Overexpression of MRPL19 in predicting poor prognosis and promoting the development of lung adenocarcinoma

Introduction

Lung cancer is still the most common cause of death globally, with non-small cell lung cancer (NSCLC) accounting for 85% of these deaths. Lung adenocarcinoma (LUAD), which accounts for around 40% of lung cancers, is now the most prevalent kind of NSCLC, and its incidence is still increasing (1,2). Surgical procedures, radiotherapy, chemotherapy, immunotherapy, molecularly targeted treatment, or combinations of these modalities are currently used to manage lung cancer (3). Although some patients with positive driver genes, such as EGFR, ALK, RET, BRAF, ROS1, NTRK, MET and KRAS (4), can achieve some benefits from targeted treatment, the 5-year survival rate is still poor and individuals still encounter problems of tumor gene mutation and drug resistance. To improve the prognosis, it is vital to identify any probable genetic alterations and pathways in the development of lung cancer.

Mitochondrial ribosomal proteins (MRPs) are encoded by nuclear genes and then translated by 80S cytoplasmic ribosomes. Following particular targeting and sorting, MRPs are imported into the mitochondria and then are assembled into mitochondrial ribosomes (5). MRPs are involved in the growth of several malignancies and can be employed as diagnostic and therapeutic markers in some cases (6), such as MRPL13 promoting the proliferation of NSCLC and being used as a potential target for the immunotherapy of NSCLC (7), MRPL42 promoting the proliferation and migration of LUAD cells by being activated by YY1 (8), MRPL35 knockdown weakening the colorectal cancer cell proliferation and inducing apoptosis and inhibiting the tumor growth (9). Mitochondrial ribosomal protein L19 (MRPL19) is a protein-coding gene, located on chromosome 2p12 and encodes the protein components of the large mitochondrial ribosome subunit that has a sedimentation coefficient of 39S. MRPL19 knockdown can decrease oxygen deprivation/reperfusion (OGDR)-induced apoptosis in the neuroblastoma cell line SK-N-BE (2) and additionally is a probable target for the therapy of cerebral ischemia-reperfusion damage (10). MRPL19 has been identified as a diffuse non-Hodgkin lymphoma (DNHL)-associated gene by a transcriptome-wide association study (TWAS) although the potential biological mechanism has not been verified (11). For type I or II endometrial malignancies (12), melanoma (13) and pancreatic carcinoma (14), MRPL19 has also been employed as an intrinsic reference gene. Furthermore, neither the expression nor medical importance of MRPL19 in LUAD has been investigated, and whether MRPL19 has functions similar to other MRPs remains unclear.

Using information from the Gene Expression Omnibus (GEO) and The Cancer Genome Atlas (TCGA) databases, we examined MRPL19 expression in LUAD and its potential predictive significance. Additionally, we investigated MRPL19’s role in cancer immunity and clarified the underlying biological processes (BPs) and important pathways underscoring the relationship between MRPL19 and LUAD. We further employed immunohistochemistry (IHC) staining to confirm the expression of MRPL19 and its possible prognostic significance in LUAD and conducted in vitro cell experiments to clarify the functions of MRPL19 that promote the development of LUAD. We present this article in accordance with the MDAR and REMARK reporting checklists (available at https://tlcr.amegroups.com/article/view/10.21037/tlcr-23-306/rc).

Methods

Data acquisition and preprocessing

For this investigation, TCGA (https://portal.gdc.cancer.gov/) and GEO (https://www.ncbi.nlm.nih.gov/geo/) were used to retrieve all malignant cell data. TCGA-ALL provided the RNA sequencing information for 11,093 pan-cancer specimens, whereas TCGA-LUAD provided the information for 535 LUAD cases and 59 healthy lung tissue samples. To make it easier to compare these data with chip data, TCGA standardizes all raw RNA-sequencing data in terms of fragments per kilobase million (FPKM) through log2 (FPKM+1), which was then converted to the form of transcripts per million (TPM) for this study. The microarray and RNA sequencing data for LUAD were acquired from the GEO database and included GSE21933 (n=11) and GSE33532 (n=60). Data from the 2 datasets were normalized with the R package “preprocessCore” (The R Foundation of Statistical Computing, Vienna, Austria) and log2 conversion and then processed with the “limma” package. After processing, the GEO dataset included 51 LUAD specimens and 20 healthy lung tissue specimens. The Cancer Cell Line Encyclopedia (CCLE) dataset (available at https://sites.broadinstitute.org/ccle) was employed to construct the cell line expression matrix for pan-cancer (15). A total of 56 LUAD specimens and 55 surrounding nontumor specimens were obtained from patients with LUAD undergoing surgery at the First Affiliated Hospital of Hebei North University. Hematoxylin and eosin staining, paraffin embedding, and plating of samples onto a human tissue microarray (TMA) were all completed. The study was conducted in accordance with the Declaration of Helsinki (as revised in 2013). The study was approved by the Ethics Committee of the First Affiliated Hospital of Hebei North University (No. W2023012). None of the patients were subjected to radiotherapy or chemotherapeutics before operation and all of the participants signed an informed consent. The HBE135-E6E7 healthy lung cell line [American Type Culture Collection (ATCC) CRL-2741] and the LUAD cell lines NCI-H1299 (CVCL-0060), A549 (CVCL-0023), and 95-D (ATCC CL-0011) were examined in this study.

