中文   |   English   |   Email Alert
Fig/Tab
Advanced Search
image

Nanotechnology for Detection of Circulating Tumor Cells and Extracellular Vesicles

Jiali Wang , Ling Zhu , Chen Wang , Shengbin Lei , Yanlian Yang

Progress in Chemistry ›› 2022, Vol. 34 ›› Issue (1) : 178 -197.

PDF
Progress in Chemistry ›› 2022, Vol. 34 ›› Issue (1) : 178-197 DOI: 10.7536/PC210346
research-article
Scan to read & Share
Nanotechnology for Detection of Circulating Tumor Cells and Extracellular Vesicles
Author information +
History +
PDF

Abstract

Tumor liquid biopsy achieves accurate diagnosis of disease by detecting biomarkers in the body fluids which are of great importance for early diagnosis and dynamic monitoring of malignant tumors and are essential biomarkers for liquid biopsies. Circulating tumor cells (CTC) are tumor cells released into the blood from tumor tissue, and extracellular vesicles (EV) are membrane vesicles secreted by cells. Both of them carry tumor molecular information and are closely related to tumor progression and metastasis. Nanomaterials are widely used to detect CTCs and EVs due to their high specific surface area, unique optical, electrical, magnetic and other physical and chemical characteristics that can improve the detection sensitivity and specificity. Nanomaterial-based detection of CTCs and EVs has provided important information for tumor formation, progression, metastasis, and treatment response, and holds great potential in the clinical application. This article reviewes the progress of nanotechnology in three aspects: specific recognition, efficient capture or isolation, and identification of CTC and EV. It includes the functionalization of recognition probes on the surface of nanomaterials to improve the detection specificity and the latest advances in capture and identification of nanomaterials and nanotechnology. It may provide information for the development of liquid biopsy nanotechnology by discussing the advantages and challenges of liquid biopsy technology based on functionalized nanomaterials.

Contents

1 Introduction

2 Functionalized modification of CTC and EV recognition probes

3 Efficient capture of CTC and EV by nanomaterials

4 Identification and detection of CTC and EV

4.1 Signal amplification technology based on functional nanomaterials

4.2 Signal conversion technology based on functional nanomaterials

5 Integration technology of capture and detection of nanomaterials and microchips

6 POCT

7 Conclusion and prospect

Graphical abstract

Keywords

liquid biopsy / extracellular vesicles / circulating tumor cells / functionalized nanomaterials / in vitro diagnosis of tumor

Cite this article

Download citation ▾
Jiali Wang, Ling Zhu, Chen Wang, Shengbin Lei, Yanlian Yang. Nanotechnology for Detection of Circulating Tumor Cells and Extracellular Vesicles. Progress in Chemistry, 2022, 34(1): 178-197 DOI:10.7536/PC210346

登录浏览全文

4963

注册一个新账户 忘记密码

1 Introduction

The term "Liquid Biopsy" was first proposed in 2010, which refers to a new diagnostic concept related to the analysis of Circulating Tumor Cell (CTC) and Circulating Tumor DNA (ctDNA) in the blood to obtain the information of Tumor lesions in patients[1]. After that, the term was expanded to include almost all circulating biomarkers of Tumor origin, including CTC, ctDNA, Extracellular vesicles (Extra cellular Vesicle, EV), microRNA (Cell Free microRNA, cfmiRNA) in blood circulation, mRNA, long non-coding RNA, small RNA, protein markers, and most recently, tumor-educated Platelets (TEPs), and gradually became a viable adjuvant protocol for cancer detection[2]. Corresponding to liquid biopsy is tissue biopsy, which is a technique for pathological examination by cutting, forceps or puncture from the patient's body, and is currently the gold standard for tumor diagnosis and treatment decision-making. However, tissue biopsy also has some disadvantages: (1) tissue biopsy requires surgery or puncture to obtain samples, and the detection process is invasive; (2) It is difficult to obtain specimens from some tumor sites (for example, lung, pancreas, or brain), or it is difficult to obtain metastatic tissue in patients with recurrence and metastasis after surgery. (3) In clinical practice, it is impossible to perform continuous tissue biopsy on patients to achieve the purpose of real-time monitoring of treatment; (4) Because of the heterogeneity of tumors, only one tissue biopsy may miss important tumor clonal subsets related to clinical indications in the diagnosis of tumors.Alternatively, the information obtained by analyzing only the resected primary tumor (the current standard practice in oncology) may deviate significantly from the molecular characteristics of the tumor metastasis (genome, proteome, transcriptome, metabolome, etc.), even if the tumor metastasis has not yet formed a detectable mass at the time of examination of the primary tumor. In addition, metastases often coexist in different organs and are highly organ-specific and heterogeneous. (5) This process is time-consuming[3]. All these make tissue biopsy a great challenge and inaccessible, and it is these diagnostic problems that promote the rapid development of "liquid biopsy"[4⇓⇓~7]. On the contrary, liquid biopsy has obvious advantages in this process: (1) non-invasive, negligible damage to patients, and high patient compliance; (2) repeated sampling can be carried out to overcome information loss or deviation caused by tumor heterogeneity; (3) that detection can be quickly complete; (4) It can overcome the heterogeneity of the same tumor and the organ-specific tumor heterogeneity of the primary and different metastatic foci to a certain extent; (5) real-time monitoring of disease progression and drug response can be achieved; (6) It can provide information about the possible mechanism of drug resistance during tumor treatment. Of course, liquid biopsy also has some difficulties, such as high difficulty in detection technology, and it still needs a long way to go to become a clinical diagnostic standard. Liquid biopsy and tissue biopsy are complementary, and comprehensive detection can provide data information from different aspects, which is expected to achieve a comprehensive assessment of cancer[8,9].
Circulating tumor cells (CTCs) are tumor cells that are shed from primary or metastatic tumors into the peripheral blood circulation. During Tumor metastasis, the Epithelial-type tumor cells in solid tumors acquire an invasive phenotype through Epithelial-Mesenchymal Transition (EMT), break away from the constraints of the previous organization, and slough off from the primary or metastatic tumor, then the free tumor cells invade the surrounding stroma and enter the blood vessels through intravasation.In the form of CTC in the blood circulation, most CTC cells will undergo apoptosis or be eliminated by the immune system, and a small part of them will become dormant, escape the surveillance of the immune system or the killing of chemotherapeutic drugs, and then adapt to the new environment through Mesenchymal-Epithelial Transition (MET) process to form new tumors (metastases), as shown in Figure 1A. A large number of studies have shown that more CTCs can be obtained from the blood of patients with metastatic tumors, but their concentrations are usually very low, usually 1 to 10 CTCs per milliliter of whole blood, but there are 7×106 white blood cells and 5×109 red blood cells, which can easily mask the signal of CTC[10][11]. Therefore, there is a need to develop a technique capable of efficiently separating and detecting CTCs from blood. A variety of CTC capture and detection techniques based on physical, chemical, and biological characteristics such as cell size, density, dielectric properties, and surface biomarkers have been developed so far. Because the capture and detection of CTC involve surface and interface physical and chemical processes, nanomaterials have the characteristics of high specific surface area, unique physical and chemical properties such as light, electricity and magnetism, and easy functional modification.It provides abundant CTC efficient capture technology, signal amplification and conversion technology in the detection process, so researchers are developing CTC efficient capture and detection technology based on new nanomaterials or nanotechnology for clinical research of CTC. There are also some researchers who believe that direct detection of CTC in vivo has the advantages of higher sensitivity, real-time monitoring of changes in the level of CTC in vivo, and no need for redundant processing steps, so there are also reviews on the research progress of CTC detection technology in vivo, and those who are interested can refer to relevant review articles[12].
Extracellular vesicle (EV) is a kind of membrane vesicle secreted by cells, which widely exists in various body fluids, including blood, saliva, urine, cerebrospinal fluid and milk, and is an important biomarker for liquid biopsy[13]. Different types of EV have different secretory pathways. Microvesicle is formed by direct exocytosis of the cell, while the secretion of Exosome is caused by invagination of the cell membrane to form early endosomes, and then biomolecules such as proteins, DNA, RNA and lipids in the cell are wrapped in the vesicle to form multivesicular bodies, some of which fuse with the cell membrane to release the Exosome outside the cell, as shown in Figure 1b. According to the standard of Joural of Extracellular Vesicles, microvesicles and exosomes are collectively called Extracellular Vesicles (EV)[14,15]. In the process of EV formation, biological information molecules such as proteins, phospholipids, nucleic acids, amino acids and metabolites from the source cells are carried, and some transmembrane proteins, such as CD9, CD63 and CD81, which are currently considered as EV markers, are also included[16,17][18⇓~20]. Because the diameter of EV is in the nanometer size range (exosomes 30 ~ 150 nm, microvesicles 100 ~ 1000 nm), nanotechnology is very important to improve the capture, separation and detection of EV.Researchers have also developed a wealth of functional nanomaterials and new nano-detection technologies for efficient capture and detection of EV.
The application of biosensors based on nanomaterials in CTC and EV detection, the design of nanomaterials or microfluidic technology, and the detection principle can be referred to the relevant reviews and literatures[21⇓⇓~24][25,26]. Nanomaterials and nanotechnology have both commonness and individuality in the separation and detection of CTC and EV. In terms of separation, for biological methods, they all use probe molecules for specific recognition. However, because the number of CTCs in peripheral blood is rare and their size is large, more sensitive techniques are needed. Generally, CTCs are separated first and then analyzed downstream. EV is a kind of nanoscale membrane vesicle secreted by cells, which widely exists in various body fluids, so various technologies are often used to achieve the purpose of signal amplification. In addition, in addition to the use of some gold standard methods (such as ultracentrifugation), in most cases, separation and capture will be carried out at the same time, so there are obvious differences between the two. In terms of detection, biological information such as surface proteins and genes can be analyzed. Therefore, from the three levels of specific recognition, capture/separation and identification of CTCs and EVs, this paper introduces the functionalization of recognition probes for specific recognition of molecular markers on the surface of CTCs and EVs, respectively, and the use of functionalized nanomaterials or nanodevices for efficient capture and separation of CTCs or EVs.The nano material is used for signal enhancement or signal transduction of identification, analysis, characterization, detection and the like of a target CTC or EV, an integrated detection method of the nano material and a microfluidic chip, and a real-time detection technology. Figs. 1c-f represent the liquid biopsy nanodetection technology mentioned herein, wherein fig. 1C is the surface-enhanced Raman technology, fig. 1D is the microfluidic chip technology, fig. 1e is the nanoparticle capture technology, and fig. 1f is the fluorescence nanotechnology. In addition, this article will mainly introduce the latest progress of functionalized nanomaterials for separation and analysis of EV and CTC, while other liquid biopsy markers are not within the scope of this article, and other traditional biological methods and special microfluidic device design can be referred to other relevant literature for details[27,28].

2 Functional Modification of CTC and EV Recognition Probes

Magnetic Nanoparticles (MNPs), metal nanoparticles, Quantum dots (QDs), nanorods and so on are the main nanomaterials used for CTC and EV capture and detection. Antibodies, aptamers and polypeptides are the main recognition molecules for the functionalization of nanomaterials. These molecules are often coupled to nanoparticles or microarray surfaces of devices to specifically recognize CTCs and EVs. The methods of modification include physical adsorption, covalent binding and the use of special coupling molecules. The methods of physical adsorption and ionic binding usually have limited applications because of their lack of stability, the need for a large number of recognition molecules and high cost.The commonly used method is to modify the surface of nanomaterials or chips with recognition probes by covalent coupling[29].
One of the most common methods for covalent binding of probe molecules to nanomaterials is to use the amino groups in the probe molecules to couple to the materials through amidation reactions[29,30]. Carboxyl groups on the surface of nanomaterials undergo condensation reaction with amino groups under the action of water-soluble condensation agent 1-ethyl-3- (-3-dimethylaminopropyl) carbodiimide (EDC) to produce stable amide bonds, which is the classic condensation reaction "carbodiimide chemistry". In this reaction, EDC can activate the carboxyl group to form an intermediate activated ester O-acylurea, which then reacts with the amino group to form a stable amide bond. However, the intermediate mentioned above is unstable and will have side reactions, while N-hydroxysuccinimide (NHS) and hydroxysulfosuccinimide (Sulfo-NHS) can further react with the intermediate to reduce the occurrence of side reactions. The one-step reaction using EDC alone is therefore particularly suitable for biomolecules in which an amino group is present without a carboxyl group. The two-step activation modification method avoids the intramolecular and intermolecular coupling of the antibody containing amino and carboxyl groups, and the coupling efficiency is higher, so the two-step activation modification method is suitable for modifying the antibody on the nanomaterial.
Notably, these amino groups may be located in the antigen-binding region, and their use may reduce the recognition efficacy of the antibody. Therefore, some researchers have also developed strategies to improve the orientation of antibodies by modifying the sites of antibodies and coupling them with high-activity reactions. For example, Puertas et al. Modified the antibody on the surface of the nanoparticle by reacting the aldehyde group (located in the Fc region) in the antibody polysaccharide with the amino group modified on the nanoparticle to form a Schiff base[31]. The click chemistry reaction is another reaction for modifying an antibody, for example, the cycloaddition reaction between 1,2,4,5-tetrazine (Tz) and trans-cyclooctene (TCO) is used for modifying the antibody on the nanoparticle, and the reaction has the advantages of high activity, very high reaction rate and high product selectivity[32].
Because of the randomness of the orientation and binding sites of the probe molecules modified by the above methods on nanomaterials, researchers have developed maleimide chemical modification methods to achieve site-specific coupling. Because many recognition probes contain -SH group and -S-S group, and can easily self-assemble into a monolayer on the gold surface through the Au-S bond, the probe molecules connected with sulfhydryl groups can be directly assembled on the gold surface.The surface of the gold is modified with a sulfur-containing compound with a functional group at the end, and then the functional group at the end is coupled with the probe molecule directly or under the action of an activator (or a coupling agent), so that the stable combination of the probe molecule and the nano material is realized[33]. This method can ensure that the probe molecules have good orientation, but at the same time, the non-selectivity of maleimide to cysteine allows the reaction with thiols in serum, and the reaction requires the reduction or thiolation of the probe, which may change the conformation of the antibody.When the cysteine in the polypeptide is used to directionally assemble the polypeptide on the surface of a nanomaterial or a chip through the Au-S bond, the cysteine in other positions of the polypeptide reacts with the cysteine in the middle of the polypeptide sequence, resulting in random orientation and other disadvantages[30].
There are also researchers who can directionally couple probe molecules on the surface of nanomaterials through the non-covalent method of Biotin-Streptavidin. The most common methods of using biotin-avidin interactions are modification of probe molecules with biotin and modification of nanomaterials with avidin or its derivatives. Biotin directionally modifies the Fc region of the antibody by reacting with maleimide-biotin, a free sulfhydryl group obtained after reduction of the disulfide bond. Avidin is positively charged when the pH value is lower than the isoelectric point (pI), and the negatively charged nanomaterials can be functionalized by electrostatic adsorption to obtain avidin-modified nanomaterials. Then the polypeptide or antibody can be directionally assembled on the surface of the nanomaterial through the high-affinity interaction of biotin-streptavidin[30]. Biotin-Streptavidin method was used to couple the designed peptides to the surface of magnetic nanoparticles, and the peptides were targeted to epithelial cell adhesion molecule (EpCAM) and human epidermal growth factor receptor 2 (HER2) respectively, which could be used for efficient CTC capture with a recovery rate of up to 90%[34,35].

