A T cell resilience model associated with response to immunotherapy in multiple tumor types

Nat Med. 2022 Jul;28(7):1421-1431. doi: 10.1038/s41591-022-01799-y. | PubMed

Yu Zhang^1,2,3, Trang Vu¹, Douglas C Palmer^4,5, Rigel J Kishton^4,6, Lanqi Gong², Jiao Huang², Thanh Nguyen^7,8, Zuojia Chen⁹, Cari Smith¹⁰, Ferenc Livák¹¹, Rohit Paul¹², Chi-Ping Day¹³, Chuan Wu⁹, Glenn Merlino¹³, Kenneth Aldape⁷, Xin-Yuan Guan², Peng Jiang¹⁴

1. Cancer Data Science Laboratory, Center for Cancer Research, National Cancer Institute, National Institutes of Health, Bethesda, MD, USA.
2. Department of Clinical Oncology, The University of Hong Kong, Hong Kong, China.
3. Sun Yat-sen University Cancer Center, State Key Laboratory of Oncology in South China, Collaborative Innovation Center for Cancer Medicine, Guangzhou, China.
4. Surgery Branch, National Cancer Institute, National Institutes of Health, Bethesda, MD, USA.
5. AstraZeneca, Gaithersburg, MD, USA.
6. Lyell Immunopharma, South San Francisco, CA, USA.
7. Laboratory of Pathology, Center for Cancer Research, National Cancer Institute, National Institutes of Health, Bethesda, MD, USA.
8. Gaia Foods, Singapore, Singapore.
9. Experimental Immunology Branch, Center for Cancer Research, National Cancer Institute, National Institutes of Health, Bethesda, MD, USA.
10. Laboratory Animal Science Program, Leidos Biomedical Research Inc, Frederick, MD, USA.
11. Flow Cytometry Core, Center for Cancer Research, National Cancer Institute, National Institutes of Health, Bethesda, MD, USA.
12. Office of the Director, Center for Cancer Research, National Cancer Institute, National Institutes of Health, Bethesda, MD, USA.
13. Laboratory of Cancer Biology and Genetics, Center for Cancer Research, National Cancer Institute, National Institutes of Health, Bethesda, MD, USA.
14. Cancer Data Science Laboratory, Center for Cancer Research, National Cancer Institute, National Institutes of Health, Bethesda, MD, USA. peng.jiang@nih.gov.

Abstract

Despite breakthroughs in cancer immunotherapy, most tumor-reactive T cells cannot persist in solid tumors due to an immunosuppressive environment. We developed Tres (tumor-resilient T cell), a computational model utilizing single-cell transcriptomic data to identify signatures of T cells that are resilient to immunosuppressive signals, such as transforming growth factor-β1, tumor necrosis factor-related apoptosis-inducing ligand and prostaglandin E2. Tres reliably predicts clinical responses to immunotherapy in melanoma, lung cancer, triple-negative breast cancer and B cell malignancies using bulk T cell transcriptomic data from pre-treatment tumors from patients who received immune-checkpoint inhibitors (n = 38), infusion products for chimeric antigen receptor T cell therapies (n = 34) and pre-manufacture samples for chimeric antigen receptor T cell or tumor-infiltrating lymphocyte therapies (n = 84). Further, Tres identified FIBP, whose functions are largely unknown, as the top negative marker of tumor-resilient T cells across many solid tumor types. FIBP knockouts in murine and human donor CD8+ T cells significantly enhanced T cell-mediated cancer killing in in vitro co-cultures. Further, Fibp knockout in murine T cells potentiated the in vivo efficacy of adoptive cell transfer in the B16 tumor model. Fibp knockout T cells exhibit reduced cholesterol metabolism, which inhibits effector T cell function. These results demonstrate the utility of Tres in identifying biomarkers of T cell effectiveness and potential therapeutic targets for immunotherapies in solid tumors.

Presented By Yu Zhang