Abstract

   Metabolism reprogramming is a hallmark of many cancer types. We focused
   on clear cell renal carcinoma (ccRCC) which is characterized by its
   clear and glycogen-enriched cytoplasm with unknown reasons. The aim of
   this study was to identify the clinical significance, biological
   function, and molecular regulation of glycogen synthase 1 (GYS1) in
   ccRCC glycogen accumulation and tumor progression.

   Methods: We determined the clinical relevance of GYS1 and glycogen in
   ccRCC by immunohistochemistry and periodic acid-schiff staining in
   fresh tissue and by tissue micro-array. Metabolic profiling with GYS1
   depletion was performed by metabolomics analysis. In vitro and
   xenograft mouse models were used to evaluate the impact of GYS1 on cell
   proliferation. High-throughput RNA-Seq analyses and
   co-immunoprecipitation-linked mass spectrometry were used to
   investigate the downstream targets of GYS1. Flow cytometry and CCK8
   assays were performed to determine the effect of GYS1 and sunitinib on
   cell viability.

   Results: We observed that GYS1 was significantly overexpressed and
   glycogen was accumulated in ccRCC tissues. These effects were
   correlated with unfavorable patient survival. Silencing of GYS1 induced
   metabolomic perturbation manifested by a carbohydrate metabolism shift.
   Overexpression of GYS1 promoted tumor growth whereas its silencing
   suppressed it by activating the canonical NF-κB pathway. The indirect
   interaction between GYS1 and NF-κB was intermediated by RPS27A, which
   facilitated the phosphorylation and nuclear import of p65. Moreover,
   silencing of GYS1 increased the synthetic lethality of ccRCC cells to
   sunitinib treatment by concomitantly suppressing p65.

   Conclusions: Our study findings reveal an oncogenic role for GYS1 in
   cell proliferation and glycogen metabolism in ccRCC. Re-sensitization
   of ccRCC cells to sunitinib suggests that GYS1 is a useful indicator of
   unfavorable prognosis as well as a therapeutic target for patients with
   ccRCC.

   Keywords: clear cell renal carcinoma, GYS1, glycogen, metabolomics,
   NF-κB

Introduction

   Renal cell carcinoma is one of the most lethal human malignancies
   worldwide, causing nearly 140,000 deaths per year. Clear cell renal
   cell carcinoma (ccRCC) is the most common subtype and accounts for
   approximately 70-80% of RCCs in the urological system. Despite progress
   in tumor diagnostics and treatment, surgery remains the optimal
   curative therapy for ccRCC patients. Chemotherapy drugs such as
   sunitinib, which target vascular endothelial growth factor receptor
   (VEGFR) and platelet-derived growth factor receptor (PDGFR), are used
   as the standard of care for ccRCC. Sunitinib, which has been approved
   by the Food and Drug Administration, is a broad-spectrum small-molecule
   inhibitor of receptor tyrosine kinases (RTK) and is used as the
   first-line therapy for advanced ccRCC [41]^1. Although an early
   response was observed in selected patients, most patients eventually
   develop resistance to sunitinib. Therefore, it is necessary to improve
   our understanding of the molecular mechanisms of ccRCC progression to
   develop better treatment regimens [42]^2.