Differential expression and survival analysis based on public databases

The analysis of differential MRPL19 gene expression between LUAD samples and adjacent nontumor samples was completed using R software, and the outcomes were displayed using the “ggplot2” package. The expression differences of MRPL19 between pan-cancer samples and their adjacent nontumor samples accordingly, and the expression of MRPL19 in pan-cancer cells were also analyzed with the above-mentioned method. MRPL19 expression in cancer subgroups was examined based on clinicopathological features using UALCAN (http://ualcan.path.uab.edu/), which includes TCGA level 3 RNA-sequencing and medical data from 31 kinds of tumors (16). The Kaplan-Meier (KM) plotter (https://kmplot.com/analysis/) online database and Gene Expression Profiling Interactive Analysis (GEPIA) (http://gepia.cancer-pku.cn/) web tools were employed to create a survival curve and to evaluate the impact of MRPL19 on the prognosis of LUAD. The median MRPL19 expression was used as a threshold, while overall survival (OS) was used as the end point to plot the survival curve.

RNA extraction and real-time quantitative polymerase chain reaction (RT-qPCR) analysis

The manufacturer’s recommendations were followed in conducting the RNA isolation and RT-qPCR tests. TRIzol reagents (3101-100; Pufei Biotechnology, Shanghai, China) were used to obtain total RNA, and a Moloney murine leukemia virus reverse transcriptase kit was used to reverse-transcribe the extracted total RNA into complement DNA (cDNA; M1705; Promega Corp., Shanghai, China). SYBR Premix Ex Taq (DRR041B; Takara Bio, Kusatsu, Japan) was adopted in RT-qPCR to identify gene expression. Primers (RiboBio, Guangzhou, China) were used to target MRPL19 and its endogenous control ACTB (beta actin). The MRPL19 expression in several cell lines was assessed with ΔCt, and the effectiveness of MRPL19’s subsequent gene knockdown in comparison to the control group was expressed as 2^−ΔΔCt. The primers used in this study were the following: MRPL19 (F: 5'-GAGAAACGGCTGGATGATAGC-3'; R: 5'-AGGCTCTTGTACTACTGGCTTC-3'); and ACTB (F: 5'-GCGTGACATTAAGGAGAAGC-3'; R: 5'-CCACGTCACACTTCATGATGG-3').

IHC

The expression of MRPL19 was analyzed in TMA by IHC. Primary MRPL19 antibody was diluted to 1:100 (16517-1-AP; Proteintech Corp., Chicago, USA). The UltraSensitive SP IHC Kit (mouse/rabbit; KIT-9720; Fuzhou Maixin Biotech Co., Ltd., Fuzhou, China) was employed as secondary antibody for visualization. Counterstaining was performed using hematoxylin. Two experienced independent pathologists who were not informed of the patient's situation evaluated the IHC data. Staining was scored by the intensity of the positive staining (0, negative; 1, weak; 2, moderate; and 3, strong) multiplied by the stained regions (0, negative; 1, 1–25%; 2, 26–50%; 3, 51–75%; and 4, 76–100%). By analyzing the receiver operating characteristic (ROC) curve, the best threshold was identified.

Coexpression gene assessment

The LinkedOmics database (http://www.linkedomics.org/login.php) is an online tool for examining multidimensional data sets related to TCGA (17). A total of 515 high-throughput sequencing messenger mRNA (Hiseq-mRNA) data sets of LUAD from the LinkedOmics Database were employed to assess MRPL19 coexpressed genes via Pearson correlation coefficients, the results of which were displayed in volcano plots and heatmaps. GEPIA2 (http://gepia2.cancer-pku.cn/) was employed to construct the survival map of the 50 major genes positively and negatively correlating with MRPL19.

Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) mechanism enrichment assessment

A threshold of |R-statistic| >0.2 was used to identify genes that were coexpressed with MRPL19. The “clusterProfiler” package in R was employed to examine the GO and KEGG enrichment assessment of these obtained co-expression genes. The GO enrichment study included BPs, cellular components (CCs), and molecular functions (MFs). The “ggplot2” package in R was employed to display the findings.

Gene set enrichment analysis (GSEA)

Gene ranking was completed on the coexpression genes of MRPL19 according to |R-statistic|. GSEA was conducted to investigate the underlying biological pathway of MRPL19 in the development of LUAD. To this end, the packages “clusterProfiler” and “org.Hs.eg.db” were used on the hallmark gene sets from the GSEA’s official website. For each experiment, a total of 1,000 cycles of gene permutations were run to identify the enriched mechanisms. To identify significantly the enriched gene sets and mechanisms, false-discovery rate (FDR)-modified P values and normalized enrichment scores (NESs) were calculated.

Construction of a protein-protein interaction (PPI) network

An effective tool for functional enrichment, interactome assessment, gene annotation, and membership search is provided on Metascape website (http://metascape.org/) (18). Those MRPL19 coexpression genes that met the threshold of |R-statistic| >0.4 and a P value <0.05 were selected. A PPI network was constructed using these acquired coexpressed genes with the aid of Metascape, and the main pathways were analyzed.

The prediction of upstream regulators

In total, 515 Hiseq-mRNA datasets of LUAD from the LinkedOmics database were examined. To conduct kinase-target enrichment, microRNA (miRNA)-target enrichment, and transcription factor-target enrichment using GSEA, the LinkedOmics LinkInterpreter module was used with a criterion of an FDR-adjusted P value <0.05

Immune infiltration analysis

The Tumor Immune Estimation Resource (TIMER) database (19) from TCGA provides a comprehensive means for systematically examining immune infiltrates in types of malignancy (https://cistrome.shinyapps.io/timer/) with a deconvolution technique. Using the “Gene” module, this study investigated the link between the expression of MRPL19 and the LUAD purity and the quantity of tumor-infiltrating immune cells (TIICs). The SCNA (somatic copy number alterations) module was employed to clarify the connection among MRPL19 copy number variations (CNVs) and the degree of immune cell infiltration. The relationship between MRPL19 expression and immune cell infiltration level with prognosis was investigated using the “Survival” module.

