Prostate cancers are among the most common types of cancer in men, which, like other cancers, are driven by genetic mutations. Roughly half of all prostate cancers contain a genetic change that incorrectly fuses two genes together, causing the cells to produce abnormally high levels of a protein called ERG.

ERG is a transcription factor, a protein that binds to specific sequences of DNA to influence the activity of nearby genes. ERG represses genes that help to prevent prostate cancers from growing, and so promotes prostate cancer development. Like most other transcription factors, ERG is difficult to target with drugs and no therapies that directly prevent the activity of ERG currently exist.

Mounir et al. wanted to find out whether ERG cooperates with other proteins to cause prostate cancer cells to grow, with the hope that these proteins could be more easily targeted with a drug. By using various biochemical techniques in human prostate cancer cell lines, Mounir et al. found that ERG interacts with an enzyme called PRMT5. This interaction enables PRMT5 to chemically modify other proteins to change their activity. In the case of prostate cancer cells, PRMT5 inappropriately modifies the androgen receptor, a protein that regulates the growth of normal prostate cells. This abnormal modification contributes to the excessive growth of the cancer cells.

Although PRMT5 will be easier to target with drugs than ERG, it also has many other roles besides those described by Mounir et al. Much more work is therefore needed to investigate whether PRMT5 could be safely targeted to treat patients with prostate cancer.

Prostate cancer (PC) is highly prevalent and lethal (Siegel et al., 2015). Drugs targeting the Androgen Receptor (AR), a 'lineage driver' of PC (Garraway and Sellers, 2006), are an important therapeutic approach. AR is an androgen (i.e. testosterone)-activated nuclear hormone receptor that regulates normal prostate gland growth and differentiation. In PC however, AR facilitates unregulated proliferation (Mills, 2014). While it is unclear how AR and other lineage factors switch between promoting normal lineage differentiation vs. tumor growth, it is hypothesized that somatic mutations in additional genes may facilitate such changes (Garraway and Sellers, 2006). Many PCs bear chromosomal translocations resulting in aberrant expression of the ETS transcription factor ERG, most commonly through the TMPRSS2:ERG fusion (Shah and Chinnaiyan, 2009). TMPRSS2:ERG, alone or in combination with additional genetic alterations, promotes prostate tumor formation in mice (Baena et al., 2013; Chen et al., 2013; King et al., 2009; Klezovitch et al., 2008; Mounir et al., 2015; Tomlins et al., 2008). ERG is recruited to many AR target genes and represses AR-dependent transcription (Yu et al., 2010), suggesting ERG functions at least in part through attenuating AR target gene expression. However, ERG also regulates the expression of AR-independent genes thought to drive oncogenic function (Klezovitch et al., 2008; Mounir et al., 2015; Tomlins et al., 2008; Wang et al., 2008). We explored whether a deeper mechanistic understanding of ERG proliferative function could yield therapeutic insights into targeting this key PC oncogene.

To identify genes that selectively facilitate the growth of TMPRSS2:ERG positive PC cells, we performed a pooled short hairpin RNA (shRNA) screen in TMPRSS2:ERG and AR-positive VCaP prostate cancer cells, using ERG-negative 22Rv1 cells as a control (Materials and methods). The shRNA pool targets 648 genes involved in transcriptional and epigenetic regulation (Supplementary file 1). While ERG shRNAs were not in the pool, AR shRNAs were preferentially depleted from VCaP cells, underscoring AR dependence in this cell line. Thirty two (32) genes showing VCaP-selective shRNA depletion (Materials and methods) were considered for further study (Figure 1A; Supplementary file 1).

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We next narrowed the shRNA screen hit list by focusing on candidates more likely to be ERG interacting proteins. We immunoprecipitated ERG from VCaP cells, and then identified co-immunoprecipitated proteins by mass spectrometry (Materials and methods). Identified proteins (Supplementary file 2) included AR and DNA-PKcs, previously known ERG interactors (Brenner et al., 2011; Yu et al., 2010). Eight of the VCaP-selective shRNA screen hits that also co-immunoprecipitated with ERG were further validated by directed ERG co-immunoprecipitation experiments in VCaP cells. Of these, AR and PRMT5 were the only proteins that co-immunoprecipitated with ERG but not IgG control; these interactions were not overtly influenced by exposure to an androgen analog (R1881, Figure 1B; Figure 1—figure supplement 1A). We next tested whether the ERG/PRMT5 interaction is observed in other models. PRMT5 co-immunoprecipitated with ERG in 22Rv1 cells ectopically expressing ERG. This interaction was still observed upon expression of ERG bearing mutations in the DNA binding domain ('Dx', Figure 1C), suggesting DNA binding is not required for the ERG/PRMT5 interaction. Reciprocal co-immunoprecipitation experiments using overexpressed ERG and PRMT5 in AR-negative 293 and PC3 cells suggest the ERG/PRMT5 interaction can occur in the absence of AR (Figure 1—figure supplement 1B). Further work in 293 cells using truncated ERG constructs suggested that the conserved ETS DNA binding domain of ERG was necessary for the observed co-immunoprecipitation with PRMT5 (Figure 1—figure supplement 1C). Given this evidence that ERG and PRMT5 co-exist in a protein complex, we focused further efforts on PRMT5, as to our knowledge it has not been previously linked to ERG biology.

