Transcript
Page 1: The Genomic Landscape and Pharmacogenomic Interactions of

Cell Systems, Volume 6

Supplemental Information

The Genomic Landscape and Pharmacogenomic

Interactions of Clock Genes

in Cancer Chronotherapy

Youqiong Ye, Yu Xiang, Fatma Muge Ozguc, Yoonjin Kim, Chun-Jie Liu, Peter K.Park, Qingsong Hu, Lixia Diao, Yanyan Lou, Chunru Lin, An-YuanGuo, Bingying Zhou, LiWang, Zheng Chen, Joseph S. Takahashi, Gordon B. Mills, Seung-Hee Yoo, and Leng Han

Page 2: The Genomic Landscape and Pharmacogenomic Interactions of

Gene Expression

T/N pairs

Transcriptional dysregulation (Fig.1)

Tumor samplesDisruption of circadi-an rhythm (Fig. 4)

Time points RNAseq data of MCF7 & MCF10A

genes with circadian oscillationNumber of genes correlated with clock genes (T-N)

|log2(T/N Expression)| > 0.58 & FDR < 0.05

RPPA Pathway score

Groups with low or high expression of clock genes

Effects of clock genes on signaling pathways (Fig. 2)

Clinical Data:patient survival, tumor subtypes and stages

Interaction between clock genes and CAGs (Fig.6)

Protein-protein interaction dataChIP-seq data

MutationDNA methylation

Genetic alteration of clock genes (Fig. 3)

Gene expression in CCLEPharmacogenomic data (CTRP)

Time points RNAseq data of CRY2 KD or WT in MEF cells

Therapeutic liability of clock genes (Fig. 7)

Correlation between drug sensitivity and expression of clock genes

TCG

A da

ta: c

linic

al a

nd m

olec

ular

sig

natu

res

in 3

2 ca

ncer

type

s

Raw data | Data produced intermediate stepsResults

Clinical relevance of clock genes (Fig. 5)

GDSC gene expression &Pharmacogenomic data

Figure S1. Related to STAR Methods.The pipeline of bioinformatics analysis procedures and data used for each part of the analysis. Clinically actionable genes (CAGs), The Cancer Genome Atlas (TCGA), Reverse Phase Protein Array (RPPA), The Cancer Cell Line Encyclopedia (CCLE), Genomic of Drug Sensitivity in Cancer (GDSC), Cancer Therapeutics Response Portal (CTRP), Tumor (T), Normal (N), Knock Down (KD), Wild Type (WT), False discovery rate (FDR). The abbreviation for cancer types is listed in table S1.

