extfieldsofstudy: Biology Medicine

text:
Host factor SMYD3 is recruited by Ebola virus nucleoprotein to facilitate viral mRNA transcription

ABSTRACT The polymerase complex of Ebola virus (EBOV) is the functional unit for transcription and replication of viral genome. Nucleoprotein (NP) is a multifunctional protein with high RNA binding affinity and recruits other viral proteins to form functional polymerase complex. In our study, we investigated host proteins associated with EBOV polymerase complex using NP as bait in a transcription and replication competent minigenome system by mass spectrometry analysis and identified SET and MYND domain-containing protein 3 (SMYD3) as a novel host protein which was required for the replication of EBOV. SMYD3 specifically interacted with NP and was recruited to EBOV inclusion bodies through NP. The depletion of SMYD3 dramatically suppressed EBOV mRNA production. A mimic of non-phosphorylated VP30, which is a transcription activator, could partially rescue the viral mRNA production downregulated by the depletion of SMYD3. In addition, SMYD3 promoted NP-VP30 interaction in a dose-dependent manner. These results revealed that SMYD3 was a novel host factor recruited by NP to supporting EBOV mRNA transcription through increasing the binding of VP30 to NP. Thus, our study provided a new understanding of mechanism underlying the transcription of EBOV genome, and a novel anti-EBOV drug design strategy by targeting SMYD3.

Introduction
Ebola virus (EBOV) is an enveloped negative singlestranded RNA virus belonging to family Filoviridae in the order Mononegavirales [1]. Species Zaire, Sudan, Reston, Tai Forest and Bundibugyo ebolavirus constitute the genus Ebolavirus. Infection of EBOV can cause Ebola hemorrhagic fever (EHF) with high fatality rates in non-human primates and humans [2]. Causing over ten thousands of deaths in the West Africa outbreak between 2013 and 2015, EBOV emerges as one of the most lethal pathogens threatening public health worldwide [3].
The approximately 19-kb genome of EBOV contains 7 genes, encoding nucleoprotein (NP), virion protein of 35 kDa (VP35), VP40, glycoprotein (GP), VP30, VP24, and polymerase large protein (L) [4]. The transcription and replication of EBOV genome take place in the cytoplasm after virus entry [5]. The transcription of the viral genome generates individual primary mRNA species [6]. The viral mRNAs then utilize cellular translation machinery to produce viral proteins. Viral genomic RNA (vRNA) replicates to produce a full-length complementary RNA (cRNA), which serves as template to generate the vRNA in return. The transcription and replication competent polymerase complex of EBOV consists of NP, VP35, VP30 and L [5]. NP directly binds to VP35 and VP30 [7]. VP35 acts as a cofactor of RNA dependent RNA polymerase L, linking NP and L together. NP, VP35 and L are sufficient for viral genomic replication, while VP30 is indispensable for viral transcription [5,8]. The transcription activator function of VP30 is largely dependent on the phosphorylation states of two serine clusters (S29-S30-S31 and S42-S44-S46) in the N terminus [9,10]. Dephosphorylated VP30 has higher RNA binding affinity and stronger association with viral polymerase complex, and thus supports the viral transcription initiation and reinitiation, while highly phosphorylated VP30 favours viral replication [11][12][13][14][15]. NP recruits B56-PP2A phosphatase complex to dephosphorylate VP30 through a conserved LxxIxE motif to support viral mRNA transcription. The VP30 binding site is close to the B56-binding LxxIxE motif in NP, and both regions are required for VP30 dephosphorylation [16]. VP30 may also be dephosphorylated by PP1, however, the kinase(s) that phosphorylates VP30 is unknown [9,10].
NP is the most abundant viral protein in EBOV particles and in infected cells, and is essential for virus encapsidation and transcription and replication of viral genome. NP forms tube-like helical oligomers and binds to viral RNA in vitro and in vivo, which is the basic structure of tread-like virus particle [17,18]. Co-expression of NP, VP35 and VP24 is sufficient for the formation of typical EBOV nucleocapsid in cytoplasm [19,20]. EBOV forms inclusion bodies which are viral factories for virus replication in infected cells [21,22]. NP alone accumulates to form inclusions resembling inclusion bodies, indicating that NP functions as scaffold to recruit other proteins of viral polymerase complex for virus replication [7,23]. VP35 chaperons monomeric NP to prevent nascent NP binding to RNA, and mature NP oligomers undergo conformation change in order to bind RNA properly [24]. Optimized binding affinity between NP and VP30 is essential for viral RNA synthesis [5,25,26]. These observations suggest that NP plays key roles in the replication of EBOV.
In this study, we immunoprecipitated cellular proteins with NP in a transcription and replication competent EBOV minigenome system, and analysed the associated host proteins by mass spectrometry. Among these host factors, we focused on the role of SET and MYND domain-containing protein 3 (SMYD3) in the replication of EBOV. We found that SMYD3 specifically bound to NP, and the depletion of SMYD3 impaired the replication of EBOV, while overexpression of SMYD3 increased viral polymerase activity. SMYD3 mainly affected viral mRNA production, and a mimic of dephosphorylated VP30 partially rescued viral transcription when SMYD3 was depleted. We further found that SMYD3 promoted NP-VP30 interaction in a dose-dependent manner. Our results indicated that SMYD3 regulated the interaction between NP and the transcription activator VP30, and played a key role in viral mRNA transcription of EBOV.

Preparation of samples for mass spectrometry
HEK293T cells were seeded on 10 cm dish and transfected with 10 μg of pCAGGS-NP-HA, 750 ng of pCAGGS-VP35, 450 ng of pCAGGSVP30, 3 μg of pCAGGS-L, 1 μg of pCAGGS-T7 and 1 μg of EBOV minigenome. At 48 hours (h) after transfection, cells were collected and lysed with NP40 lysis buffer (10 mM Tris-HCl, pH7.4, 150 mM NaCl, 0.5% Nonidet P-40, 1% triton X-100, 2 mM EDTA, 10% glycerol) supplemented with protease inhibitor cocktail (Sigma Aldrich) on ice for 30 min. Lysates were clarified and rotated with anti-HA agarose beads for 4 h at 4°C. The beads were then washed for 4 times with 500 μl lysis buffer, boiled at 100°C with loading buffer supplemented with DTT and separated through 10% SDS-PAGE. The proteins were then visualized with ProteoSilver Plus Silver Stain Kit (Sigma Aldrich) according to the manufacturer's instructions. The whole lane was cut into ten slices and prepared for liquid chromatography-tandem mass spectrometry (LC-MS/MS) analysis as described previously [28].

Western blotting
HEK293T Cells were collected and lysed with NP40 lysis buffer supplemented protease inhibitor cocktail (Sigma Aldrich) on ice for 30 min. Lysates were clarified, boiled at 100°C with loading buffer supplemented with DTT for 10 min and separated by SDS-PAGE. Proteins were transferred to nitrocellulose membranes (PALL). The membranes were then blocked with 5% non-fatty milk for 1 h at room temperature and incubated with primary antibodies overnight at 4°C. After 3 washed, membranes incubated with IRDye secondary antibodies (LI-COR) for 1 h at room temperature and scanned with the Odyssey infrared imaging system (LI-COR).

Co-immunoprecipitation (co-IP) assay
HEK293T cells were seeded on 6 cm plates and transfected with plasmids as indicated. At 48 h after transfection, cells were collected and lysed with 500 μl NP40 lysis buffer supplemented with protease inhibitor cocktail (Sigma Aldrich) on ice for 30 min. Lysates were clarified by centrifugation and 50 μl of the lysates was taken as an input control. The remaining lysates were rotated with anti-HA agarose beads for 4 h at 4°C . The beads were then washed 4 times with 500 μl lysis buffer. Proteins were eluted with loading buffer supplemented with DTT at 100°C for 10 min. Input control and eluates were then analysed by western blotting.

Immunofluorescence assay
HEK293T cells were seeded on chambered coverglass (ThermoFisher) and transfected as indicated. At 48 h after transfection, cells were washed twice with PBS and fixed with 4% poly-formaldehyde at room temperature for 10 min. The cells were then washed twice with PBS and incubated with 0.5% Triton X-100 at room temperature for 5 min, followed by PBS washing for 2 times and blocked with 5% bovine serum albumin PBS at room temperature for 30 min. Afterwards, the cells were incubated with primary antibodies at 4°C overnight. After 3 washed with 0.1% tween-20 PBS (PBS-T), the cells were incubated with secondary antibodies (Abcam) at room temperature for 45 min. Next, the cells were washed with 0.1% PBS-T for 2 times and incubate with DAPI at room temperature for 5 min, followed by washing with 0.1% PBST for 3 times. Images were obtained with LSM880 confocal microscopy (Zeiss).

EBOV minigenome assay
The assay has been described previously [5]. Briefly, 25 ng of pCAGGS-NP, 25 ng of pCAGGS-VP35, 15 ng of pCAGGSVP30, 200 ng of pCAGGS-L, 50 ng of EBOV minignome encoding a Renilla luciferase reporter gene, 50 ng of pCAGGS-T7 and 5ng of pGL4-cmv-Firefly luciferase were co-transfected into HEK293T cells for per well in 24-well plate with Lipofectamine 2000 (Invitrogen). In some experiments, VP30-6A was used as indicated. At 48 h after transfection, the cells were lysed and analysed with a dual-luciferase assay kit (Promega) according to the manufacturer's instructions. Replication of EBOV was measured by Renilla luciferase activity normalized to Firefly luciferase values.

