Ovarian Cancer Detection Using Photoacoustic Flow Cytometry

Lusk, Joel F.; Miranda, Christopher; Smith, Barbara

doi:10.3791/60279

Cited by 3 publications

(1 citation statement)

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“…A variety of recently developed probes and endogenous markers will facilitate broadened applications of FC. By utilizing folic acid-capped copper sulfide nanoparticles (FA-CuS NPs) to target SKOV-3 ovarian cancer cells, Lusk et al showed the potential of PAFC to detect ovarian CTCs at physiologically relevant concentrations [127]. The formation of nanoparticle aggregates and the uptake of nanoparticles by cells can be monitored by analyzing the peak signals of IVFC [128].…”

Section: Toward Multimodal and Multifunctional Imagingmentioning

confidence: 99%

Advanced flow cytometry for biomedical applications

Pang

Dong

Zhu

et al. 2023

Journal of Biophotonics

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Flow cytometry (FC) is a versatile tool with excellent capabilities to detect and measure multiple characteristics of a population of cells or particles. Notable advancements in in vivo photoacoustic FC, coherent Raman FC, microfluidic FC, and so on, have been achieved in the last two decades, which endows FC with new functions and expands its applications in basic research and clinical practice. Advanced FC broadens the tools available to researchers to conduct research involving cancer detection, microbiology (COVID‐19, HIV, bacteria, etc.), and nucleic acid analysis. This review presents an overall picture of advanced flow cytometers and provides not only a clear understanding of their mechanisms but also new insights into their practical applications. We identify the latest trends in this area and aim to raise awareness of advanced techniques of FC. We hope this review expands the applications of FC and accelerates its clinical translation.

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Section: Toward Multimodal and Multifunctional Imagingmentioning

confidence: 99%

Advanced flow cytometry for biomedical applications

Pang

Dong

Zhu

et al. 2023

Journal of Biophotonics

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High-throughput single-cell analysis of nanoparticle-cell interactions

Haddad

Frickenstein

Wilhelm

2023

TrAC Trends in Analytical Chemistry

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In vivo dynamic monitoring of circulating melanoma cells and the inhibitory effect of PD-L1 inhibitor based on PAFC equipped with a deep learning framework

Pang,

Song,

Liu

et al. 2024

APL Photonics

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Melanoma is a highly metastatic and lethal skin tumor originating from melanocyte malignancy. Circulating tumor cells (CTCs) are key endogenous biomarkers in melanoma metastasis. Melanin and blood vessels exhibit substantial disparities in their absorbance profiles at select wavelengths, a characteristic that can be adeptly harnessed to differentiate the photoacoustic signals they generate. Photoacoustic flow cytometry (PAFC), which harnesses this principle, enables the monitoring of CTC flowing in vivo. However, this technique is constrained by the inefficiency and high false positive rates associated with traditional algorithms, including the Pauta criterion. In this study, a PAFC system is developed to identify dynamic features of flowing CTCs and the inhibitory effects of PD-L1 inhibitors, using a one-dimensional convolutional neural network (1D-CNN) and a long short-term memory (LSTM) network. The 1D-CNN achieves a balance between classification accuracy and speed. Meanwhile, the LSTM exhibits superior specificity but limited sensitivity. By combining the advantages of the two networks, the inhibitory effect of PD-L1 inhibitors that reduce the CTCs in the blood and block metastasis to other organs of melanoma mouse models are studied noninvasively in vivo and validated in vitro. The PAFC equipped with the deep learning framework provides a more timely and efficient assessment of PD-L1 inhibitors compared to conventional pathological methods, significantly enhancing the melanoma diagnosis and treatment monitoring. This technology demonstrates potential as a significant tool for the non-invasive, dynamic evaluation of melanoma progression and response to immunotherapy.

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Ovarian Cancer Detection Using Photoacoustic Flow Cytometry

Cited by 3 publications

References 0 publications

Advanced flow cytometry for biomedical applications

Advanced flow cytometry for biomedical applications

High-throughput single-cell analysis of nanoparticle-cell interactions

In vivo dynamic monitoring of circulating melanoma cells and the inhibitory effect of PD-L1 inhibitor based on PAFC equipped with a deep learning framework

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