Detection of Circulating Tumor Cell in Vivo:Technology and Application

Shan Guo; Xiang Zhou

doi:10.7536/PC200423

Progress in Chemistry ›› 2021, Vol. 33 ›› Issue (1) : 1-12 DOI: 10.7536/PC200423

Scan to read & Share

Detection of Circulating Tumor Cell in Vivo:Technology and Application

Shan Guo ¹^,²^,^*
, Xiang Zhou ²

Author information +

History +

PDF

Abstract

Cancer cells that shed from solid tumor and circulate into bloodstream, namely circulating tumor cells(CTCs), are closely related to tumor metastasis. Therefore, CTCs detection is of great significance for cancer diagnosis, treatment monitoring, disease assessment and understanding of the mechanisms underlying tumor metastasis. However, CTCs are extraordinarily rare, heterogeneous, nonuniform in blood. Even if strategies for detection of CTCs in static blood collected from patients have made significant progress, they still face the tumor cell loss, cell death, low fidelity, and low sensitivity. It is essential to develop approaches available for detection of tumor cells in fast-flowing blood, allowing real-time monitoring of CTC dynamic changes under physiological conditions. In this review, we summarize techniques developed for CTC detection in vivo and their related applications. Furthermore, the advantages and disadvantages of these techniques are analyzed. Finally, future techniques for detection of CTCs in vivo are discussed and predicted.

Contents

1 Introduction

2 Detection of circulating tumor cells(CTCs)in vivo

2.1 Optical imaging-based CTC detection in vivo

2.2 In vivo flow cytometry-based CTC enumeration

2.3 Scaffold implant-based CTC recruiting in vivo

2.4 Intravenous indwelling device-based CTC capture in vivo

2.5 Microfluidic chip-based CTC detection in vivo

3 Conclusion and outlook

Graphical abstract

Keywords

cancer / circulating tumor cells / in vivo detection

Cite this article

Download citation ▾

Shan Guo, Xiang Zhou. Detection of Circulating Tumor Cell in Vivo:Technology and Application. Progress in Chemistry, 2021, 33(1): 1-12 DOI:10.7536/PC200423

登录浏览全文

4963

注册一个新账户忘记密码

1 Introduction

The main cause of cancer-related death is the recurrence and metastasis of the tumor. As early as 1869, Ashworth, an Australian doctor, found tumor cells similar to autopsy in the blood of a cancer patient, and first proposed the concept of circulating tumor cells (CTCs)^[1]. CTCs are tumor cells that shed from a solid tumor, invade, and enter the circulatory system. In 1889, Paget put forward the "seed and soil hypothesis", pointing out that the organ microenvironment can affect the planting, invasion, survival and growth of specific tumor cells. After entering other organs, tumor cells in the blood can develop into new lesions, I. E. metastases, just like "seeds" meet "soil"^[2]. In 1997, Dick et al isolated some rare cells similar to stem cells from the blood of leukemia patients, and put forward and verified the theory of cancer stem cells for the first time^[3]. At present, many aspects of the mechanism of tumor metastasis have been elucidated. Specifically, prometastatic tumor cells undergo epithelial-mesenchymal transition (EMT) in epithelial lesions, resulting in decreased expression of epithelial markers such as EpCAM, CK and E-cadherin, and mesenchymal markers such as N-cadherin, vimentin and fibronectin Then it falls off from the solid tumor site, destroys and crosses the basement membrane, and enters the blood vessels or lymphatic vessels. In the circulatory system, CTCs escape the attack of the immune system by binding to platelets. Finally, CTCs adhere to new sites, spill out of blood vessels, undergo mesenchymal-epithelial transition (MET), proliferate in new sites, and form metastatic lesions^{[4⇓⇓⇓⇓⇓~10]}. Therefore, CTCs are closely related to tumor metastasis. The detection of CTCs is of great significance for the diagnosis and treatment of cancer and the study of the molecular mechanism of tumor metastasis.

Blood is composed of plasma and blood cells (including red blood cells, white blood cells and platelets). For an adult, the total amount of blood flowing through the body is about 5 L. The number of red blood cells per milliliter of blood is on the order of 10⁹, the number of white blood cells is on the order of 10⁶, and the number of platelets is 10⁸. However, the number of CTCs per milliliter of blood is below the 10³, the content is low, and the half-life of CTCs is short (within a few hours)^{[10⇓⇓⇓~14]}. In addition, CTCs are highly heterogeneous across individuals, across types of cancer, and within the same individual. Therefore, it is a great challenge to isolate CTCs with high specificity, sensitivity and throughput from a large number of background blood cells. To this end, researchers have developed a variety of technologies for CTCs capture, release, characterization and analysis, taking advantage of the advantages of chemistry, physics, biology, materials, medicine and interdisciplinary fields. As of December 2019, more than 23,000 papers can be retrieved from PubMed database with the keyword "circulating tumor cells", of which more than 3,600 are reviews. Since 2000, there have been more than 100 papers related to CTCs every year, and more than 300 papers per year in the past five years, which shows that the research related to CTCs has developed rapidly and achieved many research results.

CTCs detection technologies can be divided into two categories: in vivo and in vitro. There are three main steps in the in vitro detection of CTCs: (1) drawing blood samples to enrich and isolate tumor cells; (2) identifying the CTCs by immunofluorescence staining or fluorescence in situ hybridization (fluorescence in situ hybrid ization, FISH), and the like; and (3) observing and counting the CTCs under a fluorescence microscope. Compared with tissue biopsy by puncture and other surgical procedures, the detection of CTCs based on collected blood has the advantages of simple sampling, easy operation and non-invasive, and can be repeatedly sampled to dynamically monitor the number and phenotype of CTCs in patients. Based on the differences of physical properties (such as size, density, charge, deformability) and biological properties (mainly cell surface protein markers) between CTCs and blood cells, researchers have developed methods based on filter membrane, dielectrophoresis, micro-nano particles or substrates, microfluidic technology to achieve efficient separation of CTCs, with a sensitivity of 1-10 CTCs/mL^[15⇓~17]^[18⇓~20]^{[21⇓⇓⇓⇓⇓⇓⇓⇓~30]}^{[31⇓⇓⇓⇓⇓⇓⇓⇓⇓⇓⇓⇓⇓~45]}.

However, there are differences in the spatial and temporal distribution of CTCs in vivo^[11]. In time, CTCs can appear at any stage of tumor development. In the early stage of tumor development, the amount of CTCs in the blood is small, and as the tumor progresses, the number of CTCs in the blood increases. In space, due to the large size of CTCs and the receptor-ligand interaction between CTCs and blood vessels, CTCs may be retained in a certain part of blood vessels, resulting in different concentrations of CTCs in blood samples collected from different parts. Therefore, it is limited to collect blood from a specific part of the body at a certain time point for CTCs detection. In addition, when the number of CTCs in blood in vivo is less than 5000 (that is, less than 1 CTCs per milliliter of blood), it is difficult to capture CTCs from 1 mL of blood even if CTCs are uniformly distributed and the capture efficiency of in vitro detection technology is as high as 100%^[46]. The capture efficiency of CTCs in vitro detection techniques is typically the number of tumor cells captured divided by the number of tumor cells spiked into a fixed volume of blood (typically 1 to 10 mL). Moreover, the number of CTCs enriched and isolated from limited blood is small, and the process of transporting, storing, centrifuging and enriching and isolating CTCs in vitro after blood collection may cause cell contamination, loss, inactivation and distortion^[47].