EBOV trVLP assay
The assay was performed previously [29]. In brief, 125 ng of pCAGGS-NP, 125 ng of pCAGGS-VP35, 75 ng of pCAGGSVP30, 1 μg of pCAGGS-L, 250 ng of an EBOV tetracistronic minigenome (encoding a Renilla luciferase reporter gene, VP40, GP, and VP24), and 250 ng of pCAGGS-T7 were co-transfected into HEK293T cells (producer cells) for per well in 6-well plate with Lipofectamine 2000 (Invitrogen). After 12 h, cell culture medium was discarded and replaced with fresh medium. At 72 h after transfection, supernatants containing Ebola trVLPs were collected, filtered through a 0.45 μm pore-size filter (Pall) and stored at −80°C until use. For infection of the trVLPs, HEK293T cells (target cells) were plated in 24-well plate and transfected with 25 ng of pCAGGS-NP, 25 ng of pCAGGS-VP35, 25 ng of pCAGGSVP30, 200 ng of pCAGGS-L, 50 ng of pCAGGS-Tim-1 and 5 ng of pGL4-cmv-Firefly luciferase. At 24 h after transfection, medium was discarded and infected with trVLPs. At 12 h after infection, medium was discarded and replaced with fresh medium. At 48 h after infection, target cells were lysed and analysed with a dual-luciferase assay kit (Promega) according to the manufacturer's instructions.

Statistical analysis
A two-tailed Student t-test was used to determine the significance of statistical data. Data were considered significant at *P < 0.05, **P < 0.01 and ***P < 0.001.

Results
Identification of SMYD3 as a host factor facilitating the replication of EBOV To identify host factors associated with EBOV NP in a physiological condition, we utilized immunoprepitation (IP) with NP in a transcription and replication competent polymerase complex system. We firstly tested interactions between a C-terminal HA-tagged NP (NP-HA) and other viral proteins. As expected, NP-HA could interact with VP35 and VP30, and form homo-oligomers at the same time (Figure 1(A)). We took advantage of an EBOV minigenome system to examine the biological function of NP-HA in replication of EBOV [5]. Cells were transfected with plasmids encoding EBOV NP, VP35, VP30, L, T7 polymerase, a T7 promoter-driven EBOV monocistronic minigenome (encodes a single gene, Renilla luciferase, flanked by viral genome 3' leader and 5' trailer sequences), and a control reporter encoding Firefly luciferase in this system. The relative activity of Renilla to Firefly luciferase reflects the transcription and replication of EBOV genome. In the minigenome system, we found that NP-HA had similar activity in supporting polymerase function compared with untagged NP (Figure 1(B)). These results indicated that NP-HA was as competent as untagged NP in supporting the replication of EBOV. We then purified host proteins with NP-HA in this validated EBOV minigenome system. Cells were transfected plasmids encoding NP-HA, other viral proteins, T7 polymerase, and EBOV minigenome, and then lysed for anti-HA immunoprecipitation at 48 h post-transfection (Figure 1(C)). The associated host proteins were analysed with mass spectrometry, and we obtained 52 proteins that potentially interacted with NP (Supplementary Table 1). Comparing our results to two previous studies which also aimed to identify NP-associating host factors, we found that AP1M1, a subunit of adaptor protein complex-1, was the only protein shared by all the three results (Figure 1(D)) [30,31]. AP1M1 facilitates dengue virus (DENV) RNA replication but is not involved in virus binding and internalization [32]. Another sixteen proteins were also identified as interactors of NP by co-IP using NP-GFP as bait (Figure 1(D)) [30]. Among these proteins, HSP90 and HSP70 interact with NP, and HSP70 is require for replication of EBOV by promoting stability of NP [30]. Two poly-(A)-binding protein, PABPC1 and PABPC4, were in the shared list. PABPC1 plays positive role in DENV replication and both proteins may be involved in the replication of EBOV [33]. Interestingly, there were 5 RNA helicases uniquely identified in our study, among which DDX21, DDX3X, and DHX9 play roles in RNA synthesis of several viruses [34][35][36][37][38]. We noticed that SET and MYND domain-containing protein 3 (SMYD3) was a potential host factor associating with NP. SMYD3 belongs to the SET/MYND domain protein family consisting of SMYD1-5. SMYD3 mediates the methylation of histone H3 and H4, and several none histone proteins [39][40][41][42][43], and interacts with Pol II, BRD4 and PC4, playing important roles in mRNA transcription [43][44][45]. Considering the positive role of SMYD3 in cellular RNA synthesis, we decided to further study its function in the replication of EBOV.
To examine the effect of SMYD3 on viral transcription and replication, we tested polymerase activity after knockdown of SMYD3 using SMYD3-specific siRNAs. The depletion efficiency of SMYD3 by two siRNA was confirmed by western blotting (Figure 2(A)). After depletion of SMYD3, the replication of EBOV was significantly impaired in minigenome system (Figure 2 (B)). We next took advantage of a transcription and replication competent virus-like particle (trVLP) system, which could better simulate life cycle of wildtype virus, to investigate the role of SMYD3 in the replication of EBOV [29]. In this system, the modified EBOV genome contains Renilla luciferase reporter gene, VP40, GP, and VP24. This tetracistronic genome allows self-modulated expression of VP40 and VP24 to avoid their negative effect on viral transcription and replication when they are provided in tans, and thus produces robust viral particles in the presence of NP, VP35 VP30 and L in producer cells [46,47]. Target cells were infected with the trVLPs and viral transcription and replication were monitored by luciferase reporter assay. Replication of EBOV was significantly decreased in target cells treated with SMYD3 specific siRNAs compared to those treated with negative control siRNA after infection of trVLPs (Figure 2(C)). In addition, the replication of EBOV was enhanced by overexpression of SMYD3 (Figure 2(D)). Collectively, our data showed that host factor SMYD3 was associated with EBOV polymerase complex, and required for the efficient replication of EBOV.

SMYD3 specifically interacted with EBOV NP
To examine the interaction(s) between SMYD3 and viral proteins of EBOV polymerase complex, HA-tagged NP, VP35, VP30 and negative control GFP were transfected separately into HEK293T cells and anti-HA co-immunoprecipitation (co-IP) was performed using anti-HA agarose beads. We found that endogenous SMYD3 could only be co-purified with NP ( Figure 3(A)), suggesting that SMYD3 was associated with EBOV polymerase through interaction with NP. During infection, EBOV forms typical inclusion bodies in cytoplasm, which consist of viral proteins and are sites for virus replication [21,22]. As SMYD3 was required for replication of EBOV, we next investigated whether SMYD3 was recruited into viral inclusion bodies. Endogenous SMYD3 distributed homogenously in cytoplasm in the absence of viral proteins (Figure 3(B), panel i). When EBOV NP, VP35, VP30, and L were co-transfected into cells, inclusion bodies were formed and endogenous SMYD3 was recruited to sites of inclusions (Figure 3(C), panel ii). Transfection of NP induced inclusions, and SMYD3 was relocated to these inclusions (Figure 3(C), panel iii), which was consistent with the co-IP result. In the parallel experiments, when expressed alone, VP35 or VP30 showed homogenous distribution in the cytoplasm, and no obvious colocalization was found between SMYD3 and these two viral proteins (Figure 3(C), panel iv and v).
There may be possibility that these proteins mediated the localization of SMYD3 to NP-induced inclusions. We firstly examined whether these SG proteins could colocalize with NP. As eIF4G could not be recruited to NP inclusions, we investigated the other four SG proteins [48]. HA-tagged eIF3b, PABP1, G3BP1 or TIAR-1 was separately co-transfected with NP-FLAG and their localizations were examined. None of these SG proteins was colocalized with NP-induced inclusions ( Supplementary Fig. 1). Thus, recruitment of SMYD3 into NP-induced inclusions was not mediated by eIF4G, eIF3b, PABP1, G3BP1 or TIAR-1. Twelve hours later, cells were transfected plasmids for EBOV minigenome system. Cells were collected 48 h after siRNA transfection, followed by dual-luciferase assay. The ratio of Renilla to Firefly luciferase activity of lysates from cells treated with siNC was set to 100%. The mean and SEM from one representative experiment (n = 3) of 3 independent experiments are indicated. (C) Depletion of SMYD3 impaired the replication of EBOV in trVLP system. HEK293T cells were transfected with siNC, siSMYD3-1, or siSMYD3-2. Twelve hours later, cells were transfected with plasmids encoding NP, VP35, VP30, L and Tim-1. At 24 h p.t., medium was discarded and cells were infected with Ebola trVLPs. At 12 h post-infection (p.i.), supernatants were discarded and replaced with fresh medium. At 48 h p.i., cells were collected, followed by dual-luciferase assay. The ratio of Renilla to Firefly luciferase activity of lysates from cells treated with siNC was set to 100%. The mean and SEM from one representative experiment (n = 3) of 3 independent experiments are indicated. (D) Over-expression of SMYD3 promoted the replication of EBOV. HEK293T cells were transfected with empty vector or plasmid encoding FLAG-SMYD3. Twenty-four hours later, cells were transfected with plasmids for EBOV minigenome system. Cells were collected 48 h after the second transfection, followed by dual-luciferase assay and western blotting. The ratio of Renilla to Firefly luciferase activity of lysates from cells transfected with empty vector was set to 100%. The mean and SEM from one representative experiment (n = 3) of 3 independent experiments are indicated. *P < 0.05, **P < 0.01 (student's t-test).
In summary, we found that SMYD3 specifically bound to EBOV NP and was recruited to EBOV inclusion bodies through the interaction with NP.

