Turky AlSulaiman

تخصص المعلوماتية الحيوية · دفعة 2026

Investigating Candidate Marker Genes Across Breast Cancer Subtypes

This project investigates candidate marker genes associated with molecular subtypes of breast cancer using single-cell RNA sequencing and independent bulk transcriptomic data. Single-cell RNA-seq data from ER+, HER2+, and triple-negative breast cancer samples were processed using Seurat for quality control, normalization, dimensionality reduction, clustering, and UMAP visualization. Harmony was used for batch correction, while silhouette analysis was applied to evaluate clustering parameters and identify an appropriate resolution. Cell populations were annotated using SingleR, followed by identification of the tumour-associated macrophage (TAM) population based on clustering and expression of macrophage markers including CD14 and CD68. TAMs were then analyzed using a sample-level pseudo-bulk approach, with raw counts aggregated by patient sample and differential expression performed using DESeq2 to identify genes associated with differences between breast cancer subtypes. S100A9 was subsequently selected as a candidate gene for further investigation. Its expression was evaluated in the independent METABRIC breast cancer cohort using R, with statistical analyses examining differences across ER+, HER2+, and triple-negative tumours as well as associations with lymph-node involvement. Overall, the project combines single-cell transcriptomics, pseudo-bulk differential expression, cell-type annotation, and independent cohort analysis to identify and characterize candidate genes that may contribute to the molecular heterogeneity of breast cancer and warrant further investigation for their potential clinical relevance.

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