SNHG15 inhibits the tricarboxylic acid cycle and promotes HCC progression by facilitating the phosphorylation of PDK1 and PDHE1α

SNHG15 inhibits the tricarboxylic acid cycle and promotes HCC progression by facilitating the phosphorylation of PDK1 and PDHE1α | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Article SNHG15 inhibits the tricarboxylic acid cycle and promotes HCC progression by facilitating the phosphorylation of PDK1 and PDHE1α chunqing wang, hanxiang chen, yunqiu wang, wei chong, xiaofei wang, and 3 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-9307919/v1 This work is licensed under a CC BY 4.0 License Status: Under Review Version 1 posted 9 You are reading this latest preprint version Abstract Glucometabolic reprogramming is a defining feature of hepatocellular carcinoma (HCC). The pyruvate dehydrogenase complex (PDHc) serves as a critical intermediary between glycolysis and oxidative phosphorylation by facilitating the oxidation of pyruvate within the tricarboxylic acid cycle. However, its potential involvement in other facets of metabolic regulation has yet to be fully elucidated. Here, we found that PDHE1α could bind RNA and that lncRNA SNHG15, a small nucleolar RNA host gene, may interact with PDHE1α. Mechanistic analysis suggested that SNHG15 facilitated the interaction between PGK1 and PDK1, as well as between PDK1 and PDHE1α, resulting in increased phosphorylation of PDK1 and PDHE1α. This in turn suppressed the TCA cycle and promoted glycolysis in HCC cells. Notably, SNHG15 facilitated cellular proliferation while concurrently enhancing the growth of xenografted tumors and augmenting lactate production. This study elucidates the functional significance of SNHG15 in mediating metabolic reprogramming in HCC, thereby identifying potential therapeutic targets for clinical intervention. Biological sciences/Molecular biology/Non-coding RNAs/Long non-coding RNAs Biological sciences/Cancer/Cancer metabolism SNHG15 TCA metabolic reprogramming HCC phosphorylation Figures Figure 1 Figure 2 Figure 3 Figure 4 Figure 5 Figure 6 Figure 7 Figure 8 Introduction Hepatocellular carcinoma (HCC) presents an enormous global health concern, being the fourth leading cause of cancer-related mortality and the sixth most commonly diagnosed cancer globally [ 1 ]. HCC cells actively engage in both anaerobic and aerobic glycolysis (Warburg effect) to meet the energy, redox, and biosynthetic needs of the tumor tissue [ 1 ]. Consequently, glycolysis exacerbates immunological suppression, hypoxia, and acidosis while promoting tumor growth, angiogenesis, invasion, and metastasis [ 2 ]. Accordingly, metabolic reprogramming has received increasing attention in anticancer therapy, and many medications targeting metabolites or metabolic pathways have been developed and approved by the United States FDA for cancer treatment [ 3 ]. Currently, a few compounds can block glycolysis by targeting HK2, PFK1, or PKM2 [ 4 ]. Although a number of medications that target glucometabolism are currently undergoing phase I or II clinical studies, their clinical applications remain uncertain. Numerous challenges persist in targeting metabolic pathways for cancer treatment. Long non-coding RNAs (lncRNAs) are a diverse class of molecules that are typically longer than 200 nucleotides and do not encode proteins [ 5 ]. Several studies have demonstrated that lncRNAs contribute to the carcinogenesis and metastasis of HCC by modifying apoptosis, chemo- or radio-sensitivity, and cell invasion and proliferation [ 6 ]. Cellular energy metabolism requires mitochondria, and aberrant mitochondrial function is an important cause of dysfunction and cell death [ 7 ]. It is conceivable to predict the roles of lncRNAs in mitochondria owing to advancements in sequencing technology and bioinformatics techniques [ 8 ]. For example, lncRNA RMRP was found to regulate mitochondrial DNA replication [ 9 ]. The lncRNA GAS5 was found to promote apoptosis in ovarian cancer cells by reducing the mitochondrial membrane potential [ 10 ]. In addition, lncRNA GAS5 regulates TCA metabolism in response to nutritional stress [ 11 ]. The pyruvate dehydrogenase complex (PDHc) is an extensive and intricate multienzyme, with a molecular mass of approximately 9.5 million Daltons. It is located in the mitochondrial matrix, where it plays a pivotal role in cellular metabolism [ 12 ]. By catalyzing pyruvate oxidation, PDHc links glycolysis with oxidative phosphorylation, occupying a pivotal node in the TCA cycle. PDHc comprises four essential catalytic components: pyruvate dehydrogenase E1 (E1), dihydrolipoyl transacetylase (E2), dihydrolipoamide dehydrogenase (E3), and E3-binding protein (E3BP) [ 13 ]. The activation of PDH is intricately regulated through both transcriptional processes and various post-translational modifications, such as succinylation, acetylation, and phosphorylation [ 13 , 14 ]. Pyruvate dehydrogenase kinases (PDKs), which exhibits tissue-specific expression patterns and varied regulatory mechanisms, mediate phosphorylation as a well-established mechanism of PDH inactivation [ 15 ]. As a critical node in metabolic regulation, changes in PDHc contribute to metabolic reprogramming during HCC development, resulting in the accumulation of lactic acid, remodeling of the TCA cycle, and disruption of lipid metabolism. Through the application of an innovative approach that combines subcellular separation, two-phase extraction, and mass spectrometry quantification, we have identified a novel RNA-binding protein (RBP), PDHE1α, which exhibits binding affinity to the lncRNA SNHG15. SNHG15 plays a significant role in the progression and malignant transformation of HCC by facilitating the phosphorylation of PDK1 and PDHE1α, while concurrently inhibiting the TCA cycle. This study presents undocumented evidence regarding the role of SNHG15 in HCC progression through PDH-mediated alterations in glucometabolic reprogramming, thereby identifying a promising therapeutic target for HCC treatment. Methods Cell Culture The HCC cell lines LM3, Huh7, and Hep3B were maintained at 37°C in a humidified environment with 5% CO 2 . The cells were grown in DMEM supplemented with 10% fetal bovine serum and 1% penicillin-streptomycin (100 µg/mL). RNA Fluorescence in Situ Hybridization (FISH) The cells were permeabilized with 70% ethanol for 1 h after being fixed with 37% formaldehyde for 10 min at room temperature. Slides were hybridized for 16 hours at 37°C. The antisense probes were dissolved at 20 nM in hybridization buffer for RNA FISH. Then the slides stained with Alexa Fluor 546-conjugated streptavidin for 1 h at the same temperature. Coverslips were examined using confocal laser scanning microscopy (Olympus, Tokyo, Japan) after they had been counter-stained with DAPI. RNA Immunoprecipitation (RIP) Protein A or Protein G magnetic beads were used to separate the RNA-protein complexes using the appropriate primary antibodies. After ten rounds of washing with lysis buffer (240 mM NaCl, 40 mM Tris, and 1% Triton X-100), the co-precipitated RNAs were extracted using TRIzol (Invitrogen), and qRT-PCR was used to determine the amount of SNHG15 in the eluate. LncRNA-RMRP was used as an RNA control. RNA Pull-Down For the RNA pull-down assay, 4 µg of biotinylated SNHG15 or antisense SNHG15 was added to 40 µL of Streptavidin Dynabeads (Invitrogen) and incubated for 3 h at 4°C in binding buffer (300 mM NaCl, 50 mM Na 3 PO 4 , and 0.01% Tween-20). The beads were then mixed with the cell lysates and incubated for 4 h at 4°C. Following ten rounds of washing with lysis buffer (240 mM NaCl, 40 mM Tris, and 1% Triton X-100), the beads were mixed with SDS-PAGE sample loading buffer and examined using western blotting. His-tag Pull-Down Assay Dynabeads® His-tag isolation magnetic beads (Invitrogen) were incubated with His-tagged rPDK1 or rPDHE1α for 4 h at 4°C in the binding buffer (300 mM NaCl, 50 mM Na 3 PO 4 , and 0.01% Tween-20). The protein-coupled beads were then incubated with SNHG15 or antisense SNHG15 for 4 h at 4°C in the pull-down buffer (70 mM NaCl, 3.25 mM Na 3 PO 4 , and 0.01% Tween-20). The beads were then washed ten times with lysis buffer (240 mM NaCl, 40 mM Tris, and 1% Triton X-100). TRIzol reagent (Invitrogen) was used to extract the copurified SNHG15, and qRT-PCR was used for analysis. Enzyme Activity Measurements A pyruvate kinase activity assay kit (Abcam, Cambridge, MA, USA) was utilized to measure PDH activity according to the manufacturer’s instructions. 10 6 cells were homogenized in 0.5 mL of cold assay buffer, and the supernatant was collected by centrifugation. The test was conducted using 50 µL of diluted cell lysate, 46 µL of assay buffer, 2 µL of developer and 2 µL of substrate. To ascertain the PDH activity in the sample, the absorbance at 450 nm between T 0min and T 30min was recorded using a microplate reader (Thermo Fisher Scientific, Waltham, MA, USA). Measurement of Oxygen Consumption and Extracellular Acidification Rate The Seahorse XF extracellular flux analyzer (Agilent, Santa Clara, CA, USA) was used to measure the oxygen consumption rate (OCR) and extracellular acidification rate (ECAR). Prior to analysis, fresh assay medium was added after washing the adherent cells with the base assay medium. The cartridge was set up to deliver the chemical compounds in that order: glucose (10 mM), oligomycin (1 µM), and 2-DG (50 mM). Wave software automatically plotted the OCR and ECAR curves. In Vivo Proliferation Assay Female BALB/c-nude mice aged five weeks (Chinese Academy of Sciences, Beijing, China) were used for in vivo proliferation assays. The subcutaneous tissues of the mice were xenografted with 1×10 7 LM3 cells. Tumor volumes were measured every two days, and calculated using the formula: V = (Length×Width 2 )/2. The mice were sacrificed after four weeks, and the tumors were excised. The study was approved by the Research Ethics Committee of Shandong Provincial Qianfoshan Hospital, and conducted in compliance with the Declaration of Helsinki. Accession Numbers Sequencing data sets described in this study have been deposited in the Gene Expression Omnibus (GEO) under accession number GSE282508. Statistical Analysis All experiments were conducted at least three times. Plots were created using Prism version 10.0 (GraphPad) and statistical analysis was conducted using SPSS version 27.0 software. Data are shown as the mean values ± SD. The growth curve and in vivo proliferation data were evaluated using one-way ANOVA, and the Student's t-test was used to compare the two groups. P < 0.05 were regarded as statistically significant. Ethical Statement This study was approved by the Research Ethics Committee of Shandong Provincial Qianfoshan Hospital, and was conducted in compliance with the Declaration of Helsinki. Results RNAs interacting with PDHE1α were identified through iRIP-seq analysis We developed an analytical approach to characterize RNA-binding proteins (RBPs), by integrating subcellular separation, two phase extraction with acidic guanidinium-thiocyanate-phenol-chloroform, and quantitative mass spectrometry (Fig. 1A) [16]. Using this approach, we identified 200 enzymes from a range of metabolic pathways as