Single-Cell Profiling Defines Transcriptomic Signatures Specific to Tumor-Reactive versus Virus-Responsive CD4+ T Cells

Abstract

Most current tumor immunotherapy strategies leverage cytotoxic CD8⁺ T cells. Despite evidence for clinical potential of CD4⁺ tumor-infiltrating lymphocytes (TILs), their functional diversity limits our ability to harness their activity. Here, we use single-cell mRNA sequencing to analyze the response of tumor-specific CD4⁺ TILs and draining lymph node (dLN) T cells. Computational approaches to characterize subpopulations identify TIL transcriptomic patterns strikingly distinct from acute and chronic anti-viral responses and dominated by diversity among T-bet-expressing T helper type 1 (Th1)-like cells. In contrast, the dLN response includes T follicular helper (Tfh) cells but lacks Th1 cells. We identify a type I interferon-driven signature in Th1-like TILs and show that it is found in human cancers, in which it is negatively associated with response to checkpoint therapy. Our study provides a proof-of-concept methodology to characterize tumor-specific CD4⁺ T cell effector programs. Targeting these programs should help improve immunotherapy strategies.

Keywords: CD4(+) T cells; Tumor-infiltrating lymphocytes; cancer immunotherapy; single-cell RNA-seq.

Figure 1.. Characterization of CD4⁺ TIL, dLN, and Arm Transcriptomes by scRNA-Seq

(A–D) TILs and dLN cells from wild-type (WT) mice at day 14 after MC38-GP injection analyzed by scRNA-seq and flow cytometry. (A) Heatmap shows row-standardized expression of selected genes across TIL and dLN clusters. Bar plot indicates the percentage of cells in each cluster relative to the total TIL or dLN cell number. (B) Flow cytometry contour plots of Foxp3 versus T-bet in CD44^hi GP66⁺ dLN cells (left) and in CD44^hiCD4⁺ splenocytes from tumor-free control mice (right). (C) Flow cytometry contour plots of Foxp3 versus T-bet in PD-1⁺ and GP66⁺ TILs (left) and in CD44^hi CD4⁺ splenocytes from tumor-free control mice (right). (B and C) Data representative from 18 tumor-bearing mice analyzed in four separate experiments. (D) t-SNE display of TILs and dLN cells, shaded gray by tissue origin (left) or color coded by main group (right, as defined in A). (E) t-SNE (TIL and dLN cell positioning as shown in B) display of normalized expression levels of selected genes. (F) Heatmap shows Pearson correlation between cluster fold change vectors (as defined in the text) across the two replicate experiments for TILs (left) and dLN cells (right). See also Figures S1 and S2 and Tables S1 and S6.

Figure 2.. Transcriptomic Patterns of TILs, dLN Cells, and Arm Cells

TILs, dLN cells, and Arm cells from replicate experiments I and II analyzed by scRNA-seq. Heatmap shows row-standardized expression of selected genes across clusters. Group II (purple) t5 separated into a distinct component from t3–4 (as defined in the text). Of note, high-level expression of T-bet and other genes in Arm cells (included in this dataset), reduces the Z score (row normalized) expression value for such genes in TILs or dLN cells, accounting for their apparent lower relative expression compared with that in Figures 1A and S2B. See also Figure S2 and Table S2.

Figure 3.. Th1-like Transcriptomic Patterns

(A) Heatmap defines meta-clusters based on Pearson correlation among TIL, dLN, and Arm cluster fold change vectors (as defined in the text) (left). Tables show tissue origin and cell-type color code per cluster (right). (B and C) Comparison of TIL Th1 and Isc (clusters t1–2 and t3–4, respectively, as shown in Figure 1A), as well as Arm Th1 (as shown in Figures 2 and S2A). (B) Contour plots of Th1 (orange) and Isc (blue) TIL distribution according to scRNA-seq-detected normalized expression of Irf7 versus Ifit3b (left) and Klrc1 versus Lag3 (right). (C) Heatmap shows row-standardized expression of differentially expressed genes across TIL group II Isc, TIL group I Th1, and Arm Th1. (D) (Left) Flow cytometry contour plots of NKG2A versus CD94 (top) or IRF7 (bottom) in Foxp3⁻GP66⁺ dLN, TIL, and Arm cells. (Right) Percentage of NKG2A⁺CD94⁺ cells (top) and IRF7^hi NKG2A⁻ cells (bottom) among Foxp3⁻GP66⁺ CD4⁺ T cells; each symbol represents an individual mouse. (E) Overlaid protein expression of T-bet in NKG2A⁺ and NKG2A⁻ Foxp3⁻GP66⁺ TILs (left). The graph on the right summarizes quantification (mean fluorescence intensity, MFI) of T-bet in each subset, expressed relative to naive CD4⁺ splenocytes from tumor-free control mice. Each symbol represents an individual mouse; lines indicate pairing. (F) Flow cytometry contour plots of T-bet versus IRF7 in Foxp3⁻GP66+ dLN, TILs, and Arm cells; data from naive CD4⁺ splenocytes from tumor-free control mice is shown as a control (right plot). (D–F) Each plot is representative from 10 tumor-bearing and 9 Arm-infected mice, analyzed in two separate experiments. Each symbol on summary graphs represents one mouse. (G) (Left) Overlaid protein expression of IFNγ in NKG2A⁺ versus NKG2A⁻ TILs and Arm cells. Data are shown for Foxp3⁻GP66+ cells (plain lines); expression on Foxp3⁺ cells is shown as a negative control (shaded gray). (Right) Graph shows the percentage of IFNγ⁺ cells out of NKG2A⁺ or NKG2A⁻ Foxp3⁻ TILs or of GP66⁺ Arm CD4⁺ T cells and summarizes a single experiment with 5 tumor-bearing and 3 Arm-infected mice. Data are representative of two such experiments, with 15 tumor-bearing and 5 Arm-infected mice. Each symbol on summary graphs represents one mouse. Two-tailed unpaired (D and G) or paired (E) t test; *p < 0.05, **p < 0.01, and ****p < 0.0001. See also Figure S3 and Table S2.

