miR-384 targeting CTNNB1 regulates EMT and inhibits proliferation in gastric cancer

miR-384 targeting CTNNB1 regulates EMT and inhibits proliferation in gastric cancer | 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 Research Article miR-384 targeting CTNNB1 regulates EMT and inhibits proliferation in gastric cancer Rongjie Huang, Yubing Chen, Guoping Huang, Mingqiao Lian, Mingjie Lian, and 7 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-6248730/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 Background: MicroRNAs are important for gastric cancer (GC) EMT. This work focused on investigating how miR-384 affected GC and elucidating underlying mechanisms involved. Methods : miR-384 levels within GC and matched non-tumor tissues were determined through RT-qPCR. GC cells underwent miR-384 mimic or inhibitor transfection to investigate cell proliferation, invasion and EMT. Bioinformatic analysis was conducted to predict miR-384’s target mRNA. Also, rescued experiments were carried out for verifying targeted binding of miR-384 to CTNNB1. Furthermore, we conducted in vivo experiments for analyzing the effect of miR-384. Results : miR-384 expression declined within GC tumor tissue and cells. MiR-384 inhibited GC cell growth and migration while promoting their apoptosis. From bioinformatics analysis, we found that miR-384 targeted CTNNB1. MiR-384 inhibits the expression and nuclear translocation of CTNNB1, and regulated EMT and proliferation of GC cells. Moreover, miR-384 was targeting CTNNB1 inhibited GC tumor growth. Conclusion : miR-384 suppresses GC cell proliferation and EMT progress, and enhances their apoptosis via CTNNB1. miR-384 gastric cancer CTNNB1 EMT proliferation Figures Figure 1 Figure 2 Figure 3 Figure 4 Figure 5 Figure 6 Figure 7 Introduction Gastric cancer (GC) has the highest incidence globally, and its 5-year relative survival rate is approximately 20% [ 1 ] . GC primarily originates from gastric mucosal epithelial cells, particularly in the form of gastric adenocarcinoma. Early-stage gastric cancer often presents with no obvious symptoms, but as the disease progresses, it may cause dyspepsia and other gastric discomfort. In later stages, the main manifestations include pain, vomiting, hematemesis, melena, and may also be accompanied by signs like abdominal masses, epigastric tenderness, jaundice, splenomegaly, pelvic metastasis and distant lymph node metastasis [ 2 , 3 ] . In the research of gastric cancer, microRNAs (miRNAs) have gradually become a focal point. miRNAs, approximately 20–25 nucleotides in size, are the endogenous non-coding RNAs detected from eukaryotes [ 4 , 5 ] . They are produced through a series of cleavage and processing steps by nucleases and are assembled to RNA-induced silencing complexes (RISC) [ 6 , 7 ] . Through recognition of target mRNAs through base complementary pairing, they regulate target mRNA degradation by RISC or inhibit the translation, according to the complementarity degree. Recently, significant progress has been made in research on miRNAs and gastric cancer. For instance, a study has found that N2-polarized tumor-associated neutrophils (TANs) exosomes-derived miR-4745-5p/3911 enhances GC invasion through modulating SLIT2 [ 8 ] . This research reveals that N2-polarized TANs transmit specific miRNAs to gastric cancer cells through exosomes, thereby regulating GC cell biological behavior and promoting cancer invasion. This discovery sheds novel lights on functions of cells-derived exosomes within tumor microenvironment (TME) of GC invasion and provides candidate biomarkers for the diagnosis of GC. Furthermore, miRNAs have shown great potential in early warning, diagnosis, recurrence, and metastasis of gastric cancer. Studies indicate that miRNA expression increases in some early-stage GC patients, and their levels significantly decrease after tumor resection. Circulating miRNAs are highly sensitive and specific for diagnosing GC, potentially reaching 80–90%. Additionally, various miRNAs are closely associated with lymphatic metastasis, ovarian metastasis, liver metastasis, peritoneal metastasis, and other forms of metastasis in gastric cancer, as well as with prognosis and survival rates. Therefore, miRNA detection holds important application value in screening, diagnosing and treating GC. The present work focused on miR-384 that is crucial for diverse diseases as well as physiological processes [ 9 – 11 ] . miR-384 promoted radiosensitivity in non-small cell lung cancer (NSCLC) cells by inhibiting the DNA damage repair pathway [ 12 ] . This suggested that miR-384 could potentially serve as a sensitizing target for radiotherapy. miR-384 down-regulation within prostate cancer is related to its antitumor effect, as it inhibited tumor growth by acting on the HOXB7 gene [ 13 ] . As mentioned by Zeng et al., miR-384 had low expression within nasopharyngeal carcinoma cells and tissues, and was related to dismal prognostic outcome for nasopharyngeal carcinoma cases, as well as miRNA-384 suppressed nasopharyngeal carcinoma growth and migration via Smad5 and Wnt/β-catenin pathway [ 14 ] . We firstly explored the miR-384 expression within GC and matched non-carcinoma tissues, and evaluated its impact on cell proliferation, invasion and apoptosis. Through biological analysis, miR-384’s target gene was explored and verified. Moreover, the regulating mechanism by which miR-384 inhibited the epithelial-mesenchymal transition (EMT) and proliferation in GC was also studied. Materials and methods Clinical samples This work gained approval from Medical Ethics Committee of Zhangzhou Affiliated Hospital of Fujian Medical University. The cases offered informed consent for participation. There were altogether 20 GC cases aged 39–58 years (13 men, 7 women) enrolled into this work. Samples were processed and anonymized in line with relevant ethical and legal standards. We collected GC and matched non-carcinoma mucosal samples in 10 GC patients and verified them based on histology by one pathologist from our institute. Notably, we collected samples in patients naive to preoperative radiotherapy and chemotherapy, for the sake of eliminating possible treatment-related alterations of gene expression patterns. The samples were excised and snap frozen at once within liquid nitrogen before preservation under − 80°C for subsequent RNA extraction. Cell lines and culture Human GC cells (AGS, HGC-27, MKN-28, and MKN-45), together with Human gastric epithelial cells (GES-1) were obtained in The Cell Bank of Type Culture Collection, The Chinese Academy of Sciences, and cultured within DMEM that contained 10% fetal bovine serum (FBS, Gibco; Thermo Fisher Scientific, Inc.) under 37°C and 5% CO 2 conditions. Cell transfection This study obtained miR-384 mimic, negative control (NC) mimic, miR-384 inhibitor and NC inhibitor from Guangzhou RiboBio Co., Ltd., but their sequences remain unavailable because of the manufacturer’s confidentiality policy. To be specific, GC cells underwent transfection using oligonucleotides (50 nM) with Lipofectamine® 2000 reagent (Invitrogen; Thermo Fisher Scientific, Inc.) in line with specific protocols. At 48 h later, these cells were harvested to conduct further experiments under 37°C. Reverse transcription-quantitative (RT-q)PCR Through adopting TRIzol reagent (Invitrogen; Thermo Fisher Scientific Inc.), we extracted total tissue and cellular RNAs, and prepared them in cDNA with miRNA First-Strand cDNA Synthesis kit (Invitrogen; Thermo Fisher Scientific Inc.) as follows: 1 h under 37°C prior to additional 5 min under 85°C. Later, 7300 Real-Time PCR System (Applied Biosystems; Thermo Fisher Scientific Inc.) was adopted to conduct RT-qPCR by utilizing SYBR Green I Master Mix kit (Invitrogen; Thermo Fisher Scientific Inc.). Our thermocycling conditions included 10 min under 95°C; 15 s under 95°C and 15 s under 60°C for altogether 40 cycles. miR-384 expression was determined by 2 −ΔΔCq approach, with U6 being the internal reference. Primer sequences utilized included: for miR-384, 5′-ACGCGCATTCCTAGAAATTG-3′ (forward), 5′-GTTGTTGGTTGGTTGGTTG1-3′ (reverse); for U6: 5′-CTCGCTTCGGCAGCACA-3′ (forward), 5′-AACGCTTCACGAATTTGCGT-3′ (reverse). Invasion assay We introduced Matrigel (BD Biosciences) into upper Transwell chambers under 37°C for a 2-h duration. Later, we obtained GC cells and inoculated them at 2×10 5 cells/ml in the 24-well plate. After pre-incubation under 37°C for a 12-h duration, cells underwent 24 h of transfection under 37°C. Thereafter, cell resuspension within serum-free medium was completed, followed by suctioning of 1/4 of cell suspension (1×10 5 cells/ml) and inoculation in the serum-free upper Transwell chamber, whereas lower chamber was introduced medium that contained 20% FBS. We then eliminated medium within upper chamber with a cotton swab following incubation for 24 h, fixed cells within lower chamber by 4% paraformaldehyde under 4°C for a 20-min duration, and stained them by 0.1% crystal violet under ambient temperature for a 15-min period. The invading cell number in 5 random fields of views (×100) was calculated with the microscope (CX23 OLYMPUS, ×100). Bioinformatic analysis Based on ENCORI database (The Encyclopedia of RNA Interactomes, http://starbase.sysu.edu.cn/index.php ), this study collected mRNAs targeted by miR-384, yielding a total of 1,156 unique genes after removing duplicates. A PPI (Protein-Protein Interaction) network diagram was generated by Cytoscape. The GO pathways and KEGG pathways enriched for the related mRNA were performed. Dual-luciferase reporter assay This work obtained luciferase reporter gene vector (PGL3basic) in Magic Biotech Co., Ltd.. After inoculation of GC cells (1×10 6 /ml) in the 12-well plate, they underwent co-transfection using mutant or wild-type CTNNB1 3′-UTR sequences with miR-384 mimic, miR-384 inhibitor or corresponding NCs. After 48 h of transfection under 37°C with Lipofectamine® 2000 Transfection Reagent (Invitrogen; Thermo Fisher Scientific, Inc.), we utilized Dual Luciferase Reporter Gene Assay kit (Promega Corporation) for measuring relative luciferase activities in cells, with luciferase activity of firefly being