PCAT-1 Facilitates Breast Cancer Progression via Enhancing Oxygen-independent Stability of Hypoxia-inducible Factor-1α

Background: Hypoxia induces a series of cellular adaptive responses that enable to promote inammation and cancer development. However, only few have been fully characterized about the roles of long noncoding RNAs (lncRNAs) in hypoxia-associated cancer progression. Methods: The involvement of lncRNAs in hypoxia-related cancer progression was screened by qRT-PCR. Based on the public databases and integrating bioinformatics analysis, the alteration of prostate cancer associated transcript-1 (PCAT-1) in breast cancer tissues was detected and validated in a cohort of breast cancer tissues. Overexpression and knocking down experiments were performed to uncover the biological roles of PCAT-1 on cell hypoxia-associated phenotypes and biological behaviors. RNA immunoprecipitation (RIP) and RNA pull-down were carried out to reveal the physical interaction between PCAT-1 and receptor of activated protein-C kinase-1 (RACK1). Moreover, xenograft mouse models were used to evaluate the inuence of PCAT-1 on cancer progression and metastasis in vivo. Results: We identied PCAT-1 as a hypoxia-inducible lncRNA that regulated the hypoxia-inducible factor-1α (HIF-1α) stability, crucial for cancer progression. Extensive analyses of clinical data indicated that PCAT-1 was elevated in breast cancer patients and was associated with pathological grade, tumor size and poor clinical outcomes. Through gain and loss of function experiments, we found that PCAT-1 promoted hypoxia-associated breast cancer progression including growth, migration, invasion, colony formation, and metabolic regulation. Mechanistically, PCAT-1 directly interacted with RACK1 protein and prevented RACK1 from binding to HIF-1α, thus protecting HIF-1α from RACK1-induced oxygen-independent degradation. Conclusions: These ndings provide a new insight into lncRNA-mediated mechanisms for HIF-1α stability and suggest that a novel role of PCAT-1 as a potential therapeutic target for breast cancer. assay were detected in MDA-MB-231 cells transfected with PCAT-1 siRNA. Extracellular acid ratio (ECAR) level (g) and lactate production (h) in the culture media were determined after knockdown of PCAT-1 in MDA-MB-231. 2-DG, 2-deoxyglucose. The data are showed as fold difference compared with the level of negative control (NC) siRNA-transfected cells in normoxia. Data are shown as the mean±s.e.m. *P<0.05 and **P<0.01 compared with control. MDA-MB-231 cells transfected with PCAT-1 siRNA in hypoxia. i Expression of HIF-1α target genes in MDA-MB-231 cells transfected with PCAT-1 siRNA was measured by qRT-PCR. j Expression of HIF-1α target genes in MCF-7 cells overexpressed PCAT-1 was measured by qRT-PCR under hypoxic conditions. module prediction of the binding sites between PCAT-1 and RACK1. interaction between PCAT-1 and RACK1 was performed by RNA pull-down assay with a biotinylated PCAT1 probe in cells under hypoxic conditions. analysis of the interaction PCAT-1 RACK1 was performed using the anti-RACK1 antibody in MDA-MB-231 cells, and the level of PCAT1 was determined using qRT-PCR. The truncated PCAT-1 were used in the RNA pull-down assay to identify core regions of PCAT-1 for the physical interaction with RACK1 stability and expression HIF-1α target genes were examined in cells overexpressed (nucleotides 1-1299) or truncated PCAT-1 under hypoxic conditions. Endogenous PCAT-1 was depleted with siRNA MDA-MB-231 cells, and truncated overexpressed

