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Turanli, B., Grotli, M., Boren, J., Nielsen, J., Uhlén, M., Arga, K. Y. & Mardinoglu, A. (2018). Drug Repositioning for Effective Prostate Cancer Treatment. Frontiers in Physiology, 9, Article ID 500.
Open this publication in new window or tab >>Drug Repositioning for Effective Prostate Cancer Treatment
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2018 (English)In: Frontiers in Physiology, ISSN 1664-042X, E-ISSN 1664-042X, Vol. 9, article id 500Article, review/survey (Refereed) Published
Abstract [en]

Drug repositioning has gained attention from both academia and pharmaceutical companies as an auxiliary process to conventional drug discovery. Chemotherapeutic agents have notorious adverse effects that drastically reduce the life quality of cancer patients so drug repositioning is a promising strategy to identify non-cancer drugs which have anti-cancer activity as well as tolerable adverse effects for human health. There are various strategies for discovery and validation of repurposed drugs. In this review, 25 repurposed drug candidates are presented as result of different strategies, 15 of which are already under clinical investigation for treatment of prostate cancer (PCa). To date, zoledronic acid is the only repurposed, clinically used, and approved non-cancer drug for PCa. Anti-cancer activities of existing drugs presented in this review cover diverse and also known mechanisms such as inhibition of mTOR and VEGFR2 signaling, inhibition of PI3K/Akt signaling, COX and selective COX-2 inhibition, NF-kappa B inhibition, Wnt/beta - Catenin pathway inhibition, DNMT1 inhibition, and GSK-3 beta inhibition. In addition to monotherapy option, combination therapy with current anti-cancer drugs may also increase drug efficacy and reduce adverse effects. Thus, drug repositioning may become a key approach for drug discovery in terms of time- and cost-efficiency comparing to conventional drug discovery and development process.

Place, publisher, year, edition, pages
Frontiers Media S.A., 2018
Keywords
prostate cancer, drug repositioning, non-cancer therapeutics, repurposing, approved drugs
National Category
Physiology
Identifiers
urn:nbn:se:kth:diva-229015 (URN)10.3389/fphys.2018.00500 (DOI)000432407100001 ()2-s2.0-85047004631 (Scopus ID)
Funder
Science for Life Laboratory - a national resource center for high-throughput molecular bioscienceKnut and Alice Wallenberg Foundation
Note

QC 20180531

Available from: 2018-05-31 Created: 2018-05-31 Last updated: 2018-05-31Bibliographically approved
Zieba, A., Ponten, F., Uhlén, M. & Landegren, U. (2018). In situ protein detection with enhanced specificity using DNA-conjugated antibodies and proximity ligation. Modern Pathology, 31(2), 253-263
Open this publication in new window or tab >>In situ protein detection with enhanced specificity using DNA-conjugated antibodies and proximity ligation
2018 (English)In: Modern Pathology, ISSN 0893-3952, E-ISSN 1530-0285, Vol. 31, no 2, p. 253-263Article in journal (Refereed) Published
Abstract [en]

Antibodies are important tools in anatomical pathology and research, but the quality of in situ protein detection by immunohistochemistry greatly depends on the choice of antibodies and the abundance of the targeted proteins. Many antibodies used in scientific research do not meet requirements for specificity and sensitivity. Accordingly, methods that improve antibody performance and produce quantitative data can greatly advance both scientific investigations and clinical diagnostics based on protein expression and in situ localization. We demonstrate here protocols for antibody labeling that allow specific protein detection in tissues via bright-field in situ proximity ligation assays, where each protein molecule must be recognized by two antibodies. We further demonstrate that single polyclonal antibodies or purified serum preparations can be used for these dual recognition assays. The requirement for protein recognition by pairs of antibody conjugates can significantly improve specificity of protein detection over single-binder assays.

Place, publisher, year, edition, pages
Nature Publishing Group, 2018
Keywords
antibody conjugate, APEX 1 protein, calvasculin, DNA conjugated antibody, immunoglobulin G antibody, polyclonal antibody, protein, protein A, protein G, rabbit antiserum, reagent, trefoil factor 1, unclassified drug, animal tissue, antibody affinity, antibody labeling, antibody specificity, Article, assay, click chemistry, controlled study, DNA strand, genetic transcription, immunohistochemistry, in situ proximity ligation assay, limit of detection, mRNA expression level, nonhuman, priority journal, protein analysis, protein expression, protein expression level, protein purification, tissue microarray, tissue section
National Category
Biological Sciences
Identifiers
urn:nbn:se:kth:diva-227448 (URN)10.1038/modpathol.2017.102 (DOI)000424761400003 ()2-s2.0-85041805855 (Scopus ID)
Note

