Tumor-initiating cells with reprogramming plasticity or stem-progenitor cell properties (stemness) are thought to be essential for cancer development and metastatic regeneration in many cancers; however, elucidation of the underlying molecular network and pathways remains demanding. Combining machine learning and experimental investigation, here we report CD81, a tetraspanin transmembrane protein known to be enriched in extracellular vesicles (EVs), as a newly identified driver of breast cancer stemness and metastasis. Using protein structure modeling and interface prediction-guided mutagenesis, we demonstrate that membrane CD81 interacts with CD44 through their extracellular regions in promoting tumor cell cluster formation and lung metastasis of triple negative breast cancer (TNBC) in human and mouse models. In-depth global and phosphoproteomic analyses of tumor cells deficient with CD81 or CD44 unveils endocytosis-related pathway alterations, leading to further identification of a quality-keeping role of CD44 and CD81 in EV secretion as well as in EV-associated stemness-promoting function. CD81 is coexpressed along with CD44 in human circulating tumor cells (CTCs) and enriched in clustered CTCs that promote cancer stemness and metastasis, supporting the clinical significance of CD81 in association with patient outcomes. Our study highlights machine learning as a powerful tool in facilitating the molecular understanding of new molecular targets in regulating stemness and metastasis of TNBC.
|State||Published - 2022|
Bibliographical noteFunding Information:
We are grateful for the tremendous support by Northwestern University Core facilities, including but not limited to the CTC Core, the Center for Comparative Medicine, Flow Cytometry Core, Small Animal Imaging, Microscopy Imaging, NUSeq, Bioinformatics, Mouse Histology & Phenotyping Laboratory, and Pathology Core. We also thank Case Western Reserve University Mass Spectrometry Core and Cancer Center Small Animal Facilities for their support. This project has been partially supported by the Department of Defense grant W81XWH-16-1-0021 and W81XWH-20-1-0679 (H Liu), the NIH/NCI grants R01CA245699 (H Liu and EK Ramos); NIH/NIGMS R35GM124952 (Y Shen) and R01GM139858 (T. Shi); National Science Foundation CCF-1943008 (Y Shen); the Lynn Sage Cancer Research Foundation (X Liu, M Cristofanilli, and H Liu), Susan G Komen Foundation CCR18548501 (X Liu); American Cancer Society ACS127951-RSG-15-025-01-CSM (H Liu); Northwestern University start-up grant (H Liu), and NIH Fellowships T32 CA009560 (EK Ramos), T32 CA080621-15 and the Julius Kahn Fellowship (R Taftaf), and T32GM008061 (EJ Schuster). Portions of this research were conducted with the advanced computing resources provided by Texas A&M High Performance Research Computing.
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ASJC Scopus subject areas
- Neuroscience (all)
- Biochemistry, Genetics and Molecular Biology (all)
- Immunology and Microbiology (all)