ACC

BLCA

BRCA

CESC

CHOL

COAD

DLB

CESCA

GBM

HNSC

KICH

KIRC

KIRP

LGG

LIHC

LUAD

LUSC

MESO

OV

PAAD

PCPG

PRAD

READ

SARC

SKCM

STAD

TGCT

THCA

THYM

UCE

C

UCS

UVM

Page 3: The Genomic Landscape and Pharmacogenomic Interactions of

A

B

Activation Inhibition None

●

●

●

●

●

●

●

●●●●●●

●

●

●

●

●

●

●

●

●

●●●

●

●

●

●

●

●

●

●

●

●

●

●

●

●

●

●

●●

●

●

●

●

●

●

●

●

●●

●

●

●

●

●

●

●●

●●

●

●

●

●

●

●●●

●

●

●

●

●

●

●

●

●

●

●

●●

●

●

●

●

●

●●

●

●●

●

●

●●●

●

●

●●

●

●

●●●

●

●

●

●

●

●

●

●

●

●

●

●

●

●

●

●

●

●

●●

●●

●

●

●

●

●

●

●

●

●

●

●

●

●

●●

●

●●

●

●●

●

●

●●●●

●

●

●

●

●

●

●

●

●

●

●

●

●

●

●

●

●

●

●

●

●

●●●

●

●

●

●

●

●

●

●

●

●●

●

●●

●

●

●

●

●

●

●

●

●●

●●

●

●

●

●

●

●●●

●

●

●

●

●

●

●

●

●

●

●

●

●

●

●

●

●

●

●

●

●

●

●

●

●

●

●

●

●

●

●

●●

●

●

●

●

●

●

●

●●

●

●

●

●

RORCRORBRORA

CRY2

●

●

●

●

●

●

●

●

●

●

●

●

●

●

●

● ● ● ●

●

●

●●

●●

●

●

●

●

●

●

●

●

●

●

●

●

●

●

●●●

●

●

●

●

●

●●

●

●

●

●

●

●

●

●

●

●

●

●

●

●

●

●

●

●

●

●

●

●

●

●

●

●

●

●

●

●

●

●

●

●

●

●

●●

●

●

●

●

●

●

●

●

●

● ●

●

●

●

●

●

●

●

●

●

●

●

●

●

●

●

●

●

●

●

●

●

●

●

●

●

●

●

●

●

●

●

●

●

●

●

●

●

●

●

●

●

●

●

●

●

●

●

●

● ●

●

●

●

●

●

●

●

●

●

●

●

●

●

●

●

●

●

●

●

●

●

●

●

●

●

●

●

●

●

●

●

●

● ●

●

●

●

●

●

●

●

●

●

●

●

●

●

●

●

●

●

●

●

●

●

●

●

●

●

●

●

●

●

●

●

●

●

●

●

●

●

●

●

●

●

●

● ● ● ●

●

●

●●

●●

●

●

●

●

●

●

●

●

●

●

●

●

●

●

●●●

●

●

●

●

●

●●

●

●

●

●

●

●

●

●

●

●

●

●

●

●

●

●

●

●

●

●

●

●

●

●

●

●

●

●

●

●

●

●

●

●

●

●

●●

●

●

●

●

●

●

●

●

●

● ●

●

●

●

●

●

●

●

●

●

●

●

●

●

●

●

●

●

●

●

●

●

●

●

●

●

●

●

●

●

●

●

●

●

●

●

●

●

●

●

●

●

●

● ●

●

●

●

●

●

●

●●

●

●

●

●

●

●

●

●

●

●

●

●

●

●

●●●

●

●

●

●

●

●

●

●

● ●

●

●

●

●

●

●

●

●

●

●

●

●

●

●

●

●

RORA & RORC RORB & RORCRORA & RORB

RORA & RORB & RORC

BLC

ABR

CA

CES

CC

OAD

ESC

AH

NSC

KIR

CKI

RP

LGG

LIH

CLU

ADLU

SCM

ESO OV

PAAD

PCPG

PRAD

REA

DSA

RC

SKC

MST

ADTG

CT

THC

ATH

YMU

CEC

ApoptosisCell Cycle

DNA Damage ResponseEMT

Hormone aHormone b

PI3K/AKTRAS/MAPK

RTKTSC/mTOR

ApoptosisCell Cycle

DNA Damage ResponseEMT

Hormone aHormone b

PI3K/AKTRAS/MAPK

RTKTSC/mTOR

ApoptosisCell Cycle

DNA Damage ResponseEMT

Hormone aHormone b

PI3K/AKTRAS/MAPK

RTKTSC/mTOR

BLC

ABR

CA

CES

CC

OAD

ESC

AH

NSC

KIR

CKI

RP

LGG

LIH

CLU

ADLU

SCM

ESO OV

PAAD

PCPG

PRAD

REA

DSA

RC

SKC

MST

ADTG

CT

THC

ATH

YMU

CEC

BLC

ABR

CA

CES

CC

OAD

ESC

AH

NSC

KIR

CKI

RP

LGG

LIH

CLU

ADLU

SCM

ESO OV

PAAD

PCPG

PRAD

REA

DSA

RC

SKC

MST

ADTG

CT

THC

ATH

YMU

CEC

●

●

●

●

●

●

●

●

●

●

●

●

●

●

●

●

●

●

●

●

●

●

●

●

●

●

●

●

●

●

● ●

CRY1 & CRY2

●

●

●

●

●

●

● ●

●

●

●●

●

●

●

●

●

●●

●

●

●

●

●

●

●

●

CRY1

ApoptosisCell Cycle

DNA Damage ResponseEMT

Hormone aHormone b

PI3K/AKTRAS/MAPK

RTKTSC/mTOR

βˆ’log10(FDR)

● ● ●

0.05

0.01

1eβˆ’4

βˆ’1.0

βˆ’0.5

0.0

0.5

1.0

Difference

0 1000 2000

0.0

0.2

0.4

0.6

0.8

1.0

ESCA βˆ’ RORA & RORC

Survival in days

HighLow

p = 0.043

0 2000 4000 6000

0.0

0.2

0.4

0.6

0.8

1.0

HNSC βˆ’ RORA & RORC

Survival in days

HighLow

p = 0.044

0 1000 2000 3000

0.0

0.2

0.4

0.6

0.8

1.0

KIRC βˆ’ RORA & RORC

Survival in days

HighLow

p = 4eβˆ’08

0 1000 2000 3000

0.0

0.2

0.4

0.6

0.8

1.0

LIHC βˆ’ RORA & RORC

Survival in days

HighLow

p = 0.029

C

Surv

ival

rate

Surv

ival

rate

Surv

ival

rate

Surv

ival

rate

AHR

ALAS

1

BHLH

E40

BHLH

E41

BTR

C

CR

EB1

CR

EBBP

CSE

1L

CSN

K1D

CSN

K1E

CSN

K2A1

CSN

K2A2

CSN

K2B

DBP

EP30

0

FBXL

21

FBXL

3

FBXW

11

GN

B2L1

GSK

3B

HLF

IFN

A1

NFI

L3

NO

NO

NR

1I3

PAR

P1

PPAR

A

PPAR

G

PPP1

CA

PPP1

CC

PPP5

C

PRKA

A2

PRKC

A

SIR

T1

TEF

TNF

WD

R5

Apoptosis

Cell Cycle

DNA Damage Response

EMT

Hormone a

Hormone b

PI3K/AKT

RAS/MAPK

RTK

TSC/mTOR

Figure S2. Related to Figure 2. Clock genes associated with the activity of key signaling pathways. (A) Percentage of cancer types with 37 clock genes associated with the activation (red) or inhibition (blue) of key signaling pathways. (B) The difference of pathway scores in key signaling pathways between tumor samples with low expression and high expression of individual or paralog clock genes of CRY1/2, and RORA/B/C. The colors and size of point represent the difference and statistical significance (FDR) of protein-expression pathway scores. (C) Survival analysis for combination of RORA and RORC in ESCA, HNSC, KIRC and LIHC (blue: low expression in both genes; red: high expression in both genes).

Page 4: The Genomic Landscape and Pharmacogenomic Interactions of

A

Neg

ativ

e

Spe

arm

an C

orre

latio

n C

oeffi

cien

t

B

Posi

tive

BLC

APA

ADU

VMPC

PG LGG

MES

OTH

CA

SKC

MSA

RC

BRC

AKI

RP

PRAD

KIR

CAC

CKI

CH

CES

CST

ADES

CA

REA

DC

OAD

HN

SCLU

SCU

CEC

LUAD

LIH

CU

CS

GBM

THYM

TGC

T

TNFFBXL21BTRCTEFARNTL2HLFCSNK2BPARP1WDR5PER3PRKAA2PPARGBHLHE41SIRT1NR1D2CRY2NPAS2ARNTLNR1D1CSE1LCREB1NONOPPARABHLHE40EP300PPP5CCREBBPPRKCAALAS1RORBAHRGNB2L1CSNK2A1PPP1CARORCNR1I3PER1DBPPPP1CCCSNK2A2PER2GSK3B

Figure S3. Related to Figure 3. Epigenetic alterations in clock genes. (A) Correlation between promot-er DNA methylation levels and gene expression across clock genes. (B) Differential DNA methylation level of clock genes between paired tumor and normal samples. (Different beta-value > 0.2, FDR < 0.05, Red: up-regulation; blue: downregulation; size: p value)

