Chromophobe renal cell carcinoma (chRCC) accounts for approximately 5% of all renal cancers and around 30% of chRCC cases have mutations in TP53. chRCC is poorly supported by microvessels and has markably lower glucose uptake than clear cell RCC and papillary RCC. Currently, the metabolic status and mechanisms by which this tumor adapts to nutrient-poor microenvironments remain to be investigated. In this study, we performed proteome and metabolome profiling of chRCC tumors and adjacent kidney tissues and identified major metabolic alterations in chRCC tumors, including the classical Warburg effect, the downregulation of gluconeogenesis and amino acid metabolism, and the upregulation of protein degradation and endocytosis. chRCC cells depended on extracellular macromolecules as an amino acid source by activating endocytosis to sustain cell proliferation and survival. Inhibition of the phospholipase C gamma 2 (PLCG2)/inositol 1,4,5-trisphosphate (IP3)/Ca2+/protein kinase C (PKC) pathway significantly impaired the activation of endocytosis for amino acid uptakes into chRCC cells. In chRCC, whole-exome sequencing revealed that TP53 mutations were not related to expression of PLCG2 and activation of endocytosis. Our study provides novel perspectives on metabolic rewiring in chRCC and identifies the PLCG2/IP3/Ca2+/PKC axis as a potential therapeutic target in patients with chRCC.
This study reveals macropinocytosis as an important process utilized by chRCC to gain extracellular nutrients in a p53-independent manner.
Renal cell carcinoma (RCC) accounts for approximately 4% of adult malignancies (1) and was ranked as the sixth deadliest cancer globally in 2018 (2). RCC is composed of different subtypes with distinct histologic and molecular genetic features, mainly clear cell RCC (ccRCC), papillary RCC (pRCC), and chromophobe RCC (chRCC). chRCC is derived from intercalated cells of the collecting duct and comprises approximately 5% of all renal cancers (3). It shows either a relatively transparent cytoplasm, or in about 30% of cases, eosinophilic patterns with mitochondrial accumulation (4).
Until now, only two studies have investigated the genomic and transcriptional features of chRCC (∼100 cases combined; refs. 5, 6). One of the characteristic genetic features of chRCC is monosomy of chromosomes 1, 2, 6, 10, 13, 17, and often 21 (5, 7–10). The most commonly mutated genes in chRCC are TP53 (32%), and PTEN (9%), and gene fusions involving the TERT promoter (5–7). Mutations were also observed at lower frequencies in MTOR, NRAS, TSC1, and TSC2, indicating that genomic targeting of the mTOR pathway occurred in 23% of all chRCC (5). However, both studies failed to find any clear driver mutation in over 50% of chRCC cases.
chRCC was reported to have a significantly lower microvessel density than the other two RCC subtypes, ccRCC and pRCC (11). This is further illustrated by fluorodeoxyglucose-PET (FDG-PET), which can be used to assess the glucose uptake of tumors in vivo; chRCC showed a significantly lower value for FDG-PET than ccRCC and pRCC (12). Hence, chRCC seems to be poorly supported by blood vessels. Because comprehensive investigations and research have focused on the more frequent ccRCC subtype, the genetic alterations and pathologic mechanism of ccRCC have been elucidated. Loss of function of the von Hippel–Lindau (VHL) gene was discovered as the genetic cause of ccRCC and was shown to lead to intensive metabolic aberrations (13, 14). Therefore, ccRCC has been defined as a metabolic disease (13). In contrast, even the very basic metabolic characteristics of chRCC are still unknown, and how chRCC cells adapt to nutrient-poor environments remains to be investigated.
To address these knowledge gaps, integrated proteome, transcriptome, and metabolome analyses, fluorescence imaging and whole-exome sequencing (WES) were employed to comprehensively investigate chRCC. We identified major metabolic reprogramming of gluconeogenesis, amino acid (AA) metabolism, and endocytosis. The phospholipase C gamma 2 (PLCG2)/inositol 1,4,5-trisphosphate (IP3)/Ca2+/protein kinase C (PKC) pathway was proven to play a regulatory role in the activation of endocytosis and therefore to promote chRCC cell proliferation and survival. Our findings may provide an opportunity for the development of potential therapies for chRCC.
Materials and Methods
The chRCC cell line UOK276 (15) was given by Marston Linehan (Center for Cancer Research at the NCI, Bethesda, MD). The ccRCC cell line 786-O and the normal kidney cell line HK2 were obtained from ATCC. The pancreatic cancer cell lines MIA PaCa-2 and BxPC-3 were provided by Ulrich Keller (Charité – Universitätsmedizin Berlin, Germany). All cell lines were cultivated at 37°C in a humidified atmosphere of 5% CO2 in DMEM (Life Technologies) containing 4.5 g/L glucose, supplemented with 10% FBS (Silantes) and 1% penicillin–streptomycin–neomycin (PSN, Invitrogen). No Mycoplasma testing was performed before the experiments.
For the proliferation assays, UOK276 and HK2 cells were seeded in 96-well plates at a density of 2 × 104 cells per well in complete medium. After 12 hours, the cells were briefly rinsed and cultured in minimum essential medium (MEM) supplemented with 10% dialyzed FBS (Thermo Fisher Scientific), AAs with 0%, 1%, and 10% concentration level of MEM, and with 0 or 2.5% BSA. The number of cells was determined after 4 days.
Proteome and metabolome profiling
This study was approved by the institutional Ethics Committee (no. EA1/134/12) of Charité – Universitätsmedizin Berlin and was carried out in accordance with the Declaration of Helsinki. All participants gave written informed consent. The tumor information, proteomic and metabolomic raw data, and analysis were reported previously (10). Proteomic profiling of the UOK276 cells was performed as reported previously (16) in biological triplicates, the raw mass spectrometry (MS) data were processed and analyzed as published earlier (10).
Enzyme activity measurement
Sample preparation for a spectrophotometric assay of enzyme activity was performed as reported previously (17). In brief, approximately 5 mg samples of tumor and healthy kidney tissues were homogenized and centrifuged at 600 g at 4°C for 10 minutes. The protein concentrations of supernatants were further determined with a BCA assay (Thermo Fisher Scientific). The enzymatic activities of hexosaminidases A and B were assayed as previously described by using 4-nitrophenyl N-acetyl-β-D-glucosaminide as an artificial substrate (18). Heat inactivation of hexosaminidase A was performed by preincubation of samples for 3 hours at 48°C (19).
Stable isotopic tracer to quantify protein scavenging by endocytosis
The chRCC cell line UOK276 was initially cultured in normal DMEM (Life Technologies) supplemented with 10% dialyzed FBS and 1% PSN. Then, the medium was modified to Earle's balanced salt solution containing 13C15N-labeled AAs (13C15N-AA; Cambridge Isotope Laboratories) at the same concentrations of DMEM, 10% dialyzed FBS and 1% PSN. UOK276 cells were grown for 10 doublings in 13C15N-AA medium to ensure full labeling of the intercellular proteins and free AAs. After 10 doublings, the cells were seeded at a low cell density in the 6-well plate and switched to 2 mL of 1% 13C15N-AA medium supplemented with 2.5% BSA. After 5 hours, the medium was collected. The cells in each well were washed once with PBS, and then 300 μL of 0.1% Triton X-100 in PBS was added. The cell lysate was collected and sonicated for 1 minute. All of the medium and cell lysate were centrifuged at 1,000 g for 10 minutes at 4°C. After centrifugation, 50 μL of supernatant was placed in a new 1.5 mL tube, and 150 μL of methanol and 10 μL of internal standard (3 μmol/L chloramphenicol) were added and vortexed for 10 minutes with a Thermomixer at 1,400 rpm, then centrifuged for 10 minutes at 18,000 g at 4°C. Finally, 20 μL of supernatant per run was injected into the LC/MS-MS for analysis.
To study the inhibitory effect of PLCG2 pathway inhibitors on endocytosis, cells were treated for 5 hours with different inhibitors [10 μmol/L 5-(n-ethyl-N-isopropyl)-amiloride (EIPA), 30 μmol/L U73122, 100 μmol/L 2-aminoethoxydiphenyl borate (2-APB), 30 μmol/L BAPTA-AM and 3 μmol/L bisindolylmaleimide I (BI)], and then the total AAs in the cells and medium were extracted following the above-described protocol and injected into the LC/MS-MS for relative quantification.
Endocytic BSA uptake assay
The endocytic uptake assay was performed similarly to a previously reported protocol (20). Briefly, BxPC-3, MIA PaCa-2, 786-O, UOK276, and HK2 cells were seeded in a 96-well Screenstar Plate (Greiner) and grown for 24 hours. After starvation for the following 15 hours in serum-free DMEM with 1% PSN, a self-quenched BODIPY dye conjugate of BSA (DQ-Red BSA, 0.1 mg/mL, Molecular Probes) was added to each well. After incubation for 30 minutes, the cells were rinsed with PBS and fixed with 4 % formaldehyde for 10 minutes. Cells were then washed in PBS and stained with 1 μg/mL Hoechst 33242 for 15 minutes and washed again before proceeding to imaging acquisition. All experimental steps were performed using multichannel pipettes and stock solutions to ensure minimal well-to-well variations. Fluorescence imaging was performed using the Zeiss Celldiscoverer 7 operated by ZEN blue3.1. Cells were imaged using a 20×/0.95 Plan-Apochromat-objective with a 1× postmagnification and a Axiocam 506 camera with 2 × 2 binning, resulting in a lateral pixel size of 0.453 μm/pixel. The definite focus 2 hardware autofocus was used to ensure constant object–objective distances. A total of 88 positions (∼50 % well surface) in three channels (for Hoechst 33432, DQ-Red BSA, and transmitted light) were captured automatically. Cells were identified on the basis of nuclear Hoechst signal using a fixed fluorescence threshold. The software module dilated the identified nuclear regions of interest by 20 pixels (=0.906 μm) and quantified the red fluorescence intensities, area, and geometrics associated within that target region.
To validate the role of the PLCG2 pathway in endocytosis, UOK276 cells were seeded in a 96-well plate and grown for 24 hours. After starvation for 15 hours with serum-free DMEM with 1% AA and 1% PSN, DQ-Red BSA (0.1 mg/mL) was added to the wells and incubated for 30 minutes. Fluorescence imaging and analysis was performed as described above.
DNA was isolated from the remaining pellets after metabolite extraction, with a DNA purification kit according to the manufacturer's protocol (QIAmp DNA Mini Kit for Tissues, QIAGEN). In brief, the pellets were lysed with proteinase K, and the RNA was removed by RNase. The RNA-free genomic DNA was then purified and eluted on QIAamp Mini spin columns for library preparation. The library preparation was performed according to Agilent's SureSelect protocol (SureSelectXT Human All Exon V5, protocol version B4 August 2015) for Illumina paired-end sequencing, as reported previously (16).
DNA reads were aligned to the human reference genome hg19 using BWA (bwa-mem 0.7.17-r1188) and sorted, and duplicates were removed using Picard (v2.17.11). Somatic single-nucleotide variants were detected using established pipelines based on VarScan2 (21) and functional annotation of the variants based on Ensembl v.70 was performed using annovar (22). Somatic indels were detected using SAMtools and Dindel (23).
Analysis of The Cancer Genome Atlas RNA-seq data
The Cancer Genome Atlas [TCGA; ID: KICH (chromophobe); KIRC (clear cell)] RNA sequencing (RNA-seq) data were obtained from UCSC Xena (https://xenabrowser.net/; ref. 24). Accurate transcript quantification of chRCC (n = 66) and ccRCC (n = 533) was based on the RNA-seq by expectation maximization method (25).
Statistical rationale and pathway analyses
For proteome and metabolome datasets, a two-sample t test was performed. Multiple test correction was performed by Benjamini—Hochberg (BH) with an FDR of 0.05 by using Perseus (v184.108.40.206; ref. 26). For comprehensive proteome data analyses, gene set enrichment analysis (GSEA, v3.0; ref. 27) was applied to determine whether an a priori defined set of proteins shows statistically significant, concordant differences between chRCC and kidney tissues. Only proteins with valid values in at least 6 of 9 samples in at least one group, with replacement of missing values from the normal distribution for the other group, were used (10). GSEA default settings were applied, except that the minimum size exclusion was set to 10 and Kyoto Encyclopedia of Genes and Genomes (KEGG) v6.2 was used as a gene set database. The cut-off for significantly regulated pathways was set to a P ≤ 0.01 and an FDR ≤ 0.05.
The datasets generated in this study are available as Supplementary Files, and the raw data files were reported previously (10) and are available in the following repositories.
WES files can be accessed via https://www.ncbi.nlm.nih.gov/sra with the accession number PRJNA413158. Proteomics raw data have been deposited in the ProteomeXchange Consortium via the Pride partner repository (28) with the dataset identifier PXD019123. Metabolomics data have been deposited in the publicly available PeptideAtlas repository with the identifier PASS01250 and can be downloaded via http://www.peptideatlas.org/PASS/PASS01250.
Proteome and metabolome profiling of chRCC
To comprehensively understand the metabolic features of chRCC, we employed two systematic omics approaches, MS-based proteome and metabolome profiling, in nine chRCC and adjacent healthy kidney tissue samples (Fig. 1A and B). chRCC derives from the distal tubules, distal and proximal nephrons are known to be metabolically distinct, but we want to emphasize that they colocalize in any given section of the kidney, which serve as healthy controls in our study.