RBPs, thereby uncovering an unexpected link between metabolic activity and RNA regulation. Notably, PDHE1α was firstly identified to possess RBP characteristics. Given the well-established critical function of PDHE1α in pyruvate oxidation [17], we focused on its interaction with RNA. Treatment with RNase boosted PDH activity, indicating that RNA-binding might inhibit the enzyme (Fig. 1B). To identify RNA molecules that directly interact with PDHE1α, we employed an advanced RNA immunoprecipitation technique, enhanced for greater sensitivity and specificity, combined with high-throughput sequencing (iRIP-seq) in LM3 cells. This method involves in vivo cross-linking of RNAs and proteins using UV irradiation, followed by immunoprecipitation of RNA-bound proteins with antibodies specific for PDHE1α. Following immunoprecipitation, micrococcal nuclease (MNase) treatment was performed, and RNAs was extracted for paired-end deep sequencing using the Illumina NextSeq 500 platform (Fig. 1C). Two biological replicates were included in each test to ensure robustness and reproducibility of the results. Gene Ontology (GO) and KEGG pathway analysis were performed to obtain a more detailed understanding of the potential biological functions and pathways associated with the identified RNAs (Supplementary Fig. 1). According to GO analysis, the identified RNAs were involved in several pathways, such as translation, rRNA processing and cell growth, whereas KEGG analysis showed that PDHE1α-interacting RNAs were involved in RNA transport, ribosomes, and other functions. Mapping the distribution of reads to the reference genome revealed that the IP group and Input group reads occupied a large space in introns and intergenic regions (Fig. 2A). The correlation scatterplots of the Input and IP samples were further drawn, and the R-values of the correlation coefficients for the two repeated experiments were 0.78 and 0.74, respectively (Fig. 2B). Cluster analysis was conducted according to the sample correlation coefficient, which revealed clean differences between the IP and Input groups (Fig. 2C). The peaks in the two IP group datasets overlapped, and 515 specific peaks were enriched (Fig. 2D). We then mapped the distribution of specific overlapping peaks to the reference genome, which revealed that specific overlapping peaks were mainly concentrated in the introns (48.5%), antisense (21.6%) and intergenic regions (9.4%) (Fig. 2E). Among the shared peaks, 65.2% were mapped to mRNAs, 17.5% were mapped to lncRNAs and 3.3% were mapped to snoRNAs (Fig. 2F). We used the HOMER algorithm to examine the motifs to identify the binding sequence preference of PDHE1α, which revealed a preference for GC-rich motifs (Fig. 2G). Identification of SNHG15 as a potential PDHE1α-interacting RNA. To further investigate potential PDHE1α-interacting RNAs, the candidate lncRNA SNHG15 was selected, and its binding regions were visualized using the Integrative Genomics Viewer (Fig. 3A). SNHG15 is distributed in both the cytoplasm and nucleus of HCC cells, with an increased abundance in the cytoplasm [18]. RNA-FISH staining showed partial localization of SNHG15 in the mitochondria of LM3 cells (Figs. 3B and C), suggesting that it is a potential PDHE1α-interacting RNA. SNHG15 directly binds to PDHE1α and dampens the enzymatic activity of PDH Based on our iRIP-seq findings, lncRNA SNHG15 is identified as a potential interaction partner of PDHE1α (Fig. 3A). Immunoprecipitation (IP) utilizing antibodies specific to PDHE1α was employed to conduct RNA immunoprecipitation followed by real-time quantitative reverse transcription PCR (RIP-qPCR). Subsequent qPCR analysis demonstrated a significant enrichment of SNHG15 in immunoprecipitates of PDHE1α, validating the iRIP-seq results (Fig. 4A). In contrast, control lncRNA-RMRP was not found in the immunoprecipitates of PDHE1α, revealing a particular interaction between PDHE1α and SNHG15 (Fig. 4A). To further confirm this interaction, PDHE1α was pulled down from LM3 cell lysates using biotinylated SNHG15 rather than antisense SNHG15 (Fig. 4B). Next, we investigated the potential direct interaction between PDHE1α and SNHG15. An in vitro His-tag pulldown test demonstrated that recombinant PDHE1α (rPDHE1α) directly binds to SNHG15, as opposed to antisense SNHG15 (Fig. 4C). To further support the proposition that SNHG15 binds to PDHE1α, wild-type FLAG-tagged PDHE1α or its fragments (F1 and F2) were expressed in transfected LM3 cells for an RIP-qPCR assay using an anti-FLAG antibody. These findings indicated that both fragments 1 and 2 interacted with SNHG15 (Fig. 4D). In addition, PDH activity decreased when SNHG15 was overexpressed, but increased when SNHG15 was knocked down by ssSNHG15 (Figs. 4E and F). Moreover, two additional HCC cell lines, Huh7 and Hep3B, showed similar results (Supplementary Figs. 2A-E). Previous studies have indicated that PDH activity is regulated via phosphorylation [17]. Consequently, we hypothesized that SNHG15 might affect the phosphorylation state of PDHE1α. As shown in Figs. 4G and 4H, overexpression of SNHG15 elevated the phosphorylation levels of PDHE1α in LM3 cells, whereas SNHG15 knockdown decreased its phosphorylation levels. SNHG15 did not affect the expression of PDHE1α at the protein or mRNA levels (Fig. 4G, Supplementary Fig. 3). These data demonstrate that SNHG15 directly binds to PDHE1α and regulates the enzymatic activity of PDH by modulating its phosphorylation. SNHG15 modulates PDHE1α through PGK1-PDK1-PDHE1α axis As a protein kinase, mitochondrial PGK1 phosphorylates PDK1 at threonine 338. Upon activation through phosphorylation, PDK1 subsequently phosphorylates and inhibits the PDHc [19]. PGK1 is recognized as an RNA-binding protein. SNHG15 directly binds to PDHE1α and dampens the enzymatic activity of PDH. Based on these findings, we hypothesize that SNHG15 may modulate the PGK1-PDK1-PDHE1α signaling pathway. Initially, we investigated the potential interaction between SNHG15 and either PGK1 or PDK1.The RIP experiment demonstrated significant enrichment of SNHG15 in the immunoprecipitates of PGK1 and PDK1 (Figs. 5A and B). Additionally, the phosphorylation level of PDK1 was increased by the overexpression of SNHG15 and decreased by its knockdown (Fig. 5C). The expression levels of PGK1 and PDK1, both at the protein and mRNA levels, were not affected by SNHG15 (Fig. 5C, Supplementary Fig. 3). Moreover, overexpression of SNHG15 promoted the phosphorylation of PDHE1α (S293) and PDK1 (T338), which were impaired by the treatment with the PDK inhibitor DCA and PGK1 knockdown, suggesting that SNHG15 indeed modulated the phosphorylation of these two enzymes through PGK1 and PDK1(Fig. 5D). Furthermore, the RNA pull-down experiment revealed that SNHG15 was capable of simultaneously pulling down both recombinant PGK1 (rPGK1) and recombinant PDK1 (rPDK1) (Fig. 5E), whereas rPDK1 and rPDHE1α showed similar results (Fig. 5F). We then investigated whether the interactions between PDK1 and PDHE1α or between PGK1 and PDK1 could be affected by SNHG15. The His-tag pull-down assay revealed a direct interaction between rPGK1 and rPDK1, and their interaction was enhanced when SNHG15 was added rather than antisense SNHG15 (Fig. 5G). rPDK1 and rPDHE1α showed similar results (Fig. 5H). Collectively, these data suggest that SNHG15 may act as an adaptor molecule to enhance the interactions between PDK1 and PDHE1α or PGK1 and PDK1, driving the PGK1-PDK1-PDHE1α axis and increasing the phosphorylation of PDK1 and PDHE1α. SNHG15 suppresses the TCA cycle and promotes aerobic glycolysis in HCC The interactions between SNHG15 and PDHE1α have the potential to influence cellular metabolic processes, given that the PDHc functions as a critical junction between the TCA cycle and glycolysis. To confirm this hypothesis, we assessed the levels of oxidative phosphorylation and glycolysis in HCC cells with SNHG15 overexpression and knockdown. As expected, SNHG15 overexpression decreased oxygen consumption and acetyl-CoA concentrations, whereas SNHG15 knockdown had the opposite effect (Figs. 6A and B). Furthermore, SNHG15 overexpression significantly increases ATP levels, indicating an enhanced cellular energy state, whereas SNHG15 knockdown induced a considerable decrease in ATP production (Fig. 6C). To further confirm these findings, we investigated whether SNHG15 may have an impact on the degree of glycolysis. SNHG15 overexpression increased glucose uptake and lactate generation, whereas SNHG15 knockdown decreased these processes in LM3 cells (Figs. 6D and E). Moreover, two additional HCC cell lines, Huh7 and Hep3B, showed comparable effects (Supplementary Figs. 2C and F). We then used the Seahorse Analyzer to measure glycolytic flow. Glucose was first added to increase glycolytic flux, after which the ATP synthase inhibitor oligomycin was added to inhibit oxidative phosphorylation and quantify glycolytic ability. Glycolytic reserve was evaluated following the subsequent administration of 2-deoxy-D-glucose (2-DG), a well-established inhibitor of glycolysis (Figs. 6F and G). The analysis revealed that SNHG15 overexpression upregulated glycolysis with a considerable increase in glycolytic capacity and glycolytic reserve. Treatment with the PDH activator, sodium dichloroacetate (DCA), reversed this effect (Fig. 6F). Conversely, SNHG15 knockdown decreased total glycolytic flow with a considerable decrease in glycolysis, glycolytic capacity, and glycolytic reserve (Fig. 6G). These observations suggest that SNHG15 plays a critical role in the regulation of cellular energy metabolism. Specifically, SNHG15 appeared to inhibit oxidative phosphorylation by facilitating the conversion of pyruvate into lactate rather than acetyl-CoA for the TCA cycle. SNHG15 promotes cell proliferation via the PGK1-PDK1-PDHE1α axis SNHG15 has been implicated in the promotion of HCC cells [18, 20]. Here, we replicated these findings, as the CCK8 experiment demonstrated that SNHG15 overexpression boosted cell proliferation whereas SNHG15 knockdown had the opposite effect (Figs. 7A and B). Furthermore, the growth curve showed the same trend, whereas treatment with a PDH activator reduced the proliferation of LM3-SNHG15 cells to levels comparable to those of the untreated group (Figs. 7A and B). These findings suggest that SNHG15 plays a critical role in enhancing the proliferation of HCC cells via PDHc. To provide additional evidence that SNHG15 promotes cell proliferation via the PGK1-PDK1-PDHE1α axis, we overexpressed SNHG15 followed by rescue with PDHE1α or PDK1 knockdown. According to the CCK8 assay, SNHG15 overexpression promoted cell proliferation, whereas PDHE1α knockdown decreased it to a level comparable to that of the control group (Figs. 7C–E). Overexpressing SNHG15 did not promote cell proliferation in PDHE1α knockdown cells rescued with empty vector. In cells rescued with PDHE1α-WT, overexpression of SNHG15 enhanced cel proliferation, but overexpressing PDHE1α-S293A mutants failed to rescue the SNHG15-promoted cell proliferation (Supplementary Figs. 4A-C). Moreover, PDK1 showed similar effects (Figs. 7F–H). PDK1-T338A could also block the effect of SNHG15 on cell proliferation (Supplementary Figs. 