Integrated multi-omics characterization reveals a distinctive metabolic signature and the role of NDUFA4L2 in promoting angiogenesis, chemoresistance, and mitochondrial dysfunction in clear cell renal cell carcinoma

Global metabolic profile distinguishes ccRCC from normal renal tissue

Untargeted metabolomic analysis was performed on 60 kidney-derived tissues, including 20 normal tissues and 40 ccRCC (Supplementary Table 1), using LC-MS and GC-MS platforms. In total, 516 metabolites were identified, and 344 were found to be differentially expressed in tumor tissues compared to normal samples (168 higher and 176 lower) (Figure 1A). The application of principal component analysis (PCA) to separate normal and pathological samples as a function of the global tissue metabolome demonstrated that the two groups were clearly distinguishable (Figure 1B).

Figure 1. Volcano plot of the 516 metabolites profiled. 344 exhibited significant differential abundance when comparing ccRCC to normal kidney tissues (A). Principal component analysis (PCA) of global tissue metabolome demonstrated that the two groups (ccRCC vs normal renal tissue) were clearly distinguishable (B). ChemRICH set enrichment statistical plot. Each node reflects a significantly altered cluster of metabolites. Node sizes represent the total number of metabolites in each cluster set. The node color scale shows the proportion of increased (red) or decreased (blue) compounds in tumor compared to normal tissue. Purple color nodes have both increased and decreased metabolites (C). Hierarchical cluster analysis and heatmap of metabolite-metabolite correlation matrix. Metabolite clusters are indicated (D). Integrated metabolic pathway enrichment analysis. The stacked bars show a summary of the joint evidence from enrichment and topology analyses (E).Gene Set Enrichment Analysis (GSEA) of the GSE47032 dataset (F).

To obtain a global overview of altered biochemical processes, we performed a metabolite set enrichment analysis (MSEA) using MetaboAnalyst 3.0 [13], and an alternative enrichment analysis based on chemical similarity (ChemRICH) [14]. These functional approaches showed that the lipid metabolism and alterations in glucose utilization had the highest impact in ccRCC metabolism (Figure 1C; Supplementary Figures 1 and 2; Supplementary Table 2).

To gain additional insight into cellular metabolites status, we also employed a metabolite–metabolite correlation approach. The correlation heatmap identified 5 main blocks including highly correlated metabolites in the following compound classes: lipids, glucose metabolism-related compounds, pentose phosphate pathway metabolites, one carbon metabolism, and dipeptides (Figure 1D).

Metabolic perturbations of glucose metabolism in clear cell RCC

A hallmark of many cancers is an increased glucose utilization through glycolysis with lactate production regardless of oxygen availability (Warburg effect). A clear signature of an increased glucose uptake (glucose transporter GLUT1 was over-expressed in ccRCC, Supplementary Figure 3) and utilization was observed in tumor samples, glucose being significantly elevated, along with higher levels of other sugars (fructose and sorbitol) and their phospho-derivatives. Glycogenolysis was also activated in ccRCC, and significant elevations in glycogen synthesis/degradation products were observed. In particular, maltose, maltotriose, maltotetraose, maltopentaose, and maltohexaose were significantly elevated (ranging from 11-fold to 85-fold higher) in tumor tissue. The increased glucose availability was accompanied by elevations in upstream glycolytic intermediates (glucose 6-phosphate, fructose 6-phosphate and fructose 1,6-bisphosphate), reductions in downstream intermediates (3-phosphoglycerate, 2-phosphoglycerate, and phosphoenolpyruvate) and increased lactate production. Moreover, the higher levels of glucose 6-phosphate and fructose 6-phosphate, associated with the increased tissue level of ribulose 5-phosphate, suggested an increased shunting of the metabolites of the upper part of glycolysis into the pentose phosphate pathway (Figure 2A).

Figure 2. Schematic model summarizing the differences in glucose metabolism (A) and pentose phosphate pathway (B) between normal and tumor tissue.

Alterations in pentose phosphate pathway (PPP) activity

In addition to the observed changes in glycolytic intermediates, metabolites related to PPP activity were also altered in the tumor samples. The PPP supports key aspects of accelerated tumor growth, generating precursors for nucleotides synthesis and NADPH for anabolic reactions and redox homeostasis.

An increased glucose utilization through this pathway was observed in ccRCC tissue, as shown by higher levels of the intermediates sedoheptulose 7-phosphate, ribose 5-phosphate, and ribulose 5-phosphate/xylulose 5-phosphate (isobaric compounds). Interestingly, the tissue levels of several pentitols produced from these intermediates, such as arabitol, xylitol, and xylonate, were significantly reduced in the pathological samples, suggestive of an increased PPP activity serving to generate nucleotides (Figure 2B). In addition to supporting nucleotide biosynthesis, an increased NADPH generation through the PPP is important to supply the reducing power necessary for lipid biosynthesis and to maintain the cellular antioxidant glutathione in its reduced state. In particular, the difference in metabolites production between upper and lower glycolysis, in association with the upregulation of glucose-6-phosphate dehydrogenase (G6PDH), suggests that the metabolic flux through this pathway may be differentially partitioned [15]. In fact, while the sugars produced in the upper part of glycolysis are diverted to the PPP to promote both anabolic reactions and redox homeostasis, the triose phosphates generated in the lower part are rerouted towards the TCA cycle and one-carbon metabolism.

