Abstract
Abstract In the recent years, early detection of cancer using next-generation sequencing (NGS) has been en vogue, due to its potential to drastically improve the survival rate of cancer patients. Liquid biopsy is often viewed as the modus operandi for early detection, as taking biopsies from the actual organs is not practical for widespread screening tests. Among others, two main approaches attempted for early detection are based on cell-free tumor DNA (ctDNA) and circulating tumor cells (CTCs). The rarity of ctDNA and CTC is often debated as a major potential challