Establishing and verification of fatty acid metabolism prognosis model for breast cancer based on single-cell transcriptomic sequencing data

  • YAN Tao ,
  • FANG Lin
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  • 1. Anhui University of Science and Technology, Huainan 232001, China;
    2. Shanghai Tenth People's Hospital

Received date: 2024-04-29

  Online published: 2024-08-07

Abstract

Objective:To establish a prognostic model of fatty acid metabolism (FAM) for breast cancer based on FAM related genes, and to evaluate the prognosis of the FAM model. Methods: Breast cancer single-cell RNA sequencing (scRNA-seq) data set was sorted out to identify breast epithelial tumor cells, and the activation degree of breast cancer FAM in different tumor cells was obtained using area under the curve for expression level (AUCell) analysis. The weighted gene co-expression network analysis (WGCNA) was used to obtain FAM-related differential genes in breast cancer. The prognostic risk model of 767 patients was established using univariate and multivariate COX regression. Receiver operating characteristic curve (ROC), decision analysis curve (DAC) and concordance index (C-index) were used to evaluate the accuracy of the model. Finally, the GSE3143 dataset was used for validation. Results: A total of 597 differential genes were identified by single-cell transcriptomic analysis, and 12 risk-related genes associated with OS were identified by univariate and multivariate COX regression, which were FOXQ1, TFPI2, MACC1, ACOT7, MCEE, SLC27A2, QPRT, SLC2A1, ACAA1, NDRG1, KYNU and YOD1. Multi-index ROC analysis, DAC and C-index indicated that the model had high prediction accuracy. Conclusion: The prognostic model based on 12 FAM-related genes for breast cancer has certain accuracy, which could be used to guide clinical treatment more accurately.

Cite this article

YAN Tao , FANG Lin . Establishing and verification of fatty acid metabolism prognosis model for breast cancer based on single-cell transcriptomic sequencing data[J]. Journal of Baotou Medical College, 2024 , 40(7) : 15 -22 . DOI: 10.16833/j.cnki.jbmc.2024.07.003

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