The data that we analyzed was downloaded from TCGA database(https://www.cancer.gov/ccg/research/genome-sequencing/tcga), ICGC database(https://platform.icgc-argo.org/), and CPTAC-PDC000127(https://pdc.cancer.gov/pdc/browse) cohorts which included gene expression datasets corresponding with clinicopathological information.

The human ccRCC cell lines (786-O, Caki-1, A498, ACHN, OSRC-2) and the human normal cell line (HEK293) were sourced from the American Type Culture Collection (Manassas, VA, USA). All cell lines were authenticated through STR profiling and confirmed to be mycoplasma-free. Cells were maintained in high glucose Dulbecco’s Modified Eagle’s Medium (DMEM, Gibco, Waltham, MA, USA) with 10% fetal bovine serum (Gibco) at 37 °C in a 5% CO₂ environment.

Tissue samples from ccRCC patients were collected by the Department of Urology, Union Hospital (Wuhan, Hubei, China) from 2022 to 2023. All the patients only accepted surgery without any other antitumor treatment before. All the pathological results were ccRCC. The tumor-adjacent normal renal tissues were taken more than 2.5 cm away from the cancer tissues. All patients were informed and consented to it with written documents. Huazhong University of Science and Technology Ethics Committee approved this study (IEC-072).

TRIzol reagent (#R4801, Magen Biotechnology Co., Ltd., Guangzhou, China) was employed for the extraction of total RNA from cells and tissues. A quantity of 500 ng RNA was utilized for reverse transcription, followed by cDNA synthesis. Subsequently, qPCR analysis was performed using the Sybr Green Mix (#11203ES03, Yeasen, Shanghai, China). The qPCR procedures were performed in accordance with the manufacturer’s instructions and data analysis was conducted using the StepOnePlus™ PCR system (Thermo Fisher Scientific, Waltham, MA, USA). Primer sequences were as follows: pLCG2: Forward, 5^′-CGTCTACCCAAAGGGACAAA-3^′; Reverse, 5^′-GACTGTCAGCGTCATCAGGA-3^′. GAPDH: Forward, 5^′-GAGTCCACTGGCGTCTTCA-3^′; Reverse, 5^′-GGTCATGAGTCCTTCCAGGA-3^′.

Protein extraction from cells was performed using a mixture of radioimmunoprecipitation assay lysis buffer (#P0013C, Beyotime, Shanghai, China), phenylmethanesulfonyl fluoride, and proteinase inhibitors. Bicinchoninic acid (BCA) Protein Assay Kit (#23225, Thermo Fisher Scientific, Waltham, MA, USA) was used for protein quantification. The extracted proteins underwent electrophoresis on a sodium dodecyl sulfate-polyacrylamide gel electrophoresis at 80 V and were then transferred onto polyvinylidene fluoride membranes. The membrane was blocked using 5% non-fat dried skim milk for 30 min and subsequently incubated overnight at 4 °C with the primary antibody. Following this, the membranes were incubated with the secondary antibody for two hours at room temperature prior to development. Primary antibodies were diluted according to the manual’s instructions, including PLCG2 (1:800, #A5182, ABclonal Biotech Co., Ltd., Wuhan, China), VEGFA (1:800, #A12303, ABclonal Biotech Co., Ltd.), GAPDH (1:2000, #60004-1-Ig, Proteintech, Chicago, IL, USA), HIF-2ɑ (1:1500, #66731-1-Ig, Proteintech), VEGFR2 (1:2000, #A5609, ABclonal Biotech Co., Ltd.). Western blot utilized horseradish peroxidase (HRP)-conjugated Affinipure Goat Anti-Rabbit IgG (H+L) (1:2000, #SA00001-2, Proteintech) and HRP-conjugated Affinipure Goat Anti-Mouse IgG (H+L) (1:2000, #SA00001-1, Proteintech) as secondary antibodies.

