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. 2024 Mar 9;10(6):e27906. doi: 10.1016/j.heliyon.2024.e27906

Combination of theoretical analysis and experiments: Exploring the role of PLA2G7 in human cancers, including renal cancer

Jun Xie a, Li Zhu a, Xutao Yang a, Fengfei Yu a, Bingfu Fan b, Yibo Wu c, Zonglang Zhou d,⁎⁎, Weiqiang Lin a,⁎⁎⁎, Yi Yang a,⁎
PMCID: PMC10950723  PMID: 38509948

Abstract

Background

The pivotal role of phospholipase A2 group VII (PLA2G7) has been identified in specific human cancers, such as prostate cancer, diffuse large B cell lymphoma, and melanoma. Given PLA2G7's significant involvement in established tumors, exploring its role in other cancers is highly relevant.

Methods

In this study, we acquired and analyzed data from The Cancer Genome Atlas database, the UCSC XENA website, and other online platforms including Gene Set Cancer Analysis, cBioPortal, Tumor Immune Estimation Resource, and TISIDB to investigate PLA2G7's role in human cancers, including renal cancer. Furthermore, in vitro experiments, including immunofluorescence, western blotting, and CCK-8 assays, were conducted to elucidate PLA2G7's role in renal cancer. Finally, the relationship between PLA2G7 and various drug sensitivity was explored.

Results

Our findings demonstrate that PLA2G7 is highly expressed and may serve as a valuable candidate biomarker in pan-cancer. PLA2G7 exhibits distinct alteration frequencies across human cancers and is correlated with tumor mutation burden, tumor microenvironment, DNA stemness score, RNA stemness score, tumorigenesis, tumor immunity, and microsatellite instability in pan-cancer. Immunofluorescence and western blotting revealed a relative high level of PLA2G7 protein in renal cancer cell lines (ACHN and 786-O), predominantly localized in the cytoplasm. Treatment with a PLA2G7 gene inhibitor (darapladib) significantly decreased the viability of ACHN and 786-O cell lines. Additionally, we observed an association between PLA2G7 mRNA levels and various drug sensitivity.

Conclusions

Our study suggests that PLA2G7 has the potential to serve as a valuable biomarker and therapeutic target for cancer, particularly in the context of renal cancer.

Keywords: PLA2G7, Tumor immunity, Pan-cancer, Renal cancer, Biomarker

1. Introduction

Cancer remains a formidable global health challenge due to its clandestine onset, marked heterogeneity, frequent recurrence, and resistance to therapy [[1], [2], [3], [4], [5], [6]]. Despite relentless endeavours by scientists and advancements in radiotherapy, targeted therapy, and immunotherapy [[7], [8], [9]], the prognosis for patients with cancer remains grim [10]. Notably, renal cell carcinoma, a prevalent cancer type, sees 25–30% of patients diagnosed at an advanced stage, resulting in a dismal 5-year survival rate [11]. Hence, it is imperative to explore more effective diagnostic, prognostic, and therapeutic targets. Recently, the rapid evolution of bioinformatics has facilitated scientist to explore more potential valuable genes, which can be used for diagnosis, prognosis, and therapy [12,13].

Phospholipase A2 group VII (PLA2G7) is a phospholipase involved in the hydrolysis of platelet-activating factor and truncated phospholipids synthesized through oxidation [14]. Recent studies have identified PLA2G7 as a potential prognostic biomarker in prostate cancer, diffuse large B cell lymphoma (DLBC), and melanoma [[14], [15], [16]]. For instance, Zheng et al. discovered that, besides its potential as a DLBC biomarker, silencing PLA2G7 expression in DLBC cell lines (DB and SU-DHL-2) impeded proliferation and migration while inducing apoptotic death. Similarly, treatment with the specific PLA2G7 inhibitor (darapladib) yielded comparable results, underscoring PLA2G7's vital role in DLBC. Additionally, recent literature has revealed that heightened PLA2G7 expression and generation characterize cachexia-inducing cancer cell lines. Patients with colorectal and pancreatic cancer with cancer cachexia exhibit elevated circulating PLA2G7 levels [17], indicating a robust association between PLA2G7 and human cancers. However, despite limited reports delving into the biological function of PLA2G7 in specific human cancers, its role in pan-cancer remains unexplored, highlighting a gap in current knowledge.

