Knockdown of PVT1 inhibits cell proliferation in luminal and basal-like breast cancer subtypes by activating LATS2/Hippo signaling pathway

Knockdown of PVT1 inhibits cell proliferation in luminal and basal-like breast cancer subtypes by activating LATS2/Hippo signaling pathway | 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 Knockdown of PVT1 inhibits cell proliferation in luminal and basal-like breast cancer subtypes by activating LATS2/Hippo signaling pathway Hai-Bo Zhang, Ying Zeng, Guo Wang This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-5745151/v1 This work is licensed under a CC BY 4.0 License Status: Published Journal Publication published 19 Jul, 2025 Read the published version in World Journal of Surgical Oncology → Version 1 posted 10 You are reading this latest preprint version Abstract Background: Breast cancer (BC) is a malignant tumor seriously threatening women’s health, while current approaches to BC treatment are challenged by the existence of drug resistance. Combination strategies of targeted therapy have been successfully applied in clinical BC treatment. However, whether there exist critical long non-coding RNAs (lncRNAs) responsible for BC pathogenesis and representing promising candidates for combined targeted therapy remains an issue. Methods: Public databases and bioinformatic methods were used to identify lncRNAs abnormally expressed among different subtypes of BC. The expression level of PVT1 was verified in collected clinical samples and representative cell lines. The role of PVT1 in BC cell proliferation was examined using MTS, plate clone formation, EdU and flow cytometry assay after small interfering RNA (siRNA) treatment. RNA sequencing was performed to investigate the potential molecular events regulated by PVT1. Western blot and immunofluorescence experiments were used to verify the activation of LATS2/Hippo signaling pathway after PVT1 knockdown. In addition, its activation was confirmed to mediate PVT1 function through rescue assay. The regulatory effect of PVT1 on LATS2 was investigated using mRNA stability experiments. Results: The expression level of PVT1 in BC tissues of luminal and basal-like subtypes was significantly higher than that in paracancerous tissues. PVT1 knockdown substantially inhibited the proliferation of BC cells in both subtypes. RNA sequencing revealed that Hippo signaling pathway might be the downstream target of PVT1. After PVT1 knockdown, both mRNA and protein level of LATS2 were elevated which further decreased the distribution of YAP in cell nucleus, indicating the activation of Hippo signaling pathway. The proliferation inhibitory effect of PVT1 could be attenuated by simultaneous knockdown of LATS2. Furthermore, knockdown of PVT1 was demonstrated to significantly slow down the degradation rate of LATS2 mRNA. Conclusions: PVT1 level was significantly elevated in luminal and basal-like BC subtypes. Knockdown of PVT1 could inhibit cell proliferation of these two BC subtypes partly through activating LATS2/Hippo signaling pathway. PVT1 Hippo pathway luminal basal-like breast cancer Figures Figure 1 Figure 2 Figure 3 Figure 4 Figure 5 Figure 6 Introduction Breast cancer (BC) is the most frequent malignant tumor in women. According to the International Agency for Research on Cancer (IARC), there were an estimated 2.3 million new BC cases in 2022 worldwide, accounting for 11.6% of all newly diagnosed cancer cases[ 1 ]. BC also remains the leading cause of cancer-related deaths among women, with an estimated 665,684 deaths[ 1 ]. The incidence of breast cancer varies across regions, with higher rates observed in developed countries due to lifestyle factors, reproductive behaviors, and improved detection methods. However, mortality rates are disproportionately higher in low- and middle-income countries due to limited access to early diagnosis and treatment[ 2 – 4 ]. With increasing global cancer burden, effective screening, early detection, and improved treatment strategies are critical for reducing breast cancer mortality[ 1 ]. BC is a highly heterogeneous disease with distinct molecular subtypes, clinical characteristics, and therapeutic responses. Based on the expression level of estrogen receptor (ER), progesterone receptor (PR), human epidermal growth factor 2 (HER2) and Ki67, BC can be divided into four molecular subtypes: luminal A, luminal B, HER2-overexpressing and basal-like type[ 5 ]. The luminal subtypes are characterized by positive expression of ER and/or PR, accounting for approximately 65% of all BC cases[ 6 ]. Endocrine therapy targeting the estrogen signaling pathway is the primary treatment for these subtypes[ 7 ]. HER2-overexpressing subtype represents 15%-20% of all cases with HER2 being used as the major therapeutic target[ 8 ]. Although basal-like subtype only accounts for 10%-15% of total BC cases, it is highly invasive and lacks effective treatment targets, leading to the worst prognosis[ 9 ]. The application of targeted therapies has significantly improved the overall treatment outcomes in luminal and HER2-overexpressing BC patients[ 10 , 11 ]. However, the presence of primary and acquired resistance has become a critical challenge limiting further breakthroughs in therapeutic efficacy. For example, up to 41% of ER-positive BC patients, who had undergone 5 years of endocrine therapy and achieved clinical cure, developed distant recurrence within 15 years[ 12 ]. Once drug resistance occurs, treatment relies more heavily on chemotherapy, but the efficacy at this stage becomes unoptimistic[ 13 ]. Therefore, to enhance initial treatment responses, delay the onset of drug resistance, and ultimately improve clinical outcomes, identifying new combined therapy targets remains an urgent research focus for luminal and HER2-overexpressing BC. For basal-like BC, which lacks specific therapeutic targets, the treatment options are still limited. Thus, identifying suitable molecular drug targets for this subtype is of particularly significant practical importance. Currently, several combination strategies of targeted therapies have been successfully applied in clinical BC treatment. For example, the PIK3CA inhibitor Alpelisib was approved by FDA for PIK3CA -mutated, hormone receptor-positive advanced BC in combination with fulvestrant in 2019, significantly prolonging patients’ progression-free survival[ 14 ]. The combination of PIK3CA inhibitors and HER2 monoclonal antibodies also showed synergistic anti-tumor activity, and had been investigated in several clinical trials targeting HER2-positive BC[ 15 , 16 ]. Cyclin-dependent kinases 4 and 6 (CDK4/6) inhibitors combined with endocrine therapy have been approved for some luminal BC patients to improve their prognosis [ 13 ]. Patient-derived tumor xenograft model studies further demonstrate that CDK4/6 inhibitors can sensitize tumors to HER2-targeted therapy and delay recurrence, indicating great potential for combined use in HER2-overexpressing BC[ 17 ]. It is worth noting that both PIK3CA and CDK4 / 6 are foundational genes determining cell growth[ 18 , 19 ], as indirectly evidenced by their abnormal activity or expression across different BC subtypes[ 20 ]. To be specific, PIK3CA is the most frequently mutated gene in BC, with a mutation rate of 49%, 32%, 42% and 7% for luminal A, luminal B, HER2 and basal-like subtype respectively, while copy number amplification of CDK4 was observed in 14% of luminal A subtype, 25% of luminal B subtype, and 24% of HER2-overexpressing subtype[ 20 ]. Thus, it is suggested that identifying such "pan-subtype" dysregulated molecules is still an effective strategy for screening critical oncogenes and potential drug targets. Considering the relatively comprehensive exploration of protein-coding molecules like PIK3CA and CDK4/6, the next issue is whether there are other types of molecules in BC that show abnormal expression or activity across multiple subtypes, and play a pivotal role in basic cellular activities, thus representing promising candidates for the development of novel targets for combination therapy. Long non-coding RNAs (lncRNAs) are a class of non-coding RNAs with transcript lengths exceeding 200 nucleotides, which were long considered “transcriptional noise” of the genome[ 21 ]. However, increasing studies have revealed their extensive involvement in gene expression regulation and close association with the development and progression of various human diseases, including cancer[ 22 – 24 ]. Therefore, identifying pan-subtype lncRNAs and elucidating their roles and mechanisms may not only help deepen our insights into BC pathogenesis but also enrich the pool of candidate targets for combination therapies. Genome-wide molecular profiling techniques (such as next-generation sequencing and microarray analyses) have proven highly effective in identifying critical molecular alterations during cancer development and progression, significantly advancing the discovery of key biomarkers or therapeutic targets[ 25 – 27 ]. The Cancer Genome Atlas (TCGA) is a landmark cancer genomics program integrating multi-omics data in over 30 types of human cancers[ 28 ]. Using TCGA clinical and sequencing data, we performed differential gene expression analysis and correlation analysis between gene expression and clinicopathological features in different BC subtypes, identifying lncRNA plasmacytoma variant translocation 1 (PVT1) as a significant candidate involved in both luminal and basal-like BC. PVT1 has been identified as an oncogenic factor in various cancers including BC, which plays a crucial role in tumor progression by promoting cell proliferation, invasion, and resistance to apoptosis[ 29 – 33 ]. However, the precise mechanisms underlying PVT1’s oncogenic functions in BC have yet to be fully elucidated. We proved that PVT1 enhances BC cell proliferation, at least in part, by modulating the LATS2/Hippo pathway—a critical signaling cascade that regulates cell proliferation, apoptosis, and organ size by controlling the activity of YAP/TAZ transcriptional coactivators[ 34 ]. The findings of our study provide new insights into the role of PVT1 across different BC subtypes and may contribute to the development of PVT1-based therapeutic strategies. Materials and methods Bioinformatical analysis RNA-seq data of BC cohort and the clinical profiles with subtype information were downloaded from TCGA data portal ( https://tcga-data.nci.nih.gov/tcga/ ) and the cBioPortal for Cancer Genomics ( http://cbioportal.org ), respectively. Information of lncRNA gene annotation were obtained from the Ensembl database ( http://ensemblgenomes.org/ ). The differential analysis was conducted between BC tissues and non-cancerous tissues in the same subtype using the R package of “edgeR”, and lncRNAs with |log2 (fold change)| > 1 and P < 0.05 were considered to be differentially expressed. Next, these lncRNAs were divided into high-expression and low-expression groups based on their median expression values. BC patients were classified into a low-stage group (stages I and II) and a high-stage group (stages III and IV) according to their TNM stages. The association between lncRNA expression levels and TNM stages was assessed by the chi-square test using the "MASS" R package. A significance level of P < 0.05 was used as the screening criterion to identify lncRNAs closely associated with BC TNM stages. GEPIA 2 (Gene Expression Profiling Interactive Analysis 2, http://gepia2.cancer-pku.cn/ ) is an online tool for TCGA data analysis and visualization, suitable for gene expression and survival analysis [ 35 ]. In this study, it was used to analyze the correlation between PVT1 expression levels and overall survival prognosis in BC patients. Cell culture The human BC cell lines MCF7, T47D, MDA-MB-231 and BT549 were purchased from American Type Culture Collection (ATCC) (Manassas, VA, USA). Cells were cultured in RPMI-1640 culture medium (Gibco, Grand Island, NY, USA) supplemented with 10% fetal bovine serum, 2 mM L-glutamine, 100 u/ml of penicillin and 1 mg/ml of streptomycin (Biological Industries, Cromwell, CT, USA). All cells were maintained in a humidified incubator with 5% CO 2 at 37°C with the medium changed every 2 days. Transfection of small interfering RNA (siRNA) The siRNAs and negative control (NC) were obtained from GenePharma (Shanghai, China). Briefly, after MCF7 and BT549 cells were seeded in plates and cultured for 24 h, the cells were transfected with 50 nM single siRNA, NC or combined mix using RNAiMAX reagents (Invitrogen, Carlsbad, CA, USA) following the manufacturer's instruction. The siRNA sequences were as follows: PVT1-si1, 5’-CCC AAC AGG AGG ACA GCU UTT-3’, PVT1-si2, 5’-GCU UGG AGG CUG AGG AGU UTT-3’, LATS2-si, 5’-UAC CAU AAA UAC AAU CUU CTT-3’. Cell viability assay Cells were seeded into 96-well plates (3000 cells/well for MCF7 and 2000 cells/well for BT549) and cultured for 24 h. Then cells were transfected with single siRNA, NC or combined mix. After 48 or 72 h, cell viability was detected through MTS assay (CellTiter 96 AQueous One Solution Cell Proliferation Assay kit, Promega, Madison, WI, USA). The absorbance values were detected at 490 nm using a microplate reader. Plate clone formation assay Cells were seeded into 12-well plates at a density of 500 cells per well, cultured for 24 h and then treated with single siRNA, NC or combined mix. A week later, when most clones contained > 50 cells, they were fixed with 4% paraformaldehyde (Sigma-Aldrich, Louis, MO, USA) for 30 min and stained with 1% crystal violet for 30 min. After washing and air drying, the clone numbers were quantified by Image J software (Bethesda, MA, USA) or naked eyes. EdU assay DNA replication activity was detected using the Cell-Light EdU Apollo567 In Vitro Kit (RiboBio, Guangzhou, China) following the manufacturer’s instructions. In brief, cells were seeded into 96-well plates (3000 cells/well for MCF7 and 2000 cells/well for BT549), cultured for 24 h, and then transfected with siRNA or NC. After 48 h, cells were incubated with EdU for 2 h prior to fixation and staining. The ratio of EdU-incorporated cells was calculated to indicate the proliferation activity. Flow Cytometry Cells were seeded into 6-well plates at a density of 1 × 10 5 cells per well, cultured for 24 h and then treated with either siRNA or NC. For cell cycle analysis, cells were collected after 48 h and fixed in 70% ethanol overnight. Then, the cells were washed with precooled PBS and incubated with a freshly prepared PI staining solution (Beyotime Biotechnology, Shanghai, China) for 30 min at 37°C. The cells were then kept on ice in shade until detection on a FACScan cytometer (BD Biosciences, San Jose, CA, USA) following the manufacturer's guidelines. For cell apoptosis analysis, cells were collected after 72 h and stained with 5 µL Annexin V-FITC (Beyotime Biotechnology, Shanghai, China) and 10 µL PI solution for 10 min at room temperature. The cells were then kept on ice in shade until detection on the FACScan cytometer. RNA extraction and quantitative real-time PCR Total RNA was isolated from tissues or harvested cells by using TRIzol reagent (Takara Bio Inc., Kusatsu, Japan) and concentration was determined using the Nanodrop 2000 spectrophotometer (Thermo Fisher Scientific, Waltham, MA, USA). The quality of the RNA was assessed by electrophoresis on a non-denaturing agarose gel. One microgram of total RNA was reversely transcribed using the PrimeScriptTM RT reagent Kit (Takara Bio Inc., Kusatsu, Japan) in a 20 µL reaction system. The reaction products were then diluted to a total volume of 100 µL with distilled water. The real-time PCR reaction consisted of 2 µL of diluted reverse transcription product, 1×SYBR® Premix DimerEraser (Takara Bio Inc., Kusatsu, Japan) and 0.3 µM forward and reverse primers. Beta-actin was used as an endogenous control. The sequences of primers were listed in Table 1 . Real-time PCR conditions were as follows: 95°C for 10 min, followed by 45 cycles at 95°C for 15 s and 60°C for 1 min. Fold induction values were calculated using the 2 −ΔΔCt method. Table 1 Primer sequences of genes for quantitative real-time PCR Gene symbol Forward primer (5’-3’) Reverse primer (5’-3’) PVT1 TGAGAACTGTCCTTACGTGACC AGAGCACCAAGACTGGCTCT LATS2 TAGAGCAGAGGGCGCGGAAG CCAACACTCCACCAGTCACAGA CYR61 GCTGCGGCTGCTGTAAGGTC GGCGCCGAAGTTGCATTCCA AXL AACCAGGACGACTCCATCC AGCTCTGACCTCGTGCAGAT CCND1 CAGATCATCCGCAAACACGC AAGTTGTTGGGGCTCCTCAG MYC GTCAAGAGGCGAACACACAAC TTGGACGGACAGGATGTATGC β-actin TCAAGATCATTGCTCCTCCTGAG ACATCTGCTGGAAGGTGGACA RNA sequencing MCF7 cells were seeded into 6-well plates at a density of 1 × 10 5 cells per well, cultured for 24 h, and then transfected with either PVT1 siRNA or NC. After 48 h of transfection, total cellular RNA was obtained for sequencing by Novogene (Beijing, China) on the HiSeq 4000 Illumina platform. Genes with |log2 (fold change)| > 1 and P < 0.05 were considered to be differentially expressed. Enrichment analysis To figure out the biological function of PVT1, genes differentially regulated after PVT1 knockdown were submitted to the online DAVID website ( https://david.ncifcrf.gov/ ) for GO (Gene Ontology) analysis and KEGG (Kyoto Encyclopedia of Genes and Genomes) pathway analysis. Western blot analysis Total cellular proteins were extracted from the harvested cells using RIPA lysis buffer (Beyotime Institute of Biotechnology, Shanghai, China). The protein concentrations were determined using a BCA protein assay kit (Beyotime Institute of Biotechnology). Cellular proteins were separated on sodium dodecyl sulfate polyacrylamide gels and transferred to polyvinylidene fluoride membranes. Blots were incubated in blocking buffer (5% non-fat dry milk in Tris-buffered saline with 0.5% Tween (TBS-T)) at room temperature for 1 h. After washing with TBS-T, the blots were incubated with a specific antibody against YAP (Abcam Inc., Cambridge, MA, USA), TAZ (Santa Cruz Biotechnology, Inc., Dallas, Texas, USA), P-YAP, P-TAZ, LATS2 (Cell Signaling Technology Inc., Beverly, MA., USA), or β-actin (Sigma Chemical Co., St. Louis, MO, USA) overnight at 4°C. Following the incubation with a horseradish peroxidase-conjugated secondary antibody, the signal was detected using an ECL Western Blotting system (Promega, Madison WI, USA) and visualized using the Bio-Rad ChemiDocTM MP system. Subsequent quantification of western blot bands in each lane was conducted using the Image Lab software (Bio-Rad, Hercules, CA, USA). Immunofluorescence analysis Cells were seeded into confocal dishes at a density of 1 × 10 5 cells per dish for MCF7 and 5 × 10 4 cells per dish for BT549. Cells were fixed with 4% paraformaldehyde for 15 min at room temperature 48 h after transient transfection, and washed three times with PBS, followed by permeabilization with 0.3% Triton X-100 in PBS for 15 min. After fixation, cells were blocked with 500 µL 5% donkey serum for 40 min at room temperature, incubated with YAP or TAZ antibody (1:100) for 12 h at 4°C, and then incubated with Alexa Fluor® 488 goat anti-Mouse IgG or Alexa Fluor® 594 donkey anti-Rabbit IgG for 1 h in darkness at room temperature. Cells were then washed, incubated with antifade mounting medium containing 2-(4-Amidinophenyl)-6-indolecarbamidine dihydrochloride (DAPI) (Beyotime Biotechnology, Shanghai, China) for 10 min at room temperature, and washed three times. After the final washes, cells were visualized by a confocal laser microscope (Carl Zeiss, Jena, Germany). Photomicrographs were captured at 600 × magnification, and merged using the ZEN software (Carl Zeiss). Statistical analysis GraphPad Prism 7.0 and R software were used for plotting and statistical analysis. The experimental data were expressed as mean ± standard error (SEM). For quantitative data that followed normal distribution and had homogeneity of variance, Student's T-test (two groups) or One-way ANOVA (multiple groups) were used to compare the differences between groups. For quantitative data not subject to normal distribution, differences between groups were compared using Mann-Whitney rank-sum test (two groups) or Kruskal-Wallis test (multiple groups). All statistical tests were two-tailed and P < 0.05 was considered statistically significant. Results PVT1 was abnormally overexpressed in luminal and basal-like BC tissues. In the TCGA cohort, 683, 169 and 78 patients were classified into luminal, basal-like and HER2 subtypes, respectively. The number of corresponding paracancerous tissue samples were 79, 15 and 9 in turn. Considering the importance of sample size in statistical analysis, the HER2 subtype was excluded in the subsequent study. The clinical information of luminal and basal-like BC patients was shown in Supplementary Table 1. All patients in these two remaining subtypes were included for the differential expression analysis. Ultimately, A total of 2,947 differentially expressed lncRNAs were identified in the luminal subtype (1,724 upregulated, 1,223 downregulated) and 3,176 in the basal-like subtype (2,046 upregulated, 1,130 downregulated). Intersection analysis showed that 717 lncRNAs were upregulated and 533 downregulated in both subtypes (Supplementary Fig. 1). The full list of these lncRNAs was provided in Supplementary Table 2. TNM stage is an important clinical indicator of tumor progression. In order to further identify lncRNAs involved in the development of BC, the association between expression levels of the differentially expressed lncRNAs and TNM stages was assessed by the chi-square test. There were 132 and 60 lncRNAs found to be associated with TNM stages in the luminal and basal-like subtype, respectively, and the complete list of lncRNAs is provided in Supplementary Table 3. Unfortunately, no lncRNAs were found to be correlated with TNM stages in both subtypes. Among the candidate lncRNAs, PVT1 attracted our attention, which was abnormally up-regulated in both subtypes and significantly correlated with TNM stage. Based on the normalized PVT1 expression values obtained from previous differential analysis, its expression in cancer and adjacent non-cancerous tissues, as well as across different cancer T, N, and M stages, is further presented in detail in the two subtypes (Fig. 1 A-L). Consistent with previous results, PVT1 is upregulated in both luminal and basal-like subtypes, not only in all tumor samples (Fig. 1 A-B) but also in paired tumor samples (Fig. 1 C-D) compared to adjacent non-cancerous tissues. What’s more, its level in Stage III cancer tissues of luminal subtype is significantly than those in Stage I and Stage II tissues (Fig. 1 E). PVT1 is a widely known oncogene in various cancer types including BC[ 29 – 33 ]. However, the underlying mechanisms by which PVT1 promotes BC is still not fully understood and few studies highlighted its role among different subtypes. Therefore, we focused on PVT1 in the subsequent study from the aspect of luminal and basal-like BC. Further analysis using the GEPIA 2 website revealed that PVT1 showed marginal prognostic significance in luminal BC and no prognostic significance in basal-like BC. It was possibly due to the limitation of sample size, because when these two subtypes were combined, high PVT1 expression was found to be significantly associated with poorer overall survival prognosis (Fig. 1 M-O). Together, these findings indicated that PVT1 might be a key molecule mediating the tumorigenesis and development of the two BC subtypes, especially the luminal subtype. Knockdown of PVT1 significantly inhibited proliferation in luminal and basal-like BC cells. Before exploring the biological function of PVT1 in luminal and basal-like BC at the cellular level, PVT1 expression in several corresponding BC cell lines was detected. The results showed that the expression level of PVT1 in luminal cell lines (MCF7 and T47D) and basal-like cell lines (BT549 and MDA-MB-231) was significantly higher than that in the normal mammary epithelial cell line MCF10A (Fig. 2 A), which was consistent with the result of bioinformatical analysis. MCF7 and BT549 were selected in the subsequent study, which represented the luminal and basal-like subtype respectively. Accelerated proliferation is a classical hallmark of tumor cells[ 36 ]. To explore the role of PVT1 in cell proliferation, three siRNAs were synthesized, and their knockdown efficiency was assessed. The two siRNAs with the highest knockdown efficiency were selected for subsequent studies (Fig. 2 B). Then, MTS, clone formation EdU and flow cytometry assays were performed after PVT1 knockdown in MCF7 and BT549 cells. The results showed that PVT1 knockdown induced a significant decrease in cell viability, clone formation and DNA replication activity in both cell lines (Fig. 2 C-E). Moreover, the cell cycle could be noticeably arrested at the G0/G1 phase (Figs. 2 F). Interestingly, PVT1 knockdown significantly increased apoptosis in BT549 cells, whereas MCF7 cells showed no notable apoptotic response (Supplementary Fig. 2). Together, it could be inferred that PVT1 functioned as a driving factor in the proliferation of luminal and basal-like cell lines. Knockdown of PVT1 induced the activation of Hippo signaling pathway. In order to reveal the underlying mechanism of proliferation inhibition induced by PVT1 knockdown, RNA sequencing was conducted in MCF7 cells. A total of 866 differentially expressed genes were identified between the PVT1-knockdown group and the control group, among which 565 genes were up-regulated and 301 genes were down-regulated (Fig. 3 A). For these genes, GO analysis showed that they were mainly enriched in biological processes such as DNA replication initiation and G1/S transition of mitotic cell cycle (Fig. 3 B-D). KEGG pathway analysis showed that they were mainly enriched in cell cycle, FoxO signaling pathway, p53 signaling pathway, Hippo signaling pathway and other classic signaling pathways related to cell growth (Fig. 3 E). The Hippo signaling pathway is a growth-suppressing kinase cascade which is highly conserved in evolution and controls organ size and tissue homeostasis by regulating cell proliferation, division, and death [ 37 , 38 ]. It also plays an important regulatory role in the occurrence and development of tumors[ 39 ]. Two homologous genes, Yes-associated protein (YAP) and transcriptional co-activator with PDZ-binding motif (TAZ), were key downstream effectors of Hippo pathway, whose activity was dynamically regulated by their phosphorylation state[ 38 ]. It was found here, after PVT1 knockdown, total protein level of YAP had