Search

XLSX file 452K, DSRT Oncology drug collection

PDF file 400K, Supplementary Figures 1-9; Supplementary Tables 4-9 and Supplementary Methods

SUMMARYAcute myeloid leukaemia (AML) is a highly heterogeneous disease. Here, we decipher the disease composition of a single AML patient through longitudinal sampling scrutinized by high-resolution genetic and phenotypic approaches, including sequencing, immunophenotyping, ex vivo drug sensitivity testing and establishment of patient-derived xenograft models. Throughout the disease course we identified patterns of both divergent and convergent molecular evolution within the leukemic compartment. We identified at least six discrete leukaemia initiating cell populations, of which five were characterised by known recurrent mutations in AML. These populations partly correlated with immunophenotypically defined cell subsets, drug sensitivity profiles and population-specific potential for engraftment in immunodeficient mice. Our results indicate that the genetic and phenotypic development are closely intertwined, and that diversity in the leukaemic gene-environment likely influences disease trajectories.SIGNIFICANCENovel therapeutic approaches in AML are characterised by targeting molecular mechanisms thought to drive leukemogenesis, but emergent evidence suggests that intra-leukemic composition may be more diverse than previously appreciated. Through in-depth genetic and phenotypic characterization of the disease course of a single AML patient, we demonstrate a high degree of inter-individual complexity that exceeds the prevailing disease conception. The temporal molecular landscape of this patient suggests that leukemogenic transitions may not be categorically monoclonal. Patterns of converging molecular evolution further imply that higher levels of biological organisation than the molecular machinery of single cells may influence leukemogenic trajectories. Disease dynamics, relational properties and causal contribution from several levels of biological organization comes into conflict with the linear monocausal explanatory model on which precision oncology is largely built. This may have implications for current precision oncology oriented prectices, including molecular categorization, molecular therapeutic targeting and predictive models.

We sought to identify drugs that could counteract cytarabine resistance in acute myeloid leukemia (AML) by generating eight resistant variants from MOLM-13 and SHI-1 AML cell lines by long-term drug treatment. These cells were compared with 66 ex vivo chemorefractory samples from cytarabine-treated AML patients. The models and patient cells were subjected to genomic and transcriptomic profiling and high-throughput testing with 250 emerging and clinical oncology compounds. Genomic profiling uncovered deletion of the deoxycytidine kinase (DCK) gene in both MOLM-13- and SHI-1-derived cytarabine-resistant variants and in an AML patient sample. Cytarabine-resistant SHI-1 variants and a subset of chemorefractory AML patient samples showed increased sensitivity to glucocorticoids that are often used in treatment of lymphoid leukemia but not AML. Paired samples taken from AML patients before treatment and at relapse also showed acquisition of glucocorticoid sensitivity. Enhanced glucocorticoid sensitivity was only seen in AML patient samples that were negative for the FLT3 mutation (P = 0.0006). Our study shows that development of cytarabine resistance is associated with increased sensitivity to glucocorticoids in a subset of AML, suggesting a new therapeutic strategy that should be explored in a clinical trial of chemorefractory AML patients carrying wild-type FLT3.

Novel agents have increased survival of multiple myeloma (MM) patients, however high-risk and relapsed/refractory patients remain challenging to treat and their outcome is poor. To identify novel therapies and aid treatment selection for MM, we assessed the ex vivo sensitivity of 50 MM patient samples to 308 approved and investigational drugs. With the results we i) classified patients based on their ex vivo drug response profile; ii) identified and matched potential drug candidates to recurrent cytogenetic alterations; and iii) correlated ex vivo drug sensitivity to patient outcome. Based on their drug sensitivity profiles, MM patients were stratified into four distinct subgroups with varied survival outcomes. Patients with progressive disease and poor survival clustered in a drug response group exhibiting high sensitivity to signal transduction inhibitors. Del(17p) positive samples were resistant to most drugs tested with the exception of histone deacetylase and BCL2 inhibitors. Samples positive for t(4; 14) were highly sensitive to immunomodulatory drugs, proteasome inhibitors and several targeted drugs. Three patients treated based on the ex vivo results showed good response to the selected treatments. Our results demonstrate that ex vivo drug testing may potentially be applied to optimize treatment selection and achieve therapeutic benefit for relapsed/refractory MM.

The increasing coverage and sensitivity of LC-MS/MS-based proteomics have expanded its applications in systems medicine. In particular, label-free quantitation approaches are enabling biomarker discovery in terms of statistical comparison of proteomic profiles across large numbers of clinical samples. However, it still remains poorly understood how much protein markers can add novel insights compared to markers derived from mRNA transcriptomic profiling. Using paired label-free LC-MS/MS and gene expression microarray measurements from primary samples of patients with acute myeloid leukemia (AML), we demonstrate here that while the quantitative proteomic and transcriptomic profiles were highly correlated, in general, the marker panels showing statistically significant expression changes across the disease and healthy groups were profoundly different between protein and mRNA levels. In particular, the proteomic assay enabled unique links to known leukemic processes, which were missed when using the transcriptomic profiling alone, as well as identified additional links to metabolic regulators and chromatin remodelers, such as GPX1, fumarate hydratase, and SET oncogene, which have subsequently been evaluated in independent AML samples. Overall, these results highlighted the complementary and informative view obtained from the quantitative LC-MS/MS approach into the AML deregulated signaling networks.

Acute myeloid leukemia (AML) is an aggressive disease of clonal hematopoietic progenitor cells. Here, we applied ex-vivo drug sensitivity and resistance testing on AML patient cells with 362 emerging and 153 approved cancer drugs together with genomic and transcriptomic profiling to identify and tailor therapies for patients with advanced disease. Ex-vivo testing with freshly isolated patient cells revealed cancer-specific efficacies of approved drugs in 97% of the 164 patient cases, including 47% of the cases with no actionable driver mutations. We identified 142 statistically significant associations between drug responses and somatic mutations, including increased sensitivity to JAK inhibitors in patients with NPM1 mutations. Transcriptomic profiles predicted drug responses better than genomics and helped to identify additional response markers, especially beyond mutations. For example, overexpression of HOX family genes was associated with sensitivity to JAK inhibitors in patients with NPM1 mutation. In a prospective study, we translated the functional drug response and molecular profile data to the clinic and suggested tailored therapy with targeted drugs for 26 relapsed or refractory AML patients. In an observational intervention study, acting on these recommendations resulted in a temporary complete clinical remission or leukemia-free state in 39% of the cases. In summary, we conclude that ex-vivo testing of drugs on patient AML cells i) revealed clinically actionable drug efficacies in almost all AML patients, including patients with no actionable mutations, ii) predicted cases with actionable driver mutations with no pharmacological dependency on the target, and iii) enabled real-time tailoring of therapy with 39% clinical response rate in chemorefractory advanced AML. Taken together, we believe this real-time systems medicine approach could become a powerful strategy for tailoring therapies for individual patients in the future. Citation Format: Disha Malani, Ashwni Kumar, Bhagwan Yadav, Mika Kontro, Swapnil Potdar, Oscar Bruck, Säri Kytölä, Jani Saarela, Samuli Eldfors, Riikka Karjalainen, Muntasir M. Majumder, Imre Västrik, Pekka Ellonen, Matti Kankainen, Minna Suvela, Siv Knappila, Alun Parson, Aino Palva, Pirkko Mattila, Evgeny Kulesskiy, Laura Turunen, Karoliina Laamanen, Elina Lehtinen, Maria Nurmi, Katja Suomi, Astrid Muruimägi, Bjorn T. Gjertsen, Satu Mustjoki, Simon Anders, Maija Wolf, Tero Aittokallio, Krister Wennerberg, Caroline Heckman, Kimmo Porkka, Olli Kallioniemi. Precision systems medicine in acute myeloid leukemia: real-time translation of tailored therapeutic opportunities arising from ex-vivo drug sensitivity testing and molecular profiling [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2019; 2019 Mar 29-Apr 3; Atlanta, GA. Philadelphia (PA): AACR; Cancer Res 2019;79(13 Suppl):Abstract nr 458.

