Renal cell carcinoma (RCC) is among the most common malignancies, with an estimated 65,000 new cases and 14,000 deaths annually in the United States1. RCC can be subclassified into distinct histologic subtypes including clear cell RCC (ccRCC), papillary RCC Types 1 and 2, and chromophobe RCC2. Inherited RCC can be caused by germline mutations in multiple genes that are linked to specific histologic subtypes. In particular, VHL, MET, FH and FLCN genes are linked to development of the clear cell, papillary Type 1, papillary Type 2 and chromophobe RCC subtypes, respectively2,3,4. Not surprisingly, these genes are often found to be mutated in sporadic cases of RCC as well2,3,4,5,6.

The genetics of ccRCC have been studied in depth4. The von Hippel-Lindau tumour suppressor protein (pVHL) is broadly inactivated (80%) in sporadic ccRCC by either mutation or promoter hypermethylation3,7 and its tumour suppressor activity is dependent on its downregulation of the alpha subunits of the hypoxia-inducible factor (HIFα) family of transcription factors and in particular HIF2α (refs 8, 9, 10, 11). In addition to mutations of VHL, whole exome sequencing studies have defined a number of other significantly mutated genes in ccRCC such as PBRM1, SETD2 and BAP1, many of which are related to histone modification or nucleosome remodelling4,5,12,13. ccRCC has a relatively low mutation burden relative to other solid tumours14 but does have characteristic large deletions and gains of chromosomes 3p, 14q and 5q, respectively, as well as more focal gains and losses of 8q24 (harbouring MYC) and 9p21 (harbouring CDKN2A), respectively5,12,15.

Focal amplification of 8q24 has been demonstrated in 15–23% of ccRCC in three independent studies and in all studies the amplicon appears to harbour MYC5,12,15. Gain of 8q, as assessed by classic cytogenetics, is associated with a high risk of lymph node and distant metastases and is an independent prognostic factor16,17. Despite this genetic evidence implicating MYC in ccRCC pathogenesis, the role of MYC in ccRCC is complex. Studies demonstrate that HIF2α can potentiate MYC transcriptional activity and that MYC gene signatures are able to define a subtype of ccRCC, while HIF1α has the potential to oppose MYC transcriptional activity18,19,20.

Herein we describe the development of mouse models of papillary and clear cell RCC, by modelling the genetic events found in human kidney cancer. We uncover that MYC activation is sufficient to generate papillary RCC in mice. Moreover, MYC activation, along with Ink4a/Arf (Cdkn2a) inactivation cooperates with Vhl loss to form clear cell RCC that is occasionally metastatic. These GEM models represent the first tractable models of papillary and clear cell RCC that have a predictable latency with high penetrance. These models of papillary and clear cell RCC should therefore be significant contributions to the field of kidney cancer research.


Kidney specific MYC activation results in papillary RCC

Prior work has examined the role of MYC in the development of kidney cancer by overexpressing MYC under control of the gamma-glutamyl transferase promoter21. While the mice developed renal tumours, they appeared to be histologically and immunophenotypically most consistent with collecting duct carcinomas. We generated compound mutant mice engineered to express a doxycycline-inducible Myc transgene (Tet-O-MYC) targeted to the renal tubule cells under control of the Ksp promoter22,23 (Ksp-rtTA; Tet-O-MYC mice; hereafter called ‘MYC’ mice) and control animals expressing only Tet-O-MYC. Mice were fed chow containing doxycycline starting at 8 weeks of age to induce MYC expression and were followed for survival. MYC mice had a significantly shortened survival relative to controls (Fig. 1a, P=0.0162) and upon necropsy were found to harbour renal tumours but no evidence of macroscopic metastatic disease (Fig. 1b).

Figure 1: Kidney specific MYC activation results in papillary renal cell carcinoma.
figure 1

(a) Kaplan–Meier curve showing reduced survival rates in MYC mice (n=15) compared to controls (n=17) Log Rank P=0.0162. (b) Representative gross images and photomicrographs of H&E stained kidney sections from MYC mice (32 weeks post Dox treatment) revealed both papillary (top panels) and solid kidney tumours (bottom panels) (scale bar, 100 μm). (c) GSEA enrichment plots showing papillary kidney tumours are enriched for multiple gene sets representing MYC activation relative to normal kidney (GSE11151). (d) Kaplan–Meier curve of patients from the TCGA KIRP dataset demonstrating tumours with high MYC activity have reduced survival in patients with papillary renal cell carcinomas, Log Rank P=1.46e–9. (e) Immunoblot using whole cell lysates from MYC kidney tumor-derived cell lines (MYC-2927 and MYC-2983) shows expression of MYC is Dox dependent. (f) Cell viability assay show reduced proliferation from MYC-2927 and MYC-2983 cells upon Dox removal. Cells grown on Dox or vehicle were analysed in replicates of n=8 each day. (g) Bright field image of MYC-2927 and MYC-2983 cells on day 3 after being cultured with or without Dox. (scale bar, 100 μm). (h) Soft agar assays show anchorage independent growth of MYC-2927 and MYC-2983 cells is significantly reduced upon removal of Dox. Images are representative of each condition performed in triplicate. (i) Results from xenograft studies showing tumours formed from MYC-2983 cells remain dormant upon removal of Dox in vivo (n=5 per group). (f,g) *P<0.05, ***P<0.0001. (f,h,i) Data are presented as mean ±s.e.m. (f,h) P values obtained from student t-test.

