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  • 1.
    Abdellah, Tebani
    et al.
    KTH, Centres, Science for Life Laboratory, SciLifeLab. KTH, School of Engineering Sciences in Chemistry, Biotechnology and Health (CBH), Protein Science, Systems Biology. Normandie Univ, Dept Metab Biochem, UNIROUEN, INSERM,U1245,CHU Rouen, F-76000 Rouen, France..
    Jotanovic, Jelena
    Uppsala Univ, Dept Immunol Genet & Pathol, Uppsala, Sweden.;Uppsala Univ Hosp, Dept Clin Pathol, Uppsala, Sweden..
    Hekmati, Neda
    Uppsala Univ, Dept Immunol Genet & Pathol, Uppsala, Sweden..
    Sivertsson, Åsa
    KTH, Centres, Science for Life Laboratory, SciLifeLab. KTH, School of Engineering Sciences in Chemistry, Biotechnology and Health (CBH), Protein Science.
    Gudjonsson, Olafur
    Uppsala Univ, Dept Neurosci, Uppsala, Sweden..
    Engstrom, Britt Eden
    Uppsala Univ, Dept Med Sci Endocrinol & Mineral Metab, Uppsala, Sweden..
    Wikstrom, Johan
    Uppsala Univ, Dept Surg Sci, Neuroradiol, Uppsala, Sweden..
    Uhlén, Mathias
    KTH, Centres, Science for Life Laboratory, SciLifeLab. KTH, School of Engineering Sciences in Chemistry, Biotechnology and Health (CBH), Protein Science, Systems Biology.
    Casar-Borota, Olivera
    Uppsala Univ, Dept Immunol Genet & Pathol, Uppsala, Sweden.;Uppsala Univ Hosp, Dept Clin Pathol, Uppsala, Sweden..
    Ponten, Fredrik
    Uppsala Univ, Dept Immunol Genet & Pathol, Uppsala, Sweden..
    Annotation of pituitary neuroendocrine tumors with genome-wide expression analysis2021In: Acta neuropathologica communications, E-ISSN 2051-5960, Vol. 9, no 1, article id 181Article in journal (Refereed)
    Abstract [en]

    Pituitary neuroendocrine tumors (PitNETs) are common, generally benign tumors with complex clinical characteristics related to hormone hypersecretion and/or growing sellar tumor mass. PitNETs can be classified based on the expression pattern of anterior pituitary hormones and three main transcriptions factors (TF), SF1, PIT1 and TPIT that regulate differentiation of adenohypophysial cells. Here, we have extended this classification based on the global transcriptomics landscape using tumor tissue from a well-defined cohort comprising 51 PitNETs of different clinical and histological types. The molecular profiles were compared with current classification schemes based on immunohistochemistry. Our results identified three main clusters of PitNETs that were aligned with the main pituitary TFs expression patterns. Our analyses enabled further identification of specific genes and expression patterns, including both known and unknown genes, that could distinguish the three different classes of PitNETs. We conclude that the current classification of PitNETs based on the expression of SF1, PIT1 and TPIT reflects three distinct subtypes of PitNETs with different underlying biology and partly independent from the expression of corresponding hormones. The transcriptomic analysis reveals several potentially targetable tumor-driving genes with previously unknown role in pituitary tumorigenesis.

  • 2.
    Abouzayed, Ayman
    et al.
    Uppsala Univ, Dept Med Chem, S-75183 Uppsala, Sweden..
    Borin, Jesper
    KTH, School of Engineering Sciences in Chemistry, Biotechnology and Health (CBH), Protein Science, Protein Technology.
    Lundmark, Fanny
    Uppsala Univ, Dept Med Chem, S-75183 Uppsala, Sweden..
    Rybina, Anastasiya
    Russian Acad Sci, Canc Res Inst, Tomsk Natl Res Med Ctr, Dept Nucl Med, Tomsk 634009, Russia.;Tomsk Polytech Univ, Res Sch Chem & Appl Biomed Sci, Res Ctr Oncotheranost, Tomsk 634050, Russia..
    Hober, Sophia
    KTH, School of Engineering Sciences in Chemistry, Biotechnology and Health (CBH), Protein Science.
    Zelchan, Roman
    Russian Acad Sci, Canc Res Inst, Tomsk Natl Res Med Ctr, Dept Nucl Med, Tomsk 634009, Russia.;Tomsk Polytech Univ, Res Sch Chem & Appl Biomed Sci, Res Ctr Oncotheranost, Tomsk 634050, Russia..
    Tolmachev, Vladimir
    Uppsala Univ, Dept Immunol Genet & Pathol, S-75237 Uppsala, Sweden..
    Chernov, Vladimir
    Russian Acad Sci, Canc Res Inst, Tomsk Natl Res Med Ctr, Dept Nucl Med, Tomsk 634009, Russia..
    Orlova, Anna
    Uppsala Univ, Dept Med Chem, S-75183 Uppsala, Sweden.;Uppsala Univ, Sci Life Lab, S-75237 Uppsala, Sweden..
    The GRPR Antagonist [Tc-99m]Tc-maSSS-PEG(2)-RM26 towards Phase I Clinical Trial: Kit Preparation, Characterization and Toxicity2023In: Diagnostics, ISSN 2075-4418, Vol. 13, no 9, p. 1611-, article id 1611Article in journal (Refereed)
    Abstract [en]

    Gastrin-releasing peptide receptors (GRPRs) are overexpressed in the majority of primary prostate tumors and in prostatic lymph node and bone metastases. Several GRPR antagonists were developed for SPECT and PET imaging of prostate cancer. We previously reported a preclinical evaluation of the GRPR antagonist [Tc-99m]Tc-maSSS-PEG2-RM26 (based on [D-Phe(6), Sta(13), Leu(14)-NH2]BBN(6-14)) which bound to GRPR with high affinity and had a favorable biodistribution profile in tumor-bearing animal models. In this study, we aimed to prepare and test kits for prospective use in an early-phase clinical study. The kits were prepared to allow for a one-pot single-step radiolabeling with technetium-99m pertechnetate. The kit vials were tested for sterility and labeling efficacy. The radiolabeled by using the kit GRPR antagonist was evaluated in vitro for binding specificity to GRPR on PC-3 cells (GRPR-positive). In vivo, the toxicity of the kit constituents was evaluated in rats. The labeling efficacy of the kits stored at 4 degrees C was monitored for 18 months. The biological properties of [Tc-99m]Tc-maSSS-PEG2-RM26, which were obtained after this period, were examined both in vitro and in vivo. The one-pot (gluconic acid, ethylenediaminetetraacetic acid, stannous chloride, and maSSS-PEG(2)-RM26) single-step radiolabeling with technetium-99m was successful with high radiochemical yields (>97%) and high molar activities (16-24 MBq/nmol). The radiolabeled peptide maintained its binding properties to GRPR. The kit constituents were sterile and non-toxic when tested in living subjects. In conclusion, the prepared kit is considered safe in animal models and can be further evaluated for use in clinics.

  • 3.
    Acharjee, Animesh
    et al.
    Univ Birmingham, Coll Med & Dent Sci, Inst Canc & Genom Sci, Birmingham B15 2TT, W Midlands, England.;Fdn Trust, Univ Hosp Birmingham NHS, Inst Translat Med, Birmingham B15 2TT, W Midlands, England.;Univ Hosp Birmingham, NIHR Surg Reconstruct & Microbiol Res Ctr, Birmingham B15 2WB, W Midlands, England..
    Agarwal, Prasoon
    KTH, School of Electrical Engineering and Computer Science (EECS), Computer Science, Computational Science and Technology (CST).
    Nash, Katrina
    Univ Birmingham, Coll Med & Dent Sci, Birmingham B15 2TT, W Midlands, England..
    Bano, Subia
    Elvesys Microfluid Innovat Ctr, F-75011 Paris, France..
    Rahmans, Taufiq
    Univ Cambridge, Dept Pharmacol, Tennis Court Rd, Cambridge CB2 1PD, England..
    Gkoutos, Georgios, V
    Univ Birmingham, Coll Med & Dent Sci, Inst Canc & Genom Sci, Birmingham B15 2TT, W Midlands, England.;Fdn Trust, Univ Hosp Birmingham NHS, Inst Translat Med, Birmingham B15 2TT, W Midlands, England.;Univ Hosp Birmingham, NIHR Surg Reconstruct & Microbiol Res Ctr, Birmingham B15 2WB, W Midlands, England.;MRC Hlth Data Res UK HDR UK, London, England.;NIHR Expt Canc Med Ctr, Birmingham B15 2TT, W Midlands, England.;Univ Hosp Birmingham, NIHR Biomed Res Ctr, Birmingham B15 2TT, W Midlands, England..
    Immune infiltration and prognostic and diagnostic use of LGALS4 in colon adenocarcinoma and bladder urothelial carcinoma2021In: American Journal of Translational Research, E-ISSN 1943-8141, Vol. 13, no 10, p. 11353-11363Article in journal (Refereed)
    Abstract [en]

    Colon adenocarcinoma (COAD) is a common tumor of the gastrointestinal tract with a high mortality rate. Current research has identified many genes associated with immune infiltration that play a vital role in the development of COAD. In this study, we analysed the prognostic and diagnostic features of such immune-related genes in the context of colonic adenocarcinoma (COAD). We analysed 17 overlapping gene expression profiles of COAD and healthy samples obtained from TCGA-COAD and public single-cell sequencing resources, to identify potential therapeutic COAD targets. We evaluated the abundance of immune infiltration with those genes using the TIMER (Tumor Immune Estimation Resource) deconvolution method. Subsequently, we developed predictive and survival models to assess the prognostic value of these genes. The LGALS4 (Galectin-4) gene was found to be significantly (P<0.05) downregulated in COAD and bladder urothelial carcinoma (BLCA) compared to healthy samples. We identified LGALS4 as a prognostic and diagnostic marker for multiple cancer types, including COAD and BLCA. Our analysis reveals a series of novel candidate drug targets, as well as candidate molecular markers, that may explain the pathogenesis of COAD and BLCA. LGALS4 gene is associated with multiple cancer types and is a possible prognostic, as well as diagnostic, marker of COAD and BLCA.

  • 4. Alkharusi, Amira
    et al.
    Yu, Shengze
    KTH, School of Biotechnology (BIO).
    Landazuri, Natalia
    Zadjali, Fahad
    Davodi, Belghis
    Nystrom, Thomas
    Gräslund, Torbjörn
    KTH, School of Biotechnology (BIO), Protein Technology.
    Rahbar, Afsar
    Norstedt, Gunnar
    Stimulation of prolactin receptor induces STAT-5 phosphorylation and cellular invasion in glioblastoma multiforme2016In: Oncotarget, E-ISSN 1949-2553, Vol. 7, no 48, p. 79558-79569Article in journal (Refereed)
    Abstract [en]

    Glioblastoma multiforme (GBM) is the most common and aggressive primary brain tumor in humans and is characterized with poor outcome. In this study, we investigated components of prolactin (Prl) system in cell models of GBM and in histological tissue sections obtained from GBM patients. Expression of Prolactin receptor (PrlR) was detected at high levels in U251-MG, at low levels in U87-MG and barely detectable in U373 cell lines and in 66% of brain tumor tissues from 32 GBM patients by immunohistochemical technique. In addition, stimulation of U251-MG and U87-MG cells but not U373 with Prl resulted in increased STAT5 phosphorylation and only in U251-MG cells with increased cellular invasion. Furthermore, STAT5 phosphorylation and cellular invasion induced in Prl stimulated cells were significantly reduced by using a Prl receptor antagonist that consists of Prl with four amino acid replacements. We conclude that Prl receptor is expressed at different levels in the majority of GBM tumors and that blocking of PrlR in U251-MG cells significantly reduce cellular invasion.

  • 5.
    Alvez, Maria Bueno
    et al.
    KTH, Centres, Science for Life Laboratory, SciLifeLab. KTH, School of Engineering Sciences in Chemistry, Biotechnology and Health (CBH), Protein Science, Systems Biology.
    Edfors, Fredrik
    KTH, Centres, Science for Life Laboratory, SciLifeLab. KTH, School of Engineering Sciences in Chemistry, Biotechnology and Health (CBH), Protein Science, Systems Biology.
    von Feilitzen, Kalle
    KTH, School of Engineering Sciences in Chemistry, Biotechnology and Health (CBH), Protein Science, Systems Biology. KTH, Centres, Science for Life Laboratory, SciLifeLab.
    Zwahlen, Martin
    KTH, Centres, Science for Life Laboratory, SciLifeLab. KTH, School of Engineering Sciences in Chemistry, Biotechnology and Health (CBH), Protein Science, Systems Biology.
    Mardinoglu, Adil
    KTH, Centres, Science for Life Laboratory, SciLifeLab. KTH, School of Engineering Sciences in Chemistry, Biotechnology and Health (CBH), Protein Science, Systems Biology. Centre for Host-Microbiome Interactions, Faculty of Dentistry, Oral & Craniofacial Sciences, King’s College London, London, SE1 9RT, UK.
    Edqvist, Per Henrik
    Department of Immunology, Genetics and Pathology, Uppsala University, Uppsala, Sweden.
    Sjöblom, Tobias
    Department of Immunology, Genetics and Pathology, Uppsala University, Uppsala, Sweden.
    Lundin, Emma
    Department of Immunology, Genetics and Pathology, Uppsala University, Uppsala, Sweden.
    Rameika, Natallia
    Department of Immunology, Genetics and Pathology, Uppsala University, Uppsala, Sweden.
    Enblad, Gunilla
    Department of Immunology, Genetics and Pathology, Uppsala University, Uppsala, Sweden.
    Lindman, Henrik
    Department of Immunology, Genetics and Pathology, Uppsala University, Uppsala, Sweden.
    Höglund, Martin
    Department of Medical Sciences, Uppsala University, Uppsala, Sweden.
    Hesselager, Göran
    Department of Medical Sciences, Uppsala University, Uppsala, Sweden.
    Stålberg, Karin
    Department of Women’s and Children’s Health, Uppsala University, Uppsala, Sweden.
    Enblad, Malin
    Department of Surgical Sciences, Uppsala University, Uppsala, Sweden.
    Simonson, Oscar E.
    Department of Surgical Sciences, Uppsala University, Uppsala, Sweden.
    Häggman, Michael
    Department of Surgical Sciences, Uppsala University, Uppsala, Sweden.
    Axelsson, Tomas
    Department of Medical Sciences, Uppsala University, Uppsala, Sweden.
    Åberg, Mikael
    Department of Medical Sciences, Clinical Chemistry and SciLifeLab Affinity Proteomics, Uppsala University, Uppsala, Sweden.
    Nordlund, Jessica
    Department of Medical Sciences, Uppsala University, Uppsala, Sweden.
    Zhong, Wen
    Science for Life Laboratory, Department of Biomedical and Clinical Sciences (BKV), Linköping University, Linköping, Sweden.
    Karlsson, Max
    KTH, School of Engineering Sciences in Chemistry, Biotechnology and Health (CBH), Protein Science, Systems Biology. KTH, Centres, Science for Life Laboratory, SciLifeLab.
    Gyllensten, Ulf
    Department of Immunology, Genetics and Pathology, Uppsala University, Uppsala, Sweden.
    Ponten, Fredrik
    Department of Immunology, Genetics and Pathology, Uppsala University, Uppsala, Sweden.
    Fagerberg, Linn
    KTH, Centres, Science for Life Laboratory, SciLifeLab. KTH, School of Engineering Sciences in Chemistry, Biotechnology and Health (CBH), Protein Science, Systems Biology.
    Uhlén, Mathias
    KTH, Centres, Science for Life Laboratory, SciLifeLab. KTH, School of Engineering Sciences in Chemistry, Biotechnology and Health (CBH), Protein Science, Systems Biology. Department of Neuroscience, Karolinska Institutet, Stockholm, Sweden.
    Next generation pan-cancer blood proteome profiling using proximity extension assay2023In: Nature Communications, E-ISSN 2041-1723, Vol. 14, no 1, article id 4308Article in journal (Refereed)
    Abstract [en]

    A comprehensive characterization of blood proteome profiles in cancer patients can contribute to a better understanding of the disease etiology, resulting in earlier diagnosis, risk stratification and better monitoring of the different cancer subtypes. Here, we describe the use of next generation protein profiling to explore the proteome signature in blood across patients representing many of the major cancer types. Plasma profiles of 1463 proteins from more than 1400 cancer patients are measured in minute amounts of blood collected at the time of diagnosis and before treatment. An open access Disease Blood Atlas resource allows the exploration of the individual protein profiles in blood collected from the individual cancer patients. We also present studies in which classification models based on machine learning have been used for the identification of a set of proteins associated with each of the analyzed cancers. The implication for cancer precision medicine of next generation plasma profiling is discussed.

