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Updated: Jan 25, 2026

Predictive Immune Modeling of Solid Tumors
Published on: February 25, 2020
Research progress and clinical application of predictive biomarker for immune checkpoint inhibitors
Ke Ma1, Qingqing Jin1, Miao Wang1
1a Department of Pharmacology , School of Life Science and Biopharmaceutics, Shenyang Pharmaceutical University , Shenyang , China.
Introduction:
Immune checkpoint inhibitors (ICIs) have emerged as epochal milestones in the field of anti-cancer immunotherapy. With promising clinical effectiveness, ICIs can significantly prolong the overall survival of patients with advanced cancer of different types. Although their remarkable effectiveness has been demonstrated in clinical application, ICIs display limitations in terms of unique response patterns. Only a subset of patients exhibits objective responses, while others show rapid disease progression. Considering that there is a fair representation of both subsets of patients (responders and non-responders), clinicians ought to effectively stratify patients who will potentially benefit from ICI therapy, and optimize a strategy for patient selection. Areas covered: In this review, the authors have summarized several key factors involved in the biomarker development of ICI therapy, such as neoantigen production and presentation, the tumor microenvironment, and alternation in specific gene signaling pathways. Expert opinion: Considering the extreme complexity of the immune system, a single biomarker may fail to appropriately stratify patients for ICI therapy. Therefore, future biomarker research should focus on designing an integrated biomarker system that will successfully guide combination therapies to overcome resistance to immunotherapy.
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