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• W2062802357 abstract "•Parallel in vitro and in vivo RNAi screens identify specific tumor dependencies•DDR kinases are activated following hypoxia during tumor expansion•Tumor growth is dependent on DDR kinase activity•A “druggable” synthetic lethal relationship exists between DDR inhibition and hypoxia To identify factors preferentially necessary for driving tumor expansion, we performed parallel in vitro and in vivo negative-selection short hairpin RNA (shRNA) screens. Melanoma cells harboring shRNAs targeting several DNA damage response (DDR) kinases had a greater selective disadvantage in vivo than in vitro, indicating an essential contribution of these factors during tumor expansion. In growing tumors, DDR kinases were activated following hypoxia. Correspondingly, depletion or pharmacologic inhibition of DDR kinases was toxic to melanoma cells, including those that were resistant to BRAF inhibitor, and this could be enhanced by angiogenesis blockade. These results reveal that hypoxia sensitizes melanomas to targeted inhibition of the DDR and illustrate the utility of in vivo shRNA dropout screens for the identification of pharmacologically tractable targets. To identify factors preferentially necessary for driving tumor expansion, we performed parallel in vitro and in vivo negative-selection short hairpin RNA (shRNA) screens. Melanoma cells harboring shRNAs targeting several DNA damage response (DDR) kinases had a greater selective disadvantage in vivo than in vitro, indicating an essential contribution of these factors during tumor expansion. In growing tumors, DDR kinases were activated following hypoxia. Correspondingly, depletion or pharmacologic inhibition of DDR kinases was toxic to melanoma cells, including those that were resistant to BRAF inhibitor, and this could be enhanced by angiogenesis blockade. These results reveal that hypoxia sensitizes melanomas to targeted inhibition of the DDR and illustrate the utility of in vivo shRNA dropout screens for the identification of pharmacologically tractable targets. It is well established that many cancers are “addicted” to certain altered genes, a vulnerability that can be exploited therapeutically. Equally interesting is the premise that tumors express genes that are not mutated, but to which they are addicted nonetheless. Owing to several stress factors, including adaptation to their microenvironment, cancer cells are under continuous selective pressure to survive. This requires substantial deregulation of unmutated signaling factors, and also this phenomenon can create tumor-specific dependencies. Targeting this “non-oncogene addiction” therefore represents a complementary tactic to exploiting oncogene addiction (Luo et al., 2009Luo J. Solimini N.L. Elledge S.J. Principles of cancer therapy: oncogene and non-oncogene addiction.Cell. 2009; 136: 823-837Abstract Full Text Full Text PDF PubMed Scopus (1383) Google Scholar). This strategy builds on the concept of “synthetic lethality,” which is based on the principle that a single (genetic) perturbation is compatible with cell viability, but a second concomitant alteration is lethal (Kaelin, 2005Kaelin Jr., W.G. The concept of synthetic lethality in the context of anticancer therapy.Nat. Rev. Cancer. 2005; 5: 689-698Crossref PubMed Scopus (1124) Google Scholar). It was not until the completion of the human genome sequence as well as the availability of genome-wide RNAi that the concept of synthetic lethality could be translated to experimental mammalian systems. Several examples illustrate the feasibility of drug effectiveness and selectivity in the context of non-oncogene addiction and synthetic lethality. For example, BRCA1/2-deficient breast cancers are highly sensitive to inhibitors targeting PARP (Farmer et al., 2005Farmer H. McCabe N. Lord C.J. Tutt A.N.J. Johnson D.A. Richardson T.B. Santarosa M. Dillon K.J. Hickson I. Knights C. et al.Targeting the DNA repair defect in BRCA mutant cells as a therapeutic strategy.Nature. 2005; 434: 917-921Crossref PubMed Scopus (4749) Google Scholar, Sharma and Settleman, 2010Sharma S.V. Settleman J. Exploiting the balance between life and death: targeted cancer therapy and “oncogenic shock”.Biochem. Pharmacol. 