A total of 26,839 peptides and 3,575 proteins were identified in chRCC samples and adjacent healthy kidney tissues from 9 patients, both at a FDR of 1%. 56.9% (2,034) of these proteins were quantified in at least six out of nine samples. Between different samples, the Pearson correlation ranged from 0.659 to 0.921 in chRCC and 0.770 to 0.955 in kidney tissues (Supplementary Fig. S1A). Principal component analysis revealed that the first component distinguished the chRCC specimens and kidney tissues, but with two outliers, the chRCC tumor of patient 4 (C4) and the kidney tissue from patient 9 (K9; Supplementary Fig. S1B). These results indicate high variability within tumor samples, most likely due to differences in microenvironmental conditions or the tumor heterogeneity. A t test with the BH correction for multiple testing was performed to identify significantly (FDR ≤ 0.05) altered proteins between chRCC and the controls. Altogether, 983 significantly regulated proteins were identified, with 390 proteins upregulated and 593 downregulated in chRCC (Fig. 1C). Among these significantly changed proteins, fructose-1,6-bisphosphatase (FBP1), which was shown to oppose ccRCC progression (29), decreased more than 16-fold in the tumors. PLCG2 was increased by over 59-fold in chRCC, and its high transcript level has been considered as a potential biomarker for chRCC (6). Thus, our proteomic analysis could verify known molecular signatures of RCC and serve as a source dataset for subsequent computational analyses.
GSEA revealed several significantly (P ≤ 0.01 and FDR ≤ 0.05) regulated KEGG pathways in chRCC versus healthy tissues (Fig. 1D). The pathways upregulated in chRCC compared with normal tissue included the proteasome, ubiquitin-mediated proteolysis, lysosome, and phagocytosis. In contrast, pathways involved in energy supply chains and nutrient homeostasis, such as lipid metabolism, glutathione metabolism, peroxisome, glycolysis and gluconeogenesis, and AA metabolism, were significantly downregulated in chRCC (Fig. 1D).
Metabolome profiling targeting a panel of 366 metabolites was performed. Metabolite identification was based on three strict criteria to exclude false-positive results: (i) the correct retention time, (ii) up to three multiple reaction monitoring (MRM) transitions, and (iii) a matching MRM ion peak ratio of tuned pure metabolites as a reference (17). With this strategy, 144 metabolites were identified and quantified (Fig. 1E). Statistical analysis using a two-sample t test with the BH (FDR of 0.05) correction for multiple testing revealed 9 significantly (P < 0.01) increased and 19 significantly decreased metabolites in chRCC relative to kidney tissues (Fig. 1E). The top three significantly upregulated metabolites are all related to glutathione metabolism (including both oxidized and reduced glutathione and the glutathione precursor gamma-glutamyl cysteine; Fig. 1E), consistent with a previous study performed in chRCC (30). Interestingly, a similar pattern was reported in other RCC subtypes, including ccRCC (14), pRCC (31), and renal oncocytoma (16, 32). Thus, the increase of glutathione has been proposed as a hallmark of kidney cancer and targeting glutathione metabolism can be exploited as a specific treatment strategy (33).
Gluconeogenesis is completely stalled in chRCC
The KEGG pathway “glycolysis and gluconeogenesis” was significantly reduced in chRCC (Fig. 1D). This pathway describes two opposing metabolic functions: the generation of pyruvate from glucose and vice versa. Thus, the details of this metabolic pathway was examined, and the results showed that all glycolytic enzymes were either unchanged or slightly increased, indicating increased glycolysis in chRCC (Fig. 2A). All enzymes involved solely in gluconeogenesis were dramatically decreased in chRCC, including pyruvate carboxylase (PC, 124-fold), phosphoenolpyruvate carboxykinase 1 (PCK1, 96-fold), PCK2 (996-fold), aldolase B (ALDOB, 922-fold), and FBP1 (29-fold; Fig. 2A). The two aldolase isoforms, A (ALDOA) and C (ALDOC), which were increased in chRCC, have a high affinity for fructose-1,6-bisphosphate (F-1,6-BP) to promote glycolysis, whereas the greatly diminished isoform B has a low affinity for F-1,6-BP and hence promotes the conversion from glyceraldehyde-3-phosphate to F-1,6-BP (34). Furthermore, the decrease in PC, which is the main entry point for pyruvate into the tricarboxylic acid cycle, shows that the tumors rely on lactate fermentation, which was also indicated by significantly increased lactate dehydrogenase A (LDHA; 3-fold) protein levels in chRCC. An analysis with chRCC transcriptome data extracted from TCGA (5) showed similar regulatory effects, with a significant depletion of all transcripts involved in gluconeogenesis (Fig. 2B). Stalled gluconeogenesis can be considered as one of the most relevant metabolic changes observed in this tumor and a hallmark of chRCC.
