Veronica Y. Sabelnykova

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.

Combining tumor genome simulation with crowdsourcing to benchmark somatic single-nucleotide-variant detection

The detection of somatic mutations from cancer genome sequences is key to understanding the genetic basis of disease progression, patient survival and response to therapy. Benchmarking is needed for tool assessment and improvement but is complicated by a lack of gold standards, by extensive resource requirements and by difficulties in sharing personal genomic information. To resolve these issues, we launched the ICGC-TCGA DREAM Somatic Mutation Calling Challenge, a crowdsourced benchmark of somatic mutation detection algorithms. Here we report the BAMSurgeon tool for simulating cancer genomes and the results of 248 analyses of three in silico tumors created with it. Different algorithms exhibit characteristic error profiles, and, intriguingly, false positives show a trinucleotide profile very similar to one found in human tumors. Although the three simulated tumors differ in sequence contamination (deviation from normal cell sequence) and in subclonality, an ensemble of pipelines outperforms the best individual pipeline in all cases. BAMSurgeon is available at https://github.com/adamewing/bamsurgeon/.

Genomic hallmarks of localized, non-indolent prostate cancer

Prostate tumours are highly variable in their response to therapies, but clinically available prognostic factors can explain only a fraction of this heterogeneity. Here we analysed 200 whole-genome sequences and 277 additional whole-exome sequences from localized, non-indolent prostate tumours with similar clinical risk profiles, and carried out RNA and methylation analyses in a subset. These tumours had a paucity of clinically actionable single nucleotide variants, unlike those seen in metastatic disease. Rather, a significant proportion of tumours harboured recurrent non-coding aberrations, large-scale genomic rearrangements, and alterations in which an inversion repressed transcription within its boundaries. Local hypermutation events were frequent, and correlated with specific genomic profiles. Numerous molecular aberrations were prognostic for disease recurrence, including several DNA methylation events, and a signature comprised of these aberrations outperformed well-described prognostic biomarkers. We suggest that intensified treatment of genomically aggressive localized prostate cancer may improve cure rates.

Crowdsourced estimation of cognitive decline and resilience in Alzheimer's disease

Identifying accurate biomarkers of cognitive decline is essential for advancing early diagnosis and prevention therapies in Alzheimers disease. The Alzheimers disease DREAM Challenge was designed as a computational crowdsourced project to benchmark the current state‐of‐the‐art in predicting cognitive outcomes in Alzheimers disease based on high dimensional, publicly available genetic and structural imaging data. This meta‐analysis failed to identify a meaningful predictor developed from either data modality, suggesting that alternate approaches should be considered for prediction of cognitive performance.

Mitochondrial mutations drive prostate cancer aggression

Nuclear mutations are well known to drive tumor incidence, aggression and response to therapy. By contrast, the frequency and roles of mutations in the maternally inherited mitochondrial genome are poorly understood. Here we sequence the mitochondrial genomes of 384 localized prostate cancer patients, and identify a median of one mitochondrial single-nucleotide variant (mtSNV) per patient. Some of these mtSNVs occur in recurrent mutational hotspots and associate with aggressive disease. Younger patients have fewer mtSNVs than those who diagnosed at an older age. We demonstrate strong links between mitochondrial and nuclear mutational profiles, with co-occurrence between specific mutations. For example, certain control region mtSNVs co-occur with gain of the MYC oncogene, and these mutations are jointly associated with patient survival. These data demonstrate frequent mitochondrial mutation in prostate cancer, and suggest interplay between nuclear and mitochondrial mutational profiles in prostate cancer.In prostate cancer, the role of mutations in the maternally-inherited mitochondrial genome are not well known. Here, the authors demonstrate frequent, age-dependent mitochondrial mutation in prostate cancer. Strong links between mitochondrial and nuclear mutational profiles are associated with clinical aggressivity.

Somatic mutations in early onset luminal breast cancer

Breast cancer arising in very young patients may be biologically distinct; however, these tumors have been less well studied. We characterized a group of very young patients (≤ 35 years) for BRCA germline mutation and for somatic mutations in luminal (HER2 negative) breast cancer. Thirteen of 79 unselected very young patients were BRCA1/2 germline mutation carriers. Of the non-BRCA tumors, eight with luminal subtype (HER2 negative) were submitted for whole exome sequencing and integrated with 29 luminal samples from the COSMIC database or previous literature for analysis. We identified C to T single nucleotide variants (SNVs) as the most common base-change. A median of six candidate driver genes was mutated by SNVs in each sample and the most frequently mutated genes were PIK3CA, GATA3, TP53 and MAP2K4. Potential cancer drivers affected in the present non-BRCA tumors include GRHL2, PIK3AP1, CACNA1E, SEMA6D, SMURF2, RSBN1 and MTHFD2. Sixteen out of 37 luminal tumors (43%) harbored SNVs in DNA repair genes, such as ATR, BAP1, ERCC6, FANCD2, FANCL, MLH1, MUTYH, PALB2, POLD1, POLE, RAD9A, RAD51 and TP53, and 54% presented pathogenic mutations (frameshift or nonsense) in at least one gene involved in gene transcription. The differential biology of luminal early-age onset breast cancer needs a deeper genomic investigation.

