VD

NM

T3A

P77

7RD

NM

T3A

Q81

6*D

NM

T3A

R32

0*D

NM

T3A

R59

8*D

NM

T3A

R68

8HD

NM

T3A

R72

9WD

NM

T3A

R79

2HD

NM

T3A

W30

6*D

NM

T3A

W79

5RP

PM

1D C

478f

sP

PM

1D R

458*

SF3

B1

E62

2DS

F3B

1 K

700E

TET2

R55

0*TP

53 R

248Q

# of

Sub

ject

s w

ith D

river

s

ASXL1CBLDNMT3AJAK2PPM1DSF3B1TET2TP53

0

10

20

30

40

50

<50 >50 and <60 >60 and <70 >70

% o

f Sub

ject

s w

ith D

river

s

Drivers inNEJM, at least 10%GRAIL, at least 10%GRAIL, at least 1%GRAIL, at least 0.1%

Pro

porti

on o

f Sub

ject

s w

ith V

aria

nts * Prior therapy includes:

chemotherapy, hormonal therapy, target therapy delivered for metastatic disease, or prior neoadjuvant/adjuvant therapy

20

40

60

80

Healthy Breast Lung Prostate

Age

0

5

10

15

20

Healthy Breast Lung ProstateCohort

Num

ber o

f var

iant

s pe

r sub

ject

Unique Variants per GeneProportion of Subjects

with Variants

RANBP2DNMT3B

NF1EGFR

GRIN2ACBL

ASXL1FAT1

PTPRTATM

CHEK2TP53

PPM1DTET2

DNMT3A

0.0 0.2 0.4 0.6RANBP2DNMT3B

NF1EGFR

GRIN2ACBL

ASXL1FAT1

PTPRTATM

CHEK2TP53

PPM1DTET2

DNMT3A

0.0 0.2 0.4 0.6RANBP2DNMT3B

NF1EGFR

GRIN2ACBL

ASXL1FAT1

PTPRTATM

CHEK2TP53

PPM1DTET2

DNMT3A

0.0 0.2 0.4 0.6

N 47 48 49 54Cohort

Variants per Gene

TotalPercent in Top 15

1072 99649% 46%

Total VariantsNumber of Subjects

683 195114 37

19447

Cancer: Prior Therapy Cancer: No Prior Therapy Healthy

Previously Implicated Genes

DNMT3BGRIN2A

EGFRCBL

FAT1NF1

ASXL1KMT2CPTPRT

ATMCHEK2

TP53PPM1D

TET2DNMT3A

0 50 100 150 200DNMT3BGRIN2A

EGFRCBL

FAT1NF1

ASXL1KMT2CPTPRT

ATMCHEK2

TP53PPM1D

TET2DNMT3A

0 50 100 150 200DNMT3BGRIN2A

EGFRCBL

FAT1NF1

ASXL1KMT2CPTPRT

ATMCHEK2

TP53PPM1D

TET2DNMT3A

0.0 0.2 0.4

0

2

4

6

8

DN

MT3

A R

882C

DN

MT3

A R

882H

DN

MT3

A R

736H

DN

MT3

A W

860R

DN

MT3

A Y

735C

DN

MT3

A F

755S

DN

MT3

A P

904L

PP

M1D

R57

2*JA

K2

V61

7FD

NM

T3A

R32

6CD

NM

T3A

R73

6CD

NM

T3A

R77

1*D

NM

T3A

V65

7MA

SX

L1 R

634f

sA

SX

L1 Y

591f

sC

BL

R42

0QD

NM

T3A

G54

3CD

NM

T3A

G55

0RD

NM

T3A

I780

TD

NM

T3A

L34

4PD

NM

T3A

M76

1VD

NM

T3A

M88

0VD

NM

T3A

P77

7RD

NM

T3A

Q81

6*D

NM

T3A

R32

0*D

NM

T3A

R59

8*D

NM

T3A

R68

8HD

NM

T3A

R72

9WD

NM

T3A

R79

2HD

NM

T3A

W30

6*D

NM

T3A

W79

5RP

PM

1D C

478f

sP

PM

1D R

458*

SF3

B1

E62

2DS

F3B

1 K

700E

TET2

R55

0*TP

53 R

248Q

# of

Sub

ject

s w

ith D

river

s