Analyses of regions responsible for the interaction between SMYD3 and NP
To map the region(s) of NP interacting with SMYD3, six truncated species of NP were generated, including NP-A(Δ2-75), NP-B(Δ76-150), NP-C(Δ151-300), NP-D(Δ301-450), NP-E(Δ451-600) and NP-F(Δ601-739) (Figure 4(A) top panel). In co-IP assay, NP-E (Δ451-600) was found to be the only mutant that lost the binding to endogenous SMYD3 (Figure 4(A) bottom panel). Five mutants with deletions within amino acid (AA) 451-600 of NP were further constructed to search for regions binding to SMYD3 (Figure 4(B) top panel), among which only NP-E5 (Δ556-600) could not bind to SMYD3 (Figure 4(B) bottom panel). Interestingly, multiple sequence alignment of NP AA of five species of EBOV showed that there were two relatively conserved regions within AA 556-660, one is the LxxIxE motif which is responsible for interaction of NP with B56, another is an SLPPLESDDE sequence (Figure 4(C)) [16]. We speculated that later region was responsible for NP-SMYD3 interaction. To test this hypothesis, we constructed NP mutants with single point mutation within the SLPPLEDSDDE sequence and investigate their binding to SMYD3. The co-IP results revealed that most of these mutants exerted impaired function in binding to SMYD3, especially NP-S581A, NP-P583A, NP-L585A and NP-E586A (Figure 4(D)), suggesting that an SxPxLE motif in NP was responsible for interaction with SMYD3. To explore whether the interaction between NP and SMYD3 was conserved among different EBOV species, we generated plasmids encoding wild-type Reston virus NP (Re-NP-WT) and Reston virus NP-L585A (Re-NP-ΔSMYD3). In co-IP experiments, Re-NP-WT co-purified SMYD3 as efficiently as wild-type Zaire virus NP (Za-NP-WT), whereas Re-NP-ΔSMYD3 could not bind to SMYD3 (Figure 4 (E)). Re-NP-WT recruited SMYD3 to inclusions as Za-NP-WT did, while Re-NP-ΔSMYD3 and Zaire NP-L585A (Za-NP-ΔSMYD3) did not (Figure 4(F)). Taken together, our studies demonstrated that EBOV NP bound to SMYD3 through a relatively conserved SxPxLE motif and the NP-SMYD3 interaction was conserved among EBOV species.
The regions of NP responsible for interaction with B56, SMYD3 and VP30 are AA 562-567, 581-590 and 603-612, respectively, which are of close proximity [16,25,26]. We sought to investigate whether the failure of colocalization with NP of one protein influences that of the other two proteins. To this end, NP-WT, NP-L562A/I565A/E567A (NP-ΔB56), NP-ΔSMYD3 or NP-603-606A/610-612A (NP-ΔVP30) was separately co-transfected with B56α, SMYD3 or VP30, and their localizations were examined. As expected, no colocalization between NP-ΔB56 and B56α or NP-ΔVP30 and VP30 was observed ( Figure 5   function mutations of B56, SMYD3 or VP30 binding motif did not prevent NP recruiting the other two proteins into its inclusions. SMYD3 contains five domains [50,51]. A SET domain, a conserved catalysis region for lysine methylation, is split into an N-SET and a core-SET domain by a MYND domain, which is a zinc finger motif contribute to protein-protein and protein-DNA interaction. The SET domain is followed by a post-SET domain which supports cofactor and substrate binding, and a tetratricopeptide repeats-like (TPR) structure. We generated internal truncated SMYD3 to map region(s) binding to NP according to its crystal structure ( Figure  6(A) top panel). In co-IP experiments, although none of these mutants completely lost the binding to NP, SMYD3 without N-SET, MYND or core-SET domain showed impaired function in co-purifying NP ( Figure  6(A) bottom panel). In immunofluorescence assay, SMYD3-ΔN-SET and SMYD3-ΔMYND could not colocalize with NP-induced inclusions ( Figure 6(B) panel ii and iii). Interestingly, SMYD3-Δcore-SET formed aggregates in the cytoplasm, however, these aggregates could not colocalize with NP inclusions (Figure 6(B) panel iv). While other mutants were still redirected to NP-accumulating sites (Figure 6(B) panel v-vii). All together these results showed that the N-SET, MYND and core-SET domains of SMYD3 were important for the interaction with EBOV NP.

SMYD3 promoted the replication of EBOV through facilitating viral mRNA production
We next sought to explore the mechanism of SMYD3 in supporting the replication of EBOV. SMYD3, B56 and VP30 binding sites in NP are close to each other [16,25,26]. As VP30 and PP2A-B56 phosphatase play important role in EBOV mRNA transcription, we hypothesize that SMYD3 might be involved in the process [5,8,16]. After depletion of SMYD3, we found that viral mRNA was significantly decreased, while vRNA and cRNA only showed modest changes (Figure 7(A-C)). EBOV mRNA transcription is activated by dephosphorylated VP30. Dephosphorylation of VP30 by PP1 and PP2A promotes its activity in supporting viral transcription [10,16]. Okadaic acid could inhibit the catalytic activity of PP1 and PP2A, and thus inhibited EBOV viral transcription [9,12]. NP mutant which did not bind to PP2A-B56 phosphatase could not support viral mRNA transcription. VP30-6A with all the six serines of S29-S30-S31 and S42-S44-S46 mutated to alanine, mimicking nonphosphorylated VP30, supported viral mRNA transcription in the presence of okadaic acid or when NP lost PP2A-B56 binding ability. As SMYD3 was important for mRNA production, we hypothesized that VP30-6A could rescue replication of EBOV when SMYD3 was depleted. When transfected in the replacement of wild-type VP30 (VP30-WT) in the minigenome system, VP30-6A could partially rescue the impaired replication of EBOV induced by SMYD3-specific siRNA treatment, while it showed similar activity as VP30-WT in cells treated with negative control siRNA (Figure 7(D)). These results suggested that SMYD3 was involved in VP30-dependent mRNA transcription. We speculated that SMYD3 might strengthen the binding of B56 or VP30 to NP. We transfected increasing doses of SMYD3 and examined the amounts of B56α or VP30 co-purified with NP. Results showed the amounts of VP30 pulled-down by NP were increased in a SMYD3 dose-dependent manner (Figure 7(E)), while those of B56α co-purified with NP were not affected (Figure 7(F)), suggesting SMYD3 promoting the interaction of NP and VP30, but not that of NP and B56α.
In conclusion, our data showed that depletion of SMYD3 inhibited EBOV mRNA transcription, which could be partially rescued by VP30-6A, and SMYD3 supported vial mRNA transcription through strengthening NP-VP30 interaction.

Discussion
EBOV NP binds strongly to viral RNA and acts as scaffold to recruit other viral protein for transcription and replication of virus genome [7,23]. However, the host factors that interact with NP are largely unknown. In this study, we identified host proteins associated with EBOV polymerase complex using NP as bait by immunoprecipitation and LC-MS/MS analysis. We found that SMYD3 was a unique host factor associated with EBOV polymerase complex. Depletion of SMYD3 impaired replication of EBOV in both minigenome system and trVLP system, indicating its important role in EBOV life cycle.
Co-IP results showed that SMYD3 specifically bound to NP. EBOV forms aggregated inclusion bodies in cytoplasm of host cells. SMYD3, which homogenously distributed in the cytoplasm in cells under normal condition, was relocated to inclusion bodies formed by EBOV polymerase complex. Consistent with the co-IP results, SMYD3 was redirected to NPinduced inclusions when NP is the only viral protein provided. Studies on mapping regions of NP binding to SMYD3 showed that a SxPxLE motif was essential for the interaction. A single AA mutation of residue 585 from leucine to alanine in NP abolishes the interaction between NP and SMYD3 (NP-ΔSMYD3). NP-ΔSMYD3 induced inclusions in cytoplasm as wildtype NP did, however, it lost the ability to relocate SMYD3 into the inclusions. The SxPxLE motif is relatively conserved in between different EBOV species. Indeed, Reston virus NP bound to SMYD3 and relocated SMYD3 into inclusions, while Figure 7. SMYD3 supported EBOV replication by facilitating mRNA production. (A-C) Depletion of SMYD3 down-regulated mRNA production of EBOV. HEK293T cells were transfected with siNC, siSMYD3-1 or siSMYD3-2. At 12 h p.t., plasmids for EBOV minigenome system were transfected. At 48 p.t. of siRNA, cells were collected and RNAs were extracted and analysed by qRT-PCR to measure expression levels of EBOV mRNA (A), vRNA (B), and cRNA (C). Viral mRNA, vRNA and cRNA were reverse transcribed by specific primer. qRT-PCR were performed to measure the relative RNA levels of Renilla to Firefly luciferase. The relative RNA level of cells treated with siNC were set to 100%. The mean and SD from one representative experiment (n = 3) of 3 independent experiments are indicated. (D) VP30-6A rescued replication of EBOV after depletion of SMYD3. HEK293T cells were transfected with siNC, siSMYD3-1 or siSMYD3-2. Twelve hours later, cells were transfected with plasmids of EOBV proteins (NP, VP35, L, and VP30-WT or VP30-6A), T7 polymerase and EBOV minigenome. At 48 h after transfection of siRNA, Cells were collected, followed by dual-luciferase assay. The ratio of Renilla to Firefly luciferase activity of lysates from cells transfected with siNC and VP30-WT was set to 100%. The mean and SEM from one representative experiment (n = 3) of 3 independent experiments are indicated. (E) SMYD3 promoted NP-VP30 interaction in a dose-dependent manner. HEK293T cells were transfected with NP-HA, VP30-FLAG and increasing amounts of FLAG-SMYD3. Empty vector was used to balance the total amounts of plasmids transfected. At 48 h p.t., cells were collected, followed by anti-HA co-IP assay and western blotting. Representative results of 3 independent experiments are shown. (F) SMYD3 had no effect on NP-B56 interaction. NP-HA, B56α-FLAG and increasing amounts of FLAG-SMYD3 were co-transfected into HEK293T cells. Empty vector was used to balance the total amounts of plasmids transfected. At 48 h p.t., cells were collected, followed by anti-HA co-IP assay and western blotting. Representative results of 3 independent experiments are shown. *P < 0.05, **P < 0.01 (student's t-test).
Re-NP-ΔSMYD3 lost these functions. Interestingly, the binding site of SMYD3 in NP located in between those of B56 and VP30 [16,25,26]. Our study revealed that loss-of-function mutations of binding sites of B56, SMYD3 or VP30 in NP did not prevent the other two proteins colocalizing with NP-induced inclusions, indicating that these three binding sites functioned independently. When mapping binding sites of SMYD3 interacting with NP, we found that none of the internal deletion mutants in our study completely lost binding to NP. However, three mutants without N-SET, MYND or core-SET domain showed markedly impaired function in associating with NP, suggesting that the Nterminus of SMYD3 contributed to the interaction.
Depletion of SMYD3 significantly decreased EBOV mRNA, but not vRNA or cRNA. SMYD3 has been reported to interact with viral proteins of Human T-cell leukemia virus type 1 (HTLV-1), Hepatitis C virus (HCV) and Hepatitis B virus (HBV) [52][53][54]. In these reports, SMYD3 influenced viral protein-dependent signal transduction or virus particle production, but had no effect on viral RNA synthesis. For the first time, our study discovered that SMYD3 played a role in viral mRNA transcription. Further study showed that VP30-6A could partially rescue replication of EBOV after depletion of SMYD3. In addition, SMYD3 promoted VP30 binding to NP in a dosedependent manner, indicating that SMYD3 acted as a positive regulator of NP-VP30 interaction to support viral transcription.
In summary, we identified SMYD3 as a novel host factor which was required for efficient replication of EBOV. SMYD3 associated with EBOV polymerase complex via specific interaction with NP and supported viral mRNA transcription through promoting NP-VP30 interaction.