Previously, we discovered that chRCC has a diminished oxidative phosphorylation capacity (10), combined with a higher abundance of glycolytic proteins, a typical phenomenon of the classical Warburg effect. Hypoxia-inducible factor (HIF), a master transcriptional regulator, can regulate the Warburg effect, glycolysis, and gluconeogenesis in various tumor types and normal tissues (35, 36). In ccRCC, because of VHL loss of function, HIF accumulates and enhances the transcription of its target genes. These target genes are associated with crucial oncogenic pathways, including glucose uptake, glycolysis (e.g., glucose transporter, GLUT), cell proliferation (e.g., EGFR; TGF), and angiogenesis (e.g., VEGF; refs. 37–40). Despite the lack of known genetic alterations of HIF, we wondered whether HIF is involved in the regulation of glycolysis and gluconeogenesis in the context of chRCC. Analyzing and comparing the transcriptome data of ccRCC and chRCC (both datasets from TCGA) showed that all HIF signature targets in ccRCC had increased expression relative to that in the normal kidney (Fig. 2C). In contrast, these genes were almost all downregulated in chRCC, except for VEGFA, which displayed lower expression in chRCC than in ccRCC (Fig 2C). These results indicate that HIF is not involved in the glucose metabolism of chRCC.
Taken together, the above results show that chRCC has disrupted glucose metabolism, in which glycolysis is slightly upregulated while gluconeogenesis is entirely stalled. Unlike in ccRCC, HIF is not involved in the regulation of these alterations in chRCC.
chRCC features depletion of metabolic intermediates and pathways involved in AA metabolism
At the proteome level, 10 distinct pathways involved in AA metabolism were found to be significantly downregulated in chRCC (Fig. 1D). In total, 95 of 114 proteins involved in AA metabolism showed decreased abundance (average 22-fold; Fig. 3A). Altogether, 19 proteins decreased by over 40-fold (BBOX1, HPD, PSAT1, ACY1, DDC, ALDH3A2, CHDH, MAOB, FTCD, EHHADH, DPYS, DMGDH, ALDH4A1, SHMT1, ABAT, ASS1, AGMAT, BHMT, and GATM; Fig. 3A), indicating a major metabolic change. In addition, six pathways associated with fatty acid metabolism were significantly downregulated (Fig. 1D), including fatty acid metabolism and the peroxisome, the main organelle for fatty acid oxidation. Metabolites involved in AA metabolism were among the most depleted in chRCC, matching the decreased protein abundances of AA pathways (Fig. 3B–G). These included guanidoacetic acid (metabolism of multiple AAs, glycine, serine, threonine, arginine, and proline, 16-fold), kynurenic acid (tryptophan metabolism, 16-fold), indoleacetic acid (tryptophan intermediate, 51-fold), ureidopropionic acid (β-alanine metabolism, 6-fold), hippuric acid (glycine metabolism, 22-fold), salicyluric acid (glycine metabolism, 26-fold) and acetylglutamine (glutamine metabolism, 5-fold; Fig. 3B–G). Interestingly, all AAs were either unchanged or negligibly increased; the only exception was glycine, which was nonsignificantly decreased in chRCC (Supplementary Fig. S2). Selected AAs and intermediates were mapped together with the corresponding enzyme abundances onto their pathways to indicate upstream or downstream derivation (Supplementary Fig. S3A–S3C). These results indicate that all metabolic processes that generate AAs were significantly diminished in chRCC, but surprisingly, the amounts of the standard AAs remained unchanged.
chRCC cells feed on extracellular macromolecules via endocytosis to sustain proliferation and survival
chRCC is poorly supported by blood vessels in terms of nutrient supply and has been shown to have a significantly lower glucose uptake than other RCC types (11, 12). In addition, our analyses showed that AA metabolism was significantly downregulated in chRCC (Figs. 1D and 3), but all AA levels remained unchanged (Supplementary Fig. S2). We hypothesized that chRCC cells could preferentially internalize and catabolize external macromolecules as a source of AAs. Indeed, one pathway related to endocytosis (Fc gamma R-mediated phagocytosis) and three protein degradation pathways (lysosome, ubiquitin-mediated proteolysis, and proteasome) were significantly upregulated in chRCC (Fig. 1D). V-type proton ATPases and Rab GTPases play essential roles in endosome formation, maturation, transport, and fusion with lysosomes (41, 42). Most of these proteins were significantly upregulated in chRCC relative to kidney tissues (Fig. 4A). Interestingly, a few exceptional proteins, including three V-type proton ATPases (ATP6V1B2, ATP6V0A1, ATP6V1C1) and two Rab GTPases (RAB29, RAB5C), were more highly expressed in kidney tissues than in chRCC tumors (Fig. 4A), which might suggest different roles of these proteins in the endocytic process. Two lysosome markers, lysosomal-associated membrane protein 1 and 2 (LAMP1 and LAMP2), were upregulated by 3- and 7-fold, respectively (Fig. 4A). These metabolic changes indicate that extracellular biomass recruitment and protein degradation are preferentially used to obtain mass and nutrients in chRCC.