ASXL1CBLDNMT3AJAK2PPM1DSF3B1TET2TP53

0

10

20

30

40

50

<50 >50 and <60 >60 and <70 >70

% o

f Sub

ject

s w

ith D

river

sDrivers in

NEJM, at least 10%GRAIL, at least 10%GRAIL, at least 1%GRAIL, at least 0.1%

Pro

porti

on o

f Sub

ject

s w

ith V

aria

nts

20

40

60

80

Healthy Breast Lung Prostate

Age

0

5

10

15

20

Healthy Breast Lung ProstateCohort

Num

ber o

f var

iant

s pe

r sub

ject

Unique Variants per GeneProportion of Subjects

with Variants

RANBP2DNMT3B

NF1EGFR

GRIN2ACBL

ASXL1FAT1

PTPRTATM

CHEK2TP53

PPM1DTET2

DNMT3A

0.0 0.2 0.4 0.6RANBP2DNMT3B

NF1EGFR

GRIN2ACBL

ASXL1FAT1

PTPRTATM

CHEK2TP53

PPM1DTET2

DNMT3A

0.0 0.2 0.4 0.6RANBP2DNMT3B

NF1EGFR

GRIN2ACBL

ASXL1FAT1

PTPRTATM

CHEK2TP53

PPM1DTET2

DNMT3A

0.0 0.2 0.4 0.6

N 47 48 49 54Cohort

Variants per Gene

TotalPercent in Top 15

1072 99649% 46%

Total VariantsNumber of Subjects

683 195114 37

19447

Cancer: Prior Therapy Cancer: No Prior Therapy Healthy

Previously Implicated Genes

DNMT3BGRIN2A

EGFRCBL

FAT1NF1

ASXL1KMT2CPTPRT

ATMCHEK2

TP53PPM1D

TET2DNMT3A

0 50 100 150 200DNMT3BGRIN2A

EGFRCBL

FAT1NF1

ASXL1KMT2CPTPRT

ATMCHEK2

TP53PPM1D

TET2DNMT3A

0 50 100 150 200DNMT3BGRIN2A

EGFRCBL

FAT1NF1

ASXL1KMT2CPTPRT

ATMCHEK2

TP53PPM1D

TET2DNMT3A

0.0 0.2 0.4

0

2

4

6

8

DN

MT3

A R

882C

DN

MT3

A R

882H

DN

MT3

A R

736H

DN

MT3

A W

860R

DN

MT3

A Y

735C

DN

MT3

A F

755S

DN

MT3

A P

904L

PP

M1D

R57

2*JA

K2

V61

7FD

NM

T3A

R32

6CD

NM

T3A

R73

6CD

NM

T3A

R77

1*D

NM

T3A

V65

7MA

SX

L1 R

634f

sA

SX

L1 Y

591f

sC

BL

R42

0QD

NM

T3A

G54

3CD

NM

T3A

G55

0RD

NM

T3A

I780

TD

NM

T3A

L34

4PD

NM

T3A

M76

1VD

NM

T3A

M88

0VD

NM

T3A

P77

7RD

NM

T3A

Q81

6*D

NM

T3A

R32

0*D

NM

T3A

R59

8*D

NM

T3A

R68

8HD

NM

T3A

R72

9WD

NM

T3A

R79

2HD

NM

T3A

W30

6*D

NM

T3A

W79

5RP

PM

1D C

478f

sP

PM

1D R

458*

SF3

B1

E62

2DS

F3B

1 K

700E

TET2

R55

0*TP

53 R

248Q

# of

Sub

ject

s w

ith D

river

s

ASXL1CBLDNMT3AJAK2PPM1DSF3B1TET2TP53

0

10

20

30

40

50

<50 >50 and <60 >60 and <70 >70%

of S

ubje

cts

with

Driv

ers

Drivers inNEJM, at least 10%GRAIL, at least 10%GRAIL, at least 1%GRAIL, at least 0.1%

Pro

porti

on o

f Sub

ject

s w

ith V

aria

nts

Variants Found in Both WBC and cfDNA are Preferentially in Previously Described Clonal Hematopoiesis GenesVariants are in genes previously associated with clonal hematopoiesis (Genovese 2014).

