In the fight against cancer, researchers need all the help they can get. A pair of promising new medical studies published today in the journal Cell rely on an old and stalwart ally of science — high-powered mathematics.
US and European scientists have developed a digital “atlas” of immune cells that could lead to early detection and treatment of many types of cancer. The atlas approach works by mapping the complex interactions of immune cells that cluster around tumors when they first start to form.
By analyzing these interactions, doctors can potentially spot tumors before they take root then deliver a kind of preemptive immunotherapy strike. Immunotherapy is the use of drugs to stimulate the body's natural immune system. Given enough warning, such therapies could essentially stop cancer by preventing it from starting in the first place.
The tricky part has to do with numbers — very big numbers. The atlas approach requires tracking the interactions of millions of cells, each sorted according to up to 40 different identifying parameters. Such analysis requires high-octane mathematics and powerful computers, researcher Stéphane Chevrier said in an email.
“Since we are looking at millions of cells, making sense of this high dimensional data 'by hand' would be impossible,” Chevrier said. “Indeed, we have to use algorithms that have been specifically developed for this type of data and which require high computational power.”
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The researchers carried out two separate studies, focusing on kidney cancer and lung cancer. The goal, according to the research team, was to chronicle the entire “ecosystem” that surrounds nascent tumors when they begin forming in the human body.
These baby tumors can be difficult to locate because they camouflage themselves with other tissues and cells. The tumor becomes so entangled with other cells that the potential growth becomes a complex system in and of itself
Soma Kobayashi from the Ichan School of Medicine at Mount Sinai said that the ecosystem concept is actually a very helpful metaphor for what's happening when immune cells attack cancer.
“In the food chain, you can think of carrots being eaten by rabbits, which in turn are eaten by snakes,” said Kobayashi, who participated in the research. “In reality, though, rabbits also eat grass and have predators other than the snake, and these relationships are often visualized as a web as opposed to a linear chain of events.”
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And that's where the math comes in. Decoding the complex interaction of cells in this web is an enormous computational task. In documents announcing the new research, Bernd Bodenmiller, senior author of the Zurich kidney cancer study, said that most people would just see utter chaos in the massive data sets.
"But if you look for a bit longer, you will see patterns,” he said. “And then computational analysis reveals that there are relationships between the cell types in the tumor ecosystem that relate to a clinical outcome. We can even put this information into an equation and estimate survival."
The researchers plan to generate more of these cell atlases and share the results with the global cancer research community. Bodenmiller hopes the technique will follow the same course as human genome sequencing, with scientists sharing data and pooling computational resources worldwide. Ideally, all the industrial-strength number crunching will lead to clinical trials and new therapies for cancer patients.
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