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  • 1
    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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  • 2
    In: Blood, American Society of Hematology, Vol. 132, No. Supplement 1 ( 2018-11-29), p. 3975-3975
    Abstract: Despite the advances in the treatment of acute lymphoblastic leukemia (ALL), a major fraction of adult patients still succumb to leukemia- or treatment-related events. In particular, the outcome of elderly ALL patients remains dismal. Our aim was to discover new or repurposed drugs for B-cell ALL in a clinically relevant ex vivo drug sensitivity testing platform. We analyzed 19 primary B-ALL samples using a well-established drug sensitivity and resistance testing platform and a drug panel including 65 drugs in five different concentrations. The main drug classes were glucocorticoids, MDM2 antagonists, and inhibitors of BCR-ABL1, VEGFR, BCL-2, BCL-XL, BET, MEK, JAK, Aurora kinase, PI3K, MTOR, IGF1R, ERK, STAT3, STAT5, HSP90 and NAMPT proteins. The samples were viably frozen bone marrow (BM) mononuclear cells collected at diagnosis. The cohort included both Philadelphia-positive (Ph+) (n=10) and Ph-negative (Ph-) (n=9) patients with a median age of 43 years (range 22-68). Cell viability (CellTiter-Glo) was measured after plating and after a three-day incubation with the drugs. A drug sensitivity score (DSS) was calculated from the viability readouts, which takes into account the area under the dose response curve, measuring both drug efficacy and potency. DSS values 〉 10 are considered effective and 〉 20 highly effective. As an overall view of drug sensitivity, a heatmap and dendrograms from DSS values are shown in Figure 1A. As expected, most patients were sensitive to glucocorticoids and tyrosine kinase inhibitors (TKIs) showed efficacy in Ph+ ALL. In addition, two Ph-negative patients were sensitive to TKIs, suggesting a Philadelphia-like disease. Drugs that showed pan-ALL efficacy included BCL-2 family inhibitors, idasanutlin (MDM2 inhibitor), luminespib (HSP90 inhibitor), daporinad (NMPRT inhibitor) and plicamycin (antineoplastic antibiotic). For the other drugs, only individual patients showed sensitivity, in line with the diverse molecular background of ALL. Strikingly, 17/19 (89%) of patients in our cohort were highly sensitive (DSS 〉 20) to navitoclax (a BCL-2, BCL-XL and BCL-W inhibitor), whereas the BCL-2-specific inhibitor venetoclax was effective only in a distinct subset of patients (Figure 1B). 6/19 (32%) of patients were highly sensitive (DSS 〉 20) to venetoclax and represented all risk classes based on age, white blood cell counts and karyotype, but interestingly, all were Ph-negative. Overall, response to venetoclax correlated with response to navitoclax (Spearman, r=0.85; P 〈 0.0001). To examine differential gene expression of anti-apoptotic proteins between Ph+ and Ph- patients, we analyzed microarray gene expression data from ArrayExpress public database (www.ebi.ac.uk/arrayexpress, E-MTAB-5035). The analyzed cohort included 96 Ph- and 41 Ph+ adult B-ALL patients. Ph-negative samples were characterized with higher BCL-2 expression, whereas Ph-positive samples showed higher BCL-W expression and a trend to higher BCL-XL expression (Figure 1C). Thus, lack of venetoclax efficacy ex vivo in Ph-positive ALL indicated dependence on BCL-W and BCL-XL, as also reflected in the gene expression analyses. Inhibitors of BCL-2, such as navitoclax and venetoclax, potently induce apoptosis in a variety of cancer cells. Both inhibitors showed promising efficacy in our B-ALL samples. Dose-limiting thrombocytopenia has limited the use of navitoclax in solid tumors. However, in our assay navitoclax showed more uniform potency, particularly in Ph+ samples suggesting a rational combination with tyrosine kinase inhibitors. Similar to conventional cytotoxic agents used in ALL, a therapeutic window may exist for safe use of navitoclax in acute leukemia. In conclusion, targeting the multidomain anti-apoptotic proteins (BCL-2, BCL-XL, BCL-W, MCL-1) and TP53 with MDM2, possibly in combination, is a promising strategy for improving outcome of adult B-ALL. Figure 1. Figure 1. Disclosures Hohtari: Incyte: Research Funding. Heckman:Novartis: Research Funding; Celgene: Research Funding; Orion Pharma: Research Funding. Wennerberg:Novartis: Research Funding. Mustjoki:Ariad: Research Funding; Pfizer: Honoraria, Research Funding; Celgene: Honoraria; Novartis: Honoraria, Research Funding; Bristol-Myers Squibb: Honoraria, Research Funding. Porkka:Celgene: 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: 2018
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  • 3
    In: Science, American Association for the Advancement of Science (AAAS), Vol. 374, No. 6570 ( 2021-11-19), p. 995-999
    Abstract: Delhi, the national capital of India, experienced multiple severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) outbreaks in 2020 and reached population seropositivity of 〉 50% by 2021. During April 2021, the city became overwhelmed by COVID-19 cases and fatalities, as a new variant, B.1.617.2 (Delta), replaced B.1.1.7 (Alpha). A Bayesian model explains the growth advantage of Delta through a combination of increased transmissibility and reduced sensitivity to immune responses generated against earlier variants (median estimates: 1.5-fold greater transmissibility and 20% reduction in sensitivity). Seropositivity of an employee and family cohort increased from 42% to 87.5% between March and July 2021, with 27% reinfections, as judged by increased antibody concentration after a previous decline. The likely high transmissibility and partial evasion of immunity by the Delta variant contributed to an overwhelming surge in Delhi.
