CRISPR-Based Dissection of microRNA-23a~27a~24-2 Cluster Functionality in Hepatocellular Carcinoma

CRISPR-Based Dissection of microRNA-23a~27a~24-2 Cluster Functionality in Hepatocellular Carcinoma | 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 CRISPR-Based Dissection of microRNA-23a~27a~24-2 Cluster Functionality in Hepatocellular Carcinoma Lizhong Wang, Mengying Cui, Zhichao Liu, Shuaibin Wang, Sejong Bae, and 3 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-3885203/v1 This work is licensed under a CC BY 4.0 License Status: Published Journal Publication published 07 Aug, 2024 Read the published version in Oncogene → Version 1 posted 11 You are reading this latest preprint version Abstract The miR-23a ~ 27a ~ 24 − 2 cluster, commonly upregulated in diverse cancers, including hepatocellular carcinoma (HCC), raises questions about the specific functions of its three mature miRNAs and their integrated function. Utilizing CRISPR knockout (KO), CRISPR interference (CRISPRi), and CRISPR activation (CRISPRa) technologies, we established controlled endogenous miR-23a ~ 27 ~ a24-2 cell models to unravel their roles and signaling pathways in HCC. Both miR-23a KO and miR-27a KO displayed reduced cell growth in vitro and in vivo , revealing an integrated oncogenic function. Functional analysis indicated cell cycle arrest, particularly at the G2/M phase, through the downregulation of CDK1/cyclin B activation. High-throughput RNA-seq, combined with miRNA target prediction, unveiled the miR-23a/miR-27a-regulated gene network, validated through diverse technologies. While miR-23a and miR-27a exhibited opposing roles in cell migration and mesenchymal-epithelial transition, an integrated CRISPRi/a analysis suggested an oncogenic role of the miR-23a ~ 27a ~ 24 − 2 cluster in cell migration. This involvement potentially encompasses two signaling axes: miR-23a-BMPR2 and miR-27a-TMEM170B in HCC cells. In conclusion, our CRISPRi/a study provides a valuable tool for comprehending the integrated roles and underlying mechanisms of endogenous miRNA clusters, paving the way for promising directions in miRNA-targeted therapy interventions. Biological sciences/Cancer/Gastrointestinal cancer/Liver cancer Biological sciences/Molecular biology/Non-coding RNAs microRNA hepatocellular carcinoma CRISPR tumor progression signaling pathway Figures Figure 1 Figure 2 Figure 3 Figure 4 Figure 5 Figure 6 Figure 7 Figure 8 Introduction MicroRNAs (miRNAs or miRs) are endogenous, small non-coding RNAs involved in post-transcriptional regulation, leading to mRNA cleavage or translation repression of target genes. This regulatory process influences various biological phenomena such as cell differentiation, proliferation, apoptosis, and metabolism 1 . Remarkably, a single microRNA can regulate multiple genes, and even subtle changes in miRNA expression levels can have profound effects on biological functions 2 . Of particular importance are clustered miRNAs, which are located at the same locus in the genome and transcribed as a single primary miRNA (pri-miRNA). Unfortunately, the significance of these clustered miRNAs has often been overlooked 3 . Given the interactive and complex nature of the regulatory network between miRNAs and mRNAs, it becomes essential to comprehensively understand the regulation, properties, and biological functions of miRNAs when they are organized into clusters. The miR-23a‐27a‐24‐2 cluster located on chromosome 9q22 encodes a pri-miRNA that consists of three individual miRNAs: miR-23a, miR-27a, and miR-24 4, 5 . These three miRNAs function independently, as they regulate distinct target genes 4, 5 . Consequently, the miR-23a ~ 27a ~ 24 − 2 cluster plays diverse roles in processes such as development, tumorigenesis, invasion, metastasis, vascular remodeling, tumor immunity, and drug resistance 5 . However, despite its significance, studies on the individual mature miRNAs (miR-23a, miR-27a, miR-24) within this cluster have yielded inconclusive results. Addressing these inconsistencies requires an integrated functional analysis of the endogenous miR-23a ~ 27a ~ 24 − 2 cluster alongside the individual mature miRNAs. In human cancers, including hepatocellular carcinoma (HCC), the expression of miR‐23a‐27a‐24‐2 pri-miRNA is upregulated compared to normal tissues 6 . Nevertheless, investigations into the three mature miRNAs within the miR-23a ~ 27a ~ 24 − 2 cluster in HCC have reported inconsistent results for miR-23a 7–15 , miR-27a 16–25 , and miR-24 26–29 . This inconsistency suggests their potential involvement in distinct cell signaling pathways, contributing to self‐regulation and feedback loops under diverse circumstances 30, 31 . Traditional methods involving overexpression through transfection with plasmids or RNA interference techniques may introduce exogenous variables, potentially leading to spurious effects and not accurately reflecting endogenous miRNA dynamics. Moreover, these approaches may not capture the comprehensive expression profile governing clustered miRNAs. In the present study, we addressed these challenges by establishing an endogenous miR-23a ~ 27a ~ 24 − 2 controllable system using CRISPR technologies. Leveraging CRISPR genomic editing, we individually knocked out each endogenous mature miRNA within the miR-23a ~ 27a ~ 24 − 2 cluster in HCC cells to discern the functional roles of individual miRNAs. Furthermore, employing CRISPR epigenomic editing through CRISPR interference (CRISPRi) and CRISPR activation (CRISPRa), we precisely modulated the expression of pri-miR-23a ~ 27a ~ 24 − 2 and simultaneously controlled the co-expression of its three mature miRNAs, providing insights into the overall regulation of clustered miRNAs. In addition, we investigated the functional roles of both the miR-23a ~ 27a ~ 24 − 2 cluster and its individual mature miRNAs in HCC cell proliferation, apoptosis, and migration. Utilizing this novel platform, we conducted a comprehensive analysis to dissect the functional roles and identify underlying targets and signaling pathways associated with the microRNA-23a-27a-24-2 cluster in HCC cells. Results Characterization of miR-23a ~ 27a ~ 24 − 2 expression and its survival outcomes in HCC tissues and cell lines The transcription of three mature miRNAs from the miR-23a ~ 27a ~ 24 − 2 cluster is regulated by the same promoter (Fig. 1 A). The Cancer Genome Atlas (TCGA) dataset analysis showed no significant difference in the expression of miR-23a ( p = 0.980) and miR-27a ( p = 0.129), with only a significant difference in the expression of miR-24-2 ( p = 0.04) between HCC and normal liver tissues (Supplementary Figures S1 ). However, survival analysis revealed poor overall survival for high expression of miR-23a ( p = 0.04), miR-27a ( p = 0.017), and not miR-24 ( p = 0.03) compared to low expression of these miRNAs in HCC patients (Figs. 1 B-D). Similarly, in the Kaplan-Meier Plotter RNA-sequencing (RNA-seq) dataset, Cox regression analysis revealed poor overall survival for high expression of miR-23a (hazard ratio (HR) = 1.67, p = 0.0052), miR-27a (HR = 1.65, p = 0.0057), and miR-24 (HR = 1.77, p = 0.0021) compared to low expression of these miRNAs in HCC patients. However, the expression of these miRNAs in these datasets is likely from pri-mRNAs of the miR-23a ~ 27a ~ 24 − 2 cluster. Next, we characterized the expression level of mature miRNAs in the miR-23a ~ 27a ~ 24 − 2 cluster in HEK293T, Huh7, and HepG2 cell lines using quantitative real-time PCR (qPCR). The expression of mature miR-23a-3p/5p, miR-27a-3p/5p, and miR-24-3p/5p was higher in HepG2 and Huh7 cells than in HEK293T cells, with the highest expression evident in HepG2 cells (Figs. 1 E-G). In particular, the mature 3p miRNAs (miR-23a-3p, miR-27a-3p, and miR-24-3p) were consistently expressed more than 10-fold higher in cells compared to the mature 5p miRNAs (miR-23a-5p, miR-27a-5p, miR-24-2-5p), indicating a predominant expression of 3p miRNAs in the miR-23a ~ 27a ~ 24 − 2 cluster. Thus, using the HepG2 cell line, we established miRNA KO HCC cell models and focused on the expression of 3p’ miRNAs as the main factors when choosing miRNA KO cell colonies. In addition, miR-24 is also expressed in the miR-23b ~ 27b ~ 24 − 1 cluster at 9q22.32. To reduce the complexity of our analysis, in the present study, we only focused on miR-23a and miR-27a. Establishment of miR-23a/miR-27a KO HepG2 cell models Using CRISPR/Cas9 genomic editing, we generated scramble and miR-23a/miR-27a KO HepG2 cell models. The miRNA expression in selected cell colonies was assessed by qPCR. As shown in Supplementary Figure S2 A, miR-23a KO markedly decreased the expression of miR-23a-3p in two clones, while varied expressions of miR-23a-5p were observed. Notably, miR-23a KO also led to decreased expressions of miR-27a-3p and miR-24-3p, but not miR-27a-5p and miR-24-5p in the two miR-23a KO clones. Furthermore, miR-27a KO reduced the expression of miR-27a-3p/5p and miR-24-3p/5p in two miR-27a KO clones (Supplementary Figure S2 B). However, miR-27a KO slightly increased the expression of miR-23a-3p while decreasing the expression of miR-23a-5p in the two miR-27a KO clones (Supplementary Figure S2 B). Next, we selected miR-23a KO clones 1 and 2 (miR-23a KO1 and KO2) and miR-27a KO clones 1 and 2 (miR-27a KO1 and KO2) for Sanger DNA sequencing. Supplementary Figures S2 C and S2D show a 55bp homozygous deletion in miR-23a KO1 and KO2, a 53bp homozygous deletion in miR-27a KO1, and a heterozygous 53bp deletion with a 40bp insertion in miR-27a KO2. Identification of the functional role of miR-23a and miR-27a in HepG2 cells Initially, we transfected HepG2 and Huh7 cells with miRNA mimics or inhibitors to elucidate the individual roles of miRNAs within the miR-23a ~ 27a ~ 24 − 2 cluster in the proliferation and migration of HCC cells. In HepG2 cells, the miR-27a-3p and miR-24-3p inhibitors notably reduced both cell proliferation and migration (Figs. 1 H-L). Surprisingly, the miR-23a-3p inhibitor did not influence cell proliferation but appeared to induce cell migration (Figs. 1 H-L). In Huh7 cells, the miR-23a-3p, miR-27a-3p, and miR-24-3p mimics induced cell proliferation (Figs. 1 M-Q). However, while the miR-27a-3p and miR-24-3p mimics promoted cell migration, the miR-23a-3p mimic seemed to inhibit cell migration (Figs. 1 M-Q). Subsequently, using our established KO cell models, we conducted various cell proliferation assays to assess the impact of miRNAs in the miR-23a ~ 27a ~ 24 − 2 cluster on HepG2 cell growth. In the MTT assay, cell growth was notably slower in miR-23a KO and miR-27a KO cells compared to scrambled cells (Fig. 2 A). The colony formation assay revealed reduced clone number and area in miR-23a KO or miR-27a KO cells compared with scrambled cells (Figs. 2 B-D). Remarkably, miR-27a played a dominant role in HepG2 cells compared to miR-23a, evident in the suppression of cell growth and colony formation. Similarly, in three-dimensional cell culture models, clone area was diminished in miR-23a KO or miR-27a KO cells compared with scrambled cells (Figs. 2 E and 2 F). However, only miR-27a KO resulted in a decrease in clone number, not observed in miR-23a KO compared with scrambled cells (Figs. 2 E and 2 G). To corroborate these in vitro findings, we subcutaneously injected scramble, miR-23a KO, and miR-27a KO HepG2 cells into NGS mice. Xenograft tumor growth and weights were notably reduced in mice with miR-23a KO or miR-27a KO cells compared to those with scrambled cells (Figs. 2 H-J). miR-23a KO and miR-27a KO inhibits cell proliferation through the cell cycle arrest in HepG2 cells To examine whether the impact of miR-23a and miR-27a on cell proliferation is mediated through apoptosis, we treated scramble, miR-23a KO, and miR-27a KO HepG2 cells with H 2 O 2 to induce apoptosis. However, both miR-23a KO and miR-27a KO did not appear to affect cell apoptosis before and after H 2 O 2 stimulation when compared to scrambled cells (Supplementary Figures S3A-D). This suggests that miR-23a KO or miR-27a KO may not influence the apoptosis of HepG2 cells. Subsequently, to investigate whether the effect of miR-23a and miR-27a on cell proliferation is related to the regulation of cell cycle progression, we arrested cells at the G0-G1 phase by serum deprivation for 48 hours in scramble, miR-23a KO, and miR-27a KO HepG2 cells. After 8 hours of serum stimulation, no significant differences were observed among the three groups in the S phase. However, cells entering the G2/M phase were likely decreased in the miR-27a KO group (Figs. 3 A-B). After 22 hours of serum stimulation, fewer cells entered the G2/M phase in both miR-23a KO and miR-27a KO groups (Figs. 3 A-B). To corroborate the cell cycle results and further assess the impact of miR-23a/miR-27a on cell proliferation, BrdU staining was performed. At 8 hours after serum stimulation, 37.7% of scrambled cells, 34.1% of miR-23a KO cells, and 29.4% of miR-27a KO cells were in the S phase, with no significant differences observed between scrambled and miRNA KO cells (Figs. 3 C-D). After 16 hours of serum stimulation, 39.9%, 58%, and 64.9% of cells entered the S phase, respectively, with no significant difference among the groups (Figs. 3 C-D). However, fewer miR-23a KO cells at 8 hours and miR-27a KO cells at 16 hours entered the G2/M phase compared to scrambled cells (Figs. 3 C-D). To unravel the molecular mechanism underlying the growth suppression caused by miR-23a/miR-27a KO, we assessed the expression of cell cycle regulatory proteins through Western blot analysis. As depicted in Fig. 3 E, both miR-23a KO and miR-27a KO led to a reduction in the expression of cyclin A and cyclin B, while cyclin D and cyclin E remained unchanged in the cells. Moreover, phospho-CDK1, essential for G2/M phase transitions, exhibited an increase in miR-23a KO or miR-27a KO cells (Fig. 3 E). This suggests that the elevated phospho-CDK1 in miRNA KO cells may contribute to cell cycle arrest at the G2/M phase. Notably, the expressions of p53, p21 (essential for G1 arrest), and c-Myc (critical in G1/S progression) 32 remained unaltered among the experimental groups (Fig. 3 E). Furthermore, the increased expression of cyclin B and phospho-CDK1 observed in miR-23a KO or miR-27a KO xenograft tumors compared to scrambled xenograft tumors was also validated (Figs. 3 F-H). These findings suggest that miR-23a KO and miR-27a KO may promote cell proliferation through CDK1-dependent cell cycle arrest at the G2/M phase. Regulation of cell cycle progression and associated gene network by miR-23a and miR-27a in HepG2 Cells To unravel the regulatory gene network influenced by miR-23a and miR-27a, we conducted RNA-seq using scramble HepG2 cells as the control group and miR-23a KO/miR-27a KO HepG2 cells as the case groups. As depicted in Fig. 4 A and detailed in Supplementary Table S1 A-B, miR-23a KO led to the up-regulation of 2599 genes and the down-regulation of 795 genes (> 1.5-fold change, q 1.5-fold change, q < 0.001) compared to control cells (Fig. 4 B and Supplementary Table S1 C-D). Furthermore, potential target genes of miR-23a and miR-27a were predicted using the public miRNA TargetScan database (Supplementary Table S2 ). Seven candidate genes were selected based on the criteria of ( 1 ) Fold change > 1.5, q value < 0.001 in both miR-23a KO and miR-27a KO groups, and ( 2 ) Genes binding to the sequences of both miR-23a-3p and miR-27a-3p predicted by TargetScan (Fig. 4 C and Supplementary Table S3A-C). Next, we employed Gene Set Enrichment Analysis (GSEA) to identify enriched gene sets in miR-23a KO or miR-27a KO cells. As illustrated in Fig. 4 D and detailed in Supplementary Table S4, the up-regulated genes were predominantly associated with cell cycle regulation, encompassing E2F target, G2/M checkpoint, MYC target, mitotic spindle, and DNA repair. Additionally, the heat map of the top 30 core enrichment genes with a high "Rank Metric Score" in each gene set is presented in Fig. 4 E. Finally, among the seven-candidate target genes, PURA was identified as enriched in the G2/M checkpoint gene set (Fig. 4 C and Supplementary Table S5) and co-regulated by miR-23a and miR-27a (Supplementary Figure S4). Identification of the miR-23a ~ 27a ~ 24 − 2 cluster regulated gene network and its integrative function in HCC cells To elucidate the collaborative function of miRNAs within the miR-23a ~ 27a ~ 24 − 2 cluster, we established endogenous miR-23a ~ 27a ~ 24 − 2 CRISPR/dCas9 controllable HepG2 cell models. Utilizing the doxycycline (Dox)-inducible dCas9-VP64-p65-Rta (dCas9-VPR) for CRISPRa and Dox-inducible dCas9-KRAB for CRISPRi, we aimed to regulate the transcriptional activity of the miR-23a ~ 27a ~ 24 − 2 cluster in HepG2 cells (Figs. 5 A and 5 F). Different sequence-specific single guide RNAs (sgRNAs) in the promoter region of miR-23a ~ 27a ~ 24 − 2 were designed, and the transduced efficiency of these sgRNAs was confirmed through immunofluorescence and qPCR (Figs. 5 B and 5 G). Following Dox addition, the CRISPR/dCas9 system was induced for seven days. In the CRISPRi system, the expression of miR-23a-3p, miR-27a-3p, and miR-24-3p gradually decreased in cells transfected with sgRNA1 and sgRNA2 (Figs. 5 C). Conversely, in the CRISPRa system, the expression of miR-23a-3p, miR-27a-3p, and miR-24-3p progressively increased in cells transfected with sgRNA3 and sgRNA4 (Figs. 5 H). To validate the gene network and signaling pathway involved in the miR-23a ~ 27a ~ 24 − 2 cluster, we identified genes enriched in the G2/M phase using KEGG mapper-cell cycle and marked the enriched genes in red (Supplementary Figure S4). Most "red" genes were associated with the G2/M phase, consistent with the in vitro and in vivo results. Subsequently, genes enriched in the G2/M phase of the KEGG mapper-cell cycle were further investigated using our established endogenous miR-23a ~ 27a ~ 24 − 2 controllable HepG2 cell model. Nine genes were examined in the CRISPRi system with sgRNAs ( PURA , CDC27 , STAG1 , TTK , MAD2L1 , PLK1 , BUB1 , SMC1A , and CDK1 ) (Supplementary Figure S4). The expression of PURA , CDC27 , STAG1 , and TTK dynamically changed under the condition of Dox induction (Fig. 5 D). These four genes were validated in the CRISPRa system with sgRNAs, showing dynamic changes in expression after Dox induction (Fig. 5 I). Likewise, we established endogenous miR-23a ~ 27a ~ 24 − 2 CRISPRi/a controllable cell models in Huh7 cells (Supplementary Figures S5A-C and S5F-H). These four genes were further confirmed in the CRISPRi/a system in Huh7 cells, showing dynamic changes in expression after Dox induction (Supplementary Figures S5D and S5I). Next, we examined the functional implications of manipulating the miR-23a ~ 27a ~ 24 − 2 cluster in HepG2 and Huh7 cells. The introduction of Dox induced a decrease in cell proliferation in CRISPRi HepG2 and Huh7 cells (Fig. 5 E and Supplementary Figure S5E), while CRISPRa HepG2 and Huh7 cells exhibited an increase in cell proliferation following Dox induction (Fig. 5 J and Supplementary Figure S5J). These findings strongly suggest an oncogenic role of the miR-23a ~ 27a ~ 24 − 2 cluster in HCC cells. To gain deeper insights into the regulatory mechanisms of this miRNA cluster, we investigated the impact of 3p’ miR-23a/27a/24 mimics and inhibitors on cell proliferation in miR-23a ~ 27a ~ 24 − 2 CRISPRi/a HepG2 and Huh7 cells. Upon Dox induction, the miR-23a-3p and miR-27a-3p mimics enhanced cell proliferation in miR-23a ~ 27a ~ 24 − 2 CRISPRi cells, while the miR-23a-3p and miR-27a-3p inhibitors reduced cell proliferation in miR-23a ~ 27a ~ 24 − 2 