HIF2α‐induced upregulation of RNASET2 promotes triglyceride synthesis and enhances cell migration in clear cell renal cell carcinoma

Clear cell renal cell carcinoma (ccRCC), the most common malignant subtype of renal cell carcinoma, is characterized by the accumulation of lipid droplets in the cytoplasm. RNASET2 is a protein coding gene with a low expression level in ovarian cancers, but it is overexpressed in poorly differentiated neuroendocrine carcinomas. There is a correlation between RNASET2 upregulation and triglyceride expression levels in human serum but is unknown whether such an association is a factor contributing to lipid accumulation in ccRCC. Herein, we show that RNASET2 expression levels in ccRCC tissues and cell lines are significantly higher than those in both normal adjacent tissues and renal tubular epithelial cells. Furthermore, its upregulation is associated with increases in ccRCC malignancy and declines in patient survival. We also show that an association exists between increases in both cytoplasmic lipid accumulation and HIF‐2α transcription factor upregulation, and increases in both RNASET2 and triglyceride expression levels in ccRCC tissues. In addition, DGAT1 and DGAT2, two key enzymes involved in triglyceride synthesis, are highly expressed in ccRCC tissues. By contrast, RNASET2 knockdown inhibited their expression levels and lowered lipid droplet accumulation, as well as suppressing in vitro cell proliferation, cell invasion, and migration. In conclusion, our data suggest HIF2α upregulates RNASET2 transcription in ccRCC cells, which promotes both the synthesis of triglycerides and ccRCC migration. As such, RNASET2 may have the potential as a biomarker or target for the diagnosis and treatment of ccRCC.

Clear cell renal cell carcinoma (ccRCC), the most common malignant subtype of renal cell carcinoma, is characterized by the accumulation of lipid droplets in the cytoplasm. RNASET2 is a protein coding gene with a low expression level in ovarian cancers, but it is overexpressed in poorly differentiated neuroendocrine carcinomas. There is a correlation between RNA-SET2 upregulation and triglyceride expression levels in human serum but is unknown whether such an association is a factor contributing to lipid accumulation in ccRCC. Herein, we show that RNASET2 expression levels in ccRCC tissues and cell lines are significantly higher than those in both normal adjacent tissues and renal tubular epithelial cells. Furthermore, its upregulation is associated with increases in ccRCC malignancy and declines in patient survival. We also show that an association exists between increases in both cytoplasmic lipid accumulation and HIF-2a transcription factor upregulation, and increases in both RNASET2 and triglyceride expression levels in ccRCC tissues. In addition, DGAT1 and DGAT2, two key enzymes involved in triglyceride synthesis, are highly expressed in ccRCC tissues. By contrast, RNASET2 knockdown inhibited their expression levels and lowered lipid droplet accumulation, as well as suppressing in vitro cell proliferation, cell invasion, and migration. In conclusion, our data suggest HIF2a upregulates RNASET2 transcription in ccRCC cells, which promotes both the synthesis of triglycerides and ccRCC migration. As such, RNASET2 may have the potential as a biomarker or target for the diagnosis and treatment of ccRCC.
According to the Global Cancer Observatory in 2020, the incidence of kidney cancer in males ranks tenth among all cancers in the world. Renal cell carcinoma (RCC) is the most malignant type of kidney cancer and its incidence is recently increasing worldwide [1]. Four main subtypes of RCC are identifiable based on their histopathological classification. They include clear cell renal carcinoma (ccRCC), chromophobe cell renal carcinoma (chRCC), and papillary renal cell carcinoma (pRCC), and collect duct carcinoma. ccRCC is the most common subtype of RCC, which accounts for more than 70% of the total cases, usually accompanying a high rate of metastasis and recurrence [1,2]. Pathological analyses show that ccRCC arises from the epithelial cells lining the lumen of the proximal convoluted tubules in the kidney. Increases in the hematoxylin-eosin (H&E) staining are attributable to rises in cytoplasmic lipid and glycogen content, which caused the cytoplasm to become transparent [3]. Notably, although ccRCC presents a variety of symptoms in its early stages, it often has an asymptomatic clinical manifestation [3,4]. Its clinical diagnosis is hindered by the lack of specific biomarkers, which accounts for its poor prognosis [5]. Therefore, there is an urgent need to identify novel-targeted biomarkers that will enable earlier diagnosis and treatment of ccRCC.
RNASET2 is a single-copy gene located at chromosome 6q27, a region related to cell malignancy and chromosomal rearrangement [6]. It is a secreted protein that is the only member of the Rh/T2/S glycoprotein family expressed in humans. It is present in the cytoplasm outside the perinuclear region, where it colocalizes with endoplasmic reticulum markers and cis/trans-Golgi [7,8]. RNASET2 has diverse functions, including scavenging ribonucleic acid, degradation of self-RNA, modulating host immune responses, etc. [7][8][9][10]. The adipose coexpression networks reveal a correlation between the expression of RNASET2 in adipocytes and the content of triglycerides in humans [11]. Remarkably, RNASET2 exerts its 'antitumor function' independently of its ribonuclease activity [12]. Several studies documented that RNASET2 plays a vital role as a tumor suppressor gene in the progression of ovarian tumors and melanomas. However, a recent study showed that RNASET2 was downregulated in the early stage of gastric adenocarcinoma compared with adjacent noncancerous or normal gastric mucosa tissues, but the knockdown or knockout of RNASET2 did not significantly promote gastric adenocarcinoma cell growth [13]. Meanwhile, Uccella et al. [14] reported that the RNASET2 protein was significantly highly expressed in poorly differentiated neuroendocrine neoplasms of the lung compared with that in well-differentiated tissues. It suggested that RNASET2 may instead have different biological effects that are either tumor type-dependent or related to their stage of progression. Besides, the role of RNASET2 in disrupting lipid metabolism warranted clarification in ccRCC.
In the current study, we show that there are stagedependent variations in the RNASET2 expression level relative to their invariance in normal kidney tissue.
This difference prompted us to clarify if: (a) an association exists among RNASET2 expression levels and ccRCC oncogenesis; (b) dysfunctional lipid metabolism is an underlying mechanism of this pathological condition.

