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Bioinformatics analyses proposed xenotropic and polytropic retrovirus receptor 1 as a potential diagnostic and prognostic biomarker and immunotherapeutic target in head and neck squamous cell carcinoma
The role of Xenotropic and polytropic retrovirus receptor 1 (XPR1), a cell surface receptor for certain types of murine leukemia viruses, in human cancers has been rarely studied. We aimed to evaluate the values of XPR1 as a biomarker and therapeutic target in head and neck squamous cell carcinoma (HNSCC).
Methods
Bioinformatics tools and online databases, including R packages, ONCOMINE, The Cancer Genome Atlas (TCGA), Human Protein Atlas (HPA), UALCAN, MethSurv, cBioPortal, and TIMER2.0 were applied in this study.
Results
The mRNA and protein expression of XPR1 is significantly up-regulated in HNSCC tissues compared with normal tissues. The receiver operating characteristic (ROC) curve shows XPR1 has high specificity and accuracy in the diagnosis of HNSCC (AUC = 0.883). Patients with high-level expression of XPR1 have poorer overall survival (OS, P = 0.002), disease-specific survival (DSS, P = 0.014), and progress-free interval (PFI, P = 0.017). UALCAN analysis indicates that the methylation of XPR1 promoter in HNSCC is significantly down-regulated. MethSurve was used to investigate the impact of individual CpG islands on the prognosis of HNSCC patients. Low DNA methylation levels of cg11538848 and cg20948051 and high DNA methylation levels of cg23675362, cg18440470, and cg22026687 are significantly related to poor prognosis. The Gene Set Enrichment Analysis (GSEA), Gene Ontology (GO), and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analysis indicate that XPR1 is involved in various important biological functions and signaling pathways closely related to cancer. The co-expression analysis of XPR1 and N6-methyladenosine (m6A) RNA methylation regulators shows that XPR1 is significantly related to the expression of main m6A regulators. Immune infiltration analysis shows that the expression of XPR1 is related to certain types of immune infiltrating cells and has a positive correlation with the expression of four immune checkpoint genes, PDCD1LG2, CD274, HAVCR2, and SIGLEC15.
Conclusion
In summary, these results indicate that XPR1 is a potential diagnostic and prognostic biomarker and immunotherapy target for HNSCC. This study sheds new light on understanding the formation and development of HNSCC and sets the basis for further studying the role of XPR1 in HNSCC and other types of cancers.
]. Head and neck squamous cell carcinoma (HNSCC) is the most common pathological type of cancer originating from the head and neck region, accounting for more than 90% of the cases [
]. Recurrent and metastatic HNSCC are usually considered incurable. While a lot of efforts have been made in decades, we still have a poor understanding of the molecular mechanisms for the formation and development of HNSCC. These facts underscore the significance of discovering the molecules and signaling pathways contributing to HNSCC to develop more effective therapies for HNSCC.
Xenotropic and polytropic retrovirus receptor 1 (XPR1) is first identified as a cell-surface receptor for several types of xenotropic and polytropic murine leukemia viruses [
]. In human cells, XPR1 has been mainly recognized as an inorganic phosphate exporter that plays an essential role in maintaining intracellular phosphate homeostasis [
]. Barker et al. have reported that XPR1 regulates an efflux of intracellular inorganic phosphate accompanied by the events of stimulated insulin secretion in pancreatic β-cell and islets [
]. Malfunction of XPR1 has been reported to be related to several human diseases. Legati et al. have reported that mutations in XPR1 are involved in the cause of primary familial brain calcification (PFBC), a rare neuropsychiatric disorder characterized by bilateral cerebral calcium phosphate deposits due to altered phosphate export [
]. However, little is known about the role of XPR1 in cancer. Chen et al. have shown that XPR1 promotes the progression of tongue squamous cell carcinoma (TSCC) via activation of the NF-κB signaling pathway [
Xenotropic and polytropic retrovirus receptor 1 (XPR1) promotes progression of tongue squamous cell carcinoma (TSCC) via activation of NF-κB signaling.
]. Wu et al. have reported a promoting effect of XPR1 overexpression on cell proliferation, migration, and invasion in esophageal squamous cell carcinoma (ESCC) [
]. In recent years, accumulating studies have highlighted the important role of inorganic phosphate transportation and intracellular phosphate homeostasis in cancer [
]. Considering the importance of XPR1 in regulating phosphate homeostasis and the lack of understanding of the role of XPR1-regulated phosphate transportation in cancer, it is remarkably important to systemically evaluate the role of XPR1 in HNSCC and other types of cancers.
In this study, we performed an in-depth and comprehensive analysis of the role of XPR1 in HNSCC using multiple large-scale databases and bioinformatics tools. We investigated the mRNA and protein expression of XPR1 in HNSCC and normal tissues. We evaluated the potential values of XPR1 as a diagnostic and prognostic biomarker in HNSCC. We also investigated potential mechanisms contributing to the altered expression of XPR1, including promoter methylation, gene mutations, and RNA methylation. We also evaluated the significance of XPR1 in the immunological changes in HNSCC. The function and pathway enrichment analyses finally revealed the cellular functions and signaling pathways in which XPR1 and its related genes are involved. Hereby, this study shows the potential roles of XPR1 in HNSCC and provides clues for further studying the contribution of XPR1 in HNSCC and other types of cancer.