2010; 80: 666-673Crossref PubMed Scopus (48) Google Scholar). Similarly, in BRAF mutant melanomas, there is a strict requirement for MEK (Flaherty et al., 2012Flaherty K.T. Robert C. Hersey P. Nathan P. Garbe C. Milhem M. Demidov L.V. Hassel J.C. Rutkowski P. Mohr P. et al.METRIC Study GroupImproved survival with MEK inhibition in BRAF-mutated melanoma.N. Engl. J. Med. 2012; 367: 107-114Crossref PubMed Scopus (1756) Google Scholar, Kaelin, 2004Kaelin Jr., W.G. Gleevec: prototype or outlier?.Sci. STKE. 2004; 2004: pe12PubMed Google Scholar, Sawyers, 2005Sawyers C.L. Making progress through molecular attacks on cancer.Cold Spring Harb. Symp. Quant. Biol. 2005; 70: 479-482Crossref PubMed Scopus (25) Google Scholar, Solit et al., 2006Solit D.B. Garraway L.A. Pratilas C.A. Sawai A. Getz G. Basso A. Ye Q. Lobo J.M. She Y. Osman I. et al.BRAF mutation predicts sensitivity to MEK inhibition.Nature. 2006; 439: 358-362Crossref PubMed Scopus (1155) Google Scholar) and ERK (Chapman et al., 2011Chapman P.B. Hauschild A. Robert C. Haanen J.B. Ascierto P. Larkin J. Dummer R. Garbe C. Testori A. Maio M. et al.BRIM-3 Study GroupImproved survival with vemurafenib in melanoma with BRAF V600E mutation.N. Engl. J. Med. 2011; 364: 2507-2516Crossref PubMed Scopus (6216) Google Scholar, Hauschild et al., 2012Hauschild A. Grob J.-J. Demidov L.V. Jouary T. Gutzmer R. Millward M. Rutkowski P. Blank C.U. Miller Jr., W.H. Kaempgen E. et al.Dabrafenib in BRAF-mutated metastatic melanoma: a multicentre, open-label, phase 3 randomised controlled trial.Lancet. 2012; 380: 358-365Abstract Full Text Full Text PDF PubMed Scopus (2407) Google Scholar, Morris et al., 2013Morris E.J. Jha S. Restaino C.R. Dayananth P. Zhu H. Cooper A. Carr D. Deng Y. Jin W. Black S. et al.Discovery of a novel ERK inhibitor with activity in models of acquired resistance to BRAF and MEK inhibitors.Cancer Discov. 2013; 3: 742-750Crossref PubMed Scopus (473) Google Scholar). In addition, melanoma cells are highly dependent on pyruvate dehydrogenase kinase (PDK1), the gatekeeper enzyme linking glycolysis to the citric acid cycle (Kaplon et al., 2013Kaplon J. Zheng L. Meissl K. Chaneton B. Selivanov V.A. Mackay G. van der Burg S.H. Verdegaal E.M.E. Cascante M. Shlomi T. et al.A key role for mitochondrial gatekeeper pyruvate dehydrogenase in oncogene-induced senescence.Nature. 2013; 498: 109-112Crossref PubMed Scopus (440) Google Scholar). These examples suggest that also the “non-oncogenome” ought to be exploited for drug-target discovery. Both the limited number of clinically approved targeted drugs available and the challenging problem of common drug resistance, which can be highly pleiotropic (Jang and Atkins, 2013Jang S. Atkins M.B. Which drug, and when, for patients with BRAF-mutant melanoma?.Lancet Oncol. 2013; 14: e60-e69Abstract Full Text Full Text PDF PubMed Scopus (164) Google Scholar), underscore the need to identify novel factors amenable to targeted interference. Systematic gene silencing by RNAi libraries in cancer cells has proven to reveal such unforeseen cellular dependencies. However, because these experiments are commonly performed in vitro, they ignore the effects of in vivo parameters on both tumor progression and drug response. The complex and harsh conditions resulting from tumor expansion such as nutrient deprivation, limited oxygen availability, and the generation of reactive oxygen species (Lee and Herlyn, 2007Lee J.T. Herlyn M. Microenvironmental influences in melanoma progression.J. Cell. Biochem. 2007; 101: 862-872Crossref PubMed Scopus (63) Google Scholar) are difficult to mimic in cell culture. It is likely, therefore, that the functional mining of “druggable” targets has been far from complete and that, particularly under in vivo conditions, additional factors that are essential for tumor expansion can be unmasked. Therefore, we set out to perform parallel in vivo and in vitro negative-selection short hairpin RNA (shRNA) screens for genes that preferentially contribute to tumor cell proliferation and survival in vivo. A rate-limiting requirement for a negative-selection shRNA screen in tumors is the prevention of random loss of cells, and thereby shRNAs, which is seen when only a fraction of the cells contribute to the expanding tumor mass. In most human tumor types, only specific subpopulations of cells are endowed with tumorigenic potential when transplanted into immune-compromised mice (Shackleton et al., 2009Shackleton M. Quintana E. Fearon E.R. Morrison S.J. Heterogeneity in cancer: cancer stem cells versus clonal evolution.Cell. 2009; 138: 822-829Abstract Full Text Full Text PDF PubMed Scopus (894) Google Scholar). Also for melanomas, the presence of tumor-initiating cells has been reported (Boiko et al., 2010Boiko A.D. Razorenova O.V. van de Rijn M. Swetter S.M. Johnson D.L. Ly D.P. Butler P.D. Yang G.P. Joshua B. Kaplan M.J. et al.Human melanoma-initiating cells express neural crest nerve growth factor receptor CD271.Nature. 