Prof. Forest M White

Professor of Biological Engineering

Primary DLC

Department of Biological Engineering

MIT Room: 76-353F

Areas of Interest and Expertise

Phosphoproteomics

Research Summary

The focus of research in Professor White's lab is the identification of protein phosphorylation events regulating signal transduction cascades associated with cancer and other biological processes. With mass spectrometry-based technology, identification of protein phosphorylation occurs on a global scale, allowing for mapping of complex signal transduction cascades in a variety of biological samples. Initially, we will apply the technology to cancer, starting with human cell lines and progressing to a variety of other model systems, with the goal of analyzing staged human clinical samples. Elucidation of signal transduction cascades involved in oncogenesis, cancer progression, and metastasis will generate both novel drug targets and a host of biological markers, allowing for early diagnosis and tracking of cancer progression. A variety of other applications will be pursued, including mapping the phosphorylation events associated with DNA damage response and cell cycle regulation.

Recent Work

  • Video

    Forest White - 2016-Digital-Health_Conf-videos

    September 14, 2016Conference Video Duration: 30:23

    High Resolution Analysis of Kinase Signaling Networks

    Receptor Tyrosine Kinases (RTKs) are critical for normal human physiology, but can be oncogenic when highly expressed or mutated in a wide array of human cancers. To define the critical components in these networks, we have developed mass spectrometry based methods enabling the absolute quantification of tyrosine phosphorylation sites in RTK signaling networks at high temporal resolution following stimulation with different ligands or inhibitors, in vitro and in vivo. Quantitative phosphorylation data generated in this analysis provides insight into the occupancy of multiple tyrosine phosphorylation sites on the receptor, highlights mechanisms of differential regulation in response to different ligands, and highlights resistance mechanisms to selected inhibitors.

    2016 MIT Digital Health Conference