SUPPLEMENTARY TABLES
`
`Supplementary Table 1. Targeted Genes
`
`ABL1
`ABL2
`AKT1
`AKT2
`AKT3
`ALK
`APC
`ATM
`AURKA
`BCL2
`BRAF
`BRCA1
`BRCA2
`CCND1
`CCNE1
`CDC73
`CDH1
`CDK4
`CDK6
`CDK8
`CDKN1A
`CDKN2A
`CEBPA
`CHEK1
`CHEK2
`CREBBP
`CRKL
`CSF1R
`
`CTNNB1
`EGFR
`EPHA3
`EPHA5
`EPHB6
`ERBB2
`ERBB3
`ERBB4
`FAM123B
`FBXW7
`FGFR1
`FGFR2
`FGFR3
`FGFR4
`FHIT
`FKBP9
`FLT1
`FLT3
`FLT4
`FRAP1
`GATA1
`GNAQ
`GNAS
`GUCY1A2
`HNF1A
`HRAS
`HSP90AA1
`IDH1
`
`IDH2
`IGF1R
`IKBKE
`IKZF1
`JAK2
`JAK3
`KDR
`KEAP1
`KIAA0774
`KIAA1303
`KIT
`KRAS
`MAP2K1
`MAP2K2
`MAP2K4
`MCL1
`MDM2
`MDM4
`MEN1
`MET
`MITF
`MLH1
`MLL
`MPL
`MRE11A
`MSH2
`MSH6
`MYC
`
`MYCL1
`MYCN
`NF1
`NF2
`NKX2-1
`NOTCH1
`NOTCH2
`NOTCH3
`NOTCH4
`NPM1
`NRAS
`NTRK1
`NTRK2
`NTRK3
`PAX5
`PDGFRA
`PDGFRB
`PDPK1
`PIK3CA
`PIK3R1
`PTCH1
`PTEN
`PTK2B
`PTPN11
`PTPRD
`RAF1
`RB1
`REL
`
`RET
`RICTOR
`RUNX1
`RUNX1T1
`SMAD2
`SMAD3
`SMAD4
`SMARCA4
`SMARCB1
`SMO
`SOCS1
`SRC
`STK11
`SUFU
`TCF4
`TERT
`TET2
`TGFBR2
`TNFAIP3
`TOP1
`TP53
`TSC1
`TSC2
`TSHR
`VHL
`WT1
`ZNF668
`
`Exons from 137 genes were targeted for hybrid selection and massively parallel sequencing.
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`Supplementary Table 2. Pharmacogenomic Loci
`
`
`GENE
`ABCB1
`ABCB1
`ABCC2
`ABCC4
`ABCG2
`ABCG2
`ABCG2
`C1orf144
`CYP1B1
`CYP2C19
`CYP2C19
`CYP2C8
`CYP2C8
`CYP2C8
`CYP2C8
`CYP2C8
`CYP2D6
`CYP2D6
`CYP2D6
`CYP2D6
`CYP2D6
`CYP2D6
`CYP2D6
`CYP2D6
`CYP2D6
`CYP2D6
`CYP3A4
`CYP3A4
`CYP3A4
`CYP3A4
`CYP3A4
`CYP3A4
`CYP3A4
`CYP3A4
`CYP3A4
`CYP3A5
`CYP3A5
`CYP3A5
`DPYD
`DPYD
`DPYD
`DPYD
`ERCC2
`ESR1
`ESR2
`
`LOCUS
`chr7:86976581
`chr7:86998554
`chr10:101610761
`chr13:94613416
`chr4:89252551
`chr4:89271347
`chr4:89274403
`chr1:16578662
`chr2:38151707
`chr10:96509051
`chr10:96511647
`chr10:96786964
`chr10:96788739
`chr10:96808096
`chr10:96808109
`chr10:96817020
`chr22:40853554
`chr22:40853749
`chr22:40853887
`chr22:40854122
`chr22:40854188
`chr22:40854891
`chr22:40855030
`chr22:40855078
`chr22:40855716
`chr22:40856638
`chr7:99196395
`chr7:99196460
`chr7:99197606
`chr7:99204017
`chr7:99204029
`chr7:99205328
`chr7:99205363
`chr7:99219597
`chr7:99220032
`chr7:99088330
`chr7:99100771
`chr7:99108475
`chr1:97688202
`chr1:97753983
`chr1:97937679
`chr1:98121473
`chr19:50546759
