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  • 301.
    Karlsson, Max J.
    et al.
    KTH, Skolan för kemi, bioteknologi och hälsa (CBH), Proteinvetenskap, Systembiologi. KTH, Centra, Science for Life Laboratory, SciLifeLab.
    Svedman, Fernanda Costa
    Karolinska Inst, Dept Oncol Pathol, Stockholm, Sweden..
    Abdellah, Tebani
    KTH, Skolan för kemi, bioteknologi och hälsa (CBH), Proteinvetenskap, Systembiologi. KTH, Centra, Science for Life Laboratory, SciLifeLab.
    Kotol, David
    KTH, Skolan för kemi, bioteknologi och hälsa (CBH), Proteinvetenskap, Systembiologi. KTH, Centra, Science for Life Laboratory, SciLifeLab.
    Hoiom, Veronica
    Karolinska Inst, Dept Oncol Pathol, Stockholm, Sweden..
    Fagerberg, Linn
    KTH, Skolan för kemi, bioteknologi och hälsa (CBH), Proteinvetenskap, Systembiologi. KTH, Centra, Science for Life Laboratory, SciLifeLab.
    Edfors, Fredrik
    KTH, Skolan för kemi, bioteknologi och hälsa (CBH), Proteinvetenskap, Systembiologi. KTH, Centra, Science for Life Laboratory, SciLifeLab.
    Uhlén, Mathias
    KTH, Skolan för kemi, bioteknologi och hälsa (CBH), Proteinvetenskap, Systembiologi. KTH, Centra, Science for Life Laboratory, SciLifeLab. Karolinska Inst, Dept Neurosci, Stockholm, Sweden.;Tech Univ Denmark, Novo Nordisk Fdn Ctr Biosustainabil, Lyngby, Denmark..
    Brage, Suzanne Egyhazi
    Karolinska Inst, Dept Oncol Pathol, Stockholm, Sweden..
    Maddalo, Gianluca
    KTH, Centra, Science for Life Laboratory, SciLifeLab.
    Inflammation and Apolipoproteins Are Potential Biomarkers for Stratification of Cutaneous Melanoma Patients for Immunotherapy and Targeted Therapy2021Ingår i: Cancer Research, ISSN 0008-5472, E-ISSN 1538-7445, Vol. 81, nr 9, s. 2545-2555Artikel i tidskrift (Refereegranskat)
    Abstract [en]

    Malignant cutaneous melanoma is one of the most common cancers in young adults. During the last decade, targeted and immunotherapies have significantly increased the overall survival of patients with malignant cutaneous melanoma. Nevertheless, disease progression is common, and a lack of predictive biomarkers of patient response to therapy hinders individualized treatment strategies. To address this issue, we performed a longitudinal study using an unbiased proteomics approach to identify and quantify proteins in plasma both before and during treatment from 109 patients treated with either targeted or immunotherapy. Linear modeling and machine learning approaches identified 43 potential prognostic and predictive biomarkers. A reverse correlation between apolipoproteins and proteins related to inflammation was observed. In the immunotherapy group, patients with low pretreatment expression of apolipoproteins and high expression of inflammation markers had shorter progression-free survival. Similarly, increased expression of LDHB during treatment elicited a significant impact on response to immunotherapy. Overall, we identified potential common and treatment-specific biomarkers in malignant cutaneous melanoma, paving the way for clinical use of these biomarkers following validation on a larger cohort. Significance: This study identifies a potential biomarker panel that could improve the selection of therapy for patients with cutaneous melanoma.

  • 302.
    Karlsson, Max
    et al.
    KTH, Centra, Science for Life Laboratory, SciLifeLab. KTH, Skolan för kemi, bioteknologi och hälsa (CBH), Proteinvetenskap.
    Sjostedt, Evelina
    Karolinska Inst, Dept Neurosci, Stockholm, Sweden.;Uppsala Univ, Dept Immunol Genet & Pathol, Uppsala, Sweden..
    Oksvold, Per
    KTH, Centra, Science for Life Laboratory, SciLifeLab. KTH, Skolan för kemi, bioteknologi och hälsa (CBH), Proteinvetenskap.
    Sivertsson, Åsa
    KTH, Centra, Science for Life Laboratory, SciLifeLab. KTH, Skolan för kemi, bioteknologi och hälsa (CBH), Proteinvetenskap.
    Huang, Jinrong
    BGI Shenzhen, Shenzhen, Peoples R China.;BGI Qingdao, Qingdao Europe Adv Inst Life Sci, Lars Bolund Inst Regenerat Med, Qingdao, Peoples R China.;Aarhus Univ, Dept Biomed, Aarhus, Denmark..
    Alvez, Maria Bueno
    KTH, Skolan för kemi, bioteknologi och hälsa (CBH), Proteinvetenskap. KTH, Centra, Science for Life Laboratory, SciLifeLab.
    Arif, Muhammad
    KTH, Centra, Science for Life Laboratory, SciLifeLab. KTH, Skolan för kemi, bioteknologi och hälsa (CBH), Proteinvetenskap.
    Li, Xiangyu
    KTH, Centra, Science for Life Laboratory, SciLifeLab. KTH, Skolan för kemi, bioteknologi och hälsa (CBH), Proteinvetenskap.
    Lin, Lin
    Aarhus Univ, Dept Biomed, Aarhus, Denmark.;Aarhus Univ Hosp, Steno Diabet Ctr Aarhus, Aarhus, Denmark..
    Yu, Jiaying
    BGI Shenzhen, Shenzhen, Peoples R China.;BGI Qingdao, Qingdao Europe Adv Inst Life Sci, Lars Bolund Inst Regenerat Med, Qingdao, Peoples R China..
    Ma, Tao
    BGI Shenzhen, MGI, Shenzhen, Peoples R China..
    Xu, Fengping
    BGI Shenzhen, Shenzhen, Peoples R China.;BGI Qingdao, Qingdao Europe Adv Inst Life Sci, Lars Bolund Inst Regenerat Med, Qingdao, Peoples R China..
    Han, Peng
    BGI Qingdao, Qingdao Europe Adv Inst Life Sci, Lars Bolund Inst Regenerat Med, Qingdao, Peoples R China..
    Jiang, Hui
    BGI Shenzhen, MGI, Shenzhen, Peoples R China..
    Mardinoglu, Adil
    KTH, Centra, Science for Life Laboratory, SciLifeLab. KTH, Skolan för kemi, bioteknologi och hälsa (CBH), Proteinvetenskap.
    Zhang, Cheng
    KTH, Centra, Science for Life Laboratory, SciLifeLab. KTH, Skolan för kemi, bioteknologi och hälsa (CBH), Proteinvetenskap.
    von Feilitzen, Kalle
    KTH, Centra, Science for Life Laboratory, SciLifeLab. KTH, Skolan för kemi, bioteknologi och hälsa (CBH), Proteinvetenskap.
    Xu, Xun
    BGI Shenzhen, Shenzhen, Peoples R China..
    Wang, Jian
    BGI Shenzhen, Shenzhen, Peoples R China..
    Yang, Huanming
    BGI Shenzhen, Shenzhen, Peoples R China..
    Bolund, Lars
    BGI Shenzhen, Shenzhen, Peoples R China.;BGI Qingdao, Qingdao Europe Adv Inst Life Sci, Lars Bolund Inst Regenerat Med, Qingdao, Peoples R China.;Aarhus Univ, Dept Biomed, Aarhus, Denmark..
    Zhong, Wen
    KTH, Skolan för kemi, bioteknologi och hälsa (CBH), Proteinvetenskap. KTH, Centra, Science for Life Laboratory, SciLifeLab.
    Fagerberg, Linn
    KTH, Centra, Science for Life Laboratory, SciLifeLab. KTH, Skolan för kemi, bioteknologi och hälsa (CBH), Proteinvetenskap.
    Lindskog, Cecilia
    Uppsala Univ, Dept Immunol Genet & Pathol, Uppsala, Sweden..
    Ponten, Fredrik
    Uppsala Univ, Dept Immunol Genet & Pathol, Uppsala, Sweden..
    Mulder, Jan
    Karolinska Inst, Dept Neurosci, Stockholm, Sweden..
    Luo, Yonglun
    BGI Shenzhen, Shenzhen, Peoples R China.;BGI Qingdao, Qingdao Europe Adv Inst Life Sci, Lars Bolund Inst Regenerat Med, Qingdao, Peoples R China.;Aarhus Univ, Dept Biomed, Aarhus, Denmark.;Aarhus Univ Hosp, Steno Diabet Ctr Aarhus, Aarhus, Denmark..
    Uhlén, Mathias
    KTH, Centra, Science for Life Laboratory, SciLifeLab. KTH, Skolan för kemi, bioteknologi och hälsa (CBH), Proteinvetenskap, Systembiologi. Karolinska Inst, Dept Neurosci, Stockholm, Sweden..
    Genome-wide annotation of protein-coding genes in pig2022Ingår i: BMC Biology, E-ISSN 1741-7007, Vol. 20, nr 1, artikel-id 25Artikel i tidskrift (Refereegranskat)
    Abstract [en]

    Background: There is a need for functional genome-wide annotation of the protein-coding genes to get a deeper understanding of mammalian biology. Here, a new annotation strategy is introduced based on dimensionality reduction and density-based clustering of whole-body co-expression patterns. This strategy has been used to explore the gene expression landscape in pig, and we present a whole-body map of all protein-coding genes in all major pig tissues and organs. Results: An open-access pig expression map (www.rnaatlas.org ) is presented based on the expression of 350 samples across 98 well-defined pig tissues divided into 44 tissue groups. A new UMAP-based classification scheme is introduced, in which all protein-coding genes are stratified into tissue expression clusters based on body-wide expression profiles. The distribution and tissue specificity of all 22,342 protein-coding pig genes are presented. Conclusions: Here, we present a new genome-wide annotation strategy based on dimensionality reduction and density-based clustering. A genome-wide resource of the transcriptome map across all major tissues and organs in pig is presented, and the data is available as an open-access resource (www.rnaatlas.org), including a comparison to the expression of human orthologs.

  • 303.
    Karlsson, Max
    et al.
    KTH, Skolan för kemi, bioteknologi och hälsa (CBH), Proteinvetenskap, Systembiologi. KTH, Centra, Science for Life Laboratory, SciLifeLab.
    Zhang, Cheng
    KTH, Centra, Science for Life Laboratory, SciLifeLab. KTH, Skolan för kemi, bioteknologi och hälsa (CBH), Proteinvetenskap, Systembiologi.
    Mear, Loren
    Uppsala Univ, Dept Immunol Genet & Pathol, Uppsala, Sweden..
    Zhong, Wen
    KTH, Skolan för kemi, bioteknologi och hälsa (CBH), Proteinvetenskap. KTH, Centra, Science for Life Laboratory, SciLifeLab.
    Digre, Andreas
    Uppsala Univ, Dept Immunol Genet & Pathol, Uppsala, Sweden..
    Katona, Borbala
    Uppsala Univ, Dept Immunol Genet & Pathol, Uppsala, Sweden..
    Sjöstedt, Evelina
    Karolinska Inst, Dept Neurosci, Stockholm, Sweden..
    Butler, Lynn M.
    KTH, Centra, Science for Life Laboratory, SciLifeLab. KTH, Skolan för kemi, bioteknologi och hälsa (CBH), Proteinvetenskap, Cellulär och klinisk proteomik. Karolinska Inst, Dept Mol Med & Surg, Stockholm, Sweden.;Karolinska Univ Hosp, Karolinska Univ Lab, Clin Chem, Stockholm, Sweden.;Arctic Univ Norway, Dept Clin Med, Tromso, Norway..
    Odeberg, Jacob
    KTH, Centra, Science for Life Laboratory, SciLifeLab. KTH, Skolan för kemi, bioteknologi och hälsa (CBH), Proteinvetenskap. Arctic Univ Norway, Dept Clin Med, Tromso, Norway..
    Dusart, Philip
    KTH, Skolan för kemi, bioteknologi och hälsa (CBH), Proteinvetenskap, Cellulär och klinisk proteomik. KTH, Centra, Science for Life Laboratory, SciLifeLab. Arctic Univ Norway, Dept Clin Med, Tromso, Norway..
    Edfors, Fredrik
    KTH, Centra, Science for Life Laboratory, SciLifeLab. KTH, Skolan för kemi, bioteknologi och hälsa (CBH), Proteinvetenskap, Systembiologi.
    Oksvold, Per
    KTH, Centra, Science for Life Laboratory, SciLifeLab. KTH, Skolan för kemi, bioteknologi och hälsa (CBH), Proteinvetenskap, Systembiologi.
    von Feilitzen, Kalle
    KTH, Skolan för kemi, bioteknologi och hälsa (CBH), Proteinvetenskap, Systembiologi. KTH, Centra, Science for Life Laboratory, SciLifeLab.
    Zwahlen, Martin
    KTH, Centra, Science for Life Laboratory, SciLifeLab. KTH, Skolan för kemi, bioteknologi och hälsa (CBH), Proteinvetenskap, Systembiologi.
    Arif, Muhammad
    KTH, Skolan för kemi, bioteknologi och hälsa (CBH), Proteinvetenskap, Systembiologi. KTH, Centra, Science for Life Laboratory, SciLifeLab.
    Altay, Özlem
    KTH, Centra, Science for Life Laboratory, SciLifeLab. KTH, Skolan för kemi, bioteknologi och hälsa (CBH), Proteinvetenskap, Systembiologi.
    Li, Xiangyu
    KTH, Skolan för kemi, bioteknologi och hälsa (CBH), Proteinvetenskap, Systembiologi. KTH, Centra, Science for Life Laboratory, SciLifeLab.
    Ozcan, Mehmet
    KTH, Centra, Science for Life Laboratory, SciLifeLab. KTH, Skolan för kemi, bioteknologi och hälsa (CBH), Proteinvetenskap.
    Mardinoglu, Adil
    KTH, Centra, Science for Life Laboratory, SciLifeLab. KTH, Skolan för kemi, bioteknologi och hälsa (CBH), Proteinvetenskap, Systembiologi.
    Fagerberg, Linn
    KTH, Centra, Science for Life Laboratory, SciLifeLab. KTH, Skolan för kemi, bioteknologi och hälsa (CBH), Proteinvetenskap, Systembiologi.
    Mulder, Jan
    Karolinska Inst, Dept Neurosci, Stockholm, Sweden..
    Luo, Yonglun
    BGI Qingdao, BGI Shenzhen, Lars Bolund Inst Regenerat Med & Qingdao Europe A, Qingdao, Peoples R China.;Aarhus Univ, Dept Biomed, Aarhus, Denmark..
    Ponten, Fredrik
    Uppsala Univ, Dept Immunol Genet & Pathol, Uppsala, Sweden..
    Uhlén, Mathias
    KTH, Centra, Science for Life Laboratory, SciLifeLab. KTH, Skolan för kemi, bioteknologi och hälsa (CBH), Proteinvetenskap, Systembiologi. Karolinska Inst, Dept Neurosci, Stockholm, Sweden..
    Lindskog, Cecilia
    Uppsala Univ, Dept Immunol Genet & Pathol, Uppsala, Sweden..
    A single-cell type transcriptomics map of human tissues2021Ingår i: Science Advances, E-ISSN 2375-2548, Vol. 7, nr 31, artikel-id eabh2169Artikel i tidskrift (Refereegranskat)
    Abstract [en]

    Advances in molecular profiling have opened up the possibility to map the expression of genes in cells, tissues, and organs in the human body. Here, we combined single-cell transcriptomics analysis with spatial antibody-based protein profiling to create a high-resolution single-cell type map of human tissues. An open access atlas has been launched to allow researchers to explore the expression of human protein-coding genes in 192 individual cell type clusters. An expression specificity classification was performed to determine the number of genes elevated in each cell type, allowing comparisons with bulk transcriptomics data. The analysis highlights distinct expression clusters corresponding to cell types sharing similar functions, both within the same organs and between organs.

