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. 2020 Jun 26;4:PO.19.00350. doi: 10.1200/PO.19.00350

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© 2020 by American Society of Clinical Oncology

Creative Commons Attribution Non-Commercial No Derivatives 4.0 License: https://creativecommons.org/licenses/by-nc-nd/4.0/

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FIG 3. — Quantification of immune cell populations in the tumor environment of immune-cell rich patients. (A-B) CIBERSORT deconvolution was used to quantify relative fractions of immune cell populations in the tumor leukocyte compartment of immune-rich patients. For patients from (A) The Cancer Genome Atlas (TCGA) and (B) Molecular Taxonomy of Breast Cancer International Consortium (METABRIC) databases, 9 aggregate immune cell populations are listed on the x-axis, and the average fraction of each immune cell population for a certain subtype is quantified on the y-axis. Error bars represent standard error of the mean. Subtypes are designated by bar color. False discovery rate P_adj values are provided above each subtype comparison. (C) Quantitative immunofluorescence (QIF) signal was compared between estrogen receptor–positive breast cancer (ER-positive BC;,n = 53) and triple-negative BC (TNBC; n = 63) formalin-fixed paraffin-embedded tumor microarray tissues. Subtype is shown on the x-axis, and CD68 QIF signal in the total 4′,6-diamidino-2-phenylindole (DAPI) compartment is quantified on the y-axis. For (D) TCGA and (E) METABRIC patients, 22 immune cell populations derived by CIBERSORT are listed on the x-axis, and the average fraction of each immune cell population for a certain subtype is quantified on the y-axis. Error bars represent standard error of the mean. Subtypes are designated by bar color. False discovery rate P_adj values are provided for TCGA (ER-positive BCs, n = 119; TNBCs, n = 86) and METABRIC (ER-positive BCs, n = 225; TNBCs, n = 140) patients. NK, natural killer.