little change, whereas phosphorylated YAP (P-YAP) was significantly increased (Fig. 4 A). As for TAZ, no obvious change was observed in the expression level of either total or phosphorylated protein (Fig. 4 A). YAP and TAZ are distributed in both cytoplasm and nucleus under a state of dynamic shuttle, and phosphorylation of them promotes the cytoplasmic localization by stimulating their association with 14-3-3 proteins [ 40 , 41 ]. In the immunofluorescence assay, the fluorescence intensity of YAP protein in the nucleus region of the PVT1-knockdown group was significantly lower than that of the control group, indicating a reduced entry of YAP into the nucleus (Fig. 4 B). However, the fluorescence intensity distribution of TAZ protein remained largely unchanged, indicating that PVT1 knockdown did not significantly affect TAZ localization (Supplementary Fig. 3). Nuclear YAP/TAZ binds to TEA domain family transcription factors, initiating the expression of downstream genes, such as CYR61, MYC, AXL and CCND1[ 42 – 44 ]. As expected, these genes were all downregulated when PVT1 was knocked down (Fig. 4 C). Together, these results confirmed that knockdown of PVT1 in MCF7 and BT549 cells might activate the Hippo pathway, through specifically increasing the phosphorylation level of YAP. LATS2 up-regulation mediated the activation of Hippo signaling pathway. Large tumor suppressor 1/2 (LATS1/2), known as key upstream kinases of the pathway, can directly phosphorylate YAP through interaction with the cofactor Mps one binder 1 (MOB1)[ 45 ]. Therefore, we speculated whether the upregulation of P-YAP was mediated by LATS1/2. As expected, LATS2 expression was notably elevated after PVT1 knockdown at both mRNA and protein level (Fig. 5 A-B). Moreover, the upregulation of P-YAP induced by PVT1 knockdown could be reversed by simultaneous knockdown of LATS2 (Fig. 5 C), demonstrating that the activation of Hippo pathway was indeed mediated by LATS2 up-regulation. Then, the mechanism through which PVT1 influenced LATS2 expression was explored. Since both mRNA and protein level of LATS2 were up-regulated after PVT1 knockdown, we speculated that LATS2 expression was mainly regulated at the mRNA level. As shown in Fig. 5 D, when cells were pretreated with the mRNA transcription inhibitor actinomycin D before PVT1 knockdown, the up-regulation of LATS2 mRNA level was not reversed. However, LATS2 mRNA was found to decrease more slowly in the knockdown group than in the control group (Fig. 5 E). These results indicated that the up-regulation of LATS2 was not associated with its transcription, but due to the increased mRNA stability induced by PVT1 knockdown. LATS2 up-regulation partly mediated the inhibitory function of PVT1 knockdown on cell proliferation. Lastly, to examine whether LATS2/Hippo pathway mediated the proliferation-inhibitory function of PVT1 knockdown, a rescue experiment targeting LATS2 was conducted. Specifically, LATS2 was simultaneously interfered to block its upregulation induced by PVT1 knockdown. As shown in Fig. 6 , single PVT1 knockdown notably inhibited cell viability and clone formation ability as before, while combined knockdown of LAST2 could partially rescue it, confirming that LATS2 up-regulation mediated the inhibitory effect of PVT1 knockdown on cell proliferation in luminal and basal-like BC. Discussion In this study, we attempted to identify potential lncRNAs for combined targeted therapy of BC by using RNA-seq and clinical data from TCGA. Our strategy was to search for shared differentially expressed lncRNAs from multiple BC subtypes, considering that such “pan-subtype” lncRNAs might have more powerful biological functions than subtype-specific lncRNAs. Due to the relatively limited sample number of HER2-overexpressing subtype, our analysis finally focused on luminal and basal-like BC. The former was the most common subtype clinically, while the latter was the subtype with the worst prognosis. Therefore, identification of lncRNAs associated with these two subtypes also fitted the clinical needs. During our screening, PVT1 was found to be significantly up-regulated in BC of both luminal and basal-like subtypes. In addition, high expression of PVT1 was significantly correlated with higher clinical stages in the luminal subtype and poorer overall survival, indicating its involvement in BC development. Actually, PVT1 has been widely reported in BC, which plays an oncogenic role[29, 46]. In triple negative BC, PVT1 affects cell proliferation and migration through maintaining MYC protein stability, repressing p21 expression and activating the KLF5/β-catenin signaling pathway[47-49]. In ER positive BC, PVT1 acts as a key factor in the composition of ERα-PRC2 network, modulating cell proliferation, apoptosis, migration and response to hypoxia[50]. PVT1 also promotes BC cell proliferation and/or migration through sponging multiple miRNAs, such as miR-148a-3p, miR-128-3p, miR-543, and miR-145-5p[51-54]. Despite extensive studies, the full oncogenic mechanisms of PVT1 remain to be elucidated, especially considering the limited attention given to its pan-subtype function in existing literature. It was verified that knockdown of PVT1 could inhibit cell proliferation in both luminal and basal-like BC, partly through activating the Hippo signaling pathway. Hippo pathway was first discovered in Drosophila melanogaster, and its major members are highly conserved among different species[34]. In mammals, the core part of Hippo signaling pathway is a kinase cascade composed of mammalian Ste20-like kinases 1/2 (MST1/2), LATS1/2 and YAP/TAZ[34, 45]. When Hippo kinase cascade is triggered by different intracellular and extracellular signaling factors, the activated MST1/2 phosphorylates LATS1/2 by reacting with salvador homolog 1 (SAV1). Then activated LATS1/2 binds to MOB1 and further phosphorylates downstream effector molecule YAP/TAZ. Phosphorylated YAP/TAZ retain in the cytoplasm, and are subsequently degraded by the ubiquitin proteasome pathway. Otherwise, when Hippo signaling pathway is inhibited, the dephosphorylated YAP/TAZ can enter the nucleus and combine with TEA domain transcription factors to initiate the expression of downstream target genes. Thus, biological behaviors such as cell proliferation, survival, migration, stemness and differentiation are affected[34, 55]. An increasing body of evidence indicates that dysregulation of Hippo signaling pathway contributes to the occurrence of cancer. For example, a decreased expression of LATS1 or LATS2 mRNA is significantly associated with a large tumor size, high lymph node metastasis, and estrogen receptor and progesterone receptor negativity[56]. High expression or nuclear aggregation of YAP/TAZ has been identified in breast cancer, liver cancer, lung cancer, ovarian cancer and other cancers[39, 57]. In addition, loss of YAP potently suppresses oncogene-induced mammary tumors[58]. Since the overall mutation frequency of Hippo pathway was relatively low, and the abnormal activation of YAP/TAZ in most cancers is not linked to mutations within these genes[38], it implies that epigenetic aberrations, such as changes in the expression levels of pathway components, might play a larger role in the dysregulation of Hippo pathway in cancers. Here, PVT1 was found to regulate Hippo pathway through LATS2, the mRNA stability of which was enhanced after PVT1 knockdown. However, the precise mechanism by which PVT1 regulates mRNA stability remains unclear. According to existing studies, lncRNAs regulate mRNA stability through multipronged mechanisms: (1) Recruiting RNA-binding proteins to target mRNAs to form protective or destabilizing complexes[59]; (2) Sponging miRNAs through complementary base-pairing, preventing miRNA-mediated mRNA decay[60]; (3) Forming duplexes with mRNAs to mask destabilizing elements[61]; (4) Regulating ubiquitination enzymes to stabilize/ destabilize RNA-binding effectors, which in turn affects target transcripts[62]. Although some studies have reported that PVT1 regulates mRNA stability, these findings have predominantly been linked to its function as a competing endogenous RNA (ceRNA) through miRNA interactions, while other mechanisms remain unreported[51, 52, 54]. Moreover, PVT1 knockdown resulted in an increase rather than a decrease in LATS2 expression, suggesting that the regulation occurs through a mechanism independent of miRNA sponging. Therefore, future research would focus on identifying RNA-binding proteins that interact with PVT1, and advanced techniques such as RNA pull down and RNA immunoprecipitation could provide valuable insights into this regulatory mechanism. Although this study offers some insights, several limitations should be acknowledged. First, the number of basal-like BC samples available for analysis in the TCGA database is relatively small, and the number of cases with advanced clinical stages is even more limited. This may have contributed to the lack of statistically significant associations between PVT1 expression and clinical parameters, including overall survival, in the basal-like subtype. Moreover, due to the even smaller sample size of HER2-overexpressing BC, this subtype was not included in our analysis, preventing us from drawing a definitive conclusion regarding the pan-subtype oncogenic role of PVT1. Notably, previous studies have provided encouraging evidence supporting the potential role of PVT1 in HER2-overexpressing BC. The PVT1 gene is located at chromosomal 8q24, a well-established hotspot for genetic abnormalities in BC, with amplification detected across all subtypes[20]. In another study by Tseng et al.[49], increased copy number of PVT1 was observed in 62% of HER2-positive BC samples, suggesting that PVT1 may also be upregulated and play an oncogenic role in this subtype. Second, the functional experiments were conducted in only one luminal and one basal-like BC cell line, which may not fully represent the heterogeneity of these subtypes. Expanding the number of cell models would strengthen the robustness of our conclusions. Nevertheless, it is worth noting that previous studies have consistently demonstrated the oncogenic role of PVT1 in both ER-positive and triple-negative BC across multiple cell lines, which strongly supports the generalizability of our findings. Furthermore, in vivo validation using BC xenograft models in nude mice or genetically engineered mouse models is also warranted, to assess the effects of PVT1 knockdown on tumor growth and Hippo pathway activation. Third, while we observed high PVT1 expression in luminal and basal-like BC using TCGA data, we have yet to validate these findings in clinical tissue samples. Future studies will focus on confirming the expression pattern of PVT1 and its relationship with the LATS2/Hippo pathway in clinical specimens, as well as extending our investigation to HER2-overexpressing BC. Finally, given the critical clinical challenge posed by therapeutic resistance in BC, it will be important to explore whether PVT1 also plays a role in BC drug resistance. Establishing drug-resistant BC cell lines or employing existing resistant models could help determine whether PVT1 contributes to this process. Additionally, further functional studies are needed to expand our understanding of PVT1’s regulatory roles beyond proliferation. Emerging studies have implicated PVT1 in regulating cancer stemness and shaping tumor immune in other cancers[63, 64]. These insights prompt further functional investigations to explore whether PVT1 exerts similar regulatory roles in BC, which may ultimately broaden its translational relevance. In summary, PVT1 exhibits remarkable potential as a pan-subtype oncogenic lncRNA in BC, and holds promise as a therapeutic target, particularly in patients with dysregulated Hippo signaling. Advances in RNA-based technologies, including antisense oligonucleotides (ASOs), RNA interference, and CRISPR/Cas9 genome editing, have provided feasible strategies for targeting lncRNAs [65]. Notably, nanoparticle-based delivery systems are rapidly improving the specificity and efficacy of such therapies[66]. These developments offer encouraging prospects for the clinical translation of PVT1-targeted interventions, though further rigorous studies and clinical trials are needed to validate it. Statements & Declarations Funding This study was supported by the Zhejiang Provincial Medical and Health Science and Technology Plan (No. 2024KY225) and the National Natural Science Foundation of China (No. 81673516 and No. 82003870). Competing Interests The authors have no relevant financial or non-financial interests to disclose. Author Contributions This study was designed and supervised by Guo Wang. Material preparation was performed by Ying Zeng. Data collection and analysis were performed by Hai-Bo Zhang. The first draft of the manuscript was written by Hai-Bo Zhang and all authors commented on previous versions of the manuscript. All authors read and approved the final manuscript. 