Research
Secretome Analysis of an Osteogenic Prostate Tumor Identifies Complex Signaling Networks Mediating Cross-talk of Cancer and Stromal Cells Within the Tumor Microenvironment*[S]

https://doi.org/10.1074/mcp.M114.039909Get rights and content
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A distinct feature of human prostate cancer (PCa) is the development of osteoblastic (bone-forming) bone metastases. Metastatic growth in the bone is supported by factors secreted by PCa cells that activate signaling networks in the tumor microenvironment that augment tumor growth. To better understand these signaling networks and identify potential targets for therapy of bone metastases, we characterized the secretome of a patient-derived xenograft, MDA-PCa-118b (PCa-118b), generated from osteoblastic bone lesion. PCa-118b induces osteoblastic tumors when implanted either in mouse femurs or subcutaneously. To study signaling molecules critical to these unique tumor/microenvironment-mediated events, we performed mass spectrometry on conditioned media of isolated PCa-118b tumor cells, and identified 26 secretory proteins, such as TGF-β2, GDF15, FGF3, FGF19, CXCL1, galectins, and β2-microglobulin, which represent both novel and previously published secreted proteins. RT-PCR using human versus mouse-specific primers showed that TGFβ2, GDF15, FGF3, FGF19, and CXCL1 were secreted from PCa-118b cells. TGFβ2, GDF15, FGF3, and FGF19 function as both autocrine and paracrine factors on tumor cells and stromal cells, that is, endothelial cells and osteoblasts. In contrast, CXCL1 functions as a paracrine factor through the CXCR2 receptor expressed on endothelial cells and osteoblasts. Thus, our study reveals a complex PCa bone metastasis secretome with paracrine and autocrine signaling functions that mediate cross-talk among multiple cell types within the tumor microenvironment.

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Author contributions: Y.L. and S.L. designed research; Y.L., M.S.G., and D.J. performed research; Y.L., M.S.G., D.J., J.G.C., C.L., L.Y., G.E.G., S.N.M., and S.L. analyzed data; Y.L. and S.L. wrote the paper.

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This work was supported by Cancer Prevention and Research Institute of Texas (CPRIT RP110327), National Institutes of Health Grant RO1 174798, P50-CA140388, US Department of Defense Grant PC093132, and an award from the Prostate Cancer Foundation, a Cancer Center Support grant 2P30CA016647 from the National Cancer Institute, and the European Union FP7-PEOPLE-2012-IAPP-proposal No. 324400 - GlycoMet. This research is also in part conducted using the Rhode Island NSF/EPSCoR Proteomics Shared Resource Facility, which is supported in part by the National Science Foundation EPSCoR Grant No. 1004057, National Institutes of Health Grant No. 1S10RR020923, a Rhode Island Science and Technology Advisory Council grant, and the Division of Biology and Medicine, Brown University.

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This article contains supplemental Figs. S1 to S8 and Tables S1 to S7.