In vivo detection of CTCs is an assay based on the development of rapid intravascular flow of tumor cells under physiological conditions, and its capture efficiency is usually the number of captured tumor cells divided by the number of tumor cells injected into the body's circulating systemic blood (~ 5 L). Therefore, even if the capture efficiency of CTCs in vivo detection technology is as low as 0.02%, it is possible to detect one CTCs in vivo with high sensitivity. In addition, it has the following advantages: (1) it can dynamically monitor the changes of CTCs in patients in real time under real physiological conditions; (2) effectively avoiding the influence on the quality of the cells in the processes of clinical sample collection, pretreatment, access and CTCs separation; (3) the blood circulating in the body can contact the CTCs sorting device for a plurality of times to enhance the contact frequency of the cells and the functional modification sites, which is beneficial to improving the detection sensitivity and obtaining more CTCs for downstream analysis; (4) It is expected that CTCs from different sources can be obtained from different parts of the body and different body fluids, and further combined with subsequent molecular level analysis can comprehensively and accurately reveal the evolution process and mechanism of tumors. Therefore, it is necessary and significant to develop an efficient and reliable in vivo detection technology for CTCs, and to monitor the dynamic changes of CTCs with the development of disease, surgery or drug treatment.

In this paper, we systematically reviewed the research progress of CTCs in vivo detection techniques and their applications, and divided the developed techniques into five categories according to the different detection principles.They are CTCs detection in vivo based on optical imaging technology, CTCs counting and analysis based on in vivo flow cytometry, CTCs recruitment in vivo based on stent implants, CTCs capture in vivo using intravenous indwelling needle devices, and CTCs detection based on microfluidic chips. Finally, the development trend of these technologies applied to the detection of CTCs in patients was summarized and prospected.

2 In vivo detection of CTCs

2.1 Detection of CTCs in vivo based on optical imaging technique

Clinically, the commonly used imaging techniques include computed tomography (CT), magnetic resonance imaging (MRI), positron emission tomography (PET), photoacoustic tomography (PAT) and optical coherence tomography (OCT). Among them, optical imaging technologies such as PAT and OCT have higher resolution (μm level) than that of CT, MRI and PET (mm level), and are expected to be used for real-time imaging of fast-flowing cells in blood vessels, including tumor cells^{[48⇓⇓⇓⇓~53]}.

In the aspect of CTCs in vivo imaging based on optical microscopy, Chen et al. Used near-infrared light excited multiphoton laser scanning microscopy to monitor the changes of CTCs number, flow velocity and trajectory in the blood vessels of solid tumors near the ear lobe of mice in real time^[54]. To distinguish from other normal cells, human pancreatic cancer cells BxPC3 stably expressing red and green fluorescent proteins (RFP, GFP) were injected into the ear lobes of nude mice (5-week-old BALC/cx male mice) and solid tumors were formed there. In addition, chemical molecular dyes Evans blue and fluorescein isothiocyanate (FITC) -labeled dextran were injected into the tail vein of mice as vascular fluorescence contrast agents. He and Wei et al. Quantitatively analyzed the number of GFP-labeled human hepatocellular carcinoma cells HCCLM3 and prostate cancer cells PC-3 after injection into mice and with tumor growth by confocal microscope linear scanning^[55]. GFP labeled HCCLM3 was injected into BALC/C male mice (25 G) via the tail vein. GFP labeled PC3 was subcutaneously implanted into BALC/C male mice. The lipophilic membrane dye DiI was injected through the tail vein for vascular staining. The results showed that CTCs could be detected by confocal microscopy in mouse ear arteries (diameter ~ 40 μm) at an early stage of tumor development (day 5 after subcutaneous tumor implantation), and that single CTCs and clusters of CTCs could be distinguished based on the detected fluorescent signal contours of the target cells.

PAT combines the optical absorption characteristics of tissues with the low scattering of ultrasound in soft tissues, breaking through the imaging depth limitation of pure optical imaging technology and achieving high-resolution imaging at a depth of several centimeters. Wang et al. Used the advantages of PAT imaging and strong light absorption of melanin to detect melanoma CTCs clusters injected into rats (12-13 weeks old RH-Foxn1^rnu∕Foxn1⁺ male nude mice), and applied them to detect CTCs in melanoma patients^[56,57]. OCT is an optical imaging technology based on the principle of weak coherent light interference to obtain tissue structure information at different depths. This technique measures the backscattered light of the sample, which is label-free and non-invasive. De la Zerda et al. successfully detected free RPMI-8226 myeloma cells in the longitudinal cross section (parallel to the direction of blood flow) of the ear blood vessels of nude mice (6-8 weeks old De la Zerda female mice) using speckle-modulating OCT (SM-OCT) (Figure 1)^[58]. In this work, gold nanorods (~ 100 × 30 nm) were used as contrast agents to label tumor cells and enhance the contrast of target cells, and OCT was first applied to the detection of single cells in the blood circulation system of animal models. Therefore, high-resolution optical imaging techniques can capture tumor cells labeled with nanoparticles or fluorescent molecules and unlabeled melanoma cells in blood vessels, but the imaging speed of these techniques is slow (< 100 frames/s), which makes it difficult to accurately quantify the dynamic changes of CTCs in fast-flowing blood^[59].

2.2 in vivo flow cytometry (in vivo flow cytometry, IVFC)

Conventional in vitro flow cytometry is capable of efficiently analyzing and counting monochromatic or polychromatic fluorescently labeled cells that pass through a laser beam in the form of a single cell fluid stream (flow rates up to a few millimeters per second)^[60]. When each cell passes through the laser beam, the fluorescent marker it carries will be activated by the laser to emit fluorescence, and then the optical signal will be converted into an amplified electrical signal by a detector such as a photomultiplier tube (PMT), and then the electrical signal will be converted into a digital signal of 0 and 1 that can be recognized by the computer by an analog-to-digital converter (A/D). And finally, identify that fluorescent-labeled cells through data proces and analysis. Unlike in vitro flow cytometry, IVFC directly uses the natural blood circulation system as the fluid flow system (blood vessels and lymphatic vessels as the "sheath") to quantitatively analyze the changes of fast-flowing target cells in real time. According to the different signals generated by target cells and other cells under light irradiation, such as fluorescence, photothermal effect, photoacoustic signal and light scattering intensity, IVFC can be divided into in vivo fluorescence flow cytometry, in vivo photothermal flow cytometry and in vivo photoacoustic flow cytometry. At present, fluorescence IVFC (IVFFC) and photoacoustic IVFC (IVPAFC) are widely used in the detection of CTCs.

2.2.1 In Vivo fluorescence flow cytometry

In 2004, Lin et al. First developed IVFFC for the detection of circulating free cells, including CTCs, in vivo^[61,62]. During the detection, firstly, a blood vessel with a proper size is selected by means of charge coupled device (CCD) image information, then a laser slit with a certain width focused by a microscope objective is vertically irradiated on the selected blood vessel for a period of time, and the fluorescence signal generated by the target cell passing through the laser slit is recorded. The length of the laser slit needs to match the diameter of the blood vessel to ensure that all cells flowing through the selected blood vessel can be detected. The number of the obtained fluorescence signal peaks represents the number of the cells, and the width of the fluorescence signal peaks represents the time for the fluorescent-labeled cells to flow through the laser slit, so that the blood flow velocity and the blood flow rate can be estimated through the time width, that is, the flow velocity = (laser slit width + cell diameter)/fluorescence signal peak time width; Blood flow = cross-sectional area of blood vessel × flow velocity.

In the experiment, Lin et al designed to focus He-Ne continuous laser into a slit with a width of about 5 μm through a microscope, vertically irradiate the small artery of the mouse ear (diameter of about 40 μm, distance from the body surface of 70-100 μm), and test the evanescent kinetics of human androgen-dependent prostate cancer cells LNCaP and rat prostate cells MLL (labeled with GFP) injected into the blood circulation system of the mouse through the tail vein^[62]. The mice used in the experiment were 4-6 week-old male SCID mice and 6-8 week-old male Copenhagen rats. It was found that the method could stably detect CTCs from mouse ears when the number of fluorescent-labeled cells injected was more than 10³. More than 80% of the cells disappeared 2 to 4 hours after the cells were injected into the tail vein of mice. In addition, the number of highly metastatic murine MLL cells decreased significantly faster than that of human LnCap cells. Based on this technique, Wei and Mosig et al. Also found that the more metastatic PC-3 cells and HCCLM3 cells injected into mice from the tail vein died faster than LNCap and HepG2 (DiD labeled)^[63]. Male BALB/cASlac nude mice aged 6-8 weeks were used in this study. Furthermore, Wei et al found that macrophages accelerated the disappearance of PC-3 cells injected into BALC/C nude mice^[64]. Therefore, the disappearance kinetics of CTCs is related to the metastatic ability of the cells themselves and the microenvironment such as macrophages.