Lentivirus short hairpin RNA and transfection

Control small interfering RNA (siRNA) and short hairpin RNA (shRNA) were obtained from Generay (Shanghai, China) for the interference sequence targeting of MRPL19. Using the GV115 vector, siRNA control and siRNA-MRPL19 were transfected into the A549 and H1299 cell lines (GeneChem Inc., Shanghai, China). The target sequence of shRNA MRPL19 was 5'TGGATGATAGCTTGCTATA-3'.

Western blotting

Cells were lysed in radioimmunoprecipitation assay (RIPA) lysis buffer on ice after being rinsed twice with phosphate-buffered saline (PBS). Sodium dodecyl sulfate (12%)-polyacrylamide gel electrophoresis (SDS-PAGE) was employed to disassociate and separate all the proteins according to their molecular masses. The protein amount was detected with a bicinchoninic acid (BCA) reagent kit (AS1086; Aspen Technology, Inc., Shanghai, China). SDS-PAGE gels were transferred onto polyvinylidene fluoride (PVDF) membranes. Total protein was identified using Western blotting with anti-MRPL19 (1:3,000; 16517-1-AP; Proteintech) and anti-β-Actin (1:10,000; TDY051; TDY Biotech Corp., Beijing, China). After incubation with the second antibodies (goat anti-rabbit: 1:10,000; AS1107; Aspen Technology, Inc.), proteins were identified using an enhanced chemiluminescence (ECL) detection kit (AS1059; Aspen Technology, Inc.) in accordance with the manufacturer’s guidelines.

Celigo cell growth test

96-well plates were seeded with shCtrl and shMRPL19 cells at a density of 1,000–2,000 cells/well depending on the growth rate. Cells were cultured in an incubator (MOC-175-175; Sanyo, Osaka, Japan) with 5% CO₂ at 37 ℃. Cells were screened every day for 5 days to acquire images using a Celigo full-field cell scan analyzer (Celigo; Nexcelom Bioscience, Shenzhen, China) and the number of cells was calculated with a cell counter (Auto1000; Nexcelom Bioscience). Cell proliferation curves were plotted after 5 consecutive days of counting.

Colony formation test

The capability of cells to grow was evaluated with the colony formation test. Experimental and control cells were added and cultivated in 6-well soft agar mixture plates at 1,000 cells per well for 7 days. Following crystal violet (CB0331; Sangon Biotech, Shanghai, China) staining, the colonies with greater than 50 cells that survived were counted. Three separate cycles of the trials were performed.

Apoptosis assay

Six-well plates (no less than 5×10⁵ cells per well) each were seeded with experimental and control cells. According to the manufacturer’s recommendations, Annexin V-APC (88-8007; eBioscience, San Diego, USA) staining was used to analyze apoptosis, and flow cytometry (C6 PLUS; BD, New Jersey, USA) was used to determine the rate of apoptosis in the cells.

MTT assay

shCtrl and shMRPL19 cells were multiplied at a concentration of 2×10³ cells per well in 96-well plates. On days 1, 2, 3, 4, and 5, a total of 20 µL of MTT (methyl thiazolyl tetrazolium) (5 mg/mL) was administered to every well. Following a further 4 hours of cultivation, 100 µL of dimethyl sulfoxide was administered to each well. With a microplate reader (M2009PR; Tecan Infinite, Mannedorf, Switzerland), the concentration of every well at 490 nm [optical density (OD) 490] was determined following reduced-speed shaking for 5 min. Curves for cell growth were drawn.

Cell migration and invasion assay

Transwell tests were used for examinations on migration and invasion. For 48 hours, cells were transfected with shCtrl or shMRPL19. Transfected NCI-H1299 cells were then implanted at a density of 5×10⁴ cells, and A549 cells were transfected at a concentration of 1×10⁵ cells in 24-well Transwell chambers with 8-µm-thick polycarbonate membrane (Corning, New York, USA). After 100 µL of serum-free medium was added to the top chamber and 600 µL of media with 30% fetal bovine serum was added to the bottom chamber, cells were cultivated at 37 ℃ for 16 hours to test for migration. Cotton swabs were used to eliminate cells from the filter’s top surface, while migrating cells that adhered to the membrane’s bottom surface were preserved in 4% paraformaldehyde solution and subjected to 0.5% crystal violet stain. To calculate the number of cells, 9 random selection microscope fields (×200) were chosen. A Matrigel covering was introduced to the polycarbonate membrane for invasion testing, and the experiments were conducted using the same procedure. Three separate repetitions of the tests were conducted.

Statistical analysis

R software (version 3.6.3), SPSS 20.0 (IBM Corp., Armonk, New York, USA), and GraphPad Prism 8.1.1 (GraphPad Software, Inc., San Diego, CA, USA) were used for statistical analyses. The association between MRPL19 expression and the clinical characteristics of LUAD was evaluated using the chi-squared (χ²) test. The comparison between the 2 cohorts (the experimental group and the control) was completed with the Mann-Whitney test and Student’s t-tests. To determine the survival time in the MRPL19 low- and high-expression groups, KM analysis was performed. The IHC score ≤3 was considered as low expression while >3 was the high expression. The cutoff value was obtained by ROC curve. The relationship between survival time, clinical prognostic markers, and MRPL19 expression was examined using univariate and multivariate Cox regression models. The relation between the degree of immune cell infiltration and MRPL19 expression was examined using the partial Spearman correlation coefficient. Statistical significance was recognized as a 2-sided P<0.05.

