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      Distinct initiating events underpin the immune and metabolic heterogeneity of KRAS-mutant lung adenocarcinoma

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          Abstract

          The KRAS oncoprotein, a critical driver in 33% of lung adenocarcinoma (LUAD), has remained an elusive clinical target due to its perceived undruggable nature. The identification of dependencies borne through common co-occurring mutations are sought to more effectively target KRAS-mutant lung cancer. Approximately 20% of KRAS-mutant LUAD carry loss-of-function mutations in KEAP1, a negative regulator of the antioxidant response transcription factor NFE2L2/NRF2. We demonstrate that Keap1-deficient Kras G12D lung tumors arise from a bronchiolar cell-of-origin, lacking pro-tumorigenic macrophages observed in tumors originating from alveolar cells. Keap1 loss activates the pentose phosphate pathway, inhibition of which, using 6-AN, abrogated tumor growth. These studies highlight alternative therapeutic approaches to specifically target this unique subset of KRAS-mutant LUAD cancers.

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          Most cited references36

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          Controlling the False Discovery Rate: A Practical and Powerful Approach to Multiple Testing

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            Integrative analysis of complex cancer genomics and clinical profiles using the cBioPortal.

            The cBioPortal for Cancer Genomics (http://cbioportal.org) provides a Web resource for exploring, visualizing, and analyzing multidimensional cancer genomics data. The portal reduces molecular profiling data from cancer tissues and cell lines into readily understandable genetic, epigenetic, gene expression, and proteomic events. The query interface combined with customized data storage enables researchers to interactively explore genetic alterations across samples, genes, and pathways and, when available in the underlying data, to link these to clinical outcomes. The portal provides graphical summaries of gene-level data from multiple platforms, network visualization and analysis, survival analysis, patient-centric queries, and software programmatic access. The intuitive Web interface of the portal makes complex cancer genomics profiles accessible to researchers and clinicians without requiring bioinformatics expertise, thus facilitating biological discoveries. Here, we provide a practical guide to the analysis and visualization features of the cBioPortal for Cancer Genomics.
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              Testing significance relative to a fold-change threshold is a TREAT

              Motivation: Statistical methods are used to test for the differential expression of genes in microarray experiments. The most widely used methods successfully test whether the true differential expression is different from zero, but give no assurance that the differences found are large enough to be biologically meaningful. Results: We present a method, t-tests relative to a threshold (TREAT), that allows researchers to test formally the hypothesis (with associated p-values) that the differential expression in a microarray experiment is greater than a given (biologically meaningful) threshold. We have evaluated the method using simulated data, a dataset from a quality control experiment for microarrays and data from a biological experiment investigating histone deacetylase inhibitors. When the magnitude of differential expression is taken into account, TREAT improves upon the false discovery rate of existing methods and identifies more biologically relevant genes. Availability: R code implementing our methods is contributed to the software package limma available at http://www.bioconductor.org. Contact: smyth@wehi.edu.au
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                Author and article information

                Journal
                Nature Communications
                Nat Commun
                Springer Science and Business Media LLC
                2041-1723
                December 2019
                September 13 2019
                December 2019
                : 10
                : 1
                Article
                10.1038/s41467-019-12164-y
                00db1013-59f2-4cc3-ba10-db407ac5a572
                © 2019

                https://creativecommons.org/licenses/by/4.0

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