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Published in: Discover Oncology 1/2024

Open Access 01-12-2024 | Melanoma | Research

Transcriptome and single-cell transcriptomics reveal prognostic value and potential mechanism of anoikis in skin cutaneous melanoma

Authors: Xing Liu, Hong-Yan Zhang, Hong-Ao Deng

Published in: Discover Oncology | Issue 1/2024

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Abstract

Background

Skin cutaneous melanoma (SKCM) is a highly lethal cancer, ranking among the top four deadliest cancers. This underscores the urgent need for novel biomarkers for SKCM diagnosis and prognosis. Anoikis plays a vital role in cancer growth and metastasis, and this study aims to investigate its prognostic value and mechanism of action in SKCM.

Methods

Utilizing consensus clustering, the SKCM samples were categorized into two distinct clusters A and B based on anoikis-related genes (ANRGs), with the B group exhibiting lower disease-specific survival (DSS). Gene set enrichment between distinct clusters was examined using Gene Set Variation Analysis (GSVA) and the Kyoto Encyclopedia of Genes and Genomes (KEGG) analysis.

Results

We created a predictive model based on three anoikis-related differently expressed genes (DEGs), specifically, FASLG, IGF1, and PIK3R2. Moreover, the mechanism of these prognostic genes within the model was investigated at the cellular level using the single-cell sequencing dataset GSE115978. This analysis revealed that the FASLG gene was highly expressed on cluster 1 of Exhausted CD8( +) T (Tex) cells.

Conclusions

In conclusion, we have established a novel classification system for SKCM based on anoikis, which carries substantial clinical implications for SKCM patients. Notably, the elevated expression of the FASLG gene on cluster 1 of Tex cells could significantly impact SKCM prognosis through anoikis, thus offering a promising target for the development of immunotherapy for SKCM.
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Metadata
Title
Transcriptome and single-cell transcriptomics reveal prognostic value and potential mechanism of anoikis in skin cutaneous melanoma
Authors
Xing Liu
Hong-Yan Zhang
Hong-Ao Deng
Publication date
01-12-2024
Publisher
Springer US
Keywords
Melanoma
Melanoma
Published in
Discover Oncology / Issue 1/2024
Print ISSN: 1868-8497
Electronic ISSN: 2730-6011
DOI
https://doi.org/10.1007/s12672-024-00926-0

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