2010; 466: 133-137Crossref PubMed Scopus (577) Google Scholar, Roesch et al., 2010Roesch A. Fukunaga-Kalabis M. Schmidt E.C. Zabierowski S.E. Brafford P.A. Vultur A. Basu D. Gimotty P. Vogt T. Herlyn M. A temporarily distinct subpopulation of slow-cycling melanoma cells is required for continuous tumor growth.Cell. 2010; 141: 583-594Abstract Full Text Full Text PDF PubMed Scopus (894) Google Scholar, Schatton et al., 2008Schatton T. Murphy G.F. Frank N.Y. Yamaura K. Waaga-Gasser A.M. Gasser M. Zhan Q. Jordan S. Duncan L.M. Weishaupt C. et al.Identification of cells initiating human melanomas.Nature. 2008; 451: 345-349Crossref PubMed Scopus (1164) Google Scholar). However, specific modifications in the xenotransplantation methods strongly increase the efficiency of melanoma formation (Quintana et al., 2008Quintana E. Shackleton M. Sabel M.S. Fullen D.R. Johnson T.M. Morrison S.J. Efficient tumour formation by single human melanoma cells.Nature. 2008; 456: 593-598Crossref PubMed Scopus (1498) Google Scholar, Quintana et al., 2010Quintana E. Shackleton M. Foster H.R. Fullen D.R. Sabel M.S. Johnson T.M. Morrison S.J. Phenotypic heterogeneity among tumorigenic melanoma cells from patients that is reversible and not hierarchically organized.Cancer Cell. 2010; 18: 510-523Abstract Full Text Full Text PDF PubMed Scopus (469) Google Scholar). In particular, when tumor cells are embedded in Matrigel and inoculated into severely immune-compromised NOD/SCID IL2Rγnull (NSG) mice human melanomas develop faster and more efficiently, even when inoculated as single cells. Because under these conditions most melanoma cells have tumor-forming potential, we selected this tumor type and mouse model for the screens outlined below. To investigate whether such conditions are compatible with negative-selection screening of high-complexity shRNA libraries, we first performed a proof-of-principle experiment using a GFP-tagged library comprising 2,600 barcodes (noncoding semirandom DNA sequences), which do not affect cellular fitness. This library has been employed successfully to dissect T cell lineage relationships previously (Gerlach et al., 2013Gerlach C. Rohr J.C. Perié L. van Rooij N. van Heijst J.W.J. Velds A. Urbanus J. Naik S.H. Jacobs H. Beltman J.B. et al.Heterogeneous differentiation patterns of individual CD8+ T cells.Science. 2013; 340: 635-639Crossref PubMed Scopus (265) Google Scholar, Schepers et al., 2008Schepers K. Swart E. van Heijst J.W.J. Gerlach C. Castrucci M. Sie D. Heimerikx M. Velds A. Kerkhoven R.M. Arens R. Schumacher T.N. Dissecting T cell lineage relationships by cellular barcoding.J. Exp. Med. 2008; 205: 2309-2318Crossref PubMed Scopus (93) Google Scholar). Our feasibility experiment was based on the premise that similar recoveries of the barcodes from independent tumors would indicate that a sufficient number of cells participate in tumor establishment. The barcode library was introduced into melanoma cells by retroviral transduction using a low multiplicity of infection (MOI) to ensure that each cell received one barcode copy only. GFP-positive cells were sorted and inoculated subcutaneously (s.c.) into two NSG mice (Figure 1A). We removed the tumors from the mice when they reached a measurable size and subsequently analyzed the distribution of barcodes. Genomic DNA isolated from each tumor was divided into two half-samples, and a “self-self” test showed that the ratio between barcodes detected in each sample was close to one for both tumors (Figure S1), indicating that the prevalence of individual genetic tags could be reproducibly quantified. This result also predicted that statistically significant outliers in self-nonself comparisons (in