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Journal of Cell Communication and Signaling logoLink to Journal of Cell Communication and Signaling
. 2023 Feb 27;17(3):863–879. doi: 10.1007/s12079-023-00733-2

Sam68 promotes osteogenic differentiation of aortic valvular interstitial cells by TNF-α/STAT3/autophagy axis

Xing Liu 1,#, Qiang Zheng 1,#, Kan Wang 1, Jinjing Luo 1, Zhijie Wang 1, Huadong Li 1, Zongtao Liu 1, Nianguo Dong 1, Jiawei Shi 1,✉
PMCID: PMC10409708  PMID: 36847917

Abstract

Calcified aortic valve disease (CAVD) is a major non-rheumatic heart valve disease in the world, with a high mortality rate and without suitable pharmaceutical therapy due to its complex mechanisms. Src-associated in mitosis 68-KD (Sam68), an RNA binding protein, has been reported as a signaling adaptor in numerous signaling pathways (Huot in Mol Cell Biol, 29(7), 1933-1943, 2009), particularly in inflammatory signaling pathways. The effects of Sam68 on the osteogenic differentiation process of hVICs and its regulation on signal transducer and activator of transcription 3 (STAT3) signaling pathway have been investigated in this study. Human aortic valve samples detection found that Sam68 expression was up-regulated in human calcific aortic valves. We used tumor necrosis factor α (TNF-α) as an activator for osteogenic differentiation in vitro and the result indicated that Sam68 was highly expressed after TNF-α stimulation. Overexpression of Sam68 promoted osteogenic differentiation of hVICs while Sam68 knockdown reversed this effect. Sam68 interaction with STAT3 was predicted by using String database and was verified in this study. Sam68 knockdown reduced phosphorylation of STAT3 activated by TNF-α and the downstream gene expression, which further influenced autophagy flux in hVICs. STAT3 knockdown alleviated the osteogenic differentiation and calcium deposition promoted by Sam68 overexpression. In conclusion, Sam68 interacts with STAT3 and participates in its phosphorylation to promote osteogenic differentiation of hVICs to induce valve calcification. Thus, Sam68 may be a new therapeutic target for CAVD.

Graphical abstract

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Regulatory of Sam68 in TNF-α/STAT3/Autophagy Axis in promoting osteogenesis of hVICs

Supplementary Information

The online version contains supplementary material available at 10.1007/s12079-023-00733-2.

Keywords: CAVD, Sam68, hVICs, Osteogenic differentiation, STAT3, Autophagy

Introduction

Calcific aortic valve disease (CAVD) is a leading heart valvular disease with its morbidity having increased 3.51 folds from 1990 globally (Yi et al. 2021). Currently, no effective pharmaceutical therapy but only choice for patients with CAVD is the aortic valve replacement surgery (Nishimura et al. 2014). CAVD is an actively regulated pathological process that involves multiple factors (Small et al. 2017; Myasoedova et al. 2018).CAVD pathological process could be divided into two stages: the initial stage and the progressive stage. The initial stage is characterized by lesion development which is similar to that of atherosclerosis, such as endothelial injury, lipid infiltration, and inflammatory response (Stewart et al. 1997). The ectopic fibrosis and mineralization of human aortic valve tissue are considered the most characteristic pathology of the progress stage (Lindman et al. 2016). It has been demonstrated that the osteogenic differentiation of human valvular interstitial cells (hVICs) is crucial for ectopic mineralization in aortic valve (Rajamannan et al. 2011; Kostyunin et al. 2019; Wang et al. 2021).

Src-associated in mitosis 68 (Sam68) is an RNA-binding protein that participates in multiple physiological or pathological processes, including spermatogenesis (Paronetto et al. 2011), obesity (Huot et al. 2012; Vogel and Richard 2012), and hepatic gluconeogenesis (Qiao et al. 2021). Furthermore, studies demonstrate that Sam68 can work as a signaling adaptor in numerous signaling pathways (Huot 2009), particularly in inflammatory signaling pathways (Ramakrishnan and Baltimore 2011; Tomalka et al. 2017). In the cardiovascular field, it is recently reported that Sam68 accelerates artery injury due to its role in transduction of nuclear factor kappa-B (NF-κB) signaling pathway (Han et al. 2019). The osteogenic differentiation of hVICs is primarily related to inflammatory signaling pathways activated by inflammatory cell or cytokines (Pawade et al. 2015; O'Brien et al. 1995; Coté et al. 2013; Husseini et al. 2014). TNF-α activating NF-κB signaling pathway through Toll-like receptor (TLR) is the classic inflammatory pathway and also been proved promoting osteogenic differentiation process in hVICs (Éva Sikura et al. 2021). Our preliminary experiments have shown high expression of Sam68 in calcific valve tissue. Whether Sam68 participates in CAVD progression by promoting osteogenic differentiation of hVICs was investigated in this work.