Selective RNASET2 upregulation in clear cell renal cell carcinoma
Although several studies reported that RNASET2 is a tumor suppressor gene in ovarian cancer and melanoma [12,[15][16][17], RNASET2 is overexpressed in poorly differentiated rather than in well-differentiated neuroendocrine neoplasms of the lung [14]. This disconnect prompted us to speculate that RNASET2 may have diverse expression levels and functions in different tumors. The Broad Institute controls a cancer research project entitled the Cancer Cell Line Encyclopedia (CCLE), which originally focused on characterizing DNA copy numbers, DNA mutations, gene expression, and microRNA profiling, as well as assessing DNA methylation status, across nearly 1000 cell lines from over 30 kinds of cancerous tissues. These studies were appended with metabolite profiling in 2019 [18]. CCLE reveals that the expression of RNASET2 is significantly higher in kidney cancer than that in other cancers (Fig. 1A). GEPIA2 (Gene Expression Profiling Interactive Analysis 2) developed from GEPIA has been a valuable resource for gene expression analysis based on tumor and normal samples from the TCGA (The Cancer Genome Atlas) and GTEx (Genotype-Tissue Expression) databases [19]. Since ccRCC is the main type of tumor in kidney malignancy, we analyzed using TCGA datasets at GEPIA2 and found that RNASET2 gene expression was significantly higher in ccRCC tissues compared with that in other cancers (Fig. 1B). Moreover, the expression of RNASET2 mRNA increased significantly in the advanced stages of ccRCC (Fig. 1C).
We then assessed the survival duration of patients with different RNASET2 expression levels using TCGA datasets at GEPIA2. Overall survival analysis showed that ccRCC patients with high RNASET2 expression levels had survival times that were significantly shorter than those ccRCC patients with lower RNASET2 expression levels (Fig. 1D). Disease-free survival (DFS) analyses revealed that the RNASET2 expression level was correlated with DFS of ccRCC patients (Fig. 1E).
To confirm the actual expression level of RNASET2 in cancer tissues obtained from the ccRCC patients in our affiliated hospital, real-time quantitative RT-PCR and western blot analyses were applied, respectively, to detect both the RNASET2 mRNA expression levels and their corresponding protein contents in ccRCC tissues. In 28 ccRCC cases, their expression levels were compared with the corresponding adjacent normal tissues (ANT). The results showed that the RNASET2 expression levels were significantly higher in ccRCC tissues both at both the mRNA and protein expression levels ( Fig. 2A,B). IHC analysis using an RNASET2 antibody confirmed higher RNASET2 protein expression levels than those in the ANT tissues (Fig. 2C). These results agreed with those obtained from the analyses of the TCGA datasets (Fig. 1B). On the contrary, an analysis was performed of an immunohistochemical chip (IHC chip) including 74 pairs of ccRCC tissues and their corresponding ANT. The results showed that the levels of RNASET2 protein were much higher in the poorly differentiated (high-grade) ccRCC (Fig. 2D, E). Then, we determined whether there is a correlation between the RNASET2 protein expression level and several key factors relevant to the patient's health status, including age, gender, tumor size, tumor grades, and clinical tumor node metastasis (cTNM) stages. The results revealed that the RNASET2 protein expression level significantly correlated with the ccRCC grades and Tumor stages (T stages) of ccRCC patients ( Table 1, Fig. 2E,F). In other words, increases in RNASET2 protein expression levels correlated with both rises in ccRCC malignancy and RNASET2 mRNA upregulation. Thus, these agreements strongly suggest that RNASET2 may be a relevant molecular marker for both diagnosis and improved therapeutic management of ccRCC disease.

