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. 2023 Nov 16;39:101819. doi: 10.1016/j.tranon.2023.101819

GPR37-centered ceRNA network contributes to metastatic potential in lung adenocarcinoma: Evidence from high-throughput sequencing

Chuanhui Chen 1,1, Mengzhi Wan 1,1, Xiong Peng 1, Qing Zhang 1, Yu Liu 1,⁎
PMCID: PMC10656721  PMID: 37979558

Highlights

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    GPR37 dominates in mitosis-related pathways and may be a key gene in LUAD.

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    2. GPR37 can serve as an independent factor to predict the prognosis of LUAD patients.

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    3. DLEU1 may competitively bind to miR-4458 and up-regulate GPR37 expression.

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    4. DLEU1 is associated with poor prognosis and tumor growth and metastasis in LUAD.

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    5. This study provides novel insights into the mechanism of LUAD metastasis.

Keywords: Lung adenocarcinoma, High-throughput sequencing, GPR37, DLEU1, miR-4458, ceRNA regulatory network

Abstract

The competing endogenous RNA (ceRNA)-based profiling has been extensively studied in carcinogenesis of lung adenocarcinoma (LUAD), while it has seldomly been applied to investigate the metastatic potential of LUAD. This study aims to examine the function and in-depth mechanism of GPR37-centered ceRNA network in LUAD. Cancer tissues and adjacent normal tissues from three LUAD patients were collected for high-throughput sequencing to screen for differentially expressed genes. A PPI network was constructed to screen the key gene GPR37, followed by analysis for the functions and pathways. Clinical data from LUAD patients were integrated with gene expression data in TCGA-LUAD dataset for survival analysis. Based on the miRNAs targeting_GPR37 and lncRNAs targeting_miRNAs, a lncRNA-miRNA-mRNA ceRNA network was established. GPR37 was up-regulated in LUAD tissue samples, and it may be a key gene involved in LUAD progression. GPR37 in LUAD was mainly enriched in the mitosis-related pathways. High GPR37 expression corresponded to poor prognosis in LUAD patients. Meanwhile, GPR37 could be used as an independent factor to predict the prognosis in LUAD patients. LncRNA DLEU1, up-regulated in LUAD tissue samples, may competitively bind to miR-4458 to up-regulate the expression of the miR-4458 downstream target GPR37. DLEU1 was associated with poor prognosis and tumor metastasis in LUAD patients. Altogether, our findings reveal a novel ceRNA network of DLEU1/miR-4458/GPR37 in LUAD growth and metastasis.

Introduction

Lung adenocarcinoma (LUAD) is the most common histological type of lung cancer and a malignant and deadly disease [1,2]. It has a high level of morphologic heterogeneity and is composed of tumor cells of multiple histological subtypes [3]. Most patients suffering from LUAD have developed metastatic disease at their diagnosis [4]. In recent years, advances in molecular biology and genomics have enabled the identification of specific genes and signaling pathways involved in developing LUAD [5]. Understanding these molecular mechanisms is critical to the design of effective treatments for patients with LUAD [6].

The competitive endogenous RNA (ceRNA) hypothesis has recently emerged as a crucial regulatory mechanism by which non-coding RNAs (ncRNAs) interact with messenger RNA (mRNA) and exert regulatory functions in cancer biology [7]. ceRNAs are a novel type of regulatory RNA playing an essential role in the pathogenesis of diseases, and a lncRNA-miRNA-mRNA ceRNA network may serve as an independent predictor of LUAD metastasis [8,9]. High-throughput sequencing is a powerful and versatile tool that has dramatically enhanced our understanding of the complex molecular aberrations that drive tumorigenesis [10,11]. G protein-coupled receptor 37 (GPR37) has been identified as a prognostic biomarker with a critical role in LUAD progression. A recent study has indicated that up-regulation of GPR37 promotes the proliferation, migration, and invasion of LUAD cells, while knockdown of GPR37 can repress malignant behaviors [12]. In addition, GPR37 may serve as a potential prognostic marker and therapeutic target for patients with dual TP53/EGFR mutation LUAD [13]. In the present study, the TargetScan database predicted that microRNA (miR)-4458 is a potential upstream miRNA of GPR37. A recent study has indicated that miR-4458 is markedly down-regulated in non-small-cell lung cancer cells, while overexpression of miR-4458 strongly reduces the proliferation and migration in non-small-cell lung cancer cell lines by directly targeting HMGA1 [14]. In addition, miR-4458 functions as a tumor suppressor to inhibit human lung cancer cell growth and colony formation by targeting Lin28B [15].

Despite increasing studies revealing that miR-4458 is associated with human cancer progression, the molecular mechanism of miR-4458 in LUAD remains largely unknown. In the current study, deleted lymphocytic leukemia 1 (DLEU1) could bind to miR-4458, as predicted by the miRcode database. DLEU1 is a novel cancer-related lncRNA and abnormally overexpressed in various malignancies, which participates in proliferation, migration, invasion and inhibition of apoptosis of cancer cells, representing a promising target for biotherapy in numerous tumors [16]. DLEU1 is highly expressed in non-small-cell lung cancer tissues and induces the proliferation, migration, and invasion of cancer cells while inhibiting their apoptosis [17]. Identifying the GPR37-centered ceRNA network in LUAD provides new opportunities for developing targeted therapies and predictive tools.

Methods

Ethics statement

The Clinical Ethics Committee of The First Affiliated Hospital of Nanchang University approved the current study conducted by the Declaration of Helsinki. All participants signed informed consent before sample collection.

