Mass Cytometry and Topological Data Analysis Reveal Immune Parameters Associated with Complications after Allogeneic Stem Cell Transplantation
![Mass Cytometry and Topological Data Analysis Reveal Immune Parameters Associated with Complications after Allogeneic Stem Cell Transplantation](/image/eyJ1cmkiOiJodHRwOi8vc3RhY2thZGVtaWMuaGVyb2t1YXBwLmNvbS9pbWFnZT9pbWFnZV9pZD0xNzA2NSIsImZvcm1hdCI6IndlYnAiLCJxdWFsaXR5IjoxMDAsIm5vQ2FjaGUiOnRydWV9.webp)
Summary
Human immune systems are variable, and immune responses are often unpredictable. Systems-level analyses offer increased power to sort patients on the basis of coordinated changes across immune cells and proteins. Allogeneic stem cell transplantation is a well-established form of immunotherapy whereby a donor immune system induces a graft-versus-leukemia response. This fails when the donor immune system regenerates improperly, leaving the patient susceptible to infections and leukemia relapse. We present a systems-level analysis by mass cytometry and serum profiling in 26 patients sampled 1, 2, 3, 6, and 12 months after transplantation. Using a combination of machine learning and topological data analyses, we show that global immune signatures associated with clinical outcome can be revealed, even when patients are few and heterogeneous. This high-resolution systems immune monitoring approach holds the potential for improving the development and evaluation of immunotherapies in the future.
Publisher URL: http://www.cell.com/cell-reports/fulltext/S2211-1247(17)31113-0
DOI: 10.1016/j.celrep.2017.08.021
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