Results

High expression of MRPL19 in LUAD

By employing pan-cancer information from TCGA database, the changes in MRPL19 expression at the transcriptional level were assessed in 33 different kinds of cancers. In LUAD, MRPL19 mRNA expression was substantially high (Figure 1A). The CCLE database indicated that MRPL19 mRNA was elevated in LUAD and other cancer cells at the cellular level (Figure 1B). Expression differences between LUAD samples and adjacent nontumor samples were analyzed using TCGA-LUAD data, which also indicated that MRPL19 mRNA expression was substantially elevated in LUAD compared to neighboring healthy tissues (Figure 1C). Moreover, the upregulated levels of MRPL19 mRNA in LUAD were also validated in the GEO database data sets (Figure 1D). RT-qPCR assessment was conducted to evaluate the relative levels of mRNA among healthy lung epithelial cells (HBE135-E6E7) and several LUAD cell lines, including NCI-H1299, A549, and 95-D, in order to further confirm this result. NCI-H1299, A549, and 95-D cells had higher levels of MRPL19 mRNA than did the HBE135-E6E7 cell line (Figure 1E). The outcomes also showed that the NCI-H1299 and A549 cell lines had higher levels of MRPL19 mRNA than did the 95-D cell line.

Figure 1 Expression of MRPL19 in LUAD. (A) The mRNA expression level of MRPL19 in the pan-cancer data from TCGA database. (B) The expression of MRPL19 mRNA in different tumor cells. (C) Differential expression of MRPL19 mRNA from TCGA database. (D) Differential expression of MRPL19 mRNA from GEO database. (E) Expression of MRPL19 mRNA in different LUAD cell lines and normal lung epithelial cell lines. (F) Expression of MRPL19 protein from clinical samples. (G) Typical IHC staining images of MRPL19 in normal lung tissue and LUAD tissues (IHC staining method. Magnification ×200 and ×400). *, P<0.05; **, P<0.01; ***, P<0.001; ****, P<0.0001; ns, not significant. MRPL19, mitochondrial ribosomal protein L19; TPM, transcripts per million; ACTB, beta actin; IHC, immunohistochemistry; LUAD, lung adenocarcinoma; TCGA, The Cancer Genome Atlas; GEO, Gene Expression Omnibus.

For the MRPL19 knockdown assays, the NCI-H1299 and A549 cell lines were used. MRPL19 expression at the protein level was much higher in the IHC results of 56 LUAD specimens than of the 55 neighboring healthy samples (P<0.01; Figure 1F,1G). Upregulation of MRPL19 was shown at both the transcription and protein level through subgroup examination of multiple clinicopathological features of TCGA-LUAD specimens using the UALCAN database. MRPL19 expression at the transcription level was substantially higher in LUAD than in healthy controls in the subgroup investigation depending on gender, age, ethnicity, and cancer stage (Figure 2A-2E). Additionally, upregulation of MRPL19 at the protein level was also demonstrated in LUAD in the subgroup evaluation depending on gender, race, tumor grade, and stage (Figure 2F-2J).

Figure 2 Expression of MRPL19 in subgroups of patients with LUAD. (A) Relative expression of MRPL19 mRNA in healthy and LUAD samples. (B) Differential expression of MRPL19 mRNA between healthy individuals and male or female patients with LUAD. (C) Differential expression of MRPL19 mRNA between healthy individuals of any age and patients with LUAD aged 21–40, 41–60, 61–80, or 81–100 years. (D) Differential expression of MRPL19 mRNA between healthy individuals and African-American, White, and Asian patients with LUAD. (E) Differential expression of MRPL19 mRNA between healthy individuals and patients with stages 1–4 LUAD. (F) Relative expression of MRPL19 protein in healthy and LUAD samples. (G) The differential expression of MRPL19 protein between healthy individuals and male or female patients with LUAD. (H) The differential expression of MRPL19 protein between healthy individuals and African-American, White, and Asian patients with LUAD. (I) The differential expression of MRPL19 protein between healthy individuals and patients with Grade 1–3 LUAD tumor. (J) The differential expression of MRPL19 protein between healthy individuals and patients with stages 1–4 LUAD. The t-test was used to estimate the significance of difference in gene expression levels between groups. *, P<0.05; ***, P<0.001. TCGA, The Cancer Genome Atlas; CPTAC, the Clinical Proteomic Tumor Analysis Consortium; MRPL19, mitochondrial ribosomal protein L19; LUAD, lung adenocarcinoma.

MRPL19 overexpression was correlated with poor prognosis in individuals with LUAD

To evaluate the impacts of MRPL19 expression on LUAD prognosis, KM survival curves based on OS were constructed to evaluate the relation between MRPL19 expression and survival using LUAD data sets with available survival information. The cohort with aa higher expression of MRPL19 had a substantially shorter OS [hazard ratio (HR) =1.5; log rank P=0.0059] than did the reduced expression group according to KM analysis of the GEPIA TCGA-LUAD datasets (Figure 3A). Furthermore, KM survival curve examination employing KM Plotter GEO datasets from the KM plotter further confirmed the association between elevated MRPL19 expression and poor survival (HR =1.45; log rank P=0.0029; Figure 3B). Additionally, IHC staining in TMA samples confirmed these findings (P=0.0004; Figure 3C). The relationship between MRPL19 expression in LUAD and clinicopathological traits was also examined using TMA samples. According to the findings, there was a substantial association between MRPL19 expression and OS status (living vs. dead: P=0.003), differentiation grade (P=0.046), and lymph node metastasis (positive vs. negative: P=0.026) (Table 1). To confirm the prognostic efficacy of MRPL19 in LUAD, univariate and multivariate Cox regression assessment was conducted. The findings revealed that that overexpression of MRPL19 was an independent prognostic variable in LUAD (HR =2.822, 95% CI: 1.113–7.159; P=0.029; Table 2).

