已发表论文

揭示皮肤黑色素瘤信号通路的异质性:预后价值和免疫相互作用的见解

 

Authors Liu Y, Li C, Deng W 

Received 7 November 2024

Accepted for publication 1 January 2025

Published 8 January 2025 Volume 2025:18 Pages 47—59

DOI https://doi.org/10.2147/CCID.S500654

Checked for plagiarism Yes

Review by Single anonymous peer review

Peer reviewer comments 3

Editor who approved publication: Dr Jeffrey Weinberg

Yufang Liu,1,* Chunyan Li,2,* Weiwei Deng2 

1Department of Dermatology and Venereology, Fuyang People’s Hospital, Fuyang, Anhui, 236000, People’s Republic of China; 2Department of Dermatology and Venereology, Dermatology Hospital of Southern Medical University, Department of Dermatology, Guangzhou, People’s Republic of China

*These authors contributed equally to this work

Correspondence: Weiwei Deng, Email dengww@smu.edu.cn

Background: Signaling pathways play crucial roles in tumor cells. However, functional heterogeneity of signaling pathways in skin cutaneous melanoma (SKCM) has not been established.
Methods: Based on a recent computational pipeline, pathway activities between SKCM and normal samples were identified.
Results: The results showed that high activities in 12 pathways were associated with poor prognoses, while high activities in 17 pathways were associated with favorable prognoses. Interestingly, elevated metabolic pathway activity was unfavorable, whereas elevated immune activity was favorable for SKCM. Unfavorably elevated metabolic pathways strongly correlated with Wnt/beta-catenin signaling. Conversely, favorable pathways, such as glycosaminoglycan biosynthesis and keratan sulfate, were strongly correlated with anti-tumor pathways. Moreover, the activities of favorable pathways were strongly positively correlated with infiltrating CD8+ T cells, macrophages M1, immune score, and stromal score, all of which were favorable for SKCM.
Conclusion: Taken together, our study provides insights into the characteristics of several pathways in SKCM.

Keywords: skin cutaneous melanoma, pathway activity, immune infiltration, prognosis, bioinformatics, tumor microenvironment