4D-F). Additionally, we determined the half-maximal inhibitory concentrations (IC50) of oligomycin and 2-DG in LM3 cells overexpressing SNHG15. Compared to the control group, the IC50 of oligomycin, an inhibitor of oxidative phosphorylation, was higher in LM3-SNHG15 cells, indicating that they were less sensitive to the inhibition of mitochondrial ATP synthesis. In contrast, LM3-SNHG15 cells showed a significantly lower IC50 for 2-DG, indicating an increased sensitivity to glycolytic inhibition. This suggested that SNHG15 may suppress oxidative phosphorylation and enhance glycolytic activity, making these cells more dependent on glycolysis for energy production. These data suggest that SNHG15 may promote metabolic reprogramming, favoring glycolysis over oxidative phosphorylation and altering the cells' energy production pathways. Finally, we assessed the functional role of SNHG15 in vivo by conducting a series of experiments using animal models. These studies aimed to evaluate the influence of SNHG15 on tumor growth and overall disease progression in a more complex physiological environment. SNHG15 overexpression promoted tumor growth in mice, which is consistent with the findings of the cultured-cell assays (Figs. 7J and K). Compared with control cells, tumors generated from SNHG15 overexpressing cells showed lower PDH activity and higher lactate levels (Fig. 7L). We examined RNA-sequencing data from TCGA database to further investigate the expression of SNHG15 in clinical samples. The findings showed that SNHG15 was markedly elevated in HCC tumor samples compared to the surrounding non-tumorous tissues (Supplementary Fig. 5A). Survival analysis revealed that the elevated SNHG15 expression was correlated with poorer overall survival and a higher risk of disease progression, suggesting its potential as a prognostic biomarker in HCC (Supplementary Fig. 5B). These data collectively indicate that SNHG15 substantially enhances glycolytic activity and facilitates the proliferation of HCC cells in both in vitro and in vivo settings. Consequently, SNHG15 may play a pivotal role in tumor progression by acting as a key factor in sustaining proliferative capacity through the modulation of cellular metabolism. These findings highlight the critical role of SNHG15 in regulating cellular metabolism and identify it as a potential target for therapeutic interventions in clinical treatment. Discussion Two key classes of biological macromolecules, RNA and proteins, can physically interact to control each other's fate and function. In this study, PDHE1α was characterized as an RBP and SNHG15 was identified as a potential PDHE1α-interacting lncRNA. We further investigated the mechanism of SHNG15-mediated carcinogenesis by its interaction with PDHE1α. Specifically, SNHG15 served as an adaptor molecule, enhancing the interactions of the PGK1-PDK1-PDHE1α axis. This, in turn, increase the levels of phosphorylation and dampens the PDH enzyme activity. Finally, reduced PDH activity impaired oxidative phosphorylation, promoted glycolysis and ultimately accelerated HCC cell growth (Fig. 8). LncRNAs are critical factors in the mechanisms of carcinogenesis [21], while a class of RBPs are essential regulators of RNAs that participate in several processes at the post-transcriptional level, ultimately dictating the fate and function of each transcript in the cell [22-24]. In addition, the dysregulated expression of some RBPs can cause a wide variety of diseases, including cardiovascular disorders and cancers [25, 26]. In a previous study, we combined subcellular separation, two phase extraction with acidic guanidinium-thiocyanate-phenol-chloroform, and quantitative mass spectrometry to characterize RBPs. Using this approach, we identified 200 enzymes from a range of metabolic pathways as RBPs. This included PDHE1α, a critical gatekeeper of mitochondrial respiration. Since mitochondrial metabolism and dysfunction have been reported to contribute to the development of cancer [27], we chose PDHE1α for this study. Next, iRIP-seq was conducted to identify RNA molecules that specifically bind to PDHE1α in LM3 cells, and lncRNA SNHG15 was one of the candidates that intrigued us most, as it is essential to the development of certain human cancers [28]. In particular, SNHG15 expression was found to be increased in HCC and correlated with a negative prognosis [29]. SNHG15 regulates miRNAs such as miR‐141‐3p [18], miR-490-3p [30] and miR-18b-5p [31] to promote HCC progression. Consistent with this role, our study confirmed the aberrant expression and oncogenic role of SNHG15, after which we focused on the regulatory mechanisms of SNHG15 in HCC. In addition to energy generation, mitochondria are involved in cell division, growth, senescence, and cell death [32]. PDHc is crucial for the mitochondrial TCA cycle function, acting as a central enzyme complex that facilitates the metabolism of pyruvate to acetyl-CoA, a key step in cellular energy production. Recent studies have demonstrated the significant role of PDHc dysfunction in various pathological conditions, linking it to the development of metabolic diseases such as obesity and diabetes, ischemic injury responses and cancer [17, 33-35]. Our experiments showed that SNHG15 could directly bind to PDHE1α, thereby reducing PDH activity but did not alter PDHE1α expression levels. The regulation of PDH complex activity is largely controlled by the reversible phosphorylation of PDHE1α [36]. Consistently, SNHG15 enhanced the phosphorylation of PDHE1α. PDK1 directly phosphorylates PDHE1α and inhibits its enzymatic activity [37]. Mitochondrial PGK1 acts as a protein kinase that phosphorylates PDK1 at threonine 338, leading to its activation. Activated PDK1 phosphorylates and inhibits PDHc [19]. Interestingly, the RIP experiment confirmed that SNHG15 can bind to both PDK and PGK1 without altering their expression levels. However, SNHG15 facilitated the interaction between PGK1 and PDK1, as well as between PDK1 and PDHE1α, leading to increased phosphorylation of both PDK1 and PDHE1α. Therefore, we suggest that SNHG15 modulates PDHE1α phosphorylation to reduce its enzyme activity via the PGK1-PDK1-PDHE1α signaling axis. Based on Warburg’s observations, aerobic glycolysis in cancer cells is caused by mitochondrial malfunction, which is thought to be a risk factor for cancer [38]. The availability of anabolic substrates necessary for the synthesis of DNA, proteins, and lipids is essential because of the dysregulated proliferation of cancer cells, which involves the mitochondrial TCA cycle [39]. Considering the metabolic rearrangements typical of HCC, an increasing number of studies have focused on key metabolic enzymes as well as the drivers of metabolic changes [40]. Several key findings of this study highlight the intricate and multifaceted nature of SNHG15-induced alterations in HCC cell metabolism. Crucially, we demonstrated that SNHG15 decreased PDH enzyme activity to increase the conversion of pyruvate into lactate, thus impairing oxidative phosphorylation. Accordingly, SNHG15 enhanced cell proliferation via the PGK1-PDK1-PDHE1α axis. These findings may facilitate the development of innovative therapeutic strategies for HCC treatment. Declarations Funding This work was supported by grants from the National Natural Science Foundation of China (82303249 to C.W., 82002755 to H.C.), Natural Science Foundation of Shandong Province (ZR2023QH144 to C.W., ZR2022QH007 to X.Z, ZR2022QH290 to Y.W.), National Natural Science Foundation Cultivating Fund from the Qianfoshan Hospital of Shandong Province (QYPY-RC2022NSFC1004 to C.W., QYPY2022NSFC0604 to Y.W.), National Natural Science Foundation Cultivating Fund from the Shandong First Medical University (202201-090 to C.W.), Youth Innovation Team Plan in Colleges and Universities of Shandong Province (2023KJ172 to C.W., 2022KJ198 to H.C.), and Beijing Kechuang Medical Development Foundation (KC2023-JX-0186-BQ076 to C.W., KC2023-JX-0186-FQ028 to Y.W.). Competing Interests The authors declare no competing interests. Author contributions C. W. and X. Z. conceived and designed the study. H. C., Y. W., W.C., and X. 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Metabolic dysregulation and emerging therapeutical targets for hepatocellular carcinoma. Acta pharmaceutica Sinica B 12(2), 558–580 (2022). Additional Declarations There is no conflict of interest Supplementary Files SupplementaryMaterial.docx Supplementary Material Sourcedata.docx Source data. Cite Share Download PDF Status: Under Review Version 1 posted Review # 2 received at journal 25 Apr, 2026 Review # 1 received at journal 23 Apr, 2026 Reviewer # 3 agreed at journal 19 Apr, 2026 Reviewer # 2 agreed at journal 15 Apr, 2026 Reviewer # 1 agreed at journal 15 Apr, 2026 Reviewers invited by journal 15 Apr, 2026 Submission checks completed at journal 07 Apr, 2026 Editor assigned by journal 02 Apr, 2026 First submitted to journal 02 Apr, 2026 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-9307919","acceptedTermsAndConditions":true,"allowDirectSubmit":false,"archivedVersions":[],"articleType":"Article","associatedPublications":[],"authors":[{"id":623841663,"identity":"2baa8d17-167f-4d8e-af18-bb07cd1a484d","order_by":0,"name":"chunqing wang","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAABAklEQVRIiWNgGAWjYLACxgYgwQzEHxiY+cEiPMRqYZzBwCzZQLwWkC4eYrQYHD97+MXPHYfz+I7zHn5t88daQndGAuODt20M8ua4tJzJS7PsPXO4WPIwX5p1blu6hNmNBGbDuW0MhjsbsGsxO5BjZszYdjhxw2EeM+PchsN1QC1s0rxtDAkGB3BoOf8GSYvFn8MgW9h/49VyI8f4MVSL8WMGNrAWNmZ8WuxvvDFj7G1LT5wJtAXEkDA787BZcs45CcMNOLRI9ucYf/jZZp3Yd/6M8YcfwBAzO5588MObMht5XLYAAZsEmDoAY0CiSQKneiBg/gDVAmWMglEwCkbBKEADAAhSYa13PutcAAAAAElFTkSuQmCC","orcid":"","institution":"The First Affiliated Hospital of Shandong First Medical University \u0026 Shandong Provincial Qianfoshan Hospital","correspondingAuthor":true,"prefix":"","firstName":"chunqing","middleName":"","lastName":"wang","suffix":""},{"id":623841664,"identity":"4e7469aa-40ae-4b55-923d-76a1cd214b7f","order_by":1,"name":"hanxiang chen","email":"","orcid":"","institution":"Shandong Qianfoshan Hospital","correspondingAuthor":false,"prefix":"","firstName":"hanxiang","middleName":"","lastName":"chen","suffix":""},{"id":623841665,"identity":"b7c3ae81-73fc-4e42-8250-71435a017ca3","order_by":2,"name":"yunqiu wang","email":"","orcid":"","institution":"Shandong Qianfoshan Hospital","correspondingAuthor":false,"prefix":"","firstName":"yunqiu","middleName":"","lastName":"wang","suffix":""},{"id":623841666,"identity":"29fb7f28-ecdc-4081-9138-2f67706bf4ce","order_by":3,"name":"wei chong","email":"","orcid":"https://orcid.org/0000-0002-1074-8595","institution":"","correspondingAuthor":false,"prefix":"","firstName":"wei","middleName":"","lastName":"chong","suffix":""},{"id":623841667,"identity":"4c3bad5b-ec9c-4f78-8834-bb5dba0c2f48","order_by":4,"name":"xiaofei wang","email":"","orcid":"","institution":"The First Affiliated Hospital of Shandong First Medical University \u0026 Shandong Provincial Qianfoshan Hospital","correspondingAuthor":false,"prefix":"","firstName":"xiaofei","middleName":"","lastName":"wang","suffix":""},{"id":623841668,"identity":"25281802-7183-4a56-9960-10835c6ac730","order_by":5,"name":"lili Wang","email":"","orcid":"","institution":"The First Affiliated Hospital of Shandong First Medical University \u0026 Shandong Provincial Qianfoshan Hospital","correspondingAuthor":false,"prefix":"","firstName":"lili","middleName":"","lastName":"Wang","suffix":""},{"id":623841669,"identity":"dc7013fc-f26a-44b1-ba01-54f3bc2ed440","order_by":6,"name":"Jinjin zhang","email":"","orcid":"","institution":"The First Affiliated Hospital of Shandong First Medical University \u0026 Shandong Provincial Qianfoshan Hospital","correspondingAuthor":false,"prefix":"","firstName":"Jinjin","middleName":"","lastName":"zhang","suffix":""},{"id":623841670,"identity":"66213103-e072-4c54-900a-4758cba9227a","order_by":7,"name":"Zhao Xiaoqing","email":"","orcid":"","institution":"The Second Hospital, Cheeloo College of Medicine, Shandong University","correspondingAuthor":false,"prefix":"","firstName":"Zhao","middleName":"","lastName":"Xiaoqing","suffix":""}],"badges":[],"createdAt":"2026-04-03 02:30:59","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-9307919/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-9307919/v1","draftVersion":[],"editorialEvents":[],"editorialNote":"","failedWorkflow":false,"files":[{"id":107707850,"identity":"a124b3b1-5d64-411e-a1c4-a04f5d6ea471","added_by":"auto","created_at":"2026-04-24 09:21:16","extension":"jpg","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":969909,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eOutline of the iRIP-seq protocol for\u003c/strong\u003e \u003cstrong\u003ethe identification of PDHE1α- interacting RNAs.