Figure 3 The expression of MRPL19 was associated with survival outcome. OS based on (A) TCGA-LUAD datasets from GEPIA, (B) the GEO datasets from the Kaplan-Meier plotter, and (C) IHC staining of TMA specimens. GEPIA, Gene Expression Profiling Interactive Analysis; OS, overall survival; TPM, transcripts per million; HR, hazard ratio; KM, Kaplan-Meier; MRPL19, mitochondrial ribosomal protein L19; TCGA, The Cancer Genome Atlas; LUAD, lung adenocarcinoma; GEO, Gene Expression Omnibus; IHC, immunohistochemistry; TAM, tissue microarray.

MRPL19 coexpression genes in LUAD

The utility of gene coexpression analysis in examining the roles of certain genes has previously been established. According to various research, coexpressed genes functioned in comparable BPs. Therefore, an analysis of MRPL19 coexpression genes was performed in LUAD. The LinkedOmics function module was used to analyze MRPL19 coexpression genes in LUAD, and all coexpression genes are presented in a volcano plot (Figure 4A and available online https://cdn.amegroups.cn/static/public/tlcr-23-306-1.pdf).The genes coexpressed with MRPL19 were screened with the threshold of |R-statistic| >0.2 and FDR <0.05. In all 5,434 MRPL19 coexpression genes were identified, including 1,833 genes with substantial positive correlations and 3,601 genes with substantial negative correlations (available online https://cdn.amegroups.cn/static/public/tlcr-23-306-2.pdf). Figure 4B,4C shows the heatmap of the top 50 major genes that were both positively and negatively associated with MRPL19. Substantial positive correlations between the expressions of MTIF2 and MRPL19 were observed (R=0.612; P=3.05E-50), whereas strong negative correlations between the expressions of CBX7 and MRPL19 were observed (R=−0.536; P=1.26E-36). With 31 of these 50 genes having an increased HR (P<0.05), the top 50 substantial genes that were positively linked with MRPL19 revealed the increased opportunity of having elevated-risk genes in LUAD. Moreover, among the top 50 negatively significant genes, 27 genes had a low HR (P<0.05) (Figure 4D,4E).

Figure 4 MRPL19 coexpression genes in LUAD. (A) A volcano plot of the MRPL19 coexpression genes. Heat maps showing the top 50 genes (B) positively (red) correlated and (C) negatively (blue) correlated with MRPL19 in LUAD. Survival map of the top 50 genes (D) positively and (E) negatively correlated with MRPL19 in LUAD. MRPL19, mitochondrial ribosomal protein L19; LUAD, lung adenocarcinoma; HR, hazard ratio.

Biological significance of MRPL19

To explore the biological relevance of MRPL19, GO annotation, KEGG signaling pathway analysis, PPI network, and GSEA were performed on the MRPL19 coexpression genes. The outcomes of GO annotation examination revealed that the coexpressed genes of MRPL19 at the BP level were primarily enriched in the biogenesis of ribonucleoprotein complexes, chromosome segregation, mitotic nuclear division or differentiation, proliferation, or triggering of immune cells, such as mononuclear cells, leukocytes, and T cells. At the CC level, MRPL19 coexpressed genes were mainly enriched in chromosomal area, mitochondrial matrix, and MHC (major histocompatibility complex) protein compound, while at the MF level, genes were mainly enriched in ATPase activity, GTPase regulator activity, and catalytic activity acting on DNA (Figure 5A,5B and available online https://cdn.amegroups.cn/static/public/tlcr-23-306-3.xlsx). The outcomes of the examination of the KEGG signaling mechanism showed enrichment in the cell cycle, nucleocytoplasmic transport, cell adhesion molecules, spliceosome, and T helper (TH) cell 1, 2, and 17 differentiations. (Figure 5C,5D and available online https://cdn.amegroups.cn/static/public/tlcr-23-306-4.xlsx). The PPI network was constructed using Metascape, and 7 key nodes were included in the network (Figure 5E,5F). Nineteen main signaling pathways were included in these key nodes, including anaphase promoting complex/cyclosome (APC/C)-mediated degradation of cyclin A, modulation of the DNA metabolic pathway, and mitotic spinal checkpoint (Table S1). The outcomes of GSEA revealed that the MRPL19 coexpression genes were mainly enriched in the G2M_Checkpoint pathway, MYC_Targets_V1 pathway, MYC_ Targets _V2 pathway, and E2F_Targets pathway (Figure 5G-5J).