Changes in tricarboxylic acid (TCA) cycle intermediates and related metabolites

Through glycolysis the glucose metabolism contributes to an increased production of the TCA cycle intermediate, citrate, which can be exported to the cytoplasm and used for lipid synthesis. In addition, many cancer cells utilize the amino acids glutamine and glutamate via glutaminolysis to replenish the TCA cycle. In cancer tissues, citrate and succinate were markedly increased but fumarate and malate were both decreased, suggestive of a metabolic signature that may be consistent with an increased glutaminolysis, because pyruvate levels were maintained and lactate was elevated. In fact, nearly all the amino acids were significantly reduced in tumor tissue, with the exception of glutamine and glutamate, which were significantly elevated (Figure 3A). Taken together, these findings suggest that mitochondrial bioenergetics and oxidative phosphorylation processes are impaired in ccRCC. In addition, the different expression of TCA metabolites, in association with increased levels of glutamine, indicates the activation of reductive carboxylation in ccRCC.

Figure 3. Schematic model summarizing the differences in tricarboxylic acid (TCA) cycle metabolites between normal and tumor tissue (A). Alterations in amino acid and lipid metabolism (B).

An important metabolic adaptation observed in tumor cells is the reported increased lipid biosynthesis for cellular proliferation, membrane formation and cell signaling. In particular, de novo lipogenesis and cholesterogenesis are sustained by conversion in the cytosol of citrate to acetyl-CoA by ATP citrate lyase (ACLY). In this context, the abundance of citrate in ccRCC offers a fundamental substrate for the lipogenesis and lipid metabolism changes observed in this tumor (see below).

In addition to changes in energetics, the significant increase in the oncometabolite 2-hydroxyglutarate (2-HG) is consistent with the findings of a recent study that demonstrated that the increased level of 2-HG in ccRCC was associated with reduced levels of 5-hydroxymethylcytosine (5hmC) in genomic DNA. These results are in accordance with the ability of 2-HG to inhibit TET enzymatic activity [16].

Integrated metabolomics/transcriptomic signature

To compare the relative changes in gene expression and metabolite abundance in ccRCC, we integrated the metabolomics data with gene expression data from 10 ccRCC tumor samples and matched non-tumor kidney tissues samples obtained from patients who underwent nephrectomy in our department (GSE47032). The combined analysis identified 20 significantly enriched biochemical pathways (p<0.05), including those of glycolysis and fatty acid metabolism (Figure 1E).

Human renal tumor cells display an altered expression profile of metabolic and damaged mitochondria-associated genes

Gene Set Enrichment Analysis (GSEA) [19] of the GSE47032 dataset showed that ccRCC featured multiple enriched gene sets depicting HIF-1 and hypoxia pathway activation, glycolysis and an enhanced lipid metabolism (Figure 1F).

To gain further insight into the specific contribution of renal cancer cells to the global metabolic profile of ccRCC, 5 clones of normal renal tubule epithelial cells and 6 clones of primary renal cancer cells, derived from different patients, were used for genome-wide gene expression profiling by oligonucleotide microarray (Dataset GSE117890). Primary renal cancer cells showed a distinct gene expression profile, with 302 differentially expressed genes. In this aberrant gene expression signature, we found the overexpression of molecules involved in cell metabolism such as PTG/PPP1R3C (involved in glycogen metabolism), CA IX and XII (pH homeostasis), ENO2 and PFKFB4 (glucose metabolism), as well as ACLY and HILPDA (lipogenesis and cholesterogenesis). Interestingly, NADH dehydrogenase (ubiquinone) 1 alpha sub complex 4-like 2 (NDUFA4L2, Gene ID: 56901), was the most highly expressed gene in cancer cells compared with normal tubular cells (absolute FC = 86.180; Log FC = 6.43). This gene was also highly expressed in the GSE47032 dataset. To confirm the above findings, we analyzed the differential expression of NDUFA4L2 mRNA by data mining of the Oncomine microarray gene expression datasets (Supplementary Table 3). In accordance with our results, NDUFA4L2 was significantly upregulated in all the ccRCC datasets (global P=1.30 E-11). In addition, exploration of the Metabologram Data Portal showed the abundance of succinate, reduced levels of malate and fumarate, and the upregulation of NDUFA4L2 in tumor tissues (Supplementary Figure 4). These findings are consistent with a reduced oxidative phosphorylation rate in ccRCC.

NDUFA4L2 is a HIF-1 target gene encoding for a regulatory protein that attenuates mitochondrial oxygen consumption through the inhibition of Complex I activity [20]. The gene expression profile also showed the overexpression of two genes (SPATA18 and ATG9A) encoding for proteins that are recruited to damaged mitochondria to mediate mitochondrial quality control mechanisms [21,22].

