Abstract P2-23-19: Interrogating multicellular signaling in breast cancer using a bio-orthogonal chemistry-based proteomics platform

Abstract

Abstract Tumors are multicellular ecosystems that communicate through the exchange of extracellular signaling molecules. In breast cancer, this multicellular communication can enable tumor cells to cooperate in a range of contexts, including tumor invasion and the outgrowth of distal metastases. Illuminating the mechanisms by which tumor cells communicate may reveal new therapies. To this end, three-dimensional tumor organoid models have emerged as versatile platforms for modeling multicellular behavior ex vivo. However, organoid culture typically requires the use of poorly defined, animal-derived extracellular matrices, such as Matrigel. These exogenous matrices contain thousands of proteins that dominate over and conceal cell-secreted factors in conventional proteomics approaches. Revealing low abundance cell-secreted factors from this complex exogenous background presents a formidable challenge. To surmount this challenge, we develop a new method to isolate the pericellular proteome in 3D organotypic culture models. This technology harnesses biorthogonal click chemistry to bypass exogenous factors, infiltrate intercellular spaces, and retrieve the endogenous intercellular proteome. This approach requires no genetic manipulation, requires only 1 million cells, and can be adapted to diverse organotypic models. These capabilities enable isolation of intercellular signaling factors in models that yield precious amounts of material and that can sustain only limited manipulation ex vivo, which we demonstrate using organoids established from patient-derived xenografts. To establish the generalizability of our approach, we apply this technology to a panel of breast cancer and small-cell lung cancer organoid models. Furthermore, we demonstrate that this method can be readily adapted to different extracellular matrix environments that are widely employed in organoid research, including basement membrane matrices and collagen gels. Taken together, our results establish this technology as a scalable and generalizable platform that may open opportunities for researchers investigating diverse questions in organoid models of cancer. Moving forward, we are leveraging these capabilities to investigate changes in the intercellular proteome that emerge after the acquisition of therapy resistance. We hope to uncover new mechanisms of collective signaling that may be targeted to overcome therapy resistance. Citation Format: Brad A. Krajina, Ami Yamamoto, Kevin J. Cheung, Samuel Madasu. Interrogating multicellular signaling in breast cancer using a bio-orthogonal chemistry-based proteomics platform [abstract]. In: Proceedings of the 2022 San Antonio Breast Cancer Symposium; 2022 Dec 6-10; San Antonio, TX. Philadelphia (PA): AACR; Cancer Res 2023;83(5 Suppl):Abstract nr P2-23-19.