Validating HMMR Expression and Its Prognostic Significance in Lung Adenocarcinoma Based on Data Mining and Bioinformatics Methods

Xia Li; Haiwei Zuo; Li Zhang; Qiuwen Sun; Yong Xin; Longzhen Zhang

doi:10.3389/fonc.2021.720302

Validating HMMR Expression and Its Prognostic Significance in Lung Adenocarcinoma Based on Data Mining and Bioinformatics Methods

Front Oncol. 2021 Aug 30:11:720302. doi: 10.3389/fonc.2021.720302. eCollection 2021.

Authors

Xia Li^{1

2}, Haiwei Zuo³, Li Zhang⁴, Qiuwen Sun⁵, Yong Xin^{2

6}, Longzhen Zhang^{2

6}

Affiliations

¹ First Clinical College, Xuzhou Medical University, Xuzhou, China.
² Department of Radiation Oncology, Affiliated Hospital of Xuzhou Medical University, Xuzhou, China.
³ School of Medical Information & Engineering, Xuzhou Medical University, Xuzhou, China.
⁴ School of Information and Control Engineering, China University of Mining and Technology, Xuzhou, China.
⁵ School of Medical Imaging, Xuzhou Medical University, Xuzhou, China.
⁶ Cancer Institute, Xuzhou Medical University, Xuzhou, China.

Abstract

Hyaluronic acid-mediated motility receptor (HMMR), a tumor-related gene, plays a vital role in the occurrence and progression of various cancers. This research is aimed to reveal the effect of HMMR in lung adenocarcinoma (LUAD). We first obtained the gene expression profiles and clinical data of patients with LUAD from The Cancer Genome Atlas (TCGA) database. Then, based on the TCGA cohort, the HMMR expression difference between LUAD tissues and nontumor tissues was detected and verified with public tissue microarrays (TMAs), clinical LUAD specimen cohort, and Gene Expression Omnibus (GEO) cohort. Logistic regression analysis and chi-square test were adopted to study the correlation between HMMR expression and clinicopathological parameters. The effect of HMMR expression on survival was evaluated by Kaplan-Meier survival analysis and using the Cox regression model. Furthermore, Gene Set Enrichment Analysis (GSEA) was utilized to screen out signaling pathways related to LUAD and the co-expression analysis was employed to build the protein-protein interaction (PPI) network. The HMMR expression level in LUAD tissues was dramatically higher than that in nontumor tissues. Logistic regression analysis and chi-square test demonstrated that the high HMMR expression in LUAD has relation with gender, pathological stage, T classification, lymph node metastasis, and distant metastasis. The Kaplan-Meier curve suggested a poor prognosis for LUAD patients with high HMMR expression. Multivariate analysis implied that the high HMMR expression was a vital independent predictor of poor overall survival (OS). GSEA indicated that a total of 15 signaling pathways were enriched in samples with the high HMMR expression phenotype. The PPI network gave 10 genes co-expressed with HMMR. HMMR may be an oncogene in LUAD and is expected to become a potential prognostic indicator and therapeutic target for LUAD.

Keywords: GSEA; HMMR; PPI; TCGA; analysis; bioinformatics; lung adenocarcinoma; prognosis.