A recent study has identified key gene signatures that could help predict the efficacy of immune checkpoint blockade therapy in patients with metastatic melanoma. Melanoma, a highly aggressive form of skin cancer, often originates from abnormal melanocytes. While immune checkpoint blockade therapy has significantly improved survival rates, many patients do not respond effectively to the treatment, leading to disease progression.
Researchers analysed data from multiple sources, focusing on samples collected during immune checkpoint blockade treatment. Using single-sample gene set enrichment analysis (ssGSEA) and an elastic network algorithm, they calculated immunogenic cell death scores (ICDS) to assess the immune response in these patients. Among 18 immune-related gene signatures, 9 key signatures were identified that effectively predict a patient’s response to immune checkpoint blockade therapy.
The study found that patients with higher ICD scores had significantly better response rates to immune checkpoint blockade therapy and longer progression-free survival. With a predictive accuracy of around 80%, this new model offers potential for personalised treatment plans. The findings suggest that assessing ICD gene signatures in metastatic melanoma could improve treatment outcomes and guide clinical decisions for immunotherapy, marking a promising step towards more tailored approaches in cancer treatment.
Helena Bradbury, EMJ
Reference
Zeng H et al. Immunogenic cell death signatures from on-treatment tumor specimens predict immune checkpoint therapy response in metastatic melanoma. Sci Rep. 2024;14:22872.