Histologic examination showed that the majority of the tumours found in the kidneys of MYC mice had either a papillary or a more solid and infiltrative appearance. Smaller tumours (<3 mm) were predominantly papillary (Fig. 1b ‘papillary’), while larger tumours (>3 mm) were either papillary or consisted of more solid appearing tumours characterized by tightly packed papillary structures lacking distinct fibrovascular cores (Fig. 1b ‘solid’). These larger, solid tumours were characterized by hyperchromatic cells with a high nuclear to cytoplasmic ratio. In addition, the cells contained nuclei with large nucleoli, significant pleomorphism and were high grade (Supplementary Fig. 1A). Notably, intra-tumoral foamy macrophages and psammoma bodies (features that are commonly seen in human papillary renal cell carcinoma) were lacking in the MYC tumours.

Papillary RCC with MYC activation has a worse prognosis

Prior work has shown that a subset of pRCC, primarily Type 2 pRCC, is enriched for gene signatures of MYC activation and that tumours with MYC activation have a worse overall survival24. We confirmed and extended these findings using multiple gene expression datasets, which revealed that pRCC tumours were enriched for MYC activation gene signatures when compared to normal kidney (Fig. 1c and Supplementary Fig. 1B)25. Finally, to determine the impact of MYC activation on prognosis, we classified TCGA KIRP tumours as MYC activated (n=23, defined as tumours with a Z score of the PID_MYC_ACTIV_PATHWAY greater than 1.0 s.d. above the mean) or not MYC-activated (n=153). Consistent with previous work, patients with MYC activated pRCC tumours had a significantly worse overall survival (Fig. 1d, P=1.46e–9)24.

Cell lines from MYC mice are dependent upon MYC expression

To better characterize the phenotype of the kidney tumours from MYC mice we generated two cell lines from separate MYC tumours (MYC-2927 and MYC-2983). After verifying the Dox responsiveness of the Tet-O-Myc transgene in these MYC cells (Fig. 1e), we examined the effect of MYC expression on cell proliferation in vitro. MYC cells grown in the presence of Dox (activated MYC) had increased proliferation at 4 days (Fig. 1f), as well as a visible increase in cell number (Fig. 1g). In addition, while MYC cells without Dox were unable to form colonies in soft agar, MYC cells grown in Dox formed colonies robustly in an anchorage independent manner (Fig. 1h). Finally, we assessed the ability of MYC-2983 cells to form tumours in vivo and their in vivo growth dependence on MYC expression. To this end, 5 × 106 MYC-2983 cells were injected subcutaneously and monitored for growth in mice fed Dox chow. Once tumours reached 300 mm3, mice were either continued on or withdrawn from Dox (Fig. 1i). As expected, tumours of mice that remained on Dox continued to have rapid growth, while tumours in mice withdrawn from Dox remained dormant. Therefore, MYC-induced papillary RCCs are dependent upon MYC expression for in vitro and in vivo growth.

Vhl loss with MYC activation promotes clear cell changes

Focal amplification of 8q24 is found in 15% of ccRCC in the TCGA KIRC data set5. To ensure that MYC was located in the minimal common region (MCR) of amplification, we used GISTIC 2.0 analysis to identify a broad statistically significant (q value<0.25) region of amplification on chr8. This MCR contains MYC. A plot of mean gene-level DNA copy number measurement by genomic position (Supplementary Data 1 and Supplementary Fig. 2A) shows that mean MYC copy number is larger than the 70% of the mean gene-level DNA copy values. Therefore, while these data suggest that MYC is an important target of amplification in this region there are still 100 genes with mean copy number values that are higher. Similarly, focal loss of 9p21 was found in 32% of ccRCC in the TCGA KIRC data set5. GISTIC 2.0 analysis demonstrated the presence of only three genes in the minimal common region of copy number loss, CDKN2A, CDKN2B and C9orf53 (Supplementary Fig. 2B). These results suggest that both MYC and CDKN2A may be involved in the development or progression of ccRCC.

To model the interplay of genomic events observed in human RCC, we next examined the phenotypes of kidney specific Vhl inactivation in combination with MYC overexpression or combined MYC overexpression and Ink/Arf deletion. Specifically, MYC mice were crossed to conditional Vhl knock-out mice (VhlF/F)26, Cdkn2a (Ink4a/Arf−/−) germline knock-out mice27, as well as mice expressing tamoxifen-inducible Cre recombinase under control of the Ksp cadherin promoter (KspCreERT2) to generate cohorts of KspCreERT2; VhlF/F control mice (conditional inactivation of Vhl, hereafter called V), KspCreERT2; VhlF/F; Ksp-rtTA; Tet-O-Myc (conditional inactivation of Vhl and Dox-inducible MYC overexpression, hereafter called VM), and KspCreERT2; VhlF/F; Ink/Arf−/−; Ksp-rtTA; Tet-O-Myc (conditional inactivation of Vhl, germline Ink/Arf−/−, and Dox inducible MYC overexpression, hereafter called VIM) (see Supplementary Table 1).