To validate the growth effects of PRMT5 knockdown, we transduced ERG-positive VCaP cells, and ERG-negative 22Rv1 and LNCaP PC cells, with three independent doxycycline (Dox)-inducible shRNA vectors targeting PRMT5 and a non-targeting control shRNA (NTC). PRMT5 knockdown was robust in all cell lines (Figure 1—figure supplement 1D). Robust growth inhibition was observed in VCaP cells; in contrast PRMT5 knockdown had no growth effects in ERG-negative 22Rv1 cells, and only minor effects in ERG negative LNCaP cells (Figure 1D–F). Deletion of methylthioadenosine phosphorylase (MTAP), which is common across cancers, is a major determinant of sensitivity to PRMT5 inhibition (Kryukov et al., 2016; Mavrakis et al., 2016); as VCaP, LNCaP, and 22Rv1 cells are all MTAP intact, the observed sensitivity of VCaP to PRMT5 shRNA is not due to MTAP deletion. The project Achilles shRNA screen dataset (Kryukov et al., 2016) contains three prostate cancer cell lines (VCaP, 22Rv1 and TMPRSS2:ERG positive NCI-H660) and one PRMT5 hairpin likely to have minimal off-target effects. This shRNA shows a trend of sensitivity in ERG-positive lines, in agreement with our findings (Figure 1—figure supplement 1E).

PRMT5 is a protein arginine methyltransferase that regulates multiple signaling pathways through the mono- and symmetric di-methylation of arginines on its target proteins (Yang and Bedford, 2013).To determine whether the antiproliferative effects of PRMT5 knockdown in ERG positive VCaP cells were mediated through methyltransferase activity, we expressed shRNA-resistant wild-type PRMT5, or a catalytically inactive G365A/R368A double mutant (Materials and methods) (Antonysamy et al., 2012) along with PRMT5 shRNA in VCaP cells. WT PRMT5, but not the G365A/R368A mutant, rescued the effects of PRMT5 knockdown on VCaP cell proliferation (Figure 1G), indicating a requirement for PRMT5 catalytic function to support VCaP proliferation.

To understand pathways affected by PRMT5, we performed transcriptional profiling of PRMT5 knockdown in VCaP cells, followed by the identification of significantly altered pathways (Figure 2A; Supplementary file 3; see Materials and methods). Among these, AR activation was the second most significantly affected pathway, and is a key pathway in common with previous reports of ERG knockdown in VCaP cells (Chen et al., 2013; Mounir et al., 2015; Yu et al., 2010). AR pathway upregulation was apparent using multiple published AR gene signatures (Figure 2—figure supplement 1). Using quantitative PCR of reverse transcribed RNA (qRT-PCR), we confirmed that knockdown of either PRMT5 or ERG increased the expression of the AR target genes PSA, NKX3-1 and SLC45A3 (Figure 2B). Expression of shRNA-resistant WT PRMT5, but not the G365A/R368A mutant, rescued the effects of PRMT5 knockdown on AR target gene expression (Figure 2C; Figure 2—figure supplement 2A), demonstrating that PRMT5 methyltransferase activity is required for repression of AR target genes. The effect of PRMT5 knockdown was restricted to genes co-regulated by both AR and ERG, as PRMT5 knockdown did not affect previously published (Mounir et al., 2015) AR-independent ERG target genes in VCaP (Figure 2—figure supplement 2B). In addition, PRMT5 knockdown did not induce AR target gene expression in ERG negative 22Rv1 or LNCaP PC cells (Figure 2—figure supplement 2C). In 22Rv1 cells, exogenous ERG expression is sufficient to attenuate PSA, NKX3-1, and SLC45A3 expression (Mounir et al., 2015). Under these conditions, PRMT5 knockdown restored the expression of these genes to baseline levels, yet had no effect on their expression in the background of the DNA-binding defective (i.e. inactive) ERG mutant ('Dx', Figure 2—figure supplement 2D). These data indicate that PRMT5’s ability to repress AR function is dependent on ERG.

