Publications by authors named "Natalie Fox"

There are myriad types of biomedical data-molecular, clinical images, and others. When a group of patients with the same underlying disease exhibits similarities across multiple types of data, this is called a subtype. Existing subtyping approaches struggle to handle diverse data types with missing information.

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Prostate cancer is one of the most heritable cancers. Hundreds of germline polymorphisms have been linked to prostate cancer diagnosis and prognosis. Polygenic risk scores can predict genetic risk of a prostate cancer diagnosis.

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Intergovernmental policy is targeting public ocean literacy to help achieve the societal changes needed to reach a sustainable ocean agenda within a 10-year timeframe. To create a culture of care for the ocean, which is under threat from Anthropocentric pressures, informed ocean citizens are central to upholding meaningful actions and best practices. This research focuses on recreational ocean users, specifically surfers and how their blue space activities may inform understanding of ocean processes and human-ocean interconnections.

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Purpose: The tumor microenvironment is complex, comprising heterogeneous cellular populations. As molecular profiles are frequently generated using bulk tissue sections, they represent an admixture of multiple cell types (including immune, stromal, and cancer cells) interacting with each other. Therefore, these molecular profiles are confounded by signals emanating from many cell types.

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Multi-omics datasets represent distinct aspects of the central dogma of molecular biology. Such high-dimensional molecular profiles pose challenges to data interpretation and hypothesis generation. ActivePathways is an integrative method that discovers significantly enriched pathways across multiple datasets using statistical data fusion, rationalizes contributing evidence and highlights associated genes.

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Solid tumours comprise mixtures of tumour cells (TCs) and tumour-adjacent cells (TACs), and the intricate interconnections between these diverse populations shape the tumour's microenvironment. Despite this complexity, clinical genomic profiling is typically performed from bulk samples, without distinguishing TCs from TACs. To better understand TC-TAC interactions, we computationally distinguish their transcriptomes in 1780 primary breast tumours.

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DNA sequencing has identified recurrent mutations that drive the aggressiveness of prostate cancers. Surprisingly, the influence of genomic, epigenomic, and transcriptomic dysregulation on the tumor proteome remains poorly understood. We profiled the genomes, epigenomes, transcriptomes, and proteomes of 76 localized, intermediate-risk prostate cancers.

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Article Synopsis
  • The study analyzed the complex transcriptome of localized prostate cancer using ultra-deep RNA sequencing on 144 tumors, uncovering a subtype linked to aggressive cancer behavior and distinct fusion patterns differentiating localized from metastatic disease.* -
  • Researchers discovered a significant prevalence of circular RNAs (circRNAs) in tumors, with an average of 7,232 circRNAs per tumor, and found that circRNA production levels correlated with disease progression across various patient groups.* -
  • Functional screening revealed that about 11% of the highly expressed circRNAs were crucial for cancer cell proliferation, with some circRNAs, like circCSNK1G3, specifically promoting cell growth through interactions with microRNAs.*
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Background: We introduce BPG, a framework for generating publication-quality, highly-customizable plots in the R statistical environment.

Results: This open-source package includes multiple methods of displaying high-dimensional datasets and facilitates generation of complex multi-panel figures, making it suitable for complex datasets. A web-based interactive tool allows online figure customization, from which R code can be downloaded for integration with computational pipelines.

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Background: Biomarkers are a key component of precision medicine. However, full clinical integration of biomarkers has been met with challenges, partly attributed to analytical difficulties. It has been shown that biomarker reproducibility is susceptible to data preprocessing approaches.

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The majority of newly diagnosed prostate cancers are slow growing, with a long natural life history. Yet a subset can metastasize with lethal consequences. We reconstructed the phylogenies of 293 localized prostate tumors linked to clinical outcome data.

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Almost all genomic studies of breast cancer have focused on well-established tumours because it is technically challenging to study the earliest mutational events occurring in human breast epithelial cells. To address this we created a unique dataset of epithelial samples ductoscopically obtained from ducts leading to breast carcinomas and matched samples from ducts on the opposite side of the nipple. Here, we demonstrate that perturbations in mRNA abundance, with increasing proximity to tumour, cannot be explained by copy number aberrations.

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Article Synopsis
  • Prostate tumours show diverse responses to treatment, and current prognostic factors only account for some of this variation, prompting further investigation into their genetic profiles.* -
  • Analysis of 200 whole-genome and 277 whole-exome sequences revealed that localized, non-indolent tumours lack key mutations found in metastatic cases, instead featuring non-coding changes and large-scale rearrangements.* -
  • Many genetic abnormalities were linked to disease recurrence, and a new signature of these abnormalities was found to be more effective than established biomarkers, suggesting that targeted treatments could enhance cure rates for aggressive localized prostate cancer.*
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Background: Visualization of data generated by high-throughput, high-dimensionality experiments is rapidly becoming a rate-limiting step in computational biology. There is an ongoing need to quickly develop high-quality visualizations that can be easily customized or incorporated into automated pipelines. This often requires an interface for manual plot modification, rapid cycles of tweaking visualization parameters, and the generation of graphics code.

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Article Synopsis
  • Researchers studied 74 patients with a type of prostate cancer called Gleason score 7 to understand how different parts of their tumors were unique.
  • They looked closely at 5 patients by analyzing 23 specific areas of their tumors and found lots of differences in the cancer's genetic makeup.
  • A new gene called MYCL was found to be important, and this study helps doctors predict how a patient's cancer might behave, which could lead to better treatments in the future.
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Background: The reproducibility of transcriptomic biomarkers across datasets remains poor, limiting clinical application. We and others have suggested that this is in-part caused by differential error-structure between datasets, and their incomplete removal by pre-processing algorithms.

Methods: To test this hypothesis, we systematically assessed the effects of pre-processing on biomarker classification using 24 different pre-processing methods and 15 distinct signatures of tumour hypoxia in 10 datasets (2,143 patients).

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Background: Quantitative real-time PCR (qPCR) is the "gold-standard" technique for measuring mRNA abundances. To correctly compare samples and generate biologically valid results, qPCR data usually require comprehensive normalization to account for sample content variation between reactions. The most common normalization approaches use one or more endogenous controls (reference or house-keeping genes) to adjust the measured levels of experimental genes appropriately.

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