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Supplementary Files rawblotsimages.pdf supplementaryfigures.doc supplementarytables.docx Cite Share Download PDF Status: Published Journal Publication published 19 Jul, 2025 Read the published version in World Journal of Surgical Oncology → Version 1 posted Editorial decision: Revision requested 04 May, 2025 Reviews received at journal 04 May, 2025 Reviewers agreed at journal 04 May, 2025 Reviews received at journal 16 Apr, 2025 Reviews received at journal 09 Apr, 2025 Reviewers agreed at journal 09 Apr, 2025 Reviewers agreed at journal 08 Apr, 2025 Reviewers invited by journal 08 Apr, 2025 Submission checks completed at journal 07 Apr, 2025 First submitted to journal 06 Apr, 2025 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-5745151","acceptedTermsAndConditions":true,"allowDirectSubmit":false,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":440188636,"identity":"c3bcfcaa-15a8-4b51-b6e4-176e17b10bf7","order_by":0,"name":"Hai-Bo Zhang","email":"","orcid":"","institution":"Hangzhou Women’s Hospital (Hangzhou Maternity and Child Health Care Hospital)","correspondingAuthor":false,"prefix":"","firstName":"Hai-Bo","middleName":"","lastName":"Zhang","suffix":""},{"id":440188637,"identity":"23178317-1a94-4364-8776-78d3ef362185","order_by":1,"name":"Ying Zeng","email":"","orcid":"","institution":"The Affiliated Changsha Central Hospital, University of South China","correspondingAuthor":false,"prefix":"","firstName":"Ying","middleName":"","lastName":"Zeng","suffix":""},{"id":440188639,"identity":"1d2a57c4-f9bc-47ef-bbad-a2a6c9c1c5a7","order_by":2,"name":"Guo Wang","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAAA0klEQVRIie3PMQrCMBSA4ZRAXCKuKQ65QkIHl6JXeVLwCOJYENLFA2TQO3R1iwidSl0FF7srxFkQFRcXSbo55Nse5Oe9IBQEf2iAB9bYRfqZqE8SF7lsdT3rkIjaJElf7Tsk6AizWJMD5xqi81UhPnIVkYaKWXqS5RGw3Cgkt7kjwWyqYs1OIBiQYV8hEMaREJaRIRUNvA7r3b0SSiucUDDw+hTBXgnrraJWm0yWdbuM1w2TpSuZ7Ckyt8eY8yLb2cs85c4tX6L8vdX/fRAEQfDbE90KP8e3AdvbAAAAAElFTkSuQmCC","orcid":"","institution":"Xiangya Hospital Central South University","correspondingAuthor":true,"prefix":"","firstName":"Guo","middleName":"","lastName":"Wang","suffix":""}],"badges":[],"createdAt":"2025-01-01 07:53:12","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-5745151/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-5745151/v1","draftVersion":[],"editorialEvents":[{"content":"https://doi.org/10.1186/s12957-025-03944-6","type":"published","date":"2025-07-19T15:57:17+00:00"}],"editorialNote":"","failedWorkflow":false,"files":[{"id":80224478,"identity":"d53d5a29-9a0d-442f-af79-1b49998a92e7","added_by":"auto","created_at":"2025-04-09 11:27:44","extension":"png","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":4175742,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eRelative expression and prognosis significance of PVT1 in luminal and basal-like breast cancer subtypes. \u003c/strong\u003e(A-B) Relative expression of PVT1 in cancer and paracancerous tissues of luminal (A) and basal-like (B) breast cancer subtypes from TCGA. (C-D) Relative expression of PVT1 in paired cancer and paracancerous tissues of luminal (C) and basal-like (D) breast cancer subtypes from TCGA. (E-F) Relative expression of PVT1 in paracancerous tissues and cancer tissues with different TNM stages in luminal (E) and basal-like (F) breast cancer subtypes from TCGA. (G-H) Relative expression of PVT1 in paracancerous tissues and cancer tissues with different T stages in luminal (G) and basal-like (H) breast cancer subtypes from TCGA. (I-J) Relative expression of PVT1 in paracancerous tissues and cancer tissues with different N stages in luminal (I) and basal-like (J) breast cancer subtypes from TCGA. (K-L) Relative expression of PVT1 in paracancerous tissues and cancer tissues with different M stages in luminal (K) and basal-like (L) breast cancer subtypes from TCGA. (M-O) The overall survival curves for breast cancer patients of luminal (M), basal-like (N) and combined subtypes (O) in the TCGA cohort, grouped by the median expression level of PVT1 as the cut-off value. T, tumor; N, lymph node; M, metastasis; PT, paracancerous tissue; CT, cancerous tissue. *\u003cem\u003eP\u003c/em\u003e \u0026lt; 0.05; **\u003cem\u003eP\u003c/em\u003e \u0026lt; 0.01; ***\u003cem\u003eP\u003c/em\u003e \u0026lt; 0.001.\u003c/p\u003e","description":"","filename":"1.png","url":"https://assets-eu.researchsquare.com/files/rs-5745151/v1/876b008b318d49ae2a5ff25b.png"},{"id":80224480,"identity":"6055a5c1-666e-4039-aeff-344efd6ea48e","added_by":"auto","created_at":"2025-04-09 11:27:44","extension":"png","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":11304624,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eEffect of PVT1 knockdown on proliferation in luminal and basal-like breast cancer cells . \u003c/strong\u003e(A) Relative expression of PVT1 in the normal mammary epithelial cell and breast cancer cell lines. (B)Relative expression of PVT1after targeting it using three siRNAs; (C) Relative cell viability of MCF7 and BT549 cells after 48 h and 72 h of PVT1 knockdown measured using the MTS assay. (D) Representative images of cell clones and statistical histograms of clone number of MCF7 and BT549 cells after PVT1 knockdown in the plate clone formation assay.(E) Representative images of Hoechst 33342 or Apollo dyed cells and statistical histograms of the ratio of EdU positive cells in MCF7 and BT549 cells after 48 h of PVT1 knockdown in the EdU assay. (F) Representative images of cell cycle obtained from the flow cytometer and the statistical histograms of relative percentage of each cell cycle phase in MCF7 and BT549 cells after 48 h of PVT1 knockdown. NC, negative control; *\u003cem\u003eP\u003c/em\u003e \u0026lt; 0.05; **\u003cem\u003eP\u003c/em\u003e \u0026lt; 0.01; ***\u003cem\u003eP\u003c/em\u003e \u0026lt; 0.001.\u003c/p\u003e","description":"","filename":"2.png","url":"https://assets-eu.researchsquare.com/files/rs-5745151/v1/20b4cfda1a1b17f5fe896a6b.png"},{"id":80224506,"identity":"bd2afe3a-3280-4215-b34f-94c072d19b77","added_by":"auto","created_at":"2025-04-09 11:27:47","extension":"png","order_by":3,"title":"Figure 3","display":"","copyAsset":false,"role":"figure","size":2695630,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eEnrichment analysis of differentially expressed genes in MCF7 cells after PVT1 knockdown. \u003c/strong\u003e(A) The volcano plot of differentially expressed genes. Red dots: up-regulated lncRNAs; Blue dots: down-regulated lncRNAs; Black dots: lncRNAs not meeting the significance threshold. (B-D) Top 15 items with the most significant \u003cem\u003eP\u003c/em\u003e values in GO analysis: (B) Biological process; (C) Cellular component; (D) Molecular function. (E) Top 15 signaling pathways with the most significant \u003cem\u003eP\u003c/em\u003e values in KEGG analysis.\u003c/p\u003e","description":"","filename":"3.png","url":"https://assets-eu.researchsquare.com/files/rs-5745151/v1/1526dee0e03a799d7acfc5b9.png"},{"id":80224495,"identity":"3776d2b7-31c9-438b-afaf-5b245ac72fac","added_by":"auto","created_at":"2025-04-09 11:27:45","extension":"png","order_by":4,"title":"Figure 4","display":"","copyAsset":false,"role":"figure","size":8980118,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003ePVT1 knockdown activated the Hippo signaling pathway. \u003c/strong\u003e(A) Representative western blot images of total and phosphorylated protein level of YAP/TAZ in MCF7 and BT549 cells after 48 h of PVT1 knockdown. (B) Representative immunofluorescence images of YAP protein (red) and cell nucleus (blue) acquired by confocal microscopy in MCF7 and BT549 cells after 48 h of PVT1 knockdown. The relative fluorescence intensity in the nucleus versus the cytoplasm was evaluated. (C) Relative mRNA expression of downstream genes of Hippo pathway after 48 h of PVT1 knockdown. * \u003cem\u003eP\u003c/em\u003e \u0026lt; 0.05; **\u003cem\u003eP\u003c/em\u003e \u0026lt; 0.01; NS, not significant.\u003c/p\u003e","description":"","filename":"4.png","url":"https://assets-eu.researchsquare.com/files/rs-5745151/v1/35ce3b036d7df11495d45db6.png"},{"id":80224483,"identity":"5f186978-e16a-44a1-983f-b05eb9653422","added_by":"auto","created_at":"2025-04-09 11:27:44","extension":"png","order_by":5,"title":"Figure 5","display":"","copyAsset":false,"role":"figure","size":1299737,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eLATS2 up-regulation mediated the activation of Hippo pathway. \u003c/strong\u003e(A) Relative expression of LATS2 mRNA in MCF7 and BT549 cells after 48 h of PVT1 knockdown. (B) Representative western blot images of LATS2 protein in MCF7 and BT549 cells after 48 h of PVT1 knockdown. (C) Representative western blot images of LATS2, YAP and P-YAP in MCF7 and BT549 cells after knocking down PVT1 or/and LATS2. (D) Relative expression of LATS2 mRNA in MCF7 and BT549 cells pretreated with DMSO (1‰) or 2 µM actinomycin D followed by 48 h of PVT1 knockdown. (E) After 48 h of PVT1 knockdown, MCF7 and BT549 cells were treated with 2 µM actinomycin D for 0, 1, 2, 4, 8, 16 and 24 h, respectively. Relative LATS2 mRNA expression was detected at different time points. Act D, actinomycin D; *\u003cem\u003eP\u003c/em\u003e \u0026lt; 0.05; **\u003cem\u003eP\u003c/em\u003e\u0026lt; 0.01.\u003c/p\u003e","description":"","filename":"5.png","url":"https://assets-eu.researchsquare.com/files/rs-5745151/v1/281a030d225077dc3f756995.png"},{"id":80224484,"identity":"3368666b-e475-4817-bdf4-573567e37dcc","added_by":"auto","created_at":"2025-04-09 11:27:44","extension":"png","order_by":6,"title":"Figure 6","display":"","copyAsset":false,"role":"figure","size":1746105,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eLATS2 up-regulation partly mediated the inhibitory effect of PVT1 knockdown on breast cancer cell proliferation. \u003c/strong\u003e(A) Relative cell viability of MCF7 and BT549 cells after knocking down PVT1 or/and LATS2 measured using the MTS assay. (B) Representative images of cell clones and statistical histograms of clone number of MCF7 and BT549 cells after knocking down PVT1 or/and LATS2 in the plate clone formation assay. *\u003cem\u003eP\u003c/em\u003e \u0026lt; 0.05; **\u003cem\u003eP\u003c/em\u003e \u0026lt; 0.01; ***\u003cem\u003eP\u003c/em\u003e\u0026lt; 0.001.\u003c/p\u003e","description":"","filename":"6.png","url":"https://assets-eu.researchsquare.com/files/rs-5745151/v1/429c142fcef520330e01c868.png"},{"id":88506063,"identity":"746ecbcd-c90f-4a8a-b2ed-af1045113c60","added_by":"auto","created_at":"2025-08-07 07:30:14","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":31747784,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-5745151/v1/fe5c31e0-e1a4-4daf-b10d-d7524fae0f4f.pdf"},{"id":80224482,"identity":"e6ff3566-7521-4334-94c5-fa91a07ffa74","added_by":"auto","created_at":"2025-04-09 11:27:44","extension":"pdf","order_by":1,"title":"","display":"","copyAsset":false,"role":"supplement","size":275526,"visible":true,"origin":"","legend":"","description":"","filename":"rawblotsimages.pdf","url":"https://assets-eu.researchsquare.com/files/rs-5745151/v1/366607197325d05cafe68aec.pdf"},{"id":80224507,"identity":"0223b23c-1124-4582-9579-eb914db12d70","added_by":"auto","created_at":"2025-04-09 11:27:48","extension":"doc","order_by":2,"title":"","display":"","copyAsset":false,"role":"supplement","size":965120,"visible":true,"origin":"","legend":"","description":"","filename":"supplementaryfigures.doc","url":"https://assets-eu.researchsquare.com/files/rs-5745151/v1/86f41021827d21e8bc1f561a.doc"},{"id":80225097,"identity":"22ba7735-e71b-4864-9dd3-349cb9fe4800","added_by":"auto","created_at":"2025-04-09 11:35:44","extension":"docx","order_by":3,"title":"","display":"","copyAsset":false,"role":"supplement","size":31484,"visible":true,"origin":"","legend":"","description":"","filename":"supplementarytables.docx","url":"https://assets-eu.researchsquare.com/files/rs-5745151/v1/f132d1b3a259fca58c5226cb.docx"}],"financialInterests":"No competing interests reported.","formattedTitle":"Knockdown of PVT1 inhibits cell proliferation in luminal and basal-like breast cancer subtypes by activating LATS2/Hippo signaling pathway","fulltext":[{"header":"Introduction","content":"\u003cp\u003eBreast cancer (BC) is the most frequent malignant tumor in women. According to the International Agency for Research on Cancer (IARC), there were an estimated 2.3\u0026nbsp;million new BC cases in 2022 worldwide, accounting for 11.6% of all newly diagnosed cancer cases[\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e]. BC also remains the leading cause of cancer-related deaths among women, with an estimated 665,684 deaths[\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e]. The incidence of breast cancer varies across regions, with higher rates observed in developed countries due to lifestyle factors, reproductive behaviors, and improved detection methods. However, mortality rates are disproportionately higher in low- and middle-income countries due to limited access to early diagnosis and treatment[\u003cspan additionalcitationids=\"CR3\" citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e]. With increasing global cancer burden, effective screening, early detection, and improved treatment strategies are critical for reducing breast cancer mortality[\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eBC is a highly heterogeneous disease with distinct molecular subtypes, clinical characteristics, and therapeutic responses. Based on the expression level of estrogen receptor (ER), progesterone receptor (PR), human epidermal growth factor 2 (HER2) and Ki67, BC can be divided into four molecular subtypes: luminal A, luminal B, HER2-overexpressing and basal-like type[\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e]. The luminal subtypes are characterized by positive expression of ER and/or PR, accounting for approximately 65% of all BC cases[\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e]. Endocrine therapy targeting the estrogen signaling pathway is the primary treatment for these subtypes[\u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e]. HER2-overexpressing subtype represents 15%-20% of all cases with HER2 being used as the major therapeutic target[\u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e]. Although basal-like subtype only accounts for 10%-15% of total BC cases, it is highly invasive and lacks effective treatment targets, leading to the worst prognosis[\u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eThe application of targeted therapies has significantly improved the overall treatment outcomes in luminal and HER2-overexpressing BC patients[\u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e, \u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e]. However, the presence of primary and acquired resistance has become a critical challenge limiting further breakthroughs in therapeutic efficacy. For example, up to 41% of ER-positive BC patients, who had undergone 5 years of endocrine therapy and achieved clinical cure, developed distant recurrence within 15 years[\u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e]. Once drug resistance occurs, treatment relies more heavily on chemotherapy, but the efficacy at this stage becomes unoptimistic[\u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e]. Therefore, to enhance initial treatment responses, delay the onset of drug resistance, and ultimately improve clinical outcomes, identifying new combined therapy targets remains an urgent research focus for luminal and HER2-overexpressing BC. For basal-like BC, which lacks specific therapeutic targets, the treatment options are still limited. Thus, identifying suitable molecular drug targets for this subtype is of particularly significant practical importance.\u003c/p\u003e \u003cp\u003eCurrently, several combination strategies of targeted therapies have been successfully applied in clinical BC treatment. For example, the PIK3CA inhibitor Alpelisib was approved by FDA for \u003cem\u003ePIK3CA\u003c/em\u003e-mutated, hormone receptor-positive advanced BC in combination with fulvestrant in 2019, significantly prolonging patients\u0026rsquo; progression-free survival[\u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e]. The combination of PIK3CA inhibitors and HER2 monoclonal antibodies also showed synergistic anti-tumor activity, and had been investigated in several clinical trials targeting HER2-positive BC[\u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e, \u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e]. Cyclin-dependent kinases 4 and 6 (CDK4/6) inhibitors combined with endocrine therapy have been approved for some luminal BC patients to improve their prognosis [\u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e]. Patient-derived tumor xenograft model studies further demonstrate that CDK4/6 inhibitors can sensitize tumors to HER2-targeted therapy and delay recurrence, indicating great potential for combined use in HER2-overexpressing BC[\u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eIt is worth noting that both \u003cem\u003ePIK3CA\u003c/em\u003e and \u003cem\u003eCDK4\u003c/em\u003e/\u003cem\u003e6\u003c/em\u003e are foundational genes determining cell growth[\u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e18\u003c/span\u003e, \u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e19\u003c/span\u003e], as indirectly evidenced by their abnormal activity or expression across different BC subtypes[\u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e20\u003c/span\u003e]. To be specific, \u003cem\u003ePIK3CA\u003c/em\u003e is the most frequently mutated gene in BC, with a mutation rate of 49%, 32%, 42% and 7% for luminal A, luminal B, HER2 and basal-like subtype respectively, while copy number amplification of \u003cem\u003eCDK4\u003c/em\u003e was observed in 14% of luminal A subtype, 25% of luminal B subtype, and 24% of HER2-overexpressing subtype[\u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e20\u003c/span\u003e]. Thus, it is suggested that identifying such \"pan-subtype\" dysregulated molecules is still an effective strategy for screening critical oncogenes and potential drug targets. Considering the relatively comprehensive exploration of protein-coding molecules like PIK3CA and CDK4/6, the next issue is whether there are other types of molecules in BC that show abnormal expression or activity across multiple subtypes, and play a pivotal role in basic cellular activities, thus representing promising candidates for the development of novel targets for combination therapy.\u003c/p\u003e \u003cp\u003eLong non-coding RNAs (lncRNAs) are a class of non-coding RNAs with transcript lengths exceeding 200 nucleotides, which were long considered \u0026ldquo;transcriptional noise\u0026rdquo; of the genome[\u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e21\u003c/span\u003e]. However, increasing studies have revealed their extensive involvement in gene expression regulation and close association with the development and progression of various human diseases, including cancer[\u003cspan additionalcitationids=\"CR23\" citationid=\"CR22\" class=\"CitationRef\"\u003e22\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e24\u003c/span\u003e]. Therefore, identifying pan-subtype lncRNAs and elucidating their roles and mechanisms may not only help deepen our insights into BC pathogenesis but also enrich the pool of candidate targets for combination therapies.\u003c/p\u003e \u003cp\u003eGenome-wide molecular profiling techniques (such as next-generation sequencing and microarray analyses) have proven highly effective in identifying critical molecular alterations during cancer development and progression, significantly advancing the discovery of key biomarkers or therapeutic targets[\u003cspan additionalcitationids=\"CR26\" citationid=\"CR25\" class=\"CitationRef\"\u003e25\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e27\u003c/span\u003e]. The Cancer Genome Atlas (TCGA) is a landmark cancer genomics program integrating multi-omics data in over 30 types of human cancers[\u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e28\u003c/span\u003e]. Using TCGA clinical and sequencing data, we performed differential gene expression analysis and correlation analysis between gene expression and clinicopathological features in different BC subtypes, identifying lncRNA plasmacytoma variant translocation 1 (PVT1) as a significant candidate involved in both luminal and basal-like BC. PVT1 has been identified as an oncogenic factor in various cancers including BC, which plays a crucial role in tumor progression by promoting cell proliferation, invasion, and resistance to apoptosis[\u003cspan additionalcitationids=\"CR30 CR31 CR32\" citationid=\"CR29\" class=\"CitationRef\"\u003e29\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR33\" class=\"CitationRef\"\u003e33\u003c/span\u003e]. However, the precise mechanisms underlying PVT1\u0026rsquo;s oncogenic functions in BC have yet to be fully elucidated. We proved that PVT1 enhances BC cell proliferation, at least in part, by modulating the LATS2/Hippo pathway\u0026mdash;a critical signaling cascade that regulates cell proliferation, apoptosis, and organ size by controlling the activity of YAP/TAZ transcriptional coactivators[\u003cspan citationid=\"CR34\" class=\"CitationRef\"\u003e34\u003c/span\u003e]. The findings of our study provide new insights into the role of PVT1 across different BC subtypes and may contribute to the development of PVT1-based therapeutic strategies.\u003c/p\u003e"},{"header":"Materials and methods","content":"\u003cdiv id=\"Sec3\" class=\"Section2\"\u003e \u003ch2\u003eBioinformatical analysis\u003c/h2\u003e \u003cp\u003eRNA-seq data of BC cohort and the clinical profiles with subtype information were downloaded from TCGA data portal (\u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://tcga-data.nci.nih.gov/tcga/\u003c/span\u003e\u003cspan address=\"https://tcga-data.nci.nih.gov/tcga/\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e) and the cBioPortal for Cancer Genomics (\u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttp://cbioportal.org\u003c/span\u003e\u003cspan address=\"http://cbioportal.org\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e), respectively. Information of lncRNA gene annotation were obtained from the Ensembl database (\u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttp://ensemblgenomes.org/\u003c/span\u003e\u003cspan address=\"http://ensemblgenomes.org/\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e). The differential analysis was conducted between BC tissues and non-cancerous tissues in the same subtype using the R package of \u0026ldquo;edgeR\u0026rdquo;, and lncRNAs with |log2 (fold change)| \u0026gt; 1 and \u003cem\u003eP\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.05 were considered to be differentially expressed. Next, these lncRNAs were divided into high-expression and low-expression groups based on their median expression values. BC patients were classified into a low-stage group (stages I and II) and a high-stage group (stages III and IV) according to their TNM stages. The association between lncRNA expression levels and TNM stages was assessed by the chi-square test using the \"MASS\" R package. A significance level of \u003cem\u003eP\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.05 was used as the screening criterion to identify lncRNAs closely associated with BC TNM stages. GEPIA 2 (Gene Expression Profiling Interactive Analysis 2, \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttp://gepia2.cancer-pku.cn/\u003c/span\u003e\u003cspan address=\"http://gepia2.cancer-pku.cn/\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e) is an online tool for TCGA data analysis and visualization, suitable for gene expression and survival analysis [\u003cspan citationid=\"CR35\" class=\"CitationRef\"\u003e35\u003c/span\u003e]. In this study, it was used to analyze the correlation between PVT1 expression levels and overall survival prognosis in BC patients.\u003c/p\u003e \u003c/div\u003e\n\u003ch3\u003eCell culture\u003c/h3\u003e\n\u003cp\u003eThe human BC cell lines MCF7, T47D, MDA-MB-231 and BT549 were purchased from American Type Culture Collection (ATCC) (Manassas, VA, USA). Cells were cultured in RPMI-1640 culture medium (Gibco, Grand Island, NY, USA) supplemented with 10% fetal bovine serum, 2 mM L-glutamine, 100 u/ml of penicillin and 1 mg/ml of streptomycin (Biological Industries, Cromwell, CT, USA). All cells were maintained in a humidified incubator with 5% CO\u003csub\u003e2\u003c/sub\u003e at 37\u0026deg;C with the medium changed every 2 days.\u003c/p\u003e\n\u003ch3\u003eTransfection of small interfering RNA (siRNA)\u003c/h3\u003e\n\u003cp\u003eThe siRNAs and negative control (NC) were obtained from GenePharma (Shanghai, China). Briefly, after MCF7 and BT549 cells were seeded in plates and cultured for 24 h, the cells were transfected with 50 nM single siRNA, NC or combined mix using RNAiMAX reagents (Invitrogen, Carlsbad, CA, USA) following the manufacturer's instruction. The siRNA sequences were as follows: PVT1-si1, 5\u0026rsquo;-CCC AAC AGG AGG ACA GCU UTT-3\u0026rsquo;, PVT1-si2, 5\u0026rsquo;-GCU UGG AGG CUG AGG AGU UTT-3\u0026rsquo;, LATS2-si, 5\u0026rsquo;-UAC CAU AAA UAC AAU CUU CTT-3\u0026rsquo;.\u003c/p\u003e\n\u003ch3\u003eCell viability assay\u003c/h3\u003e\n\u003cp\u003eCells were seeded into 96-well plates (3000 cells/well for MCF7 and 2000 cells/well for BT549) and cultured for 24 h. Then cells were transfected with single siRNA, NC or combined mix. After 48 or 72 h, cell viability was detected through MTS assay (CellTiter 96 AQueous One Solution Cell Proliferation Assay kit, Promega, Madison, WI, USA). The absorbance values were detected at 490 nm using a microplate reader.\u003c/p\u003e\n\u003ch3\u003ePlate clone formation assay\u003c/h3\u003e\n\u003cp\u003eCells were seeded into 12-well plates at a density of 500 cells per well, cultured for 24 h and then treated with single siRNA, NC or combined mix. A week later, when most clones contained\u0026thinsp;\u0026gt;\u0026thinsp;50 cells, they were fixed with 4% paraformaldehyde (Sigma-Aldrich, Louis, MO, USA) for 30 min and stained with 1% crystal violet for 30 min. After washing and air drying, the clone numbers were quantified by Image J software (Bethesda, MA, USA) or naked eyes.\u003c/p\u003e \u003cdiv id=\"Sec8\" class=\"Section2\"\u003e \u003ch2\u003eEdU assay\u003c/h2\u003e \u003cp\u003eDNA replication activity was detected using the Cell-Light EdU Apollo567 \u003cem\u003eIn Vitro\u003c/em\u003e Kit (RiboBio, Guangzhou, China) following the manufacturer\u0026rsquo;s instructions. In brief, cells were seeded into 96-well plates (3000 cells/well for MCF7 and 2000 cells/well for BT549), cultured for 24 h, and then transfected with siRNA or NC. After 48 h, cells were incubated with EdU for 2 h prior to fixation and staining. The ratio of EdU-incorporated cells was calculated to indicate the proliferation activity.