Under hypoxic condition, HIF-1α evades the oxygen-dependent degradation, allowing it to translocate into the cell nucleus to form the transcriptionally HIF-1α complex [10]. Several studies have shown that there are oxygen-independent mechanisms about HIF-1α degradation under hypoxic conditions, including heat shock protein 90 (HSP90) and receptor of activated protein C kinase-1 (RACK1) [12][13][14]. HSP90 binds to the HIF-1α PAS domain to prevent its degradation. RACK1 competes with HSP90 for binding to HIF-1α, links HIF-1α to Elongin-C, and promotes HIF-1α degradation in an oxygen-independent manner [12,15]. Thus, equilibrium between HIF1α/RACK1 and HIF1α/HSP90 may play a key role in maintaining HIF1α stability, as well as cancer progression.
Long non-coding RNAs (lncRNAs) have emerged as important molecules in carcinogenesis with various biological effects, such as genome modi cation, transcriptional activation, and transcriptional interference [16][17][18]. They have been implicated as prospective biomarkers for early cancer diagnosis, with the potential to serve as new targets for cancer treatment [19,20]. Previous studies have identi ed lots of hypoxic-reactive lncRNAs are functionally characterized and have crucial effects on cancer progression [21]. Prostate cancer associated transcript-1 (PCAT-1) is identi ed as a prostate canceroverexpressed lncRNA, and it contributes to prostate cancer progression through regulation of target genes [22]. The high expression of PCAT-1 has been observed in several types of cancers, including colorectal cancer [23], esophageal squamous cell carcinoma [24] hilar cholangiocarcinoma [25], osteosarcoma [26] and hepatocellular carcinoma [27]. It has been shown to be involved in impairment of double-stranded DNA break repair, cancer cell proliferation, epithelial-mesenchymal transitions, migration, and invasion [28][29][30][31]. The recent report shows that PCAT-1 overexpression is also observed in breast cancer tissues [32]. However, there is no previous report of PCAT-1 regulating hypoxia-related cancers.
Currently, the clinical signi cance of PCAT-1 in the context of breast cancer and the molecular mechanisms by which it regulates remain largely unclear.
In this study, through the investigation of lncRNA in breast cancer, we identify that PCAT-1 is one of the signi cantly upregulated lncRNA under hypoxic conditions. We reveal that PCAT-1 is critical for maintaining the stability of HIF-1α in hypoxic breast cancer cells,which is related to advanced disease progression and poor prognosis. We elucidate that PCAT-1 interacts with RACK1, which mediates oxygenindependent HIF-1α stability, thereby establishing PCAT-1 as an important lncRNA in the breast cancer.

Cell culture and transfection
Human breast cancer cell lines MCF-7, MDA-MB-231, normal breast epithelial cell MCF10A and the human embryonic kidney (HEK) 293 cells were purchased from the American Type Culture Collection (Manassas, VA, USA). The cell lines were cultured in DMEM (Gibco, USA) with 10% foetal bovine serum, 100 ng/ml streptomycin and 100 U/ml penicillin. For normoxic conditions, mixed gas consisting of 20% O 2 , 5% CO 2 , and 75% N 2 at 37°C was used. For hypoxic conditions, the cells were cultured in the gas mixture of 1% O 2 , 5% CO 2 , and 94% N 2 at 37°C.

Tissue specimens
Tumors and the adjacent breast tissues used in this study were surgical specimens from patients with breast cancer. All samples were fresh frozen in liquid nitrogen and stored at -80 °C until RNA extraction.
The study protocol was approved by the Ethics Committee of the Second Hospital of Hebei Medical University (Hebei, China), and informed consent was obtained from all participants.
RNA extraction and quantitative real-time PCR (qRT-PCR) Total RNA was extracted by TRIzol reagent (Invitrogen, USA). Equal amounts of RNA were reversetranscribed using the Transcriptor First Strand cDNA Synthesis Kit (Roche), and qRT-PCR was performed with SYBR PrimeScript RT-PCR kit (Takara, Dalian, China). Unless otherwise speci ed, the ampli ed transcript level of each speci c gene was normalized against the GAPDH mRNA level. The primers were provided by Shenggong Company (Shanghai, China). The primer sequences are listed in Additional le 1: Table S1.

Bioinformatics Analysis
The Cancer Genome Atlas (TCGA) Breast Cancer datasets were retrieved from the cBioPortal for Cancer Genomics. PCAT1 gene log 2 copy number from cBioPortal was downloaded. Patients were grouped into PCAT1-low or PCAT1-ampli cation based on PCAT1 log 2 copy number. The cutoff point of PCAT1 gene log 2 copy number calls on the cases were determined as the value yielding maximum sum of sensitivity and speci city. The clinical data (including the overall survival data and disease-free survival data) were obtained from the TCGA Pan-Cancer Clinical Data Resource [33]. The patients with overall event time less than 130 months were used in this study. The survival curves were constructed according to the Kaplan-Meier method and compared using the log-rank test.
Cell growth assay The cell growth was monitored by MTT assay. Brie y, cells were treated and cultured into 96-well plates.
A total of 20 μl of MTT (Sigma, USA) dissolved in PBS at 5 mg/ml was added to the wells and then incubated for an additional 4 h at 37°C. A total of 100 μl of DMSO was added to dissolve the formed formazan crystals, and the optical density was measured on the microplate reader.