PLCG2-targeted siRNAs (siRNA#1: 5^′-CUGAGAAAGCAGAUAUAUUTT-3^′; siRNA#2: 5^′-GAGGCGAUGUGGAUGUCAACA-3^′) were supplied by Genechem Co., Ltd. (Shanghai, China). PLCG2-overexpressed lentivirus was also provided by Genechem Co., Ltd. The targeted transcript of PLCG2-overexpressed lentivirus was NM002661 and the lentiviral vector was GV492 (Ubi-MCS-3FLAG-CBh-gcGFP-IRES-puromycin). Lentivirus and vector were transduced into A498 and CAKI-1 cell lines, while siRNA and negative control were transfected into A498 and CAKI-1 cells as well.

Inoculating 2 $\times$ 10³ cancer cells in 12-well plates with 500 µL DMEM. After 24 h, the cells were fixed with 4% paraformaldehyde (#BL539A, Biosharp, Hefei, China) for 15 min. Then the plates were rinsed with phosphate-buffered saline (PBS) for 10 min, three times. Finally, cells were colored with Oil red (#G1015, Servicebio, Wuhan, China) for 15 min before being washed with water.

The cell pellets were collected in a six-well plate, and the triglyceride content was quantified using triglyceride determination kits (#A110-1-1, Nanjing Jiancheng Institute of Bioengineering, Nanjing, China) following the manufacturer’s instructions.

Immunohistochemistry (IHC) was performed on tumors and adjacent normal tissues from patients. First, the tissues are sliced, formalin-fixed, and paraffin-embedded. The following steps were de-paraffinization, rehydration, and incubating for antigen retrieval. PLCG2 antibody was the primary antibody (#A5182, ABclonal Biotech Co., Ltd.) that was used against PLCG2 for 12 h. Then the sections were washed with PBS before corresponding with secondary antibodies (#5220-0336(074-1506), KPL, Gaithersburg, MD, USA). After that, the picture was obtained by microscope (#Pannoramic SCAN, 3D Histech, Budapest, Hungary) randomly.

The cell was starvation with fetal bovine serum (FBS)-free for 24 h before transwell assays. The inserts were placed in 24-well plates with 500 µL high glucose medium (Gibco) with 10% FBS at the underpart. Cells would be cultured in the top of inserts with FBS-free DMEM to invade the inserts with or without Matrigel. After 24 h culturing, methanol (Sinopharm Chemical Reagent Co., Ltd., Beijing, China) was used to fix the cells, and crystal violet (#G1014, Servicebio) was used to stain it. The image was caught by the microscope (#DSZ2000, UOP Photoelectric Technology, Chongqing, China) randomly.

Each well was cultured 2 $\times$ 10³cells in a 96-well plate to foster 0, 24, 48, 72, and 96 h with 200 µL 10% FBS medium The CCK-8 solution (#40203ES80, Yeasen) mixed with 100 µL DMEM and 10 µL CCK-8 solution was used to add to each well. The 96-well plates would be parted into 37 °C water baths with shading treatment for 2 h. Cell viability was measured at 450 nm by NanoDrop 2000 spectrophotometer (NanoDrop Technologies, Wilmington, DE, USA).

Cultivate ccRCC cells until they reach approximately 70% confluency, then replace the medium with serum-free medium and continue to culture for 24 h. Collect the supernatant and centrifuge at 200 g for 5 min to remove any debris. Filter the supernatant through a 0.22-micron filter to obtain the conditioned medium. Store the conditioned medium at 4 °C for short-term use or at –80 °C for long-term storage. Cultivate HUVEC in endothelial cell medium until they reach approximately 70% confluency, then replace the medium with the previously prepared conditioned medium before experiments.

Add 200 µL of Matrigel to each well of a 24-well plate and incubate at 37 °C for 30 min before the addition of 6 $\times$ 10⁴ HUVECs. After adding cells to incubate 8 h with supernatant from indicated cultured cancer cells, microscopy was used to observe.