In addition, we observed a reduced expression of the RUVBL complex genes (RUVBL1 and ACTL6A). RUVBL1, and its interacting protein ACTL6A, have been shown to respond to the cell’s metabolic state, regulate mTORC1 signaling activity, and they are positively correlated with transcripts encoding proteins with a mitochondrial function [23]. Finally, a reduced expression of genes encoding mitochondrial ribosomal proteins (MRPS9 and MRPL3) was found (Supplementary Figure 3). Gene Ontology (GO) enrichment analysis performed using ClueGO [24] showed how HIF-mediated metabolic pathways and mitophagy were the most significantly overrepresented biological processes in renal cancer cell (Supplementary Figure 6).

The primary ccRCC cell line, in fact, exhibited reduced levels of mitochondrial DNA, mitochondrial mass (MitoTracker Red) and produced lower levels of ATP, as compared to normal cells. These levels were rescued when cancer cells were treated with small interfering RNA (siRNA) targeting NDUFA4L2 (siNDUFA4L2) (Figures 4 and 5). In addition, we observed an increased expression of the autophagic marker LC3, that colocalized with the mitochondrial label MitoTracker (Figure 4B). When NDUFA4L2 was silenced, we observed reduced LC3 levels, and an increase in fluorescence intensity of MitoTracker, suggesting an impaired mitochondrial degradation [25].

Figure 4. Immunofluorescence showing the increase in MitoTracker signal levels in ccRCC cells treated with small interfering RNA targeting NDUFA4L2 (siNDUFA4L2) compared to untreated cells (A). The autophagic marker LC3 is increased in ccRCC cells and co-localizes with the mitochondrial label MitoTracker. A line profile is shown (B). NDUFA4L2-silenced cancer cells show an increased superoxide radicals production (C), high levels of phospho-H2AX (C), a significant accumulation of 8-oxodG (D), and a reactive increased expression of the DNA repair enzyme OGG1 (D). NDUFA4L2 silencing increased the membrane potential in cancer cells, as shown by increased signals of the fluorescence probe TMRE (E).

Figure 5. Wounded normal and tumor cell monolayers were photographed 24 and 48 hours after the mechanical scratch and the area of the wounds was measured in 3 independent wound sites per group. When specified, the cells were treated with small interfering RNA targeting NDUFA4L2 (siNDUFA4L2). RCC cells treated with siNDUFA4L2 have decreased cell migratory capabilities compared with untreated tumor cells (A). Chick embryo chorioallantoic membrane angiogenic assay: when tumor cell are treated with siNDUFA4L2, a lower vascular reaction is detectable (B). NDUFA4L2 has a role in RCC resistance to cisplatin (CDDP)-induced cytotoxicity (C). The death rate of treated tumor cells (tumor+ siNDUFA4L2+CDDP) is significantly higher than that of untreated cells (tumor+CDDP) (P<0.001). No difference is observed in normal cells. MTT assay reveals significantly decreased cell viability when RCC cells are treated with siNDUFA4L2 before cisplatin incubation (C). RCC cells exhibit reduced levels of mitochondrial DNA, and produced lower levels of ATP, as compared to normal cells. These levels are rescued when cancer cells are treated with siNDUFA4L2 (D). NDUFA4L2 specifically inhibits mitochondrial complex I but not complex IV activity (D).

Moreover, NDUFA4L2 silencing increased the membrane potential and reactive oxygen species (ROS) production in cancer cells, as shown by increased signals of the fluorescence probe TMRE and the mitochondrial superoxide indicator MitoSOX (Figure 4E).

Since NDUFA4L2-silenced cancer cells showed an increased ROS production, and superoxide radicals can induce histone modifications, we analyzed the phosphorylation of the H2AX histone. In particular, we observed increased phospho-H2AX levels in cancer cells when NDUFA4L2 was silenced, suggesting that NDUFA4L2 plays an important role in ROS control and that its loss generates cell stress (Figure 4C).

Considering that 8-oxo-7,8-dihydro-2’-deoxyguanosine (8-oxodG) is one of the predominant forms of free radical-induced oxidative lesions in DNA damage, and that 8-oxodG is repaired by enzyme 8-oxoguanine-DNA glycosylase (OGG1), we evaluated their expression in NDUFA4L2-silenced renal tumor cells. When NDUFA4L2 was silenced, we observed a significant accumulation of 8-oxodG, as a consequence of a reactivation of oxidative phosphorylation (Figure 5) and ROS production, and a reactive increased expression of the DNA repair enzyme OGG1, that prevents excessive oxidative DNA damage in cancer cells (Figure 4D).

Taken together these findings, in association with the particular metabolomic profile (partitioned metabolic flux through glycolysis), are suggestive of an altered mitochondrial function in ccRCC (impaired mitochondrial bioenergetics and oxidative phosphorylation, and NDUFA4L2 overexpression), and indicate the activation of compensatory mechanisms to keep mitochondrial ROS under control, in association with increased levels of cellular antioxidants (glutathione, tocopherol, and ascorbate).

NDUFA4L2 expression is increased in neoplastic tissue and is a risk factor for ccRCC progression and mortality

To analyze the transcription levels, we firstly performed quantitative real-time PCR and evaluated NDUFA4L2 mRNA levels in ccRCC tissue samples compared with normal renal parenchyma (Supplementary Figure 5). Normalized gene expression levels for NDUFA4L2 were significantly higher in ccRCC as compared with normal tissues.