standardized to that of Renilla. Colony formation assay After transfection, we inoculated cells (1×10 3 /well) in 6-well plates and cultivated them with DMEM that contained 10% FBS for a 10-day period with no disturbance. Following 15 min of fixation using 70% (v/v) ethanol under 25°C, cells were subjected to 1 h of staining using 0.5% crystal violet under 37°C. We later calculated visible colony number from 10 fields to take the average level. Apoptosis assay GC cells (2×10 5 /well) were plated into 6-well plates, prior to transfection using miR-377 mimics or its corresponding NC for a 48-h duration. Afterwards, cells were briefly trypsinized, centrifuged for 5 min (170 × g, 4°C) for collection, and rinsed with pre-chilled PBS, followed by resuspension within PBS that contained Annexin V-fluorescein isothiocyanate. Later, we introduced PI (Thermo Fisher Scientific, Inc.) to incubate cells under 20°C for a 30-min duration. The FACScan flow cytometer was employed for obtaining altogether 1×10 4 cells/sample, whereas Paint-A-Gate software (BD Paint-A-Gate Pro for Windows; version 649728; BD Biosciences) was applied for analyzing labeled cell percentage. Western blotting assay Total cellular proteins were isolated in line with Whole Protein Extraction kit instructions (KGP2100; Nanjing KeyGen Biotech Co., Ltd., Nanjing, China). Thereafter, protein aliquots (40 µg/lane) underwent 10% SDS-PAGE for separation, before transfer onto polyvinylidene difluoride membranes. Later, 10% defatted milk (containing 10% bovine serum albumin (KGY00810, Nanjing KeyGen Biotech Co., Ltd) for phosphorylated-protein) was poured to block membranes, followed by overnight primary antibody incubation under 4°C. Following rinsing by Tris-Buffered saline-Tween 20, membranes underwent 1 h of incubation using horseradish peroxidase-conjugated AffiniPure goat anti-rabbit IgG (H + L) secondary antibody (1:200; cat. no. 111-035-003; Jackson Immuno Research Inc., West Grove, PA, USA) under 25°C. Thereafter, we adopted the enhanced chemiluminescence system (Pierce Biotechnology, Rockford, IL, USA) in visualizing bound secondary antibody. Primary antibodies (abcam) utilized included: CTNNB1 (1:5000; cat. no. ab32572), PTEN (1:1000; cat. no. ab267787), KRAS (1:1000; cat. no. ab275876), STAT3 (1:1000; cat. no. ab68153), HIF1A (1:1000; cat. no. ab51608), CCND1 (1:1000; cat. no. ab226977), BCL2 (1:1000; cat. no. ab182858), CASP3 (1:5000; cat. no. ab32351), t-CTNNB1 (1:1000; cat. no. ab81305), C-Myc (1:1000; cat. no. ab32072), C-JUN (1:1000; cat. no. ab40766), MMP7 (1:1000; cat. no. ab207299), p-CTNNB1 (1:1000; cat. no. ab314450), LaminB1 (1:1000; cat. no. ab16048), GAPDH (1:1000; cat. no. ab8245). Results were normalized to GAPDH. In vivo xenograft tumor assay We obtained 18 4-week-old BALB/c nude mice in Gene Line bioscience (Beijing, China). Mice could take water and food freely and were raised in the 12-h day/night room under 22°C. Animal experiments were ratified by Animal Ethics Committee of Zhangzhou Affiliated Hospital of Fujian Medical University. GC cells modified by NC anta + NC Ago, miR-384 anta and miR-384 Ago were harvested to prepare cell suspension in PBS (1 × 10 6 cells/100 µL), followed by subcutaneous injection in mouse right rear flank. We determined tumor volume every 7 days according to 0.5 × long diameter × short diameter 2 . On the 28th day, mouse euthanasia was completed by 5% isoflurane and animals were executed quickly by dislocation of the neck. The subcutaneous xenograft tumor tissue was harvested from each mouse and then weighted. CTNNB1, Ki-67, E-cad, and N-cad expression was measured through IHC. Statistical analysis GraphPad 9.0 software (GraphPad Software, Inc.) was adopted for statistical analyses. Each experimental procedure was carried out thrice. Results were represented by mean ± SD. Between-group differences were analyzed by paired or unpaired Student's t-test, whereas among-group ones were examined by one-way ANOVA plus Tukey's post hoc test. Dual-luciferase reporter assay was conducted using two-way ANOVA plus Sidak post hoc test. Differences of P < 0.05 stood for statistical significance. Results The miR-384 expression decreased within GC tumor tissues and cells We firstly examined miR-384 levels within GC tumor tissues and cells through qPCR. Figure 1 A displays miR-384 expression within 20 GC and 20 matched non-carcinoma tissues. miR-384 level obviously declined within GC tissues ( P < 0.01). miR-384 expression within human gastric epithelial cells (GES-1) and GC cells (AGS, HGC-27, MKN-28, and MKN-45) is shown in Fig. 1 B. As a result, miR-384 expression remarkably decreased within AGS, HGC-27, MKN-28, and MKN-45 ( P < 0.01). miR-384 suppresses GC cell proliferation, invasion while promoting their apoptosis This study subsequently studied miR-384’s role in GC cell phenotype. miR-384 was overexpressed within AGS cells but knocked down within MKN-28 cells, and transfection efficiency was validated using qPCR (Fig. 2 A). We then used the clone formation assay for evaluating cell proliferation, the transwell assay for analyzing cell invasion, whereas flow cytometry for detecting cell apoptosis. As exhibited from Fig. 2 B, miR-384 mimic significantly suppressed cell proliferation relative to NC mimic within AGS cells ( P < 0.01), whereas miR-384 inhibitor evidently promoted cell proliferation relative to NC inhibitor ( P < 0.01) in MKN-28 cells. In Fig. 2 C, miR-384 mimic significantly inhibited cell invasion relative to NC mimic within AGS cells ( P < 0.01), whereas miR-384 inhibitor evidently promoted cell invasion relative to NC inhibitor ( P < 0.01) in MKN-28 cells. For apoptosis, miR-384 mimic enhanced cell apoptosis ( P < 0.01), and miR-384 inhibitor suppressed cell apoptosis ( P < 0.01), which was displayed in Fig. 2 D. Analysis and screening of downstream target genes mediated by miR-384 by bioinformatics Based on ENCORI database, we collected mRNAs targeted by miR-384, yielding a total of 1,156 unique genes after removing duplicates. A PPI (Protein-Protein Interaction) network diagram was generated, as shown in Fig. 3 A. The GO pathway enriched for the related mRNA is shown in Fig. 3 B, including Regulation of primary metabolic process, Regulation of cellular metabolic process, Regulation of metabolic process, Regulation of macromolecule metabolic process, Regulation of nitrogen compound metabolic process and so on. The Fig. 3 C revealed the enriched KEGG pathways, including Prostate cancer, MicroRNAs in cancer, Pathways in cancer, p53 pathway, Viral carcinogenesis, Hippo pathway, FoxO pathway, PI3K-Akt pathway and so on. The top 10 genes according to the PPI network graph analysis nodes were collected for display as shown in Table 1 . Table 1 The top 10 genes according to the PPI network #node node_degree CTNNB1 172 PTEN 135 KRAS 122 STAT3 122 HIF1A 111 CCND1 105 BCL2 101 CASP3 92 FN1 90 CALM3 87 miR-384 targeted CTNNB1 The top 10 genes according to the PPI network node degree were obtained (Fig. 4 A). Figure 4 B display binding sites for CTNNB1, BCL2 and CALM3. We used dual luciferase assays to detect the interactions between CTNNB1, BCL2, and CALM3 and miR-384 within 293T cells. Consequently, CTNNB1 bound to miR-384 (Fig. 4 C). MiR-384 inhibits the expression and nuclear translocation of CTNNB1 The AGS cells underwent NC mimic or miR-384 mimic transfection, and MKN-28 cells received NC inhibitor or miR-384 inhibitor transfection. Later, CTNNB1 and downstream target levels were examined by Western blotting. In AGS cells, the expressions of t-CTNNB1, C-Myc, CCND1, C-JUN, MMP7, and n-CTNNB1 was down-regulated after miR-384 mimic transfection ( P < 0.01, Fig. 5 ). p-CTNNB1 expression was up-regulated after miR-384 mimic transfection ( P < 0.01, Fig. 5 ). In MKN-28 cells, the expressions of t-CTNNB1, C-Myc, CCND1, C-JUN, MMP7, and n-CTNNB1 was increased, while the p-CTNNB1 expression was decreased after miR-384 inhibitor transfection ( P < 0.01, Fig. 5 ). The miR-384 mimic and miR-384 inhibitor showed no obvious effect on LaminB1 expression. MiR-384 targets CTNNB1 to regulate EMT and proliferation of GC cells Overexpression of CTNNB1 within AGS cells and its knockdown within MKN-28 cells were achieved, and qPCR was carried out to validate transfection efficiency (Fig. 6 A). The AGS cells later underwent miR-384 mimic co-transfection, whereas MKN-28 cells received miR-384 inhibitor co-transfection. We detected cell proliferation, invasion and apoptosis through clone formation detection, Transwell assay and flow cytometry separately. As shown in Fig. 6 B-D, CTNNB1 overexpression enhanced proliferation and invasion, while suppressed AGS cell apoptosis ( P < 0.01, Fig. 6 B-D). CTNNB1 knockdown suppressed MKN-28 cell proliferation and invasion, while promoting their apoptosis ( P < 0.01, Fig. 6 B-D). In AGC cells, miR-384 mimic rescued CTNNB1 overexpression’s impact on cell growth, invasion and apoptosis ( P < 0.01, Fig. 6 B-D). In MKN-28 cells, miR-384 inhibitor rescued impacts of CTNNB1 silencing on cell growth, invasion and apoptosis ( P < 0.01, Fig. 6 B-D). EMT-related protein (SNAI1, ZEB1, TWIST1, E-cad, N-cad) levels were measured by Western blotting. It was shown in Fig. 6 E, CTNNB1 overexpression accelerated the expressions of SNAI1, ZEB1, TWIST1, and N-cad, and inhibited E-cad within AGS cells ( P < 0.01, Fig. 6 E). CTNNB1 knockdown showed the opposite effects on EMT-related protein levels ( P < 0.01, Fig. 6 E). miR-384 mimic rescued the effects of CTNNB1 overexpression on EMT-related protein expressions in AGS cells, and miR-384 inhibitor abolished impacts of CTNNB1 silencing on EMT-related protein expressions in MKN-28 cells ( P < 0.01, Fig. 6 E). MiR-384 targeting CTNNB1 inhibited GC tumor growth The AGS cells of NC anta + NC Ago, miR-384 anta, and miR-384 Ago were constructed respectively, and then the GC transplant tumor mice were established to observe tumor volume and size. We performed IHC for detecting CTNNB1, Ki-67, E-cad, and N-cad expression. From Fig. 7 A-C, miR-384 anta promoted GC development and increased tumor weight ( P < 0.01), miR-384 Ago had opposite effects ( P < 0.01), as compared with the NC anta + NC Ago