单细胞和批量RNA数据的综合分析揭示了黑色素瘤相互作用组的复杂性和重要性。

Integrated Analysis of Single-Cell and Bulk RNA Data Reveals Complexity and Significance of the Melanoma Interactome.

作者信息

Diaz Michael J, Tran Jasmine T, Samia Arthur M, Forouzandeh Mahtab, Grant-Kels Jane M, Montanez-Wiscovich Marjorie E

机构信息

College of Medicine, University of Florida, Gainesville, FL 32610, USA.

School of Medicine, Indiana University, Indianapolis, IN 46202, USA.

出版信息

Cancers (Basel). 2025 Jan 5;17(1):148. doi: 10.3390/cancers17010148.

Abstract

Despite significant strides in anti-melanoma therapies, resistance and recurrence remain major challenges. A deeper understanding of the underlying biology of these challenges is necessary for developing more effective treatment paradigms. Melanoma single-cell data were retrieved from the Broad Single Cell Portal (SCP11). High-dimensional weighted gene co-expression network analysis (hdWGCNA), CellChat, and ligand-receptor relative crosstalk (RC) scoring were employed to evaluate intercellular and intracellular signaling. The prognostic value of key regulatory genes was assessed via Kaplan-Meier (KM) survival analysis using the 'SKCM-TCGA' dataset. Twenty-seven (27) gene co-expression modules were identified via hdWGCNA. Notable findings include NRAS Q61L melanomas being enriched for modules involving C19orf10 and ARF4, while BRAF V600E melanomas were enriched for modules involving and . Additionally, CellChat analysis highlighted several dominant signaling pathways, namely MHC-II, CD99, and Collagen-receptor signaling, with numerous significant ligand-receptor interactions from melanocytes, including CD99-CD99 communications with cancer-associated fibroblasts, endothelial cells, NK cells, and T-cells. KM analysis revealed that higher expression of , , , , , , and improved overall survival, while higher expression correlated with worse survival. Protein-protein interaction network analysis further indicated significant interconnectivity among the identified prognostic genes. Overall, these insights underscore critical immune interactions and potential therapeutic targets to combat melanoma resistance, paving the way for more personalized and effective treatment strategies.

摘要

尽管抗黑色素瘤疗法取得了重大进展,但耐药性和复发仍然是主要挑战。深入了解这些挑战的潜在生物学机制对于开发更有效的治疗模式至关重要。黑色素瘤单细胞数据从布罗德单细胞门户(SCP11)中检索。采用高维加权基因共表达网络分析(hdWGCNA)、CellChat和配体-受体相对串扰(RC)评分来评估细胞间和细胞内信号传导。使用“SKCM-TCGA”数据集通过Kaplan-Meier(KM)生存分析评估关键调控基因的预后价值。通过hdWGCNA鉴定出27个基因共表达模块。显著发现包括NRAS Q61L黑色素瘤在涉及C19orf10和ARF4的模块中富集,而BRAF V600E黑色素瘤在涉及[此处原文缺失两个基因]和[此处原文缺失两个基因]的模块中富集。此外,CellChat分析突出了几个主要信号通路,即MHC-II、CD99和胶原蛋白受体信号通路,黑色素细胞有许多显著的配体-受体相互作用,包括与癌症相关成纤维细胞、内皮细胞、NK细胞和T细胞的CD99-CD99通讯。KM分析显示,[此处原文缺失七个基因]的高表达改善了总生存期,而[此处原文缺失一个基因]的高表达与较差的生存期相关。蛋白质-蛋白质相互作用网络分析进一步表明所鉴定的预后基因之间存在显著的相互连接性。总体而言,这些见解强调了对抗黑色素瘤耐药性的关键免疫相互作用和潜在治疗靶点,为更个性化和有效的治疗策略铺平了道路。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/3577/11720022/3344a042f000/cancers-17-00148-g001.jpg

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