Compared with intravenous tumor model and subcutaneous tumor model, orthotopic tumor model provides a suitable local microenvironment for tumor growth, and can better simulate the whole process of tumor occurrence, development, invasion and spontaneous metastasis in vivo. Based on this, Wei and Zhou et al. Used IVFFC to monitor the dynamic changes of GFP-labeled HCCLM3 in the blood circulation system in an orthotopic hepatocellular carcinoma (HCC) animal model^[65]. The results showed that there was a positive correlation between the number of CTCs and tumor size in the orthotopic tumor model, while there was no correlation between the number of CTCs and tumor size in the subcutaneous tumor model. Therefore, compared with the subcutaneous tumor model, the orthotopic tumor model can more truly reflect the status of hematogenous metastasis. In addition, hepatectomy can inhibit the hematogenous metastasis of tumor cells, and the number of CTCs is significantly reduced. In terms of drug therapy, Zhou and Wei et al., based on IVFFC and orthotopic hepatocellular carcinoma animal models, found that the number of CTCs was closely related to the development of the disease and the efficacy of multi-kinase inhibitor sorafenib^[66]. Based on IVFFC and orthotopic prostate cancer animal models, Gu and Wei found that the number of CTCs decreased significantly after androgen deprivation therapy (ADT)^[67]. high-intensity focused ultrasound (HIFU) therapy is a non-invasive tumor treatment technology, which focuses high-energy ultrasound on the lesion tissue and uses the thermal effect to kill the tissue. Similarly, Jiang and Wei et al studied the changes of CTCs in pancreatic ductal adenocarcinoma (PDAC) after HIFU treatment based on IVFFC^[68]. The results showed that HIFU ablation of local lesion tissue largely limited the hematogenous metastasis of PDAC.

CTCs exist in the circulatory system as single cells and cell clusters. Studies have shown that the transfer ability of CTC clusters is 23 to 50 times higher than that of individual CTCs^[69]. Maheswara and Haber et al. Used IVFFC to analyze the clearance rate of DiD-labeled single CTCs and CTC clusters from the circulatory system of immunodeficient mice injected via the tail vein^[69]. The results showed that the half-life of CTC clusters was 6 ~ 10 min, and that of single CTC was 25 ~ 30 min. Due to the large size of the CTC clusters, the CTC clusters are easily trapped when flowing through the small-sized capillaries and have a short half-life in the circulatory system^[70,71]. Furthermore, based on IVFFC, Wei et al found that the content of single CTC and CTC clusters increased during the development of tumor metastasis, and the proportion of CTC clusters also increased, up to 30%, while the proportion of CTC clusters isolated from CTCs based on in vitro microfluidic chip and immunomagnetic technology was less than 9%^[72]^[69,73].

Most of the tumor cells shed from the solid tumor site into the circulatory system died quickly, and less than 0.00004% of the CTCs caused tumor metastasis^[74]. Studies have found that the number of apoptotic CTCs is also related to prognosis. The more the number of apoptotic CTCs in peripheral blood collected in vitro, the better the prognosis^[75]. Lin et al. Used Annexin V labeled by Alexa Fluor 647 to specifically bind phosphatidylserine exposed outside early apoptotic cells to achieve real-time monitoring of apoptotic tumor cells in the blood circulation system^[76]. Further, Nolan et al. Used two-color fluorescent IVFC to monitor both viable and early apoptotic breast cancer cells, MDA-MB 231^[77]. In this work, Annexin V conjugated to R-Phycoerythrin (RPE) was used to specifically label early apoptotic cells to distinguish them from GFP-labeled viable cells.

To sum up, IVFFC has been widely used to monitor the dynamic changes of fluorescent labeled CTCs in the blood circulation system of tumor animal models, including single CTC, CTC cluster and apoptotic CTCs. The tumor models used were tail vein injection tumor model, subcutaneous transplantation tumor model and orthotopic transplantation tumor model. IVFFC was mainly performed in the vein and arteriole (30-50 μm in diameter) of the mouse ear, which was 30-100 μm away from the body surface. The blood flow velocity was 3-7 mm/s, and the detected blood volume was small (0.1-1 μL/min), that is, the flux was low^[60]. When the content of CTCs in blood is less than 1000/mL, the instrument needs to collect for a long time before the target cells can be detected^[47]. To this end, Niedre et al. developed a computer vision IVFC (CV-IVFC) for the detection of Vybrant-DiD-labeled multiple myeloma cells by combining a fluorescence macroscopic imaging system with an automated computer vision algorithm, with a sensitivity of 20 CTCs/mL^[78]. The imaging area of CV-IVFC in the mouse ear was about 5×5 mm², and the detection flux was up to 10 μL/min. In addition, they have developed a diffuse fluorescence IVFC with a detection flux of up to several hundred microliters per minute^{[79⇓⇓~82]}.

Biological tissue is a highly light-scattering medium due to its uneven density distribution. When light irradiates biological tissue, most of it will be scattered, some of it will be absorbed, and the depth of penetration is very limited. In the near-infrared region (700 ~ 1100 nm), the light absorption of most biological tissues is relatively low, and near-infrared light can penetrate tissues well^[83]. Shi and Wei et al extended IVFFC to the near-infrared region for the detection of circulating free cells^[84]. At present, IVFFC can detect fluorophores from visible to near-infrared, and has all the channels of in vitro flow cytometry^[59]. Based on multi-color IVFFC, single cells or cell clusters such as platelet-CTCs complexes with different fluorescent labels can be detected simultaneously^[85]. In addition, Wei et al. used the optical scavenger ESOCA (a mixture of PEG-400, fructose, and thiourea) to reduce light scattering, improve the depth of light penetration into tissue, and enhance the optical imaging depth of IVFFC^[86]. The detection depth of IVFFC after ESOCA treatment was increased by 32% compared with the commonly used glycerol immersion solution.

2.2.2 In vivo photoacoustic flow cytometer

Zharov of the University of Arkansas in the United States first developed IVPAFC, and demonstrated the feasibility and reliability of this technology in the detection of single particles, pathogens, circulating cells and other fields^[46,60,87]. Compared with IVFFC, IVPAFC uses high-frequency pulsed laser to irradiate a selected blood vessel, and uses an ultrasonic detector placed on the surface of the tissue to detect the instantaneous ultrasonic signal generated by the target cells flowing through it, so the detection depth of IVPAFC is deeper. When laser irradiates, the target cells will absorb light energy and convert it into heat energy, which will cause local temperature rise, cause tissue thermoelastic changes, and produce ultrasonic waves, that is, photoacoustic signals. To generate a photoacoustic signal from fast flowing CTCs, the frequency of the pulsed laser is f≥V_F/d(V_F the blood flow velocity, d is the width of the laser spot), the pulse width is t≤2R/c_s(R the radius of the target cell, and c_s is the acoustic velocity)^[60]. The blood flow velocity of human vein (1 ~ 2 mm) is 5 ~ 15 cm/s, so the pulse frequency f ≥ 0.5 ~ 3 kHz is required to obtain the ultrasonic signal of flowing cells by irradiating the blood vessel with 50 ~ 100 μm light spot.

