Our research is focused on making precision medicine a reality. We examine which proteins are key biomarkers for a disease condition. Our lab works hand-in-hand with clinicians to implement discoveries as soon as possible. Our primary focus is to carry out the comprehensive characterization of proteins using mass spectrometry in order to better understand protein functions and interactions under normal and disease states; primary focus being on glioblastoma, obstructive uropathy and endometrial cancer. The lab is also involved in developing novel technologies for mass spectrometry (MS)-based research.
Glioblastoma (GBM) is the most common and very aggressive type of the primary brain tumors affecting about 17,000 Americans annually. Even after initial treatment, almost all patients develop recurring tumors, which have limited treatment choices and little hope of cure. The median survival is 15 months and tumor recurrence is inevitable. Only about 10% patient population survive longer than 3 years. Given the short life span of these patients, no effective treatment, there is a need to identify a priori the patient population with short survival, and identify the protein signatures that would guide to new drug targets. Thus, there is an ongoing need for biomarker identification to determine survival outcome, and develop new and efficient drugs to treat this lethal disease.
I have been studying GBM to identify protein signatures from tumor biopsies and plasma using MS-based proteomics approaches to i) identify GBM biomarkers ii) prognostic biomarkers for survival prediction (long term vs short term) iii) predict response to bevacizumab in recurring tumors in GBM patients. Identifying specific inhibitors in these patients will open avenues to new treatment options in GBM. With this individualized approach, the physician can minimize the guesswork and time involved in finding a successful treatment. It is hoped this research will play a critical role in extending and improving the quality of life for these terminal cancer patients.
Diseases of the urinary tract in newborns can lead to infant death, kidney failure, and in those who survive, to chronic kidney disease (CKD) and early heart disease in adulthood. Despite the availability of pre-natal maternal care and advanced imaging, obstructive diseases of the urinary tract account for the majority of cases of end stage kidney disease and consume 24% of health care expenditure in this segment of population. Most of these conditions do not cause symptoms and therefore are silent killers and go undetected. Current routine urinary testing is not sensitive enough to uncover these conditions. To address this issue and identify this severe condition in infants efficiently, we discovered urinary biomarkers of congenital obstructive uropathy focusing on human ureteropelvic junction obstruction (UPJO). Using a MS-based proteomics approach we have identified biomarkers of UPJO in infants. Furthermore, we are in the process of translating these biomarkers identified from sophisticated MS technology to an easy to use multiplexed protein array for a point-of-care application. The diagnosis of these serious conditions through the low cost, point of care screening diagnostic test followed by treatment, can lead to cure in a majority of newborns and infants with congenital diseases of the urinary tract.
I have always been involved in technology development for the efficient analysis of various classes of compounds by mass spectrometry. One of the research interests in our laboratory is to develop novel MS-based technologies for the comprehensive characterization of various analytes ranging from small molecules like organic compounds and metabolites to large molecules like proteins, peptides and oligonucleotides. This is extended to my further interests in proteomics where I have developed several novel proteomics approaches for the better characterization of proteins including mapping posttranslational modifications, quantitative approaches, membrane protein identification and other MS-based proteomics approaches.