Andrew M.K. Brown

Identification of pre-leukaemic haematopoietic stem cells in acute leukaemia

In acute myeloid leukaemia (AML), the cell of origin, nature and biological consequences of initiating lesions, and order of subsequent mutations remain poorly understood, as AML is typically diagnosed without observation of a pre-leukaemic phase. Here, highly purified haematopoietic stem cells (HSCs), progenitor and mature cell fractions from the blood of AML patients were found to contain recurrent DNMT3A mutations (DNMT3Amut) at high allele frequency, but without coincident NPM1 mutations (NPM1c) present in AML blasts. DNMT3Amut-bearing HSCs showed a multilineage repopulation advantage over non-mutated HSCs in xenografts, establishing their identity as pre-leukaemic HSCs. Pre-leukaemic HSCs were found in remission samples, indicating that they survive chemotherapy. Therefore DNMT3Amut arises early in AML evolution, probably in HSCs, leading to a clonally expanded pool of pre-leukaemic HSCs from which AML evolves. Our findings provide a paradigm for the detection and treatment of pre-leukaemic clones before the acquisition of additional genetic lesions engenders greater therapeutic resistance.

Genetic variants in TPMT and COMT are associated with hearing loss in children receiving cisplatin chemotherapy

Cisplatin is a widely used and effective chemotherapeutic agent, although its use is restricted by the high incidence of irreversible ototoxicity associated with it. In children, cisplatin ototoxicity is a serious and pervasive problem, affecting more than 60% of those receiving cisplatin and compromising language and cognitive development. Candidate gene studies have previously reported associations of cisplatin ototoxicity with genetic variants in the genes encoding glutathione S-transferases and megalin. We report association analyses for 220 drug-metabolism genes in genetic susceptibility to cisplatin-induced hearing loss in children. We genotyped 1,949 SNPs in these candidate genes in an initial cohort of 54 children treated in pediatric oncology units, with replication in a second cohort of 112 children recruited through a national surveillance network for adverse drug reactions in Canada. We identified genetic variants in TPMT (rs12201199, P value = 0.00022, OR = 17.0, 95% CI 2.3–125.9) and COMT (rs9332377, P value = 0.00018, OR = 5.5, 95% CI 1.9–15.9) associated with cisplatin-induced hearing loss in children.

Pharmacogenomic Prediction of Anthracycline-Induced Cardiotoxicity in Children

PURPOSE Anthracycline-induced cardiotoxicity (ACT) is a serious adverse drug reaction limiting anthracycline use and causing substantial morbidity and mortality. Our aim was to identify genetic variants associated with ACT in patients treated for childhood cancer. PATIENTS AND METHODS We carried out a study of 2,977 single-nucleotide polymorphisms (SNPs) in 220 key drug biotransformation genes in a discovery cohort of 156 anthracycline-treated children from British Columbia, with replication in a second cohort of 188 children from across Canada and further replication of the top SNP in a third cohort of 96 patients from Amsterdam, the Netherlands. RESULTS We identified a highly significant association of a synonymous coding variant rs7853758 (L461L) within the SLC28A3 gene with ACT (odds ratio, 0.35; P = 1.8 × 10(-5) for all cohorts combined). Additional associations (P < .01) with risk and protective variants in other genes including SLC28A1 and several adenosine triphosphate-binding cassette transporters (ABCB1, ABCB4, and ABCC1) were present. We further explored combining multiple variants into a single-prediction model together with clinical risk factors and classification of patients into three risk groups. In the high-risk group, 75% of patients were accurately predicted to develop ACT, with 36% developing this within the first year alone, whereas in the low-risk group, 96% of patients were accurately predicted not to develop ACT. CONCLUSION We have identified multiple genetic variants in SLC28A3 and other genes associated with ACT. Combined with clinical risk factors, genetic risk profiling might be used to identify high-risk patients who can then be provided with safer treatment options.

