Biology subjects

Stopka, S. A.

Publications and source records attributed to Stopka, S. A..

5 recordsLinked to original sources

bioRxiv2022

Deep Learning on Multimodal Chemical and Whole Slide Imaging Data for Predicting Prostate Cancer Directly from Tissue Images

Prostate cancer is one of the most common cancers globally and is the second most common cancer in the male population in the US. Here we develop a study based on correlating the H&E-stained biopsy data with MALDI mass-spectrometric imaging of the corresponding tissue to determine the cancerous regions and their unique chemical signatures, and variation of the predicted regions with original pathological annotations. We spatially register features obtained through deep learning from high-resolution optical micrographs of whole slide H&E stained data with MSI data to correlate the chemical signature with the tissue anatomy of the data, and then use the learned correlation to predict prostate cancer from observed H&E images using trained co-registered MSI data. We found that this system is more robust than predicting from a single imaging modality and can predict cancerous regions with[~] 80% accuracy. Two chemical biomarkers were also found to be predicting the ground truth cancerous regions. This will improve on generating patient treatment trajectories by more accurately predicting prostate cancer directly from H&E-stained biopsy images.

cancer biology↗

bioRxiv2022

Single Cell Spatial Analysis Reveals the Topology of Immunomodulatory Purinergic Signaling in Glioblastoma

Glioblastoma develops an immunosuppressive microenvironment that fosters tumorigenesis and resistance to current therapeutic strategies. Here we use multiplexed tissue imaging and single-cell RNA-sequencing to characterize the composition, spatial organization, and clinical significance of extracellular purinergic signaling in glioblastoma. We show that glioblastoma exhibit strong expression of CD39 and CD73 ectoenzymes, correlating with increased adenosine levels. Microglia are the predominant source of CD39, while CD73 is principally expressed by tumor cells, particularly in tumors with amplification of EGFR and astrocyte-like differentiation. Spatially-resolved single-cell analyses demonstrate strong spatial correlation between tumor CD73 and microglial CD39, and that their spatial proximity is associated with poor clinical outcomes. Together, this data reveals that tumor CD73 expression correlates with tumor genotype, lineage differentiation, and functional states, and that core purine regulatory enzymes expressed by neoplastic and tumor-associated myeloid cells interact to promote a distinctive adenosine-rich signaling niche and immunosuppressive microenvironment potentially amenable to therapeutic targeting.

cancer biology↗

bioRxiv2021

Characterization of metabolic compartmentalization in the liver using spatially resolved metabolomics

Cells adapt their metabolism to physiological stimuli, and metabolic heterogeneity exists between cell types, within tissues, and subcellular compartments. The liver plays an essential role in maintaining whole-body metabolic homeostasis and is structurally defined by metabolic zones. These zones are well-understood on the transcriptomic level, but have not been comprehensively characterized on the metabolomic level. Mass spectrometry imaging (MSI) can be used to map hundreds of metabolites directly from a tissue section, offering an important advance to investigate metabolic heterogeneity in tissues compared to extraction-based metabolomics methods that analyze tissue metabolite profiles in bulk. We established a workflow for the preparation of tissue specimens for matrix-assisted laser desorption/ionization (MALDI) MSI and achieved broad coverage of central carbon, nucleotide, and lipid metabolism pathways. We used this approach to visualize the effect of nutrient stress and excess on liver metabolism. Our data revealed a highly organized metabolic compartmentalization in livers, which becomes disrupted under nutrient stress conditions. Fasting caused changes in glucose metabolism and increased the levels of fatty acids in the circulation. In contrast, a prolonged high-fat diet (HFD) caused lipid accumulation within liver tissues with clear zonal patterns. Fatty livers had higher levels of purine and pentose phosphate related metabolites, which generates reducing equivalents to counteract oxidative stress. This MALDI MSI approach allowed the visualization of liver metabolic compartmentalization at high resolution and can be applied more broadly to yield new insights into metabolic heterogeneity in vivo.

biochemistry↗

bioRxiv2021

De Novo Pyrimidine Synthesis is a Targetable Vulnerability in IDH Mutant Glioma

Mutations affecting isocitrate dehydrogenase (IDH) enzymes are prevalent in glioma, leukemia, and other cancers. Although mutant IDH inhibitors are effective against leukemia, they appear less active in aggressive glioma, underscoring the need for alternative treatment strategies. Through a chemical synthetic lethality screen, we discovered that IDH1 mutant glioma cells are hypersensitive to drugs targeting enzymes in the de novo pyrimidine nucleotide synthesis pathway, including dihydroorotate dehydrogenase (DHODH). We developed a genetically engineered mouse model of mutant IDH1-driven astrocytoma and used it and multiple patient-derived models to show that the brain-penetrant DHODH inhibitor BAY 2402234 displays monotherapy efficacy against IDH mutant gliomas. Mechanistically, this vulnerability selectively applies to de novo pyrimidine, but not purine, synthesis because glioma cells engage disparate programs to produce these nucleotide species and because IDH oncogenes increase DNA damage upon nucleotide pool imbalance. Our work outlines a tumor-selective, biomarker-guided therapeutic strategy that is poised for clinical translation.

cancer biology↗

bioRxiv2021

A druggable addiction to de novo pyrimidine biosynthesis in diffuse midline glioma

Diffuse midline glioma (DMG) is a uniformly fatal pediatric cancer driven by oncohistones that do not readily lend themselves to drug development. To identify druggable targets for DMG, we conducted a genome-wide CRISPR screen that reveals a DMG selective dependency on the de novo pathway for pyrimidine biosynthesis. This metabolic vulnerability reflects an elevated rate of uridine/uracil degradation that depletes DMG cells of substrates for the alternate salvage pathway for pyrimidine biosynthesis. A clinical stage inhibitor of DHODH (rate limiting enzyme in the de novo pathway) diminishes UMP pools, generates DNA damage, and induces apoptosis through suppression of replication forks--an "on target" effect, as shown by uridine rescue. MALDI mass spectroscopy imaging demonstrates that this DHODH inhibitor (BAY2402234) accumulates in brain at therapeutically relevant concentrations, suppresses de novo pyrimidine biosynthesis in vivo, and prolongs survival of mice bearing intracranial DMG xenografts, highlighting BAY2402234 as a promising therapy against DMGs.

cancer biology↗