  • 304. Karnevi, E.
    et al.
    Dror, L. B.
    Mardinoglu, Adil
    KTH, Centra, Science for Life Laboratory, SciLifeLab. KTH, Skolan för kemi, bioteknologi och hälsa (CBH), Proteinvetenskap, Systembiologi.
    Elebro, J.
    Heby, M.
    Olofsson, S. -E
    Nodin, B.
    Eberhard, J.
    Gallagher, W.
    Uhlén, Mathias
    KTH, Centra, Science for Life Laboratory, SciLifeLab. KTH, Skolan för kemi, bioteknologi och hälsa (CBH), Proteinvetenskap.
    Jirström, K.
    Translational study reveals a two-faced role of RBM3 in pancreatic cancer and suggests its potential value as a biomarker for improved patient stratification2018Ingår i: Oncotarget, E-ISSN 1949-2553, Vol. 9, nr 5, s. 6188-6200Artikel i tidskrift (Refereegranskat)
    Abstract [en]

    Periampullary adenocarcinoma, including pancreatic cancer, is a heterogeneous group of tumors with dismal prognosis, partially due to lack of reliable targetable and predictive biomarkers. RNA-binding motif protein 3 (RBM3) has previously been shown to be an independent prognostic and predictive biomarker in several types of cancer. Herein, we examined the prognostic value of RBM3 in periampullary adenocarcinoma, as well as the effects following RBM3 suppression in pancreatic cancer cells in vitro. RBM3 mRNA levels were examined in 176 pancreatic cancer patients from The Cancer Genome Atlas. Immunohistochemical expression of RBM3 was analyzed in tissue microarrays with primary tumors and paired lymph node metastases from 175 consecutive patients with resected periampullary adenocarcinoma. Pancreatic cancer cells were transfected with anti-RBM3 siRNA in vitro and the influence on cell viability following chemotherapy, transwell migration and invasion was assessed. The results demonstrated that high mRNA-levels of RBM3 were significantly associated with a reduced overall survival (p = 0.026). RBM3 protein expression was significantly higher in lymph node metastases than in primary tumors (p = 0.005). High RBM3 protein expression was an independent predictive factor for the effect of adjuvant chemotherapy and an independent negative prognostic factor in untreated patients (p for interaction = 0.003). After siRNA suppression of RBM3 in vitro, pancreatic cancer cells displayed reduced migration and invasion compared to control, as well as a significantly increased resistance to chemotherapy. In conclusion, the strong indication of a positive response predictive effect of RBM3 expression in pancreatic cancer may be highly relevant in the clinical setting and merits further validation.

  • 305. Kato, Bernet S.
    et al.
    Nicholson, George
    Neiman, Maja
    KTH, Skolan för bioteknologi (BIO), Proteomik. KTH, Centra, Science for Life Laboratory, SciLifeLab.
    Rantalainen, Mattias
    Holmes, Chris C.
    Barrett, Amy
    Uhlén, Mathias
    KTH, Skolan för bioteknologi (BIO), Proteomik. KTH, Centra, Science for Life Laboratory, SciLifeLab.
    Nilsson, Peter
    KTH, Skolan för bioteknologi (BIO), Proteomik. KTH, Centra, Science for Life Laboratory, SciLifeLab.
    Spector, Tim D.
    Schwenk, Jochen M.
    KTH, Skolan för bioteknologi (BIO), Proteomik. KTH, Centra, Science for Life Laboratory, SciLifeLab.
    Variance decomposition of protein profiles from antibody arrays using a longitudinal twin model2011Ingår i: Proteome Science, E-ISSN 1477-5956, Vol. 9, nr 1, s. 73-Artikel i tidskrift (Refereegranskat)
    Abstract [en]

    The advent of affinity-based proteomics technologies for global protein profiling provides the prospect of finding new molecular biomarkers for common, multifactorial disorders. The molecular phenotypes obtained from studies on such platforms are driven by multiple sources, including genetic, environmental, and experimental. In characterizing the contribution of different sources of variation to the measured phenotypes, the aim is to facilitate the design and interpretation of future biomedical studies employing exploratory and multiplexed technologies. Thus, biometrical genetic modelling of twin or other family data can be used to decompose the variation underlying a phenotype into biological and experimental components. RESULTS: Using antibody suspension bead arrays and antibodies from the Human Protein Atlas, we study unfractionated serum from a longitudinal study on 154 twins. In this study, we provide a detailed description of how the variation in a molecular phenotype in terms of protein profile can be decomposed into familial i.e. genetic and common environmental; individual environmental, short-term biological and experimental components. The results show that across 69 antibodies analyzed in the study, the median proportion of the total variation explained by familial sources is 12% (IQR 1-22%), and the median proportion of the total variation attributable to experimental sources is 63% (IQR 53-72%). CONCLUSION: The variability analysis of antibody arrays highlights the importance to consider variability components and their relative contributions when designing and evaluating studies for biomarker discover with exploratory, high-throughput and multiplexed methods.

  • 306.
    Kaynar, Ali
    et al.
    Kings Coll London, Ctr Host Microbiome Interact, Fac Dent Oral & Craniofacial Sci, London SE1 9RT, England..
    Altay, Özlem
    KTH, Centra, Science for Life Laboratory, SciLifeLab.
    Li, Xiangyu
    KTH, Centra, Science for Life Laboratory, SciLifeLab.
    Zhang, Cheng
    KTH, Centra, Science for Life Laboratory, SciLifeLab.
    Turkez, Hasan
    Ataturk Univ, Med Biol Dept, Fac Med, TR-25240 Erzurum, Turkey..
    Uhlén, Mathias
    KTH, Centra, Science for Life Laboratory, SciLifeLab.
    Shoaie, Saeed
    KTH, Centra, Science for Life Laboratory, SciLifeLab. Kings Coll London, Ctr Host Microbiome Interact, Fac Dent Oral & Craniofacial Sci, London SE1 9RT, England.;Royal Inst Technol KTH, Sci Life Lab, SE-10691 Stockholm, Sweden..
    Mardinoglu, Adil
    KTH, Centra, Science for Life Laboratory, SciLifeLab. Kings Coll London, Ctr Host Microbiome Interact, Fac Dent Oral & Craniofacial Sci, London SE1 9RT, England.;Royal Inst Technol KTH, Sci Life Lab, SE-10691 Stockholm, Sweden..
    Systems Biology Approaches to Decipher the Underlying Molecular Mechanisms of Glioblastoma Multiforme2021Ingår i: International Journal of Molecular Sciences, ISSN 1661-6596, E-ISSN 1422-0067, Vol. 22, nr 24, s. 13213-, artikel-id 13213Artikel i tidskrift (Refereegranskat)
    Abstract [en]

    Glioblastoma multiforme (GBM) is one of the most malignant central nervous system tumors, showing a poor prognosis and low survival rate. Therefore, deciphering the underlying molecular mechanisms involved in the progression of the GBM and identifying the key driver genes responsible for the disease progression is crucial for discovering potential diagnostic markers and therapeutic targets. In this context, access to various biological data, development of new methodologies, and generation of biological networks for the integration of multi-omics data are necessary for gaining insights into the appearance and progression of GBM. Systems biology approaches have become indispensable in analyzing heterogeneous high-throughput omics data, extracting essential information, and generating new hypotheses from biomedical data. This review provides current knowledge regarding GBM and discusses the multi-omics data and recent systems analysis in GBM to identify key biological functions and genes. This knowledge can be used to develop efficient diagnostic and treatment strategies and can also be used to achieve personalized medicine for GBM.

  • 307.
    Kelly, C. M. A.
    et al.
    UCD Sch Biomol & Biomed Sci, Conway Inst, Dublin, Ireland..
    Penny, S.
    UCD Sch Biomol & Biomed Sci, Conway Inst, Dublin, Ireland..
    Holloway, P.
    UCD Sch Biomol & Biomed Sci, Conway Inst, Dublin, Ireland..
    Brennan, D.
    UCD Sch Biomol & Biomed Sci, Conway Inst, Dublin, Ireland..
    Duffy, M. J.
    St Vincents Univ Hosp, Dublin, Ireland..
    Landberg, G.
    Lund Univ, Lund, Sweden..
    Jirstrom, K.
    Lund Univ, Lund, Sweden..
    Ponten, F.
    Uppsala Univ, S-75105 Uppsala, Sweden..
    Uhlén, Mathias
    KTH.
    Gallagher, W. M.
    UCD Sch Biomol & Biomed Sci, Conway Inst, Dublin, Ireland..
    Systematic validation of novel breast cancer progression-associated biomarkers via high-throughput antibody generation and application of tissue microarray technology: an initial report2007Ingår i: European Journal of Cancer Supplements, ISSN 1359-6349, E-ISSN 1878-1217, Vol. 5, nr 8, s. 17-17Artikel i tidskrift (Övrigt vetenskapligt)
  • 308. Kelly, C. M.
    et al.
    Penny, S.
    Brennan, D.
    O'Brien, S.
    Fagan, A.
    Culhane, A. C.
    Jirstrom, K.
    Ponten, F.
    Uhlén, Mathias
    KTH, Skolan för bioteknologi (BIO), Proteomik.
    Gallagher, W. M.
    Systematic validation of novel breast cancer progression-associated biomarkers via high-throughput antibody generation and application of tissue microarray technology: An initial report2008Ingår i: Journal of Clinical Oncology, ISSN 0732-183X, E-ISSN 1527-7755, Vol. 26, nr 15Artikel i tidskrift (Övrigt vetenskapligt)
  • 309.
    Kim, Woonghee
    et al.
    KTH, Skolan för kemi, bioteknologi och hälsa (CBH), Proteinvetenskap, Systembiologi. KTH, Centra, Science for Life Laboratory, SciLifeLab. Science for Life Laboratory, KTH - Royal Institute of Technology, Stockholm SE-17165, Sweden, Stockholm.
    Li, Mengzhen
    KTH, Skolan för kemi, bioteknologi och hälsa (CBH), Proteinvetenskap, Systembiologi. KTH, Centra, Science for Life Laboratory, SciLifeLab.
    Jin, Han
    KTH, Centra, Science for Life Laboratory, SciLifeLab. KTH, Skolan för kemi, bioteknologi och hälsa (CBH), Proteinvetenskap, Systembiologi.
    Yang, Hong
    KTH, Centra, Science for Life Laboratory, SciLifeLab. KTH, Skolan för kemi, bioteknologi och hälsa (CBH), Proteinvetenskap, Systembiologi.
    Türkez, Hasan
    Department of Medical Biology, Faculty of Medicine, Ataturk University, Erzurum, Turkey.
    Uhlén, Mathias
    KTH, Centra, Science for Life Laboratory, SciLifeLab. KTH, Skolan för kemi, bioteknologi och hälsa (CBH), Proteinvetenskap, Systembiologi. Science for Life Laboratory, KTH - Royal Institute of Technology, Stockholm SE-17165, Sweden, Stockholm.
    Zhang, Cheng
    KTH, Centra, Science for Life Laboratory, SciLifeLab. KTH, Skolan för kemi, bioteknologi och hälsa (CBH), Proteinvetenskap, Systembiologi.
    Mardinoglu, Adil
    KTH, Centra, Science for Life Laboratory, SciLifeLab. KTH, Skolan för kemi, bioteknologi och hälsa (CBH), Proteinvetenskap, Systembiologi. Centre for Host-Microbiome Interactions, Faculty of Dentistry, Oral & Craniofacial Sciences, King's College London, London SE1 9RT, UK.
    Characterization of an in vitro steatosis model simulating activated de novo lipogenesis in MAFLD patients2023Ingår i: iScience, E-ISSN 2589-0042, Vol. 26, nr 10, artikel-id 107727Artikel i tidskrift (Refereegranskat)
    Abstract [en]

    Activated de novo lipogenesis (DNL) is the critical pathway involved in the progression of metabolic-associated fatty liver disease (MAFLD). We present an in vitro steatosis model for MAFLD that induces steatosis through activated DNL. This model utilizes insulin and LXR receptor ligand T0901317, eliminating the need for fatty acid treatment. Significant increases in triglycerides (TAGs) and expression of DNL-related transcription factors were observed. Transcriptomic analysis revealed distinct gene expression profiles between the DNL and conventional oleic acid (OA)-induced steatosis model. DNL steatosis model exhibited elevated pathways related to glycolysis, cholesterol homeostasis, and bile acid metabolism, reflecting its clinical relevance to MAFLD. Moreover, C75 and JNK-IN-5A compounds effectively reduced TAG accumulation and steatosis-related protein expression in the DNL model, whereas they had no significant impact on TAG accumulation in the OA model. In conclusion, we introduce an ideal model for steatosis study, which could help in understanding the MAFLD mechanisms.

  • 310.
    Klevebring, Daniel
    et al.
    KTH, Skolan för bioteknologi (BIO), Genteknologi.
    Fagerberg, Linn
    KTH, Skolan för bioteknologi (BIO), Proteomik.
    Lundberg, Emma
    KTH, Skolan för bioteknologi (BIO), Proteomik.
    Emanuelsson, Olof
    KTH, Skolan för bioteknologi (BIO), Genteknologi.
    Uhlén, Mathias
    KTH, Skolan för bioteknologi (BIO), Proteomik.
    Lundeberg, Joakim
    KTH, Skolan för bioteknologi (BIO), Genteknologi.
    Analysis of transcript and protein overlap in a human osteosarcoma cell line2010Ingår i: BMC Genomics, E-ISSN 1471-2164, Vol. 11, nr 1, s. 684-Artikel i tidskrift (Refereegranskat)
    Abstract [en]

    Background: An interesting field of research in genomics and proteomics is to compare the overlap between the transcriptome and the proteome. Recently, the tools to analyse gene and protein expression on a whole-genome scale have been improved, including the availability of the new generation sequencing instruments and high-throughput antibody-based methods to analyze the presence and localization of proteins. In this study, we used massive transcriptome sequencing (RNA-seq) to investigate the transcriptome of a human osteosarcoma cell line and compared the expression levels with in situ protein data obtained in-situ from antibody-based immunohistochemistry (IHC) and immunofluorescence microscopy (IF).

    Results: A large-scale analysis based on 2749 genes was performed, corresponding to approximately 13% of the protein coding genes in the human genome. We found the presence of both RNA and proteins to a large fraction of the analyzed genes with 60% of the analyzed human genes detected by all three methods. Only 34 genes (1.2%) were not detected on the transcriptional or protein level with any method. Our data suggest that the majority of the human genes are expressed at detectable transcript or protein levels in this cell line. Since the reliability of antibodies depends on possible cross-reactivity, we compared the RNA and protein data using antibodies with different reliability scores based on various criteria, including Western blot analysis. Gene products detected in all three platforms generally have good antibody validation scores, while those detected only by antibodies, but not by RNA sequencing, generally consist of more low-scoring antibodies.

    Conclusion: This suggests that some antibodies are staining the cells in an unspecific manner, and that assessment of transcript presence by RNA-seq can provide guidance for validation of the corresponding antibodies.

  • 311.
    Klütsch, Cornelya
    et al.
    KTH, Skolan för bioteknologi (BIO), Genteknologi.
    Seppälä, E. H.
    Fall, T.
    Uhlén, Mathias
    KTH, Skolan för bioteknologi (BIO), Genteknologi.
    Hedhammar, Å.
    Lohi, H.
    Savolainen, Peter
    KTH, Skolan för bioteknologi (BIO), Genteknologi.
    Regional occurrence, high frequency but low diversity of mitochondrial DNA haplogroup d1 suggests a recent dog-wolf hybridization in Scandinavia2011Ingår i: Animal Genetics, ISSN 0268-9146, E-ISSN 1365-2052, Vol. 42, nr 1, s. 100-103Artikel i tidskrift (Refereegranskat)
    Abstract [en]

    P>The domestic dog mitochondrial DNA (mtDNA)-gene pool consists of a homogenous mix of haplogroups shared among all populations worldwide, indicating that the dog originated at a single time and place. However, one small haplogroup, subclade d1, found among North Scandinavian/Finnish spitz breeds at frequencies above 30%, has a clearly separate origin. We studied the genetic and geographical diversity for this phylogenetic group to investigate where and when it originated and whether through independent domestication of wolf or dog-wolf crossbreeding. We analysed 582 bp of the mtDNA control region for 514 dogs of breeds earlier shown to harbour d1 and possibly related northern spitz breeds. Subclade d1 occurred almost exclusively among Swedish/Finnish Sami reindeer-herding spitzes and some Swedish/Norwegian hunting spitzes, at a frequency of mostly 60-100%. Genetic diversity was low, with only four haplotypes: a central, most frequent, one surrounded by two haplotypes differing by an indel and one differing by a substitution. The substitution was found in a single lineage, as a heteroplasmic mix with the central haplotype. The data indicate that subclade d1 originated in northern Scandinavia, at most 480-3000 years ago and through dog-wolf crossbreeding rather than a separate domestication event. The high frequency of d1 suggests that the dog-wolf hybrid phenotype had a selective advantage.

