A T cell resilience model associated with response to immunotherapy in multiple tumor types.
A T cell resilience model associated with response to immunotherapy in multiple tumor types.
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一种与多种肿瘤类型对免疫疗法的反应相关的T细胞恢复力模型
DOI:
10.1038/s41591-022-01799-y
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发表时间:
2022-07
期刊:
影响因子:
82.9
通讯作者:
Jiang, Peng
中科院分区:
文献类型:
--
作者:
Zhang, Yu;Trang, Vu;Palmer, Douglas C.;Kishton, Rigel J.;Gong, Lanqi;Huang, Jiao;Nguyen, Thanh;Chen, Zuojia;Smith, Cari;Livak, Ferenc;Paul, Rohit;Day, Chi-Ping;Wu, Chuan;Merlino, Glenn;Aldape, Kenneth;Guan, Xin-yuan;Jiang, Peng
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, https://resilience.ccr.cancer.gov/), 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.
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影响因子:
6.2
作者:
Huang YF;Niu WB;Hu R;Wang LJ;Huang ZY;Ni SH;Wang MQ;Yang Y;Huang YS;Feng WJ;Xiao W;Zhu DJ;Xian SX;Lu L
通讯作者:
Lu L
影响因子:
82.9
作者:
Gattinoni L;Lugli E;Ji Y;Pos Z;Paulos CM;Quigley MF;Almeida JR;Gostick E;Yu Z;Carpenito C;Wang E;Douek DC;Price DA;June CH;Marincola FM;Roederer M;Restifo NP
通讯作者:
Restifo NP
影响因子:
64.5
作者:
Good CR;Aznar MA;Kuramitsu S;Samareh P;Agarwal S;Donahue G;Ishiyama K;Wellhausen N;Rennels AK;Ma Y;Tian L;Guedan S;Alexander KA;Zhang Z;Rommel PC;Singh N;Glastad KM;Richardson MW;Watanabe K;Tanyi JL;O'Hara MH;Ruella M;Lacey SF;Moon EK;Schuster SJ;Albelda SM;Lanier LL;Young RM;Berger SL;June CH
通讯作者:
June CH
影响因子:
64.8
作者:
Ghandi, Mahmoud;Huang, Franklin W.;Sellers, William R.
通讯作者:
Sellers, William R.
影响因子:
64.5
作者:
Dong, Matthew B.;Wang, Guangchuan;Chen, Sidi
通讯作者:
Chen, Sidi