text:
H1N1 influenza virus epitopes classified by monoclonal antibodies

Epitopes serve an important role in influenza infection. It may be useful to screen universal influenza virus vaccines, analyzing the epitopes of multiple subtypes of the hemagglutinin (HA) protein. A total of 40 monoclonal antibodies (mAbs) previously obtained from flu virus HA antigens (development and characterization of 40 mAbs generated using H1N1 influenza virus split vaccines were previously published) were used to detect and classify mAbs into distinct flu virus sub-categories using the ELISA method. Following this, the common continuous amino acid sequences were identified by multiple sequence alignment analysis with the GenBank database and DNAMAN software, for use in predicting the epitopes of the HA protein. Synthesized peptides of these common sequences were prepared, and used to verify and determine the predicted linear epitopes through localization and distribution analyses. With these methods, nine HA linear epitopes distributed among different strains of influenza virus were identified, which included three from influenza A, four from 2009 H1N1 and seasonal influenza, and two from H1. The present study showed that considering a combination of the antigen-antibody reaction specificity, variation in the influenza virus HA protein and linear epitopes may present a useful approach for designing effective multi-epitope vaccines. Furthermore, the study aimed to clarify the cause and pathogenic mechanism of influenza virus HA-induced flu, and presents a novel idea for identifying the epitopes of other pathogenic microorganisms.

Introduction
Infection by pathogenic microorganisms and viruses presents a significant threat to human life worldwide; their constant variation, evolution and spread render it difficult to prevent and control infection. HBV, one of the most infectious diseases worldwide, often varies due to the pressures of host immunity, natural selection and the use of antiviral agents. Such variations may cause changes in HBV pathogenicity, including the development of tolerance and immune escape, and have greatly hindered clinical diagnosis and treatment (1). A number of new HIV GAG subtypes have been reported due to its constant variation and accumulation (2). Continual variation in the influenza virus hemagglutinin (HA) antigen gene is the main cause of influenza outbreaks (3). This poses challenges for immunology, virology and immunopharmacology research, and for the development of vaccines against influenza and other pathogenic microorganisms.
Epitopes, also known as antigenic determinants, represent the material base of immunogen antigenicity, and is the part of an antigen recognized by the immune system. Epitopes can be classified as either conformational epitopes or linear epitopes, based on their structure and interaction with the paratope (4). The linear epitope is a section of the continual amino acid sequence of the antigen, and its interaction with the paratope predominantly depends on its primary structure. Variations in any area of the linear epitopes may lead to structural changes, a reduced antibody binding ability, and the ability to escape recognition by existing antibodies and vaccines (5).
Different subtypes of a pathogen may have a variety of antigens; thus, it is challenging to distinguish the subtype of pathogenic microorganisms, to establish immunodetection technologies, and to clarify the mechanisms of disease spread.
Consequently, epitope prediction and utilization are of value in differential diagnosis, the prediction of variation trends, determining the mechanisms of pathogenic microorganism infection, and in the design of multi-epitope vaccines (6).
Recently, several methods of epitope prediction have been in use, the majority of which are limited to one antigen, although they still provide a satisfactory predictive capacity (7)(8)(9). X-ray diffraction requires more time and energy to identify epitope structures. To elucidate the biological profile of the epitope, multiple factors should be considered, including its location on the surface of the antigen, the flexibility, and the accessibility, although it showed a growing acceptance among this field (10)(11)(12)(13)(14). In addition to α-helices and β-pleated sheets, glycosylation sites are also important for prediction (15). However, the predictive accuracy of these methods is just ~60% (16). Larger protein libraries are required for phage display technology, and certain peptides have strong hydrophobicity, which influences their structure on the surface of phages. Furthermore, the predictions obtained via this method still require further verification (17). Thus, a single optimal approach is required, which is capable of predicting the epitope sequences of microorganisms comprehensively and in one pass, establishing a biological profile with the characteristics and functions of the epitopes, and modeling the behavior of these epitopes during changes to virus antigenicity. This will have an important and direct role in the design of biologically active drugs, research into pathogenic mechanisms, and the prediction of variation in certain pathogenic microorganisms.
Monoclonal antibodies (mAbs) are a subset of antibodies generated by identical immune cells with a strong monovalent affinity, in that they bind to the same epitope, with high specificity and sensitivity, and define the structure and character of epitopes (18). Such specificity can also be used as a tool to analyze the epitopes of viruses and their subtypes, provide information on the main functions of the epitopes and on genetic variations involved in changes to the epitopes, and assist research into epitope variation and improvements in vaccine design (19,20).
In the present study, mAbs from 40 previously developed anti-H1N1 influenza virus HA split vaccines had been developed and characterized (21), which were used as experimental tools to predict the epitopes of influenza virus HA proteins, after which their distribution and expression were investigated using synthesized peptides. The present study aimed to illuminate the association between variation in the influenza virus and its immunogenicity, and to develop a useful method for predicting the variable epitopes of other pathogenic microorganisms. In the present study, we just preliminary report a new method for predicting the variability epitope of influenza virus. Next, we will carry out biological functional studies on predicted different epitopes one by one, which can help us to develop epitope vaccines of influenza virus, further contribute to the diagnosis and prevention of influenza virus. Antibodies. mAbs against the anti-H1N1 A influenza virus HA protein were prepared in our laboratory, and HRP-conjugated goat anti-mouse antibodies were provided by Beijing Zhongshan Golden Bridge Biotechnology Co., Ltd., (Beijing, China).

Antigens
HA protein synthetic peptides. Part of the continuous amino acid sequence of influenza virus HA was determined using DNAMAN software, and peptides were synthesized by ChinaPeptides Co., Ltd., (Shanghai, China).
ELISA analysis and classification. Indirect ELISA analyses were performed using the following: Hybridoma culture supernatant; H1N1 influenza virus split vaccine (2009); seasonal influenza viruses A1 and A3; and avian influenza viruses H5N1 and H9N2. Briefly, the 96-well plate was pre-coated with 100 µl of each vaccine (2-5 µg/ml). After washing three times with PBST (including 8 g of NaCl, 0.2 g of KCl, 1.44 g of Na 2 HPO 4 , 0.24 g of KH 2 PO 4 , 2 ml of Tween-20, pH 7.2, volume adjusted to 1L with additional distilled H 2 O), the plates were blocked with 200 µl skim milk (dilution, 1:20) and incubated for 1 h at 37˚C. Subsequently, 100 µl/well supernatant aspirated from the hybridoma cell cultures for 40 mAbs was added, including the supernatant of SP2/0 as a negative control, which was incubated for 1 h at 37˚C. After washing a further three times, the concentration (dilution, 1:2,500) of the HRP-labeled goat-anti-mouse IgG mAb (100 µl/well) was added and incubated for 1 h at 37˚C. Next, 100 µl TMB-H 2 O 2 chromogenic solution was added to each well and incubated for 10 min at 37˚C in the dark, and terminated with H 2 SO 4 solution (2 M, 50 µl/well). Finally, the proportion of bound antibodies, which is correlated with the color intensity, was measured with an ELISA reader via absorbance at 450 nm. The ratio of each test sample (OD 450 : Control OD 450 ) was calculated. Samples with a ratio of ≥2.1 were classified as exhibiting a positive reaction. Considering each test sample reaction with the five subtypes of the influenza virus, the antibodies were categorized into different groups.

Epitopes of influenza A virus HA protein prediction.
I n t h e N C BI d a t a b a s e ( h t t p: // w w w. n c b i. n l m. nih.gov/genomes/FLU/FLU.html), the amino acid sequences of various influenza virus subtypes were accessed and downloaded with their GenBank IDs (Table I). Consequently, a multiple sequence alignment analysis was performed using DNAMAN software, following which the common continuous amino acid sequence (5-7 aa) between the antigens of the different groups were defined, and used to predict the epitopes of influenza A virus HA proteins. Overall, 27 candidate epitope fragments were selected, and complementary peptides were synthesized, each with a >85% purity as measured by HPLC and MS methods; these peptides were stored as freeze-dried powders at -20˚C.
Localization of predicted epitopes with anti-influenza virus HA mAbs. To investigate the positions of the predicted epitopes of influenza A virus HA, 27 candidate-epitope peptides were used and screened using mAbs against influenza virus HA. The process was as follows: The synthesized peptides were mixed with 40 HA mAbs, and incubated for 1 h at 37˚C. A total of 100 µl mixed reagent was placed into each well of an ELISA plate pre-coated with H1N1 influenza virus HA antigens (2 µg/ml), according to standard ELISA protocols. After a 1 h incubation and three washes, the goat anti-mouse antibodies (dilution, 1:2,500) were added, and the steps of a conventional ELISA were performed. The OD 450 values for all wells were calculated from TMB coloration and an inhibition rate (IR) was calculated. The formula used to calculate the IR was as follows: IR=(OD CTL -OD TEST )/OD CTL . Correlations between the antigens and the antibody binding sites were defined according to the following criteria: No correlation (IR ≤0.4); correlation (0.4≤ IR ≤0.8); and strong correlation (IR ≥0.8).
Distribution of predicted epitopes in the HA crystal structure. The PyMOL Molecular Graphics System (http://www.PyMOL. org) and Protein Database (PDB) were used to analyze the distribution of predicted epitopes in the HA crystal structure. Peptides recognized by mAbs against influenza virus HA proteins in the ELISA experiments were selected and analyzed. First, the PDB database was used to search for and generate a model of the HA protein X-ray crystal structure by referring to the 3LZG structure, which was produced from the A/California/04/2009 H1N1 virus HA and had a similar structure to that of the antigen in the present study. Secondly, the selected peptides' distributions were determined using PyMOL software according to the manufacturer's protocol.

