Cancers · 2020 · 154 citations · 52 references
MedicineCell BiologyOncologyMetastasisMolecular OncologyTumor ProgressionCancer TranscriptomicsEpithelial-mesenchymal TransitionEpithelial-to-mesenchymal TransitionMetastatic Breast CancerMolecular Tumor ProfilingSignal Transduction In CancerCell Migration AnalysisEpithelial-mesenchymal Transition In CancerEpithelial-mesenchymal Transition MarkersGene Expression AtlasesMesenchymal TransitionMetastatic BiomarkersMetastatic Breast Cancer BiologyTumor-associated Cytokines
Neutrophil extracellular traps (NETs) have been associated with several steps of tumor progression, including primary growth and metastasis. One of the key features for the acquisition of the metastatic ability is the epithelial-mesenchymal transition (EMT), a complex cellular program. In this study, we evaluated the ability of isolated NETs in modulating the pro-metastatic phenotype of human breast cancer cells. Tumor cells were treated with isolated NETs and then samples were generated for cell migration, quantitative RT-PCR, western blotting, immunofluorescence, and flow cytometry assays. RNA-seq data from The Cancer Genome Atlas (TCGA) database were assessed. NETs changed the typical epithelial morphology of MCF7 cells into a mesenchymal phenotype, a process that was accompanied by enhanced migratory properties. Additional EMT traits were observed: increased expression of N-cadherin and fibronectin, while the E-cadherin expression was repressed. Notably, NETs positively regulated the gene expression of several factors linked to the pro-inflammatory and pro-metastatic properties. Analyses of TCGA data showed that samples from breast cancer patients exhibit a significant correlation between pro-tumoral and neutrophil signature gene expression, including several EMT and pro-metastatic factors. Therefore, NETs drive pro-metastatic phenotype in human breast cancer cells through the activation of the EMT program.
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Ethan Cerami, Jianjiong Gao, Uğur Doğrusöz et al. · Cancer Discovery · 2012 · 18.4K citations · Full text
Medicine, Bioinformatics, Oncology +15
Integrative Analysis of Complex Cancer Genomics and Clinical Profiles Using the cBioPortal
Jianjiong Gao, Bülent Arman Aksoy, Uğur Doğrusöz et al. · Science Signaling · 2013 · 15.9K citations · Full text
Medicine, Bioinformatics, Oncology +17
Comprehensive molecular portraits of human breast tumours