Exploring Vimentin's Role in Breast Cancer via PICK1 Alternative Polyadenylation and the miR-615-3p- PICK1 Interaction

Exploring Vimentin's Role in Breast Cancer via PICK1 Alternative Polyadenylation and the miR-615-3p- PICK1 Interaction | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Research Article Exploring Vimentin's Role in Breast Cancer via PICK1 Alternative Polyadenylation and the miR-615-3p- PICK1 Interaction Xinyan Jia, Lujing Shao, Hong Quan, Chunyan Dong This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-4391747/v1 This work is licensed under a CC BY 4.0 License Status: Posted Version 1 posted You are reading this latest preprint version Abstract Background: Breast cancer continues to be a major health issue for women worldwide, with Vimentin (VIM) identified as a crucial factor in its progression due to its role in cell migration and the epithelial-to-mesenchymal transition (EMT). This study focuses on elucidating VIM's regulatory mechanisms on the miR-615-3p/PICK1 axis, particularly through the lens of alternative polyadenylation (APA) of PICK1, and its implications for breast cancer progression. Methods: Utilizing the 4T1 breast cancer cell model, we first employed RNA-seq and proteomics to investigate changes in the APA of PICK1 following VIM knockout (KO). These high-throughput analyses aimed to uncover the underlying transcriptional and proteomic alterations associated with VIM's influence on breast cancer cells. Results: RNA-seq and proteomic profiling revealed significant APA in PICK1 following VIM KO, suggesting a novel mechanism by which VIM regulates breast cancer progression. Validation experiments confirmed that VIM KO affects the miR-615-3p-PICK1 axis, with miR-615-3p's regulation of PICK1 being contingent upon the APA of PICK1. These findings highlight the complex interplay between VIM, miR-615-3p, and PICK1 in the regulation of breast cancer cell behavior. Conclusion: This study unveils a critical role of VIM in breast cancer progression through its impact on the APA of PICK1, influencing the miR-615-3p-PICK1 axis. Our findings open new avenues for targeted therapies in breast cancer, focusing on the modulation of APA and the miR-615-3p-PICK1 interaction. Figures Figure 1 Figure 2 Figure 3 Figure 4 Figure 5 Introduction Recent statistics underscore that breast cancer constitutes a significant public health challenge globally, with its incidence rates witnessing an upward trajectory over the past four decades. Given its prevalence and pronounced impact on both mortality and morbidity in women, the quest for a deeper understanding and more effective treatment modalities for breast cancer is far from over( 1 ). Among the plethora of factors implicated in the progression of breast cancer, Vimentin (VIM) has been identified as a pivotal element. As a type III intermediate filament, VIM plays an instrumental role in preserving cellular integrity, alongside facilitating critical processes such as cell migration, motility, and adhesion( 2 ). Its overexpression is intricately associated with the epithelial-to-mesenchymal transition (EMT), a fundamental mechanism in the metastatic cascade of cancer( 3 ). Notably, VIM's overexpression has been correlated with adverse clinical outcomes across a spectrum of cancers, including breast cancer. Recent scholarly contributions have posited that VIM's degradation could curtail the proliferation and metastasis of breast cancer cells, thereby underscoring its potential utility as both a biomarker and therapeutic target within the domain of breast oncology( 2 , 4 – 6 ). Recently, VIM has emerged as a critical player in the post-transcriptional regulation of specific mRNAs, demonstrating the ability to interact with both the 3'-untranslated region (3'-UTR) and 5'-untranslated region (5'-UTR) of these molecules( 7 , 8 ). These findings suggest that VIM plays a pivotal role in the transcriptional regulation of mRNAs, potentially influencing the metastatic capability and progression of cancer cells. Building on this premise, our investigation endeavors to elucidate the multifarious mechanisms through which VIM modulates breast cancer progression, with an emphasis on transcriptional regulation. By leveraging a comprehensive multiomics framework, integrating both transcriptomic and proteomic analyses, we aim to demystify the intricate nexus between VIM and breast cancer pathology. Such insights could potentially herald novel therapeutic interventions targeting this critical pathway. Methods Cell culture The 4T1 cell line was acquired from Cyagen Biosciences (Guangzhou, China). Cells were cultured in complete Dulbecco's Modified Eagle Medium (DMEM) supplemented with 10% Fetal Bovine Serum (FBS, catalog number 10099141C, Invitrogen, USA) and a penicillin-streptomycin-glutamine mixture (catalog number 10378016, Invitrogen, USA). Cultures were maintained in a humidified atmosphere containing 5% CO 2 at 37°C. The culture medium was refreshed every three days to ensure optimal growth conditions. Lentivirus infection Lentiviral vectors targeting miR-615-3p mimic and control lentiviral vectors were produced by GenePharma Co., Ltd. The 4T1 cells were infected with the lentivirus in the presence of polybrene (BL628A, Biosharp, China) for 12 hours. Forty-eight hours post-infection, the infected 4T1 cells underwent antibiotic selection to ensure the integration of the viral construct. The target sequence for the miR-615-3p mimic is as follows: miR-615-3p mimic, 5′-TCCGAGCCTGGGTCTCCCTCTT-3′. Quantitative Real-Time PCR (qRT-PCR) Quantitative Real-Time PCR (qRT-PCR): Total RNA was isolated using the Vazyme Total RNA Isolation Kit (R711-01, Vazyme, China) and cDNA was synthesized following the manufacturer's protocol using HiScript III RT SuperMix for qPCR (+ gDNA wiper) (R323-01, Vazyme, China). Real-time PCR was performed using the MagicSYBR Mixture (CW3008, CWBIO, China). For miRNA detection, reverse transcription polymerase chain reaction (RT-PCR) was conducted using the TaqMan MicroRNA Reverse Transcription kit (4366596, Invitrogen, USA). The TaqMan probe for hsa-miR-615 (Assay ID: 001960, Applied Biosystems, USA) was used to detect the specific microRNA, with U6 (Assay ID: 001973, Applied Biosystems) serving as the loading control. Quantitative real-time PCR (qPCR) was conducted on a BioRad CFX96 Real-Time PCR Detection System (BioRad, USA). Each reaction was performed in triplicate and the entire experimental process was repeated three times to ensure the reliability and consistency of the results. The relative expression levels were calculated using the 2-ΔΔCt method. Protein extraction and digestion SDT(4%SDS, 100mM Tris-HCl, pH7.6) buffer was used for sample lysis and protein extraction. The amount of protein was quantified with the BCA Protein Assay Kit (Bio-Rad, USA). 20 µg of protein for each sample were mixed with 5X loading buffer respectively and boiled for 5 min. The proteins were separated on 4%-20% SDS-PAGE gel (constant voltage 180V, 45 min). Protein bands were visualized by Coomassie Blue R-250 staining. Protein digestion by trypsin was performed according to filter-aided sample preparation (FASP) procedure described by Matthias Mann. The digest peptides of each sample were desalted on C18 Cartridges (Empore™ SPE Cartridges C18 (standard density), bed I.D. 7 mm, volume 3 ml, Sigma), concentrated by vacuum centrifugation and reconstituted in 40 µl of 0.1% (v/v) formic acid. Western Blot Total protein was extracted using RIPA buffer. After quantification, equal amounts of protein samples were loaded and separated by 10% SDS-PAGE, then transferred to a 0.45-µm PVDF membrane. The membrane was blocked with 5% non-fat milk for 2 hours, followed by overnight incubation at 4°C with primary antibodies. The primary antibodies used were anti-PICK1 (10983-2-AP, Proteintech, 1/1000 dilution) and anti-GAPDH (ab8245, abcam, 1/5000 dilution). Subsequently, the membrane was incubated with secondary antibodies at room temperature for 1 hour. Immunoblots were visualized using an ECL chemiluminescence detection kit (Beyotime, Shanghai) and observed with a Tanon 4600 system (Tanon Science and Technology Co., Ltd.). Dual-Luciferase Reporter Assay The coding sequences (CDS) of wild type (wt) or mutant (mut) PICK1 were cloned into the firefly luciferase expression vector pMIR-REPORT (Sangon Biotech, Shanghai, China). The PICK1-mut, PICK1-wt, and Vector or miR-615-3p mimic were co-transfected into the 4T1 cell line using Lipofectamine 3000 (Invitrogen, Carlsbad, CA, USA). The luciferase activity in the cells was normalized by co-transfecting with a plasmid containing the full-length Renilla luciferase gene (pTK-Renilla) as a reporter (Genomeditech), and quantified 48 hours after transfection using a Dual-Luciferase Reporter Assay System (Promega). 