Colony formation assay
Cells were seeded in 6-well plates (200 cells/well) and treated for 14 days, and then the cells were xed with methanol and stained with 1% crystal violet solution. The numbers of cell colonies from three dishes were counted.

Wound healing and invasion assay
For the wound healing assays, cells were treated and cultured in six-well plates until almost totally con uent. Then, the arti cial wounds with a sterile pipette tip were scratched and images were captured at 0 h and 48 h under the microscope.
Cell invasion assays were performed using the Transwell chambers (8 μm pores, Corning, USA) that coated with Matrigel (BD Biosciences, USA). Cells were treated and suspended in medium with 1% FBS in the upper chambers. Medium containing 10% FBS was used as a chemoattractant in the bottom chamber. After incubation for 48 h, the migrated or invaded cells were xed, stained and counted under an inverted microscope.

Measurement of extracellular acidi cation rate (ECAR)
The ECAR was measured using the Seahorse Extracellular Flux Analyzer XF96 (Seahorse Bioscience, USA) according to the manufacturer's instructions. Brie y, the treated cells were seeded at a density of 10 5 per well allowed to adhere overnight. Before the assay, the cells were washed with assay medium followed by a sequential injection of 10 mM glucose, 1 µM oligomycin, and 100 mM 2-deoxyglucose (2-DG). ECAR is expressed as mpH/min and three replicates were performed for each group.
Lactate production assay Cells were seeded into 6-well plates, and the culture medium was collected for measurement of lactate concentration. The Level of lactate in the culture media was determined using the L-lactate Assay Kit (Abcam, USA) following the manufacturer's instruction.
Immunoblot analysis and Co-immunoprecipitation (Co-IP) For immunoblot analysis, RIPA buffer was added and incubated for 30 min followed by centrifugation, the supernatant contained the total protein. The nuclear and cytoplasmic proteins were extracted using the NE-PER Nuclear and Cytoplasmic Extraction Reagents (Thermo Scienti c, USA) according to the manufacturer's instructions. After determination of the protein concentrations by the Bradford method, proteins were separated by SDS-PAGE and transferred onto PVDF membranes. The membranes were blocked with 5% fat-free milk powder in TBST buffer and then exposed to primary antibodies at 4 °C overnight. Following incubation with secondary antibodies, signals were detected using the ECL detection system.
For immunoprecipitation, protein extracts from the cells were determined by the Bradford method. For the experiment, 500 μg of protein immunoprecipitated with indicated antibodies at 4°C overnight, followed by incubation with protein A Sepharose beads for 2 h. The Immunoprecipitates were washed and resolved by SDS-PAGE and immunoblotted with the indicated antibodies.

RNA pull-down assay
Biotin-labeled PCAT-1 and its fragments were transcribed with Biotin RNA Labeling Mix (Roche) and T7 RNA polymerase (Invitrogen, USA), treated with RNase-free DNase I (Invitrogen, USA), and puri ed using RNeasy Mini Kit (Qiagen, Germany). Pull downs were performed with biotinylated RNA and nuclear extracts of cells. The bead-RNA-protein complexes were isolated with streptavidin magnetic beads (Sigma, USA) and subjected to standard immunoblot analysis.

RNA immunoprecipitation (RIP)
The RIP assay was performed using the Magna RIP RNA Binding Protein Immunoprecipitation Kit (Millipore, USA). Brie y, cells were harvested and lysed in lysis buffer containing protease inhibitor cocktail and RNase inhibitors. Cell extracts were co-immunoprecipitated using the primary antibody, and the retrieved RNA was subjected to qRT-PCR analysis to demonstrate the presence of the binding products using respective primers.

