JPWO2020168008A5

JPWO2020168008A5 -

Info

Publication number: JPWO2020168008A5
Application number: JP2021547568A
Authority: JP
Publication date: 2023-02-15
Anticipated expiration: 2040-02-12

Claims

A method for determining the homologous recombination pathway status of a cancer in a test subject, comprising:
In a computer system having one or more processors and a memory storing one or more programs for execution by the one or more processors,
(A) obtaining in electronic form a first plurality of sequence reads of a first DNA sample from said test subject, wherein said first DNA sample is DNA from cancerous tissue of said subject; obtaining containing a molecule;
(B) electronically acquiring a second plurality of sequence reads of a second DNA sample from the test subject, wherein the second DNA sample is DNA from non-cancerous tissue of the subject; obtaining consisting of a molecule;
(C) aligning each sequence of said first plurality of sequence reads and each sequence of said second plurality of sequence reads to a human reference genome, thereby yielding a corresponding first plurality of sequence reads; generating aligned sequence reads and a corresponding second plurality of aligned sequence reads;
(D) generating a genomic data construct of said subject based on said first plurality of aligned sequence reads and said second plurality of aligned sequence reads, said genomic data construct comprising: a plurality of features of the genome of the cancerous tissue and the non-cancerous tissue of the subject, wherein the plurality of features comprises: (i) a first plurality of features in the genome of the cancerous tissue of the subject; (ii) a measure of loss of heterozygosity across the genome of the cancerous tissue of the subject; (iii) within the genome of the cancerous tissue of the subject; and (iv) a measure of mutant alleles detected in a second plurality of DNA damage repair genes detected in the second plurality of DNA damage repair genes in the genome of the non-cancerous tissue of the subject. generating a measure of the variant alleles obtained;
(E) inputting said genomic data constructs into a classifier trained to distinguish between cancers with homologous recombination pathway defects and cancers without homologous recombination pathway defects, thereby determining recombination pathway status.

2. The method of claim 1, wherein said first DNA sample is from a solid tumor biopsy of said cancerous tissue of said subject.

3. The method of claim 1 or 2, wherein said second DNA sample is from a buffy coat preparation of a blood sample from said subject.

2. The first plurality of sequence reads were generated by targeted sequencing using a plurality of nucleic acid probes to enrich nucleic acids from the cancerous tissue of the subject for a panel of genomic regions. 4. The method according to any one of 1 to 3.

4. The method of any one of claims 1-3, wherein the first plurality of sequence reads was generated by whole genome sequencing of nucleic acid from the cancerous tissue of the subject.

3. The second plurality of sequence reads were generated by targeted sequencing using a plurality of nucleic acid probes to enrich nucleic acids from the non-cancerous tissue of the subject for a panel of genomic regions. 6. The method according to any one of 1-5.

6. The method of any one of claims 1-5, wherein the second plurality of sequence reads was generated by whole genome sequencing of nucleic acid from the non-cancerous tissue of the subject.

wherein said measure of said loss of heterozygosity across said genome of said cancerous tissue of said subject comprises
determining loss of genomic heterozygosity in said first plurality of sequence reads; and normalizing said determined loss of heterozygosity by an estimate of tumor purity for said first plurality of sequence reads. determined by
The method of any one of claims 1-7, wherein said tumor purity estimation is based on said first plurality of sequence reads and said second plurality of sequence reads.

9. The method of claims 1-8, wherein said heterozygosity status of said first plurality of DNA damage repair genes comprises counting the number of unique frameshift mutations detected in said first plurality of DNA damage repair genes. A method according to any one of paragraphs.

10. The method of claims 1-9, wherein said heterozygosity status of said first plurality of DNA damage repair genes comprises counting the number of unique truncation mutations detected in said first plurality of DNA damage repair genes. A method according to any one of paragraphs.

11. The method of any one of claims 1-10, wherein the first plurality of DNA damage repair genes comprises BRCAl and BRCA2.

said measure of mutant alleles detected in said second plurality of DNA damage repair genes in said genome of said cancerous tissue of said subject is homologous recombination detected in said first plurality of sequence reads A method according to any one of claims 1 to 11, comprising counting the number of unique mutations associated with loss of .

said measure of mutant alleles detected in said second plurality of DNA damage repair genes in said genome of said non-cancerous tissue of said subject is a homologous set detected in said second plurality of sequence reads 13. The method of any one of claims 1-12, comprising counting the number of unique mutations associated with loss of recombination.

