New Technique May Reveal Repurposing Potential for Existing Drugs

A new technique may help reveal unknown benefits of existing drugs, according to a study from the Technical University of Munich (TUM). The new approach, called decryptE, could help identify new applications for already approved drugs and take steps toward precision medicine.

The study was published in Nature Biotechnology.

A detailed understanding of diseases

Precision medicine strives to target treatments to the right patient at the right time. The idea is to develop the most “individualized” therapies possible that are more effective and come with fewer side effects. But the drug development pipeline is an expensive and laborious process, riddled with pitfalls that cause 9 in 10 drugs to fail to make it through clinical trials.

“Developing drugs from scratch is a very time-consuming and costly undertaking and is plagued with disappointments, often related to the toxicity of newly developed drugs,” explained Bernhard Küster, a professor of proteomic and bioanalytics at TUM and senior author of the study.

One alternative to this is drug repurposing, the process of finding new therapeutic indications for existing drugs. Drugs that have already been through the trial process have plenty of clinical and safety data that could speed up approvals for new conditions.

But the premise of drug repurposing also requires a huge amount of knowledge of the disease at the cellular level, so researchers know exactly what molecular interactions to target and how.

To tackle this problem, Küster and his team developed a technique called decryptE to map and reveal these interactions, thereby uncovering new aspects of drug mechanisms. For example, showing how a class of anti-cancer drugs can also weaken the immune system.

“Sometimes, old drugs do completely unexpected things at the molecular level that may not be ‘visible’ using standard laboratory experiments,” Küster told Technology Networks. “Proteomic technologies like decryptE can help to uncover the molecular underpinnings of an observed (or presumed) beneficial (or toxic) drug effect.”

Yielding a vast amount of data

The researchers focused on 144 drugs currently used in cancer treatment or that are under investigation in clinical trials. They attempted to unearth potentially unknown benefits by mapping interactions between these drugs and 8,000 proteins.

In the decryptE approach, lab-grown cells are treated with various doses of each drug over an 18-hour period. Mass spectrometry then analyzes their impact on the cells’ proteins to learn their effects at low vs high doses, and how the drugs work at different time points.

In this way, decryptE records all information, effectively casting a wide net throughout the cell to pick up information instead of using specific experiments to answer defined questions. Digital methods trawl through the vast data with the aim of revealing previously undiscovered effects of these widely used drugs.

For example, the researchers describe a new finding involving a class of anti-cancer drugs called histone deactylase (HDAC) inhibitors. Without specifically looking at this research question, they found that HDAC inhibitors can also weaken the immune system, potentially affecting the treatment of cancers that involve the immune system such as lymphoma.

“[…] HDAC inhibitors entirely unexpectedly lead to the loss of T-cell receptors on immune cells, which has important ramifications for the combination of these drugs with so-called immune checkpoint inhibitors for the treatment of cancer patients,” Küster explained.

A resource for the wider research community

The team have now made their data available as a resource for other scientists in ProteomicsDB, sharing it with the global research community.

“We hope that many scientists with special expertise for certain diseases or proteins will look at the data and pick up findings for further research,” said Küster. “In this regard, we hope to accelerate the advancement of knowledge and translation into practical utility by following an open science policy.”

Küster has more research planned to advance this approach further.

“We are in the process of scaling the technology to the analysis of 2,500 approved drugs and in further cellular models of disease,” he explained. “We know the technology can be applied to in vitro cell culture and organoid model systems as well as to ex vivo experiments using blood cells. But we now want to investigate if the technology also works in vivo model of disease, typically in mice.”

Reference: Eckert S, Berner N, Kramer K, et al. Decrypting the molecular basis of cellular drug phenotypes by dose-resolved expression proteomics. Nat Biotechnol. 2024:1-10. doi: 10.1038/s41587-024-02218-y

About the interviewee:

Prof. Dr. Bernhard Küster is a professor of proteomics and bioanalytics at the Technical University of Munich. He holds a degree in chemistry from the University of Cologne and earned his doctorate in biochemistry at the University of Oxford. His research focuses on proteomics and precision medicine to understand how therapeutic drugs work, the molecular mechanisms of cancer and how these can inform individualized treatment approaches.