Biological Sciences Division
Research Highlights
July 2016
A Consequential New Take on How Cell Signaling is Regulated
Study of protein abundance patterns could lead to predictive models of cancer cell response
A diagram of the signaling pathway studied. The EGFR is at the top, and the MAPK at the bottom. The lines and arrows show how information flows between the proteins. The size of the circles indicates relative abundance, and the colors indicate degree of variability between cell types. The more blue they are, the less variable; the more yellow/red they are, the more variable.
Cancer is often associated with alterations in cell signaling pathways. These biochemical communication routes govern and coordinate normal cellular activities such as development, growth, and repair. When cell signaling goes awry, or "dysregulates," because of gene mutations, it can cause two main hallmarks of cancer: sustained cell proliferation and reduced apoptosis, a term for the normal and beneficial death of cells.
A paper by researchers at Pacific Northwest National Laboratory (PNNL) and Harvard University Medical School, published July 12 in Science Signaling, reveals for the first time that "adaptor" pathway proteins could play a vital role in the dysregulation seen in cancer.
To make the discovery, they used a newly developed technology of targeted, ultrasensitive proteomics, along with RNA sequencing, to reinvestigate the pathway between the epidermal growth factor (EGF) receptor and mitogen-activated protein kinase (MAPK). This pathway is well known in cancer research and plays a critical role in both stimulating cell proliferation and suppressing apoptosis.
"It is a very prominent pathway in cancer," said the paper's corresponding author H. Steven Wiley, who is a senior scientist at the Environmental Molecular Sciences Laboratory (EMSL), a Department of Energy national scientific user facility located on the PNNL campus. "Some of the earliest, most successful cancer therapies targeted the EGF receptor pathway."
It is also a highly conserved pathway in evolutionary terms, he said, found in worms and fruit flies as well as in humans. More broadly, added Wiley, an expert in mathematical modeling of signaling networks, "the EGF receptor pathway is one of the best model systems for understanding cell signaling."
The primary mission of the paper was to lay the groundwork for building predictive mathematical models of cell signaling. To assemble such mechanistic models, scientists "need to know the amounts of the different signaling proteins," said Wiley, but until recently, the technology to do this did not exist.
Today it's possible to see the pattern and interconnections between signaling proteins, thanks to the advanced proteomics developed at PNNL. "We have better technology now," said Wiley. "This is the first study to accurately measure the levels of all the proteins in a particular signaling pathway."
Results: The researchers found that the EGF receptor pathway consisted of 16 core proteins and 10 feedback regulators. They then compared populations of both healthy and cancerous mammary cells because the different cell types showed different responses to EGF. But the question was: Were the protein abundance patterns also different?
They wanted to establish absolute numbers of each kind of protein. Previous studies of protein expression established only relative numbers, which invites mathematical speculation of sorts, as if you had to estimate the number of something very small by looking through blurry lenses. But for modeling, said Wiley, "you need absolute numbers."
The new proteomics technologies not only provided accurate protein amounts, but revealed that the proteins could be sorted into two groups: those that are constant across cell types and those that are highly variable. The results were very surprising.
Some of the constant proteins—such as adaptors—were found in far lower levels than proteins either upstream along the pathway or downstream. This means these adaptor proteins, some of them present at "vanishingly low levels," according to Wiley, are primary control points in cell signaling. Wiley called them "valves."
He also called the implications of this new understanding how information flows through signaling networks "profound." All previous models of EGF receptor signaling—derived from decades of work—assumed that these adaptor proteins are highly abundant and thus could not effectively control signaling. As a result of the new data and the new methods used to get them, Wiley says, "We now have a way to build models that are predictive."
Why It Matters: Understanding signaling pathways in this new way is central to efforts to rationally design new antiproliferative drugs and other therapies. Data like this could potentially be used to build models that will predict how cancer cells respond to various treatments. At the same time, these models open the way to personalized cancer treatments. The idea: take a biopsy from a patient, analyze the key proteins, and then design a customized treatment.
This research could also have profound implications for the way cell signaling networks are modeled in the future. With the combined technologies outlined in this paper, more robust models of cell signaling are now possible. For now, said Wiley, "when you put the real numbers into the (traditional) models, the models don't work. This will help us identify what is wrong with these models so that we can build better ones."
The same results can be extended to modeling other cellular pathways, said Wiley. "Using this approach, we hope to discovered other fundamental principles of how signaling is regulated."
Methods: Researchers used a newly developed technology called PRISM selective reaction monitoring (PRISM-SRM), a combination of high-resolution separations and ultrasensitive targeted proteomics. "Shi got the technology to actually work on our samples," said Wiley of lead author Tujin Shi, an integrative omics scientist at PNNL.
The research team defined the primary components-16 core proteins and 10 feedback regulators-of the epidermal growth factor receptor (EGFR)-mitogen-activated protein kinase (MAPK) pathway in normal human mammary epithelial cells. Then they quantified the absolute abundance of these proteins across a panel of normal and breast cancer cell lines as well as fibroblasts.
What's Next? The researchers want to use data from this study, and from future applications of their methods, to build mathematical models that will predict how cancer cells will respond to treatments.
Acknowledgments
Sponsors: EMSL, NIH
Research Area: Biological Systems Science, Environmental Molecular Sciences Laboratory
User Facility: EMSL
Research Team: Tujin Shi, Jason E. McDermott, Yuqian Gao, Carrie D. Nicora, William B. Chrisler, Vladislav A. Petyuk, Richard D. Smith, Karin D. Rodland, and Wei-Jun Qian of PNNL; Lye M. Markillie and H. Steven Wiley of EMSL; and Mario Niepel and Peter K, Sorger of Harvard Medical School.
Reference: Shi T, M Niepel, JE McDermott, Y Gao, CD Nicora, WB Chrisler, LM Markillie, VA Petyuk, RD Smith, KD Rodland, PK Sorger, W-J Qian, HS Wiley. 2016. "Conservation of Protein Abundance Patterns Reveals the Regulatory Architecture of the EGFR-MAPK Pathway." Science Signaling 9(436)rs6. DOI: 10.1126/scisignal.aaf0891.
