Pan-cancer liquid biopsy screening for the identification of actionable RNA biomarkers

01 January 2018 → 31 December 2020
Funding by bilateral agreement (private and foundations)
Research disciplines
  • Medical and health sciences
    • Morphological sciences
    • Oncology
    • Morphological sciences
    • Oncology
    • Morphological sciences
    • Oncology
biopsy RNA biomarker
Project description

The biggest challenges in cancer patient management are the use of more effective and less toxic treatmant modalities, better and less invasive methods to diagnose disease, to select the right drug, to monitor treatment response and to identify relapse disease early-on. Our project proposal aims to address several of these issures by the introduction of RNA based liquid biopsy guided precision oncology. We will screen easy-to-obtain plasma RNA from cancer patients to identify truly actionable RNA biomarkers, such as mutations, fusion genes, copy number variations, and tumor-specific RNA expression markers. These so-called companion or complementary diagnostic biomarkers, treatment response biomarkers, and early-relapse prediction biomarkers directly enable selection of the right drug, monitor therapeutic efficacy and identify relapse disease long before clinical symptoms, respectively. The ultimate goals is to develop and apply molecular tools for more effective therapeutic management and to substantially increase the survival rates of cancer patients.

In our project proposal, we explore new horizons of liquid biopsy research, by investigating cell-free circulation RNA in a field that is currently dominated by the analysis of DNA molecules. Importantly, as we plan to analyze this relatively unexplored source of biomaterial in various cancer types, our pan-cancer project is relevant for many patients requiring better care today. For the identification of actionable RNA biomarkers, we have initiated a pilot study to improve and standardize procedures for plasma collection and to optimize the analytical aspects of the targeted RNA sequencing technology for which we have successful proof-of-concept data. To this purpose, the TruSight RNA Pan-Cancer Panel will be further evaluated on RNA prepared from different plasma collection tubes and using different extractin methods, to be able to analyze the potential source of pre-analytical biases related to plasma derived circulating RNA isolation. Further, to fine-tune data analysis settings and filters to identify mutations in circulating RNA, the panel will be tested on a unique collection of plasma samples from children with neurobastoma for which mutation profiles have been previously generated based on whole-exome sequencing of primary tumor DNA, normal constitutional DNA and cell-free circulating DNA. Upon successfull technology development, we will then apply this technology to four types of adult cancer (melanoma, lung, colon and breast cancer) for which there is high clinical need and for which we have ongoing collaborations. In addition to structural RNA biomartkers, we have previously shown that plasma RNA also represents an important source of tumor-specific RNA expression markers. In the 2nd part of our project, we will therfore also exploit the possibility to establish a panel of cancer-specific RNA biomarkers detectable in the blood from cancer patients. Currently, our lab is finishing the development of a comprehensive database of cancer-specific non-coding RNAs using large scale reprocessd public tumor tissue derived RNA sequencing data for almost 40 different cancer types. For almost every cancer type, several specific RNAs were identified. This database will be used to select the top 20 most promising tumor entities for which a robust set of cancer-specific ncRNAs (and thus candidate plasma RNA biomarkers) is identified. Plasma will be pooled per entity and prifiled using RNA capture sequencing. As such, we will be able to determine for the first time and on such a large scale which cander-specific candidate ncRNA biomarkers are also circulating in the blood stream. Finally, top candidate biomarkers will be selected and validated in independent patient cohorts using PCR technology. Ultimately, this should lead to a quick, easy and cost-efficient test for monitoring of treatment response and early-prediction of relapse.