( 19 ) United States
`( 12 ) Patent Application Publication ( 10 ) Pub . No .: US 2022/0195530 A1
`( 43 ) Pub . Date :
`Jun . 23 , 2022
`Diehn et al .
`
`US 20220195530A1
`
`IN
`
`( 71 )
`
`( 54 ) IDENTIFICATION AND USE OF
`CIRCULATING NUCLEIC ACID TUMOR
`MARKERS
`Applicant : The Board of Trustees of the Leland
`Stanford Junior University , Stanford ,
`CA ( US )
`( 72 ) Inventors : Maximilian Diehn , San Carlos , CA
`( US ) ; Arash Ash Alizadeh , San Mateo ,
`CA ( US ) ; Aaron M. Newman , Palo
`Alto , CA ( US ) ; Scott V. Bratman , Palo
`Alto , CA ( US )
`
`( 21 ) Appl . No .: 17 / 406,948
`
`( 22 ) Filed :
`
`Aug. 19 , 2021
`
`Related U.S. Application Data
`( 63 ) Continuation of application No. 14 / 774,518 , filed on
`Sep. 10 , 2015 , now abandoned , filed as application
`No. PCT / US2014 / 025020 on Mar. 12 , 2014 .
`( 60 ) Provisional application No. 61 / 798,925 , filed on Mar.
`15 , 2013 .
`Population
`level analysis
`
`Publication Classification
`
`( 51 ) Int . Ci .
`C12Q 1/6886
`G16B 30/00
`C12Q 1/6806
`C12Q 1/6855
`C12Q 1/6827
`G16B 30/10
`( 52 ) U.S. CI .
`???
`
`( 2006.01 )
`( 2006.01 )
`( 2006.01 )
`( 2006.01 )
`( 2006.01 )
`( 2006.01 )
`
`C12Q 1/6886 ( 2013.01 ) ; G16B 30/00
`( 2019.02 ) ; C12Q 1/6806 ( 2013.01 ) ; C12Q
`2600/156 ( 2013.01 ) ; C12Q 1/6827 ( 2013.01 ) ;
`G16B 30/10 ( 2019.02 ) ; C12Q 1/6855
`( 2013.01 )
`
`( 57 )
`ABSTRACT
`Methods for creating a selector of mutated genomic regions
`and for using the selector set to analyze genetic alterations
`in a cell - free nucleic acid sample are provided . The methods
`can be used to measure tumor - derived nucleic acids in a
`blood sample from a subject and thus to monitor the pro
`gression of disease in the subject . The methods can also be
`used for cancer screening , cancer diagnosis , cancer progno
`sis , and cancer therapy designation .
`Specification includes a Sequence Listing .
`Patient
`level analysis
`
`Recurrent
`mutations
`
`??? ?
`
`Tissue
`biopsy
`
`Blood
`draw
`
`Tumor / Normal
`genomic DNA
`
`Cell - free
`DNA
`
`CAPP - Seq
`selector
`library
`
`Personalized
`markers
`Mutation
`Mutation
`discovery
`recovery
`
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`

`Patent Application Publication
`Jun . 23 , 2022 Sheet 1 of 50
`Population
`level analysis
`
`Figure 1A
`
`US 2022/0195530 A1
`
`Patient
`level analysis
`???? ? ???
`
`Recurrent
`mutations
`EESTI
`AUTO
`
`Tissue
`biopsy
`
`Tumor / Normal
`genomic DNA
`
`Cell - free
`DNA
`
`CAPP - Seq
`selector
`library
`
`Personalized
`Mutation markers Mutation
`discovery
`recovery
`
`Figure 1B
`
`Phases of selector
`( 2 )
`
`Reccurence RI Predicted
`
`a1 SNY
`
`NVS
`
`SNE
`
`( 6 )
`Add fusions
`
`No. of targeted genomic regions
`
`
`
`NSCLC patients ( % )
`60
`
`Length ( kb )
`
`0
`
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`Patent Application Publication
`Figure 10
`
`Jun . 23 , 2022 Sheet 2 of 50
`
`US 2022/0195530 A1
`
`Lung adenocarcinoma
`
`
`
`Cumulative percentage of patients ( % )
`
`70
`
`4 mutations / patient
`
`50
`
`20
`10
`
`2
`Mutations per patient ( log , scale )
`Training
`Validation
`
`Random
`
`Other adenocarcinomas
`
`Figure 1D
`
`100
`Cumulative percentage of patients ( % )
`
`
`
`70
`
`2
`
`.....
`
`2
`Mutations per patient ( log , scale )
`Colon
`Rectal
`Endometrioid
`
`32
`
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`Patent Application Publication
`
`Jun . 23 , 2022 Sheet 3 of 50
`
`US 2022/0195530 A1
`
`Figure 2A
`
`Quenberg 400.000
`
`Figure 2B
`
`25,000
`
`20,000
`
`15 000
`
`Depth 10,000
`
`5 000
`
`Figure 2C
`
`17,500
`
`12,500
`10.000
`
`Depth
`
`5,000
`2.500
`
`0
`
`250
`200
`Fragment length ( bp )
`
`CAPP - Seq selector
`( ordered by genomic region )
`
`i
`entreteniment
`CAPP - Seq selector
`( ordered by decreasing mean depth )
`
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`Patent Application Publication
`
`Jun . 23 , 2022 Sheet 4 of 50
`
`US 2022/0195530 A1
`
`Median 75th perc . 95th perc
`
`1
`
`1
`
`Figure 2D
`
`0.4965
`0.495511
`0.00201
`
`Frequency 0.0010
`
`0.0005
`
`popper
`
`Selector - wide background rate ( % )
`( n
`40 plasma DNA samples )
`
`Figure 2E
`
`0.8
`
`NSCLC
`
`Healthy
`
`
`
`
`
`Biological background rate ( % )
`
`Store
`
`0.2
`
`Plasma DNA samples
`( n = 35 NSCLC samples , 5 healthy )
`
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`Patent Application Publication
`
`Jun . 23 , 2022 Sheet 5 of 50
`
`US 2022/0195530 A1
`
`***
`P < 0.01
`
`CINNB1 : S37A
`
`
`
`G10498 EGFR : 67196
`
`
`GTNNBI : 032Y PIK3CA
`
`061H CTNNB1 S4SF .
