Bioinformatics data combined with single-cell analysis reveals patterns of immunoinflammatory infiltration and cell death in melanoma.

Int Immunopharmacol

Department of Dermatology, The Affiliated Hospital of Southwest Medical University, Southwest Medical University, Luzhou, China; Department of Dermatology, Sichuan Provincial People's Hospital, School of medicine, University of Electronic Science and Technology of China, Chengdu, China. Electronic address:

Published: December 2024

AI Article Synopsis

  • Melanoma is a common skin cancer, but its molecular mechanisms are not well understood, prompting research into its immunological and cellular dynamics using advanced analytics.
  • The study utilized gene databases and single-cell analysis to identify 20 critical hub genes related to melanoma, revealing strong connections to immune and inflammatory responses.
  • Key findings indicated significant infiltration of various immune cells in melanoma patients, with ferroptosis and specific signaling pathways playing crucial roles in disease progression.

Article Abstract

Backgruond: Melanoma is a common cancer in dermatology, but its molecular mechanisms remain poorly explained.

Aim: Utilizing single-cell analytics and bioinformatics, the work sought to discover the immunological infiltration and cellular molecular mechanisms of melanoma.

Methods: Melanoma genes databases were downloaded from GeneCards, and gene expression profiles were chosen from the Gene Expression Omnibus (GSE244889). Establishing and analyzing protein-protein interaction networks for functional enrichment made use of the Kyoto Encyclopedia of Genes and Genomes (KEGG) and Gene Ontology (GO) databases. The process assesses the immunological cell infiltration variations between normal and malignant samples by Immune Cell AI software program. Different cell type differences were clarified by cell quality control, filtration, removal of batch effects and cell clustering analysis using single cell analysis techniques.

Results: Using a variety of machine learning techniques, 20 differentially expressed hub genes were found; among these, TP53, HSP90AB1, HSPA4, RHOA, CCND1, CYCS, PPARG, NFKBIA, CAV1, ANXA5, ENO1, ITGAM, YWHAZ, RELA, SOD1, and VDAC1 were found to be significantly significant. The results of enrichment analysis demonstrated that immune response and inflammatory response were strongly associated with melanoma. Animal mitophagy, ferroptosis, the PI3K-Akt signaling pathway, and the HIF-1 signaling pathway were the primary signaling pathways implicated. Cells of immunity, T-cells, lymphocytes, B-cells, NK-cells, monocytes, and macrophages were shown to be significantly infiltrated in melanoma patients, according to analysis. Single cell analysis also demonstrated that ferroptosis is a significant mechanism of cell death that contributes to the advancement of melanoma and that macrophages are important in the disease.

Conclusion: In summary, different immune cell infiltrations-particularly macrophages-have a significant impact on the onset and course of melanoma, and our findings may help direct future investigations into melanoma macrophages.

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Source
http://dx.doi.org/10.1016/j.intimp.2024.113347DOI Listing

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