Systems and methods for predicting homologous recombination deficiency status of a specimen

Abstract

Methods, systems, and software are provided for an ensemble model trained to distinguish between cancers with homologous recombination pathway deficiencies (HRD positive cancers) and cancers without homologous recombination pathway deficiencies (HRD negative cancers) based on nucleic acid sequencing data, e.g., both RNA and DNA sequencing data, generated from a cancerous tissue sample of the subject.

What is claimed is: 
     
         1 . A method of determining a homologous recombination pathway status of a cancer in a test subject, the method comprising:
 at a computer system having one or more processors, and memory storing one or more programs for execution by the one or more processors:   (A) obtaining a first plurality of sequence reads, in electronic form, of a DNA sample from the test subject, the DNA sample comprising DNA molecules from a cancerous tissue of the subject;   (B) obtaining a second plurality of sequence reads, in electronic, of an RNA sample from the test subject, the RNA sample comprising RNA molecules from the cancerous tissue of the subject;   (C) determining, based on the first plurality of sequence reads, a first prediction for the homologous recombination pathway status of the cancerous tissue of the subject based on a measure of genome-wide loss of heterozygosity for the cancerous tissue of the subject;   (D) determining, based on the second plurality of sequence reads, a second prediction for the homologous recombination pathway status of the cancerous tissue of the subject based on the expression levels of a plurality of genes in the cancerous tissue of the subject;   (E) generating a subject data construct comprising (i) the first prediction for the homologous recombination pathway status of the cancerous tissue of the subject and (ii) the second prediction for the homologous recombination pathway status of the cancerous tissue of the subject; and   (F) inputting the subject data construct into an ensemble model trained to distinguish between cancers with homologous recombination pathway deficiencies and cancers without homologous recombination pathway deficiencies, thereby determining the homologous recombination pathway status of the test subject.   
     
     
         2 . The method of  claim 1 , wherein:
 the method further comprises determining, based on the second plurality of sequence reads, a third prediction for the homologous recombination pathway status of the cancerous tissue of the subject based on a measure of transcriptome-wide rearrangements for the cancerous tissue of the subject; and   the subject data construct further comprises the third prediction for the homologous recombination pathway status of the cancerous tissue of the subject.   
     
     
         3 . The method of  claim 2 , wherein the measure of transcriptome-wide rearrangements is a measure of sequence insertions, sequence deletions, sequence inversions, and sequence translocations identified in the second plurality of sequence reads. 
     
     
         4 . The method of  claim 1 , wherein:
 the method further comprises determining, based on the first plurality of sequence reads, a third prediction for the homologous recombination pathway status of the cancerous tissue of the subject based on a measure of genome-wide rearrangements for the cancerous tissue of the subject; and   the subject data construct further comprises the third prediction for the homologous recombination pathway status of the cancerous tissue of the subject.   
     
     
         5 . The method of  claim 2 , wherein the measure of genome-wide rearrangements is a measure of sequence insertions, sequence deletions, sequence inversions, and sequence translocations identified in the first plurality of sequence reads. 
     
     
         6 . The method of any one of  claims 2 - 5 , wherein determining the third prediction is further based on a cancer type of the cancerous tissue of the subject. 
     
     
         7 . The method of any one of  claims 1 - 6 , wherein:
 the method further comprises determining, based on the second plurality of sequence reads, a fourth prediction for the homologous recombination pathway status of the cancerous tissue of the subject based on a plurality of single-sample gene set enrichment analysis (ssGSEA) scores for the transcriptional profile of the cancerous tissue of the subject; and   the subject data construct further comprises the fourth prediction for the homologous recombination pathway status of the cancerous tissue of the subject.   
     
     
         8 . The method of  claim 7 , wherein determining the fourth prediction is further based on a cancer type of the cancerous tissue of the subject. 
     
     
         9 . The method of any one of  claims 1 - 8 , wherein:
 the method further comprises obtaining a third plurality of sequence reads comprising the methylation status of cytosine nucleotides, in electronic form, of a DNA sample from the test subject, the DNA sample comprising DNA molecules from a cancerous tissue of the subject;   determining, based on the third plurality of sequence reads, a fifth prediction for the homologous recombination pathway status of the cancerous tissue of the subject based on a genomic methylation pattern of the cancerous tissue; and   the subject data construct further comprises the one or more methylation scores for the cancerous tissue.   
     
     
         10 . The method of  claim 9 , wherein the third plurality of sequence reads was generated by bisulfite sequencing. 
     
     
         11 . The method of  claim 9  or  10 , wherein the first plurality of sequence reads and the third plurality of sequence reads were generated using different aliquots of the same DNA sample comprising the DNA molecules from the cancerous tissue of the subject. 
     
     
         12 . The method of any one of  claims 9 - 11 , wherein the genomic methylation pattern of the cancerous tissue comprises a methylation pattern for a promoter region of a homologous recombination gene. 
     
     
         13 . The method of any one of  claims 9 - 12 , wherein the genomic methylation pattern of the cancerous tissue comprises a methylation pattern for at least 100 genomic regions. 
     
     
         14 . The method of any one of  claims 9 - 12 , wherein the genomic methylation pattern of the cancerous tissue comprises a methylation pattern for at least 1000 genomic regions. 
     
     
         15 . The method of any one of  claims 9 - 14 , wherein determining the fourth prediction is further based on a cancer type of the cancerous tissue of the subject. 
     
