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Analysis of Melanoma Gene Expression Signatures at the Single-Cell Level Uncovers 45-Gene Signature Related to Prognosis

Since the current melanoma clinicopathological staging system remains restricted to predicting survival outcomes, establishing precise prognostic targets is needed. Here, we used gene expression signature (GES) classification and Cox regression analyses to biologically characterize melanoma cells at...

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Autores principales: Bakr, Mohamed Nabil, Takahashi, Haruko, Kikuchi, Yutaka
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2022
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9313451/
https://www.ncbi.nlm.nih.gov/pubmed/35884783
http://dx.doi.org/10.3390/biomedicines10071478
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author Bakr, Mohamed Nabil
Takahashi, Haruko
Kikuchi, Yutaka
author_facet Bakr, Mohamed Nabil
Takahashi, Haruko
Kikuchi, Yutaka
author_sort Bakr, Mohamed Nabil
collection PubMed
description Since the current melanoma clinicopathological staging system remains restricted to predicting survival outcomes, establishing precise prognostic targets is needed. Here, we used gene expression signature (GES) classification and Cox regression analyses to biologically characterize melanoma cells at the single-cell level and construct a prognosis-related gene signature for melanoma. By analyzing publicly available scRNA-seq data, we identified six distinct GESs (named: “Anti-apoptosis”, “Immune cell interactions”, “Melanogenesis”, “Ribosomal biogenesis”, “Extracellular structure organization”, and “Epithelial-Mesenchymal Transition (EMT)”). We verified these GESs in the bulk RNA-seq data of patients with skin cutaneous melanoma (SKCM) from The Cancer Genome Atlas (TCGA). Four GESs (“Immune cell interactions”, “Melanogenesis”, “Ribosomal biogenesis”, and “Extracellular structure organization”) were significantly correlated with prognosis (p = 1.08 × 10(−5), p = 0.042, p = 0.001, and p = 0.031, respectively). We identified a prognostic signature of melanoma composed of 45 genes (MPS_45). MPS_45 was validated in TCGA-SKCM (HR = 1.82, p = 9.08 × 10(−6)) and three other melanoma datasets (GSE65904: HR = 1.73, p = 0.006; GSE19234: HR = 3.83, p = 0.002; and GSE53118: HR = 1.85, p = 0.037). MPS_45 was independently associated with survival (p = 0.002) and was proved to have a high potential for predicting prognosis in melanoma patients.
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spelling pubmed-93134512022-07-26 Analysis of Melanoma Gene Expression Signatures at the Single-Cell Level Uncovers 45-Gene Signature Related to Prognosis Bakr, Mohamed Nabil Takahashi, Haruko Kikuchi, Yutaka Biomedicines Article Since the current melanoma clinicopathological staging system remains restricted to predicting survival outcomes, establishing precise prognostic targets is needed. Here, we used gene expression signature (GES) classification and Cox regression analyses to biologically characterize melanoma cells at the single-cell level and construct a prognosis-related gene signature for melanoma. By analyzing publicly available scRNA-seq data, we identified six distinct GESs (named: “Anti-apoptosis”, “Immune cell interactions”, “Melanogenesis”, “Ribosomal biogenesis”, “Extracellular structure organization”, and “Epithelial-Mesenchymal Transition (EMT)”). We verified these GESs in the bulk RNA-seq data of patients with skin cutaneous melanoma (SKCM) from The Cancer Genome Atlas (TCGA). Four GESs (“Immune cell interactions”, “Melanogenesis”, “Ribosomal biogenesis”, and “Extracellular structure organization”) were significantly correlated with prognosis (p = 1.08 × 10(−5), p = 0.042, p = 0.001, and p = 0.031, respectively). We identified a prognostic signature of melanoma composed of 45 genes (MPS_45). MPS_45 was validated in TCGA-SKCM (HR = 1.82, p = 9.08 × 10(−6)) and three other melanoma datasets (GSE65904: HR = 1.73, p = 0.006; GSE19234: HR = 3.83, p = 0.002; and GSE53118: HR = 1.85, p = 0.037). MPS_45 was independently associated with survival (p = 0.002) and was proved to have a high potential for predicting prognosis in melanoma patients. MDPI 2022-06-22 /pmc/articles/PMC9313451/ /pubmed/35884783 http://dx.doi.org/10.3390/biomedicines10071478 Text en © 2022 by the authors. https://creativecommons.org/licenses/by/4.0/Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://creativecommons.org/licenses/by/4.0/).
spellingShingle Article
Bakr, Mohamed Nabil
Takahashi, Haruko
Kikuchi, Yutaka
Analysis of Melanoma Gene Expression Signatures at the Single-Cell Level Uncovers 45-Gene Signature Related to Prognosis
title Analysis of Melanoma Gene Expression Signatures at the Single-Cell Level Uncovers 45-Gene Signature Related to Prognosis
title_full Analysis of Melanoma Gene Expression Signatures at the Single-Cell Level Uncovers 45-Gene Signature Related to Prognosis
title_fullStr Analysis of Melanoma Gene Expression Signatures at the Single-Cell Level Uncovers 45-Gene Signature Related to Prognosis
title_full_unstemmed Analysis of Melanoma Gene Expression Signatures at the Single-Cell Level Uncovers 45-Gene Signature Related to Prognosis
title_short Analysis of Melanoma Gene Expression Signatures at the Single-Cell Level Uncovers 45-Gene Signature Related to Prognosis
title_sort analysis of melanoma gene expression signatures at the single-cell level uncovers 45-gene signature related to prognosis
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9313451/
https://www.ncbi.nlm.nih.gov/pubmed/35884783
http://dx.doi.org/10.3390/biomedicines10071478
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