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In eLife

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 co-expressed 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.

Ramos Erika K, Tsai Chia-Feng, Jia Yuzhi, Cao Yue, Manu Megan, Taftaf Rokana, Hoffmann Andrew D, El-Shennawy Lamiaa, Gritsenko Marina A, Adorno-Cruz Valery, Schuster Emma J, Scholten David, Patel Dhwani, Liu Xia, Patel Priyam, Wray Brian, Zhang Youbin, Zhang Shanshan, Moore Ronald J, Mathews Jeremy V, Schipma Matthew J, Liu Tao, Tokars Valerie L, Cristofanilli Massimo, Shi Tujin, Shen Yang, Dashzeveg Nurmaa K, Liu Huiping


cancer biology, computational biology, human, mouse, systems biology