`
`ARC : R1114x NAAS :
`
`W06204393
`GER : G7190
`
`KRAS G126
`
`
`
`
`Ranked list of recurrent somatic mutations ( top 25 and
`
`?INNBAS CIK
`tested ) Figure 2F
`
`bottom of 107 alleles
`R248W KRAS 041 TP63 .
`
`
`APC Q1333x
`
`
`PIEN , R233X
`
`TËN : R1GOK
`
`APC : 21450x
`
`TP53 . G2468
`HELZE 88d1
`TP53 : 2730
`
`PIEN : R1730
`
`TP53 : A2480
`
`
`0 TP53 : A3O6K
`TP53 R175H
`
`0.05
`
`
`I
`0.25 ) 0.20
`)
`( %
`rate
`Biological background
`
`> GY 0.10
`
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`Patent Application Publication
`
`Jun . 23 , 2022 Sheet 6 of 50
`
`US 2022/0195530 A1
`
`Figure 2G
`
`0.97
`0.84
`
`0.6
`
`CAPP - Seq predicted fraction ( % )
`
`
`
`0.24
`
`R 0.994
`
`1
`
`0.05 .
`
`0 00
`0.05
`0
`0 0.1 0.2 0.3 0.4 0.5 0.6 0.7 0.8 0.9 1.0
`Known fraction ( % )
`
`Figure 2H
`
`Spike
`
`www.the
`
`
`
`
`
`Mean reporter fraction ( % )
`
`0.3
`
`1
`
`www
`
`.
`
`0.5 %
`
`0.025 %
`9 10 11 12 13 14
`No. of reporters considered
`
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`Patent Application Publication
`
`Jun . 23 , 2022 Sheet 7 of 50
`
`US 2022/0195530 A1
`
`Figure 21
`
`
`
`Correlation coeficient 0.90
`
`*
`*
`
`0.85
`
`10
`23 4 5 6 7 8 9 10 11 12 13 14
`No. of reporters considered
`
`Figure 3A
`
`100
`
`80
`
`Sensitivity ( % )
`60
`
`40
`
`20
`
`0
`0
`
`Pre - treatment plasma DNA
`
`Sp AUC
`Sn
`Stages II - IV 100 % 96 % 0.99
`All stages
`85 %
`96 % 0.95
`
`??
`
`80
`60
`40
`20
`100 % -Specificity ( % )
`
`100
`
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`Patent Application Publication
`
`Jun . 23 , 2022 Sheet 8 of 50
`
`US 2022/0195530 A1
`
`Figure 3B
`
`Patient - specific reporters
`Stage 1
`Stages II to IV
`P16 * P14
`P17 P1 *
`P15 *
`P13
`
`EN
`
`Healthy
`Pg ** NSCLC
`
`P16
`
`
`
`Plasma DNA samples ( n = 18 )
`
`P3
`215
`
`TP
`
`-TN
`
`FP
`
`TN
`FN
`
`* includes indel ( s )
`** includes fusion ( s )
`
`Figure 30
`
`1,000
`
`
`
`Tumor volume ( cm ) Stage 1
`
`???? ?? ?????
`
`1
`
`= 0.89
`R
`P = 0.0002
`
`CIDNA ( pg mL- ' )
`
`1000
`
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`Patent Application Publication
`
`Jun . 23 , 2022 Sheet 9 of 50
`
`US 2022/0195530 A1
`
`Figure 4A
`
`5
`
`TO B6
`
`PET / CT
`Stage IIB
`100
`CIDNA ( pg mL )
`
`5
`SNVs / indel ( CAPP - Seg )
`O ND ( CAPP - Seq )
`
`11
`
`( months )
`
`Figure 4B
`
`Chemotherapy
`
`Month
`
`0
`
`wwwrit
`
`Stage IV
`
`CIDNA ( pg mL )
`
`
`
`Tumor volume ( cm )
`
`Tumor volume
`
`100
`
`
`
`Tumor volume ( cm )
`
`Fusions ( CAPP - Seq )
`O ND ( CAPP - Seq )
`
`( months )
`
`14
`
`A Tumor volume
`
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`Patent Application Publication
`Figure 4C
`41 Stage IV
`
`2
`
`
`
`
`
`Mutant allele frequency ( % )
`
`0.250
`
`0.125
`
`Jun . 23 , 2022 Sheet 10 of 50 US 2022/0195530 A1
`
`-1,024
`
`CUDNA ( pg mL )
`
`-256
`
`2
`3
`4
`5
`0
`Months since initiation of therapy
`SNV : TMEM132D
`SNV TP53
`A SNV : NAV3
`Fusion : KIFSB - ALK
`
`Figure 4D
`
`P5 ( Stage IV )
`Plasma
`
`50
`
`
`
`
`
`Mutant allele frequency ( 26 )
`30
`
`20
`
`i
`
`
`
`
`
`Mutant allele frequency ( 90 )
`
`0
`Dominant clone : all SNVs ( n - 3 )
`Dominant clone : EGFR 1858R
`Sublone EGFR 1790M
`
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`Patent Application Publication
`
`Jun . 23 , 2022 Sheet 11 of 50 US 2022/0195530 A1
`
`Figure 4E Imaging
`
`Treatment
`
`4
`
`22
`
`0
`
`TL
`
`400 Stage 118
`CIDNA ( pg ml - 1 )
`200
`
`P131400
`300
`
`Tumor volume ( cm
`
`2 CAPP - Seq
`OND ( CAPP - Seq )
`
`( months
`
`Tumor volume
`
`Figure 4F
`
`*
`
`Month
`
`0
`
`5
`
`159 Stage IIB
`CIDNA ( pg mL )
`
`P14810
`
`
`
`Tumor volume ( om )
`
`CAPP Seq
`
`5
`
`( months )
`
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`Patent Application Publication
`
`Jun . 23 , 2022 Sheet 12 of 50 US 2022/0195530 A1
`
`Figure 4G
`
`Treatment
`
`0
`
`32
`
`Stage 1B
`CIDNA ( pg mL- ' )
`
`Figure 4H Imaging
`
`2
`
`:
`
`3
`( months )
`
`?