5-Ethynyl-2′-deoxyuridine (EdU) Assay The EdU incorporation was detected using the BeyoClick™ EdU Cell Proliferation Kit with Alexa Fluor 594 (Beyotime, Shanghai, China). After washing with PBS, the cells were incubated with the EdU solution for 2 hours, followed by staining of the nuclei with DAPI solution. After washing, the samples were observed under an inverted microscope (Olympus). Filter-aided sample preparation (FASP Digestion) procedure The detergent DTT (with the final concentration of 10 mM) was added to each sample respectively and mixed at 600 rpm for 1.5 h (37℃).After the samples cooled to room temperature, IAA was added with the final concentration of 20 mM into the mixture to block reduced cysteine residues and the samples were incubated for 30 min in darkness. Next, the samples were transferred to the filters respectively. The filters were washed with 100 µl UA buffer three times and then 100 µl 25mM NH4HCO3 buffer twice. Finally, trypsin was added to the samples(the trypsin : protein (wt/wt) ratio was 1:50) and incubated at 37℃ for 15–18 h (overnight), and the resulting peptides were collected as a filtrate. The peptides of each sample were desalted on C18 Cartridges (Empore™ SPE Cartridges C18 (standard density), bed I.D. 7 mm, volume 3 ml, Sigma), concentrated by vacuum centrifugation and reconstituted in 40 µl of 0.1% (v/v) formic acid. The peptide content was estimated by UV light spectral density at 280 nm using an extinctions coefficient of 1.1 of 0.1% (g/l) solution that was calculated on the basis of the frequency of tryptophan and tyrosine in vertebrate proteins. LC-MS/MS analysis We conducted peptide analysis using an LC-MS/MS setup, specifically a Q Exactive mass spectrometer from Thermo Scientific, connected to an Easy nLC system from Proxeon Biosystems (now part of Thermo Fisher Scientific). The peptides were first introduced onto a reverse phase trap column, Thermo Scientific Acclaim PepMap100 (100 µm by 2 cm, nanoViper C18), and then transferred to a C18-reversed phase analytical column (Thermo Scientific Easy Column, 10 cm long, 75 µm inner diameter, with 3µm resin) using a buffer solution of 0.1% Formic acid in water. This setup separated the peptides with a gradient mixture of 84% acetonitrile and 0.1% Formic acid at a 300 nl/min flow rate. Operating in positive ion mode, the mass spectrometer targeted the most abundant precursor ions for higher-energy collisional dissociation (HCD) fragmentation, based on a data-dependent top20 method. We ensured precise measurement by setting the automatic gain control (AGC) target to 1e6, with a maximum injection time of 50 ms and a dynamic exclusion duration of 30.0 seconds. The system achieved a resolution of 60,000 at m/z 200 for survey scans and 15,000 at m/z 200 for HCD spectra, with an isolation width of 1.5 m/z. The normalized collision energy was set to 30 eV, and the underfill ratio was kept at 0.1%, ensuring that the system efficiently recognized and analyzed peptides. Identification and quantitation of proteins The MS raw data for each sample were combined and searched using the MaxQuant 1.6.14 software for identification and quantitation analysis. Protein-protein interaction analysis The protein–protein interaction (PPI) information of the studied proteins was retrieved from IntAct molecular interaction database ( http://www.ebi.ac.uk/intact/ ) by their gene symbols or STRING software ( http://string-db.org/ ). The results were downloaded in the XGMML format and imported into Cytoscape software ( http://www.cytoscape.org/ , version 3.2.1) to visualize and further analyze functional protein-protein interaction networks. Furthermore, the degree of each protein was calculated to evaluate the importance of the protein in the PPI network. RNA extraction and RNA-seq Total RNA was extracted from tumor of both VIM-KO and ctrl group. Nanodrop ND-2000(Thermo Scientific, USA) was used to detect the A260/A280 absorbance ratio of RNA samples. The Rins of RNA were determined by by an Agilent Bioanalyzer 4150 system (Agilent Technologies, CA. Only qualified RNA can be used for library construction. Prepare paired terminal libraries and purify mRNA, followed by synthesizing cDNA using mRNA fragments as templates. Afterwards, the synthesized double stranded cDNA fragments were adapter linked to prepare a paired end library and subjected to PCR amplification. Purification and evaluation of PCR products (AMPure XP system), sequencing and 150bp paired end reading on Illumina Novaseq 6000 (or MGISEQ-T7). Subsequently, quality control and related analysis will be carried out. NGS data analysis The quality of raw sequencing data was examined by FastQC (v0.11.7). Contaminated adapter and low-quality sequences were removed by using Trimmomatic (v0.38). Cleaned sequencing reads were then aligned to mm10 genome reference by STAR aligner (v2.5.2). Samtools (v1.3) was then used to remove unmapped reads and low-quality alignments. Htseq-count (v2.0.3) was used to calculate the raw counts for each transcript. The raw counts of different sample groups were compared by DESeq2 (v3.18) to identify the differentially expressed genes. For calling alternative polyadenylation (APA) events, DANPOS (v3.1.1) was used with default settings. Functional enrichment analysis To assess the biological functions, the computational web server g:Profiler( 9 ) ( https://biit.cs.ut.ee/gprofiler/gost ) was utilized to conduct Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway analyses for differentially expressed genes. The resulting GO and KEGG pathway terms were ranked according to the P value and visualized using R software (v4.1.2). Results RNA-seq reveals the fundamental transcription alternation of Vim KO breast cancer cells To investigate the roles of VIM in transcription regulation, we performed RNA-seq experiments on both VIM-KO and WT breast cancer cells. Consistent to the fundamental functions of VIM, VIM KO induced massive transcription alternations in breast cancer cells, including 4245 significant up-regulated differentially expressed genes (DEGs) and 3147 significant down-regulated DEGs ( Fig. 1 A and 1 B ) . DEGs was defined by log2FoldChange > 1 and adjusted P value < 0.05. Based on Gene Ontology analysis, up-regulated DEGs were enriched to anatomical structure morphogenesis, tissue development, movement of cell or subcellular component, cell migration, and cell motility. The down-regulated DEGs were enriched to immune related terms, such as immune response, antigen receptor-mediated signaling pathway, and B cell receptor signaling pathway ( Fig. 1 C ). Similarly, based on KEGG pathway enrichment analysis, up-regulated DEGs were enriched to focal adhesion, ECM-receptor interaction, proteoglycans in cancer, and PI3K-Akt signaling pathway. The down-regulated were enriched to primary immunodeficiency, cell adhesion molecules and T cell receptor signaling pathway ( Fig. 1 D ) . These results demonstrate not only the crucial roles of VIM in maintaining the cell integrity, regulating cell migration and cancer cell proliferation, but also its involvement in immune repones regulation, suggesting VIM contributes to the development, proliferation and migration of cancer cells through various mechanisms. Proteomic profiling of Vim KO breast cancer cells To further study the functions of VIM in protein level, we performed LC-MS/MS analysis to profile the protein levels of both WT and VIM KO breast cancer cells. In VIM KO group, the VIM protein level was reduced to 6.5% compared to WT breast cancer cells, confirming the efficient of VIM knockout in VIM KO cells. Compared to WT group, we identified 24 up-regulated genes and 99 down-regulated genes at protein level ( Fig. 2 A and 2 B ) . The top up-regulated genes include Limch1, Ltb4r, and Txnl4b, which are involved in cell migration, immune response and cell cycle progression, respectively. Top down-regulated genes include Mapre3 and Ppfibp1, which are involved in regulating cell adhesion and migration. Based on the protein-protein interaction analysis performed on DEGs, we observed three major clusters. Genes of Cluster 1 is enriched to epithelial mesenchymal transition pathway, including Vim, Itga5, Fermt2. Genes of Cluster 2 is enriched to extracellular matrix organization, including Col28a1, Cask, Col10a1, Capn3. Genes of Cluster 3 is mainly related to microtubule construction, with Mapre3 and Kif11 being the center node of this cluster ( Fig. 2 C ) . Additionally, we also performed gene ontology analysis and KEGG pathway enrichment analysis on DEGs at protein level and observed a significant enrichment to immune and inflammation related terms or pathways, such as complement activation, positive regulation of type I interferon-mediated signaling pathway and complement and coagulation cascades. DEGs at protein level are also enriched to metabolism related terms or pathways, such as polyphosphate catabolic process, taurine and hypotaurine metabolism, lipoic acid metabolism and sulfur metabolism, suggesting Vim KO has an impact on the energy supply that are required to tumor growth ( Fig. 2 D and 2 E ) . Vim regulates the EMT of breast cancer cells through APA APA is one of the major mechanisms of posttranscriptional regulation and has been demonstrated to be involved in cancer development and progression. To investigate whether Vim regulates gene expression through this mechanism, we compared Vim KO and WT breast cells and identified 1207 significant shortening genes and 663 lengthening genes ( Fig. 3 A ) . Consistent to previous report that gene shortening is related to up-regulation of gene expression, we observed significant negative correlation (Pearson correlation: -0.135; P value: 5.70E-9) between gene expression and the percentage of distal poly(A) site usage index (PDUI) value ( Fig. 3 B ) . Based on gene ontology analysis, the lengthening genes are enriched to RNA processing, peptide metabolic process, regulation of catabolic process and autophagy. The shortening genes are enriched to cellular macromolecule catabolic process, intracellular protein transport, membrane organization and mitotic cell cycle process ( Fig. 3 C and 3 D ) . We further investigated the enrichment of lengthening and shortening genes to the MSigDB Hallmark pathway. The lengthening genes are enriched to p53 pathway, mitotic spindle and PI3K/AKT/mTOR signaling while the shortening genes are enriched to G2-M checkpoint, Myc Targets V and epithelial mesenchymal transition ( Fig. 3 E and 3 F ) . These results indicates that Vim KO caused fundamental transcription alternations are partially through APA’s regulation on RNA processing and metabolism. Vim KO also influence crucial pathways related to cancer survival, proliferation, and malignancy through