Cohorts of V, VM, and VIM mice were followed for survival (Fig. 2a). VM mice had a significantly worse survival than V mice (P=0.007) and VIM mice had a significantly worse survival than both V and VM mice (both P<0.001, Fig. 2a). Histologic examination showed that the kidneys of V mice were essentially normal (Fig. 2b). In contrast, kidneys from VM and VIM mice had a high incidence of tumour formation (67% and 100% respectively, Table 1). Kidney tumours of VM mice had either a tubulo-papillary or solid appearance with intervening vessels. The tumour cells were hyperchromatic compared to the normal renal tubular epithelium. Occasional clear cell features were identified (Fig. 2b; Supplementary Fig. 3). Small tumours were generally well demarcated, while larger tumours showed a multilobulated growth pattern with frequent necrosis, haemorrhage and dystrophic calcifications (Supplementary Fig. 4A).

Figure 2: MYC activation combined with Vhl and Ink4a/Arf loss results in histopathological changes in the kidney resembling human clear cell renal carcinomas.
figure 2

(a) Kaplan-Meier survival curve comparing survival rates between V (n=8), VM (n=21) and VIM (n=12) mice. Log rank V versus VM P=0.007, V versus VIM P<0.0001, VM versus VIM P<0.001. (b) Representative gross and H&E images of kidney sections from V (33 weeks), VM (30 weeks) and VIM (19 weeks) mice at the indicated times post Dox treatment. (scale bars, 200 and 100 μm). (c) cBioPortal OncoPrint plot showing the distribution of MYC, VHL and CDKN2A copy number alterations in the TCGA KIRC data set. (d) Kaplan–Meier survival curve comparing human kidney renal clear cell carcinomas with V, VM and VIM alterations. Log rank V versus VIM P=5.08e-9, V versus VM P=0.005, VM versus VIM P=0.200. (e) Bar graph showing the correlation of V, VM and VIM tumours from the TCGA KIRC dataset with stage and (f) metastasis. (g) Bar graphs showing percentage of TCGA KIRC tumours with alterations in VHL, CDKN2A, and MYC by TNM Stage. (eg) *P<0.05; **P<0.01, ***P<0.001. P values obtained from Chi-square test.

Table 1 Comparison of VM and VIM mice.

While tumours similar to those seen in the VM mice were observed in VIM mice, the kidneys of VIM mice also harboured tumours with a solid or tightly packed tubulo-papillary appearance. The cells were small to intermediate in size with increased nuclear to cytoplasmic ratio with nuclei that were round to oval with prominent single nucleoli (Supplementary Fig. 3). Clear cell changes within the larger tumours were also present with areas within some tumours showing what appeared to be histology strikingly similar to human ccRCC (Fig. 2b). These areas were typified by nests of tumour cells with an increased amount of clear to granular cytoplasm, separated by thin vascular channels. Therefore, while Vhl loss combined with MYC activation is sufficient to induce modest clear cell changes, Vhl loss combined with MYC activation and Ink/Arf deletion induces bona fide clear cell RCC (Table 1).

ccRCC with VM and VIM alterations have worse prognosis

We next examined whether human ccRCC tumours with similar genomic characteristics (VHL inactivation; VHL inactivation and MYC activation; and VHL inactivation, CDKN2A loss and MYC activation) have similar outcomes as those seen in our mouse models. Of TCGA KIRC tumours (n=525), 87, 13 and 31% had VHL inactivation, MYC activation and CDKN2A deletion, respectively (Fig. 2c). We further classified these patients as V (n=286, 54%), VM (n=26, 5%) and VIM (n=32, 6.1%) and noted that VM and VIM patients had a significantly decreased survival relative to V patients (P=0.005 and P=5.086 × 10−9, respectively (Fig. 2d), but that VM and VIM patients had a similar overall survival. In keeping with the notion that VIM tumours are more clinically aggressive, we also noted significant enrichment of higher stage and presence of metastases in patients with VIM tumours relative to patients with V tumours (Fig. 2e,f). When limiting our analysis to stage IV tumours, we did not see significant survival differences by genotype (V, VM and VIM) (Supplementary Fig. 5). Because of the very limited patient numbers (V=28, VM=7 and VIM=11), we examined whether VIM genotype was prognostic when controlled for both TNM stage and Furhman grade. Cox proportional hazards (Cox PH) modelling using the V genotype as the reference demonstrated that the VIM genotype was still prognostic (Cox PH=1.79, P=0.034). Therefore, VIM tumours appear to have worse clinical characteristics and outcome in human ccRCC patients even when controlling for stage and grade.

