Bioinformatics analysis and validation of genes related to paclitaxel's anti-breast cancer effect through immunogenic cell death
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Updated: Jun 29, 2025
Long-term Live-cell Imaging to Assess Cell Fate in Response to Paclitaxel
Published on: May 14, 2018
Qianmei Yang1,2, Guimei Yang1,2, Yi Wu3
1School of Pharmaceutical Science & Yunnan Provincial Key Laboratory of Pharmacology for Natural Products, Kunming Medical University, Kunming, Yunnan, 650500, PR China.
Abstract:
Research indicated that Paclitaxel (PTX) can induce immunogenic cell death (ICD) through immunogenic modulation. However, the combination of PTX and ICD has not been extensively studied in breast cancer (BRCA). The TCGA-BRCA and GSE20685 datasets were enrolled in this study. Samples from the TCGA-BRCA dataset were consistently clustered based on selected immunogenic cell death-related genes (ICD-RGs). Next, candidate genes were obtained by overlapping differentially expressed genes (DEGs) between BRCA and normal groups, intersecting genes common to DEGs between cluster1 and cluster2 and hub module genes, and target genes of PTX from five databases. The univariate Cox algorithm and the least absolute shrinkage and selection operator (LASSO) were performed to obtain biomarkers and build a risk model. Following observing the immune microenvironment in differential risk subgroups, single-gene gene set enrichment analysis (GSEA) was carried out in all biomarkers. Finally, the expression of biomarkers was analyzed. Enrichment analysis showed that 626 intersecting genes were linked with inflammatory response. Further five biomarkers (CHI3L1, IL18, PAPLN, SH2D2A, and UBE2L6) were identified and a risk model was built. The model's performance was validated using GSE20685 dataset. Furthermore, the biomarkers were enriched with adaptive immune response. Lastly, the experimental results indicated that the alterations in IL18, SH2D2A, and CHI3L1 expression after treatment matched those in the public database. In this study, Five PTX-ICD-related biomarkers (CHI3L1, IL18, PAPLN, SH2D2A, and UBE2L6) were identified to aid in predicting BRCA treatment outcomes.
Insights
This study identified five key biomarkers (CHI3L1, IL18, PAPLN, SH2D2A, and UBE2L6) linked to Paclitaxel-induced immunogenic cell death (ICD) in breast cancer (BRCA). These biomarkers can help predict treatment outcomes for BRCA patients.
Area of Science:
- Oncology
- Immunology
- Genomics
Background:
- Paclitaxel (PTX) can induce immunogenic cell death (ICD), but its role in breast cancer (BRCA) requires further investigation.
- Understanding PTX-ICD interactions is crucial for improving BRCA treatment strategies.
Purpose of the Study:
- To identify novel biomarkers associated with PTX-induced ICD in BRCA.
- To develop a predictive risk model for BRCA treatment outcomes based on these biomarkers.
Main Methods:
- Utilized TCGA-BRCA and GSE20685 datasets for gene expression analysis.
- Employed differential gene expression analysis, LASSO regression, and Cox algorithms to identify biomarkers.
- Performed gene set enrichment analysis (GSEA) to explore biological pathways.
Main Results:
- Identified five key PTX-ICD-related biomarkers: CHI3L1, IL18, PAPLN, SH2D2A, and UBE2L6.
- Developed and validated a risk model using these biomarkers.
- Found that these biomarkers are enriched with adaptive immune responses and linked to inflammatory responses.
Conclusions:
- The identified biomarkers (CHI3L1, IL18, PAPLN, SH2D2A, UBE2L6) can aid in predicting BRCA treatment outcomes.
- The developed risk model shows potential for clinical application in personalized BRCA therapy.
