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Therapy resistance and metastatic processes in prostate cancer (PCa) remain undefined, due to lack of experimental models that mimic different disease stages. We describe a novel androgen-dependent PCa patient-derived xenograft (PDX) model from treatment-naïve, soft tissue metastasis (PNPCa). RNA and whole-exome sequencing of the PDX tissue and organoids confirmed transcriptomic and genomic similarity to primary tumor. PNPCa harboursBRCA2 and CHD1somatic mutations, shows anSPOP/FOXA1-like transcriptomic signature and microsatellite instability, which occurs in 3% of advanced PCa and has never been modelledin vivo. Comparison of the treatment-naïve PNPCa with additional metastatic PDXs (BM18, LAPC9), in a medium-throughput organoid screen of FDA-approved compounds, revealed differential drug sensitivities. Multikinase inhibitors (ponatinib, sunitinib, sorafenib) were broadly effective on all PDX- and patient-derived organoids from advanced cases with acquired resistance to standard-of-care compounds. This proof-of-principle study may provide a preclinical tool to screen drug responses to standard-of-care and newly identified, repurposed compounds.

Therapy resistance and metastatic processes in prostate cancer (PCa) remain undefined, due to lack of experimental models that mimic different disease stages. We describe an androgen-dependent PCa patient-derived xenograft (PDX) model from treatment-naïve, soft tissue metastasis (PNPCa). RNA and whole-exome sequencing of the PDX tissue and organoids confirmed transcriptomic and genomic similarity to primary tumor. PNPCa harbors BRCA2 and CHD1 somatic mutations, shows an SPOP/FOXA1-like transcriptomic signature and microsatellite instability, which occurs in 3% of advanced PCa and has never been modeled in vivo. Comparison of the treatment-naïve PNPCa with additional metastatic PDXs (BM18, LAPC9), in a medium-throughput organoid screen of FDA-approved compounds, revealed differential drug sensitivities. Multikinase inhibitors (ponatinib, sunitinib, sorafenib) were broadly effective on all PDX- and patient-derived organoids from advanced cases with acquired resistance to standard-of-care compounds. This proof-of-principle study may provide a preclinical tool to screen drug responses to standard-of-care and newly identified, repurposed compounds., To date, patients still succumb to cancer, due to tumors not responding to therapy or ultimately acquiring resistance. Here the authors show that by exploiting patient derived organoids and a treatment-naïve patient derived xenograft, patient therapy can be personalized.

Polycystic kidney disease (PKD) is a prevalent genetic disorder, characterized by the formation of kidney cysts that progressively lead to kidney failure. The currently available drug tolvaptan is not well tolerated by all patients and there remains a strong need for alternative treatments. The signaling rewiring in PKD that drives cyst formation is highly complex and not fully understood. As a consequence, the effects of drugs are sometimes difficult to predict. We previously established a high throughput microscopy phenotypic screening method for quantitative assessment of renal cyst growth. Here, we applied this 3D cyst growth phenotypic assay and screened 2320 small drug-like molecules, including approved drugs. We identified 81 active molecules that inhibit cyst growth. Multi-parametric phenotypic profiling of the effects on 3D cultured cysts discriminated molecules that showed preferred pharmacological effects above genuine toxicological properties. Celastrol, a triterpenoid from Tripterygium Wilfordii, was identified as a potent inhibitor of cyst growth in vitro. In an in vivo iKspCre-Pkd1lox,lox mouse model for PKD, celastrol inhibited the growth of renal cysts and maintained kidney function.

The introduction of more relevant cell models in early preclinical drug discovery, combined with high-content imaging and automated analysis, is expected to increase the quality of compounds progressing to preclinical stages in the drug development pipeline. In this review we discuss the current switch to more relevant 3D cell culture models and associated challenges for high-throughput screening and high-content analysis. We propose that overcoming these challenges will enable front-loading the drug discovery pipeline with better biology, extracting the most from that biology, and, in general, improving translation between in vitro and in vivo models. This is expected to reduce the proportion of compounds that fail in vivo testing due to a lack of efficacy or to toxicity.

Conventional high-grade osteosarcoma is the most common primary bone sarcoma, with relatively high incidence in young people. In this study we found that expression of Aven correlates inversely with metastasis-free survival in osteosarcoma patients and is increased in metastases compared to primary tumours. Aven is an adaptor protein that has been implicated in anti-apoptotic signalling and serves as an oncoprotein in acute lymphoblastic leukaemia. In osteosarcoma cells, silencing Aven triggered G2 cell-cycle arrest; Chk1 protein levels were attenuated and ATR-Chk1 DNA damage response signalling in response to chemotherapy was abolished in Aven-depleted osteosarcoma cells, while ATM, Chk2 and p53 activation remained intact. Osteosarcoma is notoriously difficult to treat with standard chemotherapy, and we examined whether pharmacological inhibition of the Aven-controlled ATR-Chk1 response could sensitize osteosarcoma cells to genotoxic compounds. Indeed, pharmacological inhibitors targeting Chk1/Chk2 or those selective for Chk1 synergized with standard chemotherapy in 2D cultures. Likewise, in 3D extracellular matrix-embedded cultures, Chk1 inhibition led to effective sensitization to chemotherapy. Together, these findings implicate Aven in ATR-Chk1 signalling and point towards Chk1 inhibition as a strategy to sensitize human osteosarcomas to chemotherapy.

