. 2016 Nov 3;539(7627):112-117.

doi: 10.1038/nature19796. Epub 2016 Sep 5.

Targeting renal cell carcinoma with a HIF-2 antagonist

Wenfang Chen^{1

2

3}, Haley Hill^{1

2}, Alana Christie¹, Min Soo Kim^{1

4}, Eboni Holloman^{1

2}, Andrea Pavia-Jimenez^{1

2}, Farrah Homayoun^{1

2}, Yuanqing Ma^{1

2}, Nirav Patel^{1

2}, Paul Yell⁵, Guiyang Hao⁶, Qurratulain Yousuf^{1

2}, Allison Joyce^{1

2}, Ivan Pedrosa^{1

6}, Heather Geiger⁷, He Zhang^{1

4}, Jenny Chang¹, Kevin H Gardner^{8

9

10}, Richard K Bruick^{1

11}, Catherine Reeves⁷, Tae Hyun Hwang^{1

4}, Kevin Courtney^{1

2}, Eugene Frenkel^{1

2}, Xiankai Sun^{1

6}, Naseem Zojwalla¹², Tai Wong¹², James P Rizzi¹², Eli M Wallace¹², John A Josey¹², Yang Xie^{1

4}, Xian-Jin Xie^{1

4}, Payal Kapur^{1

13}, Renée M McKay^{1

2}, James Brugarolas^{1

2}

Affiliations

¹ Kidney Cancer Program, Simmons Comprehensive Cancer Center, University of Texas Southwestern Medical Center, Dallas, Texas 75390, USA.
² Department of Internal Medicine, University of Texas Southwestern Medical Center, Dallas, Texas 75390, USA.
³ Department of Pathology, the First Affiliated Hospital of Sun Yat-sen University, Guangzhou, 510080, People's Republic of China.
⁴ Department of Clinical Sciences, University of Texas Southwestern Medical Center, Dallas, Texas 75390, USA.
⁵ Parkland Health and Hospital System, Dallas, Texas 75235, USA.
⁶ Department of Radiology, University of Texas Southwestern Medical Center, Dallas, Texas 75390, USA.
⁷ New York Genome Center, New York, New York 10013, USA.
⁸ Structural Biology Initiative, CUNY Advanced Science Research Center, New York, New York 10031, USA.
⁹ Department of Chemistry and Biochemistry, City College of New York, New York, New York 10031, USA.
¹⁰ Biochemistry, Chemistry and Biology Ph.D. Programs, Graduate Center, City University of New York, New York, New York 10016, USA.
¹¹ Department of Biochemistry, University of Texas Southwestern Medical Center, Dallas, Texas 75390, USA.
¹² Peloton Therapeutics Inc., Dallas, Texas 75235, USA.
¹³ Department of Pathology, University of Texas Southwestern Medical Center, Dallas, Texas 75390, USA.

PMID: 27595394
PMCID: PMC5340502
DOI: 10.1038/nature19796

Targeting renal cell carcinoma with a HIF-2 antagonist

Wenfang Chen et al. Nature. 2016.

. 2016 Nov 3;539(7627):112-117.

doi: 10.1038/nature19796. Epub 2016 Sep 5.