2. Materials and methods
2.1 ONCOMINE for XPR1 mRNA expression across different types of cancer
ONCOMINE (www.oncomine.org) is a bioinformatics initiative that collects, standardizes, and analyzes cancer transcriptome data to provide genome-wide expression analysis of genes [
]. In this study, we used ONCOMINE to compare the expression level of XPR1 mRNA in tumor tissues and normal tissues of different types of cancers, including HNSCC. The threshold for significance was P-value =< 1E-4, fold-change >= 2, and in the top 10% of gene rank. The R package “ggplot2” was used to visualize the analysis results.
2.2 The cancer genome atlas (TCGA) database
RNAseq data and related clinical information on HNSCC were downloaded from TCGA (https://portal.gdc.cancer.gov/) database. The HNSCC dataset includes 502 tumor tissues and 44 normal samples. The RNAseq data in level 3 HTSeq-FPKM (Fragments per Kilobase per Million) format was converted into TPM (Transcripts per Million Reads) format and then log2-converted. The converted XPR1 level was compared between the tumor and normal tissues. The HNSCC dataset used in the study complies with the publication guidelines provided by TCGA. This study does not include research directly involving human participants or animal experiments; therefore, it does not need further ethical approval and informed consent.
2.3 Human protein atlas (HPA) database for XPR1 protein expression
The HPA (www.proteinatlas.org) database is a valuable tool for studying protein localization and expression in different human tissues and cells. In the “Tissue and Pathology Atlas” module of HPA, proteins are mapped to various cell types in the context of neighboring cells, allowing for the evaluation of cell type-specific expression patterns and identification of proteins that are up- or down-regulated in corresponding cancer tissues [
]. In this study, HPA was used to determine the expression level of XPR1 protein in HNSCC tissues and normal tissues.
2.4 Evaluate XPR1 as a biomarker for HNSCC diagnosis and prognosis
The receiver operating characteristic (ROC) curve analysis is a well-established method for evaluating the performance of a biomarker in discriminating between patients and non-patients [
]. In this study, we performed the ROC analysis using the R package “pROC” to calculate the area under the ROC curve (AUC) to evaluate the sensitivity and specificity of XPR1 for the diagnosis of HNSCC. The Kaplan-Meier survival curve analysis was then used to investigate the influence of XPR1 expression on patients’ survival. We analyzed the overall survival (OS), disease-specific survival (DSS), and progress-free interval (PFI) in patients with low or high expression levels of XPR1 using the R package “survminer.” The analysis only included patients with complete follow-up and survival information in the TCGA HNSCC dataset; therefore, 218 cases for OS, 130 cases for DSS, and 194 cases for PFI were included in the analysis. The R package “survival” was used for the visualization of analysis results.
2.5 UALCAN
UALCAN (http://ualcan.path.uab.edu/) is a comprehensive and interactive web resource for analyzing cancer OMICS data, allowing users to identify biomarkers, perform in silico validation of genes of interest, and evaluate epigenetic regulation of gene expression by promoter methylation [
]. In this study, we determine the protein expression of XPR1 in different human cancers, including HNSCC, by using the UALCAN tool to analyze the Clinical Proteomic Tumor Analysis Consortium (CPTAC) database. We also used UALCAN to evaluate the overall promoter methylation level of XPR1 in HNSCC and normal tissues.
2.6 MethSurv
MethSurv (https://biit.cs.ut.ee/methsurv/) includes 7358 methylomes from 25 different types of human cancers, which enables researchers to perform multivariable survival analysis for a CpG located in or around the proximity of a query gene [
]. In this study, we identified the CpG sites in the XPR1 gene and analyzed the impact of each CpG site on the overall survival of HNSCC patients using the Kaplan-Meier analysis module in the MethSurv database. Log-rank P < 0.05 was considered statistically significant.
2.7 The cBio cancer genomics portal (cBioPortal) database for genetic alterations
The cBioPortal (https://www.cbioportal.org/) is an open-access tool for multidimensional analysis of cancer genomics datasets, including mutations, copy number alterations (CNAs), microarray- and RNA sequencing-based mRNA expression changes, DNA methylation, and protein and phosphoprotein levels [
]. In this study, we analyzed XPR1 genetic alterations in the TCGA HNSCC dataset (which included 496 samples with complete data) through the cBioPortal database. The data of XPR1 mutation, CNA, and mRNA expression changes were obtained and visualized via cBioPortal with a z-score threshold of ± 2.0.
2.8 Gene set enrichment analysis (GESA)
The HNSCC dataset in TCGA was used for the GESA assay. The patients were stratified according to the XPR1 mRNA expression level. The upper-quartile (n = 126) of HNSCC samples having the highest level of XPR1 (termed as XPR1High group) and the normal samples (n = 44) were included in the analysis. The R package “Limma” [
] was used to obtain the differentially expressed genes (DEGs) between the XPR1High group and the normal samples, and the Benjamini Hochberg method was then used for P-value correction. The screening criteria for differentially expressed genes include p.adj <0.05 and |log2FC|> 1.0. We then used the R package “clusterProfiler” [
] based on the DEGs. The reference gene collection h.all.v7.2.symbols.gmt was from the gene set database MSigDB Collections (https://www.gsea-msigdb.org/). For each analysis, gene set alignment was performed 1000 times. Terms satisfying p.adj <0.05 and false discovery rate (FDR) <0.05 were considered significantly enriched.