treatment. Moreover, the miR-384 anta promoted the expressions of CTNNB1, Ki-67, and N-cad, while suppressed the E-cad expression (Fig. 7 D). The miR-384 Ago inhibited the expressions of CTNNB1, Ki-67, and N-cad, as well as promoted the E-cad expression (Fig. 7 D). Discussion MiRNA has made significant progress in the research of gastric cancer, providing new ideas and methods for diagnosing and treating GC. Abnormally expressed miRNAs affect the biological behaviors of GC cells, including proliferation, invasion, migration, apoptosis, via different mechanisms, thereby participating in GC occurrence and progression. miR-21, as an oncogenic miRNA, can be activated by Helicobacter pylori and is up-regulated within GC. Through suppressing genes like PDCD4, miR-21 promotes GC cell growth and migration. miR-375 exhibits remarkable down-regulation within GC tissues and cells, affecting GC cell biological behaviors through modulating its downstream target, Jak2. miR-17-5p expression increases within GC tissues, which is associated with tumor progression and prognosis. The present work explored miR-384 expression within GC tumor tissue and normal tissue, and discovered the remarkable down-regulation of miR-384 within GC tumor tissue and cells. Its abnormal expression may be associated with the malignancy of GC progression, poor prognosis, and the risk of metastasis. We subsequently evaluated how miR-384 affected GC cell characteristics, including cell proliferation, apoptosis and EMT. According to the results, miR-384 up-regulation suppressed GC cell growth and EMT, but enhanced their apoptosis. Down-regulation of miR-384 had opposite effects. EMT facilitates GC occurrence and progression. During EMT process, epithelial cells acquire mesenchymal characteristics, making gastric cancer cells more prone to detachment from primary site and dissemination via lymphatic system and bloodstream to more body parts, thereby forming metastatic lesions [ 15 ] . SNAI1, ZEB1, TWIST1, E-cadherin, and N-cadherin are EMT-related proteins [ 16 ] , and their expression is also modulated via miR-384. The regulating mechanism of miR-384 was then By bioinformatic analysis, the targeted gene of miR-384 was explored. It was found that CTNNB1 can be bind with miR-384, which was further verified. CTNNB1 is responsible for encoding β-catenin, the crucial component of Wnt pathway [ 17 , 18 ] . Abnormal activation of Wnt signaling pathway is closely associated with the occurrence and development of various tumors. In hepatic cancer, CTNNB1 is one of the oncogenes with the highest mutation frequency. Activated β-catenin not only initiates the development of liver tumors but also exacerbates the progression of hepatic cancer mediated by P53 deficiency or hepatitis B virus infection. Polymorphisms in the CTNNB1 gene are associated with prognosis and survival in GC patients, with rs4135385 locus serving as an independent predictor of prognosis for non-cardia gastric cancer [ 19 ] . Another study found that the miR-200a/b/429 cluster can regulate the expression of CTNNB1, thereby influencing GC cell proliferation. According to our findings, miR-384 affected the nuclear translocation of CTNNB1. The cytoplasmic accumulation of β-catenin and its subsequent nuclear transport contribute to its binding to transcription factors such as T-cell factor/lymphoid enhancer factor (TCF/LEF). This binding activates downstream target transcription, including c-Myc, Axin2, CCND1, and CD44. These target genes regulate various processes in GC cells, including growth, migration, apoptosis and differentiation [ 20 ] . Moreover, miR-384 targeting CTNNB1 inhibited GC tumor growth and regulated the expressions of SNAI1, ZEB1, TWIST1, E-cadherin, and N-cadherin. The research limitations of this paper include: 1. The sample size of GC and matched non-carcinoma tissues mentioned in this paper may not be sufficiently large, which may limit the generality and reliability of the research findings. 2 Although the paper employed cell cultures and animal models to study the function of miR-384, these models may not fully simulate the complex physiological environment within the human body. 3 This study has identified CTNNB1 as miR-384’s target gene, but deeper molecular mechanisms underlying this relationship remain to be investigated. In conclusion, miR-384 suppresses GC cell proliferation and EMT progress, and enhances their apoptosis via CTNNB1. This research provides new candidate therapeutic targets for GC. New therapeutic strategies can be further explored by regulating the expression of miR-384 or developing inhibitors targeting CTNNB1. Declarations Conflicts of interest The authors confirm that there are no conflicts of interest Funding This work is supported by The Startup Fund for Scientific Research, the Fujian Medical University 2021QH1265. Data Availability The corresponding author is responsible for all data. It can be obtained by contact. Ethics approval and consent to participate The present work followed the Declaration of Helsinki and gained approval from ethics committee of Zhangzhou Affiliated Hospital of Fujian Medical University. The animal experiments gained approval from ethics committee of Zhangzhou Affiliated Hospital of Fujian Medical University. The methods were conducted following corresponding guidelines and regulations. The methods were reported following ARRIVE guidelines. Consent for publication Not applicable Authors’ contributions Rongjie Huang, Yubing Chen and Guoping Huang: Conceptualization; Formal analysis; Methodology;Writing - original draft; Validation; Resources. Mingqiao Lian, Mingjie Lian, Lixiong Luo, Weilong Lian, and Zebin Chen: Data curation; Investigation; Software; Writing - review & editing. Yangxin Zhang and Jianming Zheng: Formal analysis; Resources;Writing - review & editing;Visualization. Qiuxian Chen and Lisheng Cai: Methodology; Project administration; Supervision;Writing - review & editing; Validation. The authors agree to the final manuscript. Acknowledgements Not applicable References Zeng Y, Jin R U. Molecular pathogenesis, targeted therapies, and future perspectives for gastric cancer[J]. Semin Cancer Biol, 2022,86(Pt 3):566-582. Grantham T, Ramachandran R, Parvataneni S, et al. Epidemiology of Gastric Cancer: Global Trends, Risk Factors and Premalignant Conditions[J]. J Community Hosp Intern Med Perspect, 2023,13(6):100-106. Thrift A P, Nguyen T H. Gastric Cancer Epidemiology[J]. Gastrointest Endosc Clin N Am, 2021,31(3):425-439. Ouyang J, Xie Z, Lei X, et al. 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Downregulation of miR-384-5p attenuates rotenone-induced neurotoxicity in dopaminergic SH-SY5Y cells through inhibiting endoplasmic reticulum stress[J]. Am J Physiol Cell Physiol, 2016,310(9):C755-C763. Xu Q, Ou J, Zhang Q, et al. Effects of Aberrant miR-384-5p Expression on Learning and Memory in a Rat Model of Attention Deficit Hyperactivity Disorder[J]. Front Neurol, 2019,10:1414. Guo Q, Zheng M, Xu Y, et al. MiR-384 induces apoptosis and autophagy of non-small cell lung cancer cells through the negative regulation of Collagen alpha-1(X) chain gene[J]. Biosci Rep, 2019,39(2). Shi Z, Zhang H, Jie S, et al. Long non-coding RNA SNHG8 promotes prostate cancer progression through repressing miR-384 and up-regulating HOXB7[J]. J Gene Med, 2021,23(3):e3309. Zeng X, Liao H, Wang F. MicroRNA-384 inhibits nasopharyngeal carcinoma growth and metastasis via binding to Smad5 and suppressing the Wnt/beta-catenin axis[J]. Cytotechnology, 2021,73(2):203-215. Li S, Cong X, Gao H, et al. Tumor-associated neutrophils induce EMT by IL-17a to promote migration and invasion in gastric cancer cells[J]. J Exp Clin Cancer Res, 2019,38(1):6. Wu H T, Zhong H T, Li G W, et al. Oncogenic functions of the EMT-related transcription factor ZEB1 in breast cancer[J]. J Transl Med, 2020,18(1):51. Cheng S Y, Wu A, Batiha G E, et al. Identification of DPP4/CTNNB1/MET as a Theranostic Signature of Thyroid Cancer and Evaluation of the Therapeutic Potential of Sitagliptin[J]. Biology (Basel), 2022,11(2). Ledinek Z, Sobocan M, Knez J. The Role of CTNNB1 in Endometrial Cancer[J]. Dis Markers, 2022,2022:1442441. Tanabe S, Aoyagi K, Yokozaki H, et al. Regulation of CTNNB1 signaling in gastric cancer and stem cells[J]. World J Gastrointest Oncol, 2016,8(8):592-598. Zhang X, Dong N, Hu X. Wnt/beta-catenin Signaling Inhibitors[J]. Curr Top Med Chem, 2023,23(10):880-896. Additional Declarations No competing interests reported. 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Fujian Medical University","correspondingAuthor":false,"prefix":"","firstName":"Yubing","middleName":"","lastName":"Chen","suffix":""},{"id":430221422,"identity":"1567c642-5279-4364-a0bf-f86e95b60303","order_by":2,"name":"Guoping Huang","email":"","orcid":"","institution":"Zhangzhou Affiliated Hospital of Fujian Medical University","correspondingAuthor":false,"prefix":"","firstName":"Guoping","middleName":"","lastName":"Huang","suffix":""},{"id":430221424,"identity":"b0db9356-d2a6-4a59-8b0a-962728c25b8d","order_by":3,"name":"Mingqiao Lian","email":"","orcid":"","institution":"Zhangzhou Affiliated Hospital of Fujian Medical University","correspondingAuthor":false,"prefix":"","firstName":"Mingqiao","middleName":"","lastName":"Lian","suffix":""},{"id":430221427,"identity":"de7b6ce9-13a0-464c-b38c-e77d60ad0940","order_by":4,"name":"Mingjie Lian","email":"","orcid":"","institution":"Zhangzhou Affiliated Hospital of Fujian Medical University","correspondingAuthor":false,"prefix":"","firstName":"Mingjie","middleName":"","lastName":"Lian","suffix":""},{"id":430221429,"identity":"1aefad14-fd70-4114-9599-e9dee7734c24","order_by":5,"name":"Lixiong Luo","email":"","orcid":"","institution":"Zhangzhou Affiliated Hospital of Fujian Medical University","correspondingAuthor":false,"prefix":"","firstName":"Lixiong","middleName":"","lastName":"Luo","suffix":""},{"id":430221431,"identity":"cbfa07b3-6284-4077-bb1e-2d325b9f4739","order_by":6,"name":"Weilong Lian","email":"","orcid":"","institution":"Zhangzhou Affiliated Hospital of Fujian Medical University","correspondingAuthor":false,"prefix":"","firstName":"Weilong","middleName":"","lastName":"Lian","suffix":""},{"id":430221432,"identity":"49607948-a75f-4f1e-add5-5e2aaaf26b64","order_by":7,"name":"Zebin