Department of Anatomy, Faculty of Medicine, Maranatha Christian University, Jl. Surya Sumantri No. 65, Bandung, 40164, West Java, Indonesia.
Biomedical Research Laboratory, Faculty of Medicine, Maranatha Christian University, Bandung, 40164, West Java, Indonesia.
Breast Cancer Res Treat. 2024 Nov;208(2):379-390. doi: 10.1007/s10549-024-07428-1. Epub 2024 Jul 11.
Breast cancer is a common malignancy in women, and its metastasis is a leading cause of cancer-related deaths. Single-cell RNA sequencing (scRNA-seq) can distinguish the molecular characteristics of metastasis and identify predictor genes for patient prognosis. This article explores gene expression in primary breast cancer tumor tissue against metastatic cells in the lymph node and liver using scRNA-seq.
Breast cancer scRNA-seq data from the Gene Expression Omnibus were used. The data were processed using R and the Seurat package. The cells were clustered and identified using Metascape. InferCNV is used to analyze the variation in copy number. Differential expression analysis was conducted for the cancer cells using Seurat and was enriched using Metascape.
We identified 18 distinct cell clusters, 6 of which were epithelial. CNV analysis identified significant alterations with duplication of chromosomes 1, 8, and 19. Differential gene analysis resulted in 17 upregulated and 171 downregulated genes for the primary tumor in the primary tumor vs. liver metastasis comparison and 43 upregulated and 4 downregulated genes in the primary tumor in the primary tumor vs lymph node metastasis comparison. Several enriched terms include Ribosome biogenesis, NTP synthesis, Epithelial dedifferentiation, Autophagy, and genes associated with epithelial-to-mesenchymal transitions.
No single gene or pathway can clearly explain the mechanisms behind tumor metastasis. Several mechanisms contribute to lymph node and liver metastasis, such as the loss of differentiation, epithelial-to-mesenchymal transition, and autophagy. These findings necessitate further study of metastatic tissue for effective drug development.
乳腺癌是女性常见的恶性肿瘤，其转移是癌症相关死亡的主要原因。单细胞 RNA 测序（scRNA-seq）可以区分转移的分子特征，并识别预测患者预后的基因。本文使用 scRNA-seq 研究了原发性乳腺癌肿瘤组织与淋巴结和肝脏转移细胞的基因表达。
使用基因表达综合数据库中的乳腺癌 scRNA-seq 数据。使用 R 和 Seurat 包处理数据。使用 Metascape 对细胞进行聚类和鉴定。使用 InferCNV 分析拷贝数的变化。使用 Seurat 对癌细胞进行差异表达分析，并使用 Metascape 进行富集分析。
我们鉴定了 18 个不同的细胞簇，其中 6 个是上皮细胞。CNV 分析发现染色体 1、8 和 19 的重复存在显著改变。原发性肿瘤与肝转移比较中，原发性肿瘤的差异基因分析得到 17 个上调和 171 个下调基因，原发性肿瘤与淋巴结转移比较中，原发性肿瘤的差异基因分析得到 43 个上调和 4 个下调基因。几个富集的术语包括核糖体生物发生、NTP 合成、上皮去分化、自噬以及与上皮-间充质转化相关的基因。
没有单个基因或途径可以清楚地解释肿瘤转移的机制。几个机制导致了淋巴结和肝转移，如分化丢失、上皮-间充质转化和自噬。这些发现需要对转移性组织进行进一步研究，以开发有效的药物。