APA mechanism. Among the shortening genes in Vim KO breast cancer cells, the APA event observed in the 3’-UTR of Pick1 gene is one of the most significant events and associated with the EMT process. Pick1 was reported to be the negative regulator of TGF-beta signaling and inhibit the EMT process and cancer metastasis. Based on DANPOS results, the distal polyadenylation site (PAS) of Pick1 is mainly used in WT breast cancer cells while the usage of proximal PAS is significantly increased in Vim KO breast cancer cells. Given previous studies, the 3’-UTR of Pick1 contains the target site of miR-615-3p, which suppresses the Pick1/TGF-beta signaling axis and promotes the EMT and breast cancer metastasis ( Fig. 4 A ) . The knockout of Vim induced the increasing usage of proximal PAS and the abrogates of the miR-615-3p target sites, therefore causing the up-regulation of Pick1 at transcription level and the inhibition of EMT process ( Fig. 4 B and 4 C ) . These results demonstrate that APA is one of the major mechanisms that Vim utilizes to regulate the cancer cell progression. miR-615-3p negatively regulates PICK1 to promote breast cancer progression, with its effectiveness depending on the presence or absence of VIM knock-out We next focused on elucidating the influence of miR-615-3p on breast cancer progression through its interaction with PICK1. Initial analysis using qRT-PCR demonstrated significant transcriptional variations between the short and long 3’-UTRs of PICK1 in both VIM-WT and VIM-KO 4T1 cells, suggesting a differential regulatory mechanism that could be attributable to APA influenced by the presence or absence of VIM (Fig. 5 A). Protein levels of PICK1, as determined by Western Blot, further confirmed these transcriptional differences, revealing a nuanced layer of regulation potentially driven by miR-615-3p's interaction with PICK1, thereby modulating the protein's expression (Fig. 5 B-C). The sequence specificity of this interaction was highlighted through the delineation of the binding region between wild-type PICK1 and miR-615-3p, alongside the introduction of mutations within PICK1 that presumably disrupt this interaction. This aspect of the study underscores the targeted nature of miR-615-3p's regulatory role (Fig. 5 D). The functionality of this interaction was validated via dual-luciferase reporter assays, which unequivocally demonstrated miR-615-3p's engagement with PICK1, offering a molecular basis for the post-transcriptional regulation observed (Fig. 5 E). Subsequent analyses focused on the impact of miR-615-3p mimic transfection in both VIM-WT and VIM-KO cells. Western Blot tests after transfection showed clear changes in the levels of PICK1 protein, highlighting miR-615-3p's key role in controlling PICK1 expression. However, when VIM was knocked out, the miR-mimic didn't lower the protein expression, suggesting that the effect of miR-615-3p on PICK1 depends on whether VIM is present or not (Fig. 5 F-G). EdU proliferation assays further illuminated the functional consequences of this regulatory pathway, showing that miR-615-3p's modulation of PICK1 expression significantly affects the proliferative capacity of 4T1 cells in both VIM-WT and VIM-KO contexts (Fig. 5 H-I). This series of experiments provides strong evidence that miR-615-3p can effectively downregulate PICK1, while the regulatory region of PICK1 by miRNA is influenced by the presence or absence of VIM. This regulatory interaction plays a crucial role in advancing breast cancer progression, likely by causing changes in the cellular environment that favor tumor growth and spread. Discussion Our study revealed that VIM-KO significantly alters both the transcriptome and proteome of breast cancer cells, specifically increasing the expression of short 3’-UTRs. These finding highlights VIM's role in transcriptional regulation, with a particular emphasis on the crucial function of alternative splicing. Moreover, our research demonstrated that miR-615-3p binds more readily to the longer 3'-UTRs of PICK1 mRNA. However, VIM-KO leads to shorter 3’-UTRs, thereby affecting miR-615-3p's binding and consequently upregulating PICK1 expression. This upregulation inhibits cell proliferation in breast cancer. VIM is a type III intermediate filament protein essential for maintaining cellular integrity and stability. Ubiquitously expressed in mesenchymal cells, VIM is a key marker of EMT and interacts with various signaling pathways, influencing a wide range of cellular functions( 5 , 10 , 11 ). Although direct references to VIM's specific impact on the 3'-UTR or 5'-UTR regions of mRNAs are relatively sparse, its involvement in transcriptional regulation is intriguing. For example, VIM binds to the 5’-UTR stem-loop domain of collagen mRNAs, regulating collagen synthesis, and interacts with the 3' UTR of certain mRNAs, such as alkaline phosphatase mRNA in human primary osteoblasts and tissue factor mRNA in human breast cancer cells, stabilizing them and thus influencing their expression levels( 12 ). Specifically, in breast cancer, VIM has been shown to prevent miR-dependent negative regulation of tissue factor mRNA by interacting with its 3'-UTR during EMTs of circulating tumor cells, promoting coagulant activity associated with early metastasis( 7 ). In our study, we discovered that VIM-KO does not directly regulate PICK1 expression but instead modulates it by affecting the length of the 3’-UTR, suggesting that the mechanism of APA is involved in regulating the length of PICK1 mRNA 3’-UTR in VIM-KO cells. APA is a critical mechanism in gene expression, producing mRNA isoforms with differing 3’-UTR lengths, thereby affecting mRNA stability, translation efficiency, and cellular localization( 13 – 15 ). This process is regulated co- and post-transcriptionally, influenced by interactions between polyadenylation factors and RNA-binding proteins, and affected by the cellular environment​( 16 ). Although the connection between VIM and APA has not been explored, it presents a promising area for future research. Moreover, the modulation of PICK1 expression by VIM through altering the 3' UTR length hints at a potential role for APA in cancer progression, similar to the application of comprehensive genomic analyses in the interpretation and staging of lung cancer( 17 , 18 ), suggesting that the length of the 3' UTR might be a significant factor in the staging or prognosis of breast cancer. MicroRNAs (miRNAs) are key regulators of gene expression at the transcriptional level, often binding to complementary sequences within the 3'-UTR of target mRNAs to mediate their degradation or inhibit their translation( 19 – 21 ). Lei et al.( 22 ) elucidated the role of miR-615-3p in promoting the EMT and metastasis of breast cancer by targeting the PICK1/TGFBRI axis. According to their study, miR-615-3p facilitates breast cancer metastasis by directly targeting the 3'-UTR of PICK1 mRNA, leading to reduced PICK1 expression, which in turn influences TGF-β signaling and its downstream effects on cell migration and invasion. Building upon Lei et al.'s findings, our research further explores the intricate relationship between VIM-KO and its regulatory effects on breast cancer cell behavior. We discovered an upregulation of PICK1 in VIM-KO breast cancer cells, suggesting a novel regulatory mechanism whereby VIM may control breast cancer progression through the miR-615-3p/PICK1 axis. Experimental validation in our study supports our hypothesis that VIM-KO influences transcriptional regulation by shortening the 3’-UTR of PICK1 , interfering with miR-615-3p binding, and consequently upregulating PICK1 expression. Our findings not only corroborate the crucial role of miR-615-3p as identified by Lei et al. but also extend the understanding of VIM's involvement in breast cancer through modulation of the miR-615-3p/PICK1 axis, offering potential new avenues for therapeutic intervention in breast cancer treatment. Our study unveils a novel regulatory mechanism of VIM in breast cancer, demonstrating its significant role in modulating transcription through the alteration of 3’-UTR lengths, which consequently impacts the miR-615-3p/PICK1 axis. We found that VIM knockout VIM-KO triggers the upregulation of PICK1, potentially inhibiting cell proliferation and reducing metastasis. These discoveries emphasize a previously unrecognized pathway through which VIM influences breast cancer progression, offering promising directions for targeted therapeutic strategies against the miR-615-3p/PICK1 axis in breast cancer treatment. Declarations Ethics approval and consent to participate Considering that the data are publicly available, no ethics approval is required for this study . Consent for publication All authors reviewed and approved the manuscript. Competing interests All the authors have declared that no competing interests exist. Funding This work was supported by the National Natural Science Foundation of China (82073387), Pudong New Area Health and Family Planning Commission Industry Special Project of Shanghai (PW2021E-05) and Leading Talent Training Project of Shanghai Pudong New Area Health and Family Planning Commission (PWRl2019-07) Author Contribution Xy J, Lj S, H Q and Cy D conceived the project and participated in the study design and interpretation of the results. Xy J and Lj S wrote the manuscript. Xy J and Cy D participated in the study design and helped draft the manuscript. H Q and Lj S participated in data interpretation and provided a critical review of the manuscript. Acknowledgements We appreciate Applied Protein Technology Co. Ltd, the leading bioinformatics platform in China, for the selfless help. We also appreciate the assistance received in data processing and consultation from Villanelle Life (Shanghai) Co. Ltd. Availability of data and materials The datasets generated and/or analyzed during the current study are available from the corresponding author upon reasonable request. References Giaquinto AN, Sung H, Miller KD, Kramer JL, Newman LA, Minihan A, et al. Breast Cancer Stat 2022 CA Cancer J Clin. 2022;72(6):524–41. Wu S, Du Y, Beckford J, Alachkar H. Upregulation of the EMT marker vimentin is associated with poor clinical outcome in acute myeloid leukemia. J Transl Med. 2018;16(1):170. Sun BO, Fang Y, Li Z, Chen Z, Xiang J. Role of cellular cytoskeleton in epithelial-mesenchymal transition process during cancer progression. Biomed Rep. 2015;3(5):603–10. Ye X, Brabletz T, Kang Y, Longmore GD, Nieto MA, Stanger BZ, et al. 