We present an individualized systems medicine (ISM) approach to optimize cancer drug therapies one patient at a time. ISM is based on (i) molecular profiling and ex vivo drug sensitivity and resistance testing (DSRT) of patients' cancer cells to 187 oncology drugs, (ii) clinical implementation of therapies predicted to be effective, and (iii) studying consecutive samples from the treated patients to understand the basis of resistance. Here, application of ISM to 28 samples from patients with acute myeloid leukemia (AML) uncovered five major taxonomic drug-response subtypes based on DSRT profiles, some with distinct genomic features (e.g., MLL gene fusions in subgroup IV and FLT3-ITD mutations in subgroup V). Therapy based on DSRT resulted in several clinical responses. After progression under DSRT-guided therapies, AML cells displayed significant clonal evolution and novel genomic changes potentially explaining resistance, whereas ex vivo DSRT data showed resistance to the clinically applied drugs and new vulnerabilities to previously ineffective drugs. Significance: Here, we demonstrate an ISM strategy to optimize safe and effective personalized cancer therapies for individual patients as well as to understand and predict disease evolution and the next line of therapy. This approach could facilitate systematic drug repositioning of approved targeted drugs as well as help to prioritize and de-risk emerging drugs for clinical testing. Cancer Discov; 3(12); 1416–29. ©2013 AACR. See related commentary by Hourigan and Karp, p. 1336 This article is highlighted in the In This Issue feature, p. 1317

Background The 5-year survival rate for acute myeloid leukemia (AML) remains poor with most patients succumbing to relapse or refractory disease. Recently, the BCL2 specific inhibitor venetoclax has shown promising anti-leukemia activity in high-risk AML patients. Most patients, however, ultimately develop resistance to monotherapy and novel combination treatments with venetoclax are needed for patients with no other therapy options available. In this study we identified high expression of calcium binding protein S100A8/S100A9 to be associated with venetoclax resistance and looked for drug combinations to overcome the resistance in AML patient samples overexpressing S100A8 and S100A9. Methods Gene expression was assessed by RNA sequencing of AML patient samples and validated by qPCR. Gene enrichment analysis was performed on differentially expressed genes between venetoclax highly sensitive (n=3) and resistant (n=4) samples. Sensitivity of AML patient derived mononuclear cells was assessed to 304 different small molecule inhibitors by measuring cell viability after 72 h incubation with 5 different concentrations (1-10,000 nM) using the CellTiter-Glo (CTG) assay. A drug sensitivity score (DSS) was calculated based on a modified area under the dose response curve calculation. Drug combination studies were performed using AML cell lines resistant to venetoclax and confirmed with primary patient cells (n=15). Data of the drug combination studies were analyzed with the Zero Interaction Potency (ZIP) model by considering a dose-response matrix where two drugs are tested at 8 concentrations in a serially diluted manner. Statistical dependence between gene expression and drug sensitivity data was assessed by Pearson's correlation coefficient modelling. Results Venetoclax resistant AML patient samples were found to overexpress genes related to immune responses including inflammatory related proteins S100A8 and S100A9. The expression of S100A8 and S100A9 was upregulated in a sub-group of AML patients with somatic mutations in DNA methylation genes IDH2 and TET2 and chromatin modifier ASXL1. Functional studies with AML cell lines validated high expression of the S100 proteins in cells insensitive to venetoclax (NOMO-1, SKM-1 and SHI-1) whereas sensitive cell lines (MOLM-13, Kasumi-1 and ML-2) did not express the proteins. Integrated analysis of S100A8 and S100A9 expression and ex vivo drug sensitivity data indicated positive correlation of S100 expression with sensitivity to BET inhibitor (birabresib), PI3K inhibitor (TG100-115) and MEK1/2 inhibitor (AZD8330). In contrast, sensitivity to venetoclax and the FLT3 inhibitor quizartinib negatively correlated with S100 gene expression. Subsequently, we combined positively correlating drugs with venetoclax and tested the efficacy of these combinations in AML cell lines and patient samples. From the drug combination studies we found that BET inhibitor birabresib was able to overcome resistance to venetoclax treatment. The BCL2/BET inhibitor combination was synergistic in venetoclax resistant cell lines NOMO-1 and SKM-1, which express high-levels of S100A8 and S100A9 (Figure 1A). Efficacy of the combination on primary AML patient samples correlated with the expression level of the S100 genes. Nine of 11 high expression samples were sensitive to the venetoclax/birabresib combination (Figure 1B-C), whereas no synergy was observed in 3 of 4 samples with a low level of S100 expression. Conclusions The calcium binding proteins S100A8 and S100A9 are abundant in myeloid cells and are associated with poor prognosis in AML (Edgeworth et al, J Biol Chem. 1991; Nicolas et al, Leukemia 2011). From ex vivo and in vitro analyses of AML, we found that high expression of S100A8 and S100A9 is highly correlative with resistance to the BCL2 inhibitor venetoclax. In contrast, high S100A8 and S100A9 expression correlates with sensitivity to BET inhibitor birabresib. Interestingly, our studies showed that these two drugs act synergistically in venetoclax resistant AML cell lines and AML patient samples and may be a beneficial novel combination that should be further confirmed in preclinical and clinical investigations. Disclosures Porkka: Celgene: Honoraria, Research Funding; Novartis: Honoraria, Research Funding. Heckman:Orion Pharma: Research Funding; Novartis: Research Funding; Celgene: Research Funding.

The bone marrow (BM) provides a protective microenvironment to support the survival of leukemic cells and influence their response to therapeutic agents. In acute myeloid leukemia (AML), the high rate of relapse may in part be a result of the inability of current treatment to effectively overcome the protective influence of the BM niche. To better understand the effect of the BM microenvironment on drug responses in AML, we conducted a comprehensive evaluation of 304 inhibitors, including approved and investigational agents, comparing ex vivo responses of primary AML cells in BM stroma-derived and standard culture conditions. In the stroma-based conditions, the AML patient cells exhibited significantly reduced sensitivity to 12% of the tested compounds, including topoisomerase II, B-cell chronic lymphocytic leukemia/lymphoma 2 (BCL2), and many tyrosine kinase inhibitors (TKIs). The loss of TKI sensitivity was most pronounced in patient samples harboring FLT3 or PDGFRB alterations. In contrast, the stroma-derived conditions enhanced sensitivity to Janus kinase (JAK) inhibitors. Increased cell viability and resistance to specific drug classes in the BM stroma-derived conditions was a result of activation of alternative signaling pathways mediated by factors secreted by BM stromal cells and involved a switch from BCL2 to BCLXL-dependent cell survival. Moreover, the JAK1/2 inhibitor ruxolitinib restored sensitivity to the BCL2 inhibitor venetoclax in AML patient cells ex vivo in different model systems and in vivo in an AML xenograft mouse model. These findings highlight the potential of JAK inhibitors to counteract stroma-induced resistance to BCL2 inhibitors in AML.

Strong gain-of-function mutations have not been identified in humans in the FSH receptor (FSHR), whereas such mutations are common among many other G protein-coupled receptors. In order to predict consequences of such mutations on humans, we first identified constitutively activated mutants of the mouse (m) Fshr and then expressed them under the human anti-Müllerian hormone promoter in transgenic mice or created knock-in mutation into the mouse genome. We show here that mutations of Asp580 in the mFSHR significantly increase the basal receptor activity. D580H and D580Y mutations of mFSHR bind FSH, but the activity of the former is neither ligand-dependent nor promiscuous towards LH/human choriogonadotropin stimulation. Transgenic expression of mFshrD580H in granulosa cells leads to abnormal ovarian structure and function in the form of hemorrhagic cysts, accelerated loss of small follicles, augmented granulosa cell proliferation, increased estradiol biosynthesis, and occasional luteinized unruptured follicles or teratomas. The most affected mFshrD580H females are infertile with disturbed estrous cycle and decreased gonadotropin and increased prolactin levels. Increased estradiol and prolactin apparently underlie the enhanced development of the mammary glands, adenomatous pituitary growth, and lipofuscin accumulation in the adrenal gland. The influence of the mFSHRD580Y mutation is milder, mainly causing hemorrhagic cysts in transgenic mFSHRD580Y and mFSHRD580Y -knock-in mice. The results demonstrate that gain-of-function mutations of the FSHR in mice bring about distinct and clear changes in ovarian function, informative in the search of similar mutations in humans.

Introduction Most patients with acute myeloid leukemia (AML) are still missing effective options for targeted treatments. Here, we applied individualized systems medicine (ISM) concept1 by integrating deep molecular profiles (genomics, transcriptomics) and ex vivo drug response profiles with 521 oncology drugs in 154 AML patient samples. The aim was to identify new treatment opportunities for molecular subsets of AML patients. When feasible, ISM guided treatment opportunities were applied clinically for AML patient treatment. Serial samples were available to identify molecular alterations in response to targeted drug treatment and to monitor therapeutic success or failure. We also aimed at testing the impact of bone marrow stromal cell conditioned media on drug response profiles in AML patients2. Methods Samples from bone marrow or blood of 122 AML patients and 17 healthy donors were obtained with written consent and ethical approval (239/13/03/00/2010 and 303/13/03/01/2011) from the Hematology Clinic, Comprehensive Cancer Center, Helsinki University Hospital. The ex vivo drug sensitivity and resistance testing (DSRT) assay was performed with 521 approved oncology drugs and investigational oncology compounds as described earlier1. In this study, freshly isolated mononuclear cells were randomly resuspended either in standard mononuclear cell medium (MCM, PromoCell) or in human bone marrow stroma derived conditioned medium (CM) for drug testing. DNA samples from same mononuclear cells were subjected to whole exome and transcriptome sequencing and data were analyzed as described previsously2. Hierarchical clustering and non-parametric rank correlation were performed with drugs and samples. Wilcoxon sign ranked test was applied between wild type and mutated samples to identify significant mutation-drug associations. Results Hierarchical clustering was largely independent of clinical features such as disease status or risk class. A strong drug sub-cluster with a unique response profile was composed of that of the MDM2 antagonist idasanutlin along with BCL-2 inhibitors navitoclax and venetoclax (Figure). BET inhibitors (JQ1, I-BET151, birabresib) and MEK inhibitors (trametinib, selumetinib) were positively correlated with each other suggesting an association between bromodomain mediated epigenetic deregulation and up-regulation of the MEK pathway in a subset of patients. Comparison between patient samples profiled in CM (n=77) vs MCM medium (n=77) indicated higher efficacy of MDM2 modulator idasanutlin in MCM while BET inhibitors responded more strongly in CM. Other differences observed earlier by Karjalainen et al1 between the two media types were also validated. Furthermore, 16 chemorefractory and one diagnostic stage patients were treated with the targeted drugs suggested by this ISM approach. We observed complete remission or leukemia free state in 35% (6/17) of the AML patients given tailored treatment in an observational study. The targeted drugs used for clinical translation included ruxolitinib (in n=4 patients), temsirolimus (n=5), trametinib (n=4), sunitinib (n=7), dasatinib (n=7), sorafeninb (n=4), omacetaxine (n=3) and dexamethasone (n=5). Summary This study highlights the potential of individualized systems medicine (ISM) approach in the identification of effective treatment opportunities for individual patients with AML. Identifying molecular markers for ex vivo drug responses can help to assign treatments to the patient subgroups most likely to respond in clinical trials. Figure Figure. Disclosures Heckman: Orion Pharma: Research Funding; Novartis: Research Funding; IMI2 project HARMONY: Research Funding; Pfizer: Research Funding; Celgene: Research Funding. Porkka: Bristol-Myers Squibb: Honoraria, Research Funding; Novartis: Honoraria, Research Funding; Celgene: Honoraria, Research Funding; Pfizer: Honoraria, Research Funding.

