{"paper_id":"3bbf583c-a433-4972-aad9-94f180dde106","body_text":"Splicing Factor 3b Subunit 4 (SF3B4) Promotes Proliferation of Gastric Cancer through Regulation of VDAC1 | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Article Splicing Factor 3b Subunit 4 (SF3B4) Promotes Proliferation of Gastric Cancer through Regulation of VDAC1 Dehong Li, Yan Lu, Li Yan, Xingwen Yang, Fenghui Zhao, Xiaoyan Yang, and 3 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-4495852/v1 This work is licensed under a CC BY 4.0 License Status: Posted Version 1 posted You are reading this latest preprint version Abstract SF3B4 is a novel tumor related gene which is aberrantly expression in some malignant tumors. However, the role and mechanisms of SF3B4 in gastric cancer have not been explored. In this study, TMT-based quantitative proteomics and high content screening (HCS) revealed SF3B4 was strongly associated with GC. Immunohistochemistry revealed SF3B4 was upregulated in human gastric cancer tissues, and high SF3B4 expression was associated with shortened progression-free survival of patients. Further investigations indicated that the knockdown of SF3B4 could inhibit the proliferation and colony formation of GC cells while promoting cell apoptosis. Furthermore, knocking down SF3B4 could also inhibit the tumorigenicity of GC cells in vivo. RNA-sequencing followed by IPA was used to explore downstream of SF3B4 and identified VDAC1 as the potential target. Moreover, our study revealed that VDAC1 overexpression could alleviate the SF3B4 knockdown-induced inhibition of GC. Remarkably, we found for the first time that SF3B4 potentially facilitates the development of gastric cancer by exerting VDAC1-mediated effects on autophagy. SF3B4 promotes GC cell proliferation through regulate VDAC1 and may be a novel therapeutic target for GC. Health sciences/Diseases/Cancer/Gastrointestinal cancer/Gastric cancer Health sciences/Oncology/Cancer/Gastrointestinal cancer/Gastric cancer splicing factor 3B subunit 4 voltage-dependent anion channel 1 gastric cancer proliferation autophagy Figures Figure 1 Figure 2 Figure 3 Figure 4 Figure 5 1. Introduction Gastric cancer (GC) is the fifth most common malignancy and the third leading contributor to cancer-related mortality worldwide[ 1 ].GC is a multifactorial disease involving numerous complex genetic factors and mechanisms[ 2 ].As a result, a better understanding of the molecular mechanisms behind this disease could lead to the identification of new therapeutic targets. We screened for proteins with abnormal overexpression in GC using five gastric cancer tissues and adjacent normal tissues with tandem mass tag (TMT)-based proteomics. We confirmed the function of the identified genes by high-content shRNA screening. Using this method, we discovered that SF3B4, one subunit of the splicing factor 3b (SF3b) complex, may be essential to GC proliferation. The spliceosome, a large ribonucleoprotein complex, is responsible for precisely removing introns from pre-messenger RNA and producing multiple transcripts from a shared precursor. This process is commonly referred to as alternative splicing[ 3 , 4 ]. The spliceosome is a dynamic complex that contains five small nuclear ribonucleoproteins (snRNPs) (U1, U2, U4/U6, U5), seven Sm proteins, and a significant number of associated protein[ 5 , 6 ]. The U2 snRNP consists of two major protein complexes, SF3a (splicing factor 3a) and SF3b (splicing factor 3b)[ 7 ]. All known SF3a and SF3b subunits, except for SF3b130, can be cross-linked to the pre-mRNA near the branch site[ 8 ] and play essential roles during pre-spliceosome assembly[ 9 ]. SF3B4, as a major constituent of the SF3b complex, tethers the pre-mRNA upstream of the branch point sequence and plays an important role in binding the U2 snRNP to the branch site in the splicing processes[ 10 , 11 ].Growing evidence suggests that dysfunction of SF3B4 plays a critical role in the carcinogenesis and progression of human cancers[ 12 – 14 ]. Overexpressing SF3B4 can promote tumorigenesis in hepatocellular carcinoma (HCC)[ 15 ]. Also, SF3B4 is considered as a cancer-promoting factor of the esophageal squamous cell carcinoma[ 13 ]. Nevertheless, asa splicing factor, the biological function and detailed molecula rmechanism of SF3B4 in GC are still unclear. In this study, we demonstrate that SF3B4 promotes GC proliferation via the VDAC1.This result provides new insight into the molecular mechanisms of gastric carcinogenesis and suggesting that SF3B4 may serve as a target for the treatment of GC. 2. Results 2.1. Identification of SF3B4 as a critical gene that promotes GC proliferation We used Tandem Mass Tag analysis to identify genes with a critical role in GC tumor genesis to compare the protein expression profiles of five pairs of matched GC and adjacent normal tissue samples(CON). The results identified 6653 proteins were confirmed, 1008 differential proteins ultimately exhibited significantly different expressions between the groups according to the criteria of P value < 0.05 and fold changes > 1.20(Fig. 1 a). Among these, 649 proteins were upregulated, and 359 were downregulated in the GC group compared to the CON group. Next, 26 differential expression genes were selected as the candidate genes potentially play an essential role in the proliferation of GC on thebasisof a functional analysis (Table S2). All 26 candidate genes were then knocked down in AGS cells toassess the potential effect on potential effects on in vitro proliferation of GC cells (Fig. 1 b). Knockdown of three candidate genes, SF3B4, WDR12, and RFTN1, in AGS cells reduced the cell proliferation rate. SF3B4 knockdown showed the greatest effect on reducing the proliferation rate, cell count/fold on the fifth day in shCtrl group was 8.64, while the cell count/fold in shSF3B4 groups was only1.72(Fig. 1 c). therefore, we focused on SF3B4 in our subsequent studies. 2.2. SF3B4 was highly expressed in gastric cancer tissue and several cell lines and was associated with poor prognosis in patients To investigate whether SF3B4 was expressed in human gastric cancer cells, the expression of SF3B4 protein in human adjacent normal tissue and gastric cancer tissue was analyzed by immunohistochemistry. As shown in Fig. 2 a and statistical analysis in Table 1 , a higher level of SF3B4 expression is found in GC tissues than in normal tissues. Furthermore, the same result was obtained from the TCGA dataset, 33 original data of TCGA RNA-seq samples were presented in a line chart and the form of histogram(Fig. 2 b and 2 d). Comparing with the adjacent normal tissue, SF3B4 expression in Stomach adenocarcinoma (STAD) was significantly upregulated( P value is 1.71E-05). Kaplan–Meier analysis revealed patients with high levels of SF3B4 displayed a remarkably shorter progression-free survival time than those in the SF3B4-low group (Fig. 2 c). We also evaluated SF3B4 mRNA expression level in GC cell lines by qRT-PCR (Fig. 2 e). The value was represented with ∆Ct(SF3B4-GAPDH). SF3B4 mRNA expression was significantly increased among AGS, HGC-27, KATO III, NCI-N87and MKN-45cell lines. Table 1 Expression patterns in GC tissues and adjacent normal gastric tissues revealed in immunohistochemistry analysis SF3B4 expression Tumor tissues Adjacent normal gastric tissues p -value Cases Percentage Cases Percentage Low 20 52.6 38 100% 0.000*** High 18 47.4 0 - Meanwhile, to explore the relationship between SF3B4 expression and clinicopathological features, we stratified patients according to different clinicopathological parameters and compared the expression of SF3B4. As shown in Table 2 , under TNM stage, the percentage of low SF3B4 expression in “I- II” group was 80%, in “III- IV” group was 42.9%; while the percentage of high SF3B4 expression in “I- II” group was 20%, in “III- IV” group was 57.1%(8/23). After Pearson Chi-square test, the P value for these groups percentage was 0.043, which means III-IV stage had more percentages of high SF3B4 expression. However, differential SF3B4 expression was not observed in groups under Sex, Age, Histologic differentiation as well as Lymphovascularin vasion. Table 2 Clinical characteristics of gastric cancer patients and SF3B4 expression Feature No. of patients SF3B4 Expression p value Low High N % N % N % All patients 38 20 52.6 18 47.4 Gender 0.184 Female 9 23.7 3 33.3 6 66.7 Male 29 76.3 17 58.6 12 41.4 Age (years) 0.453 ≤ 50 6 15.8 4 66.7 2 33.3 >50 32 84.2 16 50 16 50 TNM stage 0.043* I- II 10 26.3 8 80 2 20 III- IV 28 73.7 12 42.9 16 57.1 Histologic differentiation 0.732 Well or moderate 18 44.7 10 55.6 8 44.6 Poor 20 55.3 10 50 10 50 lymphovascular invasion 0.087 Negative 3 7.9 3 100 0 0 Positive 35 92.1 17 48.6 18 51.4 2.3. SF3B4 knockdown suppressed cancer cell proliferation and increased apoptosis rate in vitro To determine the biological functions of SF3B4 in GC, Stable SF3B4 knockdowns were established in the AGS and MKN-45 cell linesusing a lentiviral delivery system. The downregulation of SF3B4 has been confirmed through mRNA and protein in this cell line (Fig. 3 a). SF3B4 mRNA expression were significantly decreased after lentivirus infection in AGS and MKN45cells compared with control group (P < 0.05), and the knockdown efficiency reached 80.0% and 89.1% in AGS cells and MKN45 cells reached separately. SF3B4 knockdown suppressed GC cell proliferation, as measured via the CCK-8 assay, colony formation assay, and 5-ethynyl-20- deoxyuridine(BrdU) assay. The OD450 value in the CCK-8 assay demonstrated that SF3B4 knockdown could inhibit proliferation in AGS and MKN45 cells comparing with the control group (Fig. 3 b). The ratio of OD450(OD450/fold) was also calculated. The value of OD450/fold of the control group on the fifth day in AGS cells increased by 7.9842 times, while the value of OD450/fold ofthe shSF3B4 group increased by only 3.8244 times which were significantly decreased(Fig S1 a). Similar results could be seen in MKN45 cells (Fig S1 b).The colony formation assay also produced similar results. The number of clone was obviously decreased after knocking down SF3B4 compared with the control group(Fig. 3 c). Results of BrdU assays further confirmed that SF3B4 knockdown significantly inhibited the cells proliferation rates(Fig. 3 d). To provide additional evidence for the impact of SF3B4 suppression on gastric cancer cell apoptosis, we employed Annexin V-APC staining and subsequent flow cytometry analysis (Fig. 3 e). There was a significant increase in apoptosis rate in shSF3B4 treated AGS cells compared to those in the control group (10.57%±0.54% vs. 2.44%±0.16%) (P < 0.01). Similar results were also obtained in shSF3B4-treated MKN45 cells. These results suggest that the knockdown of SF3B4 expression can inhibit GC cell proliferation in vitro. 2.4. SF3B4 knockdown inhibited tumorigenicity of human gastric cancer cells in vivo To investigate the potential involvement of SF3B4 in gastric cancer cell proliferation in vivo, we established xenograft models in mice through subcutaneous injection of MKN-45 cells, with or without SF3B4 knockdown. Figure 3 f demonstrated the significantly suppressed tumor growth of GC in mice of the shSF3B4 group compared with that of shCtrl group. Tumor volume and growth rates in the shSF3B4-MKN-45 injected group were significantly lower than in the shCtrl group (Fig. 3 h). The fluorescence intensity was also detected on day 19. The fluorescence intensity of shSF3B4-MKN-45 cells was significantly less than the control group (Fig. 3 g). In addition, tumor weights were determined for the two groups, and the weights of the shCtrl group had a dramatically higher weight than the shSF3B4 group(Fig. 3 i). These results suggested that knockdown of SF3B4 expression could inhibit the tumorigenicity of human gastric cancer cells in vivo. 2.5 The exploration of the downstream mechanism underlying the regulation of GC by SF3B4 The transcriptome-wide investigation was performed using RNA sequencing to better unravel the downstream mechanism behind the suppression of GC by SF3B4 knockdown. We identified 105 differentially expressed genes between shCtrl and shSF3B4-transfected cells were, including 64 upregulated and 41 downregulated genes. Subsequently, we performed Ingenuity Pathway Analysis (IPA) to identify the enrichment of genes induced by SF3B4 knockdown. The Necroptosis Signaling Pathway, Senescence Pathway, Migration of tumor cells and Autophagy were inhibited by SF3B4 knockdown, meanwhile, Mitosis and Cell cycle progression were activated(Fig. 4 a). The genes that were significantly enriched in inhibited pathways were further analyzed(Fig. 4 b). Real-time PCR was performed to detect the expression of mRNA of 8 Genes which areinvolved in multiple inhibited pathways, and the results showed that the 8 genes were downregulated after the SF3B4 knockdown (Fig. 4 c). The 4 most significantly downregulated candidates, including FOXO3, VDAC1, DNAJA3, and DRAM2, were then selected for WB verification in AGS cells (Fig. 4 d). VDAC1 was significantly reduced in SF3B4 knockdown group compared to control. Furthermore, the expression profiling data collected from TCGA datasets revealed that VDAC1 mRNA expression was upregulated in GC tissues comparison with normal tissues (Fig. 4 e). 2.6. Overexpression of VDAC1 alleviated the inhibition effect of SF3B4 knockdown on GC In order to verify that SF3B4 executes its regulation effects on GC through VDAC1, functional recovery study were performed to verify their synergistic effects on the functions of GC cells. First, gastric cancer cells AGS were infected with shSF3B4 lentivirus to knockdown SF3B4 (KD), then infected with VDAC1 overexpression lentivirus tomake them overexpression (OE), The efficiencies of transfection were evaluated by fluorescence imaging(Fig. 5 a). Marked downregulation and upregulation of SF3B4 and VDAC1 in KD + NC and KD + OE groups, respectively, were confirmed at both the mRNA and protein levels compared with the NC + NCgroup(Fig. 5 b and Fig. 5 c). we did CCK-8 assay to study the recovery function of over expression of VDAC1 to AGS cells. Compared with NC + NC group (the OD450 value at the fifth day was 1.642), the cell viability of KD + NC group decreased (the OD450 value at the fifth day was 0.620, P < 0.05), which was consistent with the previous results. However, compared with KD + NC group, the cell viability of KD + OE group increased (the OD450 value at the fifth day was 1.287, P < 0.05), indicating that VDAC1 gene overexpression restored the proliferation function of SF3B4 knockdown(Fig. 5 d). Moreover, colony formation data revealed that, compared with NC + NC group, the cloning ability of KD + NC group decreased significantly, which was consistent with the previous results (P < 0.05); However, compared with KD + NC group, after over expression VDAC1, in KD + OE groups, the clone number significantly increased, so the cloning ability of AGC cells was recovered (P < 0.05)(Fig. 5 e). Finally, to clarify the detailed mechanism of recovery of cellular function by VDAC1 in gastric cancer cell lines, we did western blot to show expression of autophagy-related genes (ATG7, ATG5, ATG9A, ATG12) when knocking down SF3B4 (KD) and overexpression VDAC1(OE). As shown in Fig. 5 f, compared with NC + NC group, the expression of ATG7, ATG5, ATG9A, ATG12 increased in KD + NC group, However, when overexpression VDAC1, the expression of ATG7, ATG5, ATG9A, ATG12 were significantly decreased, which demonstrated overexpression VDAC1 also recoverythe expression levels of ATG5, ATG7, ATG9A and ATG12 in SF3B4 knockdown. These results suggest a potential regulatory role of SF3B4 in VDAC1-mediated dysregulated autophagy, thereby promoting tumorigenesis of gastric cancer. 