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Nat Rev Genet. 2008;9(2):102–14. Farberov L, Ionescu A, Zoabi Y, Shapira G, Ibraheem A, Azan Y et al. Multiple Copies of microRNA Binding Sites in Long 3'UTR Variants Regulate Axonal Translation. Cells. 2023;12(2). Akman HB, Oyken M, Tuncer T, Can T, Erson-Bensan AE. 3'UTR shortening and EGF signaling: implications for breast cancer. Hum Mol Genet. 2015;24(24):6910–20. Lei B, Wang D, Zhang M, Deng Y, Jiang H, Li Y. miR-615-3p promotes the epithelial-mesenchymal transition and metastasis of breast cancer by targeting PICK1/TGFBRI axis. J Exp Clin Cancer Res. 2020;39(1):71. Additional Declarations No competing interests reported. Supplementary Files Supplementarymaterials.docx Cite Share Download PDF Status: Posted Version 1 posted You are reading this latest preprint version Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. 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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-4391747","acceptedTermsAndConditions":true,"allowDirectSubmit":true,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":302753121,"identity":"cb7f8282-301a-475d-8b90-670643feedf0","order_by":0,"name":"Xinyan Jia","email":"","orcid":"","institution":"Postgraduate Training Base of Jinzhou Medical University","correspondingAuthor":false,"prefix":"","firstName":"Xinyan","middleName":"","lastName":"Jia","suffix":""},{"id":302753122,"identity":"a62b6b88-f4cf-4e72-8481-5181eebfebad","order_by":1,"name":"Lujing Shao","email":"","orcid":"","institution":"Tongji University School of Medicine, Tongji University","correspondingAuthor":false,"prefix":"","firstName":"Lujing","middleName":"","lastName":"Shao","suffix":""},{"id":302753125,"identity":"5a2faf6a-cfd7-4a54-94a6-41b0ab9ffebc","order_by":2,"name":"Hong Quan","email":"","orcid":"","institution":"Tongji University School of Medicine, Tongji University","correspondingAuthor":false,"prefix":"","firstName":"Hong","middleName":"","lastName":"Quan","suffix":""},{"id":302753126,"identity":"ff7a4389-c758-446e-bf23-51eeae6ea7d7","order_by":3,"name":"Chunyan Dong","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAAA30lEQVRIiWNgGAWjYJACCSCWg7AMgMQBIrUY85CsJbEHziWkhX9GAuONjztq0/ez9x5+YVHAIMd3I4HxcwE+G24kMFvOPHM8t4fnXJoF0GHGkkAR6Rl4tBhIJLBJ87Ydy+2RyDEzAGpJ3HAjgY2Zhwgt6TxQLfXEaqlJAGoxfgDUkmBASIvEmQdAv7QdMOw5c8YMGMgShjPPPGyWxqeFvx0UYm118uztPcafJf7YyPMdTz74GZ8WBoH8D0DyMIjJJi0BjiPGBnwagNYcAJF1IIL54wf8akfBKBgFo2CEAgA/UEWBSCouZgAAAABJRU5ErkJggg==","orcid":"","institution":"Tongji University School of Medicine, Tongji University","correspondingAuthor":true,"prefix":"","firstName":"Chunyan","middleName":"","lastName":"Dong","suffix":""}],"badges":[],"createdAt":"2024-05-09 00:53:41","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-4391747/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-4391747/v1","draftVersion":[],"editorialEvents":[],"editorialNote":"","failedWorkflow":false,"files":[{"id":56779232,"identity":"bf41def8-4be1-4d5f-85a5-0a010bbfad84","added_by":"auto","created_at":"2024-05-20 11:07:09","extension":"png","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":204686,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eTranscription profiling of Vim KO and WT breast cancer cells. \u003c/strong\u003e(A) The volcano plot showing the significant differentially expressed genes between Vim KO and WT breast cancer cells. \u003cstrong\u003e(B)\u003c/strong\u003e Heatmap visualization of the DEGs. \u003cstrong\u003e(C)\u003c/strong\u003e Gene Ontology analysis of up and down-regulated DEGs. \u003cstrong\u003e(D)\u003c/strong\u003eKEGG pathway enrichment of up and down-regulated DEGs.\u003c/p\u003e","description":"","filename":"Fig1.png","url":"https://assets-eu.researchsquare.com/files/rs-4391747/v1/e1ecb1277147d29885b2add2.png"},{"id":56779239,"identity":"b4850911-d763-411d-87d4-c88e1ced413d","added_by":"auto","created_at":"2024-05-20 11:07:10","extension":"png","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":2358478,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eProteomic profiling of Vim KO and WT breast cancer cells. (A) \u003c/strong\u003eThe volcano plot showing the significant DEGs between Vim KO and WT breast cancer cells at protein level. \u003cstrong\u003e(B)\u003c/strong\u003e Heatmap visualization of DEGs at protein level. \u003cstrong\u003e(C)\u003c/strong\u003e Clusters of protein and protein interactions. Gene Ontology \u003cstrong\u003e(D)\u003c/strong\u003eand KEGG pathway \u003cstrong\u003e(E)\u003c/strong\u003e analysis of DEGs at protein level.\u003c/p\u003e","description":"","filename":"Fig2.2.png","url":"https://assets-eu.researchsquare.com/files/rs-4391747/v1/daa0081e3845fb3bb0c3feda.png"},{"id":56779242,"identity":"c384546a-80e3-4de9-a8d8-6190e3f34039","added_by":"auto","created_at":"2024-05-20 11:07:10","extension":"png","order_by":3,"title":"Figure 3","display":"","copyAsset":false,"role":"figure","size":272337,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eVim regulates transcription alternation through alternative polyadenylation in breast cancer cells.\u003c/strong\u003e \u003cstrong\u003e(A)\u003c/strong\u003e The scatter plot demonstrating the significant lengthening and shortening genes identified in Vim KO breast cancer cells by DANPOS. \u003cstrong\u003e(B)\u003c/strong\u003e The scatter plot showing the correlation between PDUI value and gene expression level. Gene ontology analysis of the APA lengthening \u003cstrong\u003e(C)\u003c/strong\u003e and shortening genes \u003cstrong\u003e(D)\u003c/strong\u003e. The MSigDB Hallmark enrichment of the APA lengthening \u003cstrong\u003e(E)\u003c/strong\u003e and shortening genes \u003cstrong\u003e(F)\u003c/strong\u003e.\u003c/p\u003e","description":"","filename":"Fig3.png","url":"https://assets-eu.researchsquare.com/files/rs-4391747/v1/c08cae2f83c3254cd57e3f1e.png"},{"id":56779243,"identity":"cd4635c8-3c1c-45fc-b8ab-bbb84bc4d6fb","added_by":"auto","created_at":"2024-05-20 11:07:10","extension":"png","order_by":4,"title":"Figure 4","display":"","copyAsset":false,"role":"figure","size":112310,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eVim KO induced the usage of proximal PAS of Pick1.\u003c/strong\u003e \u003cstrong\u003e(A)\u003c/strong\u003e The APA shortening event identified in the 3’UTR region of Pick1 in Vim KO breast cancer cells. Bar plot showing the decreased PDUI value after Vim KO \u003cstrong\u003e(B) \u003c/strong\u003eand the corresponding up-regulated gene expression level \u003cstrong\u003e(C)\u003c/strong\u003e.\u003c/p\u003e","description":"","filename":"Fig4.2.png","url":"https://assets-eu.researchsquare.com/files/rs-4391747/v1/c128f94cd776c3e501c58184.png"},{"id":56779233,"identity":"71f4886c-2e0f-4ccf-8868-957f875337c1","added_by":"auto","created_at":"2024-05-20 11:07:09","extension":"png","order_by":5,"title":"Figure 5","display":"","copyAsset":false,"role":"figure","size":353893,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003emiR-615-3p negatively regulates PICK1 to promote the progression of breast cancer. (A)\u003c/strong\u003e qRT-PCR analysis of the transcription levels of the short and long 3'UTR of PICK1 in VIM-WT and VIM-KO 4T1 cells, with relative quantification. (n=3) \u003cstrong\u003e(B-C)\u003c/strong\u003e Western Blot analysis of the protein levels of PICK1 in VIM-WT and VIM-KO 4T1 cells, with relative quantification. (n=3) \u003cstrong\u003e(D)\u003c/strong\u003e The binding region of wild-type PICK1 with miR-615-3p and the sequence information of mutant PICK1. \u003cstrong\u003e(E)\u003c/strong\u003eDual-luciferase assay demonstrates the interaction between PICK1 and miR-615-3p. (n=3) \u003cstrong\u003e(F-G)\u003c/strong\u003e Western Blot analysis of the changes in PICK1 protein levels after transfection of miR-615-3p mimic in VIM-WT and VIM-KO 4T1 cells, with relative quantification. (n=3) \u003cstrong\u003e(H-I)\u003c/strong\u003e EdU staining to assess the viability changes of the 4T1 cell line after transfection of miR-615-3p mimic in VIM-WT and VIM-KO 4T1 cells, with quantitative analysis of the proportion of EdU-positive cells. (n=3), Scale bar=50μm.