Upregulation of DGAT1 and DGAT2 expression levels in ccRCC tissues
Abnormal lipid accumulation is the most significant change in a series of different ccRCC phenotypes. On the contrary, the RNASET2 expression levels correlated significantly with the content of triglycerides in humans [11]. We next determined whether the triglyceride synthesis was promoted in ccRCC. Differences in Oil Red O staining intensity showed that the lipid content was much higher in ccRCC tissues than that in its corresponding ANT control (Fig. 3A). Furthermore, lipid droplets completely filled the cytoplasmic area in ccRCC tissue, whereas TEM analysis showed that the mitochondrial density content waned (Fig. 3B). In general, lipid accumulation in the cells is a pathophysiological process that reflects an imbalance between lipid synthesis and lipolysis. Diacylglycerol acyltransferases, DGAT1 and DGAT2, are key enzymes mediating triglyceride (TG) synthesis. They catalyze the esterification of fatty acid-CoA (FA-CoA) and promote TG synthesis from diacylglycerol (DAG). In this study, both DGAT1 and DGAT2 were highly expressed in ccRCC tissue compared with those in the corresponding ANT (Fig. 3C). Notably, according to the analysis of the GEPIA2 database, ccRCC patients with high DGAT1 or DGAT2 expression (normalized by endoplasmic reticulum marker CANX) usually had a shorter survival time (Fig. 3D). On the contrary, cytoplasmic RIP140 protein is one of the critical factors relevant to triglyceride metabolism and it can promote the lipolysis process [20]. Then, RIP140 protein was detected using IHC in ccRCC and ANT tissues. The results showed that RIP140 protein decreased significantly in ccRCC especially in the cytoplasm (Fig. 3C), indicating that the lipolysis process in ccRCC might be inhibited. Moreover, according to the analysis of the TCGA database, a diminished expression of RIP140 content was also correlated with shorter survival of ccRCC patients (Fig. 3D). Therefore, it is presumed that tumor cells extended their survival in advanced stages by enhancing TGs synthesis and inhibiting lipolysis through suppressing fatty acid b-oxidation.
Silence of RNASET2 downregulates TG synthesis, cell viability, cell invasion, and cell migration of VHL-Deficient ccRCC cells Both high expression levels of RNASET2 and TG synthesis-related genes (DGAT1 and DGAT2) in ccRCC prompted us to explore the relationship between them. Real-time quantitative RT-PCR assessed the mRNA expression levels of RNASET2 in VHL-deficient 786-O and 769-P ccRCC cells and human proximal tubular epithelial cells HK-2 cells. RNASET2 expression levels ranged from high to low levels in the following cells: 786-O cells > 769-P cells > HK-2 cells (Fig. 4A). RNASET2 shRNA plasmids were transfected into 786-O or 769-P cells followed by screening with 200 lM G418 (Fig. 4B,C). Both DGAT1 and DGAT2 expression levels were significantly reduced after RNASET2 knockdown (Fig. 4D), whereas the expression levels were invariant of the lipolysis-associated RIP140, ABHD5, and ATGL genes (Fig. S1A). The results of Oil Red O staining showed that the intracellular lipid droplets decreased after RNASET2 knockdown in 786-O and 769-P cells (Fig. 4E), and the lipi-red fluorescence staining was similar (Fig. 4F). To confirm the effect of RNASET2 expression on cell proliferation, real-time cellular analysis (RTCA) using xCELLigenceÒ Real- Values in bar graphs are the mean with SD. Statistical analysis was performed using the Student's t-test (A and B) and one-way ANOVA (E and F). *P < 0.05, **P < 0.01, ***P < 0.001, ****P < 0.0001; ns, not significant.
Time Cell Analyzer was applied. The results showed that cell proliferation was inhibited after RNASET2 knockdown in ccRCC cells (Fig. 4G). The traditional CCK-8 assay also showed that cell proliferation was significantly inhibited in 786-O cells after RNASET2 knockdown (Fig. S1B). Therefore, these results directly indicated that RNASET2 deficiency inhibited ccRCC cell growth in vitro.
In addition, cell invasion and migration are two important indicators for evaluating tumor progression. Both the transwell assay and the scratch wound healing assay showed that the RNASET2 knockdown in ccRCC cells inhibited cell invasion and migration (Fig. 4H,I). Furthermore, the expression was detected of the metastasis-associated gene (MTA2), which is a reflection of cell migratory activity [21]. It was evaluated with the scratch wound healing assay in 786-O cells. The result showed that MTA2 expression level was much lower in RNASET2 knockdown 786-O cells than that in control cells suggesting that RNASET2 knockdown impaired cell migration (Fig. S1C). Taken together, these results suggest that RNASET2 expression is essential for TG synthesis, and the maintenance of cell proliferation, cell invasion, and migration in VHL-deficient ccRCC Cells.
To further confirm the roles of RNASET2 expression in mediating control of the expression levels of the lipids-associated genes, RNASET2 coding sequences were transfected into 769-P ccRCC cells. The results showed that RNASET2 overexpression significantly upregulated the key enzymes mediating triglyceride synthesis: DGAT1 and DGAT2 but not the lipolysis-associated gene RIP140 (Fig. S1D). Meanwhile, RTCA measurements showed that cell proliferation was not influenced (Fig. S1E). These results strongly suggest that RNASET2 mainly influences triglyceride synthesis rather than lipolysis in ccRCC.
HIF2a directly regulates RNASET2 transcription in ccRCC VHL/HIFa pathway is one of the most important regulatory pathways in ccRCC. The tumor suppressor VHL targets HIF1a and HIF2a earmarked for proteasomal degradation [22]. Both HIF1a and HIF2a are hypoxia-induced transcription factors (HIF) in human cells. We evaluated whether HIF1a regulates RNA-SET2 transcription in ccRCC. Using the TCGA datasets, RNASET2 mRNA expression was negatively correlated with VHL mRNA expression in ccRCC (Fig. 5A). The two main HIFa isoforms, HIF1a and HIF2a, have opposing effects on renal cell carcinoma biology, with HIF1a acting as a tumor suppressor, whereas HIF2a is an oncogene [23]. ccRCC tumors that only express HIF2a have higher proliferation rates than those expressing both HIF1a and HIF2a [24]. HIF2a is a necessary key factor for the formation of ccRCC xenografts, whereas the knockdown of HIF1a enhances xenograft formation in cell lines expressing both HIF1a and HIF2a [25]. In the ccRCC 786-O and 769-P cell lines, which are both VHLdeficient, they display intragenic deletions of HIF1a but express wild-type HIF2a [25]. We found that the