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Uncovering the Origins of Breast Cancer: Insights from Healthy Cells Powered by Single Cell Genomics

   28/03/2025

   Cécile Thion, PhD

   8-minute read

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Breast cancer is the most common cancer among women worldwide, with an estimated 2.3 million new cases diagnosed in 2024 alone. In the United States, approximately 1 in 8 women will develop breast cancer in their lifetime. Early detection and advances in treatment have significantly improved survival rates, with a 5-year relative survival rate of 99% for localized breast cancer. However, breast cancer remains the second leading cause of cancer death among women, underscoring the need for continued research and innovation in this field. Single-cell sequencing, i.e., mainly single cell genomics and single cell transcriptomics have revolutionized cancer research by enabling detailed analyses of individual cells.  

 

How single cell sequencing brings insights into cancer development

Single cell sequencing technologies allow researchers to identify genetic and transcriptomic variations that drive cancer development and progression. Recent research has shed light on the early genetic origins of breast cancer, revealing that cancer-like mutations can occur in the cells of healthy women. This groundbreaking study, conducted by an international team of researchers from the University of British Columbia (UBC), BC Cancer, Harvard Medical School, and Memorial Sloan Kettering Cancer Center, using cellenONE, provides new insights into how breast cancer may develop from seemingly normal cells.

In this new article, Aparicio et al (2024) analyzed the genomes of over 48,000 individual breast cells from women without cancer, using advanced single-cell whole genome sequencing technology. The study involved sampling breast cells from 50 healthy women, with each woman providing multiple samples from different regions of the breast. The researchers collected both ductal and lobular cells to ensure a comprehensive analysis of the breast tissue.   

The researchers discovered that nearly all women harbored a small number of breast cells—about 3%—carrying genetic alterations commonly associated with cancer. These findings suggest that these rare genetic anomalies may represent some of the earliest steps in the development of breast cancer. The mutations identified in the study are known as copy number alterations (CNAs), which involve the duplication or loss of large segments of DNA. While the body’s natural DNA repair mechanisms usually fix these anomalies, failures in detection or repair can lead to the accumulation of mutations over time, potentially resulting in cancer. Aparicio et al. found that CNAs were specifically detected in the luminal cells that line the lobules and ducts of the breast, where milk flows. These cells are believed to be the origin of all major types of breast cancer. The accumulation of genetic alterations in luminal cells supports the hypothesis that these changes may prime or predispose these cells to cancer development. 

 

DLP+: a massively parallel single cell genomics workflow

The researchers utilized the DLP+ method, enabled by cellenONE technology, to conduct their study. This method involves image-based and precise single-cell isolation into reagent-preloaded high density nanowell substrates. The instrument allows miniaturized single cell sequencing library prep for amplification-free single cell whole-genome sequencing. DLP+ method, described in detail by Zahn et al. (2017) and Laks et al. (2019), provides greater coverage uniformity and better detection of CNAs compared to other methods. In DLP+, each isolated cell undergoes lysis to release its DNA, followed by direct library preparation (DLP) without the need for preamplification. This minimizes genomics amplification biases and ensures uniform coverage. These original articles by Zahn et al. and Laks et al. has been cited over 450 times, reflecting their significant impact on the field of single-cell genomics. Since 2019, DLP+ has been implemented at BC Cancer for sequencing more than 400,000 genomes from patient sample single cells (Salehi et al. 2021, Funnel et al. 2022, Kabheer et al. 2024).

 

Implications for Prevention and Early Detection

Understanding how these cancer-like mutations arise and accumulate could lead to new preventive strategies, therapeutic approaches, and early detection methods. The study’s findings highlight the importance of further research into the genetic origins of breast cancer to develop lifesaving interventions. This research marks a significant step forward in our understanding of breast cancer’s origins.   

 

Read our Application Note on DLP+

How cellenONE Contributed to This Success Story

This groundbreaking study, marking a significant milestone in cancer research, was made possible thanks to the advanced capabilities of the cellenONE platform. 

  • Precision and Accuracy: High accuracy in single-cell isolation and precision microdispensing into high density nanowell substrates. 
  • Versatility: Handles a wide range of cell types (whole cells and nuclei) and sample (patient fine-needle aspirate and flash frozen tissues, xenograph-derived cells and cell lines), ensuring high recovery rates. 
  • High Throughput: Isolates 96 single cells in less than 3 minutes, accelerating research processes. 
  • Image-Based Selection: Selects cells based on morphology and fluorescence markers.  
  • Miniaturized Library Prep: pL and nL liquid dispensing ability allows for efficient and cost-effective experiments, incl. single-cell sequencing library prep. 
  • Environmental Controls: Maintains optimal temperature and humidity conditions during single cell isolation.
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References

  • University of British Columbia. (2024). Cancer-like mutations in healthy cells point to origins of breast cancer. Retrieved from UBC Faculty of Medicine.  
  • Aparicio, S., et al. (2024). Copy number alterations in normal breast tissue and their role in cancer development. Nature Genetics. doi: 10.1038/s41588-024-01988-0.  
  • Zahn, H., et al. (2017). Scalable whole-genome single-cell library preparation without preamplification. Nature Methods, 14(2), 167. doi: 10.1038/nmeth.4140.   
  • Laks, E., et al. (2019). Clonal decomposition and DNA replication states defined by scaled single-cell genome sequencing. Cell, 179(5), 1207-1221.e22. doi: 10.1016/j.cell.2019.10.026.  
  • Salehi, S., et al. (2021). Clonal fitness inferred from time-series modelling of single-cell cancer genomes. Nature, 595(7868), 585-590. 
  • Funnell, T., et al. (2022). Single-cell genomic variation induced by mutational processes in cancer.” Nature 612.7938, 106-115. 
  • Kabeer, F, et al. (2024). Single-cell decoding of drug induced transcriptomic reprogramming in triple negative breast cancers. Genome Biology 25.1 (2024), 191. 
  • Centers for Disease Control and Prevention (CDC). (2025). Breast Cancer Statistics.  
  • National Breast Cancer Foundation (NBCF). (2025). Breast Cancer Facts & Stats.  

 

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