The indifferent mammalian embryonic gonad generates an ovary or testis, but the factors involved are still poorly known. The Wnt-4 signal represents one critical female determinant, since its absence leads to partial female-to-male sex reversal in mouse, but its signalling is as well implicated in the testis development. We used the Wnt-4 deficient mouse as a model to identify candidate gonadogenesis genes, and found that the Notum, Phlda2, Runx-1 and Msx1 genes are typical of the wild-type ovary and the Osr2, Dach2, Pitx2 and Tacr3 genes of the testis. Strikingly, the expression of these latter genes becomes reversed in the Wnt-4 knock-out ovary, suggesting a role in ovarian development. We identified the transcription factor Runx-1 as a Wnt-4 signalling target gene, since it is expressed in the ovary and is reduced upon Wnt-4 knock-out. Consistent with this, introduction of the Wnt-4 signal into early ovary cells ex vivo induces Runx-1 expression, while conversely Wnt-4 expression is down-regulated in the absence of Runx-1. We conclude that the Runx-1 gene can be a Wnt-4 signalling target, and that Runx-1 and Wnt-4 are mutually interdependent in their expression. The changes in gene expression due to the absence of Wnt-4 in gonads reflect the sexually dimorphic role of this signal and its complex gene network in mammalian gonad development.

We developed a systematic algorithmic solution for quantitative drug sensitivity scoring (DSS), based on continuous modeling and integration of multiple dose-response relationships in high-throughput compound testing studies. Mathematical model estimation and continuous interpolation makes the scoring approach robust against sources of technical variability and widely applicable to various experimental settings, both in cancer cell line models and primary patient-derived cells. Here, we demonstrate its improved performance over other response parameters especially in a leukemia patient case study, where differential DSS between patient and control cells enabled identification of both cancer-selective drugs and drug-sensitive patient sub-groups, as well as dynamic monitoring of the response patterns and oncogenic driver signals during cancer progression and relapse in individual patient cells ex vivo. An open-source and easily extendable implementation of the DSS calculation is made freely available to support its tailored application to translating drug sensitivity testing results into clinically actionable treatment options.

Several promising new, targeted agents are being developed for the treatment of AML. The BH3 mimetic venetoclax (ABT-199) is a specific inhibitor of BCL2, with results from a phase 2 study showing transient activity of venetoclax in relapsed/refractory AML (Konopleva et al, 2014). The bone marrow (BM) microenvironment is known to protect AML cells from drug therapy and we showed earlier that conditioned medium (CM) from BM stromal cells applied to AML patient cells conferred resistance to venetoclax, which could be reversed by the addition of the JAK1/2 inhibitor ruxolitinib (Karjalainen et al, 2015). Here, we investigated the mechanisms mediating the BM stromal cell induced resistance to venetoclax and its reversal by ruxolitinib. To identify the soluble factor(s) contributing to stroma-induced protection of BCL2 inhibition, we analyzed the cytokine content of 1) CM from the human BM stromal cell line HS-5, 2) CM from BM mesenchymal stromal cells (MSCs) isolated from AML patients, 3) supernatants from BM aspirates collected from AML patients, and 4) supernatants from BM aspirates collected from healthy donors. Although expression levels varied, the cytokines detected were similar among the different samples. In HS-5 CM, IL-6, IL-8 and MIP-3α were among the most abundant cytokines. In addition, gene expression analysis showed the receptors for these cytokines were expressed in AML patient samples. IL-6, IL-8 and MIP-3α were added individually to mononuclear cells collected from AML patients, which were then treated with venetoclax. However, none of the cytokines alone could mimic the reduced sensitivity to venetoclax conferred by the HS-5 CM suggesting that stromal cell induced cytoprotection is likely multi-factorial. Next we tested the effect of AML-derived BM MSCs on the ex vivo response of AML patient samples (n=8) to ruxolitinib or venetoclax alone or in combination in a co-culture setting. Apoptosis assays showed negligible effects of ruxolitinib at a concentration of 300 nM, while venetoclax at a dose of 100 nM induced reduction in the percentage of CD34+ AML cells. Co-treatment with venetoclax and ruxolitinib demonstrated synergistic effects in 6 out of 8 samples and significantly reduced the number of CD34+ AML cells. Mechanistic studies showed that ruxolitinib treatment inhibited the BM stromal medium-induced expression of BCL-XL mRNA on AML cells and the drugs in combination down-regulated BCL2, MCL1 and BCL-XL protein expression, which was in correlation with sensitivity to the drugs. To further evaluate the ability of the venetoclax and ruxolitinib combination to eradicate leukemic cells in vivo we used an orthotopic xenograft model of AML. NSG mice were injected with genetically engineered MOLM-13luc cells and after engraftment treated with venetoclax (25 mg/kg, i.p.), ruxolitinib (50 mg/kg BID, p.o) or both and imaged once per week for 4 weeks. At the end of the treatment period bioluminescent imaging showed significantly reduced leukemia burden in the ruxolitinib and venetoclax co-treated mice compared to controls demonstrating superior anti-tumor efficacy than either agent alone (Figure 1). In summary, our data demonstrate that the combined blockade of JAK/STAT and BCL2 pathways with ruxolitinib and ventoclax is synergistic in ex vivo co-culture models and in vivo in an AML mouse model. The addition of ruxolitinib was able to overcome intrinsic resistance to venetoclax by reducing expression of MCL1, a known escape mechanism of BCL2 inhibition. These results support further clinical investigation of this combination, particularly for relapsed/refractory AML. Disclosures Porkka: Novartis: Honoraria, Research Funding; Pfizer: Honoraria, Research Funding; Bristol-Myers Squibb: Honoraria, Research Funding. Wennerberg:Pfizer: Research Funding. Gjertsen:BerGenBio AS: Equity Ownership, Membership on an entity's Board of Directors or advisory committees; Boehringer Ingelheim: Membership on an entity's Board of Directors or advisory committees; Kinn Therapeutics AS: Equity Ownership. Heckman:Celgene: Research Funding; Pfizer: Research Funding.

