Qlucore Newsletter: Qlucore Advances Transcriptomic Based Cancer Diagnostics with €2.5 million in EU Support

Qlucore accelerates innovation in RNA-based clinical diagnostics, focusing on tests for acute myeloid leukemia (AML) and bladder cancer. The tests are software based and use established NGS lab workflows and advanced machine learning to generate subtype probabilities. The prestigious EIC Accelerator grant of 27 MSEK was awarded in 2024.

During the project, Qlucore will develop and launch CE-marked software for clinical cancer diagnostics for AML and bladder cancer. Another focus is, in collaboration with the pharmaceutical industry, to develop solutions for companion diagnostics. For this project, Qlucore will build on significant investments already made in the CE marked Qlucore Diagnostics BCP-ALL 1.0. It is a regulatory approved IVDR test that was launched in February and then sold to the first clinic shortly after.

AML and bladder cancer are of special interest to the project. This is because they harbor multiple RNA modifications. These changes can be utilized to improve diagnosis and treatment. Currently, this information is not fully utilized to ensure that the right treatment is used for the right patient. This is something the current project aims to change.

For bladder cancer, there are unique challenges for classification and treatment. Our solution combines gene expression-based classification with automatic fusion gene detection. The test will be designed to support clinicians to be able to make informed decisions faster.

Qlucore has passed all the milestones set out for the first part of the EIC Accelerator grant. All new samples have been sequenced, and RNA-seq data processing is complete. This brings our total to over 800 bladder cancer samples and 350 AML samples, significantly strengthening the foundation for training novel classifiers.

Prototype classifiers, previously trained on smaller datasets, have been successfully validated using publicly available gene expression data from two major cohorts.

The next phase involves training classifiers on these expanded datasets and preparing Qlucore Insights/Diagnostics to integrate and run the new models, bringing us closer to more precise and scalable diagnostics.