Identification of two molecularly and prognostically distinct subtypes in acral melanoma using network prediction method.

IF 8.4 2区 医学 Q1 DERMATOLOGY Journal of the European Academy of Dermatology and Venereology Pub Date : 2024-09-16 DOI:10.1111/jdv.20335
Mingzhu Yin, Yiding Zhang, Wenhua Wang, Shuang Zhao, Juan Su, Shao Li, Xiang Chen
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Abstract

Background: Acral melanoma, characterized by its aggressiveness and poor prognosis compared to other melanoma subtypes, poses significant challenges in clinical management. However, the molecular underpinnings driving the biological and clinical features of this disease remain poorly understood.

Objectives: In this study, our aim was to elucidate the molecular landscape and the correlation between subtypes and clinical features of acral melanoma.

Methods: We conducted comprehensive analyses to dissect the molecular characteristics of acral melanoma, employing a combination of multi-omics data analysis and network-based disease gene prediction algorithms. Single-cell RNA-Seq data were utilized to investigate the contribution of immunocytes to the molecular classification of acral melanoma. Additionally, we used clinical samples to validate the correlation between new subtypes and the prognosis of acral melanoma and the expression of subtype markers and verified the interaction between macrophages and acral melanoma cells at cellular level.

Results: Our study reveals the existence of two distinct subtypes of acral melanoma exhibiting marked differences in clinical behaviour, cellular and molecular mechanisms. We identified a robust biomarker panel (EREG, VSIG4, FCGR3A and RAB20) that accurately distinguishes these two subtypes with an impressive AUC of 0.946, validated using clinical samples. Subtype I, characterized by thinner Breslow thickness, demonstrates a favourable prognosis, whereas Subtype II represents a high-risk subtype with a propensity for dermal invasion. Notably, the signature gene EREG of Subtype I is enriched in FCN1+ macrophages, known for promoting inflammatory and immune responses. Conversely, signature genes VSIG4 and FCGR3A of Subtype II are enriched in SPP1+ macrophages, which exhibit significant crosstalk with tumour cells.

Conclusions: Our findings significantly enhance the understanding of the molecular landscape of acral melanoma and offer novel insights into its clinical management by identifying distinct subtypes and potential therapeutic targets. The findings have to be confirmed in different cohorts in the future for full validation.

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利用网络预测法识别尖锐湿疣黑色素瘤的两种分子和预后不同的亚型。
背景:与其他黑色素瘤亚型相比,口腔黑色素瘤的特点是侵袭性强、预后差,这给临床治疗带来了巨大挑战。然而,人们对这种疾病的生物学和临床特征的分子基础仍然知之甚少:本研究旨在阐明尖锐湿疣黑色素瘤的分子图谱以及亚型和临床特征之间的相关性:我们结合多组学数据分析和基于网络的疾病基因预测算法,对尖锐湿疣黑色素瘤的分子特征进行了全面分析。我们利用单细胞RNA-Seq数据研究了免疫细胞对尖锐湿疣黑色素瘤分子分类的贡献。此外,我们还利用临床样本验证了尖锐湿疣新亚型与预后之间的相关性以及亚型标志物的表达,并在细胞水平上验证了巨噬细胞与尖锐湿疣细胞之间的相互作用:结果:我们的研究揭示了尖锐湿疣黑色素瘤存在两种不同的亚型,它们在临床表现、细胞和分子机制方面存在明显差异。我们发现了一个强大的生物标记物面板(EREG、VSIG4、FCGR3A 和 RAB20),它能准确区分这两种亚型,并通过临床样本验证,其 AUC 值高达 0.946,令人印象深刻。亚型 I 的特点是布瑞斯洛厚度较薄,预后较好,而亚型 II 则是高风险亚型,具有真皮侵犯倾向。值得注意的是,亚型 I 的特征基因 EREG 在 FCN1+ 巨噬细胞中富集,而 FCN1+ 巨噬细胞以促进炎症和免疫反应而闻名。相反,亚型 II 的特征基因 VSIG4 和 FCGR3A 在 SPP1+ 巨噬细胞中富集,而 SPP1+ 巨噬细胞与肿瘤细胞有明显的串扰:我们的研究结果大大加深了人们对尖锐湿疣黑色素瘤分子图谱的了解,并通过识别不同亚型和潜在治疗靶点,为临床治疗提供了新的见解。这些发现还需要在未来的不同队列中得到证实,以进行全面验证。
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
CiteScore
10.70
自引率
8.70%
发文量
874
审稿时长
3-6 weeks
期刊介绍: The Journal of the European Academy of Dermatology and Venereology (JEADV) is a publication that focuses on dermatology and venereology. It covers various topics within these fields, including both clinical and basic science subjects. The journal publishes articles in different formats, such as editorials, review articles, practice articles, original papers, short reports, letters to the editor, features, and announcements from the European Academy of Dermatology and Venereology (EADV). The journal covers a wide range of keywords, including allergy, cancer, clinical medicine, cytokines, dermatology, drug reactions, hair disease, laser therapy, nail disease, oncology, skin cancer, skin disease, therapeutics, tumors, virus infections, and venereology. The JEADV is indexed and abstracted by various databases and resources, including Abstracts on Hygiene & Communicable Diseases, Academic Search, AgBiotech News & Information, Botanical Pesticides, CAB Abstracts®, Embase, Global Health, InfoTrac, Ingenta Select, MEDLINE/PubMed, Science Citation Index Expanded, and others.
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