3. Discussion This study screened the candidate gene SF3B4 by high-throughput Tandem Mass Tag analysis (TMT) and High-content screening. Then, IHC analysis of 38 GC tissues and adjacent normal tissues confirmed the upregulation of SF3B4 in GC. The expression profiling data collected from TCGA datasets also supported the comparatively high expression of SF3B4 in GC. By constructing SF3B4 knockdown cell models based on AGS and MKN-45 cell lines, we investigated the in vitro effects of endogenic SF3B4 on GC development and progression. Keeping with the potential tumor promotion effect of SF3B4 indicated by the tissue detection, the knockdown of SF3B4 inhibited the cell and colony growth and promoted cell apoptosis. Moreover, the suppression of GC tumor growth by SF3B4 knockdown was further demonstrated by the mice xenograft model in vivo.These results indicated that SF3B4 plays a critical role in gastric cancer initiation and deserve further study. SF3B4 was originally reported to be a core subunit of the metazoan SF3b complex, which is integral to U2-type spliceosomes[ 16 , 17 ]. In humans, SF3B4 interacts with another spliceosome component SF3b145, forming a protein complex which binds U2 snRNP to pre-mRNA branch sites[ 18 , 19 ]. Meanwhile, It also participates in transcription, translation, and cellular signaling pathways[ 20 , 21 ].Moreover, SF3B4 regulates cell differentiation, cell cycle, and immune deficiency[ 22 – 24 ]. In 2012, Bernier et al. reported that heterozygosity for a mutation in the SF3B4-gene (1q21.2) caused Nagersyndrome(NS)[ 17 ]. Later studies found SF3B4 encodes a spliceosome-associated protein (SAP49), a component of a spliceosomal complex is thought tobe involved in thes plicingof genes associated with limb and craniofacial development[ 25 , 26 ]. In 2015, Xu et al. conducteda meta-analysis of publicly available microarray Gene Expression Omnibus datasets about hepatocellular carcinoma (HCC), and the finding revealed that SF3B4 was generally overexpressed in HCC[ 27 ]. Subsequently, T. Iguchi and colleagues verified that SF3B4 expression was significantly higher in cancer tissues than noncancer tissues and positively correlated with SF3B4 DNA copy number in 2016[ 28 ].Mounting evidence indicates that the loss- or gain of function mutation in SF3B4 may contribute to the pathogenesis of various tumors, including liver cancer, pancreatic cancer, esophageal squamous cell carcinoma, and so on [ 29 – 31 ]. However, the role of SF3B4 in regulating the behavior of gastric cancer has not yet been elucidated. Our study examined the involvement of SF3B4 in gastric cancer and demonstrated, for the first time, that SF3B4 is also upregulated in gastric cancer, knocking down SF3B4 could inhibit cellgrowth both in vitro and in vivo, also could induced the apoptosis. An encouraging finding from this study is thatweshowed for the first time that VDAC1 might be a downstream factor of SF3B4. We used Ingenuity Pathway Analysis (IPA) to find the main downstream regulators affected by SF3B4. The result revealed VDAC1 is a protein that plays a crucial role in autophagy and necroptosis signaling pathways, further experimental confirmed that VDAC1exhibited a notable reduction at both the mRNA and protein levels in the shSF3B4 group. Moreover, the data analysis obtained from TCGA and recovery study comfirmed VDAC1 as a potential downstream regulator of SF3B4. VDAC1 is an isoform of Voltage-dependent anion-selective channel protein, which regulates energy production, mitochondrial oxidase stress, calcium transport, substance metabolism, apoptosis, and autophagy[ 32 – 35 ]. VDAC1 was found to be abnormally expressed and participate in tumorigenesis or progression in various ways[ 36 , 37 ]. For example, the study of S.K. Pandey et al. showed VDAC1 was overexpressed in mesothelioma patients, and silencing VDAC1 expression caused metabolism reprogramming to inhibit tumor growth[ 38 ]. Research on breast cancer demonstrated VDAC1 and Sarco/Endoplasmic Reticulum ATPase3 (SERCA3) mediate progesterone-triggered Ca2 + signaling to modulate cell proliferation and cell death[ 39 ]. Moreover, VDAC1 was also reported to be implicated in GC. The work of W. Gao et al. suggested VDAC1 increased in mitochondria of GC tissues than in normal adjacent tissues, and VDAC1 was a promising candidate for future biomarker development for gastric cancer[ 40 ]. In this study, the inhibition effect of VDAC1 knockdown on GC, similar to SF3B4, was also demonstrated by detecting cell proliferation and colony formation. More importantly, the inhibition of GC by knockdown of SF3B4 could be impaired to some extent by simultaneous overexpressof VDAC1, suggesting that SF3B4 may regulate the development and progression of GC through influencing VDAC1. In addition, this study also found that SF3B4 regulating VDAC1 leading to gastric carcinogenesis may be related to autophagy dysregulation(Fig S2). In summary, the experimental data in this study indicated that SF3B4 was upregulated in GC tissues. In vitro and in vivo detection demonstrated that SF3B4 acts as a tumor promoter in GC, probably through the regulation of VDAC1. To the best of our knowledge, this is the initial study addressing the contribution of SF3B4 to the advancement and progression of GC. However, further investigation is necessary to elucidate how SF3B4 and VDAC1 interact to promote the proliferation of gastric cancer cells. 4. Materials and Methods 4.1. Clinical samples GC and adjacent normal tissues were collected from patients with GC who had undergone surgical resection at the Department of Surgery, Gansu provincial Hospital (Gansu, China). H&E staining confirmed the histopathology features of clinical samples. This study has been performed in accordance with Declaration of Helsinki. Ethical approval for the study was granted on 9th March, 2021 by he Medical Ethics Committee of the Gansu Provincial Hospital (No. 2021-079) and informed consent was obtained from the patients. 4.2. TMT proteomics analysis To perform the differential proteomic experiments, five GC tissue samples and matching adjacent normal tissues were obtained for the TMT-labeled quantitative proteomics analysis. After protein extraction and digestion using SDT lysis and FASP method and the quality control of the protein samples, the samples were labeled with TMT in accordance with the manufacturer's protocol(TMT10plex label reagent set, ThermoScientific, Waltham, MA, America). The proteomics analysis was performed using a Qexactiveplus mass spectrometer (Thermo, USA) by Genechem (Shanghai, China). The original map files (.raw files) generated by Q Exactivepluswere converted into mgf files by Proteome Discoverer 2.1 (Thermo Fisher Scientific, USA) and submitted to the MASCOT2.6 server for database retrieval through the software's built-in tools. In this study, we used Uniprot_HomoSapiens_20386_20180905 for our database search. The reliable protein screening criterion was peptide FDR ≤ 0.01. Student's t-test was performed to identify the significant difference in proteins in the two groups. A P -value < 0.05 and fold change > 1.2 were considered significant. 4.3. Cell lines and culture The human gastric cancer cell lines AGS, HGC-27, KATO III, NCL-N87 and MKN-45 were purchased from Shanghai Genechem Co., LTD.ATCC previously authenticated the three cell lines viaShort Tandem Repeat (STR) typing. All cells were grown in a complete medium. Cell cultures were maintained at 37°C in a 5% CO2 incubator. In vitro assays were performed at 70–80% cell density. 4.4. Plasmids and shRNA The GV344 lentiviral vector system, pHelper 1.0 vector, pHelper 2.0 vector, and 293T cells were used to produce lentiviruses. Human SF3B4-targeting shRNA (targeting sequence: 5’-CCCTGAGATTGATGAGAAGTT-3') and control insert sequence (5’-TTCTCCGAACGTGTCACGT-3') were designed and cloned into lentiviral vector GV344. Transfection was performed in AGSand MKN-45 cells (3–5×10 4 /mL). shRNAs were designed and synthesized by Genechem (Shanghai, China). Moreover, the full length of VDAC1 was cloned into lentivirus vector pGC-FU-CMV-3FLAG-EF1-mCherry-T2A-puromycin (GV661) (Shanghai Genechem Co., LTD) for constructing VDAC1 over-expressed cells. 4.5. High-content screening and cell growth curve analysis. AGS cells were transfected with ashSF3B4 or shCtrl lentivirus seeded into 96-well plates. The expression of green fluorescent protein (GFP) was observed using a fluorescence microscope. Cells were collected for further experiments when they reached 80% confluence. Cellimages were captured using a Celigo image cytometer (NexcelomBioscience, Lawrence, MA, USA) once a day for 5 days. By adjusting the input parameters, cells (2000 cells per well) could be quantified by measuring the green fluorescence signal in each well. The number of cells at each time point was compared with the cell count on day 1 to obtain a cell proliferation ratio at the corresponding time point for each experimental group, the growth curve was plotted, and the fold change in proliferation was calculated. The cell proliferation ratio was calculated as follows: fold change (shCtrl vs. experimental group) = proliferation ratio on day 5 for the shCtrl group/proliferation ratio on day 5 for the experimental group. A fold-change value equal to or more than two indicated that cell proliferation had slowed down sufficiently. 4.6. Quantitative RT-PCR Total RNA was isolated from each sample using Trizol(Shanghai Pufei Biotech Co., Ltd, China) according to the manufacturer's protocols. The concentration and purity of the total RNA were estimated using NanoDrop 2000 (ThermoFisher, USA). cDNA was synthesized using the Promega M-MLV Reagent kit (Promega Beijing, China), following the manufacturer's instructions. Quantitative RT-PCR was performed using LightCycler® 480 II (Roche, Switzerland) according to the manufacturer's instructions, using GAPDH or β-Actin was as endogenous controls for mRNAs. Primers used for qRT-PCR are listed in Table S1 . 4.7. Cell proliferation assays Transfected AGS and MKN45 cells were incubated in 96-well plates for 24, 48, 72, 96, and 120h, and Cell Counting Kit-8 (Dojindo Laboratories, Japan) was applied to evaluate the ability of cell proliferation. Colony formation assays were performed to detect AGS and MKN45 cell cloning Capability after transfected with shSF3B4 or shCtrl. The transfected cells were seeded into a 6-well cell culture plate in 1x10 3 /well. After 8 days of culture, the cells were stained by crystal violet solution (Sangon Biotech, China), and Colonies were graphed with a digital camera and counted. BrdU assays were performed using a BrdU cell proliferation assay kit (Roche) according to the manufacturer's protocol to assess cell proliferation after cell transfection. 4.8. Apoptosis assay In transfected AGS and MKN45 cells grown to 80% confluence, the suspension cells were collected, and adherent cells on the dish were digested by trypsin into single cells. We collected all cells for apoptosis detection using Annexin V-APC apoptosis detection kit (eBioscience, USA) and flow cytometry analysis (BD, USA). 4.9. Western blot analysis A RIPA lysis buffer (Beyotime Institute of Biotechnology) containing protease inhibitors was used for lysing cells on ice as directed by the manufacturer. Detecting protein concentrations was performed with a BCA Protein Assay kit (Beyotime Institute of Biotechnology). The total cellular proteins were isolated using SDS-PAGE (10%) and then transferred to PVDF membranes. The membranes were blocked with TBST solution containing 5% non-fat milk for 60 min at room temperature and then incubated with primaryantibodies, including Anti-SF3B4 (1:500), anti-FOXO3(1:1000), anti-VDAC1(1:1000), anti-DNAJA3(1:500), anti-DRAM2 (1:500),anti- ATG7 (1:10000), anti-ATG5 (1:3000), anti- ATG9A (1:1000) and anti- ATG12 (1:1000)at4°C overnight. After washing, the membranes were incubated with secondary antibodies. All blots were developed with 20X LumiGLO® Reagent and 20x peroxide (#7003, Cell Signaling Technology, Inc). Visualized images were obtained using a Tanon4600 detector (Shanghai, China). 4.10. Immunohistochemistry (IHC) We obtained 38 pairs of gastric cancer and adjacent normal tissue specimens from surgical resections performed at the Gansu provincial hospital between May 2018 and May 2020. The Medical Ethics Committee of the Gansu provincial Hospital approved this study. The sections were deparaffinized, heat-mediated antigen repair was performed using citrate buffer, blocked by peroxidase blocking solution (maxim, Biotechnology, Fuzhou, China) for 10 min at room temperature, and treated by normal non-immunized animal serum according to the manufacturer's protocol. Next, the staining of the tissue sections by diluted primary anti-SF3B4 or anti-VDAC1 was performed at 4°C overnight. Slides were washed with PBS and incubated with biotinylated secondary antibody (maxim, Biotechnology, Fuzhou, China) per the manufacturer's instructions for 1h.Tissue sections were washed, stained with 3, 3-diaminobenzidine (DAB), counterstained with hematoxylin, dehydrated with ethanol, and mounted with resin. Images were captured using NanoZoomer 2.0-HT (Hamamatsu, Japan). The SF3B4 expression levels in each spot were assessed by the immunoreactive scores (IRS), which were calculated by multiplying the score of intensity and the extent score. Each staining intensity was scored with a score of 0–3 (0 = negative;1 = weak; 2 = moderate; 3 = strong). The extent of positively stained cells was also scored into 5 categories: 0(0%), 1 (1–25%), 2 (26–50%), 3 (51–75%), and 4 (76–100%). Using the IRS, staining patterns were classified as low (IRS: 0–6) and high (IRS: 8–12). 4.11. In vivo tumorigenicity assays 4–6-weeks female nude BALB/c mice were purchased from Shanghai Lingchang Biological Technology Co., Ltd. MKN-45 cells were transfected with shSF3B4 and shCtrl, respectively. Transfected MKN45 cells (4×10 6 ) were subcutaneously injected into the right underarm of each mouse (n = 12). The mice were cultured for 19 days post-injection, and data collection began 7 days post-injection. A measurement of thevolume (V) was made with calipers by measuring the length (L) and width (W) and calculating the volume using the formula V (mm3) =π/6×L×W×W. The volume of tumors was estimated at 7, 10, 14, 17, and 19 days post-injection. Moreover, nineteen days after cell injection, a dose of 10µL/g of D-luciferin (15 mg/mL, Qcbio, China) was injected and live images were acquired using an in vivo imaging system(Perkin Elmer, America). In the end, mice were sacrificed with pentobarbital sodium injections and their tumors were removed for taking photos and weighting. The animal experiments were complied with the ARRIVE guidelines and the Medical Ethics Committee of the Gansu provincial Hospital approved this study. 