In this investigation, our hypothesis posited that PLA2G7 could function as a potential biomarker and therapeutic target across various cancers. Consequently, we sought to delineate the role of PLA2G7 in pan-cancer by leveraging multiple databases, R software, and in vitro experiments. Our objective was to contribute to the identification of additional cancer biomarkers and therapeutic targets. Our exploration encompassed the examination of PLA2G7's expression profile in human cancers and corresponding normal tissues. Additionally, we investigated the diagnostic and prognostic value of PLA2G7 in pan-cancer. Furthermore, we scrutinized the associations between PLA2G7 and tumor immunity, mismatch repair (MMR), and its DNA methylation profile in human cancers. Subsequently, our focus shifted to unraveling the significant role of PLA2G7 in renal cancer. We anticipate that our findings will broaden perspectives on precision tumor diagnosis and treatment strategies.

2. Materials and methods

2.1. PLA2G7 expression profile in different cancer and normal tissues

The RNAseq data for PLA2G7 in pan-cancer were acquired from The Cancer Genome Atlas (TCGA) (http://portal.gdc.cancer.gov/), and analyzed using R software v3.6.3. Furthermore, the assessment of PLA2G7 protein levels in both pan-cancer and normal tissues was conducted through the University of Alabama Cancer Data Analysis Portal at Birmingham (UALCAN, http://ualcan.path.uab.edu/index.html) [18,19].

2.2. Diagnostic, prognostic, and clinicopathological features of PLA2G7 in different cancer types

Data pertaining to diagnostic, prognostic, and clinicopathological features of PLA2G7 in diverse cancer types were sourced from the UCSC XENA website (https://xenabrowser.net/datapages/) [20]. To assess the diagnostic value of PLA2G7 in human cancers, the "pROC" R package was employed. The diagnostic accuracy, as reflected by the area under the curve (AUC), was categorized as minimal (0.5–0.7), good (0.7–0.9), and excellent (>0.9). Prognostic evaluation, including progression-free interval (PFI), overall survival (OS), and disease-specific survival (DSS), along with an analysis of clinicopathological features, was conducted using R software.

2.3. PLA2G7 mutation profile in human cancers

The mutation profile of PLA2G7 in human cancers was examined using the cBioPortal online portal (https://www.cbioportal.org/) [21,22] Additionally, the SangerBox website (http://sangerbox.com/) was utilized to assess mutation information associated with PLA2G7 in various cancer types [23]. Furthermore, the cBioPortal database was employed to explore the relationship between PLA2G7 gene mutation profiles and clinical outcomes in patients with different cancer types.

2.4. PLA2G7 expression and its association with tumor immunity

To examine the correlation between PLA2G7 expression and different immune subtypes across various cancer types, the TISIDB online platform [24]. Additionally, the TISIDB website was employed to investigate the relationship between PLA2G7 expression and various immunomodulators, including immuno-inhibitors, immunostimulators, major histocompatibility complex (MHC), and chemokines.

The "Gene" module in TIMER (https://cistrome.shinyapps.io/timer/) was then employed to explore the association between PLA2G7 expression and the level of immune infiltration across diverse cancer types [25,26].

2.5. Association of PLA2G7 expression with multiple immune checkpoint (ICP) genes, microsatellite instability (MSI), tumor mutational burden (TMB), stemness score, and tumor microenvironment (TME) in different cancers

The connections between PLA2G7 and ICP genes, MSI, stemness score, and TMB were examined using SangerBox. Subsequently, the relationship between PLA2G7 expression and StromalScore and ImmuneScore was also investigated through SangerBox. The findings were then visually presented in a radar chart using R software.

2.6. Correlations between DNA methylation, MMR gene mutation, and PLA2G7

Five MMR genes (MLH1, PMS2, MSH2, EPCAM, and MSH6) and four DNA methyltransferases (DNMT1, DNMT3B, DNMT3A, and DNMT2) obtained from prior literature [27] were analyzed for their correlations with PLA2G7 using Gene Expression Profiling Interactive Analysis (GEPIA, http://gepia.cancer-pku.cn/index.html) [28]. The results were visualized in a heatmap using R software. Subsequently, the "Mutation" module of the Gene Set Cancer Analysis (GSCA, http://bioinfo.life.hust.edu.cn/GSCA/#/) was employed to investigate the connection between PLA2G7 mRNA levels and its methylation profile [29].

2.7. PLA2G7 co-expression networks in kidney renal clear cell carcinoma (KIRC)

To identify PLA2G7 co-expression genes in KIRC, the LinkedOmics portal (http://linkedomics.org/login.php) was employed for this analysis [30]. Subsequently, we further investigated PLA2G7 co-expression genes using Gene Set Enrichment Analysis (GSEA) to explore their associations with biological processes, cellular components, molecular functions, and KEGG pathways.