Xenograft experiments
The animal studies were performed as described previously [34,35]. The female BALB/c nude mice (4-5 weeks old) were purchased from Charles River (Beijing, China). All experimental procedures were approved by the Institutional Animal Care and Use Committee of the Second Hospital of Hebei medical University (Hebei, China). A total of 10 6 MDA-MB-231 cells (transfected with sh-control or sh-PCAT-1) were injected into the right ank or the tail vein of mice (n = 6 mice/group), respectively. The tumor volume was measured every 5 days, and tumor volume was estimated by the formula: V (mm 3 ) = 1/2 × length × width 2 . At the end of the experiment, the tumor tissues in the tumor growth xenograft model and the lungs and livers in the metastasis model were removed and weighed.

Statistical analysis
The overall or disease-free survival curves were calculated by the Kaplan-Meier method, and the differences were assessed using the log-rank test. Differences between two independent groups were tested with two-tailed Student's t test. Comparison of multiple groups was made using a one-or two-way ANOVA tests. Univariate and multivariate Cox proportional hazards regression models were performed to explore independent prognostic factors. Data were expressed as mean±s.e.m. Difference was considered statistically signi cant at P<0.05.

Results
The expression of PCAT-1 is induced after hypoxia treatment To identify the involvement of lncRNAs in hypoxia-related cancer progression, we selected 30 cancerassociated lncRNAs (listed in Additional le 1: Table S2) according to the previous studies [20,21] and analyzed their expression in MDA-MB-231 breast cancer cells in hypoxia and normoxia. Compared to normoxic conditions, 10 lncRNAs with >2-fold expression changes were identi ed under hypoxic conditions (Fig. 1a). Moreover, we examined the expression of these lncRNAs and identi ed 7 of them upregulated by >2-fold in MDA-MB-231 cells treated with cobalt chloride (CoCl 2 ) (Fig. 1b), which was used to create a pseudo-hypoxic environment. These lncRNAs include 4 of those induced in physical hypoxia (Fig. 1c). PCAT-1 was one of the upregulated lncRNA after cobalt chloride treatment and showed a timeand concentration-dependent induction ( Fig. 1d and e). Similarly, a time-dependent increase of PCAT-1 was observed in MDA-MB-231 cells under hypoxic conditions (Fig. 1f), con rming PCAT-1 is a hypoxiaresponsive lncRNA and is probably involved in HIF-1α signalling pathway.

PCAT-1 expression is associated with breast cancer poor prognosis
To assess the pathological and clinical value of PCAT-1 in breast cancer, we measured PCAT-1 expression in a panel of 71 matched pairs of clinical specimens containing breast cancer tissues and the normal adjacent tissues. It showed that PCAT-1 was signi cantly upregulated in the cancer tissues compared with the normal adjacent tissues (P<0.001, Fig. 1g). Moreover, statistical analysis showed that PCAT-1 overexpression was strongly correlated with the advanced tumor stage (P=0.001, Fig. 1h) and tumor size (P=0.003, Fig. 1i).
To further validate the data from our studies, we surveyed public data of The Cancer Genome Atlas (TCGA) breast cancer study using cBioPortal platform and explored the correlation between PCAT-1 gene alteration and the clinicopathological characteristics of 735 breast cancer patients (Additional le 1: Table S3). The analyses revealed that PCAT1-ampli cation was correlated with advanced tumor stage (P=0.008) and tumor sizes (P=0.002, Table 1), whereas no signi cant relationship with any other clinical characteristics was observed. Moreover, we evaluated PCAT-1 gene alteration in relation to overall survival (OS) and disease-free survial (DFS) data on the patients (Additional le 1: Table S3). Kaplan-Meier survival analysis was performed to compare the outcomes of patients dichotomized by PCAT log 2 copy number value. Patients with PCAT1-ampli cation copy number had a signi cantly worse overall survival (P<0.001) (Fig. 1j) and disease-free survial (P=0.004) (Fig. 1k), respectively. In addition, similar to the prognostic values of tumor stage (I+II versus III+IV), tumor size (≤5cm versus >5cm) and lymph node metastasis (N0 versus N1-3), the univariate Cox proportional hazards showed that PCAT1-ampli cation was another strong prognostic predictor for poor OS (hazard ratio=0.423, P<0.001) and DFS (hazard ratio=0.488, P=0.005, Table 2). Furthermore, multivariate analysis was conducted to determine risk assessment related to OS and DFS. The PCAT1-ampli cation was identi ed as an independent prognostic factor for OS (HR=0.497, P=0.005, multivariate analysis) and DFS (HR=0.556, P=0.024, multivariate analysis, Table 2). Together, our data indicated that PCAT1 could be used as an independent prognostic indicator of clinical prognosis in breast cancer patients. Fisher's exact test was used to determine the correlation between PCAT-1 gene alteration and the clinicopathological characteristics. The cutoff point is set as the value yielding maximum sum of sensitivity and speci city for disease-free survial analysis. **P<0.01.