HIF2a protein accumulated in the ccRCC cases based on the results of western blot analysis while the HIF1a protein was deficient (Fig. S2). CoCl 2 exposure is a generally accepted experimental model that simulates hypoxia and inhibition of HIFa hydroxylation, which results in its accumulation in the cytoplasm. The exposure of ccRCC cells to CoCl 2 , resulted in rises in the accumulation of both the HIF2a and the RNASET2 protein in ccRCC cells (Fig. 5B). Meanwhile, RNA-SET2 mRNA expression also was significantly induced in ccRCC cells after exposure to 150 lM CoCl 2 for 24 h (Fig. 5C). Thus, we speculated that RNA-SET2 is the target gene of HIF2a. Then, chromatin immunoprecipitation-PCR (ChIP-PCR) was performed to determine whether HIF2a interacted with the promoter of RNASET2. We designed the specific PCR primers to amplify a span from À278 to À187 upstream of the transcription start site (TSS) of the RNASET2 gene (Fig. 5D), which is generally considered the promoter region. ChIP-PCR results showed that HIF2a combined directly with the RNASET2 promoter (Fig. 5E,F). To functionally confirm the relationship between HIF2a and the RNASET2 gene, we treated ccRCC cells with a HIF2a inhibitor PT2385, which inhibits the interaction between HIF2a and ARNT (also known as HIFb) thus blocking the activity of HIF2a. After exposure to different concentrations of PT2385 for 24 h, RNASET2 transcription was detected and the results showed that treatment with 0.1 lM PT2385 significantly decreased its expression in ccRCC cells (Fig. 5G). Accordingly, VEGF, the proven target of HIF2a, was also declined in parallel as expected (Fig. 5H). Therefore, these results indicated that the accumulated HIF2a induced RNASET2 expression in ccRCC (Fig. 5I).
Discussion ccRCC, originating from the renal epithelial cells in the kidney cortex, does not only constitute the most frequent type of renal cancer, but it is also the second most prevalent tumor type listed in the urinary system. Its pathological identification includes that its   cytoplasm is full of TGs and glycogens. With H&E staining, lipid droplets caused the cells to appear transparent [1], which was confirmed based on our results with Oil Red O staining. Moreover, our TEM analysis also revealed a high density of lipid droplets and few organelles in the cancerous cytoplasm. Due to the unique characteristics of cancerous tissue, until now there are no effective therapeutic procedures except surgery to delay its progression. One of the possible reasons for the inability to arrest its spread may stem from the huge lipid deposits in the cancerous cytoplasm [26,27]. Despite this insight, there are no novel targets that can reverse ccRCC oncogenesis. If this void can be overcome, it will undoubtedly help in diagnosing and improving the therapeutic management of ccRCC and thereby prolong survival in the early stage of its development.
For tumor biology, RNASET2 is a multifunctional protein, which has dual-directional roles in tumor development. Some studies showed that RNASET2 plays a role as an antitumor gene in ovarian cancer and melanoma [12,17,28]. For example, RNASET2 expression decreased both in ovarian tumors and melanoma and it was negatively correlated with the malignancy of these tumors [12,29]. Moreover, the downregulated expression of RNASET2 is generally associated with drug resistance in the treatment of ovarian cancer [30]. On the contrary, RNASET2 expression is significantly higher in poorly differentiated cancer cells than that in the well-differentiated cancer cells in neuroendocrine neoplasms of the lung [14].
The current study provides suggestive evidence that RNASET2 has the potential to become a new target for ccRCC diagnosis and therapy. In our study, the expression of RNASET2 is significantly higher in ccRCC compared with that in the normal kidney based on TCGA dataset analyses, especially in the advanced stages of ccRCC, which was confirmed in ccRCC and ANT samples collected at our affiliated hospital. It should be emphasized that this expression pattern is somewhat different from prior reports on ovarian cancer research [12]. In addition, patients with high RNASET2 expression in the ccRCC tissues usually had a poor prognosis compared with those with low RNASET2 expression. Therefore, these indicate that RNASET2 high expression in ccRCC tissues may be associated with shorter survival times in ccRCC patients. This inverse relationship is one piece of evidence supporting the notion that monitoring RNA-SET2 expression levels may ultimately serve as a novel diagnostic and therapeutic target in a clinical setting.
There is other evidence suggesting the feasibility of RNASET2 serving as a target to improve the detection and therapeutic management of ccRCC. Haas et al. [11] reported that the high RNASET2 expression in adipocytes was associated with the high content of TG in human serum. Such high levels also underlie the H&E-stained pathological transparency of the ccRCC that results from their high TG content [1]. To clarify the influences of RNASET2 on cell lipid metabolism, we detected the expressions of key genes that are relevant to controlling the TG synthesis and lipolysis pathway. DGAT1 and DGAT2 are two diacylglycerol acyltransferases, which catalyze the terminal and are only the committed step in TG synthesis using diacylglycerol and fatty acyl-CoA. Moreover, DGAT1 is highly expressed in the intestine and it can promote fatty acid (FA) absorption. DGAT1 is also expressed in the testis, liver, and adipose tissues, while DGAT2 is highly expressed in the liver and adipose tissues, but it is expressed at low levels in the intestine [31]. Cytoplasmic Rip140 can interact with perilipin to regulate lipolysis [20]. In the current research, we found that both DGAT1 and DGAT2 expressions were upregulated, but RIP140 was downregulated in ccRCC tissues compared with those in the ANT tissues.
We determined whether there is an association between changes in these lipids-associated genes and alterations in RNASET2 expression levels. Our results documented that the expression of DGAT1 and DGAT2 decreased significantly in ccRCC cells when RNASET2 was knocked down, whereas when RNA-SET2 was overexpressed, the expression of DGAT1 and DGAT2 increased significantly. However, modulation of the RNASET2 expression level did not affect changes in the RIP140 expression levels. These results strongly confirmed that RNASET2 can regulate the lipids-synthesis genes DGAT1 and DGAT2 expression, which leads to increases in triglyceride synthesis and lipid droplet formation in ccRCC cells. Excess amounts of free fatty acids (FFAs) and diacylglycerols (DAGs) in the cell usually lead to lipotoxicity [32], while lipid droplets are generally considered as the central antilipotoxic organelles that control lipotoxicity by sequestering these potentially toxic lipids into inert triglycerides [32][33][34]. Herein, we speculate that RNA-SET2 promoted the synthesis of TGs to resist lipotoxicity in ccRCC.