2.8. Cell culture

Human renal carcinoma cell lines, including 786-O, ACHN, and 769-P, were purchased form IMMOCELL, Xiamen, China. and cultured in RPMI-1640 medium (Gibco, Billings, MT, USA) supplemented with fetal bovine serum and penicillin-streptomycin. The cells were maintained in a 5% CO2 humidified atmosphere at 37 °C, and the culture medium was replaced twice daily.

2.9. Immunofluorescence and western blotting assay

Immunofluorescence staining was conducted using previously reported methods [31]. The primary antibody anti-PLA2G7 (Abcepta, San Diego, CA, USA) was employed for immunofluorescence labeling. For western blotting, protein extraction from cells was performed when the cell density of 786-O, ACHN, and 769-P reached 90%. Proteins were separated using a 10% SDS–PAGE gel and subsequently electrically transferred to a PVDF membrane ((0.2 μm pore size), under an under a voltage of 100V. After blocking with 5% skim milk at room temperature for 1 h, the membranes were incubated with primary antibodies (anti-PLA2G7 and anti-GAPDH, diluted at a ratio of 1:1000) at 4 °C overnight. This was followed by a 1-h incubation with the corresponding secondary antibodies at room temperature.

2.10. Cell counting kit-8 (CCK-8) assay

The renal cancer cell lines (786-O and ACHN) were initially seeded in a 96-well plate at a density of 2 × 103 in 100 μL and cultured for 24 h. Following this, the medium was aspirated, and various concentrations of darapladib solutions (0, 1.5625, 3.125, 6.25, 12.5, and 25 μM) were added to each well and cultured for 3 days. Subsequently, the viability of the cells was assessed using the CCK-8 reagent (Yeasen, Shanghai, China), and the experiment was conducted three times.

2.11. Drug sensitivity

The association between PLA2G7 mRNA level and the sensitivity of drugs obtained from the Cancer Therapeutics Response Portal was investigated using the GSCA website through its "drug" module.

2.12. Statistical analysis

Statistical analysis of the data obtained from the online websites or databases mentioned above was automatically computed. Differences between groups were assessed using the Student's t-test. Statistical significance was defined as a P-value or false discovery rate less than 0.05.

3. Results

3.1. Most cancer tissues express PLA2G7 at high levels

Table S1 displays the abbreviations and full names of multiple human cancers. The findings indicate elevated PLA2G7 mRNA levels in KIRC, BRCA, ESCA, CESC, HNSC, KICH, BLCA, KIRP, STAD, LUAD, PRAD, and LIHC, while THCA and PAAD exhibit lower PLA2G7 mRNA levels (Fig. 1A). Subsequently, we assessed PLA2G7 mRNA expression profiles in various cancer types and paired normal tissues. Fig. 1B illustrates that, in comparison to paired normal tissues, higher PLA2G7 mRNA levels were observed in BRCA, ESCA, BLCA, HNSC, KIRP, KIRC, KICH, LIHC, STAD, PRAD, and LUAD. Conversely, PLA2G7 mRNA levels were lower in THCA compared to nearby normal tissues.

Fig. 1.

Fig. 1

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PLA2G7 expression profiles. (A) Analysis of PLA2G7 mRNA levels across multiple cancer types and unpaired normal tissues based on TCGA. (B) Pan-cancer analysis of PLA2G7 mRNA expression profile in various cancer tissues and paired normal tissues based on TCGA. (C–F) The UALCAN website displays the variations in the expression profiles of PLA2G7 protein across multiple cancer and normal tissues. *P < 0.05, **P < 0.01, ***P < 0.001, ns: no significance.

After evaluating PLA2G7 mRNA levels across different human cancer types, we examined PLA2G7 protein levels using the UALCAN online tool. The results revealed higher PLA2G7 protein levels in KIRC and PAAD (Fig. 1D and F) but lower levels in BRCA and LUAD (Fig. 1C and E).