`chr6:152205074
`chr14:63769569
`
`RELEVANT DRUGS
`Idarubicin, AraC, Paclitaxel
`Idarubicin, AraC, Taxanes, Platinums
`Docetaxel
`6MP
`Methotrexate
`Gefitinib
`Methotrexate
`Daunorubicin
`Daunorubicin, Paclitaxel
`Tamoxifen
`Tamoxifen
`Paclitaxel
`Paclitaxel
`Paclitaxel
`Paclitaxel
`Paclitaxel
`Tamoxifen
`Tamoxifen
`Tamoxifen
`Tamoxifen
`Tamoxifen
`Tamoxifen
`Tamoxifen
`Tamoxifen
`Tamoxifen
`Tamoxifen
`Multiple
`Multiple
`Multiple
`Multiple
`Multiple
`Multiple
`Multiple
`Multiple
`Multiple
`Multiple
`Multiple
`Multiple
`5-FU
`5-FU
`5-FU, Capecitabine
`5-FU
`5-FU
`Tamoxifen
`Tamoxifen
`
`
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`Cetuximab
`chr1:159781166
`FCGR3A
`Multiple
`chr5:176452849
`FGFR4
`Multiple
`chr11:67109265
`GSTP1
`Multiple
`chr11:67110155
`GSTP1
`6MP
`chr20:3141842
`ITPA
`Cisplatin
`chr2:169719231
`LRP2
`Daunorubicin
`chr9:139102689
`MAN1B1
`Methotrexate
`chr1:11777044
`MTHFR
`Methotrexate
`chr1:11777063
`MTHFR
`Methotrexate
`chr1:11778965
`MTHFR
`Cisplatin, Doxorubicin, Anthracyclines
`chr16:68302646
`NQO1
`Daunorubicin
`chr2:206360545
`NRP2
`Methotrexate
`chr21:45782222
`SLC19A1
`Cisplatin
`chr6:160590272
`SLC22A2
`Docetaxel
`chr12:20936961
`SLCO1B3
`Cyclophosphamide
`chr6:160033862
`SOD2
`Tamoxifen
`chr16:28524986
`SULT1A1
`Tamoxifen
`chr16:28525015
`SULT1A1
`Tamoxifen
`chr16:28528073
`SULT1A1
`Tamoxifen
`chr16:28528301
`SULT1A1
`Purines
`chr6:18247207
`TMPT
`6MP
`chr6:18238897
`TPMT
`6MP
`chr6:18238991
`TPMT
`6MP
`chr6:18251934
`TPMT
`5-FU
`chr18:647646
`TYMS
`5-FU
`chr18:663451
`TYMS
`Irinotecan
`chr2:234255266
`UGT1A1
`Irinotecan
`chr2:234255709
`UGT1A1
`Irinotecan
`chr2:234330398
`UGT1A1
`Irinotecan
`chr2:234330521
`UGT1A1
`Irinotecan
`chr2:234333620
`UGT1A1
`Irinotecan
`chr2:234333883
`UGT1A1
`Irinotecan
`chr2:234334358
`UGT1A1
`5-FU
`chr3:125939432
`UMPS
`Abbreviations: 6MP = 6-mercaptopurine, 5FU = 5-fluorouracil, AraC = cytarabine
`
`79 loci in 34 genes which might predict sensitivity or resistance to cancer therapies were also
`targeted
`for sequencing.
` Drugs
`related
`to polymorphisms at
`these
`loci are
`listed.
`
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`Supplementary Table 3. Known genomic alterations in 10 cancer cell lines.
