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. 2022 Mar 3:12:846536.
doi: 10.3389/fonc.2022.846536. eCollection 2022.

NcRNA-Mediated High Expression of HMMR as a Prognostic Biomarker Correlated With Cell Proliferation and Cell Migration in Lung Adenocarcinoma

Affiliations

NcRNA-Mediated High Expression of HMMR as a Prognostic Biomarker Correlated With Cell Proliferation and Cell Migration in Lung Adenocarcinoma

Xiulin Jiang et al. Front Oncol. .

Abstract

Background: Hyaluronan-mediated motility receptor (HMMR) plays a pivotal role in cell proliferation in various cancers, including lung cancer. However, its function and biological mechanism in lung adenocarcinoma (LUAD) remain unclear.

Methods: Data on HMMR expression from several public databases were extensively analyzed, including the prognosis of HMMR in the Gene Expression Profiling Interactive Analysis (GEPIA) database. Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathways were analyzed using DAVID and gene set enrichment analysis (GSEA) software. The correlation between HMMR expression and immune cell infiltration was analyzed in the Tumor Immune Estimation Resource (TIMER) database, and the gene and protein networks were examined using the GeneMANIA and STRING databases. Experimentally, the expression of HMMR in LUAD and lung cancer cell lines was determined using immunohistochemistry and quantitative RT-PCR assays. Besides, the function of HMMR on cancer cell proliferation and migration was examined using cell growth curve and colony formation, Transwell, and wound healing assays.

Results: In this study, we found that HMMR was elevated in LUAD and that its high expression was associated with poor clinicopathological features and adverse outcomes in LUAD patients. Furthermore, our results demonstrated that the expression of HMMR was positively correlated with immune cell infiltration and immune modulation. Interestingly, diverse immune cell infiltration affects the prognosis of LUAD. In the functional assay, depletion of HMMR significantly repressed the cancer cell growth and migration of LUAD. Mechanically, we found that that the DNA methylation/TMPO-AS1/let-7b-5p axis mediated the high expression of HMMR in LUAD. Depletion of TMPO-AS1 and overexpression of let-7b-5p could result in the decreased expression of HMMR in LUAD cells. Furthermore, we found that TMPO-AS1 was positively correlated with HMMR, yet negatively correlated with let-7b-5p expression in LUAD.

Conclusions: Our findings elucidated that the DNA methylation/TMPO-AS1/let-7b-5p axis mediated the high expression of HMMR, which may be considered as a biomarker to predict prognosis in LUAD.

Keywords: cell proliferation; hyaluronan-mediated motility receptor; immune infiltration; non-coding RNA; non-small cell lung cancer.