Finally, we attempted to assess whether VHL loss, CDKN2A loss and MYC activation are dysregulated at tumour initiation or tumour progression, by analysing their relative frequency by TNM stage in the TCGA KIRC data set (Fig. 2g). We found that the rate of VHL inactivation was relatively similar across all stages, while the rate of CDKN2A loss and MYC activation appeared to increase with TNM stage. This data are consistent with the known role of VHL as a gatekeeper tumour suppressor gene and suggests that CDKN2A loss and MYC activation are events involved in the progression of a subset of ccRCC tumours.

VM and VIM cell lines are dependent upon MYC expression

We generated cell lines from VM and VIM tumours to assess their dependency on MYC expression. We first confirmed the Dox inducibility of the MYC transgene in these VM (2849 and 3055) and VIM (3039 and 3131) cells (Fig. 3a), as well as the fact that they had undergone Cre mediated recombination of the Vhl locus (Supplementary Fig. 4B). Furthermore, we set out to confirm that VM-3055 and VIM-3039 cell lines are epithelial in nature. We performed RNAseq and co-clustered mouse 3T3 fibroblasts with VM-3055 and VIM-3039 cell lines using the top 10% of the most differentially expressed genes (Supplementary Fig. 4C). 3T3 fibroblasts show a distinctly different expression pattern from both VM-3055 and VIM-3039 cell lines showing that our VM and VIM cell lines are not fibroblastic in nature. After confirming that the VM and VIM cells were derived from renal epithelium, we assessed their growth in in vitro assays. Similar to MYC cells, the proliferation and anchorage independent growth of VM and VIM cells were dependent on MYC expression (Fig. 3b–d).

Figure 3: VM and VIM tumours are dependent on MYC expression.
figure 3

(a) Immunoblot of whole cell lysates from VM (VM-2849 and VM-3055) and VIM (VIM-3039 and VIM-3131) tumour-derived cell lines shows expression of MYC is Dox dependent. (b) Proliferation of VM and VIM cells is significantly reduced with removal of Dox. Cells grown on Dox or vehicle were analysed in replicates of n=8 each day. (c) Bright field image of VM and VIM cells three days after Dox removal show a decrease in cell number (scale bar, 100 μM). (d) Soft agar assays show anchorage independent growth of VM and VIM cells is reduced upon Dox removal. Images are representative of each condition performed in triplicate. (e) Venn diagram showing overlapping and distinct sets of genes altered upon Dox removal in VM-3055 and VIM-3039 cells. (f) Venn diagram showing Dox dependent gene expression in VM-3055 and VIM-3039 activates distinct gene sets. (b,d) ***P<0.0001. P values obtained from student t-test. Data are presented as mean ±s.e.m.

To understand the MYC dependent changes on the transcriptomes of VM-3055 and VIM-3039 cells, we performed RNAseq on these cells grown in tissue culture in the presence or absence of Dox. There were a large number of genes that were differentially regulated (increased or decreased greater than two-fold; t-test FDR<0.05) by MYC activation (Dox) in both VM-3055 (799 up and 2491 down) and VIM-3039 (1017 up and 2159 down) cells (Fig. 3e). While there was overlap among genes that were upregulated by Dox in both VM-3055 (634 of 799) and VIM-3039 cells (634 of 1017) (Fig. 3e), nearly a third of Dox inducible genes in VIM-3039 cells (378 of 1017) were not upregulated in VM-3055 cells. A similar percentage of genes repressed by MYC activation (Dox) in VIM-3039 cells were not repressed in VM-3055 cells either, suggesting that MYC may regulate both an overlapping and a unique spectrum of genes in VM-3055 and VIM-3039 cells.

We next performed gene set analysis. Gene sets that were enriched in VM-3055 cells cultured in Dox relative to those cultured without Dox included a number of gene signatures characteristic of MYC activation including those related to cell cycle progression and ribosome biogenesis (Supplementary Data 2). A parallel analysis in VIM-3039 cells also demonstrated high enrichment in proliferation and ribosome biogenesis gene signatures (Supplementary Data 3), but also included gene signatures related to DNA methylation, as well as RNA binding. Indeed, the top gene signatures significantly enriched in VM-3055 and VIM-3039 cells (an area under the curve (AUC) greater than 0.25) were relatively non-overlapping (Fig. 3f). While these findings are in keeping with the notion that MYC activation induces many unique gene expression changes specific to VM-3055 and VIM-3039 cells given the analysis is on a single-cell line, they will need to be validated in future studies.

