Figure S4 . " width="100%" height="100%">
Journal: Cancer Cell
Article Title: Distinct spatiotemporal dynamics of CD8 + T cell-derived cytokines in the tumor microenvironment
doi: 10.1016/j.ccell.2023.12.010
Figure Lengend Snippet: Frequent IFNγ sensing in a syngeneic tumor model and relationship with reduced TGFβ sensing (A) Rag2 −/− mice were injected subcutaneously with a mixture of 10% OVA antigen expressing and 90% Ag − bystander NMM tumor cells, or with Ag − NMM tumor cells only, and, following tumor establishment, were treated with either PBS (control) or OT-1 CD8 + T cells, as indicated. Ag − bystander tumor cells were harvested for scRNA-seq analysis 44 h after treatment. (B) TNFα and IFNγ gene set scores, determined using the genes shown in a, for the T cell-exposed condition (green) and the two control conditions (T cell-exposed-Ag − bystander NMM tumor cells only tumors, and PBS treated tumors, shades of gray). Dots represent gene set scores of individual cells, violins represent densities of score distributions, white dots represent group medians. (C) Left panel: UMAP of NMM melanoma single cell data, as described in (A) and (B). Middle and right panels: a Milo model was fitted to the data to test for enrichment or depletion for any of the experimental conditions in neighborhoods of transcriptionally similar cells. Non-significantly imbalanced neighborhoods (Spatial FDR >0.05), as well as homogeneous neighborhoods, are colored white. (D) Left panel: heatmap of top 250 genes (rows) most strongly correlated (Spearman correlation) with enrichment for the T cell-exposed condition in cell state neighborhoods (columns) of transcriptionally similar cells. Depicted values are neighborhood averages. Neighborhoods are ordered according to compositional enrichment of cells from the T cell-exposed condition. Top panels show log fold change in differential abundance (logFC DA) for the indicated experimental condition relative to control condition. Right panel: heatmap showing bulk RNA-seq gene expression profiles of NMM cells exposed to indicated cytokines for the same genes as in the heatmap in the left panel, ordered identically. (E) As in (D), but for TGFβ responsive genes selected on bulk RNA-seq data. (F) Deconvolution mixing weights of neighborhoods in an independent bulk RNA-seq experiment. Neighborhoods ordered as in (D). Only the 6 out of 28 most highly selected reference profiles are shown, jointly comprising 94% of all assigned similarity. (G) Left: Increase in reconstruction error when the 17 reference profiles with TGFβ are omitted as compared to when all 28 profiles are included. Permutation testing was employed to test whether increase in reconstruction error could be explained by a lower number of reference profiles . Right: As left, but omitting the 17 reference profiles with IFNγ. (H) Model visualizing secondary effects of long range IFNγ sensing. In parallel to the mechanism in which long range IFNγ sensing leads to generation of, for instance, CXCL9/10/11 chemokine fields and subsequent increased immune cell infiltration, long range IFNγ sensing may result in secondary changes in the TME by decreasing TGFβ sensing. See also Figure S4 .
Article Snippet: Recombinant murine TGFβ , ebioscience , CAT#: 14-8342-80.
Techniques: Injection, Expressing, Control, RNA Sequencing, Gene Expression
Figure S4 . " width="250" height="auto" />
Table S2 ). (F) Representative histological images of picrosirius red staining in kidney of aged mice with and without Cmp60. (n = 5–6)/group. (G) Quantification of interstitial fibrosis determined by the percentage of positive picrosirius red staining/high power field, in mice treated with and without Cmpd60. Percentage of positive staining was assessed with ImageJ software. Data are expressed as mean ± SEM and the Mann Whitney test was used to determine statistical significance. ∗p < 0.05, (n = 5–6)/group. " width="250" height="auto" />