  • 312.
    Klütsch, Cornelya
    et al.
    KTH, Skolan för bioteknologi (BIO), Genteknologi.
    Seppälä, Eija H.
    Uhlén, Mathias
    KTH, Skolan för bioteknologi (BIO), Genteknologi.
    Lohi, Hannes
    Savolainen, Peter
    KTH, Skolan för bioteknologi (BIO), Genteknologi.
    Segregation of point mutation heteroplasmy in the control region of dog mtDNA studied systematically in deep generation pedigrees2011Ingår i: International journal of legal medicine, ISSN 0937-9827, E-ISSN 1437-1596, Vol. 125, nr 4, s. 527-535Artikel i tidskrift (Refereegranskat)
    Abstract [en]

    Heteroplasmy, the presence of two or more variants in an organism, may render mitochondrial DNA (mtDNA)-based individual identification challenging in forensic analysis. However, the variation of heteroplasmic proportions and the segregation of heteroplasmic variants through generations and within families have not been systematically described at a large scale in animals such as the domestic dog. Therefore, we performed the largest study to date in domestic dogs and screened a 582-bp-long fragment of the mtDNA control region in 180 individuals in 58 pedigrees for signs of heteroplasmy. We identified three pedigrees (5.17%) with heteroplasmic point mutations. To follow the segregation of the point mutations, we then analyzed 131 samples from these three independent pedigrees and found significant differences in heteroplasmy between generations and among siblings. Frequently (10% of cases), the proportion of one base changed from 0-10% to 80-90% (as judged from Sanger electropherograms) between generations and varied to a similar extent among siblings. We included also a literature review of heteroplasmic and potential mutational hot spot positions in the studied region which showed that all heteroplasmic positions appear to be mutational hot spots. Thus, although heteroplasmy may be used to increase the significance of a match in forensic case work, it may also cause erroneous exclusion of related individuals because of sharp switches from one state to the other within a single generation or among siblings especially in the presented mutational hot spots.

  • 313. Ko, Bong-Kook
    et al.
    Lee, Sook-Yeon
    Lee, Young-Ha
    Hwang, In-Sik
    Persson, Helena
    Rockberg, Johan
    KTH, Skolan för bioteknologi (BIO), Proteomik och nanobioteknologi.
    Borrebaeck, Carl
    Park, Dongeun
    Kim, Kyu-Tae
    Uhlén, Mathias
    KTH, Skolan för bioteknologi (BIO), Proteomik och nanobioteknologi.
    Lee, Jong-Seo
    Combination of novel HER2-targeting antibody 1E11 with trastuzumab shows synergistic antitumor activity in HER2-positive gastric cancer2015Ingår i: Molecular Oncology, ISSN 1878-0261, Vol. 9, nr 2, s. 398-408Artikel i tidskrift (Refereegranskat)
    Abstract [en]

    The synergistic interaction of two antibodies targeting the same protein could be developed as an effective anti-cancer therapy. Human epidermal growth factor receptor 2 (HER2) is overexpressed in 20-25% of breast and gastric cancer patients, and HER2-targeted antibody therapy using trastuzumab is effective in many of these patients. Nonetheless, improving therapeutic efficacy and patient survival is important, particularly in patients with HER2-positive gastric cancer. Here, we describe the development of 1E11, a HER2-targeted humanized monoclonal antibody showing increased efficacy in a highly synergistic manner in combination with trastuzumab in the HER2-overexpressing gastric cancer cell lines NCI-N87 and OE-19. The two antibodies bind to sub-domain IV of the receptor, but have non-overlapping epitopes, allowing them to simultaneously bind HER2. Treatment with 1E11 alone induced apoptosis in HER2-positive cancer cells, and this effect was enhanced by combination treatment with trastuzumab. Combination treatment with 1E11 and trastuzumab reduced the levels of total HER2 protein and those of aberrant HER2 signaling molecules including phosphorylated HER3 and EGFR. The synergistic antitumor activity of 1E11 in combination with trastuzumab indicates that it could be a novel potent therapeutic antibody for the treatment of HER2-overexpressing gastric cancers.

  • 314.
    Kotol, David
    et al.
    KTH, Skolan för kemi, bioteknologi och hälsa (CBH), Proteinvetenskap, Systembiologi. KTH, Centra, Science for Life Laboratory, SciLifeLab.
    Hober, Andreas
    KTH, Skolan för kemi, bioteknologi och hälsa (CBH), Proteinvetenskap. KTH, Centra, Science for Life Laboratory, SciLifeLab.
    Strandberg, Linnéa
    KTH, Skolan för kemi, bioteknologi och hälsa (CBH), Proteinvetenskap, Systembiologi. KTH, Centra, Science for Life Laboratory, SciLifeLab.
    Svensson, Anne-Sophie
    KTH, Skolan för kemi, bioteknologi och hälsa (CBH), Proteinvetenskap.
    Uhlén, Mathias
    KTH, Centra, Science for Life Laboratory, SciLifeLab. KTH, Skolan för kemi, bioteknologi och hälsa (CBH), Proteinvetenskap, Systembiologi.
    Edfors, Fredrik
    KTH, Centra, Science for Life Laboratory, SciLifeLab. KTH, Skolan för kemi, bioteknologi och hälsa (CBH), Proteinvetenskap, Systembiologi.
    Targeted proteomics analysis of plasma proteins using recombinant protein standards for addition only workflows2021Ingår i: BioTechniques, ISSN 0736-6205, E-ISSN 1940-9818, Vol. 71, nr 3, s. 473-483Artikel i tidskrift (Refereegranskat)
    Abstract [en]

    Targeted proteomics is an attractive approach for the analysis of blood proteins. Here, we describe a novel analytical platform based on isotope-labeled recombinant protein standards stored in a chaotropic agent and subsequently dried down to allow storage at ambient temperature. This enables a straightforward protocol suitable for robotic workstations. Plasma samples to be analyzed are simply added to the dried pellet followed by enzymatic treatment and mass spectrometry analysis. Here, we show that this approach can be used to precisely (coefficient of variation <10%) determine the absolute concentrations in human plasma of hundred clinically relevant protein targets, spanning four orders of magnitude, using simultaneous analysis of 292 peptides. The use of this next-generation analytical platform for high-throughput clinical proteome profiling is discussed. 

  • 315.
    Kotol, David
    et al.
    KTH, Skolan för kemi, bioteknologi och hälsa (CBH), Proteinvetenskap. KTH, Centra, Science for Life Laboratory, SciLifeLab.
    Hunt, Helian
    KTH, Skolan för kemi, bioteknologi och hälsa (CBH). KTH, Centra, Science for Life Laboratory, SciLifeLab.
    Hober, Andreas
    KTH, Skolan för kemi, bioteknologi och hälsa (CBH), Proteinvetenskap. KTH, Centra, Science for Life Laboratory, SciLifeLab.
    Karlsson, Max J.
    KTH, Skolan för kemi, bioteknologi och hälsa (CBH), Proteinvetenskap. KTH, Centra, Science for Life Laboratory, SciLifeLab.
    Forsström, Björn
    KTH, Skolan för kemi, bioteknologi och hälsa (CBH), Proteinvetenskap. KTH, Centra, Science for Life Laboratory, SciLifeLab.
    Gummesson, Anders
    Univ Gothenburg, Sahlgrenska Acad, Dept Mol & Clin Med, SE-40530 Gothenburg, Sweden..
    Bergström, Göran
    Univ Gothenburg, Sahlgrenska Acad, Dept Mol & Clin Med, SE-40530 Gothenburg, Sweden..
    Fagerberg, Linn
    Sci Life Lab, SE-17165 Solna, Sweden..
    Uhlén, Mathias
    KTH, Skolan för kemi, bioteknologi och hälsa (CBH), Proteinvetenskap. KTH, Centra, Science for Life Laboratory, SciLifeLab. Tech Univ Denmark, Novo Nordisk Fdn Ctr Biosustainabil, DK-2970 Horsholm, Denmark..
    Edfors, Fredrik
    KTH, Skolan för kemi, bioteknologi och hälsa (CBH), Proteinvetenskap. KTH, Centra, Science for Life Laboratory, SciLifeLab.
    Longitudinal Plasma Protein Profiling Using Targeted Proteomics and Recombinant Protein Standards2020Ingår i: Journal of Proteome Research, ISSN 1535-3893, E-ISSN 1535-3907, Vol. 19, nr 12, s. 4815-4825Artikel i tidskrift (Refereegranskat)
    Abstract [en]

    Spike-in of standards of known concentrations used in proteomics-based workflows is an attractive approach for both accurate and precise multiplexed protein quantification. Here, a quantitative method based on targeted proteomics analysis of plasma proteins using isotope-labeled recombinant standards originating from the Human Protein Atlas project has been established. The standards were individually quantified prior to being employed in the final multiplex assay. The assays are mainly directed toward actively secreted proteins produced in the liver, but may also originate from other parts of the human body. This study included 21 proteins classified by the FDA as either drug targets or approved clinical protein biomarkers. We describe the use of this multiplex assay for profiling a well-defined human cohort with sample collection spanning over a one-year period. Samples were collected at four different time points, which allowed for a longitudinal analysis to assess the variable plasma proteome within individuals. Two assays toward APOA1 and APOB had available clinical data, and the two assays were benchmarked against each other. The clinical assay is based on antibodies and shows high correlation between the two orthogonal methods, suggesting that targeted proteomics with highly parallel, multiplex analysis is an attractive alternative to antibody-based protein assays.

  • 316.
    Kotol, David
    et al.
    KTH, Skolan för kemi, bioteknologi och hälsa (CBH), Proteinvetenskap, Systembiologi. KTH, Centra, Science for Life Laboratory, SciLifeLab.
    Woessmann, Jakob
    KTH, Centra, Science for Life Laboratory, SciLifeLab. KTH, Skolan för kemi, bioteknologi och hälsa (CBH), Proteinvetenskap, Systembiologi.
    Hober, Andreas
    KTH, Centra, Science for Life Laboratory, SciLifeLab. KTH, Skolan för kemi, bioteknologi och hälsa (CBH), Proteinvetenskap, Systembiologi.
    Alvez, Maria Bueno
    KTH, Centra, Science for Life Laboratory, SciLifeLab. KTH, Skolan för kemi, bioteknologi och hälsa (CBH), Proteinvetenskap, Systembiologi.
    Tran Minh, Khue Hua
    KTH, Skolan för kemi, bioteknologi och hälsa (CBH), Proteinvetenskap, Systembiologi. KTH, Centra, Science for Life Laboratory, SciLifeLab.
    Pontén, Fredrik
    Rudbeck Laboratory, Uppsala University, Uppsala, 752 36, Sweden.
    Fagerberg, Linn
    KTH, Centra, Science for Life Laboratory, SciLifeLab. KTH, Skolan för kemi, bioteknologi och hälsa (CBH), Proteinvetenskap, Systembiologi.
    Uhlén, Mathias
    KTH, Centra, Science for Life Laboratory, SciLifeLab. KTH, Skolan för kemi, bioteknologi och hälsa (CBH), Proteinvetenskap, Systembiologi.
    Edfors, Fredrik
    KTH, Centra, Science for Life Laboratory, SciLifeLab. KTH, Skolan för kemi, bioteknologi och hälsa (CBH), Proteinvetenskap, Systembiologi.
    Absolute Quantification of Pan-Cancer Plasma Proteomes Reveals Unique Signature in Multiple Myeloma2023Ingår i: Cancers, ISSN 2072-6694, Vol. 15, nr 19, artikel-id 4764Artikel i tidskrift (Refereegranskat)
    Abstract [en]

    Mass spectrometry based on data-independent acquisition (DIA) has developed into a powerful quantitative tool with a variety of implications, including precision medicine. Combined with stable isotope recombinant protein standards, this strategy provides confident protein identification and precise quantification on an absolute scale. Here, we describe a comprehensive targeted proteomics approach to profile a pan-cancer cohort consisting of 1800 blood plasma samples representing 15 different cancer types. We successfully performed an absolute quantification of 253 proteins in multiplex. The assay had low intra-assay variability with a coefficient of variation below 20% (CV = 17.2%) for a total of 1013 peptides quantified across almost two thousand injections. This study identified a potential biomarker panel of seven protein targets for the diagnosis of multiple myeloma patients using differential expression analysis and machine learning. The combination of markers, including the complement C1 complex, JCHAIN, and CD5L, resulted in a prediction model with an AUC of 0.96 for the identification of multiple myeloma patients across various cancer patients. All these proteins are known to interact with immunoglobulins.

  • 317.
    Kronqvist, Nina
    et al.
    KTH, Skolan för bioteknologi (BIO), Molekylär Bioteknologi.
    Malm, Magdalena
    KTH, Skolan för bioteknologi (BIO), Molekylär Bioteknologi.
    Rockberg, Johan
    KTH, Skolan för bioteknologi (BIO), Proteomik.
    Hjelm, Barbara
    KTH, Skolan för bioteknologi (BIO), Proteomik.
    Uhlén, Mathias
    KTH, Skolan för bioteknologi (BIO), Proteomik.
    Ståhl, Stefan
    KTH, Skolan för bioteknologi (BIO), Molekylär Bioteknologi.
    Löfblom, John
    KTH, Skolan för bioteknologi (BIO), Molekylär Bioteknologi.
    Staphylococcal surface display in combinatorial protein engineering and epitope mapping of antibodies2010Ingår i: Recent Patents on Biotechnology, ISSN 1872-2083, Vol. 4, nr 3, s. 171-182Artikel i tidskrift (Refereegranskat)
    Abstract [en]

    The field of combinatorial protein engineering for generation of new affinity proteins started in the mid 80s by the development of phage display. Although phage display is a prime example of a simple yet highly efficient method, manifested by still being the standard technique 25 years later, new alternative technologies are available today. One of the more successful new display technologies is cell display. Here we review the field of cell display for directed evolution purposes, with focus on a recently developed method employing Gram-positive staphylococci as display host. Patents on the most commonly used cell display systems and on different modifications as well as specific applications of these systems are also included. General strategies for selection of new affinity proteins from cell-displayed libraries are discussed, with detailed examples mainly from studies on the staphylococcal display system. In addition, strategies for characterization of recombinant proteins on the staphylococcal cell surface, with an emphasis on an approach for epitope mapping of antibodies, are included.