RNA extraction and sequencing

LUAD tissues and adjacent normal tissues from three LUAD patients who underwent surgery at The First Affiliated Hospital of Nanchang University were collected for RNA high-throughput next-generation sequencing. Total RNA was isolated using a TRIzol reagent (15596026, Invitrogen, Carlsbad, CA). RNA sample concentration and purity were determined using a NanoDrop 2000 spectrophotometer (1011 U, NanoDrop Technologies Inc., Wilmington, DE). Total RNA samples exhibiting an RNA Integrity Index of ≥ 7.0 and 28S: 18S ratio ≥ 1.5 were used for subsequent experiments.

Sequencing libraries were generated and sequenced by CapitalBio Technology (Beijing, China). A total of 5 μg RNA was used for each sample. Briefly, ribosomal RNA (rRNA) was removed from the total RNA using Ribo-Zero ™ Magnetic Kit (epicentre Technologies, Madison, WI). The sequencing libraries were constructed by NEB Next Ultra Directional RNA Library Prep Kit for Illumina. The RNA was then prepared into fragments of approximately 300 base pairs (bp) in length in 5 × NEB Next first-strand synthesis reaction buffer. The first-strand cDNA was synthesized using reverse transcriptase and random primers, and the second-strand cDNA was synthesized in the second-strand synthesis reaction buffer of 10 × dUTP Mix. The end repair of cDNA fragments included the addition of a ployA tail and the connection of sequencing adaptors. After connecting the Illumina sequencing adaptors, the second strand of the cDNA was digested using USER Enzyme (#M5508, NEB) to construct a strand-specific library. Library DNA was amplified, purified and enriched by PCR. Then, the library was identified using Agilent 2100 and quantified using a KAPA library quantification kit (KK4844, KAPA Biosystems, Woburn, MA). Finally, paired-end sequencing was performed on a NextSeqCN500 (Illumina) sequencer.

Quality control and reference genome alignment of sequencing data

The quality of paired-end reads of the raw sequencing data was checked using FastQC software (Version 0.11.8). Cutadapt software 1.18 was applied for the preprocessing of raw data. The Illumina sequencing adaptors and poly (A) tail sequences were removed. The reads with an N content of over 5 % were removed using a perl script. The reads with a 70 % base mass above 20 were extracted using FASTX Toolkit software (Version 0.0.13). Next, two-end sequences were repaired using BBMap software. Finally, the filtered high-quality reads fragment was aligned with the reference genome using HISAT2 software (Version 0.7.12).

TCGA data retrieval

RNA sequencing and miRNA sequencing data of LUAD in TCGA were downloaded from the UCSC Xena database. Meanwhile, the phenotypic and prognostic data of LUAD tissue samples were downloaded. The RNA sequencing data includes 526 cancer tissues and 59 adjacent normal tissues, and the miRNA sequencing data includes 518 cancer tissues and 46 adjacent normal tissues. The samples were grouped using the Perl language, and the annotation file of the GENCODE Gene Set-09.2019 version converted their ensemble IDs. LncRNA and mRNA ensemble IDs not included in the GENCODE database were excluded.

Identification of differentially expressed genes (DEGs)

Differential analysis of the sequencing data and TCGA-LUAD dataset was conducted to screen the DEGs using the R ``limma'' package with FDR < 0.05 as the threshold. The R "pheatmap" and ``ggplot2′' software packages were used to plot heat maps and volcano maps, respectively. Data between the two groups were compared using the Wilcoxon rank sum test. All analyses in this study were performed under R version 4.2.1.

Identification of the critical gene related to LUAD

Based on the differential analysis of transcriptome sequencing data, the proteins encoded by the top 50 genes most significantly up-regulated in LUAD samples were imported into the STRING database for protein-protein interaction (PPI) analysis. PPI network and node files were exported. Node statistics were then plotted using R software based on the PPI node data, and the genes with the most significant number of connected nodes were selected as the core gene of the network for subsequent analysis.

Functional enrichment analysis

LUAD samples in the TCGA-LUAD dataset were divided into a high GPR37 expression group and a low GPR37 expression group according to the median value of GPR37 expression. The difference in enriched pathways between the two groups was revealed using GSEA. The "c5.go.v2022.1.Hs.symbols.gmt" gene set from MSigDB was used as a reference.

Survival analysis

The survival time and status of LUAD patients from the TCGA-LUAD dataset were integrated with gene expression data, and the R software "survival" package was applied for survival analysis, with p < 0.05 considered to be indicative of statistical significance.

Correlation analysis of gene expression and clinicopathological features of LUAD patients

Data on the gene expression and clinicopathological features of LUAD patients in the TCGA-LUAD dataset were integrated, and their correlation was analyzed using the R "ComplexHeatmap" software package. Meanwhile, a heat map was plotted [18].

Independent prognostic analysis

Data on the gene expression and clinicopathological features of LUAD patients in the TCGA-LUAD dataset were integrated and then analyzed by univariate and multivariate Cox regression analyses using the “survival” package. Genes with a p-value < 0.05 were considered to be significantly associated with prognosis [19].

Construction of a ceRNA regulatory network

The upstream miRNAs of GPR37 were retrieved from the TargetScan database and intersected with the down-regulated miRNAs to identify the candidate miRNAs, with miRNA_GPR37 obtained. In addition, using the miRCode database, miRNAs bound by the up-regulated lncRNAs were predicted and intersected with the candidate miRNAs to obtain lncRNA-miRNA pairs. Cytoscape software (Version 3.6.0) was employed to build and visualize the regulatory network [20].

