Establishment of skin cutaneous melanoma prognosis model based on vascular mimicry risk score

Author:

Wang Yubo12ORCID,Zou Linxuan3,Song Mingzhi3,Zong Junwei3,Wang Shouyu3,Meng Lei4,Jia Zhuqiang56,Zhao Lin7,Han Xin68,Lu Ming29

Affiliation:

1. Dalian Medical University, Dalian, China

2. Department of Trauma and Tissue Repair Surgery, Dalian Municipal Central Hospital, Dalian, China

3. Department of Orthopaedic Surgery, The First Affiliated Hospital of Dalian Medical University, Dalian, China

4. The First Affiliated Hospital of Nanhua Medical University, Hengyang, China

5. The First Affiliated Hospital of Dalian Medical University, Dalian, China

6. Naqu People’s Hospital, Tibet, China

7. Department of Quality Management, Dalian Municipal Central Hospital, Dalian, China

8. Department of Orthopaedic Surgery, The Second Affiliated Hospital of Dalian Medical University, Dalian, China

9. Department of Trauma and Tissue Repair Surgery, Dalian Municipal Central Hospital of Dalian Medical University, Dalian, China.

Abstract

Studies have indicated that Vascular mimicry (VM) could contribute to the unfavorable prognosis of skin cutaneous melanoma (SKCM). Thus, the objective of this study was to identify therapeutic targets associated with VM in SKCM and develop a novel prognostic model. Gene expression data from The Cancer Genome Atlas (TCGA) and Genotype-Tissue Expression (GTEx) were utilized to identify differentially expressed genes (DEGs). By intersecting these DEGs with VM genes, we acquired VM-related DEGs specific to SKCM, and then identified prognostic-related VM genes. A VM risk score system was established based on these prognosis-associated VM genes, and patients were then categorized into high- and low-score groups using the median score. Subsequently, differences in clinical characteristics, gene set enrichment analysis (GSEA), and other analyses were further presented between the 2 groups of patients. Finally, a novel prognostic model for SKCM was established using the VM score and clinical characteristics. 26 VM-related DEGs were identified in SKCM, among the identified DEGs associated with VM in SKCM, 5 genes were found to be prognostic-related. The VM risk score system, comprised of these genes, is an independent prognostic risk factor. There were significant differences between the 2 patient groups in terms of age, pathological stage, and T stage. VM risk scores are associated with epithelial biological processes, angiogenesis, regulation of the SKCM immune microenvironment, and sensitivity to targeted drugs. The novel prognostic model demonstrates excellent predictive ability. Our study identified VM-related prognostic markers and therapeutic targets for SKCM, providing novel insights for clinical diagnosis and treatment.

Publisher

Ovid Technologies (Wolters Kluwer Health)

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