Wei Zhang, Emma Li, Lily Wang, Brian D. Lehmann, and X. Steven Chen
This github repository includes scripts used for the analyses in the above manuscript.
Cite this article: Zhang, W., Li, E., Wang, L., Lehmann, B. D., & Chen, X. S. (2023). Transcriptome Meta-Analysis of Triple-Negative Breast Cancer Response to Neoadjuvant Chemotherapy. Cancers, 15(8), 2194. https://doi.org/10.3390/cancers15082194
Triple-negative breast cancer (TNBC) is a heterogeneous disease with varying responses to neoadjuvant chemotherapy (NAC). The identification of biomarkers to predict NAC response and inform personalized treatment strategies is essential. In this study, we conducted large-scale gene expression meta-analyses to identify genes associated with NAC response and survival outcomes. The results showed that immune, cell cycle/mitotic, and RNA splicing-related pathways were significantly associated with favorable clinical outcomes. Furthermore, we integrated and divided the gene association results from NAC response and survival outcomes into four quadrants, which provided more insights into potential NAC response mechanisms and biomarker discovery.
| File | Description |
|---|---|
| code/preprocessing | Preprocessing of all the data used in the analysis |
| code/meta_analysis | Logistic regression/Cox regression and Meta analysis |
| code/pathway_analysis | ORA analysis |
| code/utility | Functions used for analysis |
Install all the R packages from the code/utility/utility_function.R file.