Cell culture

Human bronchial epithelial cells BEAS-2B (CC-Y1066) were purchased from Shanghai Biological Technology Co., Ltd. Enzyme Research (Shanghai, China), and lung cancer cell lines Calu-3 (CL-0054), NCI-H1395 (CL-0275), NCI-H1975 (CL-0298), and A549 (CL-0016) were purchased from Procell Life Science&Technology Co., Ltd. (Wuhan, China). The cells were cultured in RPMI-1640 medium (R8758, Gibco, Carlsbad, CA) supplemented with 10 % FBS, 100 μg/mL streptomycin, and 100 U/mL penicillin. All cell lines were cultured in a 5 % CO2 incubator at 37 °C with 95 % humidity. The cell culture medium was renewed 3–4 times per week based on cell growth. Cell passaging was performed when the cell confluence reached approximately 80 % [21,22].

Cell treatment

Lentiviral vectors harboring overexpression (oe)-DLEU1, short hairpin RNA (sh)-DLEU1, oe-GPR37, sh-GPR37, miR-4458, anti-miR-4458, and corresponding controls were obtained from Genecopoeia (Rockville, MD). Lipofectamine 3000 reagents (L3000015, Invitrogen) transduced the lentiviral vectors into 293T cells (CRL-3216, ATCC, Manassas, VA). After 20 h, the culture medium was replaced with 12 mL of medium supplemented with 5 % FBS. Approximately 48 h later, the virus's supernatant was collected, filtered through a 0.45 μm cellulose acetate filter (HAWG04700, Millipore Corp., Billerica, MA), and stored at −80 °C. Calu-3 or A549 cells were transduced with lentiviral vectors (MOI = 20). The cells were selected with 1 μg/mL puromycin (A1113803, Gibco) for 3 days to obtain stably transduced cells for further experimentation [23,24]. The shRNA sequences are shown in Table S1. The one with the best interference efficiency was selected for subsequent experimentation.

Dual-luciferase reporter gene assay

The targeting relationship between DLEU1/GPR37 and miR-4458 was predicted using the bioinformatics website and validated by dual-luciferase reporter gene assay. The DLEU1/GPR37 dual-luciferase reporter gene vector (pGLO-DLEU1/GPR37 3′-UTR WT) and its mutant at the DLEU1/GPR37 binding site (pGLO-DLEU1/GPR37 3′-UTR MUT) were constructed, respectively; pGLO was purchased from Bio-Rad (Hercules, CA). The correctly sequenced reporter plasmids were co-transduced into 293T cells with miR-4458 mimic and mimic-NC, respectively. After 24 h of transduction, the cells were lysed, followed by centrifugation at 12,000 g for 1 min and supernatant collection. The luciferase activity was determined using the Dual-Luciferase Reporter Assay System (E1910, Promega, Madison, WI) as normalized to Renilla luciferase activity.

CCK-8 assay

Cell proliferation was detected using CCK-8 kits (40203ES60, Yeasen, Shanghai, China). Cells in the logarithmic growth phase were collected, with the cell concentration adjusted to 5 × 104 cells/mL using a complete culture medium. Cells were spread into a 96-well culture plate, and 100 μL cell culture medium was added to each well, followed by culture in an incubator for 0, 24, 48, and 72 h. Next, 10 μL CCK-8 solution was added to each well for culture at 37 °C for 2 h, and then the absorbance value (A) was measured using a Multiskan FC Microplate Reader (51119080, Thermo Fisher Scientific, Rockford, IL) at a detection wavelength of 450 nm [25,26]. Three parallel wells were set in each group, and the average value was taken.

Transwell assay

Matrigel (YB356234, Shanghai Yubo Biological Technology, Shanghai, China) was stored at −80 °C and thawed overnight at 4 °C to become liquid. At 4 °C, 200 μL of Matrigel was added to 200 μL of serum-free culture medium to dilute the Matrigel, and 50 μL was added to the apical chamber of the Transwell plate (3422, Corning Glass Works, Corning, NY). The plate was placed in a CO2 incubator for 2–3 h until the gel solidified. Cells were detached, counted, and suspended in a serum-free culture medium to prepare a cell suspension. Next, 200 μL of the cell suspension was added to the apical chamber, and 800 μL of culture medium containing 20 % FBS was added to the basolateral chamber. The plate was taken out after being incubated at 37 °C for 20–24 h, followed by a 10-min rinse in formaldehyde and cell staining with 0.1 % crystal violet (G1062, Solarbio, Beijing, China) for 30 min at room temperature. The cells on the upper surface were wiped off with a cotton ball, and the invaded cells penetrating the Matrigel were observed, photographed, and counted under an inverted microscope (IX73, OLYMPUS, Tokyo, Japan). Cells in at least four randomly selected microscopic areas were counted [27].

RT-qPCR

Total RNA was extracted using Trizol reagent (15596026, Invitrogen). For miRNA analysis, cDNA was synthesized using the TaqMan microRNA assay kit (4366596, Invitrogen). RNA was reversely transcribed into cDNA using the PrimeScript RT reagent Kit (RR047A, Takara, Shiga, Japan) for lncRNA and mRNA detection. The synthesized cDNA was subjected to RT-qPCR using the Fast SYBR Green PCR Master Mix (11736059, Invitrogen), and three replicates were set for each well. U6 or GAPDH was used as an internal reference. The relative expression was calculated using the 2−ΔΔCt method [28], [29], [30]. The primers used in this study were synthesized by Takara (Table S2) and designed on NCBI.