3 Functionalized Nanomaterials for Efficient CTC and EV Capture

At present, according to the physical properties of CTC such as size, density, charge, dielectrophoretic mobility and biological properties such as specific biomarkers on the surface of CTC, some commercial CTC separation and enrichment methods have been established. CTC separation and detection technology based on physical methods is not discussed in detail in this paper, and interested readers can refer to it[36].
The biggest obstacle to the study of CTC is that the number of CTC in peripheral blood is extremely rare and highly heterogeneous. Antibody modified immunomagnetic beads are the most widely used method for the separation of CTC with good reliability and reproducibility. Magnetic nanoparticles with superparamagnetic properties can be coupled to more tumor-associated biomarker affinity ligands for CTC capture due to their higher specific surface area. CellSearch System (Veridex) used magnetic nanoparticles modified with EpCAM antibody to capture EpCAM-positive CTCs under magnetic field, and then further identified cells with high expression of epithelial cell marker cytokeratin CK 8, 18, 19 and no expression of leukocyte common antigen CD45 as target CTCs by immunostaining. The circulating epithelial cell in vitro diagnostic (IVD) kit was approved by the US Food and Drug Administration (FDA) in 2004, approved by the China Food and Drug Administration (CFDA) in 2011 to enter the Chinese clinical application market, and approved by the State Administration of Market Supervision and Administration (NMPA) in 2020[37]. The CellSearch platform has been widely used to monitor the prognosis and disease progression of patients with metastatic breast, colorectal, lung, or prostate cancer[38].
AdnaTest (AdnaGen AG, Langenhagen, Germany) is another commercialized technology for CTC capture using antibody-functionalized magnetic nanoparticles, which enhances CTC capture and enrichment in breast, prostate, ovarian and colon cancers by modifying a variety of capture antibodies on immunomagnetic beads. AdnaTest technology can detect the gene and protein expression of specific tumor markers in CTC and compare them with primary and metastatic tumors in clinic to find the correlation between CTC molecular analysis and clinical outcome, and evaluate the diagnostic and prognostic value of CTC molecular analysis. In a clinical study evaluating the prognostic effectiveness of CTCs in metastatic prostate cancer, AdnaTest was utilized to detect CTCs in 62% (34/47) of patient samples, compared to only 45% with CellSearch (23/47). There may be two reasons for this difference: one is the difference of CTC capture antibodies, AdnaTest is a variety of capture antibodies, while CellSearch is a single antibody, so the former may capture more kinds of CTC; The other is the difference of detection technology. The former is to identify CTC by gene expression of KLK3, PSMA and EGFR, while CellSearch is to identify CTC by immunofluorescence technology[39]. There are also many technologies that rely on immunomagnetic beads to enrich CTCs, such as Magnetic-Activated Cell Sorting (MACS) system (Miltenyi Biotec), which is also based on EpCAM-modified Magnetic beads to complete the Sorting of CTCs[40⇓~42].
In addition, based on De Novo, our group designed a specific recognition peptide targeting EpCAM and named it Pep 10. The binding force of the peptide to the target protein was comparable to that of the antibody (1.98×10-9mol/L vs 2.69×10-10mol/L). Magnetic nanoparticles functionalized the peptide on the surface by biotin-streptavidin coupling method and were used for CTC capture.Pep10 @ MNPs were shown to have comparable capture efficiency (up to 90%) and purity (up to 93%) to anti-EpCAM @ MNPs for breast cancer, prostate cancer, and liver cancer cells added to human blood. In addition, a specific recognition polypeptide H13 targeting HER2 is designed, and the affinity with the target molecule HER2 is 6.5 kal/mol. Studies have shown that the capture efficiency of breast cells (SK-BR-3, MCF-7) and cervical cancer cells (SKOV3) is as high as 68.56%, 20.04% and 79.26%, respectively (Figure 2). The specific recognition peptide has the advantages of low price, stable performance and easy operation, which indicates that the technology of peptide functionalized modified magnetic nanoparticles has potential application value in clinical CTC detection[34,35].
Based on the polypeptide nanomagnetic bead capture CTC technology (TumorFisher), Peking University Cancer Hospital conducted CTC detection in more than 300 patients with metastatic breast cancer (MBC) from March 2014 to October 2016, of which 102 breast cancer patients receiving first-line treatment were included in the study[43]. Blood samples were collected and CTC counts were performed at baseline (n = 102) and first response (n = 72). The detection rate of CTC in peripheral blood was 69.6% at baseline. Patients with baseline CTC counts ≤ 2 CTC/2 mL had a longer median progression-free survival (PFS) than patients with baseline CTC counts > 2 CTC/2 mL (17.0 months vs 8.0 months; P=0.002)。 Patients with a CTC count of ≤ 2 CTCs/2 mL had the longest PFS (18.2 months; P=0.004)。 TumorFisher technology can further stratify the PFS of SD patients (P < 0.001) and provide more information for guiding treatment. Moreover, a baseline CTC count of ≥ 2 CTCs/2 mL was strongly associated with the development of liver metastases (P = 0.010). Overall, this study confirms that this technique has prognostic value for MBC patients receiving first-line chemotherapy, and is more sensitive to liver metastasis, which may help to monitor liver metastasis and provide important information for guiding clinical practice of breast cancer.
In recent years, immune checkpoint inhibitors have become a hot topic in the field of clinical cancer therapy. Its basic principle is that the binding between PD-1 protein highly expressed on the surface of T cells and PD-L1 ligand on the surface of tumor cells will cause the braking of T cell immunity.If the combination of PD-1 antibody and PD-L1 antibody is inhibited, T cells will initiate an immune program to kill tumor cells, so the expression of PD-L1 on the surface of tumor cells is one of the predictors of this immunotherapy. Yue et al. used TumorFisher technology to capture and detect CTCs in peripheral blood of 36 patients with advanced digestive tract cancer treated with PD-1 monoclonal antibody IBI308, and found that 1-70 CTCs (median 8) could be detected in 35 patients, and evaluated the expression level of PD-L1 protein on CTCs[44]. The results showed that the proportion of PDL1-overexpressing CTCs (Objective Response Rate) before medication could predict the efficacy of PD-1 drugs. The Objective Response Rate (ORR) of patients with PD-1 drug efficacy :ratio(PD-L1highCTCs/ total CTCs) ≥ 20% was as high as 64%, while the response Rate of patients with ratio < 20% was only 14%, that is, patients with PD-L1-overexpressing CTCs in peripheral blood were more likely to benefit from PD-1 drugs, and the higher the proportion of such cells, the higher the response rate. In addition, the median PFS was 4.27 months in patients with PD-L1highratio≥20% and 2.07 months in patients with < 20%, suggesting that patients with a high proportion of PD-L1highCTCs have a better prognosis. The technology was also applied to a study carried out by Xu Jianming and others in 307 Hospital of PLA. This is an open-label, dose-escalation and extension clinical study (NCT03463876) to evaluate the efficacy and safety of the PD-1 immune checkpoint inhibitor SHR-1210 in combination with apatinib in the treatment of advanced liver, gastric, and gastroesophageal junction cancer[45]. The results showed that 47.8% of patients with 95.1% CTC detection rate and more than 20% cells with high expression of PD-L1 in CTC would benefit, while those with less than 20% cells with high expression of PD-L1 had no objective remission (ORR was 0).
In order to verify whether Tumorfisher technology can be used for the detection of early lung cancer, Liang et al selected two non-small cell lung cancer (NSCLC) cell lines A549 and NCI-H1975 for experiments, and found that the binding affinity of polypeptide to A549 and NCI-H1975 was similar to that of anti-EpCAM antibody, and the capture efficiency of polypeptide nanomagnetic beads to A549 and UCI-H1975 was slightly higher than that of anti-EpCAM antibody[46]. In terms of clinical application, the detection rate of TumorFisher was 5/7 (71.4%) in 7 patients with early NSCLC, while no CTC was detected in 7 patients with CellSearch (0%), which indicated that TumorFisher had a strong potential clinical value in early lung cancer.
The new generation of detection technology combines the advantages of immunomagnetic beads and microfluidic technology, and the target CTC is captured and immobilized on the surface by immunomagnetic beads modified with antibodies or aptamers.Separated from the whole blood, and then the magnetically labeled cells are further separated by the microfluidic platform according to the cell size or inertial focusing, thereby improving the detection sensitivity of CTC. The platform consists of two parts: first positive enrichment using EpCAM antibody-modified or CD44/CD66b antibody-modified magnetic beads (CTC iChippos) or negative enrichment using CD45 antibody-modified magnetic beads (CTC-iChipneg), and then sequentially passing the cells through three channels, the first being a deterministic lateral displacement that removes red blood cells, platelets, and unbound magnetic beads from a whole blood sample based on cell size; The second is inertial focusing to exclude white blood cells; The third is magnetophoresis, which magnetically deflects magnetically labeled cells from unlabeled cells into separate channels[47]. Compared with CellSearch (7.5 mL < 30 CTCs), the number of CTCs isolated from CTC-iChippos was significantly higher (22/36; P < 0.001). The isolated CTCs were then subjected to molecular analysis by reverse transcription PCR (RT-PCR), and four of them were EML4-ALK positive (4/22)[48]. Another example of the combination of immunomagnetic beads and microfluidic technology is the Ephesia technology, which was originally used to capture B cells in the blood of leukemia patients and later modified to capture CTCs. Magnetic beads modified by EpCAM antibody self-assembled into periodic arrays under a strong magnetic field, forming a dense network structure to capture EpCAM-positive CTCs. This technique avoids expensive and complex microfabrication techniques and allows for different sizes, different geometries, and different flow rates, which has been shown to be applicable to the detection of clinical samples with high specificity[49]. In a study comparing the Ephesia technique to the CellSearch technique, CTCs were detected in clinical samples from patients with metastatic breast cancer (4/5) or metastatic prostate cancer (6/8), with a higher specificity than the CTC capture number from CellSearch[50].
Yang Chaoyong et al. Designed a bionic octopus microfluidic chip to capture CTC[51]. The chip is composed of a microcolumn array, each microcolumn is modified with aptamers and gold nanoparticles capable of specifically recognizing CTCs, and the gold nanoparticles are coupled and modified with a plurality of aptamers. Compared with single aptamer, multiple aptamers can produce multivalent effect, improve the affinity between aptamers and CTC, and increase the capture efficiency of CTC by 3 times. In addition, the captured CTC can destroy the Au — S bond between the aptamer and the gold nanoparticles through the ligand exchange reaction of glutathione molecules, thus achieving the non-destructive release of CTC. And can be used for realizing downstream cell culture and gene mutation detection. Then, the detection rate of CTC in tumor patients could reach 100% by blindly testing the peripheral blood samples of 41 normal, prostate cancer and colon cancer patients, including the samples of early tumor patients with T1N0M0 stage. The CTC release rate in the sample can reach more than 75%.
Qasaimeh et al. used the Chevron microfluidic probe technology to capture CTCs and CTC clusters. In this work, the multi-target detection of CTCs was realized by separating the microfluidic chip substrate from the probe[52]. Through the detection of CTC in the peripheral blood of prostate patients, it was found that 6 CTC/mL could be captured from patients with local metastasis, 280 CTC/mL could be captured from patients with distant metastasis, and CTC clusters up to 50 cells could be successfully captured.
In addition, Wang Shutao et al. Also used silicon nanowires to capture CTC[53]. A biochip was fabricated by in situ growth of silica nanowires on a commercial frosted glass slide and modification of EpCAM antibody for capture detection of CTCs. The biochip was highly specific for prostate cancer cell line (PC-3) with a capture efficiency of 85.4% ± 8.3%. The reason for the high capture efficiency is that the micro-sized silica nanowires can specifically recognize CTCs. The nanochip has been successfully applied to the detection of CTC in whole blood samples of prostate cancer patients. In addition, reduced graphene oxide films were also prepared to capture CTCs statically with high sensitivity without complex microfluidic operations[54]. The extremely high CTC capture efficiency is due to the negative charge and superhydrophilicity of the prepared reduced graphene oxide film, which can reduce the non-specific adsorption and improve the sensitivity. Tang et al. also utilized EpCAM and HCC cell-specific asialoglycoprotein receptor (ASGPR) modified dual-target functionalized graphene oxide film (DTFGF) to specifically recognize HCC-CTC[55]. The LOD for this method was 5 cells per milliliter.
Zhao et al. employed folic acid (FA) functionalized Hybrid Photonic Barcodes to capture and release CTCs[56]. The hybrid photonic crystal barcode is formed by two parts, a polyethylene glycol diacrylate (PEGDA) inverse opal structure for maintaining integrity, and a gelatin methacrylate (GelMA) gel filler for binding specific recognition of FA molecules and maintaining cell viability. Effective capture was demonstrated by four cancer cells, HeLa (epithelial, folate receptor positive, FR+),A02 (bone marrow, FR+), Raji (lymphoid, FR+) and A549 (epithelial, folate receptor negative, FR-), and CTCs could be controllably released by rapid digestion with trypsin.
Dong et al. designed a near-infrared (NIR) photoresponsive substrate, which combines the NIR photothermal effect of gold nanorods with the thermosensitive effect of thermosensitive hydrogel substrates to achieve efficient capture and in situ release of CTCs[57]. Substrates were prepared by blotting target cells onto gold nanorod pre-embedded gelatin hydrogels. The micro/nanostructures generated by cell imprinting can be used as artificial receptors for cancer cells to improve the capture efficiency. After the CTC is captured from the peripheral blood of a patient, the CTC can be released by rapidly dissolving the temperature-sensitive gelatin at 37 deg C, or the CTC can be released by NIR-mediated photothermal activation of the embedded gold nanorods. The method has been applied to capture CTCs from peripheral blood of patients, release CTCs alone, and perform genetic analysis of CTCs.
According to the size and biological properties of EV, the separation techniques of EV are divided into three categories: density separation, size separation and immune separation. Among them, density separation methods, such as ultracentrifugation or size separation, and size exclusion methods are widely used and relatively mature, and will not be repeated in this paper. In most immuno-separation methods of nanomaterials, the separation of EV and detection analysis are carried out at the same time, so the capture will not be described in detail in this section, but will be described in detail in the next section.

