Mohit B. Bhatia
Celgene
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Publication
Featured researches published by Mohit B. Bhatia.
Frontiers in Immunology | 2013
Lin Kang; Vanessa Voskinarian-Berse; Eric Law; Tiffany Reddin; Mohit B. Bhatia; Alexandra Hariri; Yuhong Ning; David Xu Dong; Timothy J. Maguire; Martin L. Yarmush; Wolfgang Hofgartner; Stewart Abbot; Xiaokui Zhang; Robert J. Hariri
Recent clinical studies suggest that adoptive transfer of donor-derived natural killer (NK) cells may improve clinical outcome in hematological malignancies and some solid tumors by direct anti-tumor effects as well as by reduction of graft versus host disease (GVHD). NK cells have also been shown to enhance transplant engraftment during allogeneic hematopoietic stem cell transplantation (HSCT) for hematological malignancies. The limited ex vivo expansion potential of NK cells from peripheral blood (PB) or umbilical cord blood (UCB) has however restricted their therapeutic potential. Here we define methods to efficiently generate NK cells from donor-matched, full-term human placenta perfusate (termed Human Placenta-Derived Stem Cell, HPDSC) and UCB. Following isolation from cryopreserved donor-matched HPDSC and UCB units, CD56+CD3− placenta-derived NK cells, termed pNK cells, were expanded in culture for up to 3 weeks to yield an average of 1.2 billion cells per donor that were >80% CD56+CD3−, comparable to doses previously utilized in clinical applications. Ex vivo-expanded pNK cells exhibited a marked increase in anti-tumor cytolytic activity coinciding with the significantly increased expression of NKG2D, NKp46, and NKp44 (p < 0.001, p < 0.001, and p < 0.05, respectively). Strong cytolytic activity was observed against a wide range of tumor cell lines in vitro. pNK cells display a distinct microRNA (miRNA) expression profile, immunophenotype, and greater anti-tumor capacity in vitro compared to PB NK cells used in recent clinical trials. With further development, pNK may represent a novel and effective cellular immunotherapy for patients with high clinical needs and few other therapeutic options.
Analytical Methods | 2010
Neerav Dilip Padliya; Mohit B. Bhatia; Wolfgang Hofgartner; Robert J. Hariri
Lipid-based protein immobilization (LPI) technology is a platform recently developed to facilitate shotgun membrane proteomic studies based on a nanotechnology framework. Proteoliposomes are generated from a membraneprotein preparation. These proteoliposomes are immobilized onto an LPI chip and then subjected to proteolysis. The proteolytic peptides are then subjected to LC/MS analysis after fractionation by SCX chromatography. The focus of this study was to evaluate how the depth of coverage of the membrane proteome of a particular cell type varied as a function of the sample preparation method used. Human dermal fibroblasts (hDFs) and human bone marrow mesenchymal stem cells (BM-hMSCs) were subjected to membrane proteomic studies using two different sample preparation methods: LPI technology and methanol-facilitated solubilisation. The number of membraneproteins that could be identified from hDFs and BM-hMSCs using LC/MS was greater using LPI technology than it was using methanol-facilitated solubilisation. However, the number of membraneprotein identifications that could be made for both hDFs and BM-hMSCs increased by ∼50% when both sample preparation methods were used in parallel and the MS/MS data was convolved together. Therefore, LPI technology is a very useful technology for high-throughput shotgun membrane proteomic studies. However, in order to maximize the depth of membrane proteome coverage that can be attained for a given cell type, it is necessary to use multiple sample preparation methods in concert.
Archive | 2013
Mohit B. Bhatia; Robert J. Hariri; Wolfgang Hofgartner; Jia-Lun Wang; Qian Ye
Archive | 2012
Mohit B. Bhatia; Robert J. Hariri; Wolfgang Hofgartner; Jia-Lun Wang; Qian Ye
Archive | 2015
Jia-Lun Wang; Mohit B. Bhatia; Robert J. Hariri; Wolfgang Hofgartner; Qian Ye
Archive | 2014
Robert J. Hariri; Mohit B. Bhatia
Archive | 2013
Robert J. Hariri; Jodi P. Gurney; Mohit B. Bhatia; Wolfgang Hofgartner
Archive | 2017
Jodi Gurney; Mohit B. Bhatia; Robert J. Hariri; Wolfgang Hofgartner
Archive | 2013
Mohit B. Bhatia; Robert J. Hariri; Wolfgang Hofgartner; Jia-Lun Wang; Qian Ye
Archive | 2013
Robert J. Hariri; Mohit B. Bhatia; Qian Ye