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  • 1
    In: The Lancet, Elsevier BV, Vol. 400, No. 10349 ( 2022-07), p. 359-368
    Type of Medium: Online Resource
    ISSN: 0140-6736
    RVK:
    Language: English
    Publisher: Elsevier BV
    Publication Date: 2022
    detail.hit.zdb_id: 2067452-1
    detail.hit.zdb_id: 3306-6
    detail.hit.zdb_id: 1476593-7
    SSG: 5,21
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  • 2
    In: The Lancet, Elsevier BV, Vol. 401, No. 10387 ( 2023-05), p. 1499-1507
    Type of Medium: Online Resource
    ISSN: 0140-6736
    RVK:
    Language: English
    Publisher: Elsevier BV
    Publication Date: 2023
    detail.hit.zdb_id: 2067452-1
    detail.hit.zdb_id: 3306-6
    detail.hit.zdb_id: 1476593-7
    SSG: 5,21
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  • 3
    In: Psychopharmacology, Springer Science and Business Media LLC, Vol. 239, No. 8 ( 2022-08), p. 2457-2470
    Abstract: Compulsivity often develops during childhood and is associated with elevated glutamate levels within the frontostriatal system. This suggests that anti-glutamatergic drugs, like memantine, may be an effective treatment. Objective Our goal was to characterize the acute and chronic effect of memantine treatment on compulsive behavior and frontostriatal network structure and function in an adolescent rat model of compulsivity. Methods Juvenile Sprague–Dawley rats received repeated quinpirole, resulting in compulsive checking behavior ( n  = 32; compulsive) or saline injections ( n  = 32; control). Eight compulsive and control rats received chronic memantine treatment, and eight compulsive and control rats received saline treatment for seven consecutive days between the 10th and 12th quinpirole/saline injection. Compulsive checking behavior was assessed, and structural and functional brain connectivity was measured with diffusion MRI and resting-state fMRI before and after treatment. The other rats received an acute single memantine (compulsive: n  = 12; control: n  = 12) or saline injection (compulsive: n  = 4; control: n  = 4) during pharmacological MRI after the 12th quinpirole/saline injection. An additional group of rats received a single memantine injection after a single quinpirole injection ( n  = 8). Results Memantine treatment did not affect compulsive checking nor frontostriatal structural and functional connectivity in the quinpirole-induced adolescent rat model. While memantine activated the frontal cortex in control rats, no significant activation responses were measured after single or repeated quinpirole injections. Conclusions The lack of a memantine treatment effect in quinpirole-induced compulsive adolescent rats may be partly explained by the interaction between glutamatergic and dopaminergic receptors in the brain, which can be evaluated with functional MRI.
    Type of Medium: Online Resource
    ISSN: 0033-3158 , 1432-2072
    RVK:
    Language: English
    Publisher: Springer Science and Business Media LLC
    Publication Date: 2022
    detail.hit.zdb_id: 2066933-1
    SSG: 15,3
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  • 4
    In: European Neuropsychopharmacology, Elsevier BV, Vol. 33 ( 2020-04), p. 58-70
    Type of Medium: Online Resource
    ISSN: 0924-977X
    Language: English
    Publisher: Elsevier BV
    Publication Date: 2020
    detail.hit.zdb_id: 2019305-1
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  • 5
    In: BMC Nutrition, Springer Science and Business Media LLC, Vol. 8, No. 1 ( 2022-09-21)