4.12. RNA-Seq Analysis The RNA-sequencing analysis was performed by Genechem (Shanghai, China). Briefly, total RNA was isolated from shSF3B4 and shCtrl-transfected AGS cells using Trizol (Shanghai Pufei Biotech Co., Ltd, China)following the manufacturer's instructions. Purity of RNA was determined by the NanoPhotometer® spectrophotometer (IMPLEN, CA, USA), and integrity was assessed by the RNA Nano 6000 Assay Kit (Agilent Technologies, CA, USA). Sequencing libraries were constructed using NEBNext®UltraTMRNA Library Prep Kit for Illumina® (NEB, USA) according to the manufacturer's instructions, and index codes were added to attribute sequences to each sequencing sample. The clustering of the index-coded samples was performed on a cBotCluster Generation System using TruSeq PE Cluster Kit v3-cBot-HS (Illumia) according to the manufacturer's instructions. A 150 bp paired-end read was generated from the library preparations after cluster generation using an IlluminaNovaseq platform. Differential expression analysis of two groups was performed using the DESeq2 R package (1.16.1), Genes with an adjusted p -value < 0.05 found by DESeq2 were assigned as differentially expressed genes (DEGs). IPA (Qiagen, Hilden, Germany) was performed using all the DEGs to analyze the enriched functional annotations. 4.13. Statistical analysis Results for continuous variables are presented as means ± sd unless otherwise stated. Student's t-Test and Chi-square test were used during the data analysis. The 2 −ΔΔCt method was used during the qPCR assays. SPSS 19.0 was used for statistics, and p < 0.05 was considered significant. GraphPad Prism 6.04 was used to generate graphs. Declarations Acknowledgments Not applicable Funding This work was funded by the science and technology project of Chengguan District, Lanzhou City. (Grant No.2021SHFZ0002)and the Scientific Research Cultivation Project of Gansu Provincial Hospital (Grant No. 19SYPYB-25). Author contributions KehuYang, Dehong Li and Yan Lu carried out the studies, participated in collecting data, and drafted the manuscript. Li Yan, XingwenYang, Fenghui Zhao and XiaoyanYang performed the statistical analysis and participated in its design. XiumeiYuan and Fugui Lin participated in acquisition, analysis, or interpretation of data and draft the manuscript. All authors read and approved the final manuscript. Conflict of Interest The author(s) declare(s) that there is no conflict of interest regarding the publication of this paper Data availability All data generated or analysed during this study are included in this published article [and its supplementary information files]. References Bray,F,et al. Global cancer statistics 2018: GLOBOCAN estimates of incidence and mortality worldwide for 36 cancers in 185 countries. CA Cancer J Clin. 68,394–424(2018). Yang L, et al. Gastric cancer: Epidemiology, risk factors and prevention strategies. Chin J Cancer Res. 32,695–704(2020). Jiang W, Chen L. Alternative splicing: Human disease and quantitative analysis from high-throughput sequencing. Comput Struct Biotechnol J. 19,183 – 95(2021). Ule J, Blencowe BJ. Alternative Splicing Regulatory Networks: Functions, Mechanisms, and Evolution. Mol Cell.76,329 – 45(2019). Lee Y, Rio DC. Mechanisms and Regulation of Alternative Pre-mRNA Splicing. Annu Rev Biochem.84,291–323(2015). Yamada T, et al. Heterozygous mutation of the splicing factor Sf3b4 affects development of the axial skeleton and forebrain in mouse. Dev Dyn.;249,622 – 35(2020). Brosi R, Hauri HP, Krämer A. Separation of splicing factor SF3 into two components and purification of SF3a activity. J Biol Chem.268:17640–6(1993). Will CL, et al. Characterization of novel SF3b and 17S U2 snRNP proteins, including a human Prp5p homologue and an SF3b DEAD-box protein. EMBO J.21,4978–88(2002). Will CL, Lührmann R. Protein functions in pre-mRNA splicing. Curr Opin Cell Biol.9,320–8(1997). Matera AG, Wang Z. A day in the life of the spliceosome. Nat Rev Mol Cell Biol .15,108 – 21(2014). Ueno T, et al.Component of splicing factor SF3b plays a key role in translational control of polyribosomes on the endoplasmic reticulum. Proc Natl Acad Sci U S A.116,9340–9(2019). Kim H, et al. SF3B4 Depletion Retards the Growth of A549 Non-Small Cell Lung Cancer Cells via UBE4B-Mediated Regulation of p53/p21 and p27 Expression. Mol Cells.45,18–28(2022). Kidogami S, et al. SF3B4 Plays an Oncogenic Role in Esophageal Squamous Cell Carcinoma. Anticancer Res.40,941–6(2020). Li Y, et al. The splicing factor SF3B4 drives proliferation and invasion in cervical cancer by regulating SPAG5. Cell Death Discov.8,326(2022) Liu Z, et al. SF3B4 is regulated by microRNA-133b and promotes cell proliferation and metastasis in hepatocellular carcinoma. EBioMedicine.38,57–68(2018). Xiong F, Li S. SF3b4: A Versatile Player in Eukaryotic Cells. Front Cell Dev Biol.8,14(2020). Bernier FP, et al. Haploinsufficiency of SF3B4, a component of the pre-mRNA spliceosomal complex, causes Nager syndrome. Am J Hum Genet. 90,925 – 33(2012). Gozani O, Feld R, Reed R. Evidence that sequence-independent binding of highly conserved U2 snRNP proteins upstream of the branch site is required for assembly of spliceosomal complex A. Genes Dev.10,233 – 43(1996). Champion-Arnaud P, Reed R. The prespliceosome components SAP 49 and SAP 145 interact in a complex implicated in tethering U2 snRNP to the branch site. Genes Dev.8,1974-83(1994). Marques F, et al. Altered mRNA Splicing, Chondrocyte Gene Expression and Abnormal Skeletal Development due to SF3B4 Mutations in Rodriguez Acrofacial Dysostosis. PLoS Genet.12,e1006307(2016). Diao Y, et al. SF3B4 promotes ovarian cancer progression by regulating alternative splicing of RAD52. Cell Death Dis.13,179(2022). Watanabe H, Shionyu M, Kimura T, Kimata K, Watanabe H. Splicing factor 3b subunit 4 binds BMPR-IA and inhibits osteochondral cell differentiation. J Biol Chem.282,20728–38(2007). Terada Y, Yasuda Y. Human immunodeficiency virus type 1 Vpr induces G2 checkpoint activation by interacting with the splicing factor SAP145. Mol Cell Biol.26,8149–58(2006). Devotta A, Juraver-Geslin H, Gonzalez JA, Hong CS, Saint-Jeannet JP. Sf3b4-depleted Xenopus embryos: A model to study the pathogenesis of craniofacial defects in Nager syndrome. Dev Biol.415,371 – 82(2016). Lund IC, Vestergaard EM, Christensen R, Uldbjerg N, Becher N. Prenatal diagnosis of Nager syndrome in a 12-week-old fetus with a whole gene deletion of SF3B4 by chromosomal microarray. Eur J Med Genet.59,48–51(2016). Czeschik JC, et al. Clinical and mutation data in 12 patients with the clinical diagnosis of Nager syndrome. Hum Genet.132,85–98(2013). Xu W, Huang H, Yu L, Cao L. Meta-analysis of gene expression profiles indicates genes in spliceosome pathway are up-regulated in hepatocellular carcinoma (HCC). Med Oncol.32,96(2015). Iguchi T, et al. Increased Copy Number of the Gene Encoding SF3B4 Indicates Poor Prognosis in Hepatocellular Carcinoma. Anticancer Res.36,2139–44(2016). Lee J, et al. SRSF3 Depletion Leads to an Increase in SF3B4 Expression in SNU-368 HCC Cells. Anticancer Res.40,2033-42(2020). Zhou W, et al. SF3B4 is decreased in pancreatic cancer and inhibits the growth and migration of cancer cells. Tumour Biol.39,1010428317695913(2017). Shen Q, et al. Barrier to autointegration factor 1, procollagen-lysine, 2-oxoglutarate 5-dioxygenase 3, and splicing factor 3b subunit 4 as early-stage cancer decision markers and drivers of hepatocellular carcinoma. Hepatology.;67,1360–77(2018). Hu H, Guo L, Overholser J, Wang X. Mitochondrial VDAC1: A Potential Therapeutic Target of Inflammation-Related Diseases and Clinical Opportunities. Cells.11, 10.3390/cells11193174 (2022) Shoshan-Barmatz V, Golan M. Mitochondrial VDAC1: function in cell life and death and a target for cancer therapy. Curr Med Chem. 19,714 – 35(2012). Shoshan-Barmatz V, Maldonado EN, Krelin Y. VDAC1 at the crossroads of cell metabolism, apoptosis and cell stress. Cell Stress.1,11–36(2017). Yang X, et al. VDAC1 promotes cardiomyocyte autophagy in anoxia/reoxygenation injury via the PINK1/Parkin pathway. Cell Biol Int.;45,1448–58(2021). Shoshan-Barmatz V, Mizrachi D. VDAC1: from structure to cancer therapy. Front Oncol.2,164(2012). Magrì A, Reina S, De Pinto V. VDAC1 as Pharmacological Target in Cancer and Neurodegeneration: Focus on Its Role in Apoptosis. Front Chem.6,108(2018). Pandey SK, Machlof-Cohen R, Santhanam M, Shteinfer-Kuzmine A, Shoshan-Barmatz V. Silencing VDAC1 to Treat Mesothelioma Cancer: Tumor Reprograming and Altering Tumor Hallmarks. Biomolecules. 12, 10.3390/biom12070895 (2022) Azeez JM, et al. VDAC1 and SERCA3 Mediate Progesterone-Triggered Ca2(+) Signaling in Breast Cancer Cells. J Proteome Res.17,698–709(2018). Gao W, et al. Mitochondrial Proteomics Approach Reveals Voltage-Dependent Anion Channel 1 (VDAC1) as a Potential Biomarker of Gastric Cancer. Cell Physiol Biochem.37,2339–54(2015). Additional Declarations No competing interests reported. Supplementary Files Supplementarymaterial.pdf Cite Share Download PDF Status: Posted Version 1 posted You are reading this latest preprint version Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. As a division of Research Square Company, we’re committed to making research communication faster, fairer, and more useful. We do this by developing innovative software and high quality services for the global research community. Our growing team is made up of researchers and industry professionals working together to solve the most critical problems facing scientific publishing. Also discoverable on Platform About Our Team In Review Editorial Policies Advisory Board Help Center Resources Author Services Accessibility API Access RSS feed Manage Cookie Preferences © Research Square 2026 | ISSN 2693-5015 (online) Privacy Policy Terms of Service Do Not Sell My Personal Information {\"props\":{\"pageProps\":{\"initialData\":{\"identity\":\"rs-4495852\",\"acceptedTermsAndConditions\":true,\"allowDirectSubmit\":true,\"archivedVersions\":[],\"articleType\":\"Article\",\"associatedPublications\":[],\"authors\":[{\"id\":316443393,\"identity\":\"cacbbbcd-4809-4693-8b78-511dd959985f\",\"order_by\":0,\"name\":\"Dehong Li\",\"email\":\"\",\"orcid\":\"\",\"institution\":\"Lanzhou University\",\"correspondingAuthor\":false,\"prefix\":\"\",\"firstName\":\"Dehong\",\"middleName\":\"\",\"lastName\":\"Li\",\"suffix\":\"\"},{\"id\":316443396,\"identity\":\"9da2b54f-5c90-4888-9e68-8dd33b6a4cad\",\"order_by\":1,\"name\":\"Yan Lu\",\"email\":\"\",\"orcid\":\"\",\"institution\":\"Gansu Provincial Hospital\",\"correspondingAuthor\":false,\"prefix\":\"\",\"firstName\":\"Yan\",\"middleName\":\"\",\"lastName\":\"Lu\",\"suffix\":\"\"},{\"id\":316443397,\"identity\":\"87a4b21c-b0c5-441e-998b-637d77b00ccc\",\"order_by\":2,\"name\":\"Li Yan\",\"email\":\"\",\"orcid\":\"\",\"institution\":\"Gansu Provincial Hospital\",\"correspondingAuthor\":false,\"prefix\":\"\",\"firstName\":\"Li\",\"middleName\":\"\",\"lastName\":\"Yan\",\"suffix\":\"\"},{\"id\":316443398,\"identity\":\"76022900-940c-4c99-ac7c-32b38da78caa\",\"order_by\":3,\"name\":\"Xingwen Yang\",\"email\":\"\",\"orcid\":\"\",\"institution\":\"Gansu Provincial Hospital\",\"correspondingAuthor\":false,\"prefix\":\"\",\"firstName\":\"Xingwen\",\"middleName\":\"\",\"lastName\":\"Yang\",\"suffix\":\"\"},{\"id\":316443399,\"identity\":\"bc109775-b395-473d-815d-f69419c083ea\",\"order_by\":4,\"name\":\"Fenghui Zhao\",\"email\":\"\",\"orcid\":\"\",\"institution\":\"Gansu Provincial Hospital\",\"correspondingAuthor\":false,\"prefix\":\"\",\"firstName\":\"Fenghui\",\"middleName\":\"\",\"lastName\":\"Zhao\",\"suffix\":\"\"},{\"id\":316443401,\"identity\":\"55e7cd77-1453-43c6-bd63-03c2bb9c9d2c\",\"order_by\":5,\"name\":\"Xiaoyan Yang\",\"email\":\"\",\"orcid\":\"\",\"institution\":\"Gansu Provincial Hospital\",\"correspondingAuthor\":false,\"prefix\":\"\",\"firstName\":\"Xiaoyan\",\"middleName\":\"\",\"lastName\":\"Yang\",\"suffix\":\"\"},{\"id\":316443402,\"identity\":\"05aa7ea6-6b30-4172-a4e5-8849ca2781a7\",\"order_by\":6,\"name\":\"Xiumei Yuan\",\"email\":\"\",\"orcid\":\"\",\"institution\":\"Gansu Provincial Hospital\",\"correspondingAuthor\":false,\"prefix\":\"\",\"firstName\":\"Xiumei\",\"middleName\":\"\",\"lastName\":\"Yuan\",\"suffix\":\"\"},{\"id\":316443403,\"identity\":\"7104cff6-e803-4f84-b1f0-731a0b08240b\",\"order_by\":7,\"name\":\"Fugui Lin\",\"email\":\"\",\"orcid\":\"\",\"institution\":\"Gansu Provincial Hospital\",\"correspondingAuthor\":false,\"prefix\":\"\",\"firstName\":\"Fugui\",\"middleName\":\"\",\"lastName\":\"Lin\",\"suffix\":\"\"},{\"id\":316443404,\"identity\":\"12f1835f-c969-44da-a293-8f7d063a2449\",\"order_by\":8,\"name\":\"Kehu Yang\",\"email\":\"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAAA6klEQVRIie3LMWvCQBjG8ScEMknGYggYP8KFgCL0w1wQnE5xcm2kcJu7wS8Rt3a7o4NLqutBFm8UHBQXndrGqdOpm8P9p+eF9wfYbE+aM80AAleK6ynuJx59mDTIfYSsvr92+Qda3ZfyIC8cLV9R5zQ2kXI06C1LJL3FsBABRxIo6oZzExGsE2v+kxbVH4k50kJRz22YyGZfE7wVFduKtB43iWKJXnJQUjEIWY9bJFD7jpNzxJ+LAZHZuhnnpX4PTcTfsOQ444i6YV/r8+Q18ld9eTKRtoDX/HfX28kMAIgyuAfjh81ms9l+AR+9Vvmt5E5xAAAAAElFTkSuQmCC\",\"orcid\":\"\",\"institution\":\"Lanzhou University\",\"correspondingAuthor\":true,\"prefix\":\"\",\"firstName\":\"Kehu\",\"middleName\":\"\",\"lastName\":\"Yang\",\"suffix\":\"\"}],\"badges\":[],\"createdAt\":\"2024-05-29 09:21:04\",\"currentVersionCode\":1,\"declarations\":\"\",\"doi\":\"10.21203/rs.3.rs-4495852/v1\",\"doiUrl\":\"https://doi.org/10.21203/rs.3.rs-4495852/v1\",\"draftVersion\":[],\"editorialEvents\":[],\"editorialNote\":\"\",\"failedWorkflow\":false,\"files\":[{\"id\":59216216,\"identity\":\"04568f54-245f-4b11-866b-1a849fae6e9b\",\"added_by\":\"auto\",\"created_at\":\"2024-06-27 19:03:27\",\"extension\":\"jpeg\",\"order_by\":1,\"title\":\"Figure 1\",\"display\":\"\",\"copyAsset\":false,\"role\":\"figure\",\"size\":1123777,\"visible\":true,\"origin\":\"\",\"legend\":\"\\u003cp\\u003e\\u003cstrong\\u003eTandem Mass Tag analysis and high-content shRNA screening identified SF3B4 as a key gene in promoting GC proliferation.\\u003c/strong\\u003e (a) A heat map of gene expression profiles. Each row is a gene, and each column is a sample. A red line represents a gene that has high expression, whereas a ­­­­­blue line indicates one that has low expression. (b) A total of 26 genes were selected for validation by high-content screening. NC: negative control shRNA, PC: positive control shRNA targeting NOB1. (c) Representative fluorescence images of high-content shRNA screening for SF3B4.