In addition, signal transducer and activator of transcription 3 (STAT3) pathway has been shown to be involved in various inflammatory diseases, including atherosclerosis (Chen et al. 2019; Dutzmann et al. 2015). Recent studies suggest that inflammatory cytokines, such as interleukin 6 (IL-6) (Kurozumi et al. 2019) or interleukin 21 (IL-21) (Liu et al. 2020), promote the osteoblastic differentiation in vascular or valve calcification. STAT3 is a crucial signaling molecule that controls cellular adaption in response to stress and inflammatory stimuli such as TNF-α and IL-6, (You et al. 2015). Sam68 is considered to be essential for leptin-dependent STAT3 activation (Sanchez-Margalet and Martin-Romero 2001; Martin-Romero and Sanchez-Margalet 2001). Thus, although Sam68 plays a vital role in osteogenic differentiation of hVICs, its correlation with STAT3 is still unknown.

In this study, we aim to investigate the role of Sam68 in osteogenic differentiation process of hVICs and its association with STAT3 signaling pathway.

Results

Sam68 is highly expressed in calcified valve tissues.

To evaluate the role of Sam68 in CAVD, we determined the expression of Sam68 in normal and CAVD valve tissues. Alizarin red staining showed significant calcium deposition in calcific valve (Fig. 1A). Meanwhile histochemical staining showed that Sam68 was up-regulated in calcific valve tissue compared with normal valve tissue (Fig. 1B and C). The brown cell spot was positive form of Sam68, while the light blue spot was negative. Images were taken under a microscope continuously of one sample. The positive and total cells were counted and the mean percentage of positive cells in calcific samples were calculated for further statistical analysis shown in Fig. 1C. The higher expression abundance of Sam68 in calcific aortic valve tissues was confirmed by Western blotting (Fig. 1D and 1E). Clinical information of patients was gathered and showed (Supplementary table 1). In calcific group, aortic valve calcification (AVC) score was measured. Correlation analysis with Sam68 protein expression was performed and showed that as AVC score rises, so dose the Sam68 expression (r = 0.903, p = 0.0003) (Fig. 1F). Up-regulation of Sam68 mRNA expression in Calcific group was consistent with protein (Fig. 1G). We further detected that Sam68 (red) was mainly expressed in nucleus by co-immunofluorescence with Vimentin (green, expressed in the cytoplasm) both in primary hVICs (supplementary Fig. 1) and valve tissue slice (Fig. 1H). In summary, we revealed that Sam68 is up-regulated in human calcific valve tissues.

Fig. 1.

Fig. 1

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Sam68 is highly expressed in calcified valve tissues. Representative image of Alizarin Red S A and immunohistochemical staining B of Sam68. C Quantification of immunohistochemistry results (n = 6). D and E Protein level of Sam68 in valve tissue measured by western blotting (n = 10). F Correlation analysis between AVC score and Sam68 protein expression (n = 10). G The gene expression of Sam68 and Runx2 were tested by qRT-PCR, the relevant level was normalized to GAPDH gene expression (n = 6). H Immunofluorescent staining of Sam68 (red) and Vimentin (green), DAPI (blue). magnification was 200 × and 400 × . *p < 0.05, **p < 0.01, ***p < 0.001, ****p < 0.0001

Sam68 accelerated osteogenic differentiation in hVICs.

In this study, we first chose 5 treatments that have been used for inducing osteogenic differentiation in hVICs: Osteogenic Medium (Bian 2021), TNF-α (Éva Sikura et al. 2021), IL-6 (Husseini et al. 2014), IL-1β (Isoda et al. 2010), ox-LDL (Greenberg et al. 2022). As shown in Fig. 2A and B, activation of Sam68 was observed in OM, TNF-α and IL-6 treatment, and the most significant was TNF-α. Further, TNF-α was separately used for inducing calcification, increased Runx2, ALP protein level along with Sam68 activation were detected (Fig. 2C and D).

Fig. 2.

Fig. 2

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Sam68 accelerates osteogenic differentiation in hVICs. A, B Sam68 protein level accumulated after osteogenic medium, TNF-α and IL-6 treatment, especially in TNF-α treatment (n = 3). C, D TNF-α significantly induced osteogenic protein Runx2 and ALP expression along with Sam68 up-regulation (n = 3). E, F Runx2 and ALP were tested after overexpression of Sam68 under TNF-α intervention(n = 4). G, H Runx2, ALP in Sam68 knockdown along with TNF-α treatment (n = 3). I, J Alizarin Red staining at 21 days of TNF-α and OM (osteogenic medium) induction with Sam68 overexpressed or knocked down (n = 3). ns. not significant difference, *p < 0.05, **p < 0.01. Vector indicated empty vector group, SiNC indicated negative control siRNA group

Osteogenic differentiation of hVICs was determined by alkaline phosphatase (ALP) and runt-related transcription factor 2 (Runx2) expression, biomarkers of osteogenesis (Li et al. 2017). To explore whether Sam68 elevation in calcific valve tissue has any significance in the osteogenesis process in hVICs, TNF-α was used as an inducer of osteogenesis in hVICs (Éva Sikura et al. 2021). Overexpression of Sam68 aggravated up-regulated Runx2 and ALP protein level compared with TNF-α only intervention group (Fig. 2E and F). By contrast, silencing Sam68 expression mitigated Runx2 and ALP expression elevated by TNF-α (Fig. 2G and H). Alizarin Red S assay was also executed with TNF-α and osteogenic medium incubation for 21 days. The results indicated that Sam68 overexpression accelerated the osteogenic differentiation process and led to calcium deposition. Otherwise, knockdown Sam68 alleviated the calcified nodule formation and deposition. (Fig. 2I and J).