`
`4 stage IB
`CIONA ( pg mL - )
`
`0
`CAPP - Seq
`O ND ( CAPP - Seg )
`
`( months )
`
`216/30
`
`20
`
`Tumor volume ( cm )
`
`a 18
`Tumor volume
`
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`Patent Application Publication
`
`Jun . 23 , 2022 Sheet 13 of 50 US 2022/0195530 A1
`
`Figure 41
`
`5
`
`
`
`SNV frequency ( % )
`
`0
`sample Que
`Screening
`
`in turnor in plasma
`
`P16-31
`
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`Patent Application Publication
`
`Jun . 23 , 2022 Sheet 14 of 50 US 2022/0195530 A1
`
`Figure 5A
`
`Median % tumor DNA in plasma in NSCLC
`10
`0.8
`
`CAPP.Seq :
`4 SNVS
`( 1110 lane )
`
`Probability of detection in plasma
`
`0.2
`0.0 1
`Detection limit in plasma ( allele % )
`Exome : 218 SNVS ( 1/10 lane )
`Exome : 218 SNVs ( 1 lane )
`Genome : 15,659 SNVS ( 1 lane )
`
`WWW
`
`0
`
`Figure 5B
`Cost comparison for equal detection limit in plasma
`Whole
`CAPP - Seq
`Feature
`genome
`3,000 Mb
`15 659
`
`Bases covered
`
`0.125 Mb
`
`Xome
`
`Ne more on
`Depth
`Obs sequenced
`Relative cost
`
`2.1
`
`92
`
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`Patent Application Publication
`
`Jun . 23 , 2022 Sheet 15 of 50
`
`US 2022/0195530 A1
`
`Fusion
`
`SNV / indel ( s ) ? Fusion ( s ) ?
`
`recovery
`
`Significance FACTERA testing
`reporters
`Intersect
`Templated fusion discovery
`
`SNV / indel
`
`Selector
`Blood
`
`il
`
`Tissue biopsy
`Selector
`
`Personalized markers
`
`Fusion ( s ) ?
`
`QC
`
`Enumerate allele frequencies
`Fusion discovery FACTERA
`
`QC
`
`
`
`
`
`Reads Mapped Cell free DNA
`
`
`
`
`
`Mapped Tumori Normal Reads
`
`SNVlindel
`
`detection VarScan 2
`
`Variant annotation
`
`
`
`Tumor burden
`
`recovery
`
`Mutation
`
`Personalized markers
`
`Mutation discovery
`
`Figure 6
`
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`Patent Application Publication
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`Jun . 23 , 2022 Sheet 16 of 50 US 2022/0195530 A1
`
`Figure 7A
`2500
`
`Frequency
`
`2000
`
`1500
`
`500 .
`
`3
`
`Known / suspected drivers
`
`KRAS
`TP53
`
`CDKN2A
`
`KEADI
`PTEN
`
`30
`0
`Recurrence Index ( No. of patients per kb )
`
`Figure 7B
`
`40000
`
`30000
`
`20000
`
`No. of exons
`
`;
`8
`
`3
`
`*
`#
`
`Known / suspected drivers
`
`1
`TP53
`KRAS
`COKNZA
`PIK3CA
`EGFR
`KEADI
`PTEN
`
`2
`
`8
`6
`4
`No. of patients per exon
`
`fummum
`ammad
`10 105
`
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`Patent Application Publication
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`Jun . 23 , 2022 Sheet 17 of 50
`
`US 2022/0195530 A1
`
`
`
`Mate maps
`
`VVM
`
`Soft - clipped reads
`
`C
`
`
`
`Breakpoint validation
`
`
`
`Compare soft clipped segment
`
`
`
`to R1 using TAGC increments of size k
`
`
`
`
`
`Soft - clipped Mapped gene v
`
`GCTA
`
`R2 TCTGGCTATAGC
`
`TCTG
`
`
`
`Breakpoint identification
`
`
`
`Gene vreference
`
`
`
`Gene wreference
`
`Figure 8A
`
`
`
`
`
`Store all k - mers
`
`from mapped segment in hash
`
`table ( e.g. , k - 4 )
`
`?? ?? ??? ?? ??? . ?????? ??? . ?? ?? ????? . ??? ?? ?? ??? ??? ???