Authors

Affiliations

¹ Kidney Cancer Program, Simmons Comprehensive Cancer Center, University of Texas Southwestern Medical Center, Dallas, Texas 75390, USA.
² Department of Internal Medicine, University of Texas Southwestern Medical Center, Dallas, Texas 75390, USA.
³ Department of Pathology, the First Affiliated Hospital of Sun Yat-sen University, Guangzhou, 510080, People's Republic of China.
⁴ Department of Clinical Sciences, University of Texas Southwestern Medical Center, Dallas, Texas 75390, USA.
⁵ Parkland Health and Hospital System, Dallas, Texas 75235, USA.
⁶ Department of Radiology, University of Texas Southwestern Medical Center, Dallas, Texas 75390, USA.
⁷ New York Genome Center, New York, New York 10013, USA.
⁸ Structural Biology Initiative, CUNY Advanced Science Research Center, New York, New York 10031, USA.
⁹ Department of Chemistry and Biochemistry, City College of New York, New York, New York 10031, USA.
¹⁰ Biochemistry, Chemistry and Biology Ph.D. Programs, Graduate Center, City University of New York, New York, New York 10016, USA.
¹¹ Department of Biochemistry, University of Texas Southwestern Medical Center, Dallas, Texas 75390, USA.
¹² Peloton Therapeutics Inc., Dallas, Texas 75235, USA.
¹³ Department of Pathology, University of Texas Southwestern Medical Center, Dallas, Texas 75390, USA.

PMID: 27595394
PMCID: PMC5340502
DOI: 10.1038/nature19796

Abstract

Clear cell renal cell carcinoma (ccRCC) is characterized by inactivation of the von Hippel-Lindau tumour suppressor gene (VHL). Because no other gene is mutated as frequently in ccRCC and VHL mutations are truncal, VHL inactivation is regarded as the governing event. VHL loss activates the HIF-2 transcription factor, and constitutive HIF-2 activity restores tumorigenesis in VHL-reconstituted ccRCC cells. HIF-2 has been implicated in angiogenesis and multiple other processes, but angiogenesis is the main target of drugs such as the tyrosine kinase inhibitor sunitinib. HIF-2 has been regarded as undruggable. Here we use a tumourgraft/patient-derived xenograft platform to evaluate PT2399, a selective HIF-2 antagonist that was identified using a structure-based design approach. PT2399 dissociated HIF-2 (an obligatory heterodimer of HIF-2α-HIF-1β) in human ccRCC cells and suppressed tumorigenesis in 56% (10 out of 18) of such lines. PT2399 had greater activity than sunitinib, was active in sunitinib-progressing tumours, and was better tolerated. Unexpectedly, some VHL-mutant ccRCCs were resistant to PT2399. Resistance occurred despite HIF-2 dissociation in tumours and evidence of Hif-2 inhibition in the mouse, as determined by suppression of circulating erythropoietin, a HIF-2 target and possible pharmacodynamic marker. We identified a HIF-2-dependent gene signature in sensitive tumours. Gene expression was largely unaffected by PT2399 in resistant tumours, illustrating the specificity of the drug. Sensitive tumours exhibited a distinguishing gene expression signature and generally higher levels of HIF-2α. Prolonged PT2399 treatment led to resistance. We identified binding site and second site suppressor mutations in HIF-2α and HIF-1β, respectively. Both mutations preserved HIF-2 dimers despite treatment with PT2399. Finally, an extensively pretreated patient whose tumour had given rise to a sensitive tumourgraft showed disease control for more than 11 months when treated with a close analogue of PT2399, PT2385. We validate HIF-2 as a target in ccRCC, show that some ccRCCs are HIF-2 independent, and set the stage for biomarker-driven clinical trials.