Sam68 promotes osteogenic differentiation through STAT3 signaling pathway in hVICs.

Researchers have reported that TNF-α induced NF-κB signaling pathway was crucial during inflammatory factors stimulating osteogenic differentiation in hVICs (Kaden et al. 2005; García-Rodríguez et al. 2018). Also, STAT3 signaling pathway played an important role in osteogenic differentiation process (Liu et al. 2020), and TNF-α was reported inducible of STAT3 signaling pathway as well. To explore how Sam68 reacts on these signaling pathways, we analyzed the phosphorylation level of transcription factor P65 and STAT3 after Sam68 knockdown. The results illustrated no significant difference between Sam68 knockdown and control group after TNF-α treatment in P65 phosphorylation, but a significant declined phosphorylation level of STAT3 in silenced Sam68 groups (Fig. 3A and B). We also applied IL-6 as a classic inducer of STAT3 signaling pathway, silenced Sam68 also attenuated IL-6 induced STAT3 phosphorylation level and alleviated the osteogenesis process for decreasing Runx2 and ALP protein expression (Supplementary Fig. 2). We further silenced STAT3 expression using siRNA in hVICs with or without Sam68 overexpression. ALP, Runx2 expression and Alizarin Red S staining was performed. The result revealed that STAT3 silencing inhibited the accelerated ALP and Runx2 by Sam68 overexpression and TNF-α stimulation (Fig. 3D and EF). The overexpression of Sam68 and silence efficiency were shown in Fig. 3C. Alizarin Red S staining result showed less calcium deposition in STAT3 silenced group compared to Sam68 overexpression and control groups (Fig. 3G and H). Taken together, our data implicated that Sam68 promoted osteogenic differentiation of hVICs through STAT3 phosphorylation.

Fig. 3.

Fig. 3

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Sam68 promoted osteogenic differentiation via STAT3 signaling pathway. A, B The p-p65/t-p65 and p-STAT3/t-STAT3 ratios and protein expression were detected as TNF-α treatment by time of 0, 2, 5, 10, 30, 60 min (n = 3). C Sam68 overexpression and STAT3 silencing efficiency. D, E and F ALP and Runx2 protein expression when silencing STAT3 with or without Sam68 overexpression, a negative vector (Vector) and siRNA (SiNC) were both used and quantification (n = 4). (G, H) Alizarin Red S staining and quantification (n = 3). ns. not significant difference, *p < 0.05, *p < 0.01, ***p < 0.001, ****p < 0.0001

Sam68 further attenuated STAT3 downstream autophagy flux participating in osteogenic differentiation

Autophagy was reported closely related to inflammation signaling pathways (Luo et al. 2019; Green et al. 2011). STAT3 was also demonstrated as a negative autophagy adaptor (Lin et al. 2019; Zhang et al. 2019), due to Beclin1 and BCL-2 expression balance. Protein level was quantified and revealed that BCL-2 was down-regulated when silencing Sam68, while Beclin1 and ATG7 were up-regulated in protein level (Fig. 4A and B). Also, Sam68 silencing inhibited BCL-2 expression and along with Runx2 in mRNA expression, Beclin1 was not affected otherwise (Fig. 4C).

Fig. 4.

Fig. 4

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Sam68 further attenuated STAT3 downstream autophagy. A, B protein expression of BCL-2, Beclin1 and ATG7 examined after silencing of Sam68 (n = 3). C mRNA expression of BCL-2, Beclin1 and Runx2 was evaluated when Sam68 silencing (n = 3), D, E LC3, P62 protein level detected when overexpression of Sam68 (n = 3). F, G LC3, P62 protein level were tested after Sam68 knockdown (n = 3). ns. not significant difference, *p < 0.05, *p < 0.01, ***p < 0.001

