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      Tetraspanin CD82 drives Acute Myeloid Leukemia chemoresistance by modulating Protein Kinase C alpha and β1 integrin activation

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          Abstract

          A principal challenge in treating acute myeloid leukemia (AML) is chemotherapy refractory disease. As such, there remains a critical need to identify key regulators of chemotherapy resistance in AML. In this study, we demonstrate that the membrane scaffold, CD82, contributes to the chemoresistant phenotype of AML. Using an RNA-seq approach, we identified the increased expression of the tetraspanin family member, CD82, in response to the chemotherapeutic, daunorubicin. Analysis of the TARGET and BEAT AML databases identifies a correlation between CD82 expression and overall survival of AML patients. Moreover, using a combination of cell lines and patient samples, we find that CD82 overexpression results in significantly reduced cell death in response to chemotherapy. Investigation of the mechanism by which CD82 promotes AML survival in response to chemotherapy identified a crucial role for enhanced protein kinase c alpha (PKCα) signaling and downstream activation of the β1 integrin. Additionally, analysis of β1 integrin clustering by super-resolution imaging demonstrates that CD82 expression promotes the formation of dense β1 integrin membrane clusters. Lastly, evaluation of survival signaling following daunorubicin treatment identified robust activation of p38 mitogen-activated protein kinase (MAPK) downstream of PKCα and β1 integrin signaling when CD82 is overexpressed. Together, these data propose a mechanism where CD82 promotes chemoresistance by increasing PKCα activation and downstream activation/clustering of β1 integrin, leading to AML cell survival via activation of p38 MAPK. These observations suggest that the CD82-PKCα signaling axis may be a potential therapeutic target for attenuating chemoresistance signaling in AML.

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          Most cited references67

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          Is Open Access

          SARTools: A DESeq2- and EdgeR-Based R Pipeline for Comprehensive Differential Analysis of RNA-Seq Data

          Background Several R packages exist for the detection of differentially expressed genes from RNA-Seq data. The analysis process includes three main steps, namely normalization, dispersion estimation and test for differential expression. Quality control steps along this process are recommended but not mandatory, and failing to check the characteristics of the dataset may lead to spurious results. In addition, normalization methods and statistical models are not exchangeable across the packages without adequate transformations the users are often not aware of. Thus, dedicated analysis pipelines are needed to include systematic quality control steps and prevent errors from misusing the proposed methods. Results SARTools is an R pipeline for differential analysis of RNA-Seq count data. It can handle designs involving two or more conditions of a single biological factor with or without a blocking factor (such as a batch effect or a sample pairing). It is based on DESeq2 and edgeR and is composed of an R package and two R script templates (for DESeq2 and edgeR respectively). Tuning a small number of parameters and executing one of the R scripts, users have access to the full results of the analysis, including lists of differentially expressed genes and a HTML report that (i) displays diagnostic plots for quality control and model hypotheses checking and (ii) keeps track of the whole analysis process, parameter values and versions of the R packages used. Conclusions SARTools provides systematic quality controls of the dataset as well as diagnostic plots that help to tune the model parameters. It gives access to the main parameters of DESeq2 and edgeR and prevents untrained users from misusing some functionalities of both packages. By keeping track of all the parameters of the analysis process it fits the requirements of reproducible research.
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            Non-Classical P38 Map Kinase Functions: Cell Cycle Checkpoints and Survival

            The p38 MAPK kinase pathway is activated in response to a wide range of cellular stress stimuli and cytokines. Our understanding of the important functions of p38 MAPK in the process of differentiation and cell death has grown considerably in the recent years and is now relatively established. Here we discuss the role of p38 MAPK in the mediation of cell cycle checkpoints and cell survival, processes that have received less attention. We describe how p38 MAPK regulates both the G2/M as well as a G1/S cell cycle checkpoint in response to cellular stress such as DNA damage. While p38 MAPK has classically been associated with the induction of apoptosis, we discuss that p38 MAPK can also mediate cell survival in specific situations, such as in response to DNA damage. It is important to recognize these less appreciated functions of p38 MAPK when considering the potential use of pharmacological inhibitors of p38 MAPK in therapeutic treatments for disease.
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              Tetraspanin proteins promote multiple cancer stages.

              An abundance of evidence shows supporting roles for tetraspanin proteins in human cancer. Many studies show that the expression of tetraspanins correlates with tumour stage, tumour type and patient outcome. In addition, perturbations of tetraspanins in tumour cell lines can considerably affect cell growth, morphology, invasion, tumour engraftment and metastasis. This Review emphasizes new studies that have used de novo mouse cancer models to show that select tetraspanin proteins have key roles in tumour initiation, promotion and metastasis. This Review also emphasizes how tetraspanin proteins can sometimes participate in tumour angiogenesis. These recent data build an increasingly strong case for tetraspanins as therapeutic targets.
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                Author and article information

                Journal
                8711562
                6325
                Oncogene
                Oncogene
                Oncogene
                0950-9232
                1476-5594
                14 March 2020
                19 March 2020
                May 2020
                19 September 2020
                : 39
                : 19
                : 3910-3925
                Affiliations
                [1 ]Department of Pathology, University of New Mexico Health Sciences Center, Albuquerque, NM 87131
                [2 ]Department of Physics and Astronomy, University of New Mexico, Albuquerque, NM 87131
                [3 ]UNM Comprehensive Cancer Center, Albuquerque, NM 87131
                Author notes
                [* ]corresponding author: jgillette@ 123456salud.unm.edu
                Article
                NIHMS1572780
                10.1038/s41388-020-1261-0
                7210072
                32203165
                6695ea2b-1407-46a6-843f-f79c693c3e73

                Users may view, print, copy, and download text and data-mine the content in such documents, for the purposes of academic research, subject always to the full Conditions of use: http://www.nature.com/authors/editorial_policies/license.html#terms

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                Oncology & Radiotherapy
                Oncology & Radiotherapy

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