`
`Soft - clipped
`
`R1 [ TCTGGCTATAGI TCTGO
`
`Figure 8C Mapped gene w
`
`to gene v
`Figure 8B
`
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`Patent Application Publication
`
`Jun . 23 , 2022 Sheet 18 of 50
`
`US 2022/0195530 A1
`
`R2
`
`R2
`
`Case 2a
`
`R1
`
`Case 2b
`
`Case 2a
`
`
`
`Possible orientations
`
`22
`
`R2
`
`3 – Case 1a
`
`Case 1b
`
`Case 1a
`Figure 8D
`
`Case 1
`
`Figure 8E
`
`Comp
`
`bol
`
`bp2
`
`Breakpoint 2 = bp2 * ( -X )
`
`R1 ******
`
`Case 2
`
`
`
`Breakpoint adjustment
`
`bp2
`
`Breakpoint 2 - bp2 + (
`
`1 R2
`
`R1
`
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`CCACTGCACTCCAGCCTGGGE ! AGTAAATGCAAAGCTAAAAATCAGACCACTGCACTCCAGCCTGGGG AIGC
`
`CCACTGCACICCAGCCTGGGC TGAAGCATGATTTAAAGTAAATGCAAAGCTAAAAATCAGA CCACTGCACTCCAGCCTGGGG
`GTCTTTAATTGAAGCATGATTTAAAGTAPATGCAAAGCTAZ TCAGA
`
`
`CTGGGE
`
`
`
`ICAGA CCACTGCA
`
`AGCI
`
`ATGATTTAAAGTAAATGCAAAGCTAAAAATCAGA
`
`AAN
`
`Patent Application Publication
`
`
`
`AAATGATTAAAGAAGGTGTGTCTTTAATTGAAGCATGAITTAAAGTAXATGCAAAGCTAAA TCAGA
`
`CCACTGCACTCCAGCCTGGGE GTGTGTCTTTAATTGAAGCATGATTTAAAGTAAATGCAAAGCTAAAAATCAGACCACTGCACTCCAGCCTGGGG
`
`TCAGACCACTGCACTCCAGCCTGGGG
`GTGTCTTTAATTGAAGCATGATTTAAAGTAPATGCAAAGC
`
`
`
`TACTAATAAAATGATTAAAGAAGGTGTGTCTTTAATTGAAGCATGATTTAAAGTAXATGCAAAGCTAAAAATCAGA CCACTGCACTCCAGCCTGGGG
`
`
`
`AGAAATACTAATAAAATGATTAAAGAAGGTGTGTCTTTAATTGAAGCATGATTTAAAGTAAATGCAAAGCTAAAAATCAGA CCACTGCACTCCAGCCTGGG
`
`Figure 9A
`
`
`
`
`
`
`
`? ??? A A A G ? ? A A A A A TcAG AccA ??G CAc?ccA G ccTGGG
`
`Jun . 23 , 2022 Sheet 19 of 50
`
`US 2022/0195530 A1
`
`
`
`EML4 intron 13
`
`
`
`ALK intron 19
`
`whum
`
`M www.handlownload
`
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`Patent Application Publication
`
`Jun . 23 , 2022 Sheet 20 of 50 US 2022/0195530 A1
`
`GAACAAGAGTGAAACCCCATCTCAAAAACAAACAAACAAAACAAAACAAAAAAAACTAAG
`
`GAACAAGAGTGAAACCCCATCTCAAAAACAAACAAACAAAACAAAAC
`
`GAACAAGAGTGAAACCCCATCTCAAAAACAAACAAACA
`
`GAACAAGAGTGAAACCCCATCTCAAAAACAAA
`
`GAACAAGAGTGAAACCCCATCTCAAAAACAA
`
`GAACAAGAGTGAAACCCCATCTCAAAAAC
`
`GAACAAGAGTGAAACCCCATCTCAAAAA
`
`Figure 9A ( contd . )
`
`GAACAAGAGTGAA
`
`GAACA
`
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`Jun . 23 , 2022 Sheet 21 of 50
`
`US 2022/0195530 A1
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`GAGTAAGATTCAGTCTCAGA
`
`ACCTCACITCCAGAAAGCTTTAAGACAAAAGGTGAGTACTAGAGTAAGATTCAGTCTCAGA
`CAGAAAGCTTTAAGACAAAAGGTGAGTACTAGAGTAAGATTCAGTCTCAGA AAGACAAAAGGTGAGTACTA
`
`AATAGCACCTCACTTCCAGAAAGCTTTAAGACAAAAGGTGAGTACTAGAGTAAGATTCAGTCTCAGA
`
`1
`
`AY
`
`Patent Application Publication
`
`
`
`TGTCAGAGTAGTGGTGGTTTATAAGACGGGAGAAAATAGCACCTCACTTCCAGAAAGCTTTAAGACAAAAGGTGAGTACTA GAGTAAGATTCAGTCTCAGA
`
`ATAAGACGGGAGAAAATAGCACCTCACTTCCAGAAAGCTTTAAGACAAAAGGTGAGTACTAGAGTAAGATTCAGTCTCAGA AGAAAATAGCACCICACTTCCAGAAAGCTTIAAGACAAAAGGTGAGTACTAGAGTAAGATTCAGTCTCAGA
`
`GTTTATAAGACGGGAGAAAATAGCACCTCACTTCCAGAAAGCTTTAAGACA AGGTGAGTACTAGAGTAAGAITCAGTCTCAGA
`
`GAGTAAGATTCAGTCTCAGA GTGGTGGTTTATAAGACGGGAGAAAATAGCACCTCACTTCCAGAAAGCTTIAAGACAAAAGGTGAGTACTAGAGTAAGATTCAGTCTCAGA
`GAGTAGTGGTGGTTTATAAGACGGGAGAAAATAGCACCTCACTTCCAGAAAGCTTTAAGACAAAAGGTGAGTACTA
`
`shem
`Mu
`
`SLC34A2 intron 4
`who
`wand
`mu
`unha nh
`
`Figure 9B
`
`
`
`ROSI intron 31
`
`
`
`
`
`
`
`A A G A CA A A A G GT GAG TAC TAGA GTA A G AT TCA GT CT CAGA
`
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`Patent Application Publication
`
`Jun . 23 , 2022 Sheet 22 of 50 US 2022/0195530 A1
`
`Figure 9B ( Contnued )
`
`TCTGGGTGACACAAAGGACCATGGATTTCTGCAACCCTTGGTGCCTTTCTTGGGAACCCAT
`
`TCTGGGTGACACAAAGGACCATGGATTTCTGCAACCCTTGGTGCCTTTCT
`
`TCTGGGTGACACAAAGGACCATGGATTTCTGCAACCCTTGGTG
`ICTGGGTGACACAAAGGACCATGGATTTCTGCAA
`
`TCTGGGTGACACAAAGGACCATGGATTTCT
`
`TCTGGGTGACACAAAGGACC
`
`TCTGGGTGACACAAAG
`
`ICTGGGTGACAC
`
`TCTGG
`
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`Patent Application Publication
`
`Jun . 23 , 2022 Sheet 23 of 50 US 2022/0195530 A1
`
`Figure 10A
`
`Phusion Standard 32ng
`
`200
`Fragment length ( bp )
`
`Phusion With - Bead 32ng
`
`200000
`0 150000
`
`250
`Fragment length ( bp )
`
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`Patent Application Publication
`KAPA With - Bead 32ng
`
`Jun . 23 , 2022 Sheet 24 of 50 US 2022/0195530 A1
`
`?
