Multiple cell-death patterns predict the prognosis and drug sensitivity of melanoma patients

Zewei Chen; Ruopeng Zhang; Zhoukai Zhao; Baiwei Zhao; Feiyang Zhang; Guoming Chen; Xiaojiang Chen; Chengzhi Wei; Jun Lin; Feizhi Lin; Ziqi Zheng; Kaiming Jiang; Runcong Nie; Yingbo Chen

doi:10.3389/fphar.2024.1295687

Multiple cell-death patterns predict the prognosis and drug sensitivity of melanoma patients

Front Pharmacol. 2024 Oct 8:15:1295687. doi: 10.3389/fphar.2024.1295687. eCollection 2024.

Authors

Zewei Chen^#^{1

2}, Ruopeng Zhang^#^{1

2}, Zhoukai Zhao^#^{1

2}, Baiwei Zhao^#^{1

2}, Feiyang Zhang^{1

2}, Guoming Chen^{1

2}, Xiaojiang Chen^{1

2}, Chengzhi Wei^{1

2}, Jun Lin^{1

2}, Feizhi Lin^{1

2}, Ziqi Zheng^{1

2}, Kaiming Jiang^{1

2}, Runcong Nie^{1

2}, Yingbo Chen^{1

2}

Affiliations

¹ State Key Laboratory of Oncology in South China, Collaborative Innovation Center for Cancer Medicine, Sun Yat-Sen University Cancer Center, Guangzhou, China.
² Department of Gastric Surgery and Melanoma Surgical Section, Sun Yat-Sen University Cancer Center, Guangzhou, China.

^# Contributed equally.

Abstract

Background: Melanoma, a malignant tumor of the skin, presents challenges in its treatment process involving modalities such as surgery, chemotherapy, and targeted therapy. However, there is a need for an ideal model to assess prognosis and drug sensitivity. Programmed cell death (PCD) modes play a crucial role in tumor progression and has the potential to serve as prognostic and drug sensitivity indicators for melanoma.

Methods: 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 that incorporated genes related to these 13 PCD modes to establish a cell death index (CDI) to conduct prognosis analysis. Transcriptomic, genomic, and clinical data were collected from cohorts including TCGA-SKCM, GSE19234, and GSE65904 to validate this model.

Results: A CDI consisting of ten 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).

Conclusion: The CDI model, incorporating multiple PCD modes, accurately predicts the clinical prognosis and drug sensitivity of melanoma patients.

Keywords: cell death index; drug sensitivity; melanoma; postoperative prediction model; programmed cell death.

Grants and funding

The authors declare that financial support was received for the research, authorship, and/or publication of this article. This work was supported by Guangzhou Science and Technology Plan Projects (202201010885, to RC.N), the National Natural Science Foundation of China (81772589, to RC.N), the Guangzhou Basic and Applied Basic Research Foundation (2114050000603, to YB.C; SL2024A04J01162, to RP.Z), and the Beijing Xisike Clinical Oncology Research Foundation (Y-tongshu2021/qn-0227 and Y-Young2022--0281, to RC.N).