\\u003c/p\\u003e\",\"description\":\"\",\"filename\":\"floatimage1.jpeg\",\"url\":\"https://assets-eu.researchsquare.com/files/rs-4495852/v1/a003abdc70b8ead8dd86c4fd.jpeg\"},{\"id\":59215262,\"identity\":\"22a7dd83-738d-4282-9592-4e351ac4192a\",\"added_by\":\"auto\",\"created_at\":\"2024-06-27 18:55:26\",\"extension\":\"jpeg\",\"order_by\":2,\"title\":\"Figure 2\",\"display\":\"\",\"copyAsset\":false,\"role\":\"figure\",\"size\":396438,\"visible\":true,\"origin\":\"\",\"legend\":\"\\u003cp\\u003e\\u003cstrong\\u003eExpression patterns of SF3B4 in Gastric cancer tissues and cell lines.\\u003c/strong\\u003e (a) Protein levels of SF3B4 in Histologically normal tissue adjacent to the tumor and malignant tumor tissues in gastric cancer patients. In situ expression of SF3B4 was detected by immunohistochemical (IHC) analysis. (b) The fold line diagram of SF3B4 mRNA expression between normal and cancer tissues from TCGA RNA-seq data.The vertical axis is mRNA expression of each sample, and the horizontal axis is the adjacent normal tissueand cancer tissue of the sample. (c) The FC (ratio of cancer samples to adjacent samples) histogram of SF3B4 mRNA expression amount in TCGA RNA-seqsamples. The vertical axis is logFC, and the horizontal axis is different samples (d) Kaplan-Meier progression-free survival curve was shown according to high and low expression of SF3B4 in gastric cancer patients derived from TCGA data. (e) Expression of SF3B4 mRNA was determined by qRT-PCR analysis in fivegastric cancer cells. GAPDH was used as internal reference. The value was represented with ΔCt (SF3B4/GAPDH). Data are represented as \\u0026nbsp;mean ± SD from triplicate experiments.\\u003c/p\\u003e\",\"description\":\"\",\"filename\":\"floatimage2.jpeg\",\"url\":\"https://assets-eu.researchsquare.com/files/rs-4495852/v1/7f09ab42a73ee02ba92c135a.jpeg\"},{\"id\":59215264,\"identity\":\"21196c1b-9da1-42c2-b09f-21e2a0c8f7ad\",\"added_by\":\"auto\",\"created_at\":\"2024-06-27 18:55:27\",\"extension\":\"jpeg\",\"order_by\":3,\"title\":\"Figure 3\",\"display\":\"\",\"copyAsset\":false,\"role\":\"figure\",\"size\":460561,\"visible\":true,\"origin\":\"\",\"legend\":\"\\u003cp\\u003e\\u003cstrong\\u003eThe knockdown of SF3B4 inhibits GC tumor growth in vitro and vivo. \\u003c/strong\\u003e(a) The mRNA and protein levels of SF3B4 in AGS and MKN-45 of knockdown SF3B4. (b) Cell proliferation was measured using CCK-8 assays in AGS and MKN-45 cells of knockdown SF3B4. (c) Cell clonogenicities were measured using a clonogenic assay in AGS (up) and MKN-45 (down) cells of knockdown SF3B4.（d）Cell proliferation was assessed using BrdU assays in AGS and MKN-45 cells of knockdown SF3B4. (e) Cell apoptosis was quantified by Annexin V-APC staining followed by flow cytometric analysis statistical analysis of the apoptotic percentage of shCtrl and shSF3B4 in AGS and MKN-45 cells after SF3B4 knockdown. (f) images of shCtrl and shSF3B4 MKN-45 cells transplanted mice and tumors 19 days after injection; (g) fluorescence intensities of shCtrl or shSF3B4 -MKN-45 cells treated mice were detected and measured at 19 days after treatment; (h) Tumor volume was measured and calculated during experiments; (i) Tumors were weighed after mice models were sacrificed. Data are shown as mean with standard deviation (SD). ***\\u003cem\\u003eP\\u003c/em\\u003e\\u0026lt;.001, **\\u003cem\\u003eP\\u003c/em\\u003e\\u0026lt;.01,*\\u003cem\\u003eP\\u003c/em\\u003e\\u0026lt;.05. Statistical analysis was determined by Student's t-test.\\u003c/p\\u003e\",\"description\":\"\",\"filename\":\"floatimage3.jpeg\",\"url\":\"https://assets-eu.researchsquare.com/files/rs-4495852/v1/511c37cda22ebd85a9f3fdbc.jpeg\"},{\"id\":59215267,\"identity\":\"a69288bd-5901-4e46-8012-37eb36ea687b\",\"added_by\":\"auto\",\"created_at\":\"2024-06-27 18:55:27\",\"extension\":\"jpeg\",\"order_by\":4,\"title\":\"Figure 4\",\"display\":\"\",\"copyAsset\":false,\"role\":\"figure\",\"size\":333958,\"visible\":true,\"origin\":\"\",\"legend\":\"\\u003cp\\u003e\\u003cstrong\\u003eExploration of underlying mechanism by IPA analysisa and \\u0026nbsp;western blot analysis. \\u003c/strong\\u003e(a) IPA \\u0026nbsp;analysis \\u0026nbsp;revealed \\u0026nbsp;4 significantly inhibited pathways and 2 significantly activated pathways. The ordinate is the name of the pathway, and the abscissa is the Z-Score to the pathway (P \\u0026lt; 0.05). \\u0026nbsp;(b) The Wayne figures of overlapping and different genes among the 4 inhibited pathways. (c) The mRNA expression of 8 genes which were repetitive in multiple pathways were analyzed. All of them showed a strong decreas after SF3B4 knockdown. \\u0026nbsp;(d) Protein levels of 4 most significantly downregulated candidates (FOXO3,VDAC1,DNAJA3 and DRAM2) were further examined by WB. (e) The upregulated expression of VDAC1 in GC tissues was proved by TCGA.\\u003c/p\\u003e\",\"description\":\"\",\"filename\":\"floatimage4.jpeg\",\"url\":\"https://assets-eu.researchsquare.com/files/rs-4495852/v1/450f6adfb0640d23d00483c1.jpeg\"},{\"id\":59215263,\"identity\":\"73ea18d9-d8c5-491b-9ccf-87311d144ec3\",\"added_by\":\"auto\",\"created_at\":\"2024-06-27 18:55:27\",\"extension\":\"jpeg\",\"order_by\":5,\"title\":\"Figure 5\",\"display\":\"\",\"copyAsset\":false,\"role\":\"figure\",\"size\":495779,\"visible\":true,\"origin\":\"\",\"legend\":\"\\u003cp\\u003e\\u003cstrong\\u003eVDAC1 overexpression alleviates the effects of SF3B4 knockdown on GC cells\\u003c/strong\\u003e. (a) Green lentiviral vector fluorescence was observed in NC+NC group,SF3B4 knockdown lentivirus (KD+NC), and SF3B4 knockdown+VDAC1-overexpressing lentivirus groups (KD+OE). (b) The mRNA expression levels of SF3B4 and VDAC1 in NC+NC control, SF3B4 knockdown, and simultaneous SF3B4 knockdown and VDAC1 overexpression AGS cells. (c)The protein expression levels of SF3B4 and VDAC1 in control, SF3B4 knockdown, and simultaneous SF3B4 knockdown and VDAC1 overexpression AGS cells. (d) and (e) The influence of VDAC1 overexpression on the SF3B4 knockdown-induced proliferation changes were detected by clonogenic assay and CCK8 assay. (f) Autophagy-related proteins ATG7,ATG5,ATG9A and ATG12 were detected by WB.The data were expressed as mean ± SD (n ≥ 3), *\\u003cem\\u003eP\\u003c/em\\u003e\\u0026lt; 0.05, **\\u003cem\\u003eP \\u003c/em\\u003e\\u0026lt; 0.01,***\\u003cem\\u003eP\\u003c/em\\u003e\\u0026lt; 0.001.\\u003c/p\\u003e\",\"description\":\"\",\"filename\":\"floatimage5.jpeg\",\"url\":\"https://assets-eu.researchsquare.com/files/rs-4495852/v1/ccf2036d8d5a2208ff524bd9.jpeg\"},{\"id\":63106547,\"identity\":\"bea0789b-f88f-4cdf-8421-86d17f77e9df\",\"added_by\":\"auto\",\"created_at\":\"2024-08-23 07:52:20\",\"extension\":\"pdf\",\"order_by\":0,\"title\":\"\",\"display\":\"\",\"copyAsset\":false,\"role\":\"manuscript-pdf\",\"size\":3593083,\"visible\":true,\"origin\":\"\",\"legend\":\"\",\"description\":\"\",\"filename\":\"manuscript.pdf\",\"url\":\"https://assets-eu.researchsquare.com/files/rs-4495852/v1/9a12498e-4c31-4034-a474-033bde645e86.pdf\"},{\"id\":59215265,\"identity\":\"c44bf26c-d6b1-47a6-b1db-83ac7714666f\",\"added_by\":\"auto\",\"created_at\":\"2024-06-27 18:55:27\",\"extension\":\"pdf\",\"order_by\":9,\"title\":\"\",\"display\":\"\",\"copyAsset\":false,\"role\":\"supplement\",\"size\":322599,\"visible\":true,\"origin\":\"\",\"legend\":\"\",\"description\":\"\",\"filename\":\"Supplementarymaterial.pdf\",\"url\":\"https://assets-eu.researchsquare.com/files/rs-4495852/v1/3b14decd2f8d563e3efbda9c.pdf\"}],\"financialInterests\":\"No competing interests reported.\",\"formattedTitle\":\"Splicing Factor 3b Subunit 4 (SF3B4) Promotes Proliferation of Gastric Cancer through Regulation of VDAC1\",\"fulltext\":[{\"header\":\"1. Introduction\",\"content\":\"\\u003cp\\u003eGastric cancer (GC) is the fifth most common malignancy and the third leading contributor to cancer-related mortality worldwide[\\u003cspan citationid=\\\"CR1\\\" class=\\\"CitationRef\\\"\\u003e1\\u003c/span\\u003e].GC is a multifactorial disease involving numerous complex genetic factors and mechanisms[\\u003cspan citationid=\\\"CR2\\\" class=\\\"CitationRef\\\"\\u003e2\\u003c/span\\u003e].As a result, a better understanding of the molecular mechanisms behind this disease could lead to the identification of new therapeutic targets.\\u003c/p\\u003e \\u003cp\\u003eWe screened for proteins with abnormal overexpression in GC using five gastric cancer tissues and adjacent normal tissues with tandem mass tag (TMT)-based proteomics. We confirmed the function of the identified genes by high-content shRNA screening. Using this method, we discovered that SF3B4, one subunit of the splicing factor 3b (SF3b) complex, may be essential to GC proliferation.\\u003c/p\\u003e \\u003cp\\u003eThe spliceosome, a large ribonucleoprotein complex, is responsible for precisely removing introns from pre-messenger RNA and producing multiple transcripts from a shared precursor. This process is commonly referred to as alternative splicing[\\u003cspan citationid=\\\"CR3\\\" class=\\\"CitationRef\\\"\\u003e3\\u003c/span\\u003e, \\u003cspan citationid=\\\"CR4\\\" class=\\\"CitationRef\\\"\\u003e4\\u003c/span\\u003e]. The spliceosome is a dynamic complex that contains five small nuclear ribonucleoproteins (snRNPs) (U1, U2, U4/U6, U5), seven Sm proteins, and a significant number of associated protein[\\u003cspan citationid=\\\"CR5\\\" class=\\\"CitationRef\\\"\\u003e5\\u003c/span\\u003e, \\u003cspan citationid=\\\"CR6\\\" class=\\\"CitationRef\\\"\\u003e6\\u003c/span\\u003e]. The U2 snRNP consists of two major protein complexes, SF3a (splicing factor 3a) and SF3b (splicing factor 3b)[\\u003cspan citationid=\\\"CR7\\\" class=\\\"CitationRef\\\"\\u003e7\\u003c/span\\u003e]. All known SF3a and SF3b subunits, except for SF3b130, can be cross-linked to the pre-mRNA near the branch site[\\u003cspan citationid=\\\"CR8\\\" class=\\\"CitationRef\\\"\\u003e8\\u003c/span\\u003e] and play essential roles during pre-spliceosome assembly[\\u003cspan citationid=\\\"CR9\\\" class=\\\"CitationRef\\\"\\u003e9\\u003c/span\\u003e]. SF3B4, as a major constituent of the SF3b complex, tethers the pre-mRNA upstream of the branch point sequence and plays an important role in binding the U2 snRNP to the branch site in the splicing processes[\\u003cspan citationid=\\\"CR10\\\" class=\\\"CitationRef\\\"\\u003e10\\u003c/span\\u003e, \\u003cspan citationid=\\\"CR11\\\" class=\\\"CitationRef\\\"\\u003e11\\u003c/span\\u003e].Growing evidence suggests that dysfunction of SF3B4 plays a critical role in the carcinogenesis and progression of human cancers[\\u003cspan additionalcitationids=\\\"CR13\\\" citationid=\\\"CR12\\\" class=\\\"CitationRef\\\"\\u003e12\\u003c/span\\u003e\\u0026ndash;\\u003cspan citationid=\\\"CR14\\\" class=\\\"CitationRef\\\"\\u003e14\\u003c/span\\u003e]. Overexpressing SF3B4 can promote tumorigenesis in hepatocellular carcinoma (HCC)[\\u003cspan citationid=\\\"CR15\\\" class=\\\"CitationRef\\\"\\u003e15\\u003c/span\\u003e]. Also, SF3B4 is considered as a cancer-promoting factor of the esophageal squamous cell carcinoma[\\u003cspan citationid=\\\"CR13\\\" class=\\\"CitationRef\\\"\\u003e13\\u003c/span\\u003e]. Nevertheless, asa splicing factor, the biological function and detailed molecula rmechanism of SF3B4 in GC are still unclear. In this study, we demonstrate that SF3B4 promotes GC proliferation via the VDAC1.This result provides new insight into the molecular mechanisms of gastric carcinogenesis and suggesting that SF3B4 may serve as a target for the treatment of GC.\\u003c/p\\u003e\"},{\"header\":\"2. Results\",\"content\":\"\\u003cdiv id=\\\"Sec3\\\" class=\\\"Section2\\\"\\u003e \\u003ch2\\u003e2.1. Identification of SF3B4 as a critical gene that promotes GC proliferation\\u003c/h2\\u003e \\u003cp\\u003eWe used Tandem Mass Tag analysis to identify genes with a critical role in GC tumor genesis to compare the protein expression profiles of five pairs of matched GC and adjacent normal tissue samples(CON). The results identified 6653 proteins were confirmed, 1008 differential proteins ultimately exhibited significantly different expressions between the groups according to the criteria of \\u003cem\\u003eP\\u003c/em\\u003e value\\u0026thinsp;\\u0026lt;\\u0026thinsp;0.05 and fold changes\\u0026thinsp;\\u0026gt;\\u0026thinsp;1.20(Fig.\\u0026nbsp;\\u003cspan refid=\\\"Fig1\\\" class=\\\"InternalRef\\\"\\u003e1\\u003c/span\\u003ea). Among these, 649 proteins were upregulated, and 359 were downregulated in the GC group compared to the CON group. Next, 26 differential expression genes were selected as the candidate genes potentially play an essential role in the proliferation of GC on thebasisof a functional analysis (Table S2). All 26 candidate genes were then knocked down in AGS cells toassess the potential effect on potential effects on in vitro proliferation of GC cells (Fig.\\u0026nbsp;\\u003cspan refid=\\\"Fig1\\\" class=\\\"InternalRef\\\"\\u003e1\\u003c/span\\u003eb). Knockdown of three candidate genes, SF3B4, WDR12, and RFTN1, in AGS cells reduced the cell proliferation rate. SF3B4 knockdown showed the greatest effect on reducing the proliferation rate, cell count/fold on the fifth day in shCtrl group was 8.64, while the cell count/fold in shSF3B4 groups was only1.72(Fig.\\u0026nbsp;\\u003cspan refid=\\\"Fig1\\\" class=\\\"InternalRef\\\"\\u003e1\\u003c/span\\u003ec). therefore, we focused on SF3B4 in our subsequent studies.\\u003c/p\\u003e \\u003cp\\u003e \\u003c/p\\u003e \\u003cp\\u003e \\u003cb\\u003e2.2. SF3B4 was highly expressed in gastric cancer tissue and several cell lines and was associated with poor prognosis in patients\\u003c/b\\u003e \\u003c/p\\u003e \\u003cp\\u003eTo investigate whether SF3B4 was expressed in human gastric cancer cells, the expression of SF3B4 protein in human adjacent normal tissue and gastric cancer tissue was analyzed by immunohistochemistry. As shown in Fig.\\u0026nbsp;\\u003cspan refid=\\\"Fig2\\\" class=\\\"InternalRef\\\"\\u003e2\\u003c/span\\u003ea and statistical analysis in Table\\u0026nbsp;\\u003cspan refid=\\\"Tab1\\\" class=\\\"InternalRef\\\"\\u003e1\\u003c/span\\u003e, a higher level of SF3B4 expression is found in GC tissues than in normal tissues. Furthermore, the same result was obtained from the TCGA dataset, 33 original data of TCGA RNA-seq samples were presented in a line chart and the form of histogram(Fig.\\u0026nbsp;\\u003cspan refid=\\\"Fig2\\\" class=\\\"InternalRef\\\"\\u003e2\\u003c/span\\u003eb and \\u003cspan refid=\\\"Fig2\\\" class=\\\"InternalRef\\\"\\u003e2\\u003c/span\\u003ed). Comparing with the adjacent normal tissue, SF3B4 expression in Stomach adenocarcinoma (STAD) was significantly upregulated(\\u003cem\\u003eP\\u003c/em\\u003e value is 1.71E-05). Kaplan\\u0026ndash;Meier analysis revealed patients with high levels of SF3B4 displayed a remarkably shorter progression-free survival time than those in the SF3B4-low group (Fig.\\u0026nbsp;\\u003cspan refid=\\\"Fig2\\\" class=\\\"InternalRef\\\"\\u003e2\\u003c/span\\u003ec). We also evaluated SF3B4 mRNA expression level in GC cell lines by qRT-PCR (Fig.\\u0026nbsp;\\u003cspan refid=\\\"Fig2\\\" class=\\\"InternalRef\\\"\\u003e2\\u003c/span\\u003ee). The value was represented with ∆Ct(SF3B4-GAPDH). SF3B4 mRNA expression was significantly increased among AGS, HGC-27, KATO III, NCI-N87and MKN-45cell lines.