   Dysregulated metabolism is a hallmark of many types of cancer. Tumors
   reprogram their metabolites to produce sufficient energy for survival.
   In ccRCC, changes in the central carbon metabolism, amino acid
   metabolism and glycerophospholipid biochemistry pathways, which endow
   ccRCC cells with significantly enhanced growth and survival, have
   recently attracted attention [43]^3^, [44]^4. Cells in ccRCC are
   glycogen-enriched, generating a distinctly clear cytoplasm at the
   microscopic level. The reason for this enrichment is unknown. Synthesis
   and breakdown of glycogen involves the activity of several enzymes and
   regulatory proteins. In kidney tissues, glycogen synthase 1 (GYS1) is
   the most important rate-limiting enzyme functioning in the last step of
   glycogen synthesis [45]^5. Pathologically, its deficiency has been
   shown to cause muscle glycogen storage disease type 0 and death
   [46]^6^, [47]^7. Studies of tumors showed that GYS1 was rapidly induced
   under hypoxic conditions and positively correlated with glycogen
   accumulation in glioblastoma, breast, and colon cancer cell lines
   [48]^8. Aberrant expression of GYS1 not only decreased cellular
   glycolytic flux but also increased activation of glycogen-responsive
   AMP kinase, leading to significant growth suppression of myeloid
   leukemia cells [49]^9. However, the role of GYS1 in ccRCC is still
   unknown. Because GYS1 is the key enzyme catalyzing glycogen synthesis,
   we predicted that abnormal expression of GYS1 is involved in
   manipulating glycogen content and cellular bio-functional
   transformation in ccRCC.

   The nuclear factor NF-κB family includes NF-κB1 (p50), NF-κB2 (p52),
   RelA (p65), RelB, and c-Rel, which transcriptionally regulate diverse
   cellular processes [50]^10^, [51]^11, including two major pathways
   which exert different biological roles: the canonical and noncanonical
   NF-κB pathways. The canonical NF-κB pathway represented by p65
   activation has been recognized as the central regulator of tumor
   progression, whereas the non-canonical NF-κB2 pathway is relatively
   less well-understood. The NF-κB pathway is an attractive therapeutic
   target because of its functional correlation with drug sensitivity in
   many cancer types [52]^12^, [53]^13, including sunitinib resistance in
   ccRCC [54]^14^, [55]^15. However, whether the status of the NF-κB
   pathways is related to the effectiveness of chemo-drugs requires
   further analysis.

   In this study, we focused on the clinical and biological importance of
   GYS1 in ccRCC and metabolic alterations during this process. Our aim
   was to investigate GYS1 as a potential oncogene and potential
   therapeutic target for in ccRCC.

Material and Methods

Patients, tissue specimens, and follow-up

   A total of 306 patients with primary ccRCC who underwent surgery
   between January 2004 and December 2012 at Sun Yat-sen University Cancer
   Center (SYSUCC, Guangzhou, China) were included in this study. The
   paraffin-embedded tissue samples of these patients were re-embedded
   into new paraffin blocks for tissue microarray (TMA). This research was
   approved by the Institute Research Medical Ethics Committee of SYSUCC.
   All patients provided written informed consent to use of their tissues
   and data for research purposes. Pathological specimens and pathological
   data were collected, and all samples were anonymous. The overall
   survival follow-up period was defined as the interval from the date of
   surgery to the date of death or last follow-up. No patients had been
   administered radiotherapy or chemotherapy prior to surgery.

Hematoxylin-eosin and immunohistochemistry staining

   The ccRCC TMA blocks were cut into 4 μm slices and mounted onto glass
   slides. These slides were then dewaxed and treated with 3% hydrogen
   peroxide in methanol and blocked using a biotin-blocking kit (DAKO,
   Glostrup, Germany). Hematoxylin-eosin (HE) and immunohistochemistry
   (IHC) staining of GYS1 were then conducted and assessed by two
   independent pathologists who calculated their corresponding IHC score.
   The scores were determined based on multiplying the staining intensity
   by the expression proportion. Staining intensity was recorded as four
   grades (0-3) and proportion was recorded as five grades (0-4) in
   ascending order of severity. The median IHC score was used as the
   cut-off value to separate patients into high and low GYS1 expression
   groups.

Glycogen detection

   PAS staining and quantification assays were conducted using similar
   protocols as described previously [56]^16. Briefly, the low- and
   high-PAS staining groups were divided depending on the percentage of
   positively stained cells. The high-PAS group included >10% positive
   cells or cluster staining, while sporadic staining or staining area
   ≤10% were assigned to the low PAS group. Specimens were controlled by
   diastase PAS staining (D-PAS) to eliminate false-positive cases. The
   glycogen content in fresh tissues was quantitated with a glycogen assay
   kit (ab65620, abcam, Cambridge, UK) according to the manufacturer's
   protocol.