In biological tissues, the absorption of light is mainly due to chromophores such as hemoglobin, bilirubin and melanin^[83]. In the near-infrared region, the intrinsic contrast agent melanin of melanoma cells produces a photoacoustic signal significantly stronger than the blood background under laser irradiation, so IVPAFC has obvious advantages in detecting melanoma CTCs without additional labeling. In 2009, Zharov et al. achieved in vivo detection of melanoma CTCs using IVPAFC integrated with a high repetition rate pulsed diode laser (905 nm, 10 kHz)^[88]. Melanoma cells B16F10 were injected into mice through the tail vein. In the same year, Zharov et al. Used ligand-functionalized plated carbon nanotube magnetic nanoparticles and gold-plated carbon nanotubes to specifically label breast cancer cells MDA-MB-231, so that they could produce characteristic photoacoustic signals different from the background under different wavelengths of pulsed laser irradiation to achieve specific detection of target cells^[89]. The detection of different kinds of target cells can be realized by using different ligands to modify nanoparticles. Based on the same strategy, Galanzha et al. Realized the detection of breast cancer stem cells expressing CD44^[90].

In the initial stage of tumor metastasis, tumor cells shed from solid tumors may first spread to lymphatic vessels and then to the blood circulation system, in addition to entering blood vessels. Compared with blood vessels, the structure of lymphatic vessels is smaller, and the lymph (fluid) flowing in them is colorless and transparent, so it is necessary to use contrast agents to enhance the lymphatic system and display lymphatic vessels. In addition, each collection of lymph is only a few microliters, which requires a long time of intubation collection, so there are great limitations in the analysis of CTCs in lymph based on in vitro detection methods^[60]. However, when using IVPAFC to detect CTCs, the background of PA signal produced by achromatic lymph is lower, which has obvious advantages. Galanzha et al. detected CTCs in lymphatic vessels and lymph nodes in a mouse ear melanoma model based on IVPAFC (Evans blue dye was used as a contrast agent to visualize lymphatic vessels and lymph nodes)^[91]. In addition, folic acid modified gold carbon nanotubes were used to specifically bind to MDA-MB-231 cells (FITC labeled) and directly injected into lymph nodes. Combined with the results of fluorescence microscopy imaging, the feasibility of detecting the metastasis of CTCs without intrinsic contrast agent based on IVPAFC was verified. Further, Galanzha et al. Used IVPAFC to detect CTCs in cerebrospinal fluid and bone tissue from breast cancer cells^[92]^[93].

In addition, Zharov et al. Used IVFFC and IVPAFC in combination to study whether medical procedures such as palpation, tissue biopsy and laser surgery could cause tumor cells to fall off from solid tumors and enter the blood circulation system^[94]. The results showed that pressure, palpation, biopsy and laser treatment could enhance the release of CTCs in a short time, and the number of CTCs in the blood increased significantly, while the number of CTCs decreased significantly after complete surgical resection. The above studies are all based on the detection of CTCs in tumor animal models. Recently, Zharov et al applied a cytophone device to the detection of CTCs in melanoma patients (Fig. 2a)^[95]. The device uses a pulsed laser with a wavelength of 1060 nm to irradiate veins with a diameter of 1. 1-2. 8 mm through the human skin at a depth of 1 to 1. 5 mm, and can detect 1 CTC from 1 L of blood of patients with melanin, which is much more sensitive than CellSearch system (1 CTC/7. 5 mL) and other CTCs in vitro detection methods (1 to 10 CTCs/mL). In addition, the device can also distinguish the characteristic photoacoustic signals produced by single CTC, CTC cluster, circulating blood clots (CBC) and CTC-CBC emboli, namely single CTC: single peak above baseline, peak width 0.5-1.5 ms;CTC cluster: multiple peaks above the baseline with a peak width of 3 to 5 ms; CBC: single peak below the baseline with a peak width of 20 to 50 ms; CTC-CBC: combined peaks (both above and below the baseline), in which the photoacoustic signal generated by the absorption of light by erythrocyte hemoglobin in the detection area serves as the baseline (Fig. 2b). When the laser energy was adjusted to a safe level of 240 μJ for 1 H, the number of CTCs decreased significantly. Previous studies have shown that under the continuous irradiation of high-energy laser, melanin aggregates in melanoma cells absorb excessive light energy, which can lead to local overheating and destruction of CTCs by nanobubbles^[96]. Therefore, IVPAFC can not only detect melanoma CTCs in real time and in vivo, but also kill melanoma cells, which has therapeutic effect.

2.3 In vivo recruitment of CTCs based on scaffold implants

Implant-based CTCs in vivo capture technology mainly uses biomaterial scaffolds to simulate the microenvironment of tumor cells migrating to target organs or to regulate the local microenvironment to induce tumor cells to migrate into the scaffolds. In 2007, Rsenblatt et al constructed a silk fibroin scaffold loaded with bone morphogenetic protein-2 (BMP-2) and human bone marrow stromal cells (BMSCs), and found that it could be used as a target site for the metastasis of SUM1315 breast cancer cells in mice^[97]. In 2012, Parekkadan et al. Prepared a porous type I collagen functionalized polyacrylamide hydrogel scaffold, and found that the scaffold loaded with BMSCs could also recruit hematopoietic stem cells and leukemia cells^[98]. In 2015, Shea et al. implanted a microporous polylactide-co-glycolide (PLG) scaffold (5 mm in diameter and 2 mm in height) into mice, and found that the PLG scaffold itself could regulate the local immune microenvironment, recruit and capture metastatic tumor cells, and reduce the tumor burden of solid organs^[99]. The biomaterials used in these works have good biocompatibility and can be made into tissue engineering scaffolds and drug delivery carriers, which are widely used in biomedical fields. Of these, PLG is an FDA-approved biomaterial. For patients at risk of recurrence, implantation of the above stents after primary treatment may detect metastasis at an early stage and hopefully initiate therapeutic intervention with a low burden of disease.

2.4 CTCs capture in vivo based on intravenous indwelling needle device

Venous indwelling needle is widely used in clinic, which can alleviate the pain of patients caused by repeated venipuncture. Its core components include a soft catheter that can be indwelled in blood vessels and a stainless steel puncture guide needle core. Therefore, the surface of the tip of the pillow core can be functionalized and modified to specifically recognize CTCs affinity ligands such as antibodies and aptamers, or the pillow core can be replaced by other linear materials with good biocompatibility, and the CTCs can be captured by being inserted into a blood vessel through a catheter placed in the blood vessel.

In 2012, L Lücke et al., Germany, reported a structured, FDA-approved (510k) stainless steel medical Seldinger guidewire (0.5 mm diameter, 16 cm long) for in vivo isolation of breast and non-small cell lung cancer CTCs (Fig. 3A)^[100]. The steps of the functional modification of the guide wire are as follows: (1) the front end (2 cm) of the guide wire is electroplated with a 2$\mu m$m thick gold layer; (2) modif a layer of linear polycarboxylate hydrogel on that surface of the gold; (3) the carboxyl in the hydrogel is activated by 1- (3-dimethylaminopropyl) -3-ethylcarbodiimide (EDC) and N-hydroxysuccinimide (NHS), and the antibody is covalently connected through the reaction of the carboxyl and the amino. Subsequently, the functionalized guidewire was slowly pushed through the catheter of the indwelling needle (20g) into the elbow vein (blood flow about 20 mL/min) for 30 min to capture CTCs. Finally, the guide wire was removed, washed, fixed, blocked, immunostained, and then the CTCs were observed and counted under a microscope (the cells were identified by staining the nuclei with 4 ', 6-diamidino-2-phenylindole (DAPI) dye showing blue fluorescence). Cells positive for EpCAM or cytokeratin (CK) 4, 5, 8, 9, 18, and ranging in size from 10 to 50 μm with a high nucleocytoplasmic ratio were identified as CTCs, while cells positive for CD45 were leukocytes. In the same year, this technology, namely GILUPI Cell Collector ®, was certified by CE (European Conformity), which is the first and only in-vivo CTCs capture technology on the market. It has been applied to the detection of CTCs in lung cancer, prostate cancer, neuroendocrine tumors, breast cancer and colorectal cancer, including counting, gene mutation and gene expression analysis, and has obtained a large number of clinical research data^{[100⇓⇓~103]}^[104⇓~106]^[102]^[107]^[108].