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Figures

**Extended Data Fig. 1. Effects of PT2399 on human RCC-bearing mice**
a, Platelet, white blood cell, neutrophil, and lymphocyte counts from tumorgraft-bearing mice treated with vehicle (n = 52), PT2399 (n = 58), or sunitinib (n = 53) at the end of drug trial period (~28 days). (Low lymphocyte levels throughout consistent with expected levels in age and sex matched NOD/SCID mice.) b, Tumor growth trend lines for sensitive, intermediate, and resistant groups after controlling for baseline tumor volume (refer to Fig. 1d for individual curves). c, Representative gross images of tumors from sensitive (XP373 and XP164; green) and resistant (XP490 and XP169; red) lines at the end of drug trial. d, Representative H&E images illustrating different effects of PT2399 on sensitive tumors including patchy intercellular fibrosis and hyalinization (open arrow heads), reduced tumor necrosis (red arrows), decreased tumor cell density (XP164 and XP469), reduced nuclear to cytoplasmic ratio (XP469), cell ballooning (filled arrow), and dystrophic calcification (blue stars). Scale bars = 50 µM. e, Summary of histopathological changes induced by PT2399 in 10 sensitive tumorgrafts represented as number of tumors (N) compared to the total or as mean ± s.e. in 28 vehicle-treated tumors compared to 31 PT2399-treated tumors. MVD, microvessel density per mm²; MLA, mean lumen area (μm²). PT2399 collapsed tumor vasculature without decreasing number of CD31-expressing endothelial cells. f, (Upper panel) Immunohistochemistry (IHC) for Ki67 in tumors harvested from sensitive (XP144 and XP373) or resistant (XP530 and XP506) tumors following treatment with vehicle or PT2399. (Lower panel) H&E staining and IHC for CD31 in sensitive tumors (XP373 and XP469) treated with vehicle or PT2399. Scale bars = 100 µM. g, Representative [¹⁸F]FLT-PET/CT images of mice with subcutaneous tumorgrafts treated with either vehicle or PT2399. Yellow arrows point to tumors where there is uptake of [¹⁸F]fluoro-3'-deoxythymidine. h, Representative [¹⁸F]FLT-PET/CT images of XP144 mice with orthotopic tumors before and after treatment with PT2399 for 10 days. Yellow arrowheads, kidney tumors. White asterisks, intestine. FLT uptake in tumor compared to normal kidney reduced by 19% after 10-day treatment (n = 3; paired t-test p=0.0010). i, Human and mouse VEGF levels in plasma as determined by ELISA in different treatment groups (Vehicle: n = 63; PT2399: n = 74; Sunitinib: n = 61). **a, i:** Tests completed using a mixed model analysis with compound symmetrical covariance structure for mice in the same tumorgraft line using vehicle as the reference group. b: Trend lines were obtained from a mixed model analysis for each response group using an autoregressive (1) covariance structure for the longitudinal measurements on each mouse, compound symmetry for mice within the same tumorgraft line, and controlled for baseline volume. e: Continuous measures were analyzed using a mixed model with compound symmetrical covariance structure for mice in the same tumorgraft line and using vehicle treatment as the reference group. Specifically for categorical variables, a binomial test was used to test if the proportion of tumors affected by PT2399 compared to vehicle was different than 10%. hVEGF, and mVEGF levels were Box-Cox transformed; Raw values depicted in all graphs. All boxplots have median centre values. *, p < 0.05; ***, p < 0.001; and ****, p < 0.0001.

**Extended Data Fig. 2. Evaluation of the effects of PT2399 on tumors progressing on sunitinib**
a, Tumor volumes in mice from sensitive lines (XP374 or XP144) switched from vehicle or sunitinib to PT2399 as indicated (bottom black arrows). b, Circulating tumor-produced hVEGF levels in mice treated with vehicle, sunitinib, or sunitinib followed by PT2399. The Wilcoxon rank-sum test was used to determine if sunitinib (n = 4) or sunitinib followed by PT2399 (n = 6) were different than vehicle (n = 4). *, p<0.05. Boxplots have median centre values. c, Representative images of H&E and Ki67 staining of tumors from mice (XP144) treated with vehicle or sunitinib (left panel) and from tumors following a switch to PT2399 (right panel). Scale bars = 100 µM.

**Extended Data Fig. 3. RNAseq analyses of vehicle and PT2399-treated tumorgrafts**
a, Unsupervised clustering analyses of all tumorgraft samples (sensitive and resistant, both vehicle- and PT2399-treated) showing clustering by tumorgraft line. b, RNA sequencing in sensitive tumorgrafts evaluating the effects of PT2399 on selected HIF-2 target genes. All tests completed using a mixed model analysis with compound symmetrical covariance structure for mice in the same TG line. Values were log2-transformed for analysis; Raw values depicted in all graphs as individual bars.