Cell culture

   The ccRCC cells lines Caki-1 and Caki-2 were obtained from the Type
   Culture Collection Cell Bank, Chinese Academy of Science Committee
   (Shanghai, China) and were cultured in Dulbecco's modified Eagle's
   medium (Gibco, Grand Island, NY, USA) supplemented with 10% fetal
   bovine serum (Gibco, south American). All cells were maintained in a
   humidified incubator at 37 °C and 5% CO[2].

Construction of GYS1 overexpression and knockdown cells

   Full-length GYS1 cDNA was cloned into the mammalian vector pENTER. The
   plasmids were transfected into ccRCC cell lines using Lipofectamine™
   3000 (Invitrogen, Carlsbad, CA, USA) reagent. Small interfering RNAs
   (siRNAs) and short hairpin RNAs (shRNA) targeting GYS1, NF-κB (p65) and
   RPS27A were purchased from Shanghai GenePharma Co. Ltd (Shanghai,
   China). Transfections experiments were performed by using the
   Lipofectamine™ RNAiMAX (Invitrogen). Puromycin and G418 (Sigma-Aldrich,
   St. Louis, MO, USA) were used to select stably transduced cells. The
   siRNAs sequences were listed in [57]Table S1.

Western Blot

   Total cell proteins were extracted using lysis buffer (Beyotime
   Biotechnology, Shanghai, China) supplemented with protease inhibitor.
   Western blot was performed based on the previously described standard
   method [58]^16. Briefly, total protein (30 μg) was loaded in each lane
   and separated in 10% SDS-PAGE by electrophoresis. The following
   antibodies against the indicated proteins were used in the immunoblot
   assays: GYS1 (1:1000, CST, Boston, MA, USA), NF-κB (p65) (1:1000, CST,
   Boston, MA, USA), p-NF-κB (p-p65) (1:1000, CST, Boston, MA, USA), p-52
   (1:1000, CST, Boston, MA, USA), Lamin B1 (1: 500, Santa Cruz
   Biotechnology, Dallas, TX, USA), β-actin (1:2000, Santa Cruz
   Biotechnology, Dallas, TX, USA). Band intensities were quantified using
   the Bio-Rad Molecular Imager ChemiDoc™ XRS+ system.

RNA extraction and quantitative real-time RT-PCR (qRT-PCR)

   Total RNA of fresh tissue and cell lines were isolated and purified
   using TRIzol reagent (BIOO Scientific Co., Austin, TX, USA). The mRNA
   was reverse-transcribed into cDNA using standard procedures with
   Reverse Transcriptase Kits (Vazyme Biotech, Nanjing, China). SYBR
   green-based quantitative real-time PCR was performed subsequently. The
   mRNA levels were normalized to the expression of 18S mRNA. The primer
   sequences used were listed in [59]Table S1.

Migration assays

   After transfection, 5 × 10^4 cells were harvested and re-plated in the
   upper compartment of transwell chambers (8 μm pore size, Millipore,
   Billerica, MA, USA) in serum-free medium. Fresh media containing 10%
   fetal bovine serum was placed in the lower chamber. The cells were
   attracted by fetal bovine serum-containing medium in the lower chamber.
   After incubation for 36 h, the cells in the lower membrane were fixed
   with methanol for 30 min and then stained with 0.1% crystal violet.
   Three 20 × magnification fields under a microscope were randomly chosen
   for counting the cell number.