3.2. PLA2G7 as a potential biomarker for pan-cancer

The receiver operating characteristic (ROC) analysis of PLA2G7 in different human cancers is depicted in Fig. 2 and S1, showing the AUC values. PLA2G7 demonstrated robust accuracy in diagnosing diverse human cancers, with notable AUC values for HNSC (0.883), KICH (0.880), PRAD (0.889), READ (0.871), BRCA (0.701), BLCA (0.732), COAD (0.819), CHOL (0.710), LGG (0.811), UCEC (0.832), OV (0.790), LIHC (0.799), and SKCM (0.849). Remarkably, PLA2G7 exhibited excellent accuracy in diagnosing CESC (0.966), DLBC (0.994), ESCA (0.987), KIRC (0.957), KIRP (0.952), LAML (0.913), PAAD (0.973), STAD (0.980), TGCT (0.996), and UCS (0.952). Next, we explored the prognostic significance of PLA2G7 in human malignancies. Results indicated that high PLA2G7 expression correlated with better OS in CESC (Hazard ratio [HR] = 0.59, P = 0.027) and SKCM (HR = 0.74, P = 0.026). Conversely, patients with UVM and high PLA2G7 expression had poorer OS (HR = 3.2, P = 0.01) (Fig. 3A–C). Patients with high PLA2G7 expression in CESC (HR = 0.55, P = 0.031), KIRP (HR = 0.44, P = 0.042), and SKCM (HR = 0.73, P = 0.031) showed improved DSS. Additionally, those with UVM and high PLA2G7 expression exhibited better DSS (HR = 3.49, P = 0.009) (Fig. 3D–G). Furthermore, enhanced PLA2G7 expression in CESC was associated with better PFI (HR = 0.61, P = 0.039) (Fig. 3H). Finally, we investigated the link between PLA2G7 expression and various clinicopathologic stages in pan-cancer. As illustrated in Fig. 4, PLA2G7 was prominently expressed in various advanced tumors, including BLCA, ESCA, HNSC, STAD, etc. These findings suggest that PLA2G7 could serve as a promising diagnostic and prognostic biomarker across various human cancers.

Fig. 2.

Fig. 2

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ROC curves assessing the sensitivity of PLA2G7 in diagnosing various human cancers.

Fig. 3.

Fig. 3

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Clinical outcomes in pan-cancer correlated with PLA2G7 expression. (A–C) Association between PLA2G7 expression and overall survival (OS) in human cancers. (D–G) Association between PLA2G7 expression profile and disease-specific survival (DSS) in various human cancers. (H) Association between PLA2G7 expression and progression-free interval (PFI) in CESC.

Fig. 4.

Fig. 4

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Associations between PLA2G7 expression and various tumor stages in human cancers. (A–I) Correlations between PLA2G7 expression and different tumor stages in BLCA, ESCA, HNSC, KICH, KIRC, KIRP, LIHC, LUAD, and STAD, respectively. *P < 0.05, **P < 0.01, ***P < 0.001, ns: no significance.

3.3. PLA2G7 genetic alteration profile in human cancer

The PLA2G7 mutation status in various cancer types was explored through the cBioPortal website. In Fig. 5A, it is evident that PLA2G7 exhibits different alteration frequencies across human cancers. Notably, SKCM demonstrated the highest mutation frequency (>6%) for PLA2G7, whereas no mutations were detected in LAML, CHOL, KICH, PCPG, TGCT, THYM, and THCA, with "amplification" being the most prevalent mutation type. Additionally, we further analyzed the specific types of PLA2G7 mutations using mutation data from 19 cancers obtained from the SangerBox website. The findings revealed that "missense mutation" was the predominant type of PLA2G7 mutation (Fig. 5B). Prior literature has established that both "amplification mutation" and "missense mutation" can contribute to tumorigenesis by altering the amino acid sequence. Consequently, PLA2G7 may play a role in tumorigenesis in human cancer. Finally, the relationship between PLA2G7 gene mutation status and clinical outcomes in multiple human cancers was investigated using the cBioPortal tool. The results indicated that patients with LIHC, KIRP, and STAD with PLA2G7 mutation experienced poorer clinical outcomes (Fig. 5D–F), while those with HNSC and PLA2G7 mutation exhibited better OS (Fig. 5C). These findings suggest that PLA2G7 may be involved in tumorigenesis and further validate its potential as a viable prognostic biomarker in human cancers.

Fig. 5.

Fig. 5

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Mutation profile of PLA2G7 in pan-cancer. (A) Frequency of PLA2G7 alterations in different human cancer types. (B) Mutation information of PLA2G7 in human cancers. (C) Association between PLA2G7 gene mutation status and overall survival (OS) in HNSC. (D) Association between PLA2G7 gene mutation status and disease-free survival in LIHC. (E) Association between PLA2G7 gene mutation status and progression-free survival in KIRP. (F) Association between PLA2G7 gene mutation status and OS in STAD.

3.4. PLA2G7 and tumor immunity

We initially constructed a protein-protein interaction network between PLA2G7 and its 10 inter-acting proteins (APOE, APOB, GHRL, PLA2G10, LPCAT2, LPCAT1, PAFAH1B1, PLA2G1B, APOA1, and APOA5) using the STRING website (Fig. S2A) before conducting GO enrichment analysis. As depicted in Fig. S2B, PLA2G7 and its interacting proteins were associated with "immune system process," "positive regulation of response to stimulus," and "regulation of immune system process." Furthermore, we investigated the link between PLA2G7 expression and several immune subtypes in pan-cancer using the TISIDB web tool. The findings revealed that PLA2G7 expression was associated with various immune subtypes in STAD, BLCA, CESC, BRCA, LUAD, LUSC, MESO, as well as SARC (Fig. 6). Detailed information regarding PLA2G7 expression and different immune subtypes in other human cancers is presented in Fig. S3. These outcomes suggest that PLA2G7 plays a role in tumor immunity.

