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Publications

2018

Vaseva AV et al. KRAS Suppression-Induced Degradation of MYC Is Antagonized by a MEK5-ERK5 Compensatory Mechanism. Cancer Cell. 2018Nov 12;34(5):807-822.e7. doi: 10.1016/j.ccell.2018.10.001.

Tanoli Z, et al. Drug Target Commons 2.0: a community platform for systematic analysis of drug-target interaction profiles. Database (Oxford). 2018Jan 1;2018:1-13. doi: 10.1093/database/bay083.

Dyczynski M, et al. Targeting autophagy by small molecule inhibitors of vacuolar protein sorting 34 (Vps34) improves the sensitivity of breast cancer cells to Sunitinib. Cancer Lett. 2018Oct 28;435:32-43. doi: 10.1016/j.canlet.2018.07.028.

Zusinaite E,et al. A Systems Approach to Study Immuno- and Neuro-Modulatory Properties of Antiviral Agents. Viruses. 2018Aug 12;10(8). pii: E423. doi: 10.3390/v10080423. Review.

Loevenich S,et al. Single Passage of Human Metapneumovirus in LLC-MK2 Cells Does Not Affect Viral Protein-Coding Capacity. Genome Announc. 2018May 24;6(21). pii: e00440-18. doi: 10.1128/genomeA.00440-18.

Ianevski A et al. Novel activities of safe-in-human broad-spectrum antiviral agents. Antiviral Res. 2018Jun;154:174-182. doi: 10.1016/j.antiviral.2018.04.016. 

Kauko O, et al. PP2A inhibition is a druggable MEK inhibitor resistance mechanism in KRAS mutant lung cancer cells. Sci Transl Med. 2018Jul 18;10(450). pii: eaaq1093. doi: 10.1126/scitranslmed.aaq1093.

Nepal C, et al. Genomic Perturbations Reveal Distinct Regulatory Networks in Intrahepatic Cholangiocarcinoma. Hepatology. 2018Sep;68(3):949-963. doi: 10.1002/hep.29764.

Lepikhova T, et al. Drug sensitivity screening and genomic characterization of 45 HPV-negative head and neck carcinoma cell lines for novel biomarkers of drug efficacy. Mol Cancer Ther. 2018Sep;17(9):2060-2071. doi: 10.1158/1535-7163.MCT-17-0733.

Andersson EI, et al. Discovery of novel drug sensitivities in T-PLL by high-throughput ex vivo drug testing and mutation profiling. Leukemia. 2018,32(3):774-787. doi: 10.1038/leu.2017.252. 

Härmä H, et al. Toward universal protein post-translational modification detection in high throughput format. Chem Commun (Camb). 2018Mar 15;54(23):2910-2913. doi: 10.1039/c7cc09575a.

He L,et al. Patient-customized Drug Combination Prediction and Testing for T-cell Prolymphocytic Leukemia Patients. Cancer Res. 2018,May 1;78(9):2407-2418. doi: 10.1158/0008-5472.CAN-17-3644. 

Tang J, et al. Drug Target Commons: A Community Effort to Build a Consensus Knowledge Base for Drug-Target Interactions. Cell Chem Biol.2018, Feb 15;25(2):224-229.e2. doi: 10.1016/j.chembiol.2017.11.009.

He L, et al. Methods for High-throughput Drug Combination Screening and Synergy Scoring. Methods in molecular biology.2018,1711, p. 351-398, ISSN: 1064-3745. doi: 10.1007/978-1-4939-7493-1_17.

Ali M, et al. Global proteomics profiling improves drug sensitivity prediction: results from a multi-omics, pan-cancer modeling approach. Bioinformatics. 2018, Apr 15;34(8):1353-1362. doi: 10.1093/bioinformatics/btx766. 

2017

Tang J et al. 2018 Drug Target Commons: A Community Effort to Build a Consensus Knowledge Base for Drug-Target Interactions. Cell Chem Biol. 25(2): 224-229.

Bulanova D et al. 2017. Antiviral properties of chemical inhibitors of cellular anti-apoptotic Bcl-2 proteins. Viruses. 9, 271.

Kuusanmäki H et al. 2017. Drug sensitivity profiling identifies potential therapies for lymphoproliferative disorders with overactive JAK/STAT3 signaling. Oncotarget. Vol. 8, (No. 57), pp: 97516-97527.

Kreutzman A et al. 2017. Dasatinib reversibly disrupts endothelial vascular integrity by increasing non-muscle myosin II contractility in a ROCK-dependent manner. Clin Cancer Res. 23(21):6697-6707.

Cichonska A et al. 2017. Computational-experimental approach to drug-target interaction mapping: A case study on kinase inhibitors. PLOS Computational Biology. 13(8): e1005678.