`
`Fragment length ( bp )
`
`WGA Phusion With - Bead
`
`200
`
`400
`
`Figure 10A
`( Continued )
`
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`Patent Application Publication
`
`Jun . 23 , 2022 Sheet 25 of 50 US 2022/0195530 A1
`
`Figure 10B
`
`Phusion Standard 32ng
`
`wwwwww
`
`Targeted loci ( bp resolution )
`Phusion With - Bead 32ng
`
`15000
`
`810000
`
`Targeted loci ( bp resolution )
`
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`Patent Application Publication
`
`Jun . 23 , 2022 Sheet 26 of 50 US 2022/0195530 A1
`
`KAPA With - Bead 32ng
`
`10000
`
`WW Why
`
`Targeted loci ( bp resolution )
`
`WGA Phusion With - Bead
`
`S6e 04
`
`Targeted loci ( op resolution )
`Figure 10B
`( Continued )
`
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`Patent Application Publication
`Figure 10C
`1
`
`Jun . 23 , 2022 Sheet 27 of 50 US 2022/0195530 A1
`
`0.6
`
`
`
`Fraction of reads mapped
`
`0.2
`
`0.7
`0.6
`
`On - target rate 0.3
`
`0.2
`0.1
`
`0
`
`0.35
`
`www .
`
`www
`
`HE
`
`0.25
`
`
`
`Uniqueness index 0.2
`
`0.05
`0
`
`Phusion / Standard ( 1 )
`* Phusion / With - Bead ( ii )
`* KAPA - HIFI / With - Bead ( iii )
`WGA + Phusion / With - Bead ( iv )
`
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`Patent Application Publication
`Figure 11A
`
`Jun . 23 , 2022 Sheet 28 of 50 US 2022/0195530 A1
`
`p = 0.03
`P = P = 0.004
`
`I
`
`NS
`
`T
`
`1.4
`1.2
`
`want
`
`
`
`Normalized yield
`
`0.4
`0.2
`0
`
`***********************************
`
`manning
`
`16hr / Cycle
`16hr / 16 ° C
`15min / 20 ° C
`Adapter ligation duration and temperature
`Figure 11B
`
`NS
`
`NS
`
`NS
`
`??????
`
`50UL
`
`25uL
`Adapter ligation volume
`
`100L
`
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`Patent Application Publication
`Figure 11C
`2
`
`Jun . 23 , 2022 Sheet 29 of 50 US 2022/0195530 A1
`
`P0.017
`
`
`
`Normalized yield
`
`1.6
`14
`1.2
`1
`
`0.6
`
`0.2
`0
`
`Figure 110
`
`With - Bead
`Control
`SPRI bead processing
`
`100X
`10X
`Adapterfragment molar ratio
`
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`Patent Application Publication
`Figure 11E
`
`Jun . 23 , 2022 Sheet 30 of 50 US 2022/0195530 A1
`
`P
`
`0.001
`
`....
`
`*****
`
`???? HiFi
`Phusion
`DNA polymerase used for PCR
`
`Figure 11F
`
`P
`
`0.011
`
`* . * . * . * . * .. * . ***
`
`T
`
`KAPA
`NUGEN
`Library Preparation Kit
`
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`Patent Application Publication
`
`Jun . 23 , 2022 Sheet 31 of 50 US 2022/0195530 A1
`
`KAPA With - Bead 4ng
`
`L
`
`Fragment length ( bp )
`KAPA With - Bead 32ng
`
`Figure 12A
`
`250000
`
`150000
`
`50000
`
`Be # 05
`
`200
`Fragment length ( bp )
`
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`Patent Application Publication
`
`Jun . 23 , 2022 Sheet 32 of 50 US 2022/0195530 A1
`
`KAPA With - Bead 128ng
`
`100000
`
`0
`
`Figure 12B
`
`25000
`200
`??
`15000
`$
`000 20
`5000
`
`Figure 12A
`( Continued )
`
`KAPA With - Bead 4ng
`
`Targeted loci ( bp resolution )
`
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`Patent Application Publication
`
`Jun . 23 , 2022 Sheet 33 of 50 US 2022/0195530 A1
`
`20000
`
`?d?n 10000
`
`6000
`
`KAPA With - Bead 32ng
`
`IM
`
`Targeted loci ( bp resolution )
`
`KAPA With - Bead 128ng
`
`.