  • 6.
    Andersson, Alma
    et al.
    KTH, School of Engineering Sciences in Chemistry, Biotechnology and Health (CBH), Gene Technology. KTH, Centres, Science for Life Laboratory, SciLifeLab.
    Larsson, Ludvig
    KTH, School of Engineering Sciences in Chemistry, Biotechnology and Health (CBH), Gene Technology. KTH, Centres, Science for Life Laboratory, SciLifeLab.
    Stenbeck, Linnea
    KTH, School of Engineering Sciences in Chemistry, Biotechnology and Health (CBH), Gene Technology. KTH, Centres, Science for Life Laboratory, SciLifeLab.
    Salmén, Fredrik
    KTH, Centres, Science for Life Laboratory, SciLifeLab. KTH, School of Engineering Sciences in Chemistry, Biotechnology and Health (CBH), Gene Technology. Hubrecht Inst KNAW Royal Netherlands Acad Arts &, Utrecht, Netherlands.;Univ Med Ctr Utrecht, Canc Genom Netherlands, Utrecht, Netherlands..
    Ehinger, Anna
    Dept Genet & Pathol, Lab Med Reg Sane, Lund, Sweden.;Lund Univ, Dept Clin Sci Lund, Div Oncol, Lund, Sweden..
    Wu, Sunny Z.
    Garvan Inst Med Res, Kinghorn Canc Ctr, Sydney, NSW, Australia.;St Vincents Clin Sch, Fac Med, Sydney, NSW, Australia..
    Al-Eryani, Ghamdan
    Garvan Inst Med Res, Kinghorn Canc Ctr, Sydney, NSW, Australia.;St Vincents Clin Sch, Fac Med, Sydney, NSW, Australia..
    Roden, Daniel
    Garvan Inst Med Res, Kinghorn Canc Ctr, Sydney, NSW, Australia.;St Vincents Clin Sch, Fac Med, Sydney, NSW, Australia..
    Swarbrick, Alex
    Garvan Inst Med Res, Kinghorn Canc Ctr, Sydney, NSW, Australia.;St Vincents Clin Sch, Fac Med, Sydney, NSW, Australia..
    Borg, Ake
    Lund Univ, Dept Clin Sci Lund, Div Oncol, Lund, Sweden..
    Frisen, Jonas
    Karolinska Inst, Dept Cell & Mol Biol, Stockholm, Sweden..
    Engblom, Camilla
    Karolinska Inst, Dept Cell & Mol Biol, Stockholm, Sweden..
    Lundeberg, Joakim
    KTH, Centres, Science for Life Laboratory, SciLifeLab. KTH, School of Engineering Sciences in Chemistry, Biotechnology and Health (CBH), Gene Technology.
    Spatial deconvolution of HER2-positive breast cancer delineates tumor-associated cell type interactions2021In: Nature Communications, E-ISSN 2041-1723, Vol. 12, no 1, article id 6012Article in journal (Refereed)
    Abstract [en]

    In the past decades, transcriptomic studies have revolutionized cancer treatment and diagnosis. However, tumor sequencing strategies typically result in loss of spatial information, critical to understand cell interactions and their functional relevance. To address this, we investigate spatial gene expression in HER2-positive breast tumors using Spatial Transcriptomics technology. We show that expression-based clustering enables data-driven tumor annotation and assessment of intra- and interpatient heterogeneity; from which we discover shared gene signatures for immune and tumor processes. By integration with single cell data, we spatially map tumor-associated cell types to find tertiary lymphoid-like structures, and a type I interferon response overlapping with regions of T-cell and macrophage subset colocalization. We construct a predictive model to infer presence of tertiary lymphoid-like structures, applicable across tissue types and technical platforms. Taken together, we combine different data modalities to define a high resolution map of cellular interactions in tumors and provide tools generalizing across tissues and diseases. While transcriptomics have enhanced our understanding for cancer, spatial transcriptomics enable the characterisation of cellular interactions. Here, the authors integrate single cell data with spatial information for HER2 + tumours and develop tools for the prediction of interactions between tumour-infiltrating cells.

  • 7.
    Andersson, Ken G.
    et al.
    KTH, School of Biotechnology (BIO), Protein Technology.
    Oroujeni, Maryam
    Garousi, Javad
    Mitran, Bogdan
    Ståhl, Stefan
    KTH, School of Biotechnology (BIO), Protein Technology.
    Orlova, Anna
    Löfblom, John
    KTH, School of Biotechnology (BIO), Protein Technology.
    Tolmachev, Vladimir
    Feasibility of imaging of epidermal growth factor receptor expression with ZEGFR:2377 affibody molecule labeled with Tc-99m using a peptide-based cysteine-containing chelator2016In: International Journal of Oncology, ISSN 1019-6439, E-ISSN 1791-2423, Vol. 49, no 6, p. 2285-2293Article in journal (Refereed)
    Abstract [en]

    The epidermal growth factor receptor (EGFR) is overexpressed in a number of malignant tumors and is a molecular target for several specific anticancer antibodies and tyrosine kinase inhibitors. The overexpression of EGFR is a predictive biomarker for response to several therapy regimens. Radionuclide molecular imaging might enable detection of EGFR overexpression by a non-invasive procedure and could be used repeatedly. Affibody molecules are engineered scaffold proteins, which could be selected to have a high affinity and selectivity to predetermined targets. The anti-EGFR ZEGFR:2377 affibody molecule is a potential imaging probe for EGFR detection. The use of the generator-produced radionuclide Tc-99m should facilitate clinical translation of an imaging probe due to its low price, availability and favorable dosimetry of the radionuclide. In the present study, we evaluated feasibility of ZEGFR:2377 labeling with Tc-99m using a peptide-based cysteine-containing chelator expressed at the C-terminus of ZEGFR:2377. The label was stable in vitro under cysteine challenge. In addition, Tc-99m-ZEGFR:2377 was capable of specific binding to EGFR-expressing cells with high affinity (274 pM). Studies in BALB/C nu/nu mice bearing A431 xenografts demonstrated that Tc-99m-ZEGFR:2377 accumulates in tumors in an EGFR-specific manner. The tumor uptake values were 3.6 1 and 2.5 0.4% ID/g at 3 and 24 h after injection, respectively. The corresponding tumor-to-blood ratios were 1.8 0.4 and 8 3. The xenografts were clearly visualized at both time-points. This study demonstrated the potential of Tc-99m-labeled ZEGFR:2377 for imaging of EGFR in vivo.

  • 8.
    Arruda, Lucas C. M.
    et al.
    Karolinska Inst, Dept Clin Sci Intervent & Technol, Stockholm, Sweden..
    Stikvoort, Arwen
    Karolinska Inst, Dept Clin Sci Intervent & Technol, Stockholm, Sweden..
    Lambert, Melanie
    Karolinska Inst, Dept Med, Ctr Hematol & Regenerat Med, Stockholm, Sweden..
    Jin, Liqing
    Univ Hlth Network, Princess Margaret Canc Ctr, Toronto, ON, Canada..
    Sanchez-Rivera, Laura
    KTH, Centres, Science for Life Laboratory, SciLifeLab. KTH, School of Engineering Sciences in Chemistry, Biotechnology and Health (CBH), Protein Science, Affinity Proteomics.
    Alves, Renato M. P.
    KTH, School of Engineering Sciences (SCI), Applied Physics. KTH, Centres, Science for Life Laboratory, SciLifeLab.
    de Moura, Tales Rocha
    KTH, School of Engineering Sciences in Chemistry, Biotechnology and Health (CBH), Biomedical Engineering and Health Systems.
    Mim, Carsten
    KTH, School of Engineering Sciences in Chemistry, Biotechnology and Health (CBH), Biomedical Engineering and Health Systems, Structural Biotechnology.
    Lehmann, Soren
    Karolinska Inst, Dept Med, Ctr Hematol & Regenerat Med, Stockholm, Sweden..
    Axelsson-Robertson, Rebecca
    Karolinska Inst, Dept Clin Sci Intervent & Technol, Stockholm, Sweden.;Karolinska Univ Hosp, Dept Immunol & Transfus Med, Stockholm, Sweden..
    Dick, John E.
    Univ Hlth Network, Princess Margaret Canc Ctr, Toronto, ON, Canada.;Univ Toronto, Dept Mol Genet, Toronto, ON, Canada..
    Mattsson, Jonas
    Univ Hlth Network, Princess Margaret Canc Ctr, Toronto, ON, Canada.;Univ Hlth Network, Princess Margaret Canc Ctr, Gloria & Seymour Epstein Chair Cell Therapy & Tra, Toronto, ON, Canada..
    Önfelt, Björn
    KTH, School of Engineering Sciences (SCI), Applied Physics. KTH, Centres, Science for Life Laboratory, SciLifeLab. Karolinska Inst, Sci Life Lab, Dept Microbiol Tumor & Cell Biol, Stockholm, Sweden..
    Carlsten, Mattias
    Karolinska Inst, Dept Med, Ctr Hematol & Regenerat Med, Stockholm, Sweden.;Karolinska Univ Hosp, Ctr Cell Therapy & Allogene Stem Cell Transplanta, Stockholm, Sweden..
    Uhlin, Michael
    KTH, School of Engineering Sciences (SCI), Applied Physics, Biophysics. KTH, Centres, Science for Life Laboratory, SciLifeLab. Karolinska Inst, Dept Clin Sci Intervent & Technol, Stockholm, Sweden.; Karolinska Univ Hosp, Dept Immunol & Transfus Med, Stockholm, Sweden..
    A novel CD34-specific T-cell engager efficiently depletes acute myeloid leukemia and leukemic stem cells in vitro and in vivo2022In: Haematologica, ISSN 0390-6078, E-ISSN 1592-8721, Vol. 107, no 8, p. 1786-1795Article in journal (Refereed)
    Abstract [en]

    Less than a third of patients with acute myeloid leukemia (AML) are cured by chemotherapy and/or hematopoietic stem cell transplantation, highlighting the need to develop more efficient drugs. The low efficacy of standard treatments is associated with inadequate depletion of CD34(+) blasts and leukemic stem cells, the latter a drug-resistant subpopulation of leukemia cells characterized by the CD34(+)CD38(-) phenotype. To target these drug-resistant primitive leukemic cells better, we have designed a CD34/CD3 bi-specific T-cell engager (BTE) and characterized its anti-leukemia potential in vitro, ex vivo and in vivo. Our results show that this CD34-specific BTE induces CD34-dependent T-cell activation and subsequent leukemia cell killing in a dose-dependent manner, further corroborated by enhanced T-cell-mediated killing at the singlecell level. Additionally, the BTE triggered efficient T-cell-mediated depletion of CD34(+) hematopoietic stem cells from peripheral blood stem cell grafts and CD34(+) blasts from AML patients. Using a humanized AML xenograft model, we confirmed that the CD34-specific BTE had in vivo efficacy by depleting CD34(+) blasts and leukemic stem cells without side effects. Taken together, these data demonstrate that the CD34-specific BTE has robust antitumor effects, supporting development of a novel treatment modality with the aim of improving outcomes of patients with AML and myelodysplastic syndromes.

  • 9.
    Asem, Heba
    et al.
    KTH, School of Information and Communication Technology (ICT), Materials- and Nano Physics, Functional Materials, FNM. Karolinska Inst, Sweden.
    Abd El-Fattah, Ahmed
    Nafee, Noha
    Zhao, Ying
    Khalil, Labiba
    Muhammed, Mamoun
    KTH, School of Information and Communication Technology (ICT), Materials- and Nano Physics, Functional Materials, FNM.
    Hassan, Moustapha
    Kandil, Sherif
    Development and biodistribution of a theranostic aluminum phthalocyanine nanophotosensitizer2016In: Photodiagnosis and Photodynamic Therapy, ISSN 1572-1000, E-ISSN 1873-1597, Vol. 13, p. 48-57Article in journal (Refereed)
    Abstract [en]

    Background: Aluminum phthalocyanine (AlPc) is an efficient second generation photosensitizer (PS) with high fluorescence ability. Its use in photodynamic therapy (PDT) is hampered by hydrophobicity and poor biodistribution. Methods: AlPc was converted to a biocompatible nanostructure by incorporation into amphiphilic polyethylene glycol-polycaprolactone (PECL) copolymer nanoparticles, allowing efficient entrapment of the PS in the hydrophobic core, water dispersibility and biodistribution enhancement by PEG-induced surface characteristics. A series of synthesized PECL copolymers were used to prepare nanophotosensitizers with an average diameter of 66.5-99.1 nm and encapsulation efficiency (EE%) of 66.4-78.0%. One formulation with favorable colloidal properties and relatively slow release over 7 days was selected for in vitro photophysical assessment and in vivo biodistribution studies in mice. Results: The photophysical properties of AlPc were improved by encapsulating AlPc into PECL-NPs, which showed intense fluorescence emission at 687 nm and no AlPc aggregation has been induced after entrapment into the nanoparticles. Biodistribution of AlPc loaded NPs (AlPc-NPs) and free AlPc drug in mice was monitored by in vivo whole body fluorescence imaging and ex vivo organ imaging, with in vivo imaging system (IVIS). Compared to a AlPc solution in aqueous TWEEN 80 (2 w/v%), the developed nanophotosensitizer showed targeted drug delivery to lungs, liver and spleen as monitored by the intrinsic fluorescence of AlPc at different time points (1 h, 24 h and 48 h) post iv. administration. Conclusions: The AlPc-based copolymer nanoparticles developed offer potential as a single agent multifunctional theranostic nanophotosensitizer for PDT coupled with imaging-guided drug delivery and biodistribution, and possibly also fluorescence diagnostics.

  • 10. Aslian, Hossein
    et al.
    Sadeghi, Mahdi
    Mahdavi, Seied Rabie
    Mofrad, Farshid Babapour
    Astarakee, Mehdi
    Khaledi, Navid
    Fadavi, Pedram
    Magnetic resonance imaging-based target volume delineation in radiation therapy treatment planning for brain tumors using localized region-based active contour2013In: International Journal of Radiation Oncology, Biology, Physics, ISSN 0360-3016, E-ISSN 1879-355X, Vol. 87, no 1, p. 195-201Article in journal (Refereed)
  • 11.
    Begum, Neelu
    et al.
    Kings Coll London, Fac Dent Oral & Craniofacial Sci, Ctr Host Microbiome Interact, London SE1 9RT, England..
    Lee, Sunjae
    Kings Coll London, Fac Dent Oral & Craniofacial Sci, Ctr Host Microbiome Interact, London SE1 9RT, England..
    Pellon, Aize
    Kings Coll London, Fac Dent Oral & Craniofacial Sci, Ctr Host Microbiome Interact, London SE1 9RT, England..
    Nasab, Shervin Sadeghi
    Kings Coll London, Fac Dent Oral & Craniofacial Sci, Ctr Host Microbiome Interact, London SE1 9RT, England..
    Nieslen, Jens
    Chalmers Univ Technol, Dept Biol & Biol Engn, Kemivagen 10, SE-41296 Gothenburg, Sweden.;Biolnnovat Inst, Ole Maaloes Vej 3, DK-2200 Copenhagen N, Denmark..
    Uhlén, Mathias
    KTH, Centres, Science for Life Laboratory, SciLifeLab. KTH, School of Engineering Sciences in Chemistry, Biotechnology and Health (CBH), Protein Science, Systems Biology.
    Moyes, David
    Kings Coll London, Fac Dent Oral & Craniofacial Sci, Ctr Host Microbiome Interact, London SE1 9RT, England..
    Shoaie, Saeed
    KTH, Centres, Science for Life Laboratory, SciLifeLab. KTH, School of Engineering Sciences in Chemistry, Biotechnology and Health (CBH), Protein Science, Systems Biology. Kings Coll London, Fac Dent Oral & Craniofacial Sci, Ctr Host Microbiome Interact, London SE1 9RT, England..
    Portlock, Theo John
    KTH, Centres, Science for Life Laboratory, SciLifeLab. KTH, School of Engineering Sciences in Chemistry, Biotechnology and Health (CBH), Protein Science, Systems Biology.
    Integrative functional analysis uncovers metabolic differences between Candida species2022In: Communications Biology, E-ISSN 2399-3642, Vol. 5, no 1, article id 1013Article in journal (Refereed)
    Abstract [en]

    Metabolic differences between Candida species are uncovered using the BioFung database alongside genomic and metabolic analysis. Candida species are a dominant constituent of the human mycobiome and associated with the development of several diseases. Understanding the Candida species metabolism could provide key insights into their ability to cause pathogenesis. Here, we have developed the BioFung database, providing an efficient annotation of protein-encoding genes. Along, with BioFung, using carbohydrate-active enzyme (CAZymes) analysis, we have uncovered core and accessory features across Candida species demonstrating plasticity, adaption to the environment and acquired features. We show a greater importance of amino acid metabolism, as functional analysis revealed that all Candida species can employ amino acid metabolism. However, metabolomics revealed that only a specific cluster of species (AGAu species-C. albicans, C. glabrata and C. auris) utilised amino acid metabolism including arginine, cysteine, and methionine metabolism potentially improving their competitive fitness in pathogenesis. We further identified critical metabolic pathways in the AGAu cluster with biomarkers and anti-fungal target potential in the CAZyme profile, polyamine, choline and fatty acid biosynthesis pathways. This study, combining genomic analysis, and validation with gene expression and metabolomics, highlights the metabolic diversity with AGAu species that underlies their remarkable ability to dominate they mycobiome and cause disease.