  • 318.
    Kronqvist, Nina
    et al.
    KTH, Skolan för bioteknologi (BIO), Molekylär Bioteknologi.
    Rockberg, Johan
    KTH, Skolan för bioteknologi (BIO), Proteomik.
    Hjelm, Barbara
    KTH, Skolan för bioteknologi (BIO), Proteomik.
    Ståhl, Stefan
    KTH, Skolan för bioteknologi (BIO), Molekylär Bioteknologi.
    Uhlén, Mathias
    KTH, Skolan för bioteknologi (BIO), Proteomik.
    Löfblom, John
    KTH, Skolan för bioteknologi (BIO), Molekylär Bioteknologi.
    New Ways for Discovery of Biopharmaceuticals: Emerging Techniques using Surface Display on Gram-positive Bacteria for Combinatorial Protein Engineering and Characterization2009Ingår i: Bioforum Europe, ISSN 1611-597X, Vol. 13, nr 6-7, s. 022-Artikel i tidskrift (Refereegranskat)
  • 319.
    Kürten, Charlotte
    et al.
    KTH, Skolan för kemi, bioteknologi och hälsa (CBH), Fiber- och polymerteknologi, Ytbehandlingsteknik. KTH, Centra, Science for Life Laboratory, SciLifeLab.
    Eriksson, Adam
    Maddalo, Gianluca
    Edfors, Fredrik
    Uhlén, Mathias
    KTH, Centra, Science for Life Laboratory, SciLifeLab.
    Syrén, Per-Olof
    KTH, Centra, Science for Life Laboratory, SciLifeLab.
    Engineering of water networks in class II terpene cyclases underscores the importance of amino acid hydration and entropy in biocatalysis and enzyme designManuskript (preprint) (Övrigt vetenskapligt)
  • 320.
    Kürten, Charlotte
    et al.
    KTH, Skolan för bioteknologi (BIO), Proteomik och nanobioteknologi.
    Uhlén, Mathias
    KTH, Skolan för bioteknologi (BIO), Proteomik och nanobioteknologi.
    Syrén, Per-Olof
    KTH, Skolan för bioteknologi (BIO), Proteomik och nanobioteknologi.
    Overexpression of functional human oxidosqualene cyclase in Escherichia coli2015Ingår i: Protein Expression and Purification, ISSN 1046-5928, E-ISSN 1096-0279, Vol. 115, s. 46-53Artikel i tidskrift (Refereegranskat)
    Abstract [en]

    The generation of multicyclic scaffolds from linear oxidosqualene by enzymatic polycyclization catalysis constitutes a cornerstone in biology for the generation of bioactive compounds. Human oxidosqualene cyclase (hOSC) is a membrane-bound triterpene cyclase that catalyzes the formation of the tetracyclic steroidal backbone, a key step in cholesterol biosynthesis. Protein expression of hOSC and other eukaryotic oxidosqualene cyclases has traditionally been performed in yeast and insect cells, which has resulted in protein yields of 2.7 mg protein/g cells (hOSC in Pichia pastoris) after 48 h of expression. Herein we present, to the best of our knowledge, the first functional expression of hOSC in the model organism Escherichia coli. Using a codon-optimized gene and a membrane extraction procedure for which detergent is immediately added after cell lysis, a protein yield of 2.9 mg/g bacterial cells was achieved after four hours of expression. It is envisaged that the isolation of high amounts of active eukaryotic oxidosqualene cyclase in an easy to handle bacterial system will be beneficial in pharmacological, biochemical and biotechnological applications.

  • 321.
    Lakshmikanth, Tadepally
    et al.
    Karolinska Inst, Dept Womens & Childrens Hlth, Sci Life Lab, Karolinska, Solna, Sweden..
    Muhammad, Sayyed Auwn
    Karolinska Inst, Dept Womens & Childrens Hlth, Sci Life Lab, Karolinska, Solna, Sweden..
    Olin, Axel
    Karolinska Inst, Dept Womens & Childrens Hlth, Sci Life Lab, Karolinska, Solna, Sweden..
    Chen, Yang
    Karolinska Inst, Dept Womens & Childrens Hlth, Sci Life Lab, Karolinska, Solna, Sweden..
    Mikes, Jaromir
    Karolinska Inst, Dept Womens & Childrens Hlth, Sci Life Lab, Karolinska, Solna, Sweden..
    Fagerberg, Linn
    KTH, Centra, Science for Life Laboratory, SciLifeLab.
    Gummesson, Anders
    Univ Gothenburg, Inst Med, Dept Mol & Clin Med, Wallenberg Lab, Gothenburg, Sweden.;Sahlgrens Univ Hosp, Dept Physiol, Gothenburg, Sweden..
    Bergström, Göran
    Univ Gothenburg, Inst Med, Dept Mol & Clin Med, Wallenberg Lab, Gothenburg, Sweden.;Sahlgrens Univ Hosp, Dept Physiol, Gothenburg, Sweden..
    Uhlén, Mathias
    KTH, Centra, Science for Life Laboratory, SciLifeLab.
    Brodin, Petter
    Karolinska Inst, Dept Womens & Childrens Hlth, Sci Life Lab, Karolinska, Solna, Sweden.;Karolinska Univ Hosp, Dept Pediat Rheumatol, Karolinska, Solna, Sweden..
    Human Immune System Variation during 1 Year2020Ingår i: Cell Reports, E-ISSN 2211-1247, Vol. 32, nr 3, artikel-id 107923Artikel i tidskrift (Refereegranskat)
    Abstract [en]

    The human immune system varies extensively between individuals, but variation within individuals over time has not been well characterized. Systems-level analyses allow for simultaneous quantification of many interacting immune system components and the inference of global regulatory principles. Here, we present a longitudinal, systems-level analysis in 99 healthy adults 50 to 65 years of age and sampled every third month for 1 year. We describe the structure of interindividual variation and characterize extreme phenotypes along a principal cum. From coordinated measurement fluctuations, we infer relationships between 115 immune cell populations and 750 plasma proteins constituting the blood immune system. While most individuals have stable immune systems, the degree of longitudinal variability is an individual feature. The most variable individuals, in the absence of overt infections, exhibited differences in markers of metabolic health suggestive of a possible link between metabolic and immunologic homeostatic regulation.

  • 322.
    Lam, Simon
    et al.
    Kings Coll London, Fac Dent Oral & Craniofacial Sci, Ctr Host Microbiome Interact, London, England..
    Arif, Muhammad
    KTH, Skolan för kemi, bioteknologi och hälsa (CBH), Proteinvetenskap, Systembiologi. KTH, Centra, Science for Life Laboratory, SciLifeLab.
    Song, Xiya
    KTH, Centra, Science for Life Laboratory, SciLifeLab. KTH, Skolan för kemi, bioteknologi och hälsa (CBH), Proteinvetenskap, Systembiologi.
    Uhlén, Mathias
    KTH, Centra, Science for Life Laboratory, SciLifeLab. KTH, Skolan för kemi, bioteknologi och hälsa (CBH), Proteinvetenskap, Systembiologi.
    Mardinoglu, Adil
    KTH, Centra, Science for Life Laboratory, SciLifeLab. KTH, Skolan för kemi, bioteknologi och hälsa (CBH), Proteinvetenskap, Systembiologi. Kings Coll London, Fac Dent Oral & Craniofacial Sci, Ctr Host Microbiome Interact, London, England.;.
    Machine Learning Analysis Reveals Biomarkers for the Detection of Neurological Diseases2022Ingår i: Frontiers in Molecular Neuroscience, ISSN 1662-5099, Vol. 15, artikel-id 889728Artikel i tidskrift (Refereegranskat)
    Abstract [en]

    It is critical to identify biomarkers for neurological diseases (NLDs) to accelerate drug discovery for effective treatment of patients of diseases that currently lack such treatments. In this work, we retrieved genotyping and clinical data from 1,223 UK Biobank participants to identify genetic and clinical biomarkers for NLDs, including Alzheimer's disease (AD), Parkinson's disease (PD), motor neuron disease (MND), and myasthenia gravis (MG). Using a machine learning modeling approach with Monte Carlo randomization, we identified a panel of informative diagnostic biomarkers for predicting AD, PD, MND, and MG, including classical liver disease markers such as alanine aminotransferase, alkaline phosphatase, and bilirubin. A multinomial model trained on accessible clinical markers could correctly predict an NLD diagnosis with an accuracy of 88.3%. We also explored genetic biomarkers. In a genome-wide association study of AD, PD, MND, and MG patients, we identified single nucleotide polymorphisms (SNPs) implicated in several craniofacial disorders such as apnoea and branchiootic syndrome. We found evidence for shared genetic risk loci among NLDs, including SNPs in cancer-related genes and SNPs known to be associated with non-brain cancers such as Wilms tumor, leukemia, and colon cancer. This indicates overlapping genetic characterizations among NLDs which challenges current clinical definitions of the neurological disorders. Taken together, this work demonstrates the value of data-driven approaches to identify novel biomarkers in the absence of any known or promising biomarkers.

  • 323.
    Lam, Simon
    et al.
    Kings Coll London, Fac Dent Oral & Craniofacial Sci, Ctr Host Microbiome Interact, London SE1 9RT, England..
    Bayraktar, Abdulahad
    Kings Coll London, Fac Dent Oral & Craniofacial Sci, Ctr Host Microbiome Interact, London SE1 9RT, England..
    Zhang, Cheng
    KTH, Centra, Science for Life Laboratory, SciLifeLab.
    Turkez, Hasan
    Ataturk Univ, Fac Med, Dept Med Biol, TR-25240 Erzurum, Turkey..
    Nielsen, Jens
    Chalmers Univ Technol, Dept Biol & Biol Engn, SE-41296 Gothenburg, Sweden..
    Boren, Jan
    Univ Gothenburg, Sahlgrenska Univ Hosp, Dept Mol & Clin Med, Wallenberg Lab, SE-41345 Gothenburg, Sweden..
    Shoaie, Saeed
    KTH, Centra, Science for Life Laboratory, SciLifeLab. Kings Coll London, Fac Dent Oral & Craniofacial Sci, Ctr Host Microbiome Interact, London SE1 9RT, England..
    Uhlén, Mathias
    KTH, Centra, Science for Life Laboratory, SciLifeLab.
    Mardinoglu, Adil
    KTH, Centra, Science for Life Laboratory, SciLifeLab. Kings Coll London, Fac Dent Oral & Craniofacial Sci, Ctr Host Microbiome Interact, London SE1 9RT, England.
    A systems biology approach for studying neurodegenerative diseases2020Ingår i: Drug Discovery Today, ISSN 1359-6446, E-ISSN 1878-5832, Vol. 25, nr 7, s. 1146-1159Artikel, forskningsöversikt (Refereegranskat)
    Abstract [en]

    Neurodegenerative diseases (NDDs), such as Alzheimer's (AD) and Parkinson's (PD), are among the leading causes of lost years of healthy life and exert a great strain on public healthcare systems. Despite being first described more than a century ago, no effective cure exists for AD or PD. Although extensively characterised at the molecular level, traditional neurodegeneration research remains marred by narrow-sense approaches surrounding amyloid beta (A beta), tau, and alpha-synuclein (alpha-syn). A systems biology approach enables the integration of multi-omics data and informs discovery of biomarkers, drug targets, and treatment strategies. Here, we present a comprehensive timeline of high-throughput data collection, and associated biotechnological advancements and computational analysis related to AD and PD. We hereby propose that a philosophical change in the definitions of AD and PD is now needed.

  • 324.
    Lam, Simon
    et al.
    Kings Coll London, Fac Dent Oral & Craniofacial Sci, Ctr Host Microbiome Interact, London SE1 9RT, England..
    Doran, Stephen
    Kings Coll London, Fac Dent Oral & Craniofacial Sci, Ctr Host Microbiome Interact, London SE1 9RT, England..
    Yüksel, Hatice Hilal
    KTH, Centra, Science for Life Laboratory, SciLifeLab. KTH, Skolan för kemi, bioteknologi och hälsa (CBH), Proteinvetenskap, Systembiologi.
    Altay, Özlem
    KTH, Centra, Science for Life Laboratory, SciLifeLab. KTH, Skolan för kemi, bioteknologi och hälsa (CBH), Proteinvetenskap, Systembiologi.
    Turkez, Hasan
    Ataturk Univ, Fac Med, Dept Med Biol, TR-25240 Erzurum, Turkey..
    Nielsen, Jens
    Chalmers Univ Technol, Dept Biol & Biol Engn, SE-41296 Gothenburg, Sweden..
    Boren, Jan
    Univ Gothenburg, Sahlgrenska Univ Hosp, Dept Mol & Clin Med, Wallenberg Lab, Gothenburg, Sweden..
    Uhlén, Mathias
    KTH, Centra, Science for Life Laboratory, SciLifeLab. KTH, Skolan för kemi, bioteknologi och hälsa (CBH), Proteinvetenskap, Systembiologi.
    Mardinoglu, Adil
    KTH, Centra, Science for Life Laboratory, SciLifeLab. KTH, Skolan för kemi, bioteknologi och hälsa (CBH), Proteinvetenskap, Systembiologi. Kings Coll London, Fac Dent Oral & Craniofacial Sci, Ctr Host Microbiome Interact, London SE1 9RT, England.;KTH Royal Inst Technol, Sci Life Lab, SE-17121 Stockholm, Sweden..
    Addressing the heterogeneity in liver diseases using biological networks2021Ingår i: Briefings in Bioinformatics, ISSN 1467-5463, E-ISSN 1477-4054, Vol. 22, nr 2, s. 1751-1766Artikel, forskningsöversikt (Refereegranskat)
    Abstract [en]

    The abnormalities in human metabolism have been implicated in the progression of several complex human diseases, including certain cancers. Hence, deciphering the underlying molecular mechanisms associated with metabolic reprogramming in a disease state can greatly assist in elucidating the disease aetiology. An invaluable tool for establishing connections between global metabolic reprogramming and disease development is the genome-scale metabolic model (GEM). Here, we review recent work on the reconstruction of cell/tissue-type and cancer-specific GEMs and their use in identifying metabolic changes occurring in response to liver disease development, stratification of the heterogeneous disease population and discovery of novel drug targets and biomarkers. We also discuss how GEMs can be integrated with other biological networks for generating more comprehensive cell/tissue models. In addition, we review the various biological network analyses that have been employed for the development of efficient treatment strategies. Finally, we present three case studies in which independent studies converged on conclusions underlying liver disease.

  • 325.
    Lam, Simon
    et al.
    Kings Coll London, Fac Dent Oral & Craniofacial Sci, London SE1 9RT, England..
    Hartmann, Nils
    Leibniz Inst Aging Fritz Lipmann Inst, D-07745 Jena, Germany.;Univ Med Ctr, Inst Pathol, D-55131 Mainz, Germany..
    Benfeitas, Rui
    Stockholm Univ, Dept Biochem & Biophys, Sci Life Lab, Natl Bioinformat Infrastruct Sweden NBIS, SE-17121 Stockholm, Sweden..
    Zhang, Cheng
    KTH, Centra, Science for Life Laboratory, SciLifeLab. KTH, Skolan för kemi, bioteknologi och hälsa (CBH), Proteinvetenskap, Systembiologi.
    Arif, Muhammad
    KTH, Skolan för kemi, bioteknologi och hälsa (CBH), Proteinvetenskap, Systembiologi. KTH, Centra, Science for Life Laboratory, SciLifeLab.
    Turkez, Hasan
    Ataturk Univ, Fac Med, Dept Med Biol, TR-25240 Erzurum, Turkey..
    Uhlén, Mathias
    KTH, Centra, Science for Life Laboratory, SciLifeLab. KTH, Skolan för kemi, bioteknologi och hälsa (CBH), Proteinvetenskap, Systembiologi.
    Englert, Christoph
    Leibniz Inst Aging Fritz Lipmann Inst, D-07745 Jena, Germany.;Freidrich Schiller Univ Jena, Inst Biochem & Biophys, D-07745 Jena, Germany..
    Knight, Robert
    Kings Coll London, Fac Dent Oral & Craniofacial Sci, London SE1 9RT, England..
    Mardinoglu, Adil
    KTH, Centra, Science for Life Laboratory, SciLifeLab. KTH, Skolan för kemi, bioteknologi och hälsa (CBH), Proteinvetenskap, Systembiologi. Kings Coll London, Fac Dent Oral & Craniofacial Sci, London SE1 9RT, England..
    Systems Analysis Reveals Ageing-Related Perturbations in Retinoids and Sex Hormones in Alzheimer's and Parkinson's Diseases2021Ingår i: Biomedicines, E-ISSN 2227-9059, Vol. 9, nr 10, artikel-id 1310Artikel i tidskrift (Refereegranskat)
    Abstract [en]

    Neurodegenerative diseases, including Alzheimer's (AD) and Parkinson's diseases (PD), are complex heterogeneous diseases with highly variable patient responses to treatment. Due to the growing evidence for ageing-related clinical and pathological commonalities between AD and PD, these diseases have recently been studied in tandem. In this study, we analysed transcriptomic data from AD and PD patients, and stratified these patients into three subclasses with distinct gene expression and metabolic profiles. Through integrating transcriptomic data with a genome-scale metabolic model and validating our findings by network exploration and co-analysis using a zebrafish ageing model, we identified retinoids as a key ageing-related feature in all subclasses of AD and PD. We also demonstrated that the dysregulation of androgen metabolism by three different independent mechanisms is a source of heterogeneity in AD and PD. Taken together, our work highlights the need for stratification of AD/PD patients and development of personalised and precision medicine approaches based on the detailed characterisation of these subclasses.