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We next used chromatin immunoprecipitation (ChIP) to investigate ERG, AR, and PRMT5 recruitment to the AR targets PSA and NKX3-1 following modulation of ERG or PRMT5 expression. ERG knockdown in VCaP reduced its recruitment to previously characterized (Wei et al., 2010) binding sites on both genes (Figure 2D). We also observed PRMT5 recruitment to these same sites, which was dramatically reduced upon ERG knockdown. Conversely, ERG expression in 22Rv1 cells induced PRMT5 recruitment to these same sites (Figure 2—figure supplement 3A). In VCaP, PRMT5 knockdown reduced its own recruitment to both genes but had virtually no effect on ERG recruitment (Figure 2D). As expected (Yu et al., 2010), ERG expression in 22Rv1 reduced AR recruitment to both genes (Figure 2—figure supplement 3A), and ERG knockdown in VCaP increased AR recruitment (Figure 2D). Like ERG, PRMT5 knockdown in VCaP strongly induced AR recruitment (Figure 2D).

To extend these findings to a genome wide scale, we performed AR and ERG ChIP-seq experiments in androgen (DHT or R1881) stimulated VCaP cells upon PRMT5 knockdown (Materials and methods; available PRMT5 antibodies did not work in our hands for ChIP-seq). ERG and AR recruitment were robust in these experiments, as judged by recovery of the canonical DNA binding sites of these proteins (Figure 2—figure supplement 3B–D). In agreement with directed ChIP experiments, AR ChIP-seq demonstrated that PRMT5 knockdown increased the recruitment of AR at a subset of peaks (6% p-val 0.01, q-val 0.151), (Figure 2E), but did not significantly affect ERG binding on the same set of sites. Collectively, these data support a model where ERG recruits PRMT5 to AR targets, and PRMT5 is required for ERG-dependent attenuation of AR binding to specific regulatory regions.

In many cell types, PRMT5 represses gene expression through symmetric di-methylation of histone H4 at arginine 3 (H4R3me2s) (Yang and Bedford, 2013), suggesting this as a mechanism for PRMT5 function at AR target genes. However, ERG expression in 22Rv1 cells did not alter H4R3me2s levels at the PSA or NKX3-1 loci (Figure 3—figure supplement 1). We therefore hypothesized that PRMT5 directly methylates AR. To test this, we immunoprecipitated AR from ERG-positive VCaP cells, and blotted for AR, mono-methyl arginine (MMA), or symmetric di-methyl arginine (SDMA). MMA and SDMA signals were indeed detected in AR immunoprecipitates from VCaP cells, and were reduced following knockdown of either ERG or PRMT5 (Figure 3A). To confirm these findings in an additional ERG-dependent model, we also immunoprecipitated AR from the prostates of wild-type and TMPRSS2:ERG transgenic mice, the latter of which show ERG-dependent hyperproliferative phenotypes (Mounir et al., 2015). Like VCaP, immunoprecipitated AR from TMPRSS2:ERG mouse prostates showed high mono- (MMA) and symmetric di-methylation (SDMA) levels compared to wild-type controls (Figure 3B). On the other hand, LNCaP cells, which bear a translocation in the ETS factor ETV1, do not show any SDMA signal on AR, and show reduced levels of MMA versus VCaP (Figure 3C), suggesting that AR symmetric dimethylation is unique to ERG versus ETV1. We next immunoprecipitated AR from 22Rv1 cells, which express wild-type AR as well as a roughly 80 kDa truncated AR variant that lacks its ligand binding domain (LBD) (Dehm et al., 2008). In these cells, ERG expression increased MMA and SDMA signals on wild-type AR but not the truncated variant, and these ERG-dependent signals were reduced upon PRMT5 knockdown (Figure 3D), suggesting the AR LBD is mono- and symmetrically di-methylated in an ERG- and PRMT5-dependent manner.

