Ni Gaofeng, Li Xinhan, Nie Wenyang, Zhao Zhenzhen, Li Hua, Zang Hongyan
Department of Breast Surgery, Yantaishan Hospital Affiliated to Binzhou Medical University, Yantai, China.
The First Clinical Medical College, Shandong University of Traditional Chinese Medicine, Jinan, Shandong, China.
Front Immunol. 2025 Mar 6;16:1539074. doi: 10.3389/fimmu.2025.1539074. eCollection 2025.
Breast Cancer (BC) ranks among the top three most prevalent cancers globally and stands as the principal contributor to cancer-related fatalities among women. In spite of the substantial occurrence rate of BC, the early stage of this disease is generally regarded as curable. However, intra-tumor heterogeneity presents a formidable obstacle to the success of effective treatment.
In this research, single cell RNA sequencing was utilized to dissect the tumor microenvironment within BC. Slingshot, CytoTRACE and Monocle 2 were applied to illustrate the differentiation process of each subpopulation in the pseudotime sequence. To comprehensively comprehend the tumor cells (TCs) in BC, an analysis of upstream transcription factors was carried out via pySCENIC, while downstream pathway enrichment was conducted through KEGG, GO and GSEA. The prognosis model was established based on the bulk data obtained from TCGA and GEO databases. Knock-down experiments were also implemented to explore the function of the transcription factor in the TCs.
Our in-depth analysis identified eight principal cell types. Notably, TCs were predominantly found within epithelial cells. The classification of TCs further uncovered five unique subpopulations, with one subpopulation characterized by high expression. This subpopulation was shown to possess distinct metabolic features in metabolism-related investigations. The intricate communication modalities among different cell types were effectively demonstrated by means of CellChat. Additionally, a crucial transcription factor, , was identified, which demonstrated a pronounced propensity towards tumors and harbored potential tumor-advancing characteristics. Its role in promoting cancer was subsequently verified through knock-down experiments. Moreover, a prognostic model was also developed, and a risk score was established based on the genes incorporated in the model. Through comparing the prognoses of different UTRS levels, it was determined that the group with a high UTRS had a less favorable prognosis.
These outcomes contributed to the elucidation of the complex interrelationships within the BC tumor microenvironment. By specifically targeting certain subpopulations of TCs, novel treatment strategies could potentially be devised. This study shed light on the direction that future research in BC should take, furnishing valuable information that can be utilized to enhance treatment regimens.
乳腺癌（BC）是全球最常见的三大癌症之一，也是女性癌症相关死亡的主要原因。尽管BC的发病率很高，但这种疾病的早期通常被认为是可以治愈的。然而，肿瘤内异质性是有效治疗成功的巨大障碍。
在本研究中，利用单细胞RNA测序剖析BC内的肿瘤微环境。应用Slingshot、CytoTRACE和Monocle 2以伪时间序列说明每个亚群的分化过程。为全面了解BC中的肿瘤细胞（TCs），通过pySCENIC进行上游转录因子分析，同时通过KEGG、GO和GSEA进行下游通路富集分析。基于从TCGA和GEO数据库获得的批量数据建立预后模型。还进行了敲低实验以探索转录因子在TCs中的功能。
我们的深入分析确定了八种主要细胞类型。值得注意的是，TCs主要存在于上皮细胞中。TCs的分类进一步揭示了五个独特的亚群，其中一个亚群具有高表达特征。在代谢相关研究中，该亚群显示出独特的代谢特征。通过CellChat有效地展示了不同细胞类型之间复杂的通讯方式。此外，还鉴定出一个关键转录因子，其显示出明显的肿瘤倾向并具有潜在的肿瘤促进特性。随后通过敲低实验验证了其在促进癌症中的作用。此外，还开发了一种预后模型，并基于模型中纳入的基因建立了风险评分。通过比较不同UTRS水平的预后情况，确定UTRS高的组预后较差。
这些结果有助于阐明BC肿瘤微环境内的复杂相互关系。通过特异性靶向TCs的某些亚群，可能设计出新的治疗策略。本研究为BC未来的研究方向提供了线索，提供了可用于改进治疗方案的有价值信息。