`
`Cell Line
`Somatic Alterations in COSMIC
`Primary Disease
`CDKN2A, NRAS, TP53
`HL-60
`Acute Myelogenous Leukemia
`Colon Cancer
`HT-29
`APC, BRAF, PIK3CA, SMAD4, TP53
`Breast Cancer
`MCF7
`CDKN2A, PIK3CA
`Breast Cancer
`MDA-MB-231
`BRAF, CDKN2A, KRAS, NF2, TP53
`NCI-H1395
`BRAF, STK11
`Lung Adenocarcinoma
`NCI-H358
`Lung Bronchoalveolar Carcinoma KRAS
`PIK3CA, RB1, TP53
`NCI-H69
`Lung Small Cell Carcinoma
`Breast Cancer
`ZR-75-30
`CDH1
`Prostate Cancer
`PC-3
`PTEN, TP53
`Melanoma
`SK-MEL-2
`BRAF, EGFR, TP53
`
`DNA from 10 cancer cell lines were sequenced. Known genomic alterations in these cell lines
`were obtained from the COSMIC database.
`
`
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`Supplementary Table 4. Summary of sequencing results for cell lines
`
`
`CELL LINE
`
`TUMOR
`TYPE
`
`HAPMAP
`HT-29 (50% input)
`MCF7
`MDA-MB-231
`ZR-75-30
`HL-60
`NCI-H69
`NCI-358
`PC-3
`SK-MEL-28
`NCI-1395
`HT-29
`
`N/A
`Colon
`Breast
`Breast
`Breast
`Leukemia
`Lung
`Lung
`Prostate
`Melanoma
`Lung
`Colon
`
`PF READS PERCENT
`OF TOTAL
`PF READS
`IN POOL
`14,316,958 8%
`7,809,802
`5%
`14,643,284 9%
`15,609,408 9%
`17,709,492 10%
`15,110,292 9%
`12,108,024 7%
`12,119,682 7%
`17,359,026 10%
`13,823,238 8%
`14,095,256 8%
`14,432,968 9%
`
`PERCENT
`SELECTED
`BASES
`
`MEAN
`TARGET
`COVERAGE
`
`55%
`60%
`60%
`59%
`57%
`58%
`61%
`61%
`55%
`65%
`55%
`62%
`
`469
`295
`540
`568
`593
`543
`451
`441
`584
`552
`510
`543
`
`PERCENT OF
`TARGET BASES
`WITH AT LEAST
`30X COVERAGE
`96%
`95%
`96%
`96%
`96%
`96%
`96%
`96%
`96%
`97%
`96%
`96%
`
`
`Pools of genomic DNA from cancer cell lines were subject to exon capture and sequenced in a
`single 100-bp paired-end Illumina HiSeq2000 lane. Purity filtered (PF) sequence reads for each
`sample are shown; the percent of total PF reads in the pool demonstrate the relative
`representation of each sample within the pool. Percent selected bases indicate the percent of
`bases that mapped within 250 bp of a target exon, including both on-bait and near-bait bases.
`Mean target coverage represents the average number of unique reads in which each base was
`sequenced.
`
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`Supplementary Table 5. Summary of genomic alterations in cell lines
`
`
`SNVs MISSENSE
`SNVs
`
`NONSENSE
`SNVs
`
`INDELS
`
`COPY
`NUMBER
`GAINS
`0
`2
`0
`2
`1
`1
`0
`0
`0
`2
`0
`
`COPY
`NUMBER
`LOSSES
`2
`1
`3
`0
`1
`0
`2
`1
`0
`0
`0
`
`CELL LINE
`
`HT-29 (50% input)
`MCF7
`MDA-MB-231
`ZR-75-30
`HL-60
`NCI-H69
`NCI-358
`PC-3
`SK-MEL-28
`NCI-1395
`HT-29
`
`MEAN
`TARGET
`COVERAGE
`295
`540
`568
`593
`543
`451
`441
`584
`552
`510
`543
`
`12
`9
`10
`22
`7
`10
`9
`2
`13
`5
`25
`
`7
`5
`6
`9
`4
`6
`7
`0
`9
`5
`14
`
`2
`1
`2
`1
`1
`2
`0
`0
`0
`0
`5
`
`2
`0
`1
`0
`0
`1
`0
`1
`0
`1
`2
`
`
`Summary of single nucleotide variants, indels, and copy number alterations for the 12 pooled cell
`lines. Copy number alterations are calculated as the log2 ratio of coverage as compared to a
`normal diploid sample. Copy number gains are defined as a log2 ratio greater than 1.58 (3-fold);
`copy number losses are defined as log2 ratio less than -1.58 (3-fold).