Results
Specificity and cross reactivity of mAbs. ELISA reactions between 40 influenza virus HA antigen mAbs and five different influenza virus subtype vaccines were evaluated using the OD 450 ratio, and classified as positive (OD 450 ≥2.1) or negative (OD 450 <2.1) reactions. According to the cross-ELISA results, all the assessed influenza virus HA antigens can be classified into three groups. Approximately half (20/40) were recognized by all five antigens, ~35% (14/40) were recognized by the antigens of 2009 H1N1 virus A, or seasonal influenza virus A1 and A3, and 6 mAbs only reacted with the antigens of H1N1 virus A and seasonal A1 (Table II).

Detection of conserved peptides in influenza virus A HA.
Twenty seven common continuous amino acid sequences of influenza HA antigens detected through multiple sequence alignment analysis of the three groups using DNAMAN software (Table III). There were 9 peptides located in the conserved sequences of vaccines in group 1, 7 peptides in the conserved sequences of group 2, and 11 in group 3 (Table III).
Locations of predicted epitopes determined using anti-influenza virus HA mAbs. The ELISA results demonstrated that 9/27 peptides were recognized by 13/40 mAbs, considering their IRs calculated with OD 450 values (Figs. 1-3). In group 1, 5 mAbs were identified by 3 peptides, designated peptides 1, 2 and 9 (Fig. 1); in group 2, 6 mAbs reacted with 4 peptides (peptides 10, 11, 15 and 16; Fig. 2); and 2 mAbs in group 3 were identified by 2 peptides (peptides 17 and 27; Fig. 3).  Distribution of predicted epitopes in the HA crystal structure. After the predicted epitopes were located, three peptides (including 93-WSYIVE-98, 191-LVLWGIHHP-199 and 307-LPFQNI-312), located in the continuous conserved amino acid sequences in all five HA antigens, were chosen for distribution analysis. PyMOL software analysis identified the three peptides sequences in the HA crystal structure, and predicted their location in the 3D structure of HA (Fig. 4).

Discussion
Variability in the HA proteins of the influenza virus impacts on the suitability and efficacy of existing vaccines. Developing universal vaccines effective against various subtypes of influenza is the primary approach for controlling the spread of infection (22). As epitopes are a key feature of viruses, several strategies have been successfully applied in the design and development of 'epitope-focused' vaccines (23,24), which demonstrate advantages such as high specificity, fewer side effects, simple preparation, and easy storage and transportation (25,26). These rapid and accurate strategies have become the foundation for the development of influenza virus vaccines, as well as supporting clinical diagnosis and treatment.
In the present study, we predicted the epitopes of multiple subtypes of the influenza virus HA protein using 40 previously developed mAbs, and extracted the common continuous amino acid sequences as linear epitopes. Following this, we   determined the localization and distribution with candidate peptide analysis, to verify and confirm 9 linear epitopes of the HA protein. For five common subtypes of the influenza virus, 3 epitopes (peptides 1, 2 and 9) showed a strong association with multiple influenza viruses. Additionally, three epitopes are known to overlap with three neutralizing epitopes, HA183 ~195, HA127 ~133 and HA92 ~105, of the H3 subtype influenza virus HA protein, as reported by Li et al (27). It is also suspected that the three peptides 1-LVLWGIHHP, 2-LPFQNI and 9-WSYIVE may stimulate organisms to produce neutralizing antibodies and promote immunogenicity, which may benefit the development of universal influenza vaccines.
In the second group, which included the 2009 influenza A virus H1N1, and the seasonal influenza A1 and A3 virus, four linear epitopes were identified. The epitopes in the conserved sequences of this group were immunodominant epitopes, capable of stimulating organisms to produce a high volume of antibodies in response. Therefore, there were more chances of mixed infection of three of them presently (28). In the third group, two linear epitopes were predicted, which are the main markers used to distinguish between the HA proteins of H1 and other subtypes. Our results suggested that only 15% (6/40) of the antibodies are produced by organisms when stimulated by epitopes in group 3, due to there being fewer common epitopes between these two subtypes of the influenza virus.
To an extent, this observation may also explain the significant difference between the H1N1 influenza virus subtypes in terms of the infection frequency, pathogenicity and infection scale, among other variables (29).
As identified in ELISA experiments, 13/40 anti-influenza virus HA antigens were positioned at 9 epitopes. In group 1, we synthesized 9 peptides after analyzing the common sequences of the human and avian influenza viruses using DNAMAN software and 20 mAbs against epitopes common to both viruses; we positioned 5 antigens to 3 epitopes. Li et al (27), used an E. coli model to demonstrate that rabbits and mice are immune to recombinant multi-epitope peptides specific to three neutralizing epitopes, HA183~195, HA127~133 and HA92~105, from the H3 subtype of influenza virus HA, and neutralizing antibodies with high titer were produced. This indicated that, in the first group, among peptides able to identify multiple subtypes of the influenza virus, 1-LVLWGIHHP and 9-WSYIVE could potentially stimulate organisms to produce neutralizing antibodies, which would benefit the development of universal influenza vaccines. In the second group, we designed 7 peptides complementary to the antigen-conserved areas of 14 mAbs. We positioned 4 epitopes to 6 mAbs. Epitopes in the conserved areas of the 2009 influenza A virus H1N1, and the seasonal influenza A1 and A3 viruses were immunodominant, and stimulated organisms to produce an abundance of antibodies in response. In the third group, 2 antigens were positioned to 2 epitopes. Epitopes corresponding with these antibodies are the primary markers used to distinguish between the HA proteins of H1 and other subtypes.
Influenza virus HA proteins include 562-566 amino acids and consist of a HA1 spherical head (319-328aa) and a HA2 bacilliform stalk (221-222aa). HA1 includes 8 anti-parallel β-laminated structures, including a receptor-binding domain (RBD) and 5 antigenic determinants: A, B, C, D and E (30). The RBD domain is composed of a helix at site 190, and of rings at sites 130 and 220; one of the predicted epitopes, verified by peptide 191-LVLWGIHHP-199, was located near this domain (Fig. 4), indicating that the current method was effective and reliable, and could be used to investigate the mechanisms underlying the spread of influenza, its genetic variation, and in the development of epitope-specific vaccines.
To predict the epitopes of influenza HA proteins, we used the antigen-antibody reaction method. Multiple reactivity  . Distribution of three peptides in the HA crystal structure. We searched for a crystal structure of the H1N1 influenza A virus in the PDB, and used 3LZG as a reference structure. PyMOL software was used to determine the distribution of three peptides in the 3D crystal structure of HA, from which we noted that the WSYIVE peptide (red) and the LPFQNI peptide (purple) are located on the random coil domain, whereas the LVLWGIHHP peptide (blue) is situated within the β-sheet structure. HA, hemagglutinin. modes were observed, including the one-to-one mode, the one-to-many mode (H1-74 reacted with peptides 1 and 2; H1-51 reacted with peptides 10 and 11; H1-58 reacted with peptides 17 and 27), and the unresponsive mode. Two findings were notable: First, two peptides that react with the same antibody were close to the 3D structure of HA, and formed a conformational epitope, although they were separated by a long sequence in the primary structure; second, 40 mAbs were obtained using the split influenza virus vaccine, and these immunogens can induce organisms to produce the same antibodies as those induced by natural pathogens. Synthesized peptides, for which the design and utilization were based on the primary sequence of the protein, were used for linear epitope prediction and identification.
These short peptides can be also used as good immunogens to research different subtypes of influenza virus epitope vaccines. Li et al (31) applied short-peptide immunization to the mice directly, and screened the prepared mAbs. In order to enhance immunogenicity, connection of polypeptides and macromolecular protein can also be used. Gong et al (32) coupled the short peptides P1~P6 of the chemically synthesized influenza virus H3N2 sequence with the Keyhole Limpet Hemocyanin (KLH) carrier protein in order to increase the immunogenicity of the polypeptide, and induced a strong humoral immune response. We have previously linked 9 different polypeptides with KLH one by one, obtaining high titer and high affinity polyclonal antibodies after immunizing mice. Polyclonal antibodies were then tested for their neutralizing activity and cross-reactivity with human tissues. These experiments are underway.
In conclusion, the present study identified 9 linear epitopes of the influenza HA protein via traditional mAb and antigen interaction analysis, and verified these using ELISA and 3D structure location analyses with synthesized peptides. The results provide a novel, effective and reliable method for investigating the mechanisms underlying the spread and variation of influenza virus and other pathogenic microorganisms, in addition to improving the development of epitope-focused vaccines.


extfieldsofstudy: Medicine Chemistry

text:
Islet-cell autoantigen 69 mediates the antihyperalgesic effects of electroacupuncture on inflammatory pain by regulating spinal glutamate receptor subunit 2 phosphorylation through protein interacting with C-kinase 1 in mice

Supplemental Digital Content is Available in the Text. A clear role of ICA69 in mediating the antihyperalgesic effects of electroacupuncture was confirmed, and the ICA69-PICK1-GluR2 molecular mechanism to explain these effects is proposed.