GEM tumours correlate with human RCC

Given that MYC tumours resemble human papillary tumours histologically, while VM and VIM tumours resemble ccRCC, we wanted to determine if the similarities would also be apparent at the gene expression level. Pearson correlations on whole transcriptome centroids between MYC (n=4), VM (n=4) and VIM (n=4) mouse tumours and the TCGA KIRC and KIRP data revealed that VM and VIM tumours correlated most highly with TCGA KIRC tumours, while MYC tumours correlated more highly with TCGA KIRP tumours (Fig. 4a). Further verifying the importance of MYC activity in pRCC Type 2, a cross species analysis of mouse MYC tumours with the TCGA KIRP data set demonstrated co-clustering of MYC tumours with human papillary Type 2 tumours (Fig. 4b). Moreover, transcriptome wide Pearson correlations revealed that MYC tumours more closely resemble TCGA KIRP tumours verified to be Type 2 pRCC (Fig. 4c). Collectively, these analyses support the clinical relevance of the MYC, VM and VIM mouse models with human papillary and clear cell renal cancers.

Figure 4: Renal carcinoma mouse models reflect the transcriptomic landscape of human renal carcinoma.
figure 4

(a) Pearson correlation of whole-transcriptome centroids of M/VM/VIM mouse models and papillary renal cell carcinoma (KIRP)/clear cell renal cell carcinoma (KIRC) TCGA tumor samples. (b) Heatmap clustering of M mouse model samples with TCGA KIRP samples identified by subtype. (c) Pearson correlation of whole-transcriptome centroids of the M mouse model with KIRP TCGA Type 1/Type 2 samples.

Ink4a/Arf loss in VM mice promotes metastases

During necropsies of VIM mice, we noted that a number of mice had what appeared to be macroscopic metastases to the liver at a low frequency (Fig. 5a,b, and Table 1). Histologically, the liver metastases were either tubulo-solid or clear cell with cytologic features consistent with the primary renal tumour. Metastases were identified in the subcapsular area and within the parenchyma. Notably, vascular spaces were involved by tumour in some of the liver specimens (Fig. 5a). We did not see any macroscopic metastases to other organs such as the lung.

Figure 5: Combinatorial loss of Vhl and Ink4a/Arf with MYC activation promotes metastasis and activation of EMT genes.
figure 5

(a) A representative H&E stained liver sections from a VIM mouse shows metastasis to the liver parenchyma as well as intravascular mets. Higher power magnification reveals features resembling renal clear cell carcinomas within the metastatic lesions. (Scale bar, 100 μm). (b) Bar graph showing percentage of mice with metastases. (c) Heat map showing the expression patterns of EMT associated genes in VM-3055 and VIM-3039 cells. (d) Higher expression of genes involved in invasion and metastasis is observed in VIM-3039 cells compared to VM-3055 cells. (e) Matrigel invasion assays show increased invasion from VIM-3039 cells compared to VM-3055 cells. ****P<0.0001. (d,e) P values obtained from student t-test. Data are presented as mean ±s.e.m.

Given the metastatic phenotype seen in the VIM mice but not in the VM mice, we examined a panel of genes that characterize epithelial to mesenchymal transition (EMT) (Cdh1 (E-cadherin), Cdh2 (N-cadherin), Vim (vimentin)), as well as a panel of transcription factors well known to regulate EMT (Snai1, Snai2, Zeb1, Zeb2, Twist1) in the RNAseq data from our cell lines. VIM-3039 cells demonstrated gene expression changes that were consistent with a state of EMT with decreased expression of E-cadherin (Cdh1) and increased expression of N-cadherin (Cdh2) and Vimentin (Vim) as well as upregulated expression of Snai1, Snai2, Twist1, Zeb1 and Zeb2 (Fig. 5c). In addition, we noted that a number of the most differentially expressed genes (Supplementary Data 4) are implicated in invasion and metastasis through remodelling of the extracellular matrix such as the lysyl oxidase family members Lox, Loxl1, Loxl2 and hyaluronan synthase 2 (Has2) (Fig. 5d)28. Given these differences in gene expression, we examined the invasiveness of our VM-3055 and VIM-3039 cell lines in vitro in matrigel invasion assays. As predicted, VIM-3039 cells had significantly increased matrigel invasion (Fig. 5e). Therefore, Ink4a/Arf inactivation appears to facilitate EMT, invasion and metastases and the metastatic phenotype seen in vivo is recapitulated in vitro.

VHL restoration has no effect on VIM cells

Previous work in human ccRCC cell lines has shown that VHL does not affect in vitro proliferation or anchorage independent growth33. To assess whether this was true in our VIM cell lines, we established isogenic VIM cells expressing eGFP or HA-VHL (Fig. 6a). As predicted, there were no VHL dependent differences in in vitro growth (Fig. 6b) or ability to form colonies in soft agar (Fig. 6c). These results are in keeping with those seen in human ccRCC cell lines. At this time we have not been able to reliably generate allograft tumours from our VM or VIM cell lines and therefore cannot interrogate whether VHL plays a tumour suppressor role in vivo, as previously shown with human RCC cell lines33. Therefore, whether our GEM models are overdriven remains a possibility.

Figure 6: Restoration of VHL does not significantly reverse tumorigenic capacity of VIM cells.
figure 6

(a) Immunoblot of whole cell lysates from VIM cells infected with pBabe eGFP and pBabe HA-VHL. (b) Cell growth assay shows no significant reduction in cell number in VIM cells when VHL is expressed. Cells grown on Dox or vehicle were analysed in triplicate each day. (c) Soft agar assays show VIM-3039 cells form colonies in an anchorage independent manner despite the presence of VHL. (b,c) P values obtained from student t-test. Data are presented as mean ±s.e.m.


