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      Immunotherapy for early breast cancer: too soon, too superficial, or just right?

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      Annals of Oncology
      Elsevier BV

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          The Immune Landscape of Cancer

          We performed an extensive immunogenomic analysis of more than 10,000 tumors comprising 33 diverse cancer types by utilizing data compiled by TCGA. Across cancer types, we identified six immune subtypes-wound healing, IFN-γ dominant, inflammatory, lymphocyte depleted, immunologically quiet, and TGF-β dominant-characterized by differences in macrophage or lymphocyte signatures, Th1:Th2 cell ratio, extent of intratumoral heterogeneity, aneuploidy, extent of neoantigen load, overall cell proliferation, expression of immunomodulatory genes, and prognosis. Specific driver mutations correlated with lower (CTNNB1, NRAS, or IDH1) or higher (BRAF, TP53, or CASP8) leukocyte levels across all cancers. Multiple control modalities of the intracellular and extracellular networks (transcription, microRNAs, copy number, and epigenetic processes) were involved in tumor-immune cell interactions, both across and within immune subtypes. Our immunogenomics pipeline to characterize these heterogeneous tumors and the resulting data are intended to serve as a resource for future targeted studies to further advance the field.
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            Atezolizumab and Nab-Paclitaxel in Advanced Triple-Negative Breast Cancer

            Unresectable locally advanced or metastatic triple-negative (hormone-receptor-negative and human epidermal growth factor receptor 2 [HER2]-negative) breast cancer is an aggressive disease with poor outcomes. Nanoparticle albumin-bound (nab)-paclitaxel may enhance the anticancer activity of atezolizumab.
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              Immune-Related Adverse Events Associated with Immune Checkpoint Blockade

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                Author and article information

                Journal
                Annals of Oncology
                Annals of Oncology
                Elsevier BV
                09237534
                March 2021
                March 2021
                : 32
                : 3
                : 323-336
                Article
                10.1016/j.annonc.2020.11.022
                33307202
                332ea1ca-933c-4c6c-97e1-5b8b545102c2
                © 2021

                https://www.elsevier.com/tdm/userlicense/1.0/

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