PubMed Disclaimer

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
HMMR was highly expressed in pan-cancer. (A) The expression of HMMR in pan-cancers examined by TIMER tools. (B) The expression of HMMR in pan-cancers examined by GEPIA tools. (C) The expression of HMMR in pan-cancers cells lines examined by CCLE database. *P < 0.05; ***P < 0.001.
Figure 2
Figure 2
Pathological stage analysis of hyaluronan-mediated motility receptor (HMMR) in various human cancers. (A–K) Pathological stage of HMMR in adrenocortical carcinoma (ACC) (A), breast invasive carcinoma (BRCA) (B), esophageal carcinoma (ESCA) (C), head and neck squamous cell carcinoma (HNSC) (D), chromophobe renal cell carcinoma (KICH) (E), kidney renal clear cell carcinoma (KIRC) (F), kidney renal papillary cell carcinoma (KIRP) (G), acute myeloid leukemia (LAML) (H), liver hepatocellular carcinoma (LIHC) (I), lung adenocarcinoma (LUAD) (J), lung squamous cell carcinoma (LUSC) (K), and ovarian serous cystadenocarcinoma (OV) (L) examined using Gene Expression Profiling Interactive Analysis (GEPIA).
Figure 3
Figure 3
HMMR was up-regulated in LUAD. (A, B) The expression of HMMR in LUAD examine by TCGA databases. (C–I) The correlation between HMMR expression and clinical features in LUAD. (J) The ROC curve of HMMR in LUAD. (K) The prognosis of HMMR in LUAD examine by TCGA database. Overall survival (os), disease specific survival (DSS), progression-free survival (PFS), SD (stable disease), and PD (progressive disease). Ns, P > 0.05; ***P < 0.001.
Figure 4
Figure 4
Prognosis of hyaluronan-mediated motility receptor (HMMR) based on different subgroups. (A–H) Prognosis of HMMR based on TNM stage, age, pathologic stage, and smoking status.
Figure 5
Figure 5
Kyoto Encyclopedia of Genes and Genomes (KEGG) pathways of hyaluronan-mediated motility receptor (HMMR) in lung adenocarcinoma (LUAD). (A) Differentially expressed genes displayed in a volcano plot. (B, C) Positive and negative correlations with HMMR displayed in a heatmap. (D) Analysis of the biological process of HMMR. (E) Analysis of the KEGG pathways of HMMR. (F) Gene interaction network of HMMR constructed using GeneMANIA. (G) Construction of the protein–protein interaction network of HMMR using STRING. (H) Signaling pathways enriched using gene set enrichment analysis (GSEA) software.
Figure 6
Figure 6
HMMR expression was associated with immune infiltration in LUAD. (A) The correlation between HMMR CNV and immune cells in LUAD examined by TIMER database. (B) The correlation between HMMR expression and immune infiltration in LUAD examined by TIMER database. (C) The correlation between HMMR expression and immune checkpoints related gene expression in LUAD. (D) The correlation between HMMR expression level and 24 immune cell types. *P < 0.05; **P < 0.01; *** < 0.001.
Figure 7
Figure 7
Prognostic potential of the expression of hyaluronan-mediated motility receptor (HMMR) in different tumors based on immune cells. (A–L) Relationship between HMMR expression and overall survival (OS) based on the immune cell subgroups examined using the Kaplan–Meier (KM) plotter.
Figure 8
Figure 8
Predicted and analysis the upstream miRNAs of HMMR in LUAD. (A) The correlation between the HMMR expression and miRNA-18a-5p, miR-33a-5p and miR-369-3p analysis by starBase. (B) The target sites between HMMR and hsa-let-7b-5p were predicted by starBase. (C) The correlation between the HMMR expression and hsa-let-7b-5p analysis by starbase. (D) The expression of hsa-let-7b-5p in LUAD analysis by TCGA. (E–G) The correlation between hsa-let-7b-5p expression and clinical features in LUAD. (H) The prognosis of hsa-let-7b-5p in LUAD analysis by kmplot. (I) The ROC curve of hsa-let-7b-5p in LUAD. (J) The expression of hsa-let-7b-5p in LUAD cells analysis by employed qRT-PCR assay. (K) The expression of HMMR after overexpression of hsa-let-7b-5p in LUAD cells analysis by qRT-PCR assay. (L) The expression of HMMR after overexpression of hsa-let-7b-5p in LUAD Cells analysis by western blot assay. NC, Negative control. P > 0.05 (ns), ***P < 0.001, was considered significantly.
Figure 9
Figure 9
Predicted and analysis the upstream LncRNAs of let-7b-5p in LUAD. (A) The target sites between the TMPO-AS1 and hsa-let-7b-5p were predicted by starbase. (B) The correlation between hsa-let-7b-5p expression and TMPO-AS1 analysis by starbase. (C) The correlation between the HMMR expression and TMPO-AS1 analysis by starbase. (D) The expression of TMPO-AS1 in LUAD analysis by starbase. (E, F) The prognosis of TMPO-AS1 in LUAD analysis by kmplot. (G) The ROC curve of TMPO-AS1 in LUAD. (H) The subcellular localization of TMPO-AS1 analysis by the lncLocator tools. (I) The coding potential of TMPO-AS1 analysis by the coding potential calculator. (J) The HMMR and hsa-let-7b-5p expression after depletion of TMPO-AS1 in LUAD cells analysis by qRT-PCR assay. (K) The DNA methylation of TMPO-AS1 in LUAD. (L) The correlation between DNA methylation and expression of TMPO-AS1 in LUAD. (M) The expression of TMPO-AS1 in LUAD cells after treat with 5Aza examined by qRT-PCR assay. P >0.05 (ns), P < 0.001 (***), was considered significantly.
Figure 10
Figure 10
Depletion of HMMR inhibits growth and migration of LUAD cells in vivro. (A) IHC analysis of HMMR in LUAD. (B) The expression of HMMR in LUAD cell lines by qRT-PCR. (C, D) Establishment of HMMR knockdown in A549 and H1299 cell lines and verified by qRT-PCR and Western blot. (E) The growth curve assay was employed detect the proliferation of LUAD cells. (F) The colony formation assay was employed detect the proliferation of LUAD cells. (G) The transwell assay was employed detect the migration of LUAD cells, (H) The wound healing assay was employed detect the migration of LUAD cells. P < 0.05 (*), P < 0.01 (**) and P < 0.001 (***), P < 0.0001 (***) was considered significantly.

References

    1. Bade BC, Dela Cruz CS. Lung Cancer 2020: Epidemiology, Etiology, and Prevention. Clin Chest Med (2020) 41(1):1–24. doi: 10.1016/j.ccm.2019.10.001 - DOI - PubMed
    1. Zheng M. Classification and Pathology of Lung Cancer. Surg Oncol Clin N Am (2016) 25(3):447–68. doi: 10.1016/j.soc.2016.02.003 - DOI - PubMed
    1. Zeng Y, Shi Y, Xu L, Zeng Y, Cui X, Wang Y, et al. Prognostic Value and Related Regulatory Networks of MRPL15 in Non-Small-Cell Lung Cancer. Front Oncol (2021) 11:656172. doi: 10.3389/fonc.2021.656172 - DOI - PMC - PubMed
    1. Liang R, Li X, Li W, Zhu X, Li C. DNA Methylation in Lung Cancer Patients: Opening a “Window of Life” Under Precision Medicine. BioMed Pharmacother (2021) 144:112202. doi: 10.1016/j.biopha.2021.112202 - DOI - PubMed
    1. Li QG, He YH, Wu H, Yang CP, Pu SY, Fan SQ, et al. A Normalization-Free and Nonparametric Method Sharpens Large-Scale Transcriptome Analysis and Reveals Common Gene Alteration Patterns in Cancers. Theranostics (2017) 7(11):2888–99. doi: 10.7150/thno.19425 - DOI - PMC - PubMed