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

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

BACKGROUND

Immunogenic cell death (ICD) is a type of regulated cell death that is capable of initiating an adaptive immune response. Induction of ICD may be a potential treatment strategy, as it has been demonstrated to activate the tumor-specific immune response.

AIMS

The biomarkers of ICD and their relationships with the tumor microenvironment, clinical features, and immunotherapy response are not fully understood in a clinical context. Therefore, we conducted pan-cancer analyses of ICD gene signatures across 33 cancer types from The Cancer Genome Atlas database.

METHODS AND RESULTS

We identified key genes that had strong relationships with survival and the tumor microenvironment, contributing to a better understanding of the role of ICD genes in cancer therapy. In addition, we predicted therapeutic agents that target ICD genes and explored the potential mechanisms by which gemcitabine induce ICD. Moreover, we developed an ICD score based on the ICD genes and found it to be associated with patient prognosis, clinical features, tumor microenvironment, radiotherapy access, and immunotherapy response. A high ICD score was linked to the immune-hot phenotype, while a low ICD score was linked to the immune-cold phenotype.

CONCLUSION

We uncovered the potential of ICD gene signatures as comprehensive biomarkers for ICD in pan-cancer. Our research provides novel insights into immuno-phenotypic assessment and cancer therapeutic strategies, which could help to broaden the application of immunotherapy to benefit more patients.

Identification of molecular subtypes and prognostic model to reveal immune infiltration and predict prognosis based on immunogenic cell death-related genes in lung adenocarcinoma

Immunogenic cell death (ICD) has been increasingly indicated to be related to caners. However, ICD's role in Lung adenocarcinoma (LUAD) is still not well investigated. Clinical data along with associated mRNA expression profiles from LUAD cases were collected in TCGA and GEO databases. 13 ICD-related genes were identified. Relations of ICD-related genes expression with prognosis of patients, tumor immune microenvironment (TIME) was analyzed. Then, candidate genes were identified and the prognostic signature were constructed. Afterwards, one nomogram incorporating those chosen clinical data together with risk scores were built. Finally, the effect of HSP90AA1, one gene of the prognostic signature, on LUAD cell were analyzed. Two clusters were identified, which were designated as the ICD-high or -low subtype according to ICD-related genes levels. ICD-high subgroup showed good prognosis, high immune cell infiltration degrees, and enhanced immune response signaling activity compared with ICD-low subtype. Moreover, we established and verified the risk signature based on ICD-related genes. High risk group predicted poor prognosis of LUAD independently and presented negative association with immune score and immune status. Furthermore, nomogram contributed to the accurate prediction of LUAD prognostic outcome. Finally, HSP90AA1 levels were remarkably elevated within tumor cells in comparison with healthy pulmonary epithelial cells. HSP90α, HSP90AA1 protein product, promoted growth, migration, and invasion of LUAD cells. Molecular subtypes and prognostic model were identified by incorporating ICD-related genes, and it was related to TIME and might be adopted for the accurate prediction of LUAD prognosis.