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. 2020 Mar 20;11(1):1507.
doi: 10.1038/s41467-020-15112-3.

Long Noncoding RNA AGPG Regulates PFKFB3-mediated Tumor Glycolytic Reprogramming

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Free PMC article

Long Noncoding RNA AGPG Regulates PFKFB3-mediated Tumor Glycolytic Reprogramming

Jia Liu et al. Nat Commun. .
Free PMC article

Abstract

Tumor cells often reprogram their metabolism for rapid proliferation. The roles of long noncoding RNAs (lncRNAs) in metabolism remodeling and the underlying mechanisms remain elusive. Through screening, we found that the lncRNA Actin Gamma 1 Pseudogene (AGPG) is required for increased glycolysis activity and cell proliferation in esophageal squamous cell carcinoma (ESCC). Mechanistically, AGPG binds to and stabilizes 6-phosphofructo-2-kinase/fructose-2,6-biphosphatase 3 (PFKFB3). By preventing APC/C-mediated ubiquitination, AGPG protects PFKFB3 from proteasomal degradation, leading to the accumulation of PFKFB3 in cancer cells, which subsequently activates glycolytic flux and promotes cell cycle progression. AGPG is also a transcriptional target of p53; loss or mutation of TP53 triggers the marked upregulation of AGPG. Notably, inhibiting AGPG dramatically impaired tumor growth in patient-derived xenograft (PDX) models. Clinically, AGPG is highly expressed in many cancers, and high AGPG expression levels are correlated with poor prognosis, suggesting that AGPG is a potential biomarker and cancer therapeutic target.

Conflict of interest statement

The authors declare no competing interests.