To further investigate whether the increased abundances of lysosomal proteins correlate with increased enzymatic activities in chRCC, we measured the activity of two lysosomal enzymes, hexosaminidase A and B. These enzymes are involved in the breakdown of gangliosides and were both found to be significantly increased in chRCC (Fig. 4B and C).
Next, we asked whether macromolecule supplementation enhances the growth rate of chRCC cells and whether this can be mirrored by alterations in the abundances of proteins in endocytosis related pathways. Therefore, we evaluated the proliferation of the chRCC-derived cells UOK276 (15) and normal kidney cells (HK2) under different AA and BSA concentrations. Overall, both UOK276 and HK2 cells grew significantly faster under all AA concentrations when supplemented with 2.5% BSA, and only the UOK276 cells grew equally well when supplied with 10% of the AA level present in minimum essential medium (Fig. 4D and E). UOK276 cells proliferated normally even at a low AA concentration of 1% and the addition of 2.5% BSA, whereas HK2 cells significantly reduced their growth rate under the same condition. This result suggests that UOK276 cells have higher potential to utilize BSA to compensate for AA depletion. Proteome profiling of UOK276 cells supplemented with 1% AAs and the addition of 2.5% BSA versus complete medium revealed a significant increase in endocytosis (transferrin endocytosis and recycling, Reactome) and lysosome (KEGG) pathways (Fig. 4F; Supplementary Table S1). Enzymatic activity measurement and comparison of the lysosomal hexosaminidases A and B of UOK276 cells between the previously mentioned conditions further confirmed that external macromolecules triggered internalization and degradation pathways to break down macromolecules enzymatically via endocytosis (Fig. 4G and H), which indicates the adaptation of chRCC cells to nutrient-poor conditions. To comprehensively validate the increased endocytosis rate in chRCC cells, a quantitative fluorescent image–based assay was applied. This assay exploits a self-quenched BODIPY dye conjugates of BSA (DQ-Red BSA), which only dequenches and starts to show a red fluorescent signal after being digested. Live-cell fluorescence imaging showed that the DQ-Red BSA accumulated in UOK276 cells over time, providing evidence that macropinocytosis is an established process in chRCC cells to uptake macromolecules as nutrient source (Supplementary Movie S1). Furthermore, the endocytic uptake of DQ-Red BSA in chRCC cells (UOK276) was compared with ccRCC cells (786-O) and with normal human kidney (HK2) cells. The KRAS WT (BxPC-3) and KRASG12C mutant (MIA PaCa-2, promotes macropinocytosis; ref. 43) pancreatic cancer cells were used as negative and positive controls, respectively. chRCC, ccRCC, and KRAS mutant cells showed a significantly higher endocytic uptake of DQ-Red BSA compared with KRAS WT and HK2 control cells (Fig. 4I–K). Hence, the experiments performed in the chRCC-derived UOK276 cell line validated the observation that chRCC obtains nutrients via endocytotic processes.
Pharmaceutical inhibition of the PLCG2/IP3/Ca2+/PKC pathway suppresses endocytosis in chRCC cells
The protein and RNA of PLCG2 were found to be dramatically upregulated in chRCC relative to normal kidney tissue (Fig. 5A). PLCG2 is a membrane protein belonging to the phospholipase C family and catalyzes the conversion of phosphatidylinositol 4,5-bisphosphate to IP3 and diacylglycerol, IP3 further activates the IP3 receptor (IP3R) on the endoplasmic reticulum to release Ca2+, which further activates PCK (44). To investigate the role of PLCG2 and its downstream IP3/Ca2+/PKC pathway in endocytosis, we developed an LC/MS-MS method by using isotope tracers to quantify protein scavenging by endocytosis (Fig. 5B). First, chRCC cells were cultured for 10 generations in medium containing 13C- and 15N-labeled AAs (13C15N-AA) to completely label all intracellular AAs and proteins. Then, 2.5% unlabeled BSA was added to the isotope-labeled medium, and the amount of internalized BSA in the form of derived unlabeled AAs was monitored. By measuring the amount of unlabeled essential AAs within the medium and cells, we were able to assess the endocytosis level under different conditions. EIPA (a widely used endocytosis inhibitor), U73122 (a general inhibitor of PLCG), 2-aminoethoxydiphenyl borate (2-APB, an IP3R antagonist), BAPTA-AM (a cell membrane-permeable Ca2+ chelator), and bisindolylmaleimide I (BI, a PKC inhibitor) were applied to UOK276 cells. Leucine and lysine, the two most abundant essential AAs in BSA, were both significantly decreased in the cells treated with the mentioned inhibitors (Fig. 5C and D), and all the other essential AAs showed the same trend (Supplementary Fig. S4). To further validate the role of the PLCG2 pathway in endocytic activation, the inhibitory effect of PLCG2 pathway inhibitors on DQ-Red BSA uptake in UOK276 cells was investigated. Similar to decreased levels of essential AAs, the endocytic uptake of DQ-Red BSA in UOK276 cells was significantly lower upon inhibition (Fig. 5E and F). Taken together, these results suggest that the PLCG/IP3/Ca2+/PKC pathway is involved in the activation of endocytosis in chRCC cells.
