Related Experiment Video
Updated: Jun 24, 2025
Predictive Immune Modeling of Solid Tumors
Published on: February 25, 2020
Defining clinically useful biomarkers of immune checkpoint inhibitors in solid tumours
Ashley M Holder1, Aikaterini Dedeilia2, Kailan Sierra-Davidson2
1Department of Surgical Oncology, University of Texas MD Anderson Cancer Center, Houston, TX, USA.
Abstract:
Although more than a decade has passed since the approval of immune checkpoint inhibitors (ICIs) for the treatment of melanoma and non-small-cell lung, breast and gastrointestinal cancers, many patients still show limited response. US Food and Drug Administration (FDA)-approved biomarkers include programmed cell death 1 ligand 1 (PDL1) expression, microsatellite status (that is, microsatellite instability-high (MSI-H)) and tumour mutational burden (TMB), but these have limited utility and/or lack standardized testing approaches for pan-cancer applications. Tissue-based analytes (such as tumour gene signatures, tumour antigen presentation or tumour microenvironment profiles) show a correlation with immune response, but equally, these demonstrate limited efficacy, as they represent a single time point and a single spatial assessment. Patient heterogeneity as well as inter- and intra-tumoural differences across different tissue sites and time points represent substantial challenges for static biomarkers. However, dynamic biomarkers such as longitudinal biopsies or novel, less-invasive markers such as blood-based biomarkers, radiomics and the gut microbiome show increasing potential for the dynamic identification of ICI response, and patient-tailored predictors identified through neoadjuvant trials or novel ex vivo tumour models can help to personalize treatment. In this Perspective, we critically assess the multiple new static, dynamic and patient-specific biomarkers, highlight the newest consortia and trial efforts, and provide recommendations for future clinical trials to make meaningful steps forwards in the field.
Insights
Immune checkpoint inhibitors (ICIs) show limited response in many patients. New dynamic and patient-specific biomarkers, including blood-based and microbiome markers, show promise for personalizing cancer treatment and improving outcomes.
Area of Science:
- Oncology
- Immunotherapy
- Biomarker Discovery
Background:
- Immune checkpoint inhibitors (ICIs) have been approved for over a decade for various cancers, yet many patients exhibit limited response.
- Current FDA-approved biomarkers like PD-L1, MSI-H, and TMB have limitations in utility and standardization for pan-cancer application.
- Static, tissue-based biomarkers offer only a single snapshot and struggle with patient and tumor heterogeneity.
Purpose of the Study:
- To critically assess existing and emerging biomarkers for predicting immune checkpoint inhibitor (ICI) response.
- To highlight current consortia and clinical trial efforts in biomarker development.
- To provide recommendations for future clinical trials to advance personalized cancer therapy.
Main Methods:
- Review and critical assessment of static, dynamic, and patient-specific biomarkers.
- Analysis of tissue-based analytes, dynamic markers (longitudinal biopsies, blood-based biomarkers, radiomics, gut microbiome), and patient-tailored predictors.
- Evaluation of consortia and trial efforts in the field.
Main Results:
- Existing biomarkers (PD-L1, MSI-H, TMB) have limited predictive value and standardization.
- Tissue-based biomarkers are limited by single time-point and spatial assessments.
- Dynamic biomarkers (blood-based, microbiome, radiomics) and patient-specific predictors show significant potential for personalized ICI treatment.
Conclusions:
- There is a critical need for improved biomarkers to predict ICI response due to limited efficacy of current methods.
- Dynamic and patient-specific biomarkers offer a promising avenue for overcoming the challenges posed by tumor heterogeneity and patient variability.
- Future clinical trials should focus on integrating novel biomarkers to personalize cancer immunotherapy and improve patient outcomes.