Disclosure statement
No potential conflict of interest was reported by the authors.


extfieldsofstudy: Medicine Biology

text:
Adult Stem Cell Functioning in the Tumor Micro-Environment

Tumor progression from an expanded cell population in a primary location to disseminated lethal growths subverts attempts at cures. It has become evident that these steps are driven in a large part by cancer cell-extrinsic signaling from the tumor microenvironment (TME), one cellular component of which is becoming more appreciated for potential modulation of the cancer cells directly and the TME globally. That cell is a heterogenous population referred to as adult mesenchymal stem cells/multipotent stromal cells (MSCs). Herein, we review emerging evidence as to how these cells, both from distant sources, mainly the bone marrow, or local resident cells, can impact the progression of solid tumors. These nascent investigations raise more questions than they answer but paint a picture of an orchestrated web of signals and interactions that can be modulated to impact tumor progression.

Introduction
Metastases, or dissemination of cancer cells to distant organs with subsequent growth of these cells, are responsible for the majority of deaths due to solid tumors. Upon dissemination, tumor cells step through two situations [1][2][3]. First, the cells must adapt to their new, hostile ectopic environment by undergoing a phenotypic shift that can lead to an extended period of dormancy, which is able to last for years to even decades; during this time the cells are resistant to death signals and chemotherapies and are invisible to the immune system [4]. During the second stage, these cryptic micrometastases emerge and outgrow as aggressive and lethal metastases. Unfortunately, these enlarging tumors acquire new modes of generalized resistance to killing, even if they do now express targets of newer immunomodulatory therapies [4]. To eliminate the mortality related to metastases, we need to keep the early metastases dormant, re-sensitize these growths to therapies, or develop new approaches. Hence, we first need to better understand the cellular behavior and molecular events that enable the dormancy, emergence, and resistances.
The metastatic nodules appear to be phenotypically plastic without the widespread specific genetic mutations that characterize the initial carcinogenesis [2]. Similarly, generalized resistance of these disseminated cells appear to be imprinted by the context of the cancer cells in the organ, as dormancy and chemoresistance can be reversed by tumor-cell extrinsic signals [5,6]. Thus, we need to explore the localized micro-environment rather than the cancer cells per se.
This specialized 'organ' construct, known as the tumor microenvironment (TME), is the tissue space comprised of the cancer cells interacting with surrounding endogenous cells, including parenchymal cells, blood vessels, fibroblasts, matrix, and tissue and hematopoietic immune cells [7][8][9]. Recently, a role for stem cells, both resident in the tissue and recruited from circulation, in regulation of the TME has been proposed. These mesenchymal stem cells (MSCs), also known as multipotent stromal cells, reside in all tissues in addition to circulating from the bone marrow [10][11][12]. MSCs are renowned for their multi-faceted therapeutic potential in tissue repair and wound healing. These cells help reestablish homeostasis not just via expansion and differentiation to provide for cell replacement, but also by altering the resident cells through numerous paracrine signaling cascades, including immune suppressive cytokines, pro-regenerative growth factors, and secretion of extracellular vesicles [13]. It is these signals that may be the greatest effect, as they have progressed to clinical use as pro-regenerative and immunosuppressive therapies while the cellular replacement implementations have lagged [14,15]. In the present review, we discuss these aspects of MSCs, and how the production of these numerous signals may impact the disseminated cells. This review aims to highlight the role of MSCs in tumor progression, the driving of metastasis in particular, in order to provide advanced and comprehensive information on the interaction of MSCs and tumor cells in both primary and metastatic sites.

Mutual Homing between Tumors and MSCs
MSCs are the key players in tumor progression [31]. It has been found that MSCs derived from various tissues can home to tumor sites. Tumor cells and MSCs are able to migrate into each other's niches, as shown in Figure 2. BM-MSCs contribute to the tumor stromal construction by differentiating into endothelial cells or myofibroblasts within and mostly surrounding the tumors in transgenic mouse models of dissemination [32,33]. Accumulating evidence suggests that MSCs can be attracted to tumor sites through multiple signals, including inflammatory cytokines, chemokines, and growth factors [34]. Those signal molecules can be generated by tumor cells themselves or by other cells in TME, and inflammatory cells in particular [35]. Inflammatory cytokines, for example, interleukin-1 beta (IL-1β) and tumor necrosis factor alpha (TNF-α) secreted by immune cells could be acting as chemoattractants for MSCs chemotaxis to tumor sites [36,37]. IL-6 is highly secreted by tumor cells under hypoxic conditions and serves to attract and activate MSCs [38]. Growth factors, such as transforming growth factor-beta (TGF-β), could also induce migration of BM-MSCs [39]. Chemokine CCL25 released by multiple myeloma cells attracts BM-MSCs' move to the tumor location. CCL5 and CXCL12 also play important roles in MSCs' migration to the osteosarcoma cell

Mutual Homing between Tumors and MSCs
MSCs are the key players in tumor progression [31]. It has been found that MSCs derived from various tissues can home to tumor sites. Tumor cells and MSCs are able to migrate into each other's niches, as shown in Figure 2. BM-MSCs contribute to the tumor stromal construction by differentiating into endothelial cells or myofibroblasts within and mostly surrounding the tumors in transgenic mouse models of dissemination [32,33]. Accumulating evidence suggests that MSCs can be attracted to tumor sites through multiple signals, including inflammatory cytokines, chemokines, and growth factors [34]. Those signal molecules can be generated by tumor cells themselves or by other cells in TME, and inflammatory cells in particular [35]. Inflammatory cytokines, for example, interleukin-1 beta (IL-1β) and tumor necrosis factor alpha (TNF-α) secreted by immune cells could be acting as chemoattractants for MSCs chemotaxis to tumor sites [36,37]. IL-6 is highly secreted by tumor cells under hypoxic conditions and serves to attract and activate MSCs [38]. Growth factors, such as transforming growth factor-beta (TGF-β), could also induce migration of BM-MSCs [39]. Chemokine CCL25 released by multiple myeloma cells attracts BM-MSCs' move to the tumor location. CCL5 and CXCL12 also play important roles in MSCs' migration to the osteosarcoma cell line Saos-2 [40]. CXCL16 is a ligand of CXCR6, and it is proved to be involved in the migration of MSCs towards prostate cancer [41].
line Saos-2 [40]. CXCL16 is a ligand of CXCR6, and it is proved to be involved in the migration of MSCs towards prostate cancer [41]. Most mesenchymal tissues are not sites of tumor metastasis with the exception of the bone marrow (and brain), which is one of the main sites of dissemination and lethal growth. As resident cells in bone marrow, MSCs contribute to the recruitment of cancer cells to the bone or bone marrow. Several studies have found that attraction of tumor cells to the bone marrow is dependent on the dual interactions of SDF-1α and its receptor CXCR4 in both cancer cells and MSCs [33,42,43]. More recently, a study has established an inverse relationship between a subpopulation of MSCs and homing of cancer to bone. Such MSC populations express markers of endothelial cells (CD31, CD144, CD146) and pericytes (CD146, CD140b), in addition to MSC markers [44]. These studies suggest that Most mesenchymal tissues are not sites of tumor metastasis with the exception of the bone marrow (and brain), which is one of the main sites of dissemination and lethal growth. As resident cells in bone marrow, MSCs contribute to the recruitment of cancer cells to the bone or bone marrow. Several studies have found that attraction of tumor cells to the bone marrow is dependent on the dual interactions of SDF-1α and its receptor CXCR4 in both cancer cells and MSCs [33,42,43]. More recently, a study has established an inverse relationship between a subpopulation of MSCs and homing of cancer to bone. Such MSC populations express markers of endothelial cells (CD31, CD144, CD146) and pericytes (CD146, CD140b), in addition to MSC markers [44]. These studies suggest that it is specific subpopulations of seemingly homogenous MSCs contribute to the site selectivity of seeding.