2.9 Functional enrichment analysis for XPR1-related genes
The R package “stat” was used to extract genes related to XPR1 in both the XPR1High group (upper-quartile, 126 samples) and XPR1Low group (lower-quartile, 126 samples). By using Spearman's rank correlation coefficient (with |cor|> 0.7 and P < 0.05 as the threshold), we identified 266 XPR1-related genes, and all of them were positively correlated with XPR1 expression. R package “org.Hs.eg.db” (version: 3.10.0) was used for ID conversion, and package “clusterProfiler” was then used to perform the gene ontology (GO) and the Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment analyses for the XPR1-related genes. A term or pathway with p.adj < 0.05 and q value < 0.05 was regarded as significantly enriched.
2.10 Co-expression analysis of XPR1 and N6 adenosine RNA methylation (m6A) regulators
Xenotropic and polytropic retrovirus receptor 1 (XPR1) promotes progression of tongue squamous cell carcinoma (TSCC) via activation of NF-κB signaling.
] was retrieved and then compared between the XPR1High group and XPR1Low group in the TCGA HNSCC dataset. And the R package “ggplot2” was used to generate a heatmap to visualize the analysis results.
The Gene_Corr module of TIMER2.0 (http://timer.cistrome.org) allows a user to discover the co-expression pattern of genes across all cancer types in TCGA [
]. We used this module to evaluate the correlation between the expression of XPR1 and the above-mentioned 16 m6A RNA methylation regulators in HNSCC. With a purity adjustment, the correlation of XPR1 and m6A regulators was determined by Spearman's correlation. A P < 0.05 was considered statistically significant.
2.11 Correlation of XPR1 with the abundance of infiltrating immune cells and the immune checkpoints in HNSCC
We also evaluated the correlations between XPR1 expression and the infiltration of 16 types of immune cells [
], including T helper 1 (Th1) cells, Th2 cells, eosinophils, T central memory (Tcm) cells, natural killer (NK) cells, T gamma delta (Tgd) cells, macrophages, T helper cells, mast cells, T follicular helper (TFH) cells, immature dendritic cells (iDC), plasmacytoid DC (pDC) cells, cytotoxic cells, CD8+ T cells, NK CD56dim cells, and B cells. XPR1 expression data were retrieved from the TCGA HNSCC dataset. Immune cell infiltration was determined by single-sample Gene Set Enrichment Analysis (ssGSEA) using the R package “Gene Set Variation Analysis (GSVA)” [
]. The association between XPR1 expression and immune cell infiltration levels was then evaluated by Spearman correlation coefficients.
Expression of XPR1 and four immune checkpoint genes, PDCD1LG2, CD274, HAVCR2, and SIGLEC15, were retrieved from the HNSCC dataset in TCGA. HNSCC patients were equally divided into the XPR1High group and XPR1Low group based on the median level of XPR1. The expression levels of the immune checkpoints were compared between the two groups, and the results were visualized with R package “ggplot2”. The correlation between the expression of XPR1 and immune checkpoints was evaluated with Spearman's rank correlation coefficient.
2.12 Statistical analysis
All statistical analysis was performed using R (version: 3.6.3). Unpaired samples were compared with the non-paired t-test; the paired samples were analyzed using paired t-test. The correlations between genes or between genes and immune cells were evaluated using Spearman's rank correlation coefficient. A P < 0.05 was considered statistically significant.
3. Results
3.1 XPR1 expression is significantly up-regulated in HNSCC
We used the ONCOMINE database to compare the transcripts level of XPR1 in tumor tissues and normal tissues across different types of cancers. We found that XPR1 mRNA expression was significantly up-regulated in four types of cancers, including head and neck cancer, lung cancer, gastric cancer, and liver cancer (Fig. 1A). The CPTAC database helps researchers to characterize the protein expression profiles of different human cancers using large-scale proteomics assays. We then applied the CPTAC database to investigate the protein expression of XPR1 across human cancers. XPR1 protein expression is significantly up-regulated in uterine corpus endometrial carcinoma, lung cancer, HNSCC, and glioblastoma (Fig. 1B). We further compared XPR1 mRNA expression between HNSCC tumor tissues and normal tissues and found that XPR1 mRNA in tumor tissues was significantly higher than that in normal tissues (Fig. 2 A and B). The protein expression of XPR1 in HNSCC was analyzed by using the HPA database. Normal tissues have low XPR1 protein levels, while the HNSCC tumor tissues have medium levels of XPR1 protein expression (Fig. 3 A and B). XPR1 protein level was also analyzed by using the CPTAC database. As shown in Fig. 3C, the XPR1 protein level is significantly up-regulated in stage II, III, and IV tumors compared to normal tissues. In summary, these results indicate that XPR1 expression is significantly up-regulated in HNSCC tumors.
Fig. 1The mRNA and protein expression of XPR1 in different types of cancers. (A) The mRNA levels of XPR1 in different types of human cancers were analyzed by using the ONCOMINE database. The expression level of XPR1 is indicated by different colors (red: overexpression, blue: down expression). (B) Protein expression of XPR1 in different types of human cancers was retrieved by analyzing the CPTAC database via the UALCAN tool. Red: tumors; blue: normal tissues. ***, P < 0.001.