\u003c/p\u003e \u003c/div\u003e\n\u003ch3\u003eFlow Cytometry\u003c/h3\u003e\n\u003cp\u003eCells were seeded into 6-well plates at a density of 1 \u0026times; 10\u003csup\u003e5\u003c/sup\u003e cells per well, cultured for 24 h and then treated with either siRNA or NC. For cell cycle analysis, cells were collected after 48 h and fixed in 70% ethanol overnight. Then, the cells were washed with precooled PBS and incubated with a freshly prepared PI staining solution (Beyotime Biotechnology, Shanghai, China) for 30 min at 37\u0026deg;C. The cells were then kept on ice in shade until detection on a FACScan cytometer (BD Biosciences, San Jose, CA, USA) following the manufacturer's guidelines. For cell apoptosis analysis, cells were collected after 72 h and stained with 5 \u0026micro;L Annexin V-FITC (Beyotime Biotechnology, Shanghai, China) and 10 \u0026micro;L PI solution for 10 min at room temperature. The cells were then kept on ice in shade until detection on the FACScan cytometer.\u003c/p\u003e\n\u003ch3\u003eRNA extraction and quantitative real-time PCR\u003c/h3\u003e\n\u003cp\u003eTotal RNA was isolated from tissues or harvested cells by using TRIzol reagent (Takara Bio Inc., Kusatsu, Japan) and concentration was determined using the Nanodrop 2000 spectrophotometer (Thermo Fisher Scientific, Waltham, MA, USA). The quality of the RNA was assessed by electrophoresis on a non-denaturing agarose gel. One microgram of total RNA was reversely transcribed using the PrimeScriptTM RT reagent Kit (Takara Bio Inc., Kusatsu, Japan) in a 20 \u0026micro;L reaction system. The reaction products were then diluted to a total volume of 100 \u0026micro;L with distilled water. The real-time PCR reaction consisted of 2 \u0026micro;L of diluted reverse transcription product, 1\u0026times;SYBR\u0026reg; Premix DimerEraser (Takara Bio Inc., Kusatsu, Japan) and 0.3 \u0026micro;M forward and reverse primers. Beta-actin was used as an endogenous control. The sequences of primers were listed in Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e. Real-time PCR conditions were as follows: 95\u0026deg;C for 10 min, followed by 45 cycles at 95\u0026deg;C for 15 s and 60\u0026deg;C for 1 min. Fold induction values were calculated using the 2\u003csup\u003e\u0026minus;ΔΔCt\u003c/sup\u003e method.\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab1\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 1\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003ePrimer sequences of genes for quantitative real-time PCR\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"3\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eGene symbol\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eForward primer (5\u0026rsquo;-3\u0026rsquo;)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eReverse primer (5\u0026rsquo;-3\u0026rsquo;)\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePVT1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eTGAGAACTGTCCTTACGTGACC\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eAGAGCACCAAGACTGGCTCT\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eLATS2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eTAGAGCAGAGGGCGCGGAAG\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eCCAACACTCCACCAGTCACAGA\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eCYR61\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eGCTGCGGCTGCTGTAAGGTC\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eGGCGCCGAAGTTGCATTCCA\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAXL\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eAACCAGGACGACTCCATCC\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eAGCTCTGACCTCGTGCAGAT\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eCCND1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eCAGATCATCCGCAAACACGC\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eAAGTTGTTGGGGCTCCTCAG\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMYC\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eGTCAAGAGGCGAACACACAAC\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eTTGGACGGACAGGATGTATGC\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eβ-actin\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eTCAAGATCATTGCTCCTCCTGAG\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eACATCTGCTGGAAGGTGGACA\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cdiv id=\"Sec11\" class=\"Section2\"\u003e \u003ch2\u003eRNA sequencing\u003c/h2\u003e \u003cp\u003eMCF7 cells were seeded into 6-well plates at a density of 1 \u0026times; 10\u003csup\u003e5\u003c/sup\u003e cells per well, cultured for 24 h, and then transfected with either PVT1 siRNA or NC. After 48 h of transfection, total cellular RNA was obtained for sequencing by Novogene (Beijing, China) on the HiSeq 4000 Illumina platform. Genes with |log2 (fold change)| \u0026gt; 1 and \u003cem\u003eP\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.05 were considered to be differentially expressed.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec12\" class=\"Section2\"\u003e \u003ch2\u003eEnrichment analysis\u003c/h2\u003e \u003cp\u003eTo figure out the biological function of PVT1, genes differentially regulated after PVT1 knockdown were submitted to the online DAVID website (\u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://david.ncifcrf.gov/\u003c/span\u003e\u003cspan address=\"https://david.ncifcrf.gov/\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e) for GO (Gene Ontology) analysis and KEGG (Kyoto Encyclopedia of Genes and Genomes) pathway analysis.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec13\" class=\"Section2\"\u003e \u003ch2\u003eWestern blot analysis\u003c/h2\u003e \u003cp\u003eTotal cellular proteins were extracted from the harvested cells using RIPA lysis buffer (Beyotime Institute of Biotechnology, Shanghai, China). The protein concentrations were determined using a BCA protein assay kit (Beyotime Institute of Biotechnology). Cellular proteins were separated on sodium dodecyl sulfate polyacrylamide gels and transferred to polyvinylidene fluoride membranes. Blots were incubated in blocking buffer (5% non-fat dry milk in Tris-buffered saline with 0.5% Tween (TBS-T)) at room temperature for 1 h. After washing with TBS-T, the blots were incubated with a specific antibody against YAP (Abcam Inc., Cambridge, MA, USA), TAZ (Santa Cruz Biotechnology, Inc., Dallas, Texas, USA), P-YAP, P-TAZ, LATS2 (Cell Signaling Technology Inc., Beverly, MA., USA), or β-actin (Sigma Chemical Co., St. Louis, MO, USA) overnight at 4\u0026deg;C. Following the incubation with a horseradish peroxidase-conjugated secondary antibody, the signal was detected using an ECL Western Blotting system (Promega, Madison WI, USA) and visualized using the Bio-Rad ChemiDocTM MP system. Subsequent quantification of western blot bands in each lane was conducted using the Image Lab software (Bio-Rad, Hercules, CA, USA).\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec14\" class=\"Section2\"\u003e \u003ch2\u003eImmunofluorescence analysis\u003c/h2\u003e \u003cp\u003eCells were seeded into confocal dishes at a density of 1 \u0026times; 10\u003csup\u003e5\u003c/sup\u003e cells per dish for MCF7 and 5 \u0026times; 10\u003csup\u003e4\u003c/sup\u003e cells per dish for BT549. Cells were fixed with 4% paraformaldehyde for 15 min at room temperature 48 h after transient transfection, and washed three times with PBS, followed by permeabilization with 0.3% Triton X-100 in PBS for 15 min. After fixation, cells were blocked with 500 \u0026micro;L 5% donkey serum for 40 min at room temperature, incubated with YAP or TAZ antibody (1:100) for 12 h at 4\u0026deg;C, and then incubated with Alexa Fluor\u0026reg; 488 goat anti-Mouse IgG or Alexa Fluor\u0026reg; 594 donkey anti-Rabbit IgG for 1 h in darkness at room temperature. Cells were then washed, incubated with antifade mounting medium containing 2-(4-Amidinophenyl)-6-indolecarbamidine dihydrochloride (DAPI) (Beyotime Biotechnology, Shanghai, China) for 10 min at room temperature, and washed three times. After the final washes, cells were visualized by a confocal laser microscope (Carl Zeiss, Jena, Germany). Photomicrographs were captured at 600 \u0026times; magnification, and merged using the ZEN software (Carl Zeiss).\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec15\" class=\"Section2\"\u003e \u003ch2\u003eStatistical analysis\u003c/h2\u003e \u003cp\u003eGraphPad Prism 7.0 and R software were used for plotting and statistical analysis. The experimental data were expressed as mean\u0026thinsp;\u0026plusmn;\u0026thinsp;standard error (SEM). For quantitative data that followed normal distribution and had homogeneity of variance, Student's T-test (two groups) or One-way ANOVA (multiple groups) were used to compare the differences between groups. For quantitative data not subject to normal distribution, differences between groups were compared using Mann-Whitney rank-sum test (two groups) or Kruskal-Wallis test (multiple groups). All statistical tests were two-tailed and \u003cem\u003eP\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.05 was considered statistically significant.\u003c/p\u003e \u003c/div\u003e"},{"header":"Results","content":"\u003cp\u003e \u003cb\u003ePVT1 was abnormally overexpressed in luminal and basal-like BC tissues.\u003c/b\u003e \u003c/p\u003e \u003cp\u003eIn the TCGA cohort, 683, 169 and 78 patients were classified into luminal, basal-like and HER2 subtypes, respectively. The number of corresponding paracancerous tissue samples were 79, 15 and 9 in turn. Considering the importance of sample size in statistical analysis, the HER2 subtype was excluded in the subsequent study. The clinical information of luminal and basal-like BC patients was shown in Supplementary Table\u0026nbsp;1. All patients in these two remaining subtypes were included for the differential expression analysis. Ultimately, A total of 2,947 differentially expressed lncRNAs were identified in the luminal subtype (1,724 upregulated, 1,223 downregulated) and 3,176 in the basal-like subtype (2,046 upregulated, 1,130 downregulated). Intersection analysis showed that 717 lncRNAs were upregulated and 533 downregulated in both subtypes (Supplementary Fig.\u0026nbsp;1). The full list of these lncRNAs was provided in Supplementary Table\u0026nbsp;2.\u003c/p\u003e \u003cp\u003eTNM stage is an important clinical indicator of tumor progression. In order to further identify lncRNAs involved in the development of BC, the association between expression levels of the differentially expressed lncRNAs and TNM stages was assessed by the chi-square test. There were 132 and 60 lncRNAs found to be associated with TNM stages in the luminal and basal-like subtype, respectively, and the complete list of lncRNAs is provided in Supplementary Table\u0026nbsp;3. Unfortunately, no lncRNAs were found to be correlated with TNM stages in both subtypes.\u003c/p\u003e \u003cp\u003eAmong the candidate lncRNAs, PVT1 attracted our attention, which was abnormally up-regulated in both subtypes and significantly correlated with TNM stage. Based on the normalized PVT1 expression values obtained from previous differential analysis, its expression in cancer and adjacent non-cancerous tissues, as well as across different cancer T, N, and M stages, is further presented in detail in the two subtypes (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003eA-L). Consistent with previous results, PVT1 is upregulated in both luminal and basal-like subtypes, not only in all tumor samples (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003eA-B) but also in paired tumor samples (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003eC-D) compared to adjacent non-cancerous tissues. What\u0026rsquo;s more, its level in Stage III cancer tissues of luminal subtype is significantly than those in Stage I and Stage II tissues (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003eE). PVT1 is a widely known oncogene in various cancer types including BC[\u003cspan additionalcitationids=\"CR30 CR31 CR32\" citationid=\"CR29\" class=\"CitationRef\"\u003e29\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR33\" class=\"CitationRef\"\u003e33\u003c/span\u003e]. However, the underlying mechanisms by which PVT1 promotes BC is still not fully understood and few studies highlighted its role among different subtypes. Therefore, we focused on PVT1 in the subsequent study from the aspect of luminal and basal-like BC.\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003eFurther analysis using the GEPIA 2 website revealed that PVT1 showed marginal prognostic significance in luminal BC and no prognostic significance in basal-like BC. It was possibly due to the limitation of sample size, because when these two subtypes were combined, high PVT1 expression was found to be significantly associated with poorer overall survival prognosis (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003eM-O). Together, these findings indicated that PVT1 might be a key molecule mediating the tumorigenesis and development of the two BC subtypes, especially the luminal subtype.