CRISPRa cells (Supplementary Figures S6A-D). However, miR-24-3p mimic and inhibitor did not exhibit effects on cell proliferation. These results suggest that miR-23a and miR-27a contributes to the integrative oncogenic function of the miR-23a ~ 27a ~ 24 − 2 cluster in HCC cells. miR-23a/miR-27a co-target PURA directly to promote cell proliferation in HepG2 cells To investigate the interaction between miR-23a-3p/miR-27a-3p and its target mRNAs, we conducted a miRNA-mRNA interaction analysis using miRNA target immunoprecipitation (IP) with Argonaute proteins (Ago1/2/3) following transfection with the miR-23a-3p/miR-27a-3p mimic in HepG2 cells (Fig. 6 A). The Ago IP analysis revealed a direct binding of PURA mRNA with Ago1/2/3 proteins in the presence of miR-23a/miR-27a compared to the scrambled miRNA control (Fig. 6 B), supporting the direct interaction of miR-23a/miR-27a with PURA mRNA in HepG2 cells. However, Figs. 6 C and 6 D demonstrated that STAG1 mRNA bound to the sequence of miR-27a but not the sequence of miR-23a, and TTK did not bind to either miR-23a or miR-27a. To delve deeper into the mechanism of miR-23a/miR-27a-mediated transcriptional regulation of PURA , we evaluated the impact of miR-23a/miR-27a KO, mimic, and inhibitor on PURA transcription in HepG2 cells. As depicted in Fig. 6 E, compared to the scrambled cells, PURA expression was higher in miR-23 KO cells, lower in cells transfected with miR-23a-3p mimic, and unchanged in cells transfected with miR-23a-3p inhibitor. Similar results were observed in miR-27a KO cells or cells transfected with mimic or inhibitor (Fig. 6 E). Western blot analysis also revealed elevated PURA expression in miR-23a KO and miR-27a KO cells compared to scrambled cells (Fig. 6 F). Consistent results were confirmed by immunohistochemical staining (IHC) in miR-23a KO and miR-27a KO xenograft tumors relative to scrambled xenograft tumors (Fig. 6 G). Subsequent sequence alignment analysis identified potential miR-23a-3p/miR-27a-3p targeting sites in the PURA 3’- untranslated region (UTR) (Fig. 6 H). Using a pmiR-luciferase reporting system, we elucidated the post-transcriptional regulation mechanism of PURA by miRNAs. Transfection of miR-23a-3p/miR-27a-3p mimics reduced the luciferase activity of the wild-type PURA 3’-UTR (Figs. 6 I and 6 J). However, deletion of the miR-23a-3p-targeting sequence (AAUGUGA)/miR-27a-3p-targeting sequence (ACUGUGA) in the PURA 3’-UTR rescued the luciferase activity of PURA 3’-UTR in HepG2 cells transfected with miR-23a-3p/miR-27a-3p mimics (Figs. 6 I and 6 J). Confirming the impact of PURA on cell proliferation, we assessed cell growth in miR-23a KO/miR-27a KO cells transfected with PURA siRNA (Fig. 6 K). As depicted in Figs. 6 L and 6 M, the suppression of cell growth in miR-23a/miR-27a KO HepG2 cells was partly rescued after PURA silencing. Validation of miR-23a/miR-27a-regulated gene network in HepG2 cells To confirm the regulatory impact of miR-23a/miR-27a on gene expression, Western blot analysis revealed that STAG1 was up-regulated, while TTK was down-regulated in miR-23a KO and miR-27a KO cells, respectively, compared to scrambled control cells (Fig. 6 N). Subsequently, we introduced PURA siRNAs into scrambled HepG2 cells to investigate whether the regulation of STAG1 and TTK was PURA-dependent. The expression of STAG1 decreased, whereas TTK increased after PURA siRNA silencing (Fig. 6 N), indicating a PURA-dependent expression pattern for STAG1 and TTK. Further investigation into the miR-23a/miR-27a KO effects on the PURA-STAG1/TTK axes and their regulation in both scramble and miR-23a/miR-27a KO HepG2 cells revealed intriguing insights. For STAG1 expression analysis, miR-23a KO increased the expression of STAG1, but this effect was diminished by PURA siRNA in miR-23a KO cells (Fig. 6 O). Conversely, miR-23a-3p mimic decreased STAG1 expression, and this effect was rescued by PURA siRNA in miR-23a-3p mimic-transfected HepG2 cells (Fig. 6 O), indicating a miR-23a-PURA-STAG1 axis. Likewise, miR-27a KO increased STAG1 expression, but this increase was reversed by PURA siRNA in miR-27a KO cells (Fig. 6 O). However, miR-27a-3p mimic decreased STAG1 expression, and PURA siRNA did not rescue this decrease in miR-27a-3p mimic-transfected HepG2 cells (Fig. 6 O), suggesting a PURA-independent miR-27a-STAG1 axis. Notably, miR-27a may directly target STAG1 in the miRNA target IP assay (Fig. 6 C), further supporting a PURA-independent miR-27a-STAG1 axis. Effect of miR-23a/miR-27 and its cluster in cell migration and epithelial-mesenchymal transition (EMT) in HCC cells Given the reported role of the miR-23a ~ 27a ~ 24 − 2 cluster in promoting cell migration 33 and the observed regulation of cell migration by miR-23a-3p/miR-27a-3p mimics (Figs. 1 I-L), we investigated the impact of miR-23a/miR-27a KO on cell migration in HepG2 cells. Utilizing scratch assays and Transwell assays, we found that cell migration was accelerated in miR-23a KO cells and decelerated in miR-27a KO cells compared to scrambled control cells (Figs. 7 A-D). Additionally, IHC analysis revealed that, in miR-23a KO xenograft tumors, E-cadherin expression decreased while N-cadherin increased, indicating a role for miR-23a in promoting cell migration and EMT. Conversely, miR-27a KO xenograft tumors exhibited an opposite trend, with increased E-cadherin and decreased N-cadherin expression (Fig. 7 E), suggesting a distinct role for miR-27a in these processes. Next, we investigated the impact of manipulating the miR-23a ~ 27a ~ 24 − 2 cluster on cell migration in both HepG2 and Huh7 cells. Upon Dox induction, CRISPRi inhibited cell migration in HepG2 and Huh7 cells. The introduction of miR-23a-3p mimic further enhanced cell migration, whereas miR-27a-3p mimic reduced cell migration. Interestingly, miR-24-3p mimic did not significantly alter cell migration (Figs. 7 G-J and Supplementary Figure S7A-D). Conversely, CRISPRa did not enhance cell migration. However, miR-27a-3p inhibitor, but not miR-23a-3p and miR-24-3p inhibitors, reduced cell migration (Figs. 7 K-N and Supplementary Figure S7E-H). This differential impact of miR-23a, miR-27a, and miR-24 on cell migration suggests distinct roles for each miRNA within the miR-23a ~ 27a ~ 24 − 2 cluster, further underscoring the integrative oncogenic function of this cluster in HCC cells. To understand the molecular mechanisms underlying the miR-23a ~ 27a ~ 24 − 2 cluster-regulated migration of HCC cells, we investigated proteins involved in EMT and relevant regulatory molecules. In HepG2 cells, miR-23a KO decreased E-cadherin but increased N-cadherin expression, while miR-27a had the opposite effect (Fig. 7 F). Among EMT-related or upstream regulatory molecules, only Snail exhibited inter-group differences, indicating that the miR-23a ~ 27a ~ 24 − 2 cluster appear to influence EMT through the regulation of Snail (Fig. 7 F). Identification of miR-23a/miR-27 signaling axes in HCC cell migration Upon re-analyzing the candidate target genes (Fig. 4 C), we identified BMPR2 as a target gene of miR-23a that regulates EMT through the BMP-Smad-Snail signaling pathway 34 . In HepG2 cells, we observed up-regulation of BMPR2 in miR-23a KO cells, while no significant difference in BMPR2 was observed in miR-27a KO cells compared to scrambled cells (Fig. 8 A). miRNA target IP further confirmed the direct binding of miR-23a, but not miR-27a, to the BMPR2 3'-UTR (Fig. 8 B). Silencing BMPR2 using siRNAs rescued the enhanced cell migration observed in miR-23a KO HepG2 cells (Figs. 8 C-E). Transfecting miR-23a-3p mimics into miR-23a KO cells rescued the expression of E-cadherin, reduced the expression of N-cadherin, and led to decreases in BMPR2, Snail, and phospho-Smad1 (Fig. 8 F). These findings suggest a miR-23a-BMPR2-Smad-Snail axis in the regulation of EMT signaling. Likewise, we identified TMEM170B as a potential target gene of miR-27a that regulates EMT via the TMEM170B-Twist-β-catenin signaling pathway 35 . Testing the effect of miR-23a/miR-27a on this EMT signaling in HepG2 cells, we found that TMEM170B was up-regulated in miR-27a KO cells but not in miR-23a KO cells compared to scrambled cells (Fig. 8 G). miRNA target IP validated the direct binding of miR-27a, but not miR-23a, to the TMEM170B 3'-UTR (Fig. 8 H). Silencing TMEM170B using siRNAs rescued the reduced cell migration observed in miR-27a KO HepG2 cells (Figs. 8 I-K). Transfecting miR-27a-3p mimics into miR-27a KO cells rescued the expression of TMEM170B and E-cadherin, induced the expression of N-cadherin and vimentin, and led to increases in Twist and nuclear β-catenin (Fig. 8 L). These results suggest a miR-27a-TMEM170B-Twist-β-catenin axis in the regulation of EMT signaling. Discussion The utilization of CRISPR/Cas9 for genetic and epigenetic editing holds promise as a tool for investigating the regulation and function of clustered miRNAs 36 . In this study, we employed CRISPR KO, CRISPRi, and CRISPRa approaches to dissect the functional role and underlying signaling of the miR-23a ~ 27a ~ 24 − 2 cluster in HCC cells. Either miR-23a KO or miR-27a KO resulted in reduced cell growth both in vitro and in vivo . Moreover, the endogenous miRNAs within the miR-23a ~ 27a ~ 24 − 2 cluster were effectively regulated by CRISPRi/a. Notably, using the CRISPRi/a approach, we identified an integrated oncogenic role of the miR-23a ~ 27a ~ 24 − 2 cluster in the proliferation of HCC cells. Functional analysis revealed that miR-23a KO and miR-27a KO induced cell cycle arrest at the G2/M phase by reducing CDK1/cyclin B activation in HCC cells. Furthermore, employing a high-throughput RNA-seq approach with miRNA target prediction, we identified the miR-23a/miR-27a-regulated gene network. Various analyses validated that miR-23a/miR-27a co-target PURA directly to promote cell proliferation in HepG2 cells. In addition, miR-23a and miR-27a exhibited opposite roles in cell migration and EMT. However, an integrated analysis by CRISPRi/a suggested an oncogenic role of the miR-23a ~ 27a ~ 24 − 2 cluster in cell migration may occur through an interaction of miR-23a-BMPR2-Smad-Snail axis and miR-27a-TMEM170B-Twist-β-catenin axis in HCC cells (Supplementary Figure S8). Given the involvement of miRNAs in the miR-23a ~ 27a ~ 24 − 2 cluster in various functions and signaling pathways in HCC 5 , depicting their integrative role and complete regulatory network is challenging. However, our established endogenous miRNA controllable system offers a comprehensive platform for identifying the functional role and underlying signaling of clustered miRNAs. In this study, we used CRISPR KO to assess the potential role and gene network of individual mature miR-23a/miR-27a in HCC cells. However, due to the joint transcription of miRNAs in the miR-23a ~ 27a ~ 24 − 2 cluster, miR-23a KO disrupted the expression of miR-27 and miR-24, while miR-27a KO affected the expression of miR-24 but unlikely changed the expression of miR-23a. Thus, the CRISPR KO approach is not ideal for defining the role of individual miRNAs from the miRNA cluster. Next, using CRISPRi/a, we addressed the role and gene network of the miR-23a ~ 27a ~ 24 − 2 cluster in HCC cells. Combining CRISPRi/a-mediated endogenous miRNA regulation with exogenous miRNA mimic and inhibitor intervention, we validated the role and gene network of individual mature miR-23a/miR-27a in HCC cells. Additionally, both the miR-23a ~ 27a ~ 24 − 2 and miR-23b ~ 27b ~ 24 − 1 clusters include miR-24 and encode the pri-miRNA transcript that composes miR-24 4 . To address the role of miR-24, CRISPR KO or CRISPRi/a should target both clusters for transcriptional regulation of miR-24. However, this approach may introduce more complexity to the CRISPR system, off-target effects, or complicate functional analysis between the two clusters. Therefore, we focused solely on miR-23a/miR-27a and did not establish the miR-24 KO in the HCC cell model. Recently, we have developed a flexible CRISPR/dCas9-based platform for complex gene regulation, allowing independent control of the expression of different genes (repression and activation) within the same cell, using two different S. pyogenes (Sp)-dCas9 and S. aureus (Sa)-dCas9 37 . This dual CRISPR platform for repression and activation may serve as an ideal tool for our future studies to distinguish the roles of the two miRNA clusters, including miR-24, within the same HCC cell. Our gene network analysis revealed that the enriched gene set in both miR-23a KO and miR-27a KO groups was predominantly associated with the cell cycle signaling network. Further analysis of the enriched genes in the KEGG map showed that the majority of these genes were concentrated in the G2/M phase of the cell cycle. This finding was consistent with the observed changes in cell cycle regulatory proteins at the G2/M phase, such as CDK1/cyclin B 38 . Using endogenous miR-23a ~ 27a ~ 24 − 2 controllable CRISPRi/a cell models, we confirmed dynamic changes in genes enriched in the G2/M phase based on miR-23a ~ 27a ~ 24 − 2 up-/down-regulation. The miR-23a ~ 27a ~ 24 − 2 cluster directly/indirectly regulated the gene network, including PURA , STAG1 , and TTK , in HCC cells. In HepG2 cells, miR-23a and miR-27a induced cell cycle progression by directly targeting PURA , implicating cancer cell proliferation by inhibiting cell cycle progression at G1-S or G2-M checkpoints 39 , resulting in increased HCC cell growth. MiR-23a and miR-27a targeted specific sites in the 3’-UTR of PURA to regulate post-transcription of PURA . Notably, the miR-23a and miR-27a-mediated proliferation phenotype was partly retrieved by PURA siRNA. However, another study also suggested that miR-23a may promote G1/S cell cycle transition in HCC 8 . Although in our study, a few relevant genes of the G1/S phase were enriched in the miR-23a KO group, we did not observe an apparent change in cell cycle progression and proteins of the G1/S phase. Furthermore, our data support the notion that miR-27a may play a dominant role in the regulation of G2/M cell cycle transition. Additionally, other studies suggest that miR-23a/miR-27a regulate apoptosis in HCC cells 6, 40 , but our analysis showed no significant change in apoptosis after miR-23a KO or miR-27a KO. Thus, our data suggest that miR-23a/miR-27a may synergistically induce cell cycle progression, promoting cell proliferation in HCC cells. The members of the miR-23a ~ 27a ~ 24 − 2 cluster integrally inhibit the aggressiveness of breast cancer cells by targeting NCOA1 , NLK , and RAP1B 41 . Additionally, the c-MYC-regulated miR-23a ~ 27a ~ 24 − 2 cluster promotes cell invasion and hepatic metastasis of breast cancer by targeting SPRY2 33 . Our CRISPR analysis is the first to provide an integrated and dynamic analysis supporting the idea that the miR-23a ~ 27a ~ 24 − 2 cluster promotes cell migration and EMT through a complex gene network in HCC cells. However, individual miR-23a/miR-27a have been reported to be associated with both tumor-promoting 42–49 and tumor-suppressing 18, 50–52 activities, depending on the specific context and cancer type. In this study, there are opposing effects between miR-23a (repression) and miR-27a (promotion) on cell migration and EMT in HCC cells, suggesting that miR-23a/miR-27a may play distinctive roles in tumor progression and metastasis through two different signaling axes, such as the miR-23a-BMPR2-Smad-Snail axis and the miR-27a-TMEM170B-Twist-β-catenin. Given an oncogenic role of the miR-23a ~ 27a ~ 24 − 2 cluster in cell migration and EMT, miR-27a may play a predominant role in cell migration and EMT of HCC cells. In addition, an early study has reported that, through miRNA mimic and inhibitor, miR-27a-3p inhibits the growth and metastasis of HCC cells 18 . Specifically, miR-27a-3p inhibits the cell migration, invasion, and EMT of HCC cells. Conversely, through miRNA KO with mimic and inhibitor, we identified an oncogenic role of miR-27a-3p in cell migration and EMT of HCC cells. The different results may be attributed to the potential effect of CRISPR KO on the transcription of the miR-23a ~ 27a ~ 24 − 2 cluster and its individual members, including miR-24. However, through CRISPRi/a with miRNA mimic and inhibitor, we validated an oncogenic role of miR-27a-3p in HCC cell migration. In conclusion, we developed an integrated CRISPR genetic and epigenetic approach to investigate the functional role and underlying signaling of the miR-23a ~ 27a ~ 24 − 2 cluster in HCC cells. Our CRISPR analysis offers a valuable research tool for dissecting the complex functions and underlying gene network of an endogenous miRNA cluster. Furthermore, this CRISPR approach provides new avenues for intervening in miRNA clusters, enabling an integrated analysis to determine the specific roles of individual miRNAs within the cluster. Materials and Methods Cell lines The hepatocellular carcinoma cell lines HepG2 and Huh7, as well as the human embryonic kidney cell line HEK293T, were procured from the American Type Culture Collection (ATCC, Rockville, Maryland). These cell lines were cultured for less than 6 months, authenticated through examination of morphology and growth characteristics, and confirmed to be mycoplasma-free. Short tandem-repeat analysis for DNA fingerprinting was also employed to verify the cell lines. All cell lines were cultured in Dulbecco's Modified Eagle's medium (DMEM) supplemented with 10% fetal bovine serum (FBS) under standard conditions of 37°C and 5% CO 2 . Antibodies Antibodies specific for the following proteins were used as primary antibodies for Western blot or IHC: Beta catenin (ab32572, 1:5000, Abcam, Cambridge, MA), beta IV Tubulin (ab179509, 1:5000, Abcam), CDC27 (A1954, 1:1000, Abclonal, Woburn, MA), BMPR2 (A16778, 1:1000, Abclonal), CDK1 (626901, 1:1000, Biolegend, San Diego, CA), CDK2 (643901, 1:1000, Biolegend), CDK4 (2906, 1:1000, Cell Signaling, Danvers, MA), c-Myc (5605, 1:1000, Cell Signaling), Cyclin A (644001, 1:1000, Biolegend), PURA (A9296, 1:1000 for Western blot and 1:100 for IHC, Abclonal), Cyclin B (647902, 1:1000 for Western blot and 1:100 for IHC, Biolegend), Cyclin D1 (ab134175, 1:5000, Abcam), Cyclin E (sc-247, 1:1000, Santa Cruz Biotechnology, Dallas, TX), E-cadherin (3195, 1:1000 for Western blot and 1:100 for IHC, Cell Signaling), GAPDH (2118, 1:5000, Cell Signaling), Ki67 (ab15580, 1:5000 for Western blot and 1:200 for IHC, Abcam), Lamin B (sc-374015, 1:5000, Santa Cruz Biotechnology), N-cadherin (844702, 1:1000 for Western blot and 1:100 for IHC, Biolegend), p21 (2947, 1:1000, Cell Signaling), p53 (sc-126, 1:1000, Santa Cruz Biotechnology), phospho-cdc2 (Tyr15) (4539, 1:1000 for Western blot and 1:100 for IHC, Cell Signaling), phospho-Smad1/Smad5/Smad9 (13820, 1:1000, Cell Signaling), Smad1 (6944, 1:1000, Cell Signaling), Snail (ab167609, 1:5000, Abcam), STAG1 (A13715, 1:1000, Abclonal), TMEM170B (NBP2-33739, 1:1000 NOVUS Biologicals, Centennial CO), TTK (A2500, 1:1000, Abclonal), Twist (ab175430, 1:5000, Abcam), Vimentin (sc-6260, 1:1000, Santa Cruz Biotechnology), and ZEB1 (3396, 1:1000, Cell Signaling). Establishment of CRISPR KO and CRISPRi/a cell models The Benchling CRISPR design tool (San Francisco, CA, https://benchling.com ) was employed for designing sgRNAs. The CRISPR/Cas9 editing targeted the pri-miR-23a ~ 27a ~ 24 − 2 region. Pair sgRNAs with high specificity and efficiency scores were chosen at two flanking sites of the mature miR-23a or miR-27a sequence. All sgRNAs were assessed using the Cas-OFFinder off-target searching tool (South Korea, http://www.rgenome.net/cas-offinder ). To mitigate off-target effects, potential off-target regions underwent PCR and Sanger sequence analysis (Supplementary Table S6). The sequences of the pair sgRNAs targeting miR-23a or miR-27a are listed in Supplementary Table S7. The pair sgRNA oligos were annealed by slow cooling from 95°C down to 10°C and then ligated to BbsI-digested pSpCas9(BB)-2A-GFP (PX458) vector (Addgene, Cambridge, MA). The integrity of the miR-23a- and miR-27a-targeted-Cas9 constructed vectors was confirmed by DNA sequencing. The constructed vector with the miR-23a or miR-27a targeting sequence, or the PX458 empty vector, was transfected into cells using Lipofectamine 3000 (Thermo Fisher Scientific). miR-23a or miR-27a KO colonies were confirmed by qPCR and Sanger sequencing after single-cell sorting (BD FACSMelody™ Cell Sorter) with GFP. All selected colonies of miRNA scramble and KO cells were validated by PCR and Sanger sequence analysis to exclude off-target effects in potential off-target regions of sgRNAs, as described previously 53, 54 . CRISPRi/a epigenetic editing technology was used to establish the endogenous miR-23a ~ 27a ~ 24 − 2 controllable cell models. The carrier of sgRNAs for the CRISPR nuclease-dead Cas9 (dCas9) system is pSLQ2837 pLenti U6-spsgTRE3G CMV-mIFP (a gift from Stanley Qi lab, Stanford University). pSLQ1922-dCas9-GFP-KRAB-Zeocin and pSLQ1932-dCas9-GFP-VPR-Zeocin (gift from Stanley Qi lab) are piggyBac (PB)-based DNA constructs with dCas9 elements (Supplementary Table S8). The promoter region of pri-miR-23a ~ 27a ~ 24 − 2 was the candidate target region for CRISPRi and CRISPRa, respectively. Four sgRNAs (Supplementary Table S7) were designed around the − 50 to + 300 bp of the transcription start site (TSS) of the miR-23a ~ 27a ~ 24 − 2 cluster for CRISPRi (CRISPR/dCas9-KRAB-mediated transcriptional repression). Similarly, four sgRNAs were designed around the − 400 to -50 bp of the TSS for CRISPRa (CRISPR/dCas9-VPR-mediated transcriptional activation). Then, we established various cell models as follows: 1) Vectors with CRISPRi or CRISPRa system were transfected with PB transposase vector into cells, as previously described 55 . 