New pipeline analyzes drug responses in primary tumors

In a major step toward more effective cancer treatments, researchers at the University of Oulu have developed an innovative pipeline designed to directly analyze drug responses in tumor samples from primary patients. This method closes a critical gap in cancer treatment – ​​the difficulty of finding the right drug or drug combination for each patient. The new discovery represents a major step toward personalized medicine as it allows analysis of how individual cancers behave in response to different therapies.

The pipeline, which leverages live-cell barcoding, enables simultaneous screening of 96 drug treatments at single-cell resolution. The study focused on high-grade serous ovarian cancer (HGSOC) and the pipeline revealed the complex transcriptional landscape of tumors treated with 45 different drugs representing 13 different classes of mechanisms of action. By integrating advanced single-cell RNA sequencing, researchers can now map the gene regulatory dynamics that control resistance and sensitivity to cancer drugs directly on a patient's tumor in real time.

Experimental approaches using traditional cell line models often oversimplify the biology of real tumors, making it difficult to predict how a patient will respond to therapy. Working with primary patient samples not only improves the accuracy of these predictions, but also opens the door to building a large-scale, data-driven “omics” database of drug reactions.

“Our ability to directly study drug responses at the single cell level in primary tumor samples from patients in a multiplexed manner represents a major step towards personalized medicine,” said Daniela Ungureanu, Associate Professor at the University of Oulu.

This approach allows us to study how individual cancers behave in response to different therapies, which could help overcome the unpredictability of using cell lines or animal models. With this new data, we can create a powerful resource to guide treatment decisions in the clinic.”

Daniela Ungureanu, Associate Professor, University of Oulu

Establishing a comprehensive drug response database using primary samples will significantly improve the ability to match patients to therapies most likely to be effective and ultimately improve outcomes in personalized cancer treatment. By leveraging data from a broad range of patient tumors, physicians can determine specific gene regulatory responses that lead to resistance or sensitivity to treatments, creating a more tailored, data-driven treatment approach.

“Our results provide a promising framework for improving drug reuse and improving patient selection strategies, especially for those suffering from cancers with poor prognosis and limited treatment options,” said Alice Dini from the University of Oulu, the study's first author. “By leveraging advanced sequencing technologies, we can pave the way for more effective and personalized treatment approaches for HGSOC.”

In addition to researchers from the University of Oulu, researchers from the University of Helsinki and the Institute of Molecular Medicine Finland (FIMM) were also involved in the study.