**Extended Data Fig. 4. HIF-2α and HIF-1α levels in sensitive and resistant tumorgrafts**
a, HIF-2α and HIF-1α immunohistochemistry. 786-O cells, which express high levels of HIF-2α, shown as controls. Scale bars, 100 µm. b, Western blot analyses showing heterogeneity within tumors but with overall similar results (compare to Fig. 3c). Green, sensitive; Red, resistant. Asterisks, underloaded samples. c, Heatmap from RNA-seq analysis showing differentially expressed genes in sensitive (S) versus resistant (R) tumourgrafts based on uniform cutoff (see Extended Data Table 3). See Supplementary Fig. 1 for gel source data.

**Extended Data Fig. 5. Evaluation of imaging characteristics of tumors in patients corresponding to sensitive, intermediate, and resistant tumorgrafts**
CT scan images from patient tumors that gave rise to tumorgrafts according to TG sensitivity to PT2399. Tumors were classified into masses with peripheral hypervascularity and a central non-enhancing area (blue outline), focally infiltrating (brown outline) and diffuse infiltrating (yellow outline). Three of the seven resistant tumors presented as non-mass-like, infiltrative neoplasms (red arrows) whereas another tumor presented with both a largely necrotic renal mass and retroperitoneal lymph nodes (black outline; white arrows).

**Extended Data Fig. 6. Extended disease control in heavily pretreated patient with metastatic ccRCC with sensitive (XP165) tumorgraft**
CT images of selected lesions in patient treated with highly related HIF-2 inhibitor (PT2385) in phase 1 clinical trial showing overall stability in the size of lesions over time. Start of treatment, day 0.

**Fig. 1. Evaluation of PT2399 in RCC tumorgraft-bearing mice**
a, Mean change in mouse body weights after treatment with vehicle (veh; n = 89), PT2399 (100 mg/kg) by oral gavage every 12 hours (PT; n = 96), or sunitinib (10 mg/kg) by oral gavage every 12 hours (Sun; n = 82). b, Hemoglobin levels, reticulocyte counts, and erythropoietin (EPO) levels in mice treated as indicated. (Hemoglobin and reticulocytes vehicle n = 52, PT2399 n = 58, sunitinib n = 53; EPO vehicle n = 63, PT2399 n = 74, sunitinib n = 61). c, Mean percent change in tumor volume in mice treated with vehicle (n = 89), PT2399 (n = 96), or sunitinib (n = 82). d, Growth curves of each tumorgraft line grouped according to PT2399 responsiveness into sensitive (GI [growth inhibition] at end of trial >80%), intermediate (GI=40%-80%), or resistant (GI<40%). Treatment starts on day 0 and values represent mean tumor volume +/− s.e.m. To minimize bias (despite overestimation) volumes calculated as length×width×height. Each XP had n ~ 3–5 tumors per treatment group (vehicle n = 89, PT2399 n = 96, sunitinib n = 82). **a–c,** Tests completed using a mixed model with compound symmetrical covariance structure for mice in the same tumourgraft line using vehicle as the reference group. **, p < 0.01; ***, p < 0.001; and ****, p < 0.0001.