To determine Sam68 blocking autophagy in hVICs, we further detected the expression of light chain 3 (LC3) and P62 to reveal the autophagy alteration. The result showed that Sam68 overexpression increased P62 accumulation in cells while LC3II/I change was not evident among the four groups (Fig. 4D and E). By contrast, the P62 accumulation was alleviated by Sam68 knockdown. LC3II/I was elevated in both TNF-α treatment and SiSam68 transfection, but not between TNF-α treatment group and SiSam68 plus TNF-α group (Fig. 4F and G). The LC3 ratio alteration may be concealed by the long hours of TNF-α treatment for 72 h, so further estimations of autophagic flux using the red fluorescent protein (RFP)-green fluorescent protein (GFP)-LC3 plasmid were observed with 24 h treatment of TNF-α. The result suggested that overexpression of Sam68 could remarkably reduce the number of autophagosomes (shown as yellow dots) and autolysosomes (shown as free red dots). In contrast, knocking down Sam68 significantly increased autophagosome number (Fig. 5A and B). Further comparison of LC3II and P62 protein assay was detected under the alteration by inducer Rapamycin and inhibitor Bafilomycin A1 in SiNC or SiSam68 group. Detection was performed 4 h after the intervention of Rapamycin or/and Bafilomycin A1. The LC3II level indicated mature autophagosome number was significantly enhanced and P62 diminished in the SiSam68 group (Fig. 5C, D and E). To verify the effect of autophagy adapted by Sam68 in osteogenic differentiation, we detected the osteogenic marker ALP and Runx2 with autophagy stimulated by rapamycin. The result showed that ALP and Runx2 protein expression was downregulated in rapamycin pretreated group (Fig. 5F and G). Also, the calcium deposition was alleviated by rapamycin pretreatment (Fig. 5H and I). Thus, the induced osteogenic differentiation by TNF-α and Sam68 was mitigated by rapamycin.

Fig. 5.

Fig. 5

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Sam68 blocked autophagy flux participating in osteogenic differentiation. A, B Autophagic flux detection by LC3-GFP-RFP system of overexpression and silencing of Sam68 with TNF-α intervention. Yellow dots in merged graphic and free red dots were calculated (n = 7). C, D and E LC3 and P62 protein level was tested after Silencing of Sam68 and then treated with autophagy inducer Rapamycin and inhibitor Bafilomycin, relative level was normalized by GAPDH protein expression(n = 3). F, G Runx2, ALP was tested when Rapamycin was added along with TNF-α treatment (n = 3). H, I Alizarin Red S staining and quantification. ns. not significant difference, *p < 0.05, *p < 0.01, ***p < 0.001

Sam68 attenuated STAT3 phosphorylation by interacting with STAT3 SH2 domain

Many biological functions of proteins depend on the formation of protein–protein interactions. To further investigate on how Sam68 affects the phosphorylation of STAT3, protein–protein interactions (PPIs) were predicted by using the online tool (String www.string.com). The result showed that Sam68 potentially interacts with STAT3 (Fig. 6A), and one research paper has revealed that Sam68 was leptin-dependent interact with STAT3 in monocyte (Sanchez-Margalet and Martin-Romero 2001). As shown in Fig. 6B, the binding mode of the Sam68-STAT3 complex was obtained by ZDOCK 3.0.2 predictions. Wheat color is STAT3, blue is Sam68 protein. The yellow dashed line indicates hydrogen bonding. From the cartoon image or surface image, it can be seen that the Sam68 protein is combined with the SH2 domain of STAT3 protein, the TYR-103 and ASP-115 on Sam68 protein and ASN-664 and ASN-647 on STAT3 protein was hydrogen bonding. In addition, LEU-114, LEU-125, LEU-124, PHE-118 on Sam68 protein and MET-660, LEU-666, LYS-658, MET-648 on STAT3 protein formed hydrophobic interactions. In addition, the ZDOCK software gave a binding score of 985.194, further indicating that the two proteins are tightly bound. Interacts was incubated with immunoglobulin (IgG) or anti-Sam68 antibody, then mass spectrometry analysis identified STAT3 as a binding matter of Sam68 (Fig. 6D and E). To verify the interaction in hVICs, immunoprecipitation was performed. Our data showed Sam68 interacts with STAT3 in vitro (Fig. 6C).

Fig. 6.

Fig. 6

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Sam68 attenuated STAT3 phosphorylation by interacting with STAT3 SH2 domain. A Protein–protein interactions (PPIs) were predicted by using the online String database (www.string.com). B Predicted binding mode of Sam68 and STAT3 based on docking, the yellow dashed line represents the hydrogen bond interaction. stick indicates amino acids that form hydrogen bonds. C Immunoprecipitation was performed in hVICs. D Silver-stained gel of total protein from hVICs after immunoprecipitation with IgG or anti-Sam68 antibody. E STAT3 peptides were derived from the mass spectrometric analysis. F Immunoprecipitation analysis of hVICs with C188-9 and BP-1–102 treatment. G, H Binding mode of small molecules and proteins obtained by docking, an overall view and a partial view were both displayed, the blue stick in the picture is the small molecule, the light cyan Cartoon is the protein, the yellow dotted line indicates hydrogen bonding, and the gray dotted line indicates hydrophobicity effect. I The schematic diagram of competitive binding inhibitors

