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Permanent URI for this collectionhttps://hdl.handle.net/20.500.14288/6

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Department: search.filters.department.Department of Industrial EngineeringSubject: search.filters.subject.Oncology

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    PublicationOpen Access
    Identifying tissue- and cohort-specific RNA regulatory modules in cancer cells using multitask learning
    (Multidisciplinary Digital Publishing Institute (MDPI), 2022) Maass, Philipp G.; N/A; Department of Industrial Engineering; Mokhtaridoost, Milad; Gönen, Mehmet; Faculty Member; Department of Industrial Engineering; Graduate School of Sciences and Engineering; College of Engineering; School of Medicine; N/A; 237468
    Understanding the underlying biological mechanisms of primary tumors is crucial for predicting how tumors respond to therapies and exploring accurate treatment strategies. miRNA-mRNA interactions have a major effect on many biological processes that are important in the formation and progression of cancer. In this study, we introduced a computational pipeline to extract tissue- and cohort-specific miRNA-mRNA regulatory modules of multiple cancer types from the same origin using miRNA and mRNA expression profiles of primary tumors. Our model identified regulatory modules of underlying cancer types (i.e., cohort-specific) and shared regulatory modules between cohorts (i.e., tissue-specific). MicroRNA (miRNA) alterations significantly impact the formation and progression of human cancers. miRNAs interact with messenger RNAs (mRNAs) to facilitate degradation or translational repression. Thus, identifying miRNA-mRNA regulatory modules in cohorts of primary tumor tissues are fundamental for understanding the biology of tumor heterogeneity and precise diagnosis and treatment. We established a multitask learning sparse regularized factor regression (MSRFR) method to determine key tissue- and cohort-specific miRNA-mRNA regulatory modules from expression profiles of tumors. MSRFR simultaneously models the sparse relationship between miRNAs and mRNAs and extracts tissue- and cohort-specific miRNA-mRNA regulatory modules separately. We tested the model's ability to determine cohort-specific regulatory modules of multiple cancer cohorts from the same tissue and their underlying tissue-specific regulatory modules by extracting similarities between cancer cohorts (i.e., blood, kidney, and lung). We also detected tissue-specific and cohort-specific signatures in the corresponding regulatory modules by comparing our findings from various other tissues. We show that MSRFR effectively determines cancer-related miRNAs in cohort-specific regulatory modules, distinguishes tissue- and cohort-specific regulatory modules from each other, and extracts tissue-specific information from different cohorts of disease-related tissue. Our findings indicate that the MSRFR model can support current efforts in precision medicine to define tumor-specific miRNA-mRNA signatures.
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    PublicationOpen Access
    Identification of SERPINE1 as a regulator of glioblastoma cell dispersal with transcriptome profiling
    (Multidisciplinary Digital Publishing Institute (MDPI), 2019) Uyulur, Fırat; Selvan, Myvizhi Esa; Gümüş, Zeynep Hülya; Bayraktar, Halil; Wakimoto, Hiroaki; Department of Industrial Engineering; Şeker-Polat, Fidan; Cingöz, Ahmet; Sur, İlknur Erdem; Ergüder, Nazlı; Erkent, Mahmut Alp; Önder, Tuğba Bağcı; Gönen, Mehmet; PhD Student; Faculty Member; Department of Industrial Engineering; Graduate School of Sciences and Engineering; College of Engineering; N/A; N/A; N/A; N/A; N/A; 184359; 237468
    High mortality rates of glioblastoma (GBM) patients are partly attributed to the invasive behavior of tumor cells that exhibit extensive infiltration into adjacent brain tissue, leading to rapid, inevitable, and therapy-resistant recurrence. In this study, we analyzed transcriptome of motile (dispersive) and non-motile (core) GBM cells using an in vitro spheroid dispersal model and identified SERPINE1 as a modulator of GBM cell dispersal. Genetic or pharmacological inhibition of SERPINE1 reduced spheroid dispersal and cell adhesion by regulating cell-substrate adhesion. We examined TGFβ as a potential upstream regulator of SERPINE1 expression. We also assessed the significance of SERPINE1 in GBM growth and invasion using TCGA glioma datasets and a patient-derived orthotopic GBM model. SERPINE1 expression was associated with poor prognosis and mesenchymal GBM in patients. SERPINE1 knock-down in primary GBM cells suppressed tumor growth and invasiveness in the brain. Together, our results indicate that SERPINE1 is a key player in GBM dispersal and provide insights for future anti-invasive therapy design.