LPAR2 is correlated with different prognosis and immune infiltrates in head and neck squamous cell carcinoma and kidney renal clear cell carcinoma

Background: LPA and its receptors represent two key players in regulating cancer progression. Recent findings suggest that upregulation of lysophosphatidic acid receptor 2(LPAR2) may play a role in carcinogenesis. But there are few studies on the relationship between LPAR2 and tumor immune microenvironment. Methods: In this study, we analyzed LPAR2 expression in pan tumors via the Oncomine, Tumor Immune Estimation Resource (TIMER), and UALCAN . We investigated the influence of LPAR2 on clinical prognosis from Kaplan-Meier plotter (K-M plotter), Gene Expression Profiling Interactive Analysis (GEPIA), UALCAN and Human Protein Atlas (HPA) . We also examined the relationship of Then we explored the relationship between LPAR2 expression and prognosis in HNSC and KIRC patients with different clinical characteristics via K-M plotter. The correlations between LPAR2 and cancer immune infiltrates was examined via TIMER. In addition, correlations between the expression of LPAR2 and gene markers of immune infiltrates were analyzed by TIMER and GEPIA. We also used the cBioPortal to calculate mutations, methylations and altered neighbor genes of LPAR2. Results: We found that LPAR2 different expression was significantly related with the outcome of multiple types of cancer from The Cancer Genome Atlas (TCGA), particularly in head and neck squamous cell carcinoma (HNSC) and kidney renal clear cell carcinoma (KIRC). Furthermore, high expression levels of LPAR2 were found to be significantly associated with a variety of immune markers in particular immune cell subsets in HNSC and KIRC. Conclusions: Our finding indicates that high LPAR2 expression playing significantly different prognostic roles in HNSC and KIRC, might be due to associate with different immune markers. And LPAR2 is correlated with tumor immune cell infiltration and is a valuable prognostic biomarker in HNSC and KIRC patients. Cor, R value of Spearman’s correlation; None, correlation without adjustment. Purity, correlation adjusted by purity. *P <0 .01(1e-02); **P < 0.001(1e-03); ***P < 0.0001(1e-04). Abbreviations: HNSC: Head and Neck squamous cell carcinoma; carcinoma; tumor-correlated macrophage;

Although there are many studies on the expression and function of LPAR1 and LPAR3 in several tumors, the research of LPAR2 is fewer. Several studies find that LPAR2 is aberrantly expressed in several tumors, such as breast cancer, colorectal cancer, kidney cancer and pancreatic cancer [15][16][17][18] .
Some research reveal LPAR2 can promote a robust activation of RhoA to mediate cell migration [19] .
Recent report indicates LPAR2 can regulate the cell-cell adhesion level of neural crest cells by internalization of N-cadherin downstream [20] . A literature also reports LPAR2 is significantly associated with LPA-induced IL-6 and IL-8 expression, which promoted BC progression [21] .
However, the mechanisms of action of the LPAR2 in tumors appear diverse and are not well understood.
In this study, we systematic investigated the expression of LPAR2 and its relationship with prognosis of pan tumors via the Oncomine, Tumor Immune Estimation Resource (TIMER), UALCAN, GEPIA, Human Protein Atlas (HPA), and K-M plotter. We examined the relationship of expression of LPAR2 and clinical and molecular criteria in by UALCAN. Then we explored the relationship between LPAR2 expression and HNSC and KIRC patient prognosis with different clinical characteristics via K-M plotter. Next, we analyzed the correlation of LPAR2 and tumorinfiltrating immune cells in microenvironments of pan tumors via TIMER and GEPIA. Finally, we used the cBioPortal online tool to analyze alterations, mutations, methylations and pathways of LPAR2. This study showed a potential LPAR2 expression mechanism and different prognostic roles in HNSC and KIRC, LPAR2 is a key factor in HNSC and KIRC immune microenvironment.

Oncomine database analysis
The online cancer microarray database (ONCOMINE) gene expression array dataset (www.oncomine.org) compiled 715 gene expression data in 86,733 samples. We analyzed the mRNA expression levels of LPAR2 in pan cancers by ONCIMINE. The Student's t test was used to compare the mRNA expression of LPAR2 in different normal specimens and that in cancers specimens, P value for difference. The fold change was 1.5. The cut-off of P value was defined as 0.0001.