  • 12.
    Benfeitas, Rui
    et al.
    KTH, Centres, Science for Life Laboratory, SciLifeLab.
    Uhlén, Mathias
    KTH, Centres, Science for Life Laboratory, SciLifeLab.
    Nielsen, Jens
    KTH, Centres, Science for Life Laboratory, SciLifeLab.
    Mardinoglu, A.
    New challenges to study heterogeneity in cancer redox metabolism2017In: Frontiers in Cell and Developmental Biology, E-ISSN 2296-634X, Vol. 5, no JUL, article id 65Article in journal (Refereed)
    Abstract [en]

    Reactive oxygen species (ROS) are important pathophysiological molecules involved in vital cellular processes. They are extremely harmful at high concentrations because they promote the generation of radicals and the oxidation of lipids, proteins, and nucleic acids, which can result in apoptosis. An imbalance of ROS and a disturbance of redox homeostasis are now recognized as a hallmark of complex diseases. Considering that ROS levels are significantly increased in cancer cells due to mitochondrial dysfunction, ROS metabolism has been targeted for the development of efficient treatment strategies, and antioxidants are used as potential chemotherapeutic drugs. However, initial ROS-focused clinical trials in which antioxidants were supplemented to patients provided inconsistent results, i.e., improved treatment or increased malignancy. These different outcomes may result from the highly heterogeneous redox responses of tumors in different patients. Hence, population-based treatment strategies are unsuitable and patient-tailored therapeutic approaches are required for the effective treatment of patients. Moreover, due to the crosstalk between ROS, reducing equivalents [e.g., NAD(P)H] and central metabolism, which is heterogeneous in cancer, finding the best therapeutic target requires the consideration of system-wide approaches that are capable of capturing the complex alterations observed in all of the associated pathways. Systems biology and engineering approaches may be employed to overcome these challenges, together with tools developed in personalized medicine. However, ROS- and redox-based therapies have yet to be addressed by these methodologies in the context of disease treatment. Here, we review the role of ROS and their coupled redox partners in tumorigenesis. Specifically, we highlight some of the challenges in understanding the role of hydrogen peroxide (H2O2), one of the most important ROS in pathophysiology in the progression of cancer. We also discuss its interplay with antioxidant defenses, such as the coupled peroxiredoxin/thioredoxin and glutathione/glutathione peroxidase systems, and its reducing equivalent metabolism. Finally, we highlight the need for system-level and patient-tailored approaches to clarify the roles of these systems and identify therapeutic targets through the use of the tools developed in personalized medicine.

  • 13.
    Bengtsson, Ivar
    et al.
    KTH, School of Engineering Sciences (SCI), Mathematics (Dept.), Optimization and Systems Theory. RaySearch Labs AB, Stockholm, Sweden..
    Fredriksson, A.
    RaySearch Labs AB, Stockholm, Sweden..
    Forsgren, Anders
    KTH, School of Engineering Sciences (SCI), Mathematics (Dept.), Optimization and Systems Theory.
    Implications of Including Tumor Presence Probabilities as Weights in Radiotherapy Optimization2022In: International Journal of Radiation Oncology, Biology, Physics, ISSN 0360-3016, E-ISSN 1879-355X, Vol. 114, no 3, p. E576-E576Article in journal (Other academic)
  • 14.
    Bergenstråhle, Ludvig
    et al.
    KTH, School of Engineering Sciences in Chemistry, Biotechnology and Health (CBH), Gene Technology. KTH, Centres, Science for Life Laboratory, SciLifeLab.
    He, B.
    Bergenstråhle, Joseph
    KTH, School of Engineering Sciences in Chemistry, Biotechnology and Health (CBH), Gene Technology. KTH, Centres, Science for Life Laboratory, SciLifeLab.
    Abalo, Xesús M
    KTH, School of Engineering Sciences in Chemistry, Biotechnology and Health (CBH), Gene Technology. KTH, Centres, Science for Life Laboratory, SciLifeLab.
    Mirzazadeh, Reza
    KTH, Centres, Science for Life Laboratory, SciLifeLab. KTH, School of Engineering Sciences in Chemistry, Biotechnology and Health (CBH), Gene Technology.
    Thrane, Kim
    KTH, School of Engineering Sciences in Chemistry, Biotechnology and Health (CBH), Gene Technology. KTH, Centres, Science for Life Laboratory, SciLifeLab.
    Ji, A. L.
    Andersson, Alma
    KTH, School of Engineering Sciences in Chemistry, Biotechnology and Health (CBH), Gene Technology. KTH, Centres, Science for Life Laboratory, SciLifeLab.
    Larsson, Ludvig
    KTH, School of Engineering Sciences in Chemistry, Biotechnology and Health (CBH), Gene Technology. KTH, Centres, Science for Life Laboratory, SciLifeLab.
    Stakenborg, N.
    Boeckxstaens, G.
    Khavari, P.
    Zou, J.
    Lundeberg, Joakim
    KTH, Centres, Science for Life Laboratory, SciLifeLab. KTH, School of Engineering Sciences in Chemistry, Biotechnology and Health (CBH), Gene Technology.
    Maaskola, Jonas
    KTH, School of Engineering Sciences in Chemistry, Biotechnology and Health (CBH), Gene Technology. KTH, Centres, Science for Life Laboratory, SciLifeLab. Department of Biochemistry and Biophysics, Stockholm University, Stockholm, Sweden.
    Super-resolved spatial transcriptomics by deep data fusion2022In: Nature Biotechnology, ISSN 1087-0156, E-ISSN 1546-1696, Vol. 40, no 4, p. 476-479Article in journal (Refereed)
    Abstract [en]

    Current methods for spatial transcriptomics are limited by low spatial resolution. Here we introduce a method that integrates spatial gene expression data with histological image data from the same tissue section to infer higher-resolution expression maps. Using a deep generative model, our method characterizes the transcriptome of micrometer-scale anatomical features and can predict spatial gene expression from histology images alone. 

  • 15. Bersani, Cinzia
    et al.
    Huss, Mikael
    KTH, School of Biotechnology (BIO). KTH, Centres, Science for Life Laboratory, SciLifeLab.
    Giacomello, Stefania
    KTH, School of Biotechnology (BIO). KTH, Centres, Science for Life Laboratory, SciLifeLab.
    Xu, Li-Di
    Bianchi, Julie
    Eriksson, Sofi
    Jerhammar, Fredrik
    Alexeyenko, Andrey
    Vilborg, Anna
    Lundeberg, Joakim
    KTH, School of Biotechnology (BIO). KTH, Centres, Science for Life Laboratory, SciLifeLab.
    Lui, Weng-Onn
    Wiman, Klas G.
    Genome-wide identification of Wig-1 mRNA targets by RIP-Seq analysis2016In: Oncotarget, E-ISSN 1949-2553, Vol. 7, no 2, p. 1895-1911Article in journal (Refereed)
    Abstract [en]

    RNA-binding proteins (RBPs) play important roles in the regulation of gene expression through a variety of post-transcriptional mechanisms. The p53-induced RBP Wig-1 (Zmat3) binds RNA through its zinc finger domains and enhances stability of p53 and N-Myc mRNAs and decreases stability of FAS mRNA. To identify novel Wig-1-bound RNAs, we performed RNA-immunoprecipitation followed by high-throughput sequencing (RIP-Seq) in HCT116 and Saos-2 cells. We identified 286 Wig-1-bound mRNAs common between the two cell lines. Sequence analysis revealed that AU-rich elements (AREs) are highly enriched in the 3'UTR of these Wig-1-bound mRNAs. Network enrichment analysis showed that Wig-1 preferentially binds mRNAs involved in cell cycle regulation. Moreover, we identified a 2D Wig-1 binding motif in HIF1A mRNA. Our findings confirm that Wig-1 is an ARE-BP that regulates cell cycle-related processes and provide a novel view of how Wig-1 may bind mRNA through a putative structural motif. We also significantly extend the repertoire of Wig-1 target mRNAs. Since Wig-1 is a transcriptional target of the tumor suppressor p53, these results have implications for our understanding of p53-dependent stress responses and tumor suppression.

  • 16.
    Beza, Abebe Dress
    et al.
    Bahir Dar Univ, Fac Civil & Water Resources Engn, Bahir Dar Inst Technol, POB 26, Bahir Dar, Ethiopia.;Univ Mons, Fac Engn, B-7000 Mons, Belgium..
    Zefreh, Mohammad Maghrour
    KTH, School of Architecture and the Built Environment (ABE), Civil and Architectural Engineering, Transport planning.
    Torok, Adam
    Budapest Univ Technol & Econ, Dept Transport Technol & Econ, H-1111 Budapest, Hungary.;KTI Inst Transport Sci, Dept Transport Policy & Econ, H-1111 Budapest, Hungary..
    Impacts of Different Types of Automated Vehicles on Traffic Flow Characteristics and Emissions: A Microscopic Traffic Simulation of Different Freeway Segments2022In: Energies, E-ISSN 1996-1073, Vol. 15, no 18, article id 6669Article in journal (Refereed)
    Abstract [en]

    Different types of automated vehicles (AVs) have emerged promptly in recent years, each of which might have different potential impacts on traffic flow and emissions. In this paper, the impacts of autonomous automated vehicles (AAVs) and cooperative automated vehicles (CAVs) on capacity, average traffic speed, average travel time per vehicle, and average delay per vehicle, as well as traffic emissions such as carbon dioxide (CO2), nitrogen oxides (NOx), and particulate matter (PM10) have been investigated through a microsimulation study in VISSIM. Moreover, the moderating effects of different AV market penetration, and different freeway segments on AV's impacts have been studied. The simulation results show that CAVs have a higher impact on capacity improvement regardless of the type of freeway segment. Compared to other scenarios, CAVs at 100% market penetration in basic freeway segments have a greater capacity improvement than AAVs. Furthermore, merging, diverging, and weaving segments showed a moderating effect on capacity improvements, particularly on CAVs' impact, with merging and weaving having the highest moderating effect on CAVs' capacity improvement potential. Taking average delay per vehicle, average traffic speed, and average travel time per vehicle into account, simulation results were diverse across the investigated scenarios. The emission estimation results show that 100% AAV scenarios had the best performance in emission reductions in basic freeway and merging sections, while other scenarios increased emissions in diverging and weaving sections.

  • 17.
    Birgersson, Madeleine
    et al.
    KTH, Centres, Science for Life Laboratory, SciLifeLab. KTH, School of Engineering Sciences in Chemistry, Biotechnology and Health (CBH), Protein Science. Department of Biosciences and Nutrition, Karolinska Institutet, 141 83 Huddinge, Sweden.
    Indukuri, Rajitha
    KTH, School of Engineering Sciences in Chemistry, Biotechnology and Health (CBH), Protein Science, Cellular and Clinical Proteomics. KTH, Centres, Science for Life Laboratory, SciLifeLab.
    Antonson, Per
    Department of Biosciences and Nutrition, Karolinska Institutet, 141 83 Huddinge, Sweden.
    Nalvarte, Ivan
    Department of Biosciences and Nutrition, Karolinska Institutet, 141 83 Huddinge, Sweden.
    Archer, Amena
    KTH, Centres, Science for Life Laboratory, SciLifeLab. KTH, School of Engineering Sciences in Chemistry, Biotechnology and Health (CBH), Protein Science, Cellular and Clinical Proteomics. Department of Biosciences and Nutrition, Karolinska Institutet, 141 83 Huddinge, Sweden.
    Williams, Cecilia
    KTH, Centres, Science for Life Laboratory, SciLifeLab. KTH, School of Engineering Sciences in Chemistry, Biotechnology and Health (CBH), Protein Science, Cellular and Clinical Proteomics. Department of Biosciences and Nutrition, Karolinska Institutet, 141 83 Huddinge, Sweden.
    ERβ in Granulosa Cell Tumors and Its Clinical Potential2023In: Endocrinology, ISSN 0013-7227, E-ISSN 1945-7170, Endocrinology, ISSN 1945-7170, Vol. 164, no 6Article, review/survey (Refereed)
    Abstract [en]

    Granulosa cell tumors (GCTs) are rare ovarian tumors comprising an adult and a juvenile subtype. They have a generally good prognosis, but the survival rate drastically declines in patients with late-stage or recurring tumors. Due to the rarity of GCTs, the tumor type is largely understudied and lacks a specific treatment strategy. Estrogen receptor beta (ERβ/ESR2) has been found to be highly expressed in GCTs, which could be of therapeutic importance since it can be targeted with small molecules. However, its role in GCTs is not known. In this review, we summarize the current knowledge about the action of ERβ in the ovary and discuss its prospective role in GCTs.

  • 18. Bjarnadottir, O.
    et al.
    Romero, Q.
    Bendahl, P-O
    Ryden, L.
    Rose, C.
    Loman, N.
    Uhlén, Mathias
    KTH, School of Biotechnology (BIO), Proteomics and Nanobiotechnology.
    Jirstrom, K.
    Grabau, D.
    Borgquist, S.
    Statin-induced decrease in proliferation depends on HMG-CoA reductase expression in breast cancer2012In: Cancer Research, ISSN 0008-5472, E-ISSN 1538-7445, Vol. 72Article in journal (Other academic)
  • 19. Boman, K.
    et al.
    Larsson, A. H.
    Segersten, U.
    Kuteeva, E.
    Johannesson, H.
    Nodin, B.
    Eberhard, J.
    Uhlén, Mathias
    KTH, School of Biotechnology (BIO), Proteomics and Nanobiotechnology. KTH, Centres, Science for Life Laboratory, SciLifeLab.
    Malmström, P-U
    Jirström, K.
    Membranous expression of podocalyxin-like protein is an independent factor of poor prognosis in urothelial bladder cancer2013In: British Journal of Cancer, ISSN 0007-0920, E-ISSN 1532-1827, Vol. 108, no 11, p. 2321-2328Article in journal (Refereed)
    Abstract [en]

    Background: Membranous expression of the anti-adhesive glycoprotein podocalyxin-like (PODXL) has previously been found to correlate with poor prognosis in several major cancer forms. Here we examined the prognostic impact of PODXL expression in urothelial bladder cancer. Methods: Immunohistochemical PODXL expression was examined in tissue microarrays with tumours from two independent cohorts of patients with urothelial bladder cancer: n = 100 (Cohort I) and n = 343 (Cohort II). The impact of PODXL expression on disease-specific survival (DSS; Cohort II), 5-year overall survival (OS; both cohorts) and 2-year progression-free survival (PFS; Cohort II) was assessed. Results: Membranous PODXL expression was significantly associated with more advanced tumour (T) stage and high-grade tumours in both cohorts, and a significantly reduced 5-year OS (unadjusted HR = 2.25 in Cohort I and 3.10 in Cohort II, adjusted HR = 2.05 in Cohort I and 2.18 in Cohort II) and DSS (unadjusted HR = 4.36, adjusted HR = 2.70). In patients with Ta and T1 tumours, membranous PODXL expression was an independent predictor of a reduced 2-year PFS (unadjusted HR = 6.19, adjusted HR = 4.60) and DSS (unadjusted HR = 8.34, adjusted HR = 7.16). Conclusion: Membranous PODXL expression is an independent risk factor for progressive disease and death in patients with urothelial bladder cancer.

  • 20.
    Bonagas, Nadilly
    et al.
    Karolinska Inst, Dept Oncol Pathol, Sci Life Lab, Solna, Sweden..
    Andersson, Yasmin
    KTH, School of Engineering Sciences in Chemistry, Biotechnology and Health (CBH), Protein Science, Drug Discovery and Development. KTH, Centres, Science for Life Laboratory, SciLifeLab.
    Dahllund, Leif
    KTH, School of Engineering Sciences in Chemistry, Biotechnology and Health (CBH), Protein Science, Drug Discovery and Development. KTH, Centres, Science for Life Laboratory, SciLifeLab.
    Helleday, Thomas
    Karolinska Inst, Dept Oncol Pathol, Sci Life Lab, Solna, Sweden.;Univ Sheffield, Med Sch, Dept Oncol & Metab, Weston Pk Canc Ctr, Sheffield, S Yorkshire, England..
    Pharmacological targeting of MTHFD2 suppresses acute myeloid leukemia by inducing thymidine depletion and replication stress2022In: Nature Cancer, ISSN 2662-1347, Vol. 3, no 2, p. 156-172Article in journal (Refereed)
    Abstract [en]

    The folate metabolism enzyme MTHFD2 (methylenetetrahydrofolate dehydrogenase/cyclohydrolase) is consistently overexpressed in cancer but its roles are not fully characterized, and current candidate inhibitors have limited potency for clinical development. In the present study, we demonstrate a role for MTHFD2 in DNA replication and genomic stability in cancer cells, and perform a drug screen to identify potent and selective nanomolar MTHFD2 inhibitors; protein cocrystal structures demonstrated binding to the active site of MTHFD2 and target engagement. MTHFD2 inhibitors reduced replication fork speed and induced replication stress followed by S-phase arrest and apoptosis of acute myeloid leukemia cells in vitro and in vivo, with a therapeutic window spanning four orders of magnitude compared with nontumorigenic cells. Mechanistically, MTHFD2 inhibitors prevented thymidine production leading to misincorporation of uracil into DNA and replication stress. Overall, these results demonstrate a functional link between MTHFD2-dependent cancer metabolism and replication stress that can be exploited therapeutically with this new class of inhibitors. Helleday and colleagues describe a nanomolar MTHFD2 inhibitor that causes replication stress and DNA damage accumulation in cancer cells via thymidine depletion, demonstrating a potential therapeutic strategy in AML tumors in vivo.

