Physics, statistics and genetics come together to reveal cancer's strategies
Nate Silver and Richard Feynman walk into a bar and bump into a biologist . . .
While this may sound like the setup to some late-night nerd sketch, researchers have taken this premise and applied it to an increasingly cumbersome problem in modern biology, namely, finding meaning in the rising oceans of genomic data.
In this specific instance, the data comprisesreams of cancer mutations that genome-wide studies are publishing at a dizzying rate. The challenge is finding new and efficient ways to parse the signal from the noise (and there is no shortage of noise).
As a new way to tackle this, a group of scientists have fused the power of statistical physics and artificial intelligence into a mathematical toolkit that can turn cancer-mutation data into multidimensional models that show how specific mutations alter the social networks of proteins in cells. From this they can deduce which mutations among the myriad mutations present in cancer cells might actually play a role in driving disease.
At the core of this new approach is an algorithm based on statistical mechanics, a branch of theoretical physics that describes large phenomena by predicting the macroscopic properties of its microscopic components.
"Here we have found that a fundamental concept in statistical mechanics, which many of us learned as undergraduates in theoretical physics courses and then largely forgot because it didn't apply to our everyday lives as biologists, can be relevant to one of the most difficult problems in cancer genetics," said Peter Sorger, the HMS Otto Krayer Professor of Systems Pharmacology and senior author on the paper.
These findings, which are among the first to be produced from the new Laboratory of Systems Pharmacology (LSP), are published November 2 online in Nature Genetics.
Dark Matter Matters
Many of the most widely studied cancer genes, such as P53 and Ras, were discovered after decades of work by many groups. But today, in the era of high throughput genomics, we have thousands of times more data from thousands of samples. As a result, the sheer volume of catalogued cancer mutations is vast. But not all mutations actually influence tumor behavior. Many appear to be along for the ride, so to speak, and are as a result called "passenger mutations."
In order to separate the drivers from the passengers, researchers typically use a kind of "polling" strategy in which they identify the most common mutations, reasoning that those are the significant ones. Only the most promising candidates are then subjected to the detailed and painstaking analysis that has been applied to P53 and Ras.
Mohammed AlQuraishi, an independent HMS Systems Biology fellow associated with the LSP and Sorger lab and lead author of the paper, reasoned that biologists were in dire need of much more biophysically rigorous tools for scouring this data. With a background in genetics, statistics and physics, AlQuraishi realized that biologists can exploit the statistical power from live data sets and marry it to theoretical physics. "It's the way that Silver and Feynman together would do it," he joked.
Statistical mechanics is a precise physical description of how collections of individual molecules give rise to the macroscopic properties we perceive, such as temperature and pressure. AlQuraishi used its core principles as the basis for a platform that would analyze information housed in the Cancer Genome Atlas. As a result he was able to generate detailed schematics of how certain mutations altered the vast, complex cellular world of protein social networks—networks that largely determine a cell's health, or lack thereof. In doing so, he stumbled upon a few unexpected findings.
Again, many cancer mutations are common, and many more cancer mutations are rare—some so rare that they only occur in a handful of patients. AlQuraishi found that common and rare mutations are equally likely to affect the protein network.
"Both kinds of mutations are equally strong," he said. "In both cases, about one percent of the common and one percent of the rare mutations alter the tumor networks we studied. But rare mutations are being largely ignored. We need to start paying attention to them."
For every common mutation, there are approximately four rare ones, so, based on numbers, rare mutations might be much more significant than previously suspected. "That's where much of the action is, in the rare mutations. We've long considered this large universe of rare mutations to be dark matter, but here we have just found that all this dark matter actually matters."
The researchers also found that mutations are not really the blunt force that they expected. Rather than knocking out an entire branch of a network, e.g., a neighborhood power outage, or inserting an entirely new character, i.e., a protein, mutations cause a subtle, almost surgically precise, altering of the communication pathway.
"From the perspective of the mutation, it is hard to be so precise," said AlQuraishi. "But cancer can't be too disruptive, or else it might die. It needs to fly under the radar. This subtle altering of networks achieves that objective. Drug companies can exploit this and possibly develop more targeted therapies."