MSCs in Tumor Metastasis
Tumor dissemination from the prostate results from a metastatic cascade that involves a series of phenotypic switches. This progression is described in detail in other publications (examples of which include [1,4,8,45]). In brief, a subset of the carcinoma cells undergo a cancer-associated epithelial to mesenchymal transition (cEMT) to separate from the primary tumor and intravasate into circulatory conduits (lymph and blood vessels). At the other end of the circulatory conduits, the cancer cells are arrested in the capillaries, extravasate into the parenchyma and then undergo a phenotypic reversion back to a more epithelial state (cMET), at least transiently, as this not only enables survival in a hostile ectopic environment, but also puts the cells in a state of quiescent dormancy. After a variable period of dormancy, the carcinoma cells again shift towards mesenchymal to enable outgrowth as a lethal metastasis. It should be noted that these phenotypic switches are neither complete nor stringent, in that markers of both epithelial and mesenchymal phenotypes may be present or absent during any state [46]; rather the phenotype relates to the cell functioning and surface expression and ligandation of E-cadherin. While the general outline of this epithelial-mesenchymal plasticity during tumor progression and the functional implications thereof are well described, the TME signals that impart the switches are not understood, and serve as the basis for this review, as we propose that MSCs provide many of these triggers.
MSCs can enhance tumor metastasis by imparting a cEMT. Upon recruitment to the tumor sites, MSCs communicate with tumor cells in multiple ways: (1) direct contact; (2) paracrine secretome including extracellular vesicles; (3) modify other cell types in TME, e.g., immune cells; (4) differentiate into fibroblasts, and (5) fusion with tumor cells [47][48][49][50]. While most studies examine the interaction of MSCs with primary tumor sites, a recent study has shown that circulating MSCs preferentially home to micrometastases [51]. Still, the effects of the invading, and resident MSCs on the tumor cell behaviors may be similar for both the primary and micrometastatic nodules.

Soluble Factors from MSCs Contribute in Tumor EMT
Cancer-associated epithelial to mesenchymal transition (cEMT) and reverting transition (cMET) are required for escape from the primary site and successful metastatic seeding during metastases, respectively [1][2][3]. A plethora of studies have shown that MSCs drive tumor progression, via cEMT in particular, as well as create pre-metastatic niches as supportive microenvironments to aid circulating tumor cell in colonization of the target organ [52]; this is accomplished through the crosstalk between the MSCs and tumor cells, as shown in Figure 3. First, tumor cells can be modulated by MSC-derived signals, including cytokines, chemokines, growth factor, and exosomes. Second, tumor cells in turn affect MSC differentiation and proliferation. Hence, the consequent effects of MSCs in tumor progression depends on the phenotype, molecular signals, and cellular behavior of both tumor cells and MSCs.
In the tumor sites, the chemokines released by immune cells attract MSCs from bone marrow or surrounding tissues; this secretion is increased in the presence of inflammation and may represent the link between inflammation and cancer progression and death. In this case, not only are the MSCs attracted to the tumor, but are also activated to release signals that affect the tumor cells. The chemokine receptors CXCR2, CXCR3, and CXCR4, as well as their ligands, are found to be involved in this progression [49,[53][54][55]. Inhibition of CXCR4 to block the crosstalk between MSCs and tumor cells suppressed hepatocellular carcinoma and osteosarcoma cell line proliferation, migration, and invasion. Inhibition of CXCR4 in the MSCs abolished elevated VEGF secretion, as well as p-Erk and p-Akt levels [53,55]. Increased CXCR2 and its ligands CXCL1, CXCL5, and CXCL7 were found in co-cultured MSCs and breast cancer, with this axis augmenting breast cancer cell migration [49,54]. Moreover, TNF-α stimulated MSCs released more CXCL9, CXCL10, and CXCL11, which are the ligands of CXCR3 [56], to increase cell migration of co-cultured breast cancer cell line MDA-MB-231 via the NF-κB signaling pathway [57]. In the tumor sites, the chemokines released by immune cells attract MSCs from bone marrow or surrounding tissues; this secretion is increased in the presence of inflammation and may represent the link between inflammation and cancer progression and death. In this case, not only are the MSCs attracted to the tumor, but are also activated to release signals that affect the tumor cells. The chemokine receptors CXCR2, CXCR3, and CXCR4, as well as their ligands, are found to be involved in this progression [49,[53][54][55]. Inhibition of CXCR4 to block the crosstalk between MSCs and tumor cells suppressed hepatocellular carcinoma and osteosarcoma cell line proliferation, migration, and invasion. Inhibition of CXCR4 in the MSCs abolished elevated VEGF secretion, as well as p-Erk and p-Akt levels [53,55]. Increased CXCR2 and its ligands CXCL1, CXCL5, and CXCL7 were found in cocultured MSCs and breast cancer, with this axis augmenting breast cancer cell migration [49,54]. Moreover, TNF-α stimulated MSCs released more CXCL9, CXCL10, and CXCL11, which are the ligands of CXCR3 [56], to increase cell migration of co-cultured breast cancer cell line MDA-MB-231 via the NF-κB signaling pathway [57].
Several cytokines including IL-6, IL-8, IL-10, and VEGF have been found to be secreted at higher levels by MSCs activated by IL-37, macrophages, or tumor cells [47,[58][59][60]. Within the tumor microenvironment, IL-6 signaling is generally considered a malevolent player, promoting tumor progression [61]. IL-6 was firstly found mediating the communications between osteosarcoma cell Several cytokines including IL-6, IL-8, IL-10, and VEGF have been found to be secreted at higher levels by MSCs activated by IL-37, macrophages, or tumor cells [47,[58][59][60]. Within the tumor microenvironment, IL-6 signaling is generally considered a malevolent player, promoting tumor progression [61]. IL-6 was firstly found mediating the communications between osteosarcoma cell line Saos-2 and MSCs; a manner in which proliferation was promoted by each other's conditioned media [47]. MSCs isolated from colorectal tumors (CC-MSCs) secreted very high levels of IL-6 in vitro. With the presence of conditioned media from CC-MSCs, colorectal cancer cell lines SW48 and SW480 underwent cEMT, concomitant with enhanced cell migration, invasion, and proliferation [62]. Co-injecting CC-MSCs and SW48 cells in a murine xenograft model enhanced the tumor growth and lung metastasis. IL-6 in the CC-MSC-conditioned media activated Stat3 through Jak2, and PI3K-Akt signaling pathways [62], that latter also being a pathway that promotes tumor cell survival [6]. Macrophages, a major cell component in TME, are able to active MSCs with increased IL-6 and CXCL10 secretion as well [58,63].
Growth factors also play an important role in the interaction between tumor cells and MSCs. TGF-β family members drive cEMT [64]. IFN-γ and/or TNF-α primed adipose-derived MSCs (AD-MSCs) reduced E-cadherin expression in breast cancer cell line MCF-7 via elevated TGF-β1 signaling [65]. This is also true in the melanoma cell line B16. MSC-conditioned media mediated B16 cEMT via the TGF-β1/snail signaling pathway. Co-injection of MSCs with B16 promoted xenografted tumors cEMT [66]. VEGFC and fibroblast growth factor 10 (FGF10) may also participate in the process of tumor cell EMT [59]. MSCs enhanced VEGF expression in tumor cells, accompanied with the activation of RhoA-GTPase and ERK1/2, and a "reprogramming" of tumor growth [67]. Epidermal growth factor (EGF) from breast cancer-associated MSCs promote mammosphere formation via the PI3K/Akt signaling pathway [68].

MSCs Influence Tumor EMT via Multiple Signals
MSCs drive tumor progression not only through these soluble factors but also matrix changes [69][70][71]. When co-cultured BM-MSCs with colon cancer cell line KM12SM, the cEMT related matricellular factors-fibronectin, SPARC, and galectin 1-were only found elevated at the boundary of cancer clusters where direct contact happens [50]. The tumor-progression linked matricellular protein tenascin-C is found at the front of invading tumors and within metastatic tumors to promote survival [4,72]. While these matrix components can be generated by the tumor cells themselves or resident fibroblasts and macrophages, activated MSCs also produce these matricellular signalers at high levels [73][74][75]. Still, more extensive studies are needed to define the contribution of the MSCs in this mode of tumor progression.
Cell fusion may play a crucial role in cancer progression and leads to massive aberrant genotypic and phenotypic changes, though this is still controversial as to the extent in the human situation. It has been reported MSCs are able to fuse with breast, ovarian, lung, gastric, liver, and myeloma cell lines to modulate cancer cell proliferation and cEMT. Fusion of MSCs with SK-OV-3 cells-an ovarian cancer cell line-contributed to the generation of new cancer hybrid populations displaying a significantly reduced tumorigenicity [76]. However, most evidence has shown fusion of MSCs with cancer cells augmented its tumorigenic or metastatic abilities. Lewis lung cancer (LLC) or gastric cancer cell lines and MSC hybrid cells showed enhanced metastatic capacity and characteristics of cancer stem cells by undergoing cEMT. Instead of promoting gastric cancer cell proliferation, the cell cycle was blocked in the G0/G1 phase with elevated expression of p21, p27, and p53 in fused lung cancers [77,78]. This growth suppression in fusion progeny might be mediated by FOXF1 [79]. Fusion of rat BM-MSCs with human liver cancer cells HepG2 with low metastatic potential enhanced EMT promoting markers, such as vimentin, Twist, Snail, and matrix metalloproteinase (MMP) 2 and 9 activities. However, E-cadherin, the presence of which defines the epithelial phenotype, was increased [48]. Meanwhile, the fused cells generated increased numbers of metastatic liver and lung lesions. Moreover, myeloma cells and BM-MSC hybrid cells acquired more stemness potential and increased chemoresistance [80]. Still, whether these findings are generalizable to the human situation remains to be determined.
A specialized situation for promoting tumor progression and survival may occur through the well-described angiogenic actions of MSCs. After being co-cultured with AD-MSCs, the secretome of the breast cancer cell line MCF7, but not MDA-MB-231, was found to be more angiogenic; this was mediated by CXCL1 and CXCL8 released by AD-MSCs [81]. Similar results were also found in the prostate cancer cell line DU-145 [82]. To be notable, both MCF7 and DU-145 are E-cadherin positive cell lines, but MDA-MB-231 is E-cadherin negative; suggesting that this may be a switch to progress the non-metastatic epithelial cells towards dissemination. In mice, MSC-secreted IL-6 mediates cancer cells releasing proangiogenic factor endothelin-1 (ET-1) [83]. Angiogenic factors such as leukemia inhibitory factor (LIF), macrophage colony-stimulating factor (M-CSF), macrophage inflammatory protein-2 (MIP-2), and VEGF are highly generated by MSCs when co-cultured with melanoma B16 cells [84]. Moreover, MSC-derived IL-8 drives angiogenesis in colorectal carcinoma models [85]. Interestingly, aquaporin 1 (AQP1)-a water channel known to promote metastasis-was found to be increased significantly in osteosarcoma and hepatocellular carcinoma cells exposed to conditioned media from BM-MSCs [86]. These studies suggest MSCs may drive progression via upregulation of molecules already linked to metastasis.