`
`WI
`
`Targeted loci ( bp resolution )
`
`Figure 12B
`( Continued )
`
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`Jun . 23 , 2022 Sheet 34 of 50 US 2022/0195530 A1
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`Patent Application Publication
`Figure 12c
`1
`
`0.8
`
`0.6
`
`
`
`Fraction of reads mapped
`
`( ii )
`
`0.2
`
`0
`
`0.6
`0.5
`0.4
`
`On - target rate 0.3
`0.2
`
`0
`
`( )
`
`wy
`
`
`
`Uniqueness index 0.2
`
`0.3
`
`0
`
`with ( 0 )
`
`i w
`
`4ng ( 0 )
`» 32ng ( 1 )
`128ng ( 111 )
`
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`Patent Application Publication
`Figure 13A
`
`50 %
`
`Jun . 23 , 2022 Sheet 35 of 50 US 2022/0195530 A1
`
`Additional library complexity ( lower
`
`+ 30 %
`bound )
`* 20 %
`
`
`
`
`
`2
`
`Y
`Tumor
`
`E
`PBL
`
`+ 0 %
`
`Plasma DNA
`
`Figure 13B
`
`
`
`
`
`Fraction of Expected Library Yield
`
`1.09
`
`0.84
`
`0.64
`
`0.2
`
`Plasma DNA Libraries
`
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`Patent Application Publication
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`Jun . 23 , 2022 Sheet 36 of 50
`
`US 2022/0195530 A1
`
`P1 P2
`
`P3 P5
`
`P9
`
`SNPs
`
`0.06 %
`
`Figure 14
`
`
`
`Patient DNA samples
`
`
`
`3 P9 sample
`
`
`2 P9 sample
`
`
`1 P9 sample
`
`
`2 P5 sample
`
`
`1 P5 sample
`
`
`2 P3 sample
`
`
`1 P3 sample
`
`
`2 P2 sample
`
`
`1 P2 sample
`
`
`2 P1 sample
`
`
`1 P1 sample
`
`0.001
`
`SNPs 100
`
`10
`
`1
`
`0.100
`
`0.010
`
`
`
` ( % ) Allele fraction
`
`
`
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`Jun . 23 , 2022 Sheet 37 of 50 US 2022/0195530 A1
`
`0.87
`0.7
`0.675
`
`
`
`Allelic fraction
`
`**
`
`Figure 15
`
`0.5 - E f ?? ?? ??? ????
`
`:
`
`M
`
`*
`
`0.4
`0.34
`0.2
`0.14
`0.0
`P6 P8 pg P11
`P1 P2
`P3 P4
`P5 P7
`P10
`PBL patient samples
`
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`Patent Application Publication
`Figure 16A
`
`Jun . 23 , 2022 Sheet 38 of 50 US 2022/0195530 A1
`
`
`
`
`
`CAPP - Seq predicted fraction ( % )
`
`Homozygous SNPs ( n = 24 )
`R2 = 1
`
`1
`
`1
`9
`8
`7
`
`4
`
`2
`
`0
`
`5 6
`1 2 3
`4
`Known fraction ( % )
`
`8
`
`Figure 16B
`10
`
`( )
`
`0.87
`0.7
`
`Coefficient of Variation ( CV ) 0.64
`0.5-1
`0.44
`0.3
`0.2
`
`***
`
`????
`
`1.0000
`
`-0.9995
`
`-0.9990
`
`-0.9985
`
`-0.9980
`
`
`
`Mean correlation
`
`2 4
`
`10 12 14 16 18 20 22 24
`8
`No. of reporters considered
`Mean correlation ( 1 )
`CV of 1 % spike ( iii )
`CV of 10 % spike ( ii )
`CV of 0.1 % spike ( iv )
`
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`Patent Application Publication
`
`Jun . 23 , 2022 Sheet 39 of 50 US 2022/0195530 A1
`
`Figure 16C
`
`9
`
`00
`
`..................................................................................................
`
`
`
`
`
`Mean reporter fraction ( % )
`
`Spike
`
`10 %
`
`** - ' ; ' - " .
`
`2
`
`1
`
`2
`
`4
`
`1 %
`0.1 %
`8 10 12 14 16 18 20 22 24
`6
`No. of reporters considered
`
`2
`
`Figure 160
`
`R2 0.97
`
`0 ( ii ) ( ii ) ( iv )
`
`0 ( 0 ) ( iii ) ( iv )
`
`
`
`
`
`CAPP - Seq predicted fraction ( % )
`
`0.10
`
`1
`Known fraction ( % )
`Fusion
`
`SNPs
`
`Deletion
`
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`Patent Application Publication
`
`Jun . 23 , 2022 Sheet 40 of 50
`
`US 2022/0195530 A1
`
`NCI - H3122 29446607
`P9 29447437
`
`ALK ( chr2 )
`
`P8 29446579
`P6 29446725
`
`P7 29448163
`
`Exon 20
`
`Exon 19
`
`Exon 7
`
`Exon 14
`
`Exon 21
`
`Exon 25
`
`P6 32304729
`
`KIF5B ( chr10 )
`
`P8 42552920
`
`NCI - H3122 42526889
`
`EML4 ( chr2 )
`
`P9
`
`42552797
`
`P7 42493258
`
`Exon 6
`
`Exon 13
`
`Exon 20
`
`Exon 24
`
`
`
`Figure 17A
`
`
`
`
`
`Predicted ALK Fusion Genes P7
`
`Exon 20
`
`NCI - H3122
`Exon 6
`
`Exon 20
`
`Exon 13
`
`Exon 20
`
`Exon 20
`
`P9
`
`P8
`
`P6
`
`Exon 20
`
`Exon 24
`
`E6 , A20
`
`E13 ; A20
`
`E20 ; A20
`
`K24 ; A20
`
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`Patent Application Publication
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`Jun . 23 , 2022 Sheet 41 of 50
`
`US 2022/0195530 A1
`
`Exon 32
`
`Exon 33
`
`Exon 34
`
`Exon 35
`
`Exon 36
`
`P10 117646137
`
`117646113
`117646780
`
`ROS1 ( chr6 )
`
`P9 117646780 6467
`HCC78 25666630
`
`Exon 31
`
`Exon 32
`
`Exon 33
`
`Exon 34
`
`Exon 35
`
`1
`
`8 8
`
`8 8 ?
`
`Exon 13
`
`Exon 7
`
`Exon 3
`
`Exon ?