`
`
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`Supplementary Table 6. Single-nucleotide variants and indels in breast cancer cell line
`MDA-MB-231
`
`
`NUMBER
`TYPE OF
`PROTEIN
`CODING
`OF READS
`SNV
`CHANGE
`CHANGE
`GENE
`701
`Missense
`p.G464V
`c.1391G>T
`BRAF
`428
`Nonsense
`p.E839*
`c.2515G>T
`EPHA3
`Synonymous 354
`p.N6N
`c.18C>T
`GNAS
`Missense
`70
`p.G13D
`c.38G>A
`KRAS
`Missense
`996
`p.E226K
`c.676G>A
`MYCL1
`c1398_1399insC p.T467Hfs*3 Frameshift
`227
`NF1
`c.691G>T
`p.E231*
`Nonsense
`350
`NF2
`NOTCH3 c.1102A>T
`p.T368S
`Missense
`951
`PDGFRA c.515A>T
`p.Y172F
`Missense
`996
`PIK3CA
`c.363C>T
`p.I121I
`Synonymous 123
`TP53
`c.839G>A
`p.R280K
`Missense
`769
`
`ALLELE
`FREQUENCY
`56%
`32%
`20%
`66%
`35%
`100%
`100%
`66%
`35%
`39%
`100%
`
`
`The single nucleotide variants and indels detected in one of the 12 pooled samples, breast cancer
`cell line MD-MBA-231. Total number of reads and the frequency of the variant (out of the total
`reads) are shown. Mutations listed in bold have previously been reported in the COSMIC database
`for this cell line.
`
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`Supplementary Table 7. Correlation of copy number alterations detected by exon capture
`and microarrays in cell lines
`
`Cell Line
`HT-29 (50% input)
`MCF7
`MDA-MB-231
`ZR-75-30
`HL-60
`NCI-H69
`NCI-358
`PC-3
`SK-MEL-28
`NCI-1395
`HT-29
`
`Correlation Coefficient
`0.90
`0.96
`0.94
`0.94
`0.96
`0.94
`0.98
`0.89
`0.97
`0.98
`0.98
`
`
`
`
`
`
`
`
`
`
`
`
`
`
`Correlation coefficients between gene-level copy number alterations as detected by exon capture
`and copy number data previously obtained using a high-density SNParray (Affymetrix SNP 6.0
`platform).
`
`
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`Supplementary Table 8. Summary of genomic alterations in FFPE tumor samples
`
`SAMPLE
`
`TUMOR
`TYPE
`
`TUMOR
`PURITY
`
`MEAN
`TARGET
`COVERAGE
`
`SNVs MISSENSE
`SNVs
`
`NONSENSE
`SNVs
`
`INDELS COPY
`NUMBER
`GAINS
`
`COPY
`NUMBER
`LOSSES
`
`Colon
`Colon
`Colon
`Colon
`Breast
`Breast
`Colon
`Breast
`Colon
`Colon
`
`60%
`10%
`20%
`60%
`80%
`70%
`50%
`80%
`60%
`50%
`
`457
`353
`498
`300
`472
`532
`250
`537
`116
`410
`
`12
`8
`33
`12
`9
`15
`30
`5
`4
`27
`
`7
`5
`20
`6
`5
`7
`15
`4
`3
`13
`
`0
`0
`1
`3
`0
`0
`1
`0
`1
`3
`
`FFPE 1
`FFPE 2
`FFPE 3
`FFPE 4
`FFPE 5
`FFPE 6
`FFPE 7
`FFPE 8
`FFPE 9
`FFPE 10
`
`Summary of single nucleotide variants, indels, and copy number alterations for the pooled FFPE
`samples. Copy number alterations are calculated as the log2 ratio of coverage as compared to a
`normal diploid sample. Copy number gains are defined as a log2 ratio greater than 1.58 (3-fold);
`copy number losses are defined as log2 ratio less than -1.58 (3-fold).