In 2014, Liu and Zhang et al. Used anti-EpCAM antibody-modified nylon wire (10 cm long) interventional device to capture CTCs in vivo in nude mouse tumor model^[109]. The working length of the antibody modified nylon thread in contact with blood was ~ 10 mm. This work only shows the CTCs capture potential of the device, but has not yet accurately quantified the CTCs capture efficiency. In addition, the device first dissects the back cavity of the mouse before capturing CTCs, which is invasive. Furthermore, Tang et al. developed an in vivo CTCs capture technique based on an infusion type venous indwelling needle (Fig. 3B)^[110]. In this work, they coated the surface of the indwelling needle with polydimethylsiloxane (PDMS), and then modified the anti-EpCAM antibody by non-specific adsorption. In this way, the improved indwelling needle can capture CTCs while infusing the patient, which avoids the pain caused by additional puncture and is easy to be accepted by the patient. In the experiment, the antibody-modified indwelling needle remained in the rabbit ear vein and rat tail vein for 3 H (before the experiment, DAPI-stained MCF-7 breast cancer cells were injected into the rabbit ear vein and rat tail vein), and the working length of blood contact was ~ 1.7 cm. Finally, the captured cells were eluted from the indwelling needle, and CTCs were identified by immunostaining, and the capture efficiency was calculated. The efficiency of this system to capture CTCs from rabbit ear vein was 1.9% ~ 11%. CTCs capture from that tail vein of wild-type mice was 0. 9% -15%; The efficiency of capturing CTCs from the tail vein of immunodeficient nude mice was 9.3% ~ 33%. In addition, the system was able to detect CTCs on day 7 after subcutaneous inoculation of murine breast cancer cell line 4 T1, while the size of the solid tumor in situ was less than 2 cm and no metastasis was observed. With the development of tumor, the number of captured CTCs increased. These results indicate that this system can detect CTCs at the early stage of tumor development and is expected to be used for early diagnosis of tumors.

On this basis, Zhang and Wang et al used anti-EpCAM and anti-EGFR antibody-modified indwelling needles and multicolor fluorescent-labeled aptamers to capture and identify CTCs from breast cancer and hepatocellular carcinoma^[111]. The combined use of multiple antibodies effectively improves the capture efficiency of CTCs. The CTCs capture efficiency of HCC was increased from 3.17% to 26.67%. The capture efficiency of breast cancer CTCs increased from 27% to 29.84%. Recently, Huang and Xie et al. embedded anti-EpCAM-modified three-dimensional porous PDMS scaffolds (with pores ranging from 40 to 250 μm in size) into indwelling needles for in vivo capture of rat CTCs (Fig. 3C)^[112]. Because of the large specific surface area of the through porous scaffold, it can load more antibodies and effectively enhance the contact frequency between cells and the scaffold, so the cell capture performance of the indwelling needle embedded in PDMS scaffold is better than that of GILUPI Cell Collector. In addition, the captured cells were released from the scaffold with trypsin, and their DNA was collected and extracted. The T790M and L858R mutations of EGFR gene in H1975 cells could be analyzed and identified by PCR.

In addition, Gambhir et al. prepared a magnetic wire consisting of 60 cylindrical neodymium magnets (6 cm long and 0.75 mm in diameter) and inserted it into blood vessels via an intravenous catheter to capture and enrich tumor cells labeled with superparamagnetic iron oxide particles (1 μm in diameter)^[113]. Anti-EpCAM antibody-modified particles were injected into the blood vessels in advance to label the target cells. After the cells are enriched, the magnetic wire is taken out, and after the magnet is removed, the captured cells can be released for subsequent molecular analysis. The magnetic wire was inserted into the vein near the pig ear (blood flow was about 20 mL/min) to capture the magnetic particle-labeled non-small cell lung cancer cells H1650. The capture efficiency was 1% -8%, and the number of captured CTCs was 10-80 times that of the in vitro detection method (blood volume was 5 mL) and 500-5000 times that of the GILUPI Cell Collector (0.0016 ± 0.0003%).

In general, the CTCs in vivo capture technology based on venous indwelling needle device directly contacts the blood flowing in the vein to capture CTCs, and the throughput is high. However, these methods rely on antibodies and may result in the omission of CTCs that do not express the corresponding antigen of the antibody. In addition, CTCs captured on stainless steel wires or indwelling needles are not convenient to directly observe the morphology of cells under the microscope, and need to be eluted, which may damage cells or even lose cells.

2.5 Detection of CTCs in Vivo Based on Microfluidic Chip

In 2019, Hamza et al. Developed an optofluic system to detect fluorescently labeled CTCs in mice^[114]. The system is mainly composed of a PDMS microfluidic chip for sorting CTCs, a fluorescence detector and a computer-controlled pneumatic valve. In the experiment, blood (30.mu.L/min) from the catheter implanted in the left carotid artery of the mouse was drawn by a peristaltic pump and then flowed into the CTC-sorting chip. When the fluorescently labeled cells flow through the two sites of laser irradiation, fluorescence pulses are generated and detected by PMT. Then, based on the time difference between the two pulses, the program calculates the flow rate of the cells and operates a pneumatic valve to introduce fluorescently labeled CTCs into the collection tube for subsequent analysis. Finally, the CTCs were removed and the blood returned to the right jugular vein of the mice via another implanted catheter. Also based on extracorporeal circulation, Zhang et al. Used a pump to drain blood from mice through a microfluidic chip integrated with magnetic nanoparticles modified by anti-EpCAM antibodies to specifically enrich and isolate CTCs (Fig. 4)^[115]. Therefore, the detection of CTCs can be achieved by using peristaltic pump to drain blood into the developed in vitro enrichment methods of CTCs, such as microfluidic chips. However, placement of catheters in arteries and veins is invasive, and the biotoxicity of the materials used and the sterility of the CTCs sorting device must be taken into account.

3 Conclusion and prospect

As the "precursor seed" of tumor metastasis, CTCs are expected to become a marker for tumor diagnosis and treatment monitoring. In order to achieve this goal, it is very important to develop real-time and accurate analytical techniques to monitor the dynamic changes of CTCs in vivo. CTCs in vivo detection technology is based on the rapid flow of blood in the circulatory system, even lymph, cerebrospinal fluid and other body fluids, which can record the dynamic changes of CTCs number, recruitment and capture of tumor cells in different parts of the body in real physiological state. At present, the main animal models of CTCs in vivo detection technology are mouse tumor models, including intravenous injection tumor, subcutaneous transplantation tumor and orthotopic tumor. There are two main methods for quantitative analysis of CTCs in vivo. One is based on optical IVFCs, which automatically records the fluorescence signals and photoacoustic signals generated by target cells to count CTCs. The other is to capture CTCs first, then label the tumor cells by staining, observe them under the microscope and count the number of cells. Among them, the commercialized Cell Collector is the most representative. In order to improve the sensitivity of CTCs capture, the specific surface area of the matrix can be increased, such as the use of three-dimensional scaffolds, and the loading of affinity ligands such as antibodies can be increased. Because of the limited size of blood vessels in the body, it is also possible to drain blood from the body to the outside of the body and capture CTCs in combination with efficient in vitro enrichment methods.

However, in addition to the dynamic changes in the number of CTCs with the development of tumors, CTCs detection is also expected to obtain biological information such as tumor-related phenotype, genome, transcriptome, proteome and metabolome from CTCs. Therefore, it is required to develop a technology that can isolate high-quality CTCs with integrity, high activity and high purity. To this end, CTCs in vitro detection technology has been developed with the added function of mild and specific release of captured CTCs. CTCs can also be obtained by constructing a negative selection method for specifically enriching and removing normal blood cells; And/or a module capable of directly culturing and analyzing the enriched CTCs in situ is integrated. Although the developed CTCs capture technology in vivo effectively ensures the quality of CTCs before and during the capture process, the downstream analysis of CTCs in vitro also faces problems such as cell inactivation and distortion, so it is necessary to integrate new functions into the capture device to facilitate the release of CTCs from the surface of the capture matrix in vivo, so as to meet the requirements of subsequent CTCs culture and molecular analysis. In addition, we can also develop a CTCs detection system with integrated diagnosis and treatment to capture and kill tumor cells in vivo, or recruit metastatic tumor cells to reduce tumor load, which is beneficial to therapeutic intervention, such as CTCs recruitment technology in vivo based on stent implants.

