Genomic analysis of immunogenic cell death-related subtypes for predicting prognosis and immunotherapy outcomes in glioblastoma multiforme

Abstract

Immunogenic cell death (ICD), a unique form of cancer cell death, has therapeutic potential in anti-tumour immunotherapy. The aim of this study is to explore the predictive potential of ICD in the prognosis and immunotherapy outcomes of glioblastoma multiforme (GBM). RNA sequencing data and clinical information were downloaded from three databases. Unsupervised consistency clustering analysis was used to identify ICD-related clusters and gene clusters. Additionally, the ICD scores were determined using principal component analysis and the Boruta algorithm via dimensionality reduction techniques. Subsequently, three ICD-related clusters and three gene clusters with different prognoses were identified, with differences in specific tumour immune infiltration-related lymphocytes in these clusters. Moreover, the ICD score was well differentiated among patients with GBM, and the ICD score was considered an independent prognostic factor for patients with GBM. Furthermore, two datasets were used for the external validation of ICD scores as predictors of prognosis and immunotherapy outcomes. The validation analysis suggested that patients with high ICD scores had a worse prognosis. Additionally, a higher proportion of patients with high ICD scores were non-responsive to immunotherapy. Thus, the ICD score has the potential as a biomarker to predict the prognosis and immunotherapy outcomes of patients with GBM.

Pan‐cancer analyses of immunogenic cell death‐derived gene signatures: Potential biomarkers for prognosis and immunotherapy

“…Our study, compared to this research, conducted a more in‐depth analysis of patient survival, immune microenvironment, and clinical features based on the subtypes of the ICD score. In previous studies, the high‐ICD subtype, derived from ICD genes, has been considered a protective factor for prognosis in HNSCC, lung adenocarcinoma, and ESCA, but a risk factor in pancreatic cancer and glioblastoma multiforme 10–13,27 . However, our results showed that a high ICD score was a protective factor for ACC, SKCM, and SARC, but a risk factor for UVM and LAML.…”

“…In previous studies, the high-ICD subtype, derived from ICD genes, has been considered a protective factor for prognosis in HNSCC, lung adenocarcinoma, and ESCA, but a risk factor in pancreatic cancer and glioblastoma multiforme. [10][11][12][13]27 However, our results showed that a high ICD score was a protective factor for ACC, SKCM, and SARC, but a risk factor for UVM and LAML. The reason for differences in analysis results may be the method of consensus clustering used to distinguish ICD-associated subtypes.…”

“…Extensive literature reviews led to the identification of ICD‐related genes, with Abhishek et al compiling a comprehensive summary of ICD‐derived metagene signatures that demonstrated prognostic significance in patients suffering from lung, breast, or ovarian malignancies 9 . Building upon these metagene signatures, some studies identified ICD‐associated subtypes and validated that ICD‐related genes could predict survival and immunotherapy outcomes in head and neck squamous cell carcinoma (HNSCC), lung adenocarcinoma, glioblastoma multiforme and pancreatic cancer 10–13 . This collective evidence suggests that ICD‐derived metagene signatures may serve as an integrated and effective biomarker for ICD.…”

“…9 Building upon these metagene signatures, some studies identified ICD-associated subtypes and validated that ICD-related genes could predict survival and immunotherapy outcomes in head and neck squamous cell carcinoma (HNSCC), lung adenocarcinoma, glioblastoma multiforme and pancreatic cancer. [10][11][12][13] This collective evidence suggests that ICD-derived metagene signatures may serve as an integrated and effective biomarker for ICD.…”