Chen","email":"","orcid":"","institution":"Zhangzhou Affiliated Hospital of Fujian Medical University","correspondingAuthor":false,"prefix":"","firstName":"Zebin","middleName":"","lastName":"Chen","suffix":""},{"id":430221433,"identity":"f5920bbd-8123-42b6-88c9-df2a4c2ba909","order_by":8,"name":"Yangxin Zhang","email":"","orcid":"","institution":"Zhangzhou Affiliated Hospital of Fujian Medical University","correspondingAuthor":false,"prefix":"","firstName":"Yangxin","middleName":"","lastName":"Zhang","suffix":""},{"id":430221434,"identity":"6da7752b-3075-4f0f-9648-99f2bcd75018","order_by":9,"name":"Jianming Zheng","email":"","orcid":"","institution":"Zhangzhou Affiliated Hospital of Fujian Medical University","correspondingAuthor":false,"prefix":"","firstName":"Jianming","middleName":"","lastName":"Zheng","suffix":""},{"id":430221435,"identity":"1fcaa9bd-8480-436d-9c76-ad2ef5d7018b","order_by":10,"name":"Qiuxian Chen","email":"","orcid":"","institution":"Zhangzhou Affiliated Hospital of Fujian Medical University","correspondingAuthor":false,"prefix":"","firstName":"Qiuxian","middleName":"","lastName":"Chen","suffix":""},{"id":430221436,"identity":"357e566d-1061-41cf-a1ac-49dbe4110ff1","order_by":11,"name":"Lisheng Cai","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAAA7klEQVRIiWNgGAWjYBACgwMgxGAhx8bM2Pjgg4GNHUEtlhAtEsb87M3NhjMK0pIJarEHagFSEokze463CfN8OMTYQEiL2fHmjQd+1EgwbriR2MZsY3CAmYH98NENeLWcOVZwsOeYBLMBUMvjHIM7fAw8aWk38Gq5kWNwmIFNgg2opd04x+AZM4MEjxleLQb33wC1/JPgAdkibWFwmLGBoJYbPEBlbRISkj0H26QZiNJyJq3gYG+fhAE/e2OzYY9BWjIbIb8YHD+8+cOPbzb1bczsDx/8+GNjx89++BheLZiAjTTlo2AUjIJRMAqwAQBuGFNSzLBCWAAAAABJRU5ErkJggg==","orcid":"","institution":"Zhangzhou Affiliated Hospital of Fujian Medical University","correspondingAuthor":true,"prefix":"","firstName":"Lisheng","middleName":"","lastName":"Cai","suffix":""}],"badges":[],"createdAt":"2025-03-18 02:53:10","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-6248730/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-6248730/v1","draftVersion":[],"editorialEvents":[],"editorialNote":"","failedWorkflow":false,"files":[{"id":78821865,"identity":"6ad4104f-c10c-4983-8e65-6e2fdee23f0e","added_by":"auto","created_at":"2025-03-19 11:44:51","extension":"png","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":101014,"visible":true,"origin":"","legend":"\u003cp\u003eThe miR-384 expression was down-regulated in GC tumor tissue and cell lines\u003c/p\u003e\n\u003cp\u003eA. The expression of miR-384 in GC normal tissues and cancer tissues was detected by qPCR. **\u003cem\u003eP\u003c/em\u003e\u0026lt;0.01 vs Normal group. B. The expression of miR-384 in human gastric epithelial cell line (GES-1) and GC cells (AGS, HGC-27, MKN-28, and MKN-45) was detected by qPCR. **\u003cem\u003eP\u003c/em\u003e\u0026lt;0.01 vs GES-1. Data was shown as mean ±SD.\u003c/p\u003e","description":"","filename":"figure1.png","url":"https://assets-eu.researchsquare.com/files/rs-6248730/v1/e0cdfb386e04c5838c59c7cd.png"},{"id":78821867,"identity":"472a5fa3-b180-4039-86d7-af3a9c5660d3","added_by":"auto","created_at":"2025-03-19 11:44:51","extension":"png","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":1591330,"visible":true,"origin":"","legend":"\u003cp\u003eThe effect of miR-384 on GC cell phenotype\u003c/p\u003e\n\u003cp\u003eA. The miR-384 was overexpressed in the AGS cell line and knocked down in the MKN-28 cell line, and the transfection efficiency was validated using qPCR. B. The clone formation assay was assessed to measure cell proliferation of GC cells. C. The transwell assay was performed to evaluate cell invasion. D. The flow cytometry was used to detect cell apoptosis. Data was shown as mean ± SD. **\u003cem\u003eP\u003c/em\u003e\u0026lt;0.01 vs NC group.\u003c/p\u003e","description":"","filename":"figure2.png","url":"https://assets-eu.researchsquare.com/files/rs-6248730/v1/2b956cf500ebb5045bbbc2d4.png"},{"id":78821868,"identity":"28e16b6c-3f46-47fb-bdff-ebdc4b233734","added_by":"auto","created_at":"2025-03-19 11:44:51","extension":"png","order_by":3,"title":"Figure 3","display":"","copyAsset":false,"role":"figure","size":1007555,"visible":true,"origin":"","legend":"\u003cp\u003eAnalysis and screening of downstream target genes mediated by miR-384 by bioinformatics\u003c/p\u003e\n\u003cp\u003eA. A total of 1,156 unique genes were obtained, PPI network diagram was generated. B. The GO pathway enriched for the related mRNA, including Regulation of cellular metabolic process, Regulation of primary metabolic process, Regulation of nitrogen compound metabolic process, Regulation of metabolic process, Regulation of macromolecule metabolic process and so on. C. The enriched KEGG pathways, including MicroRNAs in cancer, Prostate cancer, p53 signaling pathway, Pathways in cancer, Viral carcinogenesis, Hippo signaling pathway, FoxO signaling pathway, PI3K-Akt signaling pathway and so on.\u003c/p\u003e","description":"","filename":"figure3.png","url":"https://assets-eu.researchsquare.com/files/rs-6248730/v1/c70596ca95c5539ce2eb7498.png"},{"id":78821869,"identity":"5520d13b-0bab-4c16-90d4-41430ea1669c","added_by":"auto","created_at":"2025-03-19 11:44:51","extension":"png","order_by":4,"title":"Figure 4","display":"","copyAsset":false,"role":"figure","size":1251155,"visible":true,"origin":"","legend":"\u003cp\u003emiR-384 targeted CTNNB1\u003c/p\u003e\n\u003cp\u003eA. The top 10 genes according to the PPI network node degree. B. The binding sites of CTNNB1, BCL2 and CALM3. C. The dual luciferase assays were performed to detect the interactions between CTNNB1, BCL2, and CALM3 and miR-384 in 293T cells. Data was shown as mean ±SD. **\u003cem\u003eP\u003c/em\u003e\u0026lt;0.01 vs NC mimic group.\u003c/p\u003e","description":"","filename":"figure4.png","url":"https://assets-eu.researchsquare.com/files/rs-6248730/v1/dcb91dc4c91081dd27852f62.png"},{"id":78821872,"identity":"136e7f1d-9501-4400-a2db-6fd82a7db6c4","added_by":"auto","created_at":"2025-03-19 11:44:51","extension":"png","order_by":5,"title":"Figure 5","display":"","copyAsset":false,"role":"figure","size":1121344,"visible":true,"origin":"","legend":"\u003cp\u003eMiR-384 inhibits the expression and nuclear translocation of CTNNB1\u003c/p\u003e\n\u003cp\u003eWestern blot was performed to examine the expressions of CTNNB1 and the downstream targets ( C-Myc, CCND1, C-JUN, MMP7) in AGS cells and MKN-28 cells. Data was shown as mean ±SD. **\u003cem\u003eP\u003c/em\u003e\u0026lt;0.01 vs NC mimic group.\u003c/p\u003e","description":"","filename":"figure5.png","url":"https://assets-eu.researchsquare.com/files/rs-6248730/v1/1b6e068fb8afe762704f8a94.png"},{"id":78821875,"identity":"cc64494c-1ad8-4128-bd10-1bdb5b6c30f9","added_by":"auto","created_at":"2025-03-19 11:44:51","extension":"png","order_by":6,"title":"Figure 6","display":"","copyAsset":false,"role":"figure","size":1613555,"visible":true,"origin":"","legend":"\u003cp\u003eMiR-384 targets CTNNB1 to regulate EMT and proliferation of GC cells\u003c/p\u003e\n\u003cp\u003eA. qPCR was performed to detect the CTNNB1 expression in AGS cells and MKN-28 cells. B. Clone formation detection were performed for cell proliferation. C. Transwell was used for cell migration and invasion. D. The flow cytometry was conducted for cell apoptosis. E. Western blot was performed to detect the expressions of EMT-related protein (SNAI1, ZEB1, TWIST1, E-cad, N-cad) expression. Data was shown as mean ±SD. **\u003cem\u003eP\u003c/em\u003e\u0026lt;0.01 vs NC mimic group.\u003c/p\u003e","description":"","filename":"figure6.png","url":"https://assets-eu.researchsquare.com/files/rs-6248730/v1/1238670e3f52203c1b800af5.png"},{"id":78822255,"identity":"d6dcb9cd-7bc0-4b06-a558-f0f74db38606","added_by":"auto","created_at":"2025-03-19 11:52:51","extension":"png","order_by":7,"title":"Figure 7","display":"","copyAsset":false,"role":"figure","size":4635770,"visible":true,"origin":"","legend":"\u003cp\u003eMiR-384 targeting CTNNB1 inhibited GC tumor growth\u003c/p\u003e\n\u003cp\u003eA-C. The AGS cells of NC anta+NC Ago, miR-384 anta, and miR-384 Ago were constructed respectively, and then the GC transplant tumor mice were established to observe tumor volume and size. D. IHC was used to detect the expressions of CTNNB1, Ki-67, E-cad, and N-cad. Data was shown as mean ± SD. **\u003cem\u003eP\u003c/em\u003e\u0026lt;0.01 vs NC anta+NC Ago, \u003csup\u003e##\u003c/sup\u003e\u003cem\u003eP\u003c/em\u003e\u0026lt;0.01 vs miR-384 anta.\u003c/p\u003e","description":"","filename":"figure7.png","url":"https://assets-eu.researchsquare.com/files/rs-6248730/v1/792cc505636bf589ae6a30fc.png"},{"id":79581413,"identity":"986587d7-d5be-42e3-9912-8629093b29b5","added_by":"auto","created_at":"2025-03-31 11:54:00","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":11345841,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-6248730/v1/07497797-c92c-4846-8cf6-e85cca3f20ea.pdf"}],"financialInterests":"No competing interests reported.","formattedTitle":"miR-384 targeting CTNNB1 regulates EMT and inhibits proliferation in gastric cancer","fulltext":[{"header":"Introduction","content":"\u003cp\u003eGastric cancer (GC) has the highest incidence globally, and its 5-year relative survival rate is approximately 20%\u003csup\u003e[\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e]\u003c/sup\u003e. GC primarily originates from gastric mucosal epithelial cells, particularly in the form of gastric adenocarcinoma. Early-stage gastric cancer often presents with no obvious symptoms, but as the disease progresses, it may cause dyspepsia and other gastric discomfort. In later stages, the main manifestations include pain, vomiting, hematemesis, melena, and may also be accompanied by signs like abdominal masses, epigastric tenderness, jaundice, splenomegaly, pelvic metastasis and distant lymph node metastasis\u003csup\u003e[\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e, \u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e]\u003c/sup\u003e. In the research of gastric cancer, microRNAs (miRNAs) have gradually become a focal point. miRNAs, approximately 20\u0026ndash;25 nucleotides in size, are the endogenous non-coding RNAs detected from eukaryotes\u003csup\u003e[\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e, \u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e]\u003c/sup\u003e. They are produced through a series of cleavage and processing steps by nucleases and are assembled to RNA-induced silencing complexes (RISC)\u003csup\u003e[\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e, \u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e]\u003c/sup\u003e. Through recognition of target mRNAs through base complementary pairing, they regulate target mRNA degradation by RISC or inhibit the translation, according to the complementarity degree.