an shRNA screen) would be real. More importantly, comparison of the two biological replicates showed a remarkably large overlap of barcodes (Figure 1B). This indicated that in independent transplanted melanomas, a sufficient number of cells contribute to tumor establishment and confirmed the feasibility of a large-scale dropout screen in vivo. To perform parallel in vitro and in vivo screens, we assembled an shRNA library targeting ∼500 human kinases (and related factors), with approximately five shRNAs per gene. The aim was to detect shRNAs that are selected against in vivo, but not or to a lesser extent in vitro, to identify pharmacologically tractable factors critically contributing to tumor expansion. Human melanoma cells were transduced with four lentiviral pools, together encoding the shRNA kinome library, and subsequently pharmacologically selected for successful integration and expression (Figure 1C). Two days postinfection, two independent reference samples were collected to make an inventory of the shRNAs present at the start of the screens. The remaining cells were split in two, and the first group was resuspended in Matrigel and immediately transplanted s.c. into six NSG mice. Because we aimed to identify shRNAs preferentially depleted in expanding tumors relative to an in vitro setting, we maintained the second group of cells in parallel in culture. This was done in six independent cell culture plates and for approximately the same period that the tumors were expanding in mice. Once the tumors had reached 60–100 mm3, they were removed from the mice and genomic DNA was extracted, as well as from the cultured tumor cells. We used PCR amplification of the shRNAs followed by deep sequencing for the recovery and quantification of shRNAs present in each sample. To select genuine “dropouts,” that is, shRNAs that were depleted during either in vitro propagation or during tumor expansion in vivo, we performed a strict quality-control analysis on the sequencing data. The number of shRNAs detected in each sample demonstrated that the library complexity was very well maintained in all samples in vitro and in vivo: approximately 93% of the shRNAs that were detected in the reference samples were reproducibly observed in cultured cells, while 85% of the shRNAs originally present were retrieved from the tumors (Figure 1D). Similar to what was seen for the barcode experiment, we observed a high correlation between independent biological replicates (Figure 1E). Unsupervised analysis showed clustering of all samples within each biological group, indicating that random changes were minor relative to the difference between in vitro and in vivo tumor growth (Figure 1F). Corroborating the results from the barcode screen, these data predict that the likelihood of selecting false-positive hits was minimal. To call hits, that is, to identify genes with a significant role in vivo, we applied several criteria. First, we selected genes for which at least two independent shRNAs were significantly depleted in tumors compared to both the references and the cultured cells (Figures 2A, 2B, and S2A). Second, we filtered out genes for which two or more shRNAs were depleted from cultured cells compared to the references (Figure S2B). For example, one gene that failed to score as a hit based on these stringent criteria is BRAF. The mutant form of BRAF acts as the driver oncogene in melanoma (Davies et al., 2002Davies H. Bignell G.R. Cox C. Stephens P. Edkins S. Clegg S. Teague J. Woffendin H. Garnett M.J. Bottomley W. et al.Mutations of the BRAF gene in human cancer.Nature. 2002; 417: 949-954Crossref PubMed Scopus (8396) Google Scholar), and its depletion induces cell death both in vitro and in vivo (Hingorani et al., 2003Hingorani S.R. Jacobetz M.A. Robertson G.P. Herlyn M. Tuveson D.A. Suppression of BRAF(V599E) in human melanoma abrogates transformation.Cancer Res. 2003; 63: 5198-5202PubMed Google Scholar, Tsai et al., 2008Tsai J. Lee J.T. Wang W. Zhang J. Cho H. Mamo S. Bremer R. Gillette S. Kong J. Haass N.K. et al.Discovery of a selective inhibitor of oncogenic B-Raf kinase with potent antimelanoma activity.Proc. Natl. Acad. Sci. USA. 2008; 105: 3041-3046Crossref PubMed Scopus (1113) Google Scholar). Indeed, although we observed loss of BRAF-targeting shRNAs, this occurred to similar extents in vitro and in vivo (Figure S3A); hence, BRAF failed to classify as a preferential in vivo target. Seven genes did meet our criteria: they were depleted by two or more shRNAs to a significantly greater extent in vivo than in vitro (Figure 2A). The identification in the screen of FRAP1, encoding mTOR, was reassuring because of the established role it plays in melanoma (Karbowniczek et al., 2008Karbowniczek M. Spittle C.S. Morrison T. Wu H. Henske E.P. mTOR is activated in the majority of malignant melanomas.J. Invest. Dermatol. 