Introduction Response to treatment for multiple myeloma (MM) patients is variable and often unpredictable, which may be attributed to the heterogeneous genomic landscape of the disease. However, the effect of recurrent molecular alterations on drug response is unclear. To address this, we systematically profiled 50 samples from 43 patients to assess ex vivo sensitivity to 308 anti-cancer drugs including standard of care and investigational drugs, with results correlated to genomic alterations. Our results reveal novel insights about patient stratification, therapies for high-risk (HR) patients, signaling pathway aberrations and ex-vivo-in-vivo correlation. Methods Bone marrow (BM) aspirates (n=50) were collected from MM patients (newly diagnosed n=17; relapsed/refractory n=33) and healthy individuals (n=8). CD138+ plasma cells were enriched by Ficoll separation followed by immunomagnetic bead selection. Cells were screened against 308 oncology drugs tested in a 10,000-fold concentration range. Drug sensitivity scores were calculated based on the normalized area under the dose response curve (Yadav et al, Sci Reports, 2014). MM selective responses were determined by comparing data from MM patients with those of healthy BM cells. Clustering of drug sensitivity profiles was performed using unsupervised hierarchical ward-linkage clustering with Spearman and Manhattan distance measures of drug and sample profiles. Somatic alterations were identified by exome sequencing of DNA from CD138+ cells and skin biopsies from each patient, while cytogenetics were determined by fluorescence in situ hybridization. Results Comparison of the ex vivo chemosensitive profiles of plasma cells resulted in stratification of patients into four distinct subgroups that were highly sensitive (Group I), sensitive (Group II), resistant (Group III) or highly resistant (Group IV) to the panel of drugs tested. Many of the drug responses were specific for CD138+ cells with little effect on CD138- cells from the same patient or healthy BM controls. We generated a drug activity profile for the individual drugs correlating sensitivity to recurrent alterations including mutations to KRAS, DIS3, NRAS, TP53, FAM46C, and cytogenetic alterations del(17p), t(4;14), t(14;16), t(11;14), t(14;20), +1q and -13. Cells from HR patients with del(17p) exhibited the most resistant profiles (enriched in Groups III and IV), but were sensitive to some drugs including HDAC and BCL2 inhibitors. Samples from patients with t(4;14) were primarily in Group II and very sensitive to IMiDs, proteasome inhibitors and several targeted drugs. Along with known recurrently mutated genes in myeloma, somatic mutations were identified in genes involved in several critical signaling pathways including DNA damage response, IGF1R-PI3K-AKT, MAPK, glucocorticoid receptor signaling and NF-κB signaling pathways. The predicted impact of these mutations on the activity of the pathways often corresponded to the drug response. For example, all samples bearing NF1 (DSS=21±7.9) and 67% with NRAS (DSS=15±4.35) mutations showed higher sensitivity to MEK inhibitors compared to healthy controls (DSS=5±.21). However, sensitivity was less predictable for KRAS mutants with modest response only in 47% samples (DSS=7±2.14) . One sample bearing the activating V600E mutation to BRAF showed no sensitivity to vemurafenib, which otherwise has good activity towards V600E mutated melanoma and hairy-cell leukemia. Comparison of the chemosensitive subgroups with survival showed patients in Groups I and IV had high relapse rate and poor overall survival. The ex vivo drug sensitivity results were used to decide treatment for three HR patients with results showing good ex vivo -in vivo correlation. Summary Our initial results suggest that ex vivo drug testing and molecular profiling of MM patients aids stratification. Grouping of patients based on their ex vivo chemosensitive profile proved extremely informative to predict clinical phenotype and identify responders from non-responders. While some molecular markers could be used to predict drug response, others were less predictive. Nevertheless, ex vivo drug testing identified active drugs, particularly for HR and relapsed/refractory patients, and is a powerful method to determine treatment for this group of patients. Disclosures Silvennoinen: Genzyme: Honoraria; Sanofi: Honoraria; Janssen: Research Funding; Celgene: Research Funding; Research Committee of the Kuopio University Hospital Catchment Area for State Research Funding, project 5101424, Kuopio, Finland: Research Funding; Amgen: Consultancy, Honoraria. Porkka:Bristol-Myers Squibb: Honoraria; Celgene: Honoraria; Novartis: Honoraria; Pfizer: Honoraria. Heckman:Celgene: Honoraria, Research Funding.

Introduction Multiple myeloma (MM) is an incurable malignant plasma cell disease with the highest incidence occurring at 65-70 years of age while 10% of patients are diagnosed below 55 years of age. The International Myeloma Working Group recently proposed new risk stratification standards for MM patients: high-risk (HR), standard (SR) and low-risk (LR) groups (Leukemia 2014, 28, 269−77). Although a median overall survival of LR patients is > 10 years from the diagnosis, new drugs and therapeutic innovations are urgently needed for HR patients (20%) who have a median overall survival of only two years. To identify new treatment options for MM patients, we compared ex vivo drug sensitivity data from primary CD138+ cells to standard risk stratification markers. Ex vivo responses indicated a number of investigational drugs as potential novel options for HR MM patients with links to risk markers. Methods Bone marrow aspirates were collected from newly diagnosed (n=14) and relapsed/refractory (n=21) MM patients. Cytogenetics were determined by fluorescence in situ hybridization (FISH) and the patients stratified based on the presence or absence of adverse FISH markers (t(4;14) and 17p del). Plasma cells (CD138+) were enriched from freshly isolated bone marrow samples and exome sequencing performed using DNA extracted from the CD138+ cells and matched skin biopsies. Ex vivo drug sensitivity was assessed by measuring the viability of the cells after 3-day incubation with 306 different oncology drugs in a 10,000-fold concentration range. Drug sensitivity scores were calculated based on the normalized area under the dose response curve (Scientific Reports 2014, 4, 5193) and select sensitivities determined by comparing results to healthy bone marrow cells. Based on drug sensitivities, the patients were classified in four different groups (sensitive, moderately sensitive, resistant and highly resistant). Results Of the 35 patients included in this study, 11 were classified as HR (31%) and 24 as SR/LR (69%). In the HR group 6/11 (55%) had t(4;14) and 5/11 patients (45%) had 17p13 del. In the SR/LR group common abnormalities included 13 monosomy/13q del (10/24), 1q gain (10/24) and K/NRAS mutation (11/24). Within the HR group, other co-occurring abnormalities included 1q gain (9/11), 13 monosomy/13q del (6/11), K/NRAS mutation (5/11), and TP53 mutation (2/11). Based on overall ex vivo drug sensitivity profiles of all patients, the majority of HR patients were classified as moderately sensitive (8/11; 73%) while SR/LR patients had diverse responses from sensitive to highly resistant. In the HR group, the highest select sensitivities were to BH3 mimetics and PI3K/mTOR inhibitors. While the t(4;14) is predicted to lead to upregulation and increased activity of the FGFR3, which could be targeted by FGFR inhibitors, none of the t(4;14) samples showed sensitivity to these drugs. However, with the exception of one t(4;14) sample, the rest all showed good sensitivity to dual PI3K/mTOR inhibitors, but not to rapalogs, suggesting that inhibition of PI3K and the mTORC1/2 complexes is required to inhibit t(4;14) cell growth rather than mTORC1 alone. Of the 17p del patients, 3/5 were classified as moderately sensitive, 1/5 sensitive and 1/5 highly resistant based on ex vivo drug response of CD138+ cells. All showed select sensitivity to BH3 mimetics/BCL2 inhibitors (navitoclax/ABT-263 and venetoclax/ABT-199/GDC-0199), while response to other drugs varied. Therefore, blocking cell survival signaling is likely essential for this group of HR MM patients. Conclusion By assessing the ex vivo sensitivity of primary plasma cells to a large collection of oncology drugs and comparing these data to standard risk stratification markers for MM, we have been able to identify potential new treatment options for high risk MM patients including dual PI3K/mTOR and BCL2- inhibitors. Although a larger cohort of patients is required to support the correlation between specific drug sensitivities and risk markers, these preliminary data indicate that currently used risk markers may be useful to predict the use of novel treatments. Disclosures Silvennoinen: Janssen-Cilag: Research Funding; Celgene: Research Funding; Janssen-Cilag: Honoraria; Sanofi: Honoraria; Celgene: Honoraria. Porkka:BMS: Honoraria; BMS: Research Funding; Novartis: Honoraria; Novartis: Research Funding; Pfizer: Research Funding. Heckman:Celgene: Research Funding.

Introduction New drugs have improved survival for multiple myeloma (MM) patients, however, patient outcome remains highly variable, unpredictable and often very poor. To identify novel treatments and potential biomarkers, we applied high throughput ex vivo drug sensitivity testing combined with exome and transcriptome sequencing to samples collected from newly diagnosed and relapsed MM patients. Integration of results from the different platforms indicated several oncogenic signaling pathways driving drug response and highlighted the importance of a multi-targeted approach for treatment. Methods Bone marrow (BM) aspirates (n=48) were collected from MM patients (newly diagnosed n=14; relapsed/refractory n=26) and healthy individuals (n=8). CD138+ plasma cells were enriched by Ficoll separation followed by immunomagnetic bead selection. Cells were screened against 306 oncology drugs with the drugs tested in a 10,000-fold concentration range. Drug sensitivity scores were calculated based on the normalized area under the dose response curve (Yadav et al, Sci Reports, 2014). Importantly, MM selective responses were determined by comparing data from MM patients with those of healthy BM cells. Clustering of drug sensitivity profiles was performed using unsupervised hierarchical ward-linkage clustering with Spearman and Manhattan distance measures of drug and sample profiles. Somatic mutations were identified by exome sequencing of DNA from CD138+ cells and skin biopies from each patient, while gene expression profiles were derived from RNA sequencing of CD138+ cells. Results Cluster analysis of drug response profiles segregated the samples into four MM specific groups (Figure). Group I patients (n=12) were highly sensitive to many drugs, including several signal transduction inhibitors such as those targeting PI3K-AKT, MAPK and IGF pathways, as well as HSP90 and BCL2 inhibitors plus epigenetic/chromatin modifiers such as BET and HDAC inhibitors. Group II (n=15) showed a more modest response profile and were moderately sensitive to signal transduction inhibitors and epigenetic modifiers. Group III (n=9) were largely insensitive to most drugs in the panel except for BCL2 and proteasome inhibitors, while group IV (n=3) were resistant to all drugs except BCL2 inhibitors. Many samples were selectively sensitive to navitoclax (55%), dual PI3K/mTOR inhibitors (45%) and aminopeptidase inhibitors (20%), which had little effect on healthy control or MM CD138- cells. Only 33% of the samples responded to glucocorticoids. The majority of samples including healthy BM controls were sensitive to proteasome and CDK inhibitors, suggesting low selective cytotoxicity. However, drug sensitivity profiles of healthy control and CD138- cell populations were distinct from MM CD138+ samples indicating that observed CD138+ drug responses were specific for malignant plasma cells. In addition, we observed that drugs with overlapping target profiles tended to cluster together, indicating sample responses were similar to related drugs. Diagnostic and relapse samples were spread across the different response groups. Samples with mutations to genes involved in PI3K and NF-κB signaling tended to cluster in group I, while most samples with t(4;14) fell in Group II. Samples with RAS mutations were present in all response groups and no correlation with MEK inhibitor sensitivity was observed. 17p deletion samples were also found in all response groups, however, those with additional TP53 mutation tended to have increased drug sensitivity. Summary Our results indicate that PI3K/mTOR, MAPK, IGF1R, NF-κB and cell survival (e.g. BCL2, BCLXL) signaling are important pathways mediating MM ex vivo drug response. This matched with genomic and transcriptomic data, which identified alterations of genes involved in these pathways. Although additional work is needed to correlate ex vivo drug sensitivity with in vivo treatment response, our initial results suggest the possibility that MM patients could be subjected to stratified treatment based on combined ex vivo drug testing and molecular profiling. In addition, these results highlight the multiple signaling pathways active in MM and emphasize the need for improved combination strategies for treatment. Figure: Subgrouping of MM patient samples (I-IV) based on selective drug response profiles. H/D/R denotes healthy, diagnostic and relapse, respectively. Figure:. Subgrouping of MM patient samples (I-IV) based on selective drug response profiles. H/D/R denotes healthy, diagnostic and relapse, respectively. Disclosures Silvennoinen: Research Funding of Finland Government, Research Funding from Janssen-cilag, research funding from Celgene: Research Funding; Janssen-Cilag, Sanofi, Celgene: Honoraria. Wennerberg:Pfizer: Research Funding. Kallioniemi:Medisapiens: Consultancy, Membership on an entity's Board of Directors or advisory committees. Porkka:Bristol-Myers Squibb: Honoraria, Research Funding; Novartis: Honoraria, Research Funding. Heckman:Celgene: Research Funding.