Figure 5 Significantly enriched GO annotations and KEGG pathways of MRPL19 in LUAD: (A) GO annotations that positively correlated and (B) negatively correlated with MRPL19 in LUAD. (C) KEGG pathways that positively and (D) negatively correlated with MRPL19 in LUAD. The GSEA results involving MRPL19 in LUAD: (E) G2M_Checkpoint signaling pathway. (F) MYC_Targets_V1 signaling pathway, (G) MYC_ Targets _V2 signaling pathway, and (H) E2F_Targets signaling pathway. (I) The PPI network of MRPL19. (J) Key nodes in the PPI network. BP, biological process; CC, cellular component; MF, molecular function; MHC, major histocompatibility complex; TCA, tricarboxylic acid cycle; IgA, immunoglobulin A; GO, Gene Ontology; KEGG, Kyoto Encyclopedia of Genes and Genomes; MRPL19, mitochondrial ribosomal protein L19; LUAD, lung adenocarcinoma; GSEA, gene set enrichment analysis; PPI, protein-protein interaction.

Upstream regulators of MRPL19 in LUAD

To explore the upstream regulators of MRPL19 in LUAD, an enrichment analysis of kinases, miRNAs, and transcription factors of MRPL19 co-expressed genes was performed. Significant miRNAs related primarily to MIR-200A (GTAAGAT), MIR-26A/MIR-26B (TACTTGA), MIR-302C (ATGTTAA), MIR-189 (GTAGGCA), MIR-186 (ATTCTTT), and MIR-452 (GAGACTG). No significant kinase was acquired by enrichment analysis of MRPL19 co-expressed genes. The significant transcription factors related to the co-expressed genes were mainly enriched in E2F transcription factor family, including V$E2F_Q4, V$E2F_Q6, and V$E2F1DP1_01 (Table 3).

MRPL19 expression was correlated with immune cell infiltration

According to the findings of the immune infiltration study, B cells (R=−0.224; P=6.18e-07), CD4⁺ T cells, (R=−0.167; P=2.34e-04), and dendritic cells (R=−0.09; P=4.58e-02) were substantially correlated with MRPL19 expression (Figure 6A). Additionally, B cells, CD4⁺ T cells, CD8⁺ T cells, macrophages, neutrophils, and dendritic cells were substantially linked with MRPL19 CNV (Figure 6B). The levels of B cells, dendritic cells, and neutrophil infiltration were substantially connected with the survival of individuals with LUAD, and the reduced level of infiltration indicated poor survival according to the findings of the KM survival curve assessment (Figure 6C). The degree of B-cell infiltration was demonstrated to be an independent prognostic variable in LUAD according multivariate Cox regression (HR =0.045, 95% CI: 0.003–0.782; P=0.033; Table 4).

Figure 6 Correlations of MRPL19 expression with immune infiltration level in LUAD. The association between (A) MRPL19 expression and (B) MRPL19 CNV and tumor infiltration immune cells. (C) The correlation of the infiltrating level of tumor immune cells with the OS of patients with LUAD. *, P<0.05; **, P<0.01; ***, P<0.001. MRPL19, mitochondrial ribosomal protein L19; TPM, transcripts per million; LUAD, lung adenocarcinoma; CNV, copy number variation; OS, overall survival.

MRPL19 promoted the growth of LUAD cells in vitro

To further elucidate the function of MRPL19 in LUAD, the target sequence of shRNA MRPL19 was used to silence MRPL19 expression in LUAD cells. The A549 and H1299 cell lines with a higher expression level of MRPL19 were selected for further study. RT-qPCR analysis showed that MRPL19 expression of A549 and H1299 cells transfected with MRPL19 shRNA was reduced by more than 80%, which was statistically significant compared with the control cohort (Figure 7A) (P<0.05). The target sequence of the MRPL19 shRNA was able to lower MRPL19 expression at the protein level according to Western blotting data (Figure 7B). The findings of the Celigo tests revealed that the A549 and H1299 cell lines’ ability to grow was greatly diminished by the removal of MRPL19 (Figure 7C). The MTT tests also revealed that the 2 LUAD cell lines’ proliferation was greatly slowed by MRPL19 knockdown (Figure 7D). Colony formation tests revealed that the amount of cell clones in the A549 and H1299 cell lines diminished significantly when MRPL19 was removed (Figure 7E).

Figure 7 MRPL19 knockdown suppressed LUAD cell proliferation. (A) RT-qPCR analysis was used to examine the knockdown efficiency of MRPL19. (B) Western blotting was performed to analyze protein expression levels of MRPL19. Celigo assays (fluorescence staining; magnification ×100) (C), MTT assays (D), and colony formation assays (E) were applied to evaluate cell proliferation (the inoculated cells were cultured in an incubator, and the number of cells in a single clone was observed by ×100 microscope until the number of cells in most of the single clones in the control group was more than 50. The crystal violet staining was performed. The entire culture plate was then photographed. Single clones of 0.3 to 1 mm in size in both groups were counted). **, P<0.01; ***, P<0.001; ****, P<0.0001. MRPL19, mitochondrial ribosomal protein L19; ACTB, beta actin; OD, optical density; LUAD, lung adenocarcinoma; RT-qPCR, real-time quantitative polymerase chain reaction; MTT, methyl thiazolyl tetrazolium.

Effects of MRPL19 on cell death of LUAD

Flow cytometry was employed to explore the influence of MRPL19 expression on LUAD cell death. The outcomes indicated that the average proportion of apoptosis of A549 cells in the shMRPL19 group was 3.5%, representing a significant increase compared to the shCtrl cohort (Figure 8A). The apoptosis rate of H1299 cells in the shMRPL19 group was 0.4%, which did not represent a significant change compared to the shCtrl group (Figure 8B). No obvious cell apoptosis was observed after MRPL19 knockdown.