4 Identification and detection of CTC and EV

4.1 Detection Signal Amplification Based on Functionalized Nanomaterial

CTC plays a "seed" role in metastasis, while EV plays a "soil" role in the transformation of target organs and tissues and their surrounding microenvironment, and both carry molecular markers such as nucleic acids and proteins from tumor tissues.Therefore, CTC and EV have important clinical application prospects as biomarkers for prognosis of malignant tumors, dynamic tracking of disease progression, and even early detection of tumors. But until now, it has been a challenge to detect and isolate rare CTCs and to distinguish tumours from non-tumour-derived EVs in blood.
The usual identification method of CTC is the immunofluorescence method, in which the target cells are first confirmed to be nucleated cells by 4 ', 6-diamidino-2-phenylindole (DAPI) staining,Then the cells with high expression of epithelial cell marker cytokeratin CK 8, 18, 19 and no expression of leukocyte common antigen CD45 were further identified as target CTCs by immunostaining, which is the most commonly used CTC identification method in academia and industry. In addition, Fluorescence In Situ Hybridization (Fluorescence In Situ Hybridization) can also be used to detect chromosomal abnormalities of CTC cells, so as to identify CTC cells. As these two methods are commonly used in the identification of CTC, this paper will not repeat them, and the following focuses on the study of improving the sensitivity of CTC detection through nanomaterials or nanotechnology.
Raman spectroscopy is commonly used to analyze the structure of biomolecules with high spatial resolution. Raman spectroscopy-based biosensors can be used to detect CTCs[58]. However, the Raman scattering effect is usually very weak, and it has been found that the presence of metals can enhance the signal by as much as 1015 times, a technique known as surface-enhanced Raman scattering (SERS)[59]. The SERS nanoprobe is mainly composed of three parts: a metal core with various shapes and sizes, a Raman reporter, and a recognition part. Wu et al. Designed a gold nanoparticle (AuNP-MBA-rBSA) coated by Raman probe molecule 4-mercaptobenzoic acid (4-MBA) and encoded by reduced bovine serum albumin (rBSA), and then modified the complex with folic acid (FA) ligand to form AuNP-MBA-rBSA-FA SERS biological probe[60]. The FA on the surface of AuNP-MBA-rBSA-FA can recognize a variety of cancer cells (e.g., brain, kidney, breast, lung, cervical, and nasopharyngeal cancers). The AuNP-MBA-rBSA-FA SERS bioprobe was used to detect 10 to 10 000 HeLa cells mixed in 10000 HepG2 cells with a limit of detection (LOD) of 10 cells per milliliter. Ruan et al. chose to combine superparamagnetic iron oxide nanoparticles (SPION) with triangular silver nanoprisms (AgNPR) to form an ultrasensitive CTC capture, detection, and analysis system (Figure 3)[61]. 4-MBA was also used as a Raman signal reporter molecule, rBSA was used to increase the stability of the probe and reduce non-specific adsorption, and FA was used as a recognition probe to form an MBA-AgNPR-rBSA-FA SERS biological probe. In addition, SPION nanoparticles were coated with rBSA and FA to obtain SERS bioprobes of SPION-rBSA-FA. Then a hypersensitive SERS bioprobe system was designed by using the complex of MBA-AgNPR-rBSA-FA and SPION-rBSA-FA, which can complete CTC capture in blood (by FA), CTC enrichment (by magnetic SPION) and CTC trace detection in blood (by hypersensitive SERS bioprobe) with high specificity and sensitivity. The LOD of this method can reach 1 cell per milliliter. In addition, Xue et al. synthesized SPION-PEI @ AuNP MBA-rBSA-FA magnetic SERS probes of SPION and poly (ethylenimine) (PEI)[62]. This SERS bioprobe can be used for CTC enrichment (magnetic SPION) and CTC detection (bioprobe). The LOD of this method can reach the level of single cell.
The application of metal nanoparticles in electrochemical biosensors also has significant advantages, such as low detection limit, high stability, real-time response, good reproducibility and high specific surface area, which is conducive to the combination of electron transfer and biomolecules, and is a kind of nanomaterials with excellent Electroche miluminescence (ECL) performance[63]. For example, Shen et al. captured MCF-7 cells with magnetic nanoparticles modified with EpCAM antibody, distributed the captured MCF-7 cells on the electrode surface, and amplified the electrochemical current signal through the Rolling Circle DNA Amplification (RCA) reaction. LOD can reach 1 cell per milliliter[64]. Zhao et al. used BSA @ Ag @ Ir metal-organic nanoclusters (BSA @ Ag @ Ir MONs) for dual recognition and capture of CTC, and Orion carbon black 40 (Ocb40)//AuNPs modified electrode to enhance conductivity[65]; CP1 and CP2 DNA strands containing specific recognition aptamers EpCAM and MUCIN 1 were used as recognition probes, in which the CP1strand was linked to magnetic nanoparticles. When CTCs expressing both EpCAM and MUC1 appeared, the recognition probes CP1 and CP2 produced proximity effect and were able to capture the signal probe SP (HS-BSA @ Ag @ Ir MONs), thus forming CTC/CP1/CP2/SP complexes. The composite was then immobilized on the electrode by a magnetic field, and the current was measured by the differential pulse method. The LOD of this method can reach 1 cell per milliliter, and it can also be used to capture CTC from peripheral blood of patients to prove its role in clinical practice.
Liu and Zhao et al. Used aptamer-modified magnetic nanoparticles and carbon quantum dots/cobalt oxyhydroxide nanosheet system (CDs/CoOOH) to capture and detect CTC, and coupled FA to CDs.Then CDs were further assembled onto CoOOH to obtain fluorescence quenching FA @ CDs/CoOOH. When CTC was captured by aptamer-modified magnetic nanoparticles and ascorbic acid AA was added, AA could reduce CoOOH, so that the fluorescence of CDs was restored, and the signal could be detected by fluorescence spectrometer[66]. The LOD for this method was 5 cells per milliliter.
The traditional detection techniques of EV mainly include Nanoparticle tracking analasis (NTA), Dynamic Light Scattering (DLS), Western Blotting (WB) or Enzyme Linked Immunosorbent Assay (ELISA), Flow Cytometry (FCM) and so on[67]. These techniques can provide information about EV size, concentration, or expression of specific proteins. Among them, flow cytometry is a technique for rapid analysis of cells or other biological particles arranged in a single row in a flow stream. But the size of a single EV is too small to be detected by conventional flow cytometry. The EV needs to be connected to the surface of the microsphere functionalized by the antibody or directly connected to the surface of the microsphere to realize signal amplification, and then the EV is labeled by a specific recognition antibody, so that the EV can be successfully detected by FCM. The method can be used for detecting the GPC1 protein in the EV of a pancreatic cancer patient[68]. Li et al. Also used this method to detect the expression of EV EpCAM and HER2 in serum samples of patients for breast cancer diagnosis and molecular typing[69]. In the experiment, the EVs were captured onto the surface of the microspheres by the interaction between aldehyde groups and amino groups on the surface of EVs, and then the expression of EpCAM and HER2 on the EVs captured on the surface of the microspheres was detected by specific recognition antibodies. In breast cancer cell lines, the expression of EpCAM and HER2 in EV can well reflect the expression state of the source cell protein, which verifies the feasibility of this method. Clinically, through the detection of EV in the serum of healthy people (n = 7), HER2-negative breast cancer patients (n = 12) and HER2-positive breast cancer patients (n = 19), it was proved that EpCAM and HER2-positive EV could effectively diagnose breast cancer and classify HER2 molecules. The Receiver Operating Characteristic Curve (ROC) showed that the Area Under Curve (AUC) was as high as 0.972, which proved the high sensitivity and specificity of this method. In addition, the results of HER2 molecular typing of breast cancer by this method showed a high degree of consistency with the results of clinical "gold standard" immunohistochemistry, which further verified the accuracy of this method. Wang et al. Also used this method to diagnose brain tumors[70]. EGFR protein expression was detected in the serum-derived EVs from 12 healthy controls and 23 patients with glioma, and EGFR expression in EVs was found to be able to diagnose glioma with high sensitivity and specificity (AUC 0. 900, P < 0.0001). The expression of EGFR was positively correlated with the expression of Ki-67 in tumor tissues, indicating that the expression of EGFR in EV is also an indicator of the degree of malignancy of glioma. Another work is to use this method to prove that EpCAM and folate receptor FOLR1 can effectively distinguish invasive and non-invasive non-functional pituitary adenomas (NFPA) (AUC: FOLR1: 0.94, EpCAM: 0.88), and realize the invasive judgment of NFPA based on serum EV.The expression of epithelial markers (EpCAM and E-cadherin) and stromal markers (vimentin and N-cadherin) in serum-derived EVs and tissues was also measured, and it was found that compared with non-invasive NFPA,The expression of stromal markers was higher than that of epithelial markers in serum EV and tumor tissues of invasive NFPA, demonstrating that the trend of epithelial-mesenchymal transition in tumors was consistent with serum EV (Fig. 4)[70,71]. Koliha et al. described a flow technique based on fluorescently encoded microspheres for the analysis of different subpopulations of EV[72]. 39 kinds of fluorescent microspheres were used to modify different capture antibodies to capture EVs to form microsphere-EVs complexes, which made multi-target analysis by flow cytometry possible. The combination of the capture antibody and the fluorescently labeled detection antibody allows for simultaneous analysis of EVs with both surface markers, allowing for subpopulation detection of EVs. Natural killer cell- or platelet-derived EVs were found not to express CD9 and platelet-derived EVs did not express CD81 by detection of natural killer cell- or plateletderived EVs.
Raman technology can also be used to detect EV. Kong et al. Prepared SERS nanoprobes by self-polymerization[73]. The nanoprobe was composed of gold core silver shell core-shell composite particles coated with Raman reporter 4-ortho-aminothiophenol (pATP) and specific recognition antibodies (CD9, CD63, migration inhibitor MIF, and human glypican GPC1). They modified the slide substrate with Polydopamine (PDA) to provide enough space to couple antibodies to capture EVs. When EVs appear, SERS nanoprobes can bind to EVs and be detected by Raman spectroscopy. The LOD of this assay in 2 mL of sample solution is (~9×10-19moL/L). In addition, by analyzing 2 mL of clinical serum samples, MIF expression in EVs could be used to distinguish not only pancreatic cancer patients (n = 71) from healthy controls (n = 32), but also metastatic tumors from those without metastasis, as well as tumor lymph node metastasis (TNM) from stage P3 to P1-2 (diagnostic sensitivity 95.7%). Kwizera et al. fabricated SERS nanoprobes based on gold nanorods (AuNRs)[74]. In their design, a gold film was modified on a glass substrate, and an antibody that can specifically bind to EV was modified on the surface of the gold film using a 3D printed array template to capture EV. Then AuNR coated with organic dye carboxylic acid succinimide ester (QSY21) was used to further target EV (AuNRs and EV were bound by electrostatic adsorption), and finally a portable Raman spectrometer (TSI ProRaman spectrometer) was used to detect EV. The method can bind EVs instead of certain proteins, thereby improving the sensitivity, and the LOD is a 2×106EV/mL. The method also proves that the expression levels of HER2 and EpCAM in plasma-derived EVs of HER2-positive breast cancer patients are significantly higher than those of healthy controls (P ≤ 0.01).
Tian et al. prepared SERS nanoprobes by modifying gold nanostars @ 4-mercaptobenzoic acid @ gold nanoshell complexes (AuNS @ 4MBA @ Au) with divalent cholesterol (B-Chol) -labeled DNA aptamers[75]. By using CD9 antibody functionalized magnetic beads to capture EVs and then adding SERS probes, cholesterol can form a sandwich complex with EV lipid membranes through hydrophobic interactions. The complex can be enriched for EVs by magnetic trapping and deposited on a silica slide, and finally detected using a Raman spectrometer. The LOD of this method was 2.7×104EV/mL and tested on serum samples from healthy and liver cancer patients, demonstrating an increase in the number of EVs in cancer patients, with results comparable to those obtained with the latest technology (purification using the ExoEasy kit and quantitative analysis using the qNano, a nanoparticle analysis device based on tunable resistance pulse induction technology). In addition, Pang et al. reported a one-step assay for small RNAs in EV[76]. In their experiments, SERS probes were prepared using Fe3O4@Ag magnetic nanoparticles to link DNA aptamers and Au core @ Ag shell complexes with Raman reporter genes. Based on dual SERS biosensing technology, EV microRNA-10b(LOD=1.0 nmol·L-1) in blood samples can be accurately detected and the detection signal can be enhanced, which is of great significance for early cancer diagnosis. Wang et al. prepared three types of SERS probes using CD63 aptamer-modified gold shell magnetic nanobeads (MB@SiO2@Au) and aptamer-coated gold nanoparticles for Raman reporter and EV targeting, which could specifically bind to SK-BR-3, T84, and LNCaPEV simultaneously[77]. The application of this assay to real blood samples obtained from cancer patients shows that it is a promising tool for EV-based clinical cancer screening.
Colorimetric sensing technology is widely used in the detection of EV and CTC because of its simple operation. To increase the sensitivity of the colorimetric sensing technique, a signal amplification step may be employed. Wu et al. reported a complex composed of AuNPs modified with two different antibodies[78]. The AuNPs are first modified with CD9 antibody for EV capture, and when the antibody-modified AuNPs recognize the EV, they can be retained at the Test Line where the CD9 polyclonal antibody is immobilized. Then AuNPs modified by BSA antibody were added to form a sandwich complex with the captured EV to enhance the staining effect. This design increases the light intensity of the red band formed by the AuNPs on the test line. The system was used to detect EV isolated from MCF-7 human breast cancer cells with a LOD of 1.3×106 cells/mL, and the sensitivity was improved by two orders of magnitude compared with the conventional chromatographic immunosorbent assay. The sensing technology was also successfully used to detect EV of MCF-7 cells diluted in fetal bovine serum with serum EV removed by ultracentrifugation, demonstrating its potential application in practical diagnosis. Liu et al. combined the aggregation of AuNPs with other steps to amplify the signal[79]. They designed a pair of DNA-labeled antibodies that bind to surface proteins present on EVs and hybridize DNA strands to produce unique DNA signals. The double-stranded DNA signal is amplified twice by recombinant polymerase amplification in combination with transcription-mediated amplification to produce an RNA strand. The RNA product, which is directly proportional to the initial concentration of EV, can be detected by using AuNPs coated with oligonucleotides complementary to the RNA. Mutual recognition by the RNA promotes the aggregation of AuNPs and the red to blue color change, which can be measured by absorption spectroscopy.
Sun et al. Used the technology of thermophoretic enrichment combined with fluorescently labeled aptamers to achieve the determination of seven proteomes on EV surface and cancer classification[80]. On this basis, a new detection method combining thermophoresis and nano flare was further developed to achieve a highly sensitive detection of microRNA in 0. 5 μL serum-derived EV. Nanoflares can specifically recognize microRNA and produce fluorescent signals when they enter EV. The temperature is generated by laser irradiation to initiate thermophoresis, and the EVs are rapidly converged under the action of thermophoresis, so that the fluorescence signal generated by the nano flare is effectively amplified, and the detection sensitivity of the microRNA in the EVs is improved. Detection of tumor-associated microRNA expression in clinical serum-derived EV can be used for early diagnosis of ER+ of breast cancer.
Zhang et al. proposed a highly sensitive and specific diagnostic biochip based on photonic crystals for the detection of tumor-derived EV[81]. The quantum dots were coupled with GPC1 antibody by biotin-avidin reaction to identify and capture EV, and then the signal was amplified by the biomimetic periodic nanostructures formed by photonic crystals, and the signal intensity was positively correlated with the concentration of EV. This method can be used to distinguish the simulated serum samples of pancreatic cancer patients from normal serum samples, indicating that this method has great potential in clinical detection.