Export Date: 9 May 2018; Article; CODEN: MODPE; Correspondence Address: Landegren, U.; Department of Immunology, Genetics and Pathology, Science for Life Laboratory, BMC, Uppsala University, Husargatan 3, Sweden; email: Ulf.Landegren@igp.uu.se; Funding details: VINNOVA; Funding details: 222635; Funding details: 241481; Funding details: NCI, National Cancer Institute; Funding details: #2008:0143, Knut och Alice Wallenbergs Stiftelse; Funding details: FP5, Fifth Framework Programme; Funding details: FP/2007– 2013, FP7, Seventh Framework Programme; Funding details: ERC, European Research Council; Funding details: TRC, The Research Council; Funding details: 294409, ERC, European Research Council; Funding details: IngaBritt och Arne Lundbergs Forskningsstiftelse; Funding details: Uppsala Universitet; Funding text: This work was supported by the Knut and Alice Wallenberg Foundation (#2008:0143), the European Community's 7th Framework Program (FP7/2007–2013) under grant agreement n° 222635 (AffinityProteome) 241481 (Affinomics), The Swedish Research Council, Swedish Governmental Agency for Innovation Systems, IngaBritt and Arne Lundberg Foundation, the European Research Council under the European Union's Seventh Framework Programme (FP/2007– 2013) / ERC Grant Agreement n. 294409 (ProteinSeq), and Uppsala University. UL holds stock in Olink, having rights to the in situ proximity ligation assay technology. We would also like to thank Tara Hiltke at the National Cancer Institute for providing mAbs for in situ proximity ligation assay experiments. QC 20180528

Available from: 2018-05-28 Created: 2018-05-28 Last updated: 2018-05-28Bibliographically approved
Sjöstedt, E., Sivertsson, Å., Norradin, F. H., Katona, B., Näsström, Å., Vuu, J., . . . Lindskog, C. (2018). Integration of Transcriptomics and Antibody-Based Proteomics for Exploration of Proteins Expressed in Specialized Tissues. Journal of Proteome Research
Open this publication in new window or tab >>Integration of Transcriptomics and Antibody-Based Proteomics for Exploration of Proteins Expressed in Specialized Tissues
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2018 (English)In: Journal of Proteome Research, ISSN 1535-3893, E-ISSN 1535-3907Article in journal (Refereed) Epub ahead of print
Abstract [en]

A large portion of human proteins are referred to as missing proteins, defined as protein-coding genes that lack experimental data on the protein level due to factors such as temporal expression, expression in tissues that are difficult to sample, or they actually do not encode functional proteins. In the present investigation, an integrated omics approach was used for identification and exploration of missing proteins. Transcriptomics data from three different sourcesthe Human Protein Atlas (HPA), the GTEx consortium, and the FANTOM5 consortiumwere used as a starting point to identify genes selectively expressed in specialized tissues. Complementing the analysis with profiling on more specific tissues based on immunohistochemistry allowed for further exploration of cell-type-specific expression patterns. More detailed tissue profiling was performed for >300 genes on complementing tissues. The analysis identified tissue-specific expression of nine proteins previously listed as missing proteins (POU4F1, FRMD1, ARHGEF33, GABRG1, KRTAP2-1, BHLHE22, SPRR4, AVPR1B, and DCLK3), as well as numerous proteins with evidence of existence on the protein level that previously lacked information on spatial resolution and cell-type- specific expression pattern. We here present a comprehensive strategy for identification of missing proteins by combining transcriptomics with antibody-based proteomics. The analyzed proteins provide interesting targets for organ-specific research in health and disease.

Keywords
missing proteins, transcriptomics, proteomics, protein localization, immunohistochemistry, antibodies, tissue profiling
National Category
Medical Biotechnology (with a focus on Cell Biology (including Stem Cell Biology), Molecular Biology, Microbiology, Biochemistry or Biopharmacy) Biological Sciences
Research subject
Biotechnology
Identifiers
urn:nbn:se:kth:diva-236474 (URN)10.1021/acs.jproteome.8b00406 (DOI)
Note