2) sgRNA vectors were transduced by lentivirus-mediated transduction into CRISPRi or CRISPRa transfected cells, followed by single-cell sorting with GFP (for dCas9) and mIFP ( for sgRNA). 3) A stable cell line was established after zeocin (100 µg/ml, Invitrogen) selection for two weeks. Cell transfection for virus production A total of 6.0 × 10^6 HEK293T cells were seeded onto a 10 cm dish. A transgene (21 µg), pCMV-Gag-Pol vector (21 µg), and pCMV-VSV-G-poly A vector (10.5 µg) were mixed with ddH 2 O to a final volume of 945 µl (DNA mix). To this mix, 105 µl of CaCl 2 (2.5 M) and 1,050 µl of 2 × HBSS were added, and the solution was incubated for 3 minutes. The 2,100 µl solution was then added to the cells and incubated at 37°C with 5% CO 2 for 8–10 hours. Following incubation, the media were removed, and the cells were cultured in 5% FBS + DMEM for at least 48 hours. The culture containing the virus was then collected for further experiments. Analyses of cell proliferation, cell cycle progression, and apoptosis miR-23a/miR-27a KO cells or scrambled control cells were seeded onto a 6-well plate with a density of 5 × 10^4. Cell morphology, viability, and numbers were monitored microscopically over 6 days. Additionally, the optical density of MTT (3-[4,5-dimethylthiazol-2-yl]-2,5 diphenyl tetrazolium bromide, Sigma-Aldrich, St. Louis, MO) was measured daily. For the colony formation assay, cells were seeded at 5 × 10^3 cells/ml in triplicate in a 6-well plate. After three weeks, cells were stained with 0.125% crystal violet, and colonies (> 20 cells) were photographed and counted under the microscope. In the soft agar assay, a 3.2% sterile stock agarose (Sigma-Aldrich) solution was prepared with ddH 2 O, and a 0.8% base agarose layer was created using cell culture medium. Cells (2 × 10^3 cells per 6-well plate) were trypsinized, counted, and used to prepare a 0.48% upper agarose layer. Each well received 1 ml of cell culture medium. After a 14-day incubation, colonies were stained with 4% formaldehyde and 0.005% crystal violet. Colonies (> 50 cells) were then photographed and counted under the microscope. Cell-cycle progression was determined by flow cytometry using propidium iodide (PI) staining (50 µg/ml, BD Biosciences, Franklin Lakes, NJ). This analysis was conducted after a 48-hour starvation of cells, followed by serum stimulation at 0, 8, and 22 hours. Additionally, cell-cycle progression was assessed using flow cytometry with BrdU antibody and 7AAD at 6 and 14 hours after starvation, following the manufacturer’s protocol (Phase-Flow BrdU Kit, Biolegend). Apoptosis analysis was performed by flow cytometry 24 hours after seeding, utilizing the Apoptosis Detection Kit with Annexin V and 7AAD from Biolegend. In the case of apoptosis induction by H 2 O 2 , cells were treated with 0.1 mM H 2 O 2 for 15 minutes, and the samples were subsequently subjected to flow analysis. Soft agar assay To determine anchorage-independent cell growth, a 6-well plate was prepared with a solidified 0.6% agarose bottom layer. A 0.3% agarose solution containing 1,000 cells was then added as the top layer. Following a 2–4 week incubation period in a standard cell culture incubator, allowing for the formation of colonies within the three-dimensional agarose matrix, the resulting colonies were stained using crystal violet. Quantitative analysis involved colony counting and size measurement using microscopy with ImageJ analysis software. Cell migration assays A total of 4 × 10^4 cells were cultured in 0.2% FBS + DMEM and seeded onto transwell inserts (pore size, 8µm, CORNING, Corning, NY). Next, 600–800 µL of 10% FBS + DMEM was added to the lower well of the 24-transwell plate. To mitigate the effects of cell proliferation on migration analysis, cells were pre-treated with 10 µg/ml mitomycin C (Sigma-Aldrich) for 2 hours prior to the Transwell migration assay. The transwell insert was then placed into the lower well and incubated for 18–22 hours. Following the incubation, the transwell polycarbonate membrane was fixed in 4% formaldehyde for 15 minutes. Cells that did not migrate across the membrane were gently removed with a cotton swab. The membrane was carefully cut with a scalpel and stained with DAPI for 10 minutes. For the scratch assay, 1 × 10^6 cells were seeded onto a 6-well plate. Pipette tips were used to create a wound by scratching the cells. The wound was photographed at 0 and 24 hours, and the wound-healing rates were calculated using software. qPCR Total RNA was extracted from cultured cells using Trizol reagent (Thermo Fisher Scientific) as directed by the manufacturer. For miRNA expression profiling, a 20-µl reverse transcription reaction, utilizing 5 µl of RNA and miScript II RT Kits (QIAGEN, Germantown, MD), adhered to the manufacturer’s protocol. Subsequently, 2 µl of cDNA acted as the template for real-time PCR, executed on a LightCycler 480 Real-Time PCR System (Roche Applied Sciences, Indianapolis, IN) with miScript SYBR Green PCR kits (QIAGEN). Incubation of the reaction mixtures occurred in 96-well optical plates at 95°C for 10 min, succeeded by 40 cycles of 95°C for 15 sec and 60°C for 1 min. Post-reaction, cycle threshold (CT) data were determined using fixed threshold settings, and mean CT values were derived from triplicate PCRs. Employing the 2^(-ΔCt) method for quantification, GAPDH or U6 were selected as a reference gene for mRNA or miRNA, respectively. The qPCR primer sequences are listed in Supplementary Table S7. Western blots Western blotting was performed as previously described 56, 57 . Briefly, cell lysates containing 50–100 µg of protein were prepared and subjected to 10% SDS-polyacrylamide gels. Proteins were transferred to PVDF membranes, which were incubated in 5% non-fat milk for 1 hour and overnight at 4°C in 0.25% non-fat milk containing specific primary antibodies. The membranes were subsequently incubated at room temperature for 1 hour in 0.25% non-fat milk with anti-rabbit/mouse IgG HRP-linked secondary antibody (1:5000, Cell Signaling). Enhanced chemiluminescence reagents were utilized, and the membranes were then exposed to X-films for 1–5 minutes. Luciferase assay The pmirGLO luciferase reporter vector (Promega) was utilized to construct DNA fragments from the 3’-UTR of PURA (Transcript: ENST00000331327.3) by NotI and XbaI (New England Biolabs, Ipswich, MA) digestion, following the manufacturer’s protocol. The primers for the constructed vectors and mutagenesis of PURA are listed in Supplementary Table S7. In brief, 1×10^4 cells were seeded onto a 96-well plate, cultured with DMEM + 10% FBS, incubated at 37°C and 5% CO 2 overnight, and transiently co-transfected with constructed vectors (pmirGLO-PURA-3’ UTR, pmirGLO-PURA-3’UTR-Mut) or empty pmirGLO vector and miR-23a-3p/miR-27a-3p mimics (50 nmol/L) or inhibitor (100 nmol/L) using Lipofectamine 3000. After 48 hours of transfection, substrate reagents (Promega) were added to the wells and incubated for 10 minutes. Subsequently, the luciferase activity was assessed with a Veritas Microplate Luminometer (Turner BioSystems, Sunnyvale, CA). Following this, stop reagents were added, and the luciferase activity was re-evaluated. miRNA/mRNA IP assay miRNA/mRNA immunoprecipitation was performed using miRNA Target IP kits (Active Motif, Carlsbad, CA). Briefly, cells (1 × 10^7) were seeded onto a 10 cm dish and transfected with scrambled control or miRNA mimic (50 nmol/L) or inhibitor (100 nmol/L) using Lipofectamine 3000 for 24 hours. Cell lysates were collected from each sample using 150 µL complete lysis buffer, and 10 µL of cell lysate was marked as the input. Samples and inputs were incubated on ice for 10 minutes and then at − 80°C for 2 hours. Protein G magnetic beads (50 µL) were blocked with 200 µL BSA for 1 hour and then placed on a magnet to pellet the beads. The beads were washed twice with wash buffer. Ago1/2/3 antibody (2.5 µL) or a negative control anti-IgG antibody (12.5 µL) was added to each tube and incubated for 30 minutes at room temperature. Subsequently, samples and inputs were added to the protein G magnetic beads-antibody complex and incubated overnight at 4°C. After proteinase K digestion (55°C for 30 minutes) and RNA precipitation, RT-qPCR was used to analyze if the candidate gene target could bind to miRNA. The results of Ago-IP were normalized to that of the negative control IgG-IP. IHC staining Dako retrieval buffer (Agilent, Santa Clara, CA) was employed for antigen retrieval, and the ABC detection system (Vector Laboratories, Burlingame, CA) was utilized for immunostaining. Specific primary antibodies were incubated with tissues overnight at 4°C. The secondary antibody used was goat anti-mouse/rabbit IgG (Invitrogen, 1:200). The staining process was completed following the manufacturer’s protocol of VECTASTAIN ABC Kits (Vector Laboratories). Hematoxylin was applied last for the staining of the nucleus. In vivo tumor xenograft model Scramble, miR-23a KO, and miR-27a KO HepG2 cells (100 µl, 5 × 10^7/ml) were subcutaneously injected into the left flanks of 6-week-old NSG mice (Jackson Laboratories, Bar Harbor, ME). Tumor growth was monitored every two or three days. At 31 days after injection, NSG mice were sacrificed, and tumor volume and weights were measured. All experiments were conducted in accordance with accepted standards of animal care and approved by the Institutional Animal Care and Institutional Review Board of The University of Alabama at Birmingham. RNA-seq Utilizing the TruSeq Stranded mRNA Library Prep Kit (Illumina, San Diego, CA), RNA libraries were prepared in accordance with the manufacturer's protocol. The integrity check employed an Agilent 2200 Tapestation instrument. First-strand cDNA synthesis utilized random hexamers and ProtoScript II Reverse Transcriptase (New England Biolabs, Ipswich, MA). Subsequently, libraries underwent normalization, pooling, and cluster and pair read sequencing on a HiSeqX10 instrument (Illumina) for 150 cycles, following manufacturer instructions. The generated RNA-seq data have been deposited in NCBI GEO under Accession no. GSE199332. Bioinformatic analysis Differential expression analysis of genes (DEGs) was conducted utilizing fold change and q-value. miRNA expression data from cancer and normal tissue samples were sourced from Oncomir ( www.oncomir.umn.edu ) and TCGA. To generate and visualize a functionally grouped network of terms and pathways for extensive gene clusters, the ClueGO Cytoscape plug-in (apps.cytoscape.org/apps/cluego) was employed. Gene clusters were imported from a text file or interactively from the Cytoscape network. For in-depth analysis, KEGG ( www.genome.jp/kegg/ ) analysis of the identified DEGs was executed to retrieve interacting genes and proteins (string-db.org/). The Cytoscape software (cytoscape.org/) facilitated the construction of an interaction network diagram for the DEGs. Statistical analysis Continuous variables were summarized using mean, standard deviation (SD), and median values. The distribution of samples was assessed using the one-sample Kolmogorov-Smirnov test. For samples with normal distributions, a two-tailed t -test compared means between two groups. In cases of non-normal distributions, the Mann–Whitney U test was employed to compare median variation between two groups. One-way analysis of variance (ANOVA) tested for differences among at least three groups, while two-way ANOVA was used to assess the influence of two categorically independent variables on one dependent variable. SAS (Version 9.4) and GraphPad Prism (Version 8.4.3) software were utilized for data analysis. Declarations Conflict of interest statement: There are no potential conflicts of interest for disclosure. Authors’ contributions LW and RL designed the research approach; MC, ZL, SW, and RL performed the experiments; MC, SB, HG, RL, and LW analyzed data; SB, MC, and LW performed statistical analyses; HG and JZ provided key resources; MC made a draft of the paper; MC, JZ, RL, and LW revised and edited the paper. Acknowledgements We would like to thank Dr. Lei Stanley Qi in the Department of Bioengineering, Stanford University for providing us CRISPRi/a plasmids and Dr. Guangxiang Luo in the Department of Microbiology, University of Alabama at Birmingham for providing us cell lines. Institutional Impact Fund from the University of Alabama at Birmingham supported this research work. The data underlying this article are available in in the article, its online supplementary material, and the Gene Expression Omnibus at https://www.ncbi.nlm.nih.gov/geo/ under accession code GSE199332. References Lin S, Gregory RI. MicroRNA biogenesis pathways in cancer. Nat Rev Cancer 2015; 15: 321–333. 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Supplementary Files SupplementaryFigures18andWBoriginaldata.pdf SupplementaryTables.pdf Cite Share Download PDF Status: Published Journal Publication published 07 Aug, 2024 Read the published version in Oncogene → Version 1 posted Editorial decision: revise 05 Apr, 2024 Review # 1 received at journal 30 Mar, 2024 Review # 3 received at journal 18 Mar, 2024 Review # 2 received at journal 08 Mar, 2024 Reviewer # 3 agreed at journal 27 Feb, 2024 Reviewer # 2 agreed at journal 25 Feb, 2024 Reviewer # 1 agreed at journal 08 Feb, 2024 Reviewers invited by journal 31 Jan, 2024 Submission checks completed at journal 22 Jan, 2024 Editor assigned by journal 21 Jan, 2024 First submitted to journal 21 Jan, 2024 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. 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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-3885203","acceptedTermsAndConditions":true,"allowDirectSubmit":false,"archivedVersions":[],"articleType":"Article","associatedPublications":[],"authors":[{"id":270311723,"identity":"773368c3-72ae-4790-9bf5-47cf889176a2","order_by":0,"name":"Lizhong Wang","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAAAvUlEQVRIiWNgGAWjYBACPjBpYCPHwMADZLARoQWipiDNmFQtHw4nNhCvRSL52cMvBszpG46fPcDwoewwMVrSzI1lDNhyN5zJS2CccY4YLdIJZtISBjy5Gw7kGDDzthGlJf0bUItEusH5NwbMf4nTkmMm+cHAIMHgBtAWRqK0yL8pk2YwSDCceeNdwsGec+mEtfDzHN8m+ePPf3m+87kHH/wosyasBQSYeaCMA8SpBwLGH0QrHQWjYBSMghEJAInqN5gyLmBlAAAAAElFTkSuQmCC","orcid":"https://orcid.org/0000-0003-1980-4730","institution":"University of Alabama at Birmingham","correspondingAuthor":true,"prefix":"","firstName":"Lizhong","middleName":"","lastName":"Wang","suffix":""},{"id":270311724,"identity":"7afaa93f-9f59-4650-8be3-4084294a02a3","order_by":1,"name":"Mengying Cui","email":"","orcid":"","institution":"University of Alabama at Birmingham","correspondingAuthor":false,"prefix":"","firstName":"Mengying","middleName":"","lastName":"Cui","suffix":""},{"id":270311725,"identity":"10a99700-5883-499c-9764-ebf12308ea62","order_by":2,"name":"Zhichao Liu","email":"","orcid":"","institution":"University of Alabama at Birmingham","correspondingAuthor":false,"prefix":"","firstName":"Zhichao","middleName":"","lastName":"Liu","suffix":""},{"id":270311726,"identity":"9498bf01-f83c-4833-8433-88c39e90ec80","order_by":3,"name":"Shuaibin Wang","email":"","orcid":"","institution":"University of Alabama at Birmingham","correspondingAuthor":false,"prefix":"","firstName":"Shuaibin","middleName":"","lastName":"Wang","suffix":""},{"id":270311727,"identity":"a7a7b020-26e2-488b-b6bc-995f95171d6c","order_by":4,"name":"Sejong Bae","email":"","orcid":"","institution":"University of Alabama at Birmingham","correspondingAuthor":false,"prefix":"","firstName":"Sejong","middleName":"","lastName":"Bae","suffix":""},{"id":270311728,"identity":"deffe715-cba8-4a12-a823-7bab2852c422","order_by":5,"name":"Hua Guo","email":"","orcid":"","institution":"University of Alabama at Birmingham","correspondingAuthor":false,"prefix":"","firstName":"Hua","middleName":"","lastName":"Guo","suffix":""},{"id":270311729,"identity":"b7fad781-5cc0-4dd4-9ed4-94d7ae734763","order_by":6,"name":"Jiangbing Zhou","email":"","orcid":"https://orcid.org/0000-0002-1201-5360","institution":"Yale University","correspondingAuthor":false,"prefix":"","firstName":"Jiangbing","middleName":"","lastName":"Zhou","suffix":""},{"id":270311730,"identity":"bc734874-12e6-4dc0-975d-ecd9b1f90eb6","order_by":7,"name":"Runhua Liu","email":"","orcid":"https://orcid.org/0000-0002-0892-6946","institution":"University of Alabama at Birmingham","correspondingAuthor":false,"prefix":"","firstName":"Runhua","middleName":"","lastName":"Liu","suffix":""}],"badges":[],"createdAt":"2024-01-21 16:15:23","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-3885203/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-3885203/v1","draftVersion":[],"editorialEvents":[{"content":"https://doi.org/10.1038/s41388-024-03115-z","type":"published","date":"2024-08-07T04:00:00+00:00"}],"editorialNote":"","failedWorkflow":false,"files":[{"id":50544072,"identity":"2354ff48-5a56-4e39-a206-b000feef0929","added_by":"auto","created_at":"2024-02-02 08:36:37","extension":"png","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":216176,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eEffect of miRNAs in the miR-23a~27a~24-2 cluster on cell proliferation and migration of HCC cells. A, \u003c/strong\u003eSchematic representation of endogenous has-miR-23a~27a~24-2 cluster.\u003cstrong\u003eB-D, \u003c/strong\u003eKaplan–Meier survival curves for miR-23a, miR-27a, and miR-24 expression with low and high levels in TCGA hepatocellular carcinoma (HCC) \u0026nbsp;patients. \u003cem\u003ep\u003c/em\u003e value by log rank test.