Exploring the role of sphingolipid-related genes in clinical outcomes of breast cancer

乳腺癌 癌症 肿瘤科 鞘脂 医学 计算生物学 生物信息学 内科学 生物 癌症研究 基因 遗传学
作者
Shengbin Pei,Pengpeng Zhang,Lili Yang,Yakun Kang,Huilin Chen,Shuhan Zhao,Yuhan Dai,Mingjie Zheng,Yiqin Xia,Hui Xie
出处
期刊:Frontiers in Immunology [Frontiers Media]
卷期号:14: 1116839-1116839 被引量:101
标识
DOI:10.3389/fimmu.2023.1116839
摘要

Background Despite tremendous advances in cancer research, breast cancer (BC) remains a major health concern and is the most common cancer affecting women worldwide. Breast cancer is a highly heterogeneous cancer with potentially aggressive and complex biology, and precision treatment for specific subtypes may improve survival in breast cancer patients. Sphingolipids are important components of lipids that play a key role in the growth and death of tumor cells and are increasingly the subject of new anti-cancer therapies. Key enzymes and intermediates of sphingolipid metabolism (SM) play an important role in regulating tumor cells and further influencing clinical prognosis. Methods We downloaded BC data from the TCGA database and GEO database, on which we performed in depth single-cell sequencing analysis (scRNA-seq), weighted co-expression network analysis, and transcriptome differential expression analysis. Then seven sphingolipid-related genes (SRGs) were identified using Cox regression, least absolute shrinkage, and selection operator (Lasso) regression analysis to construct a prognostic model for BC patients. Finally, the expression and function of the key gene PGK1 in the model were verified by in vitro experiments. Results This prognostic model allows for the classification of BC patients into high-risk and low-risk groups, with a statistically significant difference in survival time between the two groups. The model is also able to show high prediction accuracy in both internal and external validation sets. After further analysis of the immune microenvironment and immunotherapy, it was found that this risk grouping could be used as a guide for the immunotherapy of BC. The proliferation, migration, and invasive ability of MDA-MB-231 and MCF-7 cell lines were dramatically reduced after knocking down the key gene PGK1 in the model through cellular experiments. Conclusion This study suggests that prognostic features based on genes related to SM are associated with clinical outcomes, tumor progression, and immune alterations in BC patients. Our findings may provide insights for the development of new strategies for early intervention and prognostic prediction in BC.
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