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  • 1
    In: Genome Biology, Springer Science and Business Media LLC, Vol. 12, No. 1 ( 2011), p. R6-
    Type of Medium: Online Resource
    ISSN: 1465-6906
    Language: English
    Publisher: Springer Science and Business Media LLC
    Publication Date: 2011
    detail.hit.zdb_id: 2040529-7
    SSG: 12
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  • 2
    In: Cancer Research, American Association for Cancer Research (AACR), Vol. 73, No. 8_Supplement ( 2013-04-15), p. 65-65
    Abstract: 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
    Type of Medium: Online Resource
    ISSN: 0008-5472 , 1538-7445
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    Language: English
    Publisher: American Association for Cancer Research (AACR)
    Publication Date: 2013
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  • 3
    In: Cancer Research, American Association for Cancer Research (AACR), Vol. 72, No. 8_Supplement ( 2012-04-15), p. 895-895
    Abstract: 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
    Type of Medium: Online Resource
    ISSN: 0008-5472 , 1538-7445
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    Language: English
    Publisher: American Association for Cancer Research (AACR)
    Publication Date: 2012
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  • 4
    In: Blood, American Society of Hematology, Vol. 120, No. 21 ( 2012-11-16), p. 288-288
    Abstract: 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.
    Type of Medium: Online Resource
    ISSN: 0006-4971 , 1528-0020
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    Language: English
    Publisher: American Society of Hematology
    Publication Date: 2012
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  • 5
    In: Cancer Research, American Association for Cancer Research (AACR), Vol. 71, No. 8_Supplement ( 2011-04-15), p. 4836-4836
    Abstract: We describe here comprehensive multi-layered genomic, molecular, functional and drug-sensitivity profiles of cancer specimens for clinical diagnostic and therapeutic use. A clinically and histologically atypical metastatic bone tumor was studied with the intent to inform clinicians in real time, should actionable findings emerge. This represents a pilot for future individualized molecular oncology. Methods: We describe integration of the following profiling data: 1) Full genomic sequencing and bioinformatic analysis with 31x coverage of the tumor and 36x of germline DNA 2) aCGH analysis of the tumor and comparison with tumor derived primary cell line 3) Full transcriptome sequencing and microarray analysis 4) Bioinformatic analysis linking gene expression profiles from the patient's tumor with published data on 47 normal and 57 cancer types 5) Phosphoprotein analysis with antibody microarrays and MS covering most therapeutically relevant pathways 6) IHC profiles with multiple antibodies 7) Establishment and molecular representativity of an in vitro cell culture model and mouse xenograft 8) development of personalized plasma-DNA based monitoring of tumor load 9) High-throughput drug sensitivity testing of the patient-derived cell line against a panel of 1500 compounds, including most clinically actionable cancerdrugs and their combinations. Selected key results: The tumor resembled malignant fibrocytic histiocytoma, was pleiomorphic with high mitotic counts. Clinical presentation was atypical with multiple metastatic bone lesions but no primary tumor. Genome sequencing revealed 12 genomic rerrangements and 34 putative missense mutations, including an oncogenic p53 mutation. Array-CGH revealed p16 deletion, and amplification of PDGFRA, KIT and VEGFR2 at 4q, but no clear overexpression. In vitro drug sensitivity testing revealed little impact of targeted drugs and kinase inhibitors like sunitinib, but strong inhibition by eg. bortezomib, daunorubicin, taxanes and zolendronic acid, which helped clinicial treatment decisions. The bone cancer initially responded to the treatment, but later progressed in soft tissues. Conclusions: This deep individualized molecular oncology study highlights the advantages and challenges of translating molecular oncology data on individual patients. Transcriptome and protein expression of the primary tumors and drug sensitivity testing with representative in vitro cell lines may be informative even when diagnostic or therapeutically “actionable” gene mutations are not found. Citation Format: {Authors}. {Abstract title} [abstract]. In: Proceedings of the 102nd Annual Meeting of the American Association for Cancer Research; 2011 Apr 2-6; Orlando, FL. Philadelphia (PA): AACR; Cancer Res 2011;71(8 Suppl):Abstract nr 4836. doi:10.1158/1538-7445.AM2011-4836
    Type of Medium: Online Resource
    ISSN: 0008-5472 , 1538-7445
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    Language: English
    Publisher: American Association for Cancer Research (AACR)
