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Detection of Copy Number Alterations Using Single Cell Sequencing
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Cracking the pattern of tumor evolution based on single-cell copy number alterations.

Ying Wang1, Min Zhang2, Jian Shi3

  • 1Guangdong Cardiovascular Institute，Guangdong Provincial People's Hospital，Guangdong Academy of Medical Sciences and Medical Research Institute, Guangdong Provincial People's Hospital (Guangdong Academy of Medical Sciences), Southern Medical University.

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Copy number alterations drive tumor evolution. A new method reveals punctuated evolution dominates breast cancer, offering insights for targeted therapies.

Keywords:
copy number alterationscDNA-seqscRNA-seqsingle-celltumor evolutionary pattern

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Area of Science:

  • Genomics
  • Cancer Biology
  • Evolutionary Biology

Background:

  • Copy number alterations (CNAs) are fundamental drivers of tumor development and evolution.
  • Intra-tumor heterogeneity, arising from distinct CNAs, influences treatment response and necessitates understanding tumor evolution.
  • Single-cell sequencing technologies now allow for high-resolution analysis of CNAs within tumor cell populations.

Purpose of the Study:

  • To develop and validate a statistical approach for distinguishing neutral, linear, branching, and punctuated evolutionary patterns from single-cell copy number profiles.
  • To investigate the predominant evolutionary patterns in breast cancer and other cancer types using single-cell data.
  • To explore the relationship between tumor evolutionary patterns and immune cell infiltration.

Main Methods:

  • A novel two-step statistical method was developed to classify tumor evolutionary patterns based on single-cell copy number profiles.
  • The approach was validated using simulated and real single-cell genomic and transcriptomic datasets.
  • The method was applied to single-cell DNA sequencing data from 20 breast cancer patients and single-cell RNA sequencing data from 132 cancer patients.

Main Results:

  • The proposed statistical approach demonstrated high accuracy and robustness in predicting tumor evolutionary patterns.
  • Punctuated evolution was identified as the dominant evolutionary pattern in breast cancer.
  • Similar conclusions regarding punctuated evolution were observed across a broader range of cancer types analyzed via single-cell RNA sequencing.
  • Differential immune cell infiltration was found to be associated with specific tumor evolutionary patterns.

Conclusions:

  • The developed statistical method effectively characterizes tumor evolutionary dynamics at the single-cell level.
  • Punctuated evolution is a prevalent mode of tumor progression across various cancers, including breast cancer.
  • Understanding these evolutionary patterns may inform the development of more effective cancer therapies and highlight the role of the tumor microenvironment.