Circulating tumor cell clusters (CTCCs) are extremely rare events (<4 events per 7.5 mL of blood) found in the bloodstream of metastatic cancer patients. Despite their scarcity, they represent an increased risk for metastasis. Detection and isolation of CTCCs remain a priority for oncologists to improve cancer patients' diagnosis, stratification, and treatment. This study aims to demonstrate that confocal backscatter and fluorescence flow cytometry (BSFC) with deep learning-based signal analysis can enable sensitive detection of CTCCs in whole blood in vitro and in vivo without using exogenous labeling.
KEYWORDS: Tumors, Confocal microscopy, Luminescence, Flow cytometry, Signal to noise ratio, In vitro testing, Blood, Sensors, Signal detection, Scattering
Rare circulating tumor cells (CTCs) and circulating tumor cells clusters (CTCCs) have been shown to increase the metastatic potential of tumors, with CTCCs increasing metastatic potential by 23 to 50 times. Due to the high metastatic potential of CTCCs, there is a growing interest in the detection and isolation of these clusters to improve diagnosis, stratification, and treatment of cancer patients. This study aims to utilize a custom confocal back scatter and fluorescence flow cytometer (CBSFFC) that will leverage the high sensitivity of flow cytometers for in vitro and in vivo detection of CTCCs without the use of exogenous contrast agents.
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