  • 326. Lamond, Angus I.
    et al.
    Uhlén, Mathias
    KTH, Skolan för bioteknologi (BIO), Proteomik. KTH, Centra, Science for Life Laboratory, SciLifeLab.
    Horning, Stevan
    Makarov, Alexander
    Robinson, Carol V.
    Serrano, Luis
    Hartl, F. Ulrich
    Baumeister, Wolfgang
    Werenskiold, Anne Katrin
    Andersen, Jens S.
    Vorm, Ole
    Linial, Michal
    Aebersold, Ruedi
    Mann, Matthias
    Advancing Cell Biology Through Proteomics in Space and Time (PROSPECTS)2012Ingår i: Molecular & Cellular Proteomics, ISSN 1535-9476, E-ISSN 1535-9484, Vol. 11, nr 3Artikel i tidskrift (Refereegranskat)
    Abstract [en]

    The term "proteomics" encompasses the large-scale detection and analysis of proteins and their post-translational modifications. Driven by major improvements in mass spectrometric instrumentation, methodology, and data analysis, the proteomics field has burgeoned in recent years. It now provides a range of sensitive and quantitative approaches for measuring protein structures and dynamics that promise to revolutionize our understanding of cell biology and molecular mechanisms in both human cells and model organisms. The Proteomics Specification in Time and Space (PROSPECTS) Network is a unique EU-funded project that brings together leading European research groups, spanning from instrumentation to biomedicine, in a collaborative five year initiative to develop new methods and applications for the functional analysis of cellular proteins. This special issue of Molecular and Cellular Proteomics presents 16 research papers reporting major recent progress by the PROSPECTS groups, including improvements to the resolution and sensitivity of the Orbitrap family of mass spectrometers, systematic detection of proteins using highly characterized antibody collections, and new methods for absolute as well as relative quantification of protein levels. Manuscripts in this issue exemplify approaches for performing quantitative measurements of cell proteomes and for studying their dynamic responses to perturbation, both during normal cellular responses and in disease mechanisms. Here we present a perspective on how the proteomics field is moving beyond simply identifying proteins with high sensitivity toward providing a powerful and versatile set of assay systems for characterizing proteome dynamics and thereby creating a new "third generation"proteomics strategy that offers an indispensible tool for cell biology and molecular medicine.

  • 327. Larance, Mark
    et al.
    Kirkwood, Kathryn J.
    Xirodimas, Dimitris P.
    Lundberg, Emma
    KTH, Skolan för bioteknologi (BIO), Proteomik. KTH, Centra, Science for Life Laboratory, SciLifeLab.
    Uhlén, Mathias
    KTH, Skolan för bioteknologi (BIO), Proteomik. KTH, Centra, Science for Life Laboratory, SciLifeLab.
    Lamond, Angus I.
    Characterization of MRFAP1 Turnover and Interactions Downstream of the NEDD8 Pathway2012Ingår i: Molecular & Cellular Proteomics, ISSN 1535-9476, E-ISSN 1535-9484, Vol. 11, nr 3Artikel i tidskrift (Refereegranskat)
    Abstract [en]

    The NEDD8-Cullin E3 ligase pathway plays an important role in protein homeostasis, in particular the degradation of cell cycle regulators and transcriptional control networks. To characterize NEDD8-cullin target proteins, we performed a quantitative proteomic analysis of cells treated with MLN4924, a small molecule inhibitor of the NEDD8 conjugation pathway. MRFAP1 and its interaction partner, MORF4L1, were among the most up-regulated proteins after NEDD8 inhibition in multiple human cell lines. We show that MRFAP1 has a fast turnover rate in the absence of MLN4924 and is degraded via the ubiquitin- proteasome system. The increased abundance of MRFAP1 after MLN4924 treatment results from a decreased rate of degradation. Characterization of the binding partners of both MRFAP1 and MORF4L1 revealed a complex protein-protein interaction network. MRFAP1 bound to a number of E3 ubiquitin ligases, including CUL4B, but not to components of the NuA4 complex, including MRGBP, which bound to MORF4L1. These data indicate that MRFAP1 may regulate the ability of MORF4L1 to interact with chromatin-modifying enzymes by binding to MORF4L1 in a mutually exclusive manner with MRGBP. Analysis of MRFAP1 expression in human tissues by immunostaining with a MRFAP1-specific antibody revealed that it was detectable in only a small number of tissues, in particular testis and brain. Strikingly, analysis of the seminiferous tubules of the testis showed the highest nuclear staining in the spermatogonia and much weaker staining in the spermatocytes and spermatids. MRGBP was inversely correlated with MRFAP1 expression in these cell types, consistent with an exchange of MORF4L1 interaction partners as cells progress through meiosis in the testis. These data highlight an important new arm of the NEDD8cullin pathway.

  • 328. Larsson, A.
    et al.
    Johansson, M. E.
    Wangefjord, S.
    Gaber, A.
    Nodin, B.
    Kucharzewska, P.
    Welinder, C.
    Belting, M.
    Eberhard, J.
    Johnsson, A.
    Uhlén, Mathias
    KTH, Skolan för bioteknologi (BIO), Proteomik.
    Jirstrom, K.
    Overexpression of podocalyxin-like protein is an independent factor of poor prognosis in colorectal cancer2011Ingår i: British Journal of Cancer, ISSN 0007-0920, E-ISSN 1532-1827, Vol. 105, nr 5, s. 666-672Artikel i tidskrift (Refereegranskat)
    Abstract [en]

    BACKGROUND: Podocalyxin-like 1 (PODXL) is a cell-adhesion glycoprotein and stem cell marker that has been associated with an aggressive tumour phenotype and poor prognosis in several forms of cancer. In this study, we investigated the prognostic impact of PODXL expression in colorectal cancer (CRC). METHODS: Using tissue microarrays and immunohistochemistry, PODXL expression was evaluated in 536 incident CRC cases from a prospective, population-based cohort study. Kaplan-Meier analysis and Cox proportional hazards modelling were used to assess the impact of PODXL expression on cancer-specific survival (CSS) and overall survival (OS). RESULTS: High PODXL expression was significantly associated with unfavourable clinicopathological characteristics, a shorter CSS (hazard ratio (HR) = 1.98; 95% confidence interval (CI) 1.38-2.84, P < 0.001) and 5-year OS (HR = 1.85; 95% CI 1.29-2.64, P = 0.001); the latter remaining significant in multivariate analysis (HR = 1.52; 95% CI 1.03-2.25, P = 0.036). In addition, in curatively resected stage III (T1-4, N1-2, M0) patients (n = 122) with tumours with high PODXL expression, a significant benefit from adjuvant chemotherapy was demonstrated (p(interaction) = 0.004 for CSS and 0.015 for 5-year OS in multivariate analysis). CONCLUSION: Podocalyxin-like 1 expression is an independent factor of poor prognosis in CRC. Our results also suggest that PODXL may be a useful marker to stratify patients for adjuvant chemotherapy.

  • 329. Larsson, Anna
    et al.
    Fridberg, Marie
    Gaber, Alexander
    Nodin, Björn
    Levéen, Per
    Jonsson, Göran
    Uhlén, Mathias
    KTH, Skolan för bioteknologi (BIO), Proteomik.
    Birgisson, Helgi
    Jirström, Karin
    Validation of podocalyxin-like protein as a biomarker of poor prognosis in colorectal cancer2012Ingår i: BMC Cancer, ISSN 1471-2407, E-ISSN 1471-2407, Vol. 12, s. 282-Artikel i tidskrift (Refereegranskat)
    Abstract [en]

    Background: Podocalyxin-like 1 (PODXL) is a cell-adhesion glycoprotein and stem cell marker that has been associated with an aggressive tumour phenotype and adverse outcome in several cancer types. We recently demonstrated that overexpression of PODXL is an independent factor of poor prognosis in colorectal cancer (CRC). The aim of this study was to validate these results in two additional independent patient cohorts and to examine the correlation between PODXL mRNA and protein levels in a subset of tumours. Method: PODXL protein expression was analyzed by immunohistochemistry in tissue microarrays with tumour samples from a consecutive, retrospective cohort of 270 CRC patients (cohort 1) and a prospective cohort of 337 CRC patients (cohort 2). The expression of PODXL mRNA was measured by real-time quantitative PCR in a subgroup of 62 patients from cohort 2. Spearman's Rho and Chi-Square tests were used for analysis of correlations between PODXL expression and clinicopathological parameters. Kaplan Meier analysis and Cox proportional hazards modelling were applied to assess the relationship between PODXL expression and time to recurrence (TTR), disease free survival (DFS) and overall survival (OS). Results: High PODXL protein expression was significantly associated with unfavourable clinicopathological characteristics in both cohorts. In cohort 1, high PODXL expression was associated with a significantly shorter 5-year OS in both univariable (HR = 2.28; 95% CI 1.43-3.63, p = 0.001) and multivariable analysis (HR = 2.07; 95% CI 1.25-3.43, p = 0.005). In cohort 2, high PODXL expression was associated with a shorter TTR (HR = 2.93; 95% CI 1.26-6.82, p = 0.013) and DFS (HR = 2.44; 95% CI 1.32-4.54, p = 0.005), remaining significant in multivariable analysis, HR = 2.50; 95% CI 1.05-5.96, p = 0.038 for TTR and HR = 2.11; 95% CI 1.13-3.94, p = 0.019 for DFS. No significant correlation could be found between mRNA levels and protein expression of PODXL and there was no association between mRNA levels and clinicopathological parameters or survival. Conclusions: Here, we have validated the previously demonstrated association between immunohistochemical expression of PODXL and poor prognosis in CRC in two additional independent patient cohorts. The results further underline the potential utility of PODXL as a biomarker for more precise prognostication and treatment stratification of CRC patients.

  • 330. Larsson, Anna H.
    et al.
    Lehn, Sophie
    Wangefjord, Sakarias
    Karnevi, Emelie
    Kuteeva, Eugenia
    Sundström, Magnus
    Nodin, Björn
    Uhlén, Mathias
    KTH, Skolan för bioteknologi (BIO), Proteomik och nanobioteknologi. KTH, Centra, Science for Life Laboratory, SciLifeLab.
    Eberhard, Jakob
    Birgisson, Helgi
    Jirström, Karin
    Significant association and synergistic adverse prognostic effect of podocalyxin-like protein and epidermal growth factor receptor expression in colorectal cancer2016Ingår i: Journal of Translational Medicine, ISSN 1479-5876, E-ISSN 1479-5876, Vol. 14, artikel-id 128Artikel i tidskrift (Refereegranskat)
    Abstract [en]

    Background: Podocalyxin-like 1 (PODXL) is an anti-adhesive transmembrane protein that has been demonstrated to be an independent factor of poor prognosis in colorectal cancer (CRC). The gene encoding PODXL is located to chromosome 7, which also harbours the gene for the epidermal growth factor receptor (EGFR). The aim of this study was to examine the associations between PODXL and EGFR expression in CRC in vitro and in vivo. Methods: EGFR expression was analysed in tumours from three independent patient cohorts; cohort 1 (n = 533), cohort 2 (n = 259) and cohort 3 (n = 310), previously analysed for immunohistochemical PODXL expression and KRAS and BRAF mutations (cohort 1 and 3). Levels of EGFR and PODXL were determined by western blot in six different CRC cell lines. Results: High expression of PODXL was significantly associated with high EGFR expression (p < 0.001) in all three cohorts, and with BRAF mutation (p < 0.001) in cohort 1 and 3. High EGFR expression correlated with BRAF mutation (p < 0.001) in cohort 1. High EGFR expression was associated with adverse clinicopathological factors and independently predicted a reduced 5-year overall survival (OS) in cohort 1 (HR 1.77; 95 % CI 1.27-2.46), cohort 2 (HR 1.58; 95 % CI 1.05-2.38) and cohort 3 (HR 1.83; 95 % CI 1.19-2.81). The highest risk of death within 5 years was observed in patients with tumours displaying high expression of both EGFR and PODXL in cohort 1 and 3 (HR 1.97; 95 % CI 1.18-3.28 and HR 3.56; 95 % CI 1.75-7.22, respectively). Western blot analysis showed a uniform expression of PODXL and EGFR in all six examined CRC cell lines. Conclusions: The results from this study demonstrate that high expression of EGFR is an independent factor of poor prognosis in CRC. Moreover, strong links have been uncovered between expression of the recently proposed biomarker candidate PODXL with EGFR expression in CRC in vivo and in vitro, and with BRAF mutation in vivo. High expression of both PODXL and EGFR may also have a synergistic adverse effect on survival. These findings suggest a potential functional link in CRC between PODXL, EGFR and BRAF, all originating from chromosome 7, which may be highly relevant in the clinical setting and therefore merit future in-depth study.

  • 331. Larsson, Anna H.
    et al.
    Nodin, Björn
    Syk, Ingvar
    Palmquist, Ingrid
    Uhlén, Mathias
    KTH, Skolan för bioteknologi (BIO), Proteomik och nanobioteknologi. KTH, Centra, Science for Life Laboratory, SciLifeLab.
    Eberhard, Jakob
    Jirström, Karin
    Podocalyxin-like protein expression in primary colorectal cancer and synchronous lymph node metastases2013Ingår i: Diagnostic Pathology, E-ISSN 1746-1596, Vol. 8, nr 1, s. 109-Artikel i tidskrift (Refereegranskat)
    Abstract [en]

    Aims: Previous studies have shown that membranous expression of podocalyxin-like protein (PODXL) is associated with poor prognosis in colorectal cancer (CRC). In this study, we compared PODXL expression in primary CRC and synchronous lymph node metastases. We further analyzed whether its expression changed in rectal tumours after neoadjuvant radiation therapy. Methods and results: The studied cohort consists of 73 consecutive patients from the South-Swedish Colorectal Cancer Biobank. Immunohistochemical PODXL expression was examined on full-face sections from all primary tumours and all 140 available lymph node metastases from 31 cases. Membranous PODXL expression was denoted in 18/73 (24,7%) primary tumours, with a high concordance between primary and metastatic lesions. While all negative primary tumours had negative metastases, some PODXL positive primaries had a varying proportion of positive and negative metastatic lymph nodes. PODXL expression was also found to be mainly unaltered in pre- and post-irradiation surgically resected tumour specimens in rectal cancer patients (n=16). Conclusions: The findings in this study suggest that analysis of PODXL expression in the primary tumour is sufficient for its use as a prognostic and treatment predictive biomarker in CRC, also in patients with metastatic disease.

  • 332. Larsson, I.
    et al.
    Uhlén, Mathias
    KTH, Centra, Science for Life Laboratory, SciLifeLab. KTH, Skolan för kemi, bioteknologi och hälsa (CBH), Proteinvetenskap, Systembiologi.
    Zhang, Cheng
    KTH, Centra, Science for Life Laboratory, SciLifeLab. KTH, Skolan för kemi, bioteknologi och hälsa (CBH), Proteinvetenskap, Systembiologi.
    Mardinoglu, Adil
    KTH, Centra, Science for Life Laboratory, SciLifeLab. KTH, Skolan för kemi, bioteknologi och hälsa (CBH), Proteinvetenskap, Systembiologi.
    Genome-Scale Metabolic Modeling of Glioblastoma Reveals Promising Targets for Drug Development2020Ingår i: Frontiers in Genetics, E-ISSN 1664-8021, Vol. 11, artikel-id 381Artikel i tidskrift (Refereegranskat)
    Abstract [en]

    Glioblastoma (GBM) is an aggressive type of brain cancer with a poor prognosis for affected patients. The current line of treatment only gives the patients a survival time of on average 15 months. In this work, we use genome-scale metabolic models (GEMs) together with other systems biology tools to examine the global transcriptomics-data of GBM-patients obtained from The Cancer Genome Atlas (TCGA). We reveal the molecular mechanisms underlying GBM and identify potential therapeutic targets for effective treatment of patients. The work presented consists of two main parts. The first part stratifies the patients into two groups, high and low survival, and compares their gene expression. The second part uses GBM and healthy brain tissue GEMs to simulate gene knockout in a GBM cell model to find potential therapeutic targets and predict their side effect in healthy brain tissue. We (1) find that genes upregulated in the patients with low survival are linked to various stages of the glioma invasion process, and (2) identify five essential genes for GBM, whose inhibition is non-toxic to healthy brain tissue, therefore promising to investigate further as therapeutic targets.