The development of GEM models of cancer has had significant impact on functional genomics as well as preclinical development of novel therapies34. Indeed, robust GEMMs of non-small cell lung cancer36 and pancreatic ductal adenocarcinoma37 have led to an explosion of research into the biology underlying these diseases and facilitated the study of diverse fields such as biomarker discovery and investigations into the cell of origin of various cancers. Our own studies highlight the role of MYC in renal tumorigenesis and demonstrate that MYC activation is sufficient to generate papillary RCC and that when combined with Vhl and Ink4a/Arf inactivation results in bona fide clear cell renal cell carcinoma.

Development of robust GEM models of kidney cancer has been a long-sought after and elusive goal despite substantial efforts in this area. Multiple groups have now demonstrated that Vhl inactivation either in the germline or by conditional inactivation in the kidney results in only a mild increase in rate of renal cyst formation26,38,39,40,41. While the addition of secondary genetic events such as Pten or Kif3a loss appear to accelerate the cystic phenotype induced by Vhl inactivation, they do not result in frank neoplasia42,43. Combined inactivation of Vhl with Trp53 does appear to induce renal tumours, which have clear cell changes but not bona fide clear cell RCC histology44. A recent report demonstrated that combined inactivation of Vhl with Bap1 results in renal tumours with clear cell histology45. However, while inactivation of other tumour suppressor genes such as Flcn, Tsc1 or Fh results in renal carcinomas46,47,48,49,50, they are rarely of the clear cell histologic subtype and they exhibit long latency, impacting their utility for routine investigation. Therefore, there remains a need for RCC models that are highly penetrant, relatively rapid and that display robust papillary or clear cell histology.

Schroff and colleagues recently reported the phenotype of kidney specific overexpression of c-MYC in mice21. They found robust development of renal tumours that were dependent on upregulated glutaminolysis. Histological and immunohistochemical analysis demonstrated that these tumours were most consistent with collecting duct carcinomas. Collecting duct carcinomas are thought to arise from the collecting ducts, which are embryologically derived from the metanephros and distinct from the nephron. In support of this, the immunophenotype, as well as response to therapy are closely associated with urothelial carcinomas (bladder cancer)51 and as such, they are treated with bladder cancer specific chemotherapy regimens such as MVAC (methotrexate, vinblastine, adriamycin, and cisplatin). Our studies also examined the phenotype of kidney specific overexpression of c-MYC. However, in contrast to Schroff and colleagues our MYC mice developed renal tumours with histology highly reminiscent of human papillary RCC. We hypothesize that these distinctions may be due to the relative differences in expression patterns of the promoters used to overexpress MYC (Schroff et al. use γ-glutamyl transpeptidase while our studies use Ksp-cadherin), as well as any potential differences in the timing of MYC activation.

Our mouse models of pRCC and ccRCC faithfully recapitulate the genomics of human RCC although the incidence of ccRCC tumours that have coincident VHL and CDKN2A inactivation, along with MYC activation is only 6%. The genomics of papillary and clear cell RCC implicate MYC as a potential oncogenic driver event5,12,15 and our studies firmly place MYC as playing an active role in their pathogenesis. VHL inactivation results in the stabilization of the alpha subunits of the hypoxia-inducible factor alpha (HIF) family of transcription factors of which HIF2α is thought to be a key oncogenic driver of ccRCC tumorigenesis, while emerging evidence suggests that HIF1α may be a tumour suppressor gene3,8,10,11,52,53. Past work examining the potential interaction between HIFα subunits and MYC suggest that while HIF1α disrupts MYC transcriptional activity, particularly of those genes involved in cell cycle progression, HIF2α actually facilitates MYC/MAX interactions18,19,54. It will be interesting to determine whether these HIF and MYC interactions occur in vivo in our VM and VIM mouse models and whether these oncogenic dependencies can be used as therapeutic vulnerabilities.

The Ink4a/Arf locus is best known as a cell autonomous barrier to cellular transformation through its negative regulation of cell cycle progression and its ability to promote cellular senescence55. Our studies demonstrate that Ink4a/Arf inactivation promotes liver metastases in an autochthonous ccRCC GEM model and that Ink4a/Arf loss is associated with gene expression patterns of EMT. Several past studies support that Ink4a/Arf may regulate EMT and metastasis. For example, in the mid 1990s, Allan Balmain and colleagues noted that p16 loss was a critical event in the regulation of an invasive spindle cell phenotype of mouse skin carcinomas, which today would likely be termed EMT56. In addition, a recent genome wide CRISPR screen in a cell line xenograft model identified CDKN2A as strongly associated with increased metastases57. At this time we hypothesize that Ink4a/Arf loss does not directly regulate EMT or metastases but that its loss is permissive for the emergence of clones that allow metastatic behaviour. Nonetheless, our studies bolster the notion that Ink4a/Arf loss is a metastatic driver event and demonstrate this association in autochthonous ccRCC GEM models.