Figure 4.. Transcriptomic Continuum between TIL and dLN Tumor-Reactive Cells

(A) Violin plots of differentially expressed genes across TIL group I Th1 and dLN group IV Ccr7⁺ (clusters t1–2 and n5, respectively, as shown in Figure 1A), as well as all other TIL and dLN populations. Unpaired t-test; ***p < 0.001. (B) Heatmap shows row-standardized expression of differentially expressed genes across dLN Ccr7⁺ clusters (group IV n5–6) and other dLN clusters (Treg and Tfh clusters n1 and n7–8, respectively). (C) Flow cytometry contour plots of Cxcr5 versus Ccr7 in Foxp3⁻ dLN cells (top). Overlaid protein expression of Bcl6 and CD200 in Ccr7⁺ and Cxcr5⁺ dLN cells and naive CD4⁺ splenocytes from tumor-free control mice (bottom). Data are representative of 17 mice analyzed in three experiments. (D) Flow cytometry contour plots of Cxcr5 versus PD-1 in dLN and Arm cells. Data are representative of 10 mice analyzed in two experiments. (E) Contour plot of dLN (red, clusters n7–8) and Arm (blue) Tfh cell distribution according to scRNA-seq-detected normalized expression of Icos versus Maf (top).Overlaid protein expression of ICOS in dLN and Arm PD-1⁺Cxcr5⁺ (Tfh) cells and naive CD4⁺ splenocytes from tumor-free control mice (bottom). (F) Heatmap shows row-standardized expression of differentially expressed genes across TIL Isc and nRes clusters (as defined in the text, group II t3–4 and t5,respectively) and all other TIL clusters (Th1 and Treg clusters t1–2 and t6–7, respectively). (G) Percentage of IL7R⁺Foxp3⁻ cells out of total PD-1⁺ or GP66⁺ TILs. Nine mice analyzed in two experiments. (H) Trajectory analysis of PD-1⁺ TILs and GP66⁺ dLN cells, indicating individual cells’ assignment into a transcriptional continuum trajectory. nRes cluster (t5) is color coded orange in contrast to annotations in other figures. See also Figure S4 and Table S2.

Figure 5.. Dysfunction Transcriptomes of Th1, Isc, and Treg TILs

(A) Heatmap shows row-standardized expression of selected exhaustion genes across TIL, dLN, and Arm clusters from replicate experiments I and II. (B) Overlaid protein expression of PD-1 in GP66⁺ clone 13 (red trace) and GP66⁺ TILs (left) or dLN cells (right) (cyan trace). Gray-shaded histograms show PD-1 expression on CD44⁺CD4⁺ splenocytes from tumor-free control mice. (C) Flow cytometry contour plots of NKG2A versus CD94 (top) or IRF7 (bottom) in TILs and clone 13 Foxp3⁻GP66⁺ T cells. Graphs on the right summarize data from two experiments; each symbol represents one mouse. Two-tailed unpaired t test; ***p < 0.001 and ****p < 0.0001. (B and C) Data are from 10 mice of each condition, analyzed on two separate experiments. (D) Analysis of interleukin-27 (IL-27) signature genes overlapping with TIL subpopulation-characteristic genes. Heatmaps show Pearson correlation (left) and row-standardized expression of overlapping genes across TIL Th1, Treg, Isc, and nRes cells (clusters t1–2, t6–7, t3–4, and t5, respectively, as shown in Figure 1A) (right). See also Figure S5 and Tables S3 and S4.

Figure 6.. Correspondence to Human Data and Dysfunction Gene Signatures

(A) Analysis of human liver cancer TIL_HLC. Heatmap shows row-standardized expression of selected genes across TIL_HLC clusters. (B) Heatmap defines meta-clusters based on Pearson correlation between TIL_HLC and MC38-GP TIL clusters (top). Overlap of genes characteristic of human liver TIL Isc cluster with mouse TIL Isc gene signature (bottom). (C) Analysis of human melanoma TIL_Mel. Boxplots show the percentage of cells expressing selected IFN signaling-characteristic genes in CD4⁺CD3⁺ cells across responding and non-responding lesions. Unpaired Wilcoxon test; *p < 0.05, **p < 0.01, and ***p < 0.001. See also Figure S6 and Table S5.