  • 333.
    Larsson, Karin
    et al.
    KTH, Skolan för bioteknologi (BIO), Proteomik.
    Eriksson, Cecilia
    KTH, Skolan för bioteknologi (BIO), Proteomik.
    Schwenk, Jochen. M.
    KTH, Skolan för bioteknologi (BIO), Proteomik.
    Berglund, Lisa
    KTH, Skolan för bioteknologi (BIO), Proteomik.
    Hober, Sophia
    KTH, Skolan för bioteknologi (BIO), Proteomik.
    Uhlén, Mattias
    KTH, Skolan för bioteknologi (BIO), Proteomik.
    Characterization of PrEST-based antibodies towards human Cytokeratin-172009Ingår i: JIM - Journal of Immunological Methods, ISSN 0022-1759, E-ISSN 1872-7905, Vol. 342, s. 20-32Artikel i tidskrift (Refereegranskat)
    Abstract [en]

    Antibody-based proteomics efforts depend on validated antibodies to ensure correct annotation of analyzed proteins. We have previously argued that a low sequence identity to other proteins is a key feature for antigens used in antibody generation. Thus, a major challenge for whole-proteome studies is how to address families of highly sequence related proteins within the context of generating specific antibodies. In this study, two non-overlapping parts of human Cytokeratin-17, a protein belonging to the intermediate filament family of highly sequence-related proteins, were selected as a model system to study the specificity and cross reactivity of antibodies generated towards such a target. These recombinantly produced Protein Epitope Signature Tags (PrESTs) were immunized in five rabbits each and the batch-to-batch variations in the obtained immune responses were studied by mapping of linear epitopes using synthetic overlapping peptides. The obtained results showed a similar but not identical immune response in the respective antibody groups with a limited number of epitopes being identified. Immunohistochemical analysis of the affinity purified monospecific antibodies on tissue micro arrays resulted in a general recognition of human cytokeratins for all analyzed binders whereas antibodies identified as binding to the most unique parts of the PrESTs showed the most Cytokeratin-17 like staining. The data presented here support the strategy to use sequence identity scores as the main criteria for antigen selection but also indicate the possibility to instead produce a single antibody recognizing a defined group of proteins when the intended targets overall sequence identity score is too high. This type of group-specific antibodies would be an important tool for antibody-based projects aiming for a complete coverage of the human proteome.

  • 334.
    Larsson, Karin
    et al.
    KTH, Skolan för bioteknologi (BIO), Proteomik.
    Hofström, Camilla
    KTH, Skolan för bioteknologi (BIO), Molekylär Bioteknologi.
    Lindskog, C.
    Hansson, M.
    Angelidou, P.
    Hökfelt, T.
    Uhlén, Mathias
    KTH, Skolan för bioteknologi (BIO).
    Wernérus, H.
    Gräslund, Torbjörn
    KTH, Skolan för bioteknologi (BIO), Molekylär Bioteknologi.
    Hober, Sophia
    KTH, Skolan för bioteknologi (BIO), Molekylär Bioteknologi. KTH, Skolan för bioteknologi (BIO), Proteomik.
    Novel antigen design for the generation of antibodies to G-protein-coupled receptors2011Ingår i: JIM - Journal of Immunological Methods, ISSN 0022-1759, E-ISSN 1872-7905, Vol. 370, nr 1-2, s. 14-23Artikel i tidskrift (Refereegranskat)
    Abstract [en]

    Antibodies are important tools for the study of G-protein-coupled receptors, key proteins in cellular signaling. Due to their large hydrophobic membrane spanning regions and often very short loops exposed on the surface of the cells, generation of antibodies able to recognize the receptors in the endogenous environment has been difficult. Here, we describe an antigen-design method where the extracellular loops and N-terminus are combined to a single antigen for generation of antibodies specific to three selected GPCRs: NPY5R, B2ARN and GLP1R. The design strategy enabled straightforward antigen production and antibody generation. Binding of the antibodies to intact receptors was analyzed using flow cytometry and immunofluorescence based confocal microscopy on A-431 cells overexpressing the respective GPCR. The antibody-antigen interactions were characterized using epitope mapping, and the antibodies were applied in immunohistochemical staining of human tissues. Most of the antibodies showed specific binding to their respective overexpressing cell line but not to the non-transfected cells, thus indicating binding to their respective target receptor. The epitope mapping showed that sub-populations within the purified antibody pool recognized different regions of the antigen. Hence, the genetic combination of several different epitopes enables efficient generation of specific antibodies with potential use in several applications for the study of endogenous receptors.

  • 335.
    Larsson, Karin
    et al.
    KTH, Skolan för bioteknologi (BIO), Proteomik.
    Hofström, Camilla
    KTH, Skolan för bioteknologi (BIO).
    Lindskog, C
    Uhlén, Mattias
    KTH, Skolan för bioteknologi (BIO), Proteomik.
    Gräslund, Torbjörn
    KTH, Skolan för bioteknologi (BIO).
    Hansson, M
    Hober, Sophia
    KTH, Skolan för bioteknologi (BIO).
    Angelidou, Pia
    KTH, Skolan för bioteknologi (BIO).
    Hökfelt, T
    Wernérus, Henrik
    KTH, Skolan för bioteknologi (BIO).
    Novel antigen design for the generation of G-protein-coupled receptorantibodies.Manuskript (preprint) (Övrigt vetenskapligt)
  • 336.
    Larsson, Karin
    et al.
    KTH, Skolan för bioteknologi (BIO), Proteomik.
    Nilsson, Peter
    KTH, Skolan för bioteknologi (BIO).
    Uhlén, Mathias
    KTH, Skolan för bioteknologi (BIO).
    Hober, Sophia
    KTH, Skolan för bioteknologi (BIO).
    Wernérus, Henrik
    KTH, Skolan för bioteknologi (BIO).
    Multiplexed PrEST immunization for high-throughput affinity proteomics2006Ingår i: JIM - Journal of Immunological Methods, ISSN 0022-1759, E-ISSN 1872-7905, Vol. 315, s. 110-120Artikel i tidskrift (Refereegranskat)
    Abstract [en]

    Monospecific antibodies dfdfdfdf (msAbs) generated through antigen specific purification of polyclonal antisera are valuable tools in proteome analyses. However, proteome wide generation of msAbs would require extensive immunization programs. Therefore, it would be desirable to develop efficient immunization and purification methods to reduce the number of animals needed for such antibody-based research. Here we describe a multiplex immunization strategy for generation of msAbs towards recombinantly produced human protein fragments, denoted PrESTs. Antisera from rabbits immunized with a mixture of two, three, five and up to ten different PrESTs have been purified by a two-step immunoaffinity-based protocol and the efficiency of the purification method was analyzed using a two-color protein array concept. The obtained results showed that almost 80% of the animals immunized with antigens composed of two or three different PrESTs yielded antibodies recognizing all the included PrESTs. Furthermore, the modified two-step purification method effectively eliminated all background binding and produced pure antibody pools against individual PrESTs. This indicates that the multiplexed PrEST immunization strategy described here could become useful for high-throughput antibody-based proteomics initiatives, thus significantly reducing the number of animals needed in addition to providing a more cost-efficient method for production of msAbs.

  • 337. Larsson, M.
    et al.
    Graslund, S.
    Li, Y. B.
    Brundell, E.
    Uhlén, Mathias
    KTH, Tidigare Institutioner (före 2005), Bioteknologi.
    Hoog, C.
    Ståhl, Stefan
    KTH, Tidigare Institutioner (före 2005), Bioteknologi.
    High-throughput protein expression of cDNA products as a tool in functional genomics2000Ingår i: Journal of Biotechnology, ISSN 0168-1656, E-ISSN 1873-4863, Vol. 80, nr 2, s. 143-157Artikel i tidskrift (Refereegranskat)
    Abstract [en]

    A proteomics approach has been developed aimed to allow high throughput analysis of protein products expressed from cDNA fragments (expressed sequence tags, ESTs). The concept relies on expression of gene products to generate specific antibodies for protein analysis, such as immunolocalization of the proteins on cellular and subcellular level. To evaluate the system, 55 cDNA clones with predominantly unknown function were selected from a mouse testis cDNA-library. A bacterial expression system was designed that allowed robust expression and easy purification. Protein levels between 15 and 80 mg l(-1) were obtained for 49 of the clones. Five clones were selected for immunization and all yielded functional antibodies that gave specific staining in Western blot screening of samples from various cell types. Furthermore, extensive immunolocalization information on subcellular level was obtained for three of the five clones. All generated data were stored in a relational database, and are made available through a web-interface (http://www.biochem.kth.se/multiscale/), which also provides relevant links and allows homology searches from the original sequences. The possibility to allow analysis of gene products from whole genomes using this 'localization proteomics' approach is discussed.

  • 338. Larsson, M.
    et al.
    Ståhl, Stefan
    KTH, Tidigare Institutioner (före 2005), Bioteknologi.
    Uhlén, Mathias
    KTH, Tidigare Institutioner (före 2005), Bioteknologi.
    Wennborg, A.
    Expression profile viewer (ExProView): A software tool for transcriptome analysis2000Ingår i: Genomics, ISSN 0888-7543, E-ISSN 1089-8646, Vol. 63, nr 3, s. 341-353Artikel i tidskrift (Refereegranskat)
    Abstract [en]

    A software tool, Expression Profile Viewer (ExProView), for analysis of gene expression profiles derived from expressed sequence tags (ESTs) and SAGE (serial analysis of gene expression) is presented. The software visualizes a complete set of classified transcript data in a two-dimensional array of dots, a virtual chip, in which each dot represents a known gene as characterized in the transcript databases Expressed Gene Anatomy Database or UniGene. The virtual chip display can be changed between representations of different conceptual systems for gene/protein classification and grouping. Four alternative projections are currently available: (i) cellular role, (ii) subcellular compartment, (iii) chromosome localization, and (iv) total UniGene display. However, the chip can be adapted to any other desired layout. By selecting dots, further information about the represented genes is obtained from the local database and WWW links. The software thus provides a visualization of global mRNA expression at the descriptive level and guides in the exploration of patterns of functional expression, while maintaining direct access to detailed information on each individual gene. To evaluate the software, public EST and SAGE gene expression data obtained from the Cancer Genome Anatomy Project at the National Center for Biotechnology Information were analyzed and visualized. A demonstration of the software is available at http://www.biochem.kth. se/exproview/.

  • 339.
    Lee, Chien-Yun
    et al.
    Tech Univ Munich, Chair Prote & Bioanalyt, Emil Erlenmeyer Forum 5, D-85354 Freising Weihenstephan, Germany.;Natl Chung Hsing Univ, Grad Inst Biotechnol, Taichung, Taiwan.;Acad Sinica, Mol & Biol Agr Sci Program, Taiwan Int Grad Program, Taipei, Taiwan.;Natl Chung Hsing Univ, Taipei, Taiwan..
    Wang, Dongxue
    Tech Univ Munich, Chair Prote & Bioanalyt, Emil Erlenmeyer Forum 5, D-85354 Freising Weihenstephan, Germany..
    Wilhelm, Mathias
    Tech Univ Munich, Chair Prote & Bioanalyt, Emil Erlenmeyer Forum 5, D-85354 Freising Weihenstephan, Germany..
    Zolg, Daniel P.
    Tech Univ Munich, Chair Prote & Bioanalyt, Emil Erlenmeyer Forum 5, D-85354 Freising Weihenstephan, Germany..
    Schmidt, Tobias
    Tech Univ Munich, Chair Prote & Bioanalyt, Emil Erlenmeyer Forum 5, D-85354 Freising Weihenstephan, Germany..
    Schnatbaum, Karsten
    JPT Peptide Technol GmbH, Berlin, Germany..
    Reimer, Ulf
    JPT Peptide Technol GmbH, Berlin, Germany..
    Ponten, Fredrik
    Uppsala Univ, Dept Immunol Genet & Pathol, Uppsala, Sweden..
    Uhlén, Mathias
    KTH, Centra, Science for Life Laboratory, SciLifeLab.
    Hahne, Hannes
    OmicScouts GmbH, Freising Weihenstephan, Germany..
    Kuster, Bernhard
    Tech Univ Munich, Chair Prote & Bioanalyt, Emil Erlenmeyer Forum 5, D-85354 Freising Weihenstephan, Germany.;Natl Chung Hsing Univ, Taipei, Taiwan.;Bavarian Ctr Biomol Mass Spectrometry, Freising Weihenstephan, Germany..
    Mining the Human Tissue Proteome for Protein Citrullination2018Ingår i: Molecular & Cellular Proteomics, ISSN 1535-9476, E-ISSN 1535-9484, Vol. 17, nr 7, s. 1378-1391Artikel i tidskrift (Refereegranskat)
    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.