Conventional high-grade osteosarcoma is the most common primary bone cancer with relatively high incidence in young people. Recurrent and metastatic tumors are difficult to treat. We performed a kinase inhibitor screen in two osteosarcoma cell lines, which identified MEK1/2 inhibitors. These inhibitors were further validated in a panel of six osteosarcoma cell lines. Western blot analysis was performed to assess ERK activity and efficacy of MEK inhibition. A 3D culture system was used to validate results from 2D monolayer cultures. Gene expression analysis was performed to identify differentially expressed gene signatures in sensitive and resistant cell lines. Activation of the AKT signaling network was explored using Western blot and pharmacological inhibition. In the screen, Trametinib, AZD8330 and TAK-733 decreased cell viability by more than 50%. Validation in six osteosarcoma cell lines identified three cell lines as resistant and three as sensitive to the inhibitors. Western blot analysis of ERK activity revealed that sensitive lines had high constitutive ERK activity. Treatment with the three MEK inhibitors in a 3D culture system validated efficacy in inhibition of osteosarcoma viability. MEK1/2 inhibition represents a candidate treatment strategy for osteosarcomas displaying high MEK activity as determined by ERK phosphorylation status.

Polycystic kidney disease (PKD) is a prevalent disorder characterized by renal cysts that lead to kidney failure. Various signaling pathways have been targeted to stop disease progression, but most interventions still focus on alleviating PKD-associated symptoms. The mechanistic complexity of the disease, as well as the lack of functional in vitro assays for compound testing, has made drug discovery for PKD challenging. To identify modulators of PKD, Pkd1–/– kidney tubule epithelial cells were applied to a scalable and automated 3D cyst culture model for compound screening, followed by phenotypic profiling to determine compound efficacy. We used this screening platform to screen a library of 273 kinase inhibitors to probe various signaling pathways involved in cyst growth. We show that inhibition of several targets, including aurora kinase, CDK, Chk, IGF-1R, Syk, and mTOR, but, surprisingly, not PI3K, prevented forskolin-induced cyst swelling. Additionally, we show that multiparametric phenotypic classification discriminated potentially undesirable (i.e., cytotoxic) compounds from molecules inducing the desired phenotypic change, greatly facilitating hit selection and validation. Our findings show that a pathophysiologically relevant 3D cyst culture model of PKD coupled to phenotypic profiling can be used to identify potentially therapeutic compounds and predict and validate molecular targets for PKD.

3D tissue cultures provide a more physiologically relevant context for the screening of compounds, compared with 2D cell cultures. Cells cultured in 3D hydrogels also show complex phenotypes, increasing the scope for phenotypic profiling. Here we describe a high-content screening platform that uses invasive human prostate cancer cells cultured in 3D in standard 384-well assay plates to study the activity of potential therapeutic small molecules and antibody biologics. Image analysis tools were developed to process 3D image data to measure over 800 phenotypic parameters. Multiparametric analysis was used to evaluate the effect of compounds on tissue morphology. We applied this screening platform to measure the activity and selectivity of inhibitors of the c-Met and epidermal growth factor (EGF) receptor (EGFR) tyrosine kinases in 3D cultured prostate carcinoma cells. c-Met and EGFR activity was quantified based on the phenotypic profiles induced by their respective ligands, hepatocyte growth factor and EGF. The screening method was applied to a novel collection of 80 putative inhibitors of c-Met and EGFR. Compounds were identified that induced phenotypic profiles indicative of selective inhibition of c-Met, EGFR, or bispecific inhibition of both targets. In conclusion, we describe a fully scalable high-content screening platform that uses phenotypic profiling to discriminate selective and nonselective (off-target) inhibitors in a physiologically relevant 3D cell culture setting.

Conventional high-grade osteosarcoma is the most common primary bone sarcoma, with relatively high incidence in young people. In this study we found that expression of Aven correlates inversely with metastasis-free survival in osteosarcoma patients and is increased in metastases compared to primary tumours. Aven is an adaptor protein that has been implicated in anti-apoptotic signalling and serves as an oncoprotein in acute lymphoblastic leukaemia. In osteosarcoma cells, silencing Aven triggered G2 cell-cycle arrest; Chk1 protein levels were attenuated and ATR-Chk1 DNA damage response signalling in response to chemotherapy was abolished in Aven-depleted osteosarcoma cells, while ATM, Chk2 and p53 activation remained intact. Osteosarcoma is notoriously difficult to treat with standard chemotherapy, and we examined whether pharmacological inhibition of the Aven-controlled ATR-Chk1 response could sensitize osteosarcoma cells to genotoxic compounds. Indeed, pharmacological inhibitors targeting Chk1/Chk2 or those selective for Chk1 synergized with standard chemotherapy in 2D cultures. Likewise, in 3D extracellular matrix-embedded cultures, Chk1 inhibition led to effective sensitization to chemotherapy. Together, these findings implicate Aven in ATR-Chk1 signalling and point towards Chk1 inhibition as a strategy to sensitize human osteosarcomas to chemotherapy.