\u003c/strong\u003e \u003cstrong\u003eA \u003c/strong\u003eSchematic representation of the isolation of RBPs. \u003cstrong\u003eB\u003c/strong\u003e PDH activity of cells treated with RNase inhibitor or RNase (\u003cem\u003en \u003c/em\u003e= 5). \u003cstrong\u003eC\u003c/strong\u003e The workflow of iRIP-seq. The data represent mean values ± SD. **\u003cem\u003eP\u003c/em\u003e \u0026lt; 0.01, ***\u003cem\u003eP\u003c/em\u003e\u0026lt; 0.001, n.s., not significant.\u003c/p\u003e","description":"","filename":"Figure1.jpg","url":"https://assets-eu.researchsquare.com/files/rs-9307919/v1/9e9412b0c2fccdbee889d20b.jpg"},{"id":107707438,"identity":"233f9725-42e4-4276-aeea-62a38eba8023","added_by":"auto","created_at":"2026-04-24 09:20:18","extension":"jpg","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":882322,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eCharacterization of the PDHE1α-RNA interaction profile by iRIP-seq analysis.\u003c/strong\u003e \u003cstrong\u003eA \u003c/strong\u003eDistribution of mapped reads across the reference genome. \u003cstrong\u003eB\u003c/strong\u003e Scatterplot of read abundance across the reference genome in paired samples.\u003cstrong\u003e C\u003c/strong\u003e Heatmap displayingthe hierarchically clustered pearson correlation of Input and PDHE1α IP samples. \u003cstrong\u003eD\u003c/strong\u003e Venn plot of peaks identified from the IP_1 and IP_2 samples. \u003cstrong\u003eE\u003c/strong\u003e Distribution of specific overlapped peak reads across the reference genome. \u003cstrong\u003eF\u003c/strong\u003e Distribution of specific overlapped peak genes by types. \u003cstrong\u003eG\u003c/strong\u003eMotif analysis showing the top 5 peaks of preferred binding motifs of PDHE1α according to the HOMER algorithm.\u003c/p\u003e","description":"","filename":"Figure2.jpg","url":"https://assets-eu.researchsquare.com/files/rs-9307919/v1/abfe5879d012c047b5c9748c.jpg"},{"id":107652544,"identity":"e782fc38-2f6a-4990-9dcc-e65bc849c5a2","added_by":"auto","created_at":"2026-04-23 15:17:09","extension":"jpg","order_by":3,"title":"Figure 3","display":"","copyAsset":false,"role":"figure","size":1078163,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eIdentification of SNHG15 as a potential PDHE1α-interacting RNA. A\u003c/strong\u003eVenn diagrams of potential PDHE1α-interacting lncRNAs (Left). Cumulative distribution plot of the mapped reads of SNHG15 (Right). \u003cstrong\u003eB\u003c/strong\u003eThe cellular localization of SNHG15 was examined by RNA-FISH. Cell nuclei were counter-stained with DAPI, and mitochondria were labeled with MitoTracker. The scale bar was 20 μm. \u003cstrong\u003eC \u003c/strong\u003eThe abundance of SNHG15 and GAPDH\u003cem\u003e \u003c/em\u003e(cytosol marker) in isolated mitochondria from LM3 cells (\u003cem\u003en\u003c/em\u003e = 3). The relative enrichment of each RNA was calculated as \u003cimg height=\"17\" src=\"data:image/png;base64,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\" width=\"99\"/\u003e, followed by normalization of all ratios to GAPDH\u003cem\u003e \u003c/em\u003ein the control group (the value of the first \u003cem\u003eGAPDH \u003c/em\u003ecolumn was defined as 1). The data represent mean values ± SD. **\u003cem\u003eP\u003c/em\u003e \u0026lt; 0.01.\u003c/p\u003e","description":"","filename":"Figure3.jpg","url":"https://assets-eu.researchsquare.com/files/rs-9307919/v1/be9c60f92b455f632e46c1fc.jpg"},{"id":107707655,"identity":"b9be4618-ad44-4d26-97e2-2acd0e5de9e0","added_by":"auto","created_at":"2026-04-24 09:20:50","extension":"jpg","order_by":4,"title":"Figure 4","display":"","copyAsset":false,"role":"figure","size":1239317,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eSNHG15 interacts with PDHE1α.\u003c/strong\u003e A Immunoprecipitation of PDHE1α. The immunoblots of PDHE1α in the mitochondrial lysate and immunoprecipitates (Left). COX4 was used as a loading control. The electrophoresis with 2% agar gel of the qRT-PCR amplicon of SNHG15 (Middle). The abundance of SNHG15 in PDHE1α immunoprecipitates was determined by qRT-PCR (Right) (\u003cem\u003en\u003c/em\u003e = 3). LncRNA-RMRP was used as an RNA control.\u003cstrong\u003e B\u003c/strong\u003e\u003cem\u003e In vitro \u003c/em\u003etranscription generated biotinylated SNHG15 and antisense SNHG15, which were subsequently incubated with mitochondrial samples. Streptavidin-conjugated beads were used to separate the RNA-protein complexes. Biotinylated antisense SNHG15 acted as the control while COX4 acted as a loading control. \u003cstrong\u003eC\u003c/strong\u003e His-tagged rPDHE1α was attached to the His-tag magnetic beads. The isolated beads then incubated with SNHG15 or antisense SNHG15. The RNA-protein complexes were separated, and the levels of SNHG15 were determined by qRT-PCR (\u003cem\u003en\u003c/em\u003e = 3). \u003cstrong\u003eD\u003c/strong\u003eSchematic diagram of full-length PDHE1α and the tested fragment. FLAG immunoblots after cells were transfected with plasmids that expressed the FLAG-tagged full-length sequence or fragments of PDHE1α (Left). The electrophoresis with 2% agar gel of the SNHG15 qRT-PCR amplicon (Middle). qRT-PCR analysis of SNHG15 enrichment in the FLAG immunoprecipitates (Right) (\u003cem\u003en\u003c/em\u003e= 3). LncRNA-RMRP was used as an RNA control. \u003cstrong\u003eE\u003c/strong\u003e The abundance of SNHG15 in LM3 cells with SNHG15 overexpression (Left) and knockdown (Right) were determined by qRT-PCR (\u003cem\u003en\u003c/em\u003e = 3). \u003cstrong\u003eF \u003c/strong\u003ePDH activity of LM3 cells with SNHG15 overexpression (Left) and knockdown (Right) (\u003cem\u003en\u003c/em\u003e= 4). \u003cstrong\u003eG\u003c/strong\u003e Western blot analysis of p-PDHE1α levels in the mitochondrial lysates. COX4 acted as a loading control.\u003cstrong\u003e H\u003c/strong\u003e ImageJ was utilized to densitometrically quantify the band intensities (\u003cem\u003en\u003c/em\u003e= 3). The data represent mean values ± SD. *\u003cem\u003eP\u003c/em\u003e \u0026lt; 0.05, **\u003cem\u003eP\u003c/em\u003e \u0026lt; 0.01, ***\u003cem\u003eP\u003c/em\u003e\u0026lt; 0.001, n.s., not significant.\u003c/p\u003e","description":"","filename":"Figure4.jpg","url":"https://assets-eu.researchsquare.com/files/rs-9307919/v1/2acc2b928409f57152aad69a.jpg"},{"id":107652546,"identity":"bf8b8572-faf9-4bd1-a567-ba04c19b82e8","added_by":"auto","created_at":"2026-04-23 15:17:09","extension":"jpg","order_by":5,"title":"Figure 5","display":"","copyAsset":false,"role":"figure","size":1293058,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eSNHG15 modulates the PGK1-PDK1-PDHE1α axis. A\u003c/strong\u003e Immunoprecipitation of PGK1. Immunoblots of PGK1 in the mitochondrial lysate and immunoprecipitates (Left). COX4 was used as a loading control. The electrophoresis with 2% agar gel of the qRT-PCR amplicon of SNHG15 (Middle). The abundance of SNHG15 in PGK1 immunoprecipitates was determined by qRT-PCR (Right) (\u003cem\u003en \u003c/em\u003e= 3). LncRNA-RMRP was used as an RNA control. \u003cstrong\u003eB\u003c/strong\u003e Immunoprecipitation of PDK1. Immunoblots of PDK1 in the mitochondrial lysate and immunoprecipitates (Left). COX4 was used as a loading control. The electrophoresis with 2% agar gel of the qRT-PCR amplicon of SNHG15 (Middle). The abundance of SNHG15 in PDK1 immunoprecipitates was determined by qRT-PCR (Right) (\u003cem\u003en \u003c/em\u003e= 3). LncRNA-RMRP acted as an RNA control. \u003cstrong\u003eC\u003c/strong\u003eWestern blot analysis of p-PDK1 in the mitochondrial lysates.\u003cstrong\u003e \u003c/strong\u003eImageJ was used to densitometrically quantify the band intensities (\u003cem\u003en \u003c/em\u003e= 3). \u003cstrong\u003eD\u003c/strong\u003eImmunoblots of p-PDHE1α (S293) and p-PDK1 (T338) in the cell lysates. LM3 cells overexpressing SNHG15 were incubated with the indicated concentrations of PDK inhibitor DCA for 24 h. DMSO was added instead in the control groups. LM3 cells overexpressing SNHG15 were treated with siRNAs targeting PGK1. Biotinylated SNHG15 and antisense SNHG15 were incubated with rPGK1 and rPDK1 (\u003cstrong\u003eE\u003c/strong\u003e) or rPDK1 and rPDHE1α (\u003cstrong\u003eF\u003c/strong\u003e). Streptavidin-conjugated beads were used to separate the RNA-protein complexes. Biotinylated antisense SNHG15 acted as a control. His-tag separation magnetic beads were incubated with His-tagged rPDK1 (\u003cstrong\u003eG\u003c/strong\u003e) or rPDHE1α (\u003cstrong\u003eH\u003c/strong\u003e). Following isolation, the beads were incubated with either SNHG15 or antisense SNHG15 before rPGK1 or rPDK1 was added. Western blot analysis was performed to examine the pulled-down recombinant protein. The data represent mean values ± SD. **\u003cem\u003eP\u003c/em\u003e \u0026lt; 0.01, ***\u003cem\u003eP\u003c/em\u003e \u0026lt; 0.001, n.s., not significant.\u003c/p\u003e","description":"","filename":"Figure5.jpg","url":"https://assets-eu.researchsquare.com/files/rs-9307919/v1/83ace91a02b5865be98cf4f7.jpg"},{"id":107707678,"identity":"f90fcfdc-d7d5-4be7-87b5-449388de1ba2","added_by":"auto","created_at":"2026-04-24 09:20:54","extension":"jpg","order_by":6,"title":"Figure 6","display":"","copyAsset":false,"role":"figure","size":1160143,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eSNHG15 suppresses the TCA cycle and promotes glycolysis in cultured HCC cells.\u003c/strong\u003e \u003cstrong\u003eA\u003c/strong\u003e Relative oxygen consumption rates (OCR) of LM3 cells with SNHG15 overexpression (Above) and SNHG15 knockdown (Below). \u003cstrong\u003eB \u003c/strong\u003eAcetyl-CoA levels in LM3 cells with SNHG15 overexpression (Above) and SNHG15 knockdown (Below) (\u003cem\u003en\u003c/em\u003e= 4). \u003cstrong\u003eC\u003c/strong\u003e ATP levels in LM3 cells with SNHG15 overexpression (Above) and SNHG15 knockdown (Below) (\u003cem\u003en\u003c/em\u003e = 6). \u003cstrong\u003eD \u003c/strong\u003eRelative glucose uptake of LM3 cells with SNHG15 overexpression (Left) and SNHG15 knockdown (Right) (\u003cem\u003en \u003c/em\u003e= 3). \u003cstrong\u003eE\u003c/strong\u003e Lactate production of LM3 cells with SNHG15 overexpression (Left) and SNHG15 knockdown (Right) (\u003cem\u003en\u003c/em\u003e = 3). \u003cstrong\u003eF, G \u003c/strong\u003eAnalysis of glycolytic flux using the Seahorse Analyzer. Glycolysis analysis in LM3 cells overexpressing SNHG15 treated with the PDH activator DCA (20 mM) (\u003cem\u003en \u003c/em\u003e= 5). The data represent mean values ± SD. *\u003cem\u003eP\u003c/em\u003e \u0026lt; 0.05, **\u003cem\u003eP\u003c/em\u003e \u0026lt; 0.01, ***\u003cem\u003eP\u003c/em\u003e \u0026lt; 0.001, n.s., not significant.\u003c/p\u003e","description":"","filename":"Figure6.jpg","url":"https://assets-eu.researchsquare.com/files/rs-9307919/v1/d2027dceecaef2dbb0b8997c.jpg"},{"id":107652549,"identity":"dbdb81a5-f01d-42b5-91d5-9475a732bf0b","added_by":"auto","created_at":"2026-04-23 15:17:09","extension":"jpg","order_by":7,"title":"Figure 7","display":"","copyAsset":false,"role":"figure","size":1251866,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eSNHG15 promotes cellular proliferation via the PGK1-PDK1-PDHE1αsignaling axis.\u003c/strong\u003e \u003cstrong\u003eA\u003c/strong\u003eProliferation of LM3 cells with SNHG15 overexpression (Left) and SNHG15 knockdown (Right) was measured using the CCK8 assay.DCA (20 mM) was used to treat LM3-SNHG15 cells for rescue trials. \u003cstrong\u003eB \u003c/strong\u003eGrowth curves of LM3 cells with SNHG15 overexpression (Left) and SNHG15 knockdown (Right). For rescue experiments, LM3-SNHG15 cells were treated by DCA (20 mM). \u003cstrong\u003eC \u003c/strong\u003eWestern blot analysis of PDHE1α in the lysates. \u003cstrong\u003eD\u003c/strong\u003e The levels of SNHG15 were determined using qRT-PCR (\u003cem\u003en\u003c/em\u003e = 4). \u003cstrong\u003eE\u003c/strong\u003e The proliferation of LM3-SNHG15 cells treated with siRNAs targeting PDHE1α was measured using the CCK8 assay (\u003cem\u003en\u003c/em\u003e = 4). \u003cstrong\u003eF\u003c/strong\u003e Western blot analysis of PDK1 in the lysates. \u003cstrong\u003eG\u003c/strong\u003e The levels of SNHG15 were determined using qRT-PCR (\u003cem\u003en\u003c/em\u003e = 4). \u003cstrong\u003eH\u003c/strong\u003eThe proliferation of LM3-SNHG15 cells treated with siRNAs targeting PDK1 was measured using the CCK8 assay (\u003cem\u003en\u003c/em\u003e = 4). \u003cstrong\u003eI \u003c/strong\u003eUtilizing dose curve analysis, the IC50 values of oligomycin and 2-DG in LM3-SNHG15 cells were determined. \u003cstrong\u003eJ \u003c/strong\u003eNude mice were subcutaneously injected with LM3-SNHG15 cells, tumor sizes were measured every two days (\u003cem\u003en\u003c/em\u003e= 5). \u003cstrong\u003eK\u003c/strong\u003e The intratumoral levels of SNHG15 were measured using qRT-PCR. \u003cstrong\u003eL\u003c/strong\u003e Using the appropriate test kits, PDH activity and lactate levels in the tumors were determined. The data represent mean values ± SD. *\u003cem\u003eP\u003c/em\u003e \u0026lt; 0.05, **\u003cem\u003eP\u003c/em\u003e \u0026lt; 0.01, ***\u003cem\u003eP\u003c/em\u003e\u0026lt; 0.001, n.s., not significant.\u003c/p\u003e","description":"","filename":"Figure7.jpg","url":"https://assets-eu.researchsquare.com/files/rs-9307919/v1/c82762afb3c8a8d0fcefd8fc.jpg"},{"id":107652548,"identity":"578303fb-eabd-40ed-bd6e-722a7f1a6822","added_by":"auto","created_at":"2026-04-23 15:17:09","extension":"jpg","order_by":8,"title":"Figure 8","display":"","copyAsset":false,"role":"figure","size":931334,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eThe proposed molecular mechanism through which SNHG15 reprograms glucometabolism.\u003c/strong\u003e SNHG15 serves as an adaptor molecule, enhancing the interaction of the PGK1-PDK1-PDHE1α axis. This in turn increases the phosphorylation levels and dampens PDH enzyme activity.\u003c/p\u003e","description":"","filename":"Figure8.jpg","url":"https://assets-eu.researchsquare.com/files/rs-9307919/v1/3a536c3b9386ead5e9fec655.jpg"},{"id":107709449,"identity":"2555c1a5-506e-44f4-91b3-b489be6a2f82","added_by":"auto","created_at":"2026-04-24 09:35:55","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":13681482,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-9307919/v1/69028054-972d-4170-b9cb-265477120e35.pdf"},{"id":107652540,"identity":"b99ab8a5-1449-4036-aab4-da2d653375f7","added_by":"auto","created_at":"2026-04-23 15:17:09","extension":"docx","order_by":1,"title":"","display":"","copyAsset":false,"role":"supplement","size":1335751,"visible":true,"origin":"","legend":"Supplementary Material","description":"","filename":"SupplementaryMaterial.docx","url":"https://assets-eu.researchsquare.com/files/rs-9307919/v1/43f85ff98ca2a91f243fc5fc.docx"},{"id":107652541,"identity":"b594e7b8-6c4b-47cf-acf3-6acf36ff45bd","added_by":"auto","created_at":"2026-04-23 15:17:09","extension":"docx","order_by":2,"title":"","display":"","copyAsset":false,"role":"supplement","size":13417145,"visible":true,"origin":"","legend":"Source data.","description":"","filename":"Sourcedata.docx","url":"https://assets-eu.researchsquare.com/files/rs-9307919/v1/b9ae8a80eb41333ec3944436.docx"}],"financialInterests":"There is no conflict of interest","formattedTitle":"SNHG15 inhibits the tricarboxylic acid cycle and promotes HCC progression by facilitating the phosphorylation of PDK1 and PDHE1α","fulltext":[{"header":"Introduction","content":"\u003cp\u003eHepatocellular carcinoma (HCC) presents an enormous global health concern, being the fourth leading cause of cancer-related mortality and the sixth most commonly diagnosed cancer globally [\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e]. HCC cells actively engage in both anaerobic and aerobic glycolysis (Warburg effect) to meet the energy, redox, and biosynthetic needs of the tumor tissue [\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e]. Consequently, glycolysis exacerbates immunological suppression, hypoxia, and acidosis while promoting tumor growth, angiogenesis, invasion, and metastasis [\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e]. Accordingly, metabolic reprogramming has received increasing attention in anticancer therapy, and many medications targeting metabolites or metabolic pathways have been developed and approved by the United States FDA for cancer treatment [\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e]. Currently, a few compounds can block glycolysis by targeting HK2, PFK1, or PKM2 [\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e]. Although a number of medications that target glucometabolism are currently undergoing phase I or II clinical studies, their clinical applications remain uncertain. Numerous challenges persist in targeting metabolic pathways for cancer treatment.\u003c/p\u003e \u003cp\u003eLong non-coding RNAs (lncRNAs) are a diverse class of molecules that are typically longer than 200 nucleotides and do not encode proteins [\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e]. Several studies have demonstrated that lncRNAs contribute to the carcinogenesis and metastasis of HCC by modifying apoptosis, chemo- or radio-sensitivity, and cell invasion and proliferation [\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e]. Cellular energy metabolism requires mitochondria, and aberrant mitochondrial function is an important cause of dysfunction and cell death [\u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e]. It is conceivable to predict the roles of lncRNAs in mitochondria owing to advancements in sequencing technology and bioinformatics techniques [\u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e]. For example, lncRNA RMRP was found to regulate mitochondrial DNA replication [\u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e]. The lncRNA GAS5 was found to promote apoptosis in ovarian cancer cells by reducing the mitochondrial membrane potential [\u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e]. In addition, lncRNA GAS5 regulates TCA metabolism in response to nutritional stress [\u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eThe pyruvate dehydrogenase complex (PDHc) is an extensive and intricate multienzyme, with a molecular mass of approximately 9.5\u0026nbsp;million Daltons. It is located in the mitochondrial matrix, where it plays a pivotal role in cellular metabolism [\u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e]. By catalyzing pyruvate oxidation, PDHc links glycolysis with oxidative phosphorylation, occupying a pivotal node in the TCA cycle. PDHc comprises four essential catalytic components: pyruvate dehydrogenase E1 (E1), dihydrolipoyl transacetylase (E2), dihydrolipoamide dehydrogenase (E3), and E3-binding protein (E3BP) [\u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e]. The activation of PDH is intricately regulated through both transcriptional processes and various post-translational modifications, such as succinylation, acetylation, and phosphorylation [\u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e, \u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e]. Pyruvate dehydrogenase kinases (PDKs), which exhibits tissue-specific expression patterns and varied regulatory mechanisms, mediate phosphorylation as a well-established mechanism of PDH inactivation [\u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e]. As a critical node in metabolic regulation, changes in PDHc contribute to metabolic reprogramming during HCC development, resulting in the accumulation of lactic acid, remodeling of the TCA cycle, and disruption of lipid metabolism.\u003c/p\u003e \u003cp\u003eThrough the application of an innovative approach that combines subcellular separation, two-phase extraction, and mass spectrometry quantification, we have identified a novel RNA-binding protein (RBP), PDHE1α, which exhibits binding affinity to the lncRNA SNHG15. SNHG15 plays a significant role in the progression and malignant transformation of HCC by facilitating the phosphorylation of PDK1 and PDHE1α, while concurrently inhibiting the TCA cycle. This study presents undocumented evidence regarding the role of SNHG15 in HCC progression through PDH-mediated alterations in glucometabolic reprogramming, thereby identifying a promising therapeutic target for HCC treatment.\u003c/p\u003e"},{"header":"Methods","content":"\u003cdiv id=\"Sec3\" class=\"Section2\"\u003e \u003ch2\u003eCell Culture\u003c/h2\u003e \u003cp\u003eThe HCC cell lines LM3, Huh7, and Hep3B were maintained at 37\u0026deg;C in a humidified environment with 5% CO\u003csub\u003e2\u003c/sub\u003e. The cells were grown in DMEM supplemented with 10% fetal bovine serum and 1% penicillin-streptomycin (100 \u0026micro;g/mL).