**Fig. 2. PT2399 dissociates HIF-2 complexes in both sensitive and resistant RCCs and induces changes in gene expression in sensitive tumors**
a, Immunoprecipitation of HIF-1β from tumor lysates of sensitive (XP373), intermediate (XP391), and resistant (XP506 and XP169) tumors from mice treated with either vehicle (Veh) or PT2399. (Samples are labeled with “V” for vehicle-treated or “P” for PT2399-treated followed by the mouse identifier.) b, Proximity ligation assay detecting either HIF-2α + HIF-1β or HIF-1α + HIF-1β heterodimers from vehicle- or PT2399-treated sensitive (XP374) or resistant (XP296) tumors and summary of results across responsive and resistant tumorgrafts. (Images representative of quantitative data shown in graph.) Summary includes analyses from 11 vehicle-treated tumors and 11 PT2399-treated tumors (3 fields were analyzed for each sample) in 5 sensitive, 3 intermediate, and 3 resistant tumorgraft trials. Scale bars = 20 µM. c, qRT-PCR for the indicated HIF-2 target genes in PT2399 sensitive, intermediate, and resistant tumors treated with vehicle (blue), PT2399 (red), or sunitinib (green). HIF-1 target genes *CA9*, *PGK1,* and *LDHA* included as negative controls. Excepting *PGK1* and *LDHA*, samples were available for n = 58 vehicle-treated tumors (Sensitive: n = 11; Intermediate: n = 21; Resistant: n = 26), n = 62 PT2399-treated tumors (Sensitive: n = 15; Intermediate: n = 21; Resistant: n = 26), and n = 52 sunitinib-treated tumors (Sensitive: n = 10; Intermediate: n = 23; Resistant: n = 19). *PGK1* and *LDHA* were available for 24 tumors for each treatment group (Sensitive: n = 6; Intermediate: n = 8; Resistant: n = 10). d, Circulating tumor-produced hVEGF as well as mouse EPO levels in mice with sensitive, intermediate, and resistant tumors treated with vehicle (blue), PT2399 (red), and sunitinib (green). ELISA data was generated for 63 vehicle-treated tumors (Sensitive: n = 21; Intermediate: n = 19; Resistant: n = 23), 74 PT2399-treated tumors (Sensitive: n = 27; Intermediate: n = 21; Resistant: n = 26), and 61 sunitinib-treated tumors (Sensitive: n = 15; Intermediate: n = 23; Resistant: n = 23). e, Number of RNAs upregulated and downregulated genes by PT2399 in sensitive and resistant tumors. f, Heatmap representation from RNAseq analysis showing differentially-regulated genes by PT2399 in sensitive compared to resistant tumors. Removal of an unclassified tumor (XP169) from the resistant group, did not affect conclusions. g, RNAseq analyses showing increased expression of selected genes by PT2399 in sensitive tumors. **b–d, g**: Tests completed using a mixed model with compound symmetrical covariance structure for mice in the same tumorgraft line using vehicle as the reference group. qRT-PCR levels were log-transformed for analysis; EPO and hVEGF levels were Box-Cox transformed; RNAseq levels were log2-transformed; Raw values depicted in all graphs. All bar charts depict the mean with the error bar representing s.e.m., while all boxplots have median centre values. *, p < 0.05; **, p < 0.01; ***, p < 0.001; and ****, p < 0.0001. See Supplementary Fig. 1 for gel source data.

**Fig. 3. Sensitive and resistant tumors can be distinguished by HIF-2α levels and gene expression signature**
a, HIF-2α expression by immunohistochemistry (IHC) in sensitive (green) and resistant (red) tumors. Scale bars = 50 µM. (Images representative of quantitative data shown in 3b.) b, Quantification of HIF-2α-positive cells as determined by IHC in sensitive, intermediate, and resistant tumors from all 22 tumorgraft lines (Sensitive: n = 10; Intermediate: n = 5; Resistant: n = 7). c, Western blot analysis of sensitive (green) and resistant (red) tumorgraft lines. XP164 lysate loaded twice as a reference for comparison between the two membranes. d, qRT-PCR of EPAS1 (HIF-2α) expression in sensitive (n = 11) versus resistant (n = 26) vehicle-treated tumorgrafts. e, Candidate genes from RNAseq analysis differentially expressed in sensitive and resistant tumors. b: An ANOVA test was used to determine if sensitive tumors were different from intermediate or resistant. Bar chart depicts the mean with the error bar representing s.e.m. **d, e**: Tests completed using a mixed model analysis with compound symmetrical covariance structure for mice in the same tumorgraft line. RNAseq values were log2-transformed for analysis; Raw values depicted in all graphs. Bar charts depict individual RNA-seq values, while all boxplots have median centre values. **, p < 0.01; and ****, p < 0.0001. See Supplementary Fig. 1 for gel source data.