4.2 Detection Signal Conversion Technology Based on Functional Nanomaterial

In recent years, nanotechnology has great application prospects in detection. Nanomaterials can be used for efficient capture due to their high specific surface area, or used in signal conversion technology due to their good ECL performance or the fluorescence properties of metal materials, which shows the potential of nanomaterials in diagnostic applications, and further improves the specificity and sensitivity of capture and detection of CTC and EV.

4.2.1 Electrochemiluminescence technology

Electrochemiluminescence (ECL) is a widely used detection and analysis method, including electrochemical and chemiluminescence processes. In the electrochemiluminescence technique, a signal is generated due to an electrochemical interaction (redox reaction) between an analyte and an electrode surface, and a current signal is generated with the help of a signal converter. Zhang et al. Used antibody-modified magnetic nanoparticles to capture CTCs, and then deposited the CTC-captured magnetic nanoparticles on the electrode, and then used LiFePO4-coupled aptamers modified by gold nanoparticles to bind to the captured CTCs, and phosphate in the LiFePO4 reacted with molybdate to generate phosphomolybdate through redox reaction, resulting in an electrochemical signal[82]. The LOD for this method was 1 cell per milliliter.
Li et al. reported a method based on Photo electrochemical (PEC) for the detection of CTCs with low-toxic trimercaptopropionic acid (MPA) -encapsulated AgInS2 nanoparticles as the substrate, which showed high photoelectric conversion efficiency and generated strong photocurrent when excited by red light[83]. The nanoparticle is modified with an sgc8c nucleic acid aptamer which can be combined with the tyrosine kinase-7 protein on the surface of the cell, when the acute lymphoblastic leukemia CCRF-CEM cell appears, the photocurrent is significantly reduced, the cell can be detected, and the LOD is 16 cells per milliliter. In order to further improve the detection sensitivity, Liu et al. immobilized aptamer-modified Au @ CDs on a gold electrode, and after adding K2S2O8, the Au @ CDs showed strong electrochemiluminescence[84]. When the cells are present, the intensity of the electrochemiluminescence is reduced. The LOD for this method was 34 cells per milliliter. Yang et al. Modified the primer/circular DNA complex on the electrode and carried out rolling circle amplification to amplify a long ssDNA chain with many aptamer fragments, thus capturing rare CTCs efficiently in a multivalent manner. Then, AuNP modified with EpCAM and Horseradish Peroxidase (HRP) was used to recognize the captured CTCs and catalyze H2O2 to generate electrical signals for detection. LOD was 5 cells per milliliter (fig. 5)[85].
ECL biosensors for EV detection mainly use glassy carbon electrodes or gold electrodes. Boriachek et al. used dissolved CdSe QDs as ECL signal tags[86]. HER2 and FAM134B antibodies were attached to CdSe QDs by streptavidin-biotin reaction, and EVs were captured by CD9 or CD63 modified magnetic nanoparticles. When EV is present, sandwich complexes can be formed. Finally, Cd2+ can be obtained by dissolving the CdSe QDs complex in HNO3, and square wave anodic stripping voltammetry was used to measure EVs derived from breast cancer and colon cancer cells and serum samples, and the peak currents generated were related to the concentration of EVs.

4.2.2 Fluorescent signal probe transformation technology

Fluorescence refers to the light emitted by atoms or molecules when they return to the ground state after a previous excitation process. The target analyte can be specifically quantified by analyzing the change in fluorescence intensity or wavelength as a function of the initial concentration of the target analyte. Here, we will mainly introduce the biosensing technology in which nanoparticles with fluorescent properties are used as transduction elements. Inorganic fluorescent Nanoparticles mainly include quantum dots, metal nanoparticles, Upconversion Luminescent Nanoparticles (UCNPs) and polymers. Because fluorescent nanoparticles have good optical properties, such as high photostability, extremely wide excitation range, and narrow emission (allowing for large Stokes shifts), the limitations of many conventional fluorophores can be overcome[87].

4.2.2.1 Up-conversion luminescent nanoparticles

Lanthanide-doped UCNPs undergo a nonlinear photophysical process with an anti-Stokes effect, whereby low-energy radiation is typically converted into high-energy radiation, e.g., visible light (anti-Stokes shift), in the Near Infrared (NIR) wavelength range, and thus the wavelength required for fluorescence emission of UCNPs is shorter than the wavelength of absorbed light. This feature makes them particularly suitable for biological applications and the development of nanobiosensors, as the use of UV lasers is avoided, thereby minimizing the autofluorescence of biological samples[88,89]. Luminescence resonance energy transfer (LRET) and fluorescence resonance energy transfer (FRET) occur due to a very short distance interaction between the energy levels of two luminescent/fluorescent molecules, where the emission wavelength of the donor molecule coincides with the excitation wavelength of the acceptor molecule,Thus, when they are close enough (7-10 nm), the excitation of the donor molecule will induce the receptor to fluoresce, so the UCNP coupled to the recognition molecule is used as an energy donor in the development of sensors that bind to other fluorophores or NP receptors[90]. Wang et al. used tetramethylrhodamine (TAMRA) and UCNPs to modify the DNA aptamers EpCAM-1 and EpCAM-2, respectively, that target EpCAM present on cell-line-derived EV membranes (EpCAM-1-TAMRA, EpCAM-2-UCNPs)[91]. After aptamer-EV binding, the two DNA strands are close to each other, and the distance between the energy donor (UCNPs) and the acceptor (TAMRA) decreases, thus promoting the LRET process. Since the emission wavelength of the donor coincides with the excitation wavelength of the acceptor, infrared light excites the UCNPs to produce ultraviolet light, which in turn excites the TAMRA molecule (585 nm). And there is a linear relationship between the emission wavelength and the concentration of EV. If no EV is present, no yellow emission is detected. This method was successfully used to verify the different expression of EpCAM in EVs derived from breast cancer cell lines (MDA-MB-231, MCF-7, MCF-10a) with different degrees of malignancy, and the LOD of the LRET sensor technology was verified to be 8×104EV/mL. Consistent with the idea of the previous design, the research group used gold nanorods as acceptors and immobilized UCNPs on oxidized filter paper supports as donors. Paper-UCNP and AuNRs were modified with two fragments of CD63 aptamer (capture probe CP.5 '-NH2-CACCCCACCTCGC-3') and detection probe (DP, 5 '-TCCCGTGACACTAATGCTA-HS-3'), respectively, for targeting to EV. In the presence of EV, the targeted CD63 protein binds to both strands of the aptamer bound on AuNR and UCNP-paper, respectively, shortening the distance between the acceptor and the donor, thereby enabling LRET to occur. Therefore, the green luminescence of UCNPs is quenched under 980 nm excitation. When there is no EV, there is no CD63 protein, so the capture probe CP can not bind to the detection probe DP, LRET will not occur, and the imaging of green luminescence will not change, which can be clearly captured by the Charge Coupled Device (CCD) of the optical imaging system. Therefore, using the relationship between the quenching rate of upconversion luminescence and the concentration of EV, the highly sensitive detection of EV derived from liver cancer cell line can be accurately realized, and its LOD is 1.1×106EV/mL[92].