Introduction Adult acute myeloid leukemia (AML) exemplifies the challenges of modern cancer drug discovery and development in that molecularly targeted therapies are yet to be translated into clinical use. No effective second-line therapy exists once standard chemotherapy fails. While many genetic events have been linked with the onset and progression of AML, the fundamental disease mechanisms remain poorly understood. There is significant genomic and molecular heterogeneity among patients. Several targeted therapies have been investigated for improved second-line AML therapy but none has been approved for clinical use to date. It would be critically important to identify patient subgroups that would benefit from such therapies and to identify combinations of drugs that are likely to be effective. Methods To identify and optimize novel therapies for AML, we studied 28 samples from 18 AML patients with an individualized systems medicine (ISM) approach. The ISM platform includes functional profiling of AML patient cells ex vivo with drug sensitivity and resistance testing (DSRT), comprehensive molecular profiling as well as clinical background information. Data integration was done to identify disease- and patient-specific molecular vulnerabilities for translation in the clinic. The DSRT platform comprises 306 anti-cancer agents, each tested in a dose response series. We calculated differential drug sensitivity scores by comparing AML responses to those of control cells in order to distinguish cancer-specific drug effects. Next generation RNA- and exome-sequencing was used to identify fusion transcripts and mutations that link to drug sensitivities. Results Individual AML patient samples had a distinct drug sensitivity pattern, but unsupervised hierarchical clustering of the drug sensitivity profiles of the 28 AML patient samples identified 5 functional AML drug response subtypes. Each subtype was characterized by distinct combinations of sensitivities: Bcl-2 inhibitors (e.g. navitoclax; Group 1), JAK inhibitors (e.g. ruxolitinib) (Group 2) and MEK inhibitors (e.g. trametinib) (Groups 2 and 4), PI3K/mTOR inhibitors (e.g. temsirolimus; Groups 4 and 5), broad spectrum receptor tyrosine kinase inhibitors (e.g. dasatinib) (Groups 3, 4 and 5) and FLT3 inhibitors (e.g. quizartinib, sunitinib) (Group 5). Correlation of overall drug responses with genomic profiles revealed that RAS and FLT3 mutations were significantly linked with the drug response subgroups 4 and 5, respectively. Activating FLT3 mutations contributed to sensitivity to FLT3 inhibitors, as expected, but also to tyrosine kinase inhibitors not targeting FLT3, such as dasatinib. Hence, these data point to the potential synergistic combinatorial effects of FLT3 inhibitors with dasatinib for improved therapy outcome (Figure). Early clinical translational results based on compassionate use support this hypothesis. Therefore, by combinations of drugs we expect to see synergistic drug responses that can be translated into efficacious and safe therapies for relapsed AML cases in the clinic. Clinical application of DSRT results in the treatment of eight recurrent chemorefractory patients led to objective responses in three cases according to ELN criteria, whereas four of the remaining five patients had meaningful responses not meeting ELN criteria. After disease progression, AML patient cells showed ex vivo resistance to the drugs administered to the patients, as well as significant changes in clonal architecture during treatment response. Furthermore, we saw genomic alterations potentially explaining drug resistance, such as appearance of novel fusion genes. Summary The ISM approach represents an opportunity for improving therapies for cancer patients, one patient at the time. We show that the platform can be used to identify functional groups of AML linking to vulnerabilities to single targeted drugs and, importantly, unexpected drug combinations. This information can in turn be used for personalized medicine strategies and for creating hypotheses to be explored in systematic clinical trials, both for approved and investigational drugs. Disclosures: Off Label Use: Many of the compounds included in our DSRT platform are not indicated for AML therapy. Mustjoki:BMS: Honoraria, Research Funding; Novartis: Honoraria. Porkka:Novartis: Honoraria, Research Funding; BMS: Honoraria, Research Funding. Kallioniemi:Medisapiens: Membership on an entity’s Board of Directors or advisory committees; Roche: Research Funding.

Background Ex vivo drug sensitivity testing of cancer cells taken directly from patients would significantly facilitate optimization of clinical therapies. However, in the past, such testing has been performed in suboptimal conditions, where patient cells gradually stop proliferating and undergo apoptosis, with poor translation of Results. More reliable prediction of drug sensitivity is needed and recent focus has been directed towards Methods that take into account the supporting impact of the surrounding tumor microenvironment. Primary leukemia cell viability and long-term survival ex vivo can be promoted with co-culture Methods using stromal cells (McMillin et al. 2013). While high throughput (HT) drug testing enables rapid assessment of sensitivity to 100s of drugs or drug combinations, application of co-culture Methods is challenging considering the mixed readouts from multiple cell types. In this study we describe a HT platform based on stroma-conditioned medium for assessing the anti-leukemic activity of compounds against fresh and vital biobanked primary leukemia samples ex vivo. Methods Stroma-conditioned medium (CM) was collected from the HS-5 human bone marrow (BM) cell line and combined with RPMI medium for drug sensitivity testing. Mononuclear cell medium (Promocell) was used as the standard medium comparison. Sensitivity of primary leukemia or healthy cells to 306 approved and investigational drugs was measured at 5 different concentrations covering a 10,000-fold concentration range. Cell viability was measured after 72 h with the CellTiter-Glo assay and dose response curves generated for each tested drug. Drug sensitivity scores (DSS) were calculated based on the area under the dose response curve. Here, we compared comprehensive drug sensitivity ex vivo responses between stroma-conditioned medium and standard medium using mononuclear cells from 8 acute myeloid leukemia (AML) patients and 4 healthy donors. Results HS-5 CM supported fresh and biobanked primary AML cells, promoting proliferation and overall survival. Freshly isolated AML cells had a mean viability of 123% after 3 days in CM compared to 59% in the absence of CM. The viability of biobanked cells was 85% with CM vs. 20% in conventional medium. Improved ex vivo cell survival increased the therapeutic window of drug sensitivity testing and more drugs could be assessed with CM compared to conventional medium. Results from different healthy samples tested with the same type of medium were highly similar, but sensitivities differed significantly when comparing CM to standard medium Results. In contrast, drug sensitivity Results of AML cells from different patients were more diverse, reflecting the heterogeneity of the disease. However, comparison of CM and standard medium drug sensitivities of cells from individual AML patients showed modest differences that were primarily indicative of the increased proliferation of cells incubated with CM. Overall, both AML and healthy cells showed greater sensitivity to anti-mitotic drugs when incubated with CM. For example, the average DSS of vinblastine for healthy controls was 17 in CM vs. 9 in standard medium. In addition, AML cells often exhibited increased sensitivity to JAK inhibitors such as ruxolitinib when tested with CM compared to standard medium (DSS 14 vs. 9). In contrast, stress-related protein-targeting drugs (e.g. HSP90 inhibitors) and certain tyrosine kinase inhibitors (e.g. dasatinib, quizartinib) exhibited reduced efficacy when AML cells were incubated with CM compared to conventional media. This may be due to soluble factors present in CM that mimic the protection provided by the BM niche. Conclusions Our data support the concept that conditioned medium from stromal cells improves application of drug sensitivity testing to AML patient samples ex vivo. Stromal medium supports both fresh and biobanked AML cells, likely providing environmental cues present in the BM niche and necessary for AML cell growth and survival. This may lead to more reliable ex vivo assessment of the anti-leukemic activity of compounds for cells from leukemia patients. Importantly, stromal cell based conditions support the growth of vital biobanked leukemia samples and enable use of retrospective samples for a multitude of assays including HT drug testing. Disclosures: Porkka: Novartis: Consultancy, Research Funding, Speakers Bureau; BMS: Consultancy, Research Funding, Speakers Bureau. Kallioniemi:Medisapiens: Membership on an entity’s Board of Directors or advisory committees; Roche: Research Funding.

