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Journal Article Epublish 2 citations

PubMed: 40114930 DOI: 10.3389/fimmu.2025.1539074

Exposing the cellular situation: findings from single cell RNA sequencing in breast cancer.

Front Immunol 16:1539074

Authors: Gaofeng Ni, Xinhan Li, Wenyang Nie, Zhenzhen Zhao, Hua Li, Hongyan Zang

Affiliations

  • 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.
  • Department of General Surgery, Affiliated Hospital of Youjiang Medical University for Nationalities, Baise, Guangxi, China. Key Laboratory of Tumor Molecular Pathology of Baise, Affiliated Hospital of Youjiang Medical University for Nationalities, Baise, Guangxi, China.

Abstract

Background

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.

Method

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.

Results

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.

Conclusion

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.

MeSH

Cells, Breast Neoplasms, Transcription Factors, Neoplasms, Immune System Diseases, Breast, Research, Therapeutics, Tumor Microenvironment, Prognosis, Rna

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