Analytical validation of the CellMax platform for early detection of cancer by enumeration of rare circulating tumor cells

通过计数稀有循环肿瘤细胞对 CellMax 平台进行癌症早期检测的分析验证

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作者:Pratyush Gupta, Zulfiqar Gulzar, Ben Hsieh, Austin Lim, Drew Watson, Rui Mei

Abstract

The CellMax (CMx®) platform was developed to enrich for epithelial circulating tumor cells (CTCs) in the whole blood. This report provides assay performance data, including accuracy, linearity, limit of blank, limit of detection (LOD), specificity, and precision of enumeration of cancer cell line cells (CLCs) spiked in cell culture medium or healthy donor blood samples. Additionally, assay specificity was demonstrated in 32 young healthy donors and clinical feasibility was demonstrated in a cohort of 47 subjects consisting of healthy donors and patients who were colonoscopy verified to have colorectal cancer, adenomas, or a negative result. The CMx platform demonstrated high accuracy, linearity, and sensitivity for the enumeration of all CLC concentrations tested, including the extremely low range of 1 to 10 cells in 2 mL of blood, which is most relevant for early cancer detection. Theoretically, the assay LOD is 0.71 CTCs in 2 mL of blood. The analytical specificity was 100% demonstrated using 32 young healthy donor samples. We also demonstrated precision across multiple days and multiple operators, with good reproducibility of recovery efficiency. In a clinical feasibility study, the CMx platform identified 8 of 10 diseased subjects as positive (80% clinical sensitivity) and 4 of 5 controls as negative (80% clinical specificity). We also compared processing time and transportation effects for similar blood samples from two different sites and assessed an artificial intelligence-based counting method. Finally, unlike other platforms for which captured CTCs are retained on ferromagnetic beads or tethered to the slide surface, the CMx platform's unique airfoam-enabled release of CTCs allows captured cells to be transferred from a microfluidic chip to an Eppendorf tube, enabling a seamless transition to downstream applications such as genetic analyses and live cell manipulations.

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