`
`0
`1
`5
`0
`0
`2
`1
`1
`2
`2
`
`0
`0
`0
`0
`2
`0
`0
`0
`0
`0
`
`0
`0
`0
`0
`2
`0
`0
`0
`0
`0
`
`
`
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`Supplementary Table 9. Pharmacogenomic polymorphisms in UGT1A1 and ERCC2
`
`
`Samples
`
`Cancer
`Type
`Colon
`Colon
`Colon
`Colon
`Breast
`Breast
`Colon
`Breast
`Colon
`Colon
`
`UGT1A1-G3156A
`Reads
`Genotype
`478
`G/A
`318
`G/A
`636
`G/A
`394
`G
`321
`G/A
`589
`G
`303
`G/A
`580
`G
`121
`G
`411
`G
`
`FFPE 1
`FFPE 2
`FFPE 3
`FFPE 4
`FFPE 5
`FFPE 6
`FFPE 7
`FFPE 8
`FFPE 9
`FFPE 10
`
`Allele incidence for 2 exemplary pharmacogenomics loci across all 10 FFPE samples.
`
`ERCC2-K751QC
`Reads
`Genotype
`463
`T
`480
`T/G
`442
`T
`244
`T
`266
`T
`696
`T
`272
`T
`759
`T
`99
`T/G
`471
`T
`
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`SUPPLEMENTARY FIGURE LEGENDS
`
`Supplementary Figure 1. Approach to tumor genomic profiling. Genomic DNA is extracted
`from tumor samples and used to generate sequencing libraries. A DNA barcode is appended to
`each library by PCR. Following quantification of libraries, equimolar pools consisting of 12
`barcoded tumor DNAs and normal diploid control DNAs are made. The DNA pools are subjected to
`solution-phase hybrid capture with the biotinylated RNA baits corresponding to the coding
`sequence of the 137 “druggable” or potentially “actionable” genes known to undergo somatic
`genomic alterations in cancer. Massively parallel sequencing is performed on the captured
`sequences. The sequencing data were deconvoluted to match all high-quality reads with the
`corresponding tumor samples and call single-nucleotide variations, small insertions/deletions, and
`copy number alterations.
`
`Supplementary Figure 2. Exon capture bait performance. (A) The percent of targets in a
`normal diploid sample (HapMap) with at least the specified sequence coverage. As shown, 97% of
`targets in the HapMap sample were covered at 30x or higher. The 80th percentile target coverage
`was 191x. (B) The number of targets in a HapMap sample with specified sequence coverage. (C)
`Coverage for each target in a normal diploid sample (HapMap) was plotted as a function of GC
`content. (D) Correlation of target coverage for two independently generated libraries from the HT-
`29 cell line that were captured and sequenced within a single pool. Coverage for each genomic
`target was highly correlated with a correlation coefficient of 0.86. (E) Correlation of target coverage
`for two separate captures and sequencing runs for a single HapMap library, with a correlation
`coefficient of 0.96. (F) Correlation of target coverage for two separate captures and sequencing
`runs for a single HT-29 library, with a correlation coefficient of 0.97.
`
`Supplementary Figure 3. Copy number by quantitative PCR in sample FFPE 9. Copy number
`correlation between exon capture and QPCR in sample FFPE 9. Quantitative PCR of FGFR1,
`CCND1, and NOTCH1 using 3 independent sets of primers was performed and average values for
`each gene were compared to exon capture copy number.
