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      XBP1 Promotes Triple Negative Breast Cancer By Controlling the HIF1 α Pathway

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          Abstract

          Cancer cells induce a set of adaptive response pathways to survive in the face of stressors due to inadequate vascularization 1 . One such adaptive pathway is the unfolded protein (UPR) or endoplasmic reticulum (ER) stress response mediated in part by the ER-localized transmembrane sensor IRE1 2 and its substrate XBP1 3 . Previous studies report UPR activation in various human tumors 4- 6 , but XBP1's role in cancer progression in mammary epithelial cells is largely unknown. Triple negative breast cancer (TNBC), a form of breast cancer in which tumor cells do not express the genes for estrogen receptor, progesterone receptor, and Her2/neu, is a highly aggressive malignancy with limited treatment options 7, 8 . Here, we report that XBP1 is activated in TNBC and plays a pivotal role in the tumorigenicity and progression of this human breast cancer subtype. In breast cancer cell line models, depletion of XBP1 inhibited tumor growth and tumor relapse and reduced the CD44 high/CD24 low population. Hypoxia-inducing factor (HIF)1α is known to be hyperactivated in TNBCs 9, 10 . Genome-wide mapping of the XBP1 transcriptional regulatory network revealed that XBP1 drives TNBC tumorigenicity by assembling a transcriptional complex with HIF1α that regulates the expression of HIF1α targets via the recruitment of RNA polymerase II. Analysis of independent cohorts of patients with TNBC revealed a specific XBP1 gene expression signature that was highly correlated with HIF1α and hypoxia-driven signatures and that strongly associated with poor prognosis. Our findings reveal a key function for the XBP1 branch of the UPR in TNBC and imply that targeting this pathway may offer alternative treatment strategies for this aggressive subtype of breast cancer.

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          The JAK2/STAT3 signaling pathway is required for growth of CD44⁺CD24⁻ stem cell-like breast cancer cells in human tumors.

          Intratumor heterogeneity is a major clinical problem because tumor cell subtypes display variable sensitivity to therapeutics and may play different roles in progression. We previously characterized 2 cell populations in human breast tumors with distinct properties: CD44+CD24- cells that have stem cell-like characteristics, and CD44-CD24+ cells that resemble more differentiated breast cancer cells. Here we identified 15 genes required for cell growth or proliferation in CD44+CD24- human breast cancer cells in a large-scale loss-of-function screen and found that inhibition of several of these (IL6, PTGIS, HAS1, CXCL3, and PFKFB3) reduced Stat3 activation. We found that the IL-6/JAK2/Stat3 pathway was preferentially active in CD44+CD24- breast cancer cells compared with other tumor cell types, and inhibition of JAK2 decreased their number and blocked growth of xenografts. Our results highlight the differences between distinct breast cancer cell types and identify targets such as JAK2 and Stat3 that may lead to more specific and effective breast cancer therapies.
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            Hypoxia signalling through mTOR and the unfolded protein response in cancer.

            Hypoxia occurs in the majority of tumours, promoting angiogenesis, metastasis and resistance to therapy. Responses to hypoxia are orchestrated in part through activation of the hypoxia-inducible factor family of transcription factors (HIFs). Recently, two additional O(2)-sensitive signalling pathways have also been implicated: signalling through the mammalian target of rapamycin (mTOR) kinase and signalling through activation of the unfolded protein response (UPR). Although they are activated independently, growing evidence suggests that HIF-, mTOR- and UPR-dependent responses to hypoxia act in an integrated way, influencing each other and common downstream pathways that affect gene expression, metabolism, cell survival, tumorigenesis and tumour growth.
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              Inducible formation of breast cancer stem cells and their dynamic equilibrium with non-stem cancer cells via IL6 secretion.

              Tumors are often heterogeneous, being composed of multiple cell types with different phenotypic and molecular properties. Cancer stem-like cells (CSCs) are a highly tumorigenic cell type found in developmentally diverse tumors or cancer cell lines, and they are often resistant to standard chemotherapeutic drugs. The origins of CSCs and their relationships to nonstem cancer cells (NSCCs) are poorly understood. In an inducible breast oncogenesis model, CSCs are generated from nontransformed cells at a specific time during the transformation process, but CSC formation is not required for transformation. MicroRNA profiles indicate that CSCs and NSCCs are related, but different cell types arising from a common nontransformed population. Interestingly, medium from the transformed population stimulates NSCCs to become CSCs, and conversion of NSCCs to CSCs occurs in mouse xenografts. Furthermore, IL6 is sufficient to convert NSCCs to CSCs in genetically different breast cell lines, human breast tumors, and a prostate cell line. Thus, breast and prostate CSCs and NSCCs do not represent distinct epigenetic states, and these CSCs do not behave as or arise from classic stem cells. Instead, tumor heterogeneity involves a dynamic equilibrium between CSCs and NSCCs mediated by IL6 and activation of the inflammatory feedback loop required for oncogenesis. This dynamic equilibrium provides an additional rationale for combining conventional chemotherapy with metformin, which selectively inhibits CSCs.
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                Author and article information

                Journal
                0410462
                6011
                Nature
                Nature
                Nature
                0028-0836
                1476-4687
                9 July 2014
                23 March 2014
                3 April 2014
                03 October 2014
                : 508
                : 7494
                : 103-107
                Affiliations
                [1 ] Weill Cornell Medical College, 1300 York Avenue, New York, NY 10065
                [2 ] Center for Systems Biomedicine, Division of Digestive Diseases and Institute for Molecular Medicine, University of California, Los Angeles, Los Angeles, CA 90095, USA
                [3 ] Lineberger Comprehensive Cancer Center, Department of Pathology and Laboratory Medicine, University of North Carolina at Chapel Hill, Chapel Hill, NC 27599, USA
                [4 ] Department of Cancer Immunology and AIDS
                [5 ] Department of Medical Oncology, Dana-Farber Cancer Institute and Department of Medicine, Harvard Medical School, Boston, MA 02115, USA
                [6 ] Department of Pathology, Brigham and Women's Hospital, Boston, MA 02115, USA
                [7 ] Department of Biostatistics and Computational Biology, Dana-Farber Cancer Institute and Harvard School of Public Health, Boston, MA 02215, USA
                [8 ] Department of Bioinformatics, School of Life Science and Technology, Tongji University, Shanghai, China
                [9 ] Institute of Animal Genetics and Breeding, Sichuan Agricultural University, Chengdu, Sichuan, China
                [10 ] Whitehead Institute for Biomedical Research, 9 Cambridge Center, Cambridge, MA 02142, USA
                [11 ] Department of Nanomedicine, Houston Methodist Research Institute, Houston, TX 77030, USA
                [12 ] Endocrine Unit, Massachusetts General Hospital, Boston, MA 02114, USA
                [13 ] Division of Hematology/Oncology, Children's Hospital Boston, Boston, MA 02115, USA
                [14 ] Department of Pathology and Laboratory Medicine, Weill Cornell Medical College, 1300 York Avenue, New York, NY 10065, USA
                [15 ] Methodist Cancer Center, Houston, TX 77030, USA
                Author notes
                Correspondence and requests for materials should be addressed to L.H.G. ( lglimche@ 123456med.cornell.edu ).
                Article
                NIHMS562371
                10.1038/nature13119
                4105133
                24670641
                e6c3def5-f673-4ff3-9960-3d8faecf8dcb
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