Introduction
Inflammatory pain is a severe clinical symptom that is difficult to treat and often leads to disabling of patients. Inflammation at the injury site was caused by tissue injury; then, the inflammatory mediators such as bradykinin, substance P, PGE2, ATP, IL-1, and IL-1b, which act on nerve terminal nociceptors, were released. They can alter the nociceptor excitability through transcriptional and/or posttranslational mechanisms, giving rise to hypersensitivity. 25,31,36 Subcutaneous injection of inflammatory agents, such as formalin, capsaicin, or complete Freund adjuvant (CFA), is used to develop inflammatory pain models in mice. 19,28,42 Injecting CFA into the hind paw of mice promotes Ser880 phosphorylation in glutamate receptor subunit 2 (GluR2) and subsequent GluR2 internalization, which leads to the increasing Ca 21 -permeable a-amino-3-hydroxy-5-methyl-4isoxazole propionic acid (AMPA) receptors on neuron membrane. 3 More permeability allowing for more influx of Ca 21 results in the inflammatory pain hypersensitivity.
Electroacupuncture (EA) is one of the typical treatments of traditional Chinese medicine, and it is widely used in clinical settings to relieve pain. 4,5,26,44 The application of acupuncture has been approved for 77 diseases by the World Health Organization since 2002. 13,41 AMPA, the excitatory receptor, and its subtype (GluR2) are considered to be the key to many forms of synaptic plasticity, 15,34 and EA shows a direct effect on synaptic plasticity. 10,17,34,44,49 In addition, several studies 12,16,46,47 suggested AMPA receptor in spinal dorsal horn (SDH) might involve EA analgesia. And, the blocking of AMPA receptors can enhance the analgesic effect of acupuncture. 11,20 However, the participation of GluR2 in EA analgesia has not been well understood. 21,22 They only found that the increasing GluR2p was blocked by EA treatment.
Islet-cell autoantigen 69 (ICA69), a protein encoded by the human ICA1 or murine Ica1 gene, was initially found in patients with type I diabetes. 2 Further studies showed that ICA69 is associated with autism spectrum disorder and many autoimmune diseases such as rheumatoid arthritis and primary Sjogren syndrome, all of which are associated with deficient immune tolerance of ICA69. 27,30,40 ICA69 protein and its Caenorhabditis elegans homolog ric-19 are abundantly expressed in the neuroendocrine tissues, mainly in brain and pancreatic islets, and have been reported to regulate neuroendocrine secretion. 6,16,29 ICA69 forms tight heteromeric complexes with protein interacting with C-kinase 1 (PICK1) through the BAR domains, and PICK1-ICA69 complexes control insulin granule trafficking. 7,8 Recent studies showed that ICA69 could influence AMPA receptors, which mediate synaptic plasticity via interacting with PICK1. 38,43 Our previous investigation found that absence of ICA69 enhanced the long-lasting hyperalgesia induced by subcutaneous formalin injection into the mouse hind paw. Furthermore, ICA69 knockout (KO) led to increased GluR2 phosphorylation at Ser880 in SDH. 23 Given that EA could prevent the phosphorylation of GluR2, as well as the absence of ICA69 could cause GluR2 phosphorylation increasing in SDH, we hypothesized that ICA69 mediates the antihyperalgesic effects of EA by regulating GluR2 through PICK1.

Animals
C57BL/6 male wild-type (WT) mice, ICA69 KO, and PICK1 KO mice (10-12 weeks old) were used in this study. The original pairs of heterozygote C57BL/6 mice with a disrupted ICA69 gene (ICA691/2) and PICK1 gene (PICK11/2) were obtained from Ying Shen (Zhejiang University School of Medicine, Hangzhou, China) and were mated to intercross. The mice were housed at 23 6 1˚C on a standard 12:12-hours light/dark cycle, with water and food pellets available ad libitum. All experiments were approved by the Animal Experimentation Ethics Committee of Wenzhou Medical University and were specifically designed to minimize the number of animals used. To reduce the variability, the animals were trained for 1 to 2 days before being subjected to the behavior tests.

Complete Freund adjuvant-induced inflammatory pain and electroacupuncture simulation
The inflammatory pain test was performed on days 21, 0, 1, 3, 5, and 7 after CFA injection or EA according to previous work. 3 In brief, 25 mL of CFA (1 mg/mL; Sigma-Aldrich, St. Louis, MO) was subcutaneously injected into the right hind paw at day 0 (CFA group). Twenty-five microliters of phosphate-buffered saline (pH 7.4) were injected as control (Sham group).
Mice in CFA1EA group received EA stimulation under anesthetization with 1% sevoflurane; Sham group and CFA group were similarly anesthetized at the same time. For the EA stimulation, 2 needles, 0.3 3 13 mm (Yunlong, China), were inserted at a depth of 1.5 mm in the right hind leg at acupoints corresponding to Zusanli (ST36) and Sanyinjiao (SP6), as described previously. 22 The needles were connected to HANS LH202H Han's acupoint nerve stimulator (Beijing Hua Wei Industrial Development Co, Beijing, China). Electroacupuncture stimulation (2-15 Hz alternating wave, 1.0 mA) was initiated after CFA injection and lasted for 30 minutes. This process was repeated every 2 days (Fig. 1). Sham eletroacupuncture (SEA) was acupuncture needle insertion into acupoints without electrical stimulation or manual needle manipulation. 45

Behavioral testing
Behavioral testing was conducted as described previously. 3 Briefly, paw withdrawal responses to thermal/mechanical stimuli were separately measured with a Model 336 analgesia meter (IITC Inc, Life Science Instruments, Woodland Hills, CA) and a von Frey monofilament (0.16 g; North Coast Medical Inc, Gilroy, CA). Paw withdrawal latency (PWL) (s) and paw withdrawal frequency (PWF) ([number of paw withdrawals/10 trials] 3 100) were used to evaluate pain intensity.

Quantitative polymerase chain reaction
Total RNA was extracted from SDH (L3-L5) tissues of mice with TRIzol reagent (Invitrogen, Carlsbad, CA). Then, RNA was reverse transcribed into cDNAs with cDNA Synthesis kit (TaKaRa, Dalian, China). Quantitative polymerase chain reaction (qPCR) was performed with Platinum Taq DNA Polymerase (Bioline, London, United Kingdom). The primes of mouse Ica1 were as follows: forward 59-ACCACTCTGCTCCACTTTT-39 and reverse 59-TTCTTCCCTTC TTTCTCAACT-39. Mouse Gapdh was used as the internal reference gene and was amplified with the following primers: forward 59-AAGAAGGTGGTGAAGCAG-39 and reverse 59-AGGTGGAAGAGTGGGAGT-39.

Plasma membrane fraction isolation
The plasma membrane fraction was extracted as described previously. 1,23 In brief, SDH (L3-L5) tissues of mice were homogenized in cold isolation buffer. The homogenate was centrifuged three times as required, and the final precipitation was the the plasma membrane fraction.

Coimmunoprecipitation and Western blot
SDH (L3-L5) tissues of mice were lysed in radio immunoprecipitation assay (plus phenylmethanesulfonyl fluoride) and centrifuged. The decimus supernatant was used as the input, and the remainder was used for coimmunoprecipitation (co-IP). Mouse anti-PICK1 antibody was precoupled to protein A-Sepharose beads on the table concentrator at room temperature (20-25˚C) for 2 hours. Precleared solubilized preparations were incubated with the antibody. Proteins on the beads were extracted with 40 mL of 1X sodium dodecyl sulfate buffer and boiled for 5 minutes at 70˚C.
The total protein from SDH was obtained with lysis buffer (Beyotime, Shanghai, China). Equal amounts of protein were separated by sodium dodecyl sulfate polyacrylamide gel electrophoresis and transferred to polyvinylidene fluoride membranes (Millipore, MA). After blocking the membranes with 5% bull serum albumin for 2 hours at room temperature, they were incubated with the primary antibodies anti-GAPDH   United Kingdom), and anti-phospho-GluR2 (Ser880) (Ab52180; Abcam) at 4˚C overnight. After washing the membranes, they were probed with the corresponding secondary antibodies before development using an ECL Western blotting detection system (BioRad, Hercules, CA).

Intrathecal injection
This method has been described in detail by Hylden et al. 18 In brief, the microsyringe was inserted into L4 or L5 spinous space and advanced carefully until the tail was seen flicking. Then, inject 5 mL volume of drug over 30 seconds. In addition, note that mice with motor impairment should be excluded.

Immunohistochemistry and immunofluorescence
The mouse spinal cord tissue was fixed with 4% paraformaldehyde for 24 hours, and cross-sections of the spinal cord tissue were obtained after being embedded in paraffin. Anti-GluR2-p was used to detect corresponding proteins in the sections. The sections were stained with diaminobenzidine for 15 seconds.
Donkey serum (5%) was used to block the nonspecific binding sites at room temperature for 1 hour. The sections were incubated with primary antibodies against PICK1 and ICA69 overnight at 4˚C. After washing with phosphate-buffered saline thrice, the sections were incubated with the fluorescent secondary antibodies (Jackson) DyLight 488 goat anti-mouse lgG (H 1 L) and DyLight 594 donkey anti-rabbit lgG (H 1 L) for 1 hour at room temperature. Finally, the nuclei were stained with 4',6-diamidino-2-phenylindole and imaged with Leica Sp5 II laser confocal microscope.

Statistical analysis
Data analysis and original image productions were performed using Prism5 software. Statistical differences were determined using one-way analysis of variance for Western blots and qPCR, and 2-way repeated-measures analysis of variance was applied for the data from the behavioral tests. Data in the text and figures are shown as mean 6 SEM. Statistical significance was accepted when P , 0.05. All statistical analyses were conducted with SPSS 19.0 software.