Because the in vivo detection technology of CTCs is directly applied to the living body, the tumor cell detection elements placed in the body and the exogenous contrast agents (such as fluorescent dyes, nanoparticles, antibody probes) used for target cell labeling must be safe, sterile, non-toxic, biocompatible and harmless to the body. In addition, the test device to be developed should be fast, simple to operate, multifunctional and suitable for clinical translational applications. We believe that with the unremitting efforts of multi-disciplinary researchers and the development and cross-integration of more technologies, CTCs in vivo detection technology can make new breakthroughs, and complement each other with CTCs in vitro detection technology, jointly promote our in-depth understanding of the mechanism of tumor metastasis, and then overcome cancer.

References

Publishing order | Descend order by publishing year | Descend order by cited within

[1]	Ashworth T R. Med. J. Aust., 1869, 14: 146.

[2]	Paget S. Cancer Metastasis Rev., 1989, 8: 98.

[3]	Bonnet D, Dick J E. Nat. Med., 1997, 3: 730.

[4]	Gupta A S. Nanomedicine , 2014, 9: 1517.

[5]	Pantel K, Brakenhoff R H. Nat. Rev. Cancer , 2004, 4: 448.

[6]	Schroeder A, Heller D A, Winslow M M, Dahlman J E, Pratt G W, Langer R, Jacks T, Anderson D G. Nat. Rev. Cancer , 2012, 12: 39.

[7]	Dotan E, Cohen S J, Alpaugh K R, Meropol N J. The Oncologist , 2009, 14: 1070.

[8]	Dasgupta A, Lim A R, Ghajar C M. Mol. Oncol. , 2017, 11: 40.

[9]	Micalizzi D S, Maheswaran S, Haber D A. Genes Dev., 2017, 31: 1827.

[10]	Dianat-Moghadam H, Azizi M, Eslami-S Z, Cortes-Hernandez L E, Heidarifard M, Nouri M, Alix-Panabieres C. Cancers ( Basel), 2020, 12: 867.

[11]	Chaffer C L, Weinberg R A. Science , 2011, 331: 1559.

[12]	Alix-Panabieres C, Pantel K. Nat. Rev. Cancer , 2014, 14: 623.

[13]	Stott S L, Lee R J, Nagrath S, Yu M, Miyamoto D T, Ulkus L, Inserra E J, Ulman M, Springer S, Nakamura Z, Moore A L, Tsukrov D I, Kempner M E, Dahl D M, Wu C L, Iafrate A J, Smith M R, Tompkins R G, Sequist L V, Toner M, Haber D A, Maheswaran S. Sci. Transl. Med., 2010, 2: 23.

[14]	Banys M, Krawczyk N, Becker S, Jakubowska J, Staebler A, Wallwiener D, Fehm T, Rothmund R. Breast Cancer Res. Treat , 2012, 132: 121.

[15]	Seal S H. Cancer, 1964, 17: 637.

[16]	Vona G, Sabile A, Louha M, Sitruk V, Romana S, Schutze K, Capron F, Franco D, Pazzagli M, Vekemans M, Lacour B, Brechot C, Paterlini-Brechot P. Am. J. Pathol., 2000, 156: 57.

[17]	Lee H J, Oh J H, Oh J M, Park J M, Lee J G, Kim M S, Kim Y J, Kang H J, Jeong J, Kim S I, Lee S S, Choi J W, Huh N. Angew. Chem. Int. Ed. , 2013, 52: 8337.

[18]	Gascoyne P R, Noshari J, Anderson T J, Becker F F. Electrophoresis , 2009, 30: 1388.

[19]	Moon H S, Kwon K, Kim S I, Han H, Sohn J, Lee S, Jung H I. Lab Chip , 2011, 11: 1118.

[20]	Huang S, Wu M, Lin Y, Hsieh C, Yang C, Lin H, Tseng C, Lee G. Lab Chip , 2013, 13: 1371.

[21]	Cristofanilli M, Budd G T, Ellis M J, Stopeck A, Matera J, Miller M C, Reuben J M, Doyle G V, Allard W J, Terstappen L W, Hayes D F. N. Engl. J. Med., 2004, 351: 781.

[22]	Wen C Y, Wu L L, Zhang Z L, Liu Y L, Wei S Z, Hu J, Tang M, Sun E Z, Gong Y P, Yu J, Pang D W. ACS Nano , 2014, 8: 941.

[23]	Jo S M, Lee J J, Heu W, Kim H S. Small , 2015, 11: 1975.

[24]	Xie M, Lu N N, Cheng S B, Wang X Y, Wang M, Guo S, Wen C Y, Hu J, Pang D W, Huang W H. Anal. Chem., 2014, 86: 4618.

[25]	Chen W, Weng S, Zhang F, Allen S, Li X, Bao L, Lam R H, Macoska J A, Merajver S D, Fu J. ACS Nano , 2013, 7: 566.

[26]	Wang S, Wang H, Jiao J, Chen K J, Owens G E, Kamei K, Sun J, Sherman D J, Behrenbruch C P, Wu H, Tseng H R. Angew. Chem. Int. Ed., 2009, 48: 8970.

[27]	Zhang N, Deng Y, Tai Q, Cheng B, Zhao L, Shen Q, He R, Hong L, Liu W, Guo S, Liu K, Tseng H R, Xiong B, Zhao X Z. Adv. Mater., 2012, 24: 2756.

[28]	Wan Y, Mahmood M A, Li N, Allen P B, Kim Y T, Bachoo R, Ellington A D, Iqbal S M. Cancer , 2012, 118: 1145.

[29]	Guo S, Xu J, Xie M, Huang W, Yuan E, Liu Y, Fan L, Cheng S, Liu S, Wang F, Yuan B, Dong W, Zhang X, Huang W, Zhou X. ACS Appl. Mater. Interfaces , 2016, 8: 15917.

[30]	Zhang F, Jiang Y, Liu X, Meng J, Zhang P, Liu H, Yang G, Li G, Jiang L, Wan L J, Hu J S, Wang S. Nano Lett., 2016, 16: 766.

[31]	Yu X, He R, Li S, Cai B, Zhao L, Liao L, Liu W, Zeng Q, Wang H, Guo S S, Zhao X Z. Small , 2013, 9: 3895.

[32]	Mohamadi R M, Besant J D, Mepham A, Green B, Mahmoudian L, Gibbs T, Ivanov I, Malvea A, Stojcic J, Allan A L, Lowes L E, Sargent E H, Nam R K, Kelley S O. Angew. Chem. Int. Ed., 2015, 54: 139.

[33]

Stott S L, Hsu C H, Tsukrov D I, Yu M, Miyamoto D T, Waltman B A, Rothenberg S M, Shah A M, Smas M E, Korir G K, Floyd F J, Gilman A J, Lord J B, Winokur D, Springer S, Irimia D, Nagrath S, Sequist L V, Lee R J, Isselbacher K J, Maheswaran S, Haber D A, Toner M. Proc. Natl. Acad. Sci. U. S. A., 2010, 107: 18392.

[34]	Sheng W, Chen T, Tan W, Fan Z H. ACS Nano , 2013, 7: 7067.

[35]	Yoon H J, Kim T H, Zhang Z, Azizi E, Pham T M, Paoletti C, Lin J, Ramnath N, Wicha M S, Hayes D F, Simeone D M, Nagrath S. Nat. Nanotechnol. , 2013, 8: 735.

[36]	Cheng S B, Xie M, Xu J Q, Wang J, Lv S W, Guo S, Shu Y, Wang M, Dong W G, Huang W H. Anal. Chem. , 2016, 88: 6773.

