Lukas Orre

Lukas Orre

Principal Researcher | Docent
Visiting address: SciLifeLab, Tomtebodavägen 23A, 17121 Solna
Postal address: K7 Onkologi-Patologi, K7 Forskning Lehtiö, 171 77 Stockholm


  • Lung Cancer and Personalized Medicine
    Lung cancer is by far the deadliest form of cancer and in many cases there
    are no available therapeutic options for patients with this disease. Targeted
    therapies that inhibit growth factor signaling in lung cancer raised hope for
    improved patient survival, but ten years after approval it is evident that
    monotherapy with these agents will only delay disease progression by a few
    months and in addition only in a small subset of patients.
    It is becoming increasingly appreciated that the reasons for this lack of
    efficacy is that cancer is a heterogeneous disease. This is displayed in two
    ways. First, the molecular paths to lung cancer are not the same in different
    patients. This means that different patients will have different molecular
    drivers of their cancer and consequently they should be treated in different
    ways i.e. we should personalize the therapy. Second, the tumor cells that
    together build up a tumor in a patient are also heterogeneous i.e. each tumor
    is composed of several different clones of cells that can differ in mutation
    spectrum and cell type. These different cells within a single tumor will also
    respond differently to cancer therapy. A drug that efficiently kills one type
    of cells in the tumor can still leave other cancer cells unaffected. To
    efficiently kill all cancer cells within a tumor and ultimately cure the
    patient we need to combine several types of therapy.
    In order to personalize cancer therapy and identify efficient therapy
    combinations we need biomarkers that can be used to predict if a specific
    type of therapy will be efficient in a specific patient. Once identified, the
    presence of these biomarkers can be measured in the tumor of a patient, and
    this information can then be used for rational selection of therapy.
    The general aim of my research is to identify novel biomarkers and targets
    for cancer therapy to improve the treatment of lung cancer. To accomplish
    this I am developing and applying advanced methods as described below to
    study the effects of cancer therapy on cancer cells. By reading out the
    molecular response of cancer cells to different drugs in great detail we can
    identify the determinants of drug response or drug resistance, and use this
    information to suggest biomarkers and drug combinations for improved lung
    cancer therapy.
    Functional Proteomics and Systems Biology
    The expression, and functions of proteins in a cell is what determines the
    phenotype, i.e. the characteristics of the cell. For example the expression
    and functional activity of proteins in a cell will determine if a cell is
    cancerous or not, and whether a cancer cell is sensitive for a specific type
    of treatment. Proteomics is the large-scale study of proteins in biological
    systems, or in other words methods that aim to comprehensively describe the
    protein landscape of a biological sample. The proteomics concept can be
    further developed into functional proteomics where the ambition is to also
    describe the functional state of proteins in large-scale experiments.
    /In depth mass spectrometry based proteomics/
    In our lab we use high-resolution orbitrap mass spectrometers to identify and
    quantify thousands of proteins in biological samples. More specifically, we
    have developed a method, HiRIEF-LC-MS (Nature Methods 2014) that allows us to
    study more than 10 000 unique proteins and their regulation in response to
    treatment in a single experiment. This analytical depth gives us the
    possibility to describe the molecular response of cancer cells to cancer
    therapy in great detail, which is essential to understand the effects of the
    The activity of a protein is not only determined by the abundance of the
    protein. Since it is important for a cell to tightly regulate all cellular
    processes, the proteins are equipped with “molecular switches” that turn
    on or off certain functions of the proteins. This regulation is performed by
    adding or removing functional groups to the proteins in processes referred to
    as protein post-translational modification (PTM). The most well characterized
    type of PTM is protein phosphorylation and the phosphorylation pattern of
    proteins in cancer cells are commonly disturbed, which can result in for
    example increased cell proliferation or decreased apoptosis (cell death).
    Many targeted cancer therapies are aiming to restore the phosphorylation
    pattern in cancer cells to stop the uncontrolled cell growth and induce cell
    death. To fully understand the consequences of targeted therapies, it is
    therefor important to study changes in protein phosphorylation in response to
    treatment. In our lab we are setting up methods to specifically study protein
    phosphorylation, and these methods are then applied to analyze the effects of
    treatment on the phospho-proteome.
    Protein subcellular localization and relocalization
    The functions and activities of proteins are also determined by their
    specific localization in the cell. A protein can have one type of function
    when localized in the nucleus, and a completely different function when
    localized in the cytoplasm. More common maybe is that a protein is active
    when it is residing in one subcellular compartment and inactive when
    sequestered in another. Treatment of cells with different types of drugs will
    alter the subcellular localization of proteins, i.e. induce protein
    relocalization, which will alter the function of affected proteins.
    Currently, large-scale methods to study protein localization and
    relocalization are lacking. We are developing methods to comprehensively
    study the localization of proteins in cells, and these methods will be used
    to understand how proteins shuttle between different subcellular compartments
    in response to cancer therapy, and ultimately how this affects the drug
    Systems Biology
    Systems biology is the combination of different levels of biological
    information in order to see the full picture. In practice this means that we
    merge the information generated by several different types of experiments
    used to study the same biological question. The data included in our systems
    biology analysis is generated by the proteomics methods described above, but
    we also include data describing the transcriptional activity of cancer cells
    in response to treatment (mRNA-level analysis) as well as the genomic
    background of the cells (DNA-level analysis). All this data is then used in
    concert to understand why the cancer cells from different tumors respond
    differently to cancer drugs. Ultimately this knowledge will help us tailor
    the best cancer therapy to each lung cancer patient with the ambition to cure
    him or her from the disease.