Fig. 2XPR1 mRNA expression is up-regulated in the HNSCC tissues. XPR1 mRNA levels in normal and HNSCC tissues were retrieved from the TCGA HNSCC dataset. (A). XPR1 mRNA expression in all tumor and normal tissues was compared with an unpaired t-test. (B). XPR1 mRNA expression in matched tumor and normal tissues (n = 44 for each) was compared with paired t-test. ***, P < 0.001.
Fig. 3XPR1 protein expression in HNSCC tissues and normal tissues. IHC staining for XPR1 in HNSCC and normal tissues were retrieved from the HPA database. (A). IHC images of XPR1 in normal tissues, showing low-level staining of XPR1 (A1 and A2). (B). IHC images of XPR1 in HNSCC tissues, showing medium-level staining of XPR1 (B1 and B2). (C) XPR1 protein expression between HNSCC tumors of different stages and normal tissues was compared by analyzing the CPTAC database via the UALCAN tool. ***, P < 0.001.
3.2 The value of XPR1 expression in the diagnosis and prognosis of HNSCC
We then evaluated the ability of XPR1 to distinguish HNSCC patients from the healthy population by performing the ROC curve analysis. As shown in Fig. 4A, the AUC of XPR1 is 0.883 (95% CI = 0.835–0.931), indicating that XPR1 has high sensitivity and specificity as a diagnostic biomarker for HNSCC. Regarding the significance of XPR1 in the outcome of patients, the Kaplan-Meier survival analysis shows that patients with higher XPR1 expression have a significantly shorter OS (hazard ratio (HR) = 1.55, 95% confidence interval (CI) = 1.17–2.05, P = 0.002, Fig. 4B), DSS (HR = 1.59, 95% CI = 1.10–2.31, P = 0.014, Fig. 4C), and PFI (HR = 1.43, 95% CI = 1.07–1.91, P = 0.017, Fig. 4D) than these having a low XPR1 level. These results suggest that the high-level XPR1 expression is a risk factor for the development of HNSCC and is significantly related to the poor prognosis of HNSCC patients.
Fig. 4XPR1 is a promising biomarker for HNSCC diagnosis and is related to the poor outcome of HNSCC patients. (A). The ROC curve of XPR1 in the diagnosis of HNSCC. (B-D) The patients were classified as high or low XPR1 expression groups based on the “best p-value” criteria. (B). The OS of HNSCC patients with low or high mRNA levels of XPR1 was plotted using the Kaplan-Meier analysis. Low n = 76, high n = 142. (C). The DSS of HNSCC patients with low or high mRNA levels of XPR1 was plotted using the Kaplan-Meier analysis. Low n = 41, high n = 89. (D). The PFI of HNSCC patients with low or high mRNA expression of XPR1 was plotted using the Kaplan-Meier analysis. Low n = 74, high n = 120. OS: overall survival, DSS: disease-specific survival, PFI: progress-free interval.
3.3 XPR1 promoter methylation level and influence of CpG islands in the survival of HNSCC patients
Promoter methylation is an important epigenetic regulation of gene expression. We analyzed the XPR1 promoter methylation level in HNSCC tissues using the UALCAN database. We found that the promoter methylation level of XPR1 in HNSCC was significantly lower than that in normal tissues (P = 3.84E-04, Fig. 5A). The MethSurv database discovered 17 CpG sites in the XPR1 gene (Fig. 5B). We then investigated the DNA methylation level and the prognostic value of each CpG site using the MethSurv database (Fig. 5B and Table 1). Among these CpG sites, five CpGs are significantly related to the prognosis of HNSCC patients, including cg11538848, cg20948051, cg23675362, cg18440470, and cg22026687. Low methylation levels of cg11538848 (HR = 0.734, P = 0.018, Fig. 5C) and cg20948051 (HR = 0.746, P = 0.039, Fig. 5D) and high methylation levels of cg23675362 (HR = 1.527, P = 0.002, Fig. 5E), cg18440470 (HR = 1.346, P = 0.028, Fig. 5F), and cg22026687 (HR = 1.511, P = 0.0035, Fig. 5G) are significantly correlated with the poor prognosis of the HNSCC patients, suggesting that altered methylation of these CpG sites alone or in combination may serve as prognostic biomarkers for HNSCC patients.
Fig. 5XPR1 DNA methylation in HNSCC and the influence on the survival of patients. (A). The methylation level of the XPR1 promoter in normal tissues and HNSCC was evaluated by UALCAN. The comparison of the methylation level of XPR1 promoter between normal and HNSCC patients includes five probes around TSS200 (cg07397093, cg23675362, cg19905861, cg08638395, and cg01815035) and two probes around TSS 1500 (cg22026687 and cg19763210). (B). The heat map generated by the MethSurv database depicts the clustering of the CpG methylation levels within the XPR1 gene, which was calculated by using the average linkage method with correlation distance. The heatmap includes the methylation data of 527 HNSCC samples. Rows correspond to the CpGs, and the columns correspond to the patients. Various colorful side boxes are used to characterize the ethnicity, race, age, event, relation to UCSC_CpG_island, and UCSC_refGene_Group. The methylation levels are illustrated by color. Red to blue: high expression to low expression (1 = fully methylated; 0 = fully unmethylated). (C-G). The effects of the methylation of five CpGs, (C) Body-S_Shelf-cg11538848, (D) Body-Open_Sea-cg20948051, (E) TSS200-Island-cg23675362, (F) Body-Island_Sea-cg18440470, and (G) TSS1500-N_Shore-cg22026687, of XPR1 on the overall survival of HNSCC patients, were evaluated by the Kaplan-Meier test module in MethSurv. A log-rank P-value < 0.05 was considered significantly different.