Introduction: Conventional cytotoxic chemotherapy regimens for adult acute myeloid leukemia (AML) are effective in curing less than 50% of the patients, and there is a major need for targeted drugs with better anti-cancer selectivity. Here, our aim was to i) identify potential clinically used or emerging cancer drugs by quantitative drug sensitivity and resistance testing (DSRT) of 16 AML cell lines ii) compare the cell line data with results obtained from tested 24 ex vivo AML patient specimens iii) identify genomic correlations potentially explaining drug responsiveness. Methods: The cancer pharmacopeia-wide drug collection is composed of 119 FDA approved and 90 investigational chemical compounds including cytotoxic agents and cell signaling molecule inhibitors. Each drug was tested over a 10,000-fold concentration range and that has generated quantitative five point dose-response curves. AML cells were plated in 384 well plates (where the drugs were pre-printed using an acoustic nano-dispensing technology, Labcyte®) and incubated in standard cell culture conditions. Cell viability was measured by Cell Titer Glow® luminescence assays. Analysis of dose response curves using Dotmatics® software resulted in IC50 values. Moreover, the genomic profiles of the AML cell lines were determined by microarrays and/or next-gen sequencing data for further integration with drug responses. Results: Comprehensive data analysis of 16 AML cell lines indicated that specific targeted drugs were selectively killing AML cells. The data analysis revealed relatively strong responses for MEK inhibitors in most AML cell lines (e.g. refametinib 87%, trametinib 82%, selumetinib 75%) while 21% of ex vivo AML patient samples were sensitive to these MEK inhibitors. In case of rapalog sensitivity, 80% of AML cell lines (e.g. temsirolimus 82%, everolimus 71%, sirolimus 81%) and 25% of ex vivo AML patient cases were responsive to the mTOR inhibitors. The AML cell lines carrying FLT3-ITD mutations were extremely sensitive to FLT3 inhibitors (e.g. quizartinib, lestaurtinib, tandutinib, and sorafenib) but very few responses to FLT3 inhibitors were observed in AML patients carrying an ITD mutation in the FLT3 kinase. Summary: Systematic DSRT profiling of AML cell lines illustrates drug sensitivity patterns to classify the cell lines as sensitive or resistant to specific classes of drugs. mTOR and MEK inhibitors were among the most effective inhibitors for most cell lines and also in some ex vivo patient cases suggesting that these drugs may have potential as therapeutic agents in AML. Also, bioinformatics predictions can be used to identify key synergistic combinations of tested drugs for effective AML therapy. Further integration of molecular profiles and functional responses of AML cell lines will help provide better understanding of drug efficacy based on known genetic background of the disease. Citation Format: Disha Malani, Astrid Murumägi, Tea Pemovska, Bhagwan Yadav, Evgeny Kulesskiy, Jing Tang, John Patrick Mpindi, Maija Wolf, Riikka Karjalainen, Tero Aittokallio, Caroline Heckman, Kimmo Porkka, Krister Wennerberg, Olli Kallioniemi. Identifying AML-specific key targeted drugs using high-throughput drug sensitivity and resistance testing profiles of AML cells. [abstract]. In: Proceedings of the 104th Annual Meeting of the American Association for Cancer Research; 2013 Apr 6-10; Washington, DC. Philadelphia (PA): AACR; Cancer Res 2013;73(8 Suppl):Abstract nr 5220. doi:10.1158/1538-7445.AM2013-5220

Acute myeloid leukemia (AML) is an aggressive, heterogeneous disease with few options for targeted therapy. Here, we describe a novel translational strategy termed Individualized Systems Medicine (ISM), in which we profile primary AML patient cells functionally, molecularly and clinically to identify novel treatment strategies for patients, monitor and predict disease progression and follow-up therapies, and elucidate drug response and resistance mechanisms. We developed a comprehensive ex vivo drug sensitivity and resistance testing (DSRT) strategy to screen AML patient blast cells ex vivo against a set of 202 conventional chemotherapeutic and targeted approved (n=119) and investigational (n=83) drugs. Quantitative leukemia-selective drug sensitivity scores for each drug were determined by comparing the area under the dose response curve from the patient cells to that of healthy control mononuclear cells. Analysis of consecutive samples from the same patients with DSRT and next-generation sequencing was applied to infer clonal evolution and potential mechanisms of drug response and resistance. Twenty-four samples from 16 recurrent and refractory AML patients were profiled by DSRT, sequencing and proteomic approaches. Several approved and late stage clinical investigated targeted drugs including multi-kinase inhibitors (e.g. dasatinib, sunitinib), TORC1 inhibitors (e.g. temsirolimus), JAK inhibitors (e.g. ruxolitinib) and MEK inhibitors (e.g. trametinib, selumetinib) showed selective leukemic-specific responses in 10-30% of AML samples from patients with recurrent disease. In two refractory AML cases where dasatinib, sunitinib and temsirolimus showed selective responses, the clinical administration of these compounds resulted in complete and partial remission, but was followed by resistance to the applied drugs. Re-sampling and DSRT retesting of cells confirmed diminished sensitivities to the administered drugs, but also indicated new acquired drug sensitivities. Exome and RNA sequencing of the serial samples from both patients revealed diverse subclonal populations characterized by multiple somatic mutations, which were either lost or gained during disease progression and represented drug sensitive or resistant subclones. In conclusion, our results suggest that an ISM strategy based on consecutive cancer sampling, ex vivo DSRT and analysis of clonal evolution could facilitate the rapid design of improved combinatorial therapies for AML. This strategy can also help tailor optimized therapies for patients, and prioritize introduction of new drugs for clinical testing. Citation Format: Krister Wennerberg, Tea Pemovska, Mika Kontro, Bhagwan Yadav, Evgeny Kulesskiy, Henrik Edgren, Samuli Eldfors, Riikka Karjalainen, Naga Poojitha Kota Venkata, Anna Lehto, Muntasir Mamun Majumder, Disha Malani, Astrid Murumägi, Laura Turunen, Jonathan Knowles, Tero Aittokallio, Caroline Heckman, Kimmo Porkka, Olli Kallioniemi. Comprehensive ex vivo drug sensitivity testing combined with in depth molecular profiling of AML patients cells provides individualized treatment strategies and reveals mechanisms of drug resistance. [abstract]. In: Proceedings of the 104th Annual Meeting of the American Association for Cancer Research; 2013 Apr 6-10; Washington, DC. Philadelphia (PA): AACR; Cancer Res 2013;73(8 Suppl):Abstract nr 65. doi:10.1158/1538-7445.AM2013-65

Identification of signaling pathways that are required for the growth and differentiation block of cells from adult acute myeloid leukemia (AML) is urgently required to facilitate development of novel therapies. Here, we describe an approach to functionally determine molecular drivers of AML by quantitative drug sensitivity and resistance testing (DSRT) of AML blast cells in primary culture ex vivo. The selection of drugs covered the entire cancer pharmacopeia and much of the pipeline of drugs under development in the industry: 120 FDA approved small molecular cancer drugs and 120 emerging drugs, investigational compounds and signal transduction inhibitors. All compounds were tested over a 10,000-fold concentration range to generate quantitative and reliable dose-response data. In addition, whole exome and transcriptome sequencing and phophoproteomic profiling were also performed to derive a comprehensive understanding of the molecular AML-related aberrations on an individual basis. Comparison of 17 AML patient samples and 3 healthy bone marrow control samples based on ex vivo drug responses identified several classes of approved and investigational drugs that showed selective anti-AML activities: mTOR inhibitors (e.g. temsirolomus, everolimus, sirolimus), MEK inhibitors (e.g. AS703026, GSK1120212, RDEA119, selumetinib), tyrosine kinase inhibitors (e.g. dasatinib, ponatinib, sunitinib), Bcl-2 inhibitors (navitoclax) and HSP90 inhibitors (e.g. BIIB021, NVP-AUY922, tanespimycin). In particular, the rapamycin class of mTOR inhibitors and allosteric MEK inhibitors stood out as effective and selective inhibitors in 8/17 (47%) and 9/17 (52%) of the patients, respectively. Simultaneous data from other targeted inhibitors made it possible to dissect the critical steps in signaling and therapeutic efficacy. For example, PI3K and Akt inhibitors were not effective in these patients, suggesting that the mTOR dependency is mediated through a PI3K-Akt-independent pathway. Similarly, the dependency of MEK signaling appears to be through a Ras-Raf-independent pathway since Raf inhibitors were not effective. In conclusion, the DSRT platform allows us to derive quantitative data on the ex vivo drug response profiles of AML cells from individual patients. This information could be used as a diagnostic tool to optimize personalized therapies in the future. Our data demonstrate that mTOR and MEK signaling and the associated inhibitors are the most promising leads for improved AML therapeutics. This analysis also demonstrates gaps in our current understanding of the redundancy of key cancer cell signaling pathways and proves the significant value of data from experimental drug response testing ex vivo. Citation Format: {Authors}. {Abstract title} [abstract]. In: Proceedings of the 103rd Annual Meeting of the American Association for Cancer Research; 2012 Mar 31-Apr 4; Chicago, IL. Philadelphia (PA): AACR; Cancer Res 2012;72(8 Suppl):Abstract nr 895. doi:1538-7445.AM2012-895