TIMER database analysis
TIMER (https://cistrome.shinyapps.io/timer/) database comprise six tumor-infiltrating immune subsets [22] . The levels of six subsets are precalculated for 10,897 tumors across 32 cancer types from The Cancer Genome Atlas (TCGA). The database analyzed gene expression and tumor immune infiltration (B cells, CD4+ T cells, CD8+ T cells, Neutrophils, Macrophages and Dendritic cells) in various cancers. We used TIMER to analyze the mRNA expression of LPAR2 in various cancers， and we explored the relationship between this LPAR2 expression and the degree of infiltration by the specific immune cell subsets. We next explored the difference in survival of cancer patients with gene expression or immune cell infiltration by Kaplan-Meier survival analysis. Finally, we evaluated how LPAR2 expression associated with the expression of specific immune infiltrating cell subsets markers.

UALCAN
UALCAN (http://ualcan.path.uab.edu/index.html) is an interactive web resource for analyzing cancer OMICS data [23] . It comprises publicly available cancer OMICS data (TCGA, MET500 and CPTAC). We used UALCAN to study the mRNA expression levels of LPAR2 in different cancers specimens and that in normal specimens in TCGA database and the relationship between the expression and different clinical characteristic. Then we analyzed the prognostic values of LPAR2 in pan cancers by UALCAN, and the relationship between the expression of LPAR2 and prognosis in patients with different clinical characteristic.

Kaplan-Meier plotter analysis
Kaplan-Meier plotter(KM plotter; http://kmplot.com/analysis/) is an online database, which containing microarray gene expression data and survival information derived from European Genome-Phenome Archive, Gene Expression Omnibus and TCGA, offering a way to explore the influence of multiple genes on the survival rate of 21 different types of cancers in a large number of samples for different cancers cohorts [24] . We used Kaplan-Meier plotter to analyze the prognostic values of LPAR2 in pan cancers. We also explored the relationship between the expression of LPAR2 and prognosis in patients with different clinical characteristic.

GEPIA2 database analysis
Gene Expression Profiling Interactive Analysis (GEPIA) is using standard processing pipelines to analyze the RNA sequencing expression data of 8,587 normal samples and 9,736 tumors from GTEx and TCGA projects. GEPIA2 is a updated version of GEPIA ，Via GEPIA2, we assessed the relationship between the mRNA expression levels of LPAR2 and patient prognosis in pan cancers, and the link between expression of LPAR2 with the expression of immune cell infiltration particular markers of tumors.

HPA database
We used the human protein atlas database (HPA) (www.proteinatlas.org) to analyze protein expression of LPAR2 between HNSC tissues, KIRC tissues with their corresponding normal tissues [25] . The HPA provides access to 32 human tissues and their protein expression profiles and uses antibody profiling to accurately assess protein localization. Additionally, the HPA provides measurements of RNA levels. In this study, representative immunohistochemistry images of different LPAR2 in HNSC and KIRC tissues and corresponding normal tissues were directly visualized by HPA, and we assessed the relationship between the protien expression levels of LPAR2 and patient prognosis in HNSC and KIRC cancers.

TCGA data and cBioPortal
The cBioPortal for Cancer Genomics provides analysis, visualization, and downloading of cancer genomics datasets [26] . By using the cBioPortal for Cancer Genomics (www.cbioportal.org), the HNBC dataset (TCGA, Firehose Legacy) and the KIRC dataset (TCGA, Firehose Legacy), which contains including histopathological data of 528 HNBC patients and 537 KIRC patients, was selected for LPAR2 analysis. The genomic profiles included mutations, methylations, mRNA expression zscores (RNA Seq V2 RSEM), protein expression Z-scores (RPPA) and putative copy-number alterations (CNA) from GISTIC. Co-expression were calculated according to the online instructions of cBioPortal.

Statistical analysis
We analyzed data by a log-rank test, such as fold-change, Hazard ratio(HR), and P-values. We

Assessment of LPAR2 expression in different cancers and normal tissues
First, via the Oncomine database, we explored the mRNA expression levels of LPAR2 in pan tumors and normal tissue types. The results showed that in some tumors, such as bladder cancer, brain and CNS cancer, breast cancer, colorectal cancer, kidney cancer, lung cancer and lymphoma, the expression levels of LPAR2 were higher than normal tissue control ( Figure 1). In kidney cancer, leukemia, lung cancer, lymphoma and sarcoma tissues, LPAR2 expression was lower than normal tissue controls ( Figure 1). Table 1 summarizes the detailed findings of specific tumor types. We further assessed how LPAR2 expression differs in pan tumor types in TCGA databases via TIMER.