  • 340.
    Lee, Sunjae
    et al.
    Kings Coll London, Ctr Host Microbial Interact, London, England..
    Arefaine, Bethlehem
    Roger Williams Inst Hepatol, Fdn Liver Res, London, England..
    Begum, Neelu
    Kings Coll London, Ctr Host Microbial Interact, London, England..
    Witherden, Elizabeth
    Kings Coll London, Ctr Host Microbial Interact, London, England.;Roger Williams Inst Hepatol, Fdn Liver Res, London, England..
    Stamouli, Marilena
    Harzandi, Azadeh
    Kings Coll London, Ctr Host Microbial Interact, London, England..
    Zamalloa, Ane
    Kings Coll Hosp NHS Fdn Trust, Inst Liver Studies & Transplantat, London, England..
    Corcoran, Eleanor
    Kings Coll Hosp NHS Fdn Trust, Dept Crit Care, London, England..
    Williams, Roger
    Roger Williams Inst Hepatol, Fdn Liver Res, London, England.;Kings Coll London, Sch Immunol & Microbial Sci, Fac Life Sci & Med, London, England..
    Chokshi, Shilpa
    Roger Williams Inst Hepatol, Fdn Liver Res, London, England.;Kings Coll London, Sch Immunol & Microbial Sci, Fac Life Sci & Med, London, England..
    Proctor, Gordon
    Kings Coll London, Ctr Host Microbial Interact, London, England..
    Mardinoglu, Adil
    KTH, Skolan för kemi, bioteknologi och hälsa (CBH), Proteinvetenskap, Systembiologi. KTH, Centra, Science for Life Laboratory, SciLifeLab. Kings Coll London, Ctr Host Microbial Interact, London, England.
    Uhlén, Mathias
    KTH, Skolan för kemi, bioteknologi och hälsa (CBH), Proteinvetenskap, Systembiologi. KTH, Centra, Science for Life Laboratory, SciLifeLab.
    Shoaie, Saeed
    KTH, Skolan för kemi, bioteknologi och hälsa (CBH), Proteinvetenskap, Systembiologi. KTH, Centra, Science for Life Laboratory, SciLifeLab. Kings Coll London, Ctr Host Microbial Interact, London, England.
    Patel, Vishal C.
    Roger Williams Inst Hepatol, Fdn Liver Res, London, England.;Kings Coll London, Sch Immunol & Microbial Sci, Fac Life Sci & Med, London, England.;Kings Coll Hosp London, Inst Liver Studies & Transplantat, London, England..
    In-depth shotgun metagenomic analysis of the oral and gut microbiome identifies striking overlap in microbial community structure, virulence factors and antimicrobial resistance genes based on stage and severity of cirrhosis2022Ingår i: Journal of Hepatology, ISSN 0168-8278, E-ISSN 1600-0641, Vol. 77, s. S68-S69Artikel i tidskrift (Övrigt vetenskapligt)
  • 341.
    Lee, Sunjae
    et al.
    Kings Coll London, Ctr Host Microbial Interact, Guys Campus, London, England..
    Arefaine, Bethlehem
    Fdn Liver Res, Inst Hepatol, London, England..
    Witherden, Elizabeth
    Kings Coll London, Ctr Host Microbial Interact, Guys Campus, London, England..
    Begum, Neelu
    Kings Coll London, Ctr Host Microbial Interact, Guys Campus, London, England..
    Harzandi, Azadeh
    Kings Coll London, Ctr Host Microbial Interact, Guys Campus, London, England..
    Zamalloa, Ane
    Kings Coll Hosp London, Inst Liver Studies, London, England..
    Corcoran, Eleanor
    Kings Coll Hosp NHS Fdn Trust, Dept Crit Care, London, England..
    Smith, John
    Kings Coll Hosp NHS Fdn Trust, Dept Crit Care, London, England..
    Williams, Roger
    Fdn Liver Res, Inst Hepatol, London, England.;Kings Coll London, Sch Immunol & Microbial Sci, London, England..
    Chokshi, Shilpa
    Fdn Liver Res, Inst Hepatol, London, England.;Kings Coll London, Sch Immunol & Microbial Sci, London, England..
    Proctor, Gordon
    Kings Coll London, Ctr Host Microbial Interact, Guys Campus, London, England..
    Mardinoglu, Adil
    KTH, Centra, Science for Life Laboratory, SciLifeLab. KTH, Skolan för kemi, bioteknologi och hälsa (CBH), Proteinvetenskap, Systembiologi. Kings Coll London, Ctr Host Microbial Interact, Guys Campus, London, England..
    Uhlén, Mathias
    KTH, Centra, Science for Life Laboratory, SciLifeLab. KTH, Skolan för bioteknologi (BIO), Centra, Albanova VinnExcellence Center for Protein Technology, ProNova. KTH, Skolan för kemi, bioteknologi och hälsa (CBH), Proteinvetenskap, Systembiologi.
    Shoaie, Saeed
    KTH, Centra, Science for Life Laboratory, SciLifeLab. KTH, Skolan för kemi, bioteknologi och hälsa (CBH), Proteinvetenskap. Kings Coll London, Ctr Host Microbial Interact, Guys Campus, London, England..
    Patel, Vishal C.
    Fdn Liver Res, Inst Hepatol, London, England.;Kings Coll Hosp London, Inst Liver Studies, London, England.;Kings Coll London, Sch Immunol & Microbial Sci, London, England..
    In-depth shotgun metagenomic analysis of the gut microbiome identifies striking variations in microbial community structure based on severity and stage of cirrhosis2021Ingår i: Journal of Hepatology, ISSN 0168-8278, E-ISSN 1600-0641, Vol. 75, s. S222-S223Artikel i tidskrift (Övrigt vetenskapligt)
  • 342.
    Lee, Sunjae
    et al.
    KTH, Centra, Science for Life Laboratory, SciLifeLab.
    Zhang, Cheng
    KTH, Centra, Science for Life Laboratory, SciLifeLab.
    Arif, Muhammad
    KTH, Skolan för kemi, bioteknologi och hälsa (CBH), Proteinvetenskap, Systembiologi.
    Liu, Zhengtao
    KTH, Centra, Science for Life Laboratory, SciLifeLab.
    Benfeitas, Rui
    KTH, Centra, Science for Life Laboratory, SciLifeLab.
    Bidkhori, Gholamreza
    KTH, Centra, Science for Life Laboratory, SciLifeLab.
    Deshmukh, Sumit
    KTH, Centra, Science for Life Laboratory, SciLifeLab.
    Shobky, Mohamed AI
    KTH, Centra, Science for Life Laboratory, SciLifeLab.
    Lovric, Alen
    KTH, Centra, Science for Life Laboratory, SciLifeLab.
    Boren, Jan
    Nielsen, Jens
    KTH, Centra, Science for Life Laboratory, SciLifeLab.
    Uhlén, Mathias
    KTH, Centra, Science for Life Laboratory, SciLifeLab.
    Mardinoglu, Adil
    KTH, Centra, Science for Life Laboratory, SciLifeLab.
    TCSBN: a database of tissue and cancer specific biological networks2017Ingår i: Nucleic Acids Research, ISSN 0305-1048, E-ISSN 1362-4962, Vol. 46, nr D1, s. D595-D600Artikel i tidskrift (Refereegranskat)
    Abstract [en]

    Biological networks provide new opportunities for understanding the cellular biology in both health and disease states. We generated tissue specific integrated networks (INs) for liver, muscle and adipose tissues by integratingmetabolic, regulatory and protein-protein interaction networks. We also generated human co-expression networks (CNs) for 46 normal tissues and 17 cancers to explore the functional relationships between genes as well as their relationships with biological functions, and investigate the overlap between functional and physical interactions provided by CNs and INs, respectively. These networks can be employed in the analysis of omics data, provide detailed insight into disease mechanisms by identifying the key biological components and eventually can be used in the development of efficient treatment strategies. Moreover, comparative analysis of the networks may allow for the identification of tissue-specific targets that can be used in the development of drugs with the minimum toxic effect to other human tissues. These context-specific INs and CNs are presented in an interactive website http://inetmodels.com without any limitation.

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    fulltext
  • 343.
    Lee, Sunjae
    et al.
    KTH, Skolan för bioteknologi (BIO), Proteomik och nanobioteknologi. KTH, Centra, Science for Life Laboratory, SciLifeLab.
    Zhang, Cheng
    KTH, Skolan för bioteknologi (BIO), Proteomik och nanobioteknologi. KTH, Centra, Science for Life Laboratory, SciLifeLab.
    Kilicarslan, Murat
    Piening, Brian D.
    Björnson, Elias
    Hallström, Björn M.
    KTH, Skolan för bioteknologi (BIO), Proteomik och nanobioteknologi. KTH, Centra, Science for Life Laboratory, SciLifeLab.
    Groen, Albert K.
    Ferrannini, Ele
    Laakso, Markku
    Snyder, Michael
    Bluher, Matthias
    Uhlèn, Mathias
    KTH, Skolan för bioteknologi (BIO), Proteomik och nanobioteknologi. KTH, Centra, Science for Life Laboratory, SciLifeLab.
    Nielsen, Jens
    KTH, Skolan för bioteknologi (BIO), Genteknologi. Chalmers, Sweden.
    Smith, Ulf
    Serlie, Mireille J.
    Boren, Jan
    Mardinoglu, Adil
    Integrated Network Analysis Reveals an Association between Plasma Mannose Levels and Insulin Resistance2016Ingår i: Cell Metabolism, ISSN 1550-4131, E-ISSN 1932-7420, Vol. 24, nr 1, s. 172-184Artikel i tidskrift (Refereegranskat)
    Abstract [en]

    To investigate the biological processes that are altered in obese subjects, we generated cell-specific integrated networks (INs) by merging genome-scale metabolic, transcriptional regulatory and protein-protein interaction networks. We performed genome-wide transcriptomics analysis to determine the global gene expression changes in the liver and three adipose tissues from obese subjects undergoing bariatric surgery and integrated these data into the cell-specific INs. We found dysregulations in mannose metabolism in obese subjects and validated our predictions by detecting mannose levels in the plasma of the lean and obese subjects. We observed significant correlations between plasma mannose levels, BMI, and insulin resistance (IR). We also measured plasma mannose levels of the subjects in two additional different cohorts and observed that an increased plasma mannose level was associated with IR and insulin secretion. We finally identified mannose as one of the best plasma metabolites in explaining the variance in obesity-independent IR.

  • 344.
    Lee, Sunjae
    et al.
    KTH, Centra, Science for Life Laboratory, SciLifeLab.
    Zhang, Cheng
    KTH, Centra, Science for Life Laboratory, SciLifeLab.
    Liu, Zhengtao
    KTH, Centra, Science for Life Laboratory, SciLifeLab.
    Klevstig, Martina
    Mukhopadhyay, Bani
    Bergentall, Mattias
    Cinar, Resat
    Ståhlman, Marcus
    Sikanic, Natasa
    KTH, Skolan för kemi, bioteknologi och hälsa (CBH), Proteinvetenskap.
    Park, Joshua K.
    Deshmukh, Sumit
    KTH, Skolan för kemi, bioteknologi och hälsa (CBH), Proteinvetenskap.
    Harzandi, Azadeh M.
    KTH, Centra, Science for Life Laboratory, SciLifeLab.
    Kuijpers, Tim
    KTH.
    Grotli, Morten
    Elsässer, Simon J.
    Piening, Brian D.
    Snyder, Michael
    Smith, Ulf
    Nielsen, Jens
    KTH, Centra, Science for Life Laboratory, SciLifeLab.
    Bäckhed, Fredrik
    Kunos, George
    Uhlén, Mathias
    KTH, Centra, Science for Life Laboratory, SciLifeLab.
    Boren, Jan
    Mardinoglu, Adil
    KTH, Centra, Science for Life Laboratory, SciLifeLab.
    Network analyses identify liver-specific targets for treating liver diseases2017Ingår i: Molecular Systems Biology, ISSN 1744-4292, E-ISSN 1744-4292Artikel i tidskrift (Refereegranskat)
    Abstract [en]

    We performed integrative network analyses to identify targets that can be used for effectively treating liver diseases with minimal side effects. We first generated co-expression networks (CNs) for 46 human tissues and liver cancer to explore the functional relationships between genes and examined the overlap between functional and physical interactions. Since increased de novo lipogenesis is a characteristic of nonalcoholic fatty liver disease (NAFLD) and hepatocellular carcinoma (HCC), we investigated the liver-specific genes co-expressed with fatty acid synthase (FASN). CN analyses predicted that inhibition of these liver-specific genes decreases FASN expression. Experiments in human cancer cell lines, mouse liver samples, and primary human hepatocytes validated our predictions by demonstrating functional relationships between these liver genes, and showing that their inhibition decreases cell growth and liver fat content. In conclusion, we identified liver-specific genes linked to NAFLD pathogenesis, such as pyruvate kinase liver and red blood cell (PKLR), or to HCC pathogenesis, such as PKLR, patatin-like phospholipase domain containing 3 (PNPLA3), and proprotein convertase subtilisin/kexin type 9 (PCSK9), all of which are potential targets for drug development.

    Ladda ner fulltext (pdf)
    fulltext
  • 345. Legrain, Pierre
    et al.
    Aebersold, Ruedi
    Archakov, Alexander
    Bairoch, Amos
    Bala, Kumar
    Beretta, Laura
    Bergeron, John
    Borchers, Christoph H.
    Corthals, Garry L.
    Costello, Catherine E.
    Deutsch, Eric W.
    Domon, Bruno
    Hancock, William
    He, Fuchu
    Hochstrasser, Denis
    Marko-Varga, Gyorgy
    Salekdeh, Ghasem Hosseini
    Sechi, Salvatore
    Snyder, Michael
    Srivastava, Sudhir
    Uhlén, Mathias
    KTH, Skolan för bioteknologi (BIO), Proteomik.
    Wu, Cathy H.
    Yamamoto, Tadashi
    Paik, Young-Ki
    Omenn, Gilbert S.
    The Human Proteome Project: Current State and Future Direction2011Ingår i: Molecular & Cellular Proteomics, ISSN 1535-9476, E-ISSN 1535-9484, Vol. 10, nr 7Artikel i tidskrift (Refereegranskat)
    Abstract [en]

    After the successful completion of the Human Genome Project, the Human Proteome Organization has recently officially launched a global Human Proteome Project (HPP), which is designed to map the entire human protein set. Given the lack of protein-level evidence for about 30% of the estimated 20,300 protein-coding genes, a systematic global effort will be necessary to achieve this goal with respect to protein abundance, distribution, subcellular localization, interaction with other biomolecules, and functions at specific time points. As a general experimental strategy, HPP research groups will use the three working pillars for HPP: mass spectrometry, antibody capture, and bioinformatics tools and knowledge bases. The HPP participants will take advantage of the output and cross-analyses from the ongoing Human Proteome Organization initiatives and a chromosome-centric protein mapping strategy, termed C-HPP, with which many national teams are currently engaged. In addition, numerous biologically driven and disease-oriented projects will be stimulated and facilitated by the HPP. Timely planning with proper governance of HPP will deliver a protein parts list, reagents, and tools for protein studies and analyses, and a stronger basis for personalized medicine. The Human Proteome Organization urges each national research funding agency and the scientific community at large to identify their preferred pathways to participate in aspects of this highly promising project in a HPP consortium of funders and investigators.

  • 346.
    Leitao, Charles Dahlsson
    et al.
    KTH, Skolan för kemi, bioteknologi och hälsa (CBH), Proteinvetenskap.
    Mestre Borras, Anna
    KTH, Skolan för kemi, bioteknologi och hälsa (CBH), Proteinvetenskap.
    Jonsson, Andreas
    KTH, Skolan för kemi, bioteknologi och hälsa (CBH), Proteinvetenskap.
    Malm, Magdalena
    KTH, Skolan för kemi, bioteknologi och hälsa (CBH), Proteinvetenskap, Proteinteknologi.
    Kronqvist, Nina
    KTH, Skolan för kemi, bioteknologi och hälsa (CBH), Proteinvetenskap.
    Fleetwood, Filippa
    KTH, Skolan för kemi, bioteknologi och hälsa (CBH), Proteinvetenskap, Proteinteknologi.
    Sandersjöö, Lisa
    Uhlén, Mathias
    KTH, Skolan för kemi, bioteknologi och hälsa (CBH), Proteinvetenskap, Systembiologi.
    Löfblom, John
    KTH, Skolan för kemi, bioteknologi och hälsa (CBH), Proteinvetenskap, Proteinvetenskap.
    Ståhl, Stefan
    KTH, Skolan för kemi, bioteknologi och hälsa (CBH), Proteinvetenskap.
    Lindberg, Hanna
    KTH, Skolan för kemi, bioteknologi och hälsa (CBH), Proteinvetenskap.
    Display of a naïve affibody library on staphylococci for selection of binders by means of flow cytometry sorting2023Ingår i: Biochemical and Biophysical Research Communications - BBRC, ISSN 0006-291X, E-ISSN 1090-2104, Vol. 655, s. 75-81Artikel i tidskrift (Refereegranskat)
    Abstract [en]

    Within the field of combinatorial protein engineering there is a great demand for robust high-throughput selection platforms that allow for unbiased protein library display, affinity-based screening, and amplification of selected clones. We have previously described the development of a staphylococcal display system used for displaying both alternative-scaffolds and antibody-derived pro-teins. In this study, the objective was to generate an improved expression vector for displaying and screening a high-complexity naive affibody library, and to facilitate downstream validation of isolated clones. A high-affinity normalization tag, consisting of two ABD-moieties, was introduced to simplify off-rate screening procedures. In addition, the vector was furnished with a TEV protease substrate recog-nition sequence upstream of the protein library which enables proteolytic processing of the displayed construct for improved binding signal. In the library design, 13 of the 58 surface-exposed amino acid positions were selected for full randomization (except proline and cysteine) using trinucleotide tech-nology. The genetic library was successfully transformed to Staphylococcus carnosus cells, generating a protein library exceeding 109 members. De novo selections against three target proteins (CD14, MAPK9 and the affibody ZEGFR:2377) were successfully performed using magnetic bead-based capture followed by flow-cytometric sorting, yielding affibody molecules binding their respective target with nanomolar affinity. Taken together, the results demonstrate the feasibility of the staphylococcal display system and the proposed selection procedure to generate new affibody molecules with high affinity.