\u003c/p\u003e","description":"","filename":"Figure5.png","url":"https://assets-eu.researchsquare.com/files/rs-4391747/v1/09c044c89a87b05087dc1b19.png"},{"id":67298057,"identity":"73a7634c-55c8-463f-be1e-11cb8c02aec4","added_by":"auto","created_at":"2024-10-23 11:46:56","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":4371876,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-4391747/v1/18742046-5072-4b2d-9de5-43d6e40cdfdb.pdf"},{"id":56779236,"identity":"eda57c6b-82db-483c-8354-f241b5426cbf","added_by":"auto","created_at":"2024-05-20 11:07:10","extension":"docx","order_by":7,"title":"","display":"","copyAsset":false,"role":"supplement","size":1098955,"visible":true,"origin":"","legend":"","description":"","filename":"Supplementarymaterials.docx","url":"https://assets-eu.researchsquare.com/files/rs-4391747/v1/30446bf1ab9447fa896fb486.docx"}],"financialInterests":"No competing interests reported.","formattedTitle":"Exploring Vimentin's Role in Breast Cancer via PICK1 Alternative Polyadenylation and the miR-615-3p- PICK1 Interaction","fulltext":[{"header":"Introduction","content":"\u003cp\u003eRecent statistics underscore that breast cancer constitutes a significant public health challenge globally, with its incidence rates witnessing an upward trajectory over the past four decades. Given its prevalence and pronounced impact on both mortality and morbidity in women, the quest for a deeper understanding and more effective treatment modalities for breast cancer is far from over(\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eAmong the plethora of factors implicated in the progression of breast cancer, Vimentin (VIM) has been identified as a pivotal element. As a type III intermediate filament, VIM plays an instrumental role in preserving cellular integrity, alongside facilitating critical processes such as cell migration, motility, and adhesion(\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e). Its overexpression is intricately associated with the epithelial-to-mesenchymal transition (EMT), a fundamental mechanism in the metastatic cascade of cancer(\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e). Notably, VIM's overexpression has been correlated with adverse clinical outcomes across a spectrum of cancers, including breast cancer. Recent scholarly contributions have posited that VIM's degradation could curtail the proliferation and metastasis of breast cancer cells, thereby underscoring its potential utility as both a biomarker and therapeutic target within the domain of breast oncology(\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e, \u003cspan additionalcitationids=\"CR5\" citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eRecently, VIM has emerged as a critical player in the post-transcriptional regulation of specific mRNAs, demonstrating the ability to interact with both the 3'-untranslated region (3'-UTR) and 5'-untranslated region (5'-UTR) of these molecules(\u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e, \u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e). These findings suggest that VIM plays a pivotal role in the transcriptional regulation of mRNAs, potentially influencing the metastatic capability and progression of cancer cells.\u003c/p\u003e \u003cp\u003eBuilding on this premise, our investigation endeavors to elucidate the multifarious mechanisms through which VIM modulates breast cancer progression, with an emphasis on transcriptional regulation. By leveraging a comprehensive multiomics framework, integrating both transcriptomic and proteomic analyses, we aim to demystify the intricate nexus between VIM and breast cancer pathology. Such insights could potentially herald novel therapeutic interventions targeting this critical pathway.\u003c/p\u003e"},{"header":"Methods","content":"\u003cdiv id=\"Sec3\" class=\"Section2\"\u003e \u003ch2\u003eCell culture\u003c/h2\u003e \u003cp\u003eThe 4T1 cell line was acquired from Cyagen Biosciences (Guangzhou, China). Cells were cultured in complete Dulbecco's Modified Eagle Medium (DMEM) supplemented with 10% Fetal Bovine Serum (FBS, catalog number 10099141C, Invitrogen, USA) and a penicillin-streptomycin-glutamine mixture (catalog number 10378016, Invitrogen, USA). Cultures were maintained in a humidified atmosphere containing 5% CO\u003csub\u003e2\u003c/sub\u003e at 37\u0026deg;C. The culture medium was refreshed every three days to ensure optimal growth conditions.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec4\" class=\"Section2\"\u003e \u003ch2\u003eLentivirus infection\u003c/h2\u003e \u003cp\u003eLentiviral vectors targeting miR-615-3p mimic and control lentiviral vectors were produced by GenePharma Co., Ltd. The 4T1 cells were infected with the lentivirus in the presence of polybrene (BL628A, Biosharp, China) for 12 hours. Forty-eight hours post-infection, the infected 4T1 cells underwent antibiotic selection to ensure the integration of the viral construct. The target sequence for the miR-615-3p mimic is as follows: miR-615-3p mimic, 5\u0026prime;-TCCGAGCCTGGGTCTCCCTCTT-3\u0026prime;.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec5\" class=\"Section2\"\u003e \u003ch2\u003eQuantitative Real-Time PCR (qRT-PCR)\u003c/h2\u003e \u003cp\u003eQuantitative Real-Time PCR (qRT-PCR): Total RNA was isolated using the Vazyme Total RNA Isolation Kit (R711-01, Vazyme, China) and cDNA was synthesized following the manufacturer's protocol using HiScript III RT SuperMix for qPCR (+\u0026thinsp;gDNA wiper) (R323-01, Vazyme, China). Real-time PCR was performed using the MagicSYBR Mixture (CW3008, CWBIO, China). For miRNA detection, reverse transcription polymerase chain reaction (RT-PCR) was conducted using the TaqMan MicroRNA Reverse Transcription kit (4366596, Invitrogen, USA). The TaqMan probe for hsa-miR-615 (Assay ID: 001960, Applied Biosystems, USA) was used to detect the specific microRNA, with U6 (Assay ID: 001973, Applied Biosystems) serving as the loading control. Quantitative real-time PCR (qPCR) was conducted on a BioRad CFX96 Real-Time PCR Detection System (BioRad, USA). Each reaction was performed in triplicate and the entire experimental process was repeated three times to ensure the reliability and consistency of the results. The relative expression levels were calculated using the 2-ΔΔCt method.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec6\" class=\"Section2\"\u003e \u003ch2\u003eProtein extraction and digestion\u003c/h2\u003e \u003cp\u003eSDT(4%SDS, 100mM Tris-HCl, pH7.6) buffer was used for sample lysis and protein extraction. The amount of protein was quantified with the BCA Protein Assay Kit (Bio-Rad, USA). 20 \u0026micro;g of protein for each sample were mixed with 5X loading buffer respectively and boiled for 5 min. The proteins were separated on 4%-20% SDS-PAGE gel (constant voltage 180V, 45 min). Protein bands were visualized by Coomassie Blue R-250 staining. Protein digestion by trypsin was performed according to filter-aided sample preparation (FASP) procedure described by Matthias Mann. The digest peptides of each sample were desalted on C18 Cartridges (Empore\u0026trade; SPE Cartridges C18 (standard density), bed I.D. 7 mm, volume 3 ml, Sigma), concentrated by vacuum centrifugation and reconstituted in 40 \u0026micro;l of 0.1% (v/v) formic acid.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec7\" class=\"Section2\"\u003e \u003ch2\u003eWestern Blot\u003c/h2\u003e \u003cp\u003eTotal protein was extracted using RIPA buffer. After quantification, equal amounts of protein samples were loaded and separated by 10% SDS-PAGE, then transferred to a 0.45-\u0026micro;m PVDF membrane. The membrane was blocked with 5% non-fat milk for 2 hours, followed by overnight incubation at 4\u0026deg;C with primary antibodies. The primary antibodies used were anti-PICK1 (10983-2-AP, Proteintech, 1/1000 dilution) and anti-GAPDH (ab8245, abcam, 1/5000 dilution). Subsequently, the membrane was incubated with secondary antibodies at room temperature for 1 hour. Immunoblots were visualized using an ECL chemiluminescence detection kit (Beyotime, Shanghai) and observed with a Tanon 4600 system (Tanon Science and Technology Co., Ltd.).\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec8\" class=\"Section2\"\u003e \u003ch2\u003eDual-Luciferase Reporter Assay\u003c/h2\u003e \u003cp\u003eThe coding sequences (CDS) of wild type (wt) or mutant (mut) PICK1 were cloned into the firefly luciferase expression vector pMIR-REPORT (Sangon Biotech, Shanghai, China). The PICK1-mut, PICK1-wt, and Vector or miR-615-3p mimic were co-transfected into the 4T1 cell line using Lipofectamine 3000 (Invitrogen, Carlsbad, CA, USA). The luciferase activity in the cells was normalized by co-transfecting with a plasmid containing the full-length Renilla luciferase gene (pTK-Renilla) as a reporter (Genomeditech), and quantified 48 hours after transfection using a Dual-Luciferase Reporter Assay System (Promega).\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec9\" class=\"Section2\"\u003e \u003ch2\u003e5-Ethynyl-2\u0026prime;-deoxyuridine (EdU) Assay\u003c/h2\u003e \u003cp\u003eThe EdU incorporation was detected using the BeyoClick\u0026trade; EdU Cell Proliferation Kit with Alexa Fluor 594 (Beyotime, Shanghai, China). After washing with PBS, the cells were incubated with the EdU solution for 2 hours, followed by staining of the nuclei with DAPI solution. After washing, the samples were observed under an inverted microscope (Olympus).\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec10\" class=\"Section2\"\u003e \u003ch2\u003eFilter-aided sample preparation (FASP Digestion) procedure\u003c/h2\u003e \u003cp\u003eThe detergent DTT (with the final concentration of 10 mM) was added to each sample respectively and mixed at 600 rpm for 1.5 h (37℃).After the samples cooled to room temperature, IAA was added with the final concentration of 20 mM into the mixture to block reduced cysteine residues and the samples were incubated for 30 min in darkness. Next, the samples were transferred to the filters respectively. The filters were washed with 100 \u0026micro;l UA buffer three times and then 100 \u0026micro;l 25mM NH4HCO3 buffer twice. Finally, trypsin was added to the samples(the trypsin : protein (wt/wt) ratio was 1:50) and incubated at 37℃ for 15\u0026ndash;18 h (overnight), and the resulting peptides were collected as a filtrate. The peptides of each sample were desalted on C18 Cartridges (Empore\u0026trade; SPE Cartridges C18 (standard density), bed I.D. 7 mm, volume 3 ml, Sigma), concentrated by vacuum centrifugation and reconstituted in 40 \u0026micro;l of 0.1% (v/v) formic acid. The peptide content was estimated by UV light spectral density at 280 nm using an extinctions coefficient of 1.1 of 0.1% (g/l) solution that was calculated on the basis of the frequency of tryptophan and tyrosine in vertebrate proteins.