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Updated: Jan 3, 2026
Intramucosal Inoculation of Squamous Cell Carcinoma Cells in Mice for Tumor Immune Profiling and Treatment Response Assessment
Published on: April 22, 2019
Immunotherapy in head and neck cancer: The great challenge of patient selection
Martina Napolitano1, Francesca Matilde Schipilliti1, Lucia Trudu1
1Department of Oncology and Hematology, University Hospital of Modena, Via del Pozzo 71, 41124 Modena, Italy.
Abstract:
The development of immune checkpoint inhibitors (ICIs) revolutionized the therapeutic landscape in head and neck cancer. However, the majority of patients present primary resistance to ICIs and do not benefit from use of these agents, highlighting the need of developing predictive biomarkers to better determine who will benefit from treatment with ICIs. Patient's related clinical characteristics, disease related features, pathological and molecular factors, as well as emerging immune predictive biomarkers can be considered for the selection of those patients who would be the best candidate for immunotherapy. We examined these factors, emerging from the results of currently available studies in head and neck squamous cell carcinoma (HNSCC), in order to provide a useful tool which could assist the oncologist in their clinical practice.
Insights
Immune checkpoint inhibitors (ICIs) show promise in head and neck cancer but many patients are resistant. Identifying predictive biomarkers is crucial for selecting patients who will benefit from immunotherapy.
Area of Science:
- Oncology
- Immunotherapy
- Biomarker Discovery
Background:
- Immune checkpoint inhibitors (ICIs) have transformed head and neck cancer treatment.
- A significant portion of patients exhibit primary resistance to ICIs, limiting their effectiveness.
- Predictive biomarkers are essential for identifying patients likely to respond to immunotherapy.
Purpose of the Study:
- To review and synthesize factors that can predict response to ICIs in head and neck squamous cell carcinoma (HNSCC).
- To provide a practical tool for oncologists to select optimal candidates for immunotherapy.
Main Methods:
- Systematic review of existing studies on predictive factors in HNSCC.
- Analysis of clinical characteristics, disease features, pathological, molecular, and immune biomarkers.
Main Results:
- Multiple factors including clinical, pathological, molecular, and immune markers show potential for predicting ICI response.
- Integration of these factors may improve patient selection for immunotherapy.
Conclusions:
- A comprehensive approach considering various factors is needed to predict ICI efficacy in HNSCC.
- Further research and validation of predictive biomarkers will enhance personalized immunotherapy strategies.
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