  • 21.
    Bonfiglio, Silvia
    et al.
    IRCCS Osped San Raffaele, Ctr Omics Sci, Milan, Italy.; IRCCS Osped San Raffaele, Div Expt Oncol, B Cell Neoplasia Unit, Milan, Italy.
    Lyander, Anna
    KTH, School of Engineering Sciences in Chemistry, Biotechnology and Health (CBH), Gene Technology. KTH, Centres, Science for Life Laboratory, SciLifeLab. Sci Life Lab, Clin Genom Stockholm, Solna, Sweden; Karolinska Inst, Dept Microbiol Tumor & Cell Biol, Stockholm, Sweden.
    Ghia, Paolo
    IRCCS Osped San Raffaele, Div Expt Oncol, B Cell Neoplasia Unit, Milan, Italy.;IRCCS Osped San Raffaele, Strateg Res Program CLL, Milan, Italy.; Univ Vita Salute San Raffaele, Milan, Italy.
    BTK and PLCG2 remain unmutated in one-third of patients with CLL relapsing on ibrutinib2023In: Blood Advances, ISSN 2473-9529, Vol. 7, no 12, p. 2794-2806Article in journal (Refereed)
    Abstract [en]

    Patients with chronic lymphocytic leukemia (CLL) progressing on ibrutinib constitute an unmet need. Though Bruton tyrosine kinase (BTK) and PLCG2 mutations are associated with ibrutinib resistance, their frequency and relevance to progression are not fully understood. In this multicenter retrospective observational study, we analyzed 98 patients with CLL on ibrutinib (49 relapsing after an initial response and 49 still responding after & GE;1 year of continuous treatment) using a next-generation sequencing (NGS) panel (1% sensitivity) comprising 13 CLL-relevant genes including BTK and PLCG2. BTK hotspot mutations were validated by droplet digital polymerase chain reaction (ddPCR) (0.1% sensitivity). By integrating NGS and ddPCR results, 32 of 49 relapsing cases (65%) carried at least 1 hotspot BTK and/or PLCG2 mutation(s); in 6 of 32, BTK mutations were only detected by ddPCR (variant allele frequency [VAF] 0.1% to 1.2%). BTK/PLCG2 mutations were also identified in 6 of 49 responding patients (12%; 5/6 VAF <10%), of whom 2 progressed later. NFKBIE mutations. Using an extended capture-based panel, only BRAF and IKZF3 mutations showed a predominance in relapsing cases, who were enriched for del(8p) (n = 11; 3 BTKwt). Finally, no difference in TP53 mutation burden was observed between BTKmut and BTKwt relapsing cases, and ibrutinib treatment did not favor selection of TP53-aberrant clones. In conclusion, we show that BTK/PLCG2 mutations were absent in a substantial fraction (35%) of a real-world cohort failing ibrutinib, and propose additional mechanisms contributing to resistance.

  • 22. Borsics, Tamas
    et al.
    Lundberg, Emma
    KTH, School of Biotechnology (BIO), Centres, Albanova VinnExcellence Center for Protein Technology, ProNova.
    Geerts, Dirk
    Koomoa, Dana-Lynn T.
    Koster, Jan
    Wester, Kenneth
    Bachmann, Andres S.
    Subcellular distribution and expression of prenylated Rab acceptor 1 domain family, member 2 (PRAF2) in malignant glioma: Influence on cell survival and migration2010In: Cancer Science, ISSN 1347-9032, E-ISSN 1349-7006, Vol. 101, no 7, p. 1624-1631Article in journal (Refereed)
    Abstract [en]

    Our previous studies revealed that the expression of the 19-kDa protein prenylated Rab acceptor 1 domain family, member 2 (PRAF2) is elevated in cancer tissues of the breast, colon, lung, and ovary, when compared to noncancerous tissues of paired samples. PRAF2 mRNA expression also correlated with several genetic and clinical features and is a candidate prognostic marker in the pediatric cancer neuroblastoma. The PRAF2-related proteins, PRAF1 and PRAF3, play multiple roles in cellular processes, including endo/exocytic vesicle trafficking and glutamate uptake. PRAF2 shares a high sequence homology with these family members, but its function remains unknown. In this study, we examined PRAF2 mRNA and protein expression in 20 different human cancer types using Affymetrix microarray and human tissue microarray (TMA) analyses, respectively. In addition, we investigated the subcellular distribution of PRAF2 by immunofluorescence microscopy and cell fractionation studies. PRAF2 mRNA and protein expression was elevated in several cancer tissues with highest levels in malignant glioma. At the molecular level, we detected native PRAF2 in small, vesicle-like structures throughout the cytoplasm as well as in and around cell nuclei of U-87 malignant glioma cells. We further found that monomeric and dimeric forms of PRAF2 are associated with different cell compartments, suggesting possible functional differences. Importantly, PRAF2 down-regulation by RNA interference significantly reduced the cell viability, migration, and invasiveness of U-87 cells. This study shows that PRAF2 expression is elevated in various tumors with exceptionally high expression in malignant gliomas, and PRAF2 therefore presents a candidate molecular target for therapeutic intervention. (Cancer Sci 2010).

  • 23.
    Bragina, Olga
    et al.
    Russian Acad Sci, Canc Res Inst, Tomsk Natl Res Med Ctr, Dept Nucl Therapy & Diagnost, Tomsk 634009, Russia.;Tomsk Polytech Univ, Res Sch Chem & Appl Biomed Sci, Res Ctr Oncotheranost, Tomsk 634050, Russia..
    Chernov, Vladimir
    Russian Acad Sci, Canc Res Inst, Tomsk Natl Res Med Ctr, Dept Nucl Therapy & Diagnost, Tomsk 634009, Russia.;Tomsk Polytech Univ, Res Sch Chem & Appl Biomed Sci, Res Ctr Oncotheranost, Tomsk 634050, Russia..
    Schulga, Alexey
    Tomsk Polytech Univ, Res Sch Chem & Appl Biomed Sci, Res Ctr Oncotheranost, Tomsk 634050, Russia.;Russian Acad Sci, Shemyakin Ovchinnikov Inst Bioorgan Chem, Moscow 117997, Russia..
    Konovalova, Elena
    Tomsk Polytech Univ, Res Sch Chem & Appl Biomed Sci, Res Ctr Oncotheranost, Tomsk 634050, Russia.;Russian Acad Sci, Shemyakin Ovchinnikov Inst Bioorgan Chem, Moscow 117997, Russia..
    Hober, Sophia
    KTH, School of Engineering Sciences in Chemistry, Biotechnology and Health (CBH), Protein Science, Protein Technology.
    Deyev, Sergey
    Tomsk Polytech Univ, Res Sch Chem & Appl Biomed Sci, Res Ctr Oncotheranost, Tomsk 634050, Russia.;Russian Acad Sci, Shemyakin Ovchinnikov Inst Bioorgan Chem, Moscow 117997, Russia..
    Sorensen, Jens
    Uppsala Univ, Dept Surg Sci Nucl Med & PET, S-75185 Uppsala, Sweden..
    Tolmachev, Vladimir
    Tomsk Polytech Univ, Res Sch Chem & Appl Biomed Sci, Res Ctr Oncotheranost, Tomsk 634050, Russia.;Uppsala Univ, Dept Immunol Genet & Pathol, S-75237 Uppsala, Sweden..
    Direct Intra-Patient Comparison of Scaffold Protein-Based Tracers, [99mTc]Tc-ADAPT6 and [99mTc]Tc-(HE)3-G3, for Imaging of HER2-Positive Breast Cancer2023In: Cancers, ISSN 2072-6694, Vol. 15, no 12, article id 3149Article in journal (Refereed)
    Abstract [en]

    Simple Summary The receptor HER2 is overexpressed in some breast cancers. Tumours with a high HER2 expression can be successfully treated with the antibodies trastuzumab and pertuzumab. The radionuclide imaging of HER2 in disseminated cancer could help to select patients for treatment using these antibodies. Novel radiolabelled small-sized tracers, scaffold proteins, have shown excellent imaging properties in preclinical studies. The scaffold proteins [Tc-99m]Tc-ADAPT6 and DARPin [Tc-99m]Tc-(HE)(3)-G3 have been found to be safe in Phase I clinical trials. They showed promising results in the imaging of HER2. In this study, we compared the distribution of both tracers in the same patients with breast cancer to evaluate whether one of them has any decisive advantage. We found that both tracers provide an excellent visualization of tumours, but the accumulation of [Tc-99m]Tc-ADAPT6 in tumours is higher. The data from this study are essential for researchers developing imaging agents. Previous Phase I clinical evaluations of the radiolabelled scaffold proteins [Tc-99m]Tc-ADAPT6 and DARPin [Tc-99m]Tc-(HE)(3)-G3 in breast cancer patients have demonstrated their safety and indicated their capability to discriminate between HER2-positive and HER2-negative tumours. The objective of this study was to compare the imaging of HER2-positive tumours in the same patients using [Tc-99m]Tc-ADAPT6 and [Tc-99m]Tc-(HE)(3)-G3. Eleven treatment-naive female patients (26-65 years) with HER2-positive primary and metastatic breast cancer were included in the study. Each patient was intravenously injected with [Tc-99m]Tc-ADAPT6, followed by an [Tc-99m]Tc-(HE)(3)-G3 injection 3-4 days later and chest SPECT/CT was performed. All primary tumours were clearly visualized using both tracers. The uptake of [Tc-99m]Tc-ADAPT6 in primary tumours (SUVmax = 4.7 & PLUSMN; 2.1) was significantly higher (p < 0.005) than the uptake of [Tc-99m]Tc-(HE)(3)-G3 (SUVmax = 3.5 & PLUSMN; 1.7). There was no significant difference in primary tumour-to-contralateral site values for [Tc-99m]Tc-ADAPT6 (15.2 & PLUSMN; 7.4) and [Tc-99m]Tc-(HE)(3)-G3 (19.6 & PLUSMN; 12.4). All known lymph node metastases were visualized using both tracers. The uptake of [Tc-99m]Tc-ADAPT6 in all extrahepatic soft tissue lesions was significantly (p < 0.0004) higher than the uptake of [Tc-99m]Tc-(HE)(3)-G3. In conclusion, [Tc-99m]Tc-ADAPT6 and [Tc-99m]Tc-(HE)(3)-G3 are suitable for the visualization of HER2-positive breast cancer. At the selected time points, [Tc-99m]Tc-ADAPT6 has a significantly higher uptake in soft tissue lesions, which might be an advantage for the visualization of small metastases.

  • 24. Bragina, Olga
    et al.
    von Witting, Emma
    KTH, School of Engineering Sciences in Chemistry, Biotechnology and Health (CBH), Protein Science.
    Garousi, Javad
    Zelchan, Roman
    Sandström, Mattias
    Orlova, Anna
    Medvedeva, Anna
    Doroshenko, Artem
    Vorobyeva, Anzhelika
    Lindbo, Sarah
    Borin, Jesper
    Tarabanovskaya, Natalya
    Hober, Sophia
    KTH, School of Engineering Sciences in Chemistry, Biotechnology and Health (CBH), Protein Science, Protein Technology.
    Chernov, Vladimir
    Tolmachev, Vladimir
    Phase I study of 99mTc-ADAPT6, a scaffold protein-based probe for visualization of HER2 expression in breast cancerManuscript (preprint) (Other academic)
    Abstract [en]

    Radionuclide molecular imaging of human epidermal growth factor (HER2) expression may be helpful to stratify breast and gastroesophageal cancer patients for HER2-targeting therapies. ADAPTs (albumin-binding domain derived affinity proteins) are a new type of small (46-59 amino acids) proteins useful as probes for molecular imaging. The aim of this first in-human study was to evaluate biodistribution, dosimetry, and safety of HER2-specific 99mTc-ADAPT6.

    METHODS. Twenty-two patients with HER2-positive (n=11) or HER2-negative (n=11) primary breast cancer were intravenously injected with 385125 MBq. The injected amount of protein was either 500 μg (n=11) or 1000 μg (n=11). Planar scintigraphy followed by SPECT imaging was performed after 2, 4, 6 and 24 h. An additional cohort received a dose of 250 μg, and the planar scintigraphy followed by SPECT imaging was performed after 2 h only.

    RESULTS. Injection of 99mTc-ADAPT6 was well tolerated for all doses evaluated in the study, and was not associated with any adverse effects. 99mTc-ADAPT6 cleared rapidly from the blood and the majority of tissues. The normal organs with the highest accumulation were kidney, liver and lung. The effective doses were determined to 0.0090.002 and 0.0100.003 mSv/MBq when injecting protein amounts of 500 and 1000 μg, respectively. Injection of 500 μg resulted in excellent discrimination between HER2-positive and HER2-negative tumors already 2 h after injection (tumor-to-contralateral breast ratio was 3719 vs 52, p < 0.01). The tumor-to-contralateral breast ratios for HER2-positive tumors were significantly (p < 0.5) higher for the injected  mass of 500 μg than for both 250 and 1000 μg. In one patient, the imaging using 99mTc-ADAPT6 revealed three bone metastases, which were not found at the time of diagnosis by CT or 99mTcpyrophosphate bone scan. MRI imaging confirmed this finding.

    CONCLUSION. Injections of 99mTc-ADAPT6 are safe and associated with low absorbed and effective doses. A protein dose of 500 μg is preferable for discrimination between tumors with high and low expression of HER2. 99mTc-ADAPT6 is a promising imaging probe for the stratification of patients for HER2-targeting therapy.

  • 25.
    Bratulic, Sinisa
    et al.
    Chalmers Univ Technol, Dept Biol & Biological Engn, Kemivagen 10, Gothenburg, Sweden..
    Gatto, Francesco
    Chalmers Univ Technol, Dept Biol & Biological Engn, Kemivagen 10, Gothenburg, Sweden.;Elypta, Teknikringen 38, 11428 Stockholm, Sweden..
    Nielsen, Jens
    KTH, School of Engineering Sciences in Chemistry, Biotechnology and Health (CBH), Gene Technology. KTH, Centres, Science for Life Laboratory, SciLifeLab. Chalmers Univ Technol, Dept Biol & Biological Engn, Kemivagen 10, Gothenburg, Sweden.;Chalmers Univ Technol, Wallenberg Centre Prot Res, Kemivagen 10, Gothenburg, Sweden,Syst Univ Denmark, Novo Nord Fdn Ctr Biosustainabil, 2800 KGS Lyngby, Denmark.;Bioinnovat Inst, Ole Maaloes Vej 3, 2200 Copenhagen, DK, Denmark..
    The Translational Status of Cancer Liquid Biopsies2021In: Regenerative Engineering and Translational Medicine, ISSN 2364-4133, Vol. 7, no 3, p. 312-352Article in journal (Refereed)
    Abstract [en]

    Precision oncology aims to tailor clinical decisions specifically to patients with the objective of improving treatment outcomes. This can be achieved by leveraging omics information for accurate molecular characterization of tumors. Tumor tissue biopsies are currently the main source of information for molecular profiling. However, biopsies are invasive and limited in resolving spatiotemporal heterogeneity in tumor tissues. Alternative non-invasive liquid biopsies can exploit patient's body fluids to access multiple layers of tumor-specific biological information (genomes, epigenomes, transcriptomes, proteomes, metabolomes, circulating tumor cells, and exosomes). Analysis and integration of these large and diverse datasets using statistical and machine learning approaches can yield important insights into tumor biology and lead to discovery of new diagnostic, predictive, and prognostic biomarkers. Translation of these new diagnostic tools into standard clinical practice could transform oncology, as demonstrated by a number of liquid biopsy assays already entering clinical use. In this review, we highlight successes and challenges facing the rapidly evolving field of cancer biomarker research. Lay Summary Precision oncology aims to tailor clinical decisions specifically to patients with the objective of improving treatment outcomes. The discovery of biomarkers for precision oncology has been accelerated by high-throughput experimental and computational methods, which can inform fine-grained characterization of tumors for clinical decision-making. Moreover, advances in the liquid biopsy field allow non-invasive sampling of patient's body fluids with the aim of analyzing circulating biomarkers, obviating the need for invasive tumor tissue biopsies. In this review, we highlight successes and challenges facing the rapidly evolving field of liquid biopsy cancer biomarker research.