\u003c/p\u003e \u003cp\u003eRecently, significant progress has been made in research on miRNAs and gastric cancer. For instance, a study has found that N2-polarized tumor-associated neutrophils (TANs) exosomes-derived miR-4745-5p/3911 enhances GC invasion through modulating SLIT2 \u003csup\u003e[\u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e]\u003c/sup\u003e. This research reveals that N2-polarized TANs transmit specific miRNAs to gastric cancer cells through exosomes, thereby regulating GC cell biological behavior and promoting cancer invasion. This discovery sheds novel lights on functions of cells-derived exosomes within tumor microenvironment (TME) of GC invasion and provides candidate biomarkers for the diagnosis of GC. Furthermore, miRNAs have shown great potential in early warning, diagnosis, recurrence, and metastasis of gastric cancer. Studies indicate that miRNA expression increases in some early-stage GC patients, and their levels significantly decrease after tumor resection. Circulating miRNAs are highly sensitive and specific for diagnosing GC, potentially reaching 80\u0026ndash;90%. Additionally, various miRNAs are closely associated with lymphatic metastasis, ovarian metastasis, liver metastasis, peritoneal metastasis, and other forms of metastasis in gastric cancer, as well as with prognosis and survival rates. Therefore, miRNA detection holds important application value in screening, diagnosing and treating GC.\u003c/p\u003e \u003cp\u003eThe present work focused on miR-384 that is crucial for diverse diseases as well as physiological processes\u003csup\u003e[\u003cspan additionalcitationids=\"CR10\" citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e]\u003c/sup\u003e. miR-384 promoted radiosensitivity in non-small cell lung cancer (NSCLC) cells by inhibiting the DNA damage repair pathway\u003csup\u003e[\u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e]\u003c/sup\u003e. This suggested that miR-384 could potentially serve as a sensitizing target for radiotherapy. miR-384 down-regulation within prostate cancer is related to its antitumor effect, as it inhibited tumor growth by acting on the HOXB7 gene\u003csup\u003e[\u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e]\u003c/sup\u003e. As mentioned by Zeng et al., miR-384 had low expression within nasopharyngeal carcinoma cells and tissues, and was related to dismal prognostic outcome for nasopharyngeal carcinoma cases, as well as miRNA-384 suppressed nasopharyngeal carcinoma growth and migration via Smad5 and Wnt/β-catenin pathway \u003csup\u003e[\u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e]\u003c/sup\u003e.\u003c/p\u003e \u003cp\u003eWe firstly explored the miR-384 expression within GC and matched non-carcinoma tissues, and evaluated its impact on cell proliferation, invasion and apoptosis. Through biological analysis, miR-384\u0026rsquo;s target gene was explored and verified. Moreover, the regulating mechanism by which miR-384 inhibited the epithelial-mesenchymal transition (EMT) and proliferation in GC was also studied.\u003c/p\u003e"},{"header":"Materials and methods","content":"\u003cdiv id=\"Sec3\" class=\"Section2\"\u003e \u003ch2\u003eClinical samples\u003c/h2\u003e \u003cp\u003e This work gained approval from Medical Ethics Committee of Zhangzhou Affiliated Hospital of Fujian Medical University. The cases offered informed consent for participation. There were altogether 20 GC cases aged 39\u0026ndash;58 years (13 men, 7 women) enrolled into this work. Samples were processed and anonymized in line with relevant ethical and legal standards. We collected GC and matched non-carcinoma mucosal samples in 10 GC patients and verified them based on histology by one pathologist from our institute. Notably, we collected samples in patients naive to preoperative radiotherapy and chemotherapy, for the sake of eliminating possible treatment-related alterations of gene expression patterns. The samples were excised and snap frozen at once within liquid nitrogen before preservation under \u0026minus;\u0026thinsp;80\u0026deg;C for subsequent RNA extraction.\u003c/p\u003e \u003c/div\u003e\n\u003ch3\u003eCell lines and culture\u003c/h3\u003e\n\u003cp\u003eHuman GC cells (AGS, HGC-27, MKN-28, and MKN-45), together with Human gastric epithelial cells (GES-1) were obtained in The Cell Bank of Type Culture Collection, The Chinese Academy of Sciences, and cultured within DMEM that contained 10% fetal bovine serum (FBS, Gibco; Thermo Fisher Scientific, Inc.) under 37\u0026deg;C and 5% CO\u003csub\u003e2\u003c/sub\u003e conditions.\u003c/p\u003e\n\u003ch3\u003eCell transfection\u003c/h3\u003e\n\u003cp\u003eThis study obtained miR-384 mimic, negative control (NC) mimic, miR-384 inhibitor and NC inhibitor from Guangzhou RiboBio Co., Ltd., but their sequences remain unavailable because of the manufacturer\u0026rsquo;s confidentiality policy. To be specific, GC cells underwent transfection using oligonucleotides (50 nM) with Lipofectamine\u0026reg; 2000 reagent (Invitrogen; Thermo Fisher Scientific, Inc.) in line with specific protocols. At 48 h later, these cells were harvested to conduct further experiments under 37\u0026deg;C.\u003c/p\u003e\n\u003ch3\u003eReverse transcription-quantitative (RT-q)PCR\u003c/h3\u003e\n\u003cp\u003eThrough adopting TRIzol reagent (Invitrogen; Thermo Fisher Scientific Inc.), we extracted total tissue and cellular RNAs, and prepared them in cDNA with miRNA First-Strand cDNA Synthesis kit (Invitrogen; Thermo Fisher Scientific Inc.) as follows: 1 h under 37\u0026deg;C prior to additional 5 min under 85\u0026deg;C. Later, 7300 Real-Time PCR System (Applied Biosystems; Thermo Fisher Scientific Inc.) was adopted to conduct RT-qPCR by utilizing SYBR Green I Master Mix kit (Invitrogen; Thermo Fisher Scientific Inc.). Our thermocycling conditions included 10 min under 95\u0026deg;C; 15 s under 95\u0026deg;C and 15 s under 60\u0026deg;C for altogether 40 cycles. miR-384 expression was determined by 2\u003csup\u003e\u0026minus;ΔΔCq\u003c/sup\u003e approach, with U6 being the internal reference. Primer sequences utilized included: for miR-384, 5\u0026prime;-ACGCGCATTCCTAGAAATTG-3\u0026prime; (forward), 5\u0026prime;-GTTGTTGGTTGGTTGGTTG1-3\u0026prime; (reverse); for U6: 5\u0026prime;-CTCGCTTCGGCAGCACA-3\u0026prime; (forward), 5\u0026prime;-AACGCTTCACGAATTTGCGT-3\u0026prime; (reverse).\u003c/p\u003e\n\u003ch3\u003eInvasion assay\u003c/h3\u003e\n\u003cp\u003eWe introduced Matrigel (BD Biosciences) into upper Transwell chambers under 37\u0026deg;C for a 2-h duration. Later, we obtained GC cells and inoculated them at 2\u0026times;10\u003csup\u003e5\u003c/sup\u003e cells/ml in the 24-well plate. After pre-incubation under 37\u0026deg;C for a 12-h duration, cells underwent 24 h of transfection under 37\u0026deg;C. Thereafter, cell resuspension within serum-free medium was completed, followed by suctioning of 1/4 of cell suspension (1\u0026times;10\u003csup\u003e5\u003c/sup\u003e cells/ml) and inoculation in the serum-free upper Transwell chamber, whereas lower chamber was introduced medium that contained 20% FBS. We then eliminated medium within upper chamber with a cotton swab following incubation for 24 h, fixed cells within lower chamber by 4% paraformaldehyde under 4\u0026deg;C for a 20-min duration, and stained them by 0.1% crystal violet under ambient temperature for a 15-min period. The invading cell number in 5 random fields of views (\u0026times;100) was calculated with the microscope (CX23 OLYMPUS, \u0026times;100).\u003c/p\u003e \u003cdiv id=\"Sec8\" class=\"Section2\"\u003e \u003ch2\u003eBioinformatic analysis\u003c/h2\u003e \u003cp\u003eBased on ENCORI database (The Encyclopedia of RNA Interactomes,\u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttp://starbase.sysu.edu.cn/index.php\u003c/span\u003e\u003cspan address=\"http://starbase.sysu.edu.cn/index.php\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e), this study collected mRNAs targeted by miR-384, yielding a total of 1,156 unique genes after removing duplicates. A PPI (Protein-Protein Interaction) network diagram was generated by Cytoscape. The GO pathways and KEGG pathways enriched for the related mRNA were performed.\u003c/p\u003e \u003c/div\u003e\n\u003ch3\u003eDual-luciferase reporter assay\u003c/h3\u003e\n\u003cp\u003eThis work obtained luciferase reporter gene vector (PGL3basic) in Magic Biotech Co., Ltd.. After inoculation of GC cells (1\u0026times;10\u003csup\u003e6\u003c/sup\u003e/ml) in the 12-well plate, they underwent co-transfection using mutant or wild-type CTNNB1 3\u0026prime;-UTR sequences with miR-384 mimic, miR-384 inhibitor or corresponding NCs. After 48 h of transfection under 37\u0026deg;C with Lipofectamine\u0026reg; 2000 Transfection Reagent (Invitrogen; Thermo Fisher Scientific, Inc.), we utilized Dual Luciferase Reporter Gene Assay kit (Promega Corporation) for measuring relative luciferase activities in cells, with luciferase activity of firefly being standardized to that of Renilla.\u003c/p\u003e\n\u003ch3\u003eColony formation assay\u003c/h3\u003e\n\u003cp\u003eAfter transfection, we inoculated cells (1\u0026times;10\u003csup\u003e3\u003c/sup\u003e/well) in 6-well plates and cultivated them with DMEM that contained 10% FBS for a 10-day period with no disturbance. Following 15 min of fixation using 70% (v/v) ethanol under 25\u0026deg;C, cells were subjected to 1 h of staining using 0.5% crystal violet under 37\u0026deg;C. We later calculated visible colony number from 10 fields to take the average level.