Moreover, we also investigated the possible pathways relevant to the function of RNASET2 protein in VHLdeficient 786-O cells through immunoprecipitation-mass spectrometry (IP-MS; Fig. S3). The results of IP-MS showed that the proteins that interacted with RNA-SET2 were involved in various signaling pathways in 786-O cells. Besides ribosome proteins, numerous other proteins are involved in the metabolic pathways especially in fatty acid metabolism in the MS list. They include fatty acid-binding protein 5 (FABP5), elongation of very long-chain fatty acid-like 1 (ELOVL1), acyl-CoA synthetase long-chain family member proteins (ACSL3 and ACSL4), and metastasis-associated protein MTA2. Lv et al. [35] reported that FABP5 expression was significantly upregulated in ccRCC and patients with a high expression level of FABP5 were correlated with tumor metastasis classifications that were also predicted to have poor survival. ELOVL1 is an enzyme elongating saturated and monounsaturated fatty acids [36]. Silencing ELOVL1 can reduce the lipidomic profiles and viability of breast cancer cells [37]. In recent years, several studies demonstrated that ferroptosis was involved in the development of varied tumors. ACSL3 and ACSL4 can incorporate polyunsaturated fatty acids (PUFAs) into phospholipids, which is a critical step in ferroptosis [38]. ACSL3 is highly expressed in human lung cancer specimens and it can promote cancer initiation [39]. Oleic acid can protect melanoma cells from ferroptosis in an ACSL3-dependent manner [40]. ACSL4 is upregulated in many cancers, including liver cancer, prostate cancer, breast cancer, and colon cancer [26]. In addition, MTA2 is a metastasis-associated protein, which plays some vital roles during the metastasis of tumors [41,42]. In the current study, there is a correlation between MTA2 expression and RNASET2 expression, as well as cancer cell migration in ccRCC cells. Accordingly, RNASET2 may have some special effects on the development and metastasis of ccRCC through interacting with these target proteins.
Hypoxic status is one of the crucial factors controlling malignant tumor development and metastasis. Uccella et al. [14] reported that the expression of the RNASET2 protein was induced in the HIF1atransfected human breast cancer-derived MCF7 cell line. However, HIF1a activity is often deficient because of the chromosomal 14q loss in some ccRCC cases [43], whereas HIF2a is highly expressed in ccRCC due to VHL deficiency [24]. To investigate the mechanism involved in the regulation of RNASET2 transcription, we performed ChIP experiments in the ccRCC cell line 786-O characterized as having a VHL and HIF1a deficiency like most ccRCC cases. The ChIP-PCR results showed that the transcription of RNASET2 is upregulated by HIF2a directly, which is accumulated in VHL-deficient ccRCC cells.
VHL is one of the most important tumor suppressor genes in humans. Some research documented that the VHL gene is a crucial factor in the pathogenesis of ccRCC. For instance, there are VHL mutations that include loss of chromosome 3p25 where the VHL gene is located, or promoter hypermethylation of the VHL gene in nearly 80% of ccRCC cases [44][45][46][47]. VHL deficiency leads to the accumulation of HIF1a and HIF2a, which are hypoxia-inducible factors. Although HIF2a has a far greater role in ccRCC, its role in tumorigenesis has been less extensively studied than that of HIF1a [48]. Our results employing TCGA database analysis also showed that there was a negative correlation between RNASET2 and VHL expression levels in ccRCC cells. VHL deficiency-induced HIF1a accumulation can be integrated with ARNT in the cells, and then, the integrated complex is transferred into the cell nucleus to activate the transcription of the target genes or downstream genes in the pathways. They include MMP9, VEGF, and PDGF, which can promote both cancer cell proliferation and metastasis [49][50][51]. Thus, most of the drugs applied in the clinics generally target the VHL/HIF1a/VEGF signaling pathway axes. For example, Sorafenib and Sunitinib are two drugs that have been approved for the therapeutic management of advanced-stage renal cell cancer, which can depress the development of renal cell cancer by inhibiting VEGFR, PDGFR, and FLT3 expression levels [3,52]. Bevacizumab, an anti-VEGF recombination monoclonal antibody, can work together with interferon in treating ccRCC [53]. Besides, HIF2a is another critical therapeutic target for ccRCC treatment. Extensive biochemical efforts resulted in optimizing PT2385, a leading HIF2a inhibitor [54], which was later modified and improved and redesignated as PT2977, a second-generation inhibitor (now known as 'MK-6482') [55]. Both of these two inhibitors can block the transcription of HIF2a-targeted genes, including VEGFA, CCND1, and SLC2A1 [56,57]. In the current study, we demonstrated that RNASET2 is also the target gene of HIF2a in ccRCC. Therefore, it is suggested that the HIF2a inhibitors may also block the transcription of RNASET2 gene.
In conclusion, the current research shows that overexpression of RNASET2 is associated with increases in ccRCC progression, especially in poorly differentiated tumors. On the contrary, a negative correlation exists between RNASET2 mRNA and VHL mRNA expressions. Meanwhile, increases in transcription factor HIF2a, in turn, upregulate RNASET2 expression in ccRCC. Moreover, the results show that increases in RNASET2 expression promote increases in gene expression of DGAT1 and DGAT2, which account for rises in both TGs syntheses. These effects ultimately protect the cancer cells and promote cell migration in ccRCC. Therefore, this research provides valuable insight for further etiological clarification of factors controlling ccRCC progression. This endeavor is likely to identify new therapeutic targets such as RNASET2 in the clinics. However, although we elucidated the signaling pathway through which changes in RNA-SET2 expression levels modulate ccRCC oncogenesis in vitro, some important experiments in vivo, such as tumor xenograft in nude mice, are still needed to clarify how such changes affect ccRCC oncogenesis.

