Abstract
Abstract Liquid biopsy provides opportunities to guide therapy decisions using biomarkers such as circulating tumor cells (CTCs) even years after the primary tumor resection. For this, novel methods permitting the genomic profiling of CTCs are needed to characterize systemic cancer spread and identify clinically targetable genomic alterations. Hence, we developed an assay based on the FDA-approved MSK-IMPACT® assay to analyze the genomes of single-cells. We present a series of benchmarking experiments using well-characterized cell lines to demonstrate the performance of our new Single-Cell Integrated Mutation Profiling of Actionable Cancer Targets (scIMPACT) assay.The scIMPACT assay was developed using Ampli1® WGA products of single-cell and pool samples. The workflow consists of an optimized library preparation protocol followed by targeted sequencing with the scIMPACT panel. A bioinformatics mutation calling workflow facilitates the detection of single nucleotide variations (SNVs), indels, and copy number variations (CNVs). To account for WGA associated bias, we developed an in-house proprietary machine learning based classifier algorithm. Two sample collectives were prepared and used for training and validating the workflow. The first collective, including genomic libraries of MDA-MB-453, BT474, BT549 and ZR-75.1 samples, was used for training of the mutation detection workflow. The second collective, consisting of HCC1395/HCC1395BL cell lines representing matched tumor and normal cells, was used to validate the performance of the assay. The scIMPACT assay identified somatic mutations in all WGA products as predicted from bulk gDNA samples and published literature. Notably, evidence of genetic heterogeneity was reported at the single cell level. Pertaining to the SNV detection, the training collective displayed 91% sensitivity and 96% specificity (AUC=0.98) while the validation collective demonstrated similar performance with 84% sensitivity and 96% specificity (AUC=0.90) proving the applicability of our workflow across different datasets. Furthermore, CNV analysis showed high concordance between matching gDNA and WGA samples. Our workflow enables mutational profiling with high specificity and sensitivity and accurate CNV detection in single cells. The scIMPACT assay has been successfully adapted to analyze samples at the single-cell level. Therefore, our method can be applied for the genomic profiling of patient-derived CTCs. Citation Format: Clara Chaiban, Adithi Ravikumar Varadarajan, Jonas Grote, Thomas Ragg, Isabell Blochberger, Vadim Dechand, Jens Warfsmann, Christoph A. Klein, Zbigniew T. Czyż. Genomic profiling of single cancer cells using the novel single-cell integrated mutational profiling of actionable cancer targets (scIMPACT) assay [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2024; Part 1 (Regular Abstracts); 2024 Apr 5-10; San Diego, CA. Philadelphia (PA): AACR; Cancer Res 2024;84(6_Suppl):Abstract nr 3694.
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Disclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.