\u003c/p\u003e \u003c/div\u003e\n\u003ch3\u003eRNA Fluorescence in Situ Hybridization (FISH)\u003c/h3\u003e\n\u003cp\u003eThe cells were permeabilized with 70% ethanol for 1 h after being fixed with 37% formaldehyde for 10 min at room temperature. Slides were hybridized for 16 hours at 37\u0026deg;C. The antisense probes were dissolved at 20 nM in hybridization buffer for RNA FISH. Then the slides stained with Alexa Fluor 546-conjugated streptavidin for 1 h at the same temperature. Coverslips were examined using confocal laser scanning microscopy (Olympus, Tokyo, Japan) after they had been counter-stained with DAPI.\u003c/p\u003e\n\u003ch3\u003eRNA Immunoprecipitation (RIP)\u003c/h3\u003e\n\u003cp\u003eProtein A or Protein G magnetic beads were used to separate the RNA-protein complexes using the appropriate primary antibodies. After ten rounds of washing with lysis buffer (240 mM NaCl, 40 mM Tris, and 1% Triton X-100), the co-precipitated RNAs were extracted using TRIzol (Invitrogen), and qRT-PCR was used to determine the amount of SNHG15 in the eluate. LncRNA-RMRP was used as an RNA control.\u003c/p\u003e\n\u003ch3\u003eRNA Pull-Down\u003c/h3\u003e\n\u003cp\u003eFor the RNA pull-down assay, 4 \u0026micro;g of biotinylated SNHG15 or antisense SNHG15 was added to 40 \u0026micro;L of Streptavidin Dynabeads (Invitrogen) and incubated for 3 h at 4\u0026deg;C in binding buffer (300 mM NaCl, 50 mM Na\u003csub\u003e3\u003c/sub\u003ePO\u003csub\u003e4\u003c/sub\u003e, and 0.01% Tween-20). The beads were then mixed with the cell lysates and incubated for 4 h at 4\u0026deg;C. Following ten rounds of washing with lysis buffer (240 mM NaCl, 40 mM Tris, and 1% Triton X-100), the beads were mixed with SDS-PAGE sample loading buffer and examined using western blotting.\u003c/p\u003e\n\u003ch3\u003eHis-tag Pull-Down Assay\u003c/h3\u003e\n\u003cp\u003eDynabeads\u0026reg; His-tag isolation magnetic beads (Invitrogen) were incubated with His-tagged rPDK1 or rPDHE1α for 4 h at 4\u0026deg;C in the binding buffer (300 mM NaCl, 50 mM Na\u003csub\u003e3\u003c/sub\u003ePO\u003csub\u003e4\u003c/sub\u003e, and 0.01% Tween-20). The protein-coupled beads were then incubated with SNHG15 or antisense SNHG15 for 4 h at 4\u0026deg;C in the pull-down buffer (70 mM NaCl, 3.25 mM Na\u003csub\u003e3\u003c/sub\u003ePO\u003csub\u003e4\u003c/sub\u003e, and 0.01% Tween-20). The beads were then washed ten times with lysis buffer (240 mM NaCl, 40 mM Tris, and 1% Triton X-100). TRIzol reagent (Invitrogen) was used to extract the copurified SNHG15, and qRT-PCR was used for analysis.\u003c/p\u003e \u003cdiv id=\"Sec8\" class=\"Section2\"\u003e \u003ch2\u003eEnzyme Activity Measurements\u003c/h2\u003e \u003cp\u003eA pyruvate kinase activity assay kit (Abcam, Cambridge, MA, USA) was utilized to measure PDH activity according to the manufacturer\u0026rsquo;s instructions. 10\u003csup\u003e6\u003c/sup\u003e cells were homogenized in 0.5 mL of cold assay buffer, and the supernatant was collected by centrifugation. The test was conducted using 50 \u0026micro;L of diluted cell lysate, 46 \u0026micro;L of assay buffer, 2 \u0026micro;L of developer and 2 \u0026micro;L of substrate. To ascertain the PDH activity in the sample, the absorbance at 450 nm between T\u003csub\u003e0min\u003c/sub\u003e and T\u003csub\u003e30min\u003c/sub\u003e was recorded using a microplate reader (Thermo Fisher Scientific, Waltham, MA, USA).\u003c/p\u003e \u003c/div\u003e\n\u003ch3\u003eMeasurement of Oxygen Consumption and Extracellular Acidification Rate\u003c/h3\u003e\n\u003cp\u003eThe Seahorse XF extracellular flux analyzer (Agilent, Santa Clara, CA, USA) was used to measure the oxygen consumption rate (OCR) and extracellular acidification rate (ECAR). Prior to analysis, fresh assay medium was added after washing the adherent cells with the base assay medium. The cartridge was set up to deliver the chemical compounds in that order: glucose (10 mM), oligomycin (1 \u0026micro;M), and 2-DG (50 mM). Wave software automatically plotted the OCR and ECAR curves.\u003c/p\u003e \u003cp\u003e \u003cb\u003eIn Vivo\u003c/b\u003e \u003cb\u003eProliferation Assay\u003c/b\u003e\u003c/p\u003e \u003cp\u003eFemale BALB/c-nude mice aged five weeks (Chinese Academy of Sciences, Beijing, China) were used for \u003cem\u003ein vivo\u003c/em\u003e proliferation assays. The subcutaneous tissues of the mice were xenografted with 1\u0026times;10\u003csup\u003e7\u003c/sup\u003e LM3 cells. Tumor volumes were measured every two days, and calculated using the formula: V = (Length\u0026times;Width\u003csup\u003e2\u003c/sup\u003e)/2. The mice were sacrificed after four weeks, and the tumors were excised. The study was approved by the Research Ethics Committee of Shandong Provincial Qianfoshan Hospital, and conducted in compliance with the Declaration of Helsinki.\u003c/p\u003e\n\u003ch3\u003eAccession Numbers\u003c/h3\u003e\n\u003cp\u003eSequencing data sets described in this study have been deposited in the Gene Expression Omnibus (GEO) under accession number GSE282508.\u003c/p\u003e \u003cdiv id=\"Sec11\" class=\"Section2\"\u003e \u003ch2\u003eStatistical Analysis\u003c/h2\u003e \u003cp\u003eAll experiments were conducted at least three times. Plots were created using Prism version 10.0 (GraphPad) and statistical analysis was conducted using SPSS version 27.0 software. Data are shown as the mean values\u0026thinsp;\u0026plusmn;\u0026thinsp;SD. The growth curve and \u003cem\u003ein vivo\u003c/em\u003e proliferation data were evaluated using one-way ANOVA, and the Student's t-test was used to compare the two groups. \u003cem\u003eP\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.05 were regarded as statistically significant.\u003c/p\u003e \u003c/div\u003e\u003cp\u003e\u003cstrong\u003eEthical Statement\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThis study\u003cem\u003e\u0026nbsp;\u003c/em\u003ewas approved by the Research Ethics Committee of Shandong Provincial Qianfoshan Hospital, and was conducted in compliance with the Declaration of Helsinki.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e"},{"header":"Results","content":"\u003cp\u003e\u003cstrong\u003eRNAs interacting with PDHE1\u0026alpha; were identified through iRIP-seq analysis\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eWe developed an analytical approach to characterize RNA-binding proteins (RBPs), by integrating subcellular separation, two phase extraction with acidic guanidinium-thiocyanate-phenol-chloroform, and quantitative mass spectrometry (Fig. 1A) [16]. Using this approach, we identified 200 enzymes from a range of metabolic pathways as RBPs, thereby uncovering an unexpected link between metabolic activity and RNA regulation. Notably, PDHE1\u0026alpha; was firstly identified to possess RBP characteristics. Given the well-established critical function of PDHE1\u0026alpha; in pyruvate oxidation [17], we focused on its interaction with RNA. Treatment with RNase boosted PDH activity, indicating that RNA-binding might inhibit the enzyme (Fig. 1B).\u003c/p\u003e\n\u003cp\u003eTo identify RNA molecules that directly interact with PDHE1\u0026alpha;, we employed an advanced RNA immunoprecipitation technique, enhanced for greater sensitivity and specificity, combined with high-throughput sequencing (iRIP-seq) in LM3 cells. This method involves \u003cem\u003ein vivo\u003c/em\u003e cross-linking of RNAs and proteins using UV irradiation, followed by immunoprecipitation of RNA-bound proteins with antibodies specific for PDHE1\u0026alpha;. Following immunoprecipitation, micrococcal nuclease (MNase) treatment was performed, and RNAs was extracted for paired-end deep sequencing using the Illumina NextSeq 500 platform (Fig. 1C).\u0026nbsp;Two biological replicates were included in each test to ensure robustness and reproducibility of the results. Gene Ontology (GO) and KEGG pathway analysis were performed to obtain a more detailed understanding of the potential biological functions and pathways associated with the identified RNAs (Supplementary Fig. 1). According to GO analysis, the identified RNAs were involved in several pathways, such as translation, rRNA processing and cell growth, whereas KEGG analysis showed that PDHE1\u0026alpha;-interacting RNAs were involved in RNA transport, ribosomes, and other functions.\u003c/p\u003e\n\u003cp\u003eMapping the distribution of reads to the reference genome revealed that the IP group and Input group reads occupied a large space in introns and intergenic regions (Fig. 2A). The correlation scatterplots of the Input and IP samples were further drawn, and the R-values of the correlation coefficients for the two repeated experiments were 0.78 and 0.74, respectively (Fig. 2B). Cluster analysis was conducted according to the sample correlation coefficient, which revealed clean differences between the IP and Input groups (Fig. 2C). The peaks in the two IP group datasets overlapped, and 515 specific peaks were enriched (Fig. 2D). We then mapped the distribution of specific overlapping peaks to the reference genome, which revealed that specific overlapping peaks were mainly concentrated in the introns (48.5%), antisense (21.6%) and intergenic regions (9.4%) (Fig. 2E). Among the shared peaks, 65.2% were mapped to mRNAs, 17.5% were mapped to lncRNAs and 3.3% were mapped to snoRNAs (Fig. 2F). We used the HOMER algorithm to examine the motifs to identify the binding sequence preference of PDHE1\u0026alpha;, which revealed a preference for GC-rich motifs (Fig. 2G).\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eIdentification of SNHG15 as a potential PDHE1\u0026alpha;-interacting RNA.\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eTo further investigate potential PDHE1\u0026alpha;-interacting RNAs, the candidate lncRNA SNHG15 was selected, and its binding regions were visualized using the Integrative Genomics Viewer (Fig. 3A). SNHG15 is distributed in both the cytoplasm and nucleus of HCC cells, with an increased abundance in the cytoplasm [18]. RNA-FISH staining showed partial localization of SNHG15 in the mitochondria of LM3 cells (Figs. 3B and C), suggesting that it is a potential PDHE1\u0026alpha;-interacting RNA.\u003c/p\u003e\n\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eSNHG15 directly binds to PDHE1\u0026alpha; and dampens the enzymatic activity of PDH\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eBased on our iRIP-seq findings, lncRNA SNHG15 is identified as a potential interaction partner of PDHE1\u0026alpha; (Fig. 3A).\u0026nbsp;Immunoprecipitation (IP) utilizing antibodies specific to PDHE1\u0026alpha; was employed to conduct RNA immunoprecipitation followed by real-time quantitative reverse transcription PCR (RIP-qPCR). Subsequent qPCR analysis demonstrated a significant enrichment of SNHG15 in immunoprecipitates of PDHE1\u0026alpha;, validating the iRIP-seq results (Fig. 4A). In contrast, control lncRNA-RMRP was not found in the immunoprecipitates of PDHE1\u0026alpha;, revealing a particular interaction between PDHE1\u0026alpha; and SNHG15 (Fig. 4A). To further confirm this interaction, PDHE1\u0026alpha; was pulled down from LM3 cell lysates using biotinylated SNHG15 rather than antisense SNHG15 (Fig. 4B).