In vivo tumorigenicity assay

   Four-week-old male BALB/c nude mice were purchased from Vital River
   Company (Beijing, China) and fed under standard conditions. Five mice
   were randomized into GYS1 overexpression or silencing groups and
   subcutaneously inoculated with the Caki-1 and Caki-2 cells. Tumor
   formation was monitored by measuring the tumor volume every 7 days.
   Four weeks after inoculation, the tumor was harvested, and the tumor
   volume was calculated as follows: tumor volume (mm^3) = (length ×
   width^2)/2. All animal procedures were performed following the SYSUCC
   Animal Care and Use Committee (IACUC) guidelines.

Immunofluorescence staining

   The cells were seeded into confocal-specific plates. After reaching 50%
   confluence on the next day, the cells were fixed in 3.7% formaldehyde,
   permeated with 0.5% Triton X-100, and blocked with 3% bovine serum
   albumin, followed by incubation with p-p65 or p65 specific primary
   antibodies overnight or bodipy staining for 30 min. After washing with
   phosphate-buffered saline three times, the secondary antibody (1:1000,
   CST, Boston, MA, USA) was added for 1 h incubation to interact with
   primary antibodies at room temperature. DAPI solution was applied and
   staining was performed for 5 min. Images were captured using a confocal
   microscope (Olympus Corporation, Tokyo, Japan).

Assessment of cell survival and death

   For cell activity assays, cultured cells were seeded into 96-well
   plates. After treatment, the cells were incubated with the Cell
   Counting Kit-8 (CCK8) reagent for 2 h at 37 °C for 5 consecutive days
   for proliferation analysis or 48 h for IC[50] detection. Cell activity
   was quantified by colorimetric reading in a microplate reader at an
   absorbance wavelength of 450 nm. For apoptosis analysis, cultured cells
   were seeded into six-well plates. Cell death was assessed using a
   Cytotoxicity Apoptosis Detection Kit (Roche, Basel, Switzerland) by
   flow cytometry with Annexin V/propidium iodide (PI) double staining
   (Invitrogen). For the colony formation assay, 500 cells were seeded
   into six-well plates after transfection and cultured in DMEM medium for
   10-14 days. The cells were washed with phosphate-buffered saline (PBS)
   and fixed in methanol for 15 min, followed by staining with 0.1%
   crystal violet. Cell numbers were counted at the macrographic level.
   For EdU staining, cultured cells were seeded into 96-well plates after
   transfection. After 48 h, the cells were fixed in methanol for 15 min,
   permeated with 0.1% Triton X-100, and blocked with 3% bovine serum
   albumin before EdU and Hoechst staining. Fluorescence images were
   captured with a fluorescence microscope (Olympus Corporation, Tokyo,
   Japan).

Co-immunoprecipitation and shotgun mass spectrometry

   For the co-immunoprecipitation (co-IP) assay, cellular proteins were
   harvested in lysis buffer (Beyotime Biotechnology, Shanghai, China) and
   supplemented with a cocktail protease inhibitor. After 10 min of
   centrifugation at 12,000 rpm to remove the cytoskeleton, specific
   primary antibody or control rabbit IgG was added to the supernatant and
   incubated at 4 °C for 4 h. Protein A/G beads (sc-2003, Santa Cruz
   Biotechnology, Dallas, TX, USA) were then added and incubated at 4 °C
   overnight. Precipitates were collected by centrifugation at 2000 rpm
   and washed at least three times with lysis buffer. Interacting proteins
   were detected by western blotting or shotgun mass spectrometry (MS)
   (Shanghai Genechem Co., Ltd., China).