`
`Exon 5
`
`25678334
`
`149783115
`
`112111380
`
`CD74 ( chr5 )
`
`FYN ( chr6 )
`
`MKX ( chr10 )
`
`P9 28017277
`
`SLC34A2 ( chr4 )
`
`HCC78 117658325
`
`Exon 4
`
`Exon 12
`
`Exon 6
`
`Exon 2
`
`Exon 6
`
`
`
`Predicted ROS1 Fusion Genes
`
`
`
`
`
`Exon 32 NCHH3122
`
`Exon 4
`
`exon 34
`
`Exon 34
`
`P9
`
`Exon 13
`
`Exon 6
`
`Exon 2 Exon 33
`P9
`
`Exon 7
`
`Exon 33
`
`S13del37 ; R34
`
`S4 ; R32
`
`S6 ; R34
`
`F2 ; R33
`
`R33 ; M7
`
`
`
`Figure 17B
`
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`Patent Application Publication
`
`Jun . 23 , 2022 Sheet 42 of 50 US 2022/0195530 A1
`
`P = 0.002
`
`30
`
`20
`
`No. of SNVS
`
`? 10 stop
`
`0
`
`Fusions
`absent
`
`Smoking history
`O Heavy
`O Light
`O None
`
`be
`
`Fusion ( s )
`present
`
`Figure 18
`
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`Patent Application Publication
`Figure 19A
`
`Jun . 23 , 2022 Sheet 43 of 50 US 2022/0195530 A1
`
`Non - deduped ( all stages )
`
`?????
`
`Sensitivity %
`
`60
`
`Indelfusion
`
`Sn
`
`Sp AUC
`0.89
`
`%
`No correction 78 % 85 % 0.85
`
`20
`
`100 % - Specificity %
`Deduped ( all stages )
`
`Figure 19B
`
`100
`
`Sensitivity %
`
`60 %
`
`0
`
`Sn Sp AUC
`IndeVfusion
`0.86
`correction
`No correction 74 % 85 % 0.83
`
`100 % - Specificity %
`
`80
`
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`Patent Application Publication
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`Jun . 23 , 2022 Sheet 44 of 50 US 2022/0195530 A1
`
`Figure 19C
`
`Non - deduped ( stages 2-4 )
`
`( in )
`
`Sensitivity %
`
`Sn
`
`Sp AUC
`0.91
`No correction 83 % 86 % 0.87
`
`(
`
`Figure 19D
`
`20
`
`80
`
`100 % - Specificity %
`
`Deduped ( stages 2-4 )
`
`80 P
`Sensitivity %
`
`60
`
`Indellusion
`correction
`No correction 83 % 86 % 0.87
`
`Sn
`83 %
`
`Sp AUC
`90 % 0.90
`
`so
`
`100 % - Specificity %
`
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`Patent Application Publication
`
`Jun . 23 , 2022 Sheet 45 of 50 US 2022/0195530 A1
`
`Patient - specific reporters
`Stage 1
`Stages Il to IV
`Healthy
`P6 ** NSCLC
`P13 P14 P2 * P3 P15 * P4 P5
`P12 * P17
`P9 **
`P16 *
`P1 *
`
`( n = 40 )
`
`samples
`DNA
`Plasma
`
`?
`
`TN
`
`EN
`
`TP
`
`FP
`
`FF ?
`
`: . : . : . : .
`
`includes indel ( s )
`includes fusion ( s )
`
`Pre / Post - tx Pre - tx
`Stages All .IV All
`Sn 67 % 74 % 69 % 89 %
`Sp 98 % 98 % 98 % 98 %
`
`Figure 20
`
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`Patent Application Publication
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`Jun . 23 , 2022 Sheet 46 of 50
`
`US 2022/0195530 A1
`
`100
`
`
`
`20 40 60 80 No. tags ( deduped )
`
`
`
`Cutpoint ( Aho 0.85 )
`
`(
`
`.....
`
`
`
`
`
`10 20 30 Robust Mahalanobis distance
`
`
`
`mw . Iterative correlation
`
`21
`
`www
`
`0
`
`400 )
`
`300H
`
`1005
`
`0
`
`100
`
`
`
`
`
`
`
`
`
`Post - Op plasma DNA ( P1 )
`
`
`
`( 3 ) Outlier detection
`
`
`
`( 2 ) Background filter
`
`
`
`( 1 ) Germline filter
`
`( 0 ) Pre - filter
`
`
`
`Figure 21A
`
`2006 TE 100
`
`
`
`
`
`
`
`- square chi of quantiles of Square root
`
`100
`
`wwwwwwww
`
`
`
`20 40 60 80 No. tags ( deduped )
`
`2004
`300
`
`
`
`) ( nondeduped
`
`100
`
`No. tags
`
`0
`0 .
`
`
`
`Background allele
`
`
`
`Known SNV
`
`
`
`20 40 60 80 No. tags ( deduped )
`
`400
`
`300
`
`200
`
`U
`0
`
`400
`
`
`
`Figure 21B
`
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`Patent Application Publication
`
`Jun . 23 , 2022 Sheet 47 of 50
`
`US 2022/0195530 A1
`
`100
`
`80
`
`
`No. tags ( deduped )
`40
`
`20
`
`
`
`
`
`4 Robust Mahalanobis distance
`
`2
`
`0
`
`
`
`Iterative correlation
`
`Post - Op plasma DNA ( P1 )
`
`100
`
`
`
`
`
`) nondeduped ( No. tags
`
`
`
`
`
`
`
`- square chi of quantiles of Square root
`
`
`
`
`
`
`
`
`
`
`
`100
`
`40 60 80
`
`No. tags ( deduped )
`
`20
`
`0
`
`100
`
`40 60 80
`
`No. tags ( deduped )
`
`20
`
`0
`0
`
`200
`
`
`
`) ( nondeduped
`
`
`
`No. tags
`
`300
`200
`100
`
`
`
`
`
`
`) ( No , tags nondeduped
`
`400
`
`
`
`Figure 210
`
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`Patent Application Publication
`Figure 210
`
`Jun . 23 , 2022 Sheet 48 of 50 US 2022/0195530 A1
`
`P5
`
`
`
`Square root of quantles of chi - square
`
`
`
`Square root of quantles of chi - square
`
`
`
`Correlation coefficient
`
`0
`
`1.0
`
`
`
`Correlation coefficient
`
`30
`
`Iterative correlaton
`
`PO
`
`2
`Robust Mahalanobis distance
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`US 2022/0195530 A1
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`1
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`Jun . 23 , 2022
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`IDENTIFICATION AND USE OF
`CIRCULATING NUCLEIC ACID TUMOR
`MARKERS
`
`STATEMENT OF GOVERNMENTAL SUPPORT
`[ 0001 ]
`This invention was made with Government support
`under contract W81XWH - 12-1-0285 awarded by the
`Department of Defense . The Government has certain rights
`in the invention .
