NK cells are innate lymphoid cells that exert a key role in immune surveillance through the recognition and elimination of transformed cells and viral, bacterial, and protozoan pathogen-infected cells without prior sensitization. Elucidating when and how NK cell-induced intracellular microbial cell death functions in the resolution of infection and host inflammation has been an important topic of investigation. NK cell activation requires the engagement of specific activating, co-stimulatory, and inhibitory receptors which control positively and negatively their differentiation, memory, and exhaustion. NK cells secrete diverse cytokines, including IFN-γ, TNF-α/β, CD95/FasL, and TRAIL, as well as cytoplasmic cytotoxic granules containing perforin, granulysin, and granzymes A and B. Paradoxically, NK cells also kill other immune cells like macrophages, dendritic cells, and hyper-activated T cells, thus turning off self-immune reactions. Here we first provide an overview of NK cell biology, and then we describe and discuss the life–death signals that connect the microbial pathogen sensors to the inflammasomes and finally to cell death signaling pathways. We focus on caspase-mediated cell death by apoptosis and pro-inflammatory and non-caspase-mediated cell death by necroptosis, as well as inflammasome- and caspase-mediated pyroptosis.
With multiple omics strategies being applied to several cancer genomics projects, researchers have the opportunity to develop a rational planning of targeted cancer therapy. The investigation of such numerous and diverse pharmacogenomic datasets is a complex task. It requires biological knowledge and skills on a set of tools to accurately predict signaling network and clinical outcomes. Herein, we describe Web-based in silico approaches user friendly for exploring integrative studies on cancer biology and pharmacogenomics. We briefly explain how to submit a query to cancer genome databases to predict which genes are significantly altered across several types of cancers using CBioPortal. Moreover, we describe how to identify clinically available drugs and potential small molecules for gene targeting using CellMiner. We also show how to generate a gene signature and compare gene expression profiles to investigate the complex biology behind drug response using Connectivity Map. Furthermore, we discuss on-going challenges, limitations and new directions to integrate molecular, biological and epidemiological information from oncogenomics platforms to create hypothesis-driven projects. Finally, we discuss the use of Patient-Derived Xenografts models (PDXs) for drug profiling in vivo assay. These platforms and approaches are a rational way to predict patient-targeted therapy response and to develop clinically relevant small molecules drugs.
Genome-wide association studies (GWAS) and polygenic risk scores (PRS) are multistep analytical tools to identify genetic variants and to assess their contribution to phenotypes/diseases. These analyses are evolving and becoming instrumental to understand the genetic architecture of complex phenotypes/diseases. Nevertheless, to date, there is no single solution incorporating all major steps related to those analyses combined with robust populational bias correction. Here, we describe a semi-automated pipeline unifying steps involved in GWAS and PRS including widely used software. Our pipeline handles quality control (QC), GWAS, and PRS steps, managing different types of input/output files. Furthermore, it includes robust bias correction steps , such as inference of kinship matrix with correction for population structure, use of principal component analysis (PCA) with detection and removal of outlier variant followed by re-projection of related individuals (if desired), generation of PCA figures that assist in setting the best number of principal components (PCs) for association analysis, availability of mixed models, use of recommended software for GWAS based on population size, and a Markov chain Monte Carlo (MCMC) method to estimate best set of PRS parameters. Finally, we tested GARSA pipeline in a family-based Brazilian admixed population and demonstrated that the corrections implemented indeed mitigate bias in downstream analysis. The pipeline can be implemented on personal or server-side environments.
Dermcidin (DCD) is a candidate oncogene localized at 12q13.1 and co-amplified with multiple oncogenes in many tumor cells, including breast carcinomas and melanomas. DCD is one of the 100 gene signature for melanomas. To further understand the role of DCD on growth, survival and progression of melanoma cells, we selected G-361 melanoma cell clones expressing shRNA to DCD and established in vitro and in vivo models. In this study we evaluated the pharmacologic effects of vemurafenib (BRAFV600E inhibitor) and chloroquine (autophagy inhibitor) in cell viability and tumor growth of two melanoma cell lines identified as G-361 pLKO, which expresses DCD and BRAFV600E, and G-361 IBC I which express shRNA to silence DCD constitutively. Vemurafenib induces features of stress-induced senescence in addition to apoptosis. G-361 melanoma cells responded to vemurafenib (1-2 μM) alone or combined with chloroquine (50-100 μM) which increased apoptosis rates, while decreasing senescent cells expressing β-galactosidase enzyme. Vemurafenib (50 mg/kg / 21 days) inhibited melanoma growth in immunodeficient mice dependent on DCD expression. Chloroquine (30 mg/kg) in combination with vemurafenib, accelerated (given at 24-hour interval), and reduced (given at 72 hours interval), melanoma growth. Tumor cells resistant to vemurafenib and chloroquine displayed atypical cell morphology and nuclear histological patterns and diferential expression of melanocytic differentiation biomarkers S100, HMB-45, Melan-A and pancytokeratins. This work confirms the efficacy of vemurafenib and suggests potential adjuvant effects of chloroquine. It also confirms the role of dermcidin as growth factor and oncogene for melanoma cells. Citation Format: Jennifer Montoya Neyra, Jose Belizario. Modulation of cytotoxic effects of vemurafenib by chloroquine in malignant melanoma cells G-361: Role of dermcidin [abstract]. In: Proceedings of the AACR Special Conference on Tumor Immunology and Immunotherapy; 2017 Oct 1-4; Boston, MA. Philadelphia (PA): AACR; Cancer Immunol Res 2018;6(9 Suppl):Abstract nr B19.
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