Despite significant advances in characterizing the molecular genetics of AML, the clonal evolution of leukemic cells and the dynamic impact of genomic changes on the development of the disease and progression to drug resistance are not well understood. Here, we applied next-generation sequencing to quantify aberrant tumor subclones carrying specific mutant alleles of key cancer genes and developed a method to extract quantitative high-resolution copy number changes across the genome using exome sequencing data from matching cancer and normal DNA. Serial bone marrow (BM) samples collected from diagnosis to relapse to post-treatment drug resistance in a patient-centric manner made it possible to trace the clonal evolution of AML and to identify variants potentially involved in drug resistance. Exome sequencing from AML blast cells and normal skin biopsies was performed as part of the Finnish Hematology Registry and Biobanking (FHRB) effort. Consecutive paired samples from different patients revealed unique genetic patterns of clonal evolution and cancer progression in each patient. In a pre-resistant sample of one AML M5 patient, we identified four closely spaced insertions in the Wilm's Tumor (WT1) suppressor gene, none of which appear on the same sequence reads. This suggests the presence of multiple distinct leukemic subclones even before treatment resistance and underscores the strong selective advantage conferred by WT1 mutations. After relapse, one of the subclones was lost, and another one significantly increased suggesting that the relapse arose from the expansion of a pre-existing resistant subclone. In this patient, recurrent clones otherwise featured similar copy number changes and the same fusion genes as the primary diagnostic sample. In another AML patient developing recurrence an opposite pattern was observed: The relapsed, drug-resistant cells displayed an enormous increase of small microdeletions compared to the diagnostic, pre-treatment sample, while almost all sequence-level alterations in potential cancer genes were the same between the two samples. This suggests that a distinct type of DNA repair deficiency may have contributed to the drug resistant clone in this patient. Conclusions: Exome sequencing from paired samples of AML cells before and after relapse makes it possible to trace the clonal evolution of the disease and study the impact of therapy both at the level of sequence alterations of key cancer genes and simultaneously at the level of copy number changes inferred from exome sequence data. This analysis has highlighted multiple genomic patterns by which resistance may evolve in vivo during cancer treatment. Refined bioinformatic analysis and interpretation of exome-seq data provides a rich resource to identify genetic biomarkers of drug response and minimal residual disease. Citation Format: {Authors}. {Abstract title} [abstract]. In: Proceedings of the 103rd Annual Meeting of the American Association for Cancer Research; 2012 Mar 31-Apr 4; Chicago, IL. Philadelphia (PA): AACR; Cancer Res 2012;72(8 Suppl):Abstract nr 5067. doi:1538-7445.AM2012-5067

In order to discover unexpected anti-cancer efficacies of approved and emerging drugs, we established a diagnostic ex vivo drug sensitivity and resistance testing (DSRT) platform covering the entire cancer pharmacopeia as well as emerging anti-cancer compounds. Here, the platform was applied to analyze bone marrow (BM) mononuclear cells from 17 adult acute myeloid leukemia (AML) patients, 3 healthy donors as well as 7 AML cell lines. The DSRT panel covered FDA-approved small molecule oncology drugs (n=120), as well as emerging, investigational and pre-clinical oncology compounds (n=120), such as kinase (e.g. RTKs, checkpoint and mitotic kinases, Raf, MEK, JAKs, mTOR, PI3K), and non-kinase inhibitors (e.g. HSP, Bcl, activin, HDAC, PARP, Hh). To generate dose-response curves, each of the drugs was applied over a 10,000-fold concentration range. In addition, the samples underwent deep molecular profiling including exome- and transcriptome sequencing, as well as phosphoproteomic analysis. DSRT provided consistent and reliable data from ex vivo samples with a high correlation between data from individual healthy BM samples (r=0.93). Bioinformatic processing of the data from AML resulted in several key observations. First, overall drug response profiles of AML blast cells were distinctly different from healthy BM controls suggesting several potential leukemia-selective effects, such as multi-kinase (dasatinib), MEK, and mTOR inhibitors. Second, the overall drug responses from AML cell lines and the patient ex vivo samples showed differences, suggesting that ex vivo testing may reveal cancer-selective effects not previously seen in established cancer cell line panels. Third, the response data from patient samples clustered many drugs consistently into the expected functional classes (such as topoisomerase II inhibitors, MEK inhibitors and rapalogs), whereas other drug classes were more dispersed (such as FLT3 inhibitors with quizartinib clustering away from all other tyrosine kinase inhibitors), suggesting secondary targets playing a key role in drug efficacy. Fourth, analysis of serial samples from patients developing clinical resistance to targeted agents showed striking agreement between the ex-vivo DSRT profiles and clinical responses. In conclusion, comprehensive DSRT platform generated powerful novel insights on AML drug response and may enable individual optimization of therapies, particularly for recurrent leukemias. DSRT will also serve as a powerful hypothesis-generator for clinical trials, particularly for emerging drugs. The ability to correlate ex vivo response profiles for hundreds of drugs in clinical samples with deep molecular profiling data will yield exciting new translational and pharmacogenomic opportunities for cancer therapy. Citation Format: {Authors}. {Abstract title} [abstract]. In: Proceedings of the 103rd Annual Meeting of the American Association for Cancer Research; 2012 Mar 31-Apr 4; Chicago, IL. Philadelphia (PA): AACR; Cancer Res 2012;72(8 Suppl):Abstract nr 3188. doi:1538-7445.AM2012-3188

Samples from recurrent, treatment-refractory cancers are rarely available, but would be valuable in understanding the molecular drivers of drug resistance. In leukemias, consecutive samples are readily available during treatment. Hence, we explored here the progression of adult acute myeloid leukemias (AML) by serial sampling and by integrating data from multiple platforms. Next-generation exome and RNA sequencing, and phosphoproteomic data were combined with comprehensive 240 cancer drug sensitivity and resistance testing (DSRT) of leukemic blasts ex-vivo before and after clinical relapse. The data were generated in an experimental diagnostic setting, with intent to improve and personalize treatment of patients with recurrent AML. A 54-year old AML-M5 patient with a FLT-3-ITD mutation and a normal karyotype was monitored by serial sampling. The patient was initially refractory to three consecutive high-dose induction treatments and had limited therapy options. AML blasts from the patient were screened with the DSRT platform. Results implied that the blast cells were 710-times more sensitive to temsirolimus and other rapamycin analogs as compared to normal BM cells, and showed a 1100-fold increased sensitivity to dasatinib. Proteomic analysis showed high phosphorylation of several signaling molecules, such as the insulin receptor and mTOR. Sequencing identified WT1 mutations and a NUP98-NSD1 fusion transcript, an infrequent event associated with poor prognosis in AML. Based on the DSRT results, the patient received compassionate off-label treatment with dasatinib, sunitinib and temsirolimus, resulting in a remarkable clinical remission, normalization of blast counts and a rapid recovery of neutrophil counts as a sign of selective elimination of the leukemic cells. The patient relapsed 4 weeks later, and at this point a new DSRT assay was performed, which showed the blast cells to be completely resistant to temsirolimus and less sensitive to dasatinib ex vivo. Consistent with this drug sensitivity profile was a genomic evolution of a distinct AML subclone with new changes, such as NF1 mutation and a microdeletion of the LEF1 gene, which were not observed in the pre-treatment sample. Taken together, we have demonstrated, how molecular profiling and functional ex vivo drug sensitivity and resistance data can be used to individually optimize patient treatment. Remission was achieved in a patient with advanced, treatment-refractory AML. Serial sampling from human AML patients coupled with molecular profiling and drug sensitivity testing may shed light on clonal progression of disease, and the molecular events underlying drug response. Citation Format: {Authors}. {Abstract title} [abstract]. In: Proceedings of the 103rd Annual Meeting of the American Association for Cancer Research; 2012 Mar 31-Apr 4; Chicago, IL. Philadelphia (PA): AACR; Cancer Res 2012;72(8 Suppl):Abstract nr 4580. doi:1538-7445.AM2012-4580