Spatial genomic heterogeneity within localized, multifocal prostate cancer

Herein we provide a detailed molecular analysis of the spatial heterogeneity of clinically localized, multifocal prostate cancer to delineate new oncogenes or tumor suppressors. We initially determined the copy number aberration (CNA) profiles of 74 patients with index tumors of Gleason score 7. Of these, 5 patients were subjected to whole-genome sequencing using DNA quantities achievable in diagnostic biopsies, with detailed spatial sampling of 23 distinct tumor regions to assess intraprostatic heterogeneity in focal genomics. Multifocal tumors are highly heterogeneous for single-nucleotide variants (SNVs), CNAs and genomic rearrangements. We identified and validated a new recurrent amplification of MYCL, which is associated with TP53 deletion and unique profiles of DNA damage and transcriptional dysregulation. Moreover, we demonstrate divergent tumor evolution in multifocal cancer and, in some cases, tumors of independent clonal origin. These data represent the first systematic relation of intraprostatic genomic heterogeneity to predicted clinical outcome and inform the development of novel biomarkers that reflect individual prognosis.

Cancer Genomics: Technology, Discovery, and Translation

In recent years, the increasing awareness that somatic mutations and other genetic aberrations drive human malignancies has led us within reach of personalized cancer medicine (PCM). The implementation of PCM is based on the following premises: genetic aberrations exist in human malignancies; a subset of these aberrations drive oncogenesis and tumor biology; these aberrations are actionable (defined as having the potential to affect management recommendations based on diagnostic, prognostic, and/or predictive implications); and there are highly specific anticancer agents available that effectively modulate these targets. This article highlights the technology underlying cancer genomics and examines the early results of genome sequencing and the challenges met in the discovery of new genetic aberrations. Finally, drawing from experiences gained in a feasibility study of somatic mutation genotyping and targeted exome sequencing led by Princess Margaret Hospital-University Health Network and the Ontario Institute for Cancer Research, the processes, challenges, and issues involved in the translation of cancer genomics to the clinic are discussed.

A renewed model of pancreatic cancer evolution based on genomic rearrangement patterns.

Pancreatic cancer, a highly aggressive tumour type with uniformly poor prognosis, exemplifies the classically held view of stepwise cancer development. The current model of tumorigenesis, based on analyses of precursor lesions, termed pancreatic intraepithelial neoplasm (PanINs) lesions, makes two predictions: first, that pancreatic cancer develops through a particular sequence of genetic alterations (KRAS, followed by CDKN2A, then TP53 and SMAD4); and second, that the evolutionary trajectory of pancreatic cancer progression is gradual because each alteration is acquired independently. A shortcoming of this model is that clonally expanded precursor lesions do not always belong to the tumour lineage, indicating that the evolutionary trajectory of the tumour lineage and precursor lesions can be divergent. This prevailing model of tumorigenesis has contributed to the clinical notion that pancreatic cancer evolves slowly and presents at a late stage. However, the propensity for this disease to rapidly metastasize and the inability to improve patient outcomes, despite efforts aimed at early detection, suggest that pancreatic cancer progression is not gradual. Here, using newly developed informatics tools, we tracked changes in DNA copy number and their associated rearrangements in tumour-enriched genomes and found that pancreatic cancer tumorigenesis is neither gradual nor follows the accepted mutation order. Two-thirds of tumours harbour complex rearrangement patterns associated with mitotic errors, consistent with punctuated equilibrium as the principal evolutionary trajectory. In a subset of cases, the consequence of such errors is the simultaneous, rather than sequential, knockout of canonical preneoplastic genetic drivers that are likely to set-off invasive cancer growth. These findings challenge the current progression model of pancreatic cancer and provide insights into the mutational processes that give rise to these aggressive tumours.

Feasibility of real time next generation sequencing of cancer genes linked to drug response: results from a clinical trial.