\u003c/p\u003e \u003cp\u003e \u003cb\u003eKnockdown of PVT1 significantly inhibited proliferation in luminal and basal-like BC cells.\u003c/b\u003e \u003c/p\u003e \u003cp\u003eBefore exploring the biological function of PVT1 in luminal and basal-like BC at the cellular level, PVT1 expression in several corresponding BC cell lines was detected. The results showed that the expression level of PVT1 in luminal cell lines (MCF7 and T47D) and basal-like cell lines (BT549 and MDA-MB-231) was significantly higher than that in the normal mammary epithelial cell line MCF10A (Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003eA), which was consistent with the result of bioinformatical analysis. MCF7 and BT549 were selected in the subsequent study, which represented the luminal and basal-like subtype respectively.\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003eAccelerated proliferation is a classical hallmark of tumor cells[\u003cspan citationid=\"CR36\" class=\"CitationRef\"\u003e36\u003c/span\u003e]. To explore the role of PVT1 in cell proliferation, three siRNAs were synthesized, and their knockdown efficiency was assessed. The two siRNAs with the highest knockdown efficiency were selected for subsequent studies (Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003eB). Then, MTS, clone formation EdU and flow cytometry assays were performed after PVT1 knockdown in MCF7 and BT549 cells. The results showed that PVT1 knockdown induced a significant decrease in cell viability, clone formation and DNA replication activity in both cell lines (Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003eC-E). Moreover, the cell cycle could be noticeably arrested at the G0/G1 phase (Figs.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003eF). Interestingly, PVT1 knockdown significantly increased apoptosis in BT549 cells, whereas MCF7 cells showed no notable apoptotic response (Supplementary Fig.\u0026nbsp;2). Together, it could be inferred that PVT1 functioned as a driving factor in the proliferation of luminal and basal-like cell lines.\u003c/p\u003e \u003cp\u003e \u003cb\u003eKnockdown of PVT1 induced the activation of Hippo signaling pathway.\u003c/b\u003e \u003c/p\u003e \u003cp\u003eIn order to reveal the underlying mechanism of proliferation inhibition induced by PVT1 knockdown, RNA sequencing was conducted in MCF7 cells. A total of 866 differentially expressed genes were identified between the PVT1-knockdown group and the control group, among which 565 genes were up-regulated and 301 genes were down-regulated (Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003eA). For these genes, GO analysis showed that they were mainly enriched in biological processes such as DNA replication initiation and G1/S transition of mitotic cell cycle (Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003eB-D). KEGG pathway analysis showed that they were mainly enriched in cell cycle, FoxO signaling pathway, p53 signaling pathway, Hippo signaling pathway and other classic signaling pathways related to cell growth (Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003eE).\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003eThe Hippo signaling pathway is a growth-suppressing kinase cascade which is highly conserved in evolution and controls organ size and tissue homeostasis by regulating cell proliferation, division, and death [\u003cspan citationid=\"CR37\" class=\"CitationRef\"\u003e37\u003c/span\u003e, \u003cspan citationid=\"CR38\" class=\"CitationRef\"\u003e38\u003c/span\u003e]. It also plays an important regulatory role in the occurrence and development of tumors[\u003cspan citationid=\"CR39\" class=\"CitationRef\"\u003e39\u003c/span\u003e]. Two homologous genes, Yes-associated protein (YAP) and transcriptional co-activator with PDZ-binding motif (TAZ), were key downstream effectors of Hippo pathway, whose activity was dynamically regulated by their phosphorylation state[\u003cspan citationid=\"CR38\" class=\"CitationRef\"\u003e38\u003c/span\u003e]. It was found here, after PVT1 knockdown, total protein level of YAP had little change, whereas phosphorylated YAP (P-YAP) was significantly increased (Fig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003eA). As for TAZ, no obvious change was observed in the expression level of either total or phosphorylated protein (Fig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003eA).\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003eYAP and TAZ are distributed in both cytoplasm and nucleus under a state of dynamic shuttle, and phosphorylation of them promotes the cytoplasmic localization by stimulating their association with 14-3-3 proteins [\u003cspan citationid=\"CR40\" class=\"CitationRef\"\u003e40\u003c/span\u003e, \u003cspan citationid=\"CR41\" class=\"CitationRef\"\u003e41\u003c/span\u003e]. In the immunofluorescence assay, the fluorescence intensity of YAP protein in the nucleus region of the PVT1-knockdown group was significantly lower than that of the control group, indicating a reduced entry of YAP into the nucleus (Fig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003eB). However, the fluorescence intensity distribution of TAZ protein remained largely unchanged, indicating that PVT1 knockdown did not significantly affect TAZ localization (Supplementary Fig.\u0026nbsp;3). Nuclear YAP/TAZ binds to TEA domain family transcription factors, initiating the expression of downstream genes, such as CYR61, MYC, AXL and CCND1[\u003cspan additionalcitationids=\"CR43\" citationid=\"CR42\" class=\"CitationRef\"\u003e42\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR44\" class=\"CitationRef\"\u003e44\u003c/span\u003e]. As expected, these genes were all downregulated when PVT1 was knocked down (Fig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003eC). Together, these results confirmed that knockdown of PVT1 in MCF7 and BT549 cells might activate the Hippo pathway, through specifically increasing the phosphorylation level of YAP.\u003c/p\u003e \u003cp\u003e \u003cb\u003eLATS2 up-regulation mediated the activation of Hippo signaling pathway.\u003c/b\u003e \u003c/p\u003e \u003cp\u003eLarge tumor suppressor 1/2 (LATS1/2), known as key upstream kinases of the pathway, can directly phosphorylate YAP through interaction with the cofactor Mps one binder 1 (MOB1)[\u003cspan citationid=\"CR45\" class=\"CitationRef\"\u003e45\u003c/span\u003e]. Therefore, we speculated whether the upregulation of P-YAP was mediated by LATS1/2. As expected, LATS2 expression was notably elevated after PVT1 knockdown at both mRNA and protein level (Fig.\u0026nbsp;\u003cspan refid=\"Fig5\" class=\"InternalRef\"\u003e5\u003c/span\u003eA-B). Moreover, the upregulation of P-YAP induced by PVT1 knockdown could be reversed by simultaneous knockdown of LATS2 (Fig.\u0026nbsp;\u003cspan refid=\"Fig5\" class=\"InternalRef\"\u003e5\u003c/span\u003eC), demonstrating that the activation of Hippo pathway was indeed mediated by LATS2 up-regulation.\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003eThen, the mechanism through which PVT1 influenced LATS2 expression was explored. Since both mRNA and protein level of LATS2 were up-regulated after PVT1 knockdown, we speculated that LATS2 expression was mainly regulated at the mRNA level. As shown in Fig.\u0026nbsp;\u003cspan refid=\"Fig5\" class=\"InternalRef\"\u003e5\u003c/span\u003eD, when cells were pretreated with the mRNA transcription inhibitor actinomycin D before PVT1 knockdown, the up-regulation of LATS2 mRNA level was not reversed. However, LATS2 mRNA was found to decrease more slowly in the knockdown group than in the control group (Fig.\u0026nbsp;\u003cspan refid=\"Fig5\" class=\"InternalRef\"\u003e5\u003c/span\u003eE). These results indicated that the up-regulation of LATS2 was not associated with its transcription, but due to the increased mRNA stability induced by PVT1 knockdown.\u003c/p\u003e \u003cp\u003e \u003cb\u003eLATS2 up-regulation partly mediated the inhibitory function of PVT1 knockdown on cell proliferation.\u003c/b\u003e \u003c/p\u003e \u003cp\u003eLastly, to examine whether LATS2/Hippo pathway mediated the proliferation-inhibitory function of PVT1 knockdown, a rescue experiment targeting LATS2 was conducted. Specifically, LATS2 was simultaneously interfered to block its upregulation induced by PVT1 knockdown. As shown in Fig.\u0026nbsp;\u003cspan refid=\"Fig6\" class=\"InternalRef\"\u003e6\u003c/span\u003e, single PVT1 knockdown notably inhibited cell viability and clone formation ability as before, while combined knockdown of LAST2 could partially rescue it, confirming that LATS2 up-regulation mediated the inhibitory effect of PVT1 knockdown on cell proliferation in luminal and basal-like BC.\u003c/p\u003e \u003cp\u003e \u003c/p\u003e"},{"header":"Discussion","content":"\u003cp\u003eIn this study, we attempted to identify potential lncRNAs for combined targeted therapy of BC by using RNA-seq and clinical data from TCGA. Our strategy was to search for shared differentially expressed lncRNAs from multiple BC subtypes, considering that such “pan-subtype” lncRNAs might have more powerful biological functions than subtype-specific lncRNAs. Due to the relatively limited sample number of HER2-overexpressing subtype, our analysis finally focused on luminal and basal-like BC. The former was the most common subtype clinically, while the latter was the subtype with the worst prognosis. Therefore, identification of lncRNAs associated with these two subtypes also fitted the clinical needs.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eDuring our screening, PVT1 was found to be significantly up-regulated in BC of both luminal and basal-like subtypes. In addition, high expression of PVT1 was significantly correlated with higher clinical stages in the luminal subtype and poorer overall survival, indicating its involvement in BC development. Actually, PVT1 has been widely reported in BC, which plays an oncogenic role[29, 46]. In triple negative BC, PVT1 affects cell proliferation and migration through maintaining MYC protein stability, repressing p21 expression and activating the KLF5/β-catenin signaling pathway[47-49]. In ER positive BC,\u0026nbsp;PVT1 acts as a key factor in the composition of ERα-PRC2 network, modulating cell proliferation, apoptosis, migration and response to hypoxia[50]. PVT1 also promotes BC cell proliferation and/or migration through sponging multiple miRNAs, such as miR-148a-3p, miR-128-3p, miR-543, and miR-145-5p[51-54]. Despite extensive studies, the full oncogenic mechanisms of PVT1 remain to be elucidated, especially considering the limited attention given to its pan-subtype function in existing literature.\u003c/p\u003e\n\u003cp\u003eIt was verified that knockdown of PVT1 could inhibit cell proliferation in both luminal and basal-like BC, partly through activating the Hippo signaling pathway. Hippo pathway was first discovered in Drosophila melanogaster, and its major members are highly conserved among different species[34]. In mammals, the core part of Hippo signaling pathway is a kinase cascade composed of mammalian Ste20-like kinases 1/2 (MST1/2), LATS1/2 and YAP/TAZ[34, 45]. When Hippo kinase cascade is triggered by different intracellular and extracellular signaling factors, the activated MST1/2 phosphorylates LATS1/2 by reacting with salvador homolog 1 (SAV1). Then activated LATS1/2 binds to MOB1 and further phosphorylates downstream effector molecule YAP/TAZ. Phosphorylated YAP/TAZ retain in the cytoplasm, and are subsequently degraded by the ubiquitin proteasome pathway. Otherwise, when Hippo signaling pathway is inhibited, the dephosphorylated YAP/TAZ can enter the nucleus and combine with TEA domain transcription factors to initiate the expression of downstream target genes. Thus, biological behaviors such as cell proliferation, survival, migration, stemness and differentiation are affected[34, 55]. An increasing body of evidence indicates that dysregulation of Hippo signaling pathway contributes to the occurrence of cancer. For example, a decreased expression of LATS1 or LATS2 mRNA is significantly associated with a large tumor size, high lymph node metastasis, and estrogen receptor and progesterone receptor negativity[56]. High expression or nuclear aggregation of YAP/TAZ has been identified in breast cancer, liver cancer, lung cancer, ovarian cancer and other cancers[39, 57]. In addition, loss of YAP potently suppresses oncogene-induced mammary tumors[58]. Since the overall mutation frequency of Hippo pathway was relatively low, and the abnormal activation of YAP/TAZ in most cancers is not linked to mutations within these genes[38], it implies that epigenetic aberrations, such as changes in the expression levels of pathway components, might play a larger role in the dysregulation of Hippo pathway in cancers.