Rapid blood test sensitive to advanced adenomas could improve patient prognosis and ultimately reduce mortality
Dxcover Limited, a clinical-stage diagnostics company developing spectroscopic liquid biopsy technology for early detection of multiple cancers, today presented new data in a presentation titled “Early Detection and Molecular Markers of Prevention” on the detection of colorectal cancer (CRC) using the company’s liquid biopsy platform at the 2023 American Association for Cancer Research (AACR) Annual Meeting in Orlando, Florida from April 14-19.
Co-founder and CTO Matthew Baker, PhD, outlined data from a preclinical study evaluating the Dxcover® Cancer Liquid Biopsy platform’s capabilities to detect advanced adenomas and early cases of colorectal cancer. CRC is the third most common cancer among both men and women, which would greatly benefit from earlier detection due to decreased survival rates as the cancer progresses. On average, the survival rate after diagnosis for CRC decreases from 91% in early-stage CRC to as low as 15% for stage IV.
Dxcover analyzed a retrospective cohort of 296 samples comprised of 100 CRC, 99 advanced adenomas (AA) removed by surgical resection and 97 colonoscopy screening controls. The classifier from the discovery reported the ability to detect 59% of advanced adenomas and 83% of Stage 1 CRC at a specificity of 90% which surpasses the targets set by the Centers for Medicare and Medicaid Services (CMS) for coverage of CRC tests.
“Early detection, and the detection of pre-cancerous adenomas, is critical to advancing lifespan for those impacted by potentially devastating diseases like colorectal cancer. This data shows that Dxcover’s unique approach at detecting biomarkers beyond tumor DNA allows our technology to detect sooner, faster and with precision to ensure patients receive the treatment they need, when it has the most potential to impact outcomes,” said Prof. Baker.
The Dxcover Cancer Liquid Biopsy test uses Fourier transform infrared (FTIR) spectroscopy and machine learning algorithms to build a classifier of the resultant spectral profiles to detect cancer and can be fine-tuned to maximize either sensitivity or specificity depending on the requirements of specific international healthcare systems.
For further information go to https://www.dxcover.com/science
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