N4-Acetylcytidine Drives Glycolysis Addiction in Gastric Cancer via NAT10/SEPT9/HIF-1α Positive Feedback Loop

Abstract

Anti-angiogenic therapy has long been considered a promising strategy for solid cancers. Intrinsic resistance to hypoxia is a major cause for the failure of anti-angiogenic therapy, but the underlying mechanism remains unclear. Here, it is revealed that N4-acetylcytidine (ac4C), a newly identified mRNA modification, enhances hypoxia tolerance in gastric cancer (GC) cells by promoting glycolysis addiction. Specifically, acetyltransferase NAT10 transcription is regulated by HIF-1α, a key transcription factor of the cellular response to hypoxia. Further, acRIP-sequencing, Ribosome profiling sequencing, RNA-sequencing, and functional studies confirm that NAT10 in turn activates the HIF-1 pathway and subsequent glucose metabolism reprogramming by mediating SEPT9 mRNA ac4C modification. The formation of the NAT10/SEPT9/HIF-1α positive feedback loop leads to excessive activation of the HIF-1 pathway and induces glycolysis addiction. Combined anti-angiogenesis and ac4C inhibition attenuate hypoxia tolerance and inhibit tumor progression in vivo. This study highlights the critical roles of ac4C in the regulation of glycolysis addiction and proposes a promising strategy to overcome resistance to anti-angiogenic therapy by combining apatinib with ac4C inhibition.

Keywords: NAT10; ac4C; gastric cancer; glucose metabolism reprogramming; hypoxias.

Figure 1

A hypoxic tumor microenvironment contributes to the upregulation of NAT10 in GC. A) The NAT10 expression in CT and IM was detected by IHC. Scale bars, 50 µm. B) Dual staining of HIF‐1α and NAT10 to assay the correlation between hypoxia and NAT10 expression in human GC tissues (HIF‐1α, green; NAT10, red; DAPI, blue). Scale bars, 20 µm. C) Diagram depicting the construction processes and treatment schedule for the subcutaneous tumor model (upper panel). Tumors treated with apatinib had decreased angiogenesis (lower panel; CD31, red; DAPI, blue). Scale bars, 50 µm. D) The hypoxia and NAT10 expression in tumors treated with apatinib were detected by confocal immunofluorescence microscopy (HIF‐1α, green; NAT10, red; DAPI, blue). Scale bars, 20 µm. E) Western blot analysis of NAT10 expression in AGS cells treated with 0–250 µm CoCl₂. F) Identification of transcription factors interacting with NAT10 promoter by Pscan (http://159.149.160.88/pscan/) online promoter database. G) The motif of HIF‐1α binding NAT10 promoter, prompted by Pscan. H) Schematic representation of the mutated promoter in pEZX‐PL01‐NAT10‐luc reporter to investigate the role of HIF‐1α in NAT10 expression. I) AGS cells with CoCl₂ treatment (0–250 µm) were transfected with NAT10 promoter‐WT or Mut reporters for 24 h.

Figure 2

ac4C promotes metabolic rewiring toward a glycolytic phenotype in GC cells. A) Expression of NAT10 in shRNAs transfected AGS cells was analyzed by Western blot and qPCR. B) The total RNA ac4C level in NAT10‐knockdown AGS cells was determined by anti‐ac4C dot blot with methylene blue staining as loading control. C) Representative pathway analysis terms showing pathways of related genes significantly enriched by ac4C. D) Differential genes expression analysis showed that the expression of HK1, HK2, HKDC1, and PDK1 were down‐regulated in shNAT10 cells. E) AGS cells with NAT10 knockdown (treated with 100 µm CoCl₂) exhibited lower glucose consumption, lactate production, and ATP levels. F) Confocal laser scanning microscope analysis of mitochondrial membrane potential in NAT10‐knockdown AGS cells (treated with 100 µm CoCl₂) after Mito Tracker Red CMXRos staining. Scale bars, 10 µm. G,H) The proliferation and migration changes of AGS cells treated with Oligomycin A (1 µm) were tested using CCK8 assay G) and monolayer wound healing assay H), respectively. Scale bars, 500 µm.