QC 20181018

Available from: 2018-10-17 Created: 2018-10-17 Last updated: 2018-10-18Bibliographically approved
Bidkhori, G., Benfeitas, R., Elmas, E., Kararoudi, M. N., Arif, M., Uhlén, M., . . . Mardinoglu, A. (2018). Metabolic Network-Based Identification and Prioritization o f Anticancer Targets Based on Expression Data in Hepatocellular Carcinoma. Frontiers in Physiology, 9, Article ID 916.
Open this publication in new window or tab >>Metabolic Network-Based Identification and Prioritization o f Anticancer Targets Based on Expression Data in Hepatocellular Carcinoma
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2018 (English)In: Frontiers in Physiology, ISSN 1664-042X, E-ISSN 1664-042X, Vol. 9, article id 916Article in journal (Refereed) Published
Abstract [en]

Hepatocellular carcinoma (HCC) is a deadly form of liver cancer with high mortality worldwide. Unfortunately, the large heterogeneity of this disease makes it difficult to develop effective treatment strategies. Cellular network analyses have been employed to study heterogeneity in cancer, and to identify potential therapeutic targets. However, the existing approaches do not consider metabolic growth requirements, i.e., biological network functionality, to rank candidate targets while preventing toxicity to non-cancerous tissues. Here, we developed an algorithm to overcome these issues based on integration of gene expression data, genome-scale metabolic models, network controllability, and dispensability, as well as toxicity analysis. This method thus predicts and ranks potential anticancer non-toxic controlling metabolite and gene targets. Our algorithm encompasses both objective-driven and-independent tasks, and uses network topology to finally rank the predicted therapeutic targets. We employed this algorithm to the analysis of transcriptomic data for 50 HCC patients with both cancerous and non-cancerous samples. We identified several potential targets that would prevent cell growth, including 74 anticancer metabolites, and 3 gene targets (PRKACA, PGS1, and CRLS1). The predicted anticancer metabolites showed good agreement with existing FDA-approved cancer drugs, and the 3 genes were experimentally validated by performing experiments in HepG2 and Hep3B liver cancer cell lines. Our observations indicate that our novel approach successfully identifies therapeutic targets for effective treatment of cancer. This approach may also be applied to any cancer type that has tumor and non-tumor gene or protein expression data.

Place, publisher, year, edition, pages
Frontiers Media S.A., 2018
Keywords
hepatocellular carcinoma, genome-scale metabolic model, network analysis, biological networks, cancer, gene expression, protein expression, systems biology and network biology
National Category
Physiology
Identifiers
urn:nbn:se:kth:diva-232768 (URN)10.3389/fphys.2018.00916 (DOI)000438974200001 ()2-s2.0-850501209582-s2.0-85050120958 (Scopus ID)
Funder
Knut and Alice Wallenberg FoundationScience for Life Laboratory - a national resource center for high-throughput molecular bioscience
Note

QC 20180807

Available from: 2018-08-06 Created: 2018-08-06 Last updated: 2018-08-06Bibliographically approved
Lee, C.-Y., Wang, D., Wilhelm, M., Zolg, D. P., Schmidt, T., Schnatbaum, K., . . . Kuster, B. (2018). Mining the Human Tissue Proteome for Protein Citrullination. Molecular & Cellular Proteomics, 17(7), 1378-1391
Open this publication in new window or tab >>Mining the Human Tissue Proteome for Protein Citrullination
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2018 (English)In: Molecular & Cellular Proteomics, ISSN 1535-9476, E-ISSN 1535-9484, Vol. 17, no 7, p. 1378-1391Article in journal (Refereed) Published
Abstract [en]

Citrullination is a posttranslational modification of arginine catalyzed by five peptidylarginine deiminases (PADs) in humans. The loss of a positive charge may cause structural or functional alterations, and while the modification has been linked to several diseases, including rheumatoid arthritis (RA) and cancer, its physiological or pathophysiological roles remain largely unclear. In part, this is owing to limitations in available methodology to robustly enrich, detect, and localize the modification. As a result, only a few citrullination sites have been identified on human proteins with high confidence. In this study, we mined data from mass-spectrometry-based deep proteomic profiling of 30 human tissues to identify citrullination sites on endogenous proteins. Database searching of similar to 70 million tandem mass spectra yielded similar to 13,000 candidate spectra, which were further triaged by spectrum quality metrics and the detection of the specific neutral loss of isocyanic acid from citrullinated peptides to reduce false positives. Because citrullination is easily confused with deamidation, we synthetized similar to 2,200 citrullinated and 1,300 deamidated peptides to build a library of reference spectra. This led to the validation of 375 citrullination sites on 209 human proteins. Further analysis showed that >80% of the identified modifications sites were new, and for 56% of the proteins, citrullination was detected for the first time. Sequence motif analysis revealed a strong preference for Asp and Gly, residues around the citrullination site. Interestingly, while the modification was detected in 26 human tissues with the highest levels found in the brain and lung, citrullination levels did not correlate well with protein expression of the PAD enzymes. Even though the current work represents the largest survey of protein citrullination to date, the modification was mostly detected on high abundant proteins, arguing that the development of specific enrichment methods would be required in order to study the full extent of cellular protein citrullination.