MSCs in Tumor Chemoresistance
One of the most daunting aspects of metastatic tumors is the generalized resistance to a variety of therapies displayed by dormant and emergent metastases [4]. This is likely due to signals from the TME that imparts both cancer cell-intrinsic events (such as E-cadherin mediated survival during cMET [6]) and extrinsic signaling events. IL-6 secreted by MSCs not only regulates tumor cells' cEMT, but also induces the chemoresistance. Exposure of Saos-2 and U2-OS cells to MSC-conditioned media increased the viable cells in the presence of therapeutic concentrations of doxorubicin or cisplatin [87]. Meanwhile, these pro-proliferation effects were accompanied by reduced caspase 3/7 activity and Annexin V binding. The activated IL6-STAT3 pathway increased expression of multidrug resistance protein (MRP) and P-glycoprotein (MDR-1) [87,88]. Interestingly, the secretion of IL-6 is also under the control of chemotherapy treatment. Part of MSCs entered a senescent phase rather than apoptosis with cisplatin pre-treatment, showed marked changes in phosphorylation profiles of many kinases, as well as increased secretion of IL-6 and IL-8. It led to increased chemoresistance and stemness of breast cancer cells [89]. Given the key role of IL-6 in MSC-associated tumor metastasis and chemoresistance, and being secreted by many types of cells, it is a very promising approach to metastatic cancer therapy by targeting IL-6 and its signaling pathways in TME. In addition, the Wnt-β-catenin pathway is activated in human cholangiocarcinoma cell line QBC939 by coculturing with umbilical cord-derived MSCs, promoting tumor cell proliferation, chemoresistance, and metastasis [90]. The ability of the MSCs to contribute to a bio-active matrix containing pro-survival matricellular components including tenascin-C [91,92] are additional ways that MSCs may contribute to generalized chemoresistance.

Immune Modulation of MSCs in TME
In the solid tumors, the heterogenic population of tumor cells collaborate with MSCs and immune cells, forming a "vicious triangle" of tumor development [93,94]. Besides communicating with tumor cells directly, MSCs modulate the majority of immune cells in TME, such as macrophages, neutrophils, and nature killer cells, to affect tumor progression. MSCs isolated from spontaneous lymphomas in mouse (L-MSCs) strikingly enhanced tumor growth in comparison to BM-MSCs, by recruiting monocytes/macrophages via the CCR2 signal [94]. Similarly, macrophage-activated MSCs acquired pro-inflammatory phenotype and promoted gastric cancer growth in an NF-κB dependent manner [95]. However, macrophages are heterogeneous in population and can be classified within a spectrum of M1 or M2, polarizing dependent on the stimuli present at time of activation. Tumor-associated macrophages (TAMs) isolated from solid and metastatic tumors have a wound suppressive M2-like phenotype; a phenotype that drives cEMT [96,97]. Interestingly, MSCs educated by M1 macrophage-conditioned media possessed a greatly enhanced ability in promoting tumor growth [98]. Such MSCs expressed high levels of iNOS and MCP1, which in turn increase TAM recruiting. Meanwhile, IL-6 secreted by M1-conditioned media educated MSCs that could polarize infiltrated TAMs into M2 like macrophages [98]. Pancreatic tumor-associated MSCs could recruit monocytes or macrophages and promote alternative macrophage polarization rather than the classical subtype as well [99]. Therefore, MSCs could contribute to tumor cell EMT indirectly via modulating macrophage polarization [97]. In a study regarding the MSCs and tumor progression, tumor cell-derived exosomes affected neither the growth factor production nor the immunosuppressive property of MSCs; rather, they endowed MSCs with a strong ability to promote macrophage infiltration into the tumor by producing plenty of CCR2 ligands, CCL2 and CCL7 [100].
Besides TAMs, tumor-associated neutrophils (TANs) in the TME contribute to tumor progression, invasion, and angiogenesis as well. TNF-α-activated MSCs strikingly enhanced tumor metastasis compared with normal MSCs. Various chemokines were increased in TNF-α-activated MSCs and among them, CXCR2 ligands (CXCL1, CXCL2, and CXCL5) efficiently recruited CXCR2+ neutrophils into the tumor and were responsible for its pro-metastatic effect [101]. An interesting study was performed to investigate the interaction of neutrophils and MSCs when primed by gastric cancer-derived MSCs (GC-MSCs). GC-MSCs activated neutrophils with increased expression of IL-8, TNF-α, CCL2, and oncostatin via STAT3 and ERK1/2 pathways, consequently augmented the migration of gastric cancer cells in a cell contact dependent manner. In turn, GC-MSC primed neutrophils induced the differentiation of normal MSCs into cancer-associated fibroblasts [102].

MSCs Differentiation in TME
MSCs have been investigated mainly as to their pro-tumor effects; but they may also contribute inhibitory stimuli as has been reviewed recently [31]. Multiple aspects regarding these contradictory functions of MSCs in tumors may be context dependent, with MSC heterogeneity being key. First, the origin of MSCs used in the studies might have the distinct characters that led to the differential functions. Second, intact or primary, tumor-derived or immune cell-primed MSCs have distinct secretomes. Lee et al. reported that TNF-α pre-activated MSCs had anti-tumor activity secondary to expressing cell death inducing cytokine TRAIL in a TLR3-dependent manner [103]. Interestingly, prior to this finding and contradictorily, Waterman et al. proposed MSC polarizing resulted from TLR signaling-TLR4 stimulation promoted a pro-inflammatory MSC1, which attenuated tumor growth; whereas TLR3 promoted immunosuppressive phenotype MSC2 to polarize and promote tumor growth and metastasis [104,105]. The effects of MSCs on polarizing macrophages along the lines of pro-progression M2 or quiescing M1 spectrum phenotypes [97] is discussed above.
Cancer-associated fibroblasts (CAFs) are a heterogeneous population of stromal cells in the microenvironment of solid tumors. CAFs are the most prominent stromal cell type, and their abundance was shown to correlate with worse outcomes. Nevertheless, the origin and function of CAFs in tumors are still unclear. However, emerging evidence has shown that MSCs can be a major source of CAFs. MSCs are able to be differentiated into fibroblast-like cells in vitro with breast cancer-conditioned media [106]. Notably, a relatively long term (30 days) incubation was necessary for the transition, indicating MSCs involved in tumor progression as CAFs is a late event after MSC invasion. Moreover, MSCs and CAF share many similarities, including surface markers, as well as capacity to differentiate to osteocytes, chondrocytes, and adipocytes [107]. These differentiation shifts lead to the difficulty in characterizing MSCs and CAF in patient tissues. Most recently, Raz et al. identified PDGFRα as being absent in bone marrow-derived CAFs, but present in resident CAFs. More importantly, BM-derived CAF recruiting decreased the percentage of PDGFRα positive CAFs, and decreased PDGFRα in breast cancer patients was associated with worse prognosis. It suggests that BM-derived CAFs may have more deleterious effects in tumor progression than resident CAFs [108].

Conclusions
The roles of MSCs in tumor growth and progression are only beginning to be discerned. From animal models, copious evidence points toward active attraction of MSCs to tumor sites along with deleterious results of promoting both dissemination, metastasis, and chemoresistance. However, these findings have not been supported in human specimens due to the potentially transient nature of these effects and the differentiation of the MSCs over time. Further, as MSC biology is complex with different subpopulations potentially pulling in opposite directions, further study is critical. Major questions that remain include (a) relative contribution of the circulating versus resident MSCs, (b) effects on the inflammatory network as to indirect promotion of progression including macrophage polarization, (c) effects on immune networks including impact on immunotherapies, (d) differentiation into components of the tumor organ including CAFs, and (e) roles in dormancy and emergence both directly and via altering the TME.


s2fieldsofstudy: Biology Medicine

text:
Distribution of distinct subsets of circulating T follicular helper cells in Kawasaki disease

Background Kawasaki disease (KD) is an acute febrile vasculitis that primarily affects children. Previous studies have shown that both innate and adapt immune systems are involved in the immunopathogenesis of KD. The following study analyzes the distribution of the subsets of Circulating T follicular helper cells (cTfh cells) in KD patients with and without coronary artery lesions (CALs). Methods Twenty KD patients and fifteen healthy sex- and age- matched children were enrolled. Patients were divided into two groups depending on CALs. Blood samples were collected respectively before and after intravenous immunoglobulin (IVIG) administration. Circulating Tfh cells were categorized into three subsets by flow cytometry including cTfh1 (CXCR3 + CCR6-), cTfh2 (CXCR3-CCX6-) and cTfh17 (CXCR3-CCR6+) cells in circulating CD3 + CD4 + CXCR5 + CD45RA- T cells. Cytometric bead arrays were used to analyze the level of IFN-γ, IL-4 and IL-17A. Results We found that frequency of cTfh2 cells was significantly elevated in KD patients before IVIG administration with low expression of cTfh1 cells, where the ratio of cTfh2 + cTfh17/cTfh1 significantly increased. Levels of IFN-γ, IL-4 and IL-17A in KD were significantly higher compared to controls. Further analysis showed that cTfh1 cells were negatively correlated with serum CRP, whereas cTfh2 cells were positively correlated with serum CRP and ESR. Comparison of different groups showed that frequency of cTfh1 cells in CALs+ group were significantly lower compared to CALs- group. In contrast, cTfh2 cells in CALs+ group significantly increased. After IVIG administration, frequency of cTfh2 cells and the ratio significantly decreased while the frequency of cTfh1 cells significantly increased. Meanwhile, all levels of cytokines decreased. Conclusions Our data demonstrated that cTfh1 and cTfh2 cells participate in the pathogenesis of KD, and that the two subsets might be associated with CALs.

