Next step in precision oncology - Studying the suitability of microRNA expression pattern to predict individualized treatment in cancer

• Applicant: Dr. Alexander Wurm
• Subject Area: Hematology, Oncology ; Cell Biology
• Term: since 2021
• Project identifier: Deutsche Forschungsgemeinschaft (DFG) - Project number 452587293

Cancer comprises a group of lethal diseases caused by malignant transformation of healthy cells. It develops during a complex multi-facetted progress that includes various steps of genetic and epigenetic alterations. The competition of early cancer subclones for space and nutrients impacts the characteristics mature tumor. Activation and inactivation of cellular pathways has a huge influence on the growth advantage of dominant clones and the response to specific treatment strategies of the final tumor at diagnosis.Recent studies revealed that different tumor entities share molecular characteristics that influence intracellular pathway activity and treatment response. Although the implementation of global DNA mutation analysis by high throughput examinations enables the consideration of a variety of genetic alterations it still lacks appropriate accuracy. As a consequence, many patients show promising initial responses to targeted therapies but suffer from relapse, probably due to the clonal expansion of non-responsive small tumor subpopulations. Other proposed high throughput biomarkers with high potential are based on RNAomics, proteomics, metabolomics and epigenomics. However, accurate sensitivity and specificity is still lacking.MicroRNAs (miRNAs) are small non-coding RNAs that influence many biological processes including cancer initiation and progression. Expression of several miRNAs is associated with treatment response to standard first line therapy in cancer. In comparison to protein coding genes, measurement of miRNA gene signatures by high throughput RNA sequencing technologies give more consistent information about possible cellular activities as they are determined at a mature stage. We developed a miRNA expression pattern based drug prediction workflow that considers highly differentially expressed miRNAs, corresponding hyperactive pathways and individually highly expressed druggable target genes. We verified this strategy initially by analyzing acute myeloid leukemia (AML) and colorectal cancer (CRC) datasets. Moreover, we validated it experimentally by exploring chemoresistant HL60 AML cells in vitro. By analyzing miRNA signatures of cancer patients with distinct mutational profiles, we observed a strong reduction of groups of miRNAs inhibiting relevant mutation-associated pathways.Hence, we hypothesize that distinct miRNA signatures pass a strict negative selection process during cancer evolution and pathway activation and might be suitable to uncover important cancer cells dependencies. We presume that developing cancer target gene specific miRNA gene signatures and a corresponding drug panel will help to reach decisions towards specific individual treatment regimes in the future.The major aims of the project proposal are: 1) Verifying the miRNA signature clonal selection hypothesis in primary models of AML and CRC and 2) validating the drug prediction workflow in primary cancer models.

• DFG Programme: Research Grants