    Abstract: The 2018 World Cancer Research Fund/American Institute for Cancer Research (WCRF/AICR) 3rd expert report highlights up-to-date Cancer Prevention Recommendations that may reduce burdens of many chronic diseases, including diabetes. This study examined if following a lifestyle that aligns with the recommendations – assessed via the 2018 WCRF/AICR Score – was associated with lower risk of type 2 diabetes in high-risk adults participating in the Diabetes Prevention Program Outcomes Study (DPPOS). Methods The Diabetes Prevention Program (DPP) randomized adults at high risk for diabetes to receive a lifestyle intervention (ILS), metformin (MET) or a placebo (PLB) (mean: 3.2 years), with additional follow-up in DPPOS for 11 years (mean: 15 years total). 2018 WCRF/AICR Scores included seven components: body weight, physical activity, plant-based foods, fast foods, red and processed meat, sugar-sweetened beverages, and alcohol; the optional breastfeeding component was excluded. Scores ranged 0-7 points (with greater scores indicating greater alignment with the recommendations) and were estimated at years 0, 1, 5, 6, 9, and 15 ( N =3,147). Fasting glucose and HbA1c were measured every six months and oral glucose tolerance tests were performed annually. Adjusted Cox proportional hazard ratios (HRs) and 95% confidence intervals (CIs) were used to examine the association of both Score changes from years 0-1 and time-dependent Score changes on diabetes risk through DPP and year 15. Results Scores improved within all groups over 15 years ( p 〈 0.001); ILS Scores improved more than MET or PLB Scores after 1 year ( p 〈 0.001). For every 1-unit improvement from years 0-1, there was a 31% and 15% lower diabetes risk in ILS (95% CI: 0.56-0.84) and PLB (95% CI: 0.72-0.97) through DPP, and no significant association in MET. Associations were greatest among American Indian participants, followed by non-Hispanic White and Hispanic participants. Score changes from years 0-1 and time-dependent Score changes in ILS and PLB remained associated with lower risk through year 15. Conclusions Score improvements were associated with long-term, lower diabetes risk among high-risk adults randomized to ILS and PLB, but not MET. Future research should explore impact of the Score on cancer risk. Trial registration Diabetes Prevention Program: NCT00004992 ; Diabetes Prevention Program Outcomes Study: NCT00038727
    Type of Medium: Online Resource
    ISSN: 2055-0928
    Language: English
    Publisher: Springer Science and Business Media LLC
    Publication Date: 2022
    detail.hit.zdb_id: 2809847-X
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  • 6
    In: Diabetes Care, American Diabetes Association, Vol. 44, No. 12 ( 2021-12-01), p. 2775-2782
    Abstract: To determine whether metformin or lifestyle modification can lower rates of all-cause and cause-specific mortality in the Diabetes Prevention Program and Diabetes Prevention Program Outcomes Study. RESEARCH DESIGN AND METHODS From 1996 to 1999, 3,234 adults at high risk for type 2 diabetes were randomized to an intensive lifestyle intervention, masked metformin, or placebo. Placebo and lifestyle interventions stopped in 2001, and a modified lifestyle program was offered to everyone, but unmasked study metformin continued in those originally randomized. Causes of deaths through 31 December 2018 were adjudicated by blinded reviews. All-cause and cause-specific mortality hazard ratios (HRs) were estimated from Cox proportional hazards regression models and Fine-Gray models, respectively. RESULTS Over a median of 21 years (interquartile range 20–21), 453 participants died. Cancer was the leading cause of death (n = 170), followed by cardiovascular disease (n = 131). Compared with placebo, metformin did not influence mortality from all causes (HR 0.99 [95% CI 0.79, 1.25]), cancer (HR 1.04 [95% CI 0.72, 1.52] ), or cardiovascular disease (HR 1.08 [95% CI 0.70, 1.66]). Similarly, lifestyle modification did not impact all-cause (HR 1.02 [95% CI 0.81, 1.28] ), cancer (HR 1.07 [95% CI 0.74, 1.55]), or cardiovascular disease (HR 1.18 [95% CI 0.77, 1.81] ) mortality. Analyses adjusted for diabetes status and duration, BMI, cumulative glycemic exposure, and cardiovascular risks yielded results similar to those for all-cause mortality. CONCLUSIONS Cancer was the leading cause of mortality among adults at high risk for type 2 diabetes. Although metformin and lifestyle modification prevented diabetes, neither strategy reduced all-cause, cancer, or cardiovascular mortality rates.