  • 26. Brennan, Donal J.
    et al.
    Laursen, Henriette
    O'Connor, Darran P.
    Borgquist, Signe
    Uhlén, Mathias
    KTH, School of Biotechnology (BIO), Proteomics.
    Gallagher, William M.
    Ponten, Fredrik
    Millikan, Robert C.
    Ryden, Lisa
    Jirström, Karin
    Tumor-specific HMG-CoA reductase expression in primary premenopausal breast cancer predicts response to tamoxifen2011In: Breast Cancer Research, ISSN 1465-5411, E-ISSN 1465-542X, Vol. 13, no 1, p. R12-Article in journal (Refereed)
    Abstract [en]

    Introduction: We previously reported an association between tumor-specific 3-hydroxy-3-methylglutharyl-coenzyme A reductase (HMG-CoAR) expression and a good prognosis in breast cancer. Here, the predictive value of HMG-CoAR expression in relation to tamoxifen response was examined. Methods: HMG-CoAR protein and RNA expression was analyzed in a cell line model of tamoxifen resistance using western blotting and PCR. HMG-CoAR mRNA expression was examined in 155 tamoxifen-treated breast tumors obtained from a previously published gene expression study (Cohort I). HMG-CoAR protein expression was examined in 422 stage II premenopausal breast cancer patients, who had previously participated in a randomized control trial comparing 2 years of tamoxifen with no systemic adjuvant treatment (Cohort II). Kaplan-Meier analysis and Cox proportional hazards modeling were used to estimate the risk of recurrence-free survival (RFS) and the effect of HMG-CoAR expression on tamoxifen response. Results: HMG-CoAR protein and RNA expression were decreased in tamoxifen-resistant MCF7-LCC9 cells compared with their tamoxifen-sensitive parental cell line. HMG-CoAR mRNA expression was decreased in tumors that recurred following tamoxifen treatment (P < 0.001) and was an independent predictor of RFS in Cohort I (hazard ratio = 0.63, P = 0.009). In Cohort II, adjuvant tamoxifen increased RFS in HMG-CoAR-positive tumors (P = 0.008). Multivariate Cox regression analysis demonstrated that HMG-CoAR was an independent predictor of improved RFS in Cohort II (hazard ratio = 0.67, P = 0.010), and subset analysis revealed that this was maintained in estrogen receptor (ER)-positive patients (hazard ratio = 0.65, P = 0.029). Multivariate interaction analysis demonstrated a difference in tamoxifen efficacy relative to HMG-CoAR expression (P = 0.05). Analysis of tamoxifen response revealed that patients with ER-positive/HMG-CoAR tumors had a significant response to tamoxifen (P = 0.010) as well as patients with ER-positive or HMG-CoAR-positive tumors (P = 0.035). Stratification according to ER and HMG-CoAR status demonstrated that ER-positive/HMG-CoAR-positive tumors had an improved RFS compared with ER-positive/HMG-CoAR-negative tumors in the treatment arm (P = 0.033); this effect was lost in the control arm (P = 0.138), however, suggesting that HMG-CoAR predicts tamoxifen response. Conclusions: HMG CoAR expression is a predictor of response to tamoxifen in both ER-positive and ER-negative disease. Premenopausal patients with tumors that express ER or HMG-CoAR respond to adjuvant tamoxifen.

  • 27.
    Buddenkotte, Thomas
    et al.
    Univ Cambridge, Dept Appl Math & Theoret Phys, Cambridge, England.;Univ Cambridge, Dept Radiol, Box 218,Cambridge Biomed Campus, Cambridge CB2 0QQ, England.;Univ Hosp Hamburg Eppendorf, Dept Diagnost & Intervent Radiol & Nucl Med, Hamburg, Germany.;Jung Diagnost GmbH, Hamburg, Germany..
    Rundo, Leonardo
    Univ Cambridge, Dept Radiol, Box 218,Cambridge Biomed Campus, Cambridge CB2 0QQ, England.;Univ Cambridge, Canc Res UK Cambridge Ctr, Cambridge, England.;Univ Salerno, Dept Informat & Elect Engn & Appl Math, Fisciano, Italy..
    Woitek, Ramona
    Univ Cambridge, Dept Radiol, Box 218,Cambridge Biomed Campus, Cambridge CB2 0QQ, England.;Univ Cambridge, Canc Res UK Cambridge Ctr, Cambridge, England.;Danube Private Univ, Dept Med, Krems, Austria..
    Sanchez, Lorena Escudero
    Univ Cambridge, Dept Radiol, Box 218,Cambridge Biomed Campus, Cambridge CB2 0QQ, England.;Univ Cambridge, Canc Res UK Cambridge Ctr, Cambridge, England..
    Beer, Lucian
    Univ Cambridge, Dept Radiol, Box 218,Cambridge Biomed Campus, Cambridge CB2 0QQ, England.;Univ Cambridge, Canc Res UK Cambridge Ctr, Cambridge, England.;Med Univ Vienna, Dept Biomed Imaging & Image Guided Therapy, Vienna, Austria..
    Crispin-Ortuzar, Mireia
    Univ Cambridge, Canc Res UK Cambridge Ctr, Cambridge, England.;Univ Cambridge, Canc Res UK Cambridge Inst, Cambridge, England.;Univ Cambridge, Dept Oncol, Cambridge, England..
    Etmann, Christian
    Univ Cambridge, Dept Appl Math & Theoret Phys, Cambridge, England..
    Mukherjee, Subhadip
    Univ Cambridge, Dept Appl Math & Theoret Phys, Cambridge, England..
    Bura, Vlad
    Univ Cambridge, Dept Radiol, Box 218,Cambridge Biomed Campus, Cambridge CB2 0QQ, England.;Univ Cambridge, Canc Res UK Cambridge Ctr, Cambridge, England.;Cty Clin Emergency Hosp, Dept Radiol & Med Imaging, Cluj Napoca, Romania..
    McCague, Cathal
    Univ Cambridge, Dept Radiol, Box 218,Cambridge Biomed Campus, Cambridge CB2 0QQ, England.;Univ Cambridge, Canc Res UK Cambridge Ctr, Cambridge, England..
    Sahin, Hilal
    Univ Cambridge, Dept Radiol, Box 218,Cambridge Biomed Campus, Cambridge CB2 0QQ, England.;Univ Cambridge, Canc Res UK Cambridge Ctr, Cambridge, England.;Tepecik Training & Res Hosp, Dept Radiol, Izmir, Turkiye..
    Pintican, Roxana
    Cty Clin Emergency Hosp, Dept Radiol & Med Imaging, Cluj Napoca, Romania.;Iuliu Hatieganu Univ Med & Pharm, Dept Radiol, Cluj Napoca 400012, Romania..
    Zerunian, Marta
    Sapienza Univ Rome, St Andrea Hosp, Dept Med Surg & Translat Med, Radiol Unit, Rome, Italy..
    Allajbeu, Iris
    Univ Cambridge, Dept Radiol, Box 218,Cambridge Biomed Campus, Cambridge CB2 0QQ, England..
    Singh, Naveena
    Dept Clin Pathol, Barts Hlth NHS Trust, London, England..
    Sahdev, Anju
    Barts Hlth NHS Trust, Dept Radiol, London, England..
    Havrilesky, Laura
    Duke Univ, Med Ctr, Durham, NC USA..
    Cohn, David E.
    Ohio State Univ, Coll Med, Div Gynecol Oncol, Dept Obstet & Gynecol,Comprehens Canc Ctr, Columbus, OH USA..
    Bateman, Nicholas W.
    Uniformed Serv Univ Hlth Sci, Dept Obstet & Gynecol, Gynecol Canc Ctr Excellence, Walter Reed Natl Mil Med Ctr, Bethesda, MD USA.;Walter Reed Natl Mil Med Ctr, John P Murtha Canc Ctr, Bethesda, MD USA..
    Conrads, Thomas P.
    Uniformed Serv Univ Hlth Sci, Dept Obstet & Gynecol, Gynecol Canc Ctr Excellence, Walter Reed Natl Mil Med Ctr, Bethesda, MD USA.;Walter Reed Natl Mil Med Ctr, John P Murtha Canc Ctr, Bethesda, MD USA.;Dept Obstet & Gynecol, Inova Fairfax Med Campus, Falls Church, VA USA.;Inova Ctr Personalized Hlth, Inova Schar Canc Inst, Falls Church, VA USA..
    Darcy, Kathleen M.
    Uniformed Serv Univ Hlth Sci, Dept Obstet & Gynecol, Gynecol Canc Ctr Excellence, Walter Reed Natl Mil Med Ctr, Bethesda, MD USA.;Walter Reed Natl Mil Med Ctr, John P Murtha Canc Ctr, Bethesda, MD USA..
    Maxwell, G. Larry
    Uniformed Serv Univ Hlth Sci, Dept Obstet & Gynecol, Gynecol Canc Ctr Excellence, Walter Reed Natl Mil Med Ctr, Bethesda, MD USA.;Walter Reed Natl Mil Med Ctr, John P Murtha Canc Ctr, Bethesda, MD USA.;Dept Obstet & Gynecol, Inova Fairfax Med Campus, Falls Church, VA USA..
    Freymann, John B.
    Frederick Natl Lab Canc Res, Canc Imaging Informat Lab, Frederick, MD USA..
    Öktem, Ozan
    KTH, School of Engineering Sciences (SCI), Mathematics (Dept.), Mathematics (Div.).
    Brenton, James D.
    Univ Cambridge, Canc Res UK Cambridge Ctr, Cambridge, England.;Univ Cambridge, Canc Res UK Cambridge Inst, Cambridge, England..
    Sala, Evis
    Univ Cambridge, Dept Radiol, Box 218,Cambridge Biomed Campus, Cambridge CB2 0QQ, England.;Univ Cambridge, Canc Res UK Cambridge Ctr, Cambridge, England.;Univ Cattolica Sacro Cuore, Dipartimento Sci Radiol & Ematol, Rome, Italy.;Policlin Univ A Gemelli IRCCS, Dipartimento Diagnost Immagini Radioterapia Oncol, Rome, Italy..
    Schonlieb, Carola-Bibiane
    Univ Cambridge, Dept Appl Math & Theoret Phys, Cambridge, England..
    Deep learning-based segmentation of multisite disease in ovarian cancer2023In: EUROPEAN RADIOLOGY EXPERIMENTAL, ISSN 2509-9280, Vol. 7, no 1, article id 77Article in journal (Refereed)
    Abstract [en]

    Purpose: To determine if pelvic/ovarian and omental lesions of ovarian cancer can be reliably segmented on computed tomography (CT) using fully automated deep learning-based methods.

    Methods: A deep learning model for the two most common disease sites of high-grade serous ovarian cancer lesions (pelvis/ovaries and omentum) was developed and compared against the well-established “no-new-Net” framework and unrevised trainee radiologist segmentations. A total of 451 CT scans collected from four different institutions were used for training (n = 276), evaluation (n = 104) and testing (n = 71) of the methods. The performance was evaluated using the Dice similarity coefficient (DSC) and compared using a Wilcoxon test.

    Results: Our model outperformed no-new-Net for the pelvic/ovarian lesions in cross-validation, on the evaluation and test set by a significant margin (p values being 4 × 10–7, 3 × 10–4, 4 × 10–2, respectively), and for the omental lesions on the evaluation set (p = 1 × 10–3). Our model did not perform significantly differently in segmenting pelvic/ovarian lesions (p = 0.371) compared to a trainee radiologist. On an independent test set, the model achieved a DSC performance of 71 ± 20 (mean ± standard deviation) for pelvic/ovarian and 61 ± 24 for omental lesions.

    Conclusion: Automated ovarian cancer segmentation on CT scans using deep neural networks is feasible and achieves performance close to a trainee-level radiologist for pelvic/ovarian lesions.

    Relevance statement: Automated segmentation of ovarian cancer may be used by clinicians for CT-based volumetric assessments and researchers for building complex analysis pipelines.

    Key points:

    • The first automated approach for pelvic/ovarian and omental ovarian cancer lesion segmentation on CT images has been presented.
    • Automated segmentation of ovarian cancer lesions can be comparable with manual segmentation of trainee radiologists.
    • Careful hyperparameter tuning can provide models significantly outperforming strong state-of-the-art baselines. Graphical Abstract: [Figure not available: see fulltext.]
  • 28.
    Byström, Sanna
    et al.
    KTH, School of Biotechnology (BIO), Proteomics and Nanobiotechnology.
    Eklund, Martin
    KTH, School of Biotechnology (BIO), Proteomics and Nanobiotechnology.
    Hong, Mun-Gwan
    KTH, School of Biotechnology (BIO), Proteomics and Nanobiotechnology.
    Fredolini, Claudia
    KTH, School of Biotechnology (BIO), Proteomics and Nanobiotechnology.
    Eriksson, Mikael
    Czene, Kamila
    Hall, Per
    Schwenk, Jochen. M.
    KTH, School of Biotechnology (BIO), Proteomics and Nanobiotechnology.
    Gabrielson, Marike
    Affinity proteomic profiling of plasma for proteins associated to mammographic breast densityManuscript (preprint) (Other academic)
  • 29.
    Byström, Sanna
    et al.
    KTH, School of Biotechnology (BIO), Proteomics and Nanobiotechnology.
    Fredolini, Claudia
    KTH, School of Biotechnology (BIO), Proteomics and Nanobiotechnology.
    Edqvist, Per-Henrik
    Nyaiesh, Etienne-Nicholas
    Drobin, Kimi
    KTH, School of Biotechnology (BIO), Proteomics and Nanobiotechnology.
    Uhlén, Matthias
    KTH, School of Biotechnology (BIO), Proteomics and Nanobiotechnology.
    Bergqvist, Michael
    Pontén, Fredrik
    Schwenk, Jochen M.
    KTH, School of Biotechnology (BIO), Proteomics and Nanobiotechnology.
    Affinity proteomics exploration of melanoma identifies proteins in serum with associations to T-stage and recurrenceManuscript (preprint) (Other academic)
  • 30.
    Carannante, Valentina
    et al.
    KTH, School of Engineering Sciences (SCI), Applied Physics, Biophysics. KTH, Centres, Science for Life Laboratory, SciLifeLab.
    Sandström, Niklas
    KTH, School of Engineering Sciences (SCI), Applied Physics, Biophysics. KTH, Centres, Science for Life Laboratory, SciLifeLab.
    Olofsson, Karl
    KTH, Centres, Science for Life Laboratory, SciLifeLab. KTH, School of Engineering Sciences (SCI), Applied Physics, Biophysics.
    van Ooijen, Hanna
    KTH, School of Engineering Sciences (SCI), Applied Physics, Biophysics. KTH, Centres, Science for Life Laboratory, SciLifeLab.
    Hell, Birte
    KTH, Centres, Science for Life Laboratory, SciLifeLab. KTH, School of Engineering Sciences (SCI), Applied Physics, Biophysics.
    Wiklund, Martin
    KTH, Centres, Science for Life Laboratory, SciLifeLab. KTH, School of Engineering Sciences (SCI), Applied Physics, Biophysics.
    Önfelt, Björn
    KTH, Centres, Science for Life Laboratory, SciLifeLab. KTH, School of Engineering Sciences (SCI), Applied Physics, Biophysics. Center for Infectious Medicine, Dept. of Medicine Huddinge, Karolinska Institutet, Stockholm, Sweden.
    Generation of tumor spheroids in microwells to study NK cell cytotoxicity, infiltration and phenotype2023In: Methods in Cell Biology, Elsevier BV , 2023, Vol. 178, p. 195-208Chapter in book (Other academic)
    Abstract [en]

    The development of new immunotherapeutic drugs and combinatorial strategies requires the implementation of novel methods to test their efficacy in vitro. Here, we present a series of miniaturized in vitro assays to assess immune cell cytotoxic activity, infiltration, and phenotype in renal carcinoma spheroids with the use of a recently developed multichambered microwell chip. We provide protocols for tumor spheroid formation, NK cell culture, fluorescence labelling and imaging of live or fixed cells directly in the chip together with data analysis.

