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Understanding Non-Coding Genome & Immune Response

Neff Newitt, Valerie

doi: 10.1097/01.COT.0000547234.02935.a6
Ansuman Satpathy, MD, PhD

Ansuman Satpathy, MD, PhD

Ansuman Satpathy, MD, PhD, learned an important life lesson as an English-speaking teenager enrolled in a German-language school in Stuttgart during one of his father's teaching sabbaticals. “There's nothing more uncomfortable than being a kid in a room where you don't understand a word anyone is saying,” he recalled. “But I survived, and by the end of year I was pretty fluent in German. I learned it's OK to be uncomfortable and in new situations. You can easily draw a connection to science and medicine—if you are OK being uncomfortable, you can find the courage to move into new scientific fields, or test new hypotheses.”

Today Satpathy, a physician-scientist and an instructor in the Department of Pathology, Stanford School of Medicine, does exactly that. Though he concentrated on immunology while doing his PhD work, he has allowed himself to enter into new arenas that were not originally in his comfort zone.

“Work I do now is at the interface of several different fields—immunology, cancer biology, genetics, and computer science. And I am definitely not formally trained in all of those things. When I came to Stanford, I went into a non-immunology, pure genomics lab where I knew pretty much nothing,” he divulged with a chuckle. “So being OK with not knowing much, and yet being able to dig in anyway, learn new things, and make progress, has been extremely important to my work.”

That work is now focused on developing new genome sequencing technologies for studying the immune system, particularly immune cells directly in patients. Satpathy and team are interested in studying the so-called “dark matter” of the human genome—the 98 percent of the genome that actually does not encode genes. “Over the past 10 years, the non protein-coding genome has been shown to have a critical role in regulating the expression of genes,” he explained. “Furthermore, studies have shown that the majority of genetic risk for many human diseases actually maps to the non-coding genome, rather than the sequences that encode genes. Now we are developing tools to allow us to study this space directly in cells from patients.”

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Emerging Technologies

Satpathy hopes to challenge cancer by using new tools to study cells in patients who respond—or are resistant—to immunotherapy. “By looking at this non-coding genome, we hope to find the precise molecular switches that turn on or turn off genes associated with cancer immunotherapy response,” he detailed.

The work began using tools from basic immunology, genomics, and computer science, but has expanded with the team's development of two new technologies that enable the measurement of the non-coding genome.

“The first technology is a method that allows us to identify active regulatory sites in the non-coding genome in single immune cells, and then to pair them with other information about the cells, such as the T-cell receptor sequence, or other proteins that are expressed by the cell,” Satpathy explained. “So for example, we can use this technique to identify exactly which non-coding sites are open and active in single T cells that are responding to tumors.

“One thing we've found is that every gene has somewhere between two and 10 regulatory sites that control its expression. Depending on the cell type or tumor setting, only a fraction of those sites will be active in any cell,” he continued. “The interesting thing is those sites are not always the ones that are nearest to the gene they control. You could have a key immune response gene, and 10 regulatory sites surrounding it, and the site that actually controls the expression of the gene in tumor-specific T cells could be the farthest away.

“So now, we have a way to map these molecular switches directly in single cells from patients. The second technology we have developed links these active regulatory sites precisely to the genes they regulate, allowing us to go deeper and map these interactions in three-dimensional space in the cell.”

And more challenges are being met. “Over the last 10 years, there has been progress in developing tools to identify sites in the non-coding genome that are actually regulating genes. But the problem has always been that a large amount of sample material is necessary to do that—a lot of cells or a lot of tissue from a person—which has made it almost impossible to work directly in patient samples,” said Satpathy.

In response, he and his team have advanced those tools to work on small samples so that they can look at sites directly in human cells. “The protocols that we've developed allow us to measure those sites with higher sensitivity,” he explained. “We've spent a lot of time developing these technologies and making sure they work well in primary human samples.

“Now we are ready to go a step further,” he continued. “We are collaborating with cancer researchers here at Stanford and throughout the U.S. to use their clinical trials samples from patients who are responding well to immunotherapy, as well as from those who don't respond at all to figure out the molecular basis for that level of response directly in patient cells. I am very excited about this.”

Already closing in on short-term goals—understanding how regulators work, where the sites are, which genes they regulate, which sites are “on” in patients who respond and which are “off”—Satpathy is also keenly aware of long-term goals. “We want to take that information and find a way to engineer the genome so that therapy works better. There are ways to actually target activator or repressor proteins to those sites and turn a gene switch on or off.”

Asked the moon-shot question—“Will this help to cure cancer?”—Satpathy answered, “I think so. That is the hope. If we can really understand how the cell works well, how it ‘decides’ to fight the cancer, and how it is subverted by the cancer's activity and ‘persuaded’ not to work, then the step of engineering the cell's genetic make-up to illicit a better immune response will not be as difficult.”

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A Matter of Time

The physician-scientist shares life with his wife, also a scientist working in immune-oncology, and his daughter, Aanya, not yet 2. “I like to insert her in conversations whenever I can,” said the doting father who added that he and his wife spend non-lab hours in family activities and travels. “With two scientists in the household it can be difficult to diffuse work tension—so we have agreed not to bring work home on weekends. We spend the time de-stressing, going to parks and museums, and traveling a lot.”

As for his professional time, Satpathy spends about 10 percent in clinical work, and 90 percent in research. He admitted it is the research side of the equation that really calls to him. “I like exploring the unknown and figuring out new ways to answer problems that other people have not thought about. That is how I like to spend my time,” he declared. “Of course, I am grateful for both experiences. I do like the one-on-one interactions with patients in clinical work. But when I think about how to change or reengineer therapies for patients, I realize I can impact so many more people.”

Asked to visualize cancer therapy 15 years into the future, Satpathy said he believes genomics and precision medicine will be integral to every aspect of a patient's experience, from using genomic information to diagnose a patient's particular cancer, to determining how best to treat it with a targeted therapy that itself will likely be engineered in some way to make it more efficacious.

Ansuman Satpathy, MD, PhD

Ansuman Satpathy, MD, PhD

“There are two broader outcomes of the work that will be so important for patients. One is in the diagnostic arena—understanding very early if a patient is responding to cancer immunotherapy, or, even before they get treatment, knowing if they have a high likelihood of responding,” he stressed. “The second is in engineering better therapies—better CAR T cells or better checkpoint blockade therapies, or better combinations of those, for example. If we understand how they work really well, then we can take the next step and engineer them to work even better. I believe genomics will be the cornerstone of all of that.”

Valerie Neff Newitt is a contributing writer.

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