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To further understand if the observed AR methylation was directly dependent on PRMT5, we performed biochemical assays using purified PRMT5 (complexed with its requisite binding partner MEP50/WDR77) and AR LBD. PRMT5 activity, as judged by production of SAH (the by-product of SAM-dependent substrate methylation), was observed in the presence of AR LBD as substrate, but not in the presence of ERG ETS DNA binding domain or pointed (PNT) domain. PRMT5 activity in the presence of AR LBD further increased with the addition of ERG ETS domain protein to the reaction, but not with PNT domain (Figure 3—figure supplement 2A). Unlike PRMT5, purified PRMT1 showed no activity in the presence of AR LBD (Figure 3—figure supplement 2B). PRMT5 activity on AR, in the absence or presence of ERG ETS domain, was reduced with the addition of the tool PRMT inhibitor AMI-1 (Cheng et al., 2004). PRMT5 dependent methylation of the AR-LBD was also observed in western blots, where increased signal for MMA (but not SDMA, likely due to low overall PRMT5 activity in vitro and the distributive nature of this enzyme [Wang et al., 2014]) was observed at the correct size for the AR-LBD protein in the presence of PRMT5. This activity was increased by ERG ETS domain, and inhibited by AMI-1 (Figure 3—figure supplement 2C–D). Together this data indicates that AR LBD is a substrate of the PRMT5 enzyme in vitro, and that the ERG ETS domain can facilitate greater PRMT5 activity on AR.

To identify the arginine methylation site(s) on AR, we cloned AR cDNA and mutated all arginines in the LBD to lysine (see Materials and methods). We expressed each construct in AR-negative, ERG-negative RWPE-1 prostate cells. R1881 stimulates exogenous AR to induce target gene expression in these cells. ERG expression represses this effect (Figure 3—figure supplement 3A–B) and induces PRMT5-dependent mono- and symmetric di-methylation of AR (Figure 3E). RWPE-1 cells co-expressing ERG with each of the AR constructs were assessed for SDMA and MMA modification of AR following immunoprecipitation. All mutants were expressed at equivalent levels to wild-type AR (Figure 3—figure supplement 3C). Only one AR mutant, R761K, completely lacked MMA and SDMA of AR in the presence of ERG (Figure 3F; Figure 3—figure supplement 3D). We confirmed these results in RWPE-1 cells using a proximity ligation assay to detect symmetric di-methylation of AR (Materials and methods). We detected strong proximity signals in RWPE-1 nuclei upon expression of wild-type AR and exposure to R1881 (which stimulates nuclear translocation of AR) that were dependent upon ERG expression. These signals were not detected in the AR R761K mutant cell line (Figure 3G). This demonstrates that arginine 761 is the likely target of ERG- and PRMT5-dependent AR methylation.

Available structural information (Chandra V et al., 2008; Emsley et al., 2010; Helsen et al., 2012) (see Materials and methods) suggests R761 methylation on AR may affect LBD interactions with the DNA binding domain (DBD, Figure 4A), resulting in altered DNA binding and gene activation. To test this, we evaluated the recruitment of WT versus R761K mutant AR in RWPE-1 cells treated with R1881, using the PSA locus as a model AR-regulated gene. Relative to WT AR, the AR R761K mutant showed enhanced recruitment to PSA and increased PSA expression. Moreover, R761K mutation prevented ERG-dependent attenuation of AR recruitment to PSA and PSA expression (Figure 4B,C). In contrast to these effects, the AR R761K mutation did not affect overall AR protein levels, the ability of AR to shuttle into the nucleus upon R1881 induction (Figure 4—figure supplement 1), or the levels of ERG or PRMT5 recruitment to PSA (Figure 4—figure supplement 1C). These results indicate R761 methylation mediated through ERG and PRMT5 attenuates ligand-dependent AR activation, likely through modulating interactions between the LBD and DBD.

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Increased AR activity drives PC proliferation (Chen et al., 2004). However, we noted that RWPE-1 cells expressing AR R761K, despite increased AR activity, were more prone to R1881-induced growth arrest (Figure 4D). This suggested that heightened AR activity via R761K mutation (or loss of R761 methylation) may block proliferation in certain contexts. To further explore this, we expressed R761K mutant AR in VCaP cells. Despite transcriptional hyperactivity, as judged by increased PSA expression relative to either WT or an irrelevant R789K mutant AR, VCaP cells expressing AR R761K proliferated poorly in reduced-androgen media (Figure 4E and F).

