Using single-cell RNAseq, Magen and Nie et al. compared LCMV-specific CD4+ T cells in tumors (TIL) or draining lymph nodes (dLN) of mice with MC38 tumors expressing LCMV antigen and in spleens of mice with acute or chronic LCMV infection. These populations showed distinct, heterogeneous transcriptome patterns. TIL and dLN profiles were dominated by Th1-like and T follicular helper cells, respectively. A type I IFN-driven signature shown for exhausted PD-1+ mouse Th1-like TILs (and not for chronic LCMV exhausted T cells) was also identified for CD4+ T cells infiltrating human tumors and negatively correlated with melanoma patient response to checkpoint blockade.
Contributed by Paula Hochman
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.
Author Info: (1) Laboratory of Immune Cell Biology, Center for Cancer Research, National Cancer Institute, NIH, Bethesda, MD, USA; Center for Bioinformatics and Computational Biology, Universit
Author Info: (1) Laboratory of Immune Cell Biology, Center for Cancer Research, National Cancer Institute, NIH, Bethesda, MD, USA; Center for Bioinformatics and Computational Biology, University of Maryland, College Park, MD, USA. (2) Laboratory of Immune Cell Biology, Center for Cancer Research, National Cancer Institute, NIH, Bethesda, MD, USA. (3) Laboratory of Immune Cell Biology, Center for Cancer Research, National Cancer Institute, NIH, Bethesda, MD, USA. (4) Metaorganism Immunology Section, Laboratory of Immune System Biology, National Institute of Allergy and Infectious Diseases, NIH, Bethesda, MD, USA. (5) Advanced Biomedical and Computational Science, Frederick National Laboratory for Cancer Research, Frederick, MD, USA. (6) NCI CCR Sequencing Facility, Frederick National Laboratory for Cancer Research, Frederick, MD, USA. (7) NCI CCR Sequencing Facility, Frederick National Laboratory for Cancer Research, Frederick, MD, USA. (8) Viral Immunology and Intravital Imaging Section, National Institute of Neurological Disorders and Stroke, NIH, Bethesda, MD, USA. (9) Metaorganism Immunology Section, Laboratory of Immune System Biology, National Institute of Allergy and Infectious Diseases, NIH, Bethesda, MD, USA. (10) Laboratory of Immune Cell Biology, Center for Cancer Research, National Cancer Institute, NIH, Bethesda, MD, USA. Electronic address: remy.bosselut@nih.gov.
