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Updated: Dec 25, 2025
Predictive Immune Modeling of Solid Tumors
Published on: February 25, 2020
Translational Biomarkers and Rationale Strategies to Overcome Resistance to Immune Checkpoint Inhibitors in Solid
Justin A Chen1, Weijie Ma1, Jianda Yuan2
1Division of Hematology/Oncology, Department of Internal Medicine, University of California Davis School of Medicine, University of California, Davis Comprehensive Cancer Center, 4501 X Street, Suite 3016, Sacramento, CA, 95817, USA.
Abstract:
Immune checkpoint inhibitors (ICIs) targeting the programed cell-death protein 1 (PD-1) or its ligand PD-L1 and cytotoxic T-lymphocyte antigen 4 (CTLA-4) pathways have improved the survival for patients with solid tumors. Unfortunately, durable clinical responses are seen in only 10-40% of patients at the cost of potential immune-related adverse events. In the tumor microenvironment (TME), tumor cells can influence the microenvironment by releasing extracellular signals and generating peripheral immune tolerance, while the immune cells can affect the initiation, growth, proliferation, and evolution of cancer cells. Currently, translational biomarkers that predict responses to ICIs include high PD-L1 tumor proportion score, defective DNA mismatch repair, high microsatellite instability, and possibly high tumor mutational burden. Characterization of immune cells in the TME, such as tumor-infiltrating lymphocytes, T-cell gene expression profile, T-cell receptor sequencing, and peripheral blood biomarkers are being explored as promising biomarkers. Recent neoadjuvant studies have integrated the real-time assessment of both molecular and immune biomarkers using the tissue and blood specimens simultaneously and longitudinally. This review summarizes the current knowledge and progress in developing translational biomarkers and rational combinational strategies to improve the efficacy of ICIs tailored to individual cancer patients.
Insights
Immune checkpoint inhibitors (ICIs) improve solid tumor patient survival but lack durable responses. This review explores biomarkers and combination strategies to enhance ICI efficacy for personalized cancer therapy.
Area of Science:
- Oncology
- Immunology
- Translational Medicine
Background:
- Immune checkpoint inhibitors (ICIs) targeting PD-1/PD-L1 and CTLA-4 pathways enhance survival in solid tumors.
- Durable responses to ICIs are limited (10-40%), with potential immune-related adverse events.
- Tumor cells and immune cells within the tumor microenvironment (TME) interact, influencing cancer progression and treatment response.
Purpose of the Study:
- To review current knowledge on translational biomarkers for predicting ICI response.
- To explore rational combinational strategies to improve ICI efficacy.
- To highlight advancements in tailoring ICIs to individual cancer patients.
Main Methods:
- Review of existing literature on ICI biomarkers and combination therapies.
- Analysis of current translational biomarkers (e.g., PD-L1, MSI, TMB).
- Exploration of emerging biomarkers (e.g., TME immune cell characterization, T-cell receptor sequencing).
Main Results:
- Established biomarkers include PD-L1 expression, mismatch repair deficiency, and microsatellite instability.
- Tumor-infiltrating lymphocytes and peripheral blood biomarkers show promise for predicting response.
- Neoadjuvant studies integrate real-time molecular and immune biomarker assessment.
Conclusions:
- Developing predictive biomarkers is crucial for optimizing ICI therapy.
- Rational combination strategies are needed to overcome resistance and improve outcomes.
- Personalized approaches integrating biomarker data are key to advancing cancer treatment.
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