\u003cstrong\u003e E-G,\u003c/strong\u003e Quantification of miR-23a-3p/5p, miR-27a-3p/5p, and miR-24-3p/5p expression by qPCR as a percentage of \u003cem\u003eRNU6\u003c/em\u003eexpression in HEK293T, Huh7, and HepG2 cells. Data are presented as means ± standard deviation (SD). *** \u003cem\u003ep\u003c/em\u003e\u0026lt; 0.001 by one-way ANOVA followed by protected least-significant difference (PLSD) test for HCC cells \u003cem\u003evs\u003c/em\u003e. HEK293T cells. \u003cstrong\u003eH \u003c/strong\u003eand\u003cstrong\u003e M,\u003c/strong\u003e Cell growth curve in HepG2 and Huh7 cells treated with scramble (Scr), miRNA inhibitor, and miRNA mimic for 6 days. Data are presented as means ± SD.*** \u003cem\u003ep\u003c/em\u003e \u0026lt; 0.001 by two-way ANOVA test \u003cem\u003evs\u003c/em\u003e. Scr group. \u003cstrong\u003eI-J \u003c/strong\u003eand\u003cstrong\u003e N-O, \u003c/strong\u003eScratch migration assay and quantitative analysis in HepG2 and Huh7 cells. Data are presented as means ± SD. * \u003cem\u003ep\u003c/em\u003e \u0026lt; 0.05 by one-way ANOVA followed by PLSD test \u003cem\u003evs\u003c/em\u003e. Scr group. \u003cstrong\u003eK-L \u003c/strong\u003eand\u003cstrong\u003e P-Q, \u003c/strong\u003eTranswell migration assay and quantitative analysis in HepG2 and Huh7 cells. Data are presented as means ± SD. * \u003cem\u003ep\u003c/em\u003e \u0026lt; 0.05 and ** \u003cem\u003ep\u003c/em\u003e \u0026lt; 0.01 by one-way ANOVA followed by PLSD test \u003cem\u003evs\u003c/em\u003e. Scr group. All experiments were repeated three times.\u003c/p\u003e","description":"","filename":"1.png","url":"https://assets-eu.researchsquare.com/files/rs-3885203/v1/3f2e80bc4b7362bae983fbcc.png"},{"id":50544077,"identity":"d7a6009a-754b-4101-8f9c-6166e120faef","added_by":"auto","created_at":"2024-02-02 08:36:37","extension":"png","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":273587,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eEffect of miR-23a/miR-27a knockout on cell proliferation and xenograft tumor growth of HCC cells. A,\u003c/strong\u003e Cell growth curve in Scr, miR-23a knockout (KO), and miR-27a KO HepG2 cells for 6 days. Data are presented as means ± SD. *** \u003cem\u003ep\u003c/em\u003e \u0026lt; 0.001 by two-way ANOVA test \u003cem\u003evs\u003c/em\u003e. Scr group. \u003cstrong\u003eB-D, \u003c/strong\u003eColony formation assay and quantitative analysis of clone area and number in Scr, miR-23a KO, and miR-27a KO HepG2 cells. Data are presented as means ± SD. * \u003cem\u003ep\u003c/em\u003e \u0026lt; 0.05, ** \u003cem\u003ep\u003c/em\u003e \u0026lt; 0.01, and *** \u003cem\u003ep\u003c/em\u003e \u0026lt; 0.001 by one-way ANOVA followed by PLSD test \u003cem\u003evs\u003c/em\u003e. Scr group. \u003cstrong\u003eE-G, \u003c/strong\u003eSoft agar assay and quantitative analysis of clone area and clone number. Data are presented as means ± SD. * \u003cem\u003ep\u003c/em\u003e \u0026lt; 0.05, ** \u003cem\u003ep\u003c/em\u003e \u0026lt; 0.01, *** \u003cem\u003ep\u003c/em\u003e \u0026lt; 0.001 by one-way ANOVA followed by PLSD test \u003cem\u003evs\u003c/em\u003e. Scr group. Scale bars=500μm/100μm. \u003cstrong\u003eH-J,\u003c/strong\u003e Representative images of xenograft tumors at day 31 after injection and tumor growth and weights in NSG mice subcutaneously injected with Scr (n=7), miR-23a KO1 (n=7), miR-23a KO2 (n=7), miR-27a KO1 (n=7), or miR-27a KO2 (n=7) HepG2 cells. Data are presented as means ± SD of the tumor volumes. ** \u003cem\u003ep\u003c/em\u003e \u0026lt; 0.01 and *** \u003cem\u003ep\u003c/em\u003e\u0026lt; 0.001 by two-way ANOVA test or one-way ANOVA followed by PLSD test \u003cem\u003evs\u003c/em\u003e. Scr group. All experiments were repeated three times.\u003c/p\u003e","description":"","filename":"2.png","url":"https://assets-eu.researchsquare.com/files/rs-3885203/v1/d6d30f54e7b8487eee7bd06a.png"},{"id":50544485,"identity":"df09fdb0-6dfd-4576-a7ed-a91f59e99b2c","added_by":"auto","created_at":"2024-02-02 08:44:37","extension":"png","order_by":3,"title":"Figure 3","display":"","copyAsset":false,"role":"figure","size":386653,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eEffect of miR-23a/miR-27a knockout on cell cycle progression of HCC cells. A-B,\u003c/strong\u003e Cell cycle progression and quantitative analysis in Scr, miR-23a KO, and miR-27a KO HepG2 cells after starvation for 48 hours monitored by PI staining and flow cytometry at 0, 8, and 22 hours after serum stimulation. Data presented as means ± SD of triplicates. * \u003cem\u003ep\u003c/em\u003e \u0026lt; 0.05 by one-way ANOVA followed by PLSD test \u003cem\u003evs\u003c/em\u003e. Scr group. \u003cstrong\u003eC-D, \u003c/strong\u003eCell cycle progression and quantitative analysis in Scr, miR-23a KO, and miR-27a KO HepG2 cells after starvation for 48 hours monitored by BrdU staining and flow cytometry at 8 and 16 hours after serum stimulation. Data presented as means ± SD of triplicates. * \u003cem\u003ep\u003c/em\u003e \u0026lt; 0.05 and ** \u003cem\u003ep\u003c/em\u003e \u0026lt; 0.01 by one-way ANOVA followed by PLSD test \u003cem\u003evs\u003c/em\u003e. Scr group. \u003cstrong\u003eE, \u003c/strong\u003eProtein expression by Western blot in Scr, miR-23a KO or miR-27a KO HepG2 cells. \u003cstrong\u003eF, \u003c/strong\u003eProtein expression of Ki67, phospho (p)-CDK1(Tyr15), and Cyclin B by IHC staining in xenograft tumors injected with Scr, miR-23a KO, and miR-27a KO HepG2 cells in NSG mice. Scale bars=50μm. \u003cstrong\u003eG-H,\u003c/strong\u003eQuantitative analysis of Ki67+ and p-CDK1(Tyr15)+ cells. * \u003cem\u003ep\u003c/em\u003e \u0026lt; 0.05, ** \u003cem\u003ep\u003c/em\u003e \u0026lt; 0.01, and *** \u003cem\u003ep\u003c/em\u003e \u0026lt; 0.001 by one-way ANOVA followed by PLSD test \u003cem\u003evs\u003c/em\u003e. Scr group. All experiments were repeated three times.\u003c/p\u003e","description":"","filename":"3.png","url":"https://assets-eu.researchsquare.com/files/rs-3885203/v1/4e0693ae1e93e22ddd541e3e.png"},{"id":50544078,"identity":"ec85b004-487d-415c-90cd-9f56e416d6a1","added_by":"auto","created_at":"2024-02-02 08:36:37","extension":"png","order_by":4,"title":"Figure 4","display":"","copyAsset":false,"role":"figure","size":187371,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eBioinformatics analysis of RNA-seq data in miR-23a/miR-27a KO HCC cells. A-B, \u003c/strong\u003eGene expression profiling data showing up-regulated (red) and downregulated (green) genes in miR-23a KO or miR-27a KO HepG2 cells relative to Scr HepG2 cells by RNA-seq analysis. Blue vertical line represents log\u003csub\u003e2\u003c/sub\u003e (Fold Change) =0.58, Blue horizon line represents -log\u003csub\u003e10 \u003c/sub\u003e(\u003cem\u003eq\u003c/em\u003e value) =3. \u003cstrong\u003eC, \u003c/strong\u003eVenn diagram showing\u003cstrong\u003e \u003c/strong\u003ecandidate target genes selected by an overlap of three gene sets: 1, Genes up-regulated both in miR-23a KO group and miR-27a KO group (Fold change \u0026gt;1.5, \u003cem\u003eq\u003c/em\u003e value \u0026lt; 0.001) by RNA-seq analysis (593 genes); 2, Genes that miR-23a-3p binds to 3’-untranslated region (UTR) of target gene predicted by an online website (\u003ca href=\"http://www.targetscan/\"\u003ehttp://www.targetscan/\u003c/a\u003e) (556 genes); 3, Genes that miR-27a-3p binds to 3’-UTR of target gene predicted by an online website (\u003ca href=\"http://www.targetscan/\"\u003ehttp://www.targetscan/\u003c/a\u003e) (1180 genes). The bottom table indicates a list of 7 candidate target genes by an overlap of three gene sets. \u003cstrong\u003eD-E,\u003c/strong\u003e Gene set enrich analysis after miR-23a/miR-27a KO. \u003cstrong\u003eD, \u003c/strong\u003eTop five cell signaling pathways by normalized enrichment score (NES) score ranking; \u003cstrong\u003eE,\u003c/strong\u003e Heat map of differential gene expression of top 30 genes in each gene set by Rank Metric Score ranking.\u003c/p\u003e","description":"","filename":"4.png","url":"https://assets-eu.researchsquare.com/files/rs-3885203/v1/d326ce56edeedea7e9a6a71b.png"},{"id":50544073,"identity":"2360f399-e2f8-435d-8637-823e685ee1ea","added_by":"auto","created_at":"2024-02-02 08:36:37","extension":"png","order_by":5,"title":"Figure 5","display":"","copyAsset":false,"role":"figure","size":363510,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eEstablishment of CRISPRi/a cell models and validation of miR-23a~27a~24-2 cluster target genes in HCC cells. A \u003c/strong\u003eand\u003cstrong\u003e F, \u003c/strong\u003eDiagram of CRISPR interference (CRISPRi) and activation (CRISPRa) system. \u003cstrong\u003eB \u003c/strong\u003eand\u003cstrong\u003e G,\u003c/strong\u003e Efficacy of transfection of dCas9 (GFP) and transduction of sgRNA (mCherry) into CRISPRi/a HepG2 cells at day 4 as determined by fluorescence microscopy. Scale bar =1,000 μm. \u003cstrong\u003eC \u003c/strong\u003eand\u003cstrong\u003e H,\u003c/strong\u003e Dynamic changes of miR-23a-3p, miR-27a-3p, and miR-24-3p expression in CRISPRi/a HepG2 cellsdetected by qPCR. \u003cstrong\u003eD \u003c/strong\u003eand\u003cstrong\u003e I,\u003c/strong\u003e Dynamic changes of candidate target gene expression in CRISPRi/a HepG2 cells detected by qPCR. \u003cstrong\u003eE \u003c/strong\u003eand\u003cstrong\u003e J,\u003c/strong\u003e Cell growth curve in CRISPRi/a HepG2 cells for 96 hours. Data are presented as means ± SD. *** \u003cem\u003ep\u003c/em\u003e \u0026lt; 0.001 by two-way ANOVA test \u003cem\u003evs\u003c/em\u003e. Scr group. All experiments were repeated three times.\u003c/p\u003e","description":"","filename":"5.png","url":"https://assets-eu.researchsquare.com/files/rs-3885203/v1/b9ff4ba82c9e2d4fa6a8b4f2.png"},{"id":50544486,"identity":"4f3deb98-28d7-478b-bd15-8bf285e2d1c8","added_by":"auto","created_at":"2024-02-02 08:44:37","extension":"png","order_by":6,"title":"Figure 6","display":"","copyAsset":false,"role":"figure","size":259108,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003emiR-23a/miR-27a-target gene network in HCC cells. A.\u003c/strong\u003e Schematic representation of miRNA interaction with the 3′-UTR of its corresponding targets, miRNA target immunoprecipitation (IP) with Ago proteins, miRNA-induced mRNA silencing complex, and qPCR analysis for mRNA expression from IP. \u003cstrong\u003eB-D, \u003c/strong\u003eInteraction analysis of miR-23a-5p or miR-27a-5p mimic with the 3′-UTRs of \u003cem\u003ePURA, STAG1, \u003c/em\u003eand\u003cem\u003e TTK\u003c/em\u003e mRNA by miRNA/mRNA IP assay of HepG2 cells. Data are presented as means ± SD. *** \u003cem\u003ep\u003c/em\u003e \u0026lt; 0.001 by two-tailed \u003cem\u003et\u003c/em\u003e-test \u003cem\u003evs\u003c/em\u003e. Scr group. \u003cstrong\u003eE, \u003c/strong\u003emRNA expression of \u003cem\u003ePURA\u003c/em\u003e measured by qPCR in Scr, miR-23a KO, or miR-27a KO HepG2 cells treated with or without miRNA mimic or inhibitor. \u003cstrong\u003eF, \u003c/strong\u003eProtein expression of PURA measured by Western blot in Scr, miR-23a KO, or miR-27a KO HepG2 cells. \u003cstrong\u003eG,\u003c/strong\u003e Protein expression of PURA by IHC staining in xenograft tumors injected with Scr, miR-23a KO, and miR-27a KO HepG2 cells in NSG mice. Scale bars=50μm.\u003cstrong\u003e H, \u003c/strong\u003eSchematic of luciferase reporter constructs with Scr or mutant (deletion of residues in red) \u003cem\u003ePURA\u003c/em\u003e 3’-UTR downstream of the Firefly luciferase reporter gene. \u003cstrong\u003eI-J, \u003c/strong\u003eLuciferase reporter activity in HepG2 cells co-transfected with Scr vector, wild-type or mutant 3’-UTR \u003cem\u003ePURA\u003c/em\u003e constructs with mimics or inhibitor for miR-23a-3p or miR-27a-3p. *** \u003cem\u003ep\u003c/em\u003e \u0026lt; 0.001 by one-way ANOVA followed by PLSD test \u003cem\u003evs\u003c/em\u003e. Scr group. \u003cstrong\u003eK,\u003c/strong\u003e Protein expression of PURA measured by Western blot in Scr cells or cells transfection with \u003cem\u003ePURA\u003c/em\u003e siRNA. \u003cstrong\u003eL-M, \u003c/strong\u003eCell growth curve in Scr, miR-23a KO, miR-23a KO, miR-27a KO, and miR-27a KO cells transfected with \u003cem\u003ePURA \u003c/em\u003esiRNA for 6 days. Data are presented as means ± SD. * \u003cem\u003ep\u003c/em\u003e \u0026lt; 0.05 and *** \u003cem\u003ep\u003c/em\u003e\u0026lt; 0.001 by two-way ANOVA test \u003cem\u003evs\u003c/em\u003e. Scr or \u003cem\u003ePURA\u003c/em\u003e siRNA group. \u003cstrong\u003eN, \u003c/strong\u003eProtein expression of STAG1 and TTK measured by Western blot in Scr, miR-23a KO or miR-27a KO transfected with \u003cem\u003ePURA\u003c/em\u003e siRNA after 48 hours, respectively. \u003cstrong\u003eO, \u003c/strong\u003eProtein expression of STAG1 and TTK measured by Western blot in Scr, miR-23a KO, miR-23a KO+\u003cem\u003ePURA\u003c/em\u003e siRNA, Scr+miR-23a-3p mimic, Scr+miR-23a-3p mimic+\u003cem\u003ePURA\u003c/em\u003e siRNA, miR-27a KO, miR-27a KO+\u003cem\u003ePURA\u003c/em\u003e siRNA, Scr+miR-27a-3p mimic, and Scr+miR-27a-3p mimic+\u003cem\u003ePURA\u003c/em\u003esiRNA cells, respectively. All experiments were repeated three times.\u003c/p\u003e","description":"","filename":"6.png","url":"https://assets-eu.researchsquare.com/files/rs-3885203/v1/e7ed70387048e9d8cb98df86.png"},{"id":50544079,"identity":"e53814c5-61df-4aac-9f6d-0ba108572bad","added_by":"auto","created_at":"2024-02-02 08:36:37","extension":"png","order_by":7,"title":"Figure 7","display":"","copyAsset":false,"role":"figure","size":471663,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eEffect of miR-23a/miR-27a on cell migration and EMT in HCC cells. A-B, \u003c/strong\u003eTranswell migration assay and quantitative analysis in HepG2 cells. Data are presented as means ± SD. * \u003cem\u003ep\u003c/em\u003e \u0026lt; 0.05 and ** \u003cem\u003ep\u003c/em\u003e \u0026lt; 0.01 by one-way ANOVA followed by PLSD test \u003cem\u003evs\u003c/em\u003e. Scr group. \u003cstrong\u003eC-D, \u003c/strong\u003eScratch migration assay and quantitative analysis in HepG2 cells. Data are presented as means ± SD. * \u003cem\u003ep\u003c/em\u003e\u0026lt; 0.05 by one-way ANOVA followed by PLSD test \u003cem\u003evs\u003c/em\u003e. Scr group. \u003cstrong\u003eE,\u003c/strong\u003e Protein expression of E-cadherin and N-cadherin by IHC staining in xenograft tumors injected with Scr, miR-23a KO, and miR-27a KO HepG2 cells in NSG mice. Scale bars=50μm.\u003cstrong\u003e F,\u003c/strong\u003e Protein expression of E-cadherin, N-cadherin, Vimentin, Snail, Twist, ZEB1 measured by Western blot in Scr, miR-23a KO or miR-27a KO HepG2 cells. \u003cstrong\u003eG \u003c/strong\u003eand\u003cstrong\u003e K, \u003c/strong\u003eDiagram of CRISPRi and CRISPRa system. \u003cstrong\u003eH \u003c/strong\u003eand\u003cstrong\u003e L,\u003c/strong\u003e Efficacy of transfection of dCas9 (GFP) and transduction of sgRNA (mCherry) into CRISPRi/a HepG2 cells at day 4 as determined by fluorescence microscopy. Scale bar =1,000 μm. \u003cstrong\u003eI-J \u003c/strong\u003eand\u003cstrong\u003e M-N, \u003c/strong\u003eTranswell migration assay and quantitative analysis in CRISPRi/a HepG2 cells with miRNA mimic or inhibitor. Data are presented as means ± SD. ** \u003cem\u003ep\u003c/em\u003e \u0026lt; 0.01 and *** \u003cem\u003ep\u003c/em\u003e \u0026lt; 0.001 by one-way ANOVA followed by PLSD test \u003cem\u003evs\u003c/em\u003e. Scr group. All experiments were repeated three times.\u003c/p\u003e","description":"","filename":"7.png","url":"https://assets-eu.researchsquare.com/files/rs-3885203/v1/8738777c4310232ad26edb60.png"},{"id":50544075,"identity":"38635267-2b88-473e-82ec-569cfeb83e8b","added_by":"auto","created_at":"2024-02-02 08:36:37","extension":"png","order_by":8,"title":"Figure 8","display":"","copyAsset":false,"role":"figure","size":184881,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003emiR-23a/miR-27a-regulated signaling pathways on cell migration and EMT in HCC cells. A \u003c/strong\u003eand\u003cstrong\u003e G,\u003c/strong\u003e Protein expression of BMPR2 and TMEM170B measured by Western blot in Scr, miR-23a KO, or miR-27a KO HepG2 cells. \u003cstrong\u003eB \u003c/strong\u003eand\u003cstrong\u003e H, \u003c/strong\u003eInteraction analysis of miR-23a-5p or miR-27a-5p mimic with the 3′-UTRs of \u003cem\u003eBMPR2 \u003c/em\u003eand\u003cem\u003e TMEM170B\u003c/em\u003e mRNA by miRNA/mRNA IP assay of HepG2 cells. Data are presented as means ± SD. *** \u003cem\u003ep\u003c/em\u003e \u0026lt; 0.001 by two-tailed \u003cem\u003et\u003c/em\u003e-test \u003cem\u003evs\u003c/em\u003e. Scr group. \u003cstrong\u003eC \u003c/strong\u003eand\u003cstrong\u003e I,\u003c/strong\u003e Protein expression of BMPR2 and TMEM170B measured by Western blot in miR-23a KO or miR-27a KO HepG2 cells treated with Scr or siRNA. \u003cstrong\u003eD-E \u003c/strong\u003eand\u003cstrong\u003e J-K, \u003c/strong\u003eTranswell migration assay and quantitative analysis in in miR-23a KO or miR-27a KO HepG2 cells treated with Scr or siRNA. Data are presented as means ± SD. ** \u003cem\u003ep\u003c/em\u003e \u0026lt; 0.01 and *** \u003cem\u003ep\u003c/em\u003e \u0026lt; 0.001 by one-way ANOVA followed by PLSD test \u003cem\u003evs\u003c/em\u003e. Scr group. \u003cstrong\u003eF, \u003c/strong\u003eProtein expression of BMPR2, E-cadherin, N-cadherin, Snail, p-Smad1, Smad1 measured by Western blot in Scr, miR-23a KO, and miR-23a KO+miR-23a-3p mimic cells. \u003cstrong\u003eL, \u003c/strong\u003eProtein expression of TMEM170B, E-cadherin, N-cadherin, Vimentin, Twist, β-catenin, and nclear (N)-β-catenin measured by Western blot in Scr, miR-27a KO, and miR-27a KO+miR-27a-3p mimic cells. All experiments were repeated three times.\u003c/p\u003e","description":"","filename":"8.png","url":"https://assets-eu.researchsquare.com/files/rs-3885203/v1/f79a37969ab2d5ca6c4019e7.png"},{"id":62008817,"identity":"5bbe8be5-1616-47bb-813e-fb16c9aa63e0","added_by":"auto","created_at":"2024-08-08 07:12:32","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":3351581,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-3885203/v1/093c6fc1-1a4b-4ddf-8e1f-c2ef822d7f69.pdf"},{"id":50544080,"identity":"87721ab3-ea4a-4064-9479-946d886220ae","added_by":"auto","created_at":"2024-02-02 08:36:37","extension":"pdf","order_by":1,"title":"","display":"","copyAsset":false,"role":"supplement","size":1921793,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cbr\u003e\u003c/p\u003e","description":"","filename":"SupplementaryFigures18andWBoriginaldata.pdf","url":"https://assets-eu.researchsquare.com/files/rs-3885203/v1/d824e5f7eb2a8f1beee8f446.pdf"},{"id":50544081,"identity":"3f8698dc-0d81-4c68-a221-febd968c8010","added_by":"auto","created_at":"2024-02-02 08:36:38","extension":"pdf","order_by":2,"title":"","display":"","copyAsset":false,"role":"supplement","size":3320056,"visible":true,"origin":"","legend":"","description":"","filename":"SupplementaryTables.pdf","url":"https://assets-eu.researchsquare.com/files/rs-3885203/v1/5bec781e7bd492da3bed9664.pdf"}],"financialInterests":"There is \u003cb\u003eNO\u003c/b\u003e conflict of interest to disclose.","formattedTitle":"CRISPR-Based Dissection of microRNA-23a~27a~24-2 Cluster Functionality in Hepatocellular Carcinoma","fulltext":[{"header":"Introduction","content":"\u003cp\u003eMicroRNAs (miRNAs or miRs) are endogenous, small non-coding RNAs involved in post-transcriptional regulation, leading to mRNA cleavage or translation repression of target genes. This regulatory process influences various biological phenomena such as cell differentiation, proliferation, apoptosis, and metabolism \u003csup\u003e1\u003c/sup\u003e. Remarkably, a single microRNA can regulate multiple genes, and even subtle changes in miRNA expression levels can have profound effects on biological functions \u003csup\u003e2\u003c/sup\u003e. Of particular importance are clustered miRNAs, which are located at the same locus in the genome and transcribed as a single primary miRNA (pri-miRNA). Unfortunately, the significance of these clustered miRNAs has often been overlooked \u003csup\u003e3\u003c/sup\u003e. Given the interactive and complex nature of the regulatory network between miRNAs and mRNAs, it becomes essential to comprehensively understand the regulation, properties, and biological functions of miRNAs when they are organized into clusters.