RNA immunoprecipitation (RIP) assay

The Magna RNA-binding protein immunoprecipitation kit (17–700, Millipore) was used to detect according to the instructions. Briefly, cells were lysed with RIPA lysis buffer, and the supernatant was collected after centrifugation at 12,000 g for 10 min at 4 °C. One part of the cell extract was taken as input, and the other was incubated with antibodies for co-precipitation. Specifically, 50 μL of magnetic beads were resuspended in 100 μL of RIP Wash Buffer for each co-precipitation reaction and incubated with 5 μg of antibodies for binding purposes. The magnetic bead-antibody complex was mixed with 900 μL of RIP Wash Buffer and incubated with 100 μL of cell extract overnight at 4 °C. The samples and input were detached by proteinase K, and the RNA was extracted, followed by RT-qPCR detection. The antibodies used for RIP assay (30-min incubation at room temperature for 30 min) were AGO2 (1:50, ab186733, Abcam, Cambridge, UK) and IgG as the negative control (NC) (1:100, ab205718, Abcam) [31].

RNA pull-down assay

LUAD cells were separately transduced with biotin-labeled miR-4458 (bio-miR-4458) and its NC (bio-cel-miR67) (50 nM for each) for 48 h. Subsequently, a specific cell lysis buffer was used for incubation for 10 min, and 50 mL of the cell lysate was subpackaged. The remaining lysate was incubated with streptavidin magnetic beads (LSKMAGT, Sigma-Aldrich, St. Louis, MO) pre-coated with RNase-free and yeast tRNA (11119915001/R8759, Sigma-Aldrich) at 4 °C for 3 h, followed by rinses with cold lysis buffer, low-salt buffer, and high-salt buffer. RNA was extracted and subjected to RT-qPCR for detecting the levels of DLEU1 or GPR37 in the bio-miR-4458 or bio-cel-miR-67 pull-down samples [32,33].

Western blot

Tissue or cell total protein was extracted using an efficient RIPA lysis buffer (R0010, Solarbio). After 15 min of lysis at 4 °C, centrifugation was performed at 12,000 g for 15 min, and the supernatant was collected. The protein concentration of each sample was determined using a BCA assay kit (20201ES76, Yeasen). The wet transfer method separated proteins by SDS-PAGE and transferred them to a PVDF membrane (ISEQ07850; Millipore). The membrane was blocked with 5 % BSA at room temperature for 1 h and incubated at 4 °C overnight with diluted rabbit primary antibodies against GPR37 (MAB44501, 1:1000, Bio-Techne China, Shanghai) and GAPDH (ab8245, 1:2500, Abcam). The next day, the membrane was further incubated with HRP-labeled goat anti-mouse IgG (ab205719, 1:20,000), followed by development. ImageJ 1.48 u software (National Institutes of Health, Bethesda, MA) was used for protein quantitative analysis, using the ratio of the grayscale value of each protein to that of the internal reference GAPDH.

In vivo animal experiments

Male BALB/c nude mice (6 weeks, 18–23 g) in SPF grade were purchased from Hunan SJA Laboratory Animal Co., Ltd. (Changsha, China) and randomly assigned into 4 groups (n = 10). Subcutaneous injection of 0.2 mL single cell suspension (containing 1 × 106 cells) of stably transduced A549 cells (cell concentration = 5 × 106 cells/mL) was performed to establish a subcutaneous tumor model in nude mice. Specifically, the mice were injected with a single-cell suspension of untreated A549 cells or A549 cells transduced with sh-DLEU1, sh-DLEU1 + anti-miR-4458, or sh-DLEU1 + oe-GPR37. Real-time measurement and recording of tumor volume changes in nude mice were performed. The tumor volume was calculated based on V = A × B2 / 2 (mm3), where A is the maximum diameter and B is the vertical diameter. On the 28th day, the nude mice were euthanized, and the subcutaneously transplanted tumor was removed. RNA and protein were extracted from the transplanted tumor tissue for RT-qPCR and Western blot analysis. The study was conducted under the approval of the Ethics Committee of The First Affiliated Hospital of Nanchang University. The Guide for the Care and Use of Laboratory Animals conducted all procedures in the animal experiment.

In vivo tumor metastasis experiment: stably transduced 2 × 106 LUAD cells were injected into the tail vein of nude mice, and 200 μL d-fluorescein (150 mg; L9504, Sigma-Aldrich) was injected into the abdominal cavity. The metastasis was monitored and quantified twenty days later using the in vivo imaging system Spectrum (Caliper Life Sciences, Hopkinton, MA). After luciferase signal intensity detection, all mice were euthanized by CO2 [34], [35], [36].

Statistical analysis

All data were processed using SPSS 21.0 statistical software (IBM, Armonk, NY). The measurement data from three independent experiments were expressed by mean ± standard deviation. The comparisons of data obeying normal distribution and homogeneous variance between the two groups were performed by unpaired t-test, and those among multiple groups were performed by one-way ANOVA or repeated measures of ANOVA. Tukey post hoc tests were performed for pairwise comparisons. Data not conforming to a normal distribution or homogeneity of variance were compared using rank sum tests. p < 0.05 indicated a statistically significant difference.

Results

GPR37 may be an essential gene involved in the progression of LUAD

LUAD is a high cancer and a primary subtype of non-small cell lung cancer [8]. Identifying the critical genes associated with LUAD can help us better understand the pathogenesis of LUAD and seek new treatments. First, we performed RNA high-throughput sequencing of LUAD tissues and adjacent normal tissues from three LUAD patients, and the obtained genes were subjected to differential analysis, with 1442 DEGs obtained (Fig. 1A). A heat map illustrating the top 50 genes that were most significantly up-regulated in LUAD samples is shown in Fig. 1B. The proteins encoded by the top 50 genes were imported into the STRING database to construct a PPI network (Fig. 1C). In this network, the significantly up-regulated GPR37 was the critical gene (Fig. 1D, E).

Fig. 1.