Electroacupuncture significantly relieved the complete Freund adjuvant-induced hyperalgesia and increased ICA69 expression in SDH
We used the measurements of PWF and PWL to examine the extent of hyperalgesia induced by CFA injection and the antihyperalgesic effects of EA. The mice of CFA group developed mechanical and thermal hyperalgesia, which lasted for 7 days on the ipsilateral side (CFA vs Sham PWF P , 0.001, PWL P , 0.001), but not on the contralateral side (CFA vs Sham PWF P 5 0.572, PWL P 5 0.296). However, EA treatment at ST36 reliably inhibited the CFA-induced increase in PWF at day 1 (P , 0.001), day 3 (P , 0.001), and day 5 (P , 0.001), and blocked the CFA-induced reduction in PWL at day 1 (P 5 0.022), day 3 (P 5 0.001), and day 5 (P 5 0.009). No differences were observed in the contralateral hind paw among Sham, CFA, and CFA1EA groups (Figs. 1A-D). These results indicated that EA could relieve the CFA-induced inflammatory pain, and the effect was most obvious at day 3.
To determine whether the effects of EA were associated with ICA69, we performed qPCR, Western blot, immunofluorescence, and immunohistochemistry analyses. Samples for qPCR were respectively collected at 6 hours and 3 days after CFA injection. There were no significant changes in the Ica1 mRNA expression in response to CFA injection compared with Sham group at either 6 hours (P 5 0.993) or day 3 (P 5 0.8067). However, the Ica1 mRNA level was significantly increased on the ipsilateral side of the CFA1EA group compared with the CFA group at same time points after injection (6 hours, P 5 0.001; day 3, P , 0.001). This effect was not observed on the contralateral side (Figs. 1E and F). Next, we examined the total protein content of ICA69 in Sham, CFA, and CFA1EA groups by Western blot analysis. No significant difference was observed on the ipsilateral and contralateral sides of SDH between the CFA group and the Sham group. However, EA treatment significantly increased the ICA69 protein content on the ipsilateral side compared with the CFA group (P 5 0.037) (Fig. 1G). It seems that EA affects ICA69 expression on both ipsilateral and contralateral sides, as WB results show that ICA69 expression of the contralateral side increased with EA treatment (P 5 0.042) (Fig. 1G). This is an interesting result of the study that we will discuss later. We also used immunofluorescence and immunohistochemistry to detect the distribution of ICA69 in SDH. Consistent with the Western blot results, the ICA69 level seemed to increase on the ipsilateral side of SDH in the CFA1EA group compared with the CFA group, whereas there was no difference in ICA69 expression on the contralateral side between the 2 groups ( Fig. 1H and Supplement Figure 4, available at http://links.lww.com/PAIN/A698). These results indicated that EA relieved the CFA-induced hyperalgesia accompanied by an increase in ICA69 expression.
3.2. ICA69 expression reached the peak value around the day 3 but sham electroacupuncture had no effect To further understand the time window of the effect of EA on ICA69, we detect the variation trend of ICA69 and related protein content in the CFA1EA group during 7 days. We found that ICA69 started to rise at day 1 (P 5 0.002), and the expression reached the peak value around day 3 (P , 0.001), and gradually decreased later, indicating that EA could affect the content of ICA69. (Supplement Figure 1B, available at http://links.lww.com/PAIN/A698). It is known that ICA69 could influence AMPA receptors through interacting with PICK1 38,43 and the increasing GluR2-p could be blocked by EA treatment. So, we also detected the variation trend of GluR2-p, GluR2, and PICK1. We found that GluR2-p started to fall off at day 1 (P , 0.001), and the expression reached the bottom value around day 3 (P , 0.001), and gradually increased later (Supplement Figure 1C, available at http://links.lww.com/PAIN/ A698). And, there was no significant difference in total amount of GluR2 and PICK1 (Supplement Figures 1D and E, available at http://links.lww.com/PAIN/A698).
To ensure the ICA69 is specific in EA analgesia, we performed sham EA manipulation. The results showed that ICA69 expression was not increased in the CFA 1 SEA group (P 5 0.386) (Supplement Figure 3B, available at http://links.lww.com/PAIN/ A698), GluR2-p was not decreased (Supplement Figure 3C, available at http://links.lww.com/PAIN/A698), and there was no statistical difference in PICK1 and GluR2 compared with the CFA group (Supplement Figures 3D and E, available at http:// links.lww.com/PAIN/A698), indicating that sham EA had no effect on ICA69 and GluR2-p EA was specific.

ICA69 deletion impaired the antihyperalgesic effects of electroacupuncture
Based on our results that EA increased the content of ICA69, we used a genomic strategy to directly reveal the role of ICA69 in the analgesic effects of EA with ICA69-KO mice. ICA69-KO mice show normal spontaneous motor activity compared with their WT littermates (ICA69-WT mice). 23 We performed CFA injection with or without EA treatment on ICA69-KO mice and their WT littermates. There was no significant difference in PWF (P 5 0.195) and PWL (P 5 0.408) between the KO-Sham group and WT-Sham group, indicating that ICA69 KO did not affect the baseline of the plantar pain threshold. Injection of CFA induced a significant decrease in ICA69-KO mice (KO-Sham vs KO-CFA PWF P , 0.001, PWL P , 0.001), but no such difference was detected between WT and KO mice (KO-CFA vs WT-CFA PWF P 5 0.560, PWL P 5 0.818), indicating that ICA69 KO did not increase the intensity of CFA-induced hyperalgesia. However, the hyperalgesia intensity of the KO-CFA1EA group was significantly aggravated compared with the WT-CFA1EA group on the ipsilateral side (PWF P 5 0.001, PWL P 5 0.006), whereas no differences were seen between the KO-CFA and KO-CFA1EA groups ( Figs. 2A-D). These effects were not observed on the contralateral side. This indicated that the analgesic effects produced by EA treatment were weakened in ICA69-KO mice, suggesting that ICA69 is necessary for EA analgesia.
3.4. ICA69 deletion impaired the effects of electroacupuncture on the suppression of endogenous GluR2 Our previous investigation showed that the loss of ICA69 increased GluR2 phosphorylation in SDH after subcutaneous formalin injection into the mouse hind paws. 23 To explore the reason why the analgesic effects of EA were weakened in the ICA69-KO mice, we examined the content of GluR2-p, which plays a pivotal role in the spinal transmission of nociceptive information in ICA69-WT and ICA69-KO mice. We confirmed that the GluR2-p level significantly increased after CFA injection compared with the Sham group in both ICA69-WT (WT-Sham vs WT-CFA, P , 0.001) and ICA69-KO mice (KO-Sham vs KO-CFA, P , 0.001). Furthermore, the GluR2-p level of the KO-CFA group was significantly increased compared with WT-CFA group (P 5 0.005), which supported that ICA69 KO leads to an increase of  GluR2-p. 23 Electroacupuncture reduced the GluR2-p level to the baseline level in WT mice after CFA (WT-CFA vs WT-CFA1EA, P , 0.001), which was related to the analgesic effects confirmed by relevant studies. Electroacupuncture significantly downregulated GluR2-p expression in WT mice but not in ICA69-KO mice (KO-CFA1EA vs WT-CFA1EA, P , 0.001) (Figs. 3A and B).
As the behavioral analysis showed that the absence of ICA69 weakened but not completely abolished the relatively reduced intensity of the antihyperalgesic effects of EA, the WB results suggested that ICA69 deficiency likely weakened the regulation of GluR2-p by EA, but did not completely block the effect. Given that there were 2 factors (ICA69 KO and EA treatment) that influenced the level of GluR2-p, a further experiment of GluR2 membrane protein isolation was performed. These results showed that the GluR2 membrane protein content of the WT-CFA1EA group was significantly higher than that in the KO-CFA1EA group (P 5 0.013)    (Figs. 3D and E). This also suggested that the absence of ICA69 weakened, not completely abolished, the protective effect of EA on GluR2 to the cell membrane. We also performed an immunohistochemistry experiment, and the trend was consistent with Western blot results (Fig. 3F). In addition, EA did not affect the content of PICK1 in both ICA69-WT and ICA69-KO mice (Fig. 3C). These results indicated that ICA69 KO impaired the suppression effects of EA on endogenous GluR2, which can explain why the analgesic effects of EA were weakened in ICA69-KO mice.
3.5. Injecting ICA69 peptide into the intrathecal space of ICA69-knockout mice mimicked the effects of electroacupuncture analgesic and inhibited GluR2-p If EA exerts analgesic effects through increasing the content of ICA69, it suggests that ICA69 peptide is likely to have analgesic effects. Based on our synthesized ICA69 peptide, we detected the analgesic effects of ICA69 peptide in ICA69-KO mice. Injecting 5 mL of different concentrations of ICA69 peptide into the intrathecal space of ICA69-KO mice, we evaluated the analgesic effect of ICA69 peptide within 24 hours. There was a significant reduction in PWF of the CFA1Peptide (10 mg/mL) group compared with the CFA1LP group on the ipsilateral side at 6 and 12 hours (P 5 0.005, P 5 0.046) (Supplement Figure 2A, available at http://links.lww.com/PAIN/A698). Then, we detected the effects of ICA69 peptide on the protein levels of GluR2, GluR2-p, ICA69, and PICK1 at 6 hours. It could recover ICA69 expression in SDH of ICA69-KO mice by injecting 5 mL of ICA69 peptide (10 mg/mL) into the intrathecal space (P , 0.001) (Supplement Figure 2C, available at http://links.lww.com/PAIN/ A698). This is consistent with the results that EA increases the expression of ICA69. Then, it increased PICK1 (P 5 0.001) (Supplement Figure 2E, available at http://links.lww.com/PAIN/ A698) and inhibited GluR2-p (P 5 0.030) (Supplement Figure 2D, available at http://links.lww.com/PAIN/A698). This mimics the analgesic effects of EA and inhibited GluR2-p. And, there was no statistical difference in GluR2 (P 5 0.448) (Supplement Figure 2F, available at http://links.lww.com/PAIN/A698). Based on the results, we concluded that ICA69-PICK1-GluR2 signaling pathway may be involved in EA analgesia.
3.6. Electroacupuncture had no effect on the total amount of PICK1 protein, and did not further relieve the complete Freund adjuvant-induced hyperalgesia and GluR2-p in PICK1-knockout mice To explore whether PICK1 was involved in EA analgesic effect, we examined the PICK1 protein content in PICK1-WT mice and behavioral outcome of PICK1-KO mice with EA treatment. Similar to the previous results of Figure 3C, we found no difference in PICK1 total protein expression on both sides among the Sham group, the CFA group, and the CFA1EA group (Fig. 4A). Next, we performed CFA injection with or without EA treatment in PICK1-KO mice and their WT littermates. PICK1-KO mice showed normal spontaneous motor activity when compared with that of their WT littermates (PICK1-WT mice). Electroacupuncture relieved the CFA-induced hyperalgesia in PICK-WT mice. However, the PWF of the KO-CFA group was significantly decreased compared with the WT-CFA group (P , 0.001). These same test results confirm those of a previous relevant study. 3 Interestingly, the PICK1 knockout reduced the PWF, which was similar to the effects of EA observed in the WT-CFA1EA group (P 5 0.421). In addition, there was no significant difference in the PWF detected between the KO-CFA group and the KO-CFA1EA group (P 5 0.723). These data proved that EA could not further relieve the CFA-induced hyperalgesia in PICK1-KO mice. The experiment of PWL demonstrated the same result (PWL KO-CFA vs WT-CFA P 5 0.006; WT-CFA1EA vs KO-CFA P 5 0.613; KO-CFA vs KO-CFA1EA P 5 0.219) (Figs. 4B-E). Thus, we next examined the content of GluR2-p in PICK1-KO mice to investigate the reason that EA did not further relieve the hyperalgesia in PICK1-KO mice. Again, we confirmed that EA could inhibit the GluR2-p level, indicating that PICK1-KO leads to a decrease in the phosphorylation of GluR2 (KO-CFA vs WT-CFA, P 5 0.003). Similar to the behavioral results shown in Figures  4B-E, there was no difference in the amount of GluR2-p between the KO-CFA group and the KO-CFA1EA group (P 5 0.881) (Fig.  4F). This result suggested that PICK1 is likely to participate in the EA analgesic effect and that ICA69 probably regulates the phosphorylation-induced internalization of GluR2 through PICK1.

