Jazmine Brimhall
A5011995365- Cancer Genomics and Diagnostics
- Single-cell and spatial transcriptomics
- Evolution and Genetic Dynamics
- CRISPR and Genetic Engineering
- Cancer Cells and Metastasis
- Gene expression and cancer classification
- Epigenetics and DNA Methylation
- Genomics and Phylogenetic Studies
- Axon Guidance and Neuronal Signaling
- Gene Regulatory Network Analysis
- Cancer, Stress, Anesthesia, and Immune Response
- Molecular Biology Techniques and Applications
- Genetic factors in colorectal cancer
University of British Columbia
2015-2019
BC Cancer Agency
2014-2015
Accurate measurement of clonal genotypes, mutational processes, and replication states from individual tumor-cell genomes will facilitate improved understanding tumor evolution. We have developed DLP+, a scalable single-cell whole-genome sequencing platform implemented using commodity instruments, image-based object recognition, open source computational methods. Using we generated resource 51,926 matched cell images diverse types including lines, xenografts, diagnostic samples with limited...
How cell-to-cell copy number alterations that underpin genomic instability
Measuring gene expression of tumor clones at single-cell resolution links functional consequences to somatic alterations. Without scalable methods simultaneously assay DNA and RNA from the same single cell, parallel measurements independent cell populations must be mapped for genome-transcriptome association. We present clonealign, which assigns states cancer using sequencing independently sampled a heterogeneous population. apply clonealign triple-negative breast patient-derived xenografts...
We present Epiclomal, a probabilistic clustering method arising from hierarchical mixture model to simultaneously cluster sparse single-cell DNA methylation data and impute missing values. Using synthetic published CpG datasets, we show that Epiclomal outperforms non-probabilistic methods can handle the inherent characteristic dominates genome sequences. newly generated 5mCpG sequencing data, discovers sub-clonal patterns in aneuploid tumour genomes, thus defining epiclones match or...
The extracellular signals regulating mammary epithelial cell growth are of relevance to understanding the pathophysiology epithelia, yet they remain poorly characterized. In this study, we applied an unbiased approach functional role signalling molecules in several models normal physiological and translated these results biological breast cancer subtypes. We developed utilized a cytogenetically clonal line hTERT immortalized human cells fibroblast-enhanced co-culture assay conduct...
Summary Essential features of cancer tissue cellular heterogeneity such as negatively selected genome topologies, sub-clonal mutation patterns and replication states can only effectively be studied by sequencing single-cell genomes at scale high fidelity. Using an amplification-free approach implemented on commodity hardware (DLP+) coupled with a cloud-based computational platform, we define resource 40,000 characterized their states, across wide range types conditions. We show that shallow...
Abstract Background The encoding of cell intrinsic drug resistance states in breast cancer reflects the contributions genomic and non-genomic variations requires accurate estimation clonal fitness from co-measurement transcriptomic data. Somatic copy number (CN) variation is dominant mutational mechanism leading to transcriptional notably contributes platinum chemotherapy states. Here, we deploy time series measurements triple negative (TNBC) single-cell transcriptomes, along with...
Tumour fitness landscapes underpin selection in cancer, impacting etiology, evolution and response to treatment. Progress defining has been impeded by a lack of timeseries perturbation experiments over realistic intervals at single cell resolution. We studied the nature clonal dynamics induced genetic pharmacologic with quantitative model developed ascribe selective coefficients individual cancer clones, enable prediction clone-specific growth potential, forecast competitive time. applied...
Abstract Assessing tumour gene fitness in physiologically-relevant model systems is challenging due to biological features of vivo regeneration, including extreme variations single cell lineage progeny. Here we develop a reproducible, quantitative approach pooled genetic perturbation patient-derived xenografts (PDXs), by encoding output from transplanted CRISPR-transduced cells combination with Bayesian hierarchical model. We apply this 181 PDX transplants 21 breast cancer patients. show...
ABSTRACT Structural genome alterations are determinants of cancer ontogeny and therapeutic response. While bulk sequencing has enabled delineation structural variation (SV) mutational processes which generate patterns DNA damage, we have little understanding how these lead to cell-to-cell variations underlie selection rates accrual different genomic lesions. We analysed 309 high grade serous ovarian triple negative breast genomes determine their processes, selecting 22 from sequenced...
Abstract Cancer genomes exhibit extensive chromosomal copy number changes and structural variation, yet how allele specific alterations drive cancer genome evolution remains unclear. Here, through application of a new computational approach we report in 11,097 single cell whole from genetically engineered mammary epithelial cells 21,852 high grade serous ovarian triple negative breast cancers. Resolving profiles to individual alleles uncovered genomic background distributions gains, losses...
Abstract Background The encoding of cell intrinsic resistance states in breast cancer reflects the contributions genomic and non-genomic variation. However, identifying potential each requires accurate measurement subtraction contribution clonal fitness from co-measurement transcriptional states. Somatic variation gene dosage, copy number variation, is dominant mutational mechanism contributing to has recently been shown contribute platinum chemotherapy Here we deploy time series...
Abstract We present Epiclomal, a probabilistic clustering method arising from hierarchical mixture model to simultaneously cluster sparse single-cell DNA methylation data and impute missing values. Using synthetic published CpG datasets we show that Epiclomal outperforms non-probabilistic methods is able handle the inherent feature which dominates genome sequences. recently 5mCpG sequencing (PBAL), discovers sub-clonal patterns of in aneuploid tumour genomes, thus defining epiclones....
Abstract Measuring gene expression of genomically defined tumour clones at single cell resolution would associate functional consequences to somatic alterations, as a prelude elucidating pathways driving population growth, resistance and relapse. In the absence scalable methods simultaneously assay DNA RNA from same cell, independent sampling populations for parallel measurement must be computationally mapped genome-transcriptome association. Here we present clonealign , robust statistical...
Abstract Introduction Breast cancer is the most common in female and triple-negative breast (TNBC) aggressive subtype of which shows high rate recurrence metastasis. Malignant cells that comprise primary tumor are heterogeneous during disease progression selection occur as a mean to adapt survive. Tumor heterogeneity can be studied by grouping clones refer group related each other descent from unitary origin. Understanding mechanism clonal dynamics evolution important develop new therapeutic...