Signatures of T cell dysfunction and exclusion predict cancer immunotherapy response
By Peng Jiang, Shengqing Gu, D. Pan, Jingxin Fu, Avinash Sahu, Xihao Hu, Ziyi Li, Nicole Traugh, Xia Bu, Bo Li and 5 more. Nature Medicine, 2018
4,258 citations recorded by the source corpus.
Cancer treatment by immune checkpoint blockade (ICB) can bring long-lasting clinical benefits, but only a fraction of patients respond to treatment. To predict ICB response, we developed TIDE, a computational method to model two primary mechanisms of tumor immune evasion: the induction of T cell dysfunction in tumors with high infiltration of cytotoxic T lymphocytes (CTL) and the prevention of T cell infiltration in tumors with low CTL level. We identified signatures of T cell dysfunction from large tumor cohorts by testing how the expression of each gene in tumors interacts with the CTL infiltration level to influence patient survival. We also modeled factors that exclude T cell infiltration into tumors using expression signatures from immunosuppressive cells. Using this framework and pre-treatment RNA-Seq or NanoString tumor expression profiles, TIDE predicted the outcome of melanoma patients treated with first-line anti-PD1 or anti-CTLA4 more accurately than other biomarkers such as PD-L1 level and mutation load. TIDE also revealed new candidate ICB resistance regulators, such as SERPINB9, demonstrating utility for immunotherapy research. An algorithm-selected gene signature focused on tumor immune evasion and suppression predicts response to immune checkpoint blockade in melanoma, exceeding the accuracy of current clinical biomarkers.
Subfields: Cancer Research, Oncology, Pulmonary and Respiratory Medicine
View Paper: https://www.semanticscholar.org/paper/b9c77a9b22ea6faa2bf1a732de1d84ca39addc77
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In Oncology
Citations in the corpus
- Regulated cell death (RCD) in cancer: key pathways and targeted therapies (2022, background): “At present, immune checkpoint inhibitors (ICI) have broad application prospects in clinical tumor treatment, but relevant data show that only 1/3 of patients respond to ICI.(356) There is a synergistic effect between cell focal death and ICI.”
- Advances in immunotherapy for hepatocellular carcinoma (2021, background): “I.M. receives funding from MINECO SAF2014-52361-R and SAF 2017- 83267-C2-1R; Worldwide Cancer Research Grant (15-1146); the Asociacion Española Contra el Cancer (AECC) Foundation under grant GCB15152947MELE; and the European Union’s Horizon 2020 Program (grant agreement no. 635122 PROCROP).”
- CD8+ cytotoxic T lymphocytes in cancer immunotherapy: A review (2018, background): “TGF‐β mediates an anti‐inflammatory milieu within the stroma of tumor for immunosuppressive purposes (Zhao et al., 2018) and resistance of cancer cells to immunotherapeutic procedures (Jiang et al., 2018).”
- Development of tumor mutation burden as an immunotherapy biomarker: utility for the oncology clinic (2018, background): “The T-cell-inflamed gene expression profile (GEP) [26], immune gene expression signatures [27, 28], as well as description of the microbiome [29–31] also represent emerging predictive biomarkers.”
- TIMER2.0 for analysis of tumor-infiltrating immune cells (2020, background): “Gene expression-based approaches have been developed to predict survival and therapy response (32,34,35).”
- Integrative molecular and clinical modeling of clinical outcomes to PD-1 blockade in metastatic melanoma patients (2019, neutral): “A tumor-intrinsic resistance program signature 42 , signatures of T-cell dysfunction and exclusion 37 , and comparative immune checkpoint gene expression 34 were distinct from the immune cluster.”