NanoStringNormCNV: pre-processing of NanoString CNV data

Summary: The NanoString System is a well‐established technology for measuring RNA and DNA abundance. Although it can estimate copy number variation, relatively few tools support analysis of these data. To address this gap, we created NanoStringNormCNV, an R package for pre‐processing and copy number variant calling from NanoString data. This package implements algorithms for pre‐processing, quality‐control, normalization and copy number variation detection. A series of reporting and data visualization methods support exploratory analyses. To demonstrate its utility, we apply it to a new dataset of 96 genes profiled on 41 prostate tumour and 24 matched normal samples. Availability and implementation: NanoStringNormCNV is implemented in R and is freely available at http://labs.oicr.on.ca/boutros‐lab/software/nanostringnormcnv. Contact: paul.boutros@oicr.on.ca Supplementary information: Supplementary data are available at Bioinformatics online.

Abstract 98: The somatic mutational landscape of the mitochondrial genome in prostate cancer: evaluation of clinical impact

Prostate cancer remains the most prevalent and second most lethal non-skin cancer in men. Whole genome studies have provided important insights into specific driver genes, however most of these studies have not assessed one key portion of the genome: the mitochondrial genome. To gain a complete understanding of the most commonly-diagnosed sub-groups of prostate cancer: low- and intermediate-risk localized disease, we surveyed the mitochondrial genomes from next-generation sequencing (NGS) data of over 300 tumour samples from prostate cancer patients. These samples were mainly from prostate cancer patients with clinical Gleason Scores of 3+3, 3+4 and 4+3. All had at least 5 years of follow-up data (median > 8 years), allowing identification of clinical associations with identified somatic mutations via Cox Proportional Hazards modeling and machine-learning. Recurrent somatic mutations in mtDNA were identified, and these were associated with clinical outcomes. One third of patients were found to have a somatic mtDNA mutation. These mutations appear to be associated with age of patient. The mtDNA region with the majority of mutations was the regulatory D-loop region, although certain proteins had high numbers of mutations. Those somatic mutations occurring within the coding regions in general were nonsynonymous. Specific identified candidate somatic mutations were validated via Sanger sequencing. Clinical associations between somatic were also integrated with existing copy-number alteration (CNA) biomarkers using machine learning methods to evaluate performance. mtDNA mutations were also compared to identified aberrations (CNA, PGA, SNVs) within the nuclear genome to determine correlations between the two genomes, in addition to other somatic mutations or altered-expression in nuclear-encoded mitochondrial proteins. Taken together, these data demonstrate a key role for mitochondrial mutations in driving prostate cancer. Citation Format: Julia F. Hopkins, Veronica Y. Sabelnykova, John Watson, Lawrence E. Heisler, Junyan Zhang, Michael Fraser, Theodorus van der Kwast, Robert G. Bristow, Paul C. Boutros. The somatic mutational landscape of the mitochondrial genome in prostate cancer: evaluation of clinical impact. [abstract]. In: Proceedings of the 107th Annual Meeting of the American Association for Cancer Research; 2016 Apr 16-20; New Orleans, LA. Philadelphia (PA): AACR; Cancer Res 2016;76(14 Suppl):Abstract nr 98.

A joint model for interval-censored functional decline trajectories under informative observation.

Multi-state models are useful for modelling disease progression where the state space of the process is used to represent the discrete disease status of subjects. Often, the disease process is only observed at clinical visits, and the schedule of these visits can depend on the disease status of patients. In such situations, the frequency and timing of observations may depend on transition times that are themselves unobserved in an interval-censored setting. There is a potential for bias if we model a disease process with informative observation times as a non-informative observation scheme with pre-specified examination times. In this paper, we develop a joint model for the disease and observation processes to ensure valid inference because the follow-up process may itself contain information about the disease process. The transitions for each subject are modelled using a Markov process, where bivariate subject-specific random effects are used to link the disease and observation models. Inference is based on a Bayesian framework, and we apply our joint model to the analysis of a large study examining functional decline trajectories of palliative care patients.

Matching Kidneys and Urines: Establishing Noninvasive Surrogates of Intrarenal Events in Primary Glomerulonephritis.

Kidney biopsy is the gold standard procedure for providing diagnostic and prognostic information for patients with glomerular-based diseases, however, the utility of this procedure for assessing longitudinal disease activity is limited. The intense search for noninvasive biomarkers of kidney disease activity and injury is driven in large part by the inherent risks of the kidney biopsy procedure and limited information derived from the morphologic description of biopsy findings. Furthermore, gaps in our understanding of the core intrarenal molecular processes underlying the development and progression of glomerular-based diseases has limited the development of effective targeted therapy. In this review, we discuss the potential utility of molecular analysis of the urine to provide a dynamic window into intrarenal molecular and morphologic responses. We focus on molecular analysis of the urine to identify noninvasive surrogate markers of kidney responses, with the goal of using these biomarkers as more sensitive indicators of progression and tissue-level responses to therapeutic interventions in patients with primary glomerulonephritis.