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec11\" class=\"Section2\"\u003e \u003ch2\u003eLC-MS/MS analysis\u003c/h2\u003e \u003cp\u003eWe conducted peptide analysis using an LC-MS/MS setup, specifically a Q Exactive mass spectrometer from Thermo Scientific, connected to an Easy nLC system from Proxeon Biosystems (now part of Thermo Fisher Scientific). The peptides were first introduced onto a reverse phase trap column, Thermo Scientific Acclaim PepMap100 (100 \u0026micro;m by 2 cm, nanoViper C18), and then transferred to a C18-reversed phase analytical column (Thermo Scientific Easy Column, 10 cm long, 75 \u0026micro;m inner diameter, with 3\u0026micro;m resin) using a buffer solution of 0.1% Formic acid in water. This setup separated the peptides with a gradient mixture of 84% acetonitrile and 0.1% Formic acid at a 300 nl/min flow rate. Operating in positive ion mode, the mass spectrometer targeted the most abundant precursor ions for higher-energy collisional dissociation (HCD) fragmentation, based on a data-dependent top20 method. We ensured precise measurement by setting the automatic gain control (AGC) target to 1e6, with a maximum injection time of 50 ms and a dynamic exclusion duration of 30.0 seconds. The system achieved a resolution of 60,000 at m/z 200 for survey scans and 15,000 at m/z 200 for HCD spectra, with an isolation width of 1.5 m/z. The normalized collision energy was set to 30 eV, and the underfill ratio was kept at 0.1%, ensuring that the system efficiently recognized and analyzed peptides.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec12\" class=\"Section2\"\u003e \u003ch2\u003eIdentification and quantitation of proteins\u003c/h2\u003e \u003cp\u003eThe MS raw data for each sample were combined and searched using the MaxQuant 1.6.14 software for identification and quantitation analysis.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec13\" class=\"Section2\"\u003e \u003ch2\u003eProtein-protein interaction analysis\u003c/h2\u003e \u003cp\u003eThe protein\u0026ndash;protein interaction (PPI) information of the studied proteins was retrieved from IntAct molecular interaction database (\u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttp://www.ebi.ac.uk/intact/\u003c/span\u003e\u003cspan address=\"http://www.ebi.ac.uk/intact/\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e) by their gene symbols or STRING software (\u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttp://string-db.org/\u003c/span\u003e\u003cspan address=\"http://string-db.org/\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e). The results were downloaded in the XGMML format and imported into Cytoscape software (\u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttp://www.cytoscape.org/\u003c/span\u003e\u003cspan address=\"http://www.cytoscape.org/\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e, version 3.2.1) to visualize and further analyze functional protein-protein interaction networks. Furthermore, the degree of each protein was calculated to evaluate the importance of the protein in the PPI network.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec14\" class=\"Section2\"\u003e \u003ch2\u003eRNA extraction and RNA-seq\u003c/h2\u003e \u003cp\u003eTotal RNA was extracted from tumor of both VIM-KO and ctrl group. Nanodrop ND-2000(Thermo Scientific, USA) was used to detect the A260/A280 absorbance ratio of RNA samples. The Rins of RNA were determined by by an Agilent Bioanalyzer 4150 system (Agilent Technologies, CA. Only qualified RNA can be used for library construction. Prepare paired terminal libraries and purify mRNA, followed by synthesizing cDNA using mRNA fragments as templates. Afterwards, the synthesized double stranded cDNA fragments were adapter linked to prepare a paired end library and subjected to PCR amplification. Purification and evaluation of PCR products (AMPure XP system), sequencing and 150bp paired end reading on Illumina Novaseq 6000 (or MGISEQ-T7). Subsequently, quality control and related analysis will be carried out.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec15\" class=\"Section2\"\u003e \u003ch2\u003eNGS data analysis\u003c/h2\u003e \u003cp\u003eThe quality of raw sequencing data was examined by FastQC (v0.11.7). Contaminated adapter and low-quality sequences were removed by using Trimmomatic (v0.38). Cleaned sequencing reads were then aligned to mm10 genome reference by STAR aligner (v2.5.2). Samtools (v1.3) was then used to remove unmapped reads and low-quality alignments. Htseq-count (v2.0.3) was used to calculate the raw counts for each transcript. The raw counts of different sample groups were compared by DESeq2 (v3.18) to identify the differentially expressed genes. For calling alternative polyadenylation (APA) events, DANPOS (v3.1.1) was used with default settings.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec16\" class=\"Section2\"\u003e \u003ch2\u003eFunctional enrichment analysis\u003c/h2\u003e \u003cp\u003eTo assess the biological functions, the computational web server g:Profiler(\u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e) (\u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://biit.cs.ut.ee/gprofiler/gost\u003c/span\u003e\u003cspan address=\"https://biit.cs.ut.ee/gprofiler/gost\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e) was utilized to conduct Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway analyses for differentially expressed genes. The resulting GO and KEGG pathway terms were ranked according to the P value and visualized using R software (v4.1.2).\u003c/p\u003e \u003c/div\u003e"},{"header":"Results","content":"\u003cdiv id=\"Sec18\" class=\"Section2\"\u003e \u003ch2\u003eRNA-seq reveals the fundamental transcription alternation of Vim KO breast cancer cells\u003c/h2\u003e \u003cp\u003eTo investigate the roles of VIM in transcription regulation, we performed RNA-seq experiments on both VIM-KO and WT breast cancer cells. Consistent to the fundamental functions of VIM, VIM KO induced massive transcription alternations in breast cancer cells, including 4245 significant up-regulated differentially expressed genes (DEGs) and 3147 significant down-regulated DEGs \u003cb\u003e(\u003c/b\u003eFig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003eA and \u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003eB\u003cb\u003e)\u003c/b\u003e. DEGs was defined by log2FoldChange\u0026thinsp;\u0026gt;\u0026thinsp;1 and adjusted P value\u0026thinsp;\u0026lt;\u0026thinsp;0.05. Based on Gene Ontology analysis, up-regulated DEGs were enriched to anatomical structure morphogenesis, tissue development, movement of cell or subcellular component, cell migration, and cell motility. The down-regulated DEGs were enriched to immune related terms, such as immune response, antigen receptor-mediated signaling pathway, and B cell receptor signaling pathway \u003cb\u003e(\u003c/b\u003eFig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003eC\u003cb\u003e).\u003c/b\u003e Similarly, based on KEGG pathway enrichment analysis, up-regulated DEGs were enriched to focal adhesion, ECM-receptor interaction, proteoglycans in cancer, and PI3K-Akt signaling pathway. The down-regulated were enriched to primary immunodeficiency, cell adhesion molecules and T cell receptor signaling pathway \u003cb\u003e(\u003c/b\u003eFig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003eD\u003cb\u003e)\u003c/b\u003e. These results demonstrate not only the crucial roles of VIM in maintaining the cell integrity, regulating cell migration and cancer cell proliferation, but also its involvement in immune repones regulation, suggesting VIM contributes to the development, proliferation and migration of cancer cells through various mechanisms.\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec19\" class=\"Section2\"\u003e \u003ch2\u003eProteomic profiling of Vim KO breast cancer cells\u003c/h2\u003e \u003cp\u003eTo further study the functions of VIM in protein level, we performed LC-MS/MS analysis to profile the protein levels of both WT and VIM KO breast cancer cells. In VIM KO group, the VIM protein level was reduced to 6.5% compared to WT breast cancer cells, confirming the efficient of VIM knockout in VIM KO cells. Compared to WT group, we identified 24 up-regulated genes and 99 down-regulated genes at protein level \u003cb\u003e(\u003c/b\u003eFig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003eA and \u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003eB\u003cb\u003e)\u003c/b\u003e. The top up-regulated genes include Limch1, Ltb4r, and Txnl4b, which are involved in cell migration, immune response and cell cycle progression, respectively. Top down-regulated genes include Mapre3 and Ppfibp1, which are involved in regulating cell adhesion and migration. Based on the protein-protein interaction analysis performed on DEGs, we observed three major clusters. Genes of Cluster 1 is enriched to epithelial mesenchymal transition pathway, including Vim, Itga5, Fermt2. Genes of Cluster 2 is enriched to extracellular matrix organization, including Col28a1, Cask, Col10a1, Capn3. Genes of Cluster 3 is mainly related to microtubule construction, with Mapre3 and Kif11 being the center node of this cluster \u003cb\u003e(\u003c/b\u003eFig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003eC\u003cb\u003e)\u003c/b\u003e. Additionally, we also performed gene ontology analysis and KEGG pathway enrichment analysis on DEGs at protein level and observed a significant enrichment to immune and inflammation related terms or pathways, such as complement activation, positive regulation of type I interferon-mediated signaling pathway and complement and coagulation cascades. DEGs at protein level are also enriched to metabolism related terms or pathways, such as polyphosphate catabolic process, taurine and hypotaurine metabolism, lipoic acid metabolism and sulfur metabolism, suggesting Vim KO has an impact on the energy supply that are required to tumor growth \u003cb\u003e(\u003c/b\u003eFig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003eD and \u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003eE\u003cb\u003e)\u003c/b\u003e.