Detailed mechanisms of how the tumor context affects AR and other lineage oncogenes to switch their function from lineage differentiation to proliferation in cancer has remained elusive (Garraway and Sellers, 2006). Our results indicate that a primary effect of ERG in facilitating PC proliferation is modulating AR function. We propose that ERG- and PRMT5-dependent methylation of R761 on AR reduces AR recruitment to genes that would otherwise induce differentiation, yet R761 methylation allows sufficient AR function to promote proliferation. While our results raise the question of how R761-methylated AR may still facilitate proliferation, R761 methylation could prove a relevant biomarker for AR-mediated proliferation versus arrest in TMPRSS2:ERG positive cells. Finally, as PRMT5 is an enzyme required downstream of ERG in facilitating AR proliferative function, exploring therapeutic PRMT5 inhibition in TMPRSS2:ERG positive prostate cancers may be warranted.

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Author details

1. Zineb Mounir

   Department of Oncology, Novartis Institutes for BioMedical Research, Cambridge, United States

   Present address

   Genentech, South San Francisco, United States

   Contribution

   ZM, Conception and design, Acquisition of data, Analysis and interpretation of data, Drafting or revising the article

   Competing interests

   ZM: was the recipient of presidential postdoctoral fellowship from the Novartis Institutes for Biomedical Research and is an employee of Genentech.

2. Joshua M Korn

   Department of Oncology, Novartis Institutes for BioMedical Research, Cambridge, United States

   Contribution

   JMK, Conception and design, Analysis and interpretation of data, Drafting or revising the article

   Competing interests

   No competing interests declared.

3. Thomas Westerling

   1. Department of Medical Oncology, Harvard Medical School, Boston, United States
   2. Center for Functional Cancer Epigenetics, Harvard Medical School, Boston, United States
   3. Dana-Farber Cancer Institute, Harvard Medical School, Boston, United States

   Contribution

   TW, Conception and design, Acquisition of data, Analysis and interpretation of data

   Competing interests

   No competing interests declared.

4. Fallon Lin

   Department of Oncology, Novartis Institutes for BioMedical Research, Cambridge, United States

   Contribution

   FL, Acquisition of data, Analysis and interpretation of data, Drafting or revising the article

   Competing interests

   FL: employee of Novartis Institutes for Biomedical Research.

5. Christina A Kirby

   Center for Proteomic Chemistry, Novartis Institutes for BioMedical Research, Cambridge, United States

   Contribution

   CAK, Conception and design, Analysis and interpretation of data, Drafting or revising the article

   Competing interests

   CAK: employee of Novartis Institutes for Biomedical Research.

6. Markus Schirle

   Developmental and Molecular Pathways, Novartis Institutes for Biomedical Research, Cambridge, United States

   Contribution

   MSch, Acquisition of data, Analysis and interpretation of data, Drafting or revising the article

   Competing interests

   MSch: employee of Novartis Institutes for Biomedical Research.

7. Gregg McAllister

   Developmental and Molecular Pathways, Novartis Institutes for Biomedical Research, Cambridge, United States

   Contribution

   GM, Conception and design, Acquisition of data, Analysis and interpretation of data

   Competing interests

   GM: employee of Novartis Institutes for Biomedical Research.

8. Greg Hoffman

   Developmental and Molecular Pathways, Novartis Institutes for Biomedical Research, Cambridge, United States

   Contribution

   GH, Conception and design, Acquisition of data, Analysis and interpretation of data

   Competing interests

   GH: employee of Novartis Institutes for Biomedical Research.

9. Nadire Ramadan

   Developmental and Molecular Pathways, Novartis Institutes for Biomedical Research, Cambridge, United States

   Contribution

   NR, Conception and design, Acquisition of data, Analysis and interpretation of data

   Competing interests

   NR: employee of Novartis Institutes for Biomedical Research.

10. Anke Hartung

    Genomics Institute of the Novartis Research Foundation, Novartis Institutes for Bio Medical Resarch, San Diego, United States

    Present address

    Organovo, San Diego, United States

    Contribution

    AH, Conception and design, Acquisition of data, Analysis and interpretation of data

    Competing interests

    AH: is an employee of Organovo.

11. Yan Feng

    Developmental and Molecular Pathways, Novartis Institutes for Biomedical Research, Cambridge, United States

    Contribution

    YF, Conception and design, Acquisition of data, Analysis and interpretation of data

    Competing interests

    YF: employee of Novartis Institutes for Biomedical Research.

12. David Randal Kipp

    Department of Oncology, Novartis Institutes for BioMedical Research, Cambridge, United States

    Present address

    Laboratories Servier, Neuilly-sur-Seine, France

    Contribution

    DRK, Conceived, executed, and interpreted experiments to produce AR and ERG protein, and to use these proteins to assess the ability of PRMT5 to methylate AR

    Competing interests

    DRK: employee of Novartis Institutes for Biomedical Research.