● ● ● ●●

● ● ●●

●● ● ●●

● ●● ●

●● ●● ●●

● ●●

● ●●● ●

● ● ● ●

● ● ●

●●● ●● ●●●

● ● ●

●

PRADSTADKIRC

ESCABLCACOADKIRP

HNSCLIHC

LUADTHCABRCAKICH

LUSC

HLF

RO

RA

PER

1PE

R3

RO

RB

CRY

2TE

FPR

KAA2

PER

2FB

XL3

PPAR

GN

FIL3

NR

1I3

FBXL

21R

OR

CC

RY1

PRKC

ATN

FPP

ARA

ALAS

1N

R1D

2SI

RT1

BHLH

E41

CLO

CK

CR

EB1

CSN

K2B

FBXW

11BH

LHE4

0C

SNK2

A2BT

RC

EP30

0IF

NA1

PPP1

CC

PPP5

CC

REB

BPC

SNK1

DG

NB2

L1AR

NTL

CSN

K2A1

GSK

3BPP

P1C

AW

DR

5N

PAS2

AHR

DBP

NO

NO

PAR

P1C

SNK1

EN

R1D

1C

SE1L

ARN

TL2

βˆ’0.4βˆ’0.200.20.4

Bβˆ’Value Change

●

●

●

●

P value0.0510βˆ’5

10βˆ’10

< 10βˆ’15

Page 5: The Genomic Landscape and Pharmacogenomic Interactions of

βˆ’3053

βˆ’2βˆ’17

βˆ’2055

βˆ’660

βˆ’280

βˆ’3419

βˆ’2650

βˆ’449

βˆ’1319

βˆ’1βˆ’7

βˆ’311

βˆ’340

βˆ’1

βˆ’2312

βˆ’1948

66

βˆ’1

βˆ’1

1

βˆ’1264

βˆ’1

βˆ’1βˆ’695

βˆ’1

βˆ’2838

βˆ’744

βˆ’2573

βˆ’4663

βˆ’113

βˆ’1βˆ’935

βˆ’1760

βˆ’3310

βˆ’3649

βˆ’1

βˆ’3562

βˆ’2067

βˆ’3531

βˆ’1

βˆ’1

βˆ’1873

βˆ’2833

βˆ’3398

βˆ’3050

βˆ’3879

βˆ’3239

βˆ’35

βˆ’815

βˆ’1

βˆ’2158

βˆ’30βˆ’22

βˆ’1397

βˆ’1828

βˆ’1318

βˆ’3727

βˆ’1919

βˆ’2

βˆ’1894

βˆ’1βˆ’270

βˆ’1183

βˆ’1274

βˆ’4

βˆ’2526

βˆ’508

βˆ’3050

βˆ’1301

βˆ’10

βˆ’1655

βˆ’3960

βˆ’1705

βˆ’2610βˆ’1735

βˆ’310

βˆ’1004

βˆ’2834

βˆ’682

βˆ’2465

βˆ’2481

βˆ’453βˆ’2132

βˆ’2045

βˆ’1241

βˆ’3217

17

βˆ’2581

βˆ’2746

βˆ’144

14

βˆ’2859

βˆ’2609

βˆ’61

βˆ’1424

βˆ’2254

8

βˆ’2125

βˆ’82

βˆ’2042

26

βˆ’1806

βˆ’20143

0

βˆ’82

βˆ’715

βˆ’2524

βˆ’815

73

135

βˆ’671βˆ’153

βˆ’802

βˆ’2027

βˆ’69

βˆ’1767

βˆ’2838

βˆ’2240

12

βˆ’32

βˆ’210

βˆ’2229

βˆ’1553

βˆ’404βˆ’11

βˆ’3476

βˆ’2051

βˆ’1674

βˆ’1334

βˆ’3011

βˆ’575

βˆ’2405βˆ’667

37

βˆ’1596

βˆ’3656

βˆ’1

βˆ’1611

βˆ’2824

βˆ’3840

8

βˆ’106

βˆ’1402

βˆ’3307

βˆ’2051

βˆ’2502

βˆ’3405

βˆ’1391

504

βˆ’142

796

βˆ’887

49βˆ’319

βˆ’266

βˆ’3177

428

βˆ’2795

βˆ’330

226

βˆ’1332

βˆ’1233

βˆ’3309

βˆ’74

βˆ’1

βˆ’213

βˆ’606

βˆ’1282

βˆ’618

βˆ’2

βˆ’272

βˆ’1514

βˆ’2102

βˆ’2βˆ’870

βˆ’303

βˆ’1118

βˆ’1594

βˆ’270

βˆ’1876

βˆ’377

βˆ’2294βˆ’652

βˆ’523

38

βˆ’1562

βˆ’1040

βˆ’629

βˆ’1240

632

βˆ’5

βˆ’1200

βˆ’920

βˆ’218

βˆ’2033

694

βˆ’719

βˆ’963

βˆ’542

βˆ’496

βˆ’17

βˆ’852

βˆ’1βˆ’215

βˆ’181

βˆ’1364

βˆ’1474

βˆ’572

βˆ’315

71

1083

βˆ’14

1269

βˆ’2165

βˆ’8

751

14

βˆ’1575

809

βˆ’8

βˆ’1100

βˆ’1692

βˆ’1178

βˆ’2298βˆ’611

βˆ’75

βˆ’1236

βˆ’2055

βˆ’238

βˆ’1537

βˆ’2281

βˆ’425βˆ’1139

βˆ’1032

176

150

βˆ’1637

βˆ’2621

277

271

64

412

βˆ’2399

βˆ’1918

βˆ’484

βˆ’2527

βˆ’1203

βˆ’2004

743

βˆ’1749

βˆ’1133

βˆ’48

βˆ’457βˆ’77

βˆ’142

βˆ’1769

βˆ’1472

βˆ’950

802

βˆ’9

324

βˆ’5βˆ’24

βˆ’554

βˆ’728

βˆ’200

βˆ’104

339

46

437

30

βˆ’206

βˆ’177

βˆ’2029

1656βˆ’408

βˆ’1175

789

βˆ’526

βˆ’177

1402

βˆ’369

βˆ’1248341

βˆ’1556

278

244

βˆ’1899

βˆ’455

120

βˆ’19

16

βˆ’27

βˆ’55

βˆ’680

βˆ’903

βˆ’1402

βˆ’638

731

βˆ’504

βˆ’53

94

770

βˆ’1βˆ’20

βˆ’59

βˆ’1258

βˆ’2682

βˆ’692

175

1017

βˆ’208

βˆ’2138

βˆ’696

βˆ’3058

βˆ’1

βˆ’1897

