Skip to Content

Spying on Cancer Cells with Mass Spectrometry

Protein profiles are uncovering weak spots in cancer’s armor.

Oregon researchers have used a new mass spectrometry technique to uncover a mutation that can cause leukemia. Their discovery is the first drug target uncovered by the method, which identifies abnormal cell-signaling proteins. The new technique, called protein mass spectrometry, could uncover other drug targets and reveal how drugs affect cancer cells.

The researchers were led by Brian Druker of the Oregon Health and Science University in Portland and Roberto Polakiewicz, chief scientific officer of Cell Signaling Technology in Danvers, MA. Druker’s lab focuses on a class of 90 signaling proteins called tyrosine kinases, which have been implicated in several kinds of cancer, including leukemia, breast cancer, and lung cancer. Mutations or other genetic mistakes can cause the activity of these proteins to go awry, leading to uncontrolled cell growth and division.

In the past, these proteins have been studied by sequencing the DNA of affected individuals and looking for common mutations. But cancer isn’t simple. “There are potentially hundreds of mutations in a given patient,” says Jeffrey Tyner, a postdoc in Druker’s lab. Only some of those mutations actually contribute to the cancer – and evaluating all of them is time-consuming.

In essence, DNA sequencing reveals only what the cell could do. Protein mass spectrometry, in contrast, provides a clearer picture of what the cell is doing. That’s why Cell Signaling Technology believes its approach is more efficient. “Proteomic [mass spectrometry] gives you the true readout of what’s going on in the cell,” says Mark Cobbold, a clinician scientist at the University of Birmingham, U.K.

Druker’s mass spectrometry study focused on acute myeloid leukemia, the most common form of the disease. And, while three common gene mutations are often to blame for it, in 30 to 50 percent of cases, the cause is unknown, says Tyner.

Druker hopes to duplicate his success in previous work on another form of leukemia, which led to the first successful molecularly targeted cancer drug, Gleevec (Imatinib). Approved for clinical use in 2001, the drug works by specifically binding to an abnormal tyrosine kinase protein and inhibiting it. The drug has worked wonders for some patients. “Druker is taking molecular medicine forward. Now he’s looking for other [leukemia targets] using a proteomics approach,” Cobbold says.

Looking at a cell’s actual molecular activity using mass spectrometry lets Druker avoid much of the guesswork in searching for cancer mechanisms. Instead of years, it took his lab just weeks to uncover a mutation in a gene for a kinase called JAK3 that causes the signaling molecule to be abnormally active. They found the mutation in a cell line, then verified the result in patients.

In proteomic mass spectrometry the researchers first break up cancer cells, purify their proteins, and cut them up. They then further purify stretches of protein characteristic of active tyrosine kinases. This mixture is put into the mass spectrometry machine, which sequences the proteins. With this information, researchers know which proteins are abnormally active and why – because of a mutation, for example – and can search for a drug that acts against them.

Tyner hopes their work can be translated into clinical tests for determining the molecular cause of a patient’s tumor. Protein mass spectrometry profiles of cells from a tumor biopsy could identify which protein is running amok and what drug would work best on it. “It’s very attractive, the idea of looking at signaling in tumors and from that uncovering [genetic] profiles,” says Cobbold.

Forest White, assistant professor of biological engineering at MIT, who uses mass spectrometry to study cell-signaling networks, is more cautious about direct clinical applications for the mass spectrometry technology: “It’s hard to imagine a mass spec in every hospital,” he says, because the results require expert interpretation. White points out that even scientists with advanced biological research labs have trouble reading mass spectrometry results. Instead, he suggests that the real value of using mass spectrometry to analyze a cell’s protein content lies in the possibility for a dynamic understanding of how cancer cells behave in different stages of the disease. In his lab, for example, White exposes cancer cells to a growth factor and uses mass spectrometry to quantify how the factor affects the activity of the cells’ tyrosine kinases.

In fact, Polakiewicz of Cell Signaling Technology says drug companies have expressed interest in the technology for just this purpose. Mass spectrometry might be used during cancer drug development to assay a compound’s effects on cancer cells’ signaling proteins.

Keep Reading

Most Popular

Large language models can do jaw-dropping things. But nobody knows exactly why.

And that's a problem. Figuring it out is one of the biggest scientific puzzles of our time and a crucial step towards controlling more powerful future models.

The problem with plug-in hybrids? Their drivers.

Plug-in hybrids are often sold as a transition to EVs, but new data from Europe shows we’re still underestimating the emissions they produce.

Google DeepMind’s new generative model makes Super Mario–like games from scratch

Genie learns how to control games by watching hours and hours of video. It could help train next-gen robots too.

How scientists traced a mysterious covid case back to six toilets

When wastewater surveillance turns into a hunt for a single infected individual, the ethics get tricky.

Stay connected

Illustration 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.