Next, to analyze the expression and location of NDUFA4L2, we performed immunohistochemistry on normal and pathological tissues, eliciting results consistent with the gene expression levels (Figure 6). NDUFA4L2 protein levels were significantly higher in ccRCC than in healthy tissue (P=0.0005). Detailed clinical and pathological characteristics of the patients are summarized in Supplementary Table 4. Kaplan-Meier survival curves for cancer-specific survival (CSS) and progression-free survival (PFS), stratified by NDUFA4L2 tissue expression, are shown in figure 7. Both CSS and PFS were significantly decreased in patients with high levels of NDUFA4L2. Univariate analysis for the predefined variables showed that the pathological stage, presence of nodal and visceral metastases, Fuhrman grade, presence of necrosis, tumor size, and high levels of NDUFA4L2, were significantly associated with the risk of death (Table 1) and progression (Table 2). At multivariate analysis by Cox regression modeling, the pathological stage, presence of nodal and visceral metastases, Fuhrman grade, and increased expression of NDUFA4L2, were independent adverse prognostic factors for CSS and PFS (Tables 1 and 2).

Figure 6. NDUFA4L2 expression in normal (n=20) and ccRCC (n=390) specimens.

Figure 7. Kaplan-Meier cancer-specific survival (CSS) (A) and progression-free survival (PFS) (B) curves, stratified by NDUFA4L2 tissue expression levels. Patients with higher NDUFA4L2 levels had reduced CSS and PFS as compared to patients with lower values.

NDUFA4L2 has a role in cancer cell migration and angiogenesis, and decreases cisplatin-induced renal cancer cell death

To study the role of NDUFA4L2 in renal cancer cell proliferation, migration, angiogenesis and chemoresistance, in vitro and in vivo assays were performed. The scratch wound healing assay showed that primary ccRCC cells treated with siNDUFA4L2 had a decreased migratory ability compared with normal cells (Figure 5A). To investigate the angiogenic response, suspensions of tumor cells alone, or treated with siRNA, were seeded on the top of the chick embryo chorioallantoic membrane (CAM) and their ability to induce the formation of new vessels was histologically evaluated. In particular, the CAM assay showed that gelatin sponges soaked with the tumor cells suspension were surrounded by numerous allantoic vessels that developed radially toward the implant in a spoked wheel pattern (mean ± SD= 28 ± 4 blood vessels). In contrast, few blood vessels were identified around sponges containing tumor cells treated with siRNA targeting NDUFA4L2 (mean ± SD= 14 ± 3; P = 0.001 vs untreated tumor cells) (Figure 5B).

Next, we evaluated the role of NDUFA4L2 in sustaining cancer cell proliferation and in reducing cisplatin-induced cytotoxicity. While the absence of NDUFA4L2 did not significantly affect cell proliferation in normal renal tubular cells, NDUFA4L2-silenced renal cancer cells proliferated at a slower rate than non-silenced cancer cells. In addition, after cisplatin treatment, the death rate of tumor cells treated with siNDUFA4L2 was significantly greater than that of untreated cancer cells (p < 0.001, Figure 5C). The MTT assay confirmed these findings, demonstrating a decreased cell viability when tumor cells were pre-treated with siNDUAFA4L2 before cisplatin incubation (Figure 5C).

Silencing of NDUFA4L2 affects cell viability, increases mitochondrial mass, and induces ROS generation in hypoxia

We used Caki-2 cell lines in normoxic and hypoxic conditions to better analyze the role of NDUFA4L2 in controlling cell proliferation and the autophagic turnover of damaged mitochondria. In normoxic conditions, the silencing of NDUFA4L2 impaired cell proliferation, led to an inhibition of the autophagic machine, and increased the mitochondrial mass, as suggested by higher levels of the mitochondrial protein TOM20 (Figure 8A). These effects were more evident in hypoxia, where the absence of NDUFA4L2 significantly affected renal cancer cell viability. To investigate whether the increased production of ROS in silenced-Caki-2 cells during hypoxic conditions was responsible for the impaired cell viability, we evaluated ROS generation (using the mitochondrial superoxide indicator MitoSOX) and the effects of ascorbic acid 2-phosphate (AA2P) exposure. In NDUFA4L2-silenced cells, during hypoxia we found an overproduction of ROS in association with a significantly reduced cell viability as compared to in normoxic conditions (Figure 8B). Cell proliferation was restored when NDUFA4L2-silenced cells were pre-treated with AA2P, suggesting that an increased mitochondrial ROS generation may be involved in the impaired cell viability observed in hypoxic conditions, as a consequence of a reactivation of oxidative phosphorylation in mitochondria (Figure 8B). These findings were also in accordance with the increased levels of H2AX histone phosphorylation observed in silenced human renal cancer cells, suggesting that the lack of NDUFA4L2 induces cell stress.

Figure 8. Immunoblot analysis of Caki-2 cells cultured under normoxic (21% O2) or hypoxic (1% O2) conditions for 18 hr and probed against NDUFA4L2, LC3, and TOM20 antibodies. Beta actin was used as a loading control (A). The silencing of NDUFA4L2 impairs cancer cell proliferation, inhibits the autophagic machine, and increases the levels of the mitochondrial protein TOM20, especially in hypoxic conditions (B). Cell proliferation was restored when NDUFA4L2-silenced cells were pre-treated with ascorbic acid 2-phosphate (AA2P) (B).