20

40

60

80

Healthy Breast Lung Prostate

Age

0

5

10

15

20

Healthy Breast Lung ProstateCohort

Num

ber o

f var

iant

s pe

r sub

ject

Unique Variants per GeneProportion of Subjects

with Variants

RANBP2DNMT3B

NF1EGFR

GRIN2ACBL

ASXL1FAT1

PTPRTATM

CHEK2TP53

PPM1DTET2

DNMT3A

0.0 0.2 0.4 0.6RANBP2DNMT3B

NF1EGFR

GRIN2ACBL

ASXL1FAT1

PTPRTATM

CHEK2TP53

PPM1DTET2

DNMT3A

0.0 0.2 0.4 0.6RANBP2DNMT3B

NF1EGFR

GRIN2ACBL

ASXL1FAT1

PTPRTATM

CHEK2TP53

PPM1DTET2

DNMT3A

0.0 0.2 0.4 0.6

N 47 48 49 54Cohort

Variants per Gene

TotalPercent in Top 15

1072 99649% 46%

Total VariantsNumber of Subjects

683 195114 37

19447

Cancer: Prior Therapy Cancer: No Prior Therapy Healthy

Previously Implicated Genes

DNMT3BGRIN2A

EGFRCBL

FAT1NF1

ASXL1KMT2CPTPRT

ATMCHEK2

TP53PPM1D

TET2DNMT3A

0 50 100 150 200DNMT3BGRIN2A

EGFRCBL

FAT1NF1

ASXL1KMT2CPTPRT

ATMCHEK2

TP53PPM1D

TET2DNMT3A

0 50 100 150 200DNMT3BGRIN2A

EGFRCBL

FAT1NF1

ASXL1KMT2CPTPRT

ATMCHEK2

TP53PPM1D

TET2DNMT3A

0.0 0.2 0.4

0

2

4

6

8

DN

MT3

A R

882C

DN

MT3

A R

882H

DN

MT3

A R

736H

DN

MT3

A W

860R

DN

MT3

A Y

735C

DN

MT3

A F

755S

DN

MT3

A P

904L

PP

M1D

R57

2*JA

K2

V61

7FD

NM

T3A

R32

6CD

NM

T3A

R73

6CD

NM

T3A

R77

1*D

NM

T3A

V65

7MA

SX

L1 R

634f

sA

SX

L1 Y

591f

sC

BL

R42

0QD

NM

T3A

G54

3CD

NM

T3A

G55

0RD

NM

T3A

I780

TD

NM

T3A

L34

4PD

NM

T3A

M76

1VD

NM

T3A

M88

0VD

NM

T3A

P77

7RD

NM

T3A

Q81

6*D

NM

T3A

R32

0*D

NM

T3A

R59

8*D

NM

T3A

R68

8HD

NM

T3A

R72

9WD

NM

T3A

R79

2HD

NM

T3A

W30

6*D

NM

T3A

W79

5RP

PM

1D C

478f

sP

PM

1D R

458*

SF3

B1

E62

2DS

F3B

1 K

700E

TET2

R55

0*TP

53 R

248Q

# of

Sub

ject

s w

ith D

river

s

ASXL1CBLDNMT3AJAK2PPM1DSF3B1TET2TP53

0

10

20

30

40

50

<50 >50 and <60 >60 and <70 >70

% o

f Sub

ject

s w

ith D

river

s

Drivers inNEJM, at least 10%GRAIL, at least 10%GRAIL, at least 1%GRAIL, at least 0.1%

Pro

porti

on o

f Sub

ject

s w

ith V

aria

nts