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Get Free AccessAbstract The genomic profiling of circulating tumor cells (CTCs) in the bloodstream should provide clinically relevant information on therapeutic efficacy and help predict cancer survival. However, the molecular characterization of CTCs has so far proven extremely difficult. A variety of technologies have been developed for CTC isolation, but so far the impact on the genomic assessment of CTCs has not been fully evaluated. To fill this gap, here we contrasted the genomic profiles of CTC pools recovered from blood samples obtained from four metastatic colorectal cancer (mCRC) patients using three different enrichment strategies (CellSearch, Parsortix, and FACS). Our results suggest clear differences in the mutational burden of CTC pools depending on the enrichment method used, with all evaluated methods returning a somewhat limited representation of the mutational spectrum of individual tumors, potentially due to allelic dropout during whole-genome amplification. Nevertheless, the CTC pools from Parsortix, and in part, CellSearch, showed diversity estimates, mutational signatures and drug-suitability scores remarkably close to the ones found in matching primary tumor samples. In contrast, FACS CTC pools were substantially enriched in apparent sequencing artifacts, which led to much higher estimates of genomic diversity. Although CTC genomics still faces technical challenges, our results suggest that CTC-derived metrics can reflect the diversity scores seen in primary tumor lesions thus highlighting the utility of CTCs to assess the heterogeneity status of individual tumors, and to help clinicians prioritize drugs in mCRC.
João M. Alves, Nuria Estévez‐Gómez, Monica Valecha, Sonia Prado‐Lòpez, Laura Tomás, Pilar Alvariño, Roberto Piñeiro, Laura Muinelo‐Romay, Patricia Mondelo‐Macía, Mercedes Salgado, Agueda Iglesias‐Gómez, Laura Codesido, Joaquín Cubiella, David Posada (2022). Comparative analysis of capture methods for genomic profiling of circulating tumor cells in colorectal cancer. , DOI: https://doi.org/10.1101/2022.06.02.22275905.
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Type
Preprint
Year
2022
Authors
14
Datasets
0
Total Files
0
Language
en
DOI
https://doi.org/10.1101/2022.06.02.22275905
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