Untargeted metabolomics

   Metabolomic profiling was performed in collaboration with Guangzhou
   Genedenovo Biotechnology Co., Ltd. (Guangzhou, China) including MS
   analysis and/or bioinformatics analysis. Briefly, Caki-1 cells were
   treated with scramble or GYS1 siRNAs and dissolved in 1 mL extract
   solvent (methanol: acetonitrile: water, 2:2:1, v/v) at 36 h
   post-transfection. A quality control sample was prepared by mixing an
   equal volume of all samples in each group. The experimental and control
   groups were tested using six biological duplicates. Liquid
   chromatography (LC)-MS/MS analyses were performed using an UHPLC system
   (1290, Agilent Technologies, Santa Clara, CA, USA). MS raw data files
   were converted to mzML format using ProteoWizard and processed by using
   the R package XCMS (version 3.2). The variance of metabolites across
   samples was calculated in positive and negative ion modes according to
   the LC-MS spectra. Metabolites showing a P < 0.05 were considered as
   differentially expressed metabolites. For statistical analysis,
   principal component analysis, partial least squares discriminant
   analysis (PLS-DA), and orthogonal projection to latent
   structures-discriminant analysis (OPLS-DA) were applied to compare
   groups using the R package models ([60]http://www.r-project.org/).

Statistical analysis

   Data are shown as means ± standard deviation. Statistical analyses were
   performed using the SPSS (Version 20.0, IBM, Armonk, NY, USA) and
   GraphPad PRISM (Version 7.0, GraphPad Software Inc., LaJolla, CA, USA)
   software. Paired Student's t-test, Pearson's χ2 test, Two-way ANNOVA
   test, Kaplan-Meier, and multivariate Cox proportional hazard regression
   models were conducted to analyze independent prognostic factors in
   overall survival. P < 0.05 (two-tailed) was considered statistically
   significant.

Results

GYS1 is upregulated in ccRCC and correlated with poor patient outcomes

   To examine the mRNA expression of GYS1 in ccRCC, we first searched the
   public Oncomine database. We found that GYS1 mRNA expression was
   significantly increased in tumor tissues compared to in normal tissues
   in the Jones Renal dataset (Figure [61]1A). Consistently, elevated GYS1
   mRNA was observed in The Cancer Genome Atlas (TCGA) KIRC database
   (Figure [62]1B) as well as GEO datasets [63]GSE53757 (Figure [64]1C).
   These results were validated in 24 paired ccRCC samples from our center
   (SYSUCC) (Figure [65]1D). At the protein level, GYS1 expression was
   relatively higher in 11 of 12 ccRCC than in matched non-tumor tissues
   (Figure [66]1E). Next, a tissue-micro array (TMA) containing 306 ccRCC
   cases with complete clinicopathological data was evaluated by GYS1 IHC
   staining ([67]Table S2). GYS1 was found to be primarily located in the
   cytoplasm. Statistical analysis revealed relatively higher IHC score of
   GYS1 in tumor samples than in paired non-tumor samples (Figure [68]1F).

Figure 1.

   [69]Figure 1
   [70]Open in a new tab

   GYS1 is increased in ccRCC and correlated with poor patient outcome.
   (A) The mRNA expression of GYS1 in the Oncomine Jones Renal dataset was
   determined in tumor (T) and non-tumor (N) cells. (B) The mRNA
   expression of GYS1 in TCGA-KIRC (clear renal cell carcinoma) was
   determined. (C) Expression profile of GYS1 in GEO data [71]GSE53757 was
   compared. (D) GYS1 mRNA levels in 24 paired ccRCC samples were
   validated using Sun Yat-sen University Cancer Center (SYSUCC) samples.
   The relative fold-change was normalized with 18S RNA. (E) Protein
   expression of GYS1 was determined by western blotting in 12 paired
   fresh ccRCC tissue samples. (F) Typical IHC images of GYS1 presented in
   tumor (T) and non-tumor (N) cells. The score of each case is shown in
   the right. (G) Correlation between GYS1 expression and overall survival
   were determined in the SYSUCC cohort and TCGA cohort by Kaplan-Meier
   analysis. (H) Stratified analysis of T stage (II-IV) patients' overall
   survival and GYS1 expression. Statistical data are represented as the
   mean ± SD. **P < 0.01.

   Next, we examined the relationship between GYS1 expression and clinical
   parameters. High GYS1 expression was statistically associated with age
   over 55 years (P = 0.035), higher Fuhrman nuclear grade (P < 0.001),
   sarcomatoid differentiation (P = 0.013), and higher T stage (P = 0.038)
   ([72]Table S3).