  • 31.
    Carannante, Valentina
    et al.
    KTH, School of Engineering Sciences (SCI), Applied Physics, Biophysics.
    Wiklund, Martin
    KTH, Centres, Science for Life Laboratory, SciLifeLab. KTH, School of Engineering Sciences (SCI), Applied Physics, Biophysics.
    Önfelt, Björn
    KTH, Centres, Science for Life Laboratory, SciLifeLab. KTH, School of Engineering Sciences (SCI), Applied Physics, Biophysics. Karolinska Inst, Ctr Infect Med, Dept Med Huddinge, Sci Life Lab, Stockholm, Sweden..
    In vitro models to study natural killer cell dynamics in the tumor microenvironment2023In: Frontiers in Immunology, E-ISSN 1664-3224, Vol. 14, article id 1135148Article, review/survey (Refereed)
    Abstract [en]

    Immunotherapy is revolutionizing cancer therapy. The rapid development of new immunotherapeutic strategies to treat solid tumors is posing new challenges for preclinical research, demanding novel in vitro methods to test treatments. Such methods should meet specific requirements, such as enabling the evaluation of immune cell responses like cytotoxicity or cytokine release, and infiltration into the tumor microenvironment using cancer models representative of the original disease. They should allow high-throughput and high-content analysis, to evaluate the efficacy of treatments and understand immune-evasion processes to facilitate development of new therapeutic targets. Ideally, they should be suitable for personalized immunotherapy testing, providing information for patient stratification. Consequently, the application of in vitro 3-dimensional (3D) cell culture models, such as tumor spheroids and organoids, is rapidly expanding in the immunotherapeutic field, coupled with the development of novel imaging-based techniques and -omic analysis. In this paper, we review the recent advances in the development of in vitro 3D platforms applied to natural killer (NK) cell-based cancer immunotherapy studies, highlighting the benefits and limitations of the current methods, and discuss new concepts and future directions of the field.

  • 32.
    Chen, Xinsong
    et al.
    Department of Oncology-Pathology, Karolinska Institutet, Stockholm 17164, Sweden.
    Sifakis, Emmanouil G.
    Department of Oncology-Pathology, Karolinska Institutet, Stockholm 17164, Sweden.
    Robertson, Stephanie
    Department of Oncology-Pathology, Karolinska Institutet, Stockholm 17164, Sweden; Department of Clinical Pathology and Cancer Diagnostics, Karolinska University Hospital, Stockholm 17176, Sweden.
    Neo, Shi Yong
    Department of Oncology-Pathology, Karolinska Institutet, Stockholm 17164, Sweden.
    Jun, Seong-Hwan
    KTH, School of Electrical Engineering and Computer Science (EECS), Computer Science, Computational Science and Technology (CST). KTH, Centres, Science for Life Laboratory, SciLifeLab.
    Tong, Le
    Department of Oncology-Pathology, Karolinska Institutet, Stockholm 17164, Sweden.
    Min, Apple Tay Hui
    Department of Oncology-Pathology, Karolinska Institutet, Stockholm 17164, Sweden; School of Biological Sciences, Nanyang Technological University, Singapore 637551, Singapore.
    Lövrot, John
    Department of Oncology-Pathology, Karolinska Institutet, Stockholm 17164, Sweden.
    Hellgren, Roxanna
    Department of Breast Imaging, Södersjukhuset, Stockholm 11828, Sweden.
    Margolin, Sara
    Department of Clinical Science and Education, Södersjukhuset, Karolinska Institutet, Stockholm 11883, Sweden.
    Bergh, Jonas
    Department of Oncology-Pathology, Karolinska Institutet, Stockholm 17164, Sweden; Breast Center, Theme Cancer, Karolinska University Hospital, Stockholm 17176, Sweden.
    Foukakis, Theodoros
    Department of Oncology-Pathology, Karolinska Institutet, Stockholm 17164, Sweden; Breast Center, Theme Cancer, Karolinska University Hospital, Stockholm 17176, Sweden.
    Lagergren, Jens
    KTH, School of Electrical Engineering and Computer Science (EECS), Computer Science, Computational Science and Technology (CST). KTH, Centres, Science for Life Laboratory, SciLifeLab. Department of Computational Biology, Royal Institute of Technology, Science for Life Laboratory, Stockholm 17165, Sweden.
    Lundqvist, Andreas
    Department of Oncology-Pathology, Karolinska Institutet, Stockholm 17164, Sweden.
    Ma, Ran
    Department of Oncology-Pathology, Karolinska Institutet, Stockholm 17164, Sweden.
    Hartman, Johan
    Department of Oncology-Pathology, Karolinska Institutet, Stockholm 17164, Sweden; Department of Clinical Pathology and Cancer Diagnostics, Karolinska University Hospital, Stockholm 17176, Sweden.
    Breast cancer patient-derived whole-tumor cell culture model for efficient drug profiling and treatment response prediction2023In: Proceedings of the National Academy of Sciences of the United States of America, ISSN 0027-8424, E-ISSN 1091-6490, Vol. 120, no 1, article id e2209856120Article in journal (Refereed)
    Abstract [en]

    Breast cancer (BC) is a complex disease comprising multiple distinct subtypes with different genetic features and pathological characteristics. Although a large number of antineoplastic compounds have been approved for clinical use, patient-to-patient variability in drug response is frequently observed, highlighting the need for efficient treatment prediction for individualized therapy. Several patient-derived models have been established lately for the prediction of drug response. However, each of these models has its limitations that impede their clinical application. Here, we report that the whole-tumor cell culture (WTC) ex vivo model could be stably established from all breast tumors with a high success rate (98 out of 116), and it could reassemble the parental tumors with the endogenous microenvironment. We observed strong clinical associations and predictive values from the investigation of a broad range of BC therapies with WTCs derived from a patient cohort. The accuracy was further supported by the correlation between WTC-based test results and patients' clinical responses in a separate validation study, where the neoadjuvant treatment regimens of 15 BC patients were mimicked. Collectively, the WTC model allows us to accomplish personalized drug testing within 10 d, even for small-sized tumors, highlighting its potential for individualized BC therapy. Furthermore, coupled with genomic and transcriptomic analyses, WTC-based testing can also help to stratify specific patient groups for assignment into appropriate clinical trials, as well as validate potential biomarkers during drug development.

  • 33.
    Cheng, Yirui
    et al.
    State Key Laboratory of Oncogenes and Related Genes, Ren Ji Hospital, School of Medicine and School of Biomedical Engineering, Shanghai Jiao Tong University, 200030, Shanghai, China.
    Lu, Xin
    State Key Laboratory of Oncogenes and Related Genes, Ren Ji Hospital, School of Medicine and School of Biomedical Engineering, Shanghai Jiao Tong University, 200030, Shanghai, China.
    Li, Fan
    State Key Laboratory of Oncogenes and Related Genes, Ren Ji Hospital, School of Medicine and School of Biomedical Engineering, Shanghai Jiao Tong University, 200030, Shanghai, China.
    Chen, Zhuo
    State Key Laboratory of Oncogenes and Related Genes, Ren Ji Hospital, School of Medicine and School of Biomedical Engineering, Shanghai Jiao Tong University, 200030, Shanghai, China.
    Zhang, Yanshuang
    State Key Laboratory of Oncogenes and Related Genes, Ren Ji Hospital, School of Medicine and School of Biomedical Engineering, Shanghai Jiao Tong University, 200030, Shanghai, China.
    Han, Qing
    State Key Laboratory of Oncogenes and Related Genes, Ren Ji Hospital, School of Medicine and School of Biomedical Engineering, Shanghai Jiao Tong University, 200030, Shanghai, China.
    Zeng, Qingyu
    Shanghai Skin Disease Hospital, Tongji University School of Medicine, 200092, Shanghai, China.
    Wu, Tingyu
    State Key Laboratory of Oncogenes and Related Genes, Ren Ji Hospital, School of Medicine and School of Biomedical Engineering, Shanghai Jiao Tong University, 200030, Shanghai, China.
    Li, Ziming
    Shanghai Lung Cancer Center, Shanghai Chest Hospital, Shanghai Jiao Tong University, 200030, Shanghai, China.
    Lu, Shun
    Shanghai Lung Cancer Center, Shanghai Chest Hospital, Shanghai Jiao Tong University, 200030, Shanghai, China.
    Williams, Cecilia
    KTH, Centres, Science for Life Laboratory, SciLifeLab. KTH, School of Engineering Sciences in Chemistry, Biotechnology and Health (CBH), Protein Science, Cellular and Clinical Proteomics.
    Xia, Weiliang
    State Key Laboratory of Oncogenes and Related Genes, Ren Ji Hospital, School of Medicine and School of Biomedical Engineering, Shanghai Jiao Tong University, 200030, Shanghai, China.
    NDFIP1 limits cellular TAZ accumulation via exosomal sorting to inhibit NSCLC proliferation2023In: Protein & Cell, ISSN 1674-800X, E-ISSN 1674-8018, Vol. 14, no 2, p. 123-136Article in journal (Refereed)
    Abstract [en]

    NDFIP1 has been previously reported as a tumor suppressor in multiple solid tumors, but the function of NDFIP1 in NSCLC and the underlying mechanism are still unknown. Besides, the WW domain containing proteins can be recognized by NDFIP1, resulted in the loading of the target proteins into exosomes. However, whether WW domain-containing transcription regulator 1 (WWTR1, also known as TAZ) can be packaged into exosomes by NDFIP1 and if so, whether the release of this oncogenic protein via exosomes has an effect on tumor development has not been investigated to any extent. Here, we first found that NDFIP1 was low expressed in NSCLC samples and cell lines, which is associated with shorter OS. Then, we confirmed the interaction between TAZ and NDFIP1, and the existence of TAZ in exosomes, which requires NDFIP1. Critically, knockout of NDFIP1 led to TAZ accumulation with no change in its mRNA level and degradation rate. And the cellular TAZ level could be altered by exosome secretion. Furthermore, NDFIP1 inhibited proliferation in vitro and in vivo, and silencing TAZ eliminated the increase of proliferation caused by NDFIP1 knockout. Moreover, TAZ was negatively correlated with NDFIP1 in subcutaneous xenograft model and clinical samples, and the serum exosomal TAZ level was lower in NSCLC patients. In summary, our data uncover a new tumor suppressor, NDFIP1 in NSCLC, and a new exosome-related regulatory mechanism of TAZ.

  • 34.
    Chinnadurai, Raj Kumar
    et al.
    Mahatma Gandhi Medical Advanced Research Institute, Sri Balaji Vidhyapeeth, Pondicherry 607402, India.
    Khan, Nazam
    Clinical laboratory science Department, Applied Medical Science College, Shaqra University, Shaqra, KSA.
    Meghwanshi, Gautam Kumar
    Department of Microbiology, M.G.S. University, Bikaner, India.
    Ponne, Saravanaraman
    Department of Biotechnology, Pondicherry University, Pondicherry 605014, India.
    Althobiti, Maryam
    Clinical laboratory science Department, Applied Medical Science College, Shaqra University, Shaqra, KSA.
    Kumar, Rajender
    KTH, School of Engineering Sciences in Chemistry, Biotechnology and Health (CBH), Chemistry, Glycoscience.
    Current research status of anti-cancer peptides: Mechanism of action, production, and clinical applications2023In: Biomedicine and Pharmacotherapy, ISSN 0753-3322, E-ISSN 1950-6007, Vol. 164, article id 114996Article, review/survey (Refereed)
    Abstract [en]

    The escalating rate of cancer cases, together with treatment deficiencies and long-term side effects of currently used cancer drugs, has made this disease a global burden of the 21st century. The number of breast and lung cancer patients has sharply increased worldwide in the last few years. Presently, surgical treatment, radiotherapy, chemotherapy, and immunotherapy strategies are used to cure cancer, which cause severe side effects, toxicities, and drug resistance. In recent years, anti-cancer peptides have become an eminent therapeutic strategy for cancer treatment due to their high specificity and fewer side effects and toxicity. This review presents an updated overview of different anti-cancer peptides, their mechanisms of action and current production strategies employed for their manufacture. In addition, approved and under clinical trials anti-cancer peptides and their applications have been discussed. This review provides updated information on therapeutic anti-cancer peptides that hold great promise for cancer treatment in the near future.

  • 35.
    Cini, Giulia
    et al.
    Ctr Riferimento Oncol Aviano CRO IRCCS, Unit Funct Oncogen & Genet, Via F Gallini 2, I-33081 Aviano, Italy..
    Carnevali, Ileana
    Circolo Hosp ASST Settelaghi, Dept Pathol, Via O Rossi 9, I-21100 Varese, Italy.;Univ Insubria, Dept Med & Surg, Res Ctr Study Hereditary & Familial Tumors, Via O Rossi 9, I-21100 Varese, Italy..
    Sahnane, Nora
    Circolo Hosp ASST Settelaghi, Dept Pathol, Via O Rossi 9, I-21100 Varese, Italy.;Univ Insubria, Dept Med & Surg, Res Ctr Study Hereditary & Familial Tumors, Via O Rossi 9, I-21100 Varese, Italy..
    Chiaravalli, Anna Maria
    Circolo Hosp ASST Settelaghi, Dept Pathol, Via O Rossi 9, I-21100 Varese, Italy.;Univ Insubria, Dept Med & Surg, Res Ctr Study Hereditary & Familial Tumors, Via O Rossi 9, I-21100 Varese, Italy..
    Dell'Elice, Anastasia
    Ctr Riferimento Oncol Aviano CRO IRCCS, Unit Funct Oncogen & Genet, Via F Gallini 2, I-33081 Aviano, Italy..
    Maestro, Roberta
    Ctr Riferimento Oncol Aviano CRO IRCCS, Unit Funct Oncogen & Genet, Via F Gallini 2, I-33081 Aviano, Italy..
    Pin, Elisa
    KTH, School of Engineering Sciences in Chemistry, Biotechnology and Health (CBH), Protein Science, Affinity Proteomics. KTH, Centres, Science for Life Laboratory, SciLifeLab.
    Bestetti, Ilaria
    IRCCS Ist Auxol Italiano, Res Lab Med Cytogenet & Mol Genet, Via Zucchi 18, I-20095 Cusano Milanino, MI, Italy.;Univ Milan, Dept Med Biotechnol & Translat Med, Via Vanvitelli 32, I-20133 Milan, Italy..
    Radovic, Slobodanka
    IGA Technol Serv Srl, Via J Linussio 51, I-33100 Udine, Italy..
    Armelao, Franco
    APSS, Osped S Chiara, UO Gastroenterol & Endoscopia Digest, Via A de Gasperi 79, I-38123 Trento, Italy..
    Viel, Alessandra
    Ctr Riferimento Oncol Aviano CRO IRCCS, Unit Funct Oncogen & Genet, Via F Gallini 2, I-33081 Aviano, Italy..
    Tibiletti, Maria Grazia
    Circolo Hosp ASST Settelaghi, Dept Pathol, Via O Rossi 9, I-21100 Varese, Italy.;Univ Insubria, Dept Med & Surg, Res Ctr Study Hereditary & Familial Tumors, Via O Rossi 9, I-21100 Varese, Italy..
    Lynch syndrome and Muir-Torre phenotype associated with a recurrent variant in the 3 ' UTR of the MSH6 gene2021In: Cancer Genetics, ISSN 2210-7762, E-ISSN 2210-7770, Vol. 254, p. 1-10Article in journal (Refereed)
    Abstract [en]

    A MSH6 3'UTR variant (c.*23_26dup) was found in 13 unrelated families consulted for Lynch/Muir-Torre Syndrome. This variant, which is very rare in the genomic databases, was absent in healthy controls and strongly segregated with the disease in the studied pedigrees. All tumors were defective for MSH2/MSH6/MSH3 proteins expression, but only MSH2 somatic pathogenic mutations were found in 5 of the 12 sequenced tumors. Moreover, we had no evidence of MSH6 transcript decrease in carriers, whereas MSH2 transcript was downregulated. Additional evaluations performed in representative carriers, including karyotype, arrayCGH and Linked-Reads whole genome sequencing, failed to evidence any MSH2 germline pathogenic variant. Posterior probability of pathogenicity for MSH6 c.*23_26dup was obtained from a multifactorial analysis incorporating segregation and phenotypic data and resulted >0.999, allowing to classify the variant as pathogenic (InSiGHT Class 5). Carriers shared a common haplotype involving MSH2/MSH6 loci, then a cryptic disease-associated variant, linked with MSH6 c.*23_26dup, cannot be completely excluded. Even if it is not clear whether the MSH6 variant is pathogenic per se or simply a marker of a disease-associated MSH2/MSH6 haplotype, all data collected on patients and pedigrees prompted us to manage the variant as pathogenic and to offer predictive testing within these families.