The ELISA kit utilized was the Human VEGF-A ELISA Kit from Elabscience (#E-EL-H0111c, Elabscience Biotechnology Co., Ltd., Wuhan, China), following all procedures as per the manufacturer’s instructions. In summary, a preliminary experiment was conducted to determine the optimal dilution concentration. Thereafter, the extracted conditioned medium, diluted to the identified concentration, was added in equal volumes to the antibody-coated plates supplied by the kit. The protocol involved repeated cycles of incubation at 37 °C in the dark, followed by washing and blotting dry. Finally, the substrate solution was added and incubated for 15 min, after which the stop solution was introduced. The absorbance was immediately measured at 450 nm. After calibrating the obtained ptical density (OD) values, the corresponding concentrations were calculated using the curve fitted to the standard samples.

The negative control and lentivirus were used to infect 1 $\times$ 10⁶ A498 cells, which were subsequently injected into nude mice via tail vein injection to assess their metastasis ability. After a 45-day observation period, all mice were first subjected to live small animal fluorescent imaging assays. Subsequently, they were complete anesthetized with 100 mg/kg/ip of pentobarbital sodium, followed by cervical dislocation as a secondary euthanasia method to ensure death.

Using negative control and lentivirus infected 1 $\times$ 10⁶ A498 cells. Then cells were injected respectively into the subcutaneous tissue of nude mice to evaluate the proliferation ability. Tumor size was measured every 5 days. After 45 days for observation, all mice were complete anesthetized with 100 mg/kg/ip of pentobarbital sodium, followed by cervical dislocation as a secondary euthanasia method.

Data analyses were conducted using SPSS Statistics version 25.0 (IBM Corp., Chicago, IL, USA) and GraphPad Prism version 9.0 (GraphPad Software Inc., San Diego, CA, USA). Variations between control and experimental groups were assessed through unpaired and paired Student’s t-tests. One-way ANOVA was applied to explore differences among multiple groups relative to a control group. Kaplan-Meier survival analysis was utilized to project patient prognoses. Furthermore, logistic regression analyses focusing on single genes were executed in SPSS and results were methodically presented in tabular formats. Statistical data were expressed as mean values $\pm$ standard deviations, with p-values of less than 0.05 deemed to indicate statistical significance.

The VEGF signaling pathway was markedly correlated with the clinical prognosis in ccRCC. Thus, the genes that were differential expression in TCGA-KIRC database, ICGC-KIRC database, CPTAC-PDC000127 cohorts, and a gene set of the VEGF signaling pathway were used to screen the hub gene of the angiogenesis in ccRCC. The intersection of these four datasets showed that 6 genes were significantly different expressions in ccRCC relative to the normal tissues (Fig. 1A). From go without saying, that VEGFA and VEGFB, as two famous factors of the VEGF signaling pathway, played important roles in the angiogenesis of ccRCC. There was not much innovativeness to study with those two genes. Kaplan–Meier analysis showed ccRCC patients with higher expression of FMS-like tyrosine kinase 1 (FLT1) and neuropilin 1 (NRP1) had better overall survival which was opposite to the upregulation in the tumor, indicating these two factors had no clinical significance (Fig. 1B–D). The prognostic values of PLCG2 and carboxy-terminal Src kinase (CSK) were consistent in the expression of ccRCC (Fig. 1B–D). Next, monogenic logistics were performed demonstrating that PLCG2 had more diagnostic value to be a biomarker for ccRCC (Tables 1,2). The findings from the receiver operating characteristic curve (ROC) analysis also indicated the expression of PLCG2 was associated with the clinical prognosis (Fig. 1E and Supplementary Fig. 1A). Pair comparison by TCGA and ICGC database and unpair comparison by CPTAC database showed that PLCG2 was significantly downregulated in tumor tissues (Fig. 1F and Supplementary Fig. 1B). The data from the ArrayExpress database (E-MTAB-1980) and TCGA database indicated that PLCG2 expression was associated with clinical stages of ccRCC (Supplementary Fig. 1C,D). GSEA showed the high-expression group of PLCG2 was enriched in the VEGF signaling pathway and angiogenesis (Supplementary Fig. 1E). The Kyoto Encyclopedia of Genes and Genomes (KEGG) analysis showed the same results. Even more interesting is renal cell cancer was enriched in KEGG analysis which confirmed that PLCG2 may be a hub gene to make RCC in connection with angiogenesis (Supplementary Fig. 1F). The results consistently supported the significance of PLCG2 as a pivotal gene implicated in renal cancer and angiogenesis.

