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Predictive Immune Modeling of Solid Tumors
Published on: February 25, 2020
Validation of biomarkers to predict response to immunotherapy in cancer: Volume I - pre-analytical and analytical
Giuseppe V Masucci1, Alessandra Cesano2, Rachael Hawtin3
1Department of Oncology-Pathology, Karolinska Institutet, 171 76 Stockholm, Sweden.
Abstract:
Immunotherapies have emerged as one of the most promising approaches to treat patients with cancer. Recently, there have been many clinical successes using checkpoint receptor blockade, including T cell inhibitory receptors such as cytotoxic T-lymphocyte-associated antigen 4 (CTLA-4) and programmed cell death-1 (PD-1). Despite demonstrated successes in a variety of malignancies, responses only typically occur in a minority of patients in any given histology. Additionally, treatment is associated with inflammatory toxicity and high cost. Therefore, determining which patients would derive clinical benefit from immunotherapy is a compelling clinical question. Although numerous candidate biomarkers have been described, there are currently three FDA-approved assays based on PD-1 ligand expression (PD-L1) that have been clinically validated to identify patients who are more likely to benefit from a single-agent anti-PD-1/PD-L1 therapy. Because of the complexity of the immune response and tumor biology, it is unlikely that a single biomarker will be sufficient to predict clinical outcomes in response to immune-targeted therapy. Rather, the integration of multiple tumor and immune response parameters, such as protein expression, genomics, and transcriptomics, may be necessary for accurate prediction of clinical benefit. Before a candidate biomarker and/or new technology can be used in a clinical setting, several steps are necessary to demonstrate its clinical validity. Although regulatory guidelines provide general roadmaps for the validation process, their applicability to biomarkers in the cancer immunotherapy field is somewhat limited. Thus, Working Group 1 (WG1) of the Society for Immunotherapy of Cancer (SITC) Immune Biomarkers Task Force convened to address this need. In this two volume series, we discuss pre-analytical and analytical (Volume I) as well as clinical and regulatory (Volume II) aspects of the validation process as applied to predictive biomarkers for cancer immunotherapy. To illustrate the requirements for validation, we discuss examples of biomarker assays that have shown preliminary evidence of an association with clinical benefit from immunotherapeutic interventions. The scope includes only those assays and technologies that have established a certain level of validation for clinical use (fit-for-purpose). Recommendations to meet challenges and strategies to guide the choice of analytical and clinical validation design for specific assays are also provided.
Insights
Predicting cancer immunotherapy success requires more than single biomarkers. Integrating multiple data types like protein, genomics, and transcriptomics is crucial for identifying patients who will benefit from these promising treatments.
Area of Science:
- Oncology
- Immunology
- Biomarker Discovery
Background:
- Cancer immunotherapies, particularly checkpoint receptor blockade (e.g., CTLA-4, PD-1), show promise but benefit only a subset of patients.
- Current FDA-approved assays for PD-1 ligand (PD-L1) expression offer limited predictive power for immunotherapy response.
- Predicting clinical benefit is challenging due to the complexity of tumor biology and immune responses.
Purpose of the Study:
- To address the need for robust validation of predictive biomarkers for cancer immunotherapy.
- To discuss the pre-analytical, analytical, clinical, and regulatory aspects of biomarker validation.
- To provide recommendations and strategies for validating biomarkers in cancer immunotherapy.
Main Methods:
- Convened the Society for Immunotherapy of Cancer (SITC) Immune Biomarkers Task Force Working Group 1 (WG1).
- Reviewed and discussed the validation process for predictive biomarkers in cancer immunotherapy.
- Examined examples of biomarker assays with preliminary evidence of clinical utility.
Main Results:
- A single biomarker is unlikely to be sufficient for predicting immunotherapy outcomes.
- Integration of multiple parameters (protein, genomics, transcriptomics) is likely necessary for accurate prediction.
- The study outlines requirements for clinical validity of biomarker assays.
Conclusions:
- Comprehensive validation strategies are essential for implementing new biomarkers in cancer immunotherapy.
- The Society for Immunotherapy of Cancer (SITC) provides guidance on biomarker validation for clinical use.
- Future efforts should focus on multi-parameter approaches and rigorous validation to optimize patient selection for immunotherapy.

