Publications by authors named "Christopher Patsalis"
Background: Metabolomics is a high-throughput technology that measures small molecule metabolites in cells, tissues or biofluids. Analysis of metabolomics data is a multi-step process that involves data processing, quality control and normalization, followed by statistical and bioinformatics analysis. The latter step often involves pathway analysis to aid biological interpretation of the data.
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- Analyzed molecular profiles in bladder cancer (BC) to find invasive markers that can tailor personalized treatments for patients with advanced or metastatic disease.
- Developed a less invasive liquid biopsy method using a graphene oxide microfluidic chip to isolate circulating tumor cells (CTCs) from blood samples of BC patients.
- Found that higher CTC counts correlate with worse survival outcomes and identified gene expression changes related to metastasis and chemotherapy resistance, showcasing the potential of CTCs in assessing prognosis for metastatic BC.
A significant challenge in the analysis of omics data is extracting actionable biological knowledge. Metabolomics is no exception. The general problem of relating changes in levels of individual metabolites to specific biological processes is compounded by the large number of unknown metabolites present in untargeted liquid chromatography-mass spectrometry (LC-MS) studies.
View Article and Find Full Text PDFAlterations of the extracellular matrix contribute to adipose tissue dysfunction in metabolic disease. We studied the role of matrix density in regulating human adipocyte phenotype in a tunable hydrogel culture system. Lipid accumulation was maximal in intermediate hydrogel density of 5 weight %, relative to 3% and 10%.
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