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

Abstract

BackgroundDespite 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.MethodsWe 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.ResultsThis 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.ConclusionThis 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.

Exploration of the prognostic prediction value of the PANoptosis‐based risk score and its correlation with tumor immunity in lung adenocarcinoma

“…We explored PANoptosis‐related differential genes in LUAD patients and develop a clinically feasible risk score to predict the prognosis of LUAD patients. Risk scores are commonly employed for prognostic prediction in diverse cancer types, which showed superior performance compared with conventional methods in predicting clinical outcomes 19,28,29 . After comprehensive analysis and detailed description of the single‐cell sequencing data, we performed PANoptosis scoringe on all of the cells in single‐cell sequencing, and divided the cells into high‐ and low‐PANoptosis groups.…”

“…The single-cell RNA sequencing (scRNA-seq) has become an important approach to elucidate profound insights into tumor heterogeneity and the cellular communication network within tumors. [18][19][20] At present, a series of exploration on lung adenocarcinoma have been carried out using scRNA-seq. 21,22 In this study, we integrated the scRNA-seq data and RNA expression profiles of LUAD patients from public databases, screened PANoptosis-related differential genes and constructed a novel risk score.…”

“…The single‐cell RNA sequencing (scRNA‐seq) has become an important approach to elucidate profound insights into tumor heterogeneity and the cellular communication network within tumors 18–20 . At present, a series of exploration on lung adenocarcinoma have been carried out using scRNA‐seq 21,22 .…”

A novel signature predicts prognosis and immunotherapy in lung adenocarcinoma based on cancer-associated fibroblasts

“…We filtered out single cells expressing fewer than 250 genes or those with any gene expressed in fewer than three cells. We also evaluated the percentage of mitochondria and rRNA using the PercentageFeatureSet function in the Seurat R package ( 25 , 26 ). This resulted in a total of 12,554 cells for further analysis.…”

Biomarkers Exploration of Epithelial-Mesenchymal Transition and Ferroptosis in Lung Adenocarcinoma: Transcriptomic Analysis and Mendelian Randomization

“…This method is crucial for understanding the tumor microenvironment because it provides a rare chance to identify the molecular properties of different immune cell populations there (Slovin et al 2021). It provides us with a means to precisely evaluate gene expression at the individual cell level (Pei et al 2023). ScRNA-seq has become an invaluable tool for characterizing the gene expression, compositional variations, and functional states of individual stromal cells due to the rapid development of high-dimensional pro ling tools (Yao, et al 2021).…”