In summary, we present GEM models of papillary and clear cell RCC that are faithful to the genomic events and recapitulate the histology seen in their respective human correlates. These pRCC and ccRCC GEM models should be a valuable contribution to the field of kidney cancer research and given their immune competent state should be invaluable in the development of immune based therapy.


GEM Models

Conditional Vhl knock-out mice (VhlF/F)26, germline Cdkn2a (Ink4a/Arf) knockout mice (Ink4a/Arf−/−) (ref. 27), KspCad-CreERT2 (ref. 58), KspCad-rtTA58 and Tet-O-Myc mice22 have all been previously described. Tet-O-Myc was a generous gift from Dr Dean Felsher. Protocols for all animal experiments described were approved by the UNC-CH Institutional Animal Care and Use Committee.

Reagents for in vivo studies

Conditional activation of cre recombinase was induced by oral administration of tamoxifen (Sigma T5648). Per ml of in vivo oral delivery, tamoxifen was formulated as: 100 mg of tamoxifen dissolved in 100 μl 100% EtOH, followed by the addition of 1 ml of sunflower oil to achieve 100 mg ml−1. The solution was sonicated in a water bath sonicator located at 4 °C for 10-s pulses. The solution was then placed in a water bath at 50 °C for 1 min until clear. Sonication and water bath steps were repeated until no particulates were noticeable. Animals were given 50 μl (5 mg per day) for three consecutive days by oral gavage. Tamoxifen oral solution was aliquoted and stored at −20 °C and brought to administrable solution by 50 °C water bath for no longer than 5 min. The Tet-ON conditional system was activated with doxycycline chow (Research Diets, Inc. C11300–2000 with 2,000 p.p.m. doxycycline) 7 days post oral tamoxifen administration.

Primary tumour cell line generation and culture conditions

Primary renal GEMM tumours were excised and washed in a solution of Pen-Strep, PBS solution (1:1). In sterile conditions, primary tumours were cut into 2 × 2 mm fragments and dissociated in a gentleMACS C-Tube (Miltenyi Biotec) using the gentleMACs Dissociator (program: m_imp Tumor_02) in 5 ml of 1XDMEM, 10% FBS, 1% PenStrep. 100 μl of collagenase D/dispase II (Roche: 40 mg ml−1) was added to the tumour fragments and continuously inverted for 30 min at 37 °C. Fragments were then subjected to a second round of dissociation using the gentleMACS Dissociator (program: m_imp Tumor_03). A total of 5 ml of protein extraction buffer (PEB: buffer 0.5% FBS, 2 mM EDTA in PBS) was added to the dissociated fragments and resuspended by pipetting. The cell suspension was transferred to a 50 ml conical tube through a 40 μm nylon mesh sterile cell strainer (Fisher). An additional 20 ml of PEB buffer was added to the cell suspension and then centrifuged at 300g for 5 min. Supernatant was removed and cell pellet was resuspended in 6 ml of ‘conditioned media’59 containing 2 μg ml−1 doxycycline (Sigma) and placed in a 6 cm sterile cell culture plate.On reaching confluency, cells were split and cultured in 1XDMEM, 10% FBS, 1%PS containing 2 μg ml−1 doxycycline. In vitro doxycyline was dissolved in DMSO.


Primary renal GEMM tumour cell lines were implanted subcutaneously into SCID mice flanks at 5 × 106 cells in 200 μl of PBS containing 2 μg ml−1 doxycycline. To maintain expression of c-MYC, SCID mice harbouring xenografts were placed on doxycycline chow and withdrawn from doxycycline at the indicated times.

Immunoblotting conditions

Cells were lysed in RIPA buffer complemented with Set I and Set II phosphatase inhibitors at 1 × (Calbiochem), and protease inhibitors at 1 × (Roche). Whole cell lysate concentration was determined with Bio-Rad Protein Assay Dye Reagent Concentrate (Bio-Rad). Proteins were resolved on SDS–PAGE gels and electrotransferred to nitrocellulose membranes, 0.2 μm (Bio-Rad). For detection of c-MYC protein, proteins were electrotransferred onto PVDF membranes (Millipore). Primary antibodies, c-Myc (1:1,000; SC-42), VHL (1:500; SC-5575), Ku80 (1:1,000; Cell Signaling #2,180), Vinculin-HRP (1:1,000; Cell Signaling #18799); SC: Santa Cruz Inc. (Supplementary Fig. 6).

Cell viability assay

Cell viability in the context of the various culture conditions was measured by CellTiter-Glo Luminescent Cell Viability Assay (Promega) per manufacture’s protocol. Cells were counted and in a 96 well opaque side/clear bottom cell culture plates (Corning). Luminescence measurements were captured using a Biotek Synergy 2 plate reader. Statistical significance was measured by student t-test.