\u003c/p\u003e \u003cdiv id=\"Sec11\" class=\"Section2\"\u003e \u003ch2\u003eApoptosis assay\u003c/h2\u003e \u003cp\u003eGC cells (2\u0026times;10\u003csup\u003e5\u003c/sup\u003e/well) were plated into 6-well plates, prior to transfection using miR-377 mimics or its corresponding NC for a 48-h duration. Afterwards, cells were briefly trypsinized, centrifuged for 5 min (170 \u0026times; g, 4\u0026deg;C) for collection, and rinsed with pre-chilled PBS, followed by resuspension within PBS that contained Annexin V-fluorescein isothiocyanate. Later, we introduced PI (Thermo Fisher Scientific, Inc.) to incubate cells under 20\u0026deg;C for a 30-min duration. The FACScan flow cytometer was employed for obtaining altogether 1\u0026times;10\u003csup\u003e4\u003c/sup\u003e cells/sample, whereas Paint-A-Gate software (BD Paint-A-Gate Pro for Windows; version 649728; BD Biosciences) was applied for analyzing labeled cell percentage.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec12\" class=\"Section2\"\u003e \u003ch2\u003eWestern blotting assay\u003c/h2\u003e \u003cp\u003eTotal cellular proteins were isolated in line with Whole Protein Extraction kit instructions (KGP2100; Nanjing KeyGen Biotech Co., Ltd., Nanjing, China). Thereafter, protein aliquots (40 \u0026micro;g/lane) underwent 10% SDS-PAGE for separation, before transfer onto polyvinylidene difluoride membranes. Later, 10% defatted milk (containing 10% bovine serum albumin (KGY00810, Nanjing KeyGen Biotech Co., Ltd) for phosphorylated-protein) was poured to block membranes, followed by overnight primary antibody incubation under 4\u0026deg;C. Following rinsing by Tris-Buffered saline-Tween 20, membranes underwent 1 h of incubation using horseradish peroxidase-conjugated AffiniPure goat anti-rabbit IgG (H\u0026thinsp;+\u0026thinsp;L) secondary antibody (1:200; cat. no. 111-035-003; Jackson Immuno Research Inc., West Grove, PA, USA) under 25\u0026deg;C. Thereafter, we adopted the enhanced chemiluminescence system (Pierce Biotechnology, Rockford, IL, USA) in visualizing bound secondary antibody. Primary antibodies (abcam) utilized included: CTNNB1 (1:5000; cat. no. ab32572), PTEN (1:1000; cat. no. ab267787), KRAS (1:1000; cat. no. ab275876), STAT3 (1:1000; cat. no. ab68153), HIF1A (1:1000; cat. no. ab51608), CCND1 (1:1000; cat. no. ab226977), BCL2 (1:1000; cat. no. ab182858), CASP3 (1:5000; cat. no. ab32351), t-CTNNB1 (1:1000; cat. no. ab81305), C-Myc (1:1000; cat. no. ab32072), C-JUN (1:1000; cat. no. ab40766), MMP7 (1:1000; cat. no. ab207299), p-CTNNB1 (1:1000; cat. no. ab314450), LaminB1 (1:1000; cat. no. ab16048), GAPDH (1:1000; cat. no. ab8245). Results were normalized to GAPDH.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec13\" class=\"Section2\"\u003e \u003ch2\u003eIn vivo xenograft tumor assay\u003c/h2\u003e \u003cp\u003eWe obtained 18 4-week-old BALB/c nude mice in Gene Line bioscience (Beijing, China). Mice could take water and food freely and were raised in the 12-h day/night room under 22\u0026deg;C. Animal experiments were ratified by Animal Ethics Committee of Zhangzhou Affiliated Hospital of Fujian Medical University.\u003c/p\u003e \u003cp\u003eGC cells modified by NC anta\u0026thinsp;+\u0026thinsp;NC Ago, miR-384 anta and miR-384 Ago were harvested to prepare cell suspension in PBS (1 \u0026times; 10\u003csup\u003e6\u003c/sup\u003e cells/100 \u0026micro;L), followed by subcutaneous injection in mouse right rear flank. We determined tumor volume every 7 days according to 0.5 \u0026times; long diameter \u0026times; short diameter\u003csup\u003e2\u003c/sup\u003e. On the 28th day, mouse euthanasia was completed by 5% isoflurane and animals were executed quickly by dislocation of the neck. The subcutaneous xenograft tumor tissue was harvested from each mouse and then weighted. CTNNB1, Ki-67, E-cad, and N-cad expression was measured through IHC.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec14\" class=\"Section2\"\u003e \u003ch2\u003eStatistical analysis\u003c/h2\u003e \u003cp\u003eGraphPad 9.0 software (GraphPad Software, Inc.) was adopted for statistical analyses. Each experimental procedure was carried out thrice. Results were represented by mean\u0026thinsp;\u0026plusmn;\u0026thinsp;SD. Between-group differences were analyzed by paired or unpaired Student's t-test, whereas among-group ones were examined by one-way ANOVA plus Tukey's post hoc test. Dual-luciferase reporter assay was conducted using two-way ANOVA plus Sidak post hoc test. Differences of \u003cem\u003eP\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.05 stood for statistical significance.\u003c/p\u003e \u003c/div\u003e"},{"header":"Results","content":"\u003cdiv id=\"Sec16\" class=\"Section2\"\u003e \u003ch2\u003eThe miR-384 expression decreased within GC tumor tissues and cells\u003c/h2\u003e \u003cp\u003eWe firstly examined miR-384 levels within GC tumor tissues and cells through qPCR. Figure\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003eA displays miR-384 expression within 20 GC and 20 matched non-carcinoma tissues. miR-384 level obviously declined within GC tissues (\u003cem\u003eP\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.01). miR-384 expression within human gastric epithelial cells (GES-1) and GC cells (AGS, HGC-27, MKN-28, and MKN-45) is shown in Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003eB. As a result, miR-384 expression remarkably decreased within AGS, HGC-27, MKN-28, and MKN-45 (\u003cem\u003eP\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.01).\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec17\" class=\"Section2\"\u003e \u003ch2\u003emiR-384 suppresses GC cell proliferation, invasion while promoting their apoptosis\u003c/h2\u003e \u003cp\u003eThis study subsequently studied miR-384\u0026rsquo;s role in GC cell phenotype. miR-384 was overexpressed within AGS cells but knocked down within MKN-28 cells, and transfection efficiency was validated using qPCR (Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003eA). We then used the clone formation assay for evaluating cell proliferation, the transwell assay for analyzing cell invasion, whereas flow cytometry for detecting cell apoptosis. As exhibited from Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003eB, miR-384 mimic significantly suppressed cell proliferation relative to NC mimic within AGS cells (\u003cem\u003eP\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.01), whereas miR-384 inhibitor evidently promoted cell proliferation relative to NC inhibitor (\u003cem\u003eP\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.01) in MKN-28 cells. In Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003eC, miR-384 mimic significantly inhibited cell invasion relative to NC mimic within AGS cells (\u003cem\u003eP\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.01), whereas miR-384 inhibitor evidently promoted cell invasion relative to NC inhibitor (\u003cem\u003eP\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.01) in MKN-28 cells. For apoptosis, miR-384 mimic enhanced cell apoptosis (\u003cem\u003eP\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.01), and miR-384 inhibitor suppressed cell apoptosis (\u003cem\u003eP\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.01), which was displayed in Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003eD.\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec18\" class=\"Section2\"\u003e \u003ch2\u003eAnalysis and screening of downstream target genes mediated by miR-384 by bioinformatics\u003c/h2\u003e \u003cp\u003eBased on ENCORI database, we collected mRNAs targeted by miR-384, yielding a total of 1,156 unique genes after removing duplicates. A PPI (Protein-Protein Interaction) network diagram was generated, as shown in Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003eA. The GO pathway enriched for the related mRNA is shown in Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003eB, including Regulation of primary metabolic process, Regulation of cellular metabolic process, Regulation of metabolic process, Regulation of macromolecule metabolic process, Regulation of nitrogen compound metabolic process and so on. The Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003eC revealed the enriched KEGG pathways, including Prostate cancer, MicroRNAs in cancer, Pathways in cancer, p53 pathway, Viral carcinogenesis, Hippo pathway, FoxO pathway, PI3K-Akt pathway and so on. The top 10 genes according to the PPI network graph analysis nodes were collected for display as shown in Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e.\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\u003eThe top 10 genes according to the PPI network\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"2\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003e#node\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003enode_degree\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eCTNNB1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e172\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePTEN\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e135\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eKRAS\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e122\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSTAT3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e122\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eHIF1A\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e111\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eCCND1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e105\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eBCL2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e101\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eCASP3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e92\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eFN1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e90\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eCALM3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e87\u003c/p\u003e \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=\"Sec19\" class=\"Section2\"\u003e \u003ch2\u003emiR-384 targeted CTNNB1\u003c/h2\u003e \u003cp\u003eThe top 10 genes according to the PPI network node degree were obtained (Fig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003eA). Figure\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003eB display binding sites for CTNNB1, BCL2 and CALM3. We used dual luciferase assays to detect the interactions between CTNNB1, BCL2, and CALM3 and miR-384 within 293T cells. Consequently, CTNNB1 bound to miR-384 (Fig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003eC).