    Type of Medium: Online Resource
    ISSN: 0036-8075 , 1095-9203
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    Language: English
    Publisher: American Association for the Advancement of Science (AAAS)
    Publication Date: 2021
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  • 4
    In: Cancer Research, American Association for Cancer Research (AACR), Vol. 78, No. 13_Supplement ( 2018-07-01), p. 3883-3883
    Abstract: Introduction: Ex vivo drug sensitivity studies of samples derived from acute myeloid leukemia (AML) patients have been shown to be predictive of in vivo response. These findings are based on a limited number of well-characterized agents for which in vivo patient response data and ex vivo drug sensitivity data—on that same patient—are available. To show the feasibility of scaling such ex vivo studies to large drug screens, we characterized the reproducibility of expression-based models of drug response across two independent data sets—one generated at the Oregon Health and Science University (OHSU) and the second at the Institute for Molecular Medicine Finland (FIMM). Methods: We harmonized two large-scale AML ex vivo studies screened for drug response and profiled transcriptomically—OHSU (303 AML patient samples and 160 drugs) and FIMM (48 AML samples and 480 drugs). The two panels have 94 drugs in common. Log-logistic curves were fit to the dose-response data and area under the dose-response curves (AUCs) were calculated. Predictive modeling using Ridge regression or an integrative Bayesian approach was performed for each drug AUC independently using 202 highly-variable and/or cancer-associated genes as features. Results: For each of the 94 drugs in common between the two data sets, we trained a Ridge regression model on the OHSU data set, used the model to predict response in the FIMM data set, and calculated the Pearson correlation between the predicted and observed FIMM responses. 41 of the 94 drug models had a positive and statistically significant correlation [false discovery rate (FDR) & lt; 20%; mean ρ = 0.43; 95% CI = 0.29 – 0.77]. Drugs corresponding to the top decile of these significant models (mean ρ = 0.54; 95% CI = 0.48 – 0.77) clustered into four primary classes: MEK inhibitors (PD184352, Selumetinib, and Trametinib), EGFR/VEGFR inhibitors (Cabozantinib, Erlotinib, Foretinib, and Sorafenib), and singletons Venetoclax and Sirolimus. To confirm these results, we applied a second modeling approach—an integrative Bayesian machine learning method—that allows systematic combination of both data sets. Training and evaluation of this approach using 10-fold cross validation yielded 82 positive and statistically significant correlations (FDR & lt; 20%; mean ρ = 0.35; 95% CI = 0.13 – 0.58). Five of nine drugs (Cabozantinib, Selumetinib, Sirolimus, Sorafenib, and Trametinib) corresponding to the top decile of these significant models (mean ρ = 0.54; 95% CI = 0.49 – 0.60) overlapped with drugs from the top decile of Ridge results (one-sided Fisher p = 2.5 x 10-4) Conclusions: Our results using independent data sets and two statistical approaches suggest that certain drugs (including MEK and EGFR/VEGFR inhibitors) are amenable to expression-based predictive modeling in AML. Future work will focus on inferring individual biomarkers of response. Citation Format: Brian S. White, Suleiman A. Khan, Muhammad Ammad-ud-din, Swapnil Potdar, Mike J. Mason, Cristina E. Tognon, Brian J. Druker, Caroline A. Heckman, Olli P. Kallioniemi, Stephen E. Kurtz, Kimmo Porkka, Jeffrey W. Tyner, Tero Aittokallio, Krister Wennerberg, Justin Guinney. Gene expression predicts ex vivo drug sensitivity in acute myeloid leukemia [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2018; 2018 Apr 14-18; Chicago, IL. Philadelphia (PA): AACR; Cancer Res 2018;78(13 Suppl):Abstract nr 3883.