  • 36.
    Collodet, Caterina
    et al.
    KTH, School of Engineering Sciences in Chemistry, Biotechnology and Health (CBH), Protein Science, Protein Technology.
    Blust, Kelly
    KTH, School of Engineering Sciences in Chemistry, Biotechnology and Health (CBH), Protein Science, Protein Technology.
    Gkouma, Savvini
    KTH, School of Engineering Sciences in Chemistry, Biotechnology and Health (CBH), Protein Science, Protein Technology.
    Ståhl, Emmy
    KTH, School of Engineering Sciences in Chemistry, Biotechnology and Health (CBH), Protein Science, Protein Technology.
    Chen, Xinsong
    Department of Oncology-Pathology, Karolinska Institutet, Stockholm, Sweden.
    Hartman, Johan
    Department of Oncology-Pathology, Karolinska Institutet, Stockholm, Sweden; Department of Clinical Pathology and Cancer Diagnostics, Karolinska University Hospital, Stockholm, Sweden.
    Hedhammar, My
    KTH, School of Engineering Sciences in Chemistry, Biotechnology and Health (CBH), Protein Science, Protein Technology.
    Development and characterization of a recombinant silk network for 3D culture of immortalized and fresh tumor-derived breast cancer cells2023In: Bioengineering and Translational Medicine, E-ISSN 2380-6761, Vol. 8, no 5, article id e10537Article in journal (Refereed)
    Abstract [en]

    Traditional cancer models rely on 2D cell cultures or 3D spheroids, which fail to recapitulate cell-extracellular matrix (ECM) interactions, a key element of tumor development. Existing hydrogel-based 3D alternatives lack mechanical support for cell growth and often suffer from low reproducibility. Here we report a novel strategy to make 3D models of breast cancer using a tissue-like, well-defined network environment based on recombinant spider silk, functionalized with a cell adhesion motif from fibronectin (FN-silk). With this approach, the canonical cancer cells SK-BR-3, MCF-7, and MDA-MB-231, maintain their characteristic expression of markers (i.e., ERα, HER2, and PGR) while developing distinct morphology. Transcriptomic analyses demonstrate how culture in the FN-silk networks modulates the biological processes of cell adhesion and migration while affecting physiological events involved in malignancy, such as inflammation, remodeling of the ECM, and resistance to anticancer drugs. Finally, we show that integration in FN-silk networks promotes the viability of cells obtained from the superficial scraping of patients' breast tumors.

  • 37.
    Cossío, Fernando
    et al.
    Karolinska Institute Department of Oncology-Pathology Stockholm Sweden; Karolinska University Hospital Department of Radiology Stockholm Sweden.
    Schurz, Haiko
    Karolinska Institute Department of Oncology-Pathology Stockholm Sweden.
    Engström, Mathias
    Collective Minds Radiology Stockholm Sweden.
    Barck-Holst, Carl
    West Code Group Stockholm Sweden.
    Tsirikoglou, Apostolia
    Karolinska Institute Department of Oncology-Pathology Stockholm Sweden.
    Lundström, Claes
    Linköping University Center for Medical Image Science and Visualization (CMIV) Linköping Sweden.
    Gustafsson, Håkan
    Linköping University Center for Medical Image Science and Visualization (CMIV) Linköping Sweden; Linköping University Department of Medical Radiation Physics Department of Health Medicine and Caring Sciences Linköping Sweden.
    Smith, Kevin
    KTH, School of Electrical Engineering and Computer Science (EECS), Computer Science, Computational Science and Technology (CST).
    Zackrisson, Sophia
    Lund University Department of Diagnostic Radiology Translational Medicine Malmö Sweden; Skåne University Hospital Department of Imaging and Physiology Malmö Sweden.
    Strand, Fredrik
    Karolinska Institute Department of Oncology-Pathology Stockholm Sweden; Karolinska University Hospital Department of Radiology Stockholm Sweden.
    VAI-B: A multicenter platform for the external validation of artificial intelligence algorithms in breast imaging2023In: Journal of Medical Imaging, ISSN 2329-4302, E-ISSN 2329-4310, Vol. 10, no 6, article id 061404Article in journal (Refereed)
    Abstract [en]

    Purpose: Multiple vendors are currently offering artificial intelligence (AI) computer-aided systems for triage detection, diagnosis, and risk prediction of breast cancer based on screening mammography. There is an imminent need to establish validation platforms that enable fair and transparent testing of these systems against external data. Approach: We developed validation of artificial intelligence for breast imaging (VAI-B), a platform for independent validation of AI algorithms in breast imaging. The platform is a hybrid solution, with one part implemented in the cloud and another in an on-premises environment at Karolinska Institute. Cloud services provide the flexibility of scaling the computing power during inference time, while secure on-premises clinical data storage preserves their privacy. A MongoDB database and a python package were developed to store and manage the data onpremises. VAI-B requires four data components: radiological images, AI inferences, radiologist assessments, and cancer outcomes. Results: To pilot test VAI-B, we defined a case-control population based on 8080 patients diagnosed with breast cancer and 36,339 healthy women based on the Swedish national quality registry for breast cancer. Images and radiological assessments from more than 100,000 mammography examinations were extracted from hospitals in three regions of Sweden. The images were processed by AI systems from three vendors in a virtual private cloud to produce abnormality scores related to signs of cancer in the images. A total of 105,706 examinations have been processed and stored in the database. Conclusions: We have created a platform that will allow downstream evaluation of AI systems for breast cancer detection, which enables faster development cycles for participating vendors and safer AI adoption for participating hospitals. The platform was designed to be scalable and ready to be expanded should a new vendor want to evaluate their system or should a new hospital wish to obtain an evaluation of different AI systems on their images.

  • 38.
    Dembrower, Karin
    et al.
    Karolinska Inst, Dept Physiol & Pharmacol, Stockholm, Sweden.;Capio St Gorans Hosp, Dept Radiol, Stockholm, Sweden..
    Wahlin, Erik
    Karolinska Univ Hosp, Dept Med Radiat Phys & Nucl Med, Stockholm, Sweden..
    Liu, Yue
    KTH, School of Electrical Engineering and Computer Science (EECS), Computer Science, Computational Science and Technology (CST). KTH, Centres, Science for Life Laboratory, SciLifeLab.
    Salim, Mattie
    Karolinska Inst, Dept Pathol & Oncol, Stockholm, Sweden.;Karolinska Univ Hosp, Dept Radiol, Stockholm, Sweden..
    Smith, Kevin
    KTH, School of Electrical Engineering and Computer Science (EECS), Computer Science, Computational Science and Technology (CST). KTH, Centres, Science for Life Laboratory, SciLifeLab.
    Lindholm, Peter
    Karolinska Inst, Dept Physiol & Pharmacol, Stockholm, Sweden..
    Eklund, Martin
    Karolinska Inst, Dept Med Epidemiol & Biostat, Stockholm, Sweden..
    Strand, Fredrik
    Karolinska Inst, Dept Pathol & Oncol, Stockholm, Sweden.;Karolinska Univ Hosp, Breast Radiol, Stockholm, Sweden..
    Effect of artificial intelligence-based triaging of breast cancer screening mammograms on cancer detection and radiologist workload: a retrospective simulation study2020In: The Lancet Digital Health, E-ISSN 2589-7500, Vol. 2, no 9, p. E468-E474Article in journal (Refereed)
    Abstract [en]

    Background We examined the potential change in cancer detection when using an artificial intelligence (AI) cancer-detection software to triage certain screening examinations into a no radiologist work stream, and then after regular radiologist assessment of the remainder, triage certain screening examinations into an enhanced assessment work stream. The purpose of enhanced assessment was to simulate selection of women for more sensitive screening promoting early detection of cancers that would otherwise be diagnosed as interval cancers or as next-round screen-detected cancers. The aim of the study was to examine how AI could reduce radiologist workload and increase cancer detection. Methods In this retrospective simulation study, all women diagnosed with breast cancer who attended two consecutive screening rounds were included. Healthy women were randomly sampled from the same cohort; their observations were given elevated weight to mimic a frequency of 0.7% incident cancer per screening interval. Based on the prediction score from a commercially available AI cancer detector, various cutoff points for the decision to channel women to the two new work streams were examined in terms of missed and additionally detected cancer. Findings 7364 women were included in the study sample: 547 were diagnosed with breast cancer and 6817 were healthy controls. When including 60%, 70%, or 80% of women with the lowest AI scores in the no radiologist stream, the proportion of screen-detected cancers that would have been missed were 0, 0.3% (95% CI 0.0-4.3), or 2.6% (1.1-5.4), respectively. When including 1% or 5% of women with the highest AI scores in the enhanced assessment stream, the potential additional cancer detection was 24 (12%) or 53 (27%) of 200 subsequent interval cancers, respectively, and 48 (14%) or 121 (35%) of 347 next-round screen-detected cancers, respectively. Interpretation Using a commercial AI cancer detector to triage mammograms into no radiologist assessment and enhanced assessment could potentially reduce radiologist workload by more than half, and pre-emptively detect a substantial proportion of cancers otherwise diagnosed later.

  • 39.
    Dewyngaert, J. Keith
    et al.
    New York University.
    Noz, Marilyn E.
    New York University, Department of Radiology.
    Ellerin, B.
    New York University.
    Kramer, Elissa L.
    New York University, Department of Radiology.
    Maguire Jr., Gerald Q.
    KTH, Superseded Departments (pre-2005), Microelectronics and Information Technology, IMIT.
    Zeleznik, Michael P.
    RAHD Oncology Products, St. Louis, MO, USA.
    Procedure for unmasking localization information from ProstaScint scans for prostate radiation therapy treatment planning2004In: International Journal of Radiation Oncology, Biology, Physics, ISSN 0360-3016, E-ISSN 1879-355X, Vol. 60, no 2, p. 654-662Article in journal (Refereed)
    Abstract [en]

    Purpose: To demonstrate a method to extract the meaningful biologic information from In-111-radiolabeled capromab pendetide (ProstaScint) SPECT scans for use in radiation therapy treatment planning by removing that component of the In-111 SPECT images associated with normal structures. Methods and Materials: We examined 20 of more than 80 patients who underwent simultaneous Tc-99m/In-111 SPECT scans, which were subsequently registered to the corresponding CT/MRI scans. A thresholding algorithm was used to identify Tc-99m uptake associated with blood vessels and CT electron density associated with bone marrow. Corresponding voxels were removed from the In-111 image set. Results: No single threshold value was found to be associated with the Tc-99m uptake that corresponded to the blood vessels. Intensity values were normalized to a global maximum and, as such, were dependent upon the quantity of Tc-99m pooled in the bladder. The reduced ProstaScint volume sets were segmented by use of a thresholding feature of the planning system and superimposed on the CT/MRI scans. Conclusions: ProstaScint images are now closer to becoming a biologically and therapeutically useful and accurate image set. After known sources of normal intensity are stripped away, the remaining areas that demonstrate uptake may be segmented and superimposed on the treatment-planning CT/MRI volume.

  • 40. Dijksterhuis, Jacomijn P.
    et al.
    Arthofer, Elisa
    Marinescu, Voichita D.
    Nelander, Sven
    Uhlen, Mathias
    KTH, School of Biotechnology (BIO), Proteomics and Nanobiotechnology.
    Ponten, Frederik
    Mulder, Jan
    Schulte, Gunnar
    High levels of WNT-5A in human glioma correlate with increased presence of tumor-associated microglia/monocytes2015In: Experimental Cell Research, ISSN 0014-4827, E-ISSN 1090-2422, Vol. 339, no 2, p. 280-288Article in journal (Refereed)
    Abstract [en]

    Malignant gliomas are among the most severe types of cancer, and the most common primary brain tumors. Treatment options are limited and the prognosis is poor. WNT-5A, a member of the WNT family of lipoglycoproteins, plays a role in oncogenesis and tumor progression in various cancers, whereas the role of WNT-5A in glioma remains obscure. Based on the role of WNT-5A as an oncogene, its potential to regulate microglia cells and the glioma-promoting capacities of microglia cells, we hypothesize that WNT-5A has a role in regulation of immune functions in glioma. We investigated WNT-5A expression by in silico analysis of the cancer genome atlas (TCGA) transcript profiling of human glioblastoma samples and immunohistochemistry experiments of human glioma tissue microarrays (TMA). Our results reveal higher WNT-5A protein levels and mRNA expression in a subgroup of gliomas (WNT-5A(high)) compared to non-malignant control brain tissue. Furthermore, we show a significant correlation between WNT-5A in the tumor and presence of major histocompatibility complex Class II-positive microglia/monocytes. Our data pinpoint a positive correlation between WNT-5A and a proinflammatory signature in glioma. We identify increased presence of microglia/monocytes as an important aspect in the inflammatory transformation suggesting a novel role for WNT-5A in human glioma.

  • 41.
    Djureinovic, D.
    et al.
    Uppsala Univ, Dept Immunol Genet & Pathol, Uppsala, Sweden..
    Hellström, Cecilia
    KTH, Centres, Science for Life Laboratory, SciLifeLab.
    Dodig-Crnkovic, Tea
    KTH, Centres, Science for Life Laboratory, SciLifeLab.
    Ponten, F.
    Uppsala Univ, Dept Immunol Genet & Pathol, Uppsala, Sweden..
    Bergqvist, M.
    Gavle Cent Hosp, Dept Oncol, Gavle, Sweden..
    Holgersson, G.
    Gavle Cent Hosp, Dept Oncol, Gavle, Sweden..
    Schwenk, Jochen M.
    KTH, Centres, Science for Life Laboratory, SciLifeLab.
    Micke, P.
    Uppsala Univ, Dept Immunol Genet & Pathol, Uppsala, Sweden..
    Autoantibody Profiles of Cancer-Testis Genes in Non-Small Cell Lung Cancer2017In: Journal of Thoracic Oncology, ISSN 1556-0864, E-ISSN 1556-1380, Vol. 12, no 11, p. S2002-S2002Article in journal (Other academic)
  • 42. Djureinovic, Dijana
    et al.
    Hallström, Björn
    KTH, School of Biotechnology (BIO), Proteomics and Nanobiotechnology. KTH, Centres, Science for Life Laboratory, SciLifeLab.
    Mattsson, Johanna Sofia Margareta
    La Fleur, Linnea
    Botling, Johan
    Fagerberg, Linn
    Brunnstrom, Hans
    Ekman, Simon
    Stahle, Elisabeth
    Koyi, Hirsh
    Lambe, Mats
    Branden, Eva
    Lindskog, Cecilia
    Ponten, Fredrik
    Uhlen, Mathias
    KTH, School of Biotechnology (BIO), Proteomics and Nanobiotechnology. KTH, Centres, Science for Life Laboratory, SciLifeLab.
    Micke, Patrick
    The Identification of Therapeutic Targets in Lung Cancer Based on Transcriptomic and Proteomic Characterization of Cancer-Testis Antigens2015In: Journal of Thoracic Oncology, ISSN 1556-0864, E-ISSN 1556-1380, Vol. 10, no 9, p. S256-S256Article in journal (Other academic)
  • 43.
    Dohlmar, Frida
    et al.
    Linköping Univ, Dept Hlth Med & Caring Sci, Med Radiat Phys, Linköping, Sweden.;Linköping Univ, Ctr Med Image Sci & Visualizat, CMIV, Linköping, Sweden.;Linköping Univ Hosp, Ohuset Ingang 34 Pl 08, S-58185 Linköping, Sweden..
    Moren, Bjorn
    Linköping Univ, Dept Math, Linköping, Sweden..
    Sandborg, Michael
    Linköping Univ, Dept Hlth Med & Caring Sci, Med Radiat Phys, Linköping, Sweden.;Linköping Univ, Ctr Med Image Sci & Visualizat, CMIV, Linköping, Sweden..
    Smedby, Örjan
    KTH, School of Engineering Sciences in Chemistry, Biotechnology and Health (CBH).
    Valdman, Alexander
    Karolinska Inst, Dept Oncol Pathol, Stockholm, Sweden..
    Larsson, Torbjorn
    Linköping Univ, Dept Math, Linköping, Sweden..
    Tedgren, Asa Carlsson
    Linköping Univ, Dept Hlth Med & Caring Sci, Med Radiat Phys, Linköping, Sweden.;Linköping Univ, Ctr Med Image Sci & Visualizat, CMIV, Linköping, Sweden.;Karolinska Univ Hosp, Dept Med Radiat Phys & Nucl Med, Stockholm, Sweden.;Karolinska Inst, Dept Oncol Pathol, Stockholm, Sweden..
    Validation of automated post-adjustments of HDR prostate brachytherapy treatment plans by quantitative measures and oncologist observer study2023In: Brachytherapy, ISSN 1538-4721, E-ISSN 1873-1449, Vol. 22, no 3, p. 407-415Article in journal (Refereed)
    Abstract [en]

    PURPOSE: The aim was to evaluate a postprocessing optimization algorithm's ability to improve the spatial properties of a clinical treatment plan while preserving the target coverage and the dose to the organs at risk. The goal was to obtain a more homogenous treatment plan, minimizing the need for manual adjustments after inverse treatment planning. MATERIALS AND METHODS: The study included 25 previously treated prostate cancer pa-tients. The treatment plans were evaluated on dose-volume histogram parameters established clin-ical and quantitative measures of the high dose volumes. The volumes of the four largest hot spots were compared and complemented with a human observer study with visual grading by eight oncologists. Statistical analysis was done using ordinal logistic regression. Weighted kappa and Fleiss' kappa were used to evaluate intra-and interobserver reliability. RESULTS: The quantitative analysis showed that there was no change in planning target volume (PTV) coverage and dose to the rectum. There were significant improvements for the adjusted treatment plan in: V150% and V200% for PTV, dose to urethra, conformal index, and dose nonhomogeneity ratio. The three largest hot spots for the adjusted treatment plan were significantly smaller compared to the clinical treatment plan. The observers preferred the adjusted treatment plan in 132 cases and the clinical in 83 cases. The observers preferred the adjusted treatment plan on homogeneity and organs at risk but preferred the clinical plan on PTV coverage. CONCLUSIONS: Quantitative analysis showed that the postadjustment optimization tool could improve the spatial properties of the treatment plans while maintaining the target coverage.