\u003c/p\u003e \u003cp\u003eThe miR-23a‐27a‐24‐2 cluster located on chromosome 9q22 encodes a pri-miRNA that consists of three individual miRNAs: miR-23a, miR-27a, and miR-24 \u003csup\u003e4, 5\u003c/sup\u003e. These three miRNAs function independently, as they regulate distinct target genes \u003csup\u003e4, 5\u003c/sup\u003e. Consequently, the miR-23a\u0026thinsp;~\u0026thinsp;27a\u0026thinsp;~\u0026thinsp;24\u0026thinsp;\u0026minus;\u0026thinsp;2 cluster plays diverse roles in processes such as development, tumorigenesis, invasion, metastasis, vascular remodeling, tumor immunity, and drug resistance \u003csup\u003e5\u003c/sup\u003e. However, despite its significance, studies on the individual mature miRNAs (miR-23a, miR-27a, miR-24) within this cluster have yielded inconclusive results. Addressing these inconsistencies requires an integrated functional analysis of the endogenous miR-23a\u0026thinsp;~\u0026thinsp;27a\u0026thinsp;~\u0026thinsp;24\u0026thinsp;\u0026minus;\u0026thinsp;2 cluster alongside the individual mature miRNAs. In human cancers, including hepatocellular carcinoma (HCC), the expression of miR‐23a‐27a‐24‐2 pri-miRNA is upregulated compared to normal tissues \u003csup\u003e6\u003c/sup\u003e. Nevertheless, investigations into the three mature miRNAs within the miR-23a\u0026thinsp;~\u0026thinsp;27a\u0026thinsp;~\u0026thinsp;24\u0026thinsp;\u0026minus;\u0026thinsp;2 cluster in HCC have reported inconsistent results for miR-23a \u003csup\u003e7\u0026ndash;15\u003c/sup\u003e, miR-27a \u003csup\u003e16\u0026ndash;25\u003c/sup\u003e, and miR-24 \u003csup\u003e26\u0026ndash;29\u003c/sup\u003e. This inconsistency suggests their potential involvement in distinct cell signaling pathways, contributing to self‐regulation and feedback loops under diverse circumstances \u003csup\u003e30, 31\u003c/sup\u003e.\u003c/p\u003e \u003cp\u003eTraditional methods involving overexpression through transfection with plasmids or RNA interference techniques may introduce exogenous variables, potentially leading to spurious effects and not accurately reflecting endogenous miRNA dynamics. Moreover, these approaches may not capture the comprehensive expression profile governing clustered miRNAs. In the present study, we addressed these challenges by establishing an endogenous miR-23a\u0026thinsp;~\u0026thinsp;27a\u0026thinsp;~\u0026thinsp;24\u0026thinsp;\u0026minus;\u0026thinsp;2 controllable system using CRISPR technologies. Leveraging CRISPR genomic editing, we individually knocked out each endogenous mature miRNA within the miR-23a\u0026thinsp;~\u0026thinsp;27a\u0026thinsp;~\u0026thinsp;24\u0026thinsp;\u0026minus;\u0026thinsp;2 cluster in HCC cells to discern the functional roles of individual miRNAs. Furthermore, employing CRISPR epigenomic editing through CRISPR interference (CRISPRi) and CRISPR activation (CRISPRa), we precisely modulated the expression of pri-miR-23a\u0026thinsp;~\u0026thinsp;27a\u0026thinsp;~\u0026thinsp;24\u0026thinsp;\u0026minus;\u0026thinsp;2 and simultaneously controlled the co-expression of its three mature miRNAs, providing insights into the overall regulation of clustered miRNAs. In addition, we investigated the functional roles of both the miR-23a\u0026thinsp;~\u0026thinsp;27a\u0026thinsp;~\u0026thinsp;24\u0026thinsp;\u0026minus;\u0026thinsp;2 cluster and its individual mature miRNAs in HCC cell proliferation, apoptosis, and migration. Utilizing this novel platform, we conducted a comprehensive analysis to dissect the functional roles and identify underlying targets and signaling pathways associated with the microRNA-23a-27a-24-2 cluster in HCC cells.\u003c/p\u003e"},{"header":"Results","content":"\u003cdiv id=\"Sec3\" class=\"Section2\"\u003e \u003ch2\u003eCharacterization of miR-23a\u0026thinsp;~\u0026thinsp;27a\u0026thinsp;~\u0026thinsp;24\u0026thinsp;\u0026minus;\u0026thinsp;2 expression and its survival outcomes in HCC tissues and cell lines\u003c/h2\u003e \u003cp\u003eThe transcription of three mature miRNAs from the miR-23a\u0026thinsp;~\u0026thinsp;27a\u0026thinsp;~\u0026thinsp;24\u0026thinsp;\u0026minus;\u0026thinsp;2 cluster is regulated by the same promoter (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003eA). The Cancer Genome Atlas (TCGA) dataset analysis showed no significant difference in the expression of miR-23a (\u003cem\u003ep\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.980) and miR-27a (\u003cem\u003ep\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.129), with only a significant difference in the expression of miR-24-2 (\u003cem\u003ep\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.04) between HCC and normal liver tissues (Supplementary Figures \u003cspan refid=\"MOESM1\" class=\"InternalRef\"\u003eS1\u003c/span\u003e). However, survival analysis revealed poor overall survival for high expression of miR-23a (\u003cem\u003ep\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.04), miR-27a (\u003cem\u003ep\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.017), and not miR-24 (\u003cem\u003ep\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.03) compared to low expression of these miRNAs in HCC patients (Figs.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003eB-D). Similarly, in the Kaplan-Meier Plotter RNA-sequencing (RNA-seq) dataset, Cox regression analysis revealed poor overall survival for high expression of miR-23a (hazard ratio (HR)\u0026thinsp;=\u0026thinsp;1.67, \u003cem\u003ep\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.0052), miR-27a (HR\u0026thinsp;=\u0026thinsp;1.65, \u003cem\u003ep\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.0057), and miR-24 (HR\u0026thinsp;=\u0026thinsp;1.77, \u003cem\u003ep\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.0021) compared to low expression of these miRNAs in HCC patients.\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003eHowever, the expression of these miRNAs in these datasets is likely from pri-mRNAs of the miR-23a\u0026thinsp;~\u0026thinsp;27a\u0026thinsp;~\u0026thinsp;24\u0026thinsp;\u0026minus;\u0026thinsp;2 cluster. Next, we characterized the expression level of mature miRNAs in the miR-23a\u0026thinsp;~\u0026thinsp;27a\u0026thinsp;~\u0026thinsp;24\u0026thinsp;\u0026minus;\u0026thinsp;2 cluster in HEK293T, Huh7, and HepG2 cell lines using quantitative real-time PCR (qPCR). The expression of mature miR-23a-3p/5p, miR-27a-3p/5p, and miR-24-3p/5p was higher in HepG2 and Huh7 cells than in HEK293T cells, with the highest expression evident in HepG2 cells (Figs.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003eE-G). In particular, the mature 3p miRNAs (miR-23a-3p, miR-27a-3p, and miR-24-3p) were consistently expressed more than 10-fold higher in cells compared to the mature 5p miRNAs (miR-23a-5p, miR-27a-5p, miR-24-2-5p), indicating a predominant expression of 3p miRNAs in the miR-23a\u0026thinsp;~\u0026thinsp;27a\u0026thinsp;~\u0026thinsp;24\u0026thinsp;\u0026minus;\u0026thinsp;2 cluster. Thus, using the HepG2 cell line, we established miRNA KO HCC cell models and focused on the expression of 3p\u0026rsquo; miRNAs as the main factors when choosing miRNA KO cell colonies. In addition, miR-24 is also expressed in the miR-23b\u0026thinsp;~\u0026thinsp;27b\u0026thinsp;~\u0026thinsp;24\u0026thinsp;\u0026minus;\u0026thinsp;1 cluster at 9q22.32. To reduce the complexity of our analysis, in the present study, we only focused on miR-23a and miR-27a.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec4\" class=\"Section2\"\u003e \u003ch2\u003eEstablishment of miR-23a/miR-27a KO HepG2 cell models\u003c/h2\u003e \u003cp\u003eUsing CRISPR/Cas9 genomic editing, we generated scramble and miR-23a/miR-27a KO HepG2 cell models. The miRNA expression in selected cell colonies was assessed by qPCR. As shown in Supplementary Figure \u003cspan refid=\"MOESM2\" class=\"InternalRef\"\u003eS2\u003c/span\u003eA, miR-23a KO markedly decreased the expression of miR-23a-3p in two clones, while varied expressions of miR-23a-5p were observed. Notably, miR-23a KO also led to decreased expressions of miR-27a-3p and miR-24-3p, but not miR-27a-5p and miR-24-5p in the two miR-23a KO clones. Furthermore, miR-27a KO reduced the expression of miR-27a-3p/5p and miR-24-3p/5p in two miR-27a KO clones (Supplementary Figure \u003cspan refid=\"MOESM2\" class=\"InternalRef\"\u003eS2\u003c/span\u003eB). However, miR-27a KO slightly increased the expression of miR-23a-3p while decreasing the expression of miR-23a-5p in the two miR-27a KO clones (Supplementary Figure \u003cspan refid=\"MOESM2\" class=\"InternalRef\"\u003eS2\u003c/span\u003eB). Next, we selected miR-23a KO clones 1 and 2 (miR-23a KO1 and KO2) and miR-27a KO clones 1 and 2 (miR-27a KO1 and KO2) for Sanger DNA sequencing. Supplementary Figures \u003cspan refid=\"MOESM2\" class=\"InternalRef\"\u003eS2\u003c/span\u003eC and S2D show a 55bp homozygous deletion in miR-23a KO1 and KO2, a 53bp homozygous deletion in miR-27a KO1, and a heterozygous 53bp deletion with a 40bp insertion in miR-27a KO2.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec5\" class=\"Section2\"\u003e \u003ch2\u003eIdentification of the functional role of miR-23a and miR-27a in HepG2 cells\u003c/h2\u003e \u003cp\u003eInitially, we transfected HepG2 and Huh7 cells with miRNA mimics or inhibitors to elucidate the individual roles of miRNAs within the miR-23a\u0026thinsp;~\u0026thinsp;27a\u0026thinsp;~\u0026thinsp;24\u0026thinsp;\u0026minus;\u0026thinsp;2 cluster in the proliferation and migration of HCC cells. In HepG2 cells, the miR-27a-3p and miR-24-3p inhibitors notably reduced both cell proliferation and migration (Figs.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003eH-L). Surprisingly, the miR-23a-3p inhibitor did not influence cell proliferation but appeared to induce cell migration (Figs.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003eH-L). In Huh7 cells, the miR-23a-3p, miR-27a-3p, and miR-24-3p mimics induced cell proliferation (Figs.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003eM-Q). However, while the miR-27a-3p and miR-24-3p mimics promoted cell migration, the miR-23a-3p mimic seemed to inhibit cell migration (Figs.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003eM-Q).\u003c/p\u003e \u003cp\u003eSubsequently, using our established KO cell models, we conducted various cell proliferation assays to assess the impact of miRNAs in the miR-23a\u0026thinsp;~\u0026thinsp;27a\u0026thinsp;~\u0026thinsp;24\u0026thinsp;\u0026minus;\u0026thinsp;2 cluster on HepG2 cell growth. In the MTT assay, cell growth was notably slower in miR-23a KO and miR-27a KO cells compared to scrambled cells (Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003eA). The colony formation assay revealed reduced clone number and area in miR-23a KO or miR-27a KO cells compared with scrambled cells (Figs.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003eB-D). Remarkably, miR-27a played a dominant role in HepG2 cells compared to miR-23a, evident in the suppression of cell growth and colony formation.\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003eSimilarly, in three-dimensional cell culture models, clone area was diminished in miR-23a KO or miR-27a KO cells compared with scrambled cells (Figs.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003eE and \u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003eF). However, only miR-27a KO resulted in a decrease in clone number, not observed in miR-23a KO compared with scrambled cells (Figs.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003eE and \u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003eG). To corroborate these \u003cem\u003ein vitro\u003c/em\u003e findings, we subcutaneously injected scramble, miR-23a KO, and miR-27a KO HepG2 cells into NGS mice. Xenograft tumor growth and weights were notably reduced in mice with miR-23a KO or miR-27a KO cells compared to those with scrambled cells (Figs.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003eH-J).\u003c/p\u003e \u003cp\u003e \u003cb\u003emiR-23a KO and miR-27a KO inhibits cell proliferation through the cell cycle arrest in HepG2 cells\u003c/b\u003e \u003c/p\u003e \u003cp\u003eTo examine whether the impact of miR-23a and miR-27a on cell proliferation is mediated through apoptosis, we treated scramble, miR-23a KO, and miR-27a KO HepG2 cells with H\u003csub\u003e2\u003c/sub\u003eO\u003csub\u003e2\u003c/sub\u003e to induce apoptosis. However, both miR-23a KO and miR-27a KO did not appear to affect cell apoptosis before and after H\u003csub\u003e2\u003c/sub\u003eO\u003csub\u003e2\u003c/sub\u003e stimulation when compared to scrambled cells (Supplementary Figures S3A-D). This suggests that miR-23a KO or miR-27a KO may not influence the apoptosis of HepG2 cells. Subsequently, to investigate whether the effect of miR-23a and miR-27a on cell proliferation is related to the regulation of cell cycle progression, we arrested cells at the G0-G1 phase by serum deprivation for 48 hours in scramble, miR-23a KO, and miR-27a KO HepG2 cells. After 8 hours of serum stimulation, no significant differences were observed among the three groups in the S phase. However, cells entering the G2/M phase were likely decreased in the miR-27a KO group (Figs.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003eA-B). After 22 hours of serum stimulation, fewer cells entered the G2/M phase in both miR-23a KO and miR-27a KO groups (Figs.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003eA-B). To corroborate the cell cycle results and further assess the impact of miR-23a/miR-27a on cell proliferation, BrdU staining was performed. At 8 hours after serum stimulation, 37.7% of scrambled cells, 34.1% of miR-23a KO cells, and 29.4% of miR-27a KO cells were in the S phase, with no significant differences observed between scrambled and miRNA KO cells (Figs.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003eC-D). After 16 hours of serum stimulation, 39.9%, 58%, and 64.9% of cells entered the S phase, respectively, with no significant difference among the groups (Figs.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003eC-D). However, fewer miR-23a KO cells at 8 hours and miR-27a KO cells at 16 hours entered the G2/M phase compared to scrambled cells (Figs.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003eC-D).\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003eTo unravel the molecular mechanism underlying the growth suppression caused by miR-23a/miR-27a KO, we assessed the expression of cell cycle regulatory proteins through Western blot analysis. As depicted in Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003eE, both miR-23a KO and miR-27a KO led to a reduction in the expression of cyclin A and cyclin B, while cyclin D and cyclin E remained unchanged in the cells. Moreover, phospho-CDK1, essential for G2/M phase transitions, exhibited an increase in miR-23a KO or miR-27a KO cells (Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003eE). This suggests that the elevated phospho-CDK1 in miRNA KO cells may contribute to cell cycle arrest at the G2/M phase. Notably, the expressions of p53, p21 (essential for G1 arrest), and c-Myc (critical in G1/S progression) \u003csup\u003e32\u003c/sup\u003e remained unaltered among the experimental groups (Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003eE). Furthermore, the increased expression of cyclin B and phospho-CDK1 observed in miR-23a KO or miR-27a KO xenograft tumors compared to scrambled xenograft tumors was also validated (Figs.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003eF-H). These findings suggest that miR-23a KO and miR-27a KO may promote cell proliferation through CDK1-dependent cell cycle arrest at the G2/M phase.\u003c/p\u003e \u003cp\u003e \u003cb\u003eRegulation of cell cycle progression and associated gene network by miR-23a and miR-27a in HepG2 Cells\u003c/b\u003e \u003c/p\u003e \u003cp\u003eTo unravel the regulatory gene network influenced by miR-23a and miR-27a, we conducted RNA-seq using scramble HepG2 cells as the control group and miR-23a KO/miR-27a KO HepG2 cells as the case groups. As depicted in Fig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003eA and detailed in Supplementary Table \u003cspan refid=\"MOESM1\" class=\"InternalRef\"\u003eS1\u003c/span\u003eA-B, miR-23a KO led to the up-regulation of 2599 genes and the down-regulation of 795 genes (\u0026gt;\u0026thinsp;1.5-fold change, \u003cem\u003eq\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.001) compared to control cells. Similarly, miR-27a KO resulted in the up-regulation of 2194 genes and the down-regulation of 1147 genes (\u0026gt;\u0026thinsp;1.5-fold change, \u003cem\u003eq\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.001) compared to control cells (Fig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003eB and Supplementary Table \u003cspan refid=\"MOESM1\" class=\"InternalRef\"\u003eS1\u003c/span\u003eC-D). Furthermore, potential target genes of miR-23a and miR-27a were predicted using the public miRNA TargetScan database (Supplementary Table \u003cspan refid=\"MOESM2\" class=\"InternalRef\"\u003eS2\u003c/span\u003e). Seven candidate genes were selected based on the criteria of (\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e) Fold change\u0026thinsp;\u0026gt;\u0026thinsp;1.5, \u003cem\u003eq\u003c/em\u003e value\u0026thinsp;\u0026lt;\u0026thinsp;0.001 in both miR-23a KO and miR-27a KO groups, and (\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e) Genes binding to the sequences of both miR-23a-3p and miR-27a-3p predicted by TargetScan (Fig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003eC and Supplementary Table S3A-C). Next, we employed Gene Set Enrichment Analysis (GSEA) to identify enriched gene sets in miR-23a KO or miR-27a KO cells. As illustrated in Fig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003eD and detailed in Supplementary Table S4, the up-regulated genes were predominantly associated with cell cycle regulation, encompassing E2F target, G2/M checkpoint, MYC target, mitotic spindle, and DNA repair. Additionally, the heat map of the top 30 core enrichment genes with a high \"Rank Metric Score\" in each gene set is presented in Fig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003eE. Finally, among the seven-candidate target genes, \u003cem\u003ePURA\u003c/em\u003e was identified as enriched in the G2/M checkpoint gene set (Fig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003eC and Supplementary Table S5) and co-regulated by miR-23a and miR-27a (Supplementary Figure S4).