\u003c/p\u003e\n\u003cp\u003eNext, we investigated the potential direct interaction between PDHE1\u0026alpha; and SNHG15. An \u003cem\u003ein vitro\u003c/em\u003e His-tag pulldown test demonstrated that recombinant PDHE1\u0026alpha; (rPDHE1\u0026alpha;) directly binds to SNHG15, as opposed to antisense SNHG15 (Fig. 4C). To further support the proposition that SNHG15 binds to PDHE1\u0026alpha;, wild-type FLAG-tagged PDHE1\u0026alpha; or its fragments (F1 and F2) were expressed in transfected LM3 cells for an RIP-qPCR assay using an anti-FLAG antibody. These findings indicated that both fragments 1 and 2 interacted with SNHG15 (Fig. 4D). In addition, PDH activity decreased when SNHG15 was overexpressed, but increased when SNHG15 was knocked down by ssSNHG15 (Figs. 4E and F). Moreover, two additional HCC cell lines, Huh7 and Hep3B, showed similar results (Supplementary Figs. 2A-E). Previous studies have indicated that PDH activity is regulated via phosphorylation [17]. Consequently, we hypothesized that SNHG15 might affect the phosphorylation state of PDHE1\u0026alpha;. As shown in Figs. 4G and 4H, overexpression of SNHG15 elevated the phosphorylation levels of PDHE1\u0026alpha; in LM3 cells, whereas SNHG15 knockdown decreased its phosphorylation levels. SNHG15 did not affect the expression of PDHE1\u0026alpha; at the protein or mRNA levels (Fig. 4G, Supplementary Fig. 3). These data demonstrate that SNHG15 directly binds to PDHE1\u0026alpha; and regulates the enzymatic activity of PDH by modulating its phosphorylation.\u003c/p\u003e\n\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eSNHG15 modulates PDHE1\u0026alpha; through PGK1-PDK1-PDHE1\u0026alpha; axis\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eAs a protein kinase, mitochondrial PGK1 phosphorylates PDK1 at threonine 338. Upon activation through phosphorylation, PDK1 subsequently phosphorylates and inhibits the PDHc\u0026nbsp;[19]. PGK1 is recognized as an RNA-binding protein. SNHG15 directly binds to PDHE1\u0026alpha; and dampens the enzymatic activity of PDH. Based on these findings, we hypothesize that SNHG15 may modulate the PGK1-PDK1-PDHE1\u0026alpha; signaling pathway. Initially, we investigated the potential interaction between SNHG15 and either PGK1 or PDK1.The RIP experiment demonstrated significant enrichment of SNHG15 in the immunoprecipitates of PGK1 and PDK1 (Figs. 5A and B). Additionally, the phosphorylation level of PDK1 was increased by the overexpression of SNHG15 and decreased by its knockdown (Fig. 5C). The expression levels of PGK1 and PDK1, both at the protein and mRNA levels, were not affected by SNHG15 (Fig. 5C, Supplementary Fig. 3). Moreover, overexpression of SNHG15 promoted the phosphorylation of PDHE1\u0026alpha; (S293) and PDK1 (T338), which were impaired by the treatment with the PDK inhibitor DCA and PGK1 knockdown, suggesting that SNHG15 indeed modulated the phosphorylation of these two enzymes through PGK1 and PDK1(Fig. 5D). Furthermore, the RNA pull-down experiment revealed that SNHG15 was capable of simultaneously pulling down both recombinant PGK1 (rPGK1) and recombinant PDK1 (rPDK1) (Fig. 5E), whereas rPDK1 and rPDHE1\u0026alpha; showed similar results (Fig. 5F). We then investigated whether the interactions between PDK1 and PDHE1\u0026alpha; or between PGK1 and PDK1 could be affected by SNHG15. The His-tag pull-down assay revealed a direct interaction between rPGK1 and rPDK1, and their interaction was enhanced when SNHG15 was added rather than antisense SNHG15 (Fig. 5G). rPDK1 and rPDHE1\u0026alpha; showed similar results (Fig. 5H). Collectively, these data suggest that SNHG15 may act as an adaptor molecule to enhance the interactions between PDK1 and PDHE1\u0026alpha; or PGK1 and PDK1, driving the PGK1-PDK1-PDHE1\u0026alpha; axis and increasing the phosphorylation of PDK1 and PDHE1\u0026alpha;.\u003c/p\u003e\n\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eSNHG15 suppresses the TCA cycle and promotes aerobic glycolysis in HCC\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe interactions between SNHG15 and PDHE1\u0026alpha; have the potential to influence cellular metabolic processes, given that the PDHc functions as a critical junction between the TCA cycle and glycolysis. To confirm this hypothesis, we assessed the levels of oxidative phosphorylation and glycolysis in HCC cells with SNHG15 overexpression and knockdown. As expected, SNHG15 overexpression decreased oxygen consumption and acetyl-CoA concentrations, whereas SNHG15 knockdown had the opposite effect (Figs. 6A and B). Furthermore, SNHG15 overexpression significantly increases ATP levels, indicating an enhanced cellular energy state, whereas SNHG15 knockdown induced a considerable decrease in ATP production (Fig. 6C).\u003c/p\u003e\n\u003cp\u003eTo further confirm these findings, we investigated whether SNHG15 may have an impact on the degree of glycolysis. SNHG15 overexpression increased glucose uptake and lactate generation, whereas SNHG15 knockdown decreased these processes in LM3 cells (Figs. 6D and E). Moreover, two additional HCC cell lines, Huh7 and Hep3B, showed comparable effects (Supplementary Figs. 2C and F). We then used the Seahorse Analyzer to measure glycolytic flow. Glucose was first added to increase glycolytic flux, after which the ATP synthase inhibitor oligomycin was added to inhibit oxidative phosphorylation and quantify glycolytic ability. Glycolytic reserve was evaluated following the subsequent administration of 2-deoxy-D-glucose (2-DG), a well-established inhibitor of glycolysis (Figs. 6F and G). The analysis revealed that SNHG15 overexpression upregulated glycolysis with a considerable increase in glycolytic capacity and glycolytic reserve. Treatment with the PDH activator, sodium dichloroacetate (DCA), reversed this effect (Fig. 6F). Conversely, SNHG15 knockdown decreased total glycolytic flow with a considerable decrease in glycolysis, glycolytic capacity, and glycolytic reserve (Fig. 6G). These observations suggest that SNHG15 plays a critical role in the regulation of cellular energy metabolism. Specifically, SNHG15 appeared to inhibit oxidative phosphorylation by facilitating the conversion of pyruvate into lactate rather than acetyl-CoA for the TCA cycle.\u003c/p\u003e\n\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eSNHG15 promotes cell proliferation via the PGK1-PDK1-PDHE1\u0026alpha; axis\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eSNHG15 has been implicated in the promotion of HCC cells [18, 20].\u0026nbsp;Here, we replicated these findings, as the CCK8 experiment demonstrated that SNHG15 overexpression boosted cell proliferation whereas SNHG15 knockdown had the opposite effect (Figs. 7A and B). Furthermore, the growth curve showed the same trend, whereas treatment with a PDH activator reduced the proliferation of LM3-SNHG15 cells to levels comparable to those of the untreated group (Figs. 7A and B). These findings suggest that SNHG15 plays a critical role in enhancing the proliferation of HCC cells via PDHc.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eTo provide additional evidence that SNHG15 promotes cell proliferation via the PGK1-PDK1-PDHE1\u0026alpha; axis, we overexpressed SNHG15 followed by rescue with PDHE1\u0026alpha; or PDK1 knockdown. According to the CCK8 assay, SNHG15 overexpression promoted cell proliferation, whereas PDHE1\u0026alpha; knockdown decreased it to a level comparable to that of the control group (Figs. 7C\u0026ndash;E). Overexpressing SNHG15 did not promote cell proliferation in PDHE1\u0026alpha; knockdown cells rescued with empty vector. In cells rescued with PDHE1\u0026alpha;-WT, overexpression of SNHG15 enhanced cel proliferation, but overexpressing PDHE1\u0026alpha;-S293A mutants failed to rescue the SNHG15-promoted cell proliferation (Supplementary Figs. 4A-C). Moreover, PDK1 showed similar effects (Figs. 7F\u0026ndash;H). PDK1-T338A could also block the effect of SNHG15 on cell proliferation (Supplementary Figs. 4D-F). Additionally, we determined the half-maximal inhibitory concentrations (IC50) of oligomycin and 2-DG in LM3 cells overexpressing SNHG15. Compared to the control group, the IC50 of oligomycin, an inhibitor of oxidative phosphorylation, was higher in LM3-SNHG15 cells, indicating that they were less sensitive to the inhibition of mitochondrial ATP synthesis. In contrast, LM3-SNHG15 cells showed a significantly lower IC50 for 2-DG, indicating an increased sensitivity to glycolytic inhibition. This suggested that SNHG15 may suppress oxidative phosphorylation and enhance glycolytic activity, making these cells more dependent on glycolysis for energy production. These data suggest that SNHG15 may promote metabolic reprogramming, favoring glycolysis over oxidative phosphorylation and altering the cells\u0026apos; energy production pathways.\u003c/p\u003e\n\u003cp\u003eFinally, we assessed the functional role of SNHG15 \u003cem\u003ein vivo\u0026nbsp;\u003c/em\u003eby conducting a series of experiments using animal models. These studies aimed to evaluate the influence of SNHG15 on tumor growth and overall disease progression in a more complex physiological environment. SNHG15 overexpression promoted tumor growth in mice, which is consistent with the findings of the cultured-cell assays (Figs. 7J and K). Compared with control cells, tumors generated from SNHG15 overexpressing cells showed lower PDH activity and higher lactate levels (Fig. 7L). We examined RNA-sequencing data from TCGA database to further investigate the expression of SNHG15 in clinical samples. The findings showed that SNHG15 was markedly elevated in HCC tumor samples compared to the surrounding non-tumorous tissues (Supplementary Fig. 5A).\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eSurvival analysis revealed that the elevated SNHG15 expression was correlated with poorer overall survival and a higher risk of disease progression, suggesting its potential as a prognostic biomarker in HCC (Supplementary Fig. 5B). These data collectively indicate that SNHG15 substantially enhances glycolytic activity and facilitates the proliferation of HCC cells in both \u003cem\u003ein vitro\u003c/em\u003e and \u003cem\u003ein vivo\u003c/em\u003e settings. Consequently, SNHG15 may play a pivotal role in tumor progression by acting as a key factor in sustaining proliferative capacity through the modulation of cellular metabolism. These findings highlight the critical role of SNHG15 in regulating cellular metabolism and identify it as a potential target for therapeutic interventions in clinical treatment.\u003c/p\u003e"},{"header":"Discussion","content":"\u003cp\u003eTwo key classes of biological macromolecules, RNA and proteins, can physically interact to control each other\u0026apos;s fate and function. In this study, PDHE1\u0026alpha; was characterized as an RBP and SNHG15 was identified as a potential PDHE1\u0026alpha;-interacting lncRNA. We further investigated the mechanism of SHNG15-mediated carcinogenesis by its interaction with PDHE1\u0026alpha;. Specifically, SNHG15 served as an adaptor molecule, enhancing the interactions of the PGK1-PDK1-PDHE1\u0026alpha; axis. This, in turn, increase the levels of phosphorylation and dampens the PDH enzyme activity. Finally, reduced PDH activity impaired oxidative phosphorylation, promoted glycolysis and ultimately accelerated HCC cell growth (Fig. 8).