Fig. 6.

Fig. 6

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The link between PLA2G7 expression and different immune subtypes in pan-cancer. (C1–C6 represented wound healing, IFN-gamma dominant, inflammatory, lymphocyte depleted, immunologically quiet, and TGF-β dominant, respectively).

3.5. PLA2G7 is linked to different ICP genes and immunomodulators in pan-cancer

Correlations between PLA2G7 and various immunomodulators (including immuno-inhibitors, immunostimulators, MHC molecules, receptors, and chemokines) were examined using the TISIDB website. The results revealed that PLA2G7 was positively related to most immunoinhibitors in pan-cancer, particularly in CESC, COAD, HNSC, and TGCT (Fig. 7A). Regarding immunostimulators, PLA2G7 also exhibited a positive correlation with most immunostimulators across human cancers, notably in BLCA, HNSC, LUSC, and TGCT (Fig. 7B). PLA2G7 showed a positive relationship with most MHC molecules in pan-cancers such as LUSC, TGCT, and UVM (Fig. 7C). Similarly, chemokines tended to exhibit a positive correlation with PLA2G7 in most human cancers (Fig. 7D), along with receptors (Fig. 7E). Subsequently, we explored the relationship between PLA2G7 and different ICP genes in multiple cancer types. As depicted in Fig. 8, most ICP genes showed a positive correlation with PLA2G7 in human cancers. These findings suggest that PLA2G7 may play a role in the regulation of tumor immunity and could serve as a potential target for immunotherapy.

Fig. 7.

Fig. 7

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The link between PLA2G7 and different immunomodulators in human cancers. (A–E) The link between PLA2G7 and various immunostimulators, immuno-inhibitors, MHC molecules, chemokines, and receptors in pan-cancer.

Fig. 8.

Fig. 8

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The link between PLA2G7 and different ICP genes in human cancers.

3.6. PLA2G7 is associated with ESTIMATE, TMB, MSI, and stemness scores in human cancers

Previous literature has established that TMB and MSI in the TME are associated with antitumor immunity and can predict the response to immunotherapy [32,33]. Therefore, we explored the correlations between PLA2G7 and TMB as well as MSI. As depicted in Fig. 9A, PLA2G7 was negatively related to MSI in TGCT, HNSC, LUSC, LGG, and STAD, while positively associated with MSI in COAD. Regarding TMB, our findings suggest a negative relationship between PLA2G7 and TMB in THCA and LIHC, while a positive relationship was observed between PLA2G7 and STAD, BLCA, COAD, LAML, BRCA, and SARC (Fig. 9B). Subsequently, we analyzed the relationship between PLA2G7 and two ESTIMATE scores (ImmuneScore and StromalScore) in pan-cancer. As shown in Fig. 9C and D, PLA2G7 was negatively or positively associated with ImmuneScore and StromalScore in most cancer types. Furthermore, PLA2G7 was negatively or positively related to DNA stemness score and RNA stemness score in pan-cancer (Figs. S4A–B).

Fig. 9.

Fig. 9

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Correlations of PLA2G7 expression profile and MSI, TMB, and two ESTIMATE scores in cancers. (A–B) The link between PLA2G7 expression and MSI as well as TMB in human cancers. (C–D) The link between PLA2G7 and two ESTIMATE scores (ImmuneScore and StromalScore) in various cancer types. *P < 0.05, **P < 0.01, ***P < 0.001.

3.7. Link between PLA2G7 and immune cell infiltration in pan-cancer

The association between PLA2G7 expression and six immune infiltration cells was examined using the TIMER website. The results demonstrated that PLA2G7 expression was correlated with CD4+ T cells, B cells, and CD8+ T cells in 25, 23, and 19 human cancers, respectively. Additionally, PLA2G7 expression was linked to macrophages, neutrophils, and dendritic cells in 24, 29, and 29 human cancers. Notably, as depicted in Fig. 10 and Fig. S5, PLA2G7 expression was associated with all six immune infiltration cells in 16 tumor types, including KIRC, KIRP, LIHC, LUAD, and LUSC.

Fig. 10.

Fig. 10

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The link between PLA2G7 expression and six immune infiltration cells (CD8+ T cells, CD4+ T cells, dendritic cells, B cells, neutrophils, and macrophages) in COAD, BRCA, HNSC, KIRP, LUSC, LIHC, and STAD.

