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. 2021 Mar 25:8:605754.
doi: 10.3389/fmolb.2021.605754. eCollection 2021.

Upregulation of GNPNAT1 Predicts Poor Prognosis and Correlates With Immune Infiltration in Lung Adenocarcinoma

Wenting Liu  1 , Kaiting Jiang  1 , Jingya Wang  1 , Ting Mei  1 , Min Zhao  1 , Dingzhi Huang  1
Affiliations

Upregulation of GNPNAT1 Predicts Poor Prognosis and Correlates With Immune Infiltration in Lung Adenocarcinoma

Wenting Liu et al. Front Mol Biosci. .

Abstract

Background: Glucosamine 6-phosphate N-acetyltransferase (GNPNAT1) is a key enzyme in the hexosamine biosynthetic pathway (HBP), which functions as promoting proliferation in some tumors, yet its potential biological function and mechanism in lung adenocarcinoma (LUAD) have not been explored.

Methods: The mRNA differential expression of GNPNAT1 in LUAD and normal tissues was analyzed using the Cancer Genome Atlas (TCGA) database and validated by real-time PCR. The clinical value of GNPNAT1 in LUAD was investigated based on the data from the TCGA database. Then, immunohistochemistry (IHC) of GNPNAT1 was applied to verify the expression and clinical significance in LUAD from the protein level. The relationship between GNPNAT1 and epigenetics was explored using the cBioPortal database, and the miRNAs regulating GNPNAT1 were found using the miRNA database. The association between GNPNAT1 expression and tumor-infiltrating immune cells in LUAD was observed through the Tumor IMmune Estimation Resource (TIMER). Finally, Gene set enrichment analysis (GSEA) was used to explore the biological signaling pathways involved in GNPNAT1 in LUAD.

Results: GNPNAT1 was upregulated in LUAD compared with normal tissues, which was verified through qRT-PCR in different cell lines (P < 0.05), and associated with patients' clinical stage, tumor size, and lymphatic metastasis status (all P < 0.01). Kaplan-Meier (KM) analysis suggested that patients with upregulated GNPNAT1 had a relatively poor prognosis (P < 0.0001). Furthermore, multivariate Cox regression analysis indicated that GNPNAT1 was an independent prognostic factor for LUAD (OS, TCGA dataset: HR = 1.028, 95% CI: 1.013-1.044, P < 0.001; OS, validation set: HR = 1.313, 95% CI: 1.130-1.526, P < 0.001). GNPNAT1 overexpression was correlated with DNA copy amplification (P < 0.0001), low DNA methylation (R = -0.52, P < 0.0001), and downregulation of hsa-miR-30d-3p (R = -0.17, P < 0.001). GNPNAT1 expression was linked to B cells (R = -0.304, P < 0.0001), CD4+T cells (R = -0.218, P < 0.0001), and dendritic cells (R = -0.137, P = 0.002). Eventually, GSEA showed that the signaling pathways of the cell cycle, ubiquitin-mediated proteolysis, mismatch repair and p53 were enriched in the GNPNAT1 overexpression group.

Conclusion: GNPNAT1 may be a potential prognostic biomarker and novel target for intervention in LUAD.

Keywords: GNPNAT1; biomarker; immune infiltration; lung adenocarcinoma; prognosis.

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Conflict of interest statement

The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.