    Type of Medium: Online Resource
    ISSN: 0149-5992 , 1935-5548
    Language: English
    Publisher: American Diabetes Association
    Publication Date: 2021
    detail.hit.zdb_id: 1490520-6
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  • 7
    In: Blood, American Society of Hematology, Vol. 128, No. 22 ( 2016-12-02), p. 4077-4077
    Abstract: Introduction The oncogenic TCF3-PBX1 (TP; also known as E2A-PBX1) fusion gene results from a translocation between chromosomes 1 and 19 in pre-B-cell acute leukemia (pre-B-ALL). Both TCF3 and PBX1 function as transcription factors (TF), and their fusion generates a unique transcriptional landscape in t(1;19) leukemias which differs from other pre-B-ALL subtypes. Here we explored the transcriptional regulatory landscape of t(1;19)-leukemia genome-wide and sought novel targeted therapy options. Materials & Methods We modeled the oncogenicity of the fusion protein in leukemic cells by either expressing (Nalm6-TP, induced for 16 hours) or silencing (697-shTP, down to appr. 40 %) the fusion. Proliferation, apoptosis and cell cycle were studied using fluorometric reactions and flow cytometry. Patient samples (TP, n=4; other subtypes, n=18) and various cell line models were subjected to global nuclear run-on sequencing (GRO-seq), which provides a genome-wide map of nascent (primary) transcription. All transcripts that were altered after overexpression or silencing of the fusion-TF in cell models were inspected from the patient GRO-seq samples. TCF3-PBX1-regulated genomic regions were studied for enrichment of TF binding motifs and altered signaling pathways. Mature RNA levels and potential novel long non-coding RNAs were further validated by qPCR. Gene expression differences between t(1;19) and other subtypes were compared using a curated microarray data set containing 1304 pre-B-ALL samples retrieved from 15 different data sets from the Gene Expression Omnibus. ARACNE, a network inference algorithm, and GRO-seq were used to identify TFs correlating strongly with the t(1;19) subtype and to find novel drug targets. Drugs were tested in cell culture using t(1;19)-positive cell line models and patient samples either alone or in combination with known leukemia therapies. Results GRO-seq analysis allowed elucidation of the regulatory landscape downstream of the TCF3-PBX1 fusion protein. Directly regulated enhancer RNAs were matched to the cis regulated genes, and vice versa, to clarify enhancer-gene relations. As an example, correspondingly regulated enhancer regions were located for WNT16 and ANKS1B, two genes that are known targets of TCF3-PBX1, and that were found consistently upregulated in the studied sample sets. EBF3, a tumor suppressor gene, was one of the top hits in the network inference analysis and was also found consistently regulated by TCF3-PBX1. One of the identified druggable target was RORB which was directly upregulated by TCF3-PBX1. An inhibitor targeting RORB decreased viability of TCF3-PBX1-positive cell lines and cells from a t(1;19) patient. The effect was especially prominent when the inhibitor was combined with a low dose (1 nM) of vincristine, yielding a marked synergistic effect. Conclusions Our results provide the first genome-wide transcriptional regulatory landscape of TCF3-PBX1 leukemia. We also identified novel putative druggable targets and a potential inhibitor for this leukemia subtype. Disclosures Heckman: Celgene: Research Funding; Pfizer: Research Funding.