WES reveals no association of TP53 mutations and PLCG2 expression in chRCC
Approximately 30% of all chRCC cases possess somatic mutations in the tumor suppressor gene TP53 (5, 6). Both mutant and wild-type (WT) TP53 proteins have been reported to regulate endocytosis (45–47). We suspected that TP53 mutations might affect the activation of endocytosis by upregulating PLCG2 expression. To test this hypothesis, WES of all chRCC tumors and their adjacent kidney tissues was performed to identify the somatic genomic mutations of chRCC in our cohort.
In total, 254 nuclear nonsynonymous variations were identified, of which, 147 were missense mutations, 13 nonsense mutations, 40 frameshift deletions, 12 frameshift insertions, 20 in-frame deletions, and 2 in-frame insertions (Supplementary Fig. S5A; Supplementary Table S2). The number of tumor-specific nuclear mutations in chRCC ranged from 16 to 53 (median of 24) per tumor (Supplementary Fig. S5B; Supplementary Table S2), which is similar to the chRCC cohort from TCGA (Supplementary Fig. S5C). In comparison with other tumor types of TCGA panel, chRCC showed a relatively low tumor mutational burden (Supplementary Fig. S5C), consistent with previous reports (5, 6). Among all identified mutations, TP53 was found to be the most frequently mutated gene and was altered in four of nine chRCC cases, among which, two tumors exhibited nonsense mutations and two exhibited missense mutations (Fig. 6A; Supplementary Table S2). Surprisingly, in contrast to previous reports (5, 6), no PTEN mutations were identified in our cohort.
We then compared the PLCG2 protein abundance between TP53 mutant and WT tumors. TP53 WT tumors presented higher but statistically nonsignificant (P = 0.056) PLCG2 protein levels than the mutants (Fig. 6B). The chRCC RNA-seq dataset from TCGA, comprising a larger number of cases (n = 66), also showed no significant difference in PLCG2 RNA abundance between TP53 mutants and WT tumors (Fig. 6C). These results suggest that the mutation status of TP53 does not influence on the expression of PLCG2, and endocytosis in chRCC can thus be activated regardless of genetic alterations in TP53.
This study employs and integrates proteomic, transcriptomic (from TCGA), and metabolomic approaches as well as WES to gain insights into the metabolic and genetic alterations in chRCC.
One hallmark of chRCC is the substantial reprogramming of central metabolic pathways. Glycolysis and gluconeogenesis share most of their enzymes, which can function in both directions, but only the abundance of gluconeogenesis-specific enzymes was significantly reduced in chRCC (up to a 1,000-fold; Fig. 2). Kidney is the only organ, besides liver, that can deliver anabolic glucose for the organism, but a net flux can be generated only in one direction to avoid a futile cycle, which would violate thermodynamics. All kidney tumors seem to abandon this energy-consuming pathway because similar observations were also reported at the proteome level in renal oncocytomas (16), chRCC (10), and pRCC (31) and at the transcript level in pRCC (48) and ccRCC (29). A loss of differentiation, common in cancer, is indicated by the observed changes in the abundance of these gluconeogenic proteins.
In contrast to the decrease in the abundance of gluconeogenic proteins observed in chRCC, gluconeogenic genes and proteins are frequently overexpressed in other types of tumors. Specifically, increased ALDOB expression was found to favor cancer cell proliferation and metastasis in multiple cancers, such as colon cancer (49), rectal cancer (50), and colorectal adenocarcinoma (51). This might also be one reason for the low metastatic potential (52) and high survival rate of patients with chRCC (53, 54). The downregulation of the FBP1, a key player in gluconeogenesis, was previously reported to be linked to ccRCC progression and was shown to inhibit nuclear HIF function (29). This further stimulates the metabolic switch by upregulating glycolytic target genes upon the loss of FBP1 in ccRCC. This increase in glycolytic enzymes in chRCC was also seen in our proteome data (Fig. 3). However, HIF is not involved in the regulation of glucose metabolism in chRCC. The glucose uptake is of great importance to sustain tumor growth, which was shown to be significantly lower in chRCC than in ccRCC and pRCC (12). This could be a consequence of the low microvessel density observed in chRCC compared with ccRCC tumors (11). Hence, chRCC seems to be poorly supported by classical nutrient supply chains.