PCAT-1 promotes breast cancer progression
To ascertain the potential role of PCAT-1 in breast cancer, we detected the expression of PCAT-1 in a panel of breast cancer cells MCF-7, MDA-MB-231 and normal breast epithelial cell MCF10A. Compared with MCF-7 cells that exhibited poor invasive capacity, the high invasive MDA-MB-231 cells had higher PCAT-1 expression (Fig. 2a), while MCF-7 and MCF10A cells had low level of PCAT-1, indicating PCAT-1 was possible association with cell invasion in breast cancer. Similar to MDA-MB-231 cells, PCAT-1 expression was also induced in MCF-7 cells by cobalt chloride under pseudohypoxia or under hypoxic conditions (Fig. 2b).
The cells response to pathological hypoxia is associated with many critical aspects of cancer. To further investigate the biological signi cance of PCAT-1 in breast cancer, we knocked down the expression of PCAT-1 with two independent small interfering RNAs (siRNAs). Moreover, lentiviral PCAT-1 shRNA (shRNA-PCAT-1) and empty vector (shRNA-Control) were also stably transfected in MDA-MB-231 cells, and the related phenotypes in the cells were examined. The functional assays revealed that PCAT-1 knockdown signi cantly impaired cell growth, migration, invasion and colony formation in hypoxia (Fig. 3c-f). In addition, we found the hypoxia-induced extracellular acidi cation rate (ECAR) (Fig. 2g) and lactate production (Fig. 2h) were signi cantly reduced in the PCAT-1-knockdown MDA-MB-231 cells under hypoxic conditions, indicating that PCAT-1 is essential for glycolytic metabolism in the cells. In conclusion, these results suggested that PCAT-1 played a crucial role in hypoxia-associated phenotypes and biological behaviors.
PCAT-1 contributes to HIF-1α stability HIF-1α is a core regulator of cell adaptation to hypoxia. To determine the roles of PCAT-1 in HIF-1α signalling pathway, PCAT-1 was overexpressed in MCF-7 cells. We found that HIF-1α protein expression was increased in normoxia as well as in hypoxia (Fig. 3a). However, HIF-1α mRNA expression was not changed (Fig. 3b). In addition, we investigated whether PCAT-1 regulates HIF-1α mRNA stability. We treated the cells with actinomycin D, which blocks de novo mRNA synthesis, and the HIF-1α mRNA stabilization is not affected by PCAT-1 overexpression (Fig. 3c), suggesting that HIF-1α mRNA transcription and degradation is not regulated by PCAT-1. Additionally, the cells were exposed to hypoxia, and then recovered in normoxia, and we found that the half-lives of HIF-1α protein were increased from 2.5±0.3 to 6.5±0.7 min as a consequence of PCAT-1 overexpression, indicating that PCAT-1 overexpression yielded a signi cantly delay of HIF-1α protein degradation (Fig. 3d). These results reveal that PCAT-1 overexpression increases HIF-1α expression by enhancing the stability of HIF-1α protein. In addition, PCAT-1 was depleted in MDA-MB-231 cells. HIF-1α protein expression was obviously decreased in the cells after knockdown of PCAT-1 under hypoxic environment (Fig. 3e), while HIF-1α mRNA expression and stabilization were not changed (Fig. 3f). We also found that HIF-1α protein degraded more quickly during reoxygenation in the PCAT-1 knockdown cells (Fig. 3g), and the half-lives of HIF-1α protein were decreased from 7.2±1.1 to 3.8±0.6 min, suggesting that depletion of PCAT-1 decreased the HIF-1α protein stability. Moreover, PCAT-1 knockdown reduced HIF-1α nuclear accumulation, which is consistent with the reduction of HIF-1α protein stability (Fig. 3h).
PCAT-1 interacts with RACK1 that mediates HIF-1α stability RACK1 could compete with HSP90 for binding to HIF-1α and be involved in HIF-1α degradation [12]. Given the established interaction of RACK1 with HIF-1α, we sought to analyze the mechanistic role of PCAT-1 in HIF-1α stability by focusing on the interaction between PCAT-1 and RACK1. We rst explored the possible interaction between PCAT-1 and RACK1 through bioinformatic analysis (catRAPID), which could predict the protein-RNA associations through estimating the interaction propensity between amino acids and nucleotides by secondary structure information, hydrogen bonding and Van der Waals forces. Results from catRAPID fragments analysis showed that the 1093-1172 and 1288-1367 nucleotide positions of the PCAT-1 sequence may bind to the 217-268 amino acid residues of the RACK1 protein with high a nity (Fig. 5a).
To validate the physical interaction between PCAT-1 and RACK1, we performed RNA pull-down followed by immunoblot using RACK1 antibody in MDA-MB-231 cells. The results indicated that PCAT-1 was able to interact with RACK1 (Fig. 5b). Consistently, RIP assays using nuclear extract further con rmed that PCAT-1 directly interacted with RACK1 (Fig. 5c). Moreover, a series of PCAT-1 truncated fragments analysis demonstrated that the 3′-terminal (nucleotides 801-1299) region of the PCAT-1 were required for direct interaction with RACK1, which was con rmed by RNA pull-down assays (Fig. 5d). As expected, the interaction was abrogated when using the truncated PCAT-1 (nucleotides 1-800) that lacked the binding region (Fig. 5e), proving that the critical region of PCAT-1 at the 3′-terminal (nucleotides 801-1299).

