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Growth Signaling Autonomy in Circulating Tumor Cells Aids Metastatic Seeding

ABSTRACT: Self-sufficiency (autonomy) in growth signaling, the earliest recognized hallmark of cancer, is fuelled by the tumor cell’s ability to ‘secrete-and-sense’ growth factors; this translates into cell survival and proliferation that is self-sustained by auto-/paracrine secretion. Using breast cancer cells that are either endowed or inept in growth signaling autonomy, here we reveal how tumor cell autonomy impacts cancer progression. Autonomy is associated with enhanced molecular programs for stemness, immune evasiveness, and epithelial-mesenchymal plasticity (EMP) across the entire mesenchymal spectrum. Autonomy is both necessary and sufficient for anchorage-independent growth factor-restricted growth, resistance to anti-cancer drugs and metastatic progression. Transcriptomic and proteomic studies show that autonomy is associated with self-sustained EGFR/ERBB signaling, a required signal for re-epithelialization. A gene expression signature was derived (a.k.a., autonomy signature) which revealed that autonomy is induced in circulating tumor cells (CTCs), the precursor tumor cells that re-epithelialize to initiate metastases. Autonomy in CTCs tracks therapeutic response and prognosticates outcome. Autonomy is present during reversible (but not stable) EMT and requires EGFR/ERBB signaling. These data support a role for growth signaling autonomy in the blood-borne dissemination of human breast cancer.

INSTRUMENT(S): Orbitrap Fusion Lumos

ORGANISM(S): Homo Sapiens (human)

TISSUE(S): Cell Culture

DISEASE(S): Colon Cancer

SUBMITTER: Majid Ghassemian

LAB HEAD: Pradipta Ghosh,

PROVIDER: PXD037253 | Pride | 2023-02-06

REPOSITORIES: Pride

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Project description:These 95 arrays are the basis for Figure 2 of our manuscript "An interferon-response induced by tumor-stroma interaction in a subset of human breast cancers". Abstract:Background Communication between different cell types is a cardinal feature of multi-cellular organisms and perturbations in these cell-cell interactions are a key feature of cancer. However, little is known about the systematic effects of cell-cell interaction on global gene expression in cancer. Methods and Findings We used an ex vivo culture model to simulate tumor-stroma interaction by systematically co-cultivating breast cancer cells with stromal fibroblasts and determined associated gene expression changes with cDNA microarrays. The picture of heterotypic interaction effects that emerged from this analysis is complex, reflecting the variation in signaling capacities and responsiveness of the involved cells. A frequent and prominent response to epithelial-mesenchymal interaction was an induction of interferon-response genes, observed in 4 of the 7 breast cancer cell lines in response to co-culture with fibroblasts, but not in normal mammary epithelial cells. In response to close contact with these breast cancer cells, the fibroblasts secreted type I interferons, which, in turn, induced expression of the IRGs in the tumor cells. Immunohistochemical analysis of human breast cancer tissues showed that STAT1, the key transcriptional activator of the interferon-response genes, and itself an IRG, was expressed in a subset of the cancers, with a striking pattern of elevated expression in the cancer cells in contact with, or close proximity to, the tumor stroma ? paralleling the response seen in our ex vivo model. In vivo, expression of the interferon-response genes was remarkably coherent, providing a basis for segregation of the 295 early-stage breast cancers into two groups. Tumors with high expression levels (n=161) of IRG were associated with significantly shorter overall survival; 59 % at 10 years versus 80% for tumors with low interferon-response gene expression levels (n=134) (log-rank p=0.001). Conclusion Our results suggest that an interaction between some breast cancer cells and stromal fibroblasts can induce an interferon response, and that this response may be associated with a greater propensity for tumor progression. Set of arrays organized by shared biological context, such as organism, tumors types, processes, etc. Computed

Project description:This a model from the article: A mathematical model for IL-6-mediated, stem cell driven tumor growth and targeted treatment Fereshteh Nazari, Alexander T. Pearson, Jacques Eduardo Nor, Trachette L. Jackson. PloS Computational Biology, 2018 Jan. Abstract: Targeting key regulators of the cancer stem cell phenotype to overcome their critical influence on tumor growth is a promising new strategy for cancer treatment. Here we present a modeling framework that operates at both the cellular and molecular levels, for investigating IL-6 mediated, cancer stem cell driven tumor growth and targeted treatment with anti-IL6 antibodies. Our immediate goal is to quantify the influence of IL-6 on cancer stem cell self-renewal and survival, and to characterize the subsequent impact on tumor growth dynamics. By including the molecular details of IL-6 binding, we are able to quantify the temporal changes in fractional occupancies of bound receptors and their influence on tumor volume. There is a strong correlation between the model output and experimental data for primary tumor xenografts. We also used the model to predict tumor response to administration of the humanized IL-6R monoclonal antibody, tocilizumab (TCZ), and we found that as little as 1mg/kg of TCZ administered weekly for 7 weeks is sufficient to result in tumor reduction and a sustained deceleration of tumor growth. Author Summary: A small population of cancer stem cells that share many of the biological characteristics of normal adult stem cells are believed to initiate and sustain tumor growth for a wide variety of malignancies. Growth and survival of these cancer stem cells is highly influenced by tumor micro-environmental factors and molecular signaling initiated by cytokines and growth factors. This work focuses on quantifying the influence of IL-6, a pleiotropic cytokine secreted by a variety of cell types, on cancer stem cell self-renewal and survival. We present a mathematical model for IL-6 mediated, cancer stem cell driven tumor growth that operates at the following levels: (1) the molecular level—capturing cell surface dynamics of receptor-ligand binding and receptor activation that lead to intra-cellular signal transduction cascades; and (2) the cellular level—describing tumor growth, cellular composition, and response to treatments targeted against IL-6. This model originates from BioModels Database: A Database of Annotated Published Models (http://www.ebi.ac.uk/biomodels/). It is copyright (c) 2005-2011 The BioModels.net Team. For more information see the terms of use. To cite BioModels Database, please use: Li C, Donizelli M, Rodriguez N, Dharuri H, Endler L, Chelliah V, Li L, He E, Henry A, Stefan MI, Snoep JL, Hucka M, Le Novère N, Laibe C (2010) BioModels Database: An enhanced, curated and annotated resource for published quantitative kinetic models. BMC Syst Biol., 4:92.

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Growth Signaling Autonomy in Circulating Tumor Cells Aids Metastatic Seeding

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