4.2.2.2 Quantum dot

Quantum dots have also been widely used in fluorescence-based biosensors due to their high quantum yield, symmetrical fluorescence peak shape, narrow emission spectrum and unique photophysical properties[93,94].
Zhang et al. used a quantum dot encoded magnetic microsphere system (iFMNS) to capture and detect CTCs[95]. CdSe/ZnS QDs and magnetic nanoparticles were introduced into poly (styrene-maleic anhydride) microspheres by microemulsion and solvent evaporation methods, and then the EpCAM antibody was coupled to the microspheres by biotin-avidin reaction to recognize CTCs, and finally the CTCs were separated by magnetic interaction, with a capture efficiency of 70% ~ 95%. CTCs isolated by this method can be used for further culture or downstream analysis (RT-PCR, IHC). Chen et al. Used multiphoton microscopy and antibodies coupled to quantum dots to study real-time CTC and CSC subpopulation imaging in the blood of living animals[96]. Pancreatic cancer cells expressing fluorescent proteins are injected subcutaneously into the earlobes of mice to form solid tumors, which can be observed microscopically as they metastasize through the blood.By simultaneously performing imaging studies on specific subsets of CTCs using QD525 quantum dots labeled with CD133 and CD24 antibodies, CTCs with higher metastatic potential, such as CD24+ and CD133+CTC, can be identified in animals, enabling in vivo detection of CTCs.
Bai et al. used carboxylated polystyrene microspheres modified with CD9 antibody to separate and enrich EVs, while using three antibody-labeled QDs (carcinoembryonic antigen (CEA), excitation: 490 nm, emission: 625 nm[97]; Cytokeratin CK-19 fragment (Cyfra21-1), excitation: 490 nm, emission: 525 nm; Progastrin-releasing peptide (proGRP, excitation: 490 nm, emission: 585 nm) for multi-target detection of tumor-derived EV. The method is used for analyzing EV derived from lung cancer and endothelial cell lines, the fluorescence intensity of EV derived from lung cancer is about 6 to 10 times higher than that of EV derived from endothelial cells, and the expression levels of related proteins of the EV from the lung cancer cells with different malignant degrees are different. In addition, the detection of clinical plasma samples from cancer patients using this method also showed good diagnostic ability, which could distinguish EV from lung cancer plasma and healthy controls under inverted fluorescence microscopy, and had good consistency with the test of serum markers commonly used in clinic (AUC of CEA, Cyfra21-1 and ProGRP by ROC curve were 0.84, 0.85 and 0.84, respectively). These results provide a promising approach for EV biomarker detection and early cancer diagnosis.

4.2.2.3 Metal nanoparticles

Metal nanoparticles can be used as fluorescent labels due to their inherent fluorescent properties. Many metal nanoparticles can also be synthesized by coupling fluorescent groups or ligands on their surfaces. For example, Zhai et al. constructed a biosensing platform for detecting microRNA-1246 in plasma-derived EVs based on gold nanoparticles[94][98]. The AuNP probe consists of AuNP, Cy5-labeled DNA, and capture DNA (Cy5-labeled complementary DNA sequences), and the fluorescence signal is initially suppressed (the capture DNA sequences are initially paired). The probe can enter the EV, and then the capture probe DNA is combined with the microRNA-1246 in the EV to release the Cy5-labeled DNA fragment, and the recovery of the fluorescence signal of the free Cy5-labeled DNA can be detected by a fluorescence microscope. The whole experimental process needs 4 H and only 40 μL of plasma, which has high enough sensitivity. Using this method to detect miR-124 in plasma, 46 breast cancer patients were successfully distinguished from 28 healthy controls (P < 0.0001, sensitivity: 100%, specificity: 92.9%). He et al. used CD63 aptamer-modified copper oxide nanoparticles (CuO NPs) with cholesterol-modified magnetic nanoparticles to trap EVs and form a sandwich complex structure[99]. The CuO nanoparticles were subsequently dissolved in an acidic solution (HNO3) to obtain copper (II) ions, which were reduced to fluorescent copper nanoparticles (CuNPs) in the presence of sodium ascorbate and polythymine (Fig. 6). The fluorescence intensity of CuNPs was proportional to the content of EV, and the LOD of this method was 4.8×107 EV/mL. Gao et al. used the rolling circle DNA amplification (RCA) reaction to detect EV, and used the rolling circle amplification (RCA) reaction to produce a long-chain DNA hairpin structure, which contains multiple functional domains, such as CD63 aptamer sequence, connector sequence modified by AuNPs, spacer sequence, etc., with complementary base pairs to form a hairpin structure[100]. In the presence of EV, the CD63 aptamer sequence binds to EV, and the hairpin structure changes its conformation, exposing the linker sequence. The fluorescent AuNP-complementary bioconjugate (AuNP-L/cL) can then pair with this linker sequence by strand displacement, thereby releasing the fluorescent cL probe. The fluorescence signal of cL was proportional to the concentration of EVs, and the DNA-wrap-around complex was formed simultaneously. The captured EVs could be recovered by centrifugation with a recovery rate of 80% and a LOD level of 1×108EV/mL.
De la Zerda et al. used gold nanorods as a contrast agent to label tumor cells and enhance the contrast of tumor cells, and first applied speckle-modulating OCT (SM-OCT) technology to the detection of single cells in the blood circulation system of animal models[101].

4.2.2.4 Other

Peng et al. Previously designed a small molecule NIR fluorescent dye called MLP, which has a high affinity with aminopeptidase N (APN), an enzyme highly expressed in tumor cells[102]. On this basis, a method for simultaneously separating and detecting CTCs by modifying Fe3O4 magnetic nanoparticles (MB-MLP-EpCAM) with EpCAM and MLP is proposed. The MB-MLP-EpCAM has a capture efficiency of more than 85% for CTCs. The most important thing is that the real-time identification and monitoring of CTCs in vivo can be achieved clinically by using the characteristics of fluorescence imaging.

4.2.3 Surface plasmon resonance technique

Surface Plasmon Resonance (Surface Plasmon Resonance, SPR) based techniques have attracted much attention in biomarker detection due to their ability to achieve label-free and real-time detection[103]. Gold nanoparticles can improve the sensitivity through the electronic coupling interaction between the localized surface plasmon resonance and the surface plasmon resonance electromagnetic wave of gold nanoparticles[104]. Wang et al. reported a SPR-based AuNPs aptamer sensing technique for EV detection with high sensitivity and superior specificity[105]. First, the breast cancer cell line MCF-7 derived EV was captured by a DNA aptamer modified in a gold membrane; An aptamer (T30) -coated AuNPs is specifically bound to the captured EV, and an A30 aptamer is modified on the surface of another AuNPs, which can be paired with the captured T30-coated AuNPs through the principle of base complementary pairing, thus constructing a SPR biosensor with dual AuNP amplification signals. The LOD of this sensing technique is 5×103EV/mL, which is 104 times higher than that of ELISA. Im et al. designed a Nano-Plasmonic Exosome (nPLEX) sensor array[106]. The main design idea is to etch a periodic nanopore array on the gold film, and the size of each nanopore is 200 nm, which matches the size of EV, so as to improve the sensitivity of detection. Polyethylene glycol (PEG) was used to modify the gold surface, and the CD63 antibody was attached to the PEG chain. When the EV appeared and bound to the sensor, its local refractive index changed, which shifted the spectral peak. The amplitude of the spectral shift was related to the molecular mass density covering the sensor surface, so the EV protein could be quantitatively analyzed. More importantly, the signal can be significantly enhanced by using AuNPs, which can be increased by 20% for 10 nm spherical AuNPs and 300% for 50 nm Au nanostars. The LOD of this method is about 3000 EVs, which is 100 times higher than that of the traditional ELISA. Ascites samples from ovarian cancer patients and healthy patients were detected by the sensor, and it was found that the levels of EpCAM and CD24 were elevated in ovarian cancer patients, and the diagnostic accuracy could reach 97%. In addition, the experiment can be completed in only 30 minutes, and the patient's ascites sample can be used. Liang et al. developed the nanoplasmon-Enhanced Scattering (nPES) technology to capture and detect EVs[107]. EVs were captured by modifying the microarray with CD81 antibody, and then the captured EVs were further targeted with AuNP- and AuNR-conjugated CD63 and CD9 antibodies, respectively. This binding can enhance the local surface plasmon effect, thus enhancing the sensitivity and specificity of EV detection. With only 1 μL of sample and 5 hours of analysis time, EVs from healthy people, pancreatic cancer patients and pancreatitis patients can be successfully distinguished, thus realizing the in situ diagnosis of pancreatic cancer. Its performance is better than ELISA, and its specificity and sensitivity are greatly improved, which makes the device a promising diagnostic tool.

5 Integrated Capture and Detection Technology for Nanomaterials and Chip Integration

Microfluidic chips generally have the advantages of low sample consumption, fast detection, simple operation, multi-functional integration, small size and portability, which can achieve the purpose of detection and capture at the same time. Yang Chaoyong et al. Developed a capture and enrichment Chip (SDI-Chip) combining hydrodynamic separation and specific recognition with CTC[108]. The chip consists of a microcolumn array, and the surface of the microcolumn array is modified with a specific recognition antibody. According to the principle of Deterministic lateral displacement (DLD) separation, the microcolumn array can be designed to achieve selective hydrodynamic regulation of cell size at the micron scale[51]. CTC will move along the offset direction of the microcolumn and continuously collide with the microcolumn to achieve specific recognition and capture due to its large size, while blood cells will move along the direction of liquid flow and rarely collide with the microcolumn to avoid non-specific adsorption due to its small size. The design effectively combines the differences of CTC in physical properties and surface markers and background cells, and realizes the efficient and high-purity synergistic capture of CTC. By testing a large number of peripheral blood samples from clinical cancer patients, they verified the potential application value of the developed chip technology in cancer staging diagnosis, efficacy monitoring and so on. Zhang et al. constructed an extracorporeal circulation system based on a microfluidic chip to detect and monitor CTC in vivo[109]. The system is a combination of microfluidic chip and EpCAM-modified magnetic immune nanoparticles, which can capture and monitor CTCs in blood without any pretreatment, and has higher capture efficiency without any irreversible damage to living animals.
Microfluidic chips are also widely concerned in the detection of EV. He et al. First reported an integrated microfluidic method, which can directly separate EV from cell culture supernatant or serum samples, and can analyze the expression of EV surface proteins without ultracentrifugation or other separation methods[110]. The design idea of the chip is as follows: a Polydimethylsiloxane (PDMS) chip is divided into three channels connected in series. Firstly, immunomagnetic beads modified by EpCAM antibody are used for EV capture and enrichment (the first stage of capture); The target proteins (IGF-1R and P-IGF-1R) in the EV were then cleaved and the cleaved proteins were captured using immunomagnetic beads (second stage capture) and finally using a chemiluminescence-assisted immunosandwich assay (third stage assay). Briefly, a plasma sample is mixed with EV-specific antibody-labeled magnetic beads and injected into the inlet # 1 introduction first zone; Lysis buffer was then injected through inlet # 2 and the flow was then stopped for co-incubation with the captured EVs. The products of EV lysis flowed into the serpentine channel and were incubated with magnetic beads labeled with antibodies specific for EV proteins injected through the two side channels to capture the released capsular proteins. Finally, the magnetic beads capturing the protein are retained in a second chamber into which a detection antibody and a chemiluminescent reagent are sequentially introduced for sandwich immunodetection of the protein marker. Patients with early stage non-small cell lung cancer (stage II) were distinguished from healthy controls by this method (microfluidic: P = 0.0001, CV = 11.2%; ELISA: P = 0.0097, CV = 56.4%). The plasma volume required by this method is only about 1/100 of the conventional method, and a lot of experimental time is saved, indicating that this method has the characteristics of efficient EV immunocapture and high sensitivity of specific protein analysis. Zhao et al. developed a simple microfluidic technology (ExoSearch) to capture serum-derived EVs (EVs) of ovarian cancer patients in situ by magnetic beads modified with anti-CD9 antibody, followed by multi-target detection of surface proteins with fluorescently labeled EpCAM, CA125, and CD24[111]. Finally, 15 ovarian cancer patients could be distinguished from healthy controls using this method (AUC = 1.0, P = 0.0009).