\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec6\" class=\"Section2\"\u003e \u003ch2\u003eIdentification of the miR-23a\u0026thinsp;~\u0026thinsp;27a\u0026thinsp;~\u0026thinsp;24\u0026thinsp;\u0026minus;\u0026thinsp;2 cluster regulated gene network and its integrative function in HCC cells\u003c/h2\u003e \u003cp\u003eTo elucidate the collaborative function of miRNAs within the miR-23a\u0026thinsp;~\u0026thinsp;27a\u0026thinsp;~\u0026thinsp;24\u0026thinsp;\u0026minus;\u0026thinsp;2 cluster, we established endogenous miR-23a\u0026thinsp;~\u0026thinsp;27a\u0026thinsp;~\u0026thinsp;24\u0026thinsp;\u0026minus;\u0026thinsp;2 CRISPR/dCas9 controllable HepG2 cell models. Utilizing the doxycycline (Dox)-inducible dCas9-VP64-p65-Rta (dCas9-VPR) for CRISPRa and Dox-inducible dCas9-KRAB for CRISPRi, we aimed to regulate the transcriptional activity of the miR-23a\u0026thinsp;~\u0026thinsp;27a\u0026thinsp;~\u0026thinsp;24\u0026thinsp;\u0026minus;\u0026thinsp;2 cluster in HepG2 cells (Figs.\u0026nbsp;\u003cspan refid=\"Fig5\" class=\"InternalRef\"\u003e5\u003c/span\u003eA and \u003cspan refid=\"Fig5\" class=\"InternalRef\"\u003e5\u003c/span\u003eF). Different sequence-specific single guide RNAs (sgRNAs) in the promoter region of miR-23a\u0026thinsp;~\u0026thinsp;27a\u0026thinsp;~\u0026thinsp;24\u0026thinsp;\u0026minus;\u0026thinsp;2 were designed, and the transduced efficiency of these sgRNAs was confirmed through immunofluorescence and qPCR (Figs.\u0026nbsp;\u003cspan refid=\"Fig5\" class=\"InternalRef\"\u003e5\u003c/span\u003eB and \u003cspan refid=\"Fig5\" class=\"InternalRef\"\u003e5\u003c/span\u003eG). Following Dox addition, the CRISPR/dCas9 system was induced for seven days. In the CRISPRi system, the expression of miR-23a-3p, miR-27a-3p, and miR-24-3p gradually decreased in cells transfected with sgRNA1 and sgRNA2 (Figs.\u0026nbsp;\u003cspan refid=\"Fig5\" class=\"InternalRef\"\u003e5\u003c/span\u003eC). Conversely, in the CRISPRa system, the expression of miR-23a-3p, miR-27a-3p, and miR-24-3p progressively increased in cells transfected with sgRNA3 and sgRNA4 (Figs.\u0026nbsp;\u003cspan refid=\"Fig5\" class=\"InternalRef\"\u003e5\u003c/span\u003eH).\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003eTo validate the gene network and signaling pathway involved in the miR-23a\u0026thinsp;~\u0026thinsp;27a\u0026thinsp;~\u0026thinsp;24\u0026thinsp;\u0026minus;\u0026thinsp;2 cluster, we identified genes enriched in the G2/M phase using KEGG mapper-cell cycle and marked the enriched genes in red (Supplementary Figure S4). Most \"red\" genes were associated with the G2/M phase, consistent with the \u003cem\u003ein vitro\u003c/em\u003e and \u003cem\u003ein vivo\u003c/em\u003e results. Subsequently, genes enriched in the G2/M phase of the KEGG mapper-cell cycle were further investigated using our established endogenous miR-23a\u0026thinsp;~\u0026thinsp;27a\u0026thinsp;~\u0026thinsp;24\u0026thinsp;\u0026minus;\u0026thinsp;2 controllable HepG2 cell model. Nine genes were examined in the CRISPRi system with sgRNAs (\u003cem\u003ePURA\u003c/em\u003e, \u003cem\u003eCDC27\u003c/em\u003e, \u003cem\u003eSTAG1\u003c/em\u003e, \u003cem\u003eTTK\u003c/em\u003e, \u003cem\u003eMAD2L1\u003c/em\u003e, \u003cem\u003ePLK1\u003c/em\u003e, \u003cem\u003eBUB1\u003c/em\u003e, \u003cem\u003eSMC1A\u003c/em\u003e, and \u003cem\u003eCDK1\u003c/em\u003e) (Supplementary Figure S4). The expression of \u003cem\u003ePURA\u003c/em\u003e, \u003cem\u003eCDC27\u003c/em\u003e, \u003cem\u003eSTAG1\u003c/em\u003e, and \u003cem\u003eTTK\u003c/em\u003e dynamically changed under the condition of Dox induction (Fig.\u0026nbsp;\u003cspan refid=\"Fig5\" class=\"InternalRef\"\u003e5\u003c/span\u003eD). These four genes were validated in the CRISPRa system with sgRNAs, showing dynamic changes in expression after Dox induction (Fig.\u0026nbsp;\u003cspan refid=\"Fig5\" class=\"InternalRef\"\u003e5\u003c/span\u003eI). Likewise, we established endogenous miR-23a\u0026thinsp;~\u0026thinsp;27a\u0026thinsp;~\u0026thinsp;24\u0026thinsp;\u0026minus;\u0026thinsp;2 CRISPRi/a controllable cell models in Huh7 cells (Supplementary Figures S5A-C and S5F-H). These four genes were further confirmed in the CRISPRi/a system in Huh7 cells, showing dynamic changes in expression after Dox induction (Supplementary Figures S5D and S5I).\u003c/p\u003e \u003cp\u003eNext, we examined the functional implications of manipulating the miR-23a\u0026thinsp;~\u0026thinsp;27a\u0026thinsp;~\u0026thinsp;24\u0026thinsp;\u0026minus;\u0026thinsp;2 cluster in HepG2 and Huh7 cells. The introduction of Dox induced a decrease in cell proliferation in CRISPRi HepG2 and Huh7 cells (Fig.\u0026nbsp;\u003cspan refid=\"Fig5\" class=\"InternalRef\"\u003e5\u003c/span\u003eE and Supplementary Figure S5E), while CRISPRa HepG2 and Huh7 cells exhibited an increase in cell proliferation following Dox induction (Fig.\u0026nbsp;\u003cspan refid=\"Fig5\" class=\"InternalRef\"\u003e5\u003c/span\u003eJ and Supplementary Figure S5J). These findings strongly suggest an oncogenic role of the miR-23a\u0026thinsp;~\u0026thinsp;27a\u0026thinsp;~\u0026thinsp;24\u0026thinsp;\u0026minus;\u0026thinsp;2 cluster in HCC cells. To gain deeper insights into the regulatory mechanisms of this miRNA cluster, we investigated the impact of 3p\u0026rsquo; miR-23a/27a/24 mimics and inhibitors on cell proliferation in miR-23a\u0026thinsp;~\u0026thinsp;27a\u0026thinsp;~\u0026thinsp;24\u0026thinsp;\u0026minus;\u0026thinsp;2 CRISPRi/a HepG2 and Huh7 cells. Upon Dox induction, the miR-23a-3p and miR-27a-3p mimics enhanced cell proliferation in miR-23a\u0026thinsp;~\u0026thinsp;27a\u0026thinsp;~\u0026thinsp;24\u0026thinsp;\u0026minus;\u0026thinsp;2 CRISPRi cells, while the miR-23a-3p and miR-27a-3p inhibitors reduced cell proliferation in miR-23a\u0026thinsp;~\u0026thinsp;27a\u0026thinsp;~\u0026thinsp;24\u0026thinsp;\u0026minus;\u0026thinsp;2 CRISPRa cells (Supplementary Figures S6A-D). However, miR-24-3p mimic and inhibitor did not exhibit effects on cell proliferation. These results suggest that miR-23a and miR-27a contributes to the integrative oncogenic function of the miR-23a\u0026thinsp;~\u0026thinsp;27a\u0026thinsp;~\u0026thinsp;24\u0026thinsp;\u0026minus;\u0026thinsp;2 cluster in HCC cells.\u003c/p\u003e \u003cp\u003e \u003cb\u003emiR-23a/miR-27a co-target\u003c/b\u003e \u003cb\u003ePURA\u003c/b\u003e \u003cb\u003edirectly to promote cell proliferation in HepG2 cells\u003c/b\u003e\u003c/p\u003e \u003cp\u003eTo investigate the interaction between miR-23a-3p/miR-27a-3p and its target mRNAs, we conducted a miRNA-mRNA interaction analysis using miRNA target immunoprecipitation (IP) with Argonaute proteins (Ago1/2/3) following transfection with the miR-23a-3p/miR-27a-3p mimic in HepG2 cells (Fig.\u0026nbsp;\u003cspan refid=\"Fig6\" class=\"InternalRef\"\u003e6\u003c/span\u003eA). The Ago IP analysis revealed a direct binding of \u003cem\u003ePURA\u003c/em\u003e mRNA with Ago1/2/3 proteins in the presence of miR-23a/miR-27a compared to the scrambled miRNA control (Fig.\u0026nbsp;\u003cspan refid=\"Fig6\" class=\"InternalRef\"\u003e6\u003c/span\u003eB), supporting the direct interaction of miR-23a/miR-27a with \u003cem\u003ePURA\u003c/em\u003e mRNA in HepG2 cells. However, Figs.\u0026nbsp;\u003cspan refid=\"Fig6\" class=\"InternalRef\"\u003e6\u003c/span\u003eC and \u003cspan refid=\"Fig6\" class=\"InternalRef\"\u003e6\u003c/span\u003eD demonstrated that \u003cem\u003eSTAG1\u003c/em\u003e mRNA bound to the sequence of miR-27a but not the sequence of miR-23a, and TTK did not bind to either miR-23a or miR-27a.\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003eTo delve deeper into the mechanism of miR-23a/miR-27a-mediated transcriptional regulation of \u003cem\u003ePURA\u003c/em\u003e, we evaluated the impact of miR-23a/miR-27a KO, mimic, and inhibitor on \u003cem\u003ePURA\u003c/em\u003e transcription in HepG2 cells. As depicted in Fig.\u0026nbsp;\u003cspan refid=\"Fig6\" class=\"InternalRef\"\u003e6\u003c/span\u003eE, compared to the scrambled cells, \u003cem\u003ePURA\u003c/em\u003e expression was higher in miR-23 KO cells, lower in cells transfected with miR-23a-3p mimic, and unchanged in cells transfected with miR-23a-3p inhibitor. Similar results were observed in miR-27a KO cells or cells transfected with mimic or inhibitor (Fig.\u0026nbsp;\u003cspan refid=\"Fig6\" class=\"InternalRef\"\u003e6\u003c/span\u003eE). Western blot analysis also revealed elevated \u003cem\u003ePURA\u003c/em\u003e expression in miR-23a KO and miR-27a KO cells compared to scrambled cells (Fig.\u0026nbsp;\u003cspan refid=\"Fig6\" class=\"InternalRef\"\u003e6\u003c/span\u003eF). Consistent results were confirmed by immunohistochemical staining (IHC) in miR-23a KO and miR-27a KO xenograft tumors relative to scrambled xenograft tumors (Fig.\u0026nbsp;\u003cspan refid=\"Fig6\" class=\"InternalRef\"\u003e6\u003c/span\u003eG).\u003c/p\u003e \u003cp\u003eSubsequent sequence alignment analysis identified potential miR-23a-3p/miR-27a-3p targeting sites in the \u003cem\u003ePURA\u003c/em\u003e 3\u0026rsquo;- untranslated region (UTR) (Fig.\u0026nbsp;\u003cspan refid=\"Fig6\" class=\"InternalRef\"\u003e6\u003c/span\u003eH). Using a pmiR-luciferase reporting system, we elucidated the post-transcriptional regulation mechanism of \u003cem\u003ePURA\u003c/em\u003e by miRNAs. Transfection of miR-23a-3p/miR-27a-3p mimics reduced the luciferase activity of the wild-type PURA 3\u0026rsquo;-UTR (Figs.\u0026nbsp;\u003cspan refid=\"Fig6\" class=\"InternalRef\"\u003e6\u003c/span\u003eI and \u003cspan refid=\"Fig6\" class=\"InternalRef\"\u003e6\u003c/span\u003eJ). However, deletion of the miR-23a-3p-targeting sequence (AAUGUGA)/miR-27a-3p-targeting sequence (ACUGUGA) in the \u003cem\u003ePURA\u003c/em\u003e 3\u0026rsquo;-UTR rescued the luciferase activity of \u003cem\u003ePURA\u003c/em\u003e 3\u0026rsquo;-UTR in HepG2 cells transfected with miR-23a-3p/miR-27a-3p mimics (Figs.\u0026nbsp;\u003cspan refid=\"Fig6\" class=\"InternalRef\"\u003e6\u003c/span\u003eI and \u003cspan refid=\"Fig6\" class=\"InternalRef\"\u003e6\u003c/span\u003eJ). Confirming the impact of \u003cem\u003ePURA\u003c/em\u003e on cell proliferation, we assessed cell growth in miR-23a KO/miR-27a KO cells transfected with \u003cem\u003ePURA\u003c/em\u003e siRNA (Fig.\u0026nbsp;\u003cspan refid=\"Fig6\" class=\"InternalRef\"\u003e6\u003c/span\u003eK). As depicted in Figs.\u0026nbsp;\u003cspan refid=\"Fig6\" class=\"InternalRef\"\u003e6\u003c/span\u003eL and \u003cspan refid=\"Fig6\" class=\"InternalRef\"\u003e6\u003c/span\u003eM, the suppression of cell growth in miR-23a/miR-27a KO HepG2 cells was partly rescued after \u003cem\u003ePURA\u003c/em\u003e silencing.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec7\" class=\"Section2\"\u003e \u003ch2\u003eValidation of miR-23a/miR-27a-regulated gene network in HepG2 cells\u003c/h2\u003e \u003cp\u003eTo confirm the regulatory impact of miR-23a/miR-27a on gene expression, Western blot analysis revealed that STAG1 was up-regulated, while TTK was down-regulated in miR-23a KO and miR-27a KO cells, respectively, compared to scrambled control cells (Fig.\u0026nbsp;\u003cspan refid=\"Fig6\" class=\"InternalRef\"\u003e6\u003c/span\u003eN). Subsequently, we introduced \u003cem\u003ePURA\u003c/em\u003e siRNAs into scrambled HepG2 cells to investigate whether the regulation of STAG1 and TTK was PURA-dependent. The expression of STAG1 decreased, whereas TTK increased after \u003cem\u003ePURA\u003c/em\u003e siRNA silencing (Fig.\u0026nbsp;\u003cspan refid=\"Fig6\" class=\"InternalRef\"\u003e6\u003c/span\u003eN), indicating a PURA-dependent expression pattern for STAG1 and TTK. Further investigation into the miR-23a/miR-27a KO effects on the PURA-STAG1/TTK axes and their regulation in both scramble and miR-23a/miR-27a KO HepG2 cells revealed intriguing insights. For STAG1 expression analysis, miR-23a KO increased the expression of STAG1, but this effect was diminished by \u003cem\u003ePURA\u003c/em\u003e siRNA in miR-23a KO cells (Fig.\u0026nbsp;\u003cspan refid=\"Fig6\" class=\"InternalRef\"\u003e6\u003c/span\u003eO). Conversely, miR-23a-3p mimic decreased STAG1 expression, and this effect was rescued by \u003cem\u003ePURA\u003c/em\u003e siRNA in miR-23a-3p mimic-transfected HepG2 cells (Fig.\u0026nbsp;\u003cspan refid=\"Fig6\" class=\"InternalRef\"\u003e6\u003c/span\u003eO), indicating a miR-23a-PURA-STAG1 axis. Likewise, miR-27a KO increased STAG1 expression, but this increase was reversed by \u003cem\u003ePURA\u003c/em\u003e siRNA in miR-27a KO cells (Fig.\u0026nbsp;\u003cspan refid=\"Fig6\" class=\"InternalRef\"\u003e6\u003c/span\u003eO). However, miR-27a-3p mimic decreased STAG1 expression, and \u003cem\u003ePURA\u003c/em\u003e siRNA did not rescue this decrease in miR-27a-3p mimic-transfected HepG2 cells (Fig.\u0026nbsp;\u003cspan refid=\"Fig6\" class=\"InternalRef\"\u003e6\u003c/span\u003eO), suggesting a PURA-independent miR-27a-STAG1 axis. Notably, miR-27a may directly target \u003cem\u003eSTAG1\u003c/em\u003e in the miRNA target IP assay (Fig.\u0026nbsp;\u003cspan refid=\"Fig6\" class=\"InternalRef\"\u003e6\u003c/span\u003eC), further supporting a PURA-independent miR-27a-STAG1 axis.\u003c/p\u003e \u003cp\u003e \u003cb\u003eEffect of miR-23a/miR-27 and its cluster in cell migration and epithelial-mesenchymal transition (EMT) in HCC cells\u003c/b\u003e \u003c/p\u003e \u003cp\u003eGiven the reported role of the miR-23a\u0026thinsp;~\u0026thinsp;27a\u0026thinsp;~\u0026thinsp;24\u0026thinsp;\u0026minus;\u0026thinsp;2 cluster in promoting cell migration \u003csup\u003e33\u003c/sup\u003e and the observed regulation of cell migration by miR-23a-3p/miR-27a-3p mimics (Figs.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003eI-L), we investigated the impact of miR-23a/miR-27a KO on cell migration in HepG2 cells. Utilizing scratch assays and Transwell assays, we found that cell migration was accelerated in miR-23a KO cells and decelerated in miR-27a KO cells compared to scrambled control cells (Figs.\u0026nbsp;\u003cspan refid=\"Fig7\" class=\"InternalRef\"\u003e7\u003c/span\u003eA-D). Additionally, IHC analysis revealed that, in miR-23a KO xenograft tumors, E-cadherin expression decreased while N-cadherin increased, indicating a role for miR-23a in promoting cell migration and EMT. Conversely, miR-27a KO xenograft tumors exhibited an opposite trend, with increased E-cadherin and decreased N-cadherin expression (Fig.\u0026nbsp;\u003cspan refid=\"Fig7\" class=\"InternalRef\"\u003e7\u003c/span\u003eE), suggesting a distinct role for miR-27a in these processes.\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003eNext, we investigated the impact of manipulating the miR-23a\u0026thinsp;~\u0026thinsp;27a\u0026thinsp;~\u0026thinsp;24\u0026thinsp;\u0026minus;\u0026thinsp;2 cluster on cell migration in both HepG2 and Huh7 cells. Upon Dox induction, CRISPRi inhibited cell migration in HepG2 and Huh7 cells. The introduction of miR-23a-3p mimic further enhanced cell migration, whereas miR-27a-3p mimic reduced cell migration. Interestingly, miR-24-3p mimic did not significantly alter cell migration (Figs.\u0026nbsp;\u003cspan refid=\"Fig7\" class=\"InternalRef\"\u003e7\u003c/span\u003eG-J and Supplementary Figure S7A-D). Conversely, CRISPRa did not enhance cell migration. However, miR-27a-3p inhibitor, but not miR-23a-3p and miR-24-3p inhibitors, reduced cell migration (Figs.\u0026nbsp;\u003cspan refid=\"Fig7\" class=\"InternalRef\"\u003e7\u003c/span\u003eK-N and Supplementary Figure S7E-H). This differential impact of miR-23a, miR-27a, and miR-24 on cell migration suggests distinct roles for each miRNA within the miR-23a\u0026thinsp;~\u0026thinsp;27a\u0026thinsp;~\u0026thinsp;24\u0026thinsp;\u0026minus;\u0026thinsp;2 cluster, further underscoring the integrative oncogenic function of this cluster in HCC cells.\u003c/p\u003e \u003cp\u003eTo understand the molecular mechanisms underlying the miR-23a\u0026thinsp;~\u0026thinsp;27a\u0026thinsp;~\u0026thinsp;24\u0026thinsp;\u0026minus;\u0026thinsp;2 cluster-regulated migration of HCC cells, we investigated proteins involved in EMT and relevant regulatory molecules. In HepG2 cells, miR-23a KO decreased E-cadherin but increased N-cadherin expression, while miR-27a had the opposite effect (Fig.\u0026nbsp;\u003cspan refid=\"Fig7\" class=\"InternalRef\"\u003e7\u003c/span\u003eF). Among EMT-related or upstream regulatory molecules, only Snail exhibited inter-group differences, indicating that the miR-23a\u0026thinsp;~\u0026thinsp;27a\u0026thinsp;~\u0026thinsp;24\u0026thinsp;\u0026minus;\u0026thinsp;2 cluster appear to influence EMT through the regulation of Snail (Fig.\u0026nbsp;\u003cspan refid=\"Fig7\" class=\"InternalRef\"\u003e7\u003c/span\u003eF).\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec8\" class=\"Section2\"\u003e \u003ch2\u003eIdentification of miR-23a/miR-27 signaling axes in HCC cell migration\u003c/h2\u003e \u003cp\u003eUpon re-analyzing the candidate target genes (Fig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003eC), we identified \u003cem\u003eBMPR2\u003c/em\u003e as a target gene of miR-23a that regulates EMT through the BMP-Smad-Snail signaling pathway \u003csup\u003e34\u003c/sup\u003e. In HepG2 cells, we observed up-regulation of BMPR2 in miR-23a KO cells, while no significant difference in BMPR2 was observed in miR-27a KO cells compared to scrambled cells (Fig.\u0026nbsp;\u003cspan refid=\"Fig8\" class=\"InternalRef\"\u003e8\u003c/span\u003eA). miRNA target IP further confirmed the direct binding of miR-23a, but not miR-27a, to the \u003cem\u003eBMPR2\u003c/em\u003e 3'-UTR (Fig.\u0026nbsp;\u003cspan refid=\"Fig8\" class=\"InternalRef\"\u003e8\u003c/span\u003eB). Silencing \u003cem\u003eBMPR2\u003c/em\u003e using siRNAs rescued the enhanced cell migration observed in miR-23a KO HepG2 cells (Figs.\u0026nbsp;\u003cspan refid=\"Fig8\" class=\"InternalRef\"\u003e8\u003c/span\u003eC-E). Transfecting miR-23a-3p mimics into miR-23a KO cells rescued the expression of E-cadherin, reduced the expression of N-cadherin, and led to decreases in BMPR2, Snail, and phospho-Smad1 (Fig.\u0026nbsp;\u003cspan refid=\"Fig8\" class=\"InternalRef\"\u003e8\u003c/span\u003eF). These findings suggest a miR-23a-BMPR2-Smad-Snail axis in the regulation of EMT signaling.\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003eLikewise, we identified \u003cem\u003eTMEM170B\u003c/em\u003e as a potential target gene of miR-27a that regulates EMT via the TMEM170B-Twist-β-catenin signaling pathway \u003csup\u003e35\u003c/sup\u003e. Testing the effect of miR-23a/miR-27a on this EMT signaling in HepG2 cells, we found that TMEM170B was up-regulated in miR-27a KO cells but not in miR-23a KO cells compared to scrambled cells (Fig.\u0026nbsp;\u003cspan refid=\"Fig8\" class=\"InternalRef\"\u003e8\u003c/span\u003eG). miRNA target IP validated the direct binding of miR-27a, but not miR-23a, to the \u003cem\u003eTMEM170B\u003c/em\u003e 3'-UTR (Fig.\u0026nbsp;\u003cspan refid=\"Fig8\" class=\"InternalRef\"\u003e8\u003c/span\u003eH). Silencing \u003cem\u003eTMEM170B\u003c/em\u003e using siRNAs rescued the reduced cell migration observed in miR-27a KO HepG2 cells (Figs.\u0026nbsp;\u003cspan refid=\"Fig8\" class=\"InternalRef\"\u003e8\u003c/span\u003eI-K). Transfecting miR-27a-3p mimics into miR-27a KO cells rescued the expression of TMEM170B and E-cadherin, induced the expression of N-cadherin and vimentin, and led to increases in Twist and nuclear β-catenin (Fig.\u0026nbsp;\u003cspan refid=\"Fig8\" class=\"InternalRef\"\u003e8\u003c/span\u003eL). These results suggest a miR-27a-TMEM170B-Twist-β-catenin axis in the regulation of EMT signaling.