Analysis of the cBioPortal database finds that 10% (50/496) of HNSCC patients have genetic changes in the XPR1 gene (Fig. 6A and B), including gene mutations, copy number alterations (CNA, amplification, and deletion), and mRNA changes. In more details, missense mutation accounts for 1.81% (9/496), amplification accounts for 0.81% (4/496), deep deletion accounts for 0.20% (1/496), and mRNA high accounts for 7.46% (37/496) of all genetic alterations. The locations of the missense mutations in XPR1 protein mainly focus on the SPX and EXS domains (Fig. 6C).
Fig. 6Genetic alterations of XPR1 in HNSCC. The genetic mutations and alterations of XPR1 in HNSCC were determined using cBioPortal. (A and B). XPR1 genetic alternation type and frequency in HNSCC. The types of alterations include mutation (green), amplification (red), deep deletion (blue), mRNA high (pink), and multiple alternations (gray). (C). The altered amino acids are caused by genetic mutations in the XPR1 protein. The colored graphic represents the domains of the XPR1 protein.
3.5 GESA for the DEGs between XPR1High HNSCC tissues and normal tissues
Approximately 17,300 DEGs were identified between the XPR1High HNSCC tissues (highest quantile, 126 samples) and the normal tissues in TCGA dataset. The GSEA analysis on the DEGs identified 32 significantly enriched hallmark terms. The top nine terms with the highest normalized enrichment score (NES) include epithelial mesenchymal transition (NES = 2.636, p.adj = 0.002, FDR < 0.001, Fig. 7A), E2F targets (NES = 2.426, p.adj = 0.002, FDR < 0.001, Fig. 7B), angiogenesis (NES = 2.313, p.adj = 0.002, FDR < 0.001, Fig. 7C), G2M checkpoint (NES = 2.282, p.adj = 0.002, FDR < 0.001, Fig. 7D), interferon alpha response (NES = 2.275, p.adj = 0.002, FDR < 0.001, Fig. 7E), interferon gamma response (NES = 2.147, p.adj = 0.002, FDR < 0.001, Fig. 7F), coagulation (NES = 1.881, p .adj = 0.002, FDR < 0.001, Fig. 7G), inflammatory response (NES = 1.862, p.adj = 0.002, FDR < 0.001, Fig. 7H), and mTORC1 signaling (NES = 1.858, p.adj = 0.002, FDR < 0.001, Fig. 7I). The enriched hallmark terms indicate that XPR1 and the DEGs play important roles in critical cellular functions in the development of HNSCC, such as invasion and metastasis, replicative immortality, genome instability and mutation, angiogenesis, evading growth suppressors, resisting cell death, sustaining proliferative signaling, and tumor promoting inflammation.
Fig. 7The top nine enriched hallmarks by GESA. The significantly enriched hallmarks of differentially expressed genes were determined by the GESA assay. The top nine enriched terms with the highest normalized enrichment score (NES) are listed here: (A) Epithelial-mesenchymal transition, (B) E2F targets, (C) Angiogenesis, (D) G2M checkpoint, (E) Interferon-alpha response, (F) Interferon-gamma response, (G) Coagulation, (H) Inflammatory response, and (I) mTORC1 signaling.
3.6 Functional enrichment analysis for the XPR1-related DEGs
To explore the biological functions of XPR1 and its related DEGs in HNSCC, we performed the GO analysis and KEGG enrichment analysis. The GO analysis reveals that the biological processes associated with XPR1-related DEGs include endomembrane system organization, positive regulation of the catabolic process, nucleocytoplasmic transport, TGF-β, ERBB, and EGFR signaling pathways, and mRNA 3’-end processing (Fig. 8A). The cellular components associated with XPR1-related DEGs include cell-substrate junction, focal adhesion, cell leading edge, transport vesicle, and nuclear speck (Fig. 8B). Protein serine/threonine kinase activity, Ras and Rho GTPase binding, ubiquitin-like protein transferase activity, ubiquitin-protein transferase activity, and cell adhesion molecule binding are significantly enriched molecular functions in the GO analysis (Fig. 8C). The KEGG analysis shows these DEGs are significantly enriched in the signaling pathways involving actin cytoskeleton, endocytosis, focal adhesion, MAPK signaling pathway, Proteoglycans in cancer, and viral carcinogenesis (Fig. 8D). The enriched GO terms and KEGG pathways indicate that XPR1 and its related DEGs are involved in multiple biological functions and pathways implicated in the invasion, metastasis, and development of malignant tumors, suggesting that they may play an important role in the formation and development of HNSCC.