Figures

FIGURE 1
FIGURE 1
The expression of GNPNAT1 in cancers. (A) The mRNA expression level of GNPNAT1 in cancer cells. (B) The expression level of GNPNAT1 in different tumor and normal tissues.
FIGURE 2
FIGURE 2
The differential expression of GNPNAT1 in normal tissues and LUAD. (A) The differential expression of GNPNAT1 from the TCGA database. The differential expression of GNPNAT1 in GSE19188 (B), GSE19804 (C), GSE31210 (D), and GSE32863 (E). The expression level in different LUAD and normal lung cell lines (F). The differential expression of GNPNAT1 from clinical samples (G). The typical IHC staining results of GNPNAT1 in normal lung tissue and LUAD tissues (H). *P < 0.05, **P < 0.01, ***P < 0.001, and ****P < 0.0001, ns: insignificant.
FIGURE 3
FIGURE 3
Association of GNPNAT1 expression with clinicopathologic characteristics. (A) The survival curve between low and high expression of GNPNAT1 in LUAD. The correlation between GNPNAT1 and clinicopathologic variables involved in gender (B), cancer status (C), clinical stage (D), lymph node metastasis status (E), and tumor size (F). *P < 0.05, **P < 0.01, ***P < 0.001, and ****P < 0.0001, ns: insignificant.
FIGURE 4
FIGURE 4
Association of GNPNAT1 expression with clinical features in validation set, including TNM stage (A), tumor size (B), and lymph node metastasis status (C). The Kaplan–Meier curves about the correlation between GNPNAT1 expression and overall survival (D) and disease-free survival (E). **P < 0.01 and ****P < 0.0001, ns: insignificant).
FIGURE 5
FIGURE 5
The prognostic nomograms based on GNPNAT1 and TNM stage (A) and TNM stage alone (C). The calibration curve of (A) nomogram for predicting OS at 2 year (B). The calibration curve of (C) nomogram for predicting OS at 2 year (D).
FIGURE 6
FIGURE 6
The correlation between GNPNAT1 and some epigenetic factors. The association of GNPNAT1 with its DNA copy alternations (A), methylation (B), and has-miR-30d-3p expression (C). (D) The KM curves of the correlation between has-miR-30d-3p expression and overall survival in LUAD based on TCGA data (Cutoff value of high/low group was the median of miRNA expression). (E) The predicted target region of GNPNAT1 and has-miR-30d-3p.
FIGURE 7
FIGURE 7
The role of GNPNAT1 in immunomodulation for LUAD. (A) The association between GNPNAT1 expression and tumor infiltration immune cells. (B) The expression level of MKI67 in LUAD and normal tissues from TCGA. (C) The correlation of GNPNAT1 and MKI67 based on TIMER database.
FIGURE 8
FIGURE 8
The PPI network of GNPNAT1 in LUAD. (A) The PPI network was constructed by database. The correlation between GNPNAT1 and CXCL5 (B)/EIF2SI (C).
FIGURE 9
FIGURE 9
The GSEA results about GNPNAT1 in LUAD from TCGA. The signaling pathways of the cell cycle (A), ubiquitin mediated proteolysis (B), mismatch repair (C), and p53 signaling pathway (D).
See this image and copyright information in PMC

References

    1. Abdel-Wahab A. F., Mahmoud W., Al-Harizy R. M. (2019). Targeting glucose metabolism to suppress cancer progression: prospective of anti-glycolytic cancer therapy. Pharmacol. Res. 150:104511. 10.1016/j.phrs.2019.104511 - DOI - PubMed
    1. Agarwal V., Bell G. W., Nam J. W., Bartel D. P. (2015). Predicting effective microRNA target sites in mammalian mRNAs. Elife 4:e05005. 10.7554/eLife.05005 - DOI - PMC - PubMed
    1. Akella N. M., Ciraku L., Reginato M. J. (2019). Fueling the fire: emerging role of the hexosamine biosynthetic pathway in cancer. BMC Biol. 17:52. 10.1186/s12915-019-0671-3 - DOI - PMC - PubMed
    1. Bernardino J., Bourgeois C. A., Muleris M., Dutrillaux A. M., Malfoy B., Dutrillaux B. (1997). Characterization of chromosome changes in two human prostatic carcinoma cell lines (PC-3 and DU145) using chromosome painting and comparative genomic hybridization. Cancer Genet. Cytogenet. 96 123–128. 10.1016/s0165-4608(96)00258-0 - DOI - PubMed
    1. Boehmelt G., Wakeham A., Elia A., Sasaki T., Plyte S., Potter J., et al. (2000). Decreased UDP-GlcNAc levels abrogate proliferation control in EMeg32-deficient cells. Embo. J. 19 5092–5104. 10.1093/emboj/19.19.5092 - DOI - PMC - PubMed