Study population and tissue collection

Investigation has been conducted in accordance with the ethical standards and according to the Declaration of Helsinki and according to national and international guidelines and has been approved by the authors' institutional review board. Written informed consent to take part was given by all participants.

Primary renal tumor (n=40) and non neoplastic tissues (n=20) were collected from patients who underwent radical or partial nephrectomy for ccRCC (Supplementary Table 1). All specimens were immediately used to obtain primary cell cultures after frozen-section confirmation of the diagnosis. Two pathologists confirmed the presence of clear cell RCC in the neoplastic tissues and excluded tumor cells in the healthy specimens. Patients with diabetes mellitus and/or an estimated glomerular filtration rate (MDRD equation) < 60 mL/min/1.73m² were excluded from the study.

For the NDUFA4L2 tissue expression study, tissue samples were collected from 390 patients with ccRCC. Detailed clinical and pathological characteristics of these patients are summarized in Supplementary Table 4. All patients were preoperatively staged by thoraco-abdominal Computed Tomography or Magnetic Resonance Imaging. Tumor staging was reassigned according to the seventh edition of the AJCC-UICC TNM classification. The 2016 World Health Organization and Fuhrman classifications were used to attribute histological type and nuclear grade, respectively.

Metabolite analysis

Primary cell cultures from renal tissues

Tumor (ccRCC) and normal (N) kidney tissue specimens were immediately placed in a Petri dish with phosphate-buffered saline (PBS) 1x and cut into small pieces of about 1 mm³. Each small piece of tissue was placed on the surface of the Petri dish with Dulbecco’s Modified Eagle Medium (DMEM, Invitrogen, Life Technologies, Monza, Italy) supplemented with 10% fetal bovine serum (FBS, Sigma-Aldrich, Milan, Italy) and 1% penicillin-streptomycin-L-glutamine (Sigma-Aldrich, Milan, Italy). Cell proliferation was obtained around the kidney specimens as previously described [27]. Kidney epithelial tubular and neoplastic cells were isolated with EpCAM (CD326) Ab-conjugated magnetic microbeads (Miltenyi Biotec, Bergisch Gladbach, Germany) under the effect of a magnetic field generated by the Mini MACS Separation Unit (Miltenyi Biotec), as previously described⁵. These cells were then characterized for EpCAM, CA IX, and NDUFA4L2 by immunocytochemistry. Primary ccRCC cells were used for proliferation studies at the second passage.

Human cell lines

Caki-2 was cultured in McCoy's5A medium supplemented with 10% FBS and 1% penicillin-streptomycin-L-glutamine. Normoxic Caki-2 cells (21% O2) were maintained at 37°C in 5% CO₂/95% air incubator. For hypoxic exposure, Caki-2 cell culture dishes were placed in a HERAcell 150i humidified hypoxia workstation (Thermo Scientific, Langenselbold, Germany) at 37°C in 1% O2 for 18h.

Small interfering (siRNA) transfection

Isolated normal and tumor renal cells were cultured at 2x10⁵ cells per well in a 12-well plate with Keratinocyte Serum-Free Medium (KSFM), supplemented with 5 ng/ml recombinant epidermal growth factor (rEGF), 50 µg/ml bovine pituitary extract (BPE) (Gibco, Life Technologies, Monza, Italy ) and 30 ng/ml cholera toxin (Sigma-Aldrich, Milan, Italy). The same procedure was used for Caki-2 cells in McCoy's5A medium supplemented with 10% FBS. The transfection of siRNA was carried out using Lipofectamine 3000 (Life Technologies, Monza, Italy) in accordance with the manufacturer’s procedure. For each transfection, 50 nM of small interfering RNA targeting NDUFA4L2 (siNDUFA4L2) (Qiagen, Hilden, Germania) were used. In transfection experiments, a mock-transfection control was performed by putting cells through the transfection procedure without adding siRNA. The validated non-silencing siRNA sequence AllStars Negative Control siRNA (50 nM, Qiagen, Hilden, Germania) was used as negative control. Each transfection experiment was performed in triplicate. After transfection, normal and tumor renal cells were incubated for 24h and 72h at 37°C in 5% CO2 and used for total RNA extraction, immunofluorescence, wound healing and cell viability assays, respectively.

Caki-2 cells were transfected for 72h at 37°C in 5% CO2 in normoxic conditions. For hypoxia conditions, after 54h from the addition or not of the siRNA, Caki-2 cells were transferred and maintained at 37°C in 1% O2 for 18h. Caki-2 cells were used for western blot, cell proliferation and ROS measurement assays.

Gene expression profile of primary renal tumor cells

Transcriptome data were generated using the HumanHT-12 v3 Expression BeadChip (Release 38, Illumina, San Diego, CA. USA). In this process, 500 ng total RNA were used to synthesize biotin-labeled cRNA using the Illumina®TotalPrep™ RNA amplification kit (Applied biosystems/Ambion, USA). Quality of labelled cRNA was measured using the NanoDrop® ND-100 spectrophotometer and the Agilent 2100 Bioanalyzer. 750 ng biotinylated cRNA was used for hybridization to gene-specific probes on the Illumina microarrays. The Illumina arrays were then scanned with the HiScanSQ.