6 Just-in-time test technique

Point-of-care testing (POCT), also known as on-site rapid testing, is a clinical testing method that can be carried out at the bedside of patients without complex equipment and professional laboratory inspectors. At present, the most commonly used POCT method is colorimetric sensing technology. Colorimetric sensing technology is very important for practical POCT applications because of its ease of operation. In general, colorimetric sensing technology can easily and instantly observe color changes with the naked eye, without the need for any other analytical instruments to produce a "yes/no" answer or a semi-quantitative result.
Jiang et al. Used the aptamer of CD63 to recognize EV and protect AuNPs from aggregation in high salt solution to achieve EV detection[112]. In the presence of EV, the specific binding between EV surface proteins and the corresponding aptamers occurs, and the decrease of aptamers on the surface of AuNPs leads to the aggregation of AuNPs, resulting in a color change from red to blue, which can be measured by UV-visible spectroscopy. The sensor is used to discriminate EVs from different cancer cell lines. In addition, the technology enables the detection of the expression of a particular cell line-derived EV protein by using an aptamer that binds to a tyrosine kinase-7 protein that is overexpressed in human acute lymphoblastic leukemia cells. He et al. Used immunomagnetic beads with CD9 antibodies to capture EVs from HepG2 cells[113]. Then, BChol labeled DNA was inserted into the EV membrane, and the single DNA strand on the membrane could promote the hybridization reaction of the short DNA strand linked to HRP. In the presence of H2O2, 3,3 ', 5,5' -tetramethyl benzidine (TMB) was oxidized and catalyzed to produce a blue signal. The obtained LOD was 2.2×106EV/mL, which was 100-fold higher than that of conventional ELISA. However, the use of native enzymes as signaling tags has many disadvantages, such as the need for complex purification processes and careful storage conditions. Recently, various nanoscale enzymes have attracted wide attention due to their advantages such as low cost, batch production capability, and high tolerance to pH and temperature changes. Chen et al. isolated EVs by anion-exchange magnetic nanoparticles, and then added aptamer-modified iron oxide nanoparticles (MNPs) for EV detection[114]. The rationale for this experiment is that aptamer-modified MNPs have weak intrinsic HRPase activity, and the catalytic color changes when TMB and H2O2, the substrates of peroxidase, are present. Compared with bare MNPs, the presence of aptamers on the surface of MNPs increased the HRP activity. When EV was present, these aptamers could bind to EV by molecular recognition and desorb from the surface of MNPs. After aptamer desorption, the catalytic activity of these MNP decreased, and then the color change decreased when TMB and H2O2 were present. This color change can be detected by UV-Vis spectroscopy, and there is a linear relationship between the absorbance and the EV concentration. The LOD of this technique is 7×106EV/mL, and the LOD of detection is 3.5×106EV/mL for EV isolated from simulated prostate cancer plasma samples. Song et al. Prepared a kind of sEV artificial magnetic colloid antibody (artificial magnetic colloid antibodies, MCAs) by polymer molecular imprinting method, which can be used for rapid identification and separation of sEV from cell culture supernatant and serum[115]. With magnetic nanoparticles (Fe3O4@SiO2) as the core of the carrier and sEV as the template, the organosilicon recognition shell was formed by polycondensation of organosilane monomers. The surface of the MCAs is provided with an sEV three-dimensional imprinting groove, so that the sEV can be efficiently recognized and combined through the shape and the size. And can be use for that determination of sEV from cell culture supernatant and serum. Compared with ultracentrifugation, MCAs can capture sEVs in 20 min, and the amount of sEVs obtained is three times that of ultracentrifugation. In addition, by combining the MCAs separation technology with the volume bar chart chip technology (MV-chip), it is used for the analysis of protein markers on the surface. By studying the expression of sEV surface protein markers in plasma from ovarian cancer patients and healthy controls, it was found that the levels of EpCAM and CD24 on the surface of sEV in plasma samples from ovarian cancer patients were significantly higher than those in healthy controls. The results of ROC analysis showed that using MV-chip to detect multiple specific sEV markers could effectively distinguish OvCa patients, which provided strong support for the development of POCT diagnosis of ovarian cancer.
ECL biosensors based on screen-printed electrodes have attracted much attention in recent years due to their low cost, simple operation and flexible design, and are expected to realize POCT. Jeong et al. designed a portable eight-channel device for screening EV in plasma samples from ovarian cancer patients by using magnetic beads to separate and enrich EV, antibody recognition and enzymatic signal amplification combined with screen-printed electrodes[116].
Due to the rarity of CTCs in peripheral blood, they can be easily masked by normal cells. In addition, the heterogeneity of CTCs and the lack of CTC-specific biomarkers challenge the sensitivity and specificity of POCT technology. Recently, Yang et al. Used aptamer-modified nanoparticles (oxygen) to move red ink, and the moving distance was linear with cell concentration[117]. LOD can be as low as 1 cell per ml. Gan and Xiang et al. Used two antibodies as capture probe and signal probe respectively to realize CTC detection based on POCT[118]. The specific process is as follows: SK-BR-3 cells are used to simulate CTCs in blood, EpCAM antibody functionalized magnetic beads are used as capture probes to enrich and separate tumor cells, and then HER2 antibody and invertase co-modified polystyrene microspheres are used as signal probes. The substrate sucrose can be converted into glucose under the action of invertase. Then CTC detection can be realized by using a common blood glucose meter sensor. The LOD for this method was 7 cells per milliliter. Based on the interaction of borate esters, Liu et al. reported the electrochemical and colorimetric detection of CTCs[119]. Aptamer-modified magnetic beads were used to capture CTCs, and then reduce the number of ferrocenylboronic acid (FcBA) or 4-mercaptophenylboronic acid (MPBA) molecules by forming borate ester bonds, which led to the reduction of the electrochemical signal of FcBA or the prevention of MPBA-induced aggregation and color change of AuNPs. FcBA can be detected by differential pulse voltammetry, and the aggregation and color change of AuNPs induced by MPBA can be read directly. The LOD of that method can reach 50 cell per milliliter.

7 Conclusion and prospect

Tumor heterogeneity is one of the characteristics of malignant solid tumors, which is very important for the classification, diagnosis and treatment of cancer. The study of different subsets of CTCs and EVs provides some insights into tumor heterogeneity, which can be used to study tumor heterogeneity within and between cancer patients, but it is still challenging to trace the tissue source of detection signals representing the source of heterogeneity and to confirm the clinical diagnostic significance of signals.
CTC detection has accumulated a lot of experience in clinical application, and some products have passed the product registration of NMPA. Although great progress has been made, there is still a long way to go in CTC-based liquid biopsy. Because the rarity of CTC is still a great challenge for the improvement of the sensitivity and stability of the detection technology, nanotechnology will continue to bring continuous technical input for the improvement of CTC detection technology, and it is very promising to use dual-functional nanomaterials such as magnetic core-shell nanoparticles to enrich and detect CTC to reduce false negatives. Multi-target detection is another method to improve the detection sensitivity by capturing and analyzing CTC subpopulations. Nanomaterials are ideal materials for developing multi-target detection methods, because each nanoparticle can be coupled with different specific recognition probes. In addition, combining nanomaterials with microfluidic devices is also an active strategy for CTC separation and detection. These technologies have brought clinical benefits to more cancer patients through continuous clinical practice.
Another future direction for CTC testing will be molecular analysis of CTCs, which may better inform clinical decision making. However, the ability to reliably and efficiently characterize the gene and protein expression profiles of CTCs is still limited. SERS NPs may revolutionize protein analysis at the single-cell level. SERS NPs allow high-throughput analysis of CTC protein markers. Multicolor SERS NPs (> 10 colors) can be prepared without changing the size and shape of the nanostructures. Therefore, multicolor SERS NPs will bring hope for the analysis of CTC surface proteins.
However, the basic research of EV is in full swing, and its clinical application is still in its infancy. Despite advances in the field, sample heterogeneity can affect the effective analysis of EV. Many factors, including age, gender, and body mass index, are known or suspected to affect EV secretion. Therefore, more techniques are needed to examine the effects of sample heterogeneity on the number, function, and biogenesis of EVs. EV-based markers should be detected by a few simple processing steps, preferably directly in cell-free biological fluids. In addition, further technological advances are needed to specifically detect tumor-derived EV subsets in complex mixtures because human biological fluids contain mixtures of EVs from different cell types.
Sensitivity and specificity are important issues in EV detection, and multi-target detection is the first choice to improve sensitivity and specificity. Orientation on NPs can greatly improve their sensitivity, and by controlling the functionalization process, it can help many detection platforms to improve their performance. Systems that integrate the separation and detection of EVs into the same device hold great promise as automated POCT devices. The separation and high-purity recovery methods of EV with high yield should also be paid attention to.
Finally, there are various methods to isolate CTCs, and the lack of uniform standards also leads to different final analysis results. Most devices using nanomaterials to analyze EVs still need to use traditional methods to extract EVs from cells and samples. Uch as ultracentrifugation, density gradient centrifugation, or size exclusion chromatography. These conventional extraction methods are often time consuming, require skilled technicians to perform, and may result in loss of the sample as well as contamination. Therefore, without standard extraction methods, it is difficult to establish detailed criteria to compare and evaluate the performance of these detection platforms. Moreover, many reports lack basic information about CTC and EV or important analytical indicators of detection technology (such as precision, accuracy or detection limit), which limits the application of these detection methods. In addition, even if the detection limit is stated, it is difficult to make a real comparison because of the different units of quantification between different research methods. Therefore, it is urgent to formulate more standards related to CTC and EV. In addition, most studies have isolated EV from cell lines or prepared simulated peripheral blood samples by diluting cancer cells in PBS buffer solution, which can not represent the real complex environment of blood. Although some of them include patient samples, the number is small, and the results of statistical data need to be optimized by using a large number of patient samples. Therefore, more studies are needed to establish simulated samples to make the study closer to the real environment of blood.
To sum up, the CTC and EV detection technology itself needs to be improved in the following four aspects: (1) Improve the specificity, sensitivity and multi-target detection capability of the technology. (2) Improving the stability of nanoparticles, because most of the detection signals of biosensors based on nanoparticles come from nanoparticles, and the structural stability, dispersion stability and surface modification stability of nanoparticles are the guarantee of the stability of detection signals. (3) The sensor equipment is portable as far as possible and the cost is low, which is easier for clinical application. (4) Develop more technologies related to molecular analysis of CTCs and EV surface proteins and genes. (5) Establish corresponding standard samples, standard materials, standard testing methods and clinical guidelines and consensus, so that academia, industry and regulatory authorities can better evaluate the performance of analytical methods and promote the performance of analytical methods.So as to better play their clinical application value, such as early diagnosis, prognosis, clinical medication guidance and disease progression monitoring. Although the research based on CTC and EV in liquid biopsy still faces many problems, it is believed that the development of biosensors combined with nanoparticles can play a key role in the field of advanced liquid biopsy technology. In the near future, sensitive, accurate, cheap, convenient, multi-target combined and highly integrated nano-biosensor systems for liquid biopsy will play an increasingly important role in the field of life and health.

References

Publishing order | Descend order by publishing year | Descend order by cited within
[1]

Pantel K, Alix-Panabières C. Trends Mol. Med., 2010,16(9): 398.

[2]

Pantel K, Alix-Panabières C. Nat. Rev. Clin. Oncol., 2019,16(7): 409.

[3]

Eslami-S Z, CortÉs-Hernández L E, Cayrefourcq L, Alix-Panabières C. Cold Spring Harb. Perspect. Med., 2020,10(6): a037333.

[4]

Gerlinger M, Rowan A, Horswell S, et al. Intratumor Heterogeneity and Branched Evolution Revealed by Multiregion Sequencing[J]. New England Journal of Medicine, 2012, 366(10):883.

[5]

Bardelli A, Pantel K. Cancer Cell, 2017,31(2): 172.

[6]

Murtaza M, Dawson S J, Pogrebniak K, Rueda O M, Provenzano E, Grant J, Chin S F, Tsui D W Y, Marass F, Gale D, Ali H R, Shah P, Contente-Cuomo T, Farahani H, Shumansky K, Kingsbury Z, Humphray S, Bentley D, Shah S P, Wallis M, Rosenfeld N, Caldas C. Nat. Commun., 2015,6(1): 8760.

[7]

Keller L, Pantel K. Nat. Rev. Cancer, 2019,19(10): 553.

[8]

Zhang W, Xia W J, Lv Z, Ni C, Xin Y, Yang L. Cell. Physiol. Biochem., 2017,41(2): 755.

[9]

Siravegna G, Marsoni S, Siena S, Bardelli A. Nat. Rev. Clin. Oncol., 2017,14(9): 531.

[10]

Cristofanilli M. Semin. Oncol., 2006,33: 9.

[11]

Nagrath S, Sequist L V, Maheswaran S, Bell D W, Irimia D, Ulkus L, Smith M R, Kwak E L, Digumarthy S, Muzikansky A, Ryan P, Balis U J, Tompkins R G, Haber D A, Toner M. Nature, 2007,450(7173): 1235.

[12]

Guo Shan, Zhou Xiang. Porgress in Chemistry, 2021,33(01):1.
[13]

( 郭珊, 周翔. 化学进展, 2021,33(01):1. )
[14]

Yáñez-MÓ M, Siljander P R M, Andreu Z, Bedina Zavec A, Borràs F E, Buzas E I, Buzas K, Casal E, Cappello F, Carvalho J, Colás E, Cordeiro-da Silva A, Fais S, Falcon-Perez J M, Ghobrial I M, Giebel B, Gimona M, Graner M, Gursel I, Gursel M, Heegaard N H H, Hendrix A, Kierulf P, Kokubun K, Kosanovic M, Kralj-Iglic V, Krämer-Albers E M, Laitinen S, Lässer C, Lener T, Ligeti E, Linē A, Lipps G, Llorente A, Lötvall J, Man?ek-Keber M, Marcilla A, Mittelbrunn M, Nazarenko I, Nolte-‘t Hoen E N M, Nyman T A, O'Driscoll L, Olivan M, Oliveira C, Pállinger É, del Portillo H A, ReventÓs J, Rigau M, Rohde E, Sammar M, Sánchez-Madrid F, SantarÉm N, Schallmoser K, Stampe Ostenfeld M, Stoorvogel W, Stukelj R, van der Grein S G, Helena Vasconcelos M, Wauben M H M, de Wever O. J. Extracell. Vesicles, 2015,4(1): 27066.