βˆ’3

βˆ’1820

84

βˆ’14

3

βˆ’1524

βˆ’1945

βˆ’66βˆ’748

βˆ’1648

βˆ’506

βˆ’1500

βˆ’640

βˆ’172

βˆ’4127

βˆ’1970βˆ’845

βˆ’1535

588

βˆ’302

βˆ’2109

βˆ’557

416

187

2

71

βˆ’1211

907

βˆ’1850

βˆ’2252

βˆ’2046

303

βˆ’4

βˆ’328

βˆ’1250

βˆ’941

βˆ’623βˆ’119

βˆ’139

βˆ’437

βˆ’274

βˆ’88

βˆ’406

βˆ’10

βˆ’26

1243

βˆ’177

βˆ’752

βˆ’2

βˆ’305

126

βˆ’7

βˆ’323

βˆ’37

125

βˆ’1355

147

βˆ’566βˆ’443

32

βˆ’795

βˆ’49

βˆ’760

βˆ’487

4

βˆ’1087302

βˆ’291

237

βˆ’57

βˆ’456

βˆ’320

βˆ’1035

6

0

68

βˆ’13

βˆ’517

βˆ’83

βˆ’128

180

βˆ’579

βˆ’505

βˆ’159

βˆ’536

βˆ’337

βˆ’180βˆ’396

βˆ’292

284

29

βˆ’349

βˆ’1375

32

βˆ’1177

26βˆ’253

63

βˆ’1516

9

βˆ’1102

4

9

βˆ’55

βˆ’32

βˆ’620

βˆ’2065

βˆ’316

βˆ’924βˆ’64

2

βˆ’2165

βˆ’1708

βˆ’1918

βˆ’2456

βˆ’518

205βˆ’542

βˆ’507

βˆ’289

βˆ’552

βˆ’21

βˆ’1840

βˆ’385

89

15

βˆ’64

βˆ’1947

βˆ’105

βˆ’2127

βˆ’585

βˆ’1623

βˆ’2147

114

βˆ’664

5

βˆ’497

βˆ’459βˆ’463

βˆ’388

380

62

βˆ’403

βˆ’1656

115

βˆ’660

βˆ’3βˆ’640

βˆ’331

βˆ’593

βˆ’4

βˆ’651

βˆ’56

6

βˆ’280

152

βˆ’392

βˆ’1020

βˆ’520

βˆ’891βˆ’585

βˆ’51

βˆ’467

βˆ’1026

βˆ’1523

βˆ’1581

βˆ’174

βˆ’328βˆ’210

12

22

βˆ’417

0

βˆ’1281

βˆ’1122

βˆ’419

4

βˆ’199

βˆ’1168

βˆ’218

βˆ’989

βˆ’169

βˆ’888

βˆ’980

βˆ’468

βˆ’596

39

βˆ’52

βˆ’712βˆ’12

βˆ’295

βˆ’305

βˆ’182

βˆ’821

βˆ’1101

βˆ’1685

573

βˆ’783βˆ’46

βˆ’49

βˆ’471

βˆ’385

βˆ’50

34

βˆ’923

350

βˆ’75

βˆ’534

βˆ’557

βˆ’89

βˆ’1181132

βˆ’203

βˆ’275

838

βˆ’1491

βˆ’499

βˆ’700

βˆ’7206

βˆ’234

βˆ’1202

βˆ’1287

35

617

100

βˆ’1528

6

βˆ’820

890

312

164

βˆ’1308

βˆ’1923

βˆ’926

βˆ’158

βˆ’91

βˆ’103

βˆ’2565

βˆ’290βˆ’1867

βˆ’1385

βˆ’3693

βˆ’3050

βˆ’3581

βˆ’932

βˆ’3626

βˆ’2382

βˆ’167018

βˆ’4286

βˆ’3395

βˆ’14

βˆ’2708

βˆ’4572

βˆ’2349

βˆ’3392

βˆ’4187

βˆ’1553

βˆ’3365

βˆ’2678

βˆ’495βˆ’1433

βˆ’5147

βˆ’143

βˆ’956

βˆ’1095

βˆ’3430

βˆ’1010

βˆ’2142βˆ’5309

βˆ’964

βˆ’3548

βˆ’5026

βˆ’1079

βˆ’3791

βˆ’3720

βˆ’3847

118

21

βˆ’2385

βˆ’785

βˆ’816

βˆ’4017

βˆ’4070

βˆ’2198

βˆ’4466

βˆ’1756

509

βˆ’1785

βˆ’1168βˆ’222

βˆ’73

βˆ’863

βˆ’2318

βˆ’760

βˆ’1613

110

βˆ’1175

585βˆ’52

βˆ’3

111

15

βˆ’1530

514

βˆ’131

930

14

βˆ’716

βˆ’1857

βˆ’47

βˆ’188βˆ’1496

121

βˆ’688

βˆ’1747

βˆ’805

βˆ’1144

βˆ’292

βˆ’881βˆ’1018

βˆ’225

βˆ’4

βˆ’3176

βˆ’425

βˆ’1397

βˆ’348

291

153

βˆ’117

βˆ’1679

βˆ’1555

βˆ’2542

βˆ’627

59

βˆ’803

βˆ’32

βˆ’277

βˆ’1146

IFNA1NR1D1

CRY1ARNTLNFIL3

DBPPER1

TNFNONO

BHLHE40PER2

FBXL21TEF

NR1D2NR1I3WDR5

CSNK1DCSNK2A1

AHRPER3

CLOCKALAS1

CSNK2A2PPP5C

CRY2PARP1NPAS2

PPP1CCCSNK2B

FBXL3SIRT1

ARNTL2RORB

CSE1LHLF

FBXW11RORA

BHLHE41CREB1

CSNK1EGSK3B

GNB2L1EP300PPARAPRKCARORC

CREBBPPPARG

BTRCPRKAA2PPP1CA

LIH

C

LUSC

PRAD

KIR

C

LUAD

THC

A

HN

SC

KIR

P

KIC

H

CO

AD

BLC

A

BRC

A

STAD

βˆ’5000 βˆ’2500 0 2500 5000

ARNTL

ARNTL2

CLOCK

CRY1

CRY2

NPAS2

NR1D1

NR1D2

PER1

PER2

PER3

RORA

RORB

RORC

ARNT

L

ARNT

L2

CLO

CK

CRY1

CRY2

NPAS

2

NR1D

1

NR1D

2

PER1

PER2

PER3

RORA

RORB

RORC

βˆ’0.8

βˆ’0.4

0.0

0.4

Cor

Coe

f

f.

