Publications by authors named "Matthew Bootsma"

In preclinical studies, p53 loss of function impacts chemotherapy response, but this has not been consistently validated clinically. We trained a TP53-loss phenocopy gene expression signature from pan-cancer clinical samples in the TCGA. In vitro, the TP53-loss phenocopy signature predicted chemotherapy response across cancer types.

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Therapies against cell-surface targets (CSTs) represent an emerging treatment class in solid malignancies. However, high-throughput investigations of CST expression across cancer types have been reliant on data sets of mostly primary tumors, despite therapeutic use most commonly in metastatic disease. We identified a total of 818 clinical trials of CST therapies with 78 CSTs.

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  • The study explores how three-dimensional genomic structure variations impact gene expression and mutation rates in metastatic castration-resistant prostate cancer, using a combination of advanced sequencing techniques on 80 biopsy samples.
  • Findings revealed significant differences in gene expression, methylation patterns, and structural variations between different chromatin compartments, along with specific chromatin contact loss at the AR locus linked to poor treatment responses.
  • The research identified distinct subtypes of tumors based on their methylation and gene expression profiles, suggesting that DNA interactions could contribute to structural variant formation, ultimately enhancing understanding of tumor behavior and treatment outcomes.
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Histopathologic diagnosis and classification of cancer plays a critical role in guiding treatment. Advances in next-generation sequencing have ushered in new complementary molecular frameworks. However, existing approaches do not independently assess both site-of-origin (e.

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Developing radiation tumor biomarkers that can guide personalized radiotherapy clinical decision making is a critical goal in the effort towards precision cancer medicine. High-throughput molecular assays paired with modern computational techniques have the potential to identify individual tumor-specific signatures and create tools that can help understand heterogenous patient outcomes in response to radiotherapy, allowing clinicians to fully benefit from the technological advances in molecular profiling and computational biology including machine learning. However, the increasingly complex nature of the data generated from high-throughput and "omics" assays require careful selection of analytical strategies.

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Conservation and management professionals often work across jurisdictional boundaries to identify broad ecological patterns. These collaborations help to protect populations whose distributions span political borders. One common limitation to multijurisdictional collaboration is consistency in data recording and reporting.

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Purpose: Although numerous biology-driven subtypes have been described previously in metastatic castration-resistant prostate cancer (mCRPC), unsupervised molecular subtyping based on gene expression has been less studied, especially using large cohorts. Thus, we sought to identify the intrinsic molecular subtypes of mCRPC and assess molecular and clinical correlates in the largest combined cohort of mCRPC samples with gene expression data available to date.

Experimental Design: We combined and batch-effect corrected gene expression data from four mCRPC cohorts from the Fred Hutchinson Cancer Research Center (N = 157), a small-cell neuroendocrine (NE) prostate cancer (SCNC)-enriched cohort from Weill Cornell Medicine (N = 49), and cohorts from the Stand Up 2 Cancer/Prostate Cancer Foundation East Coast Dream Team (N = 266) and the West Coast Dream Team (N = 162).

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DNA mutations in specific genes can confer preferential benefit from drugs targeting those genes. However, other molecular perturbations can "phenocopy" pathogenic mutations, but would not be identified using standard clinical sequencing, leading to missed opportunities for other patients to benefit from targeted treatments. We hypothesized that RNA phenocopy signatures of key cancer driver gene mutations could improve our ability to predict response to targeted therapies, despite not being directly trained on drug response.

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  • Liquid biopsies offer a noninvasive way to study treatment response and resistance in metastatic renal cell carcinoma (mRCC), focusing on circulating tumor cells (CTCs) instead of traditional tissue biopsies.
  • Researchers analyzed 457 liquid biopsies from 104 mRCC patients, assessing CTC numbers and the HLA I to PD-L1 ratio, discovering that lower CTC counts correlated with better treatment responses and longer survival.
  • The study highlights the significance of monitoring CTC counts and the HP ratio as potential biomarkers for predicting and tracking responses to immunotherapy in mRCC patients.
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  • We are entering a molecular medicine era where specific DNA changes help identify which patients will benefit from particular drugs, although there are still few effective predictive biomarkers in cancer treatment.
  • Researchers developed a model called TARGETS that uses DNA and RNA sequencing, alongside drug response data, to predict treatment responses using Elastic-Net regression and validated it with multiple cancer databases.
  • The TARGETS model successfully predicted treatment responses in various datasets, including FDA-approved cancer drugs, and was effective in predicting clinical outcomes in prostate cancer, suggesting it could enhance patient selection for therapies and guide future clinical trials.
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Stocking of fish is an important tool for maintaining fisheries but can also significantly alter population genetic structure and erode the portfolio of within-species diversity that is important for promoting resilience and adaptability. Walleye () are a highly valued sportfish in the midwestern United States, a region characterized by postglacial recolonization from multiple lineages and an extensive history of stocking. We leveraged genomic data and recently developed analytical approaches to explore the population structure of walleye from two midwestern states, Minnesota and Wisconsin.

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Targeted amplicon sequencing methods, such as genotyping-in-thousands by sequencing (GT-seq), facilitate rapid, accurate, and cost-effective analysis of hundreds of genetic loci in thousands of individuals. Development of GT-seq panels is nontrivial, but studies describing trade-offs associated with different steps of GT-seq panel development are rare. Here, we construct a dual-purpose GT-seq panel for walleye (Sander vitreus), discuss trade-offs associated with different development and genotyping approaches, and provide suggestions for researchers constructing their own GT-seq panels.

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Interpretation of high-throughput sequence data requires an understanding of how decisions made during bioinformatic data processing can influence results. One source of bias that is often cited is PCR clones (or PCR duplicates). PCR clones are common in restriction site-associated sequencing (RAD-seq) data sets, which are increasingly being used for molecular ecology.

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