Place, publisher, year, edition, pages
AMER SOC BIOCHEMISTRY MOLECULAR BIOLOGY INC, 2018
Keywords
Post-translational modifications, Tissues, Data evaluation, Omics, Tandem Mass Spectrometry, citrullination, human proteome, peptidylarginine deiminase, synthetic peptides
National Category
Biochemistry and Molecular Biology
Identifiers
urn:nbn:se:kth:diva-232406 (URN)10.1074/mcp.RA118.000696 (DOI)000437410300010 ()29610271 (PubMedID)2-s2.0-85049241062 (Scopus ID)
Funder
Science for Life Laboratory - a national resource center for high-throughput molecular bioscience
Note

QC 20170726

Available from: 2018-07-26 Created: 2018-07-26 Last updated: 2018-07-26Bibliographically approved
Persson, M., Zandian, A., Wingard, L., Nilsson, H., Sjostedt, E., Johansson, D., . . . Nilsson, P. (2018). Searching for Novel Autoantibodies with Clinical Relevance in Psychiatric Disorders. Paper presented at 6th Biennial Conference of the Schizophrenia-International-Research-Society (SIRS), APR 04-08, 2018, Florence, Italy. Schizophrenia Bulletin, 44, S120-S121
Open this publication in new window or tab >>Searching for Novel Autoantibodies with Clinical Relevance in Psychiatric Disorders
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2018 (English)In: Schizophrenia Bulletin, ISSN 0586-7614, E-ISSN 1745-1701, Vol. 44, p. S120-S121Article in journal, Meeting abstract (Other academic) Published
Place, publisher, year, edition, pages
Oxford University Press, 2018
National Category
Biochemistry and Molecular Biology
Identifiers
urn:nbn:se:kth:diva-226780 (URN)000429541800296 ()
Conference
6th Biennial Conference of the Schizophrenia-International-Research-Society (SIRS), APR 04-08, 2018, Florence, Italy
Funder
EU, European Research Council, 670821
Note

QC 20180522

Available from: 2018-05-22 Created: 2018-05-22 Last updated: 2018-05-22Bibliographically approved
Cengic, I., Uhlén, M. & Hudson, E. P. (2018). Surface Display of Small Affinity Proteins on Synechocystis sp Strain PCC 6803 Mediated by Fusion to the Major Type IV Pilin PilA1. Journal of Bacteriology, 200(16), Article ID e00270-18.
Open this publication in new window or tab >>Surface Display of Small Affinity Proteins on Synechocystis sp Strain PCC 6803 Mediated by Fusion to the Major Type IV Pilin PilA1
2018 (English)In: Journal of Bacteriology, ISSN 0021-9193, E-ISSN 1098-5530, Vol. 200, no 16, article id e00270-18Article in journal (Refereed) Published
Abstract [en]

Functional surface display of small affinity proteins, namely, affibodies (6.5 kDa), was evaluated for the model cyanobacterium Synechocystis sp. strain PCC 6803 through anchoring to native surface structures. These structures included confirmed or putative subunits of the type IV pili, the S-layer protein, and the heterologous Escherichia coli autotransporter antigen 43 system. The most stable display system was determined to be through C-terminal fusion to PilA1, the major type IV pilus subunit in Synechocystis, in a strain unable to retract these pili (Delta pilT1). Type IV pilus synthesis was upheld, albeit reduced, when fusion proteins were incorporated. However, pilus-mediated functions, such as motility and transformational competency, were negatively affected. Display of affibodies on Synechocystis and the complementary anti-idiotypic affibodies on E. coli or Staphylococcus carnosus was able to mediate interspecies cell-cell binding by affibody complex formation. The same strategy, however, was not able to drive cell-cell binding and aggregation of Synechocystis-only mixtures. Successful affibody tagging of the putative minor pilin PilA4 showed that it locates to the type IV pili in Synechocystis and that its extracellular availability depends on PilA1. In addition, affibody tagging of the S-layer protein indicated that the domains responsible for the anchoring and secretion of this protein are located at the N and C termini, respectively. This study can serve as a basis for future surface display of proteins on Synechocystis for biotechnological applications. IMPORTANCE Cyanobacteria are gaining interest for their potential as autotrophic cell factories. Development of efficient surface display strategies could improve their suitability for large-scale applications by providing options for designed microbial consortia, cell immobilization, and biomass harvesting. Here, surface display of small affinity proteins was realized by fusing them to the major subunit of the native type IV pili in Synechocystis sp. strain PCC 6803. The display of complementary affinity proteins allowed specific cell-cell binding between Synechocystis and Escherichia coli or Staphylococcus carnosus. Additionally, successful tagging of the putative pilin PilA4 helped determine its localization to the type IV pili. Analogous tagging of the S-layer protein shed light on the regions involved in its secretion and surface anchoring.