Fig. 8GO and KEGG enrichment analyses for the XPR1-related DEGs. (A-C). The bubble plots show the GO analysis of XPR1-related DEGs. (A) biological process terms, (B) cellular component terms, (C) molecular function terms. (D). The bubble plots show the top 10 KEGG pathways enriched for XPR1-related DEGs.
]. RNA methylation, similar to DNA or protein modifications, is regulated by various types of regulators, including methyltransferases (“writers”), demethylases (“erasers”), and RNA binding proteins (“readers”) [
]. The alterations of m6A methylation have been shown to affect tumor development by modulating the mRNA and protein levels of specific oncogenes or suppressor genes [
]. We analyzed the expression of 16 m6A regulators (six “writers”: KIAA1429, ZC3H13, CBLL1, RBM15, METTL14, WTAP; two “erasers”: FTO and ALKBH5; eight “readers”: YTHDF3, LRPPRC, YTHDF1, IGF2BP2, YTHDF2, FMR1, YTHDC1, and IGF2BP3) in the XPR1High (upper quantile, n = 126) and XPR1Low (lower quantile, n = 126) HNSCC tissues. As shown in Fig. 9, the 16 m6A regulator genes are all significantly overexpressed in the XPR1High group compared with the XPR1Low group (all P < 0.001). We then used the Gene_Corr module of the TIMER 2.0 database to further explore the correlation between XPR1 and the m6A regulators in HNSCC. We discover that the XPR1 level is positively correlated with the expression of all the 16 m6A regulator genes (all P < 0.05, Fig. 10 A–C, Table 2).
Fig. 9The differential expression of m6A regulators in XPR1Low and XPR1High tissues. The heat map illustrates the expression of 16 m6A regulators, KIAA1429, ZC3H13, CBLL1, METTL14, RBM15, WTAP, YTHDF3, LRPPRC, YTHDF1, IGF2BP2, YTHDF2, FMR1, YTHDC1, IGF2BP3, FTO, and ALKBH5, in the XPR1High and XPR1Low HNSCC tissues. Their expression in the XPR1High group is significantly higher than that in the XPR1Low group. ***, P < 0.001.
Fig. 10The correlation between XPR1 and m6A RNA methylation regulators. (A). The correlation between XPR1 and m6A “writers”, including KIAA1429, ZC3H13, CBLL1, RBM15, METTL14, and WTAP. (B). The correlation between XPR1 and m6A “readers”: YTHDF3, LRPPRC, YTHDF1, IGF2BP2, YTHDF2, FMR1, YTHDC1, and IGF2BP3. (C). The correlation between XPR1 and m6A “erasers”: FTO and ALKBH5.
]. We then analyzed the correlation between XPR1 expression and the infiltration of 16 types of tumor-infiltrating immune cells in HNSCC, including Th1 cells, Th2 cells, eosinophils, Tcm cells, NK cells, Tgd cells, macrophages, T helper cells, mast cells, TFH cells, iDC, pDC cells, cytotoxic cells, CD8+ T cells, NK CD56dim cells, and B cells. As shown in Fig. 11, XPR1 has a positive correlation with the infiltration of Th2 cells, Eosinophils, Tcm, T helper cells, NK cells, Tgd, Macrophages, Mast cells, Th1 cells, TFH, iDC (all P < 0.05), while XPR1 is negatively correlated with the infiltration of pDC, Cytotoxic cells, CD8 T cells, NK CD56dim cells and B cells (all P < 0.05). Immune checkpoints are inhibitory regulators of the immune system, which are often overexpressed on tumor cells or non-tumor cells within the tumor microenvironment, leading to the compromised ability of the immune system to initiate effective anti-tumor responses [
]. We then investigated the expression of four immune checkpoints, PDCD1LG2, CD274, HAVCR2, and SIGLEC15, in HNSCC and evaluated the correlation between their expressions and XPR1 level. We found that the expression of PDCD1LG2, CD274, HAVCR2, and SIGLEC15 in the XPR1high tissues was significantly higher than that in the XPR1low tissues (Fig. 12), and they all have a positive correlation with the expression level of XPR1 in HNSCC (Table 3).
Fig. 11XPR1 expression is related to the immune cell infiltration in HNSCC. The correlation between XPR1 expression level and 16 types of infiltrating immune cells is calculated by the Spearman correlation analysis and illustrated by a lollipop chart.
Fig. 12The expression of immune checkpoints is up-regulated in XPR1high HNSCC tissues. HNSCC patients were equally divided into the XPR1High group and XPR1Low group based on the median level of XPR1. A heat map illustrates the mRNA expression of four immune checkpoint genes, PDCD1LG2, CD274, HAVCR2, and SIGLEC15, in XPR1high and XPR1low HNSCC tissues. ***, P < 0.001.
Table 3Correlation between XPR1 and the expression of immune checkpoints in HNSCC.
Immune Checkpoints
r
P-value
PDCD1LG2
0.266
<0.001
CD274
0.195
<0.001
HAVCR2
0.179
<0.001
SIGLEC15
0.156
<0.001
XPR1: xenotropic and polytropic retrovirus receptor 1; HNSCC: head and neck squamous cell carcinoma. The correlation between XPR1 and immune checkpoints was determined using Spearman correlation analysis.