Microarray statistical analyses were performed with Genespring GX 11.0 software (Agilent Tech Inc., Santa Clara, CA, USA). Identification of genes differentially expressed between primary normal (n=5) and neoplastic renal cells (n=6) was carried out with the Benjamini-Hochberg FDR method and gene probe sets were filtered on the basis of the false discovery rate, FDR, (adjusted-P value with multiple testing on 1000 permutations) and fold-change. The fold-change filter was set at 1.5-fold in each comparison. Only genes that were significantly (adjusted-P value <0.05 and fold-change ≥1.5) modulated were considered for further analysis. The raw data have been deposited in the Gene Expression Omnibus database (GEO accession number GSE117890). Microarray data are MIAME compliant.

Real Time PCR

Total RNA of normal and tumor tissues were reverse transcribed with the High-Capacity cDNA Reverse Transcription Kit (Applied Biosystems Foster City, CA, USA), following the manufacturer’s instructions. Quantitative real-time polymerase chain reactions (PCR) were performed using the iQTM SYBR Green Supermix buffer (6mMMgCl2, dNTPs, iTaq DNA polymerase, SYBR Green I, fluorescein and stabilizers) (BIO-RAD Laboratories, Hercules, CA, USA). The primers used for Real Time PCR are listed in Supplementary Table 7.

Quantification of the mRNA levels was performed on a MiniOpticon Real-Time PCR detection system (BIO-RAD Laboratories). In the PCR reactions, the following protocol was used: polymerase activation at 95◦C for 3 min, followed by 45 cycles at 95◦C for 10 s, 60◦C for 30 s. Melting curves were generated through 60 additional cycles (65◦C for 5 s with an increment of 0.5◦C/cycle). Gene expression results were obtained as mean Ct (threshold cycle) values of triplicate samples. Expression was determined using the 2^-ΔΔCt method. Expression values were normalized to β-Actin.

Data mining using the Oncomine gene expression microarray datasets and Metabologram

NDUFA4L2 gene expression was analyzed using the microarray gene expression datasets deposited in the Oncomine database (https://www.oncomine.org/resource/login.html).

Firstly, to address the differential expression of genes between renal cancer and normal tissues, combined filters were applied to display the corresponding datasets. Cancer Type was defined as Clear Cell Renal Cell Carcinoma; Data Type was mRNA; Analysis Type was Cancer vs Normal Analysis. The expression values of the genes (log2 median-centered intensity) were read from the displayed bar chart. Student’s t test was used to calculate the significance.

In addition, the oxidative phosphorylation pathway was explored using the Metabologram data portal (http://sanderlab.org/kidneyMetabProject), a web-based application that integrates transcriptomic and metabolomics data using both gene expression (derived from TCGA database) and metabolite abundance data (derived from MSKCC metabolomics dataset).

Immunohistochemistry

Immunohistochemical evaluation of NDUFA4L2 and GLUT1 proteins expression was done on paraffin-embedded tissue sections derived from 20 normal kidney samples and 390 tumoral samples. Sections (3 mm) of paraffin-embedded tissue were deparaffinized and rehydrated through xylenes and graded alcohol series. Slides were subjected to specific epitope demasking by microwave treatment at 700 W in citrate buffer (0.01 M, pH 6.0). After antigen retrieval, the tissue samples were incubated for 10 minutes with 3% H2O2 to block endogenous peroxidase activity. Sections were blocked with Protein Block Serum-Free (Dako) at room temperature for 10 minutes and then incubated with anti-NDUFA4L2 antibody (1:100 dilution, Proteintech, Chicago, IL, USA) and anti-GLUT1 antibody (1:200, Novus Biologicals, Littleton, CO, USA) at 4C overnight. Binding of the secondary biotinylated antibody was detected using the Dako Real EnVision Detection System, Peroxidase/DAB kit (Dako, Agilent, Santa Clara, US), according to the manufacturer’s instructions. Sections were counterstained with Mayer's haematoxylin (blue) and mounted with glycerol (Dako Cytomation). Negative controls were obtained by incubating serial sections with the blocking solution and then omitting the primary antibodies. Digital images were obtained using the Aperio ScanScope CS2 device (Aperio Technologies, Vista, CA) and further analyses of the scanned images were performed with the ImageScope V12.1.0.5029 (Aperio). Specific staining was quantified by applying the Positive Pixel Count v9_v10.0.0.1805 algorithm (Aperio) and expressed as percentage of positive pixels in the analyzed area.

