Molecular Oncology Imaging

Key Faculty

Jian Tajbakhsh, PhD

Activities in the Translational Cytomics Group (TCG) involve the convergence of biogerontology, oncology, and epigenetics in the following focus areas:

  • The biology of heterochromatin hypomethylation in aging and cancer
  • Development of bioinformatics tools for the analysis of 3D-image data
  • Application of quantitative DNA Methylation Imaging (qDMI) for cancer
  • Diagnostics (pathology)
  • Utilization of qDMI in personalized medicine

Selected Publications

  • Scheuermann, MO*, Tajbakhsh, J*, Kurz, A, Saracoglu, K, Eils, R, Lichter, P. Topology of genes and non-transcribed sequences in human interphase nuclei. 2004, Exp Cell Res, 301: 266-279. (* These authors contributed equally to this work) 
  • Tajbakhsh, J, Wawrowsky, KA, Gertych, A, Bar-Nur, O, Vishnewsky E, Lindsley, EH, Farkas, DL. Characterization of tumor cells and stem cells by differential nuclear methylation imaging. 2008, Proceedings of the SPIE Vol. 6859: 68590F-1–68590F-10.
  • Gertych, A, Farkas, DL, Wawrowsky, KA, Vishnewsky, E, Lindsley, EH, Tajbakhsh, J. Automated quantification of DNA demethylation effects in cells via 3D mapping of nuclearsignatures and population homogeneity assessment. 2009, Cytometry Part A 75A: 559-583.

V. Krishnan Ramanujan, PhD

The laboratory is involved in extending the scope of the high-resolution optical imaging  technologies and nonlinear dynamical analysis approaches of biophysical processes to preclinical and clinical applications in breast cancer etiology/detection and toward characterizing age-related risk factors in breast cancer.  From the fundamental cancer biology point of view, our laboratory is involved in understanding the critical role of mitochondrial dynamics in contributing to altered energy metabolism in breast cancer cells.  By systematic modulation of mitochondrial metabolism we have recently generated a number of “modified” breast cancer cells that may provide clues to understanding the mitochondrial origins of breast cancer in vivo as well as to designing mitochondrial reprogramming strategies to suppress or even reverse cancer growth in vivo.

Selected Publications

  • V Krishnan Ramanujan, Jian-Hua Zhang, Eva Biener and B. Herman : Multiphoton Fluorescence Lifetime contrast in Deep tissue imaging : Prospects in redox imaging and disease diagnosis, J Biomed Optics, 10: 051407 (2005) PMID: 16292944
  • V Krishnan Ramanujan and Brian Herman, Aging Process Modulates Nonlinear Dynamics in Liver Cell Metabolism . J Biol Chem. 282:19217-26 (2007) PMID: 17446172
  • Ndeke Nyirenda, Daniel Farkas and V Krishnan Ramanujan : Preclinical Evaluation of Nuclear Morphometry and Tissue Topology for Breast Carcinoma Detection and Margin Assessment : Breast Cancer Res. Treatment (In Press, DOI 10.1007/s10549-010-0914-z) (2010)

Arkadiusz Gertych, PhD

The long term goal of the laboratory is the development of a modern Computer Aided Diagnosis (CAD) platform for radiology, histopathology, surgery; and cancer research.   We believe this to be an invaluable future tool for the evaluation of patient status in pre- and post-surgical procedures, screening and detection of cancer, quantitative assessment of disease progression, monitoring of health during anticancer treatment, etc. We are continuing to adapt the technology for high-content screening of cells in drug screening, evaluation of skeletal development and diseases in children, quantitative assessment of DNA signatures in epigenetic anticancer drug screening, automated analysis of cytological tests, and prognosis of cervical cancer.

Selected Publications

  • Gertych A, Pietka E, Liu B, Segmentation of regions of interest and post-segmentation edge location improvement in computer-aided bone age assessment. Pat Anal Appl 10(2):115-123, 2007
  • Gertych A, Zhang A, Sayre J, Pospiech-Kurkowska S, H.K Huang, Bone Age Assessment of Children utilizing Digital Hand Atlas, J Comp. Med. Img. Graph, 31(4-5):322-331, 2007
  • Gertych A, Wawrowsky KA, Vishnewsky E, Lindsley E, Farkas DL, Tajbakhsh J, Automated Quantification of DNA Demethylation Effects in Cells via 3D Mapping of Nuclear Signatures and Population Homogeneity Assessment, Cytometry A, 75A(7):569 – 583, 2009 (With cover story)