Fig 1

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Identification of the critical genes involved in the development of LUAD. A, Following transcriptome sequencing, A volcano plot of the DEGs in LUAD tissues and adjacent normal tissues from 3 LUAD patients. Each dot represents a gene; red indicates significantly highly expressed genes, green indicates poorly expressed genes, and black indicates non-DEGs. B, A heat map of the top 50 most significantly up-regulated genes in LUAD tissues from 3 LUAD patients. The top right histogram is a color scale, where red indicates highly expressed genes, and green indicates poorly expressed genes. C, PPI network of the proteins encoded by the top 50 most significantly up-regulated genes constructed by the STRING database. The red box marks the essential gene GPR37. D, Expression of GPR37 in LUAD tissues and adjacent normal tissues from 3 LUAD patients. E, Statistical plot of the connected protein nodes in the PPI network.

GPR37 in LUAD is mainly enriched in mitosis-related pathways

To analyze the role of GPR37 in LUAD, we obtained the TCGA-LUAD dataset and found (Fig. 2A) that GPR37 was highly expressed in cancer tissues of LUAD patients, which was consistent with our sequencing results. Next, the LUAD samples were divided into a high GPR37 expression group and a low GPR37 expression group according to the median value of GPR37 expression. Analysis using the GSEA database (Fig. 2B) showed that DNA_REPLICATION, MICROTUBULE_CYTOSKELETON_ORGANIZATIO N INVOI VER IN MITOSIS, POSITIVE_REGULATION_OF_MITOTIC_CELL_CYCLE, and SPINDLE-related gene sets were enriched in the GPR37 high expression group, and these gene sets were mainly involved in mitosis-related pathways. According to a previous study, blocking mitosis can inhibit tumor growth [37]. Therapies targeting key pathways that drive and execute cell division are currently a main research target of anti-cancer; multiple synergistic effects exist between anti-mitotic agents and anti-cancer drugs, and their combined therapy holds great promise [38]. The above results suggest that GPR37 may accelerate cell cycle progression and thus promote LUAD growth by promoting mitosis of tumor cells.

Fig. 2.

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Expression of GPR37 in TCGA-LUAD dataset and GSEA. A, GPR37 expression in LUAD tissues (n = 526) and adjacent normal tissues (n = 59) from TCGA-LUAD dataset, the y-axis represents the overall survival rate. B, GSEA showing the difference of enriched pathways between the high and low GPR37 expression groups.

GPR37 can be used as an independent prognostic factor to predict the prognosis of LUAD patients

Then, we integrated the clinical data of LUAD patients in the TCGA-LUAD dataset with GPR37 expression data to investigate the correlation between GPR37 expression and the prognosis and clinicopathological characteristics of LUAD patients. The results of the overall survival analysis (Fig. 3A) showed that LUAD patients in the GPR37 high-expression group had a lower survival rate and a worse prognosis than the GPR37 low-expression group. In addition, clinical correlation analysis results (Fig. 3B) displayed evident lymph node metastasis in LUAD patients in the GPR37 high expression group versus the GPR37 low expression group. These results suggest that high GPR37 expression is significantly associated with poor prognosis and lymph node metastasis in LUAD patients.

Fig. 3.

Fig 3

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Correlation of GPR37 expression with clinicopathological characteristics and prognosis of LUAD patients. A, A survival curve of LUAD patients with the high or low expression of GPR37. The abscissa indicates survival time, and the ordinate indicates survival rate; red lines indicate the high GPR37 expression group and blue lines indicate the low GPR37 expression group. B, A heat map showing the correlation of GPR37 expression (n = 257 for the high GPR37 expression group and n = 256 for the low GPR37 expression group) with clinical characteristics of LUAD patients. * p < 0.05. C, A forest plot of the univariate Cox regression analysis of the integrated data of clinicopathological features of LUAD patients and GPR37 expression in the TCGA-LUAD dataset. D, A forest plot of the multivariate Cox regression analysis of the integrated data of clinicopathological features of LUAD patients and GPR37 expression in the TCGA-LUAD dataset. The left indicates the clinicopathological features of LUAD patients and GPR37, and the middle is the p-value; the hazard ratio indicates the risk rate, with a hazard ratio greater than 1 indicating high risk of the gene and a hazard ratio lower than 1 indicating low risk of the gene. The right shows the hazard ratio distribution, with distribution on the left indicating low risk while on the right indicating high risk.

Next, we aimed to investigate whether GPR37 can predict the prognosis of LUAD patients in a manner independent of other clinicopathological features. Univariate Cox regression analysis of the integrated data of clinicopathological features of LUAD patients and GPR37 expression in the TCGA-LUAD dataset (Fig. 4A) indicated that tumor stage (stage, N, T) of LUAD patients and GPR37 expression were significantly associated with prognosis, respectively, and both were high-risk factors; namely, the higher tumor stage and GPR37 expression reflect the poorer prognosis of LUAD patients. Besides, univariate Cox regression analysis (Fig. 4B) showed that only GPR37 expression was associated with the prognosis of LUAD patients, suggesting that GPR37 can predict the prognosis of LUAD patients independent of other clinicopathological features. Taken together, GPR37 can be used as an independent factor to predict the prognosis of LUAD patients.

Fig. 4.