\u003c/p\u003e \u003c/div\u003e"},{"header":"Discussion","content":"\u003cp\u003eThe utilization of CRISPR/Cas9 for genetic and epigenetic editing holds promise as a tool for investigating the regulation and function of clustered miRNAs \u003csup\u003e36\u003c/sup\u003e. In this study, we employed CRISPR KO, CRISPRi, and CRISPRa approaches to dissect the functional role and underlying signaling of the miR-23a\u0026thinsp;~\u0026thinsp;27a\u0026thinsp;~\u0026thinsp;24\u0026thinsp;\u0026minus;\u0026thinsp;2 cluster in HCC cells. Either miR-23a KO or miR-27a KO resulted in reduced cell growth both \u003cem\u003ein vitro\u003c/em\u003e and \u003cem\u003ein vivo\u003c/em\u003e. Moreover, the endogenous miRNAs within the miR-23a\u0026thinsp;~\u0026thinsp;27a\u0026thinsp;~\u0026thinsp;24\u0026thinsp;\u0026minus;\u0026thinsp;2 cluster were effectively regulated by CRISPRi/a. Notably, using the CRISPRi/a approach, we identified an integrated oncogenic role of the miR-23a\u0026thinsp;~\u0026thinsp;27a\u0026thinsp;~\u0026thinsp;24\u0026thinsp;\u0026minus;\u0026thinsp;2 cluster in the proliferation of HCC cells. Functional analysis revealed that miR-23a KO and miR-27a KO induced cell cycle arrest at the G2/M phase by reducing CDK1/cyclin B activation in HCC cells. Furthermore, employing a high-throughput RNA-seq approach with miRNA target prediction, we identified the miR-23a/miR-27a-regulated gene network. Various analyses validated that miR-23a/miR-27a co-target \u003cem\u003ePURA\u003c/em\u003e directly to promote cell proliferation in HepG2 cells. In addition, miR-23a and miR-27a exhibited opposite roles in cell migration and EMT. However, an integrated analysis by CRISPRi/a suggested an oncogenic role of the miR-23a\u0026thinsp;~\u0026thinsp;27a\u0026thinsp;~\u0026thinsp;24\u0026thinsp;\u0026minus;\u0026thinsp;2 cluster in cell migration may occur through an interaction of miR-23a-BMPR2-Smad-Snail axis and miR-27a-TMEM170B-Twist-β-catenin axis in HCC cells (Supplementary Figure S8).\u003cdiv class=\"BlockQuote\"\u003e\u003cp\u003eGiven the involvement of miRNAs in the miR-23a\u0026thinsp;~\u0026thinsp;27a\u0026thinsp;~\u0026thinsp;24\u0026thinsp;\u0026minus;\u0026thinsp;2 cluster in various functions and signaling pathways in HCC \u003csup\u003e5\u003c/sup\u003e, depicting their integrative role and complete regulatory network is challenging. However, our established endogenous miRNA controllable system offers a comprehensive platform for identifying the functional role and underlying signaling of clustered miRNAs. In this study, we used CRISPR KO to assess the potential role and gene network of individual mature miR-23a/miR-27a in HCC cells. However, due to the joint transcription of miRNAs in the miR-23a\u0026thinsp;~\u0026thinsp;27a\u0026thinsp;~\u0026thinsp;24\u0026thinsp;\u0026minus;\u0026thinsp;2 cluster, miR-23a KO disrupted the expression of miR-27 and miR-24, while miR-27a KO affected the expression of miR-24 but unlikely changed the expression of miR-23a. Thus, the CRISPR KO approach is not ideal for defining the role of individual miRNAs from the miRNA cluster. Next, using CRISPRi/a, we addressed the role and gene network of the miR-23a\u0026thinsp;~\u0026thinsp;27a\u0026thinsp;~\u0026thinsp;24\u0026thinsp;\u0026minus;\u0026thinsp;2 cluster in HCC cells. Combining CRISPRi/a-mediated endogenous miRNA regulation with exogenous miRNA mimic and inhibitor intervention, we validated the role and gene network of individual mature miR-23a/miR-27a in HCC cells. Additionally, both the miR-23a\u0026thinsp;~\u0026thinsp;27a\u0026thinsp;~\u0026thinsp;24\u0026thinsp;\u0026minus;\u0026thinsp;2 and miR-23b\u0026thinsp;~\u0026thinsp;27b\u0026thinsp;~\u0026thinsp;24\u0026thinsp;\u0026minus;\u0026thinsp;1 clusters include miR-24 and encode the pri-miRNA transcript that composes miR-24 \u003csup\u003e4\u003c/sup\u003e. To address the role of miR-24, CRISPR KO or CRISPRi/a should target both clusters for transcriptional regulation of miR-24. However, this approach may introduce more complexity to the CRISPR system, off-target effects, or complicate functional analysis between the two clusters. Therefore, we focused solely on miR-23a/miR-27a and did not establish the miR-24 KO in the HCC cell model. Recently, we have developed a flexible CRISPR/dCas9-based platform for complex gene regulation, allowing independent control of the expression of different genes (repression and activation) within the same cell, using two different S. pyogenes (Sp)-dCas9 and S. aureus (Sa)-dCas9 \u003csup\u003e37\u003c/sup\u003e. This dual CRISPR platform for repression and activation may serve as an ideal tool for our future studies to distinguish the roles of the two miRNA clusters, including miR-24, within the same HCC cell.\u003c/p\u003e\u003cp\u003eOur gene network analysis revealed that the enriched gene set in both miR-23a KO and miR-27a KO groups was predominantly associated with the cell cycle signaling network. Further analysis of the enriched genes in the KEGG map showed that the majority of these genes were concentrated in the G2/M phase of the cell cycle. This finding was consistent with the observed changes in cell cycle regulatory proteins at the G2/M phase, such as CDK1/cyclin B \u003csup\u003e38\u003c/sup\u003e. Using endogenous miR-23a\u0026thinsp;~\u0026thinsp;27a\u0026thinsp;~\u0026thinsp;24\u0026thinsp;\u0026minus;\u0026thinsp;2 controllable CRISPRi/a cell models, we confirmed dynamic changes in genes enriched in the G2/M phase based on miR-23a\u0026thinsp;~\u0026thinsp;27a\u0026thinsp;~\u0026thinsp;24\u0026thinsp;\u0026minus;\u0026thinsp;2 up-/down-regulation. The miR-23a\u0026thinsp;~\u0026thinsp;27a\u0026thinsp;~\u0026thinsp;24\u0026thinsp;\u0026minus;\u0026thinsp;2 cluster directly/indirectly regulated the gene network, including \u003cem\u003ePURA\u003c/em\u003e, \u003cem\u003eSTAG1\u003c/em\u003e, and \u003cem\u003eTTK\u003c/em\u003e, in HCC cells. In HepG2 cells, miR-23a and miR-27a induced cell cycle progression by directly targeting \u003cem\u003ePURA\u003c/em\u003e, implicating cancer cell proliferation by inhibiting cell cycle progression at G1-S or G2-M checkpoints \u003csup\u003e39\u003c/sup\u003e, resulting in increased HCC cell growth. MiR-23a and miR-27a targeted specific sites in the 3\u0026rsquo;-UTR of \u003cem\u003ePURA\u003c/em\u003e to regulate post-transcription of \u003cem\u003ePURA\u003c/em\u003e. Notably, the miR-23a and miR-27a-mediated proliferation phenotype was partly retrieved by \u003cem\u003ePURA\u003c/em\u003e siRNA. However, another study also suggested that miR-23a may promote G1/S cell cycle transition in HCC \u003csup\u003e8\u003c/sup\u003e. Although in our study, a few relevant genes of the G1/S phase were enriched in the miR-23a KO group, we did not observe an apparent change in cell cycle progression and proteins of the G1/S phase. Furthermore, our data support the notion that miR-27a may play a dominant role in the regulation of G2/M cell cycle transition. Additionally, other studies suggest that miR-23a/miR-27a regulate apoptosis in HCC cells \u003csup\u003e6, 40\u003c/sup\u003e, but our analysis showed no significant change in apoptosis after miR-23a KO or miR-27a KO. Thus, our data suggest that miR-23a/miR-27a may synergistically induce cell cycle progression, promoting cell proliferation in HCC cells.\u003c/p\u003e\u003c/div\u003e\u003c/p\u003e \u003cp\u003eThe members of the miR-23a\u0026thinsp;~\u0026thinsp;27a\u0026thinsp;~\u0026thinsp;24\u0026thinsp;\u0026minus;\u0026thinsp;2 cluster integrally inhibit the aggressiveness of breast cancer cells by targeting \u003cem\u003eNCOA1\u003c/em\u003e, \u003cem\u003eNLK\u003c/em\u003e, and \u003cem\u003eRAP1B\u003c/em\u003e \u003csup\u003e41\u003c/sup\u003e. Additionally, the c-MYC-regulated miR-23a\u0026thinsp;~\u0026thinsp;27a\u0026thinsp;~\u0026thinsp;24\u0026thinsp;\u0026minus;\u0026thinsp;2 cluster promotes cell invasion and hepatic metastasis of breast cancer by targeting \u003cem\u003eSPRY2\u003c/em\u003e \u003csup\u003e33\u003c/sup\u003e. Our CRISPR analysis is the first to provide an integrated and dynamic analysis supporting the idea that the miR-23a\u0026thinsp;~\u0026thinsp;27a\u0026thinsp;~\u0026thinsp;24\u0026thinsp;\u0026minus;\u0026thinsp;2 cluster promotes cell migration and EMT through a complex gene network in HCC cells. However, individual miR-23a/miR-27a have been reported to be associated with both tumor-promoting \u003csup\u003e42\u0026ndash;49\u003c/sup\u003e and tumor-suppressing \u003csup\u003e18, 50\u0026ndash;52\u003c/sup\u003e activities, depending on the specific context and cancer type. In this study, there are opposing effects between miR-23a (repression) and miR-27a (promotion) on cell migration and EMT in HCC cells, suggesting that miR-23a/miR-27a may play distinctive roles in tumor progression and metastasis through two different signaling axes, such as the miR-23a-BMPR2-Smad-Snail axis and the miR-27a-TMEM170B-Twist-β-catenin. Given an oncogenic role of the miR-23a\u0026thinsp;~\u0026thinsp;27a\u0026thinsp;~\u0026thinsp;24\u0026thinsp;\u0026minus;\u0026thinsp;2 cluster in cell migration and EMT, miR-27a may play a predominant role in cell migration and EMT of HCC cells. In addition, an early study has reported that, through miRNA mimic and inhibitor, miR-27a-3p inhibits the growth and metastasis of HCC cells \u003csup\u003e18\u003c/sup\u003e. Specifically, miR-27a-3p inhibits the cell migration, invasion, and EMT of HCC cells. Conversely, through miRNA KO with mimic and inhibitor, we identified an oncogenic role of miR-27a-3p in cell migration and EMT of HCC cells. The different results may be attributed to the potential effect of CRISPR KO on the transcription of the miR-23a\u0026thinsp;~\u0026thinsp;27a\u0026thinsp;~\u0026thinsp;24\u0026thinsp;\u0026minus;\u0026thinsp;2 cluster and its individual members, including miR-24. However, through CRISPRi/a with miRNA mimic and inhibitor, we validated an oncogenic role of miR-27a-3p in HCC cell migration.\u003c/p\u003e \u003cp\u003eIn conclusion, we developed an integrated CRISPR genetic and epigenetic approach to investigate the functional role and underlying signaling of the miR-23a\u0026thinsp;~\u0026thinsp;27a\u0026thinsp;~\u0026thinsp;24\u0026thinsp;\u0026minus;\u0026thinsp;2 cluster in HCC cells. Our CRISPR analysis offers a valuable research tool for dissecting the complex functions and underlying gene network of an endogenous miRNA cluster. Furthermore, this CRISPR approach provides new avenues for intervening in miRNA clusters, enabling an integrated analysis to determine the specific roles of individual miRNAs within the cluster.\u003c/p\u003e"},{"header":"Materials and Methods","content":"\u003cdiv id=\"Sec11\" class=\"Section2\"\u003e \u003ch2\u003eCell lines\u003c/h2\u003e \u003cp\u003eThe hepatocellular carcinoma cell lines HepG2 and Huh7, as well as the human embryonic kidney cell line HEK293T, were procured from the American Type Culture Collection (ATCC, Rockville, Maryland). These cell lines were cultured for less than 6 months, authenticated through examination of morphology and growth characteristics, and confirmed to be mycoplasma-free. Short tandem-repeat analysis for DNA fingerprinting was also employed to verify the cell lines. All cell lines were cultured in Dulbecco's Modified Eagle's medium (DMEM) supplemented with 10% fetal bovine serum (FBS) under standard conditions of 37\u0026deg;C and 5% CO\u003csub\u003e2\u003c/sub\u003e.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec12\" class=\"Section2\"\u003e \u003ch2\u003eAntibodies\u003c/h2\u003e \u003cp\u003eAntibodies specific for the following proteins were used as primary antibodies for Western blot or IHC: Beta catenin (ab32572, 1:5000, Abcam, Cambridge, MA), beta IV Tubulin (ab179509, 1:5000, Abcam), CDC27 (A1954, 1:1000, Abclonal, Woburn, MA), BMPR2 (A16778, 1:1000, Abclonal), CDK1 (626901, 1:1000, Biolegend, San Diego, CA), CDK2 (643901, 1:1000, Biolegend), CDK4 (2906, 1:1000, Cell Signaling, Danvers, MA), c-Myc (5605, 1:1000, Cell Signaling), Cyclin A (644001, 1:1000, Biolegend), PURA (A9296, 1:1000 for Western blot and 1:100 for IHC, Abclonal), Cyclin B (647902, 1:1000 for Western blot and 1:100 for IHC, Biolegend), Cyclin D1 (ab134175, 1:5000, Abcam), Cyclin E (sc-247, 1:1000, Santa Cruz Biotechnology, Dallas, TX), E-cadherin (3195, 1:1000 for Western blot and 1:100 for IHC, Cell Signaling), GAPDH (2118, 1:5000, Cell Signaling), Ki67 (ab15580, 1:5000 for Western blot and 1:200 for IHC, Abcam), Lamin B (sc-374015, 1:5000, Santa Cruz Biotechnology), N-cadherin (844702, 1:1000 for Western blot and 1:100 for IHC, Biolegend), p21 (2947, 1:1000, Cell Signaling), p53 (sc-126, 1:1000, Santa Cruz Biotechnology), phospho-cdc2 (Tyr15) (4539, 1:1000 for Western blot and 1:100 for IHC, Cell Signaling), phospho-Smad1/Smad5/Smad9 (13820, 1:1000, Cell Signaling), Smad1 (6944, 1:1000, Cell Signaling), Snail (ab167609, 1:5000, Abcam), STAG1 (A13715, 1:1000, Abclonal), TMEM170B (NBP2-33739, 1:1000 NOVUS Biologicals, Centennial CO), TTK (A2500, 1:1000, Abclonal), Twist (ab175430, 1:5000, Abcam), Vimentin (sc-6260, 1:1000, Santa Cruz Biotechnology), and ZEB1 (3396, 1:1000, Cell Signaling).\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec13\" class=\"Section2\"\u003e \u003ch2\u003eEstablishment of CRISPR KO and CRISPRi/a cell models\u003c/h2\u003e \u003cp\u003eThe Benchling CRISPR design tool (San Francisco, CA, \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://benchling.com\u003c/span\u003e\u003cspan address=\"https://benchling.com\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e) was employed for designing sgRNAs. The CRISPR/Cas9 editing targeted the pri-miR-23a\u0026thinsp;~\u0026thinsp;27a\u0026thinsp;~\u0026thinsp;24\u0026thinsp;\u0026minus;\u0026thinsp;2 region. Pair sgRNAs with high specificity and efficiency scores were chosen at two flanking sites of the mature miR-23a or miR-27a sequence. All sgRNAs were assessed using the Cas-OFFinder off-target searching tool (South Korea, \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttp://www.rgenome.net/cas-offinder\u003c/span\u003e\u003cspan address=\"http://www.rgenome.net/cas-offinder\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e). To mitigate off-target effects, potential off-target regions underwent PCR and Sanger sequence analysis (Supplementary Table S6). The sequences of the pair sgRNAs targeting miR-23a or miR-27a are listed in Supplementary Table S7.\u003c/p\u003e \u003cp\u003eThe pair sgRNA oligos were annealed by slow cooling from 95\u0026deg;C down to 10\u0026deg;C and then ligated to BbsI-digested pSpCas9(BB)-2A-GFP (PX458) vector (Addgene, Cambridge, MA). The integrity of the miR-23a- and miR-27a-targeted-Cas9 constructed vectors was confirmed by DNA sequencing. The constructed vector with the miR-23a or miR-27a targeting sequence, or the PX458 empty vector, was transfected into cells using Lipofectamine 3000 (Thermo Fisher Scientific). miR-23a or miR-27a KO colonies were confirmed by qPCR and Sanger sequencing after single-cell sorting (BD FACSMelody\u0026trade; Cell Sorter) with GFP. All selected colonies of miRNA scramble and KO cells were validated by PCR and Sanger sequence analysis to exclude off-target effects in potential off-target regions of sgRNAs, as described previously \u003csup\u003e53, 54\u003c/sup\u003e.\u003c/p\u003e \u003cp\u003eCRISPRi/a epigenetic editing technology was used to establish the endogenous miR-23a\u0026thinsp;~\u0026thinsp;27a\u0026thinsp;~\u0026thinsp;24\u0026thinsp;\u0026minus;\u0026thinsp;2 controllable cell models. The carrier of sgRNAs for the CRISPR nuclease-dead Cas9 (dCas9) system is pSLQ2837 pLenti U6-spsgTRE3G CMV-mIFP (a gift from Stanley Qi lab, Stanford University). pSLQ1922-dCas9-GFP-KRAB-Zeocin and pSLQ1932-dCas9-GFP-VPR-Zeocin (gift from Stanley Qi lab) are piggyBac (PB)-based DNA constructs with dCas9 elements (Supplementary Table S8). The promoter region of pri-miR-23a\u0026thinsp;~\u0026thinsp;27a\u0026thinsp;~\u0026thinsp;24\u0026thinsp;\u0026minus;\u0026thinsp;2 was the candidate target region for CRISPRi and CRISPRa, respectively.\u003c/p\u003e \u003cp\u003eFour sgRNAs (Supplementary Table S7) were designed around the \u0026minus;\u0026thinsp;50 to +\u0026thinsp;300 bp of the transcription start site (TSS) of the miR-23a\u0026thinsp;~\u0026thinsp;27a\u0026thinsp;~\u0026thinsp;24\u0026thinsp;\u0026minus;\u0026thinsp;2 cluster for CRISPRi (CRISPR/dCas9-KRAB-mediated transcriptional repression). Similarly, four sgRNAs were designed around the \u0026minus;\u0026thinsp;400 to -50 bp of the TSS for CRISPRa (CRISPR/dCas9-VPR-mediated transcriptional activation). Then, we established various cell models as follows: 1) Vectors with CRISPRi or CRISPRa system were transfected with PB transposase vector into cells, as previously described \u003csup\u003e55\u003c/sup\u003e. 2) sgRNA vectors were transduced by lentivirus-mediated transduction into CRISPRi or CRISPRa transfected cells, followed by single-cell sorting with GFP (for dCas9) and mIFP ( for sgRNA). 3) A stable cell line was established after zeocin (100 \u0026micro;g/ml, Invitrogen) selection for two weeks.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec14\" class=\"Section2\"\u003e \u003ch2\u003eCell transfection for virus production\u003c/h2\u003e \u003cp\u003eA total of 6.0 \u0026times; 10^6 HEK293T cells were seeded onto a 10 cm dish. A transgene (21 \u0026micro;g), pCMV-Gag-Pol vector (21 \u0026micro;g), and pCMV-VSV-G-poly A vector (10.5 \u0026micro;g) were mixed with ddH\u003csub\u003e2\u003c/sub\u003eO to a final volume of 945 \u0026micro;l (DNA mix). To this mix, 105 \u0026micro;l of CaCl\u003csub\u003e2\u003c/sub\u003e (2.5 M) and 1,050 \u0026micro;l of 2 \u0026times; HBSS were added, and the solution was incubated for 3 minutes. The 2,100 \u0026micro;l solution was then added to the cells and incubated at 37\u0026deg;C with 5% CO\u003csub\u003e2\u003c/sub\u003e for 8\u0026ndash;10 hours. Following incubation, the media were removed, and the cells were cultured in 5% FBS\u0026thinsp;+\u0026thinsp;DMEM for at least 48 hours. The culture containing the virus was then collected for further experiments.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec15\" class=\"Section2\"\u003e \u003ch2\u003eAnalyses of cell proliferation, cell cycle progression, and apoptosis\u003c/h2\u003e \u003cp\u003emiR-23a/miR-27a KO cells or scrambled control cells were seeded onto a 6-well plate with a density of 5 \u0026times; 10^4. Cell morphology, viability, and numbers were monitored microscopically over 6 days. Additionally, the optical density of MTT (3-[4,5-dimethylthiazol-2-yl]-2,5 diphenyl tetrazolium bromide, Sigma-Aldrich, St. Louis, MO) was measured daily. For the colony formation assay, cells were seeded at 5 \u0026times; 10^3 cells/ml in triplicate in a 6-well plate. After three weeks, cells were stained with 0.125% crystal violet, and colonies (\u0026gt;\u0026thinsp;20 cells) were photographed and counted under the microscope. In the soft agar assay, a 3.2% sterile stock agarose (Sigma-Aldrich) solution was prepared with ddH\u003csub\u003e2\u003c/sub\u003eO, and a 0.8% base agarose layer was created using cell culture medium. Cells (2 \u0026times; 10^3 cells per 6-well plate) were trypsinized, counted, and used to prepare a 0.48% upper agarose layer. Each well received 1 ml of cell culture medium. After a 14-day incubation, colonies were stained with 4% formaldehyde and 0.005% crystal violet. Colonies (\u0026gt;\u0026thinsp;50 cells) were then photographed and counted under the microscope.