2008; 128: 980-987Abstract Full Text Full Text PDF PubMed Scopus (138) Google Scholar). A key advantage of large-scale shRNA screening, in addition to its unbiased nature, is the possibility of identifying multiple pathway components rather than single factors. We noted that two out of the seven screen hits were key kinases involved in the DNA damage response (DDR), ATM and Chek1, while Chek2 scored with one shRNA. Because it is an established substrate of ATM, we included Chek2 in the subsequent validation. In the screen, shRNAs targeting these three genes were more strongly selected against in vivo than in vitro, resulting in some cases in their complete loss in tumor xenografts (Figures S3B–S3D). To validate these results, we stably knocked down these three genes one by one, inoculated the melanoma cells into NSG mice, and monitored tumor growth. Silencing of CHEK1, CHEK2, or ATM, each with independent shRNAs, profoundly delayed tumor growth (Figures 3A–3C). CHEK1 shRNA #2 and CHEK2 shRNAs #1 and #2 particularly showed minimal effect on cell viability in vitro but caused strong tumor inhibition in vivo (Figures 3A–3C, inserts). We did not observe major differences in the expression levels of the proliferation marker PCNA in cell cultures versus tumor cells that grew in mice (Figure S3E), suggesting that this cannot account for the observed differential sensitivity to CHEK1, CHEK2, or ATM depletion. The average weights of shCHEK1, shCHEK2, and shATM tumors extracted at the endpoint of the experiment were significantly lower than those of control tumors (Figures S3F–S3H). Notably, whereas an efficient knockdown of all these genes was confirmed before injection, tumors that eventually grew out had restored their expression, consistent with the idea that silencing of any of these DDR genes is incompatible with melanoma outgrowth in vivo (Figures 3D–3F). Taken together, these observations indicate that three established DDR kinases individually have essential roles in driving melanoma expansion. We next investigated why deprivation of DDR factors confers a strong selective disadvantage onto expanding melanomas. We hypothesized that the DDR may be induced as a function of tumor expansion. Indeed, six out of six melanomas established in mice displayed increased phosphorylation of ATM, Chek1, and Chek2 relative to cells cultured in vitro (Figure 4A). When monitoring the dynamics of this phenomenon in an independent experiment, we found no evidence for activation of the DDR pathway in the first week after transplantation (Figure 4B). This result argues that the DDR was not induced artificially because of the mere transfer of the cells from cell culture dishes into animals. In contrast, we consistently observed induction of these DDR factors from 2 weeks post-inoculation onward, until the time that tumors reached 500 mm3. The activation of these DDR kinases coincided with the phosphorylation of an array of ATM/ATR substrates. The same pattern on the levels of DDR factors was observed when transplanting a different cell line, ruling out cell-type-specific effects (Figure S4A). DDR signaling can be activated in response to different kinds of environmental and endogenous stress signals. In order for tumors to expand, a key obstacle to overcome is to proliferate and survive under suboptimal conditions. This includes the lack of proper vasculature, necessary for transporting nutrients and oxygen (Pouysségur et al., 2006Pouysségur J. Dayan F. Mazure N.M. Hypoxia signalling in cancer and approaches to enforce tumour regression.Nature. 