PCAT-1 reduces RACK1 binding to HIF-1α
To evaluate the effect of PCAT-1 on RACK1 binding to HIF-1α, MDA-MB-231 cells transfected with shRNA-PCAT-1 were treated with MG132. Immunoprecipitation results showed that PCAT-1 knockdown reduced HIF-1α binding to HSP90 but signi cantly increased the binding e ciency between HIF-1α and RACK1 (Fig. 6a). Moreover, MCF-7 cells were cotransfected with PCAT-1 and HA-HIF-1α (P402A/P564A) under hypoxic conditions. The results showed that PCAT-1 overexpression signi cantly suppressed HA-HIF-1α binding to RACK1 (Fig. 6b). Moreover, HSP90 inhibition by 17-AAG increased the binding e ciency between RACK1 and HIF-1α, while it can be abolished by PCAT-1 overexpression. In addition, we investigated the effect of PCAT-1 on RACK1 dimerization which is necessary in HIF-1α activation [36]. FLAG-RACK1 was overexpressed in HEK 293 cells, and then it was isolated by anti-FLAG antibody immobilized on agarose resin. We further used the FLAG-RACK1-enriched resin to pull down endogenous RACK1 from the MDA-MB-231 cells transfected with shRNA-PCAT-1, and the results showed that PCAT-1 knockdown increased RACK1 dimerization in the presence of MG132 under hypoxic conditions (Fig. 6c).
Consistent with the previous study that serine phosphorylation of RACK1 was required for its dimerization and HIF-1α degradation [36], we found that PCAT-1 knockdown also enhanced RACK1 phosphorylation (Fig. 6d). These results suggest that PCAT-1/RACK1 interaction results in decreased RACK1 dimerization and phosphorylation, which in turn reduces RACK1 binding to HIF-1α.

Suppression of breast cancer progression by targeting PCAT-1 in vivo
To evaluate the biological function of PCAT-1 in vivo, MDA-MB-231 cells stably transfected with shRNA-PCAT-1 or shRNA-Control lentiviral particles were inoculated into the right ank of nude mice (n=8/group).
We further injected the cells into the tail veins of nude mice in order to evaluate the metastatic potential of the cells. The mice were sacri ced 8 weeks later and the lung and liver tissues were obtained. We found that the metastasis ability of MDA-MB-231 cells to lung and liver in the PCAT-1 silencing group were signi cantly lower relative to the control group ( Fig. 7d and e). Taken together, these results indicated that PCAT-1 knockdown signi cantly suppressed the breast cancer progression and metastasis in vivo, which further con rmed the carcinogenic effects of PCAT-1 in breast cancer.

