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Inspired by Friend, a Scientist Reinvents Himself to Treat Cancer

Written by John Chadwick | SAS Senior Writer

 

A talent for analyzing complex data is now applied to human health

Gyan Bhanot380X254Gyan Bhanot was working as a scientist at IBM when a friend and co-worker became seriously ill.

“He had kidney cancer and was not expected to survive,” Bhanot said. “At one point, they gave him just a few weeks.”

But the colleague responded to a novel therapy and made a full recovery. And Bhanot, an accomplished physicist, was stunned and then intrigued.

“He came back to work after a month, walked into my office and told me: ‘You should really switch to biology,’ ’’ Bhanot said.

That was in the late 1990s.

Today, Bhanot is a School of Arts and Sciences professor pursuing a teaching and research mission inspired by his friend’s recovery.

Working in partnership with researchers at the Rutgers Cancer Institute of New Jersey, Bhanot studies large sets of molecular data with the goal of learning how tumors metastasize and which drugs might be effective in countering the spread.

The ultimate goal is to save lives.

“I’m a computational biologist – I work with the numbers,” he said.  “I need to work with biologists to translate patterns in the data into real understanding of biological mechanisms.”

Bhanot and a team of colleagues from outside Rutgers recently drew international attention for their performance in a competition focused on translating medical research on rodents for use in humans. Although mice and rats are routinely used in experiments, many questions remain as to how well the results can be applied to humans.

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Bhanot and his team won first place in three of four sub-competitions of the Species Translation Challenge by showing how gene expression levels in rodent and human cell lines can be used as the basis for understanding how certain cellular pathways are activated in humans.

“The big question has always been: how do we translate information obtained on rodents into predictions in humans?” Bhanot said. “If we can reliably translate information then the chances are that we can develop drugs that will be more effective for humans.”

A native of India, Bhanot’s facility for analyzing complex data is in his genetic makeup: his mother was a statistician, and his father a mathematician and linguist.

Arriving in the U.S. in the mid-1970s, he has demonstrated a penchant for making bold career leaps.

At 30, he left a tenured faculty job at Florida State University to join the legendary but doomed startup, Thinking Machine Corporation, which produced high performance computers, replicas of which were visible in scenes from the Jurassic Park movie.

“My wife said, ‘you must be nuts,’ ’’ Bhanot said.  “I joined Danny Hillis’ company which had many physicists working on designing supercomputers. We had a lot of fun.”

Twenty years later, Bhanot was at IBM when his co-worker’s recovery jolted him into another career transformation. He went on sabbatical at Princeton University, read up on biology, and began “hounding biologists until they talked to me,” including his daughter who is now a physician.

“She told me: ‘dad, you don’t know anything, you need to learn a lot,’’’ he recalled.

Bhanot ended up working with several renowned biologists, including Martin Weigert, then of Princeton University, and later with Arnold J Levine, co-discoverer of the p53 gene and Director of the Simons Center for Systems Biology at the Institute for Advanced Study in Princeton. Levine persuaded him to get back into academia and helped him find a position at Rutgers and the cancer institute

At SAS, Bhanot has appointments in the departments of Molecular Biology and Biochemistry, Physics and Astronomy, and the BioMaPs Institute.

He works most closely with the cancer institute’s Shridar Ganesan, a clinical and research oncologist who studies breast cancer biology and DNA repair.

“I analyze and process cancer data and come up with hypotheses, and many of my students go into Dr. Ganesan’s lab and test these hypotheses,” Bhanot said.  “The goal is to figure out what is going on. How do different drugs affect the tumor’s growth, why do treatments sometimes fail, and what can we do about this?”

Bhanot’s students also use computational approaches to study other public health threats. One student recently came up with several findings about a particular virulent strain of bird flu called H5N1. This student is now working at Los Alamos National Lab on understanding disease progression of HIV/AIDS in patients.

“It’s amazing to see that biology can do magical things when done right,” Bhanot said in explaining why he switched course. “It must be such a wonderful feeling for doctors when they are able to treat a patient successfully.

“I wanted to have that feeling.”


For more information on Bhanot’s work in the Species Translation Challenge, please click here

 

 

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