  • 347. Li, J.
    et al.
    Newberg, J. Y.
    Uhlén, Mathias
    KTH, Skolan för bioteknologi (BIO), Proteomik. KTH, Centra, Science for Life Laboratory, SciLifeLab.
    Lundberg, Emma
    KTH, Skolan för bioteknologi (BIO), Proteomik. KTH, Centra, Science for Life Laboratory, SciLifeLab.
    Murphy, R. F.
    Automated Analysis and Reannotation of Subcellular Locations in Confocal Images from the Human Protein Atlas2012Ingår i: PLOS ONE, E-ISSN 1932-6203, Vol. 7, nr 11, s. e50514-Artikel i tidskrift (Refereegranskat)
    Abstract [en]

    The Human Protein Atlas contains immunofluorescence images showing subcellular locations for thousands of proteins. These are currently annotated by visual inspection. In this paper, we describe automated approaches to analyze the images and their use to improve annotation. We began by training classifiers to recognize the annotated patterns. By ranking proteins according to the confidence of the classifier, we generated a list of proteins that were strong candidates for reexamination. In parallel, we applied hierarchical clustering to group proteins and identified proteins whose annotations were inconsistent with the remainder of the proteins in their cluster. These proteins were reexamined by the original annotators, and a significant fraction had their annotations changed. The results demonstrate that automated approaches can provide an important complement to visual annotation.

  • 348.
    Li, Xiangyu
    et al.
    KTH, Skolan för kemi, bioteknologi och hälsa (CBH), Proteinvetenskap, Systembiologi. KTH, Centra, Science for Life Laboratory, SciLifeLab.
    Kim, Woonghee
    KTH, Skolan för kemi, bioteknologi och hälsa (CBH), Proteinvetenskap, Systembiologi. KTH, Centra, Science for Life Laboratory, SciLifeLab.
    Arif, Muhammad
    KTH, Skolan för kemi, bioteknologi och hälsa (CBH), Proteinvetenskap, Systembiologi. KTH, Centra, Science for Life Laboratory, SciLifeLab.
    Gao, Chunxia
    Univ Gothenburg, Dept Chem & Mol Biol, SE-41296 Gothenburg, Sweden..
    Hober, Andreas
    KTH, Skolan för kemi, bioteknologi och hälsa (CBH), Proteinvetenskap, Systembiologi. KTH, Centra, Science for Life Laboratory, SciLifeLab.
    Kotol, David
    KTH, Skolan för kemi, bioteknologi och hälsa (CBH), Proteinvetenskap, Systembiologi. KTH, Centra, Science for Life Laboratory, SciLifeLab.
    Strandberg, Linnéa
    KTH, Skolan för kemi, bioteknologi och hälsa (CBH), Proteinvetenskap, Systembiologi. KTH, Centra, Science for Life Laboratory, SciLifeLab.
    Forsström, Björn
    KTH, Skolan för kemi, bioteknologi och hälsa (CBH), Proteinvetenskap, Systembiologi. KTH, Centra, Science for Life Laboratory, SciLifeLab.
    Sivertsson, Åsa
    KTH, Skolan för kemi, bioteknologi och hälsa (CBH), Proteinvetenskap, Systembiologi. KTH, Centra, Science for Life Laboratory, SciLifeLab.
    Oksvold, Per
    KTH, Skolan för kemi, bioteknologi och hälsa (CBH), Proteinvetenskap, Systembiologi. KTH, Centra, Science for Life Laboratory, SciLifeLab.
    Turkez, Hasan
    Ataturk Univ, Dept Med Biol, Fac Med, TR-25240 Erzurum, Turkey..
    Grotli, Morten
    Univ Gothenburg, Dept Chem & Mol Biol, SE-41296 Gothenburg, Sweden..
    Sato, Yusuke
    Kyoto Univ, Inst Adv Study Human Biol WPI ASHBi, Dept Pathol & Tumor Biol, Kyoto 6068501, Japan.;Univ Tokyo, Grad Sch Med, Dept Urol, Tokyo 1138654, Japan..
    Kume, Haruki
    Univ Tokyo, Grad Sch Med, Dept Urol, Tokyo 1138654, Japan..
    Ogawa, Seishi
    Kyoto Univ, Inst Adv Study Human Biol WPI ASHBi, Dept Pathol & Tumor Biol, Kyoto 6068501, Japan.;Karolinska Inst, Dept Med, Ctr Hematol & Regenerat Med, SE-17177 Stockholm, Sweden..
    Boren, Jan
    Univ Gothenburg, Sahlgrenska Univ Hosp, Dept Mol & Clin Med, SE-41345 Gothenburg, Sweden..
    Nielsen, Jens
    Chalmers Univ Technol, Dept Biol & Biol Engn, SE-41296 Gothenburg, Sweden.;BioInnovat Inst, DK-2200 Copenhagen N, Denmark..
    Uhlén, Mathias
    KTH, Skolan för kemi, bioteknologi och hälsa (CBH), Proteinvetenskap, Systembiologi. KTH, Centra, Science for Life Laboratory, SciLifeLab.
    Zhang, Cheng
    KTH, Skolan för kemi, bioteknologi och hälsa (CBH), Proteinvetenskap, Systembiologi. KTH, Centra, Science for Life Laboratory, SciLifeLab. Zhengzhou Univ, Key Lab Adv Drug Preparat Technol, Sch Pharmaceut Sci, Minist Educ, Zhengzhou 450001, Peoples R China..
    Mardinoglu, Adil
    KTH, Skolan för kemi, bioteknologi och hälsa (CBH), Proteinvetenskap, Systembiologi. KTH, Centra, Science for Life Laboratory, SciLifeLab. Kings Coll London, Fac Dent Oral & Craniofacial Sci, Ctr Host Microbiome Interact, London SE1 9RT, England..
    Discovery of Functional Alternatively Spliced PKM Transcripts in Human Cancers2021Ingår i: Cancers, ISSN 2072-6694, Vol. 13, nr 2, artikel-id 348Artikel i tidskrift (Refereegranskat)
    Abstract [en]

    Simple Summary Pyruvate kinase muscle type (PKM) is a key enzyme in glycolysis and is a mediator of the Warburg effect in tumors. The association of PKM with survival of cancer patients is controversial. In this study, we investigated the associations of the alternatively spliced transcripts of PKM with cancer patients' survival outcomes and explained the conflicts in previous studies. We discovered three poorly studied alternatively spliced PKM transcripts that exhibited opposite prognostic indications in different human cancers based on integrative systems analysis. We also detected their protein products and explored their potential biological functions based on in-vitro experiments. Our analysis demonstrated that alternatively spliced transcripts of not only PKM but also other genes should be considered in cancer studies, since it may enable the discovery and targeting of the right protein product for development of the efficient treatment strategies. Pyruvate kinase muscle type (PKM) is a key enzyme in glycolysis and plays an important oncological role in cancer. However, the association of PKM expression and the survival outcome of patients with different cancers is controversial. We employed systems biology methods to reveal prognostic value and potential biological functions of PKM transcripts in different human cancers. Protein products of transcripts were shown and detected by western blot and mass spectrometry analysis. We focused on different transcripts of PKM and investigated the associations between their mRNA expression and the clinical survival of the patients in 25 different cancers. We find that the transcripts encoding PKM2 and three previously unstudied transcripts, namely ENST00000389093, ENST00000568883, and ENST00000561609, exhibited opposite prognostic indications in different cancers. Moreover, we validated the prognostic effect of these transcripts in an independent kidney cancer cohort. Finally, we revealed that ENST00000389093 and ENST00000568883 possess pyruvate kinase enzymatic activity and may have functional roles in metabolism, cell invasion, and hypoxia response in cancer cells. Our study provided a potential explanation to the controversial prognostic indication of PKM, and could invoke future studies focusing on revealing the biological and oncological roles of these alternative spliced variants of PKM.

  • 349.
    Li, Xiangyu
    et al.
    KTH, Centra, Science for Life Laboratory, SciLifeLab. Bash Biotech Inc, 600 West Broadway,Suite 700, San Diego, CA 92101 USA.
    Kim, Woonghee
    KTH, Centra, Science for Life Laboratory, SciLifeLab.
    Juszczak, Kajetan
    KTH, Centra, Science for Life Laboratory, SciLifeLab.
    Arif, Muhammad
    KTH, Centra, Science for Life Laboratory, SciLifeLab.
    Sato, Yusuke
    Kyoto Univ, Inst Adv Study Human Biol WPI ASHBi, Dept Pathol & Tumor Biol, Kyoto 6068501, Japan.;Univ Tokyo, Grad Sch Med, Dept Urol, Tokyo 1138654, Japan..
    Kume, Haruki
    Univ Tokyo, Grad Sch Med, Dept Urol, Tokyo 1138654, Japan..
    Ogawa, Seishi
    Kyoto Univ, Inst Adv Study Human Biol WPI ASHBi, Dept Pathol & Tumor Biol, Kyoto 6068501, Japan.;Karolinska Inst, Ctr Hematol & Regenerat Med, Dept Med, S-17177 Stockholm, Sweden..
    Turkez, Hasan
    Ataturk Univ, Fac Med, Dept Med Biol, TR-25240 Erzurum, Turkey..
    Boren, Jan
    Univ Gothenburg, Sahlgrenska Univ Hosp, Dept Mol & Clin Med, S-41345 Gothenburg, Sweden..
    Nielsen, Jens
    Chalmers Univ Technol, Dept Biol & Biol Engn, S-41296 Gothenburg, Sweden.;BioInnovat Inst, DK-2200 Copenhagen N, Denmark..
    Uhlén, Mathias
    KTH, Centra, Science for Life Laboratory, SciLifeLab.
    Zhang, Cheng
    KTH, Centra, Science for Life Laboratory, SciLifeLab. Zhengzhou Univ, Sch Pharmaceut Sci, Minist Educ, Key Lab Adv Drug Preparat Technol, Zhengzhou 450001, Peoples R China..
    Mardinoglu, Adil
    KTH, Centra, Science for Life Laboratory, SciLifeLab. Kings Coll London, Fac Dent Oral & Craniofacial Sci, Ctr Host Microbiome Interact, London SE1 9RT, England..
    Stratification of patients with clear cell renal cell carcinoma to facilitate drug repositioning2021Ingår i: iScience, ISSN 2589-0042, Vol. 24, nr 7, artikel-id 102722Artikel i tidskrift (Refereegranskat)
    Abstract [en]

    Clear cell renal cell carcinoma (ccRCC) is the most common histological type of kidney cancer and has high heterogeneity. Stratification of ccRCC is important since distinct subtypes differ in prognosis and treatment. Here, we applied a systems biology approach to stratify ccRCC into three molecular subtypes with different mRNA expression patterns and prognosis of patients. Further, we developed a set of biomarkers that could robustly classify the patients into each of the three subtypes and predict the prognosis of patients. Then, we reconstructed subtype-specific metabolic models and performed essential gene analysis to identify the potential drug targets. We identified four drug targets, including SOAT1, CRLS1, and ACACB, essential in all the three subtypes and GPD2, exclusively essential to subtype 1. Finally, we repositioned mitotane, an FDA-approved SOAT1 inhibitor, to treat ccRCC and showed that it decreased tumor cell viability and inhibited tumor cell growth based on in vitro experiments.

  • 350.
    Li, Xiangyu
    et al.
    KTH, Centra, Science for Life Laboratory, SciLifeLab. KTH, Skolan för kemi, bioteknologi och hälsa (CBH), Proteinvetenskap, Systembiologi. Bash Biotech Inc, 600 Est Broadway,Suite 700, San Diego, CA 92101 USA..
    Shong, Ko Eun
    KTH, Skolan för kemi, bioteknologi och hälsa (CBH), Proteinvetenskap, Systembiologi. KTH, Centra, Science for Life Laboratory, SciLifeLab.
    Kim, Woonghee
    KTH, Skolan för kemi, bioteknologi och hälsa (CBH), Proteinvetenskap, Systembiologi. KTH, Centra, Science for Life Laboratory, SciLifeLab.
    Yuan, Meng
    KTH, Centra, Science for Life Laboratory, SciLifeLab. KTH, Skolan för kemi, bioteknologi och hälsa (CBH), Proteinvetenskap, Systembiologi.
    Yang, Hong
    KTH, Centra, Science for Life Laboratory, SciLifeLab. KTH, Skolan för kemi, bioteknologi och hälsa (CBH), Proteinvetenskap, Systembiologi.
    Sato, Yusuke
    Kyoto Univ, Inst Adv Study Human Biol WPI ASHBi, Dept Pathol & Tumor Biol, Kyoto 6068501, Japan.;Univ Tokyo, Grad Sch Med, Dept Urol, Tokyo 1138654, Japan..
    Kume, Haruki
    Univ Tokyo, Grad Sch Med, Dept Urol, Tokyo 1138654, Japan..
    Ogawa, Seishi
    Kyoto Univ, Inst Adv Study Human Biol WPI ASHBi, Dept Pathol & Tumor Biol, Kyoto 6068501, Japan.;Karolinska Inst, Dept Med, Ctr Hematol & Regenerat Med, SE-17177 Stockholm, Sweden..
    Turkez, Hasan
    Ataturk Univ, Fac Med, Dept Med Biol, TR-25240 Erzurum, Turkey..
    Shoaie, Saeed
    KTH, Centra, Science for Life Laboratory, SciLifeLab. KTH, Skolan för kemi, bioteknologi och hälsa (CBH), Proteinvetenskap, Systembiologi. Kings Coll London, Fac Dent Oral & Craniofacial Sci, Ctr Host Microbiome Interact, London SE1 9RT, England..
    Boren, Jan
    Univ Gothenburg, Sahlgrenska Univ Hosp, Dept Mol & Clin Med, SE-41345 Gothenburg, Sweden..
    Nielsen, Jens
    Chalmers Univ Technol, Dept Biol & Biol Engn, SE-41296 Gothenburg, Sweden.;BioInnovat Inst, DK-2200 Copenhagen N, Denmark..
    Uhlén, Mathias
    KTH, Centra, Science for Life Laboratory, SciLifeLab. KTH, Skolan för kemi, bioteknologi och hälsa (CBH), Proteinvetenskap, Systembiologi.
    Zhang, Cheng
    KTH, Centra, Science for Life Laboratory, SciLifeLab. KTH, Skolan för kemi, bioteknologi och hälsa (CBH), Proteinvetenskap, Systembiologi. Zhengzhou Univ, Minist Educ, Sch Pharmaceut Sci, Key Lab Adv Drug Preparat Technol, Zhengzhou 450001, Peoples R China..
    Mardinoglu, Adil
    KTH, Centra, Science for Life Laboratory, SciLifeLab. KTH, Skolan för kemi, bioteknologi och hälsa (CBH), Proteinvetenskap, Systembiologi. Kings Coll London, Fac Dent Oral & Craniofacial Sci, Ctr Host Microbiome Interact, London SE1 9RT, England..
    Prediction of drug candidates for clear cell renal cell carcinoma using a systems biology-based drug repositioning approach2022Ingår i: EBioMedicine, E-ISSN 2352-3964, Vol. 78, s. 103963-, artikel-id 103963Artikel i tidskrift (Refereegranskat)
    Abstract [en]

    Summary

    Background: The response rates of the clinical chemotherapies are still low in clear cell renal cell carcinoma (ccRCC). Computational drug repositioning is a promising strategy to discover new uses for existing drugs to treat patients who cannot get benefits from clinical drugs.

    Methods: We proposed a systematic approach which included the target prediction based on the co-expression network analysis of transcriptomics profiles of ccRCC patients and drug repositioning for cancer treatment based on the analysis of shRNA-and drug-perturbed signature profiles of human kidney cell line.

    Findings: First, based on the gene co-expression network analysis, we identified two types of gene modules in ccRCC, which significantly enriched with unfavorable and favorable signatures indicating poor and good survival outcomes of patients, respectively. Then, we selected four genes, BUB1B, RRM2, ASF1B and CCNB2, as the potential drug targets based on the topology analysis of modules. Further, we repurposed three most effective drugs for each target by applying the proposed drug repositioning approach. Finally, we evaluated the effects of repurposed drugs using an in vitro model and observed that these drugs inhibited the protein levels of their corresponding target genes and cell viability.

    Interpretation: These findings proved the usefulness and efficiency of our approach to improve the drug repositioning researches for cancer treatment and precision medicine.

    Funding: This study was funded by Knut and Alice Wallenberg Foundation and Bash Biotech Inc., San Diego, CA, USA. 

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