    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: 2018
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  • 5
    In: Cancer Research, American Association for Cancer Research (AACR), Vol. 78, No. 13_Supplement ( 2018-07-01), p. 3899-3899
    Abstract: Acute myeloid leukemia (AML) is a heterogeneous disease characterized by multiple molecular subtypes and lack of effective targeted therapies. Here, we performed extensive molecular profiling and ex vivo drug testing with 515 approved and emerging cancer drugs on 164 AML patient samples. The aim was to i) assign individualized treatment options to advanced AML patients in real time, ii) explore drug response patterns across the molecular subtypes of AML and iii) identify opportunities to repurpose existing and emerging cancer drugs. Bone marrow samples (n=164) from 129 consecutive AML patients and 17 healthy donors were studied from the Helsinki University Hospital and the Haukeland University Hospital, Bergen. Mononuclear cells were resuspended either in mononuclear cell medium (MCM) or stroma conditioned medium (CM) and tested for drug sensitivity and resistance as previously described (PMID: 24056683) and studied by exome and transcriptome sequencing. The study protocol allowed us to return data to the clinician for consideration of novel treatment options. For the meta-analysis of associations between drug responses and molecular and clinical parameters, Wilcoxon signed ranked test and logistic regression were applied. Clustering of all patient samples based on ex vivo drug response patterns in both media types identified 7 distinct functional groups of AML. For example, a subgroup of samples was highly resistant to chemotherapeutics and all targeted drugs except BCL-2 inhibitors. The differences in drug responses in the two media types highlighted the importance of assay conditions for ex vivo drug testing. Strong clustering of several drugs in the same drug classes was often observed as well as clustering across different classes, for example between BET (JQ1, I-BET151, birabresib) and MEK (trametinib, cobimetinib) inhibitors. About 24 percent of the FLT3 negative AML patients manifested strong ex vivo sensitivity to glucocorticoids, highlighting a potential drug repositioning opportunity in this subset of AML patients. Overall, we identified 320 significant associations between drugs and mutated driver genes including association between NPM1 mutation and sensitivity to JAK inhibitors. Altogether, targeted treatment opportunities were clinically tested in 25 occasions in chemorefractory AML patients. The tailored clinical therapy led to transient complete remission or leukemia free state in 36% (9/25) of these cases. In conclusion, we discovered and clinically implemented individualized therapeutic options for AML patients, which resulted in a 36% clinical responses in a non-randomized proof-of-concept study. The associations identified between ex-vivo drug response and driver mutations provided novel drug repositioning opportunities in specific molecular subtypes. Citation Format: Disha Malani, Ashwini Kumar, Bhagwan Yadav, Mika Kontro, Swapnil Potdar, Oscar Brück, Sari Kytölä, Jani Saarela, Samuli Eldfors, Poojitha Ojamies, Karjalainen Riikka, Muntasir Mamun Majumder, Imre Västrik, Pekka Ellonen, Matti Kankainen, Minna Suvela, Siv Knappila, Alun Parson, Aino Palva, Pirkko Mattila, Evgeny Kulesskiy1, Laura Turunen, Karoliina Laamanen, Elina Lehtinen, Piia Mikkonen, Maria Nurmi, Sanna Timonen, Astrid Murumägi, Bjorn Tore Gjersten, Satu Mustjoki, Tero Aittokallio, Krister Wennerberg, Simon Anders, Maija Wolf, Caroline Heckman, Kimmo Porkka, Olli Kallioniemi. Discovery and clinical implementation of individualized therapies in acute myeloid leukemia based on ex vivo drug sensitivity testing and multi-omics profiling [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2018; 2018 Apr 14-18; Chicago, IL. Philadelphia (PA): AACR; Cancer Res 2018;78(13 Suppl):Abstract nr 3899.
