Fig 2: PPAR?-Deficient T Cells Show Improved Antitumor Potential(A–C) Three-day activated WT and PPAR?-deficient T cells were used to determine (A) cell surface expression of stem cell antigen (Sca1), CD122, and CD127; (B) ECAR time course in response to glucose, oligomycin, and 2DG; and (C) WT and PPAR?-/- T cells were activated either in presence or absence orlistat (100 µM). OCR under basal condition and in response to indicated mitochondrial inhibitors was determined.(D) WT and PPAR?-/- T cells were activated either in presence or absence of orlistat (100 µM) and used to determine cell viability with 7AAD staining.(E) Bodipy conjugated FL C12 uptake; and expression of CD36 by flow cytometry in day 3 activated WT and PPAR?-/- T cells.(F) Day 3 activated WT and PPAR?-deficient T cells were cultured overnight ± oleate (30 µM), followed by 24 h of starvation in low glucose (2 mM) media, and then stained with Bodipy. The numerical values within the FACS overlay plots indicate MFI. Adjacent bar diagrams represent cumulative data from at least three repeat experiments.(G) C57BL/6 HLA-A2+ mice (n = 12 mice/group) were inoculated (s.c.) with 0.3 × 106 B16F10-A2+ melanoma cells for 9 days, after which mice either kept untreated or adoptively transferred with melanoma reactive 1 × 106 TIL1383I tyrosinase epitope-reactive TCR transduced T cells generated using splenocytes from WT or PPAR?creCD4flox mice. Tumor growth was measured using digital calipers twice weekly. Left: estimated growth curves for each experimental condition. Right: survival curve (p value WT versus PPAR?-/-: 2e–04). (A–G) Error bars represent mean ± SD. *p < 0.05, **p < 0.01.See also Figure S6.

Fig 3: Regulatory T Cells Utilize Lipids for Their Mitochondrial Metabolism under Hypoxia and Prefer Lipids for Metabolism within Glioma(A and B) Flow-cytometry-sorted and expanded HIF-1α WT or HIF-1α KO Tregs were placed under 1% O2 overnight before being adhered to microplates, and extracellular flux analysis was performed over time (A) and analyzed as bar graphs (B). Eto treatment (20 μm) was added immediately before assay to determine reliance on lipids for mitochondrial metabolism.(C–F) Wild-type C57/Bl6 mice were implanted with 4 × 105 GL-261 astrocytoma cells, and after 2 weeks of tumor growth, T cell expression of surface fatty acid transporters was analyzed via flow cytometry.(C) Percent palmitic acid uptake and MFI of conventional CD4+, CD8+, and Treg subsets.(D) Percent 2-NDBG and MFI of 2-NBDG conventional CD4+, CD8+, and Treg subsets.(E) Tumor interstitial fluid was obtained from either the tumor hemisphere or the non-tumor hemisphere of mice, and FFA content was measured via colorimetric readout.(F) Data show the expression of fatty acid transporters CD36, SLC27A1, and SLC27A4 across different T cell subsets in the brains, DLN, and spleens of tumor-bearing mice (left); representative flow cytometry plots are shown on the right.Statistics were calculated as percent positive population ± SEM. Data in (A) and (B) were analyzed using Wave software from Agilent. Statistics were calculated as percent positive population ± SEM, n = 5 per group; results are representative of three experiments in (A) and (B) and two experiments in (C)–(F). One-way ANOVA followed by Tukey’s post hoc analysis was used to calculate significance. *p < 0.05; **p < 0.01; ***p < 0.001; ns, not significant.See also Figure S4.

Fig 4: SphK1-/- T Cells Preferentially Depend on Oxidative Phosphorylation and Lipolysis for Energy Need(A) Three days TCR activated WT and SphK-/- T cells were used to determine ECAR time course in response to glucose, oligomycin, and 2DG.(B) OCR in presence or absence of etomoxir (200 µM) followed by the addition of various mitochondrial inhibitors as indicated in the figure. Graph on left represents time course, and bar diagram on right represents basal OCR values. 0.5 × 106 cells/well were used to perform the study.(C) mRNA from 3 days TCR-activated WT and SphK1-/- T cells were used to determine the expression of CPT1a using qPCR.(D and E) Three days activated WT and SphK1-/- T cells were used for (D) determining ATP levels and (E) Bodipy-conjugated FL C12 uptake (left panel), and cell surface expression of CD36 (right panel) by flow cytometry.(F) Three days TCR activated WT and SphK1-/- T cells were cultured overnight ± oleate (30 µM), followed by 24 h of starvation in low glucose (2 mM) media and then stained with Bodipy.(G) Activated WT and SphK1-/- T cells were used to determine the Tip47 expression by flow cytometry.(H) Activated WT and SphK1-/- T cells were used to determine the abundance of lipid signature molecules by mass spectroscopy.(I) WT and SphK1-/- T cells were activated either in presence or absence orlistat (100 µM), and cell viability was determined using 7AAD staining.(J) Cells in (I) were also used for determining IFN-? secretion by intracellular cytokine staining using flow cytometry.(K) OCR was measured using real-time flux analysis using Seahorse and with mitochondrial inhibitors. 0.4 × 106 cells/well were used to perform the study. The numerical values within the FACS overlay plots indicate MFI, and the bar diagrams represent cumulative data from at least three repeat experiments in (A)–(K).(L) C57/BL6 mice (n = 15 mice/group) were inoculated (s.c.) with 0.3 × 106 B16-F10 melanoma cells for 9 days, after which mice either kept untreated or adoptively transferred with 1 × 106 pMel and pMel-SphK-/- T cells cultured in presence or absence of orlistat (100 µM). Tumor growth was measured using digital calipers twice weekly. Upper panel: growth curves for each experimental condition. Lower panel: survival curve (p value; pMel versus pMel SphK1-/-: 2e–06, pMel SphK1-/- + Orlistat versus pMel SphK1-/-: 5e–07). *p < 0.05, **p < 0.01, ***p < 0.001. Error bars represent mean ± SD.See also Figure S4.

Fig 5: Identification of PPARγ-regulated genes in CTCF-deficient livers. (A) Pie charts showing the total numbers and genomic distributions of PPARγ ChIP-seq peaks identified from WT and cKO livers. (B) Histogram showing the average tag density of PPARγ ChIP-seq peaks. (C) Volcano plot showing significant changes in PPARγ enrichment between WT and cKO livers. The number of peaks that showed greater than 2.0-fold increases in WT (blue) or cKO (red) livers with an adjusted P value of less than .05 is indicated. (D) RNA-seq MA plot for genes (n = 5683) associated with PPARγ peaks (n = 12,283) gained in cKO livers. Mean abundance is plotted on the x-axis, and enrichment is plotted on the y-axis. The number of genes that showed more than 2.0-fold increases in WT (blue) or cKO (red) livers with an adjusted P value of less than .05 is indicated. (E) GSEA plot illustrating the enrichment of gene signatures for cellular lipid metabolic process. (F) Heatmap of RNA-seq signals for genes enriched in the cellular lipid metabolic pathway as shown in panel E. (G) Genomic snapshot of the CD36 locus. Densities of ChIP-seq reads for PPARγ, H3K27ac, H3K4me3, and H3K27me3 are shown. Densities of RNA-seq reads also are shown. Three known promoters (P1–P3) of CD36 are indicated by arrows. TPM, transcripts per million; UTR, untranslated region.