Figure 3

SEPT9 is involved in regulating glycolysis addiction in GC cells. A) Sequence analysis of the highly enriched motif within ac4C peaks in acRIP‐seq. B) Density distribution of ac4C peaks across mRNA transcripts. C) Proportion of ac4C peak distribution in the exon, 5″UTR, start codon, CDS, stop codon or 3″UTR region across the entire set of mRNA transcripts. D) Percentage of mRNAs with different numbers of ac4C peaks. F) Expression of SEPT9 in shRNAs transfected AGS cells were analyzed by Western blot and qPCR. G,H) The GC cells were treated with 100 µm CoCl₂. G) Reduced glucose consumption, lactate production, and ATP synthesis were observed in SEPT9 knockdown AGS cells. H) Transmission electron microscopic observation of mitochondria in control and shSEPT9 AGS cells in hypoxia (mitochondria: red arrows). Scale bars, 500 nm.

Figure 4

ac4C regulates the mRNA stability and translation of SEPT9 in GC cells. A) Immunofluorescence showed that NAT10 was predominantly distributed in the nucleus (NAT10, red; DAPI, blue). Scale bars, 10 µm. B) NAT10 RIP‐qPCR analysis of SEPT9 mRNA in AGS cells. C) Translation efficiency analysis of SEPT9 mRNA using Ribo‐seq. D,E) NAT10 promoted the protein expression of SEPT9. F) the mRNA levels of SEPT9 were detected in shNAT10 AGS cells after treatment with Act‐D for the indicated times. G) Integrative Genomics Viewer (IGV) tracks revealed the results of ac4C‐seq read distribution in SEPT9 mRNA of NAT10 knockdown and control AGS cells. Square marked decreased ac4C peaks in shNAT10 AGS cells. H) Schematic representation of positions of ac4C motifs within SEPT9 mRNA (upper panel). The ac4C sites within 3″UTR of SEPT9 mRNA were mutated to remove as many ac4C sites as possible. Schematic representation of mutated 3″UTR of pEZX‐MT06 vector to investigate the roles of ac4C in 3″UTR in SEPT9 mRNA stability (lower panel). I) shNC or shNAT10 AGS cells were transfected with WT or Mut 3″UTR reporters for 24 h.

Figure 5

ac4C promotes glycolysis addiction via a NAT10/SEPT9/ HIF‐1α positive feedback loop. A) Surface diagram of the docking model and their interfacing residues between SEPT9 and HIF‐1α protein (SEPT9, blue; HIF‐1α, yellow; hydrogen bond interaction, dotted line). B) Immunoprecipitation analysis of the interaction between SEPT9 and HIF‐1α in AGS cells. C) Western blot analysis of the expression of HIF‐1α in shNAT10 or shSEPT9 AGS cells (with 100 µm CoCl₂ treatment). D) AGS cells were grown and subjected to immunofluorescence staining (SEPT9, red; DAPI, blue) and confocal microscopy. Scale bars, 10 µm E) shNAT10+SEPT9 AGS cells were subjected to nuclear and cytoplasmic proteins extraction. F) Enhanced glucose consumption, lactate production, and ATP synthesis were observed in shNAT10+SEPT9 AGS cells (treated with 100 µm CoCl₂). G) Transmission electron microscopic observation of mitochondria in control and shNAT10+SEPT9 AGS cells (treated with 100 µm CoCl₂) in hypoxia (mitochondria, blue, and red arrows; Vacuolated mitochondria, red arrows). Scale bars, 1 µm. H) Whole‐body fluorescence images of xenograft GC nude mouse model.

Figure 6

Combining ac4C inhibition with apatinib optimizes antitumor effects. A) Diagram depicting the construction processes and treatment schedule for the orthotropic xenograft GC mouse model. B) Fluorescence images of tumor metastasis in the orthotropic xenograft GC nude mouse models (left panel). The numbers of metastatic nodules (hepatic, intestinal, and peritoneal nodules) per group were quantitatively analyzed (right panel). C) Dual staining of CD31 and HIF‐1α to assay angiogenesis and hypoxic changes in the implanted tumors. (CD31, red; HIF‐1α, green; DAPI, blue). Scale bars, 50 µm. D) Representative images of implanted tumors and metastatic nodules (indicated by red circles or fluorescence) were shown and detected by hematoxylin‐eosin (H&E) staining. Scale bars, 50 µm. E) Schematic diagram depicting the mechanism of NAT10/SEPT9/HIF‐1α positive feedback loop regulating glycolysis addiction in GC cells.