13. Christopher Quinn

    Department of Oncology, Novartis Institutes for BioMedical Research, Cambridge, United States

    Present address

    Laboratories Servier, Neuilly-sur-Seine, France

    Contribution

    CQ, Conceived, executed, and interpreted experiments to produce AR and ERG protein, and to use these proteins to assess the ability of PRMT5 to methylate AR

    Competing interests

    CQ: employee of Novartis Institutes for Biomedical Research.

14. Michelle Fodor

    Department of Oncology, Novartis Institutes for BioMedical Research, Cambridge, United States

    Present address

    Laboratories Servier, Neuilly-sur-Seine, France

    Contribution

    MF, Conceived, executed, and interpreted experiments to produce AR and ERG protein, and to use these proteins to assess the ability of PRMT5 to methylate AR

    Competing interests

    MF: employee of Novartis Institutes for Biomedical Research.

15. Jason Baird

    Department of Oncology, Novartis Institutes for BioMedical Research, Cambridge, United States

    Present address

    Laboratories Servier, Neuilly-sur-Seine, France

    Contribution

    JB, Conceived, executed, and interpreted experiments to produce AR and ERG protein, and to use these proteins to assess the ability of PRMT5 to methylate AR

    Competing interests

    No competing interests declared.

16. Marie Schoumacher

    Department of Oncology, Novartis Institutes for BioMedical Research, Cambridge, United States

    Present address

    Laboratories Servier, Neuilly-sur-Seine, France

    Contribution

    MSch, Acquisition of data, Analysis and interpretation of data

    Competing interests

    No competing interests declared.

17. Ronald Meyer

    Department of Oncology, Novartis Institutes for BioMedical Research, Cambridge, United States

    Contribution

    RM, Acquisition of data, Analysis and interpretation of data

    Competing interests

    RM: employee of Novartis Institutes for Biomedical Research.

18. James Deeds

    Department of Oncology, Novartis Institutes for BioMedical Research, Cambridge, United States

    Contribution

    JD, Acquisition of data, Analysis and interpretation of data

    Competing interests

    JD: employee of Novartis Institutes for Biomedical Research.

19. Gilles Buchwalter

    1. Department of Medical Oncology, Harvard Medical School, Boston, United States
    2. Center for Functional Cancer Epigenetics, Harvard Medical School, Boston, United States
    3. Dana-Farber Cancer Institute, Harvard Medical School, Boston, United States

    Present address

    Celgene Avilomics Research, Bedford, United States

    Contribution

    GB, Conception and design, Acquisition of data, Analysis and interpretation of data

    Competing interests

    GB: is an employee of Celgene.

20. Travis Stams

    Center for Proteomic Chemistry, Novartis Institutes for BioMedical Research, Cambridge, United States

    Contribution

    TS, Conception and design, Analysis and interpretation of data

    Competing interests

    TS: employee of Novartis Institutes for Biomedical Research.

21. Nicholas Keen

    Department of Oncology, Novartis Institutes for BioMedical Research, Cambridge, United States

    Contribution

    NK, Conception and design, Analysis and interpretation of data

    Competing interests

    NK: employee of Novartis Institutes for Biomedical Research.

22. William R Sellers

    Department of Oncology, Novartis Institutes for BioMedical Research, Cambridge, United States

    Contribution

    WRS, Conception and design, Analysis and interpretation of data

    Competing interests

    WRS: employee of Novartis Institutes for Biomedical Research.

23. Myles Brown

    1. Department of Medical Oncology, Harvard Medical School, Boston, United States
    2. Center for Functional Cancer Epigenetics, Harvard Medical School, Boston, United States
    3. Dana-Farber Cancer Institute, Harvard Medical School, Boston, United States

    Contribution

    MB, Conception and design, Analysis and interpretation of data, Drafting or revising the article

    Competing interests

    MB: is a consultant to Novartis and the recipient of sponsored research support from Novartis.

    "This ORCID iD identifies the author of this article:" 0000-0002-8213-1658

24. Raymond A Pagliarini

    Department of Oncology, Novartis Institutes for BioMedical Research, Cambridge, United States

    Contribution

    RAP, Conception and design, Analysis and interpretation of data, Drafting or revising the article

    For correspondence

    raymond.pagliarini@novartis.com

    Competing interests

    RAP: employee of Novartis Institutes for Biomedical Research.

    "This ORCID iD identifies the author of this article:" 0000-0001-8920-8198

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