Place, publisher, year, edition, pages
American Society for Microbiology, 2018
National Category
Other Industrial Biotechnology
Identifiers
urn:nbn:se:kth:diva-232872 (URN)10.1128/JB.00270-18 (DOI)000439777600014 ()29844032 (PubMedID)2-s2.0-85050469301 (Scopus ID)
Note

QC 20180810

Available from: 2018-08-10 Created: 2018-08-10 Last updated: 2018-08-10Bibliographically approved
Mardinoglu, A., Boren, J., Smith, U., Uhlén, M. & Nielsen, J. (2018). Systems biology in hepatology: approaches and applications. Nature Reviews. Gastroenterology & Hepatology, 15(6), 365-377
Open this publication in new window or tab >>Systems biology in hepatology: approaches and applications
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2018 (English)In: Nature Reviews. Gastroenterology & Hepatology, ISSN 1759-5045, E-ISSN 1759-5053, Vol. 15, no 6, p. 365-377Article, review/survey (Refereed) Published
Abstract [en]

Detailed insights into the biological functions of the liver and an understanding of its crosstalk with other human tissues and the gut microbiota can be used to develop novel strategies for the prevention and treatment of liver-associated diseases, including fatty liver disease, cirrhosis, hepatocellular carcinoma and type 2 diabetes mellitus. Biological network models, including metabolic, transcriptional regulatory, protein-protein interaction, signalling and co-expression networks, can provide a scaffold for studying the biological pathways operating in the liver in connection with disease development in a systematic manner. Here, we review studies in which biological network models were used to integrate multiomics data to advance our understanding of the pathophysiological responses of complex liver diseases. We also discuss how this mechanistic approach can contribute to the discovery of potential biomarkers and novel drug targets, which might lead to the design of targeted and improved treatment strategies. Finally, we present a roadmap for the successful integration of models of the liver and other human tissues with the gut microbiota to simulate whole-body metabolic functions in health and disease.

Place, publisher, year, edition, pages
Nature Publishing Group, 2018
National Category
Gastroenterology and Hepatology
Identifiers
urn:nbn:se:kth:diva-230482 (URN)10.1038/s41575-018-0007-8 (DOI)000433166800010 ()29686404 (PubMedID)2-s2.0-85045834478 (Scopus ID)
Funder
Knut and Alice Wallenberg FoundationScience for Life Laboratory - a national resource center for high-throughput molecular bioscience
Note

QC 20180613

Available from: 2018-06-13 Created: 2018-06-13 Last updated: 2018-06-13Bibliographically approved
Mardinoglu, A., Boren, J., Smith, U., Uhlén, M. & Nielsen, J. (2018). Systems biology in hepatology: approaches and applications. Nature Reviews. Gastroenterology & Hepatology, 15(6), 365-377
Open this publication in new window or tab >>Systems biology in hepatology: approaches and applications
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2018 (English)In: Nature Reviews. Gastroenterology & Hepatology, ISSN 1759-5045, E-ISSN 1759-5053, Vol. 15, no 6, p. 365-377Article, review/survey (Refereed) Published
Abstract [en]

Detailed insights into the biological functions of the liver and an understanding of its crosstalk with other human tissues and the gut microbiota can be used to develop novel strategies for the prevention and treatment of liver-associated diseases, including fatty liver disease, cirrhosis, hepatocellular carcinoma and type 2 diabetes mellitus. Biological network models, including metabolic, transcriptional regulatory, protein-protein interaction, signalling and co-expression networks, can provide a scaffold for studying the biological pathways operating in the liver in connection with disease development in a systematic manner. Here, we review studies in which biological network models were used to integrate multiomics data to advance our understanding of the pathophysiological responses of complex liver diseases. We also discuss how this mechanistic approach can contribute to the discovery of potential biomarkers and novel drug targets, which might lead to the design of targeted and improved treatment strategies. Finally, we present a roadmap for the successful integration of models of the liver and other human tissues with the gut microbiota to simulate whole-body metabolic functions in health and disease.