●

●

●

●

●

●

●

●

●

●●

●

●

●

●

●●

●

●

●

●

●

●●

●

●

●

●

●

●

●

●

●

●

●

●

●

●

●

●● ●

●

●

●

●●

●

●

●

●

●

●●

●

●●●

●

●

●

●

●●

●

R = 0.079R = βˆ’0.47

●

●

●

●

●

●

●

●

●

●●

●

●

●

●

● ●

●

●

●

●

●

●●

●

●

●

●

●

●

●

●

●

●

●

●

●

●

●

●● ●

●

●

●

●●

●

●

●

●

●

●●

●

●● ●

●

●

●

●

●●

●

R = βˆ’0.28R = 0.46

●

●

●

●

●

●

●

●

●

● ●

●

●

●

●

●●

●

●

●

●

●

●●

●

●

●

●

●

●

●

●

●

●

●

●

●

●

●

●● ●

●

●

●

● ●

●

●

●

●

●

●●

●

●● ●

●

●

●

●

●●

●

R = βˆ’0.056R = βˆ’0.7

●

●

●

●

●

●

●

●

●

●●

●

●

●

●

●●

●

●

●

●

●

●●

●

●

●

●

●

●

●

●

●

●

●

●

●

●

●

●●●

●

●

●

●●

●

●

●

●

●

●●

●

●● ●

●

●

●

●

●●

●

R = 0.38R = 0.58

●

●

●

●

●

●

●

●

●

●●

●

●

●

●

● ●

●

●

●

●

●

●●

●

●

●

●

●

●

●

●

●

●

●

●

●

●

●

●● ●

●

●

●

● ●

●

●

●

●

●

●●

●

●●●

●

●

●

●

●●

●

R = βˆ’0.05R = βˆ’0.54

●

●

●

●

●

●

●

●

●

● ●

●

●

●

●

●●

●

●

●

●

●

●●

●

●

●

●

●

●

●

●

●

●

●

●

●

●

●

●● ●

●

●

●

●●

●

●

●

●

●

●●

●

●● ●

●

●

●

●

●●

●

R = 0.00054R = 0.32

●

●

●

●

●

●

●

●

●

●●

●

●

●

●

●●

●

●

●

●

●

●●

●

●

●

●

●

●

●

●

●

●

●

●

●

●

●

●●●

●

●

●

●●

●

●

●

●

●

●●

●

●● ●

●

●

●

●

●●

●

R = 0.13R = 0.53

●

●

●

●

●

●

●

●

●

●●

●

●

●

●

●●

●

●

●

●

●

●●

●

●

●

●

●

●

●

●

●

●

●

●

●

●

●

●●●

●

●

●

● ●

●

●

●

●

●

●●

●

●●●

●

●

●

●

●●

●

R = 0.26R = 0.49

PER2 PER3 RORB RORC

ARNTL ARNTL2 NPAS2 PER1

0 5 10 0 5 10 0 5 10 0 5 10

9

10

11

12

9

10

11

12

Gene Expression

CRY

2 G

ene

Expr

essi

on

● ●Normal Tumor

A B

C

Number of positively correlated genes

0 4 8 12 16 20 24 280 4 8 12 16 20 24 28

CTCT

MCF10A MCF7

βˆ’2βˆ’1

01

2

Zβˆ’sc

ore

Collecting duct acid secretion

Wnt signaling pathway

Oxytocin signaling pathway

Vibrio cholerae infection

Epithelial cell signaling in Helicobacter pylori infection

TNF signaling pathway

Tollβˆ’like receptor signaling pathway

0 0.5 1 1.5 2βˆ’log10(p value)D

Figure S4. Related to Figure 4. Disruption and reprogramming of circadian rhythms in cancer. (A) The number of genes which positively correlated to clock genes (Pearson correlation coefficient ≀ -0.5 and FDR < 0.05, number in cell) decreased (blue) or increased (red) in tumor samples compared to paired normal samples for each clock gene in each cancer type. Pearson correlation is corrected by tumor purity in cancer samples. (B) Heatmap presents pairwise Pearson correlation coefficient (R) of core clock genes in tumor (left upper panel) and normal (right bottom panel) samples in KIRP. Red and blue frames indicate the correlation between CRY2 and other core clock genes. (C) Correlation between the transcriptional expression of CRY2 and other eight core clock genes in tumor (red) and normal (blue) samples in KIRP cancer type. (D) Heatmaps displaying the circadian oscillation pattern of genes predicted by JTK_CYCLE and MetaCycle::meta2d (P < 0.05) in MCF7 (right), and displaying oscillation pattern of these genes in MCF10A (left) with same gene order of MCF7. Red, high expression; blue, low expression. X-axis displayed time points after serum shock. (E) Gene ontology analysis for genes with newly established circadian rhythm in MCF7.

E

Page 6: The Genomic Landscape and Pharmacogenomic Interactions of

9

10

11

12

I II III IVStages

Gen

e Ex

pres

sion

Subtypes

Gen

e Ex

pres

sion

KIRC-CRY2 (FDR = 3.9 x 10-36οΌ‰

A B

0 2000 4000 6000

0.0

0.2

0.4

0.6

0.8

1.0

Survival in days

p = 0.00045

0 1000 2000 30000.

00.

20.

40.

60.

81.

0Survival in days

HighLow

p = 1.4 x 10-5

Surv

ival

rate

Surv

ival

rate

KIRC-CRY2KIRP-CRY2C

ED

8.5

9.5

10.5

11.5

12.5

1 2 3 4

PRKCA TNF

NPAS2 NR1I3 PPARA

ARNTL2 CSNK2A2 NFIL3

TNBCLu

mALu

mBHer2

TNBCLu

mALu

mBHer2

TNBCLu

mALu

mBHer2

4

8

8

8

0

4

0

4

8

4

8

12

4

8

12

4

8

12

Gen

e E

xpre

ssio

n

PRKAA2 RORB RORC

FBXL3 NR1D1 PER2

BHLHE40 BTRC CRY2

TNBCLu

mALu

mBHer2

TNBCLu

mALu

mBHer2

TNBCLu

mALu

mBHer2

8

12

8

12

4

8

12

8

12

8

12

0

4

8

8

12

8

12

0

4

8

12

Gen

e E

xpre

ssio

n

KIRP-CRY2 (FDR = 0.0013)HighLow

Figure S5 Related to Figure 5. Individual cases for clock genes associated with patient survival, stage and subtype. (A) Association between CRY2 expression and overall survival (blue: low expression; red: high expression). (B and C) CRY2 shows differential expression in different tumor stages (B) and sub-types (C) in KIRP. (D and E) Expression levels for clock genes significantly upregulated and downregulated in TNBC compared to three other subtypes of breast cancer, respectively.

Page 7: The Genomic Landscape and Pharmacogenomic Interactions of

Num

ber o

f CAG

s

Cor

rela

tion

pairs

Negative PositiveCB

NR1D1FBXL21PPP5CPRKCAWDR5IFNA1

CSNK1DCSNK2A2

PER3FBXL3PER2

CSE1LNR1I3

TEFCSNK2A1

CLOCKALAS1

CREBBPGNB2L1

NPAS2PPP1CC

HLFDBP

RORCNR1D2NONOEP300BTRCPER1

CSNK2BSIRT1

PRKAA2PPARA

FBXW11CRY2

PPP1CAPARP1GSK3BRORBCRY1

CSNK1EPPARGCREB1ARNTL

BHLHE41AHR

RORABHLHE40

NFIL3ARNTL2

TNF

TNFR

SF4TG

FB1

CD276

ADORA2APDCD1

ICOSLG

HAVCR2CD4

CXCR4 IL2CTL

A4IL1

AIC

OSTN

FSF4

CCL2 IL6TN

FRSF9

PDCD1LG2

CD274

βˆ’10 0 10 20

Experimental evidence for protein-protein interaction

ChIP-seq evidence for interaction

The number of cancer types

Negative Positive

0

50

100

150

LUSC

CHO

LO

VBL

CACE

SCBR

CALU

AD UCS

STAD

HNSC

ESCA

UCEC

LIHC

SARC AC

CCO

ADG

BMDL

BCKI

RPLG

GPC

PGKI

RCPR

ADRE

ADTH

CAPA

ADM

ESO

SKCM

KICH

UVM

THYM

TGCT

0

1000

2000

LUSC

CH

OL

OV

LUAD

CES

CU

CS

BLC

AES

CA

BRC

AST

ADH

NSC

SAR

CAC

CLI

HC

CO

ADU

CEC

PCPG

MES

OG

BMR

EAD

KIR

CKI

RP

SKC

MLG

GPA

ADKI

CH

PRAD

DLB

CTH

CA

TGC

TU

VMTH

YM

● ●●● ● ● ● ● ● ●●●●●●●● ● ● ●●● ● ● ●●●●●● ● ●

ACC

BLC

A

BRC

A

CES

C

CH

OL

CO

AD

DLB

C

ESC

A

GBM

HN

SC

KIC

H

KIR

C

KIR

P

LGG

LIH

C

LUAD

LUSC

MES

O OV

PAAD

PCPG

PRAD

REA

D

SAR

C

SKC

M

STAD

TGC

T

THC

A

THYM

UC

EC UC

S

UVM

FDR ● ● ● ●0.05 10βˆ’5 10βˆ’10 < 10βˆ’15

βˆ’1 βˆ’0.5 0 0.5 1Cor Coeff. R

A

D

Figure S6. Related to Figure 6. Co-expression of clinically actionable genes and clock genes varied across cancer types. (A) Clock genes correlated to targeted genes for immunotherapy; blue: negative correlation; red: positive correlation; color scale: the number of cancer types with negative or positive correlation between clock genes and CAGs. If the number of cancer types is less than three, the fill color of cell is white. Bold boxes: protein-protein interactions from BioGRID and HPRD. X marks: ChIP-seq evidence for interaction. (B) Number of pairs of CAGs which correlated to clock genes across cancer types. (C) Number of correlation pairs between transcriptional expression of CAGs and clock genes across cancer type (blue: negative correlation; red: positive correlation). (D) The Pearson correlation between transcriptional expression of CLOCK and NR1D2 across 32 cancer types. The color inten-sity indicates the Pearson correlation coefficient (R), the point size indicates FDR. Black circles show the correlation with statistical significance (|R| > 0.3, FDR < 0.05).

