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Updated: Oct 11, 2025
Generation of Orthotopic Pancreatic Tumors and Ex vivo Characterization of Tumor-Infiltrating T Cell Cytotoxicity
Published on: December 7, 2019
Laboratory biomarkers of an effective antitumor immune response. Clinical significance
A M Malkova1, V V Sharoyko1, N V Zhukova1
1Saint Petersburg State University, 7/9 Universitetskaya Emb., St Petersburg 199034, Russian Federation.
Abstract:
The modern checkpoint inhibitors block the programmed death-1 receptor and its ligand, cytotoxic T-lymphocyte-associated antigen 4 on tumor cells and lymphocytes, that induces cytotoxic reactions. Nowadays, there are no approved clinical and laboratory predictor markers of immune therapy efficacy, which would allow a more personalized approach to patient selection and treatment. The aim of this review is to analyze possible biomarkers of efficacy for treatment with checkpoint inhibitors according to the pathogenic mechanisms of drug action. The review revealed possible predictive biomarkers, that could be classified to 3 groups: biomarkers of high mutagenic potential of the tumor, biomarkers of high activity of adaptive immunity, biomarkers of low activity of the tumor microenvironment. The determination of the described markers before the start of therapy can be used to formulate a treatment regimen, in which the use of various immunomodulatory drugs, inhibitors of proinflammatory cytokines, angiogenic molecules, and probiotics can be considered.
Insights
Checkpoint inhibitors enhance anti-tumor immunity but lack predictive biomarkers. This review identifies potential biomarkers related to tumor mutation burden, adaptive immunity, and the tumor microenvironment to personalize immunotherapy.
Area of Science:
- Oncology
- Immunology
- Biomarker Discovery
Background:
- Checkpoint inhibitors targeting cytotoxic T-lymphocyte-associated antigen 4 (CTLA-4) and programmed death-1 (PD-1) enhance anti-tumor immune responses.
- Currently, no validated biomarkers exist to predict patient response to immune checkpoint inhibitor therapy, hindering personalized treatment strategies.
Purpose of the Study:
- To review and categorize potential predictive biomarkers for immune checkpoint inhibitor efficacy based on their mechanisms of action.
- To explore biomarkers that can guide personalized treatment regimens involving immunomodulatory drugs.
Main Methods:
- Literature review and analysis of pathogenic mechanisms of immune checkpoint inhibitors.
- Classification of potential biomarkers into three main groups: tumor mutagenicity, adaptive immunity, and tumor microenvironment activity.
Main Results:
- Identified three categories of predictive biomarkers: high tumor mutagenic potential, high adaptive immunity activity, and low tumor microenvironment activity.
- These biomarkers can inform treatment decisions and the selection of complementary therapies.
Conclusions:
- Biomarker determination prior to therapy can facilitate personalized treatment strategies for immune checkpoint inhibitors.
- Potential biomarkers offer a pathway to optimize patient selection and treatment regimens, potentially including immunomodulatory agents.
