ITGB1-DT/ARNTL2 axis may be a novel biomarker in lung adenocarcinoma: a bioinformatics analysis and experimental validation

Abstract

Background: Lung cancer is one of the most lethal malignant tumors that endangers human health. Lung adenocarcinoma (LUAD) has increased dramatically in recent decades, accounting for nearly 40% of all lung cancer cases. Increasing evidence points to the importance of the competitive endogenous RNA (ceRNA) intrinsic mechanism in various human cancers. However, behavioral characteristics of the ceRNA network in lung adenocarcinoma need further study.

Methods: Groups based on SLC2A1 expression were used in this study to identify associated ceRNA networks and potential prognostic markers in lung adenocarcinoma. The Cancer Genome Atlas (TCGA) database was used to obtain the patients' lncRNA, miRNA, and mRNA expression profiles, as well as clinical data. Informatics techniques were used to investigate the effect of hub genes on prognosis. The Cox regression analyses were performed to evaluate the prognostic effect of hub genes. The methylation, GSEA, and immune infiltration analyses were utilized to explore the potential mechanisms of the hub gene. The CCK-8, transwell, and colony formation assays were performed to detect the proliferation and invasion of lung cancer cells.

Results: We eventually identified the ITGB1-DT/ARNTL2 axis as an independent fact may promote lung adenocarcinoma progression. Furthermore, methylation analysis revealed that hypo-methylation may cause the dysregulated ITGB1-DT/ARNTL2 axis, and immune infiltration analysis revealed that the ITGB1-DT/ARNTL2 axis may affect the immune microenvironment and the progression of lung adenocarcinoma. The CCK-8, transwell, and colonu formation assays suggested that ITGB1-DT/ARNTL2 promotes the progression of lung adenocarcinoma. And hsa-miR-30b-3p reversed the ITGB1/ARNTL2-mediated oncogenic processes.

Conclusion: Our study identified the ITGB1-DT/ARNTL2 axis as a novel prognostic biomarker affects the prognosis of lung adenocarcinoma.

Keywords: ITGB1-DT/ARNTL2 axis; Invasion; LUAD; Prognosis; Proliferation; Public database; ceRNA.

Fig. 1

The flowchart of whole study

Fig. 2

Role of SLC2A1 in LUAD. A The expression of SLC2A1 in unpaired pan-cancer tissues (* < 0.05, ** < 0.01, *** < 0.001). B The expression of SLC2A1 in paired pan-cancer tissues (* < 0.05, ** < 0.01, *** < 0.001). C The immunohistochemistry of SLC2A1 in LUAD. D The overall survival and disease-free survival of SLC2A1 in LUAD patients (OS: p < 0.001, HR: 1.80 (1.35–2.39); DFS: p < 0.001, HR: 1.62 (1.25–2.11))

Fig. 3

Analysis of DElncRNAs. A The volcano map of DElncRNAs based on the SLC2A1expression (|logFC|> 1, p.adj < 0.05). B The co-expression heatmap of top 15 upregulated lncRNAs and SLC2A1 (* < 0.05, ** < 0.01, *** < 0.001). C Suvival curve of lncRNAs (log-rank p < 0.05)

Fig. 4

Analysis of DEmiRNAs. A The volcano map of DEmiRNAs between tumor and normal tissues (|logFC|> 0.5, p.adj < 0.05). B The heatmap of DEmiRNAs. C 23 overlapping miRNAs between lncRNA targets and downregulated DEmiRNAs. D The heatmap of 23 overlapping miRNAs. E, F The significant survival curves of miRNA (log-rank p < 0.05)

Fig. 5

Analysis of DEmRNAs. A The volcano map of DEmRNAs based on the SLC2A1 expression (|logFC|> 1, p.adj < 0.05). B The co-expression heatmap of top 15 upregulated mRNAs and SLC2A1 (* < 0.05, ** < 0.01, *** < 0.001). C The overlapping targets between hsa-miR-1976 and hsa-miR-30b-3p. D The final overlapping mRNAs between DEmiRNAs targets and top15 DEmRNAs. E, F The significant survival curves of final hub mRNAs (log-rank p < 0.05)

Fig. 6

Correlation between DElncRNAs, DEmiRNAs, and DEmRNAs. A, B The cellular localization of ITGB1-DT and SLC2A1-AS. C The correlation heatmap of hub genes. D–M Correlation analysis between the DElncRNAs, DEmiRNAs, and DEmRNAs

Fig. 7

Methylation analysis of ARNTL2. A The correlation between ANRTL2 gene expression and methylation level. B The expression level of different CpG island. C, D The promoter methylation level of ARNTL2 in LUAD patients at different stages were visualized by using UALCAN database

Fig. 8

Correlation between ARNTL2 expression and immune infiltration in LUAD. A Correlation between ARNTL2 gene copy number and infiltration level. B Correlation between ARNTL2 expression and different immune cells infiltration level. C The overall survival of different immune cells infiltration level in LUAD

Fig. 9

Knockdown of ITGB1-DT regulates the expression of hsa-miR-30b-3p and ARNTL2. A The interference of ITGB1-DT expression in H1299 cells. B and C The expression of miR-30b-3p and ARNTL2 in H1299-si-ITGB1-DT_1 cell. D The miR-30b-3p expression in H1299-miR-30b-3p mimic cells. E and F The ITGB1-DT and ARNTL2 expression in H1299-miR-30b-3p mimic cells

Fig. 10

Knockdown of ITGB1-DT inhibits the LUAD progression. A–D Cell viability was determined in H1299-si-ITGB1-DT and hsa-miR-30b-3p mimic cell using CCK-8 and colony formation assays (* p < 0.05, ** p < 0.01). E and F) Invasive ability was detected in H1299-si-ITGB1-DT and hsa-miR-30b-3p mimic cell using transwell assays (* p < 0.05, ** p < 0.01)