Multiple cell-death patterns predict the prognosis and drug sensitivity of melanoma patients - Chen, Zewei; Zhang, Ruopeng; Zhao, Zhoukai; Zhao, Baiwei; Zhang, Feiyang; Chen, Guoming; Chen, Xiaojiang; Wei, Chengzhi; Lin, Jun; Lin, Feizhi; Zheng, Ziqi; Jiang, Kaiming; et al. (Frontiers in Pharmacology, 2024)
Background: Melanoma, a malignant tumor of the skin, presents challenges in its treatment process, involving various modalities such as surgery, chemotherapy and targeted therapy. However, there is a need for an ideal model to assess prognosis and drug sensitivity currently. Cell programmed death (PCD) modes play a crucial role in tumor progression and have the potential to serve as prognostic and drug sensitivity indicators for melanoma.We analyzed 13 PCD modes including apoptosis, necroptosis, ferroptosis, pyroptosis, netotic cell death, entotic cell death, lysosome-dependent cell death, parthanatos, autophagy-dependent cell death, oxeiptosis, disulfidptosis and alkaliptosis. These modes were used to construct a model. Incorporating genes related to these 13 PCD modes to establish cellular death index (CDI) and conducting prognosis analysis. Transcriptomic, genomic, and clinical data were collected from various cohorts including TCGA-SKCM, GSE19234, and GSE65904 to validate this model.Results: CDI consisting of 10 gene signatures was established using machine learning algorithms, and divided into two groups based on CDI values. The high CDI group exhibited relatively lower numbers of immune-infiltrating cells and showed resistance to commonly used drugs such as docetaxel and axitinib. Our validation results demonstrated good discrimination in PCA analysis between CDI groups, and melanoma patients with higher CDI values had worse postoperative prognoses (all p < 0.01).The CDI model, incorporating multiple PCD modes, accurately predicts the clinical prognosis and drug sensitivity of melanoma patients.