2006; 441: 437-443Crossref PubMed Scopus (1396) Google Scholar). In fact, hypoxia can activate ATM and ATR checkpoints, and hypoxic tumor cells display defective DNA repair, increased mutation rates, and chromosomal instability (Bencokova et al., 2009Bencokova Z. Kaufmann M.R. Pires I.M. Lecane P.S. Giaccia A.J. Hammond E.M. ATM activation and signaling under hypoxic conditions.Mol. Cell. Biol. 2009; 29: 526-537Crossref PubMed Scopus (169) Google Scholar, Hammond et al., 2007Hammond E.M. Kaufmann M.R. Giaccia A.J. Oxygen sensing and the DNA-damage response.Curr. Opin. Cell Biol. 2007; 19: 680-684Crossref PubMed Scopus (40) Google Scholar, Olcina et al., 2010Olcina M. Lecane P.S. Hammond E.M. Targeting hypoxic cells through the DNA damage response.Clin. Cancer Res. 2010; 16: 5624-5629Crossref PubMed Scopus (85) Google Scholar). Expanding tumors had abundant levels of Hypoxia-Inducible Transcription Factor 1α (HIF1α), the master transcription factor controlling cellular adaptation to low oxygen levels (Figure 5A). Following its stabilization, DDR signaling was induced. That this link between hypoxia and DDR may be causal was further suggested by the strong increase in phosphorylation of both ATM and Chek2, which followed the induction of HIF1α by hypoxia in vitro (Figure 5B). Under hypoxic conditions, HIF1α becomes stabilized, allowing for dimerization with HIF1β and inducing an arsenal of genes to help cells cope with harsh microenvironmental conditions (Pouysségur et al., 2006Pouysségur J. Dayan F. Mazure N.M. Hypoxia signalling in cancer and approaches to enforce tumour regression.Nature. 2006; 441: 437-443Crossref PubMed Scopus (1396) Google Scholar). HIF1α stabilization can be achieved also chemically by dimethyloxalylglycine (DMOG), which inhibits its degradation. Exposure of cells to DMOG stabilized HIF1α, which was accompanied by increased phosphorylation of particularly Chek1 and Chek2, indicating that HIF1α can induce (at least these aspects of) DDR activation (Figure 5C). To assess an in vivo correlation between hypoxia and DDR, we performed a series of immunohistochemical stainings of phospho-Chek2, phospho-ATM/ATR substrates and γH2AX on xenografted tumors (Figure 5D). This analysis revealed that the hypoxic areas in the tumors, as illustrated by the hematoxylin and eosin (H&E) staining showing many pyknotic/necrotic cells (see inset) and highlighted by the staining of pimonidazole, corresponded to the DDR areas as indicated by the intense staining of phospho-ATM/ATR substrates and γH2AX. Although few cells were positive for phospho-Chek2 staining, the positive cells were distinguishably localized in the areas where other DDR proteins were highly expressed. Furthermore, melanoma cells showed high Ki67 expression throughout the entire tumor. Since melanoma cells under hypoxic conditions and with induced levels of HIF1α exhibited increased DDR, we hypothesized that they may be more sensitive to the effects of pharmacologic Chek1/2 inhibition. Exposure to either AZD7762, an inhibitor that blocks Chek1/2 activity (Figure S5A), or DMOG caused little melanoma cell death in vitro. In contrast, combination of these compounds caused massive melanoma cell death, as illustrated by PARP cleavage and cell viability assays for several melanoma cell lines (including 888mel in which the screen was performed; Figures 6A and 6B ). Of note, this effect appeared to be shared by BRAF and NRAS mutant melanomas and independent of TP53 mutational status or activity (Figure S5B; Table S1). The effect of DMOG was dependent on HIF signaling, since depletion of ARNT (encoding HIF1β, the essential partner of HIF1α) protected DMOG-treated cells from death upon Chek1/2 inhibition (Figures 6C, S5C, and S5D). Because the emergence of resistance to BRAF inhibition poses a major clinical challenge, we also determined the sensitivity to Chek1/2 inhibition in combination with DMOG in two sets of matched treatment-naive and BRAF-inhibitor-resistant cell lines. The resistant cell lines were as sensitive to the combination treatment as their parental counterparts (Figure 6D). To determine whether this could be recapitulated in a clinically more relevant setting, we established low-passage cell lines from patient-derived xenografts (PDX; M026) of a melanoma patient prior to therapy and after resistance to vemurafenib treatment had occurred (Figure S5E). Again, we observed a strong combinatorial effect also for the resistant cells, suggesting a broad effectiveness of this