HNSCC accounts for more than 90% of the cases of head and neck cancer, the sixth most commonly diagnosed cancer worldwide. The overall survival of HNSCC remains stubbornly low, despite the advances in diagnosis and therapy in recent years. Therefore, further understanding of the mechanisms underlying the development of HNSCC and discovering novel therapeutic targets are necessary to improve the outcome of the patients.
In recent years, the “growth rate hypothesis” proposed that tumor cells have high phosphorus concentration to meet the need to form a greater amount of ribosomes to produce proteins that support the accelerated growth of cancer cells [
]. And a growing number of studies have highlighted the important role of inorganic phosphate transportation and intracellular phosphate homeostasis in cancer development [
]. XPR1 protein is composed of 696 amino acids and has multiple transmembrane-spanning domains. Besides its first identified function as a cell-surface receptor for xenotropic and polytropic classes of murine leukemia viruses (MLV) [
]. However, the roles of XPR1 in cancer are rarely studied. As far as we know, this is the first study that comprehensively investigated the roles of XPR1 in the development, diagnosis, and prognosis of HNSCC and explored the potential cellular functions of XPR1 in HNSCC.
We found that XPR1 mRNA and protein expression is up-regulated in HNSCC. XPR1 mRNA is also up-regulated in lung cancer, gastric cancer, and liver cancer. XPR1 protein expression is up-regulated in uterine corpus endometrial carcinoma, lung cancer, and glioblastoma as well. These results are consistent with the studies by other researchers. Chen et al. reported that XPR1 mRNA and protein are significantly up-regulated in the TSCC tissues [
Xenotropic and polytropic retrovirus receptor 1 (XPR1) promotes progression of tongue squamous cell carcinoma (TSCC) via activation of NF-κB signaling.
]. HNSCC comprises cancers originating from different organs in the head and neck region. We also investigated XPR1 mRNA expression in HNSCCs of different origins to see if up-regulated XPR1 in HNSCC was ascribed to a specific type of HNSCC tumor. As shown in Table 4, XPR1 is overexpressed in thyroid papillary carcinoma [
], indicating that XPR1 is overexpressed in HNSCC tumors originating from different organs in the head and neck region. These results suggest that XPR1 may serve as a biomarker for assisting the diagnosis of HNSCC and predicting the outcome of patients.
Table 4XPR1 expression in different subtypes of HNSCC.
In further analyses, we found that XPR1 has high specificity and accuracy as a diagnostic biomarker for HNSCC by analyzing the ROC curve. Additionally, patients with higher XPR1 expression had a significantly shorter OS, DSS, and PFI than those having a low level of XPR1, suggesting that high-level expression of XPR1 is a risk factor for the development of HNSCC and significantly related to the poor prognosis of HNSCC patients. This result is consistent with a study by Chen et al. [
Xenotropic and polytropic retrovirus receptor 1 (XPR1) promotes progression of tongue squamous cell carcinoma (TSCC) via activation of NF-κB signaling.
]. They found that XPR1 overexpression is correlated with poor prognosis in TSCC. We then investigated the possible mechanism for the up-regulated XPR1 in HNSCC. Using the UALCAN database, we found that the promoter methylation level of XPR1 in HNSCC was significantly lower than that of normal tissues. Methylation of the promoter of a gene prevents the binding of RNA polymerases and other transcriptional factors to the promoter region, thereby inhibiting the transcription of a specific gene; thus, the lowered promoter methylation may result in up-regulated expression of a gene [
]. However, regarding XPR1 in HNSCC, both normal tissues and HNSCC have very low promoter methylation levels (with a beta value less than 0.2); although the methylation levels of XPR1 promoter are statistically different between normal and tumor tissues, this difference is unlikely to account for the up-regulated expression of XPR1. Other mechanisms may cause increased expression of XPR1 in HNSCC, such as the up-regulated activity of transcription factors and lowered RNA and protein degradation. We need to further investigate the possible mechanisms accounting for the up-regulated expression of XPR1 in HNSCC in our future studies.
Genetic alterations of genes involved in important cellular processes may cause malfunction of the corresponding genes and finally lead to cancer. We found that 10% of HNSCC patients had genetic changes in the XPR1 gene, which mainly are mutations (missense mutation (1.81%), amplification (0.81%), deep deletion (0.20%)), copy number changes, and mRNA changes (7.46%) in the cBioPortal analysis. The missense mutations in XPR1 protein are mainly in the SPX and EXS domains. However, the influence of these changes in the functions of XPR1 is still unknown and hereby needs to be investigated in future studies.