\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec20\" class=\"Section2\"\u003e \u003ch2\u003eVim regulates the EMT of breast cancer cells through APA\u003c/h2\u003e \u003cp\u003eAPA is one of the major mechanisms of posttranscriptional regulation and has been demonstrated to be involved in cancer development and progression. To investigate whether Vim regulates gene expression through this mechanism, we compared Vim KO and WT breast cells and identified 1207 significant shortening genes and 663 lengthening genes \u003cb\u003e(\u003c/b\u003eFig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003eA\u003cb\u003e)\u003c/b\u003e. Consistent to previous report that gene shortening is related to up-regulation of gene expression, we observed significant negative correlation (Pearson correlation: -0.135; P value: 5.70E-9) between gene expression and the percentage of distal poly(A) site usage index (PDUI) value \u003cb\u003e(\u003c/b\u003eFig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003eB\u003cb\u003e)\u003c/b\u003e. Based on gene ontology analysis, the lengthening genes are enriched to RNA processing, peptide metabolic process, regulation of catabolic process and autophagy. The shortening genes are enriched to cellular macromolecule catabolic process, intracellular protein transport, membrane organization and mitotic cell cycle process \u003cb\u003e(\u003c/b\u003eFig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003eC and \u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003eD\u003cb\u003e)\u003c/b\u003e. We further investigated the enrichment of lengthening and shortening genes to the MSigDB Hallmark pathway. The lengthening genes are enriched to p53 pathway, mitotic spindle and PI3K/AKT/mTOR signaling while the shortening genes are enriched to G2-M checkpoint, Myc Targets V and epithelial mesenchymal transition \u003cb\u003e(\u003c/b\u003eFig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003eE and \u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003eF\u003cb\u003e)\u003c/b\u003e. These results indicates that Vim KO caused fundamental transcription alternations are partially through APA\u0026rsquo;s regulation on RNA processing and metabolism. Vim KO also influence crucial pathways related to cancer survival, proliferation, and malignancy through APA mechanism.\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003eAmong the shortening genes in Vim KO breast cancer cells, the APA event observed in the 3\u0026rsquo;-UTR of Pick1 gene is one of the most significant events and associated with the EMT process. Pick1 was reported to be the negative regulator of TGF-beta signaling and inhibit the EMT process and cancer metastasis. Based on DANPOS results, the distal polyadenylation site (PAS) of Pick1 is mainly used in WT breast cancer cells while the usage of proximal PAS is significantly increased in Vim KO breast cancer cells. Given previous studies, the 3\u0026rsquo;-UTR of Pick1 contains the target site of miR-615-3p, which suppresses the Pick1/TGF-beta signaling axis and promotes the EMT and breast cancer metastasis \u003cb\u003e(\u003c/b\u003eFig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003eA\u003cb\u003e)\u003c/b\u003e. The knockout of Vim induced the increasing usage of proximal PAS and the abrogates of the miR-615-3p target sites, therefore causing the up-regulation of Pick1 at transcription level and the inhibition of EMT process \u003cb\u003e(\u003c/b\u003eFig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003eB and \u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003eC\u003cb\u003e)\u003c/b\u003e. These results demonstrate that APA is one of the major mechanisms that Vim utilizes to regulate the cancer cell progression.\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003e \u003cb\u003emiR-615-3p negatively regulates PICK1 to promote breast cancer progression, with its effectiveness depending on the presence or absence of VIM knock-out\u003c/b\u003e \u003c/p\u003e \u003cp\u003eWe next focused on elucidating the influence of miR-615-3p on breast cancer progression through its interaction with PICK1. Initial analysis using qRT-PCR demonstrated significant transcriptional variations between the short and long 3\u0026rsquo;-UTRs of PICK1 in both VIM-WT and VIM-KO 4T1 cells, suggesting a differential regulatory mechanism that could be attributable to APA influenced by the presence or absence of VIM (Fig.\u0026nbsp;\u003cspan refid=\"Fig5\" class=\"InternalRef\"\u003e5\u003c/span\u003eA). Protein levels of PICK1, as determined by Western Blot, further confirmed these transcriptional differences, revealing a nuanced layer of regulation potentially driven by miR-615-3p's interaction with PICK1, thereby modulating the protein's expression (Fig.\u0026nbsp;\u003cspan refid=\"Fig5\" class=\"InternalRef\"\u003e5\u003c/span\u003eB-C).\u003c/p\u003e \u003cp\u003eThe sequence specificity of this interaction was highlighted through the delineation of the binding region between wild-type PICK1 and miR-615-3p, alongside the introduction of mutations within PICK1 that presumably disrupt this interaction. This aspect of the study underscores the targeted nature of miR-615-3p's regulatory role (Fig.\u0026nbsp;\u003cspan refid=\"Fig5\" class=\"InternalRef\"\u003e5\u003c/span\u003eD). The functionality of this interaction was validated via dual-luciferase reporter assays, which unequivocally demonstrated miR-615-3p's engagement with PICK1, offering a molecular basis for the post-transcriptional regulation observed (Fig.\u0026nbsp;\u003cspan refid=\"Fig5\" class=\"InternalRef\"\u003e5\u003c/span\u003eE).\u003c/p\u003e \u003cp\u003eSubsequent analyses focused on the impact of miR-615-3p mimic transfection in both VIM-WT and VIM-KO cells. Western Blot tests after transfection showed clear changes in the levels of PICK1 protein, highlighting miR-615-3p's key role in controlling PICK1 expression. However, when VIM was knocked out, the miR-mimic didn't lower the protein expression, suggesting that the effect of miR-615-3p on PICK1 depends on whether VIM is present or not (Fig.\u0026nbsp;\u003cspan refid=\"Fig5\" class=\"InternalRef\"\u003e5\u003c/span\u003eF-G). EdU proliferation assays further illuminated the functional consequences of this regulatory pathway, showing that miR-615-3p's modulation of PICK1 expression significantly affects the proliferative capacity of 4T1 cells in both VIM-WT and VIM-KO contexts (Fig.\u0026nbsp;\u003cspan refid=\"Fig5\" class=\"InternalRef\"\u003e5\u003c/span\u003eH-I). This series of experiments provides strong evidence that miR-615-3p can effectively downregulate PICK1, while the regulatory region of PICK1 by miRNA is influenced by the presence or absence of VIM. This regulatory interaction plays a crucial role in advancing breast cancer progression, likely by causing changes in the cellular environment that favor tumor growth and spread.\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003c/div\u003e"},{"header":"Discussion","content":"\u003cp\u003eOur study revealed that VIM-KO significantly alters both the transcriptome and proteome of breast cancer cells, specifically increasing the expression of short 3\u0026rsquo;-UTRs. These finding highlights VIM's role in transcriptional regulation, with a particular emphasis on the crucial function of alternative splicing. Moreover, our research demonstrated that miR-615-3p binds more readily to the longer 3'-UTRs of \u003cem\u003ePICK1\u003c/em\u003e mRNA. However, VIM-KO leads to shorter 3\u0026rsquo;-UTRs, thereby affecting miR-615-3p's binding and consequently upregulating PICK1 expression. This upregulation inhibits cell proliferation in breast cancer.\u003c/p\u003e \u003cp\u003eVIM is a type III intermediate filament protein essential for maintaining cellular integrity and stability. Ubiquitously expressed in mesenchymal cells, VIM is a key marker of EMT and interacts with various signaling pathways, influencing a wide range of cellular functions(\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e, \u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e, \u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e). Although direct references to VIM's specific impact on the 3'-UTR or 5'-UTR regions of mRNAs are relatively sparse, its involvement in transcriptional regulation is intriguing. For example, VIM binds to the 5\u0026rsquo;-UTR stem-loop domain of collagen mRNAs, regulating collagen synthesis, and interacts with the 3' UTR of certain mRNAs, such as alkaline phosphatase mRNA in human primary osteoblasts and tissue factor mRNA in human breast cancer cells, stabilizing them and thus influencing their expression levels(\u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e). Specifically, in breast cancer, VIM has been shown to prevent miR-dependent negative regulation of tissue factor mRNA by interacting with its 3'-UTR during EMTs of circulating tumor cells, promoting coagulant activity associated with early metastasis(\u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eIn our study, we discovered that VIM-KO does not directly regulate PICK1 expression but instead modulates it by affecting the length of the 3\u0026rsquo;-UTR, suggesting that the mechanism of APA is involved in regulating the length of \u003cem\u003ePICK1\u003c/em\u003e mRNA 3\u0026rsquo;-UTR in VIM-KO cells. APA is a critical mechanism in gene expression, producing mRNA isoforms with differing 3\u0026rsquo;-UTR lengths, thereby affecting mRNA stability, translation efficiency, and cellular localization(\u003cspan additionalcitationids=\"CR14\" citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e). This process is regulated co- and post-transcriptionally, influenced by interactions between polyadenylation factors and RNA-binding proteins, and affected by the cellular environment​(\u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e). Although the connection between VIM and APA has not been explored, it presents a promising area for future research. Moreover, the modulation of PICK1 expression by VIM through altering the 3' UTR length hints at a potential role for APA in cancer progression, similar to the application of comprehensive genomic analyses in the interpretation and staging of lung cancer(\u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e, \u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e18\u003c/span\u003e), suggesting that the length of the 3' UTR might be a significant factor in the staging or prognosis of breast cancer.