Electroacupuncture increased the formation of ICA69-PICK1 complexes and decreased the formation of PICK1-GluR2 complexes
To explore how ICA69 mediates the EA analgesic effect through PICK1 and GluR2, we examined whether endogenous ICA69-PICK1 and PICK1-GluR2 protein complexes were regulated by EA. Using quantitative co-IP experiments, we observed a significant increase in the content of the ICA69-PICK1 complex in the CFA1EA group compared with the CFA group (P 5 0.005). However, there was no significant change in the levels of ICA69-PICK1 complexes between the Sham group and the CFA group (P 5 0.891) (Figs. 5A and B). This result suggested that EA could increase the rate of ICA69 binding to PICK1. To further investigate whether ICA69 regulates the internalization of GluR2 through PICK1, we also examined the content of PICK1-GluR2 complexes. Complete Freund adjuvant treatment significantly increased the content of PICK1-GluR2 (Sham vs CFA, P , 0.001), but there was a significant decrease in GluR2 binding to PICK1 in the CFA1EA group compared with the CFA group (P , 0.001) (Figs. 5A and C). On EA treatment, the ICA69 level increases, leading to an increase in the formation of ICA69-PICK1 complexes and a decrease of PICK1-GluR2 complexes.
Next, we performed immune double staining to detect the distribution of the ICA69-PICK1 complex in SDH. Consistent with the results of quantitative co-IP, more ICA69 colocalized with PICK1 in the CFA1EA group of SDH (Fig. 5D).

Discussion
Increasing GluR2-p was blocked by EA treatment; however, the involvement of GluR2 in EA analgesia still remains unknown. 21,22 In the current study, we demonstrate that ICA69, together with PICK1, regulates GluR2 phosphorylation, and thus mediates the antihyperalgesic effects of EA on CFA-induced inflammatory pain.
We are the first to demonstrate that EA increased the content of ICA69 in the spinal dorsal horn. ICA69 expression peaked at 3 days after EA treatment, suggesting the relationship between ICA69 expression and EA treatment. ICA69 deletion impaired the antihyperalgesic effects of EA on GluR2-p. Injecting ICA69 peptide into the intrathecal space of ICA69-KO mice mimicked the effects of EA analgesic and inhibited GluR2-p, indicating increased ICA69 expression and decreased GluR2-p expression are sufficient to EA treatment. Although EA had no effect on the total amount of PICK1 protein, EA did not further relieve the CFAinduced hyperalgesia and GluR2-p in PICK1-KO mice. This suggests that PICK1 is necessary for EA analgesia. Next, we found that EA could increase the formation of ICA69-PICK1 complexes and decrease the amount of PICK1-GluR2 complexes, suggesting that EA affected the interaction between ICA69 and PICK1, as well as GluR2 and PICK1.
It is known that ICA69-PICK1 regulated the concentration of calcium ions through GluR2 in the nervous system, we speculated the potential mechanisms as follows (Fig. 6). On CFA injection, PICK1 is stimulated to transport around the cell membrane, leading to activation of protein kinase C-alpha to ultimately phosphorylate GluR2. Phosphorylation of GluR2 causes the internalization of GluR2 into the cytoplasm so that AMPA receptors lack the GluR2 subunit, making it permeable to Ca 21 . The consequent increase in intracellular Ca 21 in SDH might initiate or potentiate a variety of Ca 21 -dependent intracellular signaling cascades that are associated with the maintenance of inflammatory pain. 37 On EA treatment, ICA69 increased, leading to an increase in the formation of ICA69-PICK1 complexes so that more PICK1 might be retained in the cytoplasm, which no longer induced GluR2 phosphorylation   (Fig. 6). Ultimately, a series of the above-mentioned processes would not occur under EA treatment. Then, the inflammatory pain could be unsustainable. Therefore, our results suggest that ICA69 mediates the analgesic effects of EA and indicate that the trafficking of the ICA69-PICK1-GluR2 complex may be a new underlying mechanism.
However, how EA regulates ICA69 remains unclear. Electroacupuncture was reported to reduce the phosphorylation content of CamKII. 39 Decreased CamKII phosphorylation affects the binding capacity of CamKII and PICK1. 45 Given the interaction between PICK1 and ICA69, the possibility of EA affecting ICA69 exists. The specific mechanism will be a direction of our further research. Notably, the analgesic effects of EA were weakened but not completely obliterated in the absence of ICA69, due to the inhibition of GluR2 phosphorylation. Given that EA could influence multiple signaling pathways, including b-endorphins, 14 5hydroxytryptamine receptors, cannabinoid CB2 receptors, 33 and adenosine A1 receptor, 13 the ICA69-mediated GluR2 phosphorylation through interaction with PICK1 is likely only one of the key factors involved in EA's maintenance of analgesic effects. Moreover, PICK1 interacts with several other proteins in addition to GluR2, including acid-sensing ion channel, 9 GluA1, 24 CamKII, 39 and dopamine receptor, 48 which might also be involved in the maintenance of the analgesic effects by EA. 35 Next, we will use naloxone to block opioid receptors, or DPCPX to block A1 receptors, so as to exclude the effect of other factors on EA analgesia, and then confirm the role of ICA69.
We found increase of ICA69 on the contralateral side of the CFA1EA group but there was no statistical difference (Supplement Figure 4, available at http://links.lww.com/PAIN/A698). Electroacupuncture applied at the right ST36 acupoint increased the ICA69 protein and mRNA expression levels of the ipsilateral spinal cord in mice, and the same tendency of an increase was observed in the contralateral spinal cord. The WB results (Fig. 1) showed that ICA69 expression in the contralateral side was higher in the CFA1EA group compared with the CFA group.
These results were consistent with previous investigation on the effect of acupuncture or EA to the contralateral side. Song et al. 32 found that EA at contralateral Zusanli (ST-36) dramatically decreased intraplantar formalin-induced increase of pERK1/2positive neurons in the ipsilateral superficial dorsal horn of the rat. However, other scientists have shown that acupuncture did not affect the contralateral side. Goldman et al. 13 found that neither 2chloro-N(6)-cyclopentyladenosine nor acupuncture could change the pain response of the contralateral side. So, the effect of EA on the contralateral side is still controversial. The qPCR results showed that ICA69 mRNA level did not increase in the contralateral side, which may be due to decreased degradation in the contralateral side with EA. Based on previous experience, EA tends to exert overt therapeutic effects in certain pathological conditions, such as in a CFA inflammatory pain model, that are distinct from those in a normal physiological state. Therefore, further investigation is required to explore these effects and mechanisms under different conditions.
Li et al. 23 show that ICA69 deficiency promoted the internalization of GluR2 and FML-induced long-lasting pain hypersensitivity. More expression of GluR2-p means more internalization of GluR2 from plasma membrane and more pain. Indeed, there was significant difference in the expression of GluR2-p between the KO-CFA group and the WT-CFA group, which is consistent to the previous study. We found that gavage of ICA69 peptides could recover ICA69 expression in the spinal dorsal horn of ICA69-KO mice. Then, it increased PICK1 and inhibited GluR2-p. ICA69 peptide (10 mg/mL) generated the analgesic effect on inflammation pain induced by CFA, which mimics the effects of EA analgesic. In addition, we found that the expression of PICK1 protein increased with the recovery of ICA69, which confirmed the interaction between PICK1 and ICA69. It indicated ICA69 as a new target for enhancing the EA analgesic efficacy, and the development and application of related drugs could be promoted furthermore. Figure 6. Proposed mechanism of the antihyperalgesic effects of EA stimulation. Before EA, there is a relatively low amount of ICA69 protein in SDH, and it does not abundantly combine with PICK1 protein in the cytoplasm; the medial PICK1 protein is therefore free to transport to the cell membrane, resulting in GluR2 phosphorylation. Once GluR2 is phosphorylated into GluR2-p, endogenous GluR2 will move from the cell membrane into the cytoplasm. AMPA receptors lacking GluR2 become permeable to Ca 21 , resulting in cellular inflammation that leads to hyperalgesia. By contrast, EA treatment increases the amount of ICA69 proteins, forming abundant complexes with PICK1, thereby stranding PICK1 in the cytoplasm. This prevents GluR2 phosphorylation, and therefore AMPA receptors can maintain the impermeability of the cell membrane to Ca 21 , ultimately producing an anti-inflammatory pain effect. EA, electroacupuncture.
March 2019 · Volume 160 · Number 3 www.painjournalonline.com 721 The neuroprotective and anti-inflammation effects of EA have been verified. Because it is now established that ICA69 affects the transport of GluR2 through PICK1, this interaction could be involved in the regulation of synaptic plasticity in the central nervous system, further highlighting the theory that ICA69 mediates the neuroprotective effects of EA. Further explorations of the functions and roles of ICA69 may reveal new insight into the mechanisms underlying synaptic plasticity-associating diseases.
In conclusion, our results indicate that ICA69 mediates the antihyperalgesic effects of EA on CFA-induced inflammatory pain by regulating GluR2 phosphorylation through PICK1. Our study may provide a new target to enhance the EA analgesic efficacy.