Immunofluorescence microscopy

Tumor renal cells (ccRCC cells) were seeded at a density of 2x10⁵ on glass coverslips and left to adhere overnight at 37°C in 5% CO2. The cells were exposed to 50nM of siNDUFA4L2 or incubated in medium without siRNA for 72h. These preparations were double-stained for NDUFA4L2 (Proteintech, Chicago, IL, USA) and MitoTracker™ Red CMXRos (Molecular Probes, Life Technologies, Monza, Italy ); OGG1 (Novus Biologicals, Littleton, CO, USA) and 8-Hydroxyguanosine (Abcam, Cambridge, UK); LC3 (Novus Biologicals Littleton, CO, USA) and MitoTracker™ Red CMXRos; Gamma-H2AX (Abcam, Cambridge, UK) and MitoSOX red (Molecular Probes, Life Technologies, Monza, Italy ). The expression and localization of proteins was evaluated by indirect immunofuorescence and confocal microscopy analysis. Mitocondrial mass was determined by incubating the live cells with 500 nM MitoTracker™ Red CMXRos in growth medium, for 20 min at 37°C, whereas to study mitochondrial superoxide generation, live-cells were stained with 5 μM MitoSOX red for 10 min at 37°C. The cells were fixed using ice-cold 4% paraformaldehyde for 10 min at room temperature. Then the preparations were blocked with 1% BSA in PBS for 1 h at room temperature and incubated overnight at 4 °C with a primary antibody against NDUFA4L2 (1:25 in blocking) or LC3 (1:100 in blocking) or Gamma-H2AX (1:100 in blocking), followed by incubation for 1h at 37°C with the secondary antibody goat anti-rabbit IgG FITC (1:200; Novus Biologicals). To study markers for measuring the rate of oxidative damage to nucleic acids and the proteins involved in oxidative stress-induced DNA demethylation, the preparations were incubated overnight at 4 °C with a primary antibody against 8-Hydroxyguanosine (1:100 in blocking), followed by incubation for 2h with the secondary antibody Alexa Fluor 555 goat anti-mouse (1:200; Molecular Probes). Then, they were washed in PBS and incubated overnight at 4 °C with primary antibodies against OGG1 (1:100 in blocking) followed by incubation for 1 h at 37°C with the secondary antibody goat anti-rabbit IgG FITC (Novus Biologicals Littleton, CO, USA). All preparations were counterstained with TO-PRO-3 (Molecular Probes). Negative controls were performed by omitting the primary antibodies. Specific fluorescence was acquired by a Leica TCS SP2 (Leica, Wetzlar, Germany) confocal laser-scanning microscope using an ×63 objective lens.

Mitochondrial membrane potential

Mitochondrial membrane potential was determined by incubating the cells with the fluorescent dye tetramethylrhodamine ethyl ester (TMRE; Sigma-Aldrich, Milan, Italy). Cells were incubated with 2.5 µM TMRE for 1h at 37°C and subsequently analyzed by immunofluorescence.

Western blot

Normoxic Caki-2 cells and hypoxic Caki-2 cells both with and without siRNA NDUFA4L2 were homogenized in 1X lysis buffer (50 mM Tris-HCl, pH 7.4, 5 mM EDTA, 250 mM NaCl, 0.1% Triton X-100 [Sigma-Aldrich, Milan, Italy, T8787]) supplemented with protease and phosphatase inhibitors (Complete mini [Roche, 11836153001] and phosSTOP [Roche, 04906845001]). 50 µg of protein extracts from each sample were denatured in 4X Laemmli sample buffer [Biorad, #1610747] and loaded into an SDS-polyacrylamide gel for western blot analysis. Western blots were performed using anti b-Actin [Cell Signaling Technology, #3700S], anti-LC3 (Cell Signaling Technology, #12741), and anti-TOM20 (Santa Cruz Biotechnogy, sc-17764). Western blots were developed with the Clarity TM Western ECL substrate chemiluminescence reagent (Biorad, Uppsala, Sweden #1705061) as per manufacturer’s instructions. The densitometric evaluation was performed by the ImageJ software.

Wound healing assay

2×10⁵ normal and tumor renal cells were seeded onto a six-well plate with 2 mL of Keratinocyte Serum-Free Medium (KSFM) to create a confluent monolayer, supplemented with 5ng/ml recombinant epidermal growth factor (rEGF), 50μg/ml bovine pituitary extract (BPE) (Gibco) and 30ng/ml cholera toxin (Sigma-Aldrich, Milan, Italy). Cells were incubated overnight at 37°C, 5% CO2, and then exposed to 50nM of siRNA NDUFA4L2 (Quiagen) or incubated in medium without siRNA for 72h. After 24h from the treatment, a wound was manually created by scraping the cell monolayer with a P200 pipette tip. A reference mark was created on the dish and a time 0 image was acquired. After 24 and 48 hours, additional images were taken in the matched region, and the wound-healing area was quantified with ImageJ software (http://rsbweb.nih.gov/ij/). Each experimental condition was performed in triplicate.

Cell viability assay

Cell viability after exposure to 50nM of siNDUFA4L2 or to siNDUFA4L2 and 10μM cis-Diamminedichloroplatinum(II) (cisplatin) was evaluated using the trypan blue dye exclusion and 3-(4,5-dimethylthiazol-2-yl)-2,5-diphenyltetrazolium bromide (MTT) assay. For the dye exclusion test and MTT assay, normal and tumor cells were seeded at a density of 1.5x10⁵ and 1.5x10⁴ cells in six-well and 96-well plates, respectively (Sigma Aldrich, Milan, Italy) and incubated overnight at 37°C, 5% CO2 . In the first part of the experiment, the cells were exposed to 50nM of siNDUFA4L2 for 72h or incubated in medium alone. In the second part of the experiment, 24h after the addition of siRNA, the cells were treated with cisplatin 10 μM for 1h and 2h. After several washes to remove cisplatin the cells were again incubated in medium with 50nM of siRNA NDUFA4L2 for 48h. Each experimental condition was performed in triplicate.