Figures

Fig. 1
Fig. 1. Identification of AGPG as a metabolism-related lncRNA.
a Experimental scheme for identifying lncRNAs potentially involved in both cell viability and glucose metabolism. b Eight lncRNAs regulated both cell proliferation and lactate production in KYSE30 cells, n = 3 biologically independent samples. c qPCR detection of AGPG expression in multiple ESCC cells (n = 10 cells) and in normal esophageal epithelial cell lines (n = 2 cells). d Determination of AGPG copy number, n = 3 biologically independent samples. e Overall survival analysis based on AGPG levels in ESCC (TCGA, n = 161, log-rank test, two-sided). f Overall survival analysis based on AGPG levels in ESCC detected by qPCR (SYSUCC, n = 122, log-rank test, two-sided). g qPCR detection of AGPG expression in ESCC (training set n = 15, validation set n = 59, 127, respectively), GC (n = 46), CRC (n = 34) and normal tissues. h RNAScope ISH detection of AGPG expression in ESCC, GC, CRC, and matched normal tissues. Scale bar: 20 μm. i RNAScope ISH detection and statistical analysis of AGPG expression in ESCC, GC, CRC, and matched normal tissues. Data are presented as mean±S.D., n = 24 cases per tissue type, the p value was determined by a two-tailed unpaired Student’s t test. j qPCR detection of AGPG expression in the cytoplasmic and nuclear fractions. k RNAScope ISH detection of AGPG subcellular localization. Scale bar: 5 μm. l Subcellular localization of AGPG detected by FISH. Scale bar: 5 μm. Data in bd, g, i are representative of three independent experiments and presented as mean±S.D., the P value was determined by a two-tailed unpaired Student’s t test.
Fig. 2
Fig. 2. AGPG is required for cell proliferation and metabolism remodeling.
a qPCR and electrophoresis detection of AGPG expression in KYSE30 and KYSE150 cells. Ctrl, control. b Cell proliferation was assessed by MTS assays (OD 490 nm). c, d Colony formation assays and statistical analysis of ESCC cells transduced with shAGPG #1 or #2 or shCtrl. e The cell cycle was analyzed by flow cytometry analysis. f Statistical analysis of KYSE150 cells (%) in each cell cycle phase. g CDK1 and p27 expression levels were detected by western blotting in cells transfected with shAGPG #1 or #2 or shCtrl. h The ECAR was measured in cells transfected with shAGPG #1 or #2 or shCtrl using an XF Extracellular Flux Analyzer. i Statistical analysis of the effects of AGPG knockdown on glycolytic activity. j Flowchart of the experiments for identifying the role of AGPG in glucose metabolism. km 13C-Labeled metabolic intermediates of glycolysis were decreased after AGPG knockdown. Data in b, d, f, i, km are representative of three independent experiments and presented as mean±S.D., n = 3 biologically independent samples, the P value in b, d, f, i was determined by one-way analysis of variance (ANOVA) with Dunnett’s multiple comparisons test, no adjustments were made for multiple comparisons. The P value in km was determined by a two-tailed unpaired Student’s t test.
Fig. 3
Fig. 3. AGPG directly associates with PFKFB3.
a, b PFKFB3 in cell lysates a or purified His-tagged recombinant PFKFB3 b was pulled down by biotin-labeled AGPG but not by AGPG antisense RNA. S, sense. AS, antisense. c RIP assays indicated that AGPG precipitated with PFKFB3 in whole-cell lysates. The RNA levels of AGPG and β-actin were measured by qPCR analysis. d AGPG-binding proteins were detected by MTRAP and western blotting analysis. PFKFB3 bound to AGPG was captured by anti-FLAG antibody affinity agarose beads; IP complexes were separated and identified by specific antibodies. e Immunofluorescence analysis showed that AGPG and PFKFB3 colocalized not only in the nucleus but also in the cytoplasm. Scale bar: 5 μm. f qPCR detection of AGPG expression and western blotting detection of PFKFB3 expression in human ESCC cells. PFKFB3 expression was positively correlated with AGPG expression. (Pearson’s correlation analysis, n = 10). g In vitro-synthesized FL and truncation mutants of AGPG were incubated with protein lysates from KYSE150 and KYSE30 cells or with purified His-tagged recombinant PFKFB3. RNA pull-down and western blotting assays were then performed. h CLIP-qPCR showed that the T5 fragment of AGPG was the region responsible for PFKFB3 binding. i RNA pull-down assays showed that AGPG ΔT5 could not interact with PFKFB3. j AGPG CRISPR KO cell lines were generated using the CRISPR/Cas9 genome-editing system. Overexpression of AGPG FL, but not of AGPG ΔT5, was sufficient to reverse the decreased ECAR and cell proliferation caused by AGPG CRISPR KO. k Western blotting showed that CDK1 downregulation and p27 upregulation by AGPG CRISPR KO were abolished by AGPG FL but not by AGPG ΔT5. l HomeR was used to perform the motif analysis on the binding peaks obtained by the Piranha and CIMS analyses. Both methods suggested that CCAGCCA might be responsible for PFKFB3 binding. Data in c, f, h, j are representative of three independent experiments and presented as mean±S.D., n = 3 biologically independent samples, the P value was determined by a two-tailed unpaired Student’s t test.
Fig. 4
Fig. 4. AGPG affects PFKFB3 stability by preventing its ubiquitination.
a In vitro-synthesized AGPG was incubated with protein lysates from KYSE30 cells transfected with vectors expressing FLAG-tagged FL or truncation mutants of PFKFB3. RNA pull-down and western blotting assays were then performed. Truncation mutants included FL, N-terminal (N) and C-terminal (C) constructs. b RIP assays were performed using anti-FLAG antibodies in cells transfected with vectors expressing FLAG-tagged FL or truncation mutants of PFKFB3. c AGPG knockdown reduced PFKFB3 expression in ESCC cells. d PFKFB3 downregulation by AGPG CRISPR KO was rescued by AGPG FL but not by AGPG ΔT5. e PFKFB3 downregulation by AGPG knockdown was abolished by MG-132 (10 μm, 12 h). f Western blotting detection of PFKFB3 levels in KYSE150 cells transfected with shCtrl or shAGPG followed by treatment with CHX (100 µg per ml) for the indicated times. g IP assays showed that AGPG knockdown increased PFKFB3 ubiquitination levels. FLAG-tagged PFKFB3 was expressed in cells, which were then subjected to IP assays. h Active APC/C could be immunoprecipitated from cells using monoclonal Cdc27 antibody. CoIP assays showed that AGPG CRISPR KO significantly increased the interaction between PFKFB3 and Cdc27. i IP assays showed that AGPG knockdown did not increase ubiquitination of the PFKFB3 K302A mutant. j Cells were infected with FLAG-tagged PFKFB3 WT or K302A and treated with CHX (100 µg per ml) for the indicated time. FLAG levels were detected by western blotting. k PFKFB3 K302A overexpression significantly reversed the decreased ECAR and cell proliferation caused by AGPG CRISPR KO, whereas PFKFB3 WT could only partially rescue these effects in KYSE150 cells. l PFKFB3 K302A overexpression significantly reversed the decreased glycolysis caused by AGPG CRISPR KO, whereas PFKFB3 WT could only partially rescue this effect. m PFKFB3 K302A overexpression abolished the G1/S arrest caused by AGPG CRISPR KO, whereas PFKFB3 WT could only partially rescue this effect. Data in b, km are representative of three independent experiments and presented as mean±S.D., n = 3 biologically independent samples, the P value was determined by one-way ANOVA with Tukey’s multiple comparisons test. No adjustments were made for multiple comparisons.
Fig. 5
Fig. 5. AGPG is transcriptionally regulated by p53.
a Pathway enrichment analysis suggested that AGPG was negatively correlated with p53. The pathway analysis was performed with GSEA method, which was based on an empirical permutation test procedure. b qPCR detection of AGPG expression in TP53 KO and control HCT-116 cells. c qPCR detection of AGPG expression in ESCC cells with WT TP53 (KYSE150) or MT TP53 (KYSE30 and TE-1). d qPCR detection of AGPG expression in KYSE150 and HCT-116 cells with p53 upregulation or downregulation or control. e qPCR analysis showed that AGPG expression was negatively correlated with TP53 expression in a cohort of ESCC patients with WT TP53 (SYSUCC, Pearson’s correlation analysis, n = 72). f The AGPG promoter contains a consensus p53-binding region. g ChIP assays showed that p53 bound to the AGPG promoter. h WT TP53 overexpression diminished the transcriptional activity of AGPG in KYSE150 cells. i Schematic map of the regulatory network involving p53 and AGPG. j qPCR detection of AGPG expression in 293 T cells exposed to oncogenic stress (20 ng per ml doxycycline to induce ectopic KRasG12V expression) for 0, 24, 48, or 72 h. Doxy, doxycycline. k qPCR detection of AGPG expression in cells exposed to hypoxia or normoxia for 48 h. Data in bd, h, j, k are representative of three independent experiments and presented as mean±S.D., n = 3 biologically independent samples, the P value was determined by a two-tailed unpaired Student’s t test.
Fig. 6
Fig. 6. Effects of AGPG on tumor growth in vivo.
a AGPG knockdown inhibited cell-based xenograft growth in nude mice. b, c Statistical analysis of KYSE150 tumor volume and weight in nude mice. d Representative IHC images of randomly selected KYSE150 cell-based tumors from each group. Scale bar, 100 µm. e Quantification of IHC staining in KYSE150 cell-based tumors. f Graphic illustration of the intratumoral injection of in vivo-optimized AGPG inhibitor or control in the PDX models. g AGPG knockdown inhibited PDX growth in nude mice. The tumor tissues were from two ESCC patients (SYSUCC). h, i Statistical analysis of tumor volume and weight in the PDX #1 model. j Representative IHC images of randomly selected human-derived tumors from each group. Scale bar, 100 µm. kn Quantification of IHC staining in human-derived tumors. Data in b, c, e, h, i, kn are representative of three independent experiments and presented as mean±S.D., n = 5 mice per group, the P value was determined by one-way ANOVA with Dunnett’s multiple comparisons test. No adjustments were made for multiple comparisons.
Fig. 7
Fig. 7. Clinical relevance of the p53-AGPG-PFKFB3 axis in ESCC.
a Representative IHC staining for Ki67, PFKFB3, CDK1, p27, and p53 in ESCC patients (SYSUCC, n = 104) with low or high AGPG expression. Scale bar, 100 µm. b Percentage of specimens with low or high Ki67, PFKFB3, CDK1, p27, and p53 expression in the low or high AGPG expression groups (SYSUCC, n = 104, Chi-square test, two-sided). c, d Representative IHC images and statistical analysis of PFKFB3 expression in ESCC and matched normal tissues (SYSUCC). Scale bar, 100 µm. Data are representative of three independent experiments and presented as mean±S.D., n = 20 cases, the P value was determined by a two-tailed unpaired Student’s t test. e Kaplan–Meier analysis of the overall survival of ESCC patients (SYSUCC) with low (n = 52) or high (n = 52) PFKFB3 expression (log-rank test, two-sided). f Kaplan–Meier analysis of overall survival of ESCC patients (SYSUCC) with low (low expression of both AGPG and PFKFB3, n = 42), high (high expression of both AGPG and PFKFB3, n = 41) or intermediate (n = 21) AGPG/PFKFB3 expression (log-rank test, two-sided). g Graphical abstract showing that the lncRNA AGPG regulates glucose metabolism remodeling by affecting PFKFB3 stability.

