Organization

Division of Cancer Cell Biology

Laboratory Web site

Staff

GOTOH, Noriko

Professor
GOTOH, Noriko

NAKATA, Asuka

Assistant Professor
NAKATA, Asuka

NISHIMURA, Tatsunori

Research Assistant Professor
NISHIMURA, Tatsunori

Aims, Ongoing Projects, and Recent Achievements

 Our major research interest is to elucidate the molecular mechanisms regulating cancer cells, stem cells and cancer stem cells. Our team has two important research directions: One is to clarify the basic principles underlying biology and the other is to apply the knowledge extracted from the basic principles to translational medicine. In order to achieve the goal, we take challenging approaches of molecular biology and systems biology, in addition to conventional methods of molecular biology.

  1. Molecular mechanisms of cancer initiation, progression and metastasis: breast cancer stem cells as key players
    By analyzing the mouse cancer model or primary cancer cells derived from human specimens, we attempt to identify novel molecular targets and biomarkers for cancer.
  2. Identification of new biomarkers and molecular targets of lung cancers by systems biology approach
    Our hypothesis is that elucidation of the molecular mechanisms of addiction of lung epithelial cells to EGF RTK signaling leads us to identify new biomarkers and molecular targets of lung cancer. Our approach would certainly advance personalized medicine in the near future.
  3. Signal transduction mechanisms through receptor tyrosine kinases (RTKs) for tumorigenesis and stem cell maintenance
    Fibroblast growth factor (FGF) and epidermal growth factor (EGF) RTKs play major roles for a variety of physiological and pathological aspects of biology, including stem cell biology, and cancer biology. We focus on FRS2 family of adaptor/scaffolding docking proteins, as key intracellular signal regulators of these RTKs.


Activation of heregulin-phosphatidyl inositol (PI)-3 kinase pathway induces various cytokines, growth factors and cytoplasmic molecules that regulates cancer stem cells and their niche.


The 139 key genes involved in EGF signaling accurately predict prognosis of lung cancer patients.