3.8. Link between PLA2G7 and MMR genes and DNA methylation in human cancers

Several studies have highlighted the significant roles of MMR genes and DNA methylation in tumorigenesis [34]. We next explored the potential mechanism of PLA2G7 in tumorigenesis. The results demonstrated that PLA2G7 was partially or fully related to MMR genes in most cancer types. For example, PLA2G7 was linked to all MMR genes in COAD, PRAD, and THCA (Fig. 11A). Subsequently, we determined the association between PLA2G7 and four DNA methyltransferases in human cancer. As shown in Fig. 11B, similar to MMR genes, PLA2G7 was also related to some or all DNA methyltransferases in most human cancers. For instance, PLA2G7 was associated with all DNA methyltransferases in BRCA, LIHC, READ, TGCT, and THCA. The relationship between PLA2G7 mRNA levels and PLA2G7 gene methylation in pan-cancer was also explored. Fig. 11C and Fig. S6 demonstrated that PLA2G7 mRNA levels negatively correlated with PLA2G7 gene methylation in various cancers, including BRCA, CESC, UVM, and KIRP. Finally, the GSCA online tool was employed to ascertain the relationship between PLA2G7 gene methylation and patients’ clinical outcomes in pan-cancer. Figs. S7A and B illustrated that patients with low PLA2G7 gene methylation levels had poorer OS in THYM and UVM. For disease-free interval (DFI), patients with low PLA2G7 gene methylation levels had poorer DFI in BRCA (Fig. S7C), while those with low PLA2G7 gene methylation levels exhibited better DFI in CESC and STAD (Figs. S7D–E). As shown in Figs. S7F–H, patients with low PLA2G7 gene methylation levels had poorer progression-free survival (PFS) in BRCA, THYM, and UVM, while a poorer DSS was found in patients with low PLA2G7 gene methylation levels in LUSC and UVM (Figs. S7I–J). These results indicate that PLA2G7 may promote tumorigenesis through MMR and DNA methylation, and patients with different PLA2G7 gene methylation levels have different clinical outcomes in specific cancer types, suggesting that PLA2G7 has value as a biomarker in pan-cancer.

Fig. 11.

Fig. 11

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The link between PLA2G7 and MMR and its DNA methylation in different cancer types. (A) Link between PLA2G7 and five MMR genes (MLH1, MSH2, MSH6, EPCAM, and PMS2) in various cancer types. (B) Link between PLA2G7 and four DNA methyltransferases (DNMT1, DNMT3B, DNMT2, and DNMT3A) in various cancer types. (C) The link between PLA2G7 mRNA levels and its gene methylation level in various cancer types. *P < 0.05, **P < 0.01.

3.9. PLA2G7 co-expression genes correlate with the immune response in KIRC

We investigated the link between PLA2G7 and diagnosis, prognosis, and immunity in human cancers. Utilizing the LinkedOmics online tool, we constructed PLA2G7 co-expression networks to study its potential function in KIRC. This marks the first examination of PLA2G7 function in KIRC. The results revealed that 3618 genes (represented as red dots) and 2806 genes (represented as green dots) were significantly linked to PLA2G7 in KIRC, either positively or negatively (Fig. 12A). Subsequently, heat maps were generated to illustrate the top 50 genes that were positively or negatively linked to PLA2G7 in KIRC (Fig. 12B and C). The details of the co-expression genes are presented in Supplementary Tables 2 and 3 Notably, CCL18, GM2A, and CHRNA1 were strongly associated with PLA2G7 expression (r = 0.736, 0.701, 0.678, and P = 7.74E-92, 4.45E-80, 5.10E-79, respectively). Furthermore, GSEA using the LinkedOmics online tool indicated that PLA2G7 co-expression genes primarily participated in immunity-related Gene Ontology (GO) terms, including "immunoglobulin binding," "leukocyte cell-cell adhesion," "adaptive immune response," "T cell activation," and "MHC protein complex" (Fig. 12D–F). Regarding the Kyoto Encyclopedia of Genes and Genomes (KEGG), PLA2G7 co-expression genes were involved in the "B cell receptor signaling pathway," "Staphylococcus aureus infection," and "chemokine signaling pathway" (Fig. 12G). These findings suggest that PLA2G7 plays a crucial role in KIRC by participating in tumor immunity.

Fig. 12.

Fig. 12

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Enrichment analysis of PLA2G7 co-expression genes in KIRC investigated through the LinkedOmics website. (A) PLA2G7 co-expression genes in KIRC. (B–C) Top 50 genes that were either positively or negatively associated with PLA2G7 in KIRC. (D–F) GO biological process, cellular component, and molecular function analysis of PLA2G7 co-expression genes in KIRC. (G) KEGG analysis of PLA2G7 in KIRC.