A final area that these findings address is the problem of reproducing published results in the scientific literature. Here, however, the researchers are able to use fundamental physical principles to process datasets from different laboratories (including their own) in a way that removes the false positives and enriches for the true positives. The model is therefore more accurate and reproducible than any single data set.
"We can clean up the experiments by only using data that both the model and experiments agree on," said AlQuraishi.
"In general, much of the problem with irreproducibility in science is a problem of poor statistics," said Sorger. "We addressed that directly here."
This work was supported by the National Institutes of Health grants GM68762, GM107618 and GM072872.
Written by David Cameron
Harvard Medical School hms.harvard.edu has more than 9,000 full-time faculty working in 11 academic departments located at the School's Boston campus or in one of 47 hospital-based clinical departments at 16 Harvard-affiliated teaching hospitals and research institutes. Those affiliates include Beth Israel Deaconess Medical Center, Boston Children's Hospital, Brigham and Women's Hospital, Cambridge Health Alliance, Dana-Farber Cancer Institute, Harvard Pilgrim Health Care, Hebrew SeniorLife, Joslin Diabetes Center, Judge Baker Children's Center, Massachusetts Eye and Ear, Massachusetts General Hospital, McLean Hospital, Mount Auburn Hospital, Schepens Eye Research Institute, Spaulding Rehabilitation Hospital and VA Boston Healthcare System.
David Cameron | EurekAlert!
Transport of molecular motors into cilia
28.03.2017 | Aarhus University
Asian dust providing key nutrients for California's giant sequoias
28.03.2017 | University of California - Riverside
The Institute of Semiconductor Technology and the Institute of Physical and Theoretical Chemistry, both members of the Laboratory for Emerging Nanometrology (LENA), at Technische Universität Braunschweig are partners in a new European research project entitled ChipScope, which aims to develop a completely new and extremely small optical microscope capable of observing the interior of living cells in real time. A consortium of 7 partners from 5 countries will tackle this issue with very ambitious objectives during a four-year research program.
To demonstrate the usefulness of this new scientific tool, at the end of the project the developed chip-sized microscope will be used to observe in real-time...
Astronomers from Bonn and Tautenburg in Thuringia (Germany) used the 100-m radio telescope at Effelsberg to observe several galaxy clusters. At the edges of these large accumulations of dark matter, stellar systems (galaxies), hot gas, and charged particles, they found magnetic fields that are exceptionally ordered over distances of many million light years. This makes them the most extended magnetic fields in the universe known so far.
The results will be published on March 22 in the journal „Astronomy & Astrophysics“.
Galaxy clusters are the largest gravitationally bound structures in the universe. With a typical extent of about 10 million light years, i.e. 100 times the...
Researchers at the Goethe University Frankfurt, together with partners from the University of Tübingen in Germany and Queen Mary University as well as Francis Crick Institute from London (UK) have developed a novel technology to decipher the secret ubiquitin code.
Ubiquitin is a small protein that can be linked to other cellular proteins, thereby controlling and modulating their functions. The attachment occurs in many...
In the eternal search for next generation high-efficiency solar cells and LEDs, scientists at Los Alamos National Laboratory and their partners are creating...
Silicon nanosheets are thin, two-dimensional layers with exceptional optoelectronic properties very similar to those of graphene. Albeit, the nanosheets are less stable. Now researchers at the Technical University of Munich (TUM) have, for the first time ever, produced a composite material combining silicon nanosheets and a polymer that is both UV-resistant and easy to process. This brings the scientists a significant step closer to industrial applications like flexible displays and photosensors.
Silicon nanosheets are thin, two-dimensional layers with exceptional optoelectronic properties very similar to those of graphene. Albeit, the nanosheets are...
20.03.2017 | Event News
14.03.2017 | Event News
07.03.2017 | Event News
28.03.2017 | Life Sciences
28.03.2017 | Information Technology
28.03.2017 | Physics and Astronomy