extfieldsofstudy: Medicine Biology

text:
Aneuploid CTC and CEC

Conventional circulating tumor cell (CTC) detection technologies are restricted to large tumor cells (> white blood cells (WBCs)), or those unique carcinoma cells with double positive expression of surface epithelial cell adhesion molecule (EpCAM) for isolation, and intracellular structural protein cytokeratins (CKs) for identification. With respect to detecting the full spectrum of highly heterogeneous circulating rare cells (CRCs), including CTCs and circulating endothelial cells (CECs), it is imperative to develop a strategy systematically coordinating all tri-elements of nucleic acids, biomarker proteins, and cellular morphology, to effectively enrich and comprehensively identify CRCs. Accordingly, a novel strategy integrating subtraction enrichment and immunostaining-fluorescence in situ hybridization (SE-iFISH), independent of cell size variation and free of hypotonic damage as well as anti-EpCAM perturbing, has been demonstrated to enable in situ phenotyping multi-protein expression, karyotyping chromosome aneuploidy, and detecting cytogenetic rearrangements of the ALK gene in non-hematologic CRCs. Symbolic non-synonymous single nucleotide variants (SNVs) of both the TP53 gene (P33R) in each single aneuploid CTCs, and the cyclin-dependent kinase inhibitor 2A (CDKN2A) tumor suppressor gene in each examined aneuploid CECs, were identified for the first time across patients with diverse carcinomas. Comprehensive co-detecting observable aneuploid CTCs and CECs by SE-iFISH, along with applicable genomic and/or proteomic single cell molecular profiling, are anticipated to facilitate elucidating how those disparate categories of aneuploid CTCs and CECs cross-talk and functionally interplay with tumor angiogenesis, therapeutic drug resistance, tumor progression, and cancer metastasis.

Background
Circulating tumor cells (CTCs) are cancer cells shed from primary or metastatic solid tumors into peripheral blood, whereas circulating endothelial cells (CECs) are derived from endothelial cells (ECs) of blood vessels into circulation. Clinical relevance of CTCs in tumor metastasis and prognosis [1][2][3], CECs in tumor angiogenesis [4], and CEC clusters in carcinoma [5] have been substantially discussed elsewhere.
Aneuploidy is the hallmark of malignant cells [6,7]. In addition to aneuploid cancer cells and aneuploid endothelial cells localized in tumor tissues, existence of aneuploid CTCs and CECs in peripheral blood has been recently reported [8]. Nonetheless, how those diverse types of aneuploid malignant cells cross-talk and inter-play in tumor formation and metastasis remains to be further investigated. Detection of circulating rare cells (CRCs), including both CTCs and CECs, is the most representative of liquid biopsy due to its unique availability of frequent and non-invasive detecting tumor cells in carcinoma patients. However, the expanded application of the majority of the current CTC detection technologies, relying on either cell size or positive expression of particular anchor proteins on cancer cell surface is significantly limited.
In the present short review, conventional CTC detection strategies, and a novel integrated SE-iFISH platform, applied to examine cytogenetic gene rearrangements in cancer cells, and to co-detect, characterize, molecularly profile aneuploid CTCs as well as CECs, are discussed.

Aneuploidy
Aneuploidy refers to the abnormal alternation (either gain or loss) of chromosomes in a cell. Unlike "constitutional aneuploidy", which is derived from inappropriate chromosome segregation in meiosis of germ cell formation and present throughout whole organisms, the "somatic whole-chromosome or large segmental aneuploidy" is from deviation in mitosis, and only some of cells are affected [9]. Somatic aneuploidy is the most common characteristic of human carcinomas [6,7]. Approximately 90% of solid tumors and 75% of hematological carcinomas exhibit aneuploidy [10,11]. In particular, aneuploid chromosome 8 (Chr 8) was observed in neoplasm cells of several solid tumors, including lung, gastric, pancreatic, colon, bladder, esophageal, and hepatocellular carcinomas, etc. [12]. Besides, aneuploid Chr 8 was also revealed in endothelial cells of tumor mass, known as tumor ECs [13,14].
Aneuploidy is a cellular transformation-related dynamic chromosome mutation event regulated by a number of mitotic genes. Mutations of those mitotic genes were identified in cancer cells, implicating such mutation in induction of mis-chromosome segregated aneuploidy in neoplasm cells [15]. It has been recognized that aneuploidy drives cancer development and evolution [16].
Aberrant ploidy of extra-chromosome in cancer cells was found to lead to genomic instability [17]. In addition, chromosome or regional aneuploidy has been realized to significantly impact expression of hundreds of genes that are either gained or lost in carcinoma cells. Moreover, aneuploidy per se affects transcription of multiple genes due to activation or inhibition of several intracellular signal transduction pathways in response to chromosome copy number variation [18], resulting in a profound variety of phenotypes, which further contributes to tumor heterogeneity, drug resistance, and therapy failure [16].
Given the unique property of aneuploidy in neoplasm cells, novel anti-cancer strategies targeting aneuploidy for cancer therapy have recently been successfully developed [19,20].

CTC and CEC
CTCs and CECs constitute the principal entity of non-hematologic circulating rare cells in circulation.
CTCs in blood and disseminated tumor cells (DTCs) in bone marrow and lymph nodes, are precursors and surrogate markers of tumor metastasis and relapse [1,3,21]. Superior to routine clinic diagnostics, quantitative and qualitative detection and characterization of CTCs/DTCs have been utilized to evaluate therapeutic efficacy [22,23], monitor postsurgical cancer relapse [24,25] and drug resistance in both carcinoma patients [23,26,27] as well as metastatic "patient derived xenograft" (mPDX) tumor animal models [28]. The eminent advantage of quantified CTCs correlating with prostate cancer patients' prognosis in 5 of randomized phase III clinical trials has recently been demonstrated and reported [2]. CECs are relevant to the process of angiogenesis. Despite their pivotal roles in cardiovascular diseases [29], CECs are the biomarker of neoplasm [4,30], and play an integral part in neovascularization, known as tumor angiogenesis, which is essential for invasive tumor growth and metastasis [31]. An increased number of viable CECs correlates with plasma concentration of vascular endothelial growth factor (VEGF) [32], tumor progression, and therapeutic response [30,33,34]. Though there are several subsets of CECs, CD31 is the most common molecule shared by all diverse subtypes [35].

