Mass Cytometry and Topological Data Analysis Reveal Immune Parameters Associated with Complications after Allogeneic Stem Cell Transplantation

作者：Lakshmikanth Tadepally; Olin Axel; Chen Yang; Mikes Jaromir; Fredlund Erik; Remberger Mats; Omazic Brigitta; Brodin Petter

来源：Cell Reports, 2017, 20(9): 2238-2250.

DOI：10.1016/j.celrep.2017.08.021

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 graftversus- 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.

• 出版日期2017-8-29