Page 8: The Genomic Landscape and Pharmacogenomic Interactions of

A C

B

βˆ’10βˆ’5 0 5 10zscore

E

030

6090

PAR

P1C

REB

1PP

P1C

CTN

FSI

RT1

EP30

0N

ON

OPE

R2

RO

RB

CR

EBBP

PPP5

CC

RY2

GN

B2L1

FBXL

3C

SNK2

A2C

SNK2

A1D

BPC

SNK1

ER

OR

CW

DR

5PE

R1

NR

1I3

PPP1

CA

BTR

CAL

AS1

PPAR

APE

R3

FBXW

11G

SK3B

NFI

L3R

OR

ATE

FC

SE1L

BHLH

E41

ARN

TL2

CRY

1N

PAS2

NR

1D2

CLO

CK

CSN

K1D

PRKA

A2BH

LHE4

0PP

ARG

AHR

Com

poun

ds C

ount Positive Cor Negative CorGDSC

P

●● ● ●● ●● ●●● ● ● ●● ●●● ●● ● ●● ●●● ● ●●●●● ●● ●● ●●● ● ●● ●● ● ● ●● ● ● ●● ● ●●●●● ●● ●●● ●● ●● ● ● ●●●● ●●● ●● ●● ●● ●● ● ● ● ●● ●●●●●● ● ● ●● ● ●●●● ●● ●● ●●● ● ● ●● ●● ●● ●●● ●●● ●● ●●●● ● ●●

●●●

● ●● ● ●● ●● ●● ● ●●● ●● ●● ●●● ● ●● ●● ●● ●● ●● ●●●● ●● ●●● ●● ●●●

● ●●● ●●● ●● ●

● ●● ●

●● ● ●● ●● ● ● ●● ●●●● ●● ● ●●

●● ● ●● ●●● ●● ●● ● ●● ●●●●● ●●● ●● ●●● ● ●● ● ●● ● ●●● ●● ●● ●● ●● ●● ●● ●●●● ● ●●● ●● ●●●● ● ●●● ● ●● ● ●●● ●●● ●●● ●● ●● ●● ●●

● ●● ● ●● ●●● ●●● ● ●●● ●● ● ●●● ●● ● ●● ●●● ● ●●●●● ●● ●● ● ●●● ● ●● ●●● ● ● ●● ●●● ● ● ●● ● ●●●●● ●● ● ●●●● ● ●●● ●● ●● ● ● ●●●● ●●●●● ●● ●● ●● ●● ● ●● ● ●● ●●●●●● ● ● ●●● ● ●●●●● ●● ●● ● ●●● ●● ● ●● ●● ●● ●● ●●● ●● ●●● ●●● ●●●● ● ●●

● ●● ● ●● ●● ●●● ● ● ●● ● ●●● ●● ● ●● ●●● ● ●●●●● ●● ●● ● ●●● ● ●● ●● ● ●● ●●● ● ●● ● ●●●●● ●● ● ●●●● ●● ●● ● ● ● ●●● ● ●● ●● ●● ●● ● ●● ●●●●● ●●● ● ●●●●● ●● ●● ●●● ● ● ●●● ●● ● ●●● ●● ●●● ●● ●● ● ●●

●● ● ●● ●●● ● ●●● ●●●● ●● ● ●●● ●●●● ● ●● ●●● ●● ●● ● ●● ●● ● ● ●● ● ●●●●● ●● ● ●●●● ●● ●● ●● ● ● ●● ●●● ●● ●● ●●● ● ● ●●●● ● ●●●● ●● ●● ● ● ●●●● ● ●● ● ●● ●● ●●● ● ●●

●●● ● ●● ● ●● ● ● ●● ●● ●●● ● ● ●● ●● ●●● ●● ●●●

●

● ● ● ●●● ●●●● ● ●● ●●● ● ● ●●● ● ●● ● ●● ●● ●●●● ●● ●● ●● ●● ●● ●●●● ●● ●●● ●● ● ●● ●●●●● ●●

●● ● ● ●● ●● ●●●●● ●● ● ● ●● ●●●●● ●● ●● ●● ●●● ● ●● ●● ●● ● ●●●● ●● ● ●●● ●●● ●● ●● ●●●●● ●●● ● ● ●●●● ● ●● ●●●● ● ●●● ●●● ● ●●●● ●● ●● ●●

● ●● ●● ● ●●●● ●● ● ●● ●● ●●● ●● ●● ●● ● ●●● ●● ●● ●● ●● ●●●●

● ●● ●●● ● ●● ●●●● ●● ●●●● ●● ●● ●● ●●● ● ●●●● ●●●●●

● ●● ● ● ●●● ●● ●●● ● ●●●● ● ●●●● ● ●●●●● ●● ● ● ● ●● ● ●●●●● ●● ● ●● ●● ●● ● ●● ●●● ●● ●●●● ● ● ●● ●●●● ● ●● ● ●●●● ●● ● ●●● ● ●●● ●●● ● ●● ●● ●●● ● ●●

●● ● ●● ●● ●●● ● ●●● ●● ●● ●● ●●● ● ●●●●● ●● ●● ●●● ●● ●● ●● ●●● ● ● ●● ● ●●●●● ●● ● ●●●● ● ●●● ●● ● ● ● ●● ●●●● ●● ●● ●● ●● ●● ● ●● ●●●● ● ● ●●●●● ●● ●●● ● ● ●● ●● ● ●●● ● ●● ●●● ●●● ● ●●

●● ● ●●●● ●●● ● ●● ●●●●● ●● ●● ●● ●● ●● ●● ●● ● ●●●●● ● ●●● ● ●● ● ●●● ●● ●●● ● ●●● ● ●●● ●●●● ● ●● ●●● ●● ● ●● ●●● ●●

●

●●

● ●● ● ●● ●●● ●●● ● ●●● ●● ● ●●● ●● ● ●● ●●● ● ●●●●● ●● ●● ● ●●● ● ●● ● ●●● ● ● ●● ●●● ● ● ●● ● ●●●●● ●● ● ●●●● ● ●●● ●● ●●● ● ● ●●●● ●●●●● ●● ●● ●● ●● ● ● ● ●● ●●●●●● ● ● ●●● ● ●●●● ●● ●● ●●● ●● ● ●●● ●● ●● ●●● ●● ●●● ●●● ●●● ● ●●

● ●● ● ● ●● ●● ●●● ●●● ●● ● ●● ● ●●●●● ●● ●●●● ●● ●● ●● ● ●●●● ●● ● ●●● ●● ●● ●● ● ●●● ●●● ●●● ●●● ● ●● ●●●● ●● ●●● ●● ● ●●● ● ● ●●●● ●●●● ●● ●●●● ● ●●

●● ●● ●● ● ●● ● ● ●● ● ●●●● ●●● ● ●● ● ● ●● ●●●● ●● ●● ●● ●● ● ●● ●●●● ● ●●●● ● ● ●● ●● ● ●●● ● ●●● ●●●●

●● ●● ●● ●●●● ●● ● ●●●● ● ●● ●● ●●●● ● ● ●● ● ●●●●● ● ●●● ● ●● ● ●●● ●● ●●● ●● ● ● ●●● ● ●●● ●●●● ● ● ●●● ● ● ●●● ● ●● ●● ●● ●●

