Bioinformatic-based genetic characterizations of neural regulation in skin cutaneous melanoma.
Bioinformatic-based genetic characterizations of neural regulation in skin cutaneous melanoma.
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DOI：
10.3389/fonc.2023.1166373
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发表时间：
2023
影响因子：
4.7
通讯作者：
Zheng, Fang
中科院分区：
文献类型：
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作者：
Wang, Fengdi;Cheng, Fanjun;Zheng, Fang
关键词：
最近的发现揭示了包括皮肤黑色素瘤（SKCM）在内的几种癌症类型中复杂的癌症-神经相互作用。然而，SKCM中神经调控的遗传特征尚不清楚。收集TCGA和GTEx通道的转录组表达数据，分析正常皮肤和SKCM组织中癌-神经串音相关基因表达的差异。利用cbiopportal数据集进行基因突变分析。使用STRING数据库进行PPI分析。功能富集分析采用R包clusterProfiler进行分析。使用K-M绘图仪、单变量、多变量和LASSO回归进行预后分析和验证。使用GEPIA数据集分析基因表达与SKCM临床分期的关系。使用ssGSEA和GSCA数据集进行免疫细胞浸润分析。GSEA用于阐明显著的功能和通路差异。共鉴定出66个癌神经串扰相关基因，其中60个基因在SKCM中上调或下调，KEGG分析提示它们主要富集于钙信号通路、Ras信号通路、PI3K-Akt信号通路等。建立了包含8个基因（GRIN3A、CCR2、CHRNA4、CSF1、NTN1、ADRB1、CHRNB4和CHRNG）的基因预后模型，并通过独立队列GSE59455和GSE19234进行验证。构建包含临床特征和上述8个基因的nomogram， 1年、3年、5年ROC的auc分别为0.850、0.811、0.792。CCR2、GRIN3A和CSF1的表达与SKCM的临床分期相关。预后基因组与免疫浸润和免疫检查点基因存在广泛而强的相关性。CHRNA4和CHRNG是独立的不良预后基因，在CHRNA4高表达的细胞中丰富了多种代谢途径。我们对SKCM中肿瘤-神经串音相关基因进行了全面的生物信息学分析，并基于临床特征和与临床分期和免疫学特征广泛相关的8个基因（GRIN3A、CCR2、CHRNA4、CSF1、NTN1、ADRB1、CHRNB4、CHRNG）构建了有效的预后模型。我们的工作可能有助于进一步研究SKCM神经调控的相关分子机制，并寻找新的治疗靶点。
Recent discoveries uncovered the complex cancer–nerve interactions in several cancer types including skin cutaneous melanoma (SKCM). However, the genetic characterization of neural regulation in SKCM is unclear. Transcriptomic expression data were collected from the TCGA and GTEx portal, and the differences in cancer–nerve crosstalk-associated gene expressions between normal skin and SKCM tissues were analyzed. The cBioPortal dataset was utilized to implement the gene mutation analysis. PPI analysis was performed using the STRING database. Functional enrichment analysis was analyzed by the R package clusterProfiler. K-M plotter, univariate, multivariate, and LASSO regression were used for prognostic analysis and verification. The GEPIA dataset was performed to analyze the association of gene expression with SKCM clinical stage. ssGSEA and GSCA datasets were used for immune cell infiltration analysis. GSEA was used to elucidate the significant function and pathway differences. A total of 66 cancer–nerve crosstalk-associated genes were identified, 60 of which were up- or downregulated in SKCM and KEGG analysis suggested that they are mainly enriched in the calcium signaling pathway, Ras signaling pathway, PI3K-Akt signaling pathway, and so on. A gene prognostic model including eight genes (GRIN3A, CCR2, CHRNA4, CSF1, NTN1, ADRB1, CHRNB4, and CHRNG) was built and verified by independent cohorts GSE59455 and GSE19234. A nomogram was constructed containing clinical characteristics and the above eight genes, and the AUCs of the 1-, 3-, and 5-year ROC were 0.850, 0.811, and 0.792, respectively. Expression of CCR2, GRIN3A, and CSF1 was associated with SKCM clinical stages. There existed broad and strong correlations of the prognostic gene set with immune infiltration and immune checkpoint genes. CHRNA4 and CHRNG were independent poor prognostic genes, and multiple metabolic pathways were enriched in high CHRNA4 expression cells. Comprehensive bioinformatics analysis of cancer–nerve crosstalk-associated genes in SKCM was performed, and an effective prognostic model was constructed based on clinical characteristics and eight genes (GRIN3A, CCR2, CHRNA4, CSF1, NTN1, ADRB1, CHRNB4, and CHRNG), which were widely related to clinical stages and immunological features. Our work may be helpful for further investigation in the molecular mechanisms correlated with neural regulation in SKCM, and in searching new therapeutic targets.
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影响因子：
7.3
作者：
Gao J;Aksoy BA;Dogrusoz U;Dresdner G;Gross B;Sumer SO;Sun Y;Jacobsen A;Sinha R;Larsson E;Cerami E;Sander C;Schultz N
通讯作者：
Schultz N
影响因子：
8.8
作者：
Granados, Karol;Hueser, Laura;Utikal, Jochen
通讯作者：
Utikal, Jochen
影响因子：
2.5
作者：
Hunt PJ;Andújar FN;Silverman DA;Amit M
通讯作者：
Amit M
影响因子：
11.2
作者：
Boussouar, Amina;Tortereau, Antonin;Mehlen, Patrick
通讯作者：
Mehlen, Patrick
影响因子：
64.8
作者：
通讯作者：
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