693 research outputs found
Stem Cell-Derived Models of Neural Crest Are Essential to Understand Melanoma Progression and Therapy Resistance
Get PDFDuring development, neural crest (NC) cells are early precursors of several lineages including melanocytes. Along their differentiation from multipotent cells to mature melanocytes, NC cells will go through successive steps which require either proliferative or motile capacities. For example, they will undergo Epithelial to Mesenchymal Transition (EMT) in order the separate from the neural tube and migrate to their final location in the epidermis (Larribere and Utikal, 2013; Skrypek et al., 2017). The differentiated melanocytes are the cells of origin of melanoma tumors which progress through several stages such as radial growth phase, vertical growth phase, metastasis formation, and often resistance to current therapies. Interestingly, depending on the stage of the disease, melanoma tumor cells share phenotypes with NC cells (proliferative, motile, EMT). These phenotypes are tightly controlled by specific signaling pathways and transcription factors (TFs) which tend to be reactivated during the onset of melanoma. In this review, we summarize first the main TFs which control these common phenotypes. Then, we focus on the existing strategies used to generate human NCs. Finally we discuss how identification and regulation of NC-associated genes provide an additional approach to improving current melanoma targeted therapies
The Antithetic Roles of IQGAP2 and IQGAP3 in Cancers
Get PDFThe scaffold protein family of IQ motif-containing GTPase-activating proteins (IQGAP1, 2, and 3) share a high degree of homology and comprise six functional domains. IQGAPs bind and regulate the cytoskeleton, interact with MAP kinases and calmodulin, and have GTPase-related activity, as well as a RasGAP domain. Thus, IQGAPs regulate multiple cellular processes and pathways, affecting cell division, growth, cell–cell interactions, migration, and invasion. In the past decade, significant evidence on the function of IQGAPs in signal transduction during carcinogenesis has emerged. Compared with IQGAP1, IQGAP2 and IQGAP3 were less analyzed. In this review, we summarize the different signaling pathways affected by IQGAP2 and IQGAP3, and the antithetic roles of IQGAP2 and IQGAP3 in different types of cancer. IQGAP2 expression is reduced and plays a tumor suppressor role in most solid cancer types, while IQGAP3 is overexpressed and acts as an oncogene. In lymphoma, for example, IQGAPs have partially opposite functions. There is considerable evidence that IQGAPs regulate a multitude of pathways to modulate cancer processes and chemoresistance, but some questions, such as how they trigger this signaling, through which domains, and why they play opposite roles on the same pathways, are still unanswered
Partial reprogramming: a model for melanoma targeted therapy resistance
No full textUCR::Rectoría::Oficina de Asuntos Internacionales y Cooperación Externa (OAICE
Partial reprogramming: a model for melanoma targeted therapy resistance
No full textThesis (doctor of natural sciences)--Ruperto Carola University Heidelberg. Faculty of Natural Sciences and Mathematics, 2019UCR::Rectoría::Oficina de Asuntos Internacionales y Cooperación Externa (OAICE
Clinical characteristics and therapy response in unresectable melanoma patients stage IIIB-IIID with in-transit and satellite metastases
No full textMelanoma Extracellular Vesicles Generate Immunosuppressive Myeloid Cells by Upregulating PD-L1 via TLR4 Signaling
No full textTumor cell-derived extracellular vesicles (EV) convert normal myeloid cells into myeloid-derived suppressor cells (MDSC), inhibiting antitumor immune responses. Here, we show that EV from Ret mouse melanoma cells upregulate the expression of programmed cell death ligand 1 (PD-L1) on mouse immature myeloid cells (IMC), leading to suppression of T-cell activation. PD-L1 expression and the immunosuppressive potential of EV-generated MDSC were dependent on the expression of Toll-like receptors (TLR). IMC from Tlr4(-/-) mice failed to increase T-cell PD-L1 expression and immunosuppression with Ret-EV treatment, and this effect was dependent on heat-shock protein 86 (HSP86) as HSP86-deficient Ret cells could not stimulate PD-L1 expression on normal IMC; IMC from Tlr2(-/-) and Tlr7(-/-) mice demonstrated similar results, although to a lesser extent. HSP86-deficient Ret cells slowed tumor progression in vivo associated with decreased frequency of tumor-infiltrating PD-L1(+) CD11b(+) Gr1(+) MDSC. EV from human melanoma cells upregulated PD-L1 and immunosuppression of normal monocytes dependent on HSP86. These findings highlight a novel EV-mediated mechanism of MDSC generation from normal myeloid cells, suggesting the importance of EV targeting for tumor therapy.Significance: These findings validate the importance of TLR4 signaling in reprogramming normal myeloid cells into functional myeloid-derived suppressor cells
Lipase elevation and type 1 diabetes mellitus related to immune checkpoint inhibitor therapy – A multicentre study of 90 patients from the German Dermatooncology Group
No full textFlagellin-Induced Immune Response in Human-Induced Pluripotent Stem Cell-Derived Cardiomyocytes
No full textPathogen-associated molecular patterns (PAMPs) are involved in the pathogenesis of septic cardiomyopathy through a toll-like receptor (TLR)-mediated immune response. Human-induced pluripotent stem cell-derived cardiomyocytes (hiPSC-CMs) can reflect the innate immune abilities of cardiomyocytes. Therefore, hiPSC-CMs may provide an attractive tool with which to study PAMP-induced alterations in cardiomyocytes. HiPSC-CMs from two different healthy donors were exposed to the PAMP flagellin (FLA) at different doses and exposure times. Alterations in the expression levels of distinct inflammation-associated cytokines, intracellular inflammation pathways including TLR5 downstream signaling, reactive oxygen species levels and surface antigen composition were assessed using PCR, ELISA and FACS techniques. Higher doses of flagellin increased the expression levels of inflammation-associated cytokines like TNFα (p < 0.01) and downstream signaling molecules like caspase-8 (p < 0.05). TLR5 expression (p < 0.01) and TLR5 fluorescence proportion (p < 0.05) increased in hiPSC-CMs after prolonged FLA exposure. FLA-induced innate immune response processes in cardiomyocytes might be detectable with an hiPSC-CMs-based in vitro model
Skin Cancer Classification Using Convolutional Neural Networks: Systematic Review
Get PDFBackground: State-of-the-art classifiers based on convolutional neural networks (CNNs) were shown to classify images of skin cancer on par with dermatologists and could enable lifesaving and fast diagnoses, even outside the hospital via installation of apps on mobile devices. To our knowledge, at present there is no review of the current work in this research area. Objective: This study presents the first systematic review of the state-of-the-art research on classifying skin lesions with CNNs. We limit our review to skin lesion classifiers. In particular, methods that apply a CNN only for segmentation or for the classification of dermoscopic patterns are not considered here. Furthermore, this study discusses why the comparability of the presented procedures is very difficult and which challenges must be addressed in the future. Methods: We searched the Google Scholar, PubMed, Medline, ScienceDirect, and Web of Science databases for systematic reviews and original research articles published in English. Only papers that reported sufficient scientific proceedings are included in this review. Results: We found 13 papers that classified skin lesions using CNNs. In principle, classification methods can be differentiated according to three principles. Approaches that use a CNN already trained by means of another large dataset and then optimize its parameters to the classification of skin lesions are the most common ones used and they display the best performance with the currently available limited datasets. Conclusions: CNNs display a high performance as state-of-the-art skin lesion classifiers. Unfortunately, it is difficult to compare different classification methods because some approaches use nonpublic datasets for training and/or testing, thereby making reproducibility difficult. Future publications should use publicly available benchmarks and fully disclose methods used for training to allow comparability
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