\\u003c/p\\u003e \\u003cp\\u003e \\u003c/p\\u003e \\u003cp\\u003e \\u003cdiv class=\\\"gridtable\\\"\\u003e\\u003ctable float=\\\"Yes\\\" id=\\\"Tab1\\\" border=\\\"1\\\"\\u003e \\u003ccaption language=\\\"En\\\"\\u003e \\u003cdiv class=\\\"CaptionNumber\\\"\\u003eTable 1\\u003c/div\\u003e \\u003cdiv class=\\\"CaptionContent\\\"\\u003e \\u003cp\\u003eExpression patterns in GC tissues and adjacent normal gastric tissues revealed in immunohistochemistry analysis\\u003c/p\\u003e \\u003c/div\\u003e \\u003c/caption\\u003e \\u003ccolgroup cols=\\\"6\\\"\\u003e \\u003cdiv align=\\\"left\\\" class=\\\"colspec\\\" colname=\\\"c1\\\" colnum=\\\"1\\\"\\u003e\\u003c/div\\u003e \\u003cdiv align=\\\"left\\\" class=\\\"colspec\\\" colname=\\\"c2\\\" colnum=\\\"2\\\"\\u003e\\u003c/div\\u003e \\u003cdiv align=\\\"left\\\" class=\\\"colspec\\\" colname=\\\"c3\\\" colnum=\\\"3\\\"\\u003e\\u003c/div\\u003e \\u003cdiv align=\\\"left\\\" class=\\\"colspec\\\" colname=\\\"c4\\\" colnum=\\\"4\\\"\\u003e\\u003c/div\\u003e \\u003cdiv align=\\\"left\\\" class=\\\"colspec\\\" colname=\\\"c5\\\" colnum=\\\"5\\\"\\u003e\\u003c/div\\u003e \\u003cdiv align=\\\"char\\\" char=\\\".\\\" class=\\\"colspec\\\" colname=\\\"c6\\\" colnum=\\\"6\\\"\\u003e\\u003c/div\\u003e \\u003cthead\\u003e \\u003ctr\\u003e \\u003cth align=\\\"left\\\" colname=\\\"c1\\\"\\u003e \\u003cp\\u003eSF3B4\\u003c/p\\u003e \\u003cp\\u003eexpression\\u003c/p\\u003e \\u003c/th\\u003e \\u003cth align=\\\"left\\\" colspan=\\\"2\\\" nameend=\\\"c3\\\" namest=\\\"c2\\\"\\u003e \\u003cp\\u003eTumor tissues\\u003c/p\\u003e \\u003c/th\\u003e \\u003cth align=\\\"left\\\" colspan=\\\"2\\\" nameend=\\\"c5\\\" namest=\\\"c4\\\"\\u003e \\u003cp\\u003eAdjacent normal gastric tissues\\u003c/p\\u003e \\u003c/th\\u003e \\u003cth align=\\\"left\\\" colname=\\\"c6\\\"\\u003e \\u003cp\\u003e\\u003cem\\u003ep\\u003c/em\\u003e-value\\u003c/p\\u003e \\u003c/th\\u003e \\u003c/tr\\u003e \\u003c/thead\\u003e \\u003ctbody\\u003e \\u003ctr\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c1\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c2\\\"\\u003e \\u003cp\\u003eCases\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c3\\\"\\u003e \\u003cp\\u003ePercentage\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c4\\\"\\u003e \\u003cp\\u003eCases\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c5\\\"\\u003e \\u003cp\\u003ePercentage\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c6\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e \\u003c/tr\\u003e \\u003ctr\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c1\\\"\\u003e \\u003cp\\u003eLow\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c2\\\"\\u003e \\u003cp\\u003e20\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c3\\\"\\u003e \\u003cp\\u003e52.6\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c4\\\"\\u003e \\u003cp\\u003e38\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c5\\\"\\u003e \\u003cp\\u003e100%\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c6\\\"\\u003e \\u003cp\\u003e0.000***\\u003c/p\\u003e \\u003c/td\\u003e \\u003c/tr\\u003e \\u003ctr\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c1\\\"\\u003e \\u003cp\\u003eHigh\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c2\\\"\\u003e \\u003cp\\u003e18\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c3\\\"\\u003e \\u003cp\\u003e47.4\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c4\\\"\\u003e \\u003cp\\u003e0\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c5\\\"\\u003e \\u003cp\\u003e-\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c6\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e \\u003c/tr\\u003e \\u003c/tbody\\u003e \\u003c/colgroup\\u003e \\u003c/table\\u003e\\u003c/div\\u003e \\u003c/p\\u003e \\u003cp\\u003eMeanwhile, to explore the relationship between SF3B4 expression and clinicopathological features, we stratified patients according to different clinicopathological parameters and compared the expression of SF3B4. As shown in Table\\u0026nbsp;\\u003cspan refid=\\\"Tab2\\\" class=\\\"InternalRef\\\"\\u003e2\\u003c/span\\u003e, under TNM stage, the percentage of low SF3B4 expression in \\u0026ldquo;I- II\\u0026rdquo; group was 80%, in \\u0026ldquo;III- IV\\u0026rdquo; group was 42.9%; while the percentage of high SF3B4 expression in \\u0026ldquo;I- II\\u0026rdquo; group was 20%, in \\u0026ldquo;III- IV\\u0026rdquo; group was 57.1%(8/23). After Pearson Chi-square test, the \\u003cem\\u003eP\\u003c/em\\u003e value for these groups percentage was 0.043, which means III-IV stage had more percentages of high SF3B4 expression. However, differential SF3B4 expression was not observed in groups under Sex, Age, Histologic differentiation as well as Lymphovascularin vasion.\\u003c/p\\u003e \\u003cp\\u003e \\u003cdiv class=\\\"gridtable\\\"\\u003e\\u003ctable float=\\\"Yes\\\" id=\\\"Tab2\\\" border=\\\"1\\\"\\u003e \\u003ccaption language=\\\"En\\\"\\u003e \\u003cdiv class=\\\"CaptionNumber\\\"\\u003eTable 2\\u003c/div\\u003e \\u003cdiv class=\\\"CaptionContent\\\"\\u003e \\u003cp\\u003eClinical characteristics of gastric cancer patients and SF3B4 expression\\u003c/p\\u003e \\u003c/div\\u003e \\u003c/caption\\u003e \\u003ccolgroup cols=\\\"8\\\"\\u003e \\u003cdiv align=\\\"left\\\" class=\\\"colspec\\\" colname=\\\"c1\\\" colnum=\\\"1\\\"\\u003e\\u003c/div\\u003e \\u003cdiv align=\\\"left\\\" class=\\\"colspec\\\" colname=\\\"c2\\\" colnum=\\\"2\\\"\\u003e\\u003c/div\\u003e \\u003cdiv align=\\\"left\\\" class=\\\"colspec\\\" colname=\\\"c3\\\" colnum=\\\"3\\\"\\u003e\\u003c/div\\u003e \\u003cdiv align=\\\"left\\\" class=\\\"colspec\\\" colname=\\\"c4\\\" colnum=\\\"4\\\"\\u003e\\u003c/div\\u003e \\u003cdiv align=\\\"left\\\" class=\\\"colspec\\\" colname=\\\"c5\\\" colnum=\\\"5\\\"\\u003e\\u003c/div\\u003e \\u003cdiv align=\\\"left\\\" class=\\\"colspec\\\" colname=\\\"c6\\\" colnum=\\\"6\\\"\\u003e\\u003c/div\\u003e \\u003cdiv align=\\\"left\\\" class=\\\"colspec\\\" colname=\\\"c7\\\" colnum=\\\"7\\\"\\u003e\\u003c/div\\u003e \\u003cdiv align=\\\"left\\\" class=\\\"colspec\\\" colname=\\\"c8\\\" colnum=\\\"8\\\"\\u003e\\u003c/div\\u003e \\u003cthead\\u003e \\u003ctr\\u003e \\u003cth align=\\\"left\\\" colname=\\\"c1\\\" morerows=\\\"1\\\" rowspan=\\\"2\\\"\\u003e \\u003cp\\u003eFeature\\u003c/p\\u003e \\u003c/th\\u003e \\u003cth align=\\\"left\\\" colspan=\\\"2\\\" morerows=\\\"1\\\" nameend=\\\"c3\\\" namest=\\\"c2\\\" rowspan=\\\"2\\\"\\u003e \\u003cp\\u003eNo. of patients\\u003c/p\\u003e \\u003c/th\\u003e \\u003cth align=\\\"left\\\" colspan=\\\"4\\\" nameend=\\\"c7\\\" namest=\\\"c4\\\"\\u003e \\u003cp\\u003eSF3B4 Expression\\u003c/p\\u003e \\u003c/th\\u003e \\u003cth align=\\\"left\\\" colname=\\\"c8\\\" morerows=\\\"1\\\" rowspan=\\\"2\\\"\\u003e \\u003cp\\u003e\\u003cem\\u003ep\\u003c/em\\u003e value\\u003c/p\\u003e \\u003c/th\\u003e \\u003c/tr\\u003e \\u003ctr\\u003e \\u003cth align=\\\"left\\\" colspan=\\\"2\\\" nameend=\\\"c5\\\" namest=\\\"c4\\\"\\u003e \\u003cp\\u003eLow\\u003c/p\\u003e \\u003c/th\\u003e \\u003cth align=\\\"left\\\" colspan=\\\"2\\\" nameend=\\\"c7\\\" namest=\\\"c6\\\"\\u003e \\u003cp\\u003eHigh\\u003c/p\\u003e \\u003c/th\\u003e \\u003c/tr\\u003e \\u003c/thead\\u003e \\u003ctbody\\u003e \\u003ctr\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c1\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c2\\\"\\u003e \\u003cp\\u003eN\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c3\\\"\\u003e \\u003cp\\u003e%\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c4\\\"\\u003e \\u003cp\\u003eN\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c5\\\"\\u003e \\u003cp\\u003e%\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c6\\\"\\u003e \\u003cp\\u003eN\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c7\\\"\\u003e \\u003cp\\u003e%\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c8\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e \\u003c/tr\\u003e \\u003ctr\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c1\\\"\\u003e \\u003cp\\u003eAll patients\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c2\\\"\\u003e \\u003cp\\u003e38\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c3\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c4\\\"\\u003e \\u003cp\\u003e20\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c5\\\"\\u003e \\u003cp\\u003e52.6\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c6\\\"\\u003e \\u003cp\\u003e18\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c7\\\"\\u003e \\u003cp\\u003e47.4\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c8\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e \\u003c/tr\\u003e \\u003ctr\\u003e \\u003ctd align=\\\"left\\\" colspan=\\\"8\\\" nameend=\\\"c8\\\" namest=\\\"c1\\\"\\u003e \\u003cp\\u003eGender 0.184\\u003c/p\\u003e \\u003c/td\\u003e \\u003c/tr\\u003e \\u003ctr\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c1\\\"\\u003e \\u003cp\\u003eFemale\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c2\\\"\\u003e \\u003cp\\u003e9\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c3\\\"\\u003e \\u003cp\\u003e23.7\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c4\\\"\\u003e \\u003cp\\u003e3\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c5\\\"\\u003e \\u003cp\\u003e33.3\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c6\\\"\\u003e \\u003cp\\u003e6\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c7\\\"\\u003e \\u003cp\\u003e66.7\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c8\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e \\u003c/tr\\u003e \\u003ctr\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c1\\\"\\u003e \\u003cp\\u003eMale\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c2\\\"\\u003e \\u003cp\\u003e29\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c3\\\"\\u003e \\u003cp\\u003e76.3\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c4\\\"\\u003e \\u003cp\\u003e17\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c5\\\"\\u003e \\u003cp\\u003e58.6\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c6\\\"\\u003e \\u003cp\\u003e12\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c7\\\"\\u003e \\u003cp\\u003e41.4\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c8\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e \\u003c/tr\\u003e \\u003ctr\\u003e \\u003ctd align=\\\"left\\\" colspan=\\\"8\\\" nameend=\\\"c8\\\" namest=\\\"c1\\\"\\u003e \\u003cp\\u003eAge (years) 0.453\\u003c/p\\u003e \\u003c/td\\u003e \\u003c/tr\\u003e \\u003ctr\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c1\\\"\\u003e \\u003cp\\u003e\\u0026le;\\u0026thinsp;50\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c2\\\"\\u003e \\u003cp\\u003e6\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c3\\\"\\u003e \\u003cp\\u003e15.8\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c4\\\"\\u003e \\u003cp\\u003e4\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c5\\\"\\u003e \\u003cp\\u003e66.7\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c6\\\"\\u003e \\u003cp\\u003e2\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c7\\\"\\u003e \\u003cp\\u003e33.3\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c8\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e \\u003c/tr\\u003e \\u003ctr\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c1\\\"\\u003e \\u003cp\\u003e\\u0026gt;50\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c2\\\"\\u003e \\u003cp\\u003e32\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c3\\\"\\u003e \\u003cp\\u003e84.2\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c4\\\"\\u003e \\u003cp\\u003e16\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c5\\\"\\u003e \\u003cp\\u003e50\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c6\\\"\\u003e \\u003cp\\u003e16\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c7\\\"\\u003e \\u003cp\\u003e50\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c8\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e \\u003c/tr\\u003e \\u003ctr\\u003e \\u003ctd align=\\\"left\\\" colspan=\\\"8\\\" nameend=\\\"c8\\\" namest=\\\"c1\\\"\\u003e \\u003cp\\u003eTNM stage 0.043*\\u003c/p\\u003e \\u003c/td\\u003e \\u003c/tr\\u003e \\u003ctr\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c1\\\"\\u003e \\u003cp\\u003eI- II\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c2\\\"\\u003e \\u003cp\\u003e10\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c3\\\"\\u003e \\u003cp\\u003e26.3\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c4\\\"\\u003e \\u003cp\\u003e8\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c5\\\"\\u003e \\u003cp\\u003e80\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c6\\\"\\u003e \\u003cp\\u003e2\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c7\\\"\\u003e \\u003cp\\u003e20\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c8\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e \\u003c/tr\\u003e \\u003ctr\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c1\\\"\\u003e \\u003cp\\u003eIII- IV\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c2\\\"\\u003e \\u003cp\\u003e28\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c3\\\"\\u003e \\u003cp\\u003e73.7\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c4\\\"\\u003e \\u003cp\\u003e12\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c5\\\"\\u003e \\u003cp\\u003e42.9\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c6\\\"\\u003e \\u003cp\\u003e16\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c7\\\"\\u003e \\u003cp\\u003e57.1\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c8\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e \\u003c/tr\\u003e \\u003ctr\\u003e \\u003ctd align=\\\"left\\\" colspan=\\\"8\\\" nameend=\\\"c8\\\" namest=\\\"c1\\\"\\u003e \\u003cp\\u003eHistologic differentiation 0.732\\u003c/p\\u003e \\u003c/td\\u003e \\u003c/tr\\u003e \\u003ctr\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c1\\\"\\u003e \\u003cp\\u003eWell or moderate\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c2\\\"\\u003e \\u003cp\\u003e18\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c3\\\"\\u003e \\u003cp\\u003e44.7\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c4\\\"\\u003e \\u003cp\\u003e10\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c5\\\"\\u003e \\u003cp\\u003e55.6\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c6\\\"\\u003e \\u003cp\\u003e8\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c7\\\"\\u003e \\u003cp\\u003e44.6\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c8\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e \\u003c/tr\\u003e \\u003ctr\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c1\\\"\\u003e \\u003cp\\u003ePoor\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c2\\\"\\u003e \\u003cp\\u003e20\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c3\\\"\\u003e \\u003cp\\u003e55.3\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c4\\\"\\u003e \\u003cp\\u003e10\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c5\\\"\\u003e \\u003cp\\u003e50\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c6\\\"\\u003e \\u003cp\\u003e10\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c7\\\"\\u003e \\u003cp\\u003e50\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c8\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e \\u003c/tr\\u003e \\u003ctr\\u003e \\u003ctd align=\\\"left\\\" colspan=\\\"8\\\" nameend=\\\"c8\\\" namest=\\\"c1\\\"\\u003e \\u003cp\\u003elymphovascular invasion 0.087\\u003c/p\\u003e \\u003c/td\\u003e \\u003c/tr\\u003e \\u003ctr\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c1\\\"\\u003e \\u003cp\\u003eNegative\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c2\\\"\\u003e \\u003cp\\u003e3\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c3\\\"\\u003e \\u003cp\\u003e7.9\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c4\\\"\\u003e \\u003cp\\u003e3\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c5\\\"\\u003e \\u003cp\\u003e100\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c6\\\"\\u003e \\u003cp\\u003e0\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c7\\\"\\u003e \\u003cp\\u003e0\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c8\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e \\u003c/tr\\u003e \\u003ctr\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c1\\\"\\u003e \\u003cp\\u003ePositive\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c2\\\"\\u003e \\u003cp\\u003e35\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c3\\\"\\u003e \\u003cp\\u003e92.1\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c4\\\"\\u003e \\u003cp\\u003e17\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c5\\\"\\u003e \\u003cp\\u003e48.6\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c6\\\"\\u003e \\u003cp\\u003e18\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c7\\\"\\u003e \\u003cp\\u003e51.4\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c8\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e \\u003c/tr\\u003e \\u003c/tbody\\u003e \\u003c/colgroup\\u003e \\u003c/table\\u003e\\u003c/div\\u003e \\u003c/p\\u003e \\u003c/div\\u003e \\u003cdiv id=\\\"Sec4\\\" class=\\\"Section2\\\"\\u003e \\u003ch2\\u003e2.3. SF3B4 knockdown suppressed cancer cell proliferation and increased apoptosis rate in vitro\\u003c/h2\\u003e \\u003cp\\u003eTo determine the biological functions of SF3B4 in GC, Stable SF3B4 knockdowns were established in the AGS and MKN-45 cell linesusing a lentiviral delivery system. The downregulation of SF3B4 has been confirmed through mRNA and protein in this cell line (Fig.\\u0026nbsp;\\u003cspan refid=\\\"Fig3\\\" class=\\\"InternalRef\\\"\\u003e3\\u003c/span\\u003ea). SF3B4 mRNA expression were significantly decreased after lentivirus infection in AGS and MKN45cells compared with control group (P\\u0026thinsp;\\u0026lt;\\u0026thinsp;0.05), and the knockdown efficiency reached 80.0% and 89.1% in AGS cells and MKN45 cells reached separately.\\u003c/p\\u003e \\u003cp\\u003e \\u003c/p\\u003e \\u003cp\\u003eSF3B4 knockdown suppressed GC cell proliferation, as measured via the CCK-8 assay, colony formation assay, and 5-ethynyl-20- deoxyuridine(BrdU) assay. The OD450 value in the CCK-8 assay demonstrated that SF3B4 knockdown could inhibit proliferation in AGS and MKN45 cells comparing with the control group (Fig.\\u0026nbsp;\\u003cspan refid=\\\"Fig3\\\" class=\\\"InternalRef\\\"\\u003e3\\u003c/span\\u003eb). The ratio of OD450(OD450/fold) was also calculated. The value of OD450/fold of the control group on the fifth day in AGS cells increased by 7.9842 times, while the value of OD450/fold ofthe shSF3B4 group increased by only 3.8244 times which were significantly decreased(Fig \\u003cspan refid=\\\"MOESM1\\\" class=\\\"InternalRef\\\"\\u003eS1\\u003c/span\\u003ea). Similar results could be seen in MKN45 cells (Fig \\u003cspan refid=\\\"MOESM1\\\" class=\\\"InternalRef\\\"\\u003eS1\\u003c/span\\u003eb).The colony formation assay also produced similar results. The number of clone was obviously decreased after knocking down SF3B4 compared with the control group(Fig.\\u0026nbsp;\\u003cspan refid=\\\"Fig3\\\" class=\\\"InternalRef\\\"\\u003e3\\u003c/span\\u003ec). Results of BrdU assays further confirmed that SF3B4 knockdown significantly inhibited the cells proliferation rates(Fig.\\u0026nbsp;\\u003cspan refid=\\\"Fig3\\\" class=\\\"InternalRef\\\"\\u003e3\\u003c/span\\u003ed).\\u003c/p\\u003e \\u003cp\\u003eTo provide additional evidence for the impact of SF3B4 suppression on gastric cancer cell apoptosis, we employed Annexin V-APC staining and subsequent flow cytometry analysis (Fig.\\u0026nbsp;\\u003cspan refid=\\\"Fig3\\\" class=\\\"InternalRef\\\"\\u003e3\\u003c/span\\u003ee). There was a significant increase in apoptosis rate in shSF3B4 treated AGS cells compared to those in the control group (10.57%\\u0026plusmn;0.54% vs. 2.44%\\u0026plusmn;0.16%) (P\\u0026thinsp;\\u0026lt;\\u0026thinsp;0.01). Similar results were also obtained in shSF3B4-treated MKN45 cells. These results suggest that the knockdown of SF3B4 expression can inhibit GC cell proliferation in vitro.\\u003c/p\\u003e \\u003c/div\\u003e \\u003cdiv id=\\\"Sec5\\\" class=\\\"Section2\\\"\\u003e \\u003ch2\\u003e2.4. SF3B4 knockdown inhibited tumorigenicity of human gastric cancer cells in vivo\\u003c/h2\\u003e \\u003cp\\u003eTo investigate the potential involvement of SF3B4 in gastric cancer cell proliferation in vivo, we established xenograft models in mice through subcutaneous injection of MKN-45 cells, with or without SF3B4 knockdown. Figure\\u0026nbsp;\\u003cspan refid=\\\"Fig3\\\" class=\\\"InternalRef\\\"\\u003e3\\u003c/span\\u003ef demonstrated the significantly suppressed tumor growth of GC in mice of the shSF3B4 group compared with that of shCtrl group. Tumor volume and growth rates in the shSF3B4-MKN-45 injected group were significantly lower than in the shCtrl group (Fig.\\u0026nbsp;\\u003cspan refid=\\\"Fig3\\\" class=\\\"InternalRef\\\"\\u003e3\\u003c/span\\u003eh). The fluorescence intensity was also detected on day 19. The fluorescence intensity of shSF3B4-MKN-45 cells was significantly less than the control group (Fig.\\u0026nbsp;\\u003cspan refid=\\\"Fig3\\\" class=\\\"InternalRef\\\"\\u003e3\\u003c/span\\u003eg). In addition, tumor weights were determined for the two groups, and the weights of the shCtrl group had a dramatically higher weight than the shSF3B4 group(Fig.\\u0026nbsp;\\u003cspan refid=\\\"Fig3\\\" class=\\\"InternalRef\\\"\\u003e3\\u003c/span\\u003ei). These results suggested that knockdown of SF3B4 expression could inhibit the tumorigenicity of human gastric cancer cells in vivo.\\u003c/p\\u003e \\u003c/div\\u003e \\u003cdiv id=\\\"Sec6\\\" class=\\\"Section2\\\"\\u003e \\u003ch2\\u003e2.5 The exploration of the downstream mechanism underlying the regulation of GC by SF3B4\\u003c/h2\\u003e \\u003cp\\u003eThe transcriptome-wide investigation was performed using RNA sequencing to better unravel the downstream mechanism behind the suppression of GC by SF3B4 knockdown. We identified 105 differentially expressed genes between shCtrl and shSF3B4-transfected cells were, including 64 upregulated and 41 downregulated genes. Subsequently, we performed Ingenuity Pathway Analysis (IPA) to identify the enrichment of genes induced by SF3B4 knockdown. The Necroptosis Signaling Pathway, Senescence Pathway, Migration of tumor cells and Autophagy were inhibited by SF3B4 knockdown, meanwhile, Mitosis and Cell cycle progression were activated(Fig.\\u0026nbsp;\\u003cspan refid=\\\"Fig4\\\" class=\\\"InternalRef\\\"\\u003e4\\u003c/span\\u003ea). The genes that were significantly enriched in inhibited pathways were further analyzed(Fig.\\u0026nbsp;\\u003cspan refid=\\\"Fig4\\\" class=\\\"InternalRef\\\"\\u003e4\\u003c/span\\u003eb). Real-time PCR was performed to detect the expression of mRNA of 8 Genes which areinvolved in multiple inhibited pathways, and the results showed that the 8 genes were downregulated after the SF3B4 knockdown (Fig.\\u0026nbsp;\\u003cspan refid=\\\"Fig4\\\" class=\\\"InternalRef\\\"\\u003e4\\u003c/span\\u003ec). The 4 most significantly downregulated candidates, including FOXO3, VDAC1, DNAJA3, and DRAM2, were then selected for WB verification in AGS cells (Fig.\\u0026nbsp;\\u003cspan refid=\\\"Fig4\\\" class=\\\"InternalRef\\\"\\u003e4\\u003c/span\\u003ed). VDAC1 was significantly reduced in SF3B4 knockdown group compared to control. Furthermore, the expression profiling data collected from TCGA datasets revealed that VDAC1 mRNA expression was upregulated in GC tissues comparison with normal tissues (Fig.\\u0026nbsp;\\u003cspan refid=\\\"Fig4\\\" class=\\\"InternalRef\\\"\\u003e4\\u003c/span\\u003ee).\\u003c/p\\u003e \\u003cp\\u003e \\u003c/p\\u003e \\u003c/div\\u003e \\u003cdiv id=\\\"Sec7\\\" class=\\\"Section2\\\"\\u003e \\u003ch2\\u003e2.6. Overexpression of VDAC1 alleviated the inhibition effect of SF3B4 knockdown on GC\\u003c/h2\\u003e \\u003cp\\u003eIn order to verify that SF3B4 executes its regulation effects on GC through VDAC1, functional recovery study were performed to verify their synergistic effects on the functions of GC cells. First, gastric cancer cells AGS were infected with shSF3B4 lentivirus to knockdown SF3B4 (KD), then infected with VDAC1 overexpression lentivirus tomake them overexpression (OE), The efficiencies of transfection were evaluated by fluorescence imaging(Fig.\\u0026nbsp;\\u003cspan refid=\\\"Fig5\\\" class=\\\"InternalRef\\\"\\u003e5\\u003c/span\\u003ea). Marked downregulation and upregulation of SF3B4 and VDAC1 in KD\\u0026thinsp;+\\u0026thinsp;NC and KD\\u0026thinsp;+\\u0026thinsp;OE groups, respectively, were confirmed at both the mRNA and protein levels compared with the NC\\u0026thinsp;+\\u0026thinsp;NCgroup(Fig.\\u0026nbsp;\\u003cspan refid=\\\"Fig5\\\" class=\\\"InternalRef\\\"\\u003e5\\u003c/span\\u003eb and Fig.\\u0026nbsp;\\u003cspan refid=\\\"Fig5\\\" class=\\\"InternalRef\\\"\\u003e5\\u003c/span\\u003ec). we did CCK-8 assay to study the recovery function of over expression of VDAC1 to AGS cells. Compared with NC\\u0026thinsp;+\\u0026thinsp;NC group (the OD450 value at the fifth day was 1.642), the cell viability of KD\\u0026thinsp;+\\u0026thinsp;NC group decreased (the OD450 value at the fifth day was 0.620, P\\u0026thinsp;\\u0026lt;\\u0026thinsp;0.05), which was consistent with the previous results. However, compared with KD\\u0026thinsp;+\\u0026thinsp;NC group, the cell viability of KD\\u0026thinsp;+\\u0026thinsp;OE group increased (the OD450 value at the fifth day was 1.287, P\\u0026thinsp;\\u0026lt;\\u0026thinsp;0.05), indicating that VDAC1 gene overexpression restored the proliferation function of SF3B4 knockdown(Fig.\\u0026nbsp;\\u003cspan refid=\\\"Fig5\\\" class=\\\"InternalRef\\\"\\u003e5\\u003c/span\\u003ed). Moreover, colony formation data revealed that, compared with NC\\u0026thinsp;+\\u0026thinsp;NC group, the cloning ability of KD\\u0026thinsp;+\\u0026thinsp;NC group decreased significantly, which was consistent with the previous results (P\\u0026thinsp;\\u0026lt;\\u0026thinsp;0.05); However, compared with KD\\u0026thinsp;+\\u0026thinsp;NC group, after over expression VDAC1, in KD\\u0026thinsp;+\\u0026thinsp;OE groups, the clone number significantly increased, so the cloning ability of AGC cells was recovered (P\\u0026thinsp;\\u0026lt;\\u0026thinsp;0.05)(Fig.\\u0026nbsp;\\u003cspan refid=\\\"Fig5\\\" class=\\\"InternalRef\\\"\\u003e5\\u003c/span\\u003ee).\\u003c/p\\u003e \\u003cp\\u003e \\u003c/p\\u003e \\u003cp\\u003eFinally, to clarify the detailed mechanism of recovery of cellular function by VDAC1 in gastric cancer cell lines, we did western blot to show expression of autophagy-related genes (ATG7, ATG5, ATG9A, ATG12) when knocking down SF3B4 (KD) and overexpression VDAC1(OE). As shown in Fig.\\u0026nbsp;\\u003cspan refid=\\\"Fig5\\\" class=\\\"InternalRef\\\"\\u003e5\\u003c/span\\u003ef, compared with NC\\u0026thinsp;+\\u0026thinsp;NC group, the expression of ATG7, ATG5, ATG9A, ATG12 increased in KD\\u0026thinsp;+\\u0026thinsp;NC group, However, when overexpression VDAC1, the expression of ATG7, ATG5, ATG9A, ATG12 were significantly decreased, which demonstrated overexpression VDAC1 also recoverythe expression levels of ATG5, ATG7, ATG9A and ATG12 in SF3B4 knockdown. These results suggest a potential regulatory role of SF3B4 in VDAC1-mediated dysregulated autophagy, thereby promoting tumorigenesis of gastric cancer.\\u003c/p\\u003e \\u003c/div\\u003e\"},{\"header\":\"3. Discussion\",\"content\":\"\\u003cp\\u003eThis study screened the candidate gene SF3B4 by high-throughput Tandem Mass Tag analysis (TMT) and High-content screening. Then, IHC analysis of 38 GC tissues and adjacent normal tissues confirmed the upregulation of SF3B4 in GC. The expression profiling data collected from TCGA datasets also supported the comparatively high expression of SF3B4 in GC. By constructing SF3B4 knockdown cell models based on AGS and MKN-45 cell lines, we investigated the in vitro effects of endogenic SF3B4 on GC development and progression. Keeping with the potential tumor promotion effect of SF3B4 indicated by the tissue detection, the knockdown of SF3B4 inhibited the cell and colony growth and promoted cell apoptosis. Moreover, the suppression of GC tumor growth by SF3B4 knockdown was further demonstrated by the mice xenograft model in vivo.These results indicated that SF3B4 plays a critical role in gastric cancer initiation and deserve further study.\\u003c/p\\u003e \\u003cp\\u003eSF3B4 was originally reported to be a core subunit of the metazoan SF3b complex, which is integral to U2-type spliceosomes[\\u003cspan citationid=\\\"CR16\\\" class=\\\"CitationRef\\\"\\u003e16\\u003c/span\\u003e, \\u003cspan citationid=\\\"CR17\\\" class=\\\"CitationRef\\\"\\u003e17\\u003c/span\\u003e]. In humans, SF3B4 interacts with another spliceosome component SF3b145, forming a protein complex which binds U2 snRNP to pre-mRNA branch sites[\\u003cspan citationid=\\\"CR18\\\" class=\\\"CitationRef\\\"\\u003e18\\u003c/span\\u003e, \\u003cspan citationid=\\\"CR19\\\" class=\\\"CitationRef\\\"\\u003e19\\u003c/span\\u003e]. Meanwhile, It also participates in transcription, translation, and cellular signaling pathways[\\u003cspan citationid=\\\"CR20\\\" class=\\\"CitationRef\\\"\\u003e20\\u003c/span\\u003e, \\u003cspan citationid=\\\"CR21\\\" class=\\\"CitationRef\\\"\\u003e21\\u003c/span\\u003e].Moreover, SF3B4 regulates cell differentiation, cell cycle, and immune deficiency[\\u003cspan additionalcitationids=\\\"CR23\\\" citationid=\\\"CR22\\\" class=\\\"CitationRef\\\"\\u003e22\\u003c/span\\u003e\\u0026ndash;\\u003cspan citationid=\\\"CR24\\\" class=\\\"CitationRef\\\"\\u003e24\\u003c/span\\u003e]. In 2012, Bernier \\u003cem\\u003eet al.\\u003c/em\\u003ereported that heterozygosity for a mutation in the SF3B4-gene (1q21.2) caused Nagersyndrome(NS)[\\u003cspan citationid=\\\"CR17\\\" class=\\\"CitationRef\\\"\\u003e17\\u003c/span\\u003e]. Later studies found SF3B4 encodes a spliceosome-associated protein (SAP49), a component of a spliceosomal complex is thought tobe involved in thes plicingof genes associated with limb and craniofacial development[\\u003cspan citationid=\\\"CR25\\\" class=\\\"CitationRef\\\"\\u003e25\\u003c/span\\u003e, \\u003cspan citationid=\\\"CR26\\\" class=\\\"CitationRef\\\"\\u003e26\\u003c/span\\u003e]. In 2015, Xu\\u003cem\\u003eet al.