   To identify the correlation between GYS1 expression and patient
   outcomes, the median IHC score of GYS1 was selected as the cut-off
   value to separate ccRCC patients into a high or low expression group.
   Survival analyses revealed that GYS1 overexpression was significantly
   correlated with a worse overall survival (OS) in SYSUCC and TCGA
   patients with ccRCC (Figure [73]1G). In stratified survival analysis,
   the high GYS1 group was associated with a shorter OS in the higher T
   staging cohort (II-IV) (Figure [74]1H). Univariate and multivariate Cox
   regression analysis indicated that GYS1 overexpression was an
   independent prediction factor for OS (P < 0.001) ([75]Table S4). Taken
   together, these results indicated that an increase in GYS1 expression
   was a prognostic hallmark for ccRCC.

Metabolic profiling is altered with the depletion of GYS1

   Recently ccRCC metabolism has attracted renewed interest based on
   integrative analysis of transcriptomic and metabolomic data [76]^3. In
   this regard, we assessed whether the glycogen content was changed in
   ccRCC samples compared with corresponding non-tumor renal tissues by
   conducting PAS staining. D-PAS was also detected as a control to avoid
   false-positive staining (Figure [77]2A & [78]Figure S1A). Compared to
   paired non-tumor tissues, glycogen levels within the tumor samples were
   significantly increased and correlated with poor patient survival
   (Figure [79]2B & [80]Figure S1B). A glycogen detection kit further
   supported the increased glycogen levels in the tumors compared with
   paired non-tumor tissues, except for the Furhman grade 4 samples with
   sarcomatoid differentiation. Furthermore, there were no statistical
   differences between tumors in different grades (Figure [81]2C). By
   analyzing the TCGA-KIRC project based on the Gene Set Enrichment
   Analysis (GSEA), we found that the glycolysis, fructose, and galactose
   metabolism pathways were positively enriched in the high GYS1
   expression group, revealing that carbohydrate metabolism was markedly
   altered by elevated expression of GYS1 in cancer (Figure [82]2D).

Figure 2.

   [83]Figure 2
   [84]Open in a new tab

   Metabolic alterations in glycogen in ccRCC-associated GYS1 expression.
   (A) Representative images of tumor (T) and non-tumor (N) with PAS
   staining in ccRCC TMA. (B) Correlation of PAS staining and overall
   survival was determined by Kaplan-Meier analysis. (C) Glycogen levels
   were measured by quantitative colorimetry in ccRCC and corresponding
   adjacent non-tumor tissues (Fuhrman Grade 1: 1N & 1T; Fuhrman Grade 2:
   2N & 2T; Fuhrman Grade 3: 3N & 3T; Fuhrman Grade 4 without sarcomatoid
   differentiation: 4N & 4T; Fuhrman Grade 4 with sarcomatoid
   differentiation: 4SN & 4ST). (D) GSEA revealed that high GYS1
   expression was correlated with three KEGG glucose metabolism pathways.
   (E) Principal component analysis (PCA) of metabolomics data. Color of
   dots indicate control (red) and GYS1 knockdown (blue) samples. (F)
   Volcano plot profiling of all annotated metabolites. There were 158
   increased and 80 decreased metabolites showing significantly different
   abundance (P < 0.05) compared to in the GYS1 silencing and control
   groups. (G) Metabolic changes in central carbon metabolism in
   metabolomics data. Metabolites are labeled as color-coded squares.
   Color corresponds to the up (red) or down (blue) expression in the
   GYS1-silenced group. Gray denotes detected metabolites without
   significant changes. Pink denotes tendency to upregulation with P <
   0.1. Statistical data are represented as **P < 0.01.