`
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`SUPPLEMENTARY METHODS
`
`Blocking Oligonucleotides:
`Oligonucleotide
`Sequence (5’-3’)
`IndexBlock_1
`CAA GCA GAA GAC GGC ATA CGA GAT ATC ACG GTG ACT GGA GTT C
`IndexBlock_2
`CAA GCA GAA GAC GGC ATA CGA GAT CGA TGT GTG ACT GGA GTT C
`IndexBlock_3
`CAA GCA GAA GAC GGC ATA CGA GAT TTA GGC GTG ACT GGA GTT C
`IndexBlock_4
`CAA GCA GAA GAC GGC ATA CGA GAT TGA CCA GTG ACT GGA GTT C
`IndexBlock_5
`CAA GCA GAA GAC GGC ATA CGA GAT ACA GTG GTG ACT GGA GTT C
`IndexBlock_6
`CAA GCA GAA GAC GGC ATA CGA GAT GCC AAT GTG ACT GGA GTT C
`IndexBlock_7
`CAA GCA GAA GAC GGC ATA CGA GAT CAG ATC GTG ACT GGA GTT C
`IndexBlock_8
`CAA GCA GAA GAC GGC ATA CGA GAT ACT TGA GTG ACT GGA GTT C
`IndexBlock_9
`CAA GCA GAA GAC GGC ATA CGA GAT GAT CAG GTG ACT GGA GTT C
`IndexBlock_10
`CAA GCA GAA GAC GGC ATA CGA GAT TAG CTT GTG ACT GGA GTT C
`IndexBlock_11
`CAA GCA GAA GAC GGC ATA CGA GAT GGC TAC GTG ACT GGA GTT C
`IndexBlock_12
`CAA GCA GAA GAC GGC ATA CGA GAT CTT GTA GTG ACT GGA GTT C
`
`Primers for QPCR:
`Oligonucleotide
`Sequence (5’-3’)
`FGFR1_A_FWD
`TGA GCT GTC AAG GAC AGT GG
`FGFR1_A_REV
`GAC AGA TGT GCC TTC TGC AA
`FGFR1_B_FWD GTG GTG TTG GCA GAG GCT AT
`FGFR1_B_REV
`TGC AAG GAC AGA AGC ATC AC
`FGFR1_C_FWD GAG CCT GAA GTG GGT GAG AG
`FGFR1_C_REV
`CTC CGT GTT GCT GTT TCT GA
`CCND1_A_FWD TGA AGA ATC CCT GGA TGG AG
`CCND1_A_REV GCC TGG GGT GAG ATA CAA GA
`CCND1_B_FWD CCC TTC TCT CCC GCT AGA AC
`CCND1_B_REV
`ACC CCT TCC TCC TTC AGA AA
`CCND1_C_FWD TGA ACT ACC TGG ACC GCT TC
`CCND1_C_REV GGG GAT GGT CTC CTT CAT CT
`NOTCH1_A_FWD TCT GGG GTC CTC TTT TTC CT
`NOTCH1_A_REV ACA GAG CCG AAT CCA GCT TA
`NOTCH1_B_FWD AGG CCG TGC AGA GTA AGT GT
`NOTCH1_B_REV GGT AGC AAC TGG CAC AAA CA
`NOTCH1_C_FWD GAC TGC AGC GAG AAC ATT GA
`NOTCH1_C_REV GGG ACA CTC GCA GTA GAA GG
`LINE_CTRL_FWD AAA GCC GCT CAA CTA CAT GG
`LINE_CTRL_REV TGC TTT GAA TGC GTC CCA GAG
`
`
`
`
`
`12
`
`Foresight EX1039
`Foresight v Personalis
`
`

`

`SUPPLEMENTARY APPENDIX
`
`“Supplementary Appendix.xlsx”
`
`TAB 1: SNVs – cell lines
`TAB 2: Indels – cell lines
`TAB 3: Target Coverage – cell lines
`TAB 4: Gene Coverage – cell lines
`TAB 5: Gene Copy Number (log2 ratio) – cell lines
`TAB 6: SNP Array Copy Number – cell lines
`TAB 7: SNVs – FFPE samples
`TAB 8: Indels – FFPE samples
`TAB 9: Target Coverage – FFPE samples
`TAB 10: Gene Coverage – FFPE samples
`TAB 11: Gene Copy Number (log2 ratio) – FFPE samples
`TAB 12: Bait sequences
`
`
`
`
`13
`
`Foresight EX1039
`Foresight v Personalis
`
`