[15]

Thery C, Witwer K W, Aikawa E, Alcaraz M J, Anderson J D, Andriantsitohaina R, Antoniou A, Arab T, Archer F, Atkin-Smith G K, Ayre D C, Bach J M, Bachurski D, Baharvand H, Balaj L, Baldacchino S, Bauer N N, Baxter A A, Bebawy M, Beckham C, Bedina Z A, Benmoussa A, Berardi A C, Bergese P, Bielska E, Blenkiron C, Bobis-Wozowicz S, Boilard E, Boireau W, Bongiovanni A, Borras F E, Bosch S, Boulanger C M, Breakefield X, Breglio A M, Brennan M A, Brigstock D R, Brisson A, Broekman M L, Bromberg J F, Bryl-Gorecka P, Buch S, Buck A H, Burger D, Busatto S, Buschmann D, Bussolati B, Buzas E I, Byrd J B, Camussi G, Carter D R, Caruso S, Chamley L W, Chang Y T, Chen C, Chen S, Cheng L, Chin A R, Clayton A, Clerici S P, Cocks A, Cocucci E, Coffey R J, Cordeiro-Da-Silva A, Couch Y, Coumans F A, Coyle B, Crescitelli R, Criado M F, D'Souza-Schorey C, Das S, Datta C A, de Candia P, De Santana E F, De Wever O, Del P H, Demaret T, Deville S, Devitt A, Dhondt B, Di Vizio D, Dieterich L C, Dolo V, Dominguez R A, Dominici M, Dourado M R, Driedonks T A, Duarte F V, Duncan H M, Eichenberger R M, Ekstrom K, El A S, Elie-Caille C, Erdbrugger U, Falcon-Perez J M, Fatima F, Fish J E, Flores-Bellver M, Forsonits A, Frelet-Barrand A, Fricke F, Fuhrmann G, Gabrielsson S, Gamez-Valero A, Gardiner C, Gartner K, Gaudin R, Gho Y S, Giebel B, Gilbert C, Gimona M, Giusti I, Goberdhan D C, Gorgens A, Gorski S M, Greening D W, Gross J C, Gualerzi A, Gupta G N, Gustafson D, Handberg A, Haraszti R A, Harrison P, Hegyesi H, Hendrix A, Hill A F, Hochberg F H, Hoffmann K F, Holder B, Holthofer H, Hosseinkhani B, Hu G, Huang Y, Huber V, Hunt S, Ibrahim A G, Ikezu T, Inal J M, Isin M, Ivanova A, Jackson H K, Jacobsen S, Jay S M, Jayachandran M, Jenster G, Jiang L, Johnson S M, Jones J C, Jong A, Jovanovic-Talisman T, Jung S, Kalluri R, Kano S I, Kaur S, Kawamura Y, Keller E T, Khamari D, Khomyakova E, Khvorova A, Kierulf P, Kim K P, Kislinger T, Klingeborn M, Klinke D N, Kornek M, Kosanovic M M, Kovacs A F, Kramer-Albers E M, Krasemann S, Krause M, Kurochkin I V, Kusuma G D, Kuypers S, Laitinen S, Langevin S M, Languino L R, Lannigan J, Lasser C, Laurent L C, Lavieu G, Lazaro-Ibanez E, Le Lay S, Lee M S, Lee Y, Lemos D S, Lenassi M, Leszczynska A, Li I T, Liao K, Libregts S F, Ligeti E, Lim R, Lim S K, Line A, Linnemannstons K, Llorente A, Lombard C A, Lorenowicz M J, Lorincz A M, Lotvall J, Lovett J, Lowry M C, Loyer X, Lu Q, Lukomska B, Lunavat T R, Maas S L, Malhi H, Marcilla A, Mariani J, Mariscal J, Martens-Uzunova E S, Martin-Jaular L, Martinez M C, Martins V R, Mathieu M, Mathivanan S, Maugeri M, McGinnis L K, McVey M J, Meckes D J, Meehan K L, Mertens I, Minciacchi V R, Moller A, Moller J M, Morales-Kastresana A, Morhayim J, Mullier F, Muraca M, Musante L, Mussack V, Muth D C, Myburgh K H, Najrana T, Nawaz M, Nazarenko I, Nejsum P, Neri C, Neri T, Nieuwland R, Nimrichter L, Nolan J P, Nolte-'T H E, Noren H N, O'Driscoll L, O'Grady T, O'Loghlen A, Ochiya T, Olivier M, Ortiz A, Ortiz L A, Osteikoetxea X, Ostergaard O, Ostrowski M, Park J, Pegtel D M, Peinado H, Perut F, Pfaffl M W, Phinney D G, Pieters B C, Pink R C, Pisetsky D S, Pogge V S E, Polakovicova I, Poon I K, Powell B H, Prada I, Pulliam L, Quesenberry P, Radeghieri A, Raffai R L, Raimondo S, Rak J, Ramirez M I, Raposo G, Rayyan M S, Regev-Rudzki N, Ricklefs F L, Robbins P D, Roberts D D, Rodrigues S C, Rohde E, Rome S, Rouschop K M, Rughetti A, Russell A E, Saa P, Sahoo S, Salas-Huenuleo E, Sanchez C, Saugstad J A, Saul M J, Schiffelers R M, Schneider R, Schoyen T H, Scott A, Shahaj E, Sharma S, Shatnyeva O, Shekari F, Shelke G V, Shetty A K, Shiba K, Siljander P R, Silva A M, Skowronek A, Snyder O N, Soares R P, Sodar B W, Soekmadji C, Sotillo J, Stahl P D, Stoorvogel W, Stott S L, Strasser E F, Swift S, Tahara H, Tewari M, Timms K, Tiwari S, Tixeira R, Tkach M, Toh W S, Tomasini R, Torrecilhas A C, Tosar J P, Toxavidis V, Urbanelli L, Vader P, van Balkom B W, van der Grein S G, Van Deun J, van Herwijnen M J, Van Keuren-Jensen K, van Niel G, van Royen M E, van Wijnen A J, Vasconcelos M H, Vechetti I J, Veit T D, Vella L J, Velot E, Verweij F J, Vestad B, Vinas J L, Visnovitz T, Vukman K V, Wahlgren J, Watson D C, Wauben M H, Weaver A, Webber J P, Weber V, Wehman A M, Weiss D J, Welsh J A, Wendt S, Wheelock A M, Wiener Z, Witte L, Wolfram J, Xagorari A, Xander P, Xu J, Yan X, Yanez-Mo M, Yin H, Yuana Y, Zappulli V, Zarubova J, Zekas V, Zhang J Y, Zhao Z, Zheng L, Zheutlin A R, Zickler A M, Zimmermann P, Zivkovic A M, Zocco D, Zuba-Surma E K. J. Extracell. Vesicles, 2018,7(1):1535750.

[16]

Shao H L, Im H, Castro C M, Breakefield X, Weissleder R, Lee H. Chem. Rev., 2018,118(4): 1917.

[17]

Kalluri R, Lebleu V S. Science, 2020,367(6478): u6977.
[18]

Möller A, Lobb R J. Nat. Rev. Cancer, 2020,20(12): 697.

[19]

Wright M D, Tomlinson M G. Immunol. Today, 1994,15(12): 588.

[20]

Kourembanas S. Annu. Rev. Physiol., 2015,77(1): 13.

[21]

Kalluri R. J. Clin. Investig., 2016,126(4): 1208.

[22]

Shao B Y, Xiao Z D. Anal. Chimica Acta, 2020,1114: 74.

[23]

Martín-Gracia B, Martín-Barreiro A, Cuestas-AyllÓn C, Grazú V, Line A, Llorente A, de la Fuente J M, Moros M. J. Mater. Chem. B, 2020,8(31): 6710.

[24]

Yoon H J, Kozminsky M, Nagrath S. ACS Nano, 2014,8(3): 1995.

[25]

Chen L, Gao X Y, Gao J. Progress in Biochemistry and Biophysics, 2021,48(1):35.
[26]

( 陈璐, 高学云, 高靓. 生物化学与生物物理进展, 2021,48(1):35.)
[27]

Pei H M, Li L, Han Z J, Wang Y G, Tang B. Lab a Chip, 2020,20(21): 3854.

[28]

Zhang P, Zhou X, He M, Shang Y Q, Tetlow A L, Godwin A K, Zeng Y. Nat. Biomed. Eng., 2019,3(6): 438.

[29]

Contreras-Naranjo J C, Wu H J, Ugaz V M. Lab a Chip, 2017,17(21): 3558.

[30]

Boriachek K, Islam M N, Möller A, Salomon C, Nguyen N T, Hossain M S A, Yamauchi Y, Shiddiky M J A. Small, 2018,14(6): 1702153.

[31]

Montenegro J M, Grazu V, Sukhanova A, Agarwal S, de la Fuente J M, Nabiev I, Greiner A, Parak W J. Adv. Drug Deliv. Rev., 2013,65(5): 677.

[32]

Marques A C, Costa P J, Velho S, Amaral M H. J. Control. Release, 2020,320: 180.

[33]

Puertas S, Moros M, Fernández-Pacheco R, Ibarra M R, Grazú V, de la Fuente J M,. J. Phys. D: Appl. Phys., 2010,43(47): 474012.

[34]

Weissleder R, Haun J B, Devaraj N K, Hilderbrand S A, Lee H. Nature Nanotechnology, 2010,5(9):660.

[35]

Bartczak D, Kanaras A G. Langmuir, 2011,27(16): 10119.

[36]

Peng J X, Zhao Q, Zheng W S, Li W Z, Li P, Zhu L, Liu X R, Shao B, Li H P, Wang C, Yang Y L. ACS Appl. Mater. Interfaces, 2017,9(22): 18423.

[37]

Bai L L, Du Y M, Peng J X, Liu Y, Wang Y M, Yang Y L, Wang C. J. Mater. Chem. B, 2014,2(26): 4080.

[38]

Esmaeilsabzali H, Beischlag T V, Cox M E, Parameswaran A M, Park E J. Biotechnol. Adv., 2013,31(7): 1063.

[39]

Swennenhuis J F, van Dalum G, Zeune L L, Terstappen L W M M. Expert. Rev. Mol. Diagn., 2016,16(12): 1291.

[40]

Wang L H, Balasubramanian P, Chen A P, Kummar S, Evrard Y A, Kinders R J. Semin. Oncol., 2016,43(4): 464.

[41]

Danila D C, Samoila A, Patel C, Schreiber N, Herkal A, Anand A, Bastos D, Heller G, Fleisher M, Scher H I. Cancer J., 2016,22(5): 315.

[42]

Miltenyi S, Müller W, Weichel W, Radbruch A. Cytometry, 1990,11(2): 231.

[43]

Pluim D, Devriese L A, Beijnen J H, Schellens J H M. Cytom. A, 2012,81A(8): 664.

[44]

Giordano A, Gao H, Anfossi S, Cohen E, Mego M, Lee B N, Tin S, de Laurentiis M, Parker C A, Alvarez R H, Valero V, Ueno N T, de Placido S, Mani S A, Esteva F J, Cristofanilli M, Reuben J M. Mol. Cancer Ther., 2012,11(11): 2526.

[45]

Liu X R, Shao B, Peng J X, Li H P, Yang Y L, Kong W Y, Song G H, Jiang H F, Liang X, Yan Y. Breast, 2017,32: 119.

[46]

Yue C Y, Jiang Y B, Li P, Wang Y H, Xue J, Li N N, Li D, Wang R N, Dang Y J, Hu Z Y, Yang Y L, Xu J M. OncoImmunology, 2018,7(7): e1438111.

[47]

Xu J M, Zhang Y, Jia R, Yue C Y, Chang L P, Liu R R, Zhang G R, Zhao C H, Zhang Y Y, Chen C X, Wang Y, Yi X, Hu Z Y, Zou J J, Wang Q R. Clin. Cancer Res., 2019,25(2): 515.

[48]

Liang N X, Liu L, Li P, Xu Y, Hou Y S, Peng J X, Song Y, Bing Z X, Wang Y D, Wang Y Y, Jia Z Q, Yang X Y, Li D, Xu H H, Yu Q, Li S Q, Hu Z Y, Yang Y L. J. Thorac. Dis., 2020,12(8): 4262.

[49]

Karabacak N M, Spuhler P S, Fachin F, Lim E J, Pai V, Ozkumur E, Martel J M, Kojic N, Smith K, Chen P N, 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(3): 694.

[50]

Ozkumur E, Shah A M, Ciciliano J C, Emmink B L, Miyamoto D T, Brachtel E, Yu M, Chen P I, Morgan B, Trautwein J, Kimura A, Sengupta S, Stott S L, Karabacak N M, Barber T A, Walsh J R, Smith K, Spuhler P S, Sullivan J P, Lee R J, Ting D T, Luo X, Shaw A T, Bardia A, Sequist L V, Louis D N, Maheswaran S, Kapur R, Haber D A, Toner M. Sci. Transl. Med., 2013,5(179): 179ra47.
[51]

Svobodova Z, Kucerova J, Autebert J, Horak D, Bruckova L, Viovy J L, Bilkova Z. Electrophoresis, 2014,35(2/3): 323.