Patient specimens and cell lines
This study enrolled subjects visiting the Department of Urology, Shanghai Ruijin Hospital between September 2018 and August 2021. Their clear cell renal cell carcinoma (ccRCC) tissues and adjacent normal tissues (ANT) were obtained during the surgical operation. The study conformed to the standards set by the Declaration of Helsinki was approved by the Ethics Committee of Ruijin Hospital, Shanghai Jiao Tong University School of Medicine, China (approval number: 2018-381). All subjects gave written informed consent before their participation. Twenty-eight pairs of samples including both ccRCC and ANT tissues were collected after surgery for the following experiments. ccRCC cell lines 786-O and 769-P and human proximal tubular epithelial cell line HK-2 were provided by the National Collection of Authenticated Cell Cultures. 786-O cells and 769-P cells were immediately cultured in RPMI1640 medium (Gibco, Waltham, MA, USA) and HK-2 cells were cultured in DME/F12 medium (Gibco) when the cell lines were obtained. All the culture media contained 10% fetal bovine serum (FBS), 100 UÁmL À1 penicillin, and 100 lgÁmL À1 streptomycin, and the cultured cells were kept in 95% humidity and 37°C 5% CO 2 incubator (Thermo, Waltham, MA, USA).

RNA isolation and quantitative Real-Time PCR
Total RNA was extracted with the TRIzol reagent (Invitrogen, Carlsbad, CA, USA). cDNA synthesis of genes was performed with a PrimeScript TM RT Master Mix (Takara, Shiga, Japan). Subsequently, quantitative real-time PCR was carried out with TB GreenÒ Premix Ex Taq TM (Tli RNaseH Plus) mix (Takara). The PCR system was successfully run in Applied Biosystem 7500 (ABI, Waltham, MA, USA). All the primers for real-time RT-PCR analyses were designed by PRIMER PREMIER 6 software (Premier Inc., Palo Alto, CA, USA), which is shown in Table S1.

