Ex Vivo Model of Breast Cancer Cell Invasion in Live Lymph Node Tissue.

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Tác giả: Abhinav Arneja, Alexander G Ball, Katerina Morgaenko, Jennifer M Munson, Rebecca R Pompano, Audrey M Putelo, Melanie R Rutkowski

Ngôn ngữ: eng

Ký hiệu phân loại: 153.853 Brainwashing

Thông tin xuất bản: United States : ACS pharmacology & translational science , 2025

Mô tả vật lý:

Bộ sưu tập: NCBI

ID: 724708

Lymph nodes (LNs) are common sites of metastatic invasion in breast cancer, often preceding spread to distant organs and serving as key indicators of clinical disease progression. However, the mechanisms of cancer cell invasion into LNs are not well understood. Existing in vivo models struggle to isolate the specific impacts of the tumor-draining lymph node (TDLN) milieu on cancer cell invasion due to the coevolving relationship between TDLNs and the upstream tumor. To address these limitations, we used live ex vivo LN tissue slices with intact chemotactic function to model cancer cell spread within a spatially organized microenvironment. After showing that BRPKp110 breast cancer cells were chemoattracted to factors secreted by naïve LN tissue in a 3D migration assay, we demonstrated that ex vivo LN slices could support cancer cell seeding, invasion, and spread. This novel approach revealed dynamic, preferential cancer cell invasion within specific anatomical regions of LNs, particularly the subcapsular sinus (SCS) and cortex, as well as chemokine-rich domains of immobilized CXCL13 and CCL1. While CXCR5 was necessary for a portion of BRPKp110 invasion into naïve LNs, disruption of CXCR5/CXCL13 signaling alone was insufficient to prevent invasion toward CXCL13-rich domains. Finally, we extended this system to premetastatic TDLNs, where the ex vivo model predicted a lower invasion of cancer cells that was not due to diminished chemokine secretion. In summary, this innovative ex vivo model of cancer cell spread in live LN slices provides a platform to investigate cancer invasion within the intricate tissue microenvironment, supporting time-course analysis and parallel read-outs. We anticipate that this system will enable further research into cancer-immune interactions and allow for isolation of specific factors that make TDLNs resistant to cancer cell invasion, which is challenging to dissect in vivo.
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