     
         16 . The method of any one of  claims 1 - 15 , wherein the first plurality of sequence reads is generated from a targeted-panel DNA sequencing reaction. 
     
     
         17 . The method of any one of  claims 1 - 15 , wherein the first plurality of sequence reads is generated from low pass whole genome sequencing reaction. 
     
     
         18 . The method of any one of  claims 1 - 17 , wherein the DNA sample is prepared from a solid-tissue tumor biopsy from the subject. 
     
     
         19 . The method of any one of  claims 1 - 17 , wherein the DNA sample is prepared from a liquid biopsy from the subject. 
     
     
         20 . The method of any one of  claims 1 - 18 , wherein the first plurality of sequence reads comprises at least 10,000 sequence reads. 
     
     
         21 . The method of any one of  claims 1 - 20 , wherein the second plurality of sequence reads is generated from a whole-exome sequencing reaction. 
     
     
         22 . The method of any one of  claims 1 - 20 , wherein the second plurality of sequence reads is generated from a targeted-panel RNA sequencing reaction. 
     
     
         23 . The method of any one of  claims 1 - 22 , wherein the second plurality of sequence reads comprises at least 10,000 sequence reads. 
     
     
         24 . The method of any one of  claims 1 - 23 , wherein the RNA sample is prepared from a solid-tissue tumor biopsy from the subject. 
     
     
         25 . The method of any one of  claims 1 - 24 , wherein:
 the method further comprises obtaining a fourth plurality of sequence reads, in electronic form, of a second DNA sample from the test subject, the second DNA sample comprising DNA molecules from a non-cancerous tissue of the subject; and   the determining (C) is based on the first plurality of sequence reads and the fourth plurality of sequence reads.   
     
     
         26 . The method of any one of  claims 1 - 25 , wherein the determining (C) is further based on a cancer type of the cancerous tissue of the subject. 
     
     
         27 . The method of any one of  claims 1 - 26 , wherein the determining (C) comprises:
 determining a first probability that the cancerous tissue of the subject is homologous recombination deficiency (HRD) positive based on a first measure of genome-wide loss of heterozygosity that does not account for whole-arm or whole-chromosome chromosomal deletions;   determining a second probability that the cancerous tissue of the subject is homologous recombination deficiency (HRD) positive based on a second measure of genome-wide loss of heterozygosity that excludes loss of heterozygosity due to whole-arm or whole-chromosome loss; and   determining the first prediction for the homologous recombination pathway status of the cancerous tissue of the subject based on at least the first probability and the second probability.   
     
     
         28 . The method of any one of  claims 1 - 27 , wherein the determining (D) is based on expression values, determined from the second plurality of sequence reads, for at least 100 genes. 
     
     
         29 . The method of any one of  claims 1 - 27 , wherein the determining (D) is based on expression values, determined from the second plurality of sequence reads, for at least 1000 genes. 
     
     
         30 . The method of any one of  claims 1 - 29 , wherein the determining (C) is further based on a cancer type of the cancerous tissue of the subject. 
     
     
         31 . The method of any one of  claims 1 - 30 , wherein the cancerous tissue of the subject does not have a variant BRCA1 gene and does not have a variant BRCA2 gene. 
     
     
         32 . The method of any one of  claims 1 - 30 , wherein the cancerous tissue of the subject has no more than one variant BRCA1 or BRCA2 gene. 
     
     
         33 . The method of any one of  claims 1 - 32 , wherein the method further comprises:
 when it is determined that the cancer in the test subject is homologous recombination deficiency (HRD) positive, treating the cancer by administering a poly ADP ribose polymerase (PARP) inhibitor to the test subject; and   when it is determined the cancer in the test subject is not homologous recombination deficiency (HRD) positive, treating the cancer with a therapy that does not include administration of a PARP inhibitor to the test subject.   
     
     
         34 . The method of  claim 33 , wherein the PARP inhibitor is selected from the group consisting of olaparib, veliparib, rucaparib, niraparib, and talazoparib. 
     
     
         35 . The method of any one of  claims 1 - 34 , wherein the cancer is breast cancer. 
     
     
         36 . The method of any one of  claims 1 - 34 , wherein the cancer is ovarian cancer. 
     
     
         37 . The method of any one of  claims 1 - 34 , wherein the cancer is colorectal cancer. 
     
     
         38 . The method of any one of  claims 1 - 34 , wherein the cancer is pancreatic cancer. 
     
     
         39 . The method of any one of  claims 1 - 34 , wherein the cancer is prostate cancer. 
     
     
         40 . The method of any one of  claims 1 - 30 , wherein the method further comprises:
 when it is determined that the cancer in the test subject is homologous recombination deficiency (HRD) positive, treating the cancer by administering a platinum-containing neoadjuvant chemotherapy to the test subject; and   when it is determined the cancer in the test subject is not homologous recombination deficiency (HRD) positive, treating the cancer with a therapy that does not include administration of a platinum-containing neoadjuvant chemotherapy to the test subject.   
     
     
         41 . The method of  claim 40 , wherein the cancer is a triple-negative breast cancer. 
     
     
         42 . A computer system comprising:
 one or more processors; and   a non-transitory computer-readable medium including computer-executable instructions that, when executed by the one or more processors, cause the processors to perform a method according to any one of  claims 1 - 30 .   
     
     
         43 . A non-transitory computer-readable storage medium having stored thereon program code instructions that, when executed by a processor, cause the processor to perform the method according to any one of  claims 1 - 30 .