Considering the essential role of XPR1 in regulating intracellular phosphate and the clinical relevance of XPR1 in HNSCC, we investigated the XPR1-involved cellular processes and signaling pathways by multiple bioinformatics analyses. We identified 17,300 DEGs between the highest quantile of XPR1 expressing HNSCC tissues and the normal tissues in the TCGA dataset. The GSEA analysis on these genes identified 32 significantly enriched hallmark terms, including epithelial-mesenchymal transition, E2F targets, angiogenesis, G2M checkpoint, interferon-alpha response, interferon-gamma response, coagulation, inflammatory response, mTORC1 signaling, and so on. The GO analysis revealed that the biological processes associated with XPR1-related DEGs include endomembrane system organization, positive regulation of the catabolic process, nucleocytoplasmic transport, etc. The enriched cellular components include cell-substrate junction, focal adhesion, cell leading edge, transport vesicle, and nuclear speck. The enriched molecular functions are protein serine/threonine kinase activity, Ras and Rho GTPase binding, ubiquitin-like protein transferase activity, ubiquitin-protein transferase activity, and cell adhesion molecule binding. The KEGG analysis showed these DEGs are significantly enriched in the signaling pathways regulating actin cytoskeleton, endocytosis, focal adhesion, MAPK signaling pathway, Proteoglycans in cancer, viral carcinogenesis, etc. In summary, these enrichment assays indicate that XPR1 is involved in multiple biological functions and pathways involving the invasion, metastasis, and development of malignant tumors, suggesting that XPR1 may play an important role in the formation and development of HNSCC. Regarding the cellular functions of XPR1, Wu et al. have shown that overexpression of XPR1 promotes cell proliferation, migration, and invasion in esophageal squamous cell carcinoma, and XPR1 is under direct regulation by miR-375 [
Xenotropic and polytropic retrovirus receptor 1 (XPR1) promotes progression of tongue squamous cell carcinoma (TSCC) via activation of NF-κB signaling.
]. Notably, the cellular functions of XPR1 are poorly studied. Only a few studies have reported its other functions besides a phosphate transporter. Hereby, a series of studies need to be conducted to fully characterize the functions of XPR1 in the future.
A large number of studies have shown that m6A is the most common type of mRNA modification in eukaryotes [
]. The m6A modification of RNA plays an important role in the biology of mRNAs, including nuclear export, degradation, translation, and alternative splicing [
]. The m6A modification is a dynamic and reversible process, tightly regulated by methyltransferases (“writers”), demethylases (“erasers”), and m6A-binding proteins (“readers”) [
]. In this study, we analyzed the expression of six “writers” (KIAA1429, ZC3H13, CBLL1, RBM15, METTL14, and WTAP), two “erasers” (FTO and ALKBH5), and eight “readers” (YTHDF3, LRPPRC, YTHDF1, IGF2BP2, YTHDF2, FMR1, YTHDC1, and IGF2BP3) in the XPR1High (upper quantile) and XPR1Low (lower quantile) HNSCC tissues. We found that all these m6A regulators are significantly overexpressed in the XPR1High tissues. Furthermore, the XPR1 level is positively correlated with the expression of all these m6A regulator genes in the TIMER 2.0 database, suggesting that XPR1 may exert its function through regulating m6A RNA modification. As far as we know, this is the first study that reveals the association between XPR1 and RNA m6A methylation. However, their relationship needs to be validated in cell- and animal-based experiments in the future.
The immune infiltration of tumors is closely related to the clinical outcomes of cancer patients [
]. We found that XPR1 has a positive correlation with the infiltration of Th2 cells, Eosinophils, Tcm, T helper cells, NK cells, Tgd, Macrophages, Mast cells, Th1 cells, TFH, iDC, but XPR1 is negatively associated with the infiltration of pDC, Cytotoxic cells, CD8 T cells, NK CD56dim cells and B cells. Since cellular immunity plays a fundamental role in the anti-tumor immune responses, these results suggest that up-regulated XPR1 may impair the anti-tumor immunity by decreasing the infiltration of the main effectors of cellular immunity, such as CD8 T cells and NK cells. Immune checkpoints are inhibitory regulators of the immune system, which are often overexpressed on tumor cells or non-tumor cells within the tumor microenvironment. We found that the expression of four immune checkpoint genes, PDCD1LG2, CD274, HAVCR2, and SIGLEC15, is associated with a high expression level of XPR1 in HNSCC. However, no study on the role of XPR1 in cancer immunology has been reported; hereby, we need to conduct cell- and aminal-based experiments to characterize the role of XPR1 in anti-cancer immunity.
The main limitation of this study is that the results are based on bioinformatics analysis; no cell- and animal-based experiments are conducted. The results of this study, however, are based on the comprehensive analysis of large-scale databases to reduce the bias of this study. Same as other bioinformatics studies, the conclusions of this study definitely have to be validated by experiments in the future.
5. Conclusions
XPR1 is up-regulated in the HNSCC tissues and is closely associated with the poor prognosis of HNSCC patients. XPR1 is a potential biomarker for the diagnosis of HNSCC with high sensitivity and specificity. XPR1 is involved in various important cellular procedures and signaling pathways in addition to phosphate transportation. XPR1 is also potentially involved in m6A RNA modification and anti-tumor immunity. These results set a solid basis for further characterizing the functions of XPR1 in cancer formation and development using cell- and animal-based studies.
Funding
This project was supported by funds from the Key R&D Project of the Shaanxi Provincial Department of Science and Technology (#2019SF-176).
Declarations
Ethics approval and consent to participate
Not applicable.
Consent for publication
Not applicable.
Availability of data and materials
Not applicable.
CRediT authorship contribution statement
Lin Wang: Funding acquisition, Conceptualization, Visualization, Data curation, Formal analysis, Writing – original draft.
Decleration of Competing Interest
None.
Acknowledgments
Not applicable.
References
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The global incidence of lip, oral cavity, and pharyngeal cancers by subsite in 2012.
Xenotropic and polytropic retrovirus receptor 1 (XPR1) promotes progression of tongue squamous cell carcinoma (TSCC) via activation of NF-κB signaling.
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