Fig. 1.

PLCG2 was downregulated and was a potential biomarker in ccRCC. (A) The intersection of differential genes of TCGA-KIRC (gene set 1), ICGC-KIRC (gene set 2), CPTAC-PDC000127 cohorts (gene set 3), and a VEGF-related gene set (gene set 4). (B) The mRNA levels of 4 genes (PLCG2, FLT1, NRP1, CSK) in ccRCC tissues and normal tissues based on TCGA-KIRC cohort. (C) The mRNA levels of 4 genes (PLCG2, FLT1, NRP1, CSK) in ccRCC tissues and normal tissues based on ICGC-KIRC cohort. (D) The Kaplan-Meier survival curve of 4 genes (PLCG2, FLT1, NRP1, CSK). (E) The ROC curve of 4 genes (PLCG2, FLT1, NRP1, CSK) in TCGA-KIRC cohort. (F) The mRNA levels of PLCG2 in matched normal and cancerous tissues based on TCGA-KIRC cohort and ICGC-KIRC cohort (***p 0.001). ccRCC, clear cell renal cell carcinoma; TCGA, The Cancer Genome Atlas; ICGC, International Cancer Genome Consortium; CPTAC, Clinical Proteomic Tumor Analysis Consortium; VEGF, vascular endothelial growth factor; ROC, receiver operating characteristic; KIRC, kidney renal clear cell carcinoma; PLCG2, phospholipase C gamma 2; FLT1, FMS-like tyrosine kinase 1; NRP1, neuropilin 1; CSK, carboxy terminal Src kinase.

The expression levels of PLCG2 were found to be significantly downregulated in ccRCC. To confirm this observation, WB, qPCR, and IHC were employed to compare the expression levels of PLCG2 between ccRCC tissues and adjacent normal tissues. Both WB and qPCR results indicated a marked reduction in PLCG2 expression in ccRCC tissues (Fig. 2A,B). This finding was further supported by IHC analysis (Fig. 2C). Additionally, we confirmed the downregulation of PLCG2 in ccRCC cell lines compared to normal renal cell lines (Fig. 2D,E). In conclusion, these results collectively validated the downregulation of PLCG2 in ccRCC.

Fig. 2.

PLCG2 was downregulated in ccRCC tissues and cell lines. (A) The protein expression of PLCG2 in 12 pairs matched normal and cancerous tissues and the statistical graph of gray value. In this context, N1 represents the adjacent normal tissue of the first patient, T1 represents the cancerous tissue of the first patient, and so on. (B) The mRNA levels of PLCG2 in 16 pairs matched normal and cancerous tissues of ccRCC patients and the statistical graph. (C) The immunohistochemical analyses of 5 pairs matched normal and cancerous tissues and the statistical graph of IHC score. Scale bar = 50 µm. (D) The protein expression of PLCG2 in ccRCC cell lines (A498, 786-O, CAKI-1, ACHN, OSRC) and human embryonic kidney cell (HEK293) (n = 3) and statistical graph of gray value. (E) The mRNA levels of PLCG2 in ccRCC cell lines (A498, 786-O, CAKI-1, ACHN, OSRC) and HEK293 (n = 3) (*p 0.05, **p 0.01, ***p 0.001, ****p 0.0001). IHC, immunohistochemistry.

