Establishing a Ten Disulfidptosis-related Gene Signature for Prognostic Prediction in Skin Cutaneous Melanoma.

IF 1.6 4区医学 Q4 BIOCHEMICAL RESEARCH METHODS

Combinatorial chemistry & high throughput screening Pub Date : 2024-06-14 DOI:10.2174/0113862073307469240528065718

Haiyan Li, Zedong Chen, Yuanjie Huang, Chen Chen, Limin Cai

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引用次数: 0

Abstract

Aim: Disulfidptosis is a new metabolic-related regulated cell death associated with cancer growth. This study aimed to investigate the molecular mechanisms associated with disulfidptosis in skin cutaneous melanoma (SKCM) and establish a disulfidptosis-related gene signature for prognostic prediction in SKCM.

Methods: Disulfidptosis-associated genes were identified from RNA-seq data of SKCM. A risk score signature was developed and validated through univariate Cox and LASSO analyses. Additionally, the immune microenvironment related to the risk score signature was investigated. Finally, a disulfidptosis-related genes-transcription factor -miRNA network was developed, and the expression levels of five disulfidptosis-related genes were initially verified in SKCM cell lines.

Results: A total of 107 disulfidptosis-related differentially expressed genes in SKCM samples were identified. A ten-disulfidptosis-gene signature was established, including BIN2, CCL3L3, CCL8, CD79A, CIITA, CXCR3, DEFB1, GPR171, IL2RB, and SOCS1. The SKCM samples were divided into high- and low-risk groups, of which samples in the low-risk group showed better survival performance. The receiver operating characteristic curve analysis confirmed the good potency of the disulfidptosis-related gene prognostic model. Except for DEFB1, the other nine genes were positively related with T cell CD8+, T cell CD4+ memory activated, T cell gamma delta, NK cell activated, and macrophage M1, and they were all negatively related with NK cell resting, macrophage M0, macrophage M2, and mast cell activated. Finally, we verified downregulated levels of SOCS1 and DEFB1 and upregulated CXCR3, BIN2, and CCL3L3 in A875 and A375.

Conclusion: We successfully established ten disulfidptosis-related genes' prediction prognostic signatures for SKCM patients.

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建立用于皮肤黑色素瘤预后预测的 10 个二硫化相关基因特征。

目的：二硫化硫是一种与癌症生长相关的新的代谢调节性细胞死亡。本研究旨在探讨皮肤黑色素瘤（SKCM）中与二硫化相关的分子机制，并建立二硫化相关基因特征，用于预测SKCM的预后：方法：从SKCM的RNA-seq数据中发现了二硫化相关基因。方法：从SKCM的RNA-seq数据中发现了二硫化相关基因，并通过单变量Cox和LASSO分析建立和验证了风险评分特征。此外，还研究了与风险评分特征相关的免疫微环境。最后，建立了二硫化相关基因-转录因子-miRNA网络，并初步验证了五个二硫化相关基因在SKCM细胞系中的表达水平：结果：在 SKCM 样本中发现了 107 个与二硫化相关的差异表达基因。结果：在 SKCM 样本中总共发现了 107 个与二硫化相关的差异表达基因，其中包括 BIN2、CCL3L3、CCL8、CD79A、CIITA、CXCR3、DEFB1、GPR171、IL2RB 和 SOCS1。SKCM 样本被分为高风险组和低风险组，其中低风险组样本的存活率更高。接受者操作特征曲线分析证实了二硫化相关基因预后模型的有效性。除DEFB1外，其他9个基因与T细胞CD8+、T细胞CD4+记忆激活、T细胞γδ、NK细胞激活和巨噬细胞M1呈正相关，与NK细胞静息、巨噬细胞M0、巨噬细胞M2和肥大细胞激活呈负相关。最后，我们还验证了 A875 和 A375 中 SOCS1 和 DEFB1 的下调水平以及 CXCR3、BIN2 和 CCL3L3 的上调水平：我们成功地建立了十个二硫化相关基因对 SKCM 患者的预测预后特征。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

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来源期刊

Combinatorial chemistry & high throughput screening 化学-生化研究方法

CiteScore

3.10

自引率

5.60%

发文量

327

审稿时长

7.5 months

期刊介绍： Combinatorial Chemistry & High Throughput Screening (CCHTS) publishes full length original research articles and reviews/mini-reviews dealing with various topics related to chemical biology (High Throughput Screening, Combinatorial Chemistry, Chemoinformatics, Laboratory Automation and Compound management) in advancing drug discovery research. Original research articles and reviews in the following areas are of special interest to the readers of this journal: Target identification and validation Assay design, development, miniaturization and comparison High throughput/high content/in silico screening and associated technologies Label-free detection technologies and applications Stem cell technologies Biomarkers ADMET/PK/PD methodologies and screening Probe discovery and development, hit to lead optimization Combinatorial chemistry (e.g. small molecules, peptide, nucleic acid or phage display libraries) Chemical library design and chemical diversity Chemo/bio-informatics, data mining Compound management Pharmacognosy Natural Products Research (Chemistry, Biology and Pharmacology of Natural Products) Natural Product Analytical Studies Bipharmaceutical studies of Natural products Drug repurposing Data management and statistical analysis Laboratory automation, robotics, microfluidics, signal detection technologies Current & Future Institutional Research Profile Technology transfer, legal and licensing issues Patents.