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References

    1. WEINHOUSE S. On respiratory impairment in cancer cells. Science. 1956;124:267–269. doi: 10.1126/science.124.3215.267. - DOI - PubMed
    1. Shankaraiah RC, Veronese A, Sabbioni S, Negrini M. Non-coding RNAs in the reprogramming of glucose metabolism in cancer. Cancer Lett. 2018;419:167–174. doi: 10.1016/j.canlet.2018.01.048. - DOI - PubMed
    1. Chen F, et al. Extracellular vesicle-packaged HIF-1alpha-stabilizing lncRNA from tumour-associated macrophages regulates aerobic glycolysis of breast cancer cells. Nat. Cell Biol. 2019;21:498–510. doi: 10.1038/s41556-019-0299-0. - DOI - PubMed
    1. Ju H, et al. Modulation of redox homeostasis by inhibition of MTHFD2 in colorectal cancer: mechanisms and therapeutic implications. J. Natl Cancer Inst. 2019;111:584–596. doi: 10.1093/jnci/djy160. - DOI - PMC - PubMed
    1. Ju H, et al. ITD mutation in FLT3 tyrosine kinase promotes Warburg effect and renders therapeutic sensitivity to glycolytic inhibition. Leukemia. 2017;31:2143–2150. doi: 10.1038/leu.2017.45. - DOI - PMC - PubMed
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