Supplementary Materials

Supplementary Material for:

Clinical recovery from surgery correlates with single-cell immune signatures

Brice Gaudillière, Gabriela K. Fragiadakis, Robert V. Bruggner, Monica Nicolau, Rachel Finck, Martha Tingle, Julian Silva, Edward A. Ganio, Christine G. Yeh, William J. Maloney, James I. Huddleston, Stuart B. Goodman, Mark M. Davis, Sean C. Bendall, Wendy J. Fantl, Martin S. Angst,* Garry P. Nolan*

*Corresponding author. E-mail: ang{at}stanford.edu (M.S.A.); gnolan{at}stanford.edu (G.P.N.)

Published 24 September 2014, Sci. Transl. Med. 6, 255ra131 (2014)
DOI: 10.1126/scitranslmed.3009701

This PDF file includes:

  • Materials and Methods
  • Fig. S1. Assay performance and validation.
  • Fig. S2. Consort chart summarizes patient recruitment.
  • Fig. S3. Manual gating strategy.
  • Fig. S4. Changes in cell frequencies in serial samples from the six patients included in the pilot study.
  • Fig. S5. Annotation of cluster hierarchy plots based on surface marker expression.
  • Fig. S6. SAM analysis of cell frequency changes across clusters.
  • Fig. S7. Signaling responses over time in innate and adaptive immune compartments.
  • Fig. S8. Correlation heat maps and module derivation in CD14+ MCs.
  • Fig. S9. Immune feature correlations and identification of clusters A1, A2, and A3.
  • Table S1. Antibody panels used for mass cytometry analysis.
  • Table S2. SAM analysis of intracellular signaling responses over time.
  • Table S3. Immune features correlating with clinical parameters of surgical recovery.
  • Table S4. Immune feature correlations with clinical parameter of surgical recovery corrected for clinical covariates.

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