1301 Catherine St., Rm. 4326C
Ann Arbor, MI 48109
Available to mentor
Dr. Ray is a tenured Associate Professor in the Department of Radiation Oncology and an Adjunct Associate Professor in the Department of Nuclear Engineering and Radiological Sciences (NERS). He is also the Director of the Cancer Research Summer Internship Program (CaRSIP) at the Rogel Cancer Center. After receiving a doctoral degree from the Indian Institute of Science (IISc.), India, he completed a Postdoctoral research training at the University of Illinois at Chicago (UIC) before joining as a Research Assistant Professor at the Northwestern University, Chicago. In 2009, he joined the Department of Radiation Oncology, University of Michigan, Ann Arbor where he is continuing to lead a research team including Research Scientist, Postdoctoral Research Fellows, Undergraduate Students and Research Technicians. Dr. Ray is an expertise in the field of posttranslational Protein modifications (PTMs) that influence oncoprotein stabilities and functionalities to cause cancer progression and therapy resistance in gastrointestinal (GI) and upper thoracic cancers.
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Center MemberRogel Cancer Center
Following are major research projects in the Ray Lab:
Understanding the interplay between the ubiquitin ligases and chaperone machineries regulating mutant p53 protein stability and gain-of-function activity promoting esophageal adenocarcinoma (EAC).
Understanding the isoform specific roles of GRAIL in tumor and T-cell crosstalk causing chemoradioresistance in EAC.
Understanding the importance of mutant p53 mediated isoform switch influencing mutant KRAS hyperactivation in pancreatic and lung adenocarcinoma.
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Ray P, Jaiswal S, Ferrer-Torres D, Wang Z, Nancarrow D, Curtin M, Martinho MS, Lacy SM, Kasturirangan S, Thomas D, Spence JR, Truttmann MC, Lagisetty KH, Lawrence TS, Wang TD, Beer DG, Ray D. Mol Cancer Res, 2024 Jul 17;Journal ArticleGRAIL1 stabilizes misfolded mutant p53 through a ubiquitin ligase-independent, chaperone regulatory function.
DOI:10.1158/1541-7786.MCR-24-0361 PMID: 39018356 -
Kasturirangan S, Nancarrow DJ, Shah A, Lagisetty KH, Lawrence TS, Beer DG, Ray D. Cell Death Dis, 2024 Mar 8; 15 (3): 194Journal ArticleIsoform alterations in the ubiquitination machinery impacting gastrointestinal malignancies.
DOI:10.1038/s41419-024-06575-z PMID: 38453895 -
McEwen DP, Ray P, Nancarrow DJ, Wang Z, Kasturirangan S, Abdullah S, Balan A, Hoskeri R, Thomas D, Lawrence TS, Beer DG, Lagisetty KH, Ray D. JCI Insight, 2024 May 23; 9 (13):Journal ArticleISG15/GRAIL1/CD3 axis influences survival of patients with esophageal adenocarcinoma.
DOI:10.1172/jci.insight.179315 PMID: 38781019 -
Gaenko A, Ray D, Nancarrow DJ. bioRxiv,PreprintCoFrEE: An Application to Estimate DNA Copy Number from Genome-wide RNA Expression Data
DOI:10.1101/2023.08.25.554898 -
Awadia S, Sitto M, Ram S, Ji W, Liu Y, Damani R, Ray D, Lawrence TS, Galban CJ, Cappell SD, Rehemtulla A. J Biol Chem, 2023 Jun; 299 (6): 104786Journal ArticleThe adapter protein FADD provides an alternate pathway for entry into the cell cycle by regulating APC/C-Cdh1 E3 ubiquitin ligase activity.
DOI:10.1016/j.jbc.2023.104786 PMID: 37146968 -
Ray D. 2022 Nov 17;PresentationA novel ubiquitin ligase independent, chaperone regulating role of GRAIL in mutant p53 stabilization
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Hinton T, Karnak D, Tang M, Jiang R, Luo Y, Boonstra P, Sun Y, Nancarrow DJ, Sandford E, Ray P, Maurino C, Matuszak M, Schipper MJ, Green MD, Yanik GA, Tewari M, Naqa IE, Schonewolf CA, Haken RT, Jolly S, Lawrence TS, Ray D. Transl Oncol, 2022 Jul; 21: 101428Journal ArticleImproved prediction of radiation pneumonitis by combining biological and radiobiological parameters using a data-driven Bayesian network analysis.
DOI:10.1016/j.tranon.2022.101428 PMID: 35460942 -
Hinton T, Karnak D, Tang M, Jiang R, Luo Y, Boonstra P, Sun Y, Sandford E, Nancarrow D, Ray P, Maurino C, Matuszak M, Schipper MJ, Green M, Gadgeel SM, Yanik GA, Tewari M, Naqa IE, Schonewolf CA, Haken RT, Jolly S, Lawrence TS, Dipankar R. Translational Oncology, 2022 Apr 11; In Press:Journal ArticleImproved prediction of radiation pneumonitis by combining biological and radiobiological parameters using a data-driven Bayesian network analysis