    Type of Medium: Online Resource
    ISSN: 0006-4971 , 1528-0020
    RVK:
    RVK:
    Language: English
    Publisher: American Society of Hematology
    Publication Date: 2016
    detail.hit.zdb_id: 1468538-3
    detail.hit.zdb_id: 80069-7
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  • 8
    In: Blood, American Society of Hematology, Vol. 122, No. 21 ( 2013-11-15), p. 2719-2719
    Abstract: Advanced BCR-ABL1-positive leukemias (chronic myeloid leukemia in blast crisis and Ph+ALL) remain a therapy challenge despite advances in tyrosine kinase inhibitor (TKI) therapy. Emergence of primary and secondary resistance due to gatekeeper and compound mutations within the BCR-ABL1 kinase domain is common even with the novel 2nd and 3rd generation TKIs (dasatinib, nilotinib, ponatinib). We set out to identify novel candidate drugs for advanced BCR-ABL1-positive leukemias by using an unbiased high-throughput drug testing platform and utilizing both primary patient cells and cell lines. Methods As a study material we used 3 CML cell lines representing different types of CML blast phases. In addition to commonly used K562 cells, EM-2 and MOLM-1 cell lines were tested. AML cell lines (AML-193, AP-1060, HL60ATCC, HL60TB, Kasumi-1, KG-1, ME-1, MOLM-13, MONO-MAC-6, MUTZ-2, MV4-11, NOMO-1, SH-2, SHI-1, SIG-M5, SKM-1, THP-1) were used as cell line controls. To verify the results obtained from cell lines, primary bone marrow (BM) cells were derived from 2 TKI-resistant CML BC patients. Patient 1 had developed resistance to imatinib and dasatinib due to a T315I mutation, whereas patient 2 was resistant to nilotinib, dasatinib and ponatinib due to a V299L and a compound mutation. BM cells from 4 healthy individuals were used as controls. The functional profiling of drug responses was performed with a high-throughput drug sensitivity and resistance testing (DSRT) platform comprising of 306 anti-cancer agents (FDA/EMA approved, investigational and experimental compounds). Cells were dispensed to pre-drugged 386-well plates of 5 different concentrations and incubated in a humidified incubator with 5% CO2 at 37 °C for 72 hours. Cell viability was measured by using a luminescent cell viability assay (CellTiter-Glo). From plate reads a Drug Sensitivity Score (DSS) was calculated for each drug as a measure of cytotoxicity. In addition to DSRT, Human Phospho-Kinase Array Kit (R & D systems) was used to analyze the phosphokinase profile in patient samples. Results Based on initial comparisons between CML and AML cells lines, nonspecific cytotoxic drugs, which showed high activity in all cell lines, were omitted from further analysis. The DSS scores from different CML cells lines correlated relatively closely (EM-2 vs. K-562, r=0.89; EM-2 vs. MOLM-1, r=0.82; K-562 vs. MOLM-1, r=0.78; p 〈 0.0001 for all correlations). We next ranked the DSRT data according to the DSS values with most sensitive drugs showing the highest DSS scores. The primary cells from CML BC were further normalized against the median values from healthy controls, resulting in leukemia-specific sensitivity scores (sDSS). Ranked results from the DSRT analysis are shown in the Table. As expected, the cell lines were sensitive to TKIs, with the exception of the MOLM-1, which showed only modest sensitivity. The clinically TKI-resistant patient samples were also TKI-resistant ex vivo, further validating the DSRT assay data. Drugs which showed efficacy in both the cell lines and the TKI-resistant patients included HSP90 inhibitors (NVP-AUY922, BIIB021), a NAMPT inhibitor daporinad and the protein translation inhibitor omacetaxine (homoharringtonine). Phosphokinase antibody array results from the patient samples showed increased expression of the HSP27 protein as a putative biomarker for HSP90 inhibitor response. Conclusions DSRT is a powerful assay for identifying novel candidate molecules for refractory BCR-ABL1-positive leukemias. Our results indicate that HSP90 and NAMPT inhibitors in particular warrant further clinical evaluation both by analyzing a larger set of primary patient samples and by performing proof-of-concept clinical studies. The results also pave way for designing rational combination therapy strategies. Disclosures: Mustjoki: Novartis: Consultancy, Speakers Bureau; BMS: Consultancy, Speakers Bureau. Porkka:BMS: Consultancy, Research Funding, Speakers Bureau; Novartis: Consultancy, Research Funding, Speakers Bureau.