In addition to the dramatic reduction in enzymes involved in gluconeogenesis, decreases in the proteins of the fatty acid and AA metabolic pathways were observed in chRCC. Interestingly, the actual levels of AAs and metabolites, which can be regarded as essential “energy carriers,” such as FAD, NADH, ADP, cyclic AMP, and NAD+, were indeed unchanged (10), indicating a sufficient amount of building blocks and nutrients in chRCC. Only AA intermediates were decreased in chRCC, reflecting a lower activity of pathways involved in AA metabolism. In contrast, increased AA metabolism was frequently found in other cancer types to promote proliferation and metastasis, such as glycine and serine metabolism in breast cancer (55).
On the basis of these findings, we hypothesize that chRCC acquires nutrients preferentially in a different way. The lysosome and proteasome, which are involved in the cell recycling machinery that contributes and delivers new biomass via endocytosis, were significantly enriched. Indeed, the chRCC-derived cell line UOK276 could utilize macromolecules better under nutrient-poor conditions, and supplementation with BSA triggered a significant increase in lysosome activity. The reduced abundance of pathways involved in AA metabolism paralleled with increased abundance of the proteasome, ubiquitin-mediated proteolysis, and lysosome, suggesting that the main adaptive mechanism in chRCC involves production, recycling, and energy metabolism, such as facilitating the maintenance of proteostasis (56) or responding to stress (57).
PLCG2 was one of the most increased proteins identified by proteome profiling, and its corresponding transcript was also found to be highly upregulated in chRCC relative to healthy kidney tissues (5). Macropinosomes, which serve primarily in the uptake of solutes from the extracellular fluid (58), form as a result of macropinocytosis (known as fluid endocytosis), governed by phosphoinositides and several Rab GTPases to regulate many steps of membrane trafficking, including vesicle formation, vesicle movement, and membrane fusion (59). Consistently, most Rab GTPases were also found to be significantly increased in our chRCC specimens. During pharmaceutical inhibition of the PLCG2/IP3/Ca2+/PKC pathway, a significant decrease in endocytotic processes of macromolecules was found in the chRCC cells. Furthermore, endocytosis was reported to suppress cancer cell blebbing and invasion by increasing the cell volume and membrane tension and thus decreasing the likelihood of mechanical invasion of the surrounding tissue (60). This further matches the low rate of metastatic chRCC cases (1.3%; ref. 52) and correlates with our finding of enriched endocytosis.
In summary, chRCC is characterized by substantial metabolic rewiring, with decreased gluconeogenesis and disrupted AA metabolism. We proved that activated endocytosis and subsequent increased protein degradation are necessary for chRCC to acquire nutrients from the extracellular matrix to compensate for and counteract decreased glucose uptake and AA metabolism as well as respiratory chain activities. Moreover, the PLCG2/IP3/Ca2+/PKC axis plays a substantial role in the activation of endocytosis and could be targeted therapeutically in patients with chRCC.
J. Busch reports personal fees from MERCK, Pfizer, MSD, Roche, and Astellas outside the submitted work. M. Schütte is an employee of Alacris Theranostics GmbH. No disclosures were reported by the other authors.
Y. Xiao: Conceptualization, data curation, formal analysis, validation, visualization, methodology, writing-original draft, writing-review and editing. A. Rabien: Resources, writing-review and editing. R. Buschow: Data curation, visualization. V. Amstislavskiy: Data curation. J. Busch: Resources. E. Kilic: Validation. S.L. Villegas: Validation. B. Timmermann: Resources. M. Schütte: Data curation. T. Mielke: Data curation. M.-L. Yaspo: Data curation. K. Jung: Resources, writing-review and editing. D. Meierhofer: Conceptualization, supervision, funding acquisition, methodology, writing-original draft, project administration, writing-review and editing.
We are thankful to Marston Linehan, from the Center for Cancer Research, Bethesda, MD, for providing the chRCC cell line UOK276 and Ulrich Keller from Charité – Universitätsmedizin Berlin for giving us the MIA PaCa-2 and BxPC-3 cell lines. Our work is supported by funds from the Max Planck Society and the China Scholarship Council to Y. Xiao and from the Foundation for Urologic Research to A. Rabien and K. Jung.
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