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Building live chat app with GraphQL subscriptions
Interesting article showing the basics of writing a GraphQL app to query and post and subscribe to updates in order to make a real time application. Uses graphql-yoga library to create a simple GraphQL server for the project.
GraphQL  chat  Article  realtime  subscriptions  mutations  graphql-yoga  ChimezieEnyinnaya  node.js  npm 
8 weeks ago by searchmeister
Multi-Omics Profiling Reveals Distinct Microenvironment Characterization and Suggests Immune Escape Mechanisms of Triple-Negative Breast Cancer | Clinical Cancer Research
Purpose: The tumor microenvironment has a profound impact on prognosis and immunotherapy. However, the landscape of the triple-negative breast cancer (TNBC) microenvironment has not been fully understood.

Experimental Design: Using the largest original multi-omics dataset of TNBC (n = 386), we conducted an extensive immunogenomic analysis to explore the heterogeneity and prognostic significance of the TNBC microenvironment. We further analyzed the potential immune escape mechanisms of TNBC.

Results: The TNBC microenvironment phenotypes were classified into three heterogeneous clusters: cluster 1, the “immune-desert” cluster, with low microenvironment cell infiltration; cluster 2, the “innate immune-inactivated” cluster, with resting innate immune cells and nonimmune stromal cells infiltration; and cluster 3, the “immune-inflamed” cluster, with abundant adaptive and innate immune cells infiltration. The clustering result was validated internally with pathologic sections and externally with The Cancer Genome Atlas and METABRIC cohorts. The microenvironment clusters had significant prognostic efficacy. In terms of potential immune escape mechanisms, cluster 1 was characterized by an incapability to attract immune cells, and MYC amplification was correlated with low immune infiltration. In cluster 2, chemotaxis but inactivation of innate immunity and low tumor antigen burden might contribute to immune escape, and mutations in the PI3K-AKT pathway might be correlated with this effect. Cluster 3 featured high expression of immune checkpoint molecules.

Conclusions: Our study represents a step toward personalized immunotherapy for patients with TNBC. Immune checkpoint inhibitors might be effective for “immune-inflamed” cluster, and the transformation of “cold tumors” into “hot tumors” should be considered for “immune-desert” and “innate immune-inactivated” clusters.
TNBC  gene_expression  survival  mutations 
august 2019 by Segalllab
Oncotarget | Immunocompetent mouse allograft models for development of therapies to target breast cancer metastasis
Useful summary of the standard mouse breast cancer cell lines, including 4T1, Met1, EO771 and others - genetic mutation and gene expression analysis as well. Most are luminal. Metastasis data are in supplemental table 1 - MET1s are only metastatic by tail vein and they not high variability for them.

Effective drug development to combat metastatic disease in breast cancer would be aided by the availability of well-characterized preclinical animal models that (a) metastasize with high efficiency, (b) metastasize in a reasonable time-frame, (c) have an intact immune system, and (d) capture some of the heterogeneity of the human disease. To address these issues, we have assembled a panel of twelve mouse mammary cancer cell lines that can metastasize efficiently on implantation into syngeneic immunocompetent hosts. Genomic characterization shows that more than half of the 30 most commonly mutated genes in human breast cancer are represented within the panel. Transcriptomically, most of the models fall into the luminal A or B intrinsic molecular subtypes, despite the predominance of an aggressive, poorly-differentiated or spindled histopathology in all models. Patterns of immune cell infiltration, proliferation rates, apoptosis and angiogenesis differed significantly among models. Inherent within-model variability of the metastatic phenotype mandates large cohort sizes for intervention studies but may also capture some relevant non-genetic sources of variability. The varied molecular and phenotypic characteristics of this expanded panel of models should aid in model selection for development of antimetastatic therapies in vivo, and serve as a useful platform for predictive biomarker identification.
mouse_models  breast_cancer  mutations  gene_expression 
august 2019 by Segalllab

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