In STAT proteins, SH2 domain interactions are critical for molecular activation and nuclear accumulation of phosphorylated STAT dimers to drive transcription (Araujo et al. 2019). Bp-1-102 (Song et al. 2023) and C188-9 (Kasembeli et al. 2021) were reported as small molecular inhibitors by binding SH2 domain of STAT3, and have been widely used as potential pharmaceutics in cancer and other STAT3-related diseases. The simulated molecular-protein binding patterns were analyzed with AutoDock. As shown in Fig. 6G, BP-1-102 can hydrogen bond with GLN-644 and TYR-640 on the STAT3 protein. In addition, BP-1-102 can also have hydrophobic interactions with TYR-640, THR-641 and GLU-638 on STAT3 protein. For the C188-STAT3 protein complex (Fig. 6H), we can see more abundant interaction forces, such as the hydrogen bonding between the small molecule compound C188 and LYS-658, ILE-653 of STAT3, and hydrophobic interaction with LEU-666, LYS-658, TYR-657, ILE-653, TYR-640, VAL-637. The binding sites were more similar to Sam68-STAT3 complex. This indicated C188-9 was more likely a competitive binding inhibitor than Bp-1-102. A negative number of binding affinity indicates the possibility of binding, and generally, a value less than − 6 kcal/mol is considered to be likely to bind. The docking software gave Bp-1-102, C188-9 and STAT3 protein binding affinity scores were − 6.2, − 6.7 kcal/mol, which means C188-9 binds more effectively to STAT3 protein. Further, the effect of C188-9 blocking the protein–protein binding of Sam68-STAT3 may be better. To confirm this speculation, immunoprecipitation analysis showed that C188-9 blocked Sam68-STAT3-binding more efficiently (Fig. 6F). The schematic diagram was displayed in Fig. 5I.

Discussion

Currently, CAVD is not just considered a passive pathological process related to aging, but an active pathophysiological process affected by multiple factors. The pathogenesis of CAVD may include genes, chronic inflammation, lipid deposition, heterotopic mineralization, et. Inflammatory signaling pathways, such as NF-κB signaling pathway, Janus tyrosine Kinase (JAK)/STAT3, and transforming growth factor-β (TGF-β)/Smad2/3 signaling pathway, are closely related to osteogenic phenotype transformation of hVICs (Coté et al. 2013; Alushi et al. 2020). In this study, results had shown that Sam68 promoted osteogenic differentiation of hVICs associated with CAVD through regulation of STAT3 signaling pathway.

STAT3 was widely studied in cancer territory, and has drawn cardiovascular researchers’ attention for the last decade (Chen et al. 2019; Comità et al. 2021). STAT3 signaling pathway was reported to participate in atherosclerosis (Chen et al. 2019) and vascular calcification (Zhao et al. 2021). In addition, STAT3 has been reported in CAVD (Raddatz et al. 2020). This study found that Sam68 affects valvular osteogenesis through STAT3 signaling pathway in hVICs. Sam68 knockdown has been shown to reduce the cellular inflammatory response in chondrocytes (Xu et al. 2015). Sam68 was reported to be essential for leptin-dependent STAT3 activation (Sanchez-Margalet and Martin-Romero 2001; Martin-Romero and Sanchez-Margalet 2001). In this study, immunoprecipitation experiments were carried out in hVICs and proved Sam68 interacted with STAT3. As we examined that Sam68 could further participate in STAT3 phosphorylation induced by TNF-α. A supplementary experiment of IL-6-activated STAT3 signaling was also verified in this study. To further understand this interaction, simulator of docking analysis was performed, and we believed that Sam68 could interact with SH2 domain of STAT3 which is necessary for molecular activation and phosphorylation. As our result showed we could speculate that Sam68 can participate in STAT3 phosphorylation by interacting with the latter.

Sam68 was proved to participate in the activation of the NF-κB signaling pathway in osteoarthritis (Fu et al. 2016a), colon cancer (Fu et al. 2016b), arterial injury (Han et al. 2019) and other diseases. Studies on Sam68 involving TNF-α activation of the NF-κB signaling pathway (Han et al. 2019; Ramakrishnan and Baltimore 2011) suggested that Sam68 was a necessary factor for TNF-α activation of the downstream signaling pathway. While in this study, the silencing of Sam68 did not significantly affect the TNF-α activated NF-κB signaling pathway. Comparing those experimental processes with this study, the above experiments were mainly carried out in cancer or macrophage cell lines, hVICs have different peculiarity from these kinds of cell. Also, the expression of Sam68 could be completely knocked out in cell lines or primary cells from knocked out mice. While in this study, human primary hVICs were extracted and cultured in vitro, shRNA technology could not be used for monoclonal screening to obtain knocked-out cells, and the efficiency of small interfering RNA technology was limited in knocking out. Therefore, Sam68 effect on the NF-κB signaling pathway may be unaffected when Sam68 was not completely knocked out. Though, It has been long established that there are cross-talks between NF-κB and STAT3 signaling pathway (Grivennikov and Karin 2010). To avoid the interference of TNF-α/TLR/NF-κB signal transduction we further used IL-6 as activator of STAT3 signaling pathway, the effect of Sam68 was similar to TNF-α stimulation (shown in supplementary Fig. 2).