The successes of targeted drugs with companion predictive biomarkers and the technological advances in gene sequencing have generated enthusiasm for evaluating personalized cancer medicine strategies using genomic profiling. We assessed the feasibility of incorporating real‐time analysis of somatic mutations within exons of 19 genes into patient management. Blood, tumor biopsy and archived tumor samples were collected from 50 patients recruited from four cancer centers. Samples were analyzed using three technologies: targeted exon sequencing using Pacific Biosciences PacBio RS, multiplex somatic mutation genotyping using Sequenom MassARRAY and Sanger sequencing. An expert panel reviewed results prior to reporting to clinicians. A clinical laboratory verified actionable mutations. Fifty patients were recruited. Nineteen actionable mutations were identified in 16 (32%) patients. Across technologies, results were in agreement in 100% of biopsy specimens and 95% of archival specimens. Profiling results from paired archival/biopsy specimens were concordant in 30/34 (88%) patients. We demonstrated that the use of next generation sequencing for real‐time genomic profiling in advanced cancer patients is feasible. Additionally, actionable mutations identified in this study were relatively stable between archival and biopsy samples, implying that cancer mutations that are good predictors of drug response may remain constant across clinical stages.

Application of principal component analysis to pharmacogenomic studies in Canada

Ethnicity can confound results in pharmacogenomic studies. Allele frequencies of loci that influence drug metabolism can vary substantially between different ethnicities and underlying ancestral genetic differences can lead to spurious findings in pharmacogenomic association studies. We evaluated the application of principal component analysis (PCA) in a pharmacogenomic study in Canada to detect and correct for genetic ancestry differences using genotype data from 2094 loci in 220 key drug biotransformation genes. Using 89 Coriell worldwide reference samples, we observed a strong correlation between principal component values and geographic origin. We further applied PCA to accurately infer the genetic ancestry in our ethnically diverse Canadian cohort of 524 patients from the GATC study of severe adverse drug reactions. We show that PCA can be successfully applied in pharmacogenomic studies using a limited set of markers to detect underlying differences in genetic ancestry thereby maximizing power and minimizing false-positive findings.

CKM and LILRB5 Are Associated With Serum Levels of Creatine Kinase

Background—Statins (HMG-CoA reductase inhibitors) are the most prescribed class of lipid-lowering drugs for the treatment and prevention of cardiovascular disease. Creatine kinase (CK) is a commonly used biomarker to assist in the diagnosis of statin-induced myotoxicity but the normal range of CK concentrations is wide, which limits its use as a diagnostic biomarker. Methods and Results—We conducted a genome-wide association study of serum CK levels in 3412 statin users. Patients were recruited in Quebec, Canada, and genotyped on Illumina Human610-Quad and an iSelect panel enriched for lipid homeostasis, hypertension, and drug metabolism genes. We found a strong association signal between serum levels of CK and the muscle CK (CKM) gene (rs11559024: P=3.69×10−16; R2=0.02) and with the leukocyte immunoglobulin-like receptor subfamily B member 5 (LILRB5) gene (rs2361797: P=1.96×10−10; R2=0.01). Genetic variants in those 2 genes were independently associated with CK levels in statin users. Results were successfully replicated in 5330 participants from the Montreal Heart Institute Biobank in statin users for CKM (rs11559024: P=4.32×10−16; R2=0.02) and LILRB5 (rs12975366 P=4.45×10−10; R2=0.01) and statin nonusers (P=4.08×10−7, R2=0.01; P=3.17×10−9, R2=0.02, respectively). Conclusions—This is the first genome-wide study to report on the underlying genetic determinants of CK variation in a population of statin users. We found statistically significant association for variants in the CKM and LILRB5 genes.

Clinical genomics information management software linking cancer genome sequence and clinical decisions

Using sequencing information to guide clinical decision-making requires coordination of a diverse set of people and activities. In clinical genomics, the process typically includes sample acquisition, template preparation, genome data generation, analysis to identify and confirm variant alleles, interpretation of clinical significance, and reporting to clinicians. We describe a software application developed within a clinical genomics study, to support this entire process. The software application tracks patients, samples, genomic results, decisions and reports across the cohort, monitors progress and sends reminders, and works alongside an electronic data capture system for the trials clinical and genomic data. It incorporates systems to read, store, analyze and consolidate sequencing results from multiple technologies, and provides a curated knowledge base of tumor mutation frequency (from the COSMIC database) annotated with clinical significance and drug sensitivity to generate reports for clinicians. By supporting the entire process, the application provides deep support for clinical decision making, enabling the generation of relevant guidance in reports for verification by an expert panel prior to forwarding to the treating physician.