Integrated transcriptomic and immunological profiling reveals new diagnostic and prognostic models for cutaneous melanoma

Li, Changchang and Wu, Nanhui and Lin, Xiaoqiong and Zhou, Qiaochu and Xu, Mingyuan (2024) Integrated transcriptomic and immunological profiling reveals new diagnostic and prognostic models for cutaneous melanoma. Frontiers in Pharmacology, 15. ISSN 1663-9812

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The mortality rate associated with cutaneous melanoma (SKCM) remains alarmingly high, highlighting the urgent need for a deeper understanding of its molecular underpinnings. In our study, we leveraged bulk transcriptome sequencing data from the SKCM cohort available in public databases such as TCGA and GEO. We utilized distinct datasets for training and validation purposes and also incorporated mutation and clinical data from TCGA, along with single-cell sequencing data from GEO. Through dimensionality reduction, we annotated cell subtypes within the single-cell data and analyzed the expression of tumor-related pathways across these subtypes. We identified differentially expressed genes (DEGs) in the training set, which were further refined using the Least Absolute Shrinkage and Selection Operator (LASSO) machine learning algorithm, employing tenfold cross-validation. This enabled the construction of a prognostic model, whose diagnostic efficacy we subsequently validated. We conducted Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) analyses on the DEGs, and performed immunological profiling on two risk groups to elucidate the relationship between model genes and the immune responses relevant to SKCM diagnosis, treatment, and prognosis. We also knocked down the GMR6 expression level in the melanoma cells and verified its effect on cancer through multiple experiments. The results indicate that the GMR6 gene plays a role in promoting the proliferation, invasion, and migration of cancer cells in human melanoma. Our findings offer novel insights and a theoretical framework that could enhance prognosis, treatment, and drug development strategies for SKCM, potentially leading to more precise therapeutic interventions.

Item Type: Article
Subjects: Institute Archives > Multidisciplinary
Depositing User: Managing Editor
Date Deposited: 28 May 2024 07:39
Last Modified: 28 May 2024 07:39

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