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Bioinformatics analysis predicts and constructs a GPR37-centered ceRNA regulatory network. A, A volcano plot of differentially expressed miRNAs in 46 adjacent normal tissues and 518 LUAD tissues in the TCGA-LUAD dataset. Each dot represents a gene; red indicates significantly highly expressed genes, green indicates poorly expressed genes, and black indicates non-DEGs. B, Venn diagram showing the intersection between the upstream miRNAs of GPR37 retrieved from the TargetScan database and 326 down-regulated miRNAs. C, Expression of 21 miRNAs in 46 adjacent normal tissues and 518 LUAD tissues in TCGA-LUAD dataset. D, Visualization of the regulatory network of miRNAs_GPR37 by Cytoscape, where green represents GPR37 and pink represents the upstream miRNAs of GPR37 retrieved from the TargetScan database. E, A volcano plot of differentially expressed lncRNAs in 59 adjacent normal tissues and 526 LUAD tissues in the TCGA-LUAD dataset. Each dot represents a gene; red indicates significantly highly expressed genes, green indicates significantly poorly expressed genes and black indicates non-DEGs. F, Visualization of the regulatory network of lncRNAs_miR-4458 by Cytoscape, where orange represents miR-4458 and blue represents lncRNAs. G, Expression of 17 lncRNAs in 59 adjacent normal tissues and 526 LUAD tissues in TCGA-LUAD dataset.

LncRNAs may participate in the LUAD progression by competitively binding to miR-4458 and up-regulating the expression of GPR37

Subsequently, this study focused on revealing the ceRNA regulatory network with GPR37 as the core. miRNA sequencing data in the TCGA-LUAD dataset were first obtained, and subjected to differential analysis, which yielded 616 differentially expressed miRNAs, including 326 down-regulated miRNAs in the cancer tissues from LUAD patients (Fig. 4A). Then, the upstream miRNAs of GPR37 retrieved from the TargetScan database were intersected with the 326 down-regulated miRNAs, with 21 miRNAs obtained (Fig. 4B–D). These data indicated that 21 down-regulated miRNAs might be the upstream regulatory miRNAs of GPR37.

Meanwhile, differential analysis of lncRNAs in the TCGA-LUAD dataset (Fig. 4E) showed 2301 differentially expressed lncRNAs, of which 1306 lncRNAs were up-regulated in cancer tissues of LUAD patients. The top 500 most significantly up-regulated lncRNAs were extracted, and their binding with the above 21 miRNAs was predicted by the miRcode database. The results (Fig. 4F, G) revealed that only miR-4458 had binding sites with lncRNAs, and only 17 lncRNAs could bind to miR-4458. Growing studies have reported that miR-4458 may inhibit tumor progression by suppressing tumor cell proliferation, migration and invasion [39,40]. Overall, these results suggest that lncRNAs may be involved in the progression of LUAD by down-regulating miR-4458 and up-regulating the expression of GPR37.

DLEU1 is strongly associated with poor prognosis and lymph node metastasis in patients with LUAD

Finally, we sought to screen the lncRNAs associated with poor prognosis in LUAD patients from the 17 lncRNAs. We integrated the data of the expression of 17 lncRNAs with the clinical data of LUAD patients in the TCGA-LUAD dataset. The results of the overall survival analysis (Fig. 5A) showed that only DLEU1 was associated with poor prognosis in LUAD patients and that LUAD patients in the high DLEU1 expression group had a lower survival rate and worse prognosis compared to those in the low DLEU1 expression group. In addition, as shown in Fig. 5B, clinical correlation analysis demonstrated faster tumor growth and more lymph node metastases in the high DLEU1 expression group than in the low DLEU1 expression group. Thus, an intensive correlation was evident between amplified DLEU1 expression, dismal prognosis, and lymph node metastasis in LUAD patients.

Fig. 5.

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Correlation of DLEU1 with clinicopathological characteristics and prognosis of LUAD patients. A, A survival curve of LUAD patients with high or low expression of DLEU1, the y-axis represents the overall survival rate. The abscissa indicates survival time, and the ordinate indicates survival rate; red lines indicate the high DLEU1 expression group and blue lines indicate the low DLEU1 expression group. B, A heat map showing the correlation of DLEU1 expression (n = 257 for the high DLEU1 expression group and n = 256 for the low DLEU1 expression group) with clinical characteristics of LUAD patients. * p < 0.05, *** p < 0.001.

DLEU1 sponges miR-4458 to up-regulate GPR37 expression

We further investigate whether DLEU1 affects the expression of GPR37 through miR-4458. RT-qPCR results revealed that compared with that in the normal lung epithelial cells, the expression of DLEU1 and GPR37 significantly increased while miR-4458 expression decreased in different lung cancer cells (Fig. 6A). Among them, the highest expression of DLEU1 and GPR37 and the lowest expression of miR-4458 were found in Calu-3 or A549 cells, and these cells were thus used for subsequent analysis. We further found complementary binding sites between DLEU1 and miR-4458 and between miR-4458 and GPR37 (Fig. 6B). We mutated the binding sites between them. The dual luciferase assay results revealed that miR-4458 mimic notably inhibited the luciferase activity of DLEU1-WT and GPR37-WT but did not affect the activity of DLEU1-MUT and GPR37-MUT (Fig. 6C). The RIP assay showed a strong interaction between miR-4458 and DLEU1/GPR37 (Fig. 6D). Further, RNA pull-down results displayed that compared to Biotin-cel-miR-67, Biotin-miR-4458 could enrich more GPR37 and DLEU1 (Fig. 6E), indicating that miR-4458 had sequence specificity in recognizing DLEU1 and GPR37.

Fig. 6.

Fig 6

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Regulation of DLEU1 on GPR37 expression through miRNA-dependent mechanism. A, RT-qPCR to detect the relative expression of DLEU1, GPR3, and miR-4458 in different cell lines. B, The binding and mutation sites between miR-4458 and DLEU1/GPR37. C, The luciferase activity of DLEU1/GPR37-WT/MUT in HEK-293T cells determined using dual-luciferase reporter gene assay. D, AGO2 antibodies were used for RIP assays and specific primers were used to detect the enrichment of DLEU1 and GPR37. E, Detection of DLEU1 mRNA levels in Calu-3 and A549 cells by biotin-coupled miR-130a-3p pull-down assay. F, RT-qPCR to detect the expression of miR-4458 and GPR37 in Calu-3 or A549 cells. * p < 0.05. Each cell experiment was repeated three times.

