Now showing items 1-2 of 2

    • Drug-screening and genomic analyses of HER2-positive breast cancer cell lines reveal predictors for treatment response 

      Jernström, Sandra Johanna; Hongisto, Vesa; Leivonen, Suvi-Katri; Due, Eldri Undlien; Tadele, Dagim Shiferaw; Edgren, Henrik; Kallioniemi, Olli; Perälä, Merja; Mælandsmo, Gunhild; Sahlberg, Kristine Kleivi (Journal article; Tidsskriftartikkel; Peer reviewed, 2017-03-21)
      Background<br> Approximately 15%–20% of all diagnosed breast cancers are characterized by amplified and overexpressed HER2 (= ErbB2). These breast cancers are aggressive and have a poor prognosis. Although improvements in treatment have been achieved after the introduction of trastuzumab and lapatinib, many patients do not benefit from these drugs. Therefore, in-depth understanding of the mechanisms ...
    • Early response evaluation by single cell signaling profiling in acute myeloid leukemia 

      Tislevoll, Benedicte Sjo; Hellesøy, Monica; Fagerholt, Oda Helen Eck; Gullaksen, Stein-Erik; Srivastava, Aashish; Birkeland, Even; Kleftogiannis, Dimitrios; Ayuda Duran, Pilar; Piechaczyk, Laure Isabelle; Tadele, Dagim Shiferaw; Skavland, Jørn; Panagiotis, Baliakas; Hovland, Randi; Andresen, Vibeke; Seternes, Ole Morten; Tvedt, Tor Henrik Anderson; Aghaeepour, Nima; Gavasso, Sonia; Porkka, Kimmo; Jonassen, Inge; Fløisand, Yngvar; Enserink, Jorrit; Blaser, Nello; Gjertsen, Bjørn Tore (Journal article; Tidsskriftartikkel; Peer reviewed, 2023-01-07)
      Aberrant pro-survival signaling is a hallmark of cancer cells, but the response to chemotherapy is poorly understood. In this study, we investigate the initial signaling response to standard induction chemotherapy in a cohort of 32 acute myeloid leukemia (AML) patients, using 36-dimensional mass cytometry. Through supervised and unsupervised machine learning approaches, we find that reduction of ...