Immunohistochemistry (IHC) staining
IHC staining was performed after dewaxing and rehydrating paraffin-embedded tissue sections. Subsequently, antigen retrieval was done by boiling the tissue for 15 min in 10 mM citrate buffer, pH 6.0. Then, the Histostain LAB-SA Detection kits (Invitrogen, OR, USA) were applied according to the manufacturer's instructions, and the sections were stained using DAB, while nuclei were counterstained with hematoxylin. After the sample was washed with PBS buffer thrice, the digital images were captured under a microscope (Olympus BX53) equipped with a DP74 409 objective (Olympus, Tokyo, Japan).

Oil red O staining
The Oil Red O staining was followed by the Modified Oil Red O staining kit protocol (Solarbio, Beijing, China). Briefly, the frozen sections or cell slides were fixed in 10% formalin for 10 min and washed with distilled water, and then immersed in 60% isopropanol for 30 s. Then, the slides were immersed into the modified Oil Red O staining buffer immediately for 10 min. Next, the superfluous staining buffer was removed, and then, the slides were washed with 60% isopropanol and distilled water, respectively. Meanwhile, the nuclei were counterstained with hematoxylin for 1 min and washed with distilled water. Finally, the slides were sealed with gelatin and the digital images were captured under a microscope (Olympus) equipped with a DP74 409 objective (Olympus).

Lipi-red staining
Lipi-red staining (DOJINDO, Kumamoto, Japan) evaluated the extent of lipid droplet accumulation. G418 (200 lgÁmL À1 ) exposure was performed to screen for cell stability. The cells were plated and expanded on slides until they reached a density of about 70% at 37°C and 5% CO 2 . One micromolar lipi-red work solution was added and incubated at 37°C 5% CO 2 for 30 min. The cells were washed with PBS thrice and then covered with the antifade mounting solution containing DAPI (Yeasen). The pictures were captured under a microscope (Olympus).

Cell viability assay
The Cell Counting Kit-8 (CCK-8; DOJINDO) evaluated the effect of RNASET2 knockdown on 786-O cell viability. Stable screening cells were isolated by exposure to 200 lgÁmL À1 G418. The cells were expanded until they reached a cell density of about 70% at 37°C 5% CO 2 . CCK-8 (5 mgÁmL À1 ) was added and the cells were incubated at 37°C under 5% CO 2 for 1 h. Optical density (OD) was read on a microplate reader at an absorbance value of 450 nm (Thermo). Three independent experimental replicates were performed.

Transmission electron microscopy (TEM) analysis
Tissues for TEM were prepared just following the protocols [58]. Briefly, small pieces of ccRCC tissues and ANT tissues were immersed in 2.5% glutaraldehyde solubilized in 0.1 M phosphate buffer (pH 7.4) for 1 day. The tissues were then fixed in 1% osmium tetroxide and dehydrated through a graded ethanol series, and embedded in Epon 618 (TAAB Laboratories Equipment, Berks, UK). Ultra-thin sections (70~90 nm) sliced from the tissues were stained with lead citrate and uranyl acetate and then examined at 100 kV with a Philips CM-120 (Philips, Eindhoven, the Netherlands).

Real-Time cell analysis (RTCA)
A real-time cell analysis experiment is a more accurate method to estimate cell states using micro-electronic biosensor technology. This method detects time-dependent changes in cell proliferation in real time. Briefly, 50 lL of cell culture medium was added to each well of the RTCA plate to establish a baseline. Then, 100 lL of a cell suspension containing about 5000 cells was added to each well. Finally, cells were auto-scanned using RTCA xCELLigence system (ACEA Biosciences, San Diego, CA, USA) every 15 min.

Scratch wound healing assay
To measure cell migration, a scratch wound healing assay was performed. ccRCC cells transfected with RNASET2 shRNA-pGPU6/GFP/Neo plasmids and scramble sequence-pGPU6/GFP/Neo plasmids (control) were planted in 6-well plates with horizontal lines predrawn on the plate back, respectively. Cells grew to form a monolayer at 37°C 5% CO 2 under normoxic conditions overnight. Subsequently, cells were removed from the plates by scratching their surfaces with 10 lL pipette tips to create vertical wounds perpendicular to the drawn horizontal lines. Wells were washed thrice with PBS to remove the floating cells, and then, fresh RPMI1640 medium without FBS was added to the wells. The transfected cells 786-O and 769-P were incubated at 37°C, 5% CO 2 conditions for 15 and 31 h, respectively, depending on their migration rate. Then, the photographs were captured under the inverted microscope (Olympus). Five fields were randomly selected and the scratch wound healing was analyzed with IMAGEJ software (NIH, Bethesda, MD, USA).

Transwell assay
The upper transwell chamber was coated with a cell suspension containing 10 9 10 4 ÁmL À1 cells and Matrigel 200 lL with serum-free RPMI-1640 medium was added to this chamber, and 600 lL RPMI-1640 medium containing 20% fetal bovine serum was added to the lower chamber, respectively. The upper chamber was carefully immersed in the lower chamber liquid. A plate consisting of 24-well transwell chambers was incubated at 37°C under 5% CO 2 for 24 h. The liquid was removed from the upper chamber and washed thrice with 600 lL PBS. After staining, the upper chamber with crystal violet was observed under a microscope and photographed (Olympus). Three independent experimental replicates were performed.