\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec20\" class=\"Section2\"\u003e \u003ch2\u003eMiR-384 inhibits the expression and nuclear translocation of CTNNB1\u003c/h2\u003e \u003cp\u003eThe AGS cells underwent NC mimic or miR-384 mimic transfection, and MKN-28 cells received NC inhibitor or miR-384 inhibitor transfection. Later, CTNNB1 and downstream target levels were examined by Western blotting. In AGS cells, the expressions of t-CTNNB1, C-Myc, CCND1, C-JUN, MMP7, and n-CTNNB1 was down-regulated after miR-384 mimic transfection (\u003cem\u003eP\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.01, Fig.\u0026nbsp;\u003cspan refid=\"Fig5\" class=\"InternalRef\"\u003e5\u003c/span\u003e). p-CTNNB1 expression was up-regulated after miR-384 mimic transfection (\u003cem\u003eP\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.01, Fig.\u0026nbsp;\u003cspan refid=\"Fig5\" class=\"InternalRef\"\u003e5\u003c/span\u003e). In MKN-28 cells, the expressions of t-CTNNB1, C-Myc, CCND1, C-JUN, MMP7, and n-CTNNB1 was increased, while the p-CTNNB1 expression was decreased after miR-384 inhibitor transfection (\u003cem\u003eP\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.01, Fig.\u0026nbsp;\u003cspan refid=\"Fig5\" class=\"InternalRef\"\u003e5\u003c/span\u003e). The miR-384 mimic and miR-384 inhibitor showed no obvious effect on LaminB1 expression.\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec21\" class=\"Section2\"\u003e \u003ch2\u003eMiR-384 targets CTNNB1 to regulate EMT and proliferation of GC cells\u003c/h2\u003e \u003cp\u003eOverexpression of CTNNB1 within AGS cells and its knockdown within MKN-28 cells were achieved, and qPCR was carried out to validate transfection efficiency (Fig.\u0026nbsp;\u003cspan refid=\"Fig6\" class=\"InternalRef\"\u003e6\u003c/span\u003eA). The AGS cells later underwent miR-384 mimic co-transfection, whereas MKN-28 cells received miR-384 inhibitor co-transfection. We detected cell proliferation, invasion and apoptosis through clone formation detection, Transwell assay and flow cytometry separately. As shown in Fig.\u0026nbsp;\u003cspan refid=\"Fig6\" class=\"InternalRef\"\u003e6\u003c/span\u003eB-D, CTNNB1 overexpression enhanced proliferation and invasion, while suppressed AGS cell apoptosis (\u003cem\u003eP\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.01, Fig.\u0026nbsp;\u003cspan refid=\"Fig6\" class=\"InternalRef\"\u003e6\u003c/span\u003eB-D). CTNNB1 knockdown suppressed MKN-28 cell proliferation and invasion, while promoting their apoptosis (\u003cem\u003eP\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.01, Fig.\u0026nbsp;\u003cspan refid=\"Fig6\" class=\"InternalRef\"\u003e6\u003c/span\u003eB-D). In AGC cells, miR-384 mimic rescued CTNNB1 overexpression\u0026rsquo;s impact on cell growth, invasion and apoptosis (\u003cem\u003eP\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.01, Fig.\u0026nbsp;\u003cspan refid=\"Fig6\" class=\"InternalRef\"\u003e6\u003c/span\u003eB-D). In MKN-28 cells, miR-384 inhibitor rescued impacts of CTNNB1 silencing on cell growth, invasion and apoptosis (\u003cem\u003eP\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.01, Fig.\u0026nbsp;\u003cspan refid=\"Fig6\" class=\"InternalRef\"\u003e6\u003c/span\u003eB-D). EMT-related protein (SNAI1, ZEB1, TWIST1, E-cad, N-cad) levels were measured by Western blotting. It was shown in Fig.\u0026nbsp;\u003cspan refid=\"Fig6\" class=\"InternalRef\"\u003e6\u003c/span\u003eE, CTNNB1 overexpression accelerated the expressions of SNAI1, ZEB1, TWIST1, and N-cad, and inhibited E-cad within AGS cells (\u003cem\u003eP\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.01, Fig.\u0026nbsp;\u003cspan refid=\"Fig6\" class=\"InternalRef\"\u003e6\u003c/span\u003eE). CTNNB1 knockdown showed the opposite effects on EMT-related protein levels (\u003cem\u003eP\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.01, Fig.\u0026nbsp;\u003cspan refid=\"Fig6\" class=\"InternalRef\"\u003e6\u003c/span\u003eE). miR-384 mimic rescued the effects of CTNNB1 overexpression on EMT-related protein expressions in AGS cells, and miR-384 inhibitor abolished impacts of CTNNB1 silencing on EMT-related protein expressions in MKN-28 cells (\u003cem\u003eP\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.01, Fig.\u0026nbsp;\u003cspan refid=\"Fig6\" class=\"InternalRef\"\u003e6\u003c/span\u003eE).\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec22\" class=\"Section2\"\u003e \u003ch2\u003eMiR-384 targeting CTNNB1 inhibited GC tumor growth\u003c/h2\u003e \u003cp\u003eThe AGS cells of NC anta\u0026thinsp;+\u0026thinsp;NC Ago, miR-384 anta, and miR-384 Ago were constructed respectively, and then the GC transplant tumor mice were established to observe tumor volume and size. We performed IHC for detecting CTNNB1, Ki-67, E-cad, and N-cad expression. From Fig.\u0026nbsp;\u003cspan refid=\"Fig7\" class=\"InternalRef\"\u003e7\u003c/span\u003eA-C, miR-384 anta promoted GC development and increased tumor weight (\u003cem\u003eP\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.01), miR-384 Ago had opposite effects (\u003cem\u003eP\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.01), as compared with the NC anta\u0026thinsp;+\u0026thinsp;NC Ago treatment. Moreover, the miR-384 anta promoted the expressions of CTNNB1, Ki-67, and N-cad, while suppressed the E-cad expression (Fig.\u0026nbsp;\u003cspan refid=\"Fig7\" class=\"InternalRef\"\u003e7\u003c/span\u003eD). The miR-384 Ago inhibited the expressions of CTNNB1, Ki-67, and N-cad, as well as promoted the E-cad expression (Fig.\u0026nbsp;\u003cspan refid=\"Fig7\" class=\"InternalRef\"\u003e7\u003c/span\u003eD).\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003c/div\u003e"},{"header":"Discussion","content":"\u003cp\u003eMiRNA has made significant progress in the research of gastric cancer, providing new ideas and methods for diagnosing and treating GC. Abnormally expressed miRNAs affect the biological behaviors of GC cells, including proliferation, invasion, migration, apoptosis, via different mechanisms, thereby participating in GC occurrence and progression. miR-21, as an oncogenic miRNA, can be activated by Helicobacter pylori and is up-regulated within GC. Through suppressing genes like PDCD4, miR-21 promotes GC cell growth and migration. miR-375 exhibits remarkable down-regulation within GC tissues and cells, affecting GC cell biological behaviors through modulating its downstream target, Jak2. miR-17-5p expression increases within GC tissues, which is associated with tumor progression and prognosis.\u003c/p\u003e \u003cp\u003eThe present work explored miR-384 expression within GC tumor tissue and normal tissue, and discovered the remarkable down-regulation of miR-384 within GC tumor tissue and cells. Its abnormal expression may be associated with the malignancy of GC progression, poor prognosis, and the risk of metastasis. We subsequently evaluated how miR-384 affected GC cell characteristics, including cell proliferation, apoptosis and EMT. According to the results, miR-384 up-regulation suppressed GC cell growth and EMT, but enhanced their apoptosis. Down-regulation of miR-384 had opposite effects. EMT facilitates GC occurrence and progression. During EMT process, epithelial cells acquire mesenchymal characteristics, making gastric cancer cells more prone to detachment from primary site and dissemination via lymphatic system and bloodstream to more body parts, thereby forming metastatic lesions \u003csup\u003e[\u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e]\u003c/sup\u003e. SNAI1, ZEB1, TWIST1, E-cadherin, and N-cadherin are EMT-related proteins\u003csup\u003e[\u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e]\u003c/sup\u003e, and their expression is also modulated via miR-384.\u003c/p\u003e \u003cp\u003eThe regulating mechanism of miR-384 was then By bioinformatic analysis, the targeted gene of miR-384 was explored. It was found that CTNNB1 can be bind with miR-384, which was further verified. CTNNB1 is responsible for encoding β-catenin, the crucial component of Wnt pathway \u003csup\u003e[\u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e, \u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e18\u003c/span\u003e]\u003c/sup\u003e. Abnormal activation of Wnt signaling pathway is closely associated with the occurrence and development of various tumors. In hepatic cancer, CTNNB1 is one of the oncogenes with the highest mutation frequency. Activated β-catenin not only initiates the development of liver tumors but also exacerbates the progression of hepatic cancer mediated by P53 deficiency or hepatitis B virus infection. Polymorphisms in the CTNNB1 gene are associated with prognosis and survival in GC patients, with rs4135385 locus serving as an independent predictor of prognosis for non-cardia gastric cancer \u003csup\u003e[\u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e19\u003c/span\u003e]\u003c/sup\u003e. Another study found that the miR-200a/b/429 cluster can regulate the expression of CTNNB1, thereby influencing GC cell proliferation. According to our findings, miR-384 affected the nuclear translocation of CTNNB1. The cytoplasmic accumulation of β-catenin and its subsequent nuclear transport contribute to its binding to transcription factors such as T-cell factor/lymphoid enhancer factor (TCF/LEF). This binding activates downstream target transcription, including c-Myc, Axin2, CCND1, and CD44. These target genes regulate various processes in GC cells, including growth, migration, apoptosis and differentiation \u003csup\u003e[\u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e20\u003c/span\u003e]\u003c/sup\u003e. Moreover, miR-384 targeting CTNNB1 inhibited GC tumor growth and regulated the expressions of SNAI1, ZEB1, TWIST1, E-cadherin, and N-cadherin. The research limitations of this paper include: 1. The sample size of GC and matched non-carcinoma tissues mentioned in this paper may not be sufficiently large, which may limit the generality and reliability of the research findings. 