B.S. University of Florida, 1997Ph.D. Massachusetts Institute of Technology, 2003Post-Doc ​Massachusetts Institute of Technology, 2003-2007

"Our lab studies the biochemistry of cellular decision-making using a combination of experimental and computational approaches, with the ultimate goal of rationally designing improved therapeutic approaches for cancer and other diseases."

Matthew J. Lazzara, Professor

Work in the Lazzara Lab employs a combination of experimental and computational methods to study problems in cell signaling, the complex biochemical process cells use to make decisions. Current projects focus on the rational (model-driven) identification of combination therapies for brain and pancreas cancers and on fundamental studies of the spatiotemporal regulation of cell signaling by phosphatases and receptor trafficking.

The lab's work is funded by grants from the NIH/National Cancer Institue, American Cancer Society, and National Science Foundation. Dr. Lazzara is the recipient of several teaching awards, including the S. Reid Warren, Jr. Award and the Outstanding Faculty Award of the AIChE Delaware Valley, and is a member of the editorial board of Cellular and Molecular Bioengineering and the Cancer Drug Discovery Peer Review Committee at the American Cancer Society. He also served for more than 10 years on the National Board and Board of Directors of the Museum of Science and Industry in Tampa, FL.

Matthew Lazzara received a B.S. in Chemical Engineering (with highest honors) from the University of Florida and a Ph.D. in Chemical Engineering from the Massachusetts Institute of Technology, where he trained in the lab of William Deen. He remained at MIT for postdoctoral studies in the lab of Douglas Lauffenburger and was the recipient of an NIH Ruth L. Kirschstein National Research Service Award Postdoctoral Fellowship. Dr. Lazzara is Professor of Chemical Engineering and holds a joint appointment in the Department of Biomedical Engineering. He is also a member of the UVA Cancer Center.

Research Interests

  • Cell signaling and cellular decision-making
  • Systems biology
  • Targeted therapeutics for cancer
  • Computational modeling of biological phenomena

In the News

Selected Publications

  • Data-driven computational modeling identifies determinants of glioblastoma response to SHP2 inhibition ABS Cancer Res 2021 Apr 15;81(8):2056-2070. doi: 10.1158/0008-5472.CAN-20-1756. Epub 2021 Feb 11.
  • ERK-dependent suicide gene therapy for selective targeting of RTK/RAS-driven cancers ABS Mol Ther 2021 Apr 7;29(4):1585-1601. doi: 10.1016/j.ymthe.2020.12.019. Epub 2020 Dec 15.
  • Glioblastoma Cell Resistance to EGFR and MET Inhibition Can Be Overcome via Blockade of FGFR-SPRY2 Bypass Signaling ABS Cell Rep 2020 Mar 10;30(10):3383-3396.e7. doi: 10.1016/j.celrep.2020.02.014.
  • Disrupting the transmembrane domain-mediated oligomerization of protein tyrosine phosphatase receptor J inhibits EGFR-driven cancer cell phenotypes ABS J Biol Chem 2019 Dec 6;294(49):18796-18806. doi: 10.1074/jbc.RA119.010229. Epub 2019 Nov 1.
  • Localization dynamics of endogenous fluorescently labeled RAF1 in EGF-stimulated cells ABS Mol Biol Cell 2019 Feb 15;30(4):506-523. doi: 10.1091/mbc.E18-08-0512. Epub 2018 Dec 26.
  • Multiscale computational models of cancer ABS Curr Opin Biomed Eng 11:137-144, 2019.