    Type of Medium: Online Resource
    ISSN: 0006-4971 , 1528-0020
    RVK:
    RVK:
    Language: English
    Publisher: American Society of Hematology
    Publication Date: 2013
    detail.hit.zdb_id: 1468538-3
    detail.hit.zdb_id: 80069-7
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  • 9
    In: Blood, American Society of Hematology, Vol. 128, No. 22 ( 2016-12-02), p. 1924-1924
    Abstract: Introduction: Progression of chronic myeloid leukemia (CML) to blast crisis (BC) results from the acquisition of additional driver mutations, which still are poorly understood. In the tyrosine kinase inhibitor (TKI) era, BC-CML remains a challenging clinical entity with very poor prognosis and short survival. In addition, there is an unmet need for identification of progression-related genetic mutations and potentially targetable pathways. Patients and methods: Bone marrow samples from 16 patients with BC-CML (myeloid n=13, lymphoid n=2, unknown phenotype n=1) and 2 patients with accelerated phase (AP) were collected from the Helsinki University Hospital, Finland and National Cancer Institute, Cairo University, Egypt. In addition, skin biopsy samples were collected for germline variant controls. Whole exome sequencing (WES) (n=8) was done with Agilent or NimbleGen exome capture kits and deep-targeted sequencing with the NimbleGen (SeqCap EZ Design) comprehensive cancer gene panel (n=10) using an Illumina HiSeq instrument. The panel was comprised of 578 driver genes with documented association to common and rare cancers (gathered from Sanger and NCBI tests databases). All mutated genes identified by WES were included in the panel, as well as genes previously reported to be mutated in BC-CML. Results: We identified 55 mutations in 33 driver genes (average: 3 per patient, range 0-7). Of the identified 33 mutated genes, 27 were ranked ≥1 in the Gene Ranker Cancer scoring system (http://cbio.mskcc.org/tcga-generanker), where genes with a score of 1 have a documented association with cancer in a cancer gene database and higher scores indicate more frequent incidence of gene mutations in different cancers. Core-binding factor (CBF) aberrations (RUNX1 mutations and inv [16]) were the most recurrent variants (n=6 in 5 patients, 27.7% of the patients) followed by ABL1 mutations (n=4 in 4 patients, 22%) and BCOR mutations (n=4 in 3 patients, 16.7%). Other recurrent mutations included FLT3, IKZF1, and NOTCH1 mutations which all were found in 2 cases. Some of the discovered mutations have not been reported in BC-CML patients before, such as mutations to MTOR, PTPRJ, CD274 (PD-L1), IL21R, SETD2 and ZRSR2 genes. In silico analysis of the targeted genes showed that many of the affected genes interact with each other in different pathways and also with ABL1. The top pathways affected were associated with key biological functions: regulation of hematopoiesis (11 genes affected), leucocyte differentiation (9 genes) and transcriptional regulation (11 genes). Conclusion: The genomic landscape of advanced phases of CML (BC and AP) shows complex heterogeneity with a broad range of genes affected leading to dysregulation of multiple molecular pathways that have an impact on treatment responses and disease biology. Such complexity suggests that a personalized approach maybe the best treatment option for these patients. Disclosures Heckman: Celgene: Research Funding; Pfizer: Research Funding. Porkka:Novartis: Honoraria, Research Funding; Bristol-Myers Squibb: Honoraria, Research Funding; Pfizer: Honoraria, Research Funding. Mustjoki:Pfizer: Honoraria, Research Funding; Ariad: Research Funding; Novartis: Honoraria, Research Funding; Bristol-Myers Squibb: Honoraria, Research Funding.
