Abstract A060: Characterizing aneuploid tumor heterogeneity in prostate cancer through single-cell DNA sequencing

Abstract Genomic instability is a hallmark of cancer and contributes to disease progression through various mechanisms. DNA copy number variation (CNV) is one of the most significant consequences causing a phenomenon called aneuploidy. Aneuploidy is characterized by an imbalanced genome and is associated with lethal progression in prostate cancer. Currently, sequencing-based CNV analysis is widely used to identify cancer-specific aneuploidy that contribute to tumorigenesis, immune evasion, and disease progression. Performing low-pass whole genome sequencing (LP-WGS) on DNA extracted from bulk tissues or cell cultures, is a convenient approach to use for detecting aneuploidy and focal CNVs. However, conventional bulk LP-WGS methods average genomic signals across thousands of cells, often overlooking tumor heterogeneity and small populations with distinct CNV patterns. To address this limitation, we optimized a microfluid nanowell-based system to analyze aneuploidy patterns at a single-cell level using disassociated tissues and isolated nuclei from prostate samples. This pipeline is compatible with both preclinical models and clinical specimens and can be integrated with other multi-omics platforms to generate multimodal datasets for basic and translational research. By leveraging high-throughput single-cell sequencing technologies, our approach enables direct DNA CNV measurement with high sensitivity at a single-cell resolution. Ultimately, this approach aims to improve the resolution of CNV detection, enhance molecular stratification and enable multimodal data integration for better understanding of clinical prostate cancer samples. Citation Format: Chloe Springer, Faith Kim, Kathryn Echandía-Monroe, Aditi Shirke, Gustavo Guitierrez-Cruz, Madeline Wong, Kun-Lin Ho, Duanduan Ma, Elise G. DeArment, Amina Ali, William D. Figg, Gregory Chesnut, Matthew G. Vander Heiden, Xiaofeng A. Su. Characterizing aneuploid tumor heterogeneity in prostate cancer through single-cell DNA sequencing [abstract]. In: Proceedings of the AACR Special Conference in Cancer Research: Innovations in Prostate Cancer Research and Treatment; 2026 Jan 20-22; Philadelphia PA. Philadelphia (PA): AACR; Cancer Res 2026;86(2_Suppl):Abstract nr A060.

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Journal
Cancer Research
Published
2026-01-20
DOI
https://doi.org/10.1158/1538-7445.prostateca26-a060
Primary Topic
Cancer Genomics and Diagnostics
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article
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article

Abstract A060: Characterizing aneuploid tumor heterogeneity in prostate cancer through single-cell DNA sequencing

Aditi Shirke, Xiaofeng A. Su, Kun-Lin Ho, Elise DeArment et al.
Cancer Research
Cancer Genomics and Diagnostics
article

Abstract A060: Characterizing aneuploid tumor heterogeneity in prostate cancer through single-cell DNA sequencing

Aditi Shirke, Xiaofeng A. Su, Kun-Lin Ho, Elise DeArment, Madeline Wong, Gregory T. Chesnut, Amina Yusuf Ali, Kathryn Echandia-Monroe, Chloe Springer, Gustavo Guitierrez-Cruz, Matthew G. Vander Heiden, Faith Kim, William D. Figg, Duanduan Ma
article en

Abstract

Abstract Genomic instability is a hallmark of cancer and contributes to disease progression through various mechanisms. DNA copy number variation (CNV) is one of the most significant consequences causing a phenomenon called aneuploidy. Aneuploidy is characterized by an imbalanced genome and is associated with lethal progression in prostate cancer. Currently, sequencing-based CNV analysis is widely used to identify cancer-specific aneuploidy that contribute to tumorigenesis, immune evasion, and disease progression. Performing low-pass whole genome sequencing (LP-WGS) on DNA extracted from bulk tissues or cell cultures, is a convenient approach to use for detecting aneuploidy and focal CNVs. However, conventional bulk LP-WGS methods average genomic signals across thousands of cells, often overlooking tumor heterogeneity and small populations with distinct CNV patterns. To address this limitation, we optimized a microfluid nanowell-based system to analyze aneuploidy patterns at a single-cell level using disassociated tissues and isolated nuclei from prostate samples. This pipeline is compatible with both preclinical models and clinical specimens and can be integrated with other multi-omics platforms to generate multimodal datasets for basic and translational research. By leveraging high-throughput single-cell sequencing technologies, our approach enables direct DNA CNV measurement with high sensitivity at a single-cell resolution. Ultimately, this approach aims to improve the resolution of CNV detection, enhance molecular stratification and enable multimodal data integration for better understanding of clinical prostate cancer samples. Citation Format: Chloe Springer, Faith Kim, Kathryn Echandía-Monroe, Aditi Shirke, Gustavo Guitierrez-Cruz, Madeline Wong, Kun-Lin Ho, Duanduan Ma, Elise G. DeArment, Amina Ali, William D. Figg, Gregory Chesnut, Matthew G. Vander Heiden, Xiaofeng A. Su. Characterizing aneuploid tumor heterogeneity in prostate cancer through single-cell DNA sequencing [abstract]. In: Proceedings of the AACR Special Conference in Cancer Research: Innovations in Prostate Cancer Research and Treatment; 2026 Jan 20-22; Philadelphia PA. Philadelphia (PA): AACR; Cancer Res 2026;86(2_Suppl):Abstract nr A060.

Cancer ResearchVol. 86(2_Supplement)
National Institutes of Health (US), Uniformed Services University of the Health Sciences (US), National Institute of Arthritis and Musculoskeletal and Skin Diseases (US), National Cancer Institute (US), Massachusetts Institute of Technology (US)
Good health and well-being
Openalex Percentile: Top 83%
Cancer Genomics and Diagnostics
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