Rochester, Minnesota




Jeanette E. Eckel Passow, Ph.D., evaluates the genetics of cancer, with a particular emphasis on brain and kidney cancers. She is a principal investigator on an R01 grant from the National Institutes of Health to develop and evaluate MRI-based machine-learning models and polygenic risk models for the differential diagnosis of indeterminate brain lesions. In addition to developing and evaluating statistical methods for omics data, she has extensive statistical consulting experience in clinical, translational and basic science research.

Focus areas

  • Glioma risk. Dr. Eckel Passow collaborates with Robert B. Jenkins, M.D., Ph.D., to subtype gliomas based on acquired genetic alterations and to identify germline risk variants stratified by molecular subtype.
  • Differential diagnosis of indeterminate brain lesions. Dr. Eckel Passow and colleagues are developing MRI-based machine-learning models for differential diagnosis of high-grade glioma, tumefactive multiple sclerosis, CNS lymphoma, and solitary brain metastases. In parallel, they are also developing polygenic risk models for differential diagnosis of these brain lesions.
  • Metastatic clear cell renal cell carcinoma. Dr. Eckel Passow studies the molecular mechanisms that drive metastatic progression.
  • Experimental design and statistical methodology for omics data. Integrated omics aids the investigation of complex molecular systems and sets a foundation for systematic learning for precision medicine. Dr. Eckel Passow studies how incorporating this information into clinical studies can provide insight into how genes, proteins and epigenetic factors influence the phenotype of a disease in context of the system and help predict the host response to various diseases and cancers.

Significance to patient care

Dr. Eckel Passow's research efforts will lead to a better understanding of the susceptibility of adult diffuse glioma, which may help with differential diagnosis of indeterminate brain lesions.


Primary Appointment

  1. Consultant, Division of Computational Biology, Department of Quantitative Health Sciences

Academic Rank

  1. Professor of Biostatistics


  1. Postdoctoral Research Fellowship - Cancer Genetic Epidemiology Fellowship (Mentor: Terry Therneau, Ph.D.) Topic: Experimental Design and Analysis of High-Dimensional Biological Data Mayo School of Graduate Medical Education, Mayo Clinic College of Medicine
  2. PhD - Biostatistics (Advisors: Chris Gennings, Ph.D. & Vernon Chinchilli, Ph.D.) Topic: Statistical Analysis of Time-Course and Dose-Response Microarray Experiments Virginia Commonwealth University
  3. BS - Statistics, Mathematics Winona State University

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