[52]

Autebert J, Coudert B, Champ J, Saias L, Guneri E T, Lebofsky R, Bidard F C, Pierga J Y, Farace F, Descroix S, Malaquin L, Viovy J L. Lab a Chip, 2015,15(9): 2090.

[53]

Song Y L, Shi Y Z, Huang M J, Wang W, Wang Y, Cheng J, Lei Z C, Zhu Z, Yang C Y. Angew. Chem. Int. Ed., 2019,58(8): 2236.

[54]

Glia A, Deliorman M, Sukumar P, Janahi F K, Samara B, Brimmo A T, Qasaimeh M A. Adv. Mater. Technol., 2021,6(6): 2100053.

[55]

Cui H J, Wang B S, Wang W S, Hao Y W, Liu C Y, Song K, Zhang S D, Wang S T. ACS Appl. Mater. Interfaces, 2018,10(23): 19545.

[56]

Li Y Y, Lu Q H, Liu H L, Wang J F, Zhang P C, Liang H G, Jiang L, Wang S T. Adv. Mater., 2015,27(43): 6848.

[57]

Wu C C, Li P, Fan N N, Han J J, Zhang W, Zhang W, Tang B. ACS Appl. Mater. Interfaces, 2019,11(48): 44999.

[58]

Luan C X, Wang H, Han Q, Ma X Y, Zhang D G, Xu Y S, Chen B A, Li M L, Zhao Y J. ACS Appl. Mater. Interfaces, 2018,10(25): 21206.

[59]

Lv S W, Liu Y, Xie M, Wang J, Yan X W, Li Z, Dong W G, Huang W H. ACS Nano, 2016,10(6): 6201.

[60]

Carney R P, Hazari S, Colquhoun M, Tran D, Hwang B, Mulligan M S, Bryers J D, Girda E, Leiserowitz G S, Smith Z J, Lam K S. Anal. Chem., 2017,89(10): 5357.

[61]

Fan M K, Andrade G F S, Brolo A G. Anal. Chimica Acta, 2020,1097: 1.

[62]

Wu X X, Luo L Q, Yang S, Ma X H, Li Y L, Dong C, Tian Y C, Zhang L G, Shen Z Y, Wu A G. ACS Appl. Mater. Interfaces, 2015,7(18): 9965.

[63]

Ruan H M, Wu X X, Yang C C, Li Z H, Xia Y Z, Xue T, Shen Z Y, Wu A G. ACS Biomater. Sci. Eng., 2018,4(3): 1073.

[64]

Xue T, Wang S Q, Ou G Y, Li Y, Ruan H M, Li Z H, Ma Y Y, Zou R F, Qiu J Y, Shen Z Y, Wu A G. Anal. Methods, 2019,11(22): 2918.

[65]

Abdulbari H A, Basheer E A M. Chembioeng Rev., 2017,4(2): 92.

[66]

Shen C C, Liu S P, Li X Q, Yang M H. Anal. Chem., 2019,91(18): 11614.

[67]

Shen H W, Liu L Y, Yuan Z W, Liu Q, Li B Y, Zhang M, Tang H J, Zhang J, Zhao S Q. Biosens. Bioelectron., 2021,179: 113102.

[68]

Shen C L, Zhong L, Xiong L, Liu C, Yu L H, Chu X, Luo X, Zhao M, Liu B Z. Sens. Actuat. B: Chem., 2021,331: 129399.

[69]

Rupert D L M, Claudio V, Lässer C, Bally M. Biochim. Et Biophys. Acta BBA Gen. Subj., 2017,1861(1): 3164.
[70]

Melo S A, Luecke L B, Kahlert C, Fernandez A F, Gammon S T, Kaye J, LeBleu V S, Mittendorf E A, Weitz J, Rahbari N, Reissfelder C, Pilarsky C, Fraga M F, Piwnica-Worms D, Kalluri R. Nature, 2015,523(7559): 177.

[71]

Li W Z, Shao B, Liu C L, Wang H Y, Zheng W S, Kong W Y, Liu X R, Xu G B, Wang C, Li H P, Zhu L, Yang Y L. Small Methods, 2018,2(11): 1800050.
[72]

Wang H Y, Jiang D Z, Li W Z, Xiang X, Zhao J, Yu B, Wang C, He Z H, Zhu L, Yang Y L. Theranostics, 2019,9(18): 5347.

[73]

Wang H Y, Chen K L, Yang Z J, Li W Z, Wang C, Zhang G J, Zhu L, Liu P N, Yang Y L. Anal. Chem., 2019,91(15): 9580.

[74]

Koliha N, Wiencek Y, Heider U, Jüngst C, Kladt N, Krauthäuser S, Johnston I C D, Bosio A, Schauss A, Wild S. J. Extracell. Vesicles, 2016,5(1): 29975.

[75]

Li T D, Zhang R, Chen H, Huang Z P, Ye X, Wang H, Deng A M, Kong J L. Chem. Sci., 2018,9(24): 5372.

[76]

Kwizera E A, O'Connor R, Vinduska V, Williams M, Butch E R, Snyder S E, Chen X, Huang X H. Theranostics, 2018,8(10): 2722.

[77]

Tian Y F, Ning C F, He F, Yin B C, Ye B C. Anal., 2018,143(20): 4915.

[78]

Pang Y F, Wang C G, Lu L C, Wang C W, Sun Z W, Xiao R. Biosens. Bioelectron., 2019,130: 204.

[79]

Wang Z L, Zong S F, Wang Y J, Li N, Li L, Lu J, Wang Z Y, Chen B A, Cui Y P. Nanoscale, 2018,10(19): 9053.

[80]

Wu T T, Yang Y M, Cao Y, Huang Y, Xu L P, Zhang X J, Wang S T. Sci. China Chem., 2018,61(11): 1423.

[81]

Liu W L, Li J P, Wu Y X, Xing S, Lai Y Z, Zhang G. Biosens. Bioelectron., 2018,102: 204.

[82]

Liu C, Zhao J X, Tian F, Cai L L, Zhang W, Feng Q, Chang J Q, Wan F N, Yang Y J, Dai B, Cong Y L, Ding B Q, Sun J S, Tan W H. Nat. Biomed. Eng., 2019,3(3): 183.

[83]

Zhang J L, Zhu Y F, Shi J J, Zhang K X, Zhang Z Z, Zhang H L. ACS Appl. Mater. Interfaces, 2020,12(30): 33473.

[84]

Zhang W Z, Chen H, Yang M H, Liao L Q. Mater. Lett., 2020,276: 128219.

[85]

Li J, Lin X F, Zhang Z Y, Tu W W, Dai Z H. Biosens. Bioelectron., 2019,126: 332.

[86]

Liu P F, Wang L, Zhao K R, Liu Z J, Cao H X, Ye S Y, Liang G X. Sens. Actuat. B: Chem., 2020,316: 128131.

[87]

Yang J M, Li X L, Jiang B Y, Yuan R, Xiang Y. Anal. Chem., 2020,92(11): 7893.

[88]

Boriachek K, Islam M N, Gopalan V, Lam A K, Nguyen N T, Shiddiky M J A. Anal., 2017,142(12): 2211.

[89]

Dong H L, Chen H F, Jiang J Q, Zhang H, Cai C X, Shen Q M. Anal. Chem., 2018,90(7): 4507.

[90]

Chen G Y, Qiu H L, Prasad P N, Chen X Y. Chem. Rev., 2014,114(10): 5161.

[91]

Mendez-Gonzalez D, Lopez-Cabarcos E, Rubio-Retama J, Laurenti M. Adv. Colloid Interface Sci., 2017,249: 66.

[92]

Kikuchi K. Chem. Soc. Rev., 2010,39(6): 2048.

[93]

Wang Y H, Luo D W, Fang Y, Wu W H, Wang Y J, Xia Y K, Wu F, Li C Y, Lan J M, Chen J H. Sens. Actuat. B: Chem., 2019,298: 126900.

[94]

Chen X S, Lan J M, Liu Y X, Li L, Yan L, Xia Y K, Wu F, Li C Y, Li S R, Chen J H. Biosens. Bioelectron., 2018,102: 582.

[95]

Algar W R, Tavares A J, Krull U J. Anal. Chimica Acta, 2010,673(1): 1.

[96]

Chandan H R, Schiffman J D, Balakrishna R G. Sens. Actuat. B: Chem., 2018,258: 1191.

[97]

Zhang P F, Draz M S, Xiong A W, Yan W N, Han H X, Chen W S. J. Nanobiotechnology, 2021,19(1): 116.

[98]

Kuo C W, Chueh D Y, Chen P L. J. Nanobiotechnology, 2019,17(1): 26.

[99]

Bai Y N, Lu Y X, Wang K, Cheng Z L, Qu Y L, Qiu S H, Zhou L, Wu Z H, Liu H Y, Zhao J L, Mao H J. Nano Micro Lett., 2019,11(1): 1.
[100]

Zhai L Y, Li M X, Pan W L, Chen Y, Li M M, Pang J X, Zheng L, Chen J X, Duan W J. ACS Appl. Mater. Interfaces, 2018,10(46): 39478.

[101]

He F, Wang J, Yin B C, Ye B C. Anal. Chem., 2018,90(13): 8072.

[102]

Gao M L, Yin B C, Ye B C. Anal., 2019,144(20): 5996.

[103]

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(4):2334.

[104]

Xia W X, Li H D, Li Y Q, Li M, Fan J L, Sun W, Li N, Li R J, Shao K, Peng X J. Nano Lett., 2021,21(1): 634.

[105]

Zeng S W, Baillargeat D, Ho H P, Yong K T. Chem. Soc. Rev., 2014,43(10): 3426.

[106]

Parolo C, Merkoçi A. Mater. Today, 2010,13(7/8): 24.
[107]

Wang Q, Zou L Y, Yang X H, Liu X F, Nie W Y, Zheng Y, Cheng Q, Wang K M. Biosens. Bioelectron., 2019,135: 129.

[108]

Im H, Shao H L, Park Y I, Peterson V M, Castro C M, Weissleder R, Lee H. Nat. Biotechnol., 2014,32(5): 490.

[109]

Liang K, Liu F, Fan J, Sun D L, Liu C, Lyon C J, Bernard D W, Li Y, Yokoi K, Katz M H, Koay E J, Zhao Z, Hu Y. Nat. Biomed. Eng., 2017,1(4): 0021.

[110]

Ahmed M G, Abate M F, Song Y L, Zhu Z, Yan F, Xu Y, Wang X M, Li Q B, Yang C Y. Angew. Chem. Int. Ed., 2017,56(36): 10681.

[111]

Tang M, Xia H F, Xu C M, Feng J, Ren J G, Miao F, Wu M, Wu L L, Pang D W, Chen G, Zhang Z L. Anal. Chem., 2019,91(23): 15260.

[112]

He M, Crow J, Roth M, Zeng Y, Godwin A K. Lab a Chip, 2014,14(19): 3773.

[113]

Zhao Z, Yang Y, Zeng Y, He M. Lab a Chip, 2016,16(3): 489.

[114]

Jiang Y, Shi M L, Liu Y, Wan S, Cui C, Zhang L Q, Tan W H. Angew. Chem. Int. Ed., 2017,56(39): 11916.

[115]

He F, Liu H, Guo X G, Yin B C, Ye B C. Anal. Chem., 2017,89(23): 12968.

[116]

Chen J G, Xu Y C, Lu Y, Xing W L. Anal. Chem., 2018,90(24): 14207.

[117]

Yang J J, Pan B, Zeng F, He B S, Gao Y F, Liu X L, Song Y J. Nano Lett., 2021,21(5): 2001.

[118]

Jeong S, Park J, Pathania D, Castro C M, Weissleder R, Lee H. ACS Nano, 2016,10(2): 1802.

[119]

Abate M F, Jia S S, Ahmed M G, Li X R, Lin L, Chen X Q, Zhu Z, Yang C Y. Small, 2019,15(14): 1804890.

[120]

Yang J M, Huang X T, Gan C F, Yuan R, Xiang Y. Biosens. Bioelectron., 2019,143: 111604.

[121]

Xia N, Wu D H, Yu H Q, Sun W W, Yi X Y, Liu L. Talanta, 2021,221: 121640.

Funding

Strategic Priority Research Program of the Chinese Academy of Sciences(XDB36000000)

Key R&D Project(2017YFA0205000)

National Natural Science Foundation of China(51861135103)

National Natural Science Foundation of China(31971295)

National Natural Science Foundation of China(21773042)

Key Frontier Science Research Project(QYZDJ-SSW-SLH048)

Youth Innovation Promotion Association of Chinese Academy of Sciences(2018048)

PDF (6341KB)

1844

Accesses

0

Citation

Detail
Sections
Recommended

/

〈 〉

Address of Editorial Office: No. 33 Beisihuan Xilu, Zhongguancun , Beijing 100190, China
Tel: +86 10 8262 7757
Fax: +86 10 8262 7757
E-mail: progchem@mail.las.ac.cn
http://www.progchem.ac.cn
    • 　
    Copyright © Editorial Office of Progress in Chemistry