Figure 8 The effect of MRPL19 knockdown on LUAD cell apoptosis. (A) The apoptosis rate of A549 cells in the shMRPL19 group was significantly higher than that of the shCtrl group, but less than 5%. (B) The apoptosis rate of the H1299 cells in the shMRPL19 group was less than 5% and had no significant change compared to the shCtrl group. ****, P<0.0001; ns, not significant. MRPL19, mitochondrial ribosomal protein L19; APC-A, anaphase promoting complex A; LUAD, lung adenocarcinoma.

MRPL19 promoted the invasion and migration of LUAD cells

The outcomes of the Transwell migration examination demonstrated that the migration ability of the 2 LUAD cell lines was substantially reduced after removal of MRPL19 (Figure 9A) (P<0.05). The Transwell invasion assessment also indicated that the suppression of MRPL19 substantially reduced the degree of invasiveness in both selected LUAD cell lines (P<0.05; Figure 9B). These results verified that MRPL19 can increase LUAD cell invasion and migration.

Figure 9 MRPL19 knockdown suppressed the invasion and migration of LUAD cells. (A) Transwell invasion assay was employed to detect the invasion ability of LUAD cells. (B) Transwell migration assay was employed to detect the migration ability of LUAD cells (Giemsa staining; magnification ×200). ***, P<0.001; ****, P<0.0001. MRPL19, mitochondrial ribosomal protein L19; LUAD, lung adenocarcinoma.

Discussion

As a malignant tumor, lung cancer continues to be the leading cause of tumor-related death, representing 18.0% of all cancer-related fatalities (20). LUAD represents 38.5% of all cases and constitutes a greater proportion of lung cancer cases than other histologies (21). Recently, the development of low-dose computer tomography, targeted therapies, and immunotherapy has marginally increased the survival rate of lung cancer (22). The disease progresses in the majority of patients after 6 to 12 months of therapies with epidermal growth factor receptor (EGFR) tyrosine kinase inhibitors (TKIs) due to the appearance of mechanisms of resistance to the original agent (1), so the development of novel LUAD treatment and prognostic targets is now critically essential. According to our findings, LUAD had considerably higher levels of MRPL19 mRNA expression than did adjacent non-tumor tissue. The protein level likewise showed a similar pattern. Overexpression of MRPL19 was linked to a poor prognosis in LUAD according to KM analysis. The IHC findings confirmed the hypothesis that the overexpression of MRPL19 is connected to the OS status. Additionally, univariate and multivariate Cox regression examination pointed to MRPL19 as being an independent prognostic variable in LUAD. Therefore, the results of this investigation suggest that MRPL19 may have a potential value in LUAD prognosis, and thus its functions and mechanisms should be scrutinized further.

As MRPL19 is a member of the MRPs and recent investigations have highlighted its possible function in the biology of malignancy and may be employed as both therapeutic and diagnostic biomarkers. As MRPL19’s biological role in LUAD has not yet been examined, we tried to identify the coexpression genes related to MRPL19 in LUAD and to determine the biological roles of MRPL19 in this cancer. Strong correlations between the expression of MTIF2 and MRPL19 were observed, whereas the expression of CBX7 and MRPL19 were strongly inversely correlated. The mitochondrial function of the nuclear-encoded gene MTIF2 is to execute the translation of proteins encoded by the mitochondrial genome (23). In a 5-fluorouracil (5-FU) treatment in vivo model, MTIF2 overexpression was found suppress hepatocellular carcinoma cell death and immune cell activity by inhibiting tumor-infiltrated dendritic cell maturation (24). CBX7 is a kind of polycomb protein that is involved in the development of polycomb repressive compound 1, and downregulated CBX7 expression was reported to be a biomarker of cancer aggressiveness and a poor prognosis (25). CBX7 downregulation can reduce the sensitivity of bladder cancer to cisplatin (26). Thus, it is suggested that MRPL19 may have a role in enhancing the development of LUAD. GO annotation, KEGG signaling pathway analysis, PPI network, and GSEA were performed on the MRPL19 coexpressed genes to obtain more information regarding the biological roles of MRPL19 in LUAD. The outcomes of the GO annotation demonstrated that the genes coexpressed with MRPL19 primarily revolved around cell mitosis, energy metabolism, and tumor immunity. KEGG signaling mechanism analysis indicated that the MRPL19 coexpressed genes may be associated with cell cycle, nucleocytoplasmic transport, cell adhesion molecules, spliceosome, and Th1, Th2, and Th17 cell differentiation. Loss of cell cycle control, which is caused by the lack of equilibrium between oncogenes and tumor-suppressor genes, can lead to the occurrence of lung cancer (27). Cell adhesion molecules have a vital function in epithelial-mesenchymal transition and changes in the tumor microenvironment (TME), both of which are important in the process of tumor cell invasion and migration (28). RNA splicing changes originated by the spliceosome, the catalyst for splicing reactions, have also been potentially involved in the development and/or preservation of cancer (29). Additionally, it has been proposed that an imbalance and switch from Th1 lymphocytes to Th2 phenotype might be crucially linked to the onset and progression of lung cancer, while Th17 cells contribute to antitumor immunity by supporting the aggregation of T cells to the tumor site and the priming of CD8⁺ T cells. The Th1, Th2, and Th17 lymphocytes are all differentiated from naive CD4⁺ T cells (30). The gene sets G2M Checkpoint, MYC Targets_V1, MYC Targets_V2, and E2F Targets have been identified by the Molecular Signatures Database (MSigDB) Hallmark as being associated with cell proliferation (31). Uncontrolled growth, genetic instability, and cancer might arise from the proteolytic system being out of regulation as some changes in the ubiquitylation of cell cycle regulators (32). In this regard, the ubiquitin ligase, APC/C, is responsible for the ubiquitin-mediated proteolysis of important cell cycle regulators including cyclins and cyclin-dependent kinase (CDK) suppressors.

