Frontiers in Genetics (Jan 2023)

Melanoma molecular subtyping and scoring model construction based on ligand-receptor pairs

  • Zexu Lin,
  • Zexu Lin,
  • Xin Lin,
  • Yuming Sun,
  • Shaorong Lei,
  • Gengming Cai,
  • Zhexuan Li

DOI
https://doi.org/10.3389/fgene.2023.1098202
Journal volume & issue
Vol. 14

Abstract

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Melanoma is a malignancy of melanocytes, responsible for a high percentage of skin cancer mortality. Ligand-Receptor pairs, a type of cellular communication, are essential for tumor genesis, growth, metastasis, and prognosis. Yet, the role of Ligand-Receptor pairs in melanoma has not been fully elucidated. Our research focused on the function of Ligand-Receptor pairs in melanoma prognosis. We screened 131 melanoma prognosis corresponded ligand-receptor pairs by analyzing the TCGA data of melanoma and the 2293 LR pairs retrieved from the connectomeDB2020 database. And further developed subtypes of melanoma according to the expression of these ligand-receptor pairs by Consensus Clustering. Then we using lasso cox regression and stepwise multivariate regression analysis established a ligand-receptor pairs-based scoring model for the evaluation of melanoma prognosis. Our study demonstrated that the ligand-receptor pairs are vital to the molecular heterogeneity of melanoma, and characterized three different melanoma ligand-receptor pairs subtypes. Among them, the C3 subtype showed a better prognosis, while the C1 subtype exhibited a low prognosis state. And our analysis then found out that this could be related to the differed activation and inhabitation of the cell cycle and immune-related pathways. Using lasso cox regression and stepwise multivariate regression analysis, we further identified 9 key ligand-receptor pairs and established a scoring model that effectively correlated with the prognosis, immune pathways, and therapy of melanoma, showing that the LR.score model was a trustworthy and independent biomarker for melanoma prognosis evaluation. In sum, we found that ligand-receptor pairs are significantly associated with the prognosis and therapy of melanoma. And our ligand-receptor-based scoring model showed potential for the evaluation of melanoma prognosis and immune therapy outcome prediction, which is crucial to the survival for the patients.

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