Skip to Content
MIT News magazine

Chemotherapy, Personalized

Key genes can predict sensitivity to toxin
February 24, 2009

Genetic tests can indicate whether a given person is at risk for certain diseases. But recent work by MIT scientists suggests that it may soon be possible to test how well people will tolerate toxic compounds, as well. Such tests could even enable doctors to predict how a given patient will respond to specific chemo­therapy drugs.

The scientists, led by Leona Samson, director of MIT’s Center for Environmental Health Sciences and professor of biological engineering and biology, first measured gene expression in cells from 24 healthy people in a genetically and ethnically diverse population sample. Then they exposed these cell lines to a DNA-damaging agent, MNNG. By comparing gene expression in the four most sensitive and the four most resistant cell lines, they were able to zero in on 48 key genes correlated with MNNG sensitivity. By measuring the activity of these standouts alone, without examining every gene, they found that they could predict, with 94 percent accuracy, whether any of the remaining cell lines would stand up to the toxic compound. Because the cell lines came from a diverse group of subjects, the test should be widely applicable in the general population.

Samson says that the group already knew of a dozen genes linked to MNNG resistance, but this study scanned for all potential candidates, identifying 450 that were differently expressed. “We found an incredible number,” she says. “That made us realize that there are a whole lot of other things going on that are important for protecting against damaging agents.”

MNNG was an ideal test subject because it’s similar to toxic compounds found in common chemotherapy drugs and tobacco smoke. Now Samson’s group is expanding the study to chemotherapeutic agents. She hopes that in the long run, the group’s work will lead to tests that can determine which drugs will be most effective in killing a particular tumor and, just as important, how well a patient’s healthy cells will resist that compound’s toxic action. “You want to kill the tumor but you don’t want to kill the person,” Samson says. And while she’s hesitant to speculate, she’s hopeful about the potential of the work: “The important thing is finding the most effective treatment for each individual patient. It’s really thinking toward the possibility of personalized medicine.”

Keep Reading

Most Popular

transplant surgery
transplant surgery

The gene-edited pig heart given to a dying patient was infected with a pig virus

The first transplant of a genetically-modified pig heart into a human may have ended prematurely because of a well-known—and avoidable—risk.

Muhammad bin Salman funds anti-aging research
Muhammad bin Salman funds anti-aging research

Saudi Arabia plans to spend $1 billion a year discovering treatments to slow aging

The oil kingdom fears that its population is aging at an accelerated rate and hopes to test drugs to reverse the problem. First up might be the diabetes drug metformin.

Yann LeCun
Yann LeCun

Yann LeCun has a bold new vision for the future of AI

One of the godfathers of deep learning pulls together old ideas to sketch out a fresh path for AI, but raises as many questions as he answers.

images created by Google Imagen
images created by Google Imagen

The dark secret behind those cute AI-generated animal images

Google Brain has revealed its own image-making AI, called Imagen. But don't expect to see anything that isn't wholesome.

Stay connected

Illustration by Rose WongIllustration by Rose Wong

Get the latest updates from
MIT Technology Review

Discover special offers, top stories, upcoming events, and more.

Thank you for submitting your email!

Explore more newsletters

It looks like something went wrong.

We’re having trouble saving your preferences. Try refreshing this page and updating them one more time. If you continue to get this message, reach out to us at customer-service@technologyreview.com with a list of newsletters you’d like to receive.