Dr. Nameeta Shah

Neuro-Oncology Program

Dr. Nameeta Shah, Ph.D

Dr.Nameeta Shah is a Principal investigator of the Neuro Oncology Program, at Mazumdar Shaw Center for Translational Research (MSCTR), Narayana Health, Bangalore. She received her B.E from Gujarat University, India and M.Tech degree in Computer Science and Engineering from Indian Institute of Technology, Kanpur. She obtained her Ph.D. at University of California, Davis in 2006. Her Ph.D. thesis, “Integrated visualization and computational methods to develop a system to infer gene regulation from large-scale genomics data” led to her interest in cancer research. She received her postdoctoral research experience at Michigan Center for Translational Pathology, Ann Arbor. The focus of her work was high throughput screening of gene fusions using large scale genomics and Fluorescent In Situ Hybridization (FISH) data which led to identification of ETV5 fusions in prostate cancer. She worked as a bioinformatics scientist for brain tumor research lab in USA for seven years where she established the computational infrastructure, and clinical and genomic databases. During that period,Dr.Nameeta led the Ivy Glioblastoma Atlas Project effort from Swedish Neuroscience Institute in collaboration with the team at Allen Institute for Brain Science, Seattle, WA, USA.With her extensive experience in brain tumor research, she is working towards expanding the neuro oncology research program at MSCTR for improved glioma patient care.

Research Interests

  • Gliomas and specifically glioblastoma (GBM), grade IV brain tumors are highly heterogeneous. As a result effective treatment options for these patients are still in the waiting.Her recent work on GBM reportsthat molecular signatures of anatomic features delineated histologically are highly conserved across patientsand reflect the biological processes, pathways, cell types and microenvironment relevant to each feature. Itis therefore extremely important to develop clinically feasible biomarkers that take in to account intratumorheterogeneity, are representative of the whole tumor and capture multiple parametersrepresented by anatomic features such as tumor cells, blood vessels, immune cells, etc. Also, the current cell culture models do not sufficiently reflect the disease in the patient. It is important to better understand GBM microenvironment and develop alternate 3D models that best reflect the disease and can be used for identification of better therapeutics.

Publications

  • 1. Shah N, Puchalski RB, Miller J, Dalley R, Nomura SR, Yoon JG, et al. An anatomic transcriptional atlas of glioblastoma. Under revision, 2016.
  • 2. Shah N, Schroeder B, Cobbs C. MGMT methylation in glioblastoma: tale of the tail. Neuro Oncol. 2015.
  • 3. Shah N, Schroeder B, Rostad S, McCullough B, Aguedan B, Foltz G, et al. Genetic investigation of multicentric glioblastoma multiforme: case report. J Neurosurg. 2015.
  • 4. Shah N, Lankerovich M, Lee H, Yoon JG, Schroeder B, Foltz G. Exploration of the gene fusion landscape of glioblastoma using transcriptome sequencing and copy number data. BMC Genomics. 2013.
  • 5. Shah N, Lin B, Sibenaller Z, Ryken T, Lee H, Yoon JG, et al. Comprehensive analysis of MGMT promoter methylation: correlation with MGMT expression and clinical response in GBM. PLoSOne. 2011.
  • 6. Panchalingam KM, Paramchuk WJ, Chiang CY, Shah N, Madan A, Hood L, et al. Bioprocessing of human glioblastoma brain cancer tissue. Tissue Eng Part A. 2010.
  • 7. Shah N, Helgeson BE, Tomlins SA, Laxman B, Cao Q, Prensner JR, et al. Characterization of TMPRSS2:ETV5 and SLC45A3:ETV5 gene fusions in prostate cancer. Cancer Res. 2008.
  • 8. Filkov V, Shah N. A simple model of the modular structure of transcriptional regulation in yeast. J Comput Biol. 2008.
  • 9. Shah N, Teplitsky MV, Minovitsky S, Pennacchio LA, Hugenholtz P, Hamann B, et al. SNP-VISTA: an interactive SNP visualization tool. BMC Bioinformatics. 2005.
  • 10. Shah N, Couronne O, Pennacchio LA, Brudno M, Batzoglou S, Bethel EW, et al. Phylo-VISTA: interactive visualization of multiple DNA sequence alignments. Bioinformatics. 2004.