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- W2890875511 abstract "Immunotherapies such as checkpoint-blocking antibodies and adoptive cell transfer are emerging as treatments for a growing number of cancers. Despite clinical activity of immunotherapies across a range of cancer types, the majority of patients fail to respond to these treatments and resistance mechanisms remain incompletely defined. Responses to immunotherapy preferentially occur in tumors with a preexisting antitumor T-cell response that can most robustly be measured via expression of dendritic cell and CD8+ T cell-associated genes. The tumor subset with high expression of this signature has been described as the T cell-inflamed phenotype. Segregating tumors by expression of the inflamed signature may help predict immunotherapy responsiveness. Understanding mechanisms of resistance in both the T cell-inflamed and noninflamed subsets of tumors will be critical in overcoming treatment failure and expanding the proportion of patients responding to current immunotherapies. To maximize the impact of immunotherapy drug development, pretreatment stratification of targets associated with either the T cell-inflamed or noninflamed tumor microenvironment should be employed. Similarly, biomarkers predictive of responsiveness to specific immunomodulatory therapies should guide therapy selection in a growing landscape of treatment options. Combination strategies may ultimately require converting non-T cell-inflamed tumors into T cell-inflamed tumors as a means to sensitize tumors to therapies dependent on T-cell killing. Cancer Immunol Res; 6(9); 990-1000. ©2018 AACR." @default.
- W2890875511 created "2018-09-27" @default.
- W2890875511 creator A5016359394 @default.
- W2890875511 creator A5026264123 @default.
- W2890875511 creator A5063337705 @default.
- W2890875511 creator A5073289880 @default.
- W2890875511 date "2018-09-01" @default.
- W2890875511 modified "2023-10-12" @default.
- W2890875511 title "T Cell–Inflamed versus Non-T Cell–Inflamed Tumors: A Conceptual Framework for Cancer Immunotherapy Drug Development and Combination Therapy Selection" @default.
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- W2890875511 doi "https://doi.org/10.1158/2326-6066.cir-18-0277" @default.