Ammad-ud-din M et al. 2017. Systematic identification of feature combinations for predicting drug response with Bayesian multi-view multi-task linear regression. Bioinformatics. 33, 14, p. I359-I368.

Kohonen P et al. 2017. A transcriptomics data-driven gene space accurately predicts liver cytopathology and drug-induced liver injury. Nature Communications. 8, 15932.

Jaiswal A et al. 2017. Seed-effect modeling improves the consistency of genome-wide loss-of-function screens and identifies synthetic lethal vulnerabilities in cancer cells. Genome medicine. 9, 51.

Kopra K et al. 2017. High-Throughput Dual Screening Method for Ras Activities and Inhibitors. Analytical Chemistry. 89, 8, p. 4508-4516.

Karjalainen R et al. 2017. JAK1/2 and BCL2 inhibitors synergize to counteract bone marrow stromal cell-induced protection of AML. Blood. 130(6):789-802.

Kuivanen S et al. 2017. Obatoclax, saliphenylhalamide and gemcitabine inhibit Zika virus infection in vitro and differentially affect cellular signaling, transcription and metabolism. Antiviral Research.139, 117-128.

Uusi-Rauva K et al. 2017. Induced Pluripotent Stem Cells Derived from a CLN5 Patient Manifest Phenotypic Characteristics of Neuronal Ceroid Lipofuscinoses. Int. J. Mol. Sci. 18, 955-.

Pietarinen PO et al. 2017. Differentiation status of primary chronic myeloid leukemia cells affects sensitivity to BCR-ABL1 inhibitors. Oncotarget. 8, 22606-22615.

Malani D et al. 2017. Enhanced sensitivity to glucocorticoids in cytarabine-resistant AML. Leukemia. 31, 1187–1195.

Haltia U-M et al. 2017. Systematic drug sensitivity testing reveals synergistic growth inhibition by dasatinib or mTOR inhibitors with paclitaxel in ovarian granulosa cell tumor cells. Gynecologic Oncology. 144, 3, p. 621-630.

Ojamies PN et al. 2017. Monitoring therapy responses at the leukemic subclone level by ultra-deep amplicon resequencing in acute myeloid leukemia. Leukemia. 31,1048–1058.

Fagerholm R et al. 2017. TP53-based interaction analysis identifies cis-eQTL variants for TP53BP2, FBXO28, and FAM53A that associate with survival and treatment outcome in breast cancer. Oncotarget. 8, 18381-18398.

Eldfors S et al. 2017. Idelalisib sensitivity and mechanisms of disease progression in relapsed TCF3-PBX1 acute lymphoblastic leukemia. Leukemia. 3:51-57.

Saeed K et al. 2017. Comprehensive Drug Testing of Patient-derived Conditionally Reprogrammed Cells from Castration-resistant Prostate Cancer. European Urology, 71, 319-327.

Kontro M et al. 2017. HOX gene expression predicts response to BCL-2 inhibition in acute myeloid leukemia. Leukemia. 31, 301–309.

2016

Mpindi JP et al. 2016. Consistency in drug response profiling. Nature. 540, 7631, E5-E6.

Wennerberg K 2016. Cancer Cell Drug Response Transcriptomes in 3D. Cell chemical biology. 23, 11, p. 1323-1324.

Lindholm D et al. 2016. c-Abl Inhibitors Enable Insights into the Pathophysiology and Neuroprotection in Parkinson's Disease. Frontiers in aging neuroscience. 8, 254.

Sieberts SK et al. 2016. Rheumatoid Arth Challenge. Crowdsourced assessment of common genetic contribution to predicting anti-TNF treatment response in rheumatoid arthritis. Nature Communications2016 7, 12460.

Hayes TK et al. 2016. Long-Term ERK Inhibition in KRAS-Mutant Pancreatic Cancer Is Associated with MYC Degradation and Senescence-like Growth Suppression. Cancer Cell. 29:75-89.

Gautam P et al. 2016. Identification of selective cytotoxic and synthetic lethal drug responses in triple negative breast cancer cells. Mol Cancer.15:34.

Varghese FS et al. 2016 Discovery of berberine, abamectin and ivermectin as antivirals against chikungunya and other alphaviruses. Antiviral Research. 126, 117-124.

Gu Y et al. 2016. BRCA1-deficient breast cancer cell lines are resistant to MEK inhibitors and show distinct sensitivities to 6-thioguanine. Scientific Reports, 6, 28217.

Kulesskiy E et al. 2016. Precision Cancer Medicine in the Acoustic Dispensing Era: Ex Vivo Primary Cell Drug Sensitivity Testing. Journal of Laboratory Automation, 21, p. 27-36.

