Integrating single-cell transcriptomics and whole-genome CRISPR CAS9 screen identifies a cell cluster associated with tumor dependency in triple-negative breast cancer
Su Liu, Shuo Wang, Guixin Wang, Yingxi Li, Zhigang Zhao, Yao Tian, Junming Cao

TL;DR
This study identifies four genes linked to tumor dependency in triple-negative breast cancer, offering new biomarkers and treatment strategies.
Contribution
The integration of single-cell transcriptomics and CRISPR screens reveals a cell cluster associated with tumor dependency in TNBC.
Findings
Four tumor dependency genes were identified, highly expressed in TNBC and linked to poor prognosis.
The tumor dependency-associated subpopulation is associated with energy metabolism and cell proliferation pathways.
Patients with high TDAS infiltration may benefit from combined radiotherapy or chemotherapy rather than surgery alone.
Abstract
Triple-negative breast cancer (TNBC) is the most aggressive breast cancer subtype; however, clinically approved prognostic biomarkers and therapeutic options remain limited. This study aimed to investigate tumor dependency genes to identify novel therapeutic targets for TNBC. Tumor dependency genes for TNBC were identified using the The Cancer Dependency Map (DEPMAP) database. The TCGA-BRCA dataset was utilized to analyze the expression, survival associations, and pathway enrichment of these genes. Single-cell datasets were employed to explore cellular trajectories and biological functions within tumor dependency gene-associated cell subpopulations. Genomic sequencing was used to investigate the somatic mutational landscape influencing the infiltration abundance of the tumor dependency-associated subpopulation. The METABRIC dataset assessed the impact of the tumor dependency-associated…
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Taxonomy
TopicsSingle-cell and spatial transcriptomics · Cancer Genomics and Diagnostics · CRISPR and Genetic Engineering