\\u003c/em\\u003e conducteda meta-analysis of publicly available microarray Gene Expression Omnibus datasets about hepatocellular carcinoma (HCC), and the finding revealed that SF3B4 was generally overexpressed in HCC[\\u003cspan citationid=\\\"CR27\\\" class=\\\"CitationRef\\\"\\u003e27\\u003c/span\\u003e]. Subsequently, T. Iguchi and colleagues verified that SF3B4 expression was significantly higher in cancer tissues than noncancer tissues and positively correlated with SF3B4 DNA copy number in 2016[\\u003cspan citationid=\\\"CR28\\\" class=\\\"CitationRef\\\"\\u003e28\\u003c/span\\u003e].Mounting evidence indicates that the loss- or gain of function mutation in SF3B4 may contribute to the pathogenesis of various tumors, including liver cancer, pancreatic cancer, esophageal squamous cell carcinoma, and so on [\\u003cspan additionalcitationids=\\\"CR30\\\" citationid=\\\"CR29\\\" class=\\\"CitationRef\\\"\\u003e29\\u003c/span\\u003e\\u0026ndash;\\u003cspan citationid=\\\"CR31\\\" class=\\\"CitationRef\\\"\\u003e31\\u003c/span\\u003e]. However, the role of SF3B4 in regulating the behavior of gastric cancer has not yet been elucidated. Our study examined the involvement of SF3B4 in gastric cancer and demonstrated, for the first time, that SF3B4 is also upregulated in gastric cancer, knocking down SF3B4 could inhibit cellgrowth both in vitro and in vivo, also could induced the apoptosis.\\u003c/p\\u003e \\u003cp\\u003eAn encouraging finding from this study is thatweshowed for the first time that VDAC1 might be a downstream factor of SF3B4. We used Ingenuity Pathway Analysis (IPA) to find the main downstream regulators affected by SF3B4. The result revealed VDAC1 is a protein that plays a crucial role in autophagy and necroptosis signaling pathways, further experimental confirmed that VDAC1exhibited a notable reduction at both the mRNA and protein levels in the shSF3B4 group. Moreover, the data analysis obtained from TCGA and recovery study comfirmed VDAC1 as a potential downstream regulator of SF3B4.\\u003c/p\\u003e \\u003cp\\u003eVDAC1 is an isoform of Voltage-dependent anion-selective channel protein, which regulates energy production, mitochondrial oxidase stress, calcium transport, substance metabolism, apoptosis, and autophagy[\\u003cspan additionalcitationids=\\\"CR33 CR34\\\" citationid=\\\"CR32\\\" class=\\\"CitationRef\\\"\\u003e32\\u003c/span\\u003e\\u0026ndash;\\u003cspan citationid=\\\"CR35\\\" class=\\\"CitationRef\\\"\\u003e35\\u003c/span\\u003e]. VDAC1 was found to be abnormally expressed and participate in tumorigenesis or progression in various ways[\\u003cspan citationid=\\\"CR36\\\" class=\\\"CitationRef\\\"\\u003e36\\u003c/span\\u003e, \\u003cspan citationid=\\\"CR37\\\" class=\\\"CitationRef\\\"\\u003e37\\u003c/span\\u003e]. For example, the study of S.K. Pandey \\u003cem\\u003eet al.\\u003c/em\\u003e showed VDAC1 was overexpressed in mesothelioma patients, and silencing VDAC1 expression caused metabolism reprogramming to inhibit tumor growth[\\u003cspan citationid=\\\"CR38\\\" class=\\\"CitationRef\\\"\\u003e38\\u003c/span\\u003e]. Research on breast cancer demonstrated VDAC1 and Sarco/Endoplasmic Reticulum ATPase3 (SERCA3) mediate progesterone-triggered Ca2\\u0026thinsp;+\\u0026thinsp;signaling to modulate cell proliferation and cell death[\\u003cspan citationid=\\\"CR39\\\" class=\\\"CitationRef\\\"\\u003e39\\u003c/span\\u003e]. Moreover, VDAC1 was also reported to be implicated in GC. The work of W. Gao\\u003cem\\u003eet al.\\u003c/em\\u003e suggested VDAC1 increased in mitochondria of GC tissues than in normal adjacent tissues, and VDAC1 was a promising candidate for future biomarker development for gastric cancer[\\u003cspan citationid=\\\"CR40\\\" class=\\\"CitationRef\\\"\\u003e40\\u003c/span\\u003e]. In this study, the inhibition effect of VDAC1 knockdown on GC, similar to SF3B4, was also demonstrated by detecting cell proliferation and colony formation. More importantly, the inhibition of GC by knockdown of SF3B4 could be impaired to some extent by simultaneous overexpressof VDAC1, suggesting that SF3B4 may regulate the development and progression of GC through influencing VDAC1. In addition, this study also found that SF3B4 regulating VDAC1 leading to gastric carcinogenesis may be related to autophagy dysregulation(Fig S2).\\u003c/p\\u003e \\u003cp\\u003eIn summary, the experimental data in this study indicated that SF3B4 was upregulated in GC tissues. In vitro and in vivo detection demonstrated that SF3B4 acts as a tumor promoter in GC, probably through the regulation of VDAC1. To the best of our knowledge, this is the initial study addressing the contribution of SF3B4 to the advancement and progression of GC. However, further investigation is necessary to elucidate how SF3B4 and VDAC1 interact to promote the proliferation of gastric cancer cells.\\u003c/p\\u003e\"},{\"header\":\"4. Materials and Methods\",\"content\":\"\\u003cdiv id=\\\"Sec10\\\" class=\\\"Section2\\\"\\u003e \\u003ch2\\u003e4.1. Clinical samples\\u003c/h2\\u003e \\u003cp\\u003eGC and adjacent normal tissues were collected from patients with GC who had undergone surgical resection at the Department of Surgery, Gansu provincial Hospital (Gansu, China). H\\u0026amp;E staining confirmed the histopathology features of clinical samples. This study has been performed in accordance with Declaration of Helsinki. Ethical approval for the study was granted on 9th March, 2021 by he Medical Ethics Committee of the Gansu Provincial Hospital (No. 2021-079) and informed consent was obtained from the patients.\\u003c/p\\u003e \\u003c/div\\u003e \\u003cdiv id=\\\"Sec11\\\" class=\\\"Section2\\\"\\u003e \\u003ch2\\u003e4.2. TMT proteomics analysis\\u003c/h2\\u003e \\u003cp\\u003eTo perform the differential proteomic experiments, five GC tissue samples and matching adjacent normal tissues were obtained for the TMT-labeled quantitative proteomics analysis. After protein extraction and digestion using SDT lysis and FASP method and the quality control of the protein samples, the samples were labeled with TMT in accordance with the manufacturer's protocol(TMT10plex label reagent set, ThermoScientific, Waltham, MA, America). The proteomics analysis was performed using a Qexactiveplus mass spectrometer (Thermo, USA) by Genechem (Shanghai, China). The original map files (.raw files) generated by Q Exactivepluswere converted into mgf files by Proteome Discoverer 2.1 (Thermo Fisher Scientific, USA) and submitted to the MASCOT2.6 server for database retrieval through the software's built-in tools. In this study, we used Uniprot_HomoSapiens_20386_20180905 for our database search. The reliable protein screening criterion was peptide FDR\\u0026thinsp;\\u0026le;\\u0026thinsp;0.01. Student's t-test was performed to identify the significant difference in proteins in the two groups. A \\u003cem\\u003eP\\u003c/em\\u003e-value\\u0026thinsp;\\u0026lt;\\u0026thinsp;0.05 and fold change\\u0026thinsp;\\u0026gt;\\u0026thinsp;1.2 were considered significant.\\u003c/p\\u003e \\u003c/div\\u003e \\u003cdiv id=\\\"Sec12\\\" class=\\\"Section2\\\"\\u003e \\u003ch2\\u003e4.3. Cell lines and culture\\u003c/h2\\u003e \\u003cp\\u003eThe human gastric cancer cell lines AGS, HGC-27, KATO III, NCL-N87 and MKN-45 were purchased from Shanghai Genechem Co., LTD.ATCC previously authenticated the three cell lines viaShort Tandem Repeat (STR) typing. All cells were grown in a complete medium. Cell cultures were maintained at 37\\u0026deg;C in a 5% CO2 incubator. In vitro assays were performed at 70\\u0026ndash;80% cell density.\\u003c/p\\u003e \\u003c/div\\u003e \\u003cdiv id=\\\"Sec13\\\" class=\\\"Section2\\\"\\u003e \\u003ch2\\u003e4.4. Plasmids and shRNA\\u003c/h2\\u003e \\u003cp\\u003eThe GV344 lentiviral vector system, pHelper 1.0 vector, pHelper 2.0 vector, and 293T cells were used to produce lentiviruses. Human SF3B4-targeting shRNA (targeting sequence: 5\\u0026rsquo;-CCCTGAGATTGATGAGAAGTT-3') and control insert sequence (5\\u0026rsquo;-TTCTCCGAACGTGTCACGT-3') were designed and cloned into lentiviral vector GV344. Transfection was performed in AGSand MKN-45 cells (3\\u0026ndash;5\\u0026times;10\\u003csup\\u003e4\\u003c/sup\\u003e/mL). shRNAs were designed and synthesized by Genechem (Shanghai, China). Moreover, the full length of VDAC1 was cloned into lentivirus vector pGC-FU-CMV-3FLAG-EF1-mCherry-T2A-puromycin (GV661) (Shanghai Genechem Co., LTD) for constructing VDAC1 over-expressed cells.\\u003c/p\\u003e \\u003c/div\\u003e \\u003cdiv id=\\\"Sec14\\\" class=\\\"Section2\\\"\\u003e \\u003ch2\\u003e4.5. High-content screening and cell growth curve analysis.\\u003c/h2\\u003e \\u003cp\\u003eAGS cells were transfected with ashSF3B4 or shCtrl lentivirus seeded into 96-well plates. The expression of green fluorescent protein (GFP) was observed using a fluorescence microscope. Cells were collected for further experiments when they reached 80% confluence. Cellimages were captured using a Celigo image cytometer (NexcelomBioscience, Lawrence, MA, USA) once a day for 5 days. By adjusting the input parameters, cells (2000 cells per well) could be quantified by measuring the green fluorescence signal in each well. The number of cells at each time point was compared with the cell count on day 1 to obtain a cell proliferation ratio at the corresponding time point for each experimental group, the growth curve was plotted, and the fold change in proliferation was calculated. The cell proliferation ratio was calculated as follows: fold change (shCtrl vs. experimental group)\\u0026thinsp;=\\u0026thinsp;proliferation ratio on day 5 for the shCtrl group/proliferation ratio on day 5 for the experimental group. A fold-change value equal to or more than two indicated that cell proliferation had slowed down sufficiently.\\u003c/p\\u003e \\u003c/div\\u003e \\u003cdiv id=\\\"Sec15\\\" class=\\\"Section2\\\"\\u003e \\u003ch2\\u003e4.6. Quantitative RT-PCR\\u003c/h2\\u003e \\u003cp\\u003eTotal RNA was isolated from each sample using Trizol(Shanghai Pufei Biotech Co., Ltd, China) according to the manufacturer's protocols. The concentration and purity of the total RNA were estimated using NanoDrop 2000 (ThermoFisher, USA). cDNA was synthesized using the Promega M-MLV Reagent kit (Promega Beijing, China), following the manufacturer's instructions. Quantitative RT-PCR was performed using LightCycler\\u0026reg; 480 II (Roche, Switzerland) according to the manufacturer's instructions, using GAPDH or β-Actin was as endogenous controls for mRNAs. Primers used for qRT-PCR are listed in Table \\u003cspan refid=\\\"MOESM1\\\" class=\\\"InternalRef\\\"\\u003eS1\\u003c/span\\u003e.\\u003c/p\\u003e \\u003c/div\\u003e \\u003cdiv id=\\\"Sec16\\\" class=\\\"Section2\\\"\\u003e \\u003ch2\\u003e4.7. Cell proliferation assays\\u003c/h2\\u003e \\u003cp\\u003eTransfected AGS and MKN45 cells were incubated in 96-well plates for 24, 48, 72, 96, and 120h, and Cell Counting Kit-8 (Dojindo Laboratories, Japan) was applied to evaluate the ability of cell proliferation. Colony formation assays were performed to detect AGS and MKN45 cell cloning Capability after transfected with shSF3B4 or shCtrl. The transfected cells were seeded into a 6-well cell culture plate in 1x10\\u003csup\\u003e3\\u003c/sup\\u003e/well. After 8 days of culture, the cells were stained by crystal violet solution (Sangon Biotech, China), and Colonies were graphed with a digital camera and counted. BrdU assays were performed using a BrdU cell proliferation assay kit (Roche) according to the manufacturer's protocol to assess cell proliferation after cell transfection.\\u003c/p\\u003e \\u003c/div\\u003e \\u003cdiv id=\\\"Sec17\\\" class=\\\"Section2\\\"\\u003e \\u003ch2\\u003e4.8. Apoptosis assay\\u003c/h2\\u003e \\u003cp\\u003eIn transfected AGS and MKN45 cells grown to 80% confluence, the suspension cells were collected, and adherent cells on the dish were digested by trypsin into single cells. We collected all cells for apoptosis detection using Annexin V-APC apoptosis detection kit (eBioscience, USA) and flow cytometry analysis (BD, USA).\\u003c/p\\u003e \\u003c/div\\u003e \\u003cdiv id=\\\"Sec18\\\" class=\\\"Section2\\\"\\u003e \\u003ch2\\u003e4.9. Western blot analysis\\u003c/h2\\u003e \\u003cp\\u003eA RIPA lysis buffer (Beyotime Institute of Biotechnology) containing protease inhibitors was used for lysing cells on ice as directed by the manufacturer. Detecting protein concentrations was performed with a BCA Protein Assay kit (Beyotime Institute of Biotechnology). The total cellular proteins were isolated using SDS-PAGE (10%) and then transferred to PVDF membranes. The membranes were blocked with TBST solution containing 5% non-fat milk for 60 min at room temperature and then incubated with primaryantibodies, including Anti-SF3B4 (1:500), anti-FOXO3(1:1000), anti-VDAC1(1:1000), anti-DNAJA3(1:500), anti-DRAM2 (1:500),anti- ATG7 (1:10000), anti-ATG5 (1:3000), anti- ATG9A (1:1000) and anti- ATG12 (1:1000)at4\\u0026deg;C overnight. After washing, the membranes were incubated with secondary antibodies. All blots were developed with 20X LumiGLO\\u0026reg; Reagent and 20x peroxide (#7003, Cell Signaling Technology, Inc). Visualized images were obtained using a Tanon4600 detector (Shanghai, China).\\u003c/p\\u003e \\u003c/div\\u003e \\u003cdiv id=\\\"Sec19\\\" class=\\\"Section2\\\"\\u003e \\u003ch2\\u003e4.10. Immunohistochemistry (IHC)\\u003c/h2\\u003e \\u003cp\\u003eWe obtained 38 pairs of gastric cancer and adjacent normal tissue specimens from surgical resections performed at the Gansu provincial hospital between May 2018 and May 2020. The Medical Ethics Committee of the Gansu provincial Hospital approved this study. The sections were deparaffinized, heat-mediated antigen repair was performed using citrate buffer, blocked by peroxidase blocking solution (maxim, Biotechnology, Fuzhou, China) for 10 min at room temperature, and treated by normal non-immunized animal serum according to the manufacturer's protocol. Next, the staining of the tissue sections by diluted primary anti-SF3B4 or anti-VDAC1 was performed at 4\\u0026deg;C overnight. Slides were washed with PBS and incubated with biotinylated secondary antibody (maxim, Biotechnology, Fuzhou, China) per the manufacturer's instructions for 1h.Tissue sections were washed, stained with 3, 3-diaminobenzidine (DAB), counterstained with hematoxylin, dehydrated with ethanol, and mounted with resin. Images were captured using NanoZoomer 2.0-HT (Hamamatsu, Japan). The SF3B4 expression levels in each spot were assessed by the immunoreactive scores (IRS), which were calculated by multiplying the score of intensity and the extent score. Each staining intensity was scored with a score of 0\\u0026ndash;3 (0\\u0026thinsp;=\\u0026thinsp;negative;1\\u0026thinsp;=\\u0026thinsp;weak; 2\\u0026thinsp;=\\u0026thinsp;moderate; 3\\u0026thinsp;=\\u0026thinsp;strong). The extent of positively stained cells was also scored into 5 categories: 0(0%), 1 (1\\u0026ndash;25%), 2 (26\\u0026ndash;50%), 3 (51\\u0026ndash;75%), and 4 (76\\u0026ndash;100%). Using the IRS, staining patterns were classified as low (IRS: 0\\u0026ndash;6) and high (IRS: 8\\u0026ndash;12).