scDPN for High-throughput Single-cell CNV Detection to Uncover Clonal Evolution During HCC Recurrence

Area of Science:

• Genomics
• Cancer Research
• Molecular Biology

Background:

• Classical DNA amplification methods for single-cell genomics suffer from low throughput and amplification bias.
• Understanding cellular heterogeneity and cancer evolution requires advanced genomic profiling techniques.

Purpose of the Study:

• To develop and validate a novel single-cell DNA library preparation method without preamplification (scDPN).
• To assess the throughput, accuracy, and bias of scDPN compared to existing methods like multiple displacement amplification (MDA).
• To apply scDPN for profiling tumor clones in hepatocellular carcinoma (HCC) recurrence.

Main Methods:

• Development of a nanolitre-scale single-cell DNA library preparation method (scDPN) avoiding preamplification.
• Copy number variation (CNV) detection and evaluation of amplification bias and noise.
• Application of scDPN to paired primary and relapsed HCC tumor samples.

Main Results:

• scDPN achieved a throughput of up to 1800 cells per run for CNV detection.
• The method demonstrated lower amplification bias and noise than MDA, with high sensitivity and accuracy.
• Analysis of HCC samples revealed three clonal subpopulations and identified a minor clone from the primary tumor that became dominant in the recurrent tumor.

Conclusions:

• scDPN provides a scalable and comprehensive solution for dissecting genome heterogeneity and evolution at the single-cell level.
• The findings highlight clonal selection during HCC recurrence, offering insights into cancer progression.
• This method advances the field of single-cell genomics for cancer research.