Conventional Strategies and Current Progress in CTC Detection
The majority of the conventional strategies to isolate CRCs (including CTCs and CECs) rely on positively expressed specific cell surface anchor molecules. Application of such technologies is significantly complicated due to constant or dynamic heterogeneity of the anchor proteins. Regarding CTC detection, the majority of the current methodologies are restricted to the specific subset of CTCs showing positive expression of EpCAM [36], whereas absence of EpCAM was reported on as many as 30% of the examined 134 epithelial solid tumors [37]. Moreover, inherit dynamic expression [38,39], highly heterogeneous [12,40], or down-regulation of the anchor protein EpCAM which associates with epithelial-to-mesenchymal transition (EMT) and cancer progression as well as metastasis [41,42], will result in failure to isolate those "uncapturable" EpCAM negative CTCs by means of the anti-EpCAM strategy or its derived techniques [43,44].
Another approach to isolate CTCs is the cell size based filtration, designed to enrich CTCs via filtering out white blood cells (WBCs, 5 µm) [45]. Considering that a tremendous quantity of primary CTCs in cancer patients are of small cell size (≤ WBCs), 70% of the hepatocellular carcinoma (HCC) CTCs detected in either pre-or post-surgery patients are small CTCs [25], the obvious drawback of losing most of the clinically relevant small CTCs [25,46] for such a cell filtration strategy is unneglectable [47,48].
Currently, the most common strategy applied for CTC identification is to immunostain intracellular fibrous protein cytokeratin (CK). Similar to EpCAM, CK is down-regulated during EMT [39,49], which inevitably results in false negative detection of such "invisible" CTCs. Summarized in Figure 1A, additional efforts respectively addressing each individual element of the cellular bio-chain, including digital RT-PCR [50], single or pooled CTCs next generation sequencing (NGS) analysis [51,52], FISH [53,54], quantitative [55] and qualitative (RNAish) [56] analyses of mRNA in transient, CTC protein profiling performed by the single cell proteomics [57], G-proteins and G-protein coupled receptor (GPCR) [55,58,59], etc., were made in attempts to improve identification and characterization of tumor cells. Nonetheless, tri-element methods, rather than single element method, should be integrated into a comprehensive strategy to obtain fundamental improvement for effective detection of highly heterogeneous CTCs. mRNA in transient, CTC protein profiling performed by the single cell proteomics [57], G-proteins and G-protein coupled receptor (GPCR) [55,58,59], etc., were made in attempts to improve identification and characterization of tumor cells. Nonetheless, tri-element methods, rather than single element method, should be integrated into a comprehensive strategy to obtain fundamental improvement for effective detection of highly heterogeneous CTCs. , urine, and punctured lymph node (LN) are processed to remove both WBCs by means of immunomagnetic beads, and RBCs via Cytelligen's non-hematologic cell separation matrix based centrifugation, to enrich non-hematologic CRCs including large, small or the clusters of CTCs and CECs. iFISH: iFISH coordinates all tri-elements along the cellular bio-chain. In situ phenotypic immunostaining of multiple biomarker proteins and karyotypic FISH carried out using a centromere probe (CEP) are simultaneously co-performed on the identical enriched target cell.

Comprehensive in Situ Phenotypic, Karyotypic, and Cytogenetic characterization as well as Classification of CTCs by SE-iFISH
An effective CTC detection strategy is constituted by both efficient isolation and adequate identification. Published efforts to date have only tried to respectively improve either isolation or identification, but rarely both [12]. It is therefore imperative to develop a comprehensive strategy to effectively isolate, identify, characterize, and classify the full spectrum of highly heterogeneous CTCs.
Accordingly, aside from respectively addressing nucleic acids, proteins, or cell morphology alone, an integrated subtraction enrichment (SE), and immunostaining-FISH (iFISH) which coordinates all three elements of nucleic acids, proteins, and cell morphology along the cellular bio-chain ( Figure 1A) has been systematically developed to efficiently isolate and effectively identify CTCs [8,12,40,60,61].
Explicit description of the updated SE-iFISH experimental process in detail has been published [8]. Schematically depicted in Figure 1B, non-hematologic rare cells, including CTCs in various types of specimens, are enriched following non-hemolytic removal of RBCs and maximum depletion of most WBCs (4-5 logs). Since the prototyping SE applied for lung cancer CTC study was initially reported in 2009 [62], significant improvement was made to efficiently enrich various CTCs, DTCs, and circulating tumor microemboli (CTM) in different types of cancer patients or PDX tumor mouse models [28], despite heterogeneous expression of surface anchor molecule(s) on CTCs or cell size variation. Rapidly enriched viable tumor cells, unperturbed by antibody resistance and free of hypotonic damage, are eligible for primary tumor cell culture and a series of downstream analyses. Recently, epidermal growth factor receptor-tyrosine kinase inhibitors (EGFR-TKIs) target therapy (Gefitinib/Irresa ® ) oriented examination of EGFR mutations, performed on the enriched single non-small cell lung cancer CTCs [63], and NGS-guided in vitro drug screening carried out on the cultured metastatic breast cancer cells enriched from patient's cerebrospinal fluid by SE, to successfully select the chemotherapeutic agent palbociclib (the synthetic CDK4/6 inhibitor) upon the identification of a single nucleotide variant (SNV), have been reported [64].
The conventional FISH approach was previously applied by others in an attempt to improve the identification of CTCs [53,54]. However, such circumscribed efforts were complicated due to complicacy of hematologic compositions of blood. Substantial improvement of such attempts is required for better performance with respect to in situ co-detection of chromosome aneuploidy and multiple tumor biomarker expression on or in CTCs.
Given the existing technical hurdles, and in view of the unique and extraordinary significance in terms of performing in situ phenotyping of multiple tumor biomarkers' protein expression and karyotyping chromosome aneuploidy in CTCs, a novel immunostaining-FISH (i•FISH ® , Cytelligen, San Diego, CA, USA) has been developed to comprehensively identify and characterize non-hematologic aneuploid tumor cells ( Figures 1B and 2) [12]. Examined biomarker proteins are not restricted to the cell surface, but may also exist in the cytoplasm or nucleus [60,65]. Since i•FISH ® technology was reported for the first time on gastric CTC study [23], stepwise substantial improvement has been systematically built up to yield maximum efficiency and optimized flexibility for expeditious in situ co-detection of multiple tumor biomarkers or relevant proteins (such as PD-L1, CK, EpCAM, Vimentin, human epidermal growth factor receptor 2 (HER2), CD44, CD133, PSMA, GFAP, CD31, etc.), and aneuploidy of chromosome in CTCs at once [8,28,40,64]. "iFISHed" CTCs are classified into diverse subtypes by their identified tumor biomarker(s) and chromosome ploidy. It has been reported that different subpopulations of CTCs correlate with cancer recurrence in hepatocellular carcinoma patients [25], or chemotherapeutic resistance to cisplatin in both gastric cancer patients and PDX mice [23,28].
In addition to karyotypically examining aneuploidy of chromosomes in cancer cells, iFISH is also uniquely capable of qualitatively and quantitatively co-detecting multiple tumor biomarkers' expression and cytogenetic gene rearrangement, such as anaplastic lymphoma kinase (ALK) gene [66] in adenocarcinomic non-small cell lung cancer (NSCLC) cells, as shown in Figure 3 (ALK-iFISH, Cytelligen, San Diego, CA, USA).
PD-L1, CK, EpCAM, Vimentin, human epidermal growth factor receptor 2 (HER2), CD44, CD133, PSMA, GFAP, CD31, etc.), and aneuploidy of chromosome in CTCs at once [8,28,40,64]. "iFISHed" CTCs are classified into diverse subtypes by their identified tumor biomarker(s) and chromosome ploidy. It has been reported that different subpopulations of CTCs correlate with cancer recurrence in hepatocellular carcinoma patients [25], or chemotherapeutic resistance to cisplatin in both gastric cancer patients and PDX mice [23,28].  In addition to karyotypically examining aneuploidy of chromosomes in cancer cells, iFISH is also uniquely capable of qualitatively and quantitatively co-detecting multiple tumor biomarkers' expression and cytogenetic gene rearrangement, such as anaplastic lymphoma kinase (ALK) gene [66] in adenocarcinomic non-small cell lung cancer (NSCLC) cells, as shown in Figure 3 (ALK-iFISH, Cytelligen, San Diego, CA, USA). . iFISH to co-detect cytogenetic rearrangements of the ALK gene and multi-tumor biomarker expression in cancer cells enriched from blood. A blood specimen containing adenocarcinomic NSCLC cells A549 was subjected to subtraction enrichment, followed by ALK/CK18/Vimentin-iFISH to quantitatively and qualitatively co-detect Chr 2 cytogenetic rearrangements of the broken apart ALK gene, and expression of CK18 as well as the mesenchymal marker Vimentin in enriched cells (a). The iFISH was performed using Vysis 3′ (orange, (b)) and 5′ (green, (c)) ALK Break Apart Probes (BAP) (Abbott Laboratories, Abbott Park, IL, USA). In situ immunofluorescence staining shows that two of cells are WBCs (CD45 + , white arrows, (d)), and the rest of the enriched cells are the spiked non-hematologic cancer cells coded 1-3 (CD45 − ). Cell 1 has two nuclei. All the enriched cancer cells have positive expression of CK18 (CK18 + /CD45 − , (e)), whereas only cancer cell 3 has high amount of mesenchymal marker Vimentin co-expressed (Vimentin + /CK18 + /CD45 − , pink arrow, (f)), Cells 2 and 3 do not express Vimentin. One of the WBCs reveals significant positive staining of Vimentin (Vimentin + /CD45 + , white arrow, (f)). Analysis of ALK-iFISH detection ((g) of merged (b,c)) shows a positive signal of the broken apart ALK gene (the single isolated orange dot of BAP3′ FISH signal, orange arrow) in the lung cancer cell-1(CK18 + /Vimentin − /CD45 − ). An enlarged image of the positive break apart signal of ALK-iFISH is illustrated in top-right corner. The intact ALK genes are displayed by either adjacent (green and orange) or overlapped (yellow) ALK BAP3′ and ALK BAP5′ FISH signals (solid or diffused dots) in tumor cells 1-3 and WBCs. (h) reveals the overlapping image of merged 6 fluorescence channels (a-f), showing a CK18 + /Vimentin − cancer cell possessing the incomplete ALK gene (orange arrow), the CK18 + /Vimentin + double positive cancer cell (pink arrow) and WBCs (white arrows). All the images were acquired and analyzed by the Metafer-iFISH ® automated CRC scanning and analysis system (Zeiss, MetaSystems, and Cytelligen). . iFISH to co-detect cytogenetic rearrangements of the ALK gene and multi-tumor biomarker expression in cancer cells enriched from blood. A blood specimen containing adenocarcinomic NSCLC cells A549 was subjected to subtraction enrichment, followed by ALK/CK18/Vimentin-iFISH to quantitatively and qualitatively co-detect Chr 2 cytogenetic rearrangements of the broken apart ALK gene, and expression of CK18 as well as the mesenchymal marker Vimentin in enriched cells (a). The iFISH was performed using Vysis 3 (orange, (b)) and 5 (green, (c)) ALK Break Apart Probes (BAP) (Abbott Laboratories, Abbott Park, IL, USA). In situ immunofluorescence staining shows that two of cells are WBCs (CD45 + , white arrows, (d)), and the rest of the enriched cells are the spiked non-hematologic cancer cells coded 1-3 (CD45 − ). Cell 1 has two nuclei. All the enriched cancer cells have positive expression of CK18 (CK18 + /CD45 − , (e)), whereas only cancer cell 3 has high amount of mesenchymal marker Vimentin co-expressed (Vimentin + /CK18 + /CD45 − , pink arrow, (f)), Cells 2 and 3 do not express Vimentin. One of the WBCs reveals significant positive staining of Vimentin (Vimentin + /CD45 + , white arrow, (f)). Analysis of ALK-iFISH detection ((g) of merged (b,c)) shows a positive signal of the broken apart ALK gene (the single isolated orange dot of BAP3 FISH signal, orange arrow) in the lung cancer cell-1(CK18 + /Vimentin − /CD45 − ). An enlarged image of the positive break apart signal of ALK-iFISH is illustrated in top-right corner. The intact ALK genes are displayed by either adjacent (green and orange) or overlapped (yellow) ALK BAP3 and ALK BAP5 FISH signals (solid or diffused dots) in tumor cells 1-3 and WBCs. (h) reveals the overlapping image of merged 6 fluorescence channels (a-f), showing a CK18 + /Vimentin − cancer cell possessing the incomplete ALK gene (orange arrow), the CK18 + /Vimentin + double positive cancer cell (pink arrow) and WBCs (white arrows). All the images were acquired and analyzed by the Metafer-iFISH ® automated CRC scanning and analysis system (Zeiss, MetaSystems, and Cytelligen). Primary cancer cells in carcinoma patients are extremely heterogeneous. Evolutionary instability or variation of primary neoplasm cells, in terms of cytogenetic and/or phenotypic conversion between positivity and negativity following tumor progression or therapeutic treatments, is highly and constantly dynamic. Unlike conventional pathological biopsy routinely performed once to detect positivity of the therapeutic target (e.g., ALK, HER2, EGFR, etc.) on primary or metastatic lesions, continuously cytogenetic and/or phenotypic monitoring of dynamic target status on circulating carcinoma cells, such as the described ALK gene rearrangements, phenotypic protein expression of HER2, stem cell markers (CD133, CD44v6, EpCAM), immunotherapeutic marker PD-L1,  Figure 2B) [8], provides a unique, reliable, and convenient approach for more appropriate and accurate evaluation and selection of the expanded scope of cancer patients suitable for the targeted therapy.
"Tumor endothelial cells" located on blood vessel of tumor tissues are a specific population of CD31 + ECs with aneuploid Chr 8 [14,68]. It is reasonable to speculate that aneuploid ECs fall off from blood vessel into circulation and subsequently turn into CD31 + aneuploid tumor CECs. Depicted in Figure 2B-c/d, existence of such tumor CECs with aneuploidy of Chr 8 in peripheral blood has been recently demonstrated by SE-iFISH [8]. Illustrated in Figure 4, both hematologic and non-hematologic aneuploid CRCs, identified by iFISH, constitute the primary entity of aneuploid CRCs (apCRCs). The most representative populations of hematologic apCRCs (aneuploid Chr 12) are tumor cells of lymphoma and myeloma. Non-hematologic apCRCs with aneuploid Chr 8 are composed of aneuploid CTCs and aneuploid CECs. Effective distinguishing of aneuploid CTCs vs. aneuploid CECs ensures high specificity with respect to detecting CTCs performed by iFISH.
instability or variation of primary neoplasm cells, in terms of cytogenetic and/or phenotypic conversion between positivity and negativity following tumor progression or therapeutic treatments, is highly and constantly dynamic. Unlike conventional pathological biopsy routinely performed once to detect positivity of the therapeutic target (e.g., ALK, HER2, EGFR, etc.) on primary or metastatic lesions, continuously cytogenetic and/or phenotypic monitoring of dynamic target status on circulating carcinoma cells, such as the described ALK gene rearrangements, phenotypic protein expression of HER2, stem cell markers (CD133, CD44v6, EpCAM), immunotherapeutic marker PD-L1, and mesenchymal marker vimentin, etc. ( Figure 2B) [8], provides a unique, reliable, and convenient approach for more appropriate and accurate evaluation and selection of the expanded scope of cancer patients suitable for the targeted therapy.
"Tumor endothelial cells" located on blood vessel of tumor tissues are a specific population of CD31 + ECs with aneuploid Chr 8 [14,68]. It is reasonable to speculate that aneuploid ECs fall off from blood vessel into circulation and subsequently turn into CD31 + aneuploid tumor CECs. Depicted in Figure 2B-c/d, existence of such tumor CECs with aneuploidy of Chr 8 in peripheral blood has been recently demonstrated by SE-iFISH [8]. Illustrated in Figure 4, both hematologic and non-hematologic aneuploid CRCs, identified by iFISH, constitute the primary entity of aneuploid CRCs (apCRCs). The most representative populations of hematologic apCRCs (aneuploid Chr 12) are tumor cells of lymphoma and myeloma. Non-hematologic apCRCs with aneuploid Chr 8 are composed of aneuploid CTCs and aneuploid CECs. Effective distinguishing of aneuploid CTCs vs. aneuploid CECs ensures high specificity with respect to detecting CTCs performed by iFISH.

