Extended Data Figure 1: TMP195 modulates CD11b⁺ cells in breast tumours.

a, Gating strategy for double-sorting tumour cell suspensions from Fig. 1b. Mononuclear cells gated on the basis of FSC-A versus SSC-A were sequentially gated to select single cells (FSC-H versus FSC-W then SSC-H versus SSC-W). Single cells were then gated to select live CD45⁺ (7-AAD versus CD45). Live CD45⁺ cells were then gated to select CD19⁻ cells (CD19 versus CD3). Live/CD45⁺/CD19⁻ cells were then gated to select either CD11b⁺ or CD3⁺ cells (CD11b versus CD3). Tumour suspensions were sorted on a BD Aria II into CD11b⁺ or CD3⁺ fractions. These fractions were concentrated by centrifugation and sorted through the same gating strategy a second time to increase the purity of each population. The purity of the double-sorted population was confirmed for each sample before RNA isolation. b, c, Representative purity checks of the double-sorted CD3⁺ (b) and CD11b⁺ (c) populations are shown. d, Mean versus expression value plots of Affymetrix transcriptional profiling data. All probe sets are shown, highlights apply only to probe sets with a δ-factor >1.5. e–j, Starting with the list of genes most affected by 5-day TMP195 treatment (δ-factor >1.5), we queried their biological processes in the PANTHER GO-Slim gene ontology database and compared that to the distribution of biological processes represented in the genome. e, The genes induced by TMP195 treatment had a significant over- or under-representation of the ontologies illustrated in the pie charts and embedded table of statistics. Unbiased analysis of TMP195-induced differential gene expression through GSEA of all probe sets revealed a significant bias (χ² P value <0.05) in the distribution of the expression values of five gene sets as highlighted on the volcano plots (y axis, Student’s t-test P value). f–j, Probe sets representing genes in both the δ-factor list we selected and the GSEA gene set are labelled with the gene symbol corresponding to that probe set.