`
`BACKGROUND OF THE INVENTION
`[ 0002 ] Tumors continually shed DNA into the circulation ,
`where it is readily accessible ( Stroun et al . ( 1987 ) Eur J
`Cancer Clin Oncol 23 : 707-712 ) . Analysis of such cancer
`derived cell - free DNA ( cfDNA ) has the potential to revo
`lutionize detection and monitoring of cancer . Noninvasive
`access to malignant DNA is particularly attractive for solid
`tumors , which cannot be repeatedly sampled without inva
`sive procedures . In non - small cell lung cancer ( NSCLC ) ,
`PCR - based assays have been used previously to detect
`recurrent point mutations in genes such as KRAS or EGFR
`in plasma DNA ( Taniguchi et al . ( 2011 ) Clin . Cancer Res .
`17 : 7808-7815 ; Gautschi et al . ( 2007 ) Cancer Lett . 254 : 265
`273 ; Kuang et al . ( 2009 ) Clin . Cancer Res . 15 : 2630-2636 ;
`Rosell et al . ( 2009 ) N. Engl . J. Med . 361 : 958-967 ) , but the
`majority of patients lack mutations in these genes .
`[ 0003 ]
`Other studies have proposed identifying patient
`specific chromosomal rearrangements in tumors via whole
`genome sequencing ( WGS ) , followed by breakpoint qPCR
`from cfDNA ( Leary et al . ( 2010 ) Sci . Transl . Med . 2 : 20ral4 ;
`McBride et al . ( 2010 ) Genes Chrom . Cancer 49 : 1062-1069 ) .
`While sensitive , such methods require optimization of
`molecular assays for each patient , limiting their widespread
`clinical application . More recently , several groups have
`reported amplicon - based deep sequencing methods to detect
`cfDNA mutations in up to 6 recurrently mutated genes
`( Forshew et al .
`( 2012 ) Sci . Transl . Med . 4 : 136ra168 ;
`Narayan et al . ( 2012 ) Cancer Res . 72 : 3492-3498 ; Kinde et
`al . ( 2011 ) Proc . Natl Acad . Sci . USA 108 : 9530-9535 ) . While
`powerful , these approaches are limited by the number of
`mutations that can be interrogated ( Rachlin et al . ( 2005 )
`BMC Genomics 6 : 102 ) and the inability to detect genomic
`fusions .
`[ 0004 ] PCT International Patent Publication No. 2011 /
`103236 describes methods for identifying personalized
`tumor markers in a cancer patient using “ mate - paired ”
`libraries . The methods are limited to monitoring somatic
`chromosomal rearrangements , however , and must be per
`sonalized for each patient , thus limiting their applicability
`and increasing their cost .
`[ 0005 ]
`U.S. Patent Application Publication No. 2010 /
`0041048 Al describes the quantitation of tumor - specific
`cell - free DNA in colorectal cancer patients using the
`“ BEAMing ” technique ( Beads , Emulsion , Amplification ,
`and Magnetics ) . While this technique provides high sensi
`tivity and specificity , this method is for single mutations and
`thus any given assay can only be applied to a subset of
`patients and / or requires patient - specific optimization . U.S.
`Patent Application Publication No. 2012/0183967 A1
`describes additional methods to identify and quantify
`genetic variations , including the analysis of minor variants
`in a DNA population , using the “ BEAMing ” technique .
`
`U.S. Patent Application Publication No. 2012 /
`[ 0006 ]
`0214678 A1 describes methods and compositions for detect
`ing fetal nucleic acids and determining the fraction of
`cell - free fetal nucleic acid circulating in a maternal sample .
`While sensitive , these methods analyze polymorphisms
`occurring between maternal and fetal nucleic acids rather
`than polymorphisms that result from somatic mutations in
`tumor cells . In addition , methods that detect fetal nucleic
`acids in maternal circulation require much less sensitivity
`than methods that detect tumor nucleic acids in cancer
`patient circulation , because fetal nucleic acids are much
`more abundant than tumor nucleic acids .
`[ 0007 ]
`U.S. Patent Application Publication Nos . 2012 /
`0237928 A1 and 2013/0034546 describe methods for deter
`mining copy number variations of a sequence of interest in
`a test sample comprising a mixture of nucleic acids . While
`potentially applicable to the analysis of cancer , these meth
`ods are directed to measuring major structural changes in
`nucleic acids , such as translocations , deletions , and ampli
`fications , rather than single nucleotide variations .
`[ 0008 ]
`U.S. Patent Application Publication No. 2012 /
`0264121 Al describes methods for estimating a genomic
`fraction , for example , a fetal fraction , from polymorphisms
`such as small base variations or insertions - deletions . These
`methods do not , however , make use of optimized libraries of
`polymorphisms , such as , for example , libraries containing
`recurrently - mutated genomic regions .
`[ 0009 ]
`U.S. Patent Application Publication No. 2013 /
`0024127 A1 describes computer - implemented methods for
`calculating a percent contribution of cell - free nucleic acids
`from a major source and a minor source in a mixed sample .
`The methods do not , however , provide any advantages in
`identifying or making use of optimized libraries of poly
`morphisms in the analysis .
`[ 0010 ] PCT International Publication No. WO 2010 /
`141955 A2 describes methods of detecting cancer by ana
`lyzing panels of genes from a patient - obtained sample and
`determining the mutational status of the genes in the panel .
`The methods rely on a relatively small number of known
`cancer genes , however , and they do not provide any ranking
`of the genes according to effectiveness in detection of
`relevant mutations . In addition , the methods were unable to
`detect the presence of mutations in the majority of seru