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Updated: Oct 18, 2025
Studying Triple Negative Breast Cancer Using Orthotopic Breast Cancer Model
Published on: March 20, 2020
Gene Dosage Analysis on the Single-Cell Transcriptomes Linking Cotranslational Protein Targeting to Metastatic
1The School of Public Health, Institute for Chemical Carcinogenesis, Guangzhou Medical University, Guangzhou 511436, China.
Abstract:
Many recent efforts have been put into the association between expression heterogeneity and different cell types and states using single-cell RNA transcriptome analysis. There is only limited understanding of gene dosage effects for the genetic heterogeneity at the single-cell level. By focusing on concordant copy number variation (CNV) and expression, we presented a computational framework to explore dosage effect for aggressive metastatic triple-negative breast cancer (TNBC) at the single-cell level. In practice, we collected CNV and single-cell expression data from the same patients with independent technologies. By focusing on 47,198 consistent copy number gains (CNG) and gene up-regulation from 1145 single cells, ribosome proteins with important roles in protein targeting were enriched. Independent validation in another metastatic TNBC dataset further prioritized signal recognition particle-dependent protein targeting as the top functional module. More interesting, the increased ribosome gene copies in TNBC may associate with their enhanced stemness and metastatic potential. Indeed, the prioritization of a well-upregulated functional module confirmed by high copy numbers at the single-cell level and contributing to patient survival may indicate the possibility of targeted therapy based on ribosome proteins for TNBC.
Insights
This study reveals how copy number gains in genes, particularly those for ribosome proteins, drive aggressive triple-negative breast cancer (TNBC) stemness and metastasis. These findings suggest ribosome proteins as potential therapeutic targets for TNBC.
Area of Science:
- Genomics
- Molecular Biology
- Cancer Research
Background:
- Single-cell RNA transcriptome analysis is crucial for understanding expression heterogeneity.
- Gene dosage effects in genetic heterogeneity at the single-cell level remain poorly understood.
- Triple-negative breast cancer (TNBC) is an aggressive malignancy with limited therapeutic options.
Purpose of the Study:
- To develop a computational framework for exploring gene dosage effects in aggressive metastatic TNBC at the single-cell level.
- To investigate the association between copy number variation (CNV) and gene expression in TNBC.
- To identify potential therapeutic targets based on single-cell genomic and transcriptomic data.
Main Methods:
- Collected matched CNV and single-cell expression data from TNBC patients using independent technologies.
- Developed a computational framework to analyze concordant copy number gains (CNG) and gene up-regulation.
- Focused on 47,198 consistent CNGs and gene up-regulation events across 1145 single cells.
- Performed independent validation in another metastatic TNBC dataset.
Main Results:
- Enriched ribosome proteins, crucial for protein targeting, were identified among genes with CNV and up-regulation.
- Signal recognition particle-dependent protein targeting emerged as a top functional module upon independent validation.
- Increased ribosome gene copies in TNBC single cells correlated with enhanced stemness and metastatic potential.
- A well-upregulated functional module, confirmed by high copy numbers, was linked to patient survival.
Conclusions:
- Gene dosage effects, particularly involving ribosome proteins, play a significant role in TNBC pathogenesis.
- Ribosome proteins and associated pathways represent promising targets for novel TNBC therapies.
- The computational framework provides a novel approach to study gene dosage in single-cell cancer genomics.