\u003c/p\u003e \u003cp\u003eMicroRNAs (miRNAs) are key regulators of gene expression at the transcriptional level, often binding to complementary sequences within the 3'-UTR of target mRNAs to mediate their degradation or inhibit their translation(\u003cspan additionalcitationids=\"CR20\" citationid=\"CR19\" class=\"CitationRef\"\u003e19\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e21\u003c/span\u003e). Lei et al.(\u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e22\u003c/span\u003e) elucidated the role of miR-615-3p in promoting the EMT and metastasis of breast cancer by targeting the PICK1/TGFBRI axis. According to their study, miR-615-3p facilitates breast cancer metastasis by directly targeting the 3'-UTR of \u003cem\u003ePICK1\u003c/em\u003e mRNA, leading to reduced PICK1 expression, which in turn influences TGF-β signaling and its downstream effects on cell migration and invasion. Building upon Lei et al.'s findings, our research further explores the intricate relationship between VIM-KO and its regulatory effects on breast cancer cell behavior. We discovered an upregulation of PICK1 in VIM-KO breast cancer cells, suggesting a novel regulatory mechanism whereby VIM may control breast cancer progression through the miR-615-3p/PICK1 axis. Experimental validation in our study supports our hypothesis that VIM-KO influences transcriptional regulation by shortening the 3\u0026rsquo;-UTR of \u003cem\u003ePICK1\u003c/em\u003e, interfering with miR-615-3p binding, and consequently upregulating PICK1 expression. Our findings not only corroborate the crucial role of miR-615-3p as identified by Lei et al. but also extend the understanding of VIM's involvement in breast cancer through modulation of the miR-615-3p/PICK1 axis, offering potential new avenues for therapeutic intervention in breast cancer treatment.\u003c/p\u003e \u003cp\u003eOur study unveils a novel regulatory mechanism of VIM in breast cancer, demonstrating its significant role in modulating transcription through the alteration of 3\u0026rsquo;-UTR lengths, which consequently impacts the miR-615-3p/PICK1 axis. We found that VIM knockout VIM-KO triggers the upregulation of PICK1, potentially inhibiting cell proliferation and reducing metastasis. These discoveries emphasize a previously unrecognized pathway through which VIM influences breast cancer progression, offering promising directions for targeted therapeutic strategies against the miR-615-3p/PICK1 axis in breast cancer treatment.\u003c/p\u003e "},{"header":"Declarations","content":"\u003cp\u003e \u003ch2\u003eEthics approval and consent to participate\u003c/h2\u003e \u003cp\u003eConsidering that the data are publicly available, no ethics approval is required for this study .\u003c/p\u003e \u003c/p\u003e \u003cp\u003e \u003cstrong\u003eConsent for publication\u003c/strong\u003e \u003cp\u003eAll authors reviewed and approved the manuscript.\u003c/p\u003e \u003c/p\u003e\u003cp\u003e \u003ch2\u003eCompeting interests\u003c/h2\u003e \u003cp\u003eAll the authors have declared that no competing interests exist.\u003c/p\u003e \u003c/p\u003e\u003ch2\u003eFunding\u003c/h2\u003e \u003cp\u003eThis work was supported by the National Natural Science Foundation of China (82073387), Pudong New Area Health and Family Planning Commission Industry Special Project of Shanghai (PW2021E-05) and Leading Talent Training Project of Shanghai Pudong New Area Health and Family Planning Commission (PWRl2019-07)\u003c/p\u003e\u003ch2\u003eAuthor Contribution\u003c/h2\u003e\u003cp\u003eXy J, Lj S, H Q and Cy D conceived the project and participated in the study design and interpretation of the results. Xy J and Lj S wrote the manuscript. Xy J and Cy D participated in the study design and helped draft the manuscript. H Q and Lj S participated in data interpretation and provided a critical review of the manuscript.\u003c/p\u003e\u003ch2\u003eAcknowledgements\u003c/h2\u003e \u003cp\u003eWe appreciate Applied Protein Technology Co. Ltd, the leading bioinformatics platform in China, for the selfless help. We also appreciate the assistance received in data processing and consultation from Villanelle Life (Shanghai) Co. Ltd.\u003c/p\u003e\u003ch2\u003eAvailability of data and materials\u003c/h2\u003e \u003cp\u003eThe datasets generated and/or analyzed during the current study are available from the corresponding author upon reasonable request.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\u003cli\u003e\u003cspan\u003eGiaquinto AN, Sung H, Miller KD, Kramer JL, Newman LA, Minihan A, et al. 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Mechanisms of post-transcriptional regulation by microRNAs: are the answers in sight? Nat Rev Genet. 2008;9(2):102\u0026ndash;14.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eFarberov L, Ionescu A, Zoabi Y, Shapira G, Ibraheem A, Azan Y et al. Multiple Copies of microRNA Binding Sites in Long 3'UTR Variants Regulate Axonal Translation. Cells. 2023;12(2).\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eAkman HB, Oyken M, Tuncer T, Can T, Erson-Bensan AE. 3'UTR shortening and EGF signaling: implications for breast cancer. Hum Mol Genet. 2015;24(24):6910\u0026ndash;20.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eLei B, Wang D, Zhang M, Deng Y, Jiang H, Li Y. miR-615-3p promotes the epithelial-mesenchymal transition and metastasis of breast cancer by targeting PICK1/TGFBRI axis. J Exp Clin Cancer Res. 2020;39(1):71.\u003c/span\u003e\u003c/li\u003e\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":true,"highlight":"","institution":"","isAcceptedByJournal":false,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true},"keywords":"","lastPublishedDoi":"10.21203/rs.3.rs-4391747/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-4391747/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003e\u003cstrong\u003eBackground:\u003c/strong\u003e Breast cancer continues to be a major health issue for women worldwide, with Vimentin (VIM) identified as a crucial factor in its progression due to its role in cell migration and the epithelial-to-mesenchymal transition (EMT). This study focuses on elucidating VIM's regulatory mechanisms on the miR-615-3p/PICK1 axis, particularly through the lens of alternative polyadenylation (APA) of PICK1, and its implications for breast cancer progression.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eMethods:\u003c/strong\u003eUtilizing the 4T1 breast cancer cell model, we first employed RNA-seq and proteomics to investigate changes in the APA of PICK1 following VIM knockout (KO). These high-throughput analyses aimed to uncover the underlying transcriptional and proteomic alterations associated with VIM's influence on breast cancer cells.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eResults:\u003c/strong\u003e RNA-seq and proteomic profiling revealed significant APA in PICK1 following VIM KO, suggesting a novel mechanism by which VIM regulates breast cancer progression. Validation experiments confirmed that VIM KO affects the miR-615-3p-PICK1 axis, with miR-615-3p's regulation of PICK1 being contingent upon the APA of PICK1. These findings highlight the complex interplay between VIM, miR-615-3p, and PICK1 in the regulation of breast cancer cell behavior.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConclusion:\u003c/strong\u003e This study unveils a critical role of VIM in breast cancer progression through its impact on the APA of PICK1, influencing the miR-615-3p-PICK1 axis. Our findings open new avenues for targeted therapies in breast cancer, focusing on the modulation of APA and the miR-615-3p-PICK1 interaction.\u003c/p\u003e","manuscriptTitle":"Exploring Vimentin's Role in Breast Cancer via PICK1 Alternative Polyadenylation and the miR-615-3p- PICK1 Interaction","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2024-05-20 11:07:04","doi":"10.21203/rs.3.rs-4391747/v1","editorialEvents":[{"type":"communityComments","content":0}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"35a88880-58da-4a0d-82c0-b0d15ac73cec","owner":[],"postedDate":"May 20th, 2024","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"posted","subjectAreas":[],"tags":[],"updatedAt":"2024-10-23T11:38:45+00:00","versionOfRecord":[],"versionCreatedAt":"2024-05-20 11:07:04","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-4391747","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-4391747","identity":"rs-4391747","version":["v1"]},"buildId":"8U1c8b4HqxoKbykW_rLl7","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}