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eHere, PVT1 was found to regulate Hippo pathway through LATS2, the mRNA stability of which was enhanced after PVT1 knockdown. However, the precise mechanism by which PVT1 regulates mRNA stability remains unclear. According to existing studies, lncRNAs regulate mRNA stability through multipronged mechanisms: (1) Recruiting RNA-binding proteins to target mRNAs to form protective or destabilizing complexes[59]; (2) Sponging miRNAs through complementary base-pairing, preventing miRNA-mediated mRNA decay[60]; (3) Forming duplexes with mRNAs to mask destabilizing elements[61]; (4) Regulating ubiquitination enzymes to stabilize/ destabilize RNA-binding effectors, which in turn affects target transcripts[62]. Although some studies have reported that PVT1 regulates mRNA stability, these findings have predominantly been linked to its function as a competing endogenous RNA (ceRNA) through miRNA interactions, while other mechanisms remain unreported[51, 52, 54]. Moreover, PVT1 knockdown resulted in an increase rather than a decrease in LATS2 expression, suggesting that the regulation occurs through a mechanism independent of miRNA sponging. Therefore, future research would focus on identifying RNA-binding proteins that interact with PVT1, and advanced techniques such as RNA pull down and RNA immunoprecipitation could provide valuable insights into this regulatory mechanism.\u003c/p\u003e\n\u003cp\u003eAlthough this study offers some insights, several limitations should be acknowledged. First, the number of basal-like BC samples available for analysis in the TCGA database is relatively small, and the number of cases with advanced clinical stages is even more limited. This may have contributed to the lack of statistically significant associations between PVT1 expression and clinical parameters, including overall survival, in the basal-like subtype. Moreover, due to the even smaller sample size of HER2-overexpressing BC, this subtype was not included in our analysis, preventing us from drawing a definitive conclusion regarding the pan-subtype oncogenic role of PVT1. Notably, previous studies have provided encouraging evidence supporting the potential role of PVT1 in HER2-overexpressing BC. The PVT1 gene is located at chromosomal 8q24, a well-established hotspot for genetic abnormalities in BC, with amplification detected across all subtypes[20]. In another study by Tseng et al.[49], increased copy number of \u003cem\u003ePVT1\u003c/em\u003e was observed in 62% of HER2-positive BC samples, suggesting that PVT1 may also be upregulated and play an oncogenic role in this subtype. Second, the functional experiments were conducted in only one luminal and one basal-like BC cell line, which may not fully represent the heterogeneity of these subtypes. Expanding the number of cell models would strengthen the robustness of our conclusions. Nevertheless, it is worth noting that previous studies have consistently demonstrated the oncogenic role of PVT1 in both ER-positive and triple-negative BC across multiple cell lines, which strongly supports the generalizability of our findings. Furthermore, \u003cem\u003ein vivo\u003c/em\u003e validation using BC xenograft models in nude mice or genetically engineered mouse models is also warranted, to assess the effects of PVT1 knockdown on tumor growth and Hippo pathway activation. Third, while we observed high PVT1 expression in luminal and basal-like BC using TCGA data, we have yet to validate these findings in clinical tissue samples. Future studies will focus on confirming the expression pattern of PVT1 and its relationship with the LATS2/Hippo pathway in clinical specimens, as well as extending our investigation to HER2-overexpressing BC. Finally, given the critical clinical challenge posed by therapeutic resistance in BC, it will be important to explore whether PVT1 also plays a role in BC drug resistance. Establishing drug-resistant BC cell lines or employing existing resistant models could help determine whether PVT1 contributes to this process. Additionally, further functional studies are needed to expand our understanding of PVT1’s regulatory roles beyond proliferation. Emerging studies have implicated PVT1 in regulating cancer stemness and shaping tumor immune in other cancers[63, 64]. These insights prompt further functional investigations to explore whether PVT1 exerts similar regulatory roles in BC, which may ultimately broaden its translational relevance.\u003c/p\u003e\n\u003cp\u003eIn summary, PVT1 exhibits remarkable potential as a pan-subtype oncogenic lncRNA in BC, and holds promise as a therapeutic target, particularly in patients with dysregulated Hippo signaling. Advances in RNA-based technologies, including antisense oligonucleotides (ASOs), RNA interference, and CRISPR/Cas9 genome editing, have provided feasible strategies for targeting lncRNAs [65]. Notably, nanoparticle-based delivery systems are rapidly improving the specificity and efficacy of such therapies[66]. These developments offer encouraging prospects for the clinical translation of PVT1-targeted interventions, though further rigorous studies and clinical trials are needed to validate it.\u003c/p\u003e"},{"header":" Statements \u0026 Declarations","content":"\u003cp\u003e\u003cstrong\u003eFunding\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThis study was supported by the Zhejiang Provincial Medical and Health Science and Technology Plan (No. 2024KY225) and the National Natural Science Foundation of China (No. 81673516 and No. 82003870).\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eCompeting Interests\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe authors have no relevant financial or non-financial interests to disclose.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAuthor Contributions\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThis study was designed and supervised by Guo Wang. Material preparation was performed by Ying Zeng. Data collection and analysis were performed by Hai-Bo Zhang. The first draft of the manuscript was written by Hai-Bo Zhang and all authors commented on previous versions of the manuscript. All authors read and approved the final manuscript.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eData Availability\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe data generated during the current study is available from the corresponding author on reasonable request.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eEthics Declaration\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eNot applicable.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConsent to Participate declaration\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eNot applicable.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\n \u003cli\u003eBray F, Laversanne M, Sung H, Ferlay J, Siegel RL, Soerjomataram I, Jemal A: \u003cstrong\u003eGlobal cancer statistics 2022: GLOBOCAN estimates of incidence and mortality worldwide for 36 cancers in 185 countries\u003c/strong\u003e. \u003cem\u003eCA: a cancer journal for clinicians\u0026nbsp;\u003c/em\u003e2024, 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therapies - challenges and opportunities\u003c/strong\u003e. \u003cem\u003eJournal of controlled release : official journal of the Controlled Release Society\u0026nbsp;\u003c/em\u003e2024, \u003cstrong\u003e370\u003c/strong\u003e:763-772.\u003c/li\u003e\n\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":"world-journal-of-surgical-oncology","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"wjso","sideBox":"Learn more about [World Journal of Surgical Oncology](http://wjso.biomedcentral.com)","snPcode":"12957","submissionUrl":"https://submission.nature.com/new-submission/12957/3","title":"World Journal of Surgical Oncology","twitterHandle":"@OncoBioMed","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"em","reportingPortfolio":"BMC/SO AJ","inReviewEnabled":true,"inReviewRevisionsEnabled":true},"keywords":"PVT1, Hippo pathway, luminal, basal-like, breast cancer","lastPublishedDoi":"10.21203/rs.3.rs-5745151/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-5745151/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003e\u003cstrong\u003eBackground: \u003c/strong\u003eBreast cancer (BC) is a malignant tumor seriously threatening women’s health, while current approaches to BC treatment are challenged by the existence of drug resistance. Combination strategies of targeted therapy have been successfully applied in clinical BC treatment. However, whether there exist critical long non-coding RNAs (lncRNAs) responsible for BC pathogenesis and representing promising candidates for combined targeted therapy remains an issue.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eMethods:\u003c/strong\u003e Public databases and bioinformatic methods were used to identify lncRNAs abnormally expressed among different subtypes of BC. The expression level of PVT1 was verified in collected clinical samples and representative cell lines. The role of PVT1 in BC cell proliferation was examined using MTS, plate clone formation, EdU and flow cytometry assay after small interfering RNA (siRNA) treatment. RNA sequencing was performed to investigate the potential molecular events regulated by PVT1. Western blot and immunofluorescence experiments were used to verify the activation of LATS2/Hippo signaling pathway after PVT1 knockdown. In addition, its activation was confirmed to mediate PVT1 function through rescue assay. The regulatory effect of PVT1 on LATS2 was investigated using mRNA stability experiments.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eResults: \u003c/strong\u003eThe expression level of PVT1 in BC tissues of luminal and basal-like subtypes was significantly higher than that in paracancerous tissues. PVT1 knockdown substantially inhibited the proliferation of BC cells in both subtypes. RNA sequencing revealed that Hippo signaling pathway might be the downstream target of PVT1. After PVT1 knockdown, both mRNA and protein level of LATS2 were elevated which further decreased the distribution of YAP in cell nucleus, indicating the activation of Hippo signaling pathway. The proliferation inhibitory effect of PVT1 could be attenuated by simultaneous knockdown of LATS2. Furthermore, knockdown of PVT1 was demonstrated to significantly slow down the degradation rate of LATS2 mRNA.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConclusions: \u003c/strong\u003ePVT1 level was significantly elevated in luminal and basal-like BC subtypes. Knockdown of PVT1 could inhibit cell proliferation of these two BC subtypes partly through activating LATS2/Hippo signaling pathway.\u003c/p\u003e","manuscriptTitle":"Knockdown of PVT1 inhibits cell proliferation in luminal and basal-like breast cancer subtypes by activating LATS2/Hippo signaling pathway","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2025-04-09 11:27:39","doi":"10.21203/rs.3.rs-5745151/v1","editorialEvents":[{"type":"communityComments","content":0},{"type":"decision","content":"Revision requested","date":"2025-05-04T12:49:18+00:00","index":"","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2025-05-04T11:36:39+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"267087003264173138546968225149515343357","date":"2025-05-04T11:21:17+00:00","index":"hide","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2025-04-16T16:04:06+00:00","index":"hide","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2025-04-10T01:27:02+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"3704466139831248903016692664270106589","date":"2025-04-10T01:11:45+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"303824093070973656391663305839301578472","date":"2025-04-08T15:20:02+00:00","index":"hide","fulltext":""},{"type":"reviewersInvited","content":"","date":"2025-04-08T15:09:11+00:00","index":"","fulltext":""},{"type":"checksComplete","content":"","date":"2025-04-07T11:43:39+00:00","index":"","fulltext":""},{"type":"submitted","content":"World Journal of Surgical Oncology","date":"2025-04-06T15:55:47+00:00","index":"","fulltext":""}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"world-journal-of-surgical-oncology","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"wjso","sideBox":"Learn more about [World Journal of Surgical Oncology](http://wjso.biomedcentral.com)","snPcode":"12957","submissionUrl":"https://submission.nature.com/new-submission/12957/3","title":"World Journal of Surgical Oncology","twitterHandle":"@OncoBioMed","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"em","reportingPortfolio":"BMC/SO AJ","inReviewEnabled":true,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"79ca87ee-9fd4-41ca-affe-501a339721d7","owner":[],"postedDate":"April 9th, 2025","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"published-in-journal","subjectAreas":[],"tags":[],"updatedAt":"2025-08-07T07:12:57+00:00","versionOfRecord":{"articleIdentity":"rs-5745151","link":"https://doi.org/10.1186/s12957-025-03944-6","journal":{"identity":"world-journal-of-surgical-oncology","isVorOnly":false,"title":"World Journal of Surgical Oncology"},"publishedOn":"2025-07-19 15:57:17","publishedOnDateReadable":"July 19th, 2025"},"versionCreatedAt":"2025-04-09 11:27:39","video":"","vorDoi":"10.1186/s12957-025-03944-6","vorDoiUrl":"https://doi.org/10.1186/s12957-025-03944-6","workflowStages":[]},"version":"v1","identity":"rs-5745151","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-5745151","identity":"rs-5745151","version":["v1"]},"buildId":"8U1c8b4HqxoKbykW_rLl7","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}