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Updated: Sep 6, 2025
Experimental Melanoma Immunotherapy Model Using Tumor Vaccination with a Hematopoietic Cytokine
Published on: February 24, 2023
Immune Cell Networks Uncover Candidate Biomarkers of Melanoma Immunotherapy Response
Duong H T Vo1,2, Gerard McGleave1,2, Ian M Overton1,2
1The Patrick G Johnston Centre for Cancer Research, Queen's University Belfast, 97 Lisburn Road, Belfast BT9 7AE, UK.
Abstract:
The therapeutic activation of antitumour immunity by immune checkpoint inhibitors (ICIs) is a significant advance in cancer medicine, not least due to the prospect of long-term remission. However, many patients are unresponsive to ICI therapy and may experience serious side effects; companion biomarkers are urgently needed to help inform ICI prescribing decisions. We present the IMMUNETS networks of gene coregulation in five key immune cell types and their application to interrogate control of nivolumab response in advanced melanoma cohorts. The results evidence a role for each of the IMMUNETS cell types in ICI response and in driving tumour clearance with independent cohorts from TCGA. As expected, 'immune hot' status, including T cell proliferation, correlates with response to first-line ICI therapy. Genes regulated in NK, dendritic, and B cells are the most prominent discriminators of nivolumab response in patients that had previously progressed on another ICI. Multivariate analysis controlling for tumour stage and age highlights CIITA and IKZF3 as candidate prognostic biomarkers. IMMUNETS provide a resource for network biology, enabling context-specific analysis of immune components in orthogonal datasets. Overall, our results illuminate the relationship between the tumour microenvironment and clinical trajectories, with potential implications for precision medicine.
Insights
Identifying gene networks in immune cells helps predict patient response to immune checkpoint inhibitors (ICIs). IMMUNETS analysis reveals key cell types and biomarkers, advancing precision medicine for cancer treatment.
Area of Science:
- Immunology
- Oncology
- Computational Biology
Background:
- Immune checkpoint inhibitors (ICIs) offer long-term remission for cancer patients but lack predictive biomarkers for non-responders.
- Identifying biomarkers is crucial for optimizing ICI therapy and minimizing adverse effects.
Purpose of the Study:
- To develop and apply the IMMUNETS gene coregulation networks to understand nivolumab response in advanced melanoma.
- To identify key immune cell types and gene expression patterns associated with ICI treatment outcomes.
Main Methods:
- Analysis of gene coregulation networks (IMMUNETS) across five immune cell types.
- Interrogation of nivolumab response in advanced melanoma patient cohorts, including TCGA.
- Multivariate analysis to identify prognostic biomarkers, controlling for clinical factors.
Main Results:
- IMMUNETS networks demonstrate the role of multiple immune cell types in ICI response and tumor clearance.
- 'Immune hot' status and T cell proliferation correlate with first-line ICI therapy response.
- Genes in NK, dendritic, and B cells significantly discriminate nivolumab response in pre-treated patients; CIITA and IKZF3 emerge as candidate biomarkers.
Conclusions:
- IMMUNETS provides a valuable resource for network biology and immune component analysis in cancer.
- The study illuminates the tumor microenvironment's impact on clinical outcomes, supporting precision medicine.
- Identified biomarkers like CIITA and IKZF3 may aid in guiding ICI prescribing decisions.