Also, mutations and altered gene expression at the mitotic spindle checkpoint have been found to result in aberrant chromosomal content or aneuploidy, which may promote the growth of cancer (33). Therefore, according to our results, it can be inferred that MRPL19 may exert pro-oncogenic effects in LUAD via pathways connected with cell cycle, cell adhesion molecules, splicing, and mitotic spindle checkpoint. MRPL19 may also promote the development of LUAD by affecting the tumor immunity.

Kinase, miRNA, and transcription factor target enrichments were performed to investigate the upstream regulators for MRPL19 dysregulation in LUAD. The outcomes of miRNA-target enrichment indicated that MRPL19 in LUAD was associated with miR-200A, miR-26A/miR-26B, miR-302C, miR-189, miR-186, and miR-452 expression. In NSCLC cell lines, elevated miR-200A expression encourages growth and migration of cells (34,35). Blocking miR-26a-5p might limit NSCLC cells from proliferating, migrating, and invading, while contributing to their death (36). The development, migration, and invasion of A549 lung malignancy cells in vitro along with the development of existing malignancies in vivo may be inhibited by the overexpression of miR-26b (37). Additionally, miR-186 elevation significantly diminishes the ability for invasion and migration (38). Therefore, it has been speculated that MRPL19 may support LUAD proliferation, migration, and invasion with the regulation of miRNAs. In this study, the results of the target transcription factor enrichment showed that MRPL19 in LUAD was mainly associated with E2F transcription factors. Numerous expressions of genes crucial for cell growth are regulated by the E2F transcription factors (39). In LUAD, a greater expression of E2F family genes was linked to a poor prognosis (40). The outcomes in our study suggest that E2F transcription factors may have a vital function in the modulation of MRPL19 and may support the growth of LUAD by affecting MRPL19 expression, but more studies are needed to verify this hypothesis. However, no associated kinase was identified by enrichment analysis.

The TME includes a significant number of immune cells, which have a vital function in the survival and progress of malignancies. An environment that promotes tumor development and metastasis is eventually produced by the interaction between proximal immune cells and cancer cells (41). Thus, the TIMER database was used to investigate the association between MRPL19 expression and immune cells. The findings demonstrated a substantial negative connotation between MRPL19 expression and the infiltration of B cells, CD4⁺ T cells, and dendritic cells. Elevated infiltration of CD4⁺ T cells or dendritic cells can predict prolonged OS in lung cancer (42,43), which is consistent with the findings of the KM survival curve analysis in this study, which revealed that the low level of infiltration of B cells or dendritic cells could predict poor survival in patients with LUAD. Tumor-infiltrating B cells have been associated with better outcome for patients with lung cancer via the exertion of antitumor immunity (44). The amount of infiltrating B lymphocytes was shown to be an independent prognostic variable in LUAD according to the findings of multivariate Cox regression assessment. Therefore, it is a conceivable hypothesize that MRPL19 may influence the development of LUAD by modulating the immune cells that infiltrate tumor function.

To confirm the biological role of MRPL19 in LUAD, associated experiments were performed after MRPL19 expression was reduced in A549 and H1299 cell lines. The outcomes revealed that the ability for growth, migration, and invasion in vitro was reduced after the silencing of MRPL19. However, cell apoptosis was not affected after MRPL19 knockdown. Our experiments further verified the results of the bioinformatics examination. Therefore, we hypothesized that MRPL19 might have a pro-oncogenic function in the progression of LUAD.

There are some limitations to the present study. First, the number of clinical specimens in the validation experiment was relatively small, and the sample size should be expanded for a more substantial analysis. Second, the molecular pathways of MRPL19 in LUAD remain unclear although our investigation did evaluate several functional annotations and included enrichment analysis. Finally, more investigations using other experimental methods should be required to confirm the probable biological mechanisms underlying the relationship between MRPL19 and the development of LUAD.

Conclusions

Our investigation provides reliable support for the significance of MRPL19 in the development of LUAD and its potential as a biomarker for LUAD prognosis. Our findings revealed a substantial correlation between increased MRPL19 expression and the development of LUAD, a poor prognosis, and immune infiltration. Furthermore, our in vitro cell results indicate that MRPL19 may have a pro-oncogenic function in the growth of LUAD.

Acknowledgments

Funding: This work was supported by Hebei Provincial Health Commission Key Science and Technology Research Program (No. 20200552).

Footnote

Reporting Checklist: The authors have completed the MDAR and REMARK reporting checklists. Available at https://tlcr.amegroups.com/article/view/10.21037/tlcr-23-306/rc

Data Sharing Statement: Available at https://tlcr.amegroups.com/article/view/10.21037/tlcr-23-306/dss

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Conflicts of Interest: All authors have completed the ICMJE uniform disclosure form (available at https://tlcr.amegroups.com/article/view/10.21037/tlcr-23-306/coif). The authors have no conflicts of interest to declare.

Ethical Statement: The authors are accountable for all aspects of the work in ensuring that questions related to the accuracy or integrity of any part of the work are appropriately investigated and resolved. The study was conducted in accordance with the Declaration of Helsinki (as revised in 2013). The study was approved by the Ethics Committee of the First Affiliated Hospital of Hebei North University (No. W2023012) and informed consent was taken from all the patients.

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(English Language Editor: J. Gray)