    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: 2018
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  • 6
    In: SSRN Electronic Journal, Elsevier BV
    Type of Medium: Online Resource
    ISSN: 1556-5068
    Language: English
    Publisher: Elsevier BV
    Publication Date: 2020
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  • 7
    In: Oral Surgery, Oral Medicine, Oral Pathology and Oral Radiology, Elsevier BV, Vol. 128, No. 1 ( 2019-07), p. e48-
    Type of Medium: Online Resource
    ISSN: 2212-4403
    Language: English
    Publisher: Elsevier BV
    Publication Date: 2019
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  • 8
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    American Association for Cancer Research (AACR) ; 2018
    In:  Cancer Research Vol. 78, No. 13_Supplement ( 2018-07-01), p. 5029-5029
    In: Cancer Research, American Association for Cancer Research (AACR), Vol. 78, No. 13_Supplement ( 2018-07-01), p. 5029-5029
    Abstract: We have set up a precision medicine strategy for solid tumors to i) understand biological heterogeneity and driver signaling pathways in cancer, ii) identify new drug opportunities, iii) develop biomarkers for drug responses, and iv) eventually tailor effective treatments for individual patients. Fresh cancer tissue is obtained directly from clinics and processed to provide patient -derived cells (PDCs). PDCs and original tumor tissues are characterized using genetic profiling and image-based phenotyping, phenomics. Systematic drug sensitivity and resistance testing (DSRT) is carried out on the representative PDC models. The PDCs are plated in 384-well plates and treated with oncological compounds, each in five concentrations in 384-well plates. The cell viability and toxicity are measured as drug responses using plate readers. Alternatively, drug-treated cells are immunostained and subjected to automated high-content imaging and image analysis. Central to the success of this approach is to grow and test the patient derived cells in ex vivo conditions mimicking the tumor microenvironment. To this aim, we have developed 3D drug profiling for PDC spheroids from ovarian and renal cancers. For the 3D drug profiling, cells were cultivated either in Matrigel or in cellulose-based hydrogel, GrowDex, which has earlier been shown to support 3D growth of cell lines and stem cells. The pipetting robot Biomek FXp (Beckman Coulter) was utilized for transfer of matrices and cells to 384-well plates, and acoustic dispenser Echo 550 (Labcyte) for delivery of tailored drug library of 52 drugs to the spheroids. The drug sensitivities of cancer cell spheroids were scored using cell viability measurement as well as high-content confocal imaging. Our results with primary cells and cell lines suggest that both Matrigel and cellulose-based hydrogel are applicable in the 384-well plate drug profiling assay, and PDC spheroids are formed in both conditions. When the drug responses of ovarian cancer PDCs grown in different 2D and 3D conditions were systematically compared, we observed significant differences in sensitivity to several drugs. Here, we describe the individual drug effects in all conditions, such as some chemotherapeutics being less effective in 3D. As a conclusion, the comparison of results from 2D and 3D drug profiling increases our understanding of mechanisms of drugs, and may aid to select the most representative drugs for the patient. Citation Format: Piia Mikkonen, Laura Turunen, Lauri Paasonen, Swapnil Potdar, Lassi Paavolainen, Astrid Murumägi, Olli Kallioniemi, Vilja M. Pietiäinen. Precision cancer medicine based on 3D drug profiling of patient-derived cancer cell spheroid models [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2018; 2018 Apr 14-18; Chicago, IL. Philadelphia (PA): AACR; Cancer Res 2018;78(13 Suppl):Abstract nr 5029.
    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: 2018
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  • 9
    In: Cancer Research, American Association for Cancer Research (AACR), Vol. 79, No. 13_Supplement ( 2019-07-01), p. 458-458
    Abstract: 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.
    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: 2019
    detail.hit.zdb_id: 2036785-5
    detail.hit.zdb_id: 1432-1
    detail.hit.zdb_id: 410466-3
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  • 10
    In: Molecular Cancer Therapeutics, American Association for Cancer Research (AACR), Vol. 18, No. 10 ( 2019-10-01), p. 1863-1874
    Abstract: Most non–small cell lung cancers (NSCLC) contain nontargetable mutations, including KRAS, TP53, or STK11/LKB1 alterations. By coupling ex vivo drug sensitivity profiling with in vivo drug response studies, we aimed to identify drug vulnerabilities for these NSCLC subtypes. Primary adenosquamous carcinoma (ASC) or adenocarcinoma (AC) cultures were established from KrasG12D/+;Lkb1fl/fl (KL) tumors or AC cultures from KrasG12D/+;p53fl/fl (KP) tumors. Although p53-null cells readily propagated as conventional cultures, Lkb1-null cells required conditional reprograming for establishment. Drug response profiling revealed short-term response to MEK inhibition, yet long-term clonogenic assays demonstrated resistance, associated with sustained or adaptive activation of receptor tyrosine kinases (RTK): activation of ERBBs in KL cultures, or FGFR in AC cultures. Furthermore, pan-ERBB inhibition reduced the clonogenicity of KL cultures, which was exacerbated by combinatorial MEK inhibition, whereas combinatorial MEK and FGFR inhibition suppressed clonogenicity of AC cultures. Importantly, in vivo studies confirmed KL-selective sensitivity to pan-ERBB inhibition, which correlated with high ERBB ligand expression and activation of ERBB receptors, implying that ERBB network activity may serve as a predictive biomarker of drug response. Interestingly, in human NSCLCs, phosphorylation of EGFR or ERBB3 was frequently detected in ASCs and squamous cell carcinomas. We conclude that analysis of in situ ERBB signaling networks in conjunction with ex vivo drug response profiling and biochemical dissection of adaptive RTK activities may serve as a valid diagnostic approach to identify tumors sensitive to ERBB network inhibition.
    Type of Medium: Online Resource
    ISSN: 1535-7163 , 1538-8514
    Language: English
    Publisher: American Association for Cancer Research (AACR)
    Publication Date: 2019
    detail.hit.zdb_id: 2062135-8
    SSG: 12
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