2015

Mpindi, J-P. et al. 2015. Impact of normalization methods on high-throughput screening data with high hit rates and drug testing with dose-response data. Bioinformatics. 31, 23, p. 3815-3821

Pokharel, Y. R., et al. 2015. Relevance Rank Platform (RRP) for Functional Filtering of High Content Protein-Protein Interaction Data. Molecular & Cellular Proteomics. 14, 12, p. 3274-3283

Duellman, S. J.,et al. 2015. Bioluminescent, Nonlytic, Real-Time Cell Viability Assay and Use in Inhibitor Screening. Assay and Drug Development Technologies. 13, 8, p. 456-465

Yadav, B., et al. 2015. From drug response profiling to target addiction scoring in cancer cell models. Disease Models & Mechanisms. 8, 10,p. 1255-1264

Szwajda, A., etal. 2015. Systematic Mapping of Kinase Addiction Combinations in Breast Cancer Cells by Integrating Drug Sensitivity and Selectivity Profiles. Chemistry & Biology. 22, 8, p. 1144-1155

Al-Ali, H., et al. 2015. Rational Polypharmacology: Systematically Identifying and Engaging Multiple Drug Targets To Promote Axon Growth. ACS Chemical Biology. 10, 8, p. 1939-1951

Pietarinen, P. O., et al. 2015. Novel drug candidates for blast phase chronic myeloid leukemia from high-throughput drug sensitivity and resistance testing. Blood Cancer Journal. 5, p. 6

Pemovska, T., et al.  2015. Axitinib effectively inhibits BCR-ABL1(T315I) with a distinct binding conformation. Nature. 519, 7541, p. 102-225

van Adrichem, A. J., et al. 2015. Discovery of MINC1, a GTPase-Activating Protein Small Molecule Inhibitor, Targeting MgcRacGAP. Combinatorial Chemistry & High Throughput Screening. 18, 1, p. 3-17

Frankowiack, M., et al. 2015. The higher frequency of IgA deficiency among Swedish twins is not explained by HLA haplotypes. Genes and Immunity. 16, 3, p. 199-205

2014

Gu, Y., et al. 2014. Suppression of BRCA1 sensitizes cells to proteasome inhibitors. Cell Death and Disease. 5, p.12

Vidugiriene, J., et al. 2014. Bioluminescent Cell-Based NAD(P)/NAD(P)H Assays for Rapid Dinucleotide Measurement and Inhibitor Screening. Assay and Drug development Technologies. 12, p. 514-526.

Kontro, M., et al. 2014. Novel activating STAT5B mutations as putative drivers of T-cell acute lymphoblastic leukemia. Leukemia. 28, 8, p. 1738-1742.

Denisova O.V. et al. 2014. Akt inhibitor MK2206 prevents influenza pH1N1 virus infection in vitro. Antimicrobial Agents and Chemotherapy, 58, p. 3689-96.

Pietiainen V. et al. 2014. The high throughput biomedicine unit at the institute for molecular medicine Finland: high throughput screening meets precision medicine. Combinatorial Chemistry and High Throughput Screen. 17, p. 377-86.

Antila H. et al. 2014. Utilisation of in situ ELISA method for examining Trk receptor phosphorylation in cultured cells. Journal of Neuroscience Methods. 222, p. 142-6.

Stylinaou M. et al. 2014. Antifungal application of nonantifungal drugs. Antimicrobial Agents and Chemotherapy. 58, p. 1055-62.

2013

Pemovska T. et al. 2013. Individualized Systems Medicine (ISM) strategy to tailor treatments for patients with chemorefractory acute myeloid leukemia. Cancer Discovery. 3, p. 1416-29.

Nybond S. et al. 2013. Antimicrobial assay optimization and validation for HTS in 384-well format using a bioluminescent E. coli K-12 strain. European Journal of Pharmaceutical Sciences. 49, p. 782-9.

Tang J. et al. 2013. Target Inhibition Networks: Predicting Selective Combinations of Druggable Targets to Block Cancer Survival Pathways. PLOS Computational Biology. 9:e1003226.

2012

Denisova O.V. et al. 2012. Obatolax, Saliphenylhalamide, and Gemcitabine Inhibit Influenza A Virus Infection. Journal of Biological Chemistry 287, p. 35324-32.

Koskela H.L.M. et al. 2012. Somatic STAT3 Mutations in Large Granular Lymphocytic Leukemia. New England Journal of  Medicine. 366p. 1905-13.

 

Other publications:

von Schantz C, Saarela J. 2016. High Throughput siRNA Screening Using Reverse Transfection.  Methods in Molecular Biology, 1470, p. 25-37, ISBN: 978-1-4939-6335-5. Humana Press.

Timonen S. 2013. Master's thesis: Characterization of Blood Lipid Level-Associated Loci by Targeted siRNA screening, University of Helsinki, Faculty of Biological and Environmental Sciences, Department of Genetics.

Last updated: 06.02.2019 - 15:52