Chronic myelomonocytic leukemia (CMML) is a rare malignancy characterized by increased peripheral monocytosis and dysplasia in a single- or multilineage fashion. Gene mutations so far reported in CMML include TET2, CBL, NRAS, KRAS, RUNX1 and EZH2 but their pathogenic role and driver status in the disease remains unclear. Altered expression of the microRNA miR-125b has been implicated in the pathogenesis of many types of cancers, including myeloid leukemias and Down syndrome-associated acute myeloid leukemia (DS-AML). In addition, this miRNA has been shown to play an important role in hematopoiesis and the regulation of immune cell response. Here, integration of data from next-generation transcriptome sequencing, exome sequencing and array-CGH in a CMML patient (trisomy 21 by cytogenetics) led to the identification of a novel gene fusion event involving the nuclear receptor interacting protein NRIP1 gene and the open reading frame C21orf34 (both at 21q21 approximately 1 MB apart). The fusion was validated by capillary sequencing and found to involve two copy number transition breaks, inversion of the intervening region and the upregulation of the 3′ end of C21orf34. This intronic region harbors a cluster of three miRNAs: miR-let7c, miR-99a, and miR-125b-2. Based on genomic breakpoint analysis, the gene fusion took place just upstream of miR-125b-2. Consistent with this, only miR-125b-2 was highly expressed in the sample, and was processed to a mature miRNA. By RT-PCR, increased expression of miR-125b-2 was also observed in four other CMML patients and five CML patients when compared to healthy bone marrow controls. In contrast, five AML cases studied showed expression levels similar to or lower than that of controls. Interestingly, one AML patient with trisomy 21 had very high levels of miR-125b-2. We found the NRIP1-C21orf34 fusion only in our index patient and therefore other mechanisms of miRNA deregulation at 21q21 in CMML/CML and AML+21 will also exist. In conclusion, we describe for the first time a fusion gene involving miR-125b-2 in CMML, a previously recognized and well-studied onco-miR, which is known to impact on self-renewal of hematopoietic cell precursors. We also detected overexpression of miR-125b-2 in all CMML samples studied suggesting a key pathogenetic driver gene role for this micro-RNA. The assessment of miR-125b-2 levels could potentially be applied to the diagnosis and follow-up of patients with CMML. Citation Format: {Authors}. {Abstract title} [abstract]. In: Proceedings of the 103rd Annual Meeting of the American Association for Cancer Research; 2012 Mar 31-Apr 4; Chicago, IL. Philadelphia (PA): AACR; Cancer Res 2012;72(8 Suppl):Abstract nr 3175. doi:1538-7445.AM2012-3175

Abstract 2487 Introduction: The molecular drivers of adult AML as well as the determinants of drug response are poorly understood. While AML genomes have recently been sequenced, many cases do not harbor druggable mutations. Treatment options are particularly limited for relapsed and refractory AML. Due to the molecular heterogeneity of the disease, optimal therapy would likely consist of individualized combinations of targeted and non-targeted drugs, which poses significant challenges for the conventional paradigm of clinical drug testing. In order to better understand the molecular driver signals, identify individual variability of drug response, and to discover clinically actionable therapeutic combinations and future opportunities with emerging drugs, we established a diagnostic ex-vivo drug sensitivity and resistance testing (DSRT) platform for adult AML covering the entire cancer pharmacopeia as well as many emerging anti-cancer compounds. Methods: DSRT was implemented for primary cells from adult AML patients, focusing on relapsed and refractory cases. Fresh mononuclear cells from bone marrow aspirates (>50% blast count) were screened in a robotic high-throughput screening system using 384-well plates. The primary screening panel consisted of a comprehensive collection of FDA/EMA-approved small molecule and conventional cytotoxic drugs (n=120), as well as emerging, investigational and pre-clinical oncology compounds (currently n=90), such as major kinase (e.g. RTKs, checkpoint and mitotic kinases, Raf, MEK, JAKs, mTOR, PI3K), and non-kinase inhibitors (e.g. HSP, Bcl, activin, HDAC, PARP, Hh). The drugs are tested over a 10,000-fold concentration range resulting in a dose-response curve for each compound and with combinations of effective drugs explored in follow-up screens. The same samples also undergo deep molecular profiling including exome- and transcriptome sequencing, as well as phosphoproteomic analysis. Results: DSRT data from 11 clinical AML samples and 2 normal bone marrow controls were bioinformatically processed and resulted in several exciting observations. First, overall drug response profiles of the AML samples and the controls were distinctly different suggesting multiple leukemia-selective inhibitory effects. Second, the MEK and mTOR signaling pathways emerged as potential key molecular drivers of AML cells when analyzing targets of leukemia-specific active drugs. Third, potent new ex-vivo combinations of approved targeted drugs were uncovered, such as mTOR pathway inhibitors with dasatinib. Fourth, data from ex-vivo DSRT profiles showed excellent agreement with clinical response when serial samples were analyzed from leukemia patients developing clinical resistance to targeted agents. Summary: The rapid and comprehensive DSRT platform covering the entire cancer pharmacopeia and many emerging agents has already generated powerful insights into the molecular events underlying adult AML, with significant potential to facilitate individually optimized combinatorial therapies, particularly for recurrent leukemias. DSRT will also serve as a powerful hypothesis-generator for clinical trials, particularly for emerging drugs and drug combinations. The ability to correlate response profiles of hundreds of drugs in clinical ex vivo samples with deep molecular profiling data will yield exciting new translational and pharmacogenomic opportunities for clinical hematology. Disclosures: Mustjoki: Novartis: Honoraria; Bristol-Myers Squibb: Honoraria. Porkka:Novartis: Honoraria, Research Funding; Bristol-Myers Squibb: Honoraria, Research Funding. Kallioniemi:Abbot/Vysis: Patents & Royalties; Medisapiens: Equity Ownership, Membership on an entity's Board of Directors or advisory committees; Bayer Schering Pharma: Research Funding; Roche: Research Funding.

Abstract 288 Introduction: Recent genomic analyses of acute myeloid leukemia (AML) patients have provided new information on mutations contributing to the disease onset and progression. However, the genomic changes are often complex and highly diverse from one patient to another and often not actionable in clinical care. To rapidly identify novel patient-specific therapies, we developed a high-throughput drug sensitivity and resistance testing (DSRT) platform to experimentally validate therapeutic options for individual patients with relapsed AML. By integrating the results with exome and transcriptome sequencing plus proteomic analysis, we were able to define specific drug-sensitive subgroups of patients and explore predictive biomarkers. Methods: Ex vivo DSRT was implemented for 29 samples from 16 adult AML patients at the time of relapse and chemoresistance and from 5 healthy donors. Fresh mononuclear cells from bone marrow aspirates (>50% blast count) were screened against a comprehensive collection of cytotoxic chemotherapy agents (n=103) and targeted preclinical and clinical drugs (n=100, later 170). The drugs were tested over a 10,000-fold concentration range resulting in a dose-response curve for each compound and each leukemia sample. A leukemia-specific drug sensitivity score (sDSS) was derived from the area under each dose response curve in relation to the total area, and comparing leukemia samples with normal bone marrow results. The turnaround time for the DSRT assay was 4 days. All samples also underwent deep exome (40–100×) and transcriptome sequencing to identify somatic mutations and fusion transcripts, as well as phosphoproteomic array analysis to uncover active cell signaling pathways. Results: The drug sensitivity profiles of AML patient samples differed markedly from healthy bone marrow controls, with leukemia-specific responses mostly observed for molecularly targeted drugs. Individual AML patient samples clustered into distinct subgroups based on their chemoresponse profiles, thus suggesting that the subgroups were driven by distinct signaling pathways. Similarly, compounds clustered based on the response across the samples revealing functional groups of compounds of both expected and unexpected composition. Furthermore, subsets of patient samples stood out as highly sensitive to different compounds. Specifically, dasatinib, rapalogs, MEK inhibitors, ruxolitinib, sunitinib, sorafenib, ponatinib, foretinib and quizartinib were found to be selectively active in 5 (31%), 5 (31%), 4 (25%), 4 (25%), 3 (19%), 3 (19%), 2 (13%), 2 (13%), and 1 (6%) of the AML patients ex vivo, respectively. DSRT assays of serial samples from the same patient at different stages of leukemia progression revealed patterns of resistance to the clinically applied drugs, in conjunction with evidence of dynamic changes in the clonal genomic architecture. Emergence of vulnerabilities to novel pathway inhibitors was seen at the time of drug resistance, suggesting potential combinatorial or successive cycles of drugs to achieve remissions in an increasingly chemorefractory disease. Genomic and molecular profiling of the same patient samples not only highlighted potential biomarkers reflecting the ex vivo DSRT response patterns, but also made it possible to follow in parallel the drug sensitivities and the clonal progression of the disease in serial samples from the same patients. Summary: The comprehensive analysis of drug responses by DSRT in samples from human chemorefractory AML patients revealed a complex pattern of sensitivities to distinct inhibitors. Thus, these results suggest tremendous heterogeneity in drug response patterns and underline the relevance of individual ex vivo drug testing in selecting optimal therapies for patients (personalized medicine). Together with genomic and molecular profiling, the DSRT analysis resulted in a comprehensive view of the drug response landscape and the underlying molecular changes in relapsed AML. These data can readily be translated into the clinic via biomarker-driven stratified clinical trials. Disclosures: Mustjoki: Bristol-Myers Squibb: Honoraria, Research Funding; Novartis: Honoraria. Kallioniemi:Roche: Research Funding; Medisapiens: Membership on an entity's Board of Directors or advisory committees. Porkka:Bristol-Myers Squibb: Honoraria, Research Funding; Novartis: Honoraria, Research Funding.