\u003c/p\u003e \u003cp\u003eCell-cycle progression was determined by flow cytometry using propidium iodide (PI) staining (50 \u0026micro;g/ml, BD Biosciences, Franklin Lakes, NJ). This analysis was conducted after a 48-hour starvation of cells, followed by serum stimulation at 0, 8, and 22 hours. Additionally, cell-cycle progression was assessed using flow cytometry with BrdU antibody and 7AAD at 6 and 14 hours after starvation, following the manufacturer\u0026rsquo;s protocol (Phase-Flow BrdU Kit, Biolegend).\u003c/p\u003e \u003cp\u003eApoptosis analysis was performed by flow cytometry 24 hours after seeding, utilizing the Apoptosis Detection Kit with Annexin V and 7AAD from Biolegend. In the case of apoptosis induction by H\u003csub\u003e2\u003c/sub\u003eO\u003csub\u003e2\u003c/sub\u003e, cells were treated with 0.1 mM H\u003csub\u003e2\u003c/sub\u003eO\u003csub\u003e2\u003c/sub\u003e for 15 minutes, and the samples were subsequently subjected to flow analysis.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec16\" class=\"Section2\"\u003e \u003ch2\u003eSoft agar assay\u003c/h2\u003e \u003cp\u003eTo determine anchorage-independent cell growth, a 6-well plate was prepared with a solidified 0.6% agarose bottom layer. A 0.3% agarose solution containing 1,000 cells was then added as the top layer. Following a 2\u0026ndash;4 week incubation period in a standard cell culture incubator, allowing for the formation of colonies within the three-dimensional agarose matrix, the resulting colonies were stained using crystal violet. Quantitative analysis involved colony counting and size measurement using microscopy with ImageJ analysis software.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec17\" class=\"Section2\"\u003e \u003ch2\u003eCell migration assays\u003c/h2\u003e \u003cp\u003eA total of 4 \u0026times; 10^4 cells were cultured in 0.2% FBS\u0026thinsp;+\u0026thinsp;DMEM and seeded onto transwell inserts (pore size, 8\u0026micro;m, CORNING, Corning, NY). Next, 600\u0026ndash;800 \u0026micro;L of 10% FBS\u0026thinsp;+\u0026thinsp;DMEM was added to the lower well of the 24-transwell plate. To mitigate the effects of cell proliferation on migration analysis, cells were pre-treated with 10 \u0026micro;g/ml mitomycin C (Sigma-Aldrich) for 2 hours prior to the Transwell migration assay. The transwell insert was then placed into the lower well and incubated for 18\u0026ndash;22 hours. Following the incubation, the transwell polycarbonate membrane was fixed in 4% formaldehyde for 15 minutes. Cells that did not migrate across the membrane were gently removed with a cotton swab. The membrane was carefully cut with a scalpel and stained with DAPI for 10 minutes. For the scratch assay, 1 \u0026times; 10^6 cells were seeded onto a 6-well plate. Pipette tips were used to create a wound by scratching the cells. The wound was photographed at 0 and 24 hours, and the wound-healing rates were calculated using software.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec18\" class=\"Section2\"\u003e \u003ch2\u003eqPCR\u003c/h2\u003e \u003cp\u003eTotal RNA was extracted from cultured cells using Trizol reagent (Thermo Fisher Scientific) as directed by the manufacturer. For miRNA expression profiling, a 20-\u0026micro;l reverse transcription reaction, utilizing 5 \u0026micro;l of RNA and miScript II RT Kits (QIAGEN, Germantown, MD), adhered to the manufacturer\u0026rsquo;s protocol. Subsequently, 2 \u0026micro;l of cDNA acted as the template for real-time PCR, executed on a LightCycler 480 Real-Time PCR System (Roche Applied Sciences, Indianapolis, IN) with miScript SYBR Green PCR kits (QIAGEN). Incubation of the reaction mixtures occurred in 96-well optical plates at 95\u0026deg;C for 10 min, succeeded by 40 cycles of 95\u0026deg;C for 15 sec and 60\u0026deg;C for 1 min. Post-reaction, cycle threshold (CT) data were determined using fixed threshold settings, and mean CT values were derived from triplicate PCRs. Employing the 2^(-ΔCt) method for quantification, \u003cem\u003eGAPDH\u003c/em\u003e or \u003cem\u003eU6\u003c/em\u003e were selected as a reference gene for mRNA or miRNA, respectively. The qPCR primer sequences are listed in Supplementary Table S7.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec19\" class=\"Section2\"\u003e \u003ch2\u003eWestern blots\u003c/h2\u003e \u003cp\u003eWestern blotting was performed as previously described \u003csup\u003e56, 57\u003c/sup\u003e. Briefly, cell lysates containing 50\u0026ndash;100 \u0026micro;g of protein were prepared and subjected to 10% SDS-polyacrylamide gels. Proteins were transferred to PVDF membranes, which were incubated in 5% non-fat milk for 1 hour and overnight at 4\u0026deg;C in 0.25% non-fat milk containing specific primary antibodies. The membranes were subsequently incubated at room temperature for 1 hour in 0.25% non-fat milk with anti-rabbit/mouse IgG HRP-linked secondary antibody (1:5000, Cell Signaling). Enhanced chemiluminescence reagents were utilized, and the membranes were then exposed to X-films for 1\u0026ndash;5 minutes.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec20\" class=\"Section2\"\u003e \u003ch2\u003eLuciferase assay\u003c/h2\u003e \u003cp\u003eThe pmirGLO luciferase reporter vector (Promega) was utilized to construct DNA fragments from the 3\u0026rsquo;-UTR of \u003cem\u003ePURA\u003c/em\u003e (Transcript: ENST00000331327.3) by NotI and XbaI (New England Biolabs, Ipswich, MA) digestion, following the manufacturer\u0026rsquo;s protocol. The primers for the constructed vectors and mutagenesis of \u003cem\u003ePURA\u003c/em\u003e are listed in Supplementary Table S7. In brief, 1\u0026times;10^4 cells were seeded onto a 96-well plate, cultured with DMEM\u0026thinsp;+\u0026thinsp;10% FBS, incubated at 37\u0026deg;C and 5% CO\u003csub\u003e2\u003c/sub\u003e overnight, and transiently co-transfected with constructed vectors (pmirGLO-PURA-3\u0026rsquo; UTR, pmirGLO-PURA-3\u0026rsquo;UTR-Mut) or empty pmirGLO vector and miR-23a-3p/miR-27a-3p mimics (50 nmol/L) or inhibitor (100 nmol/L) using Lipofectamine 3000. After 48 hours of transfection, substrate reagents (Promega) were added to the wells and incubated for 10 minutes. Subsequently, the luciferase activity was assessed with a Veritas Microplate Luminometer (Turner BioSystems, Sunnyvale, CA). Following this, stop reagents were added, and the luciferase activity was re-evaluated.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec21\" class=\"Section2\"\u003e \u003ch2\u003emiRNA/mRNA IP assay\u003c/h2\u003e \u003cp\u003emiRNA/mRNA immunoprecipitation was performed using miRNA Target IP kits (Active Motif, Carlsbad, CA). Briefly, cells (1 \u0026times; 10^7) were seeded onto a 10 cm dish and transfected with scrambled control or miRNA mimic (50 nmol/L) or inhibitor (100 nmol/L) using Lipofectamine 3000 for 24 hours. Cell lysates were collected from each sample using 150 \u0026micro;L complete lysis buffer, and 10 \u0026micro;L of cell lysate was marked as the input. Samples and inputs were incubated on ice for 10 minutes and then at \u0026minus;\u0026thinsp;80\u0026deg;C for 2 hours. Protein G magnetic beads (50 \u0026micro;L) were blocked with 200 \u0026micro;L BSA for 1 hour and then placed on a magnet to pellet the beads. The beads were washed twice with wash buffer. Ago1/2/3 antibody (2.5 \u0026micro;L) or a negative control anti-IgG antibody (12.5 \u0026micro;L) was added to each tube and incubated for 30 minutes at room temperature. Subsequently, samples and inputs were added to the protein G magnetic beads-antibody complex and incubated overnight at 4\u0026deg;C. After proteinase K digestion (55\u0026deg;C for 30 minutes) and RNA precipitation, RT-qPCR was used to analyze if the candidate gene target could bind to miRNA. The results of Ago-IP were normalized to that of the negative control IgG-IP.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec22\" class=\"Section2\"\u003e \u003ch2\u003eIHC staining\u003c/h2\u003e \u003cp\u003eDako retrieval buffer (Agilent, Santa Clara, CA) was employed for antigen retrieval, and the ABC detection system (Vector Laboratories, Burlingame, CA) was utilized for immunostaining. Specific primary antibodies were incubated with tissues overnight at 4\u0026deg;C. The secondary antibody used was goat anti-mouse/rabbit IgG (Invitrogen, 1:200). The staining process was completed following the manufacturer\u0026rsquo;s protocol of VECTASTAIN ABC Kits (Vector Laboratories). Hematoxylin was applied last for the staining of the nucleus.\u003c/p\u003e \u003cp\u003e \u003cb\u003eIn vivo\u003c/b\u003e \u003cb\u003etumor xenograft model\u003c/b\u003e\u003c/p\u003e \u003cp\u003eScramble, miR-23a KO, and miR-27a KO HepG2 cells (100 \u0026micro;l, 5 \u0026times; 10^7/ml) were subcutaneously injected into the left flanks of 6-week-old NSG mice (Jackson Laboratories, Bar Harbor, ME). Tumor growth was monitored every two or three days. At 31 days after injection, NSG mice were sacrificed, and tumor volume and weights were measured. All experiments were conducted in accordance with accepted standards of animal care and approved by the Institutional Animal Care and Institutional Review Board of The University of Alabama at Birmingham.\u003c/p\u003e \u003cdiv id=\"Sec23\" class=\"Section3\"\u003e \u003ch2\u003eRNA-seq\u003c/h2\u003e \u003cp\u003eUtilizing the TruSeq Stranded mRNA Library Prep Kit (Illumina, San Diego, CA), RNA libraries were prepared in accordance with the manufacturer's protocol. The integrity check employed an Agilent 2200 Tapestation instrument. First-strand cDNA synthesis utilized random hexamers and ProtoScript II Reverse Transcriptase (New England Biolabs, Ipswich, MA). Subsequently, libraries underwent normalization, pooling, and cluster and pair read sequencing on a HiSeqX10 instrument (Illumina) for 150 cycles, following manufacturer instructions. The generated RNA-seq data have been deposited in NCBI GEO under Accession no. GSE199332.\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv id=\"Sec24\" class=\"Section2\"\u003e \u003ch2\u003eBioinformatic analysis\u003c/h2\u003e \u003cp\u003eDifferential expression analysis of genes (DEGs) was conducted utilizing fold change and q-value. miRNA expression data from cancer and normal tissue samples were sourced from Oncomir (\u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ewww.oncomir.umn.edu\u003c/span\u003e\u003cspan address=\"http://www.oncomir.umn.edu\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e) and TCGA. To generate and visualize a functionally grouped network of terms and pathways for extensive gene clusters, the ClueGO Cytoscape plug-in (apps.cytoscape.org/apps/cluego) was employed. Gene clusters were imported from a text file or interactively from the Cytoscape network. For in-depth analysis, KEGG (\u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ewww.genome.jp/kegg/\u003c/span\u003e\u003cspan address=\"http://www.genome.jp/kegg/\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e) analysis of the identified DEGs was executed to retrieve interacting genes and proteins (string-db.org/). The Cytoscape software (cytoscape.org/) facilitated the construction of an interaction network diagram for the DEGs.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec25\" class=\"Section2\"\u003e \u003ch2\u003eStatistical analysis\u003c/h2\u003e \u003cp\u003eContinuous variables were summarized using mean, standard deviation (SD), and median values. The distribution of samples was assessed using the one-sample Kolmogorov-Smirnov test. For samples with normal distributions, a two-tailed \u003cem\u003et\u003c/em\u003e-test compared means between two groups. In cases of non-normal distributions, the Mann\u0026ndash;Whitney \u003cem\u003eU\u003c/em\u003e test was employed to compare median variation between two groups. One-way analysis of variance (ANOVA) tested for differences among at least three groups, while two-way ANOVA was used to assess the influence of two categorically independent variables on one dependent variable. SAS (Version 9.4) and GraphPad Prism (Version 8.4.3) software were utilized for data analysis.\u003c/p\u003e \u003c/div\u003e"},{"header":"Declarations","content":"\u003cp\u003e\u003cstrong\u003eConflict of interest statement:\u0026nbsp;\u003c/strong\u003eThere are no potential conflicts of interest for disclosure.\u003c/p\u003e\u003ch2\u003eAuthors\u0026rsquo; contributions\u003c/h2\u003e \u003cp\u003eLW and RL designed the research approach; MC, ZL, SW, and RL performed the experiments; MC, SB, HG, RL, and LW analyzed data; SB, MC, and LW performed statistical analyses; HG and JZ provided key resources; MC made a draft of the paper; MC, JZ, RL, and LW revised and edited the paper.\u003c/p\u003e\u003ch2\u003eAcknowledgements\u003c/h2\u003e \u003cp\u003eWe would like to thank Dr. Lei Stanley Qi in the Department of Bioengineering, Stanford University for providing us CRISPRi/a plasmids and Dr. Guangxiang Luo in the Department of Microbiology, University of Alabama at Birmingham for providing us cell lines. Institutional Impact Fund from the University of Alabama at Birmingham supported this research work. The data underlying this article are available in in the article, its online supplementary material, and the Gene Expression Omnibus at \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://www.ncbi.nlm.nih.gov/geo/\u003c/span\u003e\u003cspan address=\"https://www.ncbi.nlm.nih.gov/geo/\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e under accession code GSE199332.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\u003cli\u003e\u003cspan\u003eLin S, Gregory RI. MicroRNA biogenesis pathways in cancer. Nat Rev Cancer 2015; 15: 321\u0026ndash;333.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eCalin GA, Croce CM. MicroRNA signatures in human cancers. 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Clin Cancer Res 2016; 22: 2545\u0026ndash;2554.\u003c/span\u003e\u003c/li\u003e\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":false,"highlight":"","institution":"","isAcceptedByJournal":true,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"oncogene","isNatureJournal":false,"hasQc":false,"allowDirectSubmit":false,"externalIdentity":"onc","sideBox":"Learn more about [Oncogene](http://www.nature.com/onc/)","snPcode":"41388","submissionUrl":"https://mts-onc.nature.com/cgi-bin/main.plex","title":"Oncogene","twitterHandle":"","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"ejp","reportingPortfolio":"Nature AJ","inReviewEnabled":true,"inReviewRevisionsEnabled":false},"keywords":"microRNA, hepatocellular carcinoma, CRISPR, tumor progression, signaling pathway","lastPublishedDoi":"10.21203/rs.3.rs-3885203/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-3885203/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003eThe miR-23a\u0026thinsp;~\u0026thinsp;27a\u0026thinsp;~\u0026thinsp;24\u0026thinsp;\u0026minus;\u0026thinsp;2 cluster, commonly upregulated in diverse cancers, including hepatocellular carcinoma (HCC), raises questions about the specific functions of its three mature miRNAs and their integrated function. Utilizing CRISPR knockout (KO), CRISPR interference (CRISPRi), and CRISPR activation (CRISPRa) technologies, we established controlled endogenous miR-23a\u0026thinsp;~\u0026thinsp;27\u0026thinsp;~\u0026thinsp;a24-2 cell models to unravel their roles and signaling pathways in HCC. Both miR-23a KO and miR-27a KO displayed reduced cell growth \u003cem\u003ein vitro\u003c/em\u003e and \u003cem\u003ein vivo\u003c/em\u003e, revealing an integrated oncogenic function. Functional analysis indicated cell cycle arrest, particularly at the G2/M phase, through the downregulation of CDK1/cyclin B activation. High-throughput RNA-seq, combined with miRNA target prediction, unveiled the miR-23a/miR-27a-regulated gene network, validated through diverse technologies. While miR-23a and miR-27a exhibited opposing roles in cell migration and mesenchymal-epithelial transition, an integrated CRISPRi/a analysis suggested an oncogenic role of the miR-23a\u0026thinsp;~\u0026thinsp;27a\u0026thinsp;~\u0026thinsp;24\u0026thinsp;\u0026minus;\u0026thinsp;2 cluster in cell migration. This involvement potentially encompasses two signaling axes: miR-23a-BMPR2 and miR-27a-TMEM170B in HCC cells. In conclusion, our CRISPRi/a study provides a valuable tool for comprehending the integrated roles and underlying mechanisms of endogenous miRNA clusters, paving the way for promising directions in miRNA-targeted therapy interventions.\u003c/p\u003e","manuscriptTitle":"CRISPR-Based Dissection of microRNA-23a~27a~24-2 Cluster Functionality in Hepatocellular Carcinoma","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2024-02-02 08:36:33","doi":"10.21203/rs.3.rs-3885203/v1","editorialEvents":[{"type":"communityComments","content":0},{"type":"decision","content":"revise","date":"2024-04-05T11:21:59+00:00","index":"","fulltext":""},{"type":"editorInvitedReview","content":"This content is not available.","date":"2024-03-31T00:47:04+00:00","index":1,"fulltext":"This content is not available."},{"type":"editorInvitedReview","content":"This content is not available.","date":"2024-03-18T15:58:05+00:00","index":3,"fulltext":"This content is not available."},{"type":"editorInvitedReview","content":"This content is not available.","date":"2024-03-08T08:40:21+00:00","index":2,"fulltext":"This content is not available."},{"type":"reviewerAgreed","content":"This content is not available.","date":"2024-02-27T10:52:59+00:00","index":3,"fulltext":"This content is not available."},{"type":"reviewerAgreed","content":"This content is not available.","date":"2024-02-25T11:18:53+00:00","index":2,"fulltext":"This content is not available."},{"type":"reviewerAgreed","content":"This content is not available.","date":"2024-02-08T15:47:30+00:00","index":1,"fulltext":"This content is not available."},{"type":"reviewersInvited","content":"","date":"2024-01-31T18:16:27+00:00","index":"","fulltext":""},{"type":"checksComplete","content":"","date":"2024-01-22T11:33:04+00:00","index":"","fulltext":""},{"type":"editorAssigned","content":"","date":"2024-01-21T16:12:46+00:00","index":"","fulltext":""},{"type":"submitted","content":"Oncogene","date":"2024-01-21T16:12:45+00:00","index":"","fulltext":""}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"oncogene","isNatureJournal":false,"hasQc":false,"allowDirectSubmit":false,"externalIdentity":"onc","sideBox":"Learn more about [Oncogene](http://www.nature.com/onc/)","snPcode":"41388","submissionUrl":"https://mts-onc.nature.com/cgi-bin/main.plex","title":"Oncogene","twitterHandle":"","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"ejp","reportingPortfolio":"Nature AJ","inReviewEnabled":true,"inReviewRevisionsEnabled":false}}],"origin":"","ownerIdentity":"b2b3f6cd-b71c-4177-9509-ce8243e77372","owner":[],"postedDate":"February 2nd, 2024","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"published-in-journal","subjectAreas":[{"id":28492841,"name":"Biological sciences/Cancer/Gastrointestinal cancer/Liver cancer"},{"id":28492842,"name":"Biological sciences/Molecular biology/Non-coding RNAs"}],"tags":[],"updatedAt":"2024-08-08T07:12:25+00:00","versionOfRecord":{"articleIdentity":"rs-3885203","link":"https://doi.org/10.1038/s41388-024-03115-z","journal":{"identity":"oncogene","isVorOnly":false,"title":"Oncogene"},"publishedOn":"2024-08-07 04:00:00","publishedOnDateReadable":"August 7th, 2024"},"versionCreatedAt":"2024-02-02 08:36:33","video":"","vorDoi":"10.1038/s41388-024-03115-z","vorDoiUrl":"https://doi.org/10.1038/s41388-024-03115-z","workflowStages":[]},"version":"v1","identity":"rs-3885203","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-3885203","identity":"rs-3885203","version":["v1"]},"buildId":"8U1c8b4HqxoKbykW_rLl7","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}