Complete PS:

Finding Potential Biomarkers for TNBC by Utilising Single-cell/Bulk RNA-seq Omics to Stratify High-Risk Patients

Research Gap:

Unlike ER- or PR-positive and HER2 subtypes, which have specific targets for therapy, TNBC lacks distinctive molecular markers, and no targeted drugs are currently available. While checkpoint inhibition has recently been approved for early-stage TNBC, NAC remains the backbone of systemic treatment. Nonetheless, not all TNBC patients benefit from NAC, underscoring the importance of distinguishing responders from non-responders.

Another major point is to validate markers to stratify patients. Recently, Lan Wei found a panel of markers, but owing to limitations in further validation, additional validation of the EFRSs prognostic model in larger TNBC cohorts is warranted.

Project: Reanalyse publicly available single-cell databases and integrate them to create a single-cell atlas for TNBC patients. Demonstrate that signature markers from your analysis for TNBC are replicable in different available datasets. Create a panel of genes that also shows a correlation with stages of TNBC.

Quick Start:

1.  Seurat:

2.  TNBC Datasets:

3.  Hands-on Tutorial

4.  Other Important Links

What You Will Learn:

• You will learn to integrate publicly available single-cell databases to create a unified atlas for TNBC patients.
• You will demonstrate that specific signature markers can be successfully replicated across multiple datasets.
• You will create a targeted gene panel that shows a clear correlation with the different stages of TNBC.
• You will acquire the skills to replicate published findings and curate markers from existing research papers.