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CalTech, UCSD Team Uses Single-Cell Phosphoproteomics to Predict Cancer Drug Resistance

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NEW YORK (GenomeWeb) – A team led by researchers at the California Institute of Technology and the University of California, San Diego, has used single-cell phosphoproteomics to detect changes in protein signaling linked to the development of drug resistance in glioblastoma.

Detailed in a paper published this week in Cancer Cell, the work was able to identify changes in protein signaling as early as several days after treatment, which could allow for the detection of drug resistance long before it becomes clinically apparent, CalTech researcher James Heath, senior author on the study, told GenomeWeb.

Drug resistance is a significant obstacle to precision cancer treatment as many tumors have proved able to adapt in ways that allow them to evade targeted therapies. Broadly speaking, two basic mechanisms are at play in the development of drug resistance: One, a Darwinian mechanism in which treatment acts as a selective pressure that allows tumor cells not harboring the targeted mutation to multiply; and, two, an adaptive mechanism in which cells change their signaling patterns to reroute around a targeted protein.

Enabled by the ability to do deep sequencing of tumors, researchers have been able to explore Darwinian mechanisms of resistance for some time, Heath said. Adaptive mechanisms, however, have been less studied, he said, particularly at the single-cell level.

In the Cancer Cell study, Heath and his colleagues looked at both forms of resistance, but found that in the glioblastoma cases they analyzed Darwinian mechanisms played little to no role. Adaptive mechanisms, on the other hand, proved key to the development of drug resistance, and, in fact, by identifying specific signaling changes, the researchers were able to identify combination therapies that suppressed tumor growth completely in mouse models of glioblastoma.

For their single-cell phosphoproteomics analyses, the researchers used the single-cell barcode chip (SCBC) technology developed in Heath's lab. The technology, which Heath introduced in a 2011 Nature Medicine paper, consists of hundreds or thousands of 3-nl volume microchambers, each of which can be loaded with single cells or a small defined numbers of cells. Each microchamber contains a series of immunoassays on antibody barcodes with duplicate barcodes per microchamber, allowing for the collection of single-cell protein measurements.

Heath and his colleagues have previously used the technology for work including profiling T cells used in adoptive cell transfer immunotherapy and investigating the effect of hypoxia on mTOR signaling in glioblastoma. In 2013, Heath and his former post-doc Rong Fan (now an associate professor of biomedical engineering at Yale University) launched a company, IsoPlexis, to commercialize the technology. Currently, Heath said, the firm's focus is providing single-cell analysis services to drug companies developing cell-based immunotherapies.

Commercializing phosphoproteomics pathway signaling services like those done in the Cancer Cell paper remains a ways off, Heath said, noting that while he believes the technology is sound, more clinical data is needed.

"Right now cell-based cancer immunotherapies are very hot, and the single-cell analysis that the [SCBC] platform allows is kind of uniquely enabling," he said. "But as we get a little more clinical evidence that these phosphoprotein signaling pathway analyses can really allow one to make clinical decisions, that will probably be the next technology that IsoPlexis puts forward."

Looking at the single-cell level allows researchers to identifying signaling patterns that are not readily apparent in bulk analyses, Heath said.

"If you do a bulk analysis and you look at all the phosphoprotein levels that might somehow be associated with [the drug target], basically what you find is that all those levels are suppressed, which tells you that the drug is working but doesn't give you any clue how the tumor is adapting to the drug," he said.

However, even though overall protein levels are lower, there can be changes in the relative abundances of one protein versus another that indicate the activation of pathways that will ultimately lead to resistance, Heath noted.

"At the single-cell level, one can make a scatter plot of the abundances of, say, one protein versus another, and you can start to see direct correlations," he said. "And it is those connections getting activated that you can see very early on."

In the case of the glioblastoma cells Heath and his colleagues looked at in the Cancer Cell paper, they were able to see such changes as early as 2.5 days after treatment.

Identifying which alternate pathway is activated due to drug treatment allowed the researchers to add another therapy targeted toward that second pathway, which proved effective in shutting down tumor growth in mouse models.

Heath and his colleagues have also tested the approach in other cancer types including melanoma and seen similar resistance mechanisms. They have also performed their analysis in actual patient samples, and while he noted that they have not been able to test their predictions in patients, "we can test them in vitro in cells and make a similar set of predictions and validate them."

Currently, the researchers are working to gather enough data to "set the stage for an actual clinical trial," Heath said. He noted, though, the challenge of putting together the sort of clinical trial such an effort would require where the combinations of therapies to be used would not be known until after the patients had been enrolled and their tumor analyzed.

He cited the I-SPY 2 breast cancer trial, in which researchers have used genomic and proteomic markers to guide therapy as a potential model for the sort of clinical trial he and his colleagues would like to do. In that trial, researchers used phosphoproteomics analyses to identify a marker, phosphorylated EGFR 1173, that has the potential to improve upon existing markers like HER2 and HR status while also expanding the population of patients considered likely candidates for Puma Biotechnology's tyrosine kinase inhibitor neratinib.

"The field is beginning to appreciate that this is necessary, but it is early days yet," Heath said.

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