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Updated: Dec 20, 2025

Predictive Immune Modeling of Solid Tumors
Published on: February 25, 2020
Biomarkers in Precision Cancer Immunotherapy: Promise and Challenges
William B McKean1, Justin C Moser2, David Rimm3
1Huntsman Cancer Institute, University of Utah, Salt Lake City, UT.
Abstract:
The rapid expansion of modern cancer immunotherapeutics has led to a dramatic improvement in patient survival and sustained remission for otherwise refractory malignancies. However, a significant limitation behind these current treatment modalities is an irregularity in clinical response, which is especially pronounced among checkpoint inhibition. This unpredictability leads to significant side effects, financial costs, and health care burden, with unsatisfactory clinical benefit in the majority of treated patients. Additionally, although ongoing studies and trials investigate the use of multiple biomarkers predictive of patient response or harm, none of these are comprehensive in predicting potential benefit. This unmet need for validated biomarkers is largely secondary to a prohibitive complexity within tumor parenchyma and microenvironment, dynamic clonal and proteomic changes to therapy, heterogenous host immune defects, and varied standardization among sample preparation and reporting. Herein, we discuss current advantages of predictive biomarkers, as well as limitations in their clinical use and application. We also review future directions, ideal characteristics, and trial design needed for proper precision immuno-oncology and biomarker development.
Insights
Cancer immunotherapies show promise, but unpredictable responses limit effectiveness. Developing comprehensive biomarkers is crucial for precision oncology and improving patient outcomes.
Area of Science:
- Oncology
- Immunology
- Biomarker Discovery
Background:
- Modern cancer immunotherapeutics significantly improve survival for refractory malignancies.
- Checkpoint inhibition therapies exhibit unpredictable clinical responses, leading to side effects and limited benefit.
Purpose of the Study:
- To discuss the advantages and limitations of current predictive biomarkers in cancer immunotherapy.
- To review future directions and ideal characteristics for precision immuno-oncology biomarker development.
Main Methods:
- Review of current literature on predictive biomarkers for cancer immunotherapy.
- Analysis of challenges in biomarker validation due to tumor and host complexities.
- Discussion of ideal trial designs for biomarker development.
Main Results:
- Current biomarkers are not comprehensive in predicting patient response to immunotherapy.
- Tumor microenvironment complexity, dynamic clonal changes, and standardization issues hinder biomarker validation.
Conclusions:
- There is a critical unmet need for validated biomarkers to guide precision immuno-oncology.
- Future biomarker development requires addressing biological complexities and standardizing methodologies.
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