Cell proliferation and ROS measurement assay

For the cell proliferation assay, 2 × 10⁵ Caki-2 cells were plated in a 10 cm dish, 1 day before exposure to siRNA NDUFA4L2 or to medium alone, and cultured in normoxic conditions. The cells were exposed to 50nM of siNDUFA4L2 for 24h and then treated with 100 μM of ascorbic acid 2-phosphate (AA2P) for 24h. After several washes to remove AA2P, the cells were incubated for 18 h in normoxic or hypoxic conditions. Lastly, the cells were trypsinized and the viable cells were counted using trypan blue.

To study mitochondrial superoxide generation, Caki-2 cells were seeded at a density of 2x10⁵ on glass coverslips and left to adhere overnight at 37°C in 5% CO2. The next day the cells were washed and incubated with siNDUFA4L2 and AA2P, as described above. Caki-2 cells were stained with 5 μM MitoSOX red for 10 min at 37°C and washed three times before imaging. Caki-2 cells were fixed using ice-cold 4% paraformaldehyde for 10 min at room temperature. Then, nuclei were revealed by counterstaining with TO-PRO-3 (Molecular Probes). Images were taken with a Leica TCS SP2 (Leica, Wetzlar, Germany) confocal laser-scanning microscope using an X63 objective lens. Each experimental condition was performed in triplicate.

In vivo chorioallantoic membrane (CAM) angiogenic assay

Fertilized White Leghorn chicken eggs were incubated at 37°C at constant humidity. On day 3 of incubation a square window was opened in the egg shell after removal of 2–3 ml of albumen so as to detach the developing CAM from the shell. The window was sealed with a glass and the eggs were returned to the incubator. Gelatin sponges (Gelfoam, Upjohn Company, Kalamazoo, U.S.A.) were cut to a size of 1 mm3 and placed on top of the growing CAM at day 8 incubation under sterile conditions according to Ribatti et al. [28]. The sponges were then adsorbed with 2 μl of cell suspension of tumor cells or tumor cells incubated with siNDUFA4L2. The angiogenic response was evaluated on day 12 of incubation after the implants by means of a stereomicroscope connected to an image analyzer system (Olympus Italia, Italy). Blood vessels entering the sponges within the focal plane of the CAM were counted by two observers in double blind fashion at a magnification of 50x. Means ± standard deviation (SD) were evaluated and the statistical significance of the differences between counts was determined by Student’s t-test for unpaired data.

Quantification of mitochondrial DNA content

Mitochondrial DNA was isolated from normal, ccRCC and siNDUFA4L2 tumor cells using the Mitochondrial DNA Isolation Kit (Abcam, Cambridge, UK) according to the manufacturer’s instructions. Mitochondrial DNA content was measured using real-time quantitative PCR (qPCR) as previously described. In brief, the relative quantification of mitochondrial DNA content for each sample was determined using a set of mitochondrial specific primers: mt-Mito: forward 5’- CACTTTCCACACAGACATCA - 3’ , reverse 5’- TGGTTAGGCTGGTGTTAGGG – 3’ ; and set of nuclear- specific primers: B2M forward 5’- TGTTCCTGCTGGGTAGCTCT-3’ and reverse 5’- CCTCCATGATGCTGCTTACA-3’ . qPCR was performed with a MiniOpticon real-time PCR detection system (BIO-RAD Laboratories). In the PCR reactions, the following protocol was used: polymerase activation at 95°C for 3 minutes, followed by 45 cycles at 95°C for 10 seconds, 60°C for 30 seconds. Melting curves were generated through 60 additional cycles (65°C for 5 seconds with an increment of 0.5°C/cycle). Each experimental condition was performed in triplicate. The relative mitochondrial DNA content was calculated using the 2^-∆∆Ct method.

ATP assay

Normal cells and ccRCC cells were seeded at a density of 1.5x10⁴ cells in 96-well plates with 200 μL of KSFM, supplemented with 5ng/ml rEGF, 50μg/ml BPE and 30ng/ml cholera toxin, incubated overnight at 37°C, 5% CO2 and then exposed to 50nM of siRNA NDUFA4L2 or incubated in medium without siRNA for 72h. CellTiter-Glo® assay reagent (Promega, Madison, Wisconsin, US) was added in according to the manufacturer’s instructions and the luminescent signal, proportional to the amount of ATP present, was measured using a GloMx-Multi+Microplate Multimode Reader (Promega, Madison, Wisconsin, US). Each experimental condition was performed in triplicate.

Complex I and IV activity

The activities of Complex I and Complex IV were measured in ccRCC cells and siNDUFA4L2 ccRCC cells using the Complex I Enzyme Activity Microplate Assay Kit and Complex IV Human Enzyme Activity Microplate Assay Kit (Abcam, Cambridge, UK), according to the manufacturer’s instructions. Each experimental condition was performed in triplicate.

Availability of data and material

The datasets generated and/or analysed during the current study are available in the GEO repository:

Accession number GSE47032

Accession number GSE117890