Background
Kawasaki disease (KD) is a self-limited systemic vasculitis of small-and media-sized arteries that predominately affects children under the age of 5 years. In the absence of specific indicators, the diagnosis still rests on the clinical symptoms and full exclusion of other possibilities. The conventional diagnostic criteria of KD upon clinical symptoms include fever persisting for at least 5 days, erythema and desquamation of extremity, polymorphic rash, bilateral conjunctivitis, oral changes and cervical lymphadenopathy (diameter ≥ 1.5 cm) [1]. The most serious complications of KD are coronary artery lesions (CALs), which are thought to be the leading cause of acquired heart disease in childhood. With the discovery and clinical application of intravenous immunoglobulin (IVIG) therapy, the incidence of coronary artery disease is significantly reduced. Since it was first reported in 1967, Kawasaki disease has been widely studied, nonetheless it's cause remains unclear. It is commonly thought to be triggered by a pathogen that causes a series of aberrant immune responses. Studies related to immune response have suggested that both innate and adaptive immune systems are involved, leading to impaired immune homeostasis [2,3]. Consequently, understanding the immunopathogenesis of KD is beneficial for the formulation of treatment strategies for KD patients.
Several studies have reported the role of peripheral CD4 + T cell in KD, nonetheless, the results remain controversial [4][5][6]. As a distinct subset of CD4+ T cells, follicular T helper (Tfh) cells have been initially described in the germinal centers (GC) of secondary lymphoid tissues, and can be identified by a biomarker named CXC-chemokine receptor 5 (CXCR5) and by their ability to provide help in selecting high-affinity B cells [7,8]. On account of poor access to tissue samples, Tfh cells in peripheral blood are established, and are named circulating Tfh cells [9]. Given circulating Tfh (cTfh) cells share the immunophenotype and functional nature of GC Tfh cells, cTfh cells can be categorized into distinct subsets by differential expression of biomarker such as CXCR3 and CCR6. CXCR3 is required for IFN-gamma-producing T cells (Th1 cells), while CCR6 is essential for IL-17-producing T cells (Th17 cells) [10]. Three subpopulations of cTfh cells are defined on the basis of the combination of CXCR3 and CCR6: CXCR3 + CCR6-cells share properties with Th1 cells, CXCR3-CCR6-cells share properties with Th2 cells, and CXCR3-CCR6+ cells share properties with Th17 cells [11]. For this reason, they are respectively called cTfh1, cTfh2 and cTfh17 cells. According to the ability in inducing B cells to proliferate, producing immunoglobulins and switching immunoglobulin isotypes when co-cultured with B cells, these three subsets can be divided into efficient cells (cTfh2 and cTfh17 cells) and non-efficient cells (cTfh1 cells) [12]. Furthermore, cTfh2 cells contribute to the production of IgG and IgE, whereas cTfh17 cells promote IgG and IgA secretion [13,14]. In contrast, cTfh1 cells have impact on T cells accumulation in mice, but not in human [15,16]. Current understanding of aberrant cTfh response has shown that imbalance of cTfh-cell subsets, which represents over-expression in cTfh2 or cTfh17 cells and under-expression in cTfh1 cells, is related to multiple diseases. However, the association between these three subsets and Kawasaki disease remains to be investigated.
CTfh cells are considered as a memory compartment of germinal center Tfh cells [13]. It is conventionally believed that CD4+ memory T cell contribute to endow the host with more rapid and efficient abilities in secondary immune responses. Recurring inflammation and the progression of disease are suspected to be the consequence of CD4+ memory T cell dysregulation [17]. Thus, the self-limited property and low recurrence incidence of KD have suggested that circulating memory cells are involved in this process. In the present study, we focus on the subsets of circulating Tfh cells in KD patients including those with and without coronary artery lesions, where we analyze their association with clinical parameters. Our results are helpful to further understand the immunological pathogenesis of KD.

Patients
A total of 20 first-treated KD patients and 15 sex and age-matched healthy controls were enrolled at the Department of Pediatrics, The First Hospital of Jilin University, China, from January to December 2017. The diagnostic criterion was made upon detailed physical and laboratory tests according to 2017 American Heart association (AHA) clinical statement and guidelines [1]. Z-score corrected by BSA and provided from Dallaire et al. was used to evaluate the CALs, which was defined as Z-score ≥ 2 [18]. We used Haycock et al.'s equation to compute BSA [19]. Based on the observation under echocardiography and Z-score, patients were categorized into two groups, CALs+ group and CALs-group. Six patients were subject to coronary artery lesions, and the other 14 patients were classified as CALs-group. Patients with incomplete KD and other autoimmune diseases were beyond the scope of this study.
Treatment options involved the application of IVIG at a dose of 1 g/kg per day for two days and 30-50 mg/kg of oral aspirin per day from diagnosis establishment to defervescence. From each patient, one blood sample was obtained before treatment, and the other sample was collected after IVIG administration at which time the patient had not been febrile for at least 48 h. The healthy control samples were taken from children who came for healthy examination. None of these children had suffered any diseases in the previous month.
The Ethics Committee of The First Hospital of Jilin University approved the experimental protocol and it followed the guidelines of the Declaration of Helsinki. Written informed consents were obtained from all children's parents. The recorded laboratory parameters from all individuals included: white blood cell counts, neutrophil counts, lymphocyte counts, serum C-reactive protein, erythrocyte sedimentation rate, and serum immunoglobulin (IgG, IgA, IgM).

Measurement of cytokines levels
Levels of IFN-γ, IL-4 and IL-17A were measured by CBA Human Soluble Protein Master Buffer kit (BD Biosciences) using flow cytometer. We generated a standard curve for each set of reagents. The minimum and maximum detection limits for all six cytokines were 1.0 and 10,000 pg/ml, respectively. Quantification was performed using Cell-Quest Pro and CBA software (Becton Dickinson).

Statistical analysis
The data are expressed as the median and range and analyzed with SPSS version 22.0 software. P < 0.05 is considered as statistically significant. Kruskal-Wallis test was used to analyze the difference among different phases of KD and healthy individuals as appropriate. Mann-Whitney test was applied to assess the difference between CALs+ and CALs-groups. The difference between before and after IVIG administration was analyzed using the Wilcoxon matched pairs test. The relationship between variables was evaluated using Spearman's rank correlation test.

Clinical parameters
The demographic and clinical characteristics of patients and controls are shown in Table 1. WBC, neutrophil counts, CRP and ESR were significantly higher in KD patients compared to controls. With the exception of CRP, that was significantly higher in CALs+ than in CALs-, WBC neutrophil counts and ESR had no significant difference between CALs+ and CALs-. Additionally, there were no significant differences in lymphocyte counts or serum immunoglobulin concentrations including IgG, IgA and IgM, neither between KD patients and controls or between CALs+ and CALs-.

Subsets of circulating Tfh cells and cytokine levels in different stages of KD
To investigate the importance of cTfh-cell subsets in KD, PBMCs isolated from KD patients in different stages and HCs were immunostained for CD3, CD4, CXCR5, CD45RA, CD183 and CD196 and subsequently analyzed using flow cytometry. Upon the differential expression of CXCR3 and CCR6, three subsets were defined, CXCR3 + CCR6-Tfh (cTfh1) cells, CXCR3-CCR6-Tfh (cTfh2) cells and CXCR3-CCR6+ Tfh (cTfh17) cells, initially by gating on live lymphocytes, then on CD3 + CD4+ T cells and subsequently on CXCR5 + CD45RA-T cells (Fig. 1a). Before IVIG administration, percentage of cTfh1 cells was significantly lower compared to healthy subjects (P = 0.0077, Fig. 1b), whereas percentage of cTfh2 cells was significantly higher (P = 0.0006, Fig. 1c), and the variation of cTfh17 cells was not significant (P = 0.7233, Fig.  1d). As a result, the ratio of cTfh2 plus cTfh17 cells to cTfh1 cells significantly increased (P = 0.0052, Fig. 1e). Additionally, IFN-γ, IL-4 and IL-17A levels in KD patients were significantly higher compared to healthy controls (P < 0.0001, Fig. 1f; P < 0.0001, Fig. 1g; P < 0.0001, Fig. 1h). After IVIG administration, compared with healthy controls, there were no significant differences in the percentage of these three subsets. However, cytokine levels remained significantly higher compared to controls (P = 0.0269, Fig. 1f; P = 0.0019, Fig. 1g; P = 0.0083, Fig. 1h). Our data suggested that cTfh1 and cTfh2 cells, as well as these three cytokines, were involved in the pathogenesis of KD.
The association among cTfh-cell subsets, cytokine levels and clinical parameters To further addressed the role of cTfh cells in the pathogenesis of KD, we investigated the correlation among the distinct subsets of cTfh cells, clinical parameters such as CRP, ESR and serum immunoglobulin concentration, and cytokine levels including IFN-γ, IL-4 and IL-17A. The results (Fig. 2a) showed that percentage of cTfh1 cells was negatively correlated with the value of CRP (P = 0.0179, r = − 0.5233), whereas percentage of cTfh2 cells and the ratio were positively correlated with the value of CRP (P = 0.0313, r = 0.4821; P = 0.0191, r = 0.5188; respectively). Percentage of cTfh2 cells was also positively correlated with the value of ESR (P = 0.0226, r = 0.5068, Fig. 2b). Moreover, there was no correlation among cytokine levels and percentage of cTfh cells (Fig. 2c). None of other significant correlations was found, which suggested that decreased percentage of cTfh1 cells and increased percentage of cTfh2 cells corresponded to the high levels of CRP and ESR.