[37]	Karabacak N M, Spuhler P S, Fachin F, Lim E J, Pai V, Ozkumur E, Martel J M, Kojic N, Smith K, Chen P I, Yang J, Hwang H, Morgan B, Trautwein J, Barber T A, Stott S L, Maheswaran S, Kapur R, Haber D A, Toner M. Nat. Protoc., 2014, 9: 694.

[38]	Poudineh M, Aldridge P M, Ahmed S, Green B J, Kermanshah L, Nguyen V, Tu C, Mohamadi R M, Nam R K, Hansen A, Sridhar S S, Finelli A, Fleshner N E, Joshua A M, Sargent E H, Kelley S O. Nat. Nanotechnol., 2017, 12: 274.

[39]	Ahmed M G, Abate M F, Song Y, Zhu Z, Yan F, Xu Y, Wang X, Li Q, Yang C. Angew. Chem. Int. Ed., 2017, 56: 10681.

[40]	Guo S, Huang H, Deng X, Chen Y, Jiang Z, Xie M, Liu S, Huang W, Zhou X. Nano Res., 2018, 11: 2592.

[41]	Huang D, Xiang N, Tang W L, Zhang X J, Ni Z H. Progress in Chemistry , 2015, 27: 882.

[42]	黄笛, 项南, 唐文来, 张鑫杰, 倪中华. 化学进展, 2015, 27: 882.

[43]	Pei H, Li L, Wang Y, Sheng R, Wang Y, Xie S, Shui L, Si H, Tang B. Anal. Chem., 2019, 91: 11078.

[44]	Wu L, Tang M, Zhang Z, Qi C, Hu J, Ma X, Pang D. Anal. Chem., 2018, 90: 10518.

[45]	Dong J, Jan Y J, Cheng J, Zhang R Y, Meng M, Smalley M, Chen P J, Tang X, Tseng P, Bao L, Huang T Y, Zhou D, Liu Y, Chai X, Zhang H, Zhou A, Agopian V G, Posadas E M, Shyue J J, Jonas S J, Weiss P S, Li M, Zheng G, Yu H H, Zhao M, Tseng H R, Zhu Y. Sci. Adv., 2019, 5: v9186.

[46]	Abdulla A, Liu W, Gholamipour-Shirazi A, Sun J, Ding X. Anal. Chem., 2018, 90: 4397.

[47]	Kim J, Galanzha E I, Zaharoff D A, Griffin R J, Zharov V P. Mol. Pharmaceutics , 2013, 10: 813.

[48]	Hartmann C, Patil R, Lin C P, Niedre M. Phys. Med. Biol., 2017, 63: 1T.

[49]	Pons T, Bouccara S, Loriette V, Lequeux N, Pezet S, Fragola A. ACS Nano , 2019, 13: 3125.

[50]	Adonai N, Adonai N, Nguyen K N, Walsh J, Iyer M, Toyokuni T, Phelps M E, McCarthy T, McCarthy D W, Gambhir S S. Proc. Natl. Acad. Sci. U. S. A., 2002, 99: 3030.

[51]	Ahrens E T, Bulte J W. Nat. Rev. Immunol. Immunology , 2013, 13: 755.

[52]	Zhang H F, Maslov K, Stoica G, Wang L V. Nat. Biotechnol., 2006, 24: 848.

[53]	Yi J, Backman V. Opt. Lett., 2012, 37: 4443.

[54]	Kircher M F, Gambhir S S, Grimm J. Nat. Rev. Clin. Oncol., 2011, 8: 677.

[55]	Kuo C W, Chueh D, Chen P. Nanobiotechnol., 2019, 17: 26.

[56]	Hu Y, Tang W, Cheng P, Zhou Q, Tian X, Wei X, He H. Cytometry A , 2019, 95( 6): 657.

[57]	Hai P, Zhou Y, Zhang R, Ma J, Li Y, Shao J Y, Wang L V. J. Biomed. Opt., 2017, 22: 41004.

[58]	Hai P, Qu Y, Li Y, Zhu L, Shmuylovich L, Cornelius L A, Wang L V. J. Biomed. Opt., 2020, 25: 1.

[59]	Dutta R, Liba O, Sorelle E D, Winetraub Y, Ramani V C, Jeffrey S S, Sledge G W, de la Zerda A. Nano Lett. , 2019, 19: 2334.

[60]	Suo Y, Gu Z, Wei X. Cytometry A , 2020, 97: 15.

[61]	Galanzha E, Zharov V. Cancers , 2013, 5: 1691.

[62]	Novak J, Georgakoudi I, Wei X, Prossin A, Lin C P. Opt. Lett., 2004, 29: 77.

[63]	Georgakoudi I, Solban N, Novak J, Rice W L, Wei X, Hasan T, Lin C P. Cancer Res., 2004, 64: 5044.

[64]	Li Y, Guo J, Wang C, Fan Z, Liu G, Wang C, Gu Z, Damm D, Mosig A, Wei X. Cytometry A , 2011, 79: 848.

[65]	Guo J, Fan Z, Gu Z, Wei X. J. Innov. Opt. Health Sci . , 2012, 5: 1250027.

[66]	Fan Z C, Yan J, Liu G D, Tan X Y, Weng X F, Wu W Z, Zhou J, Wei X B. Cancer Res., 2012, 7: 2683.

[67]	Yan J, Fan Z, Wu X, Xu M, Jiang J, Tan C, Wu W, Wei X, Zhou J. Cytometry A , 2015, 87: 1020.

[68]	Pang K, Xie C, Yang Z, Suo Y, Zhu X, Wei D, Weng X, Wei X, Gu Z. Cytometry A , 2018, 93: 517.

[69]	Yu Q, Yao Y, Zhu X, Gao Y, Chen Y, Wang R, Xu P, Wei X, Jiang L. Cytometry A , 2020, DOI: 10.1002/cyto.a.24014.

[70]	Aceto N, Bardia A, Miyamoto D T, Donaldson M C, Wittner B S, Spencer J A, Yu M, Pely A, Engstrom A, Zhu H, Brannigan B W, Kapur R, Stott S L, Shioda T, Ramaswamy S, Ting D T, Lin C P, Toner M, Haber D A, Maheswaran S. Cell , 2014, 158: 1110.

[71]	Plaks V, Koopman C D, Werb Z. Science , 2013, 341: 1186.

[72]	Au S H, Storey B D, Moore J C, Tang Q, Chen Y, Javaid S, Sarioglu A F, Sullivan R, Madden M W, O Keefe R, Haber D A, Maheswaran S, Langenau D M, Stott S L, Toner M. Proc. Natl. Acad. Sci. U. S. A. , 2016, 113: 4947.

[73]	Suo Y, Xie C, Zhu X, Fan Z, Yang Z, He H, Wei X. Cytometry A , 2017, 91: 250.

[74]	Cho E H, Wendel M, Luttgen M, Yoshioka C, Marrinucci D, Lazar D, Schram E, Nieva J, Bazhenova L, Morgan A, Ko A H, Korn W M, Kolatkar A, Bethel K, Kuhn P. Phys. Biol., 2012, 9: 16001.

[75]	Paterlini-Brechot P, Benali N L. Cancer Lett., 2007, 253: 180.

[76]	Kallergi G, Konstantinidis G, Markomanolaki H, Papadaki M A, Mavroudis D, Stournaras C, Georgoulias V, Agelaki S. Mol. Cancer Ther., 2013, 12: 1886.

[77]	Wei X, Sipkins D A, Pitsillides C M, Novak J, Georgakoudi I, Lin C P. Mol. Imaging , 2005, 4: 415.

[78]	Nolan J, Nedosekin D A, Galanzha E I, Zharov V P. Cytometry A , 2019, 95: 664.

[79]	Markovic S, Li S, Niedre M. J. Biomed. Opt., 2015, 20: 35005.

[80]	Zettergren E, Vickers D, Runnels J, Murthy S K, Lin C P, Niedre M. J. Biomed. Opt., 2012, 17: 37001.

[81]	Patil R A, Srinivasarao M, Amiji M M, Low P S, Niedre M. Mol. Imaging Biol. , 2020, DOI: 10.1007/s11307-020-01505-9.