\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eLncRNAs are critical factors in the mechanisms of carcinogenesis [21], while a class of RBPs are essential regulators of RNAs that participate in several processes at the post-transcriptional level, ultimately dictating the fate and function of each transcript in the cell [22-24]. In addition, the dysregulated expression of some RBPs can cause a wide variety of diseases, including cardiovascular disorders and cancers [25, 26]. In a previous study, we combined subcellular separation, two phase extraction with acidic guanidinium-thiocyanate-phenol-chloroform, and quantitative mass spectrometry to characterize RBPs. Using this approach, we identified 200 enzymes from a range of metabolic pathways as RBPs. This included PDHE1\u0026alpha;, a critical gatekeeper of mitochondrial respiration. Since mitochondrial metabolism and dysfunction have been reported to contribute to the development of cancer [27], we chose PDHE1\u0026alpha; for this study.\u003c/p\u003e\n\u003cp\u003eNext, iRIP-seq was conducted to identify RNA molecules that specifically bind to PDHE1\u0026alpha; in LM3 cells, and lncRNA SNHG15 was one of the candidates that intrigued us most, as it is essential to the development of certain human cancers [28]. In particular, SNHG15 expression was found to be increased in HCC and correlated with a negative prognosis [29]. SNHG15 regulates miRNAs such as miR‐141‐3p [18], miR-490-3p [30] and miR-18b-5p [31] to promote HCC progression. Consistent with this role, our study confirmed the aberrant expression and oncogenic role of SNHG15, after which we focused on the regulatory mechanisms of SNHG15 in HCC.\u003c/p\u003e\n\u003cp\u003eIn addition to energy generation, mitochondria are involved in cell division, growth, senescence, and cell death [32]. PDHc is crucial for the mitochondrial TCA cycle function, acting as a central enzyme complex that facilitates the metabolism of pyruvate to acetyl-CoA, a key step in cellular energy production. Recent studies have demonstrated the significant role of PDHc dysfunction in various pathological conditions, linking it to the development of metabolic diseases such as obesity and diabetes, ischemic injury responses and cancer [17, 33-35]. Our experiments showed that SNHG15 could directly bind to PDHE1\u0026alpha;, thereby reducing PDH activity but did not alter PDHE1\u0026alpha; expression levels. The regulation of PDH complex activity is largely controlled by the reversible phosphorylation of PDHE1\u0026alpha; [36]. Consistently, SNHG15 enhanced the phosphorylation of PDHE1\u0026alpha;. PDK1 directly phosphorylates PDHE1\u0026alpha; and inhibits its enzymatic activity [37]. Mitochondrial PGK1 acts as a protein kinase that phosphorylates PDK1 at threonine 338, leading to its activation. Activated PDK1 phosphorylates and inhibits PDHc [19]. Interestingly, the RIP experiment confirmed that SNHG15 can bind to both PDK and PGK1 without altering their expression levels. However, SNHG15 facilitated the interaction between PGK1 and PDK1, as well as between PDK1 and PDHE1\u0026alpha;, leading to increased phosphorylation of both PDK1 and PDHE1\u0026alpha;. Therefore, we suggest that SNHG15 modulates PDHE1\u0026alpha; phosphorylation to reduce its enzyme activity via the PGK1-PDK1-PDHE1\u0026alpha; signaling axis.\u003c/p\u003e\n\u003cp\u003eBased on Warburg\u0026rsquo;s observations, aerobic glycolysis in cancer cells is caused by mitochondrial malfunction, which is thought to be a risk factor for cancer [38]. The availability of anabolic substrates necessary for the synthesis of DNA, proteins, and lipids is essential because of the dysregulated proliferation of cancer cells, which involves the mitochondrial TCA cycle [39]. Considering the metabolic rearrangements typical of HCC, an increasing number of studies have focused on key metabolic enzymes as well as the drivers of metabolic changes [40]. Several key findings of this study highlight the intricate and multifaceted nature of SNHG15-induced alterations in HCC cell metabolism. Crucially, we demonstrated that SNHG15 decreased PDH enzyme activity to increase the conversion of pyruvate into lactate, thus impairing oxidative phosphorylation. Accordingly, SNHG15 enhanced cell proliferation via the PGK1-PDK1-PDHE1\u0026alpha; axis. These findings may facilitate the development of innovative therapeutic strategies for HCC treatment.\u003c/p\u003e"},{"header":"Declarations","content":"\u003cp\u003e\u003cstrong\u003eFunding\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThis work was supported by grants from the National Natural Science Foundation of China (82303249 to C.W., 82002755 to H.C.), Natural Science Foundation of Shandong Province (ZR2023QH144 to C.W., ZR2022QH007 to X.Z, ZR2022QH290 to Y.W.), National Natural Science Foundation Cultivating Fund from the Qianfoshan Hospital of Shandong Province (QYPY-RC2022NSFC1004 to C.W., QYPY2022NSFC0604 to Y.W.), National Natural Science Foundation Cultivating Fund from the Shandong First Medical University (202201-090 to C.W.), Youth Innovation Team Plan in Colleges and Universities of Shandong Province (2023KJ172 to C.W., 2022KJ198 to H.C.), and Beijing Kechuang Medical Development Foundation (KC2023-JX-0186-BQ076 to C.W., KC2023-JX-0186-FQ028 to Y.W.).\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eCompeting Interests\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe authors declare no competing interests.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAuthor contributions\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eC. W. and X. Z. conceived and designed the study. H. C., Y. W., W.C., and X. W. carried out the molecular and cellular biology experiments with the assistance of X. Z., L. W., J. Z. Sequencing data analysis was performed by H. C. The manuscript was written by C. W. and X. Z., with assistance from H. C.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eData availability\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe data that support the findings of this study are available from the corresponding author upon reasonable request.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\u003cli\u003e\u003cspan\u003eShang RZ, Qu SB, Wang DS. 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Acta pharmaceutica Sinica B 12(2), 558\u0026ndash;580 (2022).\u003c/span\u003e\u003c/li\u003e\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":false,"highlight":"","institution":"","isAcceptedByJournal":false,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"cell-death-discovery","isNatureJournal":false,"hasQc":false,"allowDirectSubmit":false,"externalIdentity":"cddiscovery","sideBox":"Learn more about [Cell Death Discovery](http://www.nature.com/cddiscovery/)","snPcode":"41420","submissionUrl":"https://mts-cddiscovery.nature.com/","title":"Cell Death Discovery","twitterHandle":"","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"ejp","reportingPortfolio":"Nature AJ","inReviewEnabled":true,"inReviewRevisionsEnabled":true},"keywords":"SNHG15, TCA, metabolic reprogramming, HCC, phosphorylation","lastPublishedDoi":"10.21203/rs.3.rs-9307919/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-9307919/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003eGlucometabolic reprogramming is a defining feature of hepatocellular carcinoma (HCC). The pyruvate dehydrogenase complex (PDHc) serves as a critical intermediary between glycolysis and oxidative phosphorylation by facilitating the oxidation of pyruvate within the tricarboxylic acid cycle. However, its potential involvement in other facets of metabolic regulation has yet to be fully elucidated. Here, we found that PDHE1α could bind RNA and that lncRNA SNHG15, a small nucleolar RNA host gene, may interact with PDHE1α. Mechanistic analysis suggested that SNHG15 facilitated the interaction between PGK1 and PDK1, as well as between PDK1 and PDHE1α, resulting in increased phosphorylation of PDK1 and PDHE1α. This in turn suppressed the TCA cycle and promoted glycolysis in HCC cells. Notably, SNHG15 facilitated cellular proliferation while concurrently enhancing the growth of xenografted tumors and augmenting lactate production. This study elucidates the functional significance of SNHG15 in mediating metabolic reprogramming in HCC, thereby identifying potential therapeutic targets for clinical intervention.\u003c/p\u003e","manuscriptTitle":"SNHG15 inhibits the tricarboxylic acid cycle and promotes HCC progression by facilitating the phosphorylation of PDK1 and PDHE1α","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2026-04-23 15:17:01","doi":"10.21203/rs.3.rs-9307919/v1","editorialEvents":[{"type":"communityComments","content":0},{"type":"editorInvitedReview","content":"This content is not available.","date":"2026-04-25T11:12:08+00:00","index":2,"fulltext":"This content is not available."},{"type":"editorInvitedReview","content":"This content is not available.","date":"2026-04-23T12:10:24+00:00","index":1,"fulltext":"This content is not available."},{"type":"reviewerAgreed","content":"This content is not available.","date":"2026-04-19T13:52:45+00:00","index":3,"fulltext":"This content is not available."},{"type":"reviewerAgreed","content":"This content is not available.","date":"2026-04-16T01:33:06+00:00","index":2,"fulltext":"This content is not available."},{"type":"reviewerAgreed","content":"This content is not available.","date":"2026-04-16T01:19:07+00:00","index":1,"fulltext":"This content is not available."},{"type":"reviewersInvited","content":"","date":"2026-04-15T18:42:26+00:00","index":"","fulltext":""},{"type":"checksComplete","content":"","date":"2026-04-07T07:59:30+00:00","index":"","fulltext":""},{"type":"editorAssigned","content":"","date":"2026-04-03T02:30:04+00:00","index":"","fulltext":""},{"type":"submitted","content":"Cell Death Discovery","date":"2026-04-03T02:30:02+00:00","index":"","fulltext":""}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"cell-death-discovery","isNatureJournal":false,"hasQc":false,"allowDirectSubmit":false,"externalIdentity":"cddiscovery","sideBox":"Learn more about [Cell Death Discovery](http://www.nature.com/cddiscovery/)","snPcode":"41420","submissionUrl":"https://mts-cddiscovery.nature.com/","title":"Cell Death Discovery","twitterHandle":"","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"ejp","reportingPortfolio":"Nature AJ","inReviewEnabled":true,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"e5eee677-ef5e-47e2-acc7-488bd68914a8","owner":[],"postedDate":"April 23rd, 2026","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"under-review","subjectAreas":[{"id":66394616,"name":"Biological sciences/Molecular biology/Non-coding RNAs/Long non-coding RNAs"},{"id":66394617,"name":"Biological sciences/Cancer/Cancer metabolism"}],"tags":[],"updatedAt":"2026-04-23T15:17:01+00:00","versionOfRecord":[],"versionCreatedAt":"2026-04-23 15:17:01","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-9307919","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-9307919","identity":"rs-9307919","version":["v1"]},"buildId":"XKTyCvWXoU3ODBz1xrDgd","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}