    Type of Medium: Online Resource
    ISSN: 0006-4971 , 1528-0020
    RVK:
    RVK:
    Language: English
    Publisher: American Society of Hematology
    Publication Date: 2016
    detail.hit.zdb_id: 1468538-3
    detail.hit.zdb_id: 80069-7
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  • 10
    In: Blood, American Society of Hematology, Vol. 124, No. 21 ( 2014-12-06), p. 2203-2203
    Abstract: Introduction Transcriptome analysis by next-generation sequencing (RNA-seq) allows investigation of hematologic malignancies at unsurpassed resolution and provides promising insights into their molecular etiology. Dissecting the underlying biology depends on specific molecular signatures deregulated in the disease subtypes. In addition, gene expression profiles may potentially be used to identify driver genetic alterations and stratify patients based on molecular subtype. In this study, we generated gene expression profiles from RNA-seq data derived from patients with hematologic disease, including acute myeloid leukemia (AML), acute lymphocytic leukemia (ALL), chronic myelomonocytic leukemia (CMML), myelodysplastic syndrome (MDS), chronic myeloid leukemia (CML) and multiple myeloma (MM). Using these data, we aimed to identify disease-specific differentially expressed genes and gain better understanding of the biological functions of these genes for the development of biomarkers and therapeutic strategies in these malignancies. Methods Mononuclear cells (MNCs) were isolated from bone marrow or peripheral blood by Ficoll separation from AML (n=24), ALL (n=5), CMML (n=10), MDS (n=4), CML (n=2) and MM (n=7) patients. For MM, CD138+ cells were enriched from MNCs by immunomagnetic bead selection. Total RNA from isolated cells was depleted of ribosomal RNA and reverse transcribed for cDNA. RNA-seq libraries were prepared and sequenced on the Illumina HiSeq instrument. Reads were filtered and aligned to the hg19 human reference genome using TopHat. Second step normalization was carried out to compare gene expression values (FPKM) across samples using a normalization factor derived from 18 reference genes. A log normalized relative expression value for each gene was calculated compared to the median value across all samples. Average linkage based hierarchical clustering was performed and then visualized with TreeView. Network and pathway analyses were performed with IPA (www.ingenuity.com) and Cytoscape¨. Results Unsupervised hierarchical clustering of all samples resulted in grouping based on clinical phenotypes with a unique gene signature characteristic for each group (Figure). Analyses of different hematologic malignancies ensured credibility of the classification and highlighted differences in underlying cell signaling networks of each disease. Group I consisted of the multiple myeloma samples, where we identified 25 frequently upregulated genes. Network analyses revealed expression of the upregulated molecules is controlled by two major transcription factors, IRF4 and JUN, which represent the major hubs of the gene signature network. Group II consisted of samples with the BCR-ABL1 fusion and BCR-ABL-like ALLs. Enriched genes in this subgroup included regulators of B-cell development and maturation, plus genes involved in antigen presentation including TCL1A, CD19, CD79, HLA-DQA1, HLA-DQB1 and HLA-DRB1. Group III represented myelodysplastic and myeloproliferative neoplasms and included the MDS and CMML samples. A set of 14 genes differentially enriched in this group formed a unique pro-inflammatory signature. This included TNF-α and IL1B, which act as major regulators of smoldering inflammation driving NF-κB activity and orchestrating downstream activation of signature genes. While MM is known to have activated NF-κB signaling, the gene expression signatures of the MM and MDS/MPN groups were distinct from each other, and included activation of separate sets of cytokines and chemokines. AML samples exhibited heterogeneity in gene expression and formed two groups (IVA, IVB). A HOX gene family expression signature was observed in the FLT3-ITD positive AML samples. Summary Our results show that RNA-seq can be used to identify dominant gene expression patterns characterizing different hematologic disease samples, including those sharing a common genetic base (e.g. BCR-ABL, FLT3-ITD) or clinical phenotype (e.g. MDS/MPN, MM). Based on our results, IRF4 may be an attractive therapeutic target for MM. CMML is difficult to diagnose, however, it can be defined by a set of differentially expressed genes that could potentially be used as diagnostic markers. We also show a pivotal role for NF-κB and TNF-α signaling in the pathogenesis of MDS/MPN suggesting that drugs targeting these factors may be useful for the treatment of these diseases. Figure 1 Figure 1. Disclosures Porkka: BMS: Honoraria; BMS: Research Funding; Novartis: Honoraria; Novartis: Research Funding; Pfizer: Research Funding. Kallioniemi:Medisapiens: Consultancy, Membership on an entity's Board of Directors or advisory committees. Heckman:Celgene: Research Funding.
    Type of Medium: Online Resource
    ISSN: 0006-4971 , 1528-0020
    RVK:
    RVK:
    Language: English
    Publisher: American Society of Hematology
    Publication Date: 2014
    detail.hit.zdb_id: 1468538-3
    detail.hit.zdb_id: 80069-7
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