Discussion
Hypoxia is common in solid tumors, and it modulates cancer progression as well as therapeutic response. Recently, more and more observations recognize that lncRNA can act as a regulator of cellular responses in hypoxia. Under hypoxic conditions, lncRNA plays the regulatory roles through a variety of potential mechanisms such as epigenetics, lncRNA-miRNA interaction, and lncRNA-protein interaction [37][38][39]. However, only a few have been con rmed in terms of the detailed mechanisms, while the roles of most others are still unclear.
Previous studies have implicated the elevated PCAT-1 expression is observed in breast cancer [32].
However, none of the studies have investigated the biological functions of PCAT-1 in the hypoxic environment which is contributed to the malignant progression. Our present study identi es PCAT-1 as a hypoxia-inducible lncRNA and shows a distinct mechanism in breast cancer. Indeed, we nd that PCAT-1 overexpression enhances HIF-1α protein stability and confers hypoxia-associated tumorigenesis including growth, migration, invasion, colony formation, and metabolic regulation. When we investigate the mechanisms of PCAT-1 promoting breast cancer under hypoxic conditions, we nd that RACK1 is involved and plays a key role. As a multifunctional scaffold protein for many kinases and receptors, RACK1 binds to the PAS-A subdomain of HIF-1α and recruits an Elongin-C E3 ubiquitin ligase complex to HIF-1α, enhancing HIF-1α ubiquitination and degradation. Here, we show that PCAT-1 is capable of controlling the competition of RACK1 for binding to HIF-1α. The interaction between PCAT-1 and RACK1 inhibits RACK1 dimerization and phosphorylation, and then further prevents RACK1 from binding to HIF-1α. The binding of RACK1 to HIF-1α was disrupted by PCAT-1, making HIF-1α easier to bind to HSP90, but not to RACK1, and contributing to enhance HIF-1α stability.
As the expression of PCAT-1, RACK1, HSP90 and HIF-1α is increased in many kinds of cancers [30,[40][41][42], the effects of PCAT-1 on the balance between HIF-1α/RACK1 and HIF-1α/HSP90 may contribute to the cancer progression. It is the basis for the association of PCAT-1 with the clinicopathological prognosis of the diseases. As we have shown, PCAT-1 is almost absent or at low level in the normal tissues, and it increased to high level in the tumor tissues. Considering the role of PCAT-1 in the upregulation of HIF-1α, facilitation of HIF-1α stability by PCAT-1 may explain the close relation of PCAT1 overexpression to advanced tumor stage and tumor size. In addition to hypoxia, PCAT-1 also promotes the expression of HIF-1α in normoxia. Since HIF-1α also increases in some cancer cells under normoxic conditions [43], it can be speculated that PCAT-1 also participates in the regulation of HIF-1α signaling pathway in normoxia during cancer progression.
It is demonstrated that HIF-1α and its target genes control the biological processes in cancers [42,44,45].
HIF-1α and the downstream effectors have been considered as potential targets for cancer diagnosis and therapy due to their profound impacts in cancers [11,46]. However, it is hard to design the effective inhibitors due to the complexity of the HIF-1α signaling network [45]. Because lncRNA is easy to extract and detect, it has many advantages in cancer diagnosis and prognosis [19]. Our works present the evidence showing that PCAT-1 is an independent risk factor for OS and DFS, suggesting the potential clinical application of PCAT-1 as a biomarker for breast cancer prognosis. Thus, these ndings illustrate that PCAT-1 intervention through gene silencing or other strategies could present potential new approach to anticancer therapies.
Although our study supports that the expression of PCAT-1 is critical to the breast cancer, PCAT-1 overexpression may be the result of other modulations in cells, and it may be regulated by other factors involved in cancer progression. Our research can not completely rule out the possibility that PCAT-1 may also enhance the HIF-1α stability through regulating other factors that affect HIF-1α degradation. For example, some post-translational modi cations, such as acetylation, phosphorylation, nitrosylation and SUMOylation, have also been reported to be involved in the regulation of transactivation, stability and expression of HIF-1α [47]. These questions should be solved through future experiments to clarify the role and mechanism of PCAT-1in breast cancer.

Conclusions
In summary, our studies highlight a previously unknown function of PCAT-1 in the cancer progression under hypoxic conditions, especially its role in regulating the oxygen-independent stability of HIF-1α. The effects of PCAT-1 in HIF-1α stability not only provide new insight into the survival mechanism of cells in response to oxygen de ciency but also reveal a potential utility of PCAT-1 in prognosis and therapeutic strategy for breast cancer.

Supplementary Files
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