  • 44.
    Dumke, Christoph
    et al.
    Univ Lubeck, Sect Translat Surg Oncol & Biobanking, Dept Surg, Campus Lubeck,Ratzeburger Allee 160, D-23538 Lubeck, Germany.;Univ Hosp Schleswig Holstein, Campus Lubeck,Ratzeburger Allee 160, D-23538 Lubeck, Germany..
    Gemoll, Timo
    Univ Lubeck, Sect Translat Surg Oncol & Biobanking, Dept Surg, Campus Lubeck,Ratzeburger Allee 160, D-23538 Lubeck, Germany.;Univ Hosp Schleswig Holstein, Campus Lubeck,Ratzeburger Allee 160, D-23538 Lubeck, Germany..
    Oberlaender, Martina
    Univ Lubeck, Sect Translat Surg Oncol & Biobanking, Dept Surg, Campus Lubeck,Ratzeburger Allee 160, D-23538 Lubeck, Germany.;Univ Hosp Schleswig Holstein, Campus Lubeck,Ratzeburger Allee 160, D-23538 Lubeck, Germany.;Univ Lubeck, Interdisciplinary Ctr Biobanking Lubeck ICBL, Lubeck, Germany..
    Freitag-Wolf, Sandra
    Univ Hosp Schleswig Holstein, Inst Med Informat & Stat, Campus Kiel, Kiel, Germany..
    Thorns, Christoph
    Univ Hosp Schleswig Holstein, Campus Lubeck,Ratzeburger Allee 160, D-23538 Lubeck, Germany.;Univ Lubeck, Inst Pathol, Campus Lubeck, Lubeck, Germany..
    Glaessgen, Axel
    Unilabs AB, Dept Clin Pathol & Cytol, Stockholm, Sweden..
    Klooster, Rinse
    Leiden Univ Med Ctr, Dept Human Genet, Leiden, Netherlands..
    van der Maarel, Silvere M.
    Leiden Univ Med Ctr, Dept Human Genet, Leiden, Netherlands..
    Widengren, Jerker
    KTH, School of Engineering Sciences (SCI), Applied Physics, Quantum and Biophotonics.
    Doehn, Christian
    Urologikum Lubeck, Lubeck, Germany..
    Auer, Gert
    Karolinska Inst, Dept Oncol Pathol, Stockholm, Sweden..
    Habermann, Jens K.
    Univ Lubeck, Sect Translat Surg Oncol & Biobanking, Dept Surg, Campus Lubeck,Ratzeburger Allee 160, D-23538 Lubeck, Germany.;Univ Hosp Schleswig Holstein, Campus Lubeck,Ratzeburger Allee 160, D-23538 Lubeck, Germany.;Univ Lubeck, Interdisciplinary Ctr Biobanking Lubeck ICBL, Lubeck, Germany.;Karolinska Inst, Dept Oncol Pathol, Stockholm, Sweden..
    SATB1, genomic instability and Gleason grading constitute a novel risk score for prostate cancer2021In: Scientific Reports, E-ISSN 2045-2322, Vol. 11, no 1, article id 24446Article in journal (Refereed)
    Abstract [en]

    Current prostate cancer risk classifications rely on clinicopathological parameters resulting in uncertainties for prognostication. To improve individual risk stratification, we examined the predictive value of selected proteins with respect to tumor heterogeneity and genomic instability. We assessed the degree of genomic instability in 50 radical prostatectomy specimens by DNA-Image-Cytometry and evaluated protein expression in related 199 tissue-microarray (TMA) cores. Immunohistochemical data of SATB1, SPIN1, TPM4, VIME and TBB5 were correlated with the degree of genomic instability, established clinical risk factors and overall survival. Genomic instability was associated with a GS >= 7 (p = 0.001) and worse overall survival (p = 0.008). A positive SATB1 expression was associated with a GS <= 6 (p = 0.040), genomic stability (p = 0.027), and was a predictor for increased overall survival (p = 0.023). High expression of SPIN1 was also associated with longer overall survival (p = 0.048) and lower preoperative PSA-values (p = 0.047). The combination of SATB1 expression, genomic instability, and GS lead to a novel Prostate Cancer Prediction Score (PCP-Score) which outperforms the current D'Amico et al. stratification for predicting overall survival. Low SATB1 expression, genomic instability and GS >= 7 were identified as markers for poor prognosis. Their combination overcomes current clinical risk stratification regimes.

  • 45.
    Dyczynski, Matheus
    et al.
    Karolinska Inst, Dept Oncol Pathol, Canc Ctr Karolinska, Stockholm, Sweden..
    Yu, Yasmin
    Karolinska Inst, Dept Oncol Pathol, Canc Ctr Karolinska, Stockholm, Sweden.;Sprint Biosci, Huddinge, Sweden..
    Otrocka, Magdalena
    Karolinska Inst, Dept Med Biochem & Biophys, Sci Life Lab Stockholm, Chem Biol Consortium Sweden, Solna, Sweden..
    Parpal, Santiago
    Sprint Biosci, Huddinge, Sweden..
    Braga, Tiago
    Sprint Biosci, Huddinge, Sweden..
    Henley, Aine Brigette
    Sprint Biosci, Huddinge, Sweden..
    Zazzi, Henric
    KTH, School of Electrical Engineering and Computer Science (EECS), Centres, Centre for High Performance Computing, PDC.
    Lerner, Mikael
    Karolinska Inst, Dept Oncol Pathol, Canc Ctr Karolinska, Stockholm, Sweden..
    Wennerberg, Krister
    Univ Helsinki, Inst Mol Med Finland, FIMM, Helsinki, Finland..
    Viklund, Jenny
    Sprint Biosci, Huddinge, Sweden..
    Martinsson, Jessica
    Sprint Biosci, Huddinge, Sweden..
    Grander, Dan
    Karolinska Inst, Dept Oncol Pathol, Canc Ctr Karolinska, Stockholm, Sweden..
    De Milito, Angelo
    Karolinska Inst, Dept Oncol Pathol, Canc Ctr Karolinska, Stockholm, Sweden.;Sprint Biosci, Huddinge, Sweden..
    Tamm, Katja Pokrovskaja
    Karolinska Inst, Dept Oncol Pathol, Canc Ctr Karolinska, Stockholm, Sweden..
    Targeting autophagy by small molecule inhibitors of vacuolar protein sorting 34 (Vps34) improves the sensitivity of breast cancer cells to Sunitinib2018In: Cancer Letters, ISSN 0304-3835, E-ISSN 1872-7980, Vol. 435, p. 32-43Article in journal (Refereed)
    Abstract [en]

    Resistance to chemotherapy is a challenging problem for treatment of cancer patients and autophagy has been shown to mediate development of resistance. In this study we systematically screened a library of 306 known anti-cancer drugs for their ability to induce autophagy using a cell-based assay. 114 of the drugs were classified as autophagy inducers; for 16 drugs, the cytotoxicity was potentiated by siRNA-mediated knock-down of Atg7 and Vps34. These drugs were further evaluated in breast cancer cell lines for autophagy induction, and two tyrosine kinase inhibitors, Sunitinib and Erlotinib, were selected for further studies. For the pharmacological inhibition of autophagy, we have characterized here a novel highly potent selective inhibitor of Vps34, SB02024. SB02024 blocked autophagy in vitro and reduced xenograft growth of two breast cancer cell lines, MDA-MB-231 and MCF-7, in vivo. Vps34 inhibitor significantly potentiated cytotoxicity of Sunitinib and Erlotinib in MCF-7 and MDA-MB-231 in vitro in monolayer cultures and when grown as multicellular spheroids. Our data suggests that inhibition of autophagy significantly improves sensitivity to Sunitinib and Erlotinib and that Vps34 is a promising therapeutic target for combination strategies in breast cancer.

  • 46. Ehlén, Å.
    et al.
    Nodin, B.
    Rexhepaj, E.
    Brändstedt, J.
    Uhlén, Mathias
    KTH, School of Biotechnology (BIO), Proteomics. KTH, School of Biotechnology (BIO), Centres, Albanova VinnExcellence Center for Protein Technology, ProNova.
    Alvarado-Kristensson, M.
    Pontén, F.
    Brennan, D. J.
    Jirström, K.
    RBM3-regulated genes promote DNA integrity and affect clinical outcome in epithelial ovarian cancer2011In: Translational Oncology, ISSN 1936-5233, Vol. 4, no 4, p. 202-211Article in journal (Refereed)
    Abstract [en]

    The RNA-binding motif protein 3 (RBM3) was initially discovered as a putative cancer biomarker based on its differential expression in various cancer forms in the Human Protein Atlas (HPA). We previously reported an association between high expression of RBM3 and prolonged survival in breast and epithelial ovarian cancer (EOC). Because the function of RBM3 has not been fully elucidated, the aim of this study was to use gene set enrichment analysis to identify the underlying biologic processes associated with RBM3 expression in a previously analyzed EOC cohort (cohort 1, n = 267). This revealed an association between RBM3 expression and several cellular processes involved in the maintenance of DNA integrity. RBM3-regulated genes were subsequently screened in the HPA to select for putative prognostic markers, and candidate proteins were analyzed in the ovarian cancer cell line A2780, whereby an up-regulation of Chk1, Chk2, and MCM3 was demonstrated in siRBM3-treated cells compared to controls. The prognostic value of these markers was assessed at the messenger RNA level in cohort 1 and the protein level in an independent EOC cohort (cohort 2, n = 154). High expression levels of Chk1, Chk2, and MCM3 were associated with a significantly shorter survival in both cohorts, and phosphorylated Chk2 was an adverse prognostic marker in cohort 2. These results uncover a putative role for RBM3 in DNA damage response, which might, in part, explain its cisplatin-sensitizing properties and good prognostic value in EOC. Furthermore, it is demonstrated that Chk1, Chk2, and MCM3 are poor prognostic markers in EOC.

  • 47. Eissler, N.
    et al.
    Mao, Y.
    Brodin, D.
    Reuterswärd, Philippa
    KTH, School of Biotechnology (BIO), Proteomics and Nanobiotechnology.
    Svahn Andersson, Helene
    KTH, School of Biotechnology (BIO), Proteomics and Nanobiotechnology.
    Johnsen, J. I.
    Kiessling, R.
    Kogner, P.
    Combination Therapy of Anti-PD-1 Antibody and CSF-1R Inhibitor Reverses Induction of Suppressive Myeloid Cells and Controls Spontaneous Neuroblastoma Progression2016In: Pediatric Blood & Cancer, ISSN 1545-5009, E-ISSN 1545-5017, Vol. 63, p. S28-S28Article in journal (Refereed)
  • 48.
    Eltahir, Mohamed
    et al.
    Uppsala Univ, Dept Pharmaceut Biosci, Sci Life Lab, Uppsala, Sweden..
    Persson, Helena
    KTH, Centres, Science for Life Laboratory, SciLifeLab. KTH, School of Engineering Sciences in Chemistry, Biotechnology and Health (CBH), Protein Science, Protein Technology. Sci Life Lab, Drug Discovery & Dev, Stockholm, Sweden.;Royal Inst Technol KTH, Sch Engn Sci Chem Biotechnol & Hlth, Stockholm, Sweden..
    Mangsbo, Sara
    Uppsala Univ, Dept Pharmaceut Biosci, Sci Life Lab, Uppsala, Sweden..
    Tumor localized agonistic anti-CD40 therapy and beyond2020In: Expert Opinion on Biological Therapy, ISSN 1471-2598, E-ISSN 1744-7682, Vol. 20, no 3, p. 215-217Article in journal (Other academic)
  • 49.
    Engberg, L.
    et al.
    Raysearch Labs AB, Res Dept, Stockholm, Sweden..
    Eriksson, K.
    Raysearch Labs AB, Res Dept, Stockholm, Sweden..
    Forsgren, Anders
    KTH, School of Engineering Sciences (SCI), Mathematics (Dept.).
    Automated planning through explicit optimization of plan quality2018In: Radiotherapy and Oncology, ISSN 0167-8140, E-ISSN 1879-0887, Vol. 127, p. S1025-S1026Article in journal (Other academic)
  • 50.
    Erickson, Andrew
    et al.
    Univ Oxford, Oxford, England..
    Berglund, Emelie
    KTH, School of Engineering Sciences in Chemistry, Biotechnology and Health (CBH), Gene Technology. KTH, Centres, Science for Life Laboratory, SciLifeLab.
    He, Mengxiao
    KTH, School of Engineering Sciences in Chemistry, Biotechnology and Health (CBH), Gene Technology. KTH, Centres, Science for Life Laboratory, SciLifeLab.
    Marklund, Maja
    KTH, School of Engineering Sciences in Chemistry, Biotechnology and Health (CBH), Gene Technology. KTH, Centres, Science for Life Laboratory, SciLifeLab.
    Mirzazadeh, Reza
    KTH, Centres, Science for Life Laboratory, SciLifeLab. KTH, School of Engineering Sciences in Chemistry, Biotechnology and Health (CBH), Gene Technology.
    Schultz, Niklas
    Karolinska Inst, Sci Life Lab, Solna, Sweden..
    Kvastad, Linda
    KTH, Centres, Science for Life Laboratory, SciLifeLab. KTH, School of Engineering Sciences in Chemistry, Biotechnology and Health (CBH), Gene Technology.
    Andersson, Alma
    KTH, School of Engineering Sciences in Chemistry, Biotechnology and Health (CBH), Gene Technology. KTH, Centres, Science for Life Laboratory, SciLifeLab. KTH, School of Engineering Sciences (SCI), Applied Physics.
    Bergenstråhle, Ludvig
    KTH, School of Engineering Sciences in Chemistry, Biotechnology and Health (CBH), Gene Technology. KTH, Centres, Science for Life Laboratory, SciLifeLab.
    Bergenstråhle, Joseph
    KTH, Centres, Science for Life Laboratory, SciLifeLab. KTH, School of Engineering Sciences in Chemistry, Biotechnology and Health (CBH), Gene Technology.
    Larsson, Ludvig
    KTH, School of Engineering Sciences in Chemistry, Biotechnology and Health (CBH), Gene Technology. KTH, Centres, Science for Life Laboratory, SciLifeLab.
    Shamikh, Alia
    Karolinska Inst, Stockholm, Sweden.;Karolinska Univ Hosp, Stockholm, Sweden..
    Basmaci, Elisa
    Karolinska Inst, Stockholm, Sweden.;Karolinska Univ Hosp, Stockholm, Sweden..
    De Stahl, Teresita Diaz
    Karolinska Inst, Stockholm, Sweden.;Karolinska Univ Hosp, Stockholm, Sweden..
    Rajakumar, Timothy
    Univ Oxford, Oxford, England..
    Thrane, Kim
    KTH, School of Engineering Sciences in Chemistry, Biotechnology and Health (CBH), Gene Technology. KTH, Centres, Science for Life Laboratory, SciLifeLab.
    Ji, Andrew L.
    Stanford Univ, Sch Med, Stanford, CA USA..
    Khavari, Paul A.
    Stanford Univ, Sch Med, Stanford, CA USA..
    Tarish, Firaz
    Karolinska Inst, Sci Life Lab, Solna, Sweden..
    Tanoglidi, Anna
    Univ Oxford, Oxford, England..
    Maaskola, Jonas
    KTH, School of Engineering Sciences in Chemistry, Biotechnology and Health (CBH), Gene Technology. KTH, Centres, Science for Life Laboratory, SciLifeLab.
    Colling, Richard
    Univ Oxford, Oxford, England.;Oxford Univ Hosp NHS Fdn Trust, Oxford, England..
    Mirtti, Tuomas
    Helsinki Univ Hosp, Helsinki, Finland.;Univ Helsinki, Helsinki, Finland..
    Hamdy, Freddie
    Univ Oxford, Oxford, England.;Oxford Univ Hosp NHS Fdn Trust, Oxford, England..
    Woodcock, Dan J.
    Univ Oxford, Oxford, England..
    Helleday, Thomas
    KTH, Centres, Science for Life Laboratory, SciLifeLab.
    Mills, Ian G.
    Univ Oxford, Oxford, England..
    Lamb, Alastair D.
    Univ Oxford, Oxford, England.;Oxford Univ Hosp NHS Fdn Trust, Oxford, England..
    Lundeberg, Joakim
    KTH, Centres, Science for Life Laboratory, SciLifeLab. KTH, School of Engineering Sciences in Chemistry, Biotechnology and Health (CBH), Gene Technology.
    The spatial landscape of clonal somatic mutations in benign and malignant tissue2022In: Cancer Research, ISSN 0008-5472, E-ISSN 1538-7445, Vol. 82, no 12Article in journal (Other academic)
123456 1 - 50 of 253
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