The relationship between Sam68 and autophagy was found in this study and has not been reported before. BCL-2 inhibits autophagy proteins that control the nucleation and elongation of autophagosomes to transform the cellular program from autophagy to apoptosis (Mukhopadhyay et al. 2014). We verified its downstream gene BCL-2, a central adaptor between apoptosis and autophagy, up-regulated when overexpression Sam68 and reversed by silencing Sam68. Activation and phosphorylation of STAT3 can inhibit autophagic flux, and inhibition of autophagy can in turn activate the STAT3 signaling pathway (Liang et al. 2019).The results of this study are consistent with reports that STAT3 inhibits autophagy (Lin et al. 2019, Zhang et al. 2019). In addition, literature has shown that the negative regulation of STAT3 on autophagy involves the transcriptional activation of BCL-2 expression by STAT3 (Feng et al. 2014; Tai et al. 2013). At this point, this study has revealed the same result that Sam68 participates in STAT3 phosphorylation further increases BCL-2 expression and inhibits autophagy. This article indicated the essential role of Sam68 in promoting calcification related to STAT3 signaling pathway and its effect on autophagy. We also pointed out autophagy as an important portion of STAT3 regulating osteogenic differentiation in hVICs. This may provide a new aspect to CAVD pharmaceutical therapy.

As plenty research have revealed the essential role of STAT3 signaling pathway, a substantial amount of inhibitors were presented as potential pharmaceutical therapy for cancer (Zou et al. 2020) and cardiovascular disease. C188-9 and BP-1-102 were mostly reported two competitive binding inhibitors, Using inhibitors for IP analysis, we indirectly improved Sam68 interacted with STAT3. Otherwise, in Fig. 5F, inhibitors also reduced Sam68 protein expression, which indicated Sam68 upregulation maybe rely on STAT3 signaling pathway. And on the other hand, the positive feedback of Sam68 interacts with STAT3 to further promote STAT3 phosphorylation. This accumulation of feedback accelerated osteogenic differentiation of hVICs.

Conclusions

In conclusion, we indicated that Sam68 was upregulated both in CAVD tissue and cell model in vitro, Sam68 was proved to promote osteogenic differentiation of hVICs. Mechanistically, Sam68 interacted with STAT3 SH2 domain to regulate its phosphorylation and further blocked autophagy flux. Therefore, this article pointed out the essential role of autophagy and STAT3 in TNF-α associated CAVD progression. This study also indicates that Sam68 is a potential novel pharmaceutic target for CAVD progression.

Materials and methods

Human aortic valve tissue resource

This study was approved by the Ethics Committee of Huazhong University of Science and Technology and was conducted according to the Declaration of Helsinki of 1964. Referring to the "Guidelines for the Management of Valvular Heart Disease" revised by the European Society of Cardiology and the European Society of Thoracic and Cardiac Surgeons (ESC/EACTS), symptomatic patients with an effective valve orifice area < 1.5 cm2 determined by echocardiography were included (Vahanian et al. 2022). Rheumatic valvular heart disease, infective endocarditis, and congenital bicuspid aortic valve disease were excluded. Normal aortic valve leaflets were harvested from hearts of patients who had heart transplantation due to cardiomyopathy but with normal valve morphology and function as determined by echocardiography. Informed consent was signed before operation. Valve tissues were obtained within 1 h after being removed from patients during surgical procedures. Clinical information was gathered and the aortic valve calcification (AVC) score of calcific patients was measured as reported (Sonderskov et al. 2020). Briefly, calcification was defined as occurring in the leaflet of the valve, the sinus of Valsalva (beginning 6 mm below the coronaries ostium). Coronaries and mitral valve annulus were carefully examined and excluded. All the calcifications were added up calculated for statistics analysis.

Cell culture and treatment

Interstitial cells of human aortic valves were isolated from aortic valve leaflets as previously described (Li et al. 2017). Briefly, valve leaflets were obtained immediately and washed with phosphate buffer solution (PBS) (SH30256.01, HyClone, USA) 5–7 times. Then digested in high glucose Dulbecco’s modified Eagle’s medium (DMEM) (SH30022.01B, HyClone, USA) supplemented with 1.0 mg/mL type I collagenase (BS032B, Biosharp, China). Endothelial cells were removed by vortexing after 30 min digestion at 37 ℃ and continually digested for 8–12 h at 37 °C with repeated vortex to expedite the digestion. Human valve interstitial cells were harvested by centrifuging and were cultured with high glucose DMEM supplemented with 100 units dilution of streptomycin and penicillin (SV30010, HyClone, USA), and 10% fetal bovine serum (SV30010, Gibco, USA) in a humidified atmosphere with 5% CO2 at 37 °C. Human valve interstitial cells were passaged with 0.25% trypsin (25,200–056, Gibco, USA) and were used between passages 3 and 5. To induce osteogenic differentiation of hVICs, DMEM medium supplemented with L-ascorbic acid (0.25 mmol/L), β-glycerophosphate (10 mmol/L), and dexamethasone (10 nmol/L) (all purchased from Sigma-Aldrich, USA) were used as osteogenic medium (OM) as previously described (Wang et al. 2020). Human valve interstitial cells were also incubated in complete medium with or without TNF-α (30 ng/ml, Cat. RTNFAI, Invitrogen, USA) or IL-6 (20 ng/ml, Cat. RIL6I, Invitrogen, USA). Rapamycin (100 nM, Cat. 53,123-88-9, Sigma-Aldrich, USA) was used for activation of autophagy and as a fusion inhibitor of autophagosome and lysosome Bafilomycin (100 nM, Cat. 88,899–55-2, Sigma-Aldrich, USA) was used. STAT3 inhibitor C188-9 (10uM, S8605, Selleck, China) and BP-1-102(500 nM, S7769) were purchased from Selleck.

