Label-free flow cytometry of rare circulating tumor cell clusters in whole blood

Deep learning-enabled detection of rare circulating tumor cell clusters in whole blood using label-free, flow cytometry

Metastatic tumors have poor prognoses for progression-free and overall survival for all cancer patients. Rare circulating tumor cells (CTCs) and rarer circulating tumor cell clusters (CTCCs) are potential biomarkers of metastatic growth, with CTCCs representing an increased risk factor for metastasis. Current detection platforms are optimized for ex vivo detection of CTCs only. Microfluidic chips and size exclusion methods have been proposed for CTCC detection; however, they lack in vivo utility and real-time monitoring capability. Confocal backscatter and fluorescence flow cytometry (BSFC) has been used for label-free detection of CTCCs in whole blood based on machine learning (ML) enabled peak classification. Here, we expand to a deep-learning (DL)-based, peak detection and classification model to detect CTCCs in whole blood data. We demonstrate that DL-based BSFC has a low false alarm rate of 0.78 events per min with a high Pearson correlation coefficient of 0.943 between detected events and expected events. DL-based BSFC of whole blood maintains a detection purity of 72% and a sensitivity of 35.3% for both homotypic and heterotypic CTCCs starting at a minimum size of two cells. We also demonstrate through artificial spiking studies that DL-based BSFC is sensitive to changes in the number of CTCCs present in the samples and does not add variability in detection beyond the expected variability from Poisson statistics. The performance established by DL-based BSFC motivates its use for in vivo detection of CTCCs. Using transfer learning, we additionally validate DL-based BSFC on blood samples from different species and cancer cell types. Further developments of label-free BSFC to enhance throughput could lead to critical applications in the clinical detection of CTCCs and ex vivo isolation of CTCC from whole blood with minimal disruption and processing steps.

A review of innovative electrochemical strategies for bioactive molecule detection and cell imaging: Current advances and challenges

Cellular heterogeneity poses a major challenge for tumor theranostics, requiring high-resolution intercellular bioanalysis strategies. Over the past decades, the advantages of electrochemical analysis, such as high sensitivity, good spatio-temporal resolution, and ease of use, have made it the preferred method to uncover cellular differences. To inspire more creative research, herein, we highlight seminal works in electrochemical techniques for biomolecule analysis and bioimaging. Specifically, micro/nano-electrode-based electrochemical techniques enable real-time quantitative analysis of electroactive substances relevant to life processes in the micro-nanostructure of cells and tissues. Nanopore-based technique plays a vital role in biosensing by utilizing nanoscale pores to achieve high-precision detection and analysis of biomolecules with exceptional sensitivity and single-molecule resolution. Electrochemiluminescence (ECL) technology is utilized for real-time monitoring of the behavior and features of individual cancer cells, enabling observation of their dynamic processes due to its capability of providing high-resolution and highly sensitive bioimaging of cells. Particularly, scanning electrochemical microscopy (SECM) and scanning ion conductance microscopy (SICM) which are widely used in real-time observation of cell surface biological processes and three-dimensional imaging of micro-nano structures, such as metabolic activity, ion channel activity, and cell morphology are introduced in this review. Furthermore, the expansion of the scope of cellular electrochemistry research by innovative functionalized electrodes and electrochemical imaging models and strategies to address future challenges and potential applications is also discussed in this review.

Effect of pulsed laser parameters on photoacoustic flow cytometry efficiency in vitro and in vivo

Photoacoustic flow cytometry is one of the most effective approaches to detect "alien" objects in the bloodstream, including circulating tumor cells, blood clots, parasites, and emboli. However, the possibility of detecting high-amplitude signals from these objects against the background of blood depends on the parameters of the laser pulse. So, the dependencies of photoacoustic signals amplitude and number on laser pulse energy (5-150 μJ), pulse length (1, 2, 5 ns), and pulse repetition rate (2, 5, 10 kHz) for the melanoma cells were investigated. First, the PA responses of a melanoma cell suspension in vitro were measured to directly assess the efficiency of converting laser light into an acoustic signal. After it, the same dependence with the developed murine model based on constant rate melanoma cell injection into the animal blood flow was tested. Both in vivo and in vitro experiments show that signal generation efficiency increases with laser pulse energy above 15 μJ. Shorter pulses, especially 1 ns, provide more efficient signal generation as well as higher pulse rates. A higher pulse rate also provides more efficient signal generation, but also leads to overheating of the skin. The results show the limits where the photoacoustic flow cytometry system can be effectively used for the detection of circulating tumor cells in undiluted blood both for in vitro experiments and for in vivo murine models.