Place, publisher, year, edition, pages
NATURE PUBLISHING GROUP, 2018
National Category
Bioinformatics and Systems Biology
Identifiers
urn:nbn:se:kth:diva-230414 (URN)10.1038/s41575-018-0007-8 (DOI)000433166800010 ()29686404 (PubMedID)2-s2.0-85045834478 (Scopus ID)
Funder
Science for Life Laboratory - a national resource center for high-throughput molecular bioscience
Note

QC 20180619

Available from: 2018-06-19 Created: 2018-06-19 Last updated: 2018-06-20Bibliographically approved
Azimi, A., Caramuta, S., Seashore-Ludlow, B., Boström, J., Robinson, J. L., Edfors, F., . . . Maddalo, G. (2018). Targeting CDK2 overcomes melanoma resistance against BRAF and Hsp90 inhibitors. Molecular Systems Biology, 14(3), Article ID e7858.
Open this publication in new window or tab >>Targeting CDK2 overcomes melanoma resistance against BRAF and Hsp90 inhibitors
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2018 (English)In: Molecular Systems Biology, ISSN 1744-4292, E-ISSN 1744-4292, Vol. 14, no 3, article id e7858Article in journal (Refereed) Published
Abstract [en]

Novel therapies are undergoing clinical trials, for example, the Hsp90 inhibitor, XL888, in combination with BRAF inhibitors for the treatment of therapy-resistant melanomas. Unfortunately, our data show that this combination elicits a heterogeneous response in a panel of melanoma cell lines including PDX-derived models. We sought to understand the mechanisms underlying the differential responses and suggest a patient stratification strategy. Thermal proteome profiling (TPP) identified the protein targets of XL888 in a pair of sensitive and unresponsive cell lines. Unbiased proteomics and phosphoproteomics analyses identified CDK2 as a driver of resistance to both BRAF and Hsp90 inhibitors and its expression is regulated by the transcription factor MITF upon XL888 treatment. The CDK2 inhibitor, dinaciclib, attenuated resistance to both classes of inhibitors and combinations thereof. Notably, we found that MITF expression correlates with CDK2 upregulation in patients; thus, dinaciclib would warrant consideration for treatment of patients unresponsive to BRAF-MEK and/or Hsp90 inhibitors and/or harboring MITF amplification/overexpression. 

Place, publisher, year, edition, pages
Blackwell Publishing Ltd, 2018
Keywords
CDK2, Hsp90 and BRAF inhibitors, melanoma, MITF, proteomics
National Category
Medical Biotechnology
Identifiers
urn:nbn:se:kth:diva-227407 (URN)10.15252/msb.20177858 (DOI)000429006500002 ()2-s2.0-85044744573 (Scopus ID)
Note

Export Date: 9 May 2018; Article; Correspondence Address: Maddalo, G.; Science for Life Laboratory, School of Biotechnology, KTH Royal Institute of TechnologySweden; email: gianluca.maddalo@scilifelab.se; Funding details: IHC, Idaho Humanities Council; Funding details: 154202, Cancerfonden; Funding details: 5310-7132, O. E. och Edla Johanssons Vetenskapliga Stiftelse; Funding details: MTA, Mount Allison University; Funding text: We acknowledge Prof. Sonia Lain and Prof. David Lane and their groups for technical support and for granting us permission to access their Orbitrap Fusion. The cell line pairs M026.X1.CL and M026R.X1.CL, and M029.X1.CL and M029.R.X1.CL have been used according to the Material Transfer Agreement (MTA) for academic institutions V01 13 and V08 16, respectively. GM has been awarded grants from: O. E. och Edla Johanssons foundation (5310-7132); Swedish Cancer Society (Radiumhemmets; 154202); and Lars Hiertas Minne. The authors acknowledge the entire staff of the Protein Atlas Project for the IHC images. We acknowledge Prof. Janne Lehtiö and Rozbeh Jafari for support with TPP. QC 20180529

Available from: 2018-05-29 Created: 2018-05-29 Last updated: 2018-05-29Bibliographically approved
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Identifiers
ORCID iD: ORCID iD iconorcid.org/0000-0001-8993-048X

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