ccRCC cells were transfected with lentivirus to investigate the role PLCG2 played in ccRCC. Using qPCR and Western bolt to confirm the mRNA level’s and protein expression’s upregulation compared with the vector group (Fig. 3A,B). Transwell assays suggested that increased PLCG2 expression reduced the ccRCC cells invasion and migration ability (Fig. 3C). Also, CCK-8 assays indicated that tumor cells reduced the ability of proliferation while the PLCG2 were upregulated in ccRCC cells (Fig. 3D). Lipid accumulation is the most remarkable biological feature of ccRCC. To investigate whether the PLCG2 can effect a change in ccRCC cells’ lipid metabolism, the oil red staining assay was used which showed overexpressing the PLCG2 could reduce lipid accumulation (Fig. 3E). Triglyceride determination showed that PLCG2 reduces the triglyceride content in ccRCC cells (Fig. 3F). The findings clearly demonstrate that overexpression of PLCG2 inhibits proliferation, invasion, migration, and lipid accumulation of ccRCC cells.

Fig. 3.

Overexpression PLCG2 inhibited cell proliferation, migration, invasion, and lipid accumulation in ccRCC. (A) Protein expression of A498 and CAKI-1 cells with transfected PLCG2-overpressed lentivirus (n = 3) and the statistical graph of gray value. (B) The mRNA levels of A498 and CAKI-1 cells with transfected PLCG2-overpressed lentivirus (n = 3). (C) The transwell assays were used to evaluate the migration and invasion ability of A498 and CAKI-1 transfected PLCG2 overexpression and the statistical graph was used to compare the number of cells between the PLCG2 overexpression group and vector group (n = 3). Scale bar = 50 µm. (D) Cell proliferation curves of CCK-8 assays for A498 and CAKI-1 transfected PLCG2 overexpression compared with the control group (n = 3). (E) The oil red staining of A498 and CAKI-1 transfected PLCG2 overexpression compared with the control group (n = 3) and the statistical graph of the quantitative oil red staining. Scale bar = 100 µm. (F) The relative TG content in ccRCC cells transfected PLCG2 overexpression compared with the control group (n = 3) (*p 0.05, **p 0.01, ***p 0.001). CCK-8, Cell Counting Kit-8; TG, triglyceride.

Si-RNAs targeted PLCG2 were used to study the function of PLCG2 knocking down plays in cells. As mentioned before, qPCR and WB were used to verify the decreased expression of PLCG2 in protein and mRNA levels (Fig. 4A and Supplementary Fig. 2A,B). The migration and invasion abilities of A498 and CAKI-1 were promoted by PLCG2 downregulation (Fig. 4B). The promotion of proliferation ability was verified by CCK-8 assays (Fig. 4C). The influence of PLCG2 played in lipid metabolism was verified again by oil red staining assay to compare negative control and PLCG2-downregulated group (Fig. 4D and Supplementary Fig. 2C). Triglyceride determination showed that knocking down the PLCG2 improved the triglyceride content in ccRCC (Fig. 4E). It was proved that knockdown of PLCG2 promoted cell proliferation, migration, invasion, and lipid accumulation in ccRCC.

Fig. 4.

Knocking down PLCG2 promoted cell proliferation, migration, invasion, and lipid accumulation in ccRCC. (A) Protein expression of A498 and CAKI-1 cells with PLCG2 knockdown (n = 3). (B) The transwell assays were used to evaluate the migration and invasion ability of ccRCC cells with PLCG2 knockdown. The statistical graph was used to compare the number of cells between the PLCG2 knockdown group and the control group (n = 3). Scale bar = 50 µm. (C) Cell proliferation curves of CCK-8 assays for A498 and CAKI-1 with PLCG2 knockdown and the control group (n = 3). (D) The Oil red staining PLCG2-knockdown group and the negative control group (n = 3). Scale bar = 100 µm. (E) The relative TG content in the PLCG2-knockdown group and the negative control group (n = 3) (***p 0.001, ****p 0.0001). NC, negative control.

