Looking beyond DNA to see cancer with new clarity
Mapping how mutated proteins interact reveals previously unseen drug
targets

Date:
September 30, 2021
Source:
University of California - San Francisco
Summary:
Researchers 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 avoid the side
effects common with much current chemotherapy.



FULL STORY ========================================================================== "This is an entirely new way to do cancer research," said Nevan Krogan,
PhD, director of UCSF's Quantitative Biosciences Institute who is
co-senior author, along with Trey Ideker, PhD, professor at UC San
Diego School of Medicine, on a set of three related papers that appear
Sept. 30, 2021, in Science. "We realized we need another way to look at
cancer that takes it a step beyond DNA."

========================================================================== Krogan and Ideker look to 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.

"We're elevating the conversation about cancer from individual genes to proteins, allowing us to look at how the varying mutations we see in
patients can have the same effects on protein function," said Ideker,
noting that this work represents new technological capacity to explain
the effects mutations in a more precise way. "We've produced the first
map looking at cancer through the lens of interactions between proteins."
The effort to map these effects, dubbed Cancer Cell Map Initiative (CCMI),
is revealing, on a monumental scale, genetic patterns and organizing
principles that underlie the disease and potential new ways to tackle it.

The team's new studies describe the approach in detail, and highlight
findings when it was applied to breast cancer and cancers of the head
and neck.

Looking Beyond Gene Mutations to the Protein Disruptions They Cause Our
genes contain instructions for building proteins. which then interact with other proteins, almost always in large groups called complexes. These
protein complexes often regulate an activity or turn a function on
or off. If the underlying gene has a mutation, the resulting protein
complexes will as well.



========================================================================== These gene mutations can affect how well the resulting protein complexes
do their job. 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.

Currently, there are a small number of mutated genes that physicians
look at as biomarkers -- quantifiable indicators, such as the presence
of a particular molecule, that denote a condition in the body -- to help
them determine whether a particular cancer drug might benefit a patient,
said Ideker.

"The problem is that we've only found a few genes that we can work
with in this way to help guide prescription of an FDA-approved drug,"
he said. "Our studies provide a new definition of biomarkers based not
on single genes or proteins but on the large, multi-protein complexes."
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 of the throat.



========================================================================== CCMI's goal was to map the constellation of protein complexes formed
by about 60 genes commonly involved in either breast cancer or cancers
of the head and neck, and to see what each looked like in healthy
cells. Alongside that effort, he created maps of how protein complexes
are affected by hundreds of gene mutations in two cancerous cell lines.

Doing so presented a formidable computational challenge. The CCMI
collaboration allowed the team to use advanced and novel data analysis
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 explain 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, the authors
said. For example, they are also working on similar studies of protein interactions in psychiatric and neurodegenerative disorders, as well as infectious disease.

Ideker and Krogan see the CCMI collaboration as the real source of
strength behind this 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
the team to integrate an array 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." said Krogan. "I couldn't be more excited than I am right
now. We can do such damage to cancer." Krogan and Ideker are co-senior
authors on all three papers. First authors are Danielle Swaney, PhD,
and Minkyu Kim, PhD, MS, of UCSF and Fan Zheng, PhD and Marcus Kelly,
PhD, of UCSD For further author information, please see the studies.

The research was supported by grants from the National Cancer Institute
(U54 CA209891, U54CA209988, 5F30CA236404-02) and the National institutes
of Health (F32 CA239336, R50 CA243885, S10 OD026929) as well as other
public and philanthropic sources.

========================================================================== Story Source: Materials provided by
University_of_California_-_San_Francisco. Original written by Robin
Marks. Note: Content may be edited for style and length.


========================================================================== Journal Reference:
1. Danielle L. Swaney, Dana J. Ramms, Zhiyong Wang, Jisoo Park,
Yusuke Goto,
Margaret Soucheray, Neil Bhola, Kyumin Kim, Fan Zheng, Yan Zeng,
Michael McGregor, Kari A. Herrington, Rachel O'Keefe, Nan Jin,
Nathan K.

VanLandingham, Helene Foussard, John Von Dollen, Mehdi Bouhaddou,
David Jimenez-Morales, Kirsten Obernier, Jason F. Kreisberg, Minkyu
Kim, Daniel E. Johnson, Natalia Jura, Jennifer R. Grandis, J. Silvio
Gutkind, Trey Ideker, Nevan J. Krogan. A protein network map of head
and neck cancer reveals PIK3CA mutant drug sensitivity. Science,
2021; 374 (6563) DOI: 10.1126/science.abf2911 ==========================================================================

Link to news story: https://www.sciencedaily.com/releases/2021/09/210930140745.htm

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