Soft agar assay

Anchorage independent growth was assayed following a standard soft agar assay protocol (bottom layer, 0.6% Difco Noble Agar (BD Biosciences) and top layer 0.4% Noble agar (Difco)). 200 μl of control media or media containing 2 μg ml−1 doxycycline was added to hydrate top agar every 72 h. A total of 5,000 cells were plated in each well of a tissue culture treated 6 well plate (Corning). Colonies were stained with crystal violet solution for 4 h and destained with H2O. Pictures were taken using a digital camera (Cannon). Treatment conditions were performed in triplicate. Statistical significance was measured by t-test.

Mouse RNAseq

An equal number of cells (2 × 105 cells per dish) were plated with or without Dox and collected for RNA 24 h later. RNA was isolated and purified for RNAseq analysis using the RNeasy Mini Kit (Qiagen) following manufacturer’s protocol and eluted in water. A total of 200–1,000 ng of total RNA was used to prepare libraries with the TruSeq Stranded mRNA Sample Prep Kit (Illumina). Around 75b paired-end reads were sequenced on a NextSeq 500 Desktop Sequencer using a high output flow cell kit (Illumina), yielding an average of over 28 M reads per sample. QC-passed reads were aligned to the mouse reference genome (mm9) using MapSplice60. The alignment profile was determined by Picard Tools v1.64 ( Aligned reads were sorted and indexed using SAMtools and translated to transcriptome coordinates then filtered for indels, large inserts and zero mapping quality using UBU v1.0 ( Transcript abundance estimates for each sample were performed using RSEM, an expectation-maximization algorithm (Li and Dewey, 2011) using the UCSC knownGene transcript and gene definitions61. Raw RSEM read counts for all RNAseq samples were normalized to the overall upper quartile62.

Gene set analysis was performed between two groups of samples by first ranking all genes by t-statistic between groups. A K–S test was performed to determine if the genes in each gene set from MSigDB were uniformly distributed among the ranked list. K–S test P values were corrected via B–H procedure with an overall FDR of 5%. ROC curves were then generated for each gene set using the ranked list of t-statistics, and the AUC for the top 10% of ranked genes was used to rank gene sets among those passing the K–S test.

Analysis of human renal gene expression data from TCGA

GSE11151 data set was downloaded on Jan 27, 2015 from Gene Expression Omnibus (GEO) website. RNA Expression dataset was log2-transformed/median centred across pRCC and normal tissue samples. RNA expression dataset was analysed with the Gene Set Enrichment Analysis (GSEA) desktop platform.

TCGA KIRP dataset was downloaded on Feb 1, 2015 from Broad TCGA website. RNA Expression dataset was log2-transformed/median centred. RNA expression data set was analysed with the GSEA desktop platform.

TCGA KIRC data sets were downloaded on Feb 15, 2015 from Broad TCGA website. RNA Expression dataset was log2-transformed/median centred. RNA expression dataset was analysed with the cBioPortal Oncoprint function and on R platforms.

Analysis of human copy number data from TCGA

Gene-level segmented DNA copy values for the TCGA KIRC cohort (n=528) were downloaded from the Broad Institute GDAC ( The GISTIC2 analysis (Mermel, 2012) identified a statistically significant (q<0.25) region of amplification in chr8 (69506698-146364022). Mean gene-level DNA copy number measurements were computed and plotted by genomic position.

Correlation analyses

The TCGA clear cell renal cell carcinoma (KIRC) and papillary renal cell carcinoma (KIRP) RNASeq expression datasets were downloaded through the Broad Institure pipeline (Broad Institute TCGA Genome Data Analysis Center (2016): Aggregate Analysis Features. Broad Institute of MIT and Harvard). Human homologues were identified for mouse genes from the Jackson Laboratory Mouse Genome Informatics database ( When combining datasets, batch effects were adjusted for using the SVA (surrogate variable analysis) R package version 3.12.0. Centroids were derived by taking the median expression of each gene across samples in a designated sample cohort. Centroid similarity metrics were derived by calculating the Pearson correlation between centroids. Heatmap clustering was done using centred average linkage clustering on all expressed genes in the data set.

Matrigel invasion assay

RCC GEMM cell lines were plated in serum-free medium for 24 h. A total of 50,000 cells were seeded into an 8-μm matrigel chamber (BD Biosciences) and placed in wells containing medium containing 10% FBS. Cells were allowed to invade for 24 h. Cells that had invaded through the matrigel were then stained with the Siemens Staining Kit according to manufacturer’s directions. Matrigel wells were then placed on a glass slide and analysed and photographed using an Olympus IX51 microscope. Representative pictures were taken of each matrigel well quadrant, and the number of cells that had invaded into the matrigel was determined by counting the number of stained nuclei using ImageJ.

Data availability

Raw RNA sequencing data are available from NCBI GEO under accession no. GSE97654.

Additional information

How to cite this article: Bailey, S. T. et al. MYC activation cooperates with Vhl and Ink4a/Arf loss to induce clear cell renal cell carcinoma. Nat. Commun. 8, 15770 doi: 10.1038/ncomms15770 (2017).

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