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Predictive Immune Modeling of Solid Tumors
Published on: February 25, 2020
Future prospects of immune checkpoint blockade in cancer: from response prediction to overcoming resistance
Young-Jun Park1,2, Da-Sol Kuen3,4, Yeonseok Chung5,6
1Laboratory of Immune Regulation, Research Institute of Pharmaceutical Sciences, College of Pharmacy, Seoul National University, Seoul, 08826, Republic of Korea. flavah00@snu.ac.kr.
Recent advances in the understating of tumor immunology suggest that cancer immunotherapy is an effective treatment against various types of cancer. In particular, the remarkable successes of immune checkpoint-blocking antibodies in clinical settings have encouraged researchers to focus on developing other various immunologic strategies to combat cancer. However, such immunotherapies still face difficulties in controlling malignancy in many patients due to the heterogeneity of both tumors and individual patients. Here, we discuss how tumor-intrinsic cues, tumor environmental metabolites, and host-derived immune cells might impact the efficacy and resistance often seen during immune checkpoint blockade treatment. Furthermore, we introduce biomarkers identified from human and mouse models that predict clinical benefits for immune checkpoint blockers in cancer.
Recent advances in the understating of tumor immunology suggest that cancer immunotherapy is an effective treatment against various types of cancer. In particular, the remarkable successes of immune checkpoint-blocking antibodies in clinical settings have encouraged researchers to focus on developing other various immunologic strategies to combat cancer. However, such immunotherapies still face difficulties in controlling malignancy in many patients due to the heterogeneity of both tumors and individual patients. Here, we discuss how tumor-intrinsic cues, tumor environmental metabolites, and host-derived immune cells might impact the efficacy and resistance often seen during immune checkpoint blockade treatment. Furthermore, we introduce biomarkers identified from human and mouse models that predict clinical benefits for immune checkpoint blockers in cancer.
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