3.10. PLA2G7 is mainly distributed in whole cells and influences renal cancer cell proliferation

After systematically analyzing the involvement of PLA2G7 in human cancers, we proposed that PLA2G7 is a potential biomarker and therapeutic target for human cancer, including renal cancer. Subsequently, in vitro experiments were conducted to validate this hypothesis, using renal cancer as an example. As shown in Fig. 13A, the renal cancer cell lines 786-O and ACHN expressed PLA2G7 protein, while no obvious PLA2G7 protein was detected in renal cancer cell line 769-P. Considering the PLA2G7 protein expression profile of above three renal cancer cell lines, we chose 786-O and ACHN renal cancer cell lines for further study. An immunofluorescence experiment was conducted to explore the distribution of PLA2G7 in renal cancer cells. Fig. 13B shows that PLA2G7 was distributed throughout renal cancer cells, particularly in the cytoplasm. Next, a CCK-8 assay was performed to investigate the influence of PLA2G7 on renal cancer cell proliferation. Fig. 13C illustrates that after inhibiting PLA2G7 gene expression, the viability of 786-O and ACHN cells was significantly decreased. These results suggest that PLA2G7 may serve as a promising therapeutic target in renal cancer.

Fig. 13.

Fig. 13

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Biological function of PLA2G7 in renal cancer. (A) PLA2G7 protein levels in 786-O, ACHN, and 769-P renal cancer cell lines. (B) Distribution of PLA2G7 protein in 786-O and ACHN renal cancer cell lines. (C) Viability of 786-O and ACHN renal cancer cell lines explored using CCK-8 assay after treatment with different concentrations of PLA2G7 gene inhibitor. *P < 0.05, **P < 0.01, ***P < 0.001, ****P < 0.0001.

3.11. PLA2G7 related to Cancer Therapeutics Response Portal (CTRP) drug sensitivity

We further investigated the relationship between PLA2G7 mRNA levels and CTRP drug sensitivity. Fig. 14 illustrates that PLA2G7 mRNA levels were positively or negatively linked to the sensitivity of CTRP drugs, including BCL-2 inhibitor (ABT-199), ATM inhibitor (KU-60019), and Braf/Mapk-targeting compound (GDC-0879), which have been proved having a good anti-tumor effect [[35], [36], [37]]. These findings suggest that PLA2G7 may guide the use of specific anti-cancer drugs in clinical practice.

Fig. 14.

Fig. 14

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The link between PLA2G7 expression and various CTRP drugs from the GSCA website (orange and blue-purple circles indicate positive and negative correlations, respectively). (For interpretation of the references to color in this figure legend, the reader is referred to the Web version of this article.)

4. Discussion

The current trend in tumor treatment emphasizes precision and individualized approaches. Surgical resection combined with chemotherapy is presently the preferred therapeutic strategy for most patients with advanced cancer [38]. Clinical trials are underway to explore immunotherapy as a supplementary curative and palliative treatment, potentially offering a novel strategy for patients with advanced or inoperable disease [39,40]. However, the development of precision and individualized tumor therapy is somewhat constrained by the lack of effective diagnostic and therapeutic targets.

The significance of PLA2G7 in specific cancer types has only been partially studied to date. For example, recent literature revealed that the downregulation of PLA2G7 in a breast cancer cell line (HCC1937) promoted proliferation and migration, suggesting a vital role for PLA2G7 in cancer [41]. Additionally, PLA2G7 has been implicated in the inflammatory process and associated with tumor immunity. The Lp-PLA2 protein encoded by PLA2G7 has been demonstrated to be expressed by various immune cells [16,42,43]. These findings prompted us to investigate the link between PLA2G7 and human cancers. Our findings indicate that PLA2G7 is relatively highly expressed in various human cancers and may serve as a potential biomarker, including in renal cancer. Furthermore, PLA2G7 is associated with various immune subtypes, ICP genes, immune infiltration, and immunomodulators in pan-cancer, suggesting its relevance to tumor immunity across different cancer types. This association may position PLA2G7 as a potential target for immunotherapy.