To dig deep into the correlation between the PLCG2 and the VEGF signaling pathway, we added the supernatant collected from ccRCC knocking down or overexpressing the PLCG2 group into the medium of HUVEC. The tube formation assays in vitro indicated that HUVEC co-culture with supernatant of PLCG2-overexpressed or PLCG2-knockdown group inhibited or promoted the ability of angiogenesis, respectively (Fig. 5A,B). The tube length of HUVEC co-cultured with overexpression PLCG2 was markedly shorter than HUVEC with negative control, whereas the down-regulated group exhibited the opposite effect (Supplementary Fig. 3A,B). The findings of Western blot indicate that PLCG2 may exert an influence on the process of angiogenesis mediated by VEGFA (Fig. 5C). The results of the ELISA experiment also demonstrated that overexpression of PLCG2 led to increased levels of VEGFA in the supernatant of ccRCC cell lines (Supplementary Fig. 3C). Also, CCK-8 assays suggested that HUVECs co-cultured with the overexpressing PLCG2 group reducing the ability of proliferation (Fig. 5D). As expected, knocking down group improved the proliferation of HUVEC (Fig. 5E). In order to determine whether the role of PLCG2 in promoting angiogenesis is related to HIF-2$\alpha$, we subjected ccRCC cell lines to hypoxic conditions. The results showed that PLCG2 promotes angiogenesis through a HIF-2$\alpha$-independent pathway (Supplementary Fig. 3D). In summary, PLCG2 might affect the ccRCC cell metastasis by inhibiting angiogenesis.

Fig. 5.

PLCG2 played an important role in tumor angiogenesis. (A) The tube formation assays were used to evaluate the ability of pro-angiogenic ability of A498 and CAKI-1 transfected PLCG2 overexpression compared with the vector group (n = 3), scale bar = 50 µm. (B) The tube formation assays were used to evaluate the ability to inhibit the angiogenic ability of A498 and CAKI-1 transfected PLCG2 knocking down compared with the negative control group (n = 3), scale bar = 50 µm. (C) Western blot was used to verify the VEGFA protein down-regulated and up-regulated in PLCG2 overexpression and knockdown group (n = 3) and the statistical graph of gray value. (D) Cell proliferation curves of CCK-8 assays for HUVEC cells culturing with the conditioned medium from A498 and CAKI-1 transfected PLCG2 overexpression compared with the vector group (n = 3). (E) Cell proliferation curves of CCK-8 assays for HUVEC cells culturing with the conditioned medium from A498 and CAKI-1 transfected PLCG2 knocking down compared with the negative control group (n = 3) (**p 0.01, ***p 0.001, ****p 0.0001. CM, conditioned medium; HUVEC, human umbilical vein endothelial cells).

Subcutaneous tumor models were used to verify the function of PLCG2 in vivo (Fig. 6A), and the results of tumor weight and triglyceride determination verified overexpression PLCG2 inhibited tumor proliferation and lipid accumulation in vivo (Fig. 6B,C). The tumor growth curve showed that PLCG2 reduced the tumor growth (Fig. 6D). And the live small animals fluorescent imaging assays were used to evaluate the proliferation and invasion capabilities of ccRCC in vivo (Fig. 6E,F). The findings aligned with the cell experiment. The PLCG2 overexpression group had a smaller range of ccRCC cell metastasis and invasion than the negative control group. These observations confirmed that the function of PLCG2 is to inhibit tumor growth in vivo.

Fig. 6.

The PLCG2 suppressed tumor progression in vivo. (A) Subcutaneous tumor model was constructed by overexpressing PLCG2 lentivirus and negative control cells (n = 6). (B) The statistical graph of tumor weight of the subcutaneous tumor model (n = 6). (C) The statistical graph of relative TG content in subcutaneous tumors (n = 6). (D) Growth curve of subcutaneous tumor (n = 6). (E) Small animal living fluorescence images of the vector and overexpression PLCG2 group in the metastasis model (n = 3). (F) Fluorescence intensity statistical graph of small animal living fluorescence assays (n = 3) (**p 0.01, ***p 0.001).