Further in vitro cell experiments revealed that in Calu-3 cells, treatment with oe-DLEU1 led to a significant decrease in miR-4458 expression and an increase in GPR37 expression, the effects of which could be reversed by miR-4458. In addition, in A549 cells, treatment with sh-DLEU1 resulted in a marked increase in miR-4458 expression and a decline in GPR37 expression, and these effects could be reversed by anti-miR-4458 (Fig. 6F).

The above results indicate that DLEU1 up-regulates the expression of GPR37 by sponging miR-4458.

DLEU1 regulates the miR-4458/GPR37 axis to promote the malignant phenotypes of LUAD cells

We investigated whether DLEU1 regulates the miR-4458/GPR37 axis to affect LUAD cell proliferation and metastasis. We regulated the levels of DLEU1, miR-4458, and GPR37 in Calu-3 or A549 cells. The results showed that the protein expression of GPR37 in the sh-DLEU1-treated 549 cells was reduced, while that in the 549 cells treated with sh-DLEU1 + anti-miR-4458 or sh-DLEU1 + oe-GPR37 was significantly increased (Fig. 7A), The protein expression of GPR37 in the oe-DLEU1-treated Calu-3 cells was notably increased, while that in the Calu-3 cells treated with oe-DLEU1 + miR-4458 or oe-DLEU1 + sh-GPR37 displayed a marked decline (Fig. 7B). As shown in Fig. 7C–E, in the Calu-3 cells, DLEU1 overexpression contributed to a significant increase in cell proliferation, migration, and invasion, with a decrease in E-cadherin expression and an increase in Vimentin expression. However, forced expression of miR-4458 or GPR37 knockdown led to a notable decrease in cell proliferation, migration, and invasion of oe-DLEU1-treated Calu-3 cells, with an increase in E-cadherin expression and a decrease in Vimentin expression. In A549 cells, DLEU1 knockdown inhibited the proliferation, migration, and invasion of A549 cells, accompanied by increased E-cadherin expression and decreased Vimentin expression. Either interference with miR-4458 or overexpression of GPR37 reversed the inhibitory effect of DLEU1 on A549 cell proliferation, migration, and invasion (Fig. 7C–F). The above results indicate that DLEU1 promotes the malignant phenotypes of LUAD cells by regulating the miR-4458/GPR37 axis.

Fig. 7.

Fig 7

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Effects of DLEU1 on the malignant phenotypes of LUAD cells by regulating the miR-4458/GPR37 axis. Calu-3 cells were treated with oe-DLEU1, oe-DLEU1 + miR-4458, or oe-DLEU1 + sh-GPR37. A549 cells were treated with sh-DLEU1, sh-DLEU1 + anti-miR-4458, or sh-DLEU1 + oe-GPR37.A-B, Western blot to detect the protein expression of GPR37 in Calu-3 or A549 cells. C, RT-qPCR to detect the mRNA expression of Vimentin and E-cadherin. D, CCK-8 detection of Calu-3 or A549 cell proliferation. E-F, Transwell assay to evaluate Calu-3 or A549 cell migration invasion. * p < 0.05. Each cell experiment was repeated three times.

DLEU1 mediates the miR-4458/GPR37 axis to promote tumor growth and metastasis in vivo

Furthermore, we investigated the role of DLEU1 in tumor growth and metastasis in vivo. To construct a metastatic LUAD model in nude mice in vivo, luciferase stably expressed in A549 cells was injected intravenously into the tail vein of male nude mice, and its bioluminescence signal was evaluated 10 weeks after injection. After the knockdown of DLEU1, the bioluminescence signal weakened, indicating that DLEU1 was down-regulated to inhibit LUAD metastasis (Fig. 8A).

Fig. 8.

Fig 8

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Effects of DLEU1 on tumor growth and metastasis in vivo by regulating the miR-4458/GPR37 axis. Nude mice were treated with sh-DLEU1, sh-DLEU1 + anti-miR-4458, or sh-DLEU1 + oe-GPR37. A, Biofluorescence imaging technology to detect tumor metastasis. B, Schematic diagram of transplanted tumor in nude mice, and calculation of tumor volume at different time points (7, 14, 28, 35 days). C, RT-qPCR to detect the expression of DLEU1 in transplanted tumor tissue. D, RT-qPCR to detect the expression of miR-4458 and GPR37 in transplanted tumor tissue. E, Western blot detection of GPR37 protein expression in transplanted tumor tissue. F, RT-qPCR to detect the expression of Vimentin and E-cadherin in transplanted tumor tissue. n = 10. * p < 0.05.

To evaluate the effect of DLEU1 on tumor growth, we subcutaneously injected stably transduced A549 cells into nude mice to observe tumor growth. As shown in Fig. 8B, the knockdown of DLEU1 significantly inhibited tumor growth at different time points. In addition, the expression of miR-4458 was increased in the presence of DLEU1 knockdown, while the expression of DLEU1 and GPR37 was markedly reduced (Fig. 8C–E). The expression of E-cadherin in the DLEU1 was increased, while that of Vimentin was notably reduced (Fig. 8F). Knockdown of miR-4458 or overexpression of GPR37 reversed these effects.

The above results indicate that DLEU1 regulates the miR-4458/GPR37 axis to facilitate tumor growth and metastasis in vivo.