\\u003c/p\\u003e \\u003c/div\\u003e \\u003cdiv id=\\\"Sec20\\\" class=\\\"Section2\\\"\\u003e \\u003ch2\\u003e4.11. In vivo tumorigenicity assays\\u003c/h2\\u003e \\u003cp\\u003e4\\u0026ndash;6-weeks female nude BALB/c mice were purchased from Shanghai Lingchang Biological Technology Co., Ltd. MKN-45 cells were transfected with shSF3B4 and shCtrl, respectively. Transfected MKN45 cells (4\\u0026times;10\\u003csup\\u003e6\\u003c/sup\\u003e) were subcutaneously injected into the right underarm of each mouse (n\\u0026thinsp;=\\u0026thinsp;12). The mice were cultured for 19 days post-injection, and data collection began 7 days post-injection. A measurement of thevolume (V) was made with calipers by measuring the length (L) and width (W) and calculating the volume using the formula V (mm3) =π/6\\u0026times;L\\u0026times;W\\u0026times;W. The volume of tumors was estimated at 7, 10, 14, 17, and 19 days post-injection. Moreover, nineteen days after cell injection, a dose of 10\\u0026micro;L/g of D-luciferin (15 mg/mL, Qcbio, China) was injected and live images were acquired using an in vivo imaging system(Perkin Elmer, America). In the end, mice were sacrificed with pentobarbital sodium injections and their tumors were removed for taking photos and weighting. The animal experiments were complied with the ARRIVE guidelines and the Medical Ethics Committee of the Gansu provincial Hospital approved this study.\\u003c/p\\u003e \\u003c/div\\u003e \\u003cdiv id=\\\"Sec21\\\" class=\\\"Section2\\\"\\u003e \\u003ch2\\u003e4.12. RNA-Seq Analysis\\u003c/h2\\u003e \\u003cp\\u003eThe RNA-sequencing analysis was performed by Genechem (Shanghai, China). Briefly, total RNA was isolated from shSF3B4 and shCtrl-transfected AGS cells using Trizol (Shanghai Pufei Biotech Co., Ltd, China)following the manufacturer's instructions. Purity of RNA was determined by the NanoPhotometer\\u0026reg; spectrophotometer (IMPLEN, CA, USA), and integrity was assessed by the RNA Nano 6000 Assay Kit (Agilent Technologies, CA, USA). Sequencing libraries were constructed using NEBNext\\u0026reg;UltraTMRNA Library Prep Kit for Illumina\\u0026reg; (NEB, USA) according to the manufacturer's instructions, and index codes were added to attribute sequences to each sequencing sample. The clustering of the index-coded samples was performed on a cBotCluster Generation System using TruSeq PE Cluster Kit v3-cBot-HS (Illumia) according to the manufacturer's instructions. A 150 bp paired-end read was generated from the library preparations after cluster generation using an IlluminaNovaseq platform. Differential expression analysis of two groups was performed using the DESeq2 R package (1.16.1), Genes with an adjusted \\u003cem\\u003ep\\u003c/em\\u003e-value\\u0026thinsp;\\u0026lt;\\u0026thinsp;0.05 found by DESeq2 were assigned as differentially expressed genes (DEGs). IPA (Qiagen, Hilden, Germany) was performed using all the DEGs to analyze the enriched functional annotations.\\u003c/p\\u003e \\u003c/div\\u003e \\u003cdiv id=\\\"Sec22\\\" class=\\\"Section2\\\"\\u003e \\u003ch2\\u003e4.13. Statistical analysis\\u003c/h2\\u003e \\u003cp\\u003eResults for continuous variables are presented as means\\u0026thinsp;\\u0026plusmn;\\u0026thinsp;sd unless otherwise stated. Student's t-Test and Chi-square test were used during the data analysis. The 2\\u003csup\\u003e\\u0026minus;ΔΔCt\\u003c/sup\\u003e method was used during the qPCR assays. SPSS 19.0 was used for statistics, and \\u003cem\\u003ep\\u003c/em\\u003e\\u0026thinsp;\\u0026lt;\\u0026thinsp;0.05 was considered significant. GraphPad Prism 6.04 was used to generate graphs.\\u003c/p\\u003e \\u003c/div\\u003e\"},{\"header\":\"Declarations\",\"content\":\"\\u003cp\\u003e\\u003cstrong\\u003eAcknowledgments\\u0026nbsp;\\u003c/strong\\u003e\\u003c/p\\u003e\\n\\u003cp\\u003eNot applicable\\u003c/p\\u003e\\n\\u003cp\\u003e\\u003cstrong\\u003eFunding\\u003c/strong\\u003e\\u003c/p\\u003e\\n\\u003cp\\u003eThis work was funded by the science and technology project of Chengguan District, Lanzhou City. (Grant No.2021SHFZ0002)and the Scientific Research Cultivation Project of Gansu Provincial Hospital (Grant No. 19SYPYB-25).\\u003c/p\\u003e\\n\\u003cp\\u003e\\u003cstrong\\u003eAuthor contributions\\u003c/strong\\u003e\\u003c/p\\u003e\\n\\u003cp\\u003eKehuYang, Dehong Li and Yan Lu carried out the studies, participated in collecting data, and drafted the manuscript. Li Yan, XingwenYang, Fenghui Zhao and XiaoyanYang performed the statistical analysis and participated in its design. XiumeiYuan and Fugui Lin participated in acquisition, analysis, or interpretation of data and draft the manuscript. All authors read and approved the final manuscript.\\u003c/p\\u003e\\n\\u003cp\\u003e\\u003cstrong\\u003eConflict of Interest\\u003c/strong\\u003e\\u003c/p\\u003e\\n\\u003cp\\u003eThe author(s) declare(s) that there is no conflict of interest regarding the publication of this paper\\u003c/p\\u003e\\n\\u003cp\\u003e\\u003cstrong\\u003eData availability\\u003c/strong\\u003e\\u003c/p\\u003e\\n\\u003cp\\u003eAll data generated or analysed during this study are included in this published article [and its supplementary information files].\\u003c/p\\u003e\"},{\"header\":\"References\",\"content\":\"\\u003col\\u003e\\u003cli\\u003e\\u003cspan\\u003eBray,F,et al. Global cancer statistics 2018: GLOBOCAN estimates of incidence and mortality worldwide for 36 cancers in 185 countries. CA Cancer J Clin. 68,394\\u0026ndash;424(2018).\\u003c/span\\u003e\\u003c/li\\u003e \\u003cli\\u003e\\u003cspan\\u003eYang L, et al. Gastric cancer: Epidemiology, risk factors and prevention strategies. Chin J Cancer Res. 32,695\\u0026ndash;704(2020).\\u003c/span\\u003e\\u003c/li\\u003e \\u003cli\\u003e\\u003cspan\\u003eJiang W, Chen L. Alternative splicing: Human disease and quantitative analysis from high-throughput sequencing. Comput Struct Biotechnol J. 19,183\\u0026thinsp;\\u0026ndash;\\u0026thinsp;95(2021).\\u003c/span\\u003e\\u003c/li\\u003e \\u003cli\\u003e\\u003cspan\\u003eUle J, Blencowe BJ. Alternative Splicing Regulatory Networks: Functions, Mechanisms, and Evolution. Mol Cell.76,329\\u0026thinsp;\\u0026ndash;\\u0026thinsp;45(2019).\\u003c/span\\u003e\\u003c/li\\u003e \\u003cli\\u003e\\u003cspan\\u003eLee Y, Rio DC. Mechanisms and Regulation of Alternative Pre-mRNA Splicing. Annu Rev Biochem.84,291\\u0026ndash;323(2015).\\u003c/span\\u003e\\u003c/li\\u003e \\u003cli\\u003e\\u003cspan\\u003eYamada T, et al. Heterozygous mutation of the splicing factor Sf3b4 affects development of the axial skeleton and forebrain in mouse. Dev Dyn.;249,622\\u0026thinsp;\\u0026ndash;\\u0026thinsp;35(2020).\\u003c/span\\u003e\\u003c/li\\u003e \\u003cli\\u003e\\u003cspan\\u003eBrosi R, Hauri HP, Kr\\u0026auml;mer A. Separation of splicing factor SF3 into two components and purification of SF3a activity. J Biol Chem.268:17640\\u0026ndash;6(1993).\\u003c/span\\u003e\\u003c/li\\u003e \\u003cli\\u003e\\u003cspan\\u003eWill CL, et al. Characterization of novel SF3b and 17S U2 snRNP proteins, including a human Prp5p homologue and an SF3b DEAD-box protein. EMBO J.21,4978\\u0026ndash;88(2002).\\u003c/span\\u003e\\u003c/li\\u003e \\u003cli\\u003e\\u003cspan\\u003eWill CL, L\\u0026uuml;hrmann R. Protein functions in pre-mRNA splicing. Curr Opin Cell Biol.9,320\\u0026ndash;8(1997).\\u003c/span\\u003e\\u003c/li\\u003e \\u003cli\\u003e\\u003cspan\\u003eMatera AG, Wang Z. A day in the life of the spliceosome. Nat Rev Mol Cell Biol .15,108\\u0026thinsp;\\u0026ndash;\\u0026thinsp;21(2014).\\u003c/span\\u003e\\u003c/li\\u003e \\u003cli\\u003e\\u003cspan\\u003eUeno T, et al.Component of splicing factor SF3b plays a key role in translational control of polyribosomes on the endoplasmic reticulum. Proc Natl Acad Sci U S A.116,9340\\u0026ndash;9(2019).\\u003c/span\\u003e\\u003c/li\\u003e \\u003cli\\u003e\\u003cspan\\u003eKim H, et al. SF3B4 Depletion Retards the Growth of A549 Non-Small Cell Lung Cancer Cells via UBE4B-Mediated Regulation of p53/p21 and p27 Expression. Mol Cells.45,18\\u0026ndash;28(2022).\\u003c/span\\u003e\\u003c/li\\u003e \\u003cli\\u003e\\u003cspan\\u003eKidogami S, et al. SF3B4 Plays an Oncogenic Role in Esophageal Squamous Cell Carcinoma. Anticancer Res.40,941\\u0026ndash;6(2020).\\u003c/span\\u003e\\u003c/li\\u003e \\u003cli\\u003e\\u003cspan\\u003eLi Y, et al. The splicing factor SF3B4 drives proliferation and invasion in cervical cancer by regulating SPAG5. 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Genes Dev.10,233\\u0026thinsp;\\u0026ndash;\\u0026thinsp;43(1996).\\u003c/span\\u003e\\u003c/li\\u003e \\u003cli\\u003e\\u003cspan\\u003eChampion-Arnaud P, Reed R. The prespliceosome components SAP 49 and SAP 145 interact in a complex implicated in tethering U2 snRNP to the branch site. Genes Dev.8,1974-83(1994).\\u003c/span\\u003e\\u003c/li\\u003e \\u003cli\\u003e\\u003cspan\\u003eMarques F, et al. Altered mRNA Splicing, Chondrocyte Gene Expression and Abnormal Skeletal Development due to SF3B4 Mutations in Rodriguez Acrofacial Dysostosis. PLoS Genet.12,e1006307(2016).\\u003c/span\\u003e\\u003c/li\\u003e \\u003cli\\u003e\\u003cspan\\u003eDiao Y, et al. SF3B4 promotes ovarian cancer progression by regulating alternative splicing of RAD52. Cell Death Dis.13,179(2022).\\u003c/span\\u003e\\u003c/li\\u003e \\u003cli\\u003e\\u003cspan\\u003eWatanabe H, Shionyu M, Kimura T, Kimata K, Watanabe H. Splicing factor 3b subunit 4 binds BMPR-IA and inhibits osteochondral cell differentiation. 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Silencing VDAC1 to Treat Mesothelioma Cancer: Tumor Reprograming and Altering Tumor Hallmarks. \\u003cem\\u003eBiomolecules.\\u003c/em\\u003e12, \\u003cspan class=\\\"ExternalRef\\\"\\u003e\\u003cspan class=\\\"RefSource\\\"\\u003e10.3390/biom12070895\\u003c/span\\u003e\\u003cspan address=\\\"10.3390/biom12070895\\\" targettype=\\\"DOI\\\" class=\\\"RefTarget\\\"\\u003e\\u003c/span\\u003e\\u003c/span\\u003e(2022)\\u003c/span\\u003e\\u003c/li\\u003e \\u003cli\\u003e\\u003cspan\\u003eAzeez JM, et al. VDAC1 and SERCA3 Mediate Progesterone-Triggered Ca2(+) Signaling in Breast Cancer Cells. J Proteome Res.17,698\\u0026ndash;709(2018).\\u003c/span\\u003e\\u003c/li\\u003e \\u003cli\\u003e\\u003cspan\\u003eGao W, et al. Mitochondrial Proteomics Approach Reveals Voltage-Dependent Anion Channel 1 (VDAC1) as a Potential Biomarker of Gastric Cancer. Cell Physiol Biochem.37,2339\\u0026ndash;54(2015).\\u003c/span\\u003e\\u003c/li\\u003e\\u003c/ol\\u003e\"}],\"fulltextSource\":\"\",\"fullText\":\"\",\"funders\":[],\"hasAdminPriorityOnWorkflow\":false,\"hasManuscriptDocX\":true,\"hasOptedInToPreprint\":true,\"hasPassedJournalQc\":\"\",\"hasAnyPriority\":false,\"hideJournal\":true,\"highlight\":\"\",\"institution\":\"\",\"isAcceptedByJournal\":false,\"isAuthorSuppliedPdf\":false,\"isDeskRejected\":\"\",\"isHiddenFromSearch\":false,\"isInQc\":false,\"isInWorkflow\":false,\"isPdf\":false,\"isPdfUpToDate\":true,\"isWithdrawnOrRetracted\":false,\"journal\":{\"display\":true,\"email\":\"info@researchsquare.com\",\"identity\":\"researchsquare\",\"isNatureJournal\":false,\"hasQc\":true,\"allowDirectSubmit\":true,\"externalIdentity\":\"\",\"sideBox\":\"\",\"snPcode\":\"\",\"submissionUrl\":\"/submission\",\"title\":\"Research Square\",\"twitterHandle\":\"researchsquare\",\"acdcEnabled\":true,\"dfaEnabled\":false,\"editorialSystem\":\"\",\"reportingPortfolio\":\"\",\"inReviewEnabled\":false,\"inReviewRevisionsEnabled\":true},\"keywords\":\"splicing factor 3B subunit 4, voltage-dependent anion channel 1, gastric cancer, proliferation, autophagy\",\"lastPublishedDoi\":\"10.21203/rs.3.rs-4495852/v1\",\"lastPublishedDoiUrl\":\"https://doi.org/10.21203/rs.3.rs-4495852/v1\",\"license\":{\"name\":\"CC BY 4.0\",\"url\":\"https://creativecommons.org/licenses/by/4.0/\"},\"manuscriptAbstract\":\"\\u003cp\\u003eSF3B4 is a novel tumor related gene which is aberrantly expression in some malignant tumors. However, the role and mechanisms of SF3B4 in gastric cancer have not been explored. In this study, TMT-based quantitative proteomics and high content screening (HCS) revealed SF3B4 was strongly associated with GC. Immunohistochemistry revealed SF3B4 was upregulated in human gastric cancer tissues, and high SF3B4 expression was associated with shortened progression-free survival of patients. Further investigations indicated that the knockdown of SF3B4 could inhibit the proliferation and colony formation of GC cells while promoting cell apoptosis. Furthermore, knocking down SF3B4 could also inhibit the tumorigenicity of GC cells in vivo. RNA-sequencing followed by IPA was used to explore downstream of SF3B4 and identified VDAC1 as the potential target. Moreover, our study revealed that VDAC1 overexpression could alleviate the SF3B4 knockdown-induced inhibition of GC. Remarkably, we found for the first time that SF3B4 potentially facilitates the development of gastric cancer by exerting VDAC1-mediated effects on autophagy. SF3B4 promotes GC cell proliferation through regulate VDAC1 and may be a novel therapeutic target for GC.\\u003c/p\\u003e\",\"manuscriptTitle\":\"Splicing Factor 3b Subunit 4 (SF3B4) Promotes Proliferation of Gastric Cancer through Regulation of VDAC1\",\"msid\":\"\",\"msnumber\":\"\",\"nonDraftVersions\":[{\"code\":1,\"date\":\"2024-06-27 18:55:22\",\"doi\":\"10.21203/rs.3.rs-4495852/v1\",\"editorialEvents\":[{\"type\":\"communityComments\",\"content\":0}],\"status\":\"published\",\"journal\":{\"display\":true,\"email\":\"info@researchsquare.com\",\"identity\":\"researchsquare\",\"isNatureJournal\":false,\"hasQc\":true,\"allowDirectSubmit\":true,\"externalIdentity\":\"\",\"sideBox\":\"\",\"snPcode\":\"\",\"submissionUrl\":\"/submission\",\"title\":\"Research Square\",\"twitterHandle\":\"researchsquare\",\"acdcEnabled\":true,\"dfaEnabled\":false,\"editorialSystem\":\"\",\"reportingPortfolio\":\"\",\"inReviewEnabled\":false,\"inReviewRevisionsEnabled\":true}}],\"origin\":\"\",\"ownerIdentity\":\"c8365a88-ae7f-4c9b-85c5-4b172d6a56a4\",\"owner\":[],\"postedDate\":\"June 27th, 2024\",\"published\":true,\"recentEditorialEvents\":[],\"rejectedJournal\":[],\"revision\":\"\",\"amendment\":\"\",\"status\":\"posted\",\"subjectAreas\":[{\"id\":33462450,\"name\":\"Health sciences/Diseases/Cancer/Gastrointestinal cancer/Gastric cancer\"},{\"id\":33462451,\"name\":\"Health sciences/Oncology/Cancer/Gastrointestinal cancer/Gastric cancer\"}],\"tags\":[],\"updatedAt\":\"2024-08-23T07:44:12+00:00\",\"versionOfRecord\":[],\"versionCreatedAt\":\"2024-06-27 18:55:22\",\"video\":\"\",\"vorDoi\":\"\",\"vorDoiUrl\":\"\",\"workflowStages\":[]},\"version\":\"v1\",\"identity\":\"rs-4495852\",\"journalConfig\":\"researchsquare\"},\"__N_SSP\":true},\"page\":\"/article/[identity]/[[...version]]\",\"query\":{\"redirect\":\"/article/rs-4495852\",\"identity\":\"rs-4495852\",\"version\":[\"v1\"]},\"buildId\":\"qtupq5eGEP_6zYnWcrvyt\",\"isFallback\":false,\"isExperimentalCompile\":false,\"dynamicIds\":[84888],\"gssp\":true,\"scriptLoader\":[]}","source_license":"CC-BY-4.0","license_restricted":false}