Arun Wiita, MD, PhD
|School||UCSF School of Medicine|
|Address||1700 4th Street|
San Francisco CA 94107
|Gabrielle's Angels Foundation for Cancer Research||2017||Janet Rowley Memorial Medical Research Award|
|NIH Director's Common Fund||2016||New Innovator Award (DP2)|
|Doris Duke Charitable Foundation||2016||Clinical Scientist Development Award|
|Damon Runyon Cancer Research Foundation||2015||Dale Frey Breakthrough Award|
|UCSF-American Cancer Society||2015||Individual Research Award|
||2019||K08 Mentored Clinical Scientist Award|
|Damon Runyon Cancer Research Foundation||2012
|Columbia University||2008||Dean's Award for Excellence in Research (top PhD thesis prize)|
My research laboratory spans a number of areas within genomics, proteomics, and hematologic malignancies. One major area of research involves the use of targeted, quantitative proteomics to answer important biological questions in myeloma and B-cell leukemia. We are particularly interested in questions related to translational regulation after cancer therapy as well as how clinically-relevant genomic alterations result in phenotypic changes at the level of the proteome. Furthermore, my group includes the UCSF Stephen and Nancy Grand Multiple Myeloma Translational Initiative Laboratory. In this role, we collaborate with industry and academic partners to advance preclinical evaluation of novel myeloma therapeutics using a suite of in vitro and in vivo approaches.
In my clinical work, I am Assistant Director of the UCSF Clinical Cytogenetics laboratory. In this role, I interpret molecular genetic testing for the prenatal and postnatal diagnosis of microdeletion and microduplication syndromes. In this area we have translational interests in emerging technologies for determination of DNA copy number variation, integration of single-nucleotide variants and CNV interpretation, and cell-free DNA for prenatal testing. In my research laboratory we are also using quantitative proteomics to evaluate the role of protein homeostasis in determining the phenotypic effects of CNVs, as well using CRISPR/Cas9 genome engineering to generate new functional models of syndromic CNVs.
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