Proteomic and Genomic Profiling of Single Aneuploid CTCs and CECs
Adequate approaches for molecular profiling, including both protein and genomic profiling performed on single CTC have been established. Protein profiling performed by single cell proteomics on the targeted individual CTC is expected to complement transcriptomic and genomic characterization [57]. Concerning cellular genotyping, a variety of strategies were proven applicable to carry out genomic profiling of single CTCs [51,52]. Gene mutations may lead to the inactivation of functional proteins they encode. By means of a non-laser microscopic single cell manipulator (NMSCM, Cytelligen) to collect intact individual iFISHed CRCs detected in various types of carcinoma patients [8], non-synonymous SNVs and additional gene mutations were identified for the first time by us, in the collected single aneuploid CTCs and CECs following whole genome amplification (WGA) of each of the collected cells. Preliminary NGS analyses performed on the single aneuploid CTCs and CECs detected by SE-iFISH in a population of lung, breast, and renal cell carcinoma patients indicated that, in contrast to the relatively low mutation frequency of TP53 in primary carcinoma lesions, a high mutation frequency of tumor suppressor gene TP53, encoding the tumor suppressor protein p53 [69], was shown in every aneuploid CTC across all the cancer patients subjected to SE-iFISH. Specific TP53 gene mutation results were pinpointed in non-functional phenotypic variants (P33R) of the tumor suppressor p53 in the detected circulating neoplasm cells.
An additional distinct, non-synonymous SNV identified in another tumor suppressor gene, CDKN2A, was found to be shared by most of the examined single aneuploid CECs in all the inspected subjects of the same population of patients with diverse carcinomas (our unpublished, ongoing study). CDKN2A encodes two different tumor suppressor proteins: p14, the alternate reading frame protein (ARF) to protect p53 from being broken down; and p16, known as the "inhibitor of CDK4" (INK4a), which is the inhibitor of intracellular endogenous CDK4/6. p16 activates retinoblastoma (Rb) family of proteins, and subsequently blocks traversal from G1 to S-phase [70]. Such regulatory effect is speculated to be impaired when the tumor suppressor gene CDKN2A is mutated in aneuploid CECs. Existence of disparate gene mutations in aneuploid CTCs and CECs, respectively, indicates striking diversity between these two categories of aneuploid circulating cells.
The clinical relevance of aneuploid CECs has remained unknown since their existence was reported [8]. Given that triploid gastric CTCs are resistant to the chemotherapeutic agent cisplatin [23], and moreover, aneuploid tumor ECs possess resistance to both anti-angiogenic drugs [71] and the anti-cancer therapeutic agent, vincristine [72], it is anticipated that effective detection of aneuploid CECs derived from aneuploid ECs may promote more precise evaluation of therapeutic efficacy and tumor progression in carcinoma patients.

Conclusions
There are 22 worldwide ongoing multi-center CTC clinical trials, involving 20 biomarkers for CTCs and 14 for DTCs [3]. The established SE-iFISH strategy, facilitated by the newly developed Metafer-iFISH ® automated CRC image scanning and analysis system (Carl Zeiss, Oberkochen, Germany; MetaSystems, Altlussheim, Germany; and Cytelligen) [8], provides a unique comprehensive platform to effectively detect, phenotypically and karyotypically characterize CRCs with cytogenetic abnormalities of chromosome aneuploidy or gene rearrangements (such as ALK gene) in situ, in both patients and PDX tumor animal models. Diverse subtypes of CRCs, classified by biomarker expression and chromosome ploidy, are relevant to distinct clinical utilities.
A series of intriguing questions, including whether identified mutant TP53 and CDKN2A tumor suppressor genes, respectively shared by CTCs and CECs, could function as a driver to promote those cells into circulation, whether aneuploid CECs in motion could provide a microenvironment for CTCs to facilitate metastatic lesion formation, and how aneuploid CTCs and CECs correlate with tumor formation and progression remains unclear. Extensive co-investigation of aneuploid CTCs and CECs will shed light on how the diverse categories of aneuploid cells in circulation cross-talk and functionally interplay with tumor angiogenesis, progression, and metastasis.