3D tissue cultures provide a more physiologically relevant context for the screening of compounds, compared to 2D cell cultures. Cells cultured in 3D hydrogels also show complex phenotypes, increasing the scope for phenotypic profiling. Here we describe a high-content screening platform that uses human micro-tissues cultured in 3D in standard 384 well assay plates to study the activity of biologically active molecules. Image analysis tools were developed to process 3D image data to measure 854 phenotype-derived parameters. Multiparametric analysis was used to evaluate the effect of compounds on tissue morphology. We applied this screening platform to measure the activity and selectivity of inhibitors of the c-Met and EGF receptor (EGFR) tyrosine kinases in 3D cultured prostate carcinoma cells. c-Met and EGFR activity was quantified based on the invasive phenotypic profiles induced by their respective ligands, HGF and EGF, which were added in parallel assays. c-Met and EGFR inhibitors generally showed the expected inhibitory profile equivalent to that obtained in the absence of cognate ligand. However, one phase-III c-Met inhibitor, displayed an unexpected phenotypic profile characterised by potent inhibition of tumour cell invasion and off-target effects consistent with a previously reported polypharmacology of this compound. The screening method was applied to a novel collection of 70 bi-specific compounds designed to target both c-Met and EGFR. Compounds were identified that induced phenotypic profiles indicative of selective inhibition of either c-Met, EGFR or both targets. In conclusion, this poster describes a fully scalable high-content screening platform that uses phenotypic profiling to evaluate receptor tyrosine kinase inhibitor selectivity and activity in a physiologically relevant setting. Citation Format: Leo S. Price, Tijmen Booij, Maarten Klop. A 3D tissue culture-based utra-high content screening platform that uses phenotypic profiling of cancer tissues to identify selective inhibitors of receptor tyrosine kinases. [abstract]. In: Proceedings of the 106th Annual Meeting of the American Association for Cancer Research; 2015 Apr 18-22; Philadelphia, PA. Philadelphia (PA): AACR; Cancer Res 2015;75(15 Suppl):Abstract nr 1703. doi:10.1158/1538-7445.AM2015-1703

Osteosarcoma is the most common primary bone malignancy with relatively high incidence in young people. Here, we found that expression of Aven was inversely correlated with metastasis-free survival in osteosarcoma patients and is increased in metastases compared to primary osteosarcoma biopsies. Also in chondrosarcoma, the second most common bone sarcoma, expression correlated with increased histological grade. Aven is an adaptor protein that has been implicated in anti-apoptotic signaling and serves as an oncoprotein in acute lymphoblastic leukemia. In human osteosarcoma cells, silencing Aven triggered a G2 cell cycle arrest. Chk1 protein levels were attenuated and ATR-Chk1 DNA damage response signaling in response to chemotherapy was abolished in Aven-depleted osteosarcoma cells while ATM, Chk2, and p53 activation remained intact. Osteosarcoma is notoriously difficult to treat with standard chemotherapy, and we examined whether pharmacological inhibition of the Aven-controlled ATR-Chk1 response could sensitize osteosarcoma cells to genotoxic compounds. Indeed, pharmacological inhibitors targeting Chk1/Chk2 or those selective for Chk1 synergized with standard chemotherapy in 2D cultures. Likewise, in 3D extracellular matrix-embedded cultures Chk1 inhibition effectively sensitized human osteosarcoma cells to chemotherapy. Together, these findings implicate Aven in ATR-Chk1 signaling and point towards Chk1 inhibition as a strategy to sensitize osteosarcomas to chemotherapy. Citation Format: Zuzanna Baranski, Tijmen T.H. Booij, Yvonne de Jong, Jolieke van Oosterwijk, Anne-Marie Cleton, Leo Price, Bob van de Water, Judith V.M.G. Bovée, Pancras C.W. Hogendoorn, Erik Danen. Aven-mediated checkpoint kinase control regulates proliferation and resistance to chemotherapy in osteosarcoma cells. [abstract]. In: Proceedings of the 106th Annual Meeting of the American Association for Cancer Research; 2015 Apr 18-22; Philadelphia, PA. Philadelphia (PA): AACR; Cancer Res 2015;75(15 Suppl):Abstract nr 3780. doi:10.1158/1538-7445.AM2015-3780