   As GYS1 was known to catalyze glycogen synthesis, we detected
   metabolomic perturbations in Caki-1 cells with GYS1 silencing by
   untargeted metabolomics. MS revealed a total of 628 differential peaks
   in positive and negative ion modes totally, which matched 228
   identifiable metabolites ([85]Figure S1C). Principal component analysis
   (PCA), PLS-DA, and OPLS-DA revealed clear separation between the
   control and GYS1 knock-down groups (Figure [86]2E & [87]Figure S1D). A
   volcano map revealed 158 increased and 70 decreased metabolites (P <
   0.05) (Figure [88]2F). The glucose downstream metabolite fructose
   6-phosphate was significantly increased in Caki-1 cells. Five TCA cycle
   intermediate metabolites were measured, which revealed a dichotomous
   pattern of changes with an elevated level of oxaloacetate and decreased
   in the transient intermediate product cis-aconitate. α-Ketoglutarate
   tended to be higher in GYS1-silenced cells although not significantly
   (fold-change = 5.73, P = 0.051). We also observed a relatively large
   increase in glutamate, which was consistent with the previous findings
   that TCA flux alteration activated anaplerotic glutamine flux and amino
   acid content via broad shifts from central carbon metabolism to amino
   acid metabolism [89]^3^, [90]^17 (Figure [91]2G).

   To further explore whether GYS1 plays a role in lipid metabolism, we
   analyzed the correlation of GYS1 expression with lipid storage and
   synthesis. We found that overexpressed or silenced GYS1 did not
   influence lipid content in Caki-1 or Caki-2 cells ([92]Figure S2A). FAS
   activity detection and qRT-PCR assays. Results showed that
   overexpressed or silenced GYS1 did not influence lipid content in
   Caki-1 and Caki-2 cells ([93]Figure S2A). Fatty acid synthase activity
   was not associated with GYS1 in ccRCC cells ([94]Figure S2B). The mRNA
   expression of the lipid storage and synthesis enzymes FAS, CPT1A, and
   SERBP1 were not changed ([95]Figure S2C). These results indicated that
   GYS1 expression did not directly correlated with lipid metabolism in
   ccRCC.

GYS1 promotes ccRCC cell proliferation both in vitro and in vivo

   Next, we focused on the biological function of GYS1 in ccRCC cells. We
   explored the effects of GYS1 overexpression by transfecting an
   ectopic-expressing vector into the Caki-1 and Caki-2 cell lines (Figure
   [96]3A). Forced expression of GYS1 increased cell proliferation
   capacity and colony formation ability compared to in the scrambled
   control according to EdU staining, CCK8, and colony formation assays
   (Figure [97]3B-D). Upon GYS1 overexpression, the glycogen content in
   ccRCC cells increased (Figure [98]3E). In contrast, silencing of GYS1
   by two mixed siRNAs in Caki-1 and Caki-2 attenuated cell growth with
   concomitantly reduced glycogen content in ccRCC cells ([99]Figure
   S3A-E). However, overexpression or silencing of GYS1 did not affect
   cell migration as detected by Transwell assays ([100]Figure S4). The
   effects of GYS1 on cell proliferation were further corroborated in
   xenograft models. Caki-1 and Caki-2 cells transfected with GYS1
   overexpression vector grew faster with stronger staining of the
   proliferation marker Ki67 (Figure [101]3F & [102]Figure S5A). In
   contrast, GYS1 silencing reduced the tumor growth rate ([103]Figure S3F
   & [104]Figure S5B). Based on these results, GYS1 promoted ccRCC cell
   proliferation both in vitro and in vivo.

Figure 3.