2 Although the paper employed cell cultures and animal models to study the function of miR-384, these models may not fully simulate the complex physiological environment within the human body. 3 This study has identified CTNNB1 as miR-384\u0026rsquo;s target gene, but deeper molecular mechanisms underlying this relationship remain to be investigated.\u003c/p\u003e \u003cp\u003eIn conclusion, miR-384 suppresses GC cell proliferation and EMT progress, and enhances their apoptosis via CTNNB1. This research provides new candidate therapeutic targets for GC. New therapeutic strategies can be further explored by regulating the expression of miR-384 or developing inhibitors targeting CTNNB1.\u003c/p\u003e"},{"header":"Declarations","content":"\u003cp\u003e\u003cstrong\u003eConflicts of interest\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe authors confirm that there are no conflicts of interest\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eFunding\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThis work is supported by The Startup Fund for Scientific Research, the Fujian Medical University 2021QH1265.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eData Availability\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe corresponding author is responsible for all data. It can be obtained by contact.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eEthics approval and consent to participate\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe present work followed the Declaration of Helsinki and gained approval from ethics committee of Zhangzhou Affiliated Hospital of Fujian Medical University.\u003c/p\u003e\n\u003cp\u003eThe animal experiments gained approval from ethics committee of Zhangzhou Affiliated Hospital of Fujian Medical University.\u003c/p\u003e\n\u003cp\u003eThe methods were conducted following corresponding guidelines and regulations.\u003c/p\u003e\n\u003cp\u003eThe methods were reported following ARRIVE guidelines.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConsent for publication\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eNot applicable\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAuthors\u0026rsquo; contributions\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eRongjie Huang, Yubing Chen and Guoping Huang: Conceptualization; Formal analysis; Methodology;Writing - original draft; Validation; Resources.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eMingqiao Lian, Mingjie Lian, Lixiong Luo, Weilong Lian, and Zebin Chen: Data curation; Investigation; Software; Writing - review \u0026amp; editing.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eYangxin Zhang and Jianming Zheng: Formal analysis; Resources;Writing - review \u0026amp; editing;Visualization.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eQiuxian Chen and Lisheng Cai: Methodology; Project administration; Supervision;Writing - review \u0026amp; editing; Validation.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eThe authors agree to the final manuscript.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAcknowledgements\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eNot applicable\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\n\u003cli\u003eZeng Y, Jin R U. Molecular pathogenesis, targeted therapies, and future perspectives for gastric cancer[J]. Semin Cancer Biol, 2022,86(Pt 3):566-582.\u003c/li\u003e\n\u003cli\u003eGrantham T, Ramachandran R, Parvataneni S, et al. Epidemiology of Gastric Cancer: Global Trends, Risk Factors and Premalignant Conditions[J]. J Community Hosp Intern Med Perspect, 2023,13(6):100-106.\u003c/li\u003e\n\u003cli\u003eThrift A P, Nguyen T H. Gastric Cancer Epidemiology[J]. Gastrointest Endosc Clin N Am, 2021,31(3):425-439.\u003c/li\u003e\n\u003cli\u003eOuyang J, Xie Z, Lei X, et al. Clinical crosstalk between microRNAs and gastric cancer (Review)[J]. Int J Oncol, 2021,58(4).\u003c/li\u003e\n\u003cli\u003eZare A, Ganji M, Omrani M D, et al. Gastric Cancer MicroRNAs Meta-signature[J]. Int J Mol Cell Med, 2019,8(2):94-102.\u003c/li\u003e\n\u003cli\u003eYu X, Zhang Y, Luo F, et al. The role of microRNAs in the gastric cancer tumor microenvironment[J]. Mol Cancer, 2024,23(1):170.\u003c/li\u003e\n\u003cli\u003eLiu X, Ma R, Yi B, et al. MicroRNAs are involved in the development and progression of gastric cancer[J]. Acta Pharmacol Sin, 2021,42(7):1018-1026.\u003c/li\u003e\n\u003cli\u003eZhang J, Yu D, Ji C, et al. Exosomal miR-4745-5p/3911 from N2-polarized tumor-associated neutrophils promotes gastric cancer metastasis by regulating SLIT2[J]. Mol Cancer, 2024,23(1):198.\u003c/li\u003e\n\u003cli\u003eBai P S, Xia N, Sun H, et al. Pleiotrophin, a target of miR-384, promotes proliferation, metastasis and lipogenesis in HBV-related hepatocellular carcinoma[J]. J Cell Mol Med, 2017,21(11):3023-3043.\u003c/li\u003e\n\u003cli\u003eJiang M, Yun Q, Shi F, et al. Downregulation of miR-384-5p attenuates rotenone-induced neurotoxicity in dopaminergic SH-SY5Y cells through inhibiting endoplasmic reticulum stress[J]. Am J Physiol Cell Physiol, 2016,310(9):C755-C763.\u003c/li\u003e\n\u003cli\u003eXu Q, Ou J, Zhang Q, et al. Effects of Aberrant miR-384-5p Expression on Learning and Memory in a Rat Model of Attention Deficit Hyperactivity Disorder[J]. Front Neurol, 2019,10:1414.\u003c/li\u003e\n\u003cli\u003eGuo Q, Zheng M, Xu Y, et al. MiR-384 induces apoptosis and autophagy of non-small cell lung cancer cells through the negative regulation of Collagen alpha-1(X) chain gene[J]. Biosci Rep, 2019,39(2).\u003c/li\u003e\n\u003cli\u003eShi Z, Zhang H, Jie S, et al. Long non-coding RNA SNHG8 promotes prostate cancer progression through repressing miR-384 and up-regulating HOXB7[J]. J Gene Med, 2021,23(3):e3309.\u003c/li\u003e\n\u003cli\u003eZeng X, Liao H, Wang F. MicroRNA-384 inhibits nasopharyngeal carcinoma growth and metastasis via binding to Smad5 and suppressing the Wnt/beta-catenin axis[J]. Cytotechnology, 2021,73(2):203-215.\u003c/li\u003e\n\u003cli\u003eLi S, Cong X, Gao H, et al. Tumor-associated neutrophils induce EMT by IL-17a to promote migration and invasion in gastric cancer cells[J]. J Exp Clin Cancer Res, 2019,38(1):6.\u003c/li\u003e\n\u003cli\u003eWu H T, Zhong H T, Li G W, et al. Oncogenic functions of the EMT-related transcription factor ZEB1 in breast cancer[J]. J Transl Med, 2020,18(1):51.\u003c/li\u003e\n\u003cli\u003eCheng S Y, Wu A, Batiha G E, et al. Identification of DPP4/CTNNB1/MET as a Theranostic Signature of Thyroid Cancer and Evaluation of the Therapeutic Potential of Sitagliptin[J]. Biology (Basel), 2022,11(2).\u003c/li\u003e\n\u003cli\u003eLedinek Z, Sobocan M, Knez J. The Role of CTNNB1 in Endometrial Cancer[J]. Dis Markers, 2022,2022:1442441.\u003c/li\u003e\n\u003cli\u003eTanabe S, Aoyagi K, Yokozaki H, et al. Regulation of CTNNB1 signaling in gastric cancer and stem cells[J]. World J Gastrointest Oncol, 2016,8(8):592-598.\u003c/li\u003e\n\u003cli\u003eZhang X, Dong N, Hu X. Wnt/beta-catenin Signaling Inhibitors[J]. Curr Top Med Chem, 2023,23(10):880-896.\u003c/li\u003e\n\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":true,"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":"[email protected]","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":"miR-384, gastric cancer, CTNNB1, EMT, proliferation","lastPublishedDoi":"10.21203/rs.3.rs-6248730/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-6248730/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003e\u003cem\u003eBackground: \u003c/em\u003eMicroRNAs are important for gastric cancer (GC) EMT. This work focused on investigating how miR-384 affected GC and elucidating underlying mechanisms involved.\u003c/p\u003e\n\u003cp\u003e\u003cem\u003eMethods\u003c/em\u003e: miR-384 levels within GC and matched non-tumor tissues were determined through RT-qPCR. GC cells underwent miR-384 mimic or inhibitor transfection to investigate cell proliferation, invasion and EMT. Bioinformatic analysis was conducted to predict miR-384’s target mRNA. Also, rescued experiments were carried out for verifying targeted binding of miR-384 to CTNNB1. Furthermore, we conducted \u003cem\u003ein vivo\u003c/em\u003e experiments for analyzing the effect of miR-384.\u003c/p\u003e\n\u003cp\u003e\u003cem\u003eResults\u003c/em\u003e: miR-384 expression declined within GC tumor tissue and cells. MiR-384 inhibited GC cell growth and migration while promoting their apoptosis. From bioinformatics analysis, we found that miR-384 targeted CTNNB1. MiR-384 inhibits the expression and nuclear translocation of CTNNB1, and regulated EMT and proliferation of GC cells. Moreover, miR-384 was targeting CTNNB1 inhibited GC tumor growth.\u003c/p\u003e\n\u003cp\u003e\u003cem\u003eConclusion\u003c/em\u003e: miR-384 suppresses GC cell proliferation and EMT progress, and enhances their apoptosis via CTNNB1.\u003c/p\u003e","manuscriptTitle":"miR-384 targeting CTNNB1 regulates EMT and inhibits proliferation in gastric cancer","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2025-03-19 11:44:46","doi":"10.21203/rs.3.rs-6248730/v1","editorialEvents":[{"type":"communityComments","content":0}],"status":"published","journal":{"display":true,"email":"[email protected]","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":"7495461f-9fa1-4b59-8079-2a1f3d81039a","owner":[],"postedDate":"March 19th, 2025","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"posted","subjectAreas":[],"tags":[],"updatedAt":"2025-03-31T11:53:29+00:00","versionOfRecord":[],"versionCreatedAt":"2025-03-19 11:44:46","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-6248730","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-6248730","identity":"rs-6248730","version":["v1"]},"buildId":"8U1c8b4HqxoKbykW_rLl7","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}