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Updated: Jul 31, 2025
Predictive Immune Modeling of Solid Tumors
Published on: February 25, 2020
[Advances in predictive biomarkers associated with immune checkpoint inhibitors for tumor therapy]
Rui Guo1, Xiaoning Li1, Mingxuan Hao1
1Innovation Center of Molecular Diagnostics, College of Life Science and Technology, Beijing University of Chemical Technology, Beijing 100029, China.
Abstract:
Malignant tumors are diseases that seriously threaten human health and social development. Traditional tumor therapies such as surgery, radiotherapy, chemotherapy and targeted therapy cannot fully meet the needs of clinical treatment, and emerging immunotherapy has become a research hotspot in the field of tumor treatment. Immune checkpoint inhibitors (ICIs) have been approved as a tumor immunotherapy method for the treatment of various tumors, such as lung cancer, liver cancer, stomach cancer and colorectal cancer, etc. However, during the clinical use of ICIs, only a small number of patients experienced durable responses, which also led to drug resistance and adverse reactions. Therefore, the identification and development of predictive biomarkers is crucial to improve the therapeutic efficacy of ICIs. The predictive biomarkers of tumor ICIs mainly include tumor biomarkers, tumor microenvironment biomarkers, circulation-related biomarkers, host environmental biomarkers and combinatorial biomarkers. They are of great significance for screening, individualized treatment and prognosis evaluation of tumor patients. This article reviews the advances of predictive markers for tumor ICIs therapy.
Insights
Predictive biomarkers are essential for improving immune checkpoint inhibitor (ICI) therapy effectiveness in cancer. This review explores various biomarkers to enhance patient selection and treatment outcomes for ICI immunotherapy.
Area of Science:
- Oncology
- Immunotherapy
- Biomarker Discovery
Background:
- Malignant tumors pose significant health challenges, with traditional therapies often insufficient.
- Immune checkpoint inhibitors (ICIs) represent a promising immunotherapy but exhibit limited response rates and resistance in many patients.
- Developing predictive biomarkers is critical to optimize ICI therapy efficacy.
Approach:
- This review synthesizes current research on predictive biomarkers for tumor immune checkpoint inhibitor therapy.
- It categorizes biomarkers into tumor-specific, tumor microenvironment, circulation-related, host environmental, and combinatorial types.
- The focus is on their role in patient screening, personalized treatment, and prognosis.
Key Points:
- Predictive biomarkers are crucial for identifying patients likely to respond to ICIs.
- Biomarker categories include tumor, microenvironment, circulation, host, and combinatorial markers.
- These markers aid in screening, individualized treatment strategies, and evaluating prognosis.
Conclusions:
- Advances in predictive biomarkers are vital for enhancing the therapeutic success of immune checkpoint inhibitors.
- Effective biomarker identification and development will improve patient outcomes and overcome treatment resistance.
- This review highlights the significance of diverse biomarkers in advancing personalized cancer immunotherapy.