   [105]Figure 3
   [106]Open in a new tab

   GYS1 promotes ccRCC proliferation in vitro and in vivo. (A) GYS1 was
   overexpressed by transfection with GYS1 exogenous vector in Caki-1 and
   Caki-2 cells. The mRNA and protein levels of GYS1 were determined by
   qRT-PCR and western blotting. (B) EdU assays showed the replication of
   DNA in cells induced by GYS1. Green staining denotes duplicated cells
   and blue denotes the cell nucleus. (C) Cell activity was detected by
   CCK8 assay over five consecutive days. Relative absorbance was measured
   at OD[450]. Fold-enrichment was normalized to the absorbance on day 1.
   (D) Colony formation assays to determine the effect of GYS1 on cell
   growth. The number of colonies was counted using ImageJ software (NIH,
   Bethesda, MD, USA). (E) The glycogen content in cell lines with GYS1
   overexpression were detected by a quantitative glycogen detection kit.
   (F) Xenograft mice experiment to evaluate tumor growth in vivo. Mice
   were sacrificed at 28 days after inoculation with Caki-2 cells. The
   volume of tumors in each group was calculated. Representative images of
   HE staining and IHC are shown. Statistical data are represented as the
   mean ± SD. *P < 0.05, **P < 0.01.

Functional and pathway enrichment analysis of GYS1-related genes in ccRCC

   To further dissect the functions and molecular mechanisms of GYS1 in
   ccRCC progression, we performed transcriptome profiling by
   RNA-sequencing in Caki-1 and Caki-2 cells transfected with GYS1 siRNAs.
   Based on the filtering conditions of false discovery rate (FDR) < 0.05
   and |log[2]FC|>1, 897 and 634 genes were differentially expressed in
   Caki-1 and Caki-2 cells respectively, among which 284 genes were
   mutually up- or downregulated in both cell lines (Figure [107]4A-B).
   Gene ontology (GO) analysis of these shared genes showed biological
   processes enrichment in carbohydrate biosynthetic processes and cell
   proliferation involved in kidney development (Figure [108]4C). KEGG
   enrichment analysis revealed that tumor necrosis factor-α (TNF-α)
   signaling pathways were markedly influenced by GYS1 (Figure [109]4D). A
   heatmap showed that the expression of a series of genes in the BIOCARTA
   NF-κB pathway were altered (Figure [110]4E). According to previous
   studies, canonical NF-κB (p65/RELA) was the pivotal pathway involved in
   TNF-α stimulation. We found that overexpression of GYS1 increased,
   whereas GYS1 knockdown decreased total p65 and phosphorylated p65
   (p-p65) (Figure [111]4F). Thus, the Caki-1 and Caki-2 cell lines might
   share similar mechanisms of cell growth through the cascade response
   triggered by the canonical NF-κB pathway.

Figure 4.

   [112]Figure 4
   [113]Open in a new tab

   Pathway-based analysis of GYS1 depletion by RNA sequencing. (A)
   Clustering of transcriptome sequencing in Caki-1 and Caki-2 cells with
   GYS1 siRNA transfection. Significance was set based on P < 0.05 and
   absolute fold-change > 2. (B) Venn diagraph filtered 284 shared
   differential genes in Caki-1 and Caki-2 cells with GYS1 silencing. (C)
   Gene Ontology (GO) enrichment analysis indicated the biological
   processes influenced by the filtered genes. (D) KEGG enrichment of
   filtered genes indicated signaling transduction pathway alterations.
   (E) Heatmap was generated based on BIOCARTA NF-κB pathway clustering.
   (F) Western blot indicated the expression of p-p65 and p65 regulated by
   GYS1.

GYS1 promotes p65 phosphorylation and nuclear accumulation

   Since p-p65 was activated by its nuclear accumulation, we separated the
   cytoplasmic and nuclear protein to determine whether p-p65 was
   relocated by GYS1.The p-p65 nuclear accumulation was observed with GYS1
   overexpression whereas GYS1 knockdown reduced nuclear proportion of
   p-p65 (Figure [114]5A). These results were supported by those of IF
   staining (Figure [115]5B and [116]Figure S6).

Figure 5.

   [117]Figure 5
   [118]Open in a new tab

   GYS1 activates the NF-κB signaling pathway. (A) Western blot revealed
   the expression of p-p65 in the cytoplasm and nucleus. β-Actin and Lamin
   B were used as internal references in the cytoplasm and nucleus,