Page 94 - EJMO-9-3

Eurasian Journal of Medicine

and Oncology

ORIGINAL RESEARCH ARTICLE
Development of a novel risk model for stratifying

skin cutaneous melanoma patients based on
prognostic senescence-related genes

Yiting Feng 1 , Lanlan Liu 2,3,4,5 * , Yunjin Xie 2,3,4,5 * , and Mingzhu Yin 2,3,4,5 *

1 Department of Dermatology, Hunan Engineering Research Center of Skin Health and Disease,
Hunan Key Laboratory of Skin Cancer and Psoriasis, Xiangya Hospital, Central South University,
Changsha, Hunan Province, China
2 Clinical Research Center, Medical Pathology Center, Cancer Early Detection and Treatment
Center, and Translational Medicine Research Center, Chongqing University Three Gorges Hospital,
Chongqing University, Chongqing, China
3 Chongqing Technical Innovation Center for Quality Evaluation and Identification of Authentic
Medicinal Herbs, Chongqing, China
4 Chongqing University Three Gorges Hospital and Academy for Advanced Interdisciplinary
Technology, CQU - Ferenc Krausz Nobel Laureate Scientific Workstation, Chongqing, China
5 School of Medicine, Chongqing University, Chongqing, China

*Corresponding authors: Abstract
Lanlan Liu
(liulanlan@cqu.edu.cn); Introduction: Skin cutaneous melanoma (SKCM) is a highly lethal skin carcinoma.
Yunjin Xie
(xieyunjin_2024@cqu.edu.cn); Cellular senescence has a dual effect on tumor progression.
Mingzhu Yin Objective: This study investigates whether senescence-related genes can guide
(yinmingzhu@cqu.edu.cn) patient stratification by examining their association with survival outcomes in SKCM.
Citation: Feng Y, Liu L, Xie Y, Methods: Univariate and multivariate Cox regression analyses were performed to identify
Yin M. Development of a novel risk prognostic senescence-related genes. Based on these genes, samples were classified into
model for stratifying skin cutaneous
melanoma patients based on two subtypes using consensus unsupervised clustering. Kaplan-Meier survival analysis
prognostic senescence-related was conducted, with statistical significance assessed via the log-rank test. Immune
genes. Eurasian J Med Oncol. infiltration patterns were assessed using CIBERSORT. Finally, a prognostic risk model was
2025;9(3):86-99.
doi: 10.36922/ejmo.8574 constructed using Lasso regression following by multivariate Cox regression.
Results: Based on the prognostic senescence-related genes, samples were classified
Received: January 17, 2025 into two subtypes with distinct survival outcomes and immune profiles. Cluster 2,
Revised: March 4, 2025 linked to improved survival and enriched in cytokine-cytokine receptor interactions,
Accepted: March 26, 2025 showed higher infiltration of activated natural killer (NK) cells, CD8+ T cells as well as
CD4+ memory T cells, along with enhanced immune pathway activation compared
Published online: April 9, 2025 to cluster 1. Subsequently, a risk model was constructed based on the identified
Copyright: © 2025 Author(s). key genes and validated using both internal and external datasets. Stratification of
This is an Open-Access article patients by the median risk score showed that the low-risk cohort had a significantly
distributed under the terms of the
Creative Commons Attribution better prognosis, with a favorable immune microenvironment enriched in CD8+ T
License, permitting distribution, cells, anti-tumor M1 macrophages, and activated NK cells.
and reproduction in any medium, Conclusion: Senescence-related gene expression effectively stratified SKCM patients
provided the original work is
properly cited. into subtypes with distinct survival outcomes and immune microenvironment
profiles, offering new insights for the development of personalized medicine.
Publisher’s Note: AccScience
Publishing remains neutral with
regard to jurisdictional claims in
published maps and institutional Keywords: Skin cutaneous melanoma; Cellular senescence; Immune microenvironment;
affiliations. Risk model; High-throughput RNA sequencing

Volume 9 Issue 3 (2025) 86 doi: 10.36922/ejmo.8574