Quantitative RT-PCR (qRT-PCR) assay

Total RNA was extracted by using an RNA extraction reagent RNAiso plus (Trizol) (T9108, Takara, Japan) and was reversed transcribed to cDNA using Super-Master Reverse Mix (R123-01, Vazyme, China). Quantitative PCR (qPCR) was performed with a reaction volume of 10 μl containing 10 ng of cDNA, 300 nM of each primer, and 5 μl of the qPCR SYBR® green reagent (Q711-00, Vazyme, China) in the StepOne™ quantitative RT-PCR system (Thermo Fishier Scientific, USA). The thermal cycling condition of the qRT-PCR reaction was 95℃ 10 s, 60℃ 30 s for 40 cycles. The results were normalized to the glyceraldehyde-3-phosphate dehydrogenase (GAPDH) gene expression, which was used as a housekeeping gene, using the 2ΔΔCt method. The primers are listed in Table S1.

Western blotting

For Western blotting analysis, hVICs were lysed in RIPA buffer (P0013B, Beyotime, China) and ultrasonic disrupted (Cui et al. 2021). After being added with loading buffer (P0015L, Beyotime, China), The protein extracts were denatured at 95 °C for 5 min. Protein lysate concentrations were determined using BCA Protein Assay Kit (P0010, Beyotime, China) as per instruction. Equal quantities of proteins (30‐50 μg/lane) were loaded in and separated by SDS-PAGE gel. Then the proteins were transferred onto a 0.25 μm PVDF Membrane (Millipore, USA), and then probed with the respective antibodies overnight at 4 °C. The primary antibody used in this study was shown in supporting information (Table S2). On the second day, after washing, membranes were incubated with the corresponding secondary antibodies conjugated with horseradish peroxidase. At last, blots were visualized with chemiluminescence (CLINX, China). The quantification of bands was performed via Image J.

SiRNA transfection

An RNA interference (RNAi) approach was used to knock down gene expression. The small interfering RNA (siRNA) for transient knockdown experiments was purchased from Life USA. Human valve interstitial cells were transfected with either 50 nM Sam68 siRNAs (Cat. 1,299,001 Life USA) or STAT3 siRNA (Cat. AM16708 Life USA) along with a negative control siRNA (SiNC) using lipofectamine 3000 (Invitrogen, USA) as transfecting reagent recommended by the manufacturer’s book.

Adenoviral transduction

Adenovirus-delivered Sam68 overexpression was obtained from Vigene, China. Cells were infected with a negative control or Sam68 overexpressing adenovirus overnight in DMEM high glucose with 2% fetal bovine serum (FBS), and cultured in a fresh complete medium (DMEM high glucose with 10% FBS) for an additional 24 h. The multiplicity of infection (MOI) of adenovirus was 50 pfu number/cell. The protein was extracted and the immunoblots were probed with his-tag antibody to verify successfully overexpression. The empty construct was used as a control for all experiments.

Alizarin Red S assay

Minerals in hVICs were evaluated by using Alizarin red S staining on day 21 of osteogenic induction as previously described (Wang et al. 2019). The hVICs were gently washed with phosphate buffer solution 3 times and then fixed with 4% formalin for 15 min and washed again. With another wash by ddH2O, hVICs were incubated in 0.1% Alizarin Red S staining solution (Cat.332, Siencell, USA) for 30 min. Then remove the staining solution, wash with ddH2O at least 3 times until the background was clean. The stained minerals were captured by the naked eye or the stereomicroscope (Leica DM2500 Germany). The positive area percentage was calculated by the average of 9 pictures taken randomly under a microscope for each duplicate. The experiments were repeated three times.

Immunofluorescence staining

Human valvular interstitial cells or valvular tissue sections were fixed with 4% formalin and permeabilized with phosphate buffered solution (PBS) with 0.2% Triton X-100 (BS084, Biosharp, China). Then samples were incubated with 5% goat serum (G9023, Sigma-Aldrich, USA) diluted in PBS (blocking buffer) at room temperature. Then, hVICs were incubated with primary antibodies dissolved in a 1% bovine serum albumin (BSA) dilution buffer at 4 °C overnight and with an appropriate second antibody for 1 h at room temperature after. For negative controls, samples were incubated with the mouse, or rabbit, or goat IgG (all from Santa Cruz Biotechnology, USA). Cells were counter-stained with 4′,6-diamino-2-phenylindole (DAPI) to show nuclei. Images were viewed and captured using a fluorescence microscope (Zeiss, Germany) with Zeiss Efficient Navigation (ZEN) software. The positive area was quantified by Image J as a percentage of the whole target area.