    Publication Date: 2011
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  • 6
    In: Cancer Research, American Association for Cancer Research (AACR), Vol. 71, No. 8_Supplement ( 2011-04-15), p. 4850-4850
    Abstract: Fusion genes have recently been described in common solid tumors, revealing an important class of mutations that contribute to cancer development and progression. Next-generation sequencing technologies allow systematic characterization of cancer cell transcriptomes, including the fusion genes resulting from underlying chromosomal translocations. Using paired-end RNA-sequencing in conjunction with high-resolution chromosomal copy number analyses we characterized 24 novel and 3 previously known fusion genes in breast cancer cell lines. An improved bioinformatic approach allowed fusion gene validation with a 95% success rate by RT-PCR, Sanger sequencing and FISH. Among the identified fusions, partner genes were found to contribute both promoters (5′UTR; e.g. TATDN1-GSDMB), coding sequences (e.g. ACACA-STAC2) as well as 3′UTRs (e.g. CSE1L-ENSG00000236127). Most fusion genes (82%) were associated with copy number transitions, such as high level amplifications at e.g. 8q21, 17q12, 17q23 and 20q13, implying that fusion gene formation may contribute to the selective advantage provided by copy number amplifications. Although no prevalent single fusion gene was detected, the functional importance of the multiple fusion genes is supported by several lines of evidence. First, some of the fusion partner genes were expressed exclusively as fusion transcripts, e.g. TATDN1-GSDMB, indicating that the fusion event lead to the activation of a latent gene. Second, several fusion gene partners, including ACACA, NOTCH1 and RARA, have been previously found to be involved in oncogenic fusions in leukemias and lymphomas. Third, functional analysis using RNAi-mediated knockdown suggested a potential role for two fusion genes in controlling cancer cell proliferation. In conclusion, using RNA-sequencing together with improved bioinformatics and genomic copy number profiling, we have discovered multiple novel fusion genes in breast cancer, which may provide new insights on breast cancer, and provide therapeutic and diagnostic clues. Citation Format: {Authors}. {Abstract title} [abstract]. In: Proceedings of the 102nd Annual Meeting of the American Association for Cancer Research; 2011 Apr 2-6; Orlando, FL. Philadelphia (PA): AACR; Cancer Res 2011;71(8 Suppl):Abstract nr 4850. doi:10.1158/1538-7445.AM2011-4850
    Type of Medium: Online Resource
    ISSN: 0008-5472 , 1538-7445
    RVK:
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    Language: English
    Publisher: American Association for Cancer Research (AACR)
    Publication Date: 2011
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    detail.hit.zdb_id: 1432-1
    detail.hit.zdb_id: 410466-3
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  • 7
    In: Cancer Research, American Association for Cancer Research (AACR), Vol. 72, No. 8_Supplement ( 2012-04-15), p. 5067-5067
    Abstract: 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
    Type of Medium: Online Resource
    ISSN: 0008-5472 , 1538-7445
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    Language: English
    Publisher: American Association for Cancer Research (AACR)
    Publication Date: 2012
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  • 8
    In: Blood, American Society of Hematology, Vol. 130, No. Suppl_1 ( 2017-12-07), p. 854-854
    Abstract: 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.
    Type of Medium: Online Resource
    ISSN: 0006-4971 , 1528-0020
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    Language: English
    Publisher: American Society of Hematology
    Publication Date: 2017
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  • 9
    In: Blood, American Society of Hematology, Vol. 118, No. 21 ( 2011-11-18), p. 2487-2487
    Abstract: 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.
    Type of Medium: Online Resource
    ISSN: 0006-4971 , 1528-0020
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    Language: English
    Publisher: American Society of Hematology
    Publication Date: 2011
    detail.hit.zdb_id: 1468538-3
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  • 10
    In: Cancer Research, American Association for Cancer Research (AACR), Vol. 73, No. 8_Supplement ( 2013-04-15), p. 5220-5220
    Abstract: 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
    Type of Medium: Online Resource
    ISSN: 0008-5472 , 1538-7445
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    Language: English
    Publisher: American Association for Cancer Research (AACR)
    Publication Date: 2013
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    detail.hit.zdb_id: 1432-1
    detail.hit.zdb_id: 410466-3
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