TMB and MSI have been demonstrated to be associated with antitumor immunity and can serve as predictors for immunotherapy response [[44], [45], [46]]. In this study, we investigated the relationship between PLA2G7 and MSI, as well as TMB, using the SangerBox online tool. Our results revealed that PLA2G7 was linked to MSI in TGCT, LUSC, HNSC, LGG, and COAD, and it was also associated with THCA, LIHC, STAD, BLCA, COAD, LAML, BRCA, and SARC. Previous studies have established that the TME significantly influences cancer survival, immune evasion, proliferation, clinical prognosis, and metastasis [47,48]. As integral components of the TME, ImmuneScore and StromalScore play crucial roles in the immune metabolism of tumor cells [49]. Our findings indicated a close association between PLA2G7 and ImmuneScore in 32 cancer types, StromalScore in 32 cancer types, and all tumor-infiltrating lymphocytes in 16 cancer types. These results suggest that PLA2G7 is intricately linked to the TME and could potentially serve as a target for immunotherapy across various cancer types.

MMR and DNA methylation are pivotal for maintaining genome stability and may serve as novel biomarkers in tumorigenesis [27]. Consequently, we examined the relationship between PLA2G7 and various MMR genes, along with four DNA methyltransferases in pan-cancer. Our findings revealed a significant association between PLA2G7 and MMR, as well as DNA methylation, in different cancer types, implying that PLA2G7 may contribute to tumorigenesis through MMR and DNA methylation mechanisms.

Patients with renal cancer, such as KIRC, often experience poor prognosis, and there is a lack of effective diagnostic and therapeutic targets in clinical practice. Therefore, there is an urgent need to identify potential therapeutic targets for kidney cancer. In our study, we delved into the role of PLA2G7 in renal cancer to provide a theoretical basis for its treatment. The results of GO enrichment demonstrated that PLA2G7 and its co-expression genes were associated with the "regulation of immune system process," "immune system process," and "positive regulation of response to stimulus." Additionally, CCK-8 experiments revealed a significant decrease in the cell viability of renal cancer cells after inhibiting the PLA2G7 gene. Taken together, we propose that PLA2G7 may be a promising therapeutic target for renal cancer. Finally, we explored the correlations between PLA2G7 mRNA levels and CTRP drug sensitivity. Our findings suggest that PLA2G7 may guide the use of specific anticancer drugs in clinical practice.

Bioinformatics has garnered significant attention from scientists in recent years, owing to its large sample size, convenient operation, and high analytical efficiency. It has evolved into a powerful tool for researchers seeking potential disease diagnostic and therapeutic biomarkers. The booming development of bioinformatics is expected to unearth more effective tumor biomarkers and therapeutic targets, including those for renal cancer, over the next five years. This progress is anticipated to drive advancements in precision and individualized tumor treatment.

While this study comprehensively explores the role of PLA2G7 in human cancers, certain limitations persist. in our study. First, the majority of findings are data-driven, with only a limited number of experiments conducted to validate our analyses. Additionally, our investigation into the proliferation capacity of renal cancer was confined to cellular-level experiments, warranting further validation at the animal level. Second, although we have demonstrated the crucial role of PLA2G7 in human cancers, including renal cancer, the specific tumor-promoting mechanisms of PLA2G7 necessitate further elucidation.

5. Conclusions

In summary, our study establishes PLA2G7 as a promising diagnostic and prognostic biomarker across various cancers, including renal cancer. Furthermore, it emerges as a potential therapeutic target in human cancers, offering a valuable theoretical foundation for advancing cancer treatment strategies.

Data availability statement

The original data of this work can be acquired from the corresponding authors upon reasonable request.

Funding

The Major Social Development Projects of Jinhua (#2020-3-002) and the National Natural Science Foundation of China (#82170681) funded the project.

CRediT authorship contribution statement

Jun Xie: Writing – review & editing, Writing – original draft, Conceptualization. Li Zhu: Methodology, Investigation. Xutao Yang: Investigation, Data curation. Fengfei Yu: Software, Methodology. Bingfu Fan: Methodology, Investigation. Yibo Wu: Software. Zonglang Zhou: Data curation, Conceptualization. Weiqiang Lin: Writing – review & editing, Methodology, Conceptualization. Yi Yang: Writing – review & editing, Funding acquisition, Conceptualization.

Declaration of competing interest

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

Acknowledgement

We thank Bullet Edits Limited for the linguistic editing and proofreading of the manuscript.

Footnotes

Appendix A

Supplementary data to this article can be found online at https://doi.org/10.1016/j.heliyon.2024.e27906.

Contributor Information

Zonglang Zhou, Email: 13456213819@163.com.

Weiqiang Lin, Email: wlin@zju.edu.cn.

Yi Yang, Email: yangyixk@zju.edu.cn.

Appendix A. Supplementary data

The following is the Supplementary data to this article:

Multimedia component 1
mmc1.docx (186.1MB, docx)

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Associated Data

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Supplementary Materials

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Data Availability Statement

The original data of this work can be acquired from the corresponding authors upon reasonable request.

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