Machine learning-assisted elucidation of CD81–CD44 interactions in promoting cancer stemness and extracellular vesicle integrity

Abstract

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.

Document Details

Document Type
Pub Defense Publication
Publication Date
Oct 04, 2022
Source ID
10.7554/elife.82669

Entities

People

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

Organizations

  • American Cancer Society
  • National Cancer Institute
  • National Institute of General Medical Sciences
  • National Science Foundation
  • Northwestern University
  • Pacific Northwest National Laboratory
  • Susan G. Komen for the Cure
  • Texas A&M University
  • United States Department of Defense
  • University of Kentucky

Tags

Fields of Study

  • Biology

Readers

  • Materials Science and Engineering.
  • Oncology (Cancer Research).

Technology Areas

  • AI & ML