Hani Goodarzi, PhD, Associate Professor, University of California, San Francisco

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Hani Goodarzi, PhD, Associate Professor, University of California, San Francisco

November 2 @ 4:00 pm - 5:00 pm

Biomedical Data Science Seminar Series, BRB Gaulton Auditorium.

Title: Translational reprogramming in metastatic breast cancer

This week hosted by IBI – invited by Crystal Conn, PhD

Abstract

Aberrant translational control of oncogenes and tumor suppressors is one of the hallmarks of cancer. However, the molecular programs that govern dysregulated control of protein synthesis during metastatic progression. Taking advantage of established cell line- and patient-derived xenograft models of metastasis, we used ribosome footprinting to measure changes in translational efficiency transcriptome-wide. Using a new computational framework we have developed, we identified a previously unknown regulatory program that reduces translation of target mRNAs in metastatic cells. In this pathway, the RNA-binding protein HNRNPC binds the 3’ untranslated regions (3’UTRs) of ~150 genes and inhibits their translation. Using systematic transcriptomic, biochemical, in vitro, and in vivo assays, we have carefully dissected the role of this regulatory program that governs aberrant translational control from the nucleus.

Bio

Dr. Hani Goodarzi is an Associate Professor and a Chan Zuckerberg Biohub Investigator at the University of California, San Francisco. With a dual background in computational and experimental genomics, he brings a multidisciplinary approach to studying complex human diseases. His research is focused on developing novel discovery platforms that help reveal previously unknown molecular mechanisms underlying cellular homeostasis and disease progression. By developing novel technologies for genome-wide measurement of hard-to-quantify RNA molecules, he has also made key discoveries about the role of non-coding RNAs in health and disease. On the computational front, Dr. Goodarzi is focused on building biology-inspired and genome-scale machine learning models that help decode the biology of human genome. Most recently, for his contributions to cancer research, he was awarded the Vilcek Prize for Creative Promise and AACR-MPM Transformative Cancer Research Award. He was previously a recipient of the Martin and Rose Wachtel Award in Cancer Research and an American Cancer Society scholar.

Details

Date:
November 2
Time:
4:00 pm - 5:00 pm
Event Category:

Organizer

Jessica Incmikoski
Email:
jessicai@pennmedicine.upenn.edu

Venue

Upenn, Biomedical Research Building
421 Curie Boulevard
Philadelphia, PA 19104 United States
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Phone:
215-746-4060
View Venue Website