● ●●● ●●●● ●● ●● ● ●●● ● ●● ●●● ●● ●●

● ●● ● ●● ●●● ●●● ● ●●● ●● ● ●●● ●● ● ●● ●●● ● ●●●●● ●● ●● ● ●●● ● ●● ● ●●● ● ● ●● ●●● ● ● ●● ● ●●●●● ●● ● ●●●● ● ●●● ●● ●●● ● ● ●●●● ●●●●● ●● ●● ●● ●● ● ● ● ●● ●●●●●● ● ● ●●● ● ●●●●● ●● ●● ● ●●● ●● ● ●● ●● ●● ●● ●●● ●● ●●● ●●● ●●●● ● ●●

●● ●● ●●● ●● ● ●●●●● ●● ●●● ●●● ●●●● ●●● ●● ● ●● ●● ●● ● ●● ●●●● ● ●●● ● ● ● ● ●●● ● ●●●●●

● ●● ● ●●● ●●● ● ●● ●●● ● ● ●● ●●●●● ●● ●● ●● ●● ● ●● ● ●● ●●● ●● ● ●●●●● ● ● ●●●● ●●● ● ●● ● ●● ●● ●● ●●● ●● ●●●●● ●●● ●●● ●● ● ●● ●● ●● ●● ●●● ● ●● ●●● ●● ●●

●● ●● ●

●● ●

●●●● ●● ●●● ● ●●● ● ●●●●● ●●●●● ●● ● ●● ●●● ● ●●● ●● ● ●● ●● ●● ● ● ●● ●● ●● ● ●●● ●● ● ● ● ● ●●● ●● ●●●

●● ● ● ●●● ●●● ● ●●● ●● ● ●●● ●● ● ●● ●●● ● ●●●●● ●● ●● ● ●●● ● ●● ● ●●● ● ● ●● ●●● ● ● ●● ● ●●●●● ●● ● ●●●● ● ●●● ●● ●●● ● ● ●●●● ●●●●● ●● ●● ●● ●● ● ● ● ●● ●●●●●● ● ● ●●● ● ●●● ●● ●● ● ●●● ●● ● ●● ●● ●● ●● ●●● ●● ●●● ●●● ●●●● ● ●●

● ●● ● ●● ●● ● ● ●●● ●● ● ● ●●● ● ●●●● ● ●●● ●● ●● ● ● ● ●● ●●●●● ●● ●●● ●● ●● ●● ●●● ●●● ●●● ● ●●●●●● ● ●●● ● ●●● ●● ●● ●● ●●● ●● ●●● ●● ●● ●●● ●●

● ● ●● ●●● ● ●●●●● ●● ●●● ●● ●●● ●● ● ●● ●●● ●●● ● ● ●●● ●●● ●● ●● ●●● ●● ● ● ●●●● ● ●●●●● ●● ●●● ●● ● ●● ●●●●●

● ●● ● ●● ●● ●● ●● ● ●●● ●● ● ●●● ●● ● ●●● ●● ●●

●●● ● ●● ●● ●● ●●●● ●● ● ●● ●● ● ●● ●● ● ● ●●●●●

●

●

●● ● ●● ●●● ●●● ● ●● ●● ● ●●● ● ● ●● ●●● ● ●●●●● ●● ●● ● ●●● ● ●● ●● ● ● ●● ●●● ● ● ●● ● ●●●●● ●● ● ●●●● ● ●●● ●● ●● ● ● ●●●● ●●●● ●● ●● ●● ●● ● ●● ● ●● ●●●●●● ● ● ●●● ● ●●●●● ●● ●● ●●● ●● ● ●●● ●● ●● ●●● ●● ●●● ●● ●●● ● ●●

● ●●● ●●

● ●● ●● ●● ●●●● ● ● ●●●● ●●● ●● ●● ● ●● ●●●●● ●● ●● ●● ●● ● ● ●● ●●● ●●● ●● ● ● ●●●● ● ● ●● ●●● ●● ● ●● ● ●●● ● ●● ●●●● ●●

●● ● ●● ●● ●●● ● ●● ●●●●● ●●● ● ●● ●●●● ●● ●● ● ●●● ● ●●● ● ●● ●● ● ●● ●● ●● ● ●●●● ● ●●●● ● ●● ●●●● ● ●● ●● ●● ●●●●

PARP1CREB1NONO

PPP1CCSIRT1

CREBBPEP300CRY2PER2DBP

PPP5CCSNK2A1

TNFGNB2L1

WDR5CSNK1E

PER1CSNK2A2CSNK2B

RORANR1I3BTRC

ALAS1PPARANFIL3

GSK3BRORBRORCCRY1

FBXW11FBXL21FBXL3

HLFIFNA1

ARNTLPPP1CACSNK1D

BHLHE41PER3

TEFBHLHE40

CSE1LPRKCA

ARNTL2NR1D1PPARG

PRKAA2NR1D2CLOCKNPAS2

AHR

PXβˆ’1

2de

cita

bine

cyta

rabi

ne h

ydro

chlo

ride

YK 4

βˆ’279

vinc

ristin

etr

iazo

loth

iadi

azin

eis

oevo

diam

ine

LYβˆ’2

1832

40G

SK46

1364

etop

osid

edo

xoru

bici

nSR

βˆ’IIβˆ’

138A

parb

enda

zole

ML3

11M

erck

60cl

ofar

abin

ePH

Aβˆ’7

9388

7K

X2βˆ’3

91ci

clop

irox

BR

Dβˆ’K

6645

3893

BIβˆ’

2536

topo

teca

nSB

βˆ’743

921

rigos

ertib

PLβˆ’D

IN

VPβˆ’2

31B

RD

βˆ’K70

5115

74B

RD

βˆ’K61

1665

97ba

rase

rtib

alis

ertib

indi

sula

mIβˆ’

BET

151

GSK

5257

62A

CH

Mβˆ’1

BR

Dβˆ’K

3422

2889

SBβˆ’2

2500

2pi

perlo

ngum

ine

narc

icla

sine

JQβˆ’1

FQIβˆ’

2C

Rβˆ’1

βˆ’31B

CD

βˆ’437

apic

idin

pano

bino

stat

pacl

itaxe

lna

kite

rpio

sin

KW

βˆ’244

9ch

lora

mbu

cil

cera

nibβˆ’

2vo

rinos

tat

mito

myc

inm

anum

ycin

Age

mci

tabi

neax

itini

bpe

vone

dist

atN

SC95

397

MK

βˆ’177

5A

ZD77

623βˆ’

Clβˆ’

AH

PCte

nipo

side

PRIM

Aβˆ’1

KPT

185

GW

βˆ’843

682X

entin

osta

tSN

Xβˆ’21

12se

rdem

etan

NVP

βˆ’BSK

805

NSC

4830

0LR

RK

2βˆ’IN

βˆ’1flu

orou

raci

lda

carb

azin

eC

ompo

und

23 c

itrat

ece

rule

nin

BR

Dβˆ’K

8018

3349

BIX

βˆ’012

94be

linos

tat

tipifa

rnib

βˆ’P1

obat

ocla

xne

uron

al d

iffer

entia

tion

indu

cer I

IIle

ptom

ycin

BIS

OX

GW

βˆ’405

833

curc

umin

CC

T036

477

BR

Dβˆ’A

9437

7914

STFβˆ’

