AUTHOR=Kang Zhen , Sun Jiang-Bo , Lin Fei , Huang Xu-Yun , Huang Qi , Chen Dong-Ning , Zheng Qing-Shui , Xue Xue-Yi , Xu Ning , Wei Yong 

TITLE=Subtype and prognostic analysis of immunogenic cell death-related gene signature in prostate cancer

JOURNAL=Frontiers in Oncology

VOLUME=Volume 13 - 2023

YEAR=2023

URL=https://www.frontiersin.org/journals/oncology/articles/10.3389/fonc.2023.1160972

DOI=10.3389/fonc.2023.1160972

ISSN=2234-943X

ABSTRACT=Background: Immunogenic cell death (ICD) plays a vital role in tumor progression and immune response. However, the integrative role of ICD-related genes and subtype in the tumor microenvironment (TME) in prostate cancer (PCa) remains unknown.
Materials and Methods:The sample data were obtained from TCGA,GEO, and MSKCC prostate cancer-related databases. We firstly divided the sbutype based on ICD-genes from 901 PCa patients, and then identified the prognostic related genes（PRGs）between different ICD subtype. Subsequently, all the patients were randomly split into training/ test groups. We developed a risk signature in the training set by LASSO-cox regression. Following this, we verified this prognostic signature in both training- test- external test set. The relationships between the different subgroups and clinical pathological characteristics, immune infiltration characteristics, and mutation status of the TME were examined. Finally, the artificial neural network (ANN) and fundamental experiment study were constructed to verified the acurracy of prognostic signature.
Results: We identified two ICD clusters with immunologic features, three gene cluster composed with PRGs. Additionally,  we demonstrated that the risk signature can be used to evaluate tumor immune cell infiltration, prognostic status and immune checkpoint inhibitor.The low-risk group, which has a high overlap with group C of the gene cluster, is characterized by high ICD levels, immunocompetence, and favorable survival probability.  Furthermore, the tumor progression genes selected by the artificial neural network (ANN) also exhibit potential associations with risk signature genes.
Conclusions: This study identified individuals with high ICD levels in prostate cancer who may had more abundant immune infiltration, and revealed the potential effects of risk signature on the TME, immune checkpoint inhibitor and prognosis of PCa.