[82]	Bartosik P B, Fitzgerald J E, El K M, Yaseen M A, Vinogradov S A, Niedre M. Int. J. Nanomed., 2020, 15: 1709.

[83]	Tan X, Patil R, Bartosik P, Runnels J M, Lin C P, Niedre M. Sci. Rep., 2019, 9: 3366.

[84]	Woodard H Q, White D R. Br. J. Radiol. , 1986, 59: 1209.

[85]	Suo Y, Liu T, Xie C, Wei D, Tan X, Wu L, Wang X, He H, Shi G, Wei X, Shi C. Cytometry A , 2015, 87: 878.

[86]	Labelle M, Begum S, Hynes R O. Proc. Natl. Acad. Sci. U. S. A. , 2014, 111: 3053.

[87]	Ding Y, Wang J, Fan Z, Wei D, Shi R, Luo Q, Zhu D, Wei X. Biomed. Opt .Express , 2013, 4: 2518.

[88]	Zharov V P, Galanzha E I, Shashkov E V, Kim J, Khlebtsov N G, Tuchin V V. J. Biomed. Opt., 2007, 12: 51503.

[89]	Galanzha E I, Shashkov E V, Spring P M, Suen J Y, Zharov V P. Cancer Res., 2009, 69: 7926.

[90]	Galanzha E I, Shashkov E V, Kelly T, Kim J, Yang L, Zharov V P. Nat. Nanotechnol., 2009, 4: 855.

[91]	Galanzha E I, Kim J, Zharov V P. J. Biophoton., 2009, 2: 725.

[92]	Galanzha E I, Kokoska M S, Shashkov E V, Kim J, Tuchin V V, Zharov V P. J. Biophoton. , 2009, 2: 528.

[93]	Nedosekin D A, Juratli M A, Sarimollaoglu M, Moore C L, Rusch N J, Smeltzer M S, Zharov V P, Galanzha E I. J. Biophoton., 2013, 6: 523.

[94]	de la Zerda A, Kim J W, Galanzha E I, Gambhir S S, Zharov V P. Contrast Media Mol. Imaging , 2011, 6: 346.

[95]	Juratli M A, Sarimollaoglu M, Siegel E R, Nedosekin D A, Galanzha E I, Suen J Y, Zharov V P. Head Neck , 2014, 36: 1207.

[96]	Galanzha E I, Menyaev Y A, Yadem A C, Sarimollaoglu M, Juratli M A, Nedosekin D A, Foster S R, Jamshidi-Parsian A, Siegel E R, Makhoul I, Hutchins L F, Suen J Y, Zharov V P. Sci. Transl. Med., 2019, 11: 5857.

[97]	Sarimollaoglu M, Nedosekin D A, Menyaev Y A, Juratli M A, Zharov V P. Photoacoustics , 2014, 2: 1.

[98]	Moreau J E, Anderson K, Mauney J R, Nguyen T, Kaplan D L, Rosenblatt M. Cancer Res., 2007, 67: 10304.

[99]	Lee J, Li M, Milwid J, Dunham J, Vinegoni C, Gorbatov R, Iwamoto Y, Wang F, Shen K, Hatfield K, Enger M, Shafiee S, McCormack E, Ebert B L, Weissleder R, Yarmush M L, Parekkadan B. Proc. Natl. Acad. Sci. U. S. A. , 2012, 109: 19638.

[100]

Azarin S M, Yi J, Gower R M, Aguado B A, Sullivan M E, Goodman A G, Jiang E J, Rao S S, Ren Y, Tucker S L, Backman V, Jeruss J S, Shea L D. Nat. Commun., 2015, 6: 8094.

[101]

Saucedo-Zeni N, Mewes S, Niestroj R, Gasiorowski L, Murawa D, Nowaczyk P, Tomasi T, Weber E, Dworacki G, Morgenthaler N G, Jansen H, Propping C, Sterzynska K, Dyszkiewicz W, Zabel M, Kiechle M, Reuning U, Schmitt M, Lücke K. Int. J. Oncol., 2012, 41: 1241.

[102]

Gallerani G, Cocchi C, Bocchini M, Piccinini F, Fabbri F. J. Vis. Exp., 2017, 130: 56930.

[103]

Mandair D, Vesely C, Ensell L, Lowe H, Spanswick V, Hartley J A, Caplin M E, Meyer T. Endocr. Relat. Cancer , 2016, 23: 29.

[104]

Gasiorowski L, Dyszkiewicz W, Zielinski P. Neoplasma , 2017, 64: 938.

[105]

El-Heliebi A, Hille C, Laxman N, Svedlund J, Haudum C, Ercan E, Kroneis T, Chen S, Smolle M, Rossmann C, Krzywkowski T, Ahlford A, Darai E, von Amsberg G, Alsdorf W, Konig F, Lohr M, de Kruijff I, Riethdorf S, Gorges T M, Pantel K, Bauernhofer T, Nilsson M, Sedlmayr P. Clin. Chem., 2018, 64: 536.

[106]

Markou A, Lazaridou M, Paraskevopoulos P, Chen S, Swierczewska M, Budna J, Kuske A, Gorges T M, Joosse S A, Kroneis T, Zabel M, Sedlmayr P, Alix-Panabieres C, Pantel K, Lianidou E S. Clin. Chem., 2018, 64: 297.

[107]

Chen S, Tauber G, Langsenlehner T, Schmolzer L M, Potscher M, Riethdorf S, Kuske A, Leitinger G, Kashofer K, Czyz Z T, Polzer B, Pantel K, Sedlmayr P, Kroneis T, El-Heliebi A. Cancers ( Basel), 2019, 11: 933.

[108]

Li J B, Geng C Z, Yan M, Wang Y S, Ouyang Q C, Yin Y M, Wu L N, He J, Jiang Z F. Zhonghua Yi Xue Za Zhi , 2017, 97: 1857.

[109]

李健斌, 耿翠芝, 闫敏, 王永胜, 欧阳取长, 殷咏梅, 武林楠, 贺佳, 江泽飞. 中华医学杂志, 2017, 97: 1857.

[110]

Dizdar L, Fluegen G, van Dalum G, Honisch E, Neves R P, Niederacher D, Neubauer H, Fehm T, Rehders A, Krieg A, Knoefel W T, Stoecklein N H. Mol. Oncol., 2019, 13: 1548.

[111]

Wang H, Yue G, Dong C, Wu F, Wei J, Yang Y, Zou Z, Wang L, Qian X, Zhang T, Liu B. ACS Appl. Mater. Interfaces , 2014, 6: 4550.

[112]

Zhang H, Jia Z, Wu C, Zang L, Yang G, Chen Z, Tang B. ACS Appl. Mater. Interfaces , 2015, 7: 20477.

[113]

Jia M, Mao Y, Wu C, Wang S, Zhang H. Anal. Chim. Acta , 2019, 1082: 136.

[114]

Cheng S B, Wang M, Zhang C, Chen M M, Wang Y K, Tian S, Zhan N, Dong W G, Xie M, Huang W H. Anal. Chem. , 2020, 92: 5447.

[115]

Vermesh O, Aalipour A, Ge T J, Saenz Y, Guo Y, Alam I S, Park S, Adelson C N, Mitsutake Y, Vilches-Moure J, Godoy E, Bachmann M H, Ooi C C, Lyons J K, Mueller K, Arami H, Green A, Solomon E I, Wang S X, Gambhir S S. Nat. Biomed. Eng., 2018, 2: 696.

[116]

Hamza B, Ng S R, Prakadan S M, Delgado F F, Chin C R, King E M, Yang L F, Davidson S M, Degouveia K L, Cermak N, Navia A W, Winter P S, Drake R S, Tammela T, Li C M, Papagiannakopoulos T, Gupta A J, Shaw Bagnall J, Knudsen S M, Vander Heiden M G, Wasserman S C, Jacks T, Shalek A K, Manalis S R. Proc. Natl. Acad. Sci. U. S. A., 2019, 116: 2232.