Abstract 48P
Background
Liquid biopsies have become increasingly important diagnostic tools for early cancer detection due to their high sensitivity and minimal invasiveness. Within liquid biopsy samples, cell-free RNA (cfRNA) is a promising biomarker source for early cancer detection. However, as an emerging field rife with technical challenges, cfRNA profiling for diagnostic purposes lacks gold standards for both laboratory and bioinformatic protocols. At Flomics Biotech, we have overcome these challenges by developing a cfRNA-Seq pipeline that profiles human plasma cfRNA in a robust and reproducible manner. We are currently applying this pipeline to the ongoing LiquiDx pre-clinical study, with the goal of developing a cfRNA-based multicancer early detection test.
Methods
In this study, we apply our cfRNA-Seq pipeline to plasma samples from a cohort of 1,300 donors. The cohort consists of patients with colorectal, lung, breast, pancreatic or prostate cancer, or non-cancer diseases of the same organs, and healthy individuals. For each cancer type, patients with early or late stage disease were recruited. We analyze the cfRNA-Seq data using a combination of gold-standard bioinformatics tools, and advanced machine learning methods to identify cancer type-specific biomarker signatures.
Results
The study is at an early stage but we have already identified promising biomarker signatures that separate cancer from non-cancer patients, while the identification of cancer type-specific signatures is ongoing. Preliminary results indicate that our cfRNA-Seq pipeline is sufficiently sensitive for the identification of patients with early stage cancer or pre-cancerous conditions, and is even capable of identifying individuals with viral infections at the time of blood collection.
Conclusions
We demonstrate that the Flomics cfRNA-Seq pipeline has great potential for the identification of biomarkers for early cancer detection, which will accelerate treatment and result in more favorable patient outcomes. Beyond early cancer detection, our technology can be applied to other biofluids and diseases, including infectious and neurodegenerative diseases. This technology can also be applied to areas such as guiding (cancer) treatment selection and tracking response to therapies.
Editorial acknowledgement
Clinical trial identification
Legal entity responsible for the study
Flomics Biotech SL.
Funding
The Spanish Ministry of Science, Innovation and Universities.
Disclosure
All authors have declared no conflicts of interest.
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