14. The method of any one of claims 1-13, wherein the second plurality of DNA damage repair genes comprises BRCAl and BRCA2.

15. The method of claim 14, wherein the unique mutations associated with loss of homologous recombination in BRCA1 and BRCA2 comprise at least 50 of the mutations listed in Table 1.

15. The method of claim 14, wherein the unique mutations associated with loss of homologous recombination in BRCA1 and BRCA2 comprise mutations listed in Table 1.

said method comprising:
treating the cancer by administering a poly ADP ribose polymerase (PARP) inhibitor to the test subject when the cancer of the test subject is determined to be homologous recombination deficient;
and treating the cancer with a therapy that does not include administering a PARP inhibitor to the test subject when the cancer of the test subject is determined not to be homologous recombination deficient. , a method according to any one of claims 1-16.

18. The method of claim 17, wherein said PARP inhibitor is selected from the group consisting of olaparib, veliparib, rucaparib, niraparib, and talazoparib.

19. The method of any one of claims 1-18, wherein the cancer is breast cancer.

19. The method of any one of claims 1-18, wherein the cancer is ovarian cancer.

19. The method of any one of claims 1-18, wherein the cancer is colorectal cancer.

3. The classifier is a neural network algorithm, a support vector machine algorithm, a Naive Bayes algorithm, a nearest neighbor algorithm, a boosted tree algorithm, a random forest algorithm, a convolutional neural network algorithm, a decision tree algorithm, a regression algorithm, or a clustering algorithm. 22. The method according to any one of 1-21.

A method according to any preceding claim, wherein said classifier is a random forest algorithm.

24. The method of any one of claims 1-3 and 8-23, wherein said first plurality of sequence reads was generated by exome sequencing of a cDNA molecule generated from said cancerous tissue of said subject. Method.

24. Any one of claims 1-3 and 8-23, wherein said second plurality of sequence reads was generated by exome sequencing of a cDNA molecule generated from said non-cancerous tissue of said subject. the method of.

said first plurality of sequence reads comprises at least 300 each unique sequence reads for each of at least 10 different loci in the human genome, and the second plurality of sequence reads comprises at least 10 different sequence reads in the human genome 26. The method of any one of claims 1-25, comprising at least 300 respective unique sequence reads for each of the loci.

a computer system,
one or more processors;
a non-transitory computer-readable medium containing computer-executable instructions which, when executed by said one or more processors, cause said processor to perform the method of any one of claims 1-26; computer system.

A non-transitory computer-readable storage medium storing program code instructions which, when executed by a processor, cause the processor to perform the method of any one of claims 1-26 .

A method for training an algorithm for determining homologous recombination pathway status in a cancer, comprising:
A computer system comprising at least one processor and a memory storing at least one program for execution by the at least one processor,
(A) obtaining, for each training subject in a plurality of training subjects with cancer, a corresponding genomic data construct for each said training subject, wherein said corresponding genomic training construct comprises: (a) said homologous recombination pathway status of each of the cancers of each training subject; and (b) a plurality of genomic features of cancerous and non-cancerous tissues of each of said training subjects, wherein said plurality of features comprises: (i) the heterozygosity status of a first plurality of DNA damage repair genes in the genome of the cancerous tissue of each of the training subjects; (ii) the genome of the cancerous tissue of each of the training subjects. (iii) a measure of total loss of heterozygosity, (iii) a measure of mutant alleles detected in a second plurality of DNA damage repair genes in the genome of the cancerous tissue of each of the training subjects; and ( iv) obtaining, including a measure of mutant alleles detected in the second plurality of DNA damage repair genes in the genome of the non-cancerous tissue of each of the training subjects;
(B) for each training subject, at least (a) the homologous recombination pathway status of the cancer of the respective training subject; and (b) the correspondence from the cancerous tissue of the respective training subject. and training a classification algorithm on the plurality of features determined from the DNA samples.

a computer system,
one or more processors;
and a non-transitory computer-readable medium containing computer-executable instructions that, when executed by the one or more processors, cause the processors to perform the method of claim 29 .

30. A non-transitory computer readable storage medium storing program code instructions which, when executed by a processor, cause the processor to perform the method of claim 29 .