antitumor strategy in melanoma (Figure 6D). The results shown above raise the possibility that reduced oxygen conditions render melanoma cells more vulnerable to inhibition of the DDR, providing a rationale for pharmacological modulation of both of these factors in vivo. To explore this possibility, we first used the AZD7762 compound to treat mice immediately after transplantation of human melanoma cells. This single agent treatment significantly delayed tumor outgrowth, again illustrating the in vitro/in vivo window seen in the screens (Figure S6A). Systemic drug toxicity was not observed. Control tumors had large necrotic areas that were largely confined to the inner tumor mass, indicative of insufficient oxygen supply. Although AZD7762-treated tumors were smaller, they were much more necrotic and these areas extended well beyond the tumor centers (Figure S6B). Of more clinical relevance, a similar extent of tumor suppression was achieved upon treatment after tumors had already established (Figure 7A), excluding that the effect seen after Chek1/2 inhibition was simply due to a consequence of impairment of early tumor cell engraftment. Above, we showed that a low-passage PDX-derived cell line from a melanoma patient with acquired resistance to vemurafenib could be effectively eliminated by Chek1/2 inhibition in combination with DMOG. Next, we determined the treatment response of a PDX from a patient with primary resistance to vemurafenib (Figure S6C). Chek1/2 inhibition after establishment of the xenograft strongly delayed tumor growth (Figure 7B). Finally, we set out to recapitulate in vivo the cooperative induction of tumor cell death upon hypoxia and DDR inhibition that we had observed in vitro. Treatment of transplanted melanoma cells with the monoclonal antibody bevacizumab, which neutralizes VEGF, accelerated the appearance of large hypoxic areas surrounding necrotic tumor fields after 1 week of tumor transplantation (Figure 7C). More importantly, when bevacizumab and AZD7762 were used in combination, synergistic tumor inhibition was achieved (Figures 7D and S6D). Similarly, synthetic lethality by hypoxia induction and Chek1/2 inhibition in vivo was observed for the PDX derived from a melanoma patient who had acquired resistance to BRAF inhibition (“M026R.X2”; Figure 7E). We conclude from these results that the combined inhibition of DDR kinases and induction of hypoxia represents a potentially valuable treatment option for melanoma, inclusively in the context of BRAF-inhibitor-resistant tumor cells. This study aimed to identify pharmacologically tractable cancer targets by building on a fundamental principle: non-oncogene addiction in vivo. We reasoned that physiologic experimental conditions could identify critical cancer vulnerabilities that would not readily be discovered in cells cultured in vitro. Indeed, in vivo negative-selection screens can uncover specific dependencies (Beronja et al., 2013Beronja S. Janki P. Heller E. Lien W.-H. Keyes B.E. Oshimori N. Fuchs E. RNAi screens in mice identify physiological regulators of oncogenic growth.Nature. 2013; 501: 185-190Crossref PubMed Scopus (128) Google Scholar, Meacham et al., 2009Meacham C.E. Ho E.E. Dubrovsky E. Gertler F.B. Hemann M.T. In vivo RNAi screening identifies regulators of actin dynamics as key determinants of lymphoma progression.Nat. Genet. 2009; 41: 1133-1137Crossref PubMed Scopus (117) Google Scholar, Possemato et al., 2011Possemato R. Marks K.M. Shaul Y.D. Pacold M.E. Kim D. Birsoy K. Sethumadhavan S. Woo H.-K. Jang H.G. Jha A.K. et al.Functional genomics reveal that the serine synthesis pathway is essential in breast cancer.Nature. 2011; 476: 346-350Crossref PubMed Scopus (1143) Google Scholar). For melanoma, single cells can drive tumor growth (Quintana et al., 2008Quintana E. Shackleton M. Sabel M.S. Fullen D.R. Johnson T.M. Morrison S.J. Efficient tumour formation by single human melanoma cells.Nature. 2008; 456: 593-598Crossref PubMed Scopus (1498) Google Scholar, Quintana et al., 2010Quint" @default.
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• W2062802357 title "Parallel In Vivo and In Vitro Melanoma RNAi Dropout Screens Reveal Synthetic Lethality between Hypoxia and DNA Damage Response Inhibition" @default.
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