CoCl 2 treatment
ccRCC cell line 786-O cells or 769-P cells were planted in a 6-well plate and incubated at 37°C, 5% CO 2 overnight. Then, the cells were incubated with fresh RPMI1640 media containing 10% FBS and treated with 0, 50, 100, 150, and 300 lM CoCl 2 , respectively, for 24 h. Cells were harvested and washed thrice with PBS buffer, and then applied for use in various experiments.

PT2385 treatment
Cells were placed in a 6-well plate and incubated at 37°C under 5% CO 2 overnight. Then, the medium was replaced with fresh RPMI1640 medium containing 10% FBS and exposed to 0.01, 0.1, 1.0, and 10 lM PT2385, respectively, for 24 h (control: DMSO). Cells were harvested and washed thrice with PBS buffer and then applied for use in various experiments.

Coimmunoprecipitation and mass spectrometry (MS)
For MS analysis, coimmunoprecipitation was performed according to Capturem TM IP & Co-IP Kit (Takara). Briefly, 786-O cells were washed with cold PBS once the culture media was removed. The cellular lysate was prepared using lysis/equilibration buffer and incubated on ice for 15 min and then centrifuged at 17 000 9 g for 10 min at 4°C. The supernatant was transferred into a new 1.5 mL tube and incubated with RNASET2 antibody on a rotator at 4°C overnight. Next, 100 lL of lysis buffer was added to a spin column in a provided collection tube for equilibration, and then, the tube was centrifuged at 1000 9 g for 1 min at room temperature. The column was placed into a new collection tube following loading of the protein-RNASET2 antibody mixture and centrifuged at 1000 9 g for 1 min at room temperature. Finally, the sample flowthrough was saved for MS analysis. The MS analysis was performed with the Orbitrap Fusion Lumos spectrometer (ThermoFisher Scientific). The peak list MS features were annotated using KEGG (Kyoto Encyclopedia of Genes and Genomes) pathway analysis.

Chromatin immunoprecipitation-PCR (ChIP-PCR)
786-O cells were cross-linked with formaldehyde, and chromatin was isolated and sheared by the Bioruptor Sonication System (Diagenode, Liege, Belgium) to obtain an average fragment size of 200~1000 bp. Sheared chromatin fragments were incubated with the anti-HIF2a antibody (NB100-122; Novus). Meanwhile, an equal concentration of nonspecific IgG was used as the negative control. The immunoprecipitated protein-DNA complex was obtained using protein A/G immunomagnetic beads, and DNA was isolated by the standard phenol/chloroform/ethanol precipitation method. PCR was amplified with the RNASET2 primers (forward primer 5 0 -GGTGGTCTAGGTTAGCTC GG-3 0 ; reverse primer: 5 0 -GCTGTGTTCCTTCGCCAC-3 0 ). The amplicon was corresponding to the À278 to À187 region located the upstream of RNASET2 transcript start site (TSS).

Statistical analysis
All data were analyzed using the SAS 8.2 software (SAS Institute Inc., Cary, NC, USA), and results are presented as mean AE SD. The paired t-test or Student's t-test was used where appropriate. A one-way analysis of variance test was used assuming a two-tailed hypothesis with P < 0.05. The survival curves were plotted using the Kaplan-Meier method, and the differences were assessed using the log-rank test. P < 0.05 was considered a statistically significant difference. The gray values of western blot bands were analyzed by IMAGEJ software (NIH). In addition, the survival time of subjects was calculated from the date of surgery to the date of death. Statistical analysis of survival time was carried out using the Kaplan-Meier survival test. Meanwhile, the cancer genome atlas program (TCGA) and the online tool GEPIA2 (gepia2.cancer-pku.cn) were also applied to analyze the survival curve.

Supporting information
Additional supporting information may be found online in the Supporting Information section at the end of the article. Table S1. Primer sequences for qPCR. Fig. S1. Effects of RNASET2 knockdown or overexpression on ccRCC cells. (A) RNASET2 knockdown in 786-O cells had no significant effect on the expression of lipolysis-related genes, n = 6; (B) Viability of 786-O cells was evaluated with the CCK-8 kit. The results showed that RNASET2 shRNA transfection suppressed this parameter, n = 4; (C) RNASET2 knockdown downregulated metastasis-associated genes MTA2 in 786-O cells, n = 6; (D) RNASET2 overexpression in 769-P cells upregulated the expressions of DGAT1 and DGAT2 but did not influence RIP140 expression, n = 6; (E) RNASET2 overexpression in 769-P cells did not influence cell proliferation. Values in bar graphs are the mean with SD. Statistical analysis was performed using the Student's t-test. *P < 0.05, **P < 0.01, ****P < 0.0001; ns, not significant. Western blot analysis showed that the HIF1a protein was deficient in ccRCC tissues; (B) Western blot analysis showed that the HIF2a protein expression level was higher in ccRCC tissues than that in ANT.