Discussion

LUAD is a highly malignant tumor. Despite significant progress in LUAD research in recent years, the prognosis for these patients remains poor [41,42]. The rapid proliferation and migration characteristics of LUAD limit the identification of effective treatment strategies and are major factors contributing to poor prognosis [43,44]. Therefore, understanding the mechanisms of proliferation and migration in LUAD is crucial for improving patient prognosis.

Transcriptome analysis, one of the most common bioinformatics methods, has been widely applied in various cancer research studies. For example, in prostate cancer, researchers have elucidated the molecular mechanisms of VNPP433-3β in tumor stem cells through transcriptome analysis [45]. Additionally, numerous studies in lung cancer have used transcriptome analysis to elucidate the molecular mechanisms of tumor cell progression or metastasis [46,47]. Initially, we conducted transcriptome analysis to identify key molecules involved in LUAD proliferation and migration. The results indicated that GPR37 is an essential gene involved in LUAD progression, significantly upregulated in LUAD patients, and associated with poor prognosis. Previous studies have also shown that GPR37 can interact with CDK6, a cell cycle protein that promotes LUAD progression by inducing cell cycle arrest in the G1 phase [48]. Moreover, a recent clinical study has identified the expression level of GPR37 as a potential prognostic biomarker for LUAD [43]. These conclusions from the cited references align with our current results, suggesting that increased expression of GPR37 is associated with poor prognosis in LUAD patients and that GPR37 can serve as an independent prognostic factor in predicting LUAD patient outcomes. However, further investigation with a larger clinical sample size is still needed to confirm these conclusions.

Further research revealed that GPR37 in LUAD mainly enriches the pathways related to cell mitosis, which is a universal biological process necessary for LUAD progression [44]. Targeting microtubules and microtubule protein polymerization and disrupting mitosis are specific mechanisms by which AMP-Na exerts its anti-tumor effect in LUAD cell lines [49]. In future studies, interfering with mitosis through targeting GPR37 may be a potential therapeutic target for treating LUAD patients. Additionally, the combination of anti-mitotic drugs and anticancer drugs has great potential, as they have multiple synergistic effects (38). Similar reports have yielded satisfactory results in clinical settings [50]. However, this study lacks direct evidence supporting GPR37′s regulation of cell mitosis, which requires further experimental validation in future work.

Database predictions and dual-luciferase assays suggest that miR-4458 is an upstream miRNA of GPR37 and it is downregulated in LUAD, which is consistent with previous reports in resistant non-small cell lung cancer tissues and cells [51]. Furthermore, the expression level of miR-4458 is decreased in other cancer tissues, where it inhibits tumor cell proliferation by blocking G0/G1 phase and suppressing CCND1 expression [52].

Competing endogenous RNAs (ceRNAs) play a significant role in tumor proliferation and metastasis [53]. Some lncRNAs, such as KCNQ1OT1, HEIH, and CDKN2B-AS1, have been demonstrated to act as ceRNAs for miR-4458, enhancing the expression of downstream target genes [54], [55], [56]. To the best of our knowledge, this study is the first to discover that lncRNA DLEU1 may competitively bind to miR-4458 and upregulate GPR37 expression, thus participating in LUAD progression and metastasis. Bioinformatics analysis suggests that DLEU1 may function through signaling pathways like lymphatic metastasis in LUAD. Studies in non-small cell lung cancer have shown that upregulated expression of DLEU1 leads to increased proliferation, migration, and invasion of cancer cells, accelerating tumor growth [17]. Furthermore, abnormal overexpression of DLEU1 has been associated with poor prognosis in patients with pancreatic ductal adenocarcinoma, gliomas, and cervical cancer [57], [58], [59]. These findings, which are consistent with the literature, not only enrich our understanding of the molecular mechanisms underlying LUAD but also suggest that DLEU1 could potentially serve as a therapeutic target in future work.

In summary, this study reveals a novel ceRNA network involving DLEU1/miR-4458/GPR37 in the growth and metastasis of LUAD (Fig. 9). DLEU1 may upregulate GPR37 expression by sequestering miR-4458, thereby accelerating the malignant phenotype of cancer cells and ultimately promoting the growth and metastasis of LUAD. The correlation of DLEU1 with poor prognosis and tumor metastasis suggests that targeting this ceRNA network may have a significant clinical impact on managing metastatic LUAD. These findings provide a foundation for future research on potential therapeutic strategies for LUAD and offer compelling evidence for the potential key role of ceRNA networks in cancer biology and progression.

Fig. 9.

Fig 9

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Schematic illustration of the GPR37-based ceRNA regulatory network mechanism involved in LUAD growth and metastasis. DLEU1 may up-regulate the key gene GPR37 expression through sequestering miR-4458, thereby promoting tumor cell malignant phenotypes, and ultimately promoting LUAD growth and metastasis.

Funding

This study was funded by Regional Programs of the National Natural Science Foundation of China (81960008) and Jiangxi Provincial Natural Science Foundation (20232BAB206003).

CRediT authorship contribution statement

Chuanhui Chen: Conceptualization, Writing – original draft, Funding acquisition. Mengzhi Wan: Validation, Writing – original draft. Xiong Peng: Writing – review & editing, Formal analysis. Qing Zhang: Data curation, Writing – review & editing. Yu Liu: Data curation, Writing – review & editing.

Declaration of Competing Interest

The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper.

Acknowledgment

We thank our colleagues for their technical help and stimulating discussions during this investigation.

Footnotes

Supplementary material associated with this article can be found, in the online version, at doi:10.1016/j.tranon.2023.101819.

Appendix. Supplementary materials

mmc1.docx (25.2KB, docx)

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