SAN FRANCISCO, Sept. 30 (Korea Bizwire) — Researchers at UC San Francisco and UC San Diego have mapped out how hundreds of mutations involved in two types of cancer affect the activity of proteins that are the ultimate actors behind the disease. The work points the way to identifying new precision treatments that may skirt side effects common with much current chemotherapy.
The effort, dubbed Cancer Cell Mapping Initiative (CCMI), is led by Nevan Krogan, PhD, director of UCSF’s Quantitative Biosciences Institute and Trey Ideker, PhD, professor at University of California San Diego School of Medicine and Moores Cancer Center, who are also co-senior authors on a set of three related studies that describe the map. The papers appear September 30 in Science (Swaney et al.; Kim et al.; Zheng et al.).
“This is an entirely new way to do cancer research,” said Nevan Krogan. Krogan noted that targeted treatments based simply on DNA sequencing of tumors haven’t been as effective as hoped. “We realized we need another way to look at cancer that takes it a step beyond DNA.”
“The bottom line is that we’re elevating the conversation about cancer from individual genes to whole protein complexes,” Ideker said. “For years different groups have been discovering more and more gene mutations that are involved in cancers. But now we’re able to explain these mutations at the next level — by looking at how the different gene mutations in different patients actually have the same downstream effects on the same protein machines. This is the first map of cancer from the protein complex lens.”
Looking Beyond Gene Mutations to the Protein Disruptions They Cause
The team looked at proteins, which carry out the vast majority of functions in the body—and which take on a collection of forms that far outnumber our genes, providing a much more expansive view of the activity underlying cancer.
DNA contains the instructions for building proteins, which then interact with other proteins, almost always in large groups called complexes. These protein complexes regulate an activity or turn a function on or off. If the underlying DNA has a mutation, the resulting protein complexes will as well.
These gene mutations can affect how well the resulting protein complexes do their jobs. For example, a particular interaction between two proteins might be crucial to repairing damaged DNA. If the mutated version of one of those proteins is shaped differently than normal, it may not interact correctly with the other protein, and the DNA might not get repaired, leading to cancer.
Mapping Protein Mutations
There is a subset of genes that are commonly mutated in cancer, Krogan said, and each of these genes can be mutated in hundreds of different ways. In addition, the function of a particular protein may be different in different types of cells, so a mutation in a breast cancer cell might have different effects on protein complexes than that same mutation’s effect in a cell in the throat.
CCMI’s goal was to map the constellation of protein complexes formed by approximately 60 proteins commonly involved in either breast cancer and cancers of the head and neck, and to see what each looked like in healthy cells. Alongside that effort, they created maps of how protein complexes are affected by hundreds of different gene mutations in two cancerous cell lines.
Doing so presented a formidable computational challenge. But the CCMI collaboration allowed the team to use advanced and novel data analyses to reveal not only whether the mutation affected interactions between proteins, but to what extent.
“That kind of detail shows us how well an existing drug might work, or explains why it doesn’t,” Ideker said.
The most powerful aspect of these extensive protein interaction maps is that they can shed the same light on many other conditions, Krogan said. For example, the team is also at work on similar studies of protein interactions in psychiatric and neurodegenerative disorders, as well as infectious disease.
Collaboration is Key
Krogan and Ideker see the CCMI collaboration as the real source of strength behind the approach.
“We’re not only making connections between different genes and proteins but between different people and different disciplines,” Krogan said. “Those collaborations have built up an infrastructure that allows them to integrate an array of types of information and push the boundaries of what’s possible in applying data science to complex diseases.”
“We’re in the perfect position to take advantage of this revolution on every level. I couldn’t be more excited than I am right now. We can do such damage to cancer.”
Funding: This research was supported by grants from the National Cancer Institute (U54 CA209891, U54 CA209988, 5F30CA236404-02) and the National institutes of Health (F32 CA239336, R50 CA243885, S10 OD026929) as well as other public and philanthropic sources.
About QBI: The Quantitative Biosciences Institute (QBI) fosters collaborations across the biomedical and the physical sciences, seeking quantitative methods to address pressing problems in biology and biomedicine. Motivated by problems of human disease, QBI is committed to investigating fundamental biological mechanisms, because ultimately solutions to many diseases have been revealed by unexpected discoveries in the basic sciences.
About UCSF: The University of California, San Francisco (UCSF) is exclusively focused on the health sciences and is dedicated to promoting health worldwide through advanced biomedical research, graduate-level education in the life sciences and health professions, and excellence in patient care. UCSF Health, which serves as UCSF’s primary academic medical center, includes top-ranked specialty hospitals and other clinical programs, and has affiliations throughout the Bay Area. UCSF School of Medicine also has a regional campus in Fresno. Learn more at ucsf.edu or see our Fact Sheet.
Gina Nguyen, 646-326-8936
GinaT.Nguyen@ucsf.edu | @QBI_UCSF
Robin Marks, 415-663-6768
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Source: Quantitative Biosciences Institute at the University of California, San Francisco via GLOBE NEWSWIRE