**Fig. 4. Acquired resistance following prolonged PT2399 exposure**
a, Tumor volumes from a cohort of mice of the XP164 tumorgraft line treated with vehicle (blue lines, n=2; V3286 and V3299); sunitinib until the development of resistance (green lines, n = 2; S3295 and S3296; compare to Fig. 1d); or PT2399 (red lines, n = 2; P3283 and P3288). b, Circulating human VEGF levels in mice treated for the indicated number of days (d) showing increased tumor-produced VEGF with development of resistance (all bars, n = 2). c, Bidirectional chromatograms from tumorgrafts developing resistance compared to controls: P3283 (c.968G>A in *EPAS1* [*HIF2A*] leading to a G323E) and P5123 (derived from P3288; c.1338C>A in *ARNT* [*HIF1B*] leading to a F446L). d, Crystal structure of PAS-B domains from HIF-2α bound to HIF-1β (PDB entry 4ZP4) highlighting side chains of G323 (lining opening of PT2399 binding pocket in HIF-2α) and F446 (in HIF-1β at the interface with HIF-2α). In another structure (PDB entry 4GHI) quaternary arrangement between HIF-2α and HIF-1β PAS-B domains differs, but F446 remains at the interface. e, HIF-1β IP from XP164 tumorgrafts before and after (red) development of resistance showing reformation of HIF-2α/HIF-1β complexes following the acquisition of resistance (V, vehicle; P, PT2399). f, HIF-1β IP from tumors of mice with HIF-2α or HIF-1β mutations (or wild-type controls) treated with PT2399 (n=3 mice per group). g, FLAG IP from HEK293T cells transfected with plasmids encoding FLAG-tagged HIF-1β (FLAG-HIF-1β; FLAG-HIF-1β-F446L) or HA-tagged HIF-2α (HA-HIF-2α; HA-HIF-2α-G323E) and treated with either vehicle or PT2399. See Supplementary Fig. 1 for gel source data.

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Comment in

Kidney cancer: HIF-2α - a new target in RCC.
Thoma C. Thoma C. Nat Rev Urol. 2016 Nov;13(11):627. doi: 10.1038/nrurol.2016.184. Epub 2016 Sep 27. Nat Rev Urol. 2016. PMID: 27670614 No abstract available.
Targeting HIF2α in Clear-Cell Renal Cell Carcinoma.
Ricketts CJ, Crooks DR, Linehan WM. Ricketts CJ, et al. Cancer Cell. 2016 Oct 10;30(4):515-517. doi: 10.1016/j.ccell.2016.09.016. Cancer Cell. 2016. PMID: 27728802
The therapeutic potential of HIF-2 antagonism in renal cell carcinoma.
Cuvillier O. Cuvillier O. Transl Androl Urol. 2017 Feb;6(1):131-133. doi: 10.21037/tau.2017.01.12. Transl Androl Urol. 2017. PMID: 28217462 Free PMC article.
Re: Targeting Renal Cell Carcinoma with a HIF-2 Antagonist.
Ferguson JE 3rd, Matin SF. Ferguson JE 3rd, et al. Eur Urol. 2017 Jun;71(6):987. doi: 10.1016/j.eururo.2017.02.015. Epub 2017 Feb 23. Eur Urol. 2017. PMID: 28237787 No abstract available.
Re: Targeting Renal Cell Carcinoma with a HIF-2 Antagonist.
Shenoy N, Pagliaro L. Shenoy N, et al. Eur Urol. 2018 Feb;73(2):304-305. doi: 10.1016/j.eururo.2017.10.007. Epub 2017 Nov 2. Eur Urol. 2018. PMID: 29102314 No abstract available.

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Targeting renal cell carcinoma with a HIF-2 antagonist

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