Autophagy analysis by light chain 3 monitoring

Autophagy analysis was performed as previously reported (Jang et al. 2014). Quantity of autophagosome or autolysosome was counted by the numbers of light chain 3 (LC3) puncta (red fluorescent protein (RFP) positive, green fluorescent protein (GFP) positive LC3 and RFP+/GFP− LC3. Images were randomly taken from each sample, n = 7. Then LC3 yellow puncta and free red puncta (in a merged image) were counted as autophagosomes and autolysosomes respectively, then calculated for average puncta in each cell for further statistical analysis. When autophagosome fused with the lysosome, GFP on LC3 queching because of the acid environment in autolysosome. Hence, the number of autophagosomes was shown as yellow dots and autolysosomes were shown as free red dots. GFP-RFP-LC3 plasmid was obtained from Designgene, China.

Immunoprecipitation analysis

Immunoprecipitation was performed as earlier described (Abboud et al. 2020). Human valvular interstitial cell lysates were precleared using protein A/G Plus-Agarose beads (sc-2003, Santa Cruz Biotechnology, USA). Lysates were incubated and placed on a rotator overnight with Sam68 antibody at 4 ℃. After conjugation, Agarose beads were added again for 1 h additionally on a rotator at 4 °C. Immune complexes were subsequently washed five times and resuspended with RIPA buffer containing protease and phosphatase inhibitors. A nonimmune rabbit IgG (A7016, Beyotime, China) was used for negative control. The immunoprecipitated lysates were subsequently immunoblotted by t-STAT3 antibody (9139S, 1:1000, CST, USA).

Protein/molecule: protein Docking prediction

In this study, we used ZDOCK 3.0.21 to predict the binding mode of Sam68 and STAT3 protein. Before the docking started, we obtained the structure files of these proteins separately from the Uniprot database. Subsequently, they were processed using PyMol2.5.2, including removal of water molecules, removal of hydrogen atoms, and non-target structural proteins. When docking, the default configuration of ZDOCK 3.0.2 is used for docking research, and global rigid docking is performed. After docking, AMBER18 was used for energy minimization under the ff14SB force field. Finally, the energy-minimized protein complex conformation was visualized using PyMOL 2.52, including the analysis of hydrogen bonding and salt bridge interactions.

The crystal structure of the STAT3 protein used for docking was downloaded from the PDB database. The PDB ID is 6NJS. The 3D structures of small molecules STAT3 inhibitor BP-1-102 and C188-9 were constructed and obtained by Chem3D v20, and the energy was minimized under the MMFF94 force field. AutoDock Vina 1.1.2 software 3 was used for molecular docking work. Before docking, PyMol 2.52 was used to process the receptor protein, including the removal of water molecules, salt ions and small molecules. The docking box is then set up to wrap the entire protein structure. In addition, ADFRsuite 1.04 was used to convert all processed small molecules and receptor proteins into PDBQT format required for docking with AutoDock Vina 1.1.2. When docking, the exhaustiveness of the global search is set to 32, and the rest of the parameters remain the default settings. The highest-scoring docked conformation of the output was considered as the binding conformation and finally visualized using PyMol 2.5 docking results.

Statistical analysis

Statistical analyses were performed using Prism version 9.0 (GraphPad Software). All data were presented as the mean ± standard error of the mean (SEM). The difference between two groups was tested for significance using an independent T-Test. Overall differences between groups were tested for significance via one-way analysis of variance (ANOVA). When analysis of variance demonstrated a significant effect, post hoc analysis was performed using the Tukey test. Pearson correlation analysis was used. A value of p < 0.05 was considered statistically significant.

Supplementary Information

Below is the link to the electronic supplementary material.

Supplementary file1 (DOCX 538 KB) (538.3KB, docx)

Acknowledgements

We acknowledge the technical support given by Dr. Kang Xu and Dr. Jiangyang Chi.

Author contributions

XL; QZ and JS performed study concept and design; KW; ZW. JL and HL Performed development of methodology; XL; QZ; HL and JS performed writing, review and revision of the paper; KW; XL; QZ; ZL provided acquisition, analysis and interpretation of data, and statistical analysis; ND provided technical and material support. All authors read and approved the final paper.

Funding

This research was funded by the National Natural Science Foundation of China, the grant number 81770387.

Declarations

Conflicts of interest

The authors declare no conflict of interest.

Ethical approval

The study was conducted in accordance with the Declaration of Helsinki, and approved by Ethics Committee of Huazhong University of Science and technology (S036).

Footnotes

Publisher's Note

Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Xing Liu and Qiang Zheng contributed equally to this work.

Contributor Information

Xing Liu, Email: stan331@foxmail.com.

Qiang Zheng, Email: ycdfq521@163.com.

Kan Wang, Email: kanwang_tj@126.com.

Jinjing Luo, Email: luojingjing677@foxmail.com.

Zhijie Wang, Email: wang_zhijie225@163.com.

Huadong Li, Email: lihuadong@hust.edu.cn.

Zongtao Liu, Email: 501308843@qq.com.

Nianguo Dong, Email: dongnianguo@hotmail.com.

Jiawei Shi, Email: shijiawei@hotmail.com.

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