31om

acet

axin

e m

epes

ucci

nate

criz

otin

ibC

OLβˆ’

3B

RD

βˆ’K66

5322

83tr

etin

oin

TPC

Aβˆ’1

tivan

tinib

siro

limus

phlo

retin

PAC

βˆ’1nu

tlinβˆ’

3ne

cros

ulfo

nam

ide

MST

βˆ’312

BR

D18

12TG

βˆ’101

348

SNβˆ’3

8PF

βˆ’573

228

NSC

6328

39K

Uβˆ’6

0019

KU

006

0648

GM

Xβˆ’17

78cu

curb

itaci

n I

Com

poun

d 7d

βˆ’cis

CAY

1061

8B

RD

βˆ’K35

6044

18ta

cedi

nalin

eSN

Sβˆ’03

2PF

βˆ’184

ouab

ain

olap

arib

NSC

1963

0m

omel

otin

ibva

ldec

oxib

TWβˆ’3

7tip

ifarn

ibβˆ’P

2SU

1127

4so

tras

taur

inSC

Hβˆ’7

9797

RIT

API

Kβˆ’9

3pi

fithr

inβˆ’m

uPI

βˆ’103

PFβˆ’3

7583

09O

SIβˆ’9

30M

L239

MK

βˆ’220

6go

ssyp

olfin

golim

odep

igal

loca

tech

inβˆ’3

βˆ’mon

ogal

late

WP1

130

trip

tolid

eSt

emR

egen

in 1

SMER

βˆ’3ru

xolit

inib

ML2

10M

GC

Dβˆ’2

65lin

ifani

bdo

ceta

xel

dexa

met

haso

neda

porin

adB

RD

βˆ’K92

8560

60A

BTβˆ’

737

RG

βˆ’108

olig

omyc

in A

NVP

βˆ’TA

E684

MLN

2238

ML0

31m

etho

trex

ate

eras

tindi

naci

clib

BR

Dβˆ’K

4159

7374

BR

Dβˆ’K

2653

1177

bort

ezom

ibB

MSβˆ’

3455

41ba

rdox

olon

e m

ethy

lA

Zβˆ’31

46AT

7867

Pvalue ● ● ● ●0.05 10βˆ’5 10βˆ’10 < 10βˆ’15

BHLH

E40

AHR

NPA

S2C

SNK1

DPP

ARG

CSE

1LC

RY1

CLO

CK

PRKA

A2N

R1D

2TN

FPE

R2

EP30

0PA

RP1

CR

EB1

PPP1

CC

NO

NO

RO

RB

SIR

T1C

REB

BP

BHLHE40AHRNPAS2CSNK1DPPARGCSE1LCRY1CLOCKPRKAA2NR1D2TNFPER2EP300PARP1CREB1PPP1CCNONORORBSIRT1CREBBP

βˆ’0.5 0 0.5Cor Coeff R

βˆ’20 βˆ’10 0 10 20

0.00

0.05

0.10

0.15

zβˆ’scored correlation strength

Prob

alilit

y de

nsity

est

imat

e

D

Random pairs

Targeted pairs

Figure S7. Related to Figure 7. Correlation between clock gene expression and drug sensitivity. (A) Distribution of z-scored Pearson correlation coefficients between 128 annotated small molecule–target pairs (111 compounds and 83 target genes, green) across all cancer cell lines compared to random sampling of correlation coefficients (black) in GDSC. Dashed line represents two-tailed Bonferroni-corrected significance (|z| = 3.89). (B) and (D) The number of compounds with positive (red) and negative (blue) correlation of expression levels of clock related genes and drug sensitivity in GDSC and CTRP, respectively. (C) Hierarchi-cal clustering of Pearson correlation coefficient for top 10 genes of same correlation tendency with drug sen-sitivity in two groups (left and right of top 10 genes in Figure 6A, respectively). (E) Correlation between drug sensitivity and clock genes in at least 10 clock genes (green: negative correlation; magenta: positive correla-tion; size: p-value) in CTRP .

010

020

0C

ompo

unds

Cou

nt Positive Cor Negative CorCTRP

PAR

P1C

REB

1N

ON

OPP

P1C

CSI

RT1

CR

EBBP

EP30

0PE

R2

CRY

2PP

P5C

DBP

CSN

K2A1

GN

B2L1

TNF

WD

R5

CSN

K1E

PER

1C

SNK2

A2C

SNK2

BR

OR

AN

R1I

3BT

RC

ALAS

1N

FIL3

P PAR

AR

OR

BAR

NTL

CRY

1G

SK3B HLF

RO

RC

CSN

K1D

FBXW

11BH

LHE4

1PE

R3

TEF

BHLH

E40

CSE

1LPR

KCA

ARN

TL2

NR

1D1

PAR

GPR

KAA2

NR

1D2

CLO

CK

NPA

S2AH

R

Page 9: The Genomic Landscape and Pharmacogenomic Interactions of

Cancer type Abbreviation Name

# of Tumor Samples

# of Normal Samples

Tumor/Normal Pair

Adrenocortical Carcinoma ACC 79 0 No Bladder Urothelial Carcinoma BLCA 408 19 Yes Breast Invasive Carcinoma BRCA 1104 114 Yes Cervical Squamous Cell Carcinoma and Endocervical Adenocarcinoma CESC 307 0 No Cholangiocarcinoma CHOL 36 0 No Colon Adenocarcinoma COAD 288 26 Yes Lymphoid Neoplasm Diffuse Large B-cell Lymphoma DLBC 48 0 No Esophageal Carcinoma ESCA 185 11 Yes Glioblastoma Multiforme GBM 169 0 No Head and Neck squamous Cell Carcinoma HNSC 522 43 Yes Kidney Chromophobe KICH 66 25 Yes Kidney Renal Clear Cell Carcinoma KIRC 534 72 Yes Kidney Renal Papillary Cell Carcinoma KIRP 291 32 Yes Brain Lower Grade Glioma LGG 534 0 No Liver Hepatocellular Carcinoma LIHC 374 50 Yes Lung Adenocarcinoma LUAD 517 58 Yes Lung Cquamous Cell Carcinoma LUSC 503 51 Yes Mesothelioma MESO 87 0 No Ovarian Serous Cystadenocarcinoma OV 309 0 No Pancreatic Adenocarcinoma PAAD 179 0 No Pheochromocytoma and Paraganglioma PCPG 184 0 No Prostate Adenocarcinoma PRAD 498 52 Yes Rectum Adenocarcinoma READ 95 0 No Sarcoma SARC 263 0 No Skin Cutaneous Melanoma SKCM 473 0 No Stomach Adenocarcinoma STAD 415 32 Yes Testicular Germ Cell Tumors TGCT 156 0 No Thyroid Carcinoma THCA 513 59 Yes Thymoma THYM 120 0 No Uterine Corpus Endometrial Carcinoma UCEC 177 0 No Uterine Carcinosarcoma UCS 57 0 No Uveal Melanoma UVM 80 0 No

Supplementary tables

Table S1. Related to STAR Methods. Number of tumor and normal samples in each cancer type


Recommended