    Selected publications:

    Brunner A, Li Q, Fisicaro S, Kourtesakis A, Viiliäinen J, Johansson HJ, Pandey V, Mayank AK, Lehtiö J, Wohlschlegel JA, Spruck C, Rantala JK,  

  • Orre LM, Sangfelt O. 
  • FBXL12 degrades FANCD2 to regulate replication recovery and promote cancer cell 
  • survival under conditions of replication stress. 
  • Molecular Cell. 2023 Oct 19
  • 83(20):3720-3739.e8. PMID: 37591242


  • Taner Arslan, Yanbo Pan, Georgios Mermelekas, Mattias Vesterlund, Lukas M. Orre 

  • and Janne Lehtiö. SubCellBarCode: integrated workflow for robust spatial proteomics 
  • by mass spectrometry. Nature Protocols. 2022 Aug
  • 17(8):1832-1867. PMID: 35732783

    Janne Lehtiö, Taner Arslan, Ioannis Siavelis, Yanbo Pan, Fabio Socciarelli, Olena Berkovska, Husen M. Umer, Georgios Mermelekas, Mohammad Pirmoradian, Mats Jönsson, Hans Brunnström, Odd Terje Brustugun, Krishna Pinganksha Purohit, Richard Cunningham, Hassan Foroughi Asl, Sofi Isaksson, Elsa Arbajian, Mattias Aine, Anna Karlsson, Marija Kotevska, Carsten Gram Hansen, Vilde Drageset Haakensen, Åslaug Helland, David Tamborero, Henrik J. Johansson, Rui M. Branca, Maria Planck, Johan Staaf, and 

  • Lukas M. Orre. Proteogenomics of non-small cell lung cancer reveals molecular subtypes associated with specific therapeutic targets and immune evasion mechanisms. Nature Cancer. 2021 Nov 22 (2), 1224–1242. PMID: 34870237


  • Zhou Tran Y, Minozada R, Cao X, Johansson HJ, Branca RM, Seashore-Ludlow B and 

  • Orre LM. Immediate Adaptation Analysis Implicates BCL6 as an EGFR-TKI Combination Therapy Target in NSCLC. 
  • Mol Cell Proteomics. 2020 Jun
  • 19(6):928-943. PMID: 32234966


  • Fotouhi O, Kjellin H, Juhlin CC, Pan Y, Vesterlund M, Ghaderi M, Yousef A, Andersson-Sand H, Kharaziha P, Caramuta S, Kjellman M, Zedenius J, Larsson C and 

  • Orre LM. Proteomics identifies neddylation as a potential therapy target in small intestinal neuroendocrine tumors. 
  • Oncogene. 2019 

  • Oct
  • 38(43):6881-6897. PMID: 31406256


  • Johansson HJ, Socciarelli F, Vacanti NM, Haugen MH, Zhu Y, Siavelis I, Fernandez-Woodbridge A, Aure MR, Sennblad B, Vesterlund M, Branca RM,  

  • Orre LM, Huss M, Fredlund E, Beraki E, Garred Ø, Boekel J, Sauer T, Zhao W, Nord S, Höglander EK, Jans DC, Brismar H, Haukaas TH, Bathen TF, Schlichting E, Naume B
  • Consortia Oslo Breast Cancer Research Consortium (OSBREAC), Luders T, Borgen E, Kristensen VN, Russnes HG, Lingjærde OC, Mills GB, Sahlberg KK, Børresen-Dale AL, Lehtiö J. Breast cancer quantitative proteome and proteogenomic landscape. 
  • Nature Communications. 2019 Apr 8
  • 10(1):1600. PMID: 30962452


  • Orre LM, Vesterlund M, Pan Y, Arslan T, Zhu Y, Fernandez Woodbridge A, Frings O, Fredlund E, Lehtiö J. SubCellBarCode: Proteome-wide Mapping of 

  • Protein Localization and Relocalization. Molecular Cell. 2019 Jan 3
  • 73(1):166-182.e7. PMID: 30609389


  • Wei B, Jolma A, Sahu B, Orre LM, Zhong F, Zhu F, Kivioja T, Sur I, Lehtiö J, Taipale M, Taipale J. A protein activity assay to measure global transcription factor activity reveals determinants of chromatin accessibility. 

  • Nature Biotechnology. 2018 Jul
  • 36(6):521-529. PMID: 29786094


  • Zhu Y, Orre LM, Johansson HJ, Huss M, Boekel J, Vesterlund M, Fernandez-Woodbridge A, Branca RMM, Lehtiö J. Discovery of coding regions in 

  • the human genome by integrated proteogenomics analysis workflow. Nature Communications. 2018 Mar 2
  • 9(1):903. PMID: 29500430


  • Zhou Y, Frings O, Branca RM, Boekel J, le Sage C, Fredlund E, Agami R and Orre LM. microRNAs with AAGUGC seed motif constitute an integral part of an oncogenic signaling network. 

  • Oncogene. 2017 Feb 9
  • 36(6):731-745. PMID: 27477696


  • Branca RM, Orre LM, Johansson HJ, Granholm V, Huss M, Pérez-Bercoff Å, Forshed J, Käll L, Lehtiö J. HiRIEF LC-MS enables deep proteome coverage and unbiased proteogenomics. 

  • Nature Methods. 2014 Jan
  • 11 (1): 59-62. PMID: 24240322


All other publications


  • Principal Researcher, Department of Oncology-Pathology, Karolinska Institutet, 2022-

Degrees and Education

  • Docent, Karolinska Institutet, 2022
  • Degree Of Doctor Of Philosophy, Department of Oncology-Pathology, Karolinska Institutet, 2008

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