Circulating Tfh-cell subsets and cytokine levels in different groups
Coronary artery lesions of KD lead to high mortality and disability rates. Consequently, understanding the immune-manifestation of CALs is beneficial for developing strategies for the management of KD patients. As shown in Fig. 3, the percentage of cTfh1 cells was significantly reduced in CALs+ group compared to CALsgroup (P < 0.0001, Fig. 3b), whereas a significant elevated  Fig. 3c). Yet, there were no significant differences in the percentage of cTfh17 cells between two groups (P = 0.5466, Fig. 3d). With high expression of cTfh2 cells and low expression of cTfh1 cells, the ratio was significantly increased in CALs+ group (P < 0.0001, Fig. 3e). Differences in cytokine levels between two groups were not significant (Fig. 3f-h). Thus, much lower cTfh1 cells and higher cTfh2 cells might predict higher possibility of coronary artery lesions.

Variation of cTfh-cell subsets and cytokines after treatment
Next, we explored the percentages of distinct subsets of cTfh cells after IVIG treatment. Among these 20 KD patients, guardians of five patients, including two CALs+ and three CAL-patients, refused blood examination considering that clinical symptoms of their youngsters were improved. Regardless of the CALs+ or CALs-status, the patients showed a consistent variation trend. As exhibited in Fig. 4, percentage of cTfh1 cells significantly increased (P < 0.0001 Fig. 4a), whereas percentage of cTfh2 cells significantly decreased (P < 0.0001 Fig. 4b). Although the variation of percentage of cTfh17 cells was not significant (P = 0.8160, Fig. 4c), the ratio was significantly lower after IVIG application (P < 0.0001, Fig. 4d). Following clinical improvement, levels of cytokines were also downregulated (P = 0.0001, Fig. 4e; P < 0.0001, Fig. 4f; P < 0.0001, Fig. 4g). It can be concluded that the imbalance of cTfh-cell subsets with addition of high levels of IFN-γ, IL-4 and IL-17A contributed to the pathogenesis of KD patients, where following medical treatment, the aberrant immune state was restored.

Discussion
CD4 + CXCR5+ T cells are well-known as a distinct subset of CD4+ T cells, which have the ability to induce B cell proliferation, to differentiate to plasma cells and to secret immunoglobulin. Tfh cells differentiate from naïve T cells via multi-stage and multi-factorial processes [20]. There is also another point of view according to which cTfh cells are derived from T helper cells because they are resemblant at transcriptional level [21]. Currently, the former conception is more convincible. Circulating Tfh cells are thought to be a memory compart of GC Tfh cells with the capacity of rapid and efficient secondary immune responses [22]. The contribution of cTfh cells in the pathogenesis of multiple diseases has been well-established. A study on the relation between cTfh cells and lupus has revealed an increased percentage of cTfh2 cells, associated with disease activity [23]. Another study has indicated that elevation of cTfh17 cells might participate in primary Sjögren Syndrome and that it may be used as biomarker for evaluating the activation of immune stage [24]. In our previous study, we have observed significantly increased cTfh2 and cTfh17 cells, which were related to the occurrence and development of IgA vasculitis [25]. Consequently, we concluded that cTfh cells have an essential role in autoimmunity. In the present study, percentage of cTfh1 cells significantly decreased before IVIG administration. Similarly, a previous research has shown reduced frequencies of IFN-γ-producing CD4+ and CD4-cells in KD [26]. On the contrary, the percentage of cTfh2 cells significantly increased in acute stage. In comparison with cTfh1 cells, cTfh2 cells display more efficient capacity in helping B cells and secreting IL-21 [12]. These data elucidate the increase of IL-21 in KD, which has been proved by Bae and colleagues [27]. It also can be speculated that there may be some changes in B cells. In fact, Yan Ding et al. found that both the absolute value and percentage of B cells in KD were significantly higher than those in healthy and febrile controls [28]. Besides, another study demonstrated that children with KD have a higher allergic susceptibility [29]. The elevated cTfh2 cells might contribute to this process due to their ability in secreting IL-4 and inducing IgE production. After applying IVIG, all these significant variations disappeared with clinical symptom improvement, which made us believe that this memory compartment was involved, even though the exact cause of KD remains unclear.
The over-represented cTfh2 cells and under-represented cTfh1 cells resulted in the imbalance of cTfh-cell subsets, which is thought to be related to disease activities such as SLEIDA score in SLE, PASI score in psoriasis and CDAI score in RA. However, the criterion for systemic assessment of KD activity remains to be established. CRP and ESR values are traditionally considered as the most commonly used indicators to evaluate inflammatory severity of KD. Through further investigation on the association between cTfh cells and CRP or ESR, we found that percentage of cTfh1 cells was negatively correlated with CRP, whereas percentage of cTfh2 cells was positively correlated with both CRP and ESR. Consequently, lower expression of cTfh1 cells and higher expression of cTfh2 cells corresponded to more sever inflammatory response. Interestingly, the existing research has demonstrated that patients with CRP levels higher than 30 mg/L and ESR higher than 40 mm/h are more likely to suffer coronary artery lesions [30]. Given that cTfh cells were correlated with CRP and/or ESR, which associated with CALs, we suspected that cTfh cells would be linked to CALs. So, next we compared percentages of distinct cTfh-cell subsets in CALs+ and CALs-groups and found much lower percentage of cTfh1 cells and much higher percentage of cTfh2 cells in CALs+ group. Therefore, cTfh1 and cTfh2 cells are essential in the development of CALs, and maybe potential indicators of CALs. An optional method is to formulate a range of cTfh1 and cTfh2 cells, which can predict the occurrence of CAL among KD patients, sequentially paying more attention to those individuals. The role of cTfh1 and cTfh2 cells in KD may be related to their cytokines. CTfh1 cells have capacity to secret IFN-γ, which has been recognized to induce type I immunity through stimulating phagocytosis, the oxidative burst and production of proinflammatory cytokines [31]. Previous studies have shown that IFN-γ might contribute to activation of CD4 + CXCR3+ T cells and infiltration of these CXCR3+ T cells in the vessel wall [32]. Additionally, another experiment found that CD4 + CXCR3+ T cells infiltrated in the coronary arterial wall through autopsying dying patients during acute stage [33]. Thus, the percentage of cTfh1 cells in KD was significantly decreased, which might be explained with the expression of cTfh1 cells that is not a real down-regulation, but an increase in consumption. Based on these theories, reducing the level of IFN-γ and preventing these kinds of CD4 + CXCR3+ T cells from infiltrating the coronary arterial wall may be useful in the treatment of Kawasaki disease and prevention of CALs. By contrast, cTfh2 cells produce IL-4. IL-4 seems to have limited roles on the innate immune response. Nevertheless, IL-4 is characterized by inducing type-2 immunity, and is essential in mediating wound-repair, suppression of autoimmune disease and maintenance of tissue homeostasis [34]. Hence, it may be reasonable that the increase of cTfh2 cells and their correlation with CRP and ESR in KD are considered to be secondary to inflammatory to maintain the immune homeostasis. In summary, cTfh cells contribute to the development of KD not only by means of IL-21 secretion but also by producing other cytokines such as IFN-γ and IL-4, the levels of which were significantly higher in KD group. Significantly increased IFN-γ and IL-4 in acute stage of KD have also been proved by a Korean study, which has also indicated the importance of the two cytokines in KD [35]. However, neither our nor the Korean study found further elevated levels of IFN-γ or IL-4 in CALs+ group. We suspected that the formation of CALs, which is a complex process with too many unknown mechanisms that might include a decompensation signal pathway. Certainly, it is insufficient to explain the variation of cTfh cells only by these cytokines in KD patients with CALs. After all, the causes of CALs in KD are diversified, such as cell dysfunction, epigenetic hypomethylation and genetic polymorphisms [36,37]. It is necessary to further investigate the relationship between cTfh cells and CALs+.
It was unexpected that both cTfh-cell subsets and the ratio were not correlated with the levels of serum immunoglobulin, which might be explained with the immature adaptive immune function in children. There are some limitations in this study that should be mentioned. Enlargement of the sample size, particularly of CAL+ group both before and after IVIG administration, is imperative. Moreover, IFN-gamma secreted by cTfh1 cells and IL-4 secreted by cTfh2 cells should be incorporated in the future studies.

Conclusions
In conclusion, to the best of our knowledge, this is the first study that described these three subsets and their imbalance in KD patients. Among these subsets, cTfh1 and cTfh2 cells might have a key role in the development of KD as well as in progression of CALs. It might be beneficial to keep the balance of cTfh-cells subsets for preventing CALs.