The relationship between the expression of LPAR2 and cancer patient prognosis
We employed the Kaplan-Meier plotter database to explore correlation between the expression levels of LPAR2 and the survival of patients in pan tumors and normal tissue types ( Figure S1). A few cancer types, such as BLCA, BRCA, CESC, HNSC, KIRC, STAD, THYM and UCEC, exhibited a significant correlation between LPAR2 expression levels and patient prognosis, (Figure 4) .We   (Figure11 N, O).
These results suggested that LPAR2 expression levels could impact the prognosis in HNSC patients with tumor stage and grade status, but had no significant difference in KIRC patients.
Upregulated expression levels of LPAR2 brought good outcome in male HNSC patients or LPAR2 mutation burden low HNSC patients. In addition, LPAR2 expression levels were significant associated with prognosis in white HNSC and KIRC patients.

The expression of LPAR2 associated with immune cell infiltration in HNSC and KIRC.
Tumor-infiltrating lymphocytes are independent predictors of tumor stage, grade and lymph node status in cancers [27,28] . Therefore, we used the TIMER database to explore the relationship between LPAR2 expression and the degree of immune cell infiltration in HNSC and KIRC ( Figure 12). Our finding suggested that LPAR2 expression was a significant correlated with tumor purity levels (R   Figure 14A)  Table 2). Next, we explored the relationship between expression of LPAR2 and the expression levels of these markers via the GEPIA database. The correlations between LPAR2 expression and these markers were similar to those in TIMER ( Table   3). These findings suggested that LPAR2 was significantly related with immune infiltrating cells in HNSC and KIRC, and it seemed that LPAR2 played a significant role in HNSC and KIRC immune microenvironment.

Alterations, mutations and methylations in LPAR2 and its frequently altered neighbor genes in patients with HNSC and KIRC.
We analyzed the LPAR2 alterations by using the cBioPortal online tool in the HNBC dataset (TCGA, Firehose Legacy) and the KIRC dataset (TCGA, Firehose Legacy). LPAR2 altered in 0.6% of 528 patients with HNSC and did not alter in 537 KIRC patients ( Figure 12A, B). We also calculated

DISCUSSION
LPA are growth-factor-like phospholipids, widely exists in human tissues and fluids [21] . LPA participate in many biological behaviors, such as migration, proliferation, inflammation, angiogenesis, survival, and many more [29] . LPA has several G-protein coupled receptors, named as lysophosphatidic acid receptors (LPARs) [5,8] . LPAR2 belongs to the endothelial differentiation gene family and contains 351 amino acids [21,30] . LPAR2 is unique at the C-terminus, in the proximal region it contains several putative palmitoylated cysteine residues and a dileucine motif [31] . A few studies have suggested that LPA2 is associated with several cancers , such as breast cancer [18,32,33] , colon cancer [19] , ovarian cancer [34] and stomach cancer [35] . These studies indicate LPAR2 expression is important in cancer biology, it maybe promote gene transcription and cell proliferation in tumor microenvironment [35] .But how LPAR2 acts in tumor microenvironment is not clear at this point.
After the traditional treatment of cancer, cancer immunotherapy has become an important therapy due to its good efficacy and few side-effects. But immunotherapy has not been well studied or applied in HNSC and KIRC. Since immunotherapy mainly targets tumor immune microenvironment, in this study, we explored the effects of LPAR2 on tumor microenvironment in HNSC and KIRC.
In this study, we examined the mRNA and protein expression levels of LPAR2 in pan tumors and corresponding normal tissues using datasets from Oncomine, TCGA in TIMER, ULACAN and HPA databases. The expression levels of LPAR2 were differentially between tumor tissues and normal tissues in multiple cancer types (Figures 1-3,6)  Then, we employed the KM plotter, GEPIA, HPV and TCGA databases to explore the critical role of LPAR2 in patient outcomes in multiple cancer types. We found that high LPAR2 expression was significantly correlated to a poorer prognosis in KIRC (Figure 4, 5,7). But interestingly, we found that the high expression level of LPAR2 was strong associated with improved prognosis in HNSC  Table 2). Remarkably, LPAR2 expression had closely relationship with INOS of M1 macrophage, STAT5A of Th2 and BCL6 of Tfh (P < 0.0001, Cor > 0.2, Figure 14A). These results indicate LPAR2 may promote the polarization of macrophages to M1 macrophages and regulate T cell responses. BCL6 recognizes DNA target sequences similar to those recognized by STAT5 [36] .
Some research found that STAT5A inhibits breast cancer cell invasion and metastasis [37] . LPAR2 may play role in HNSC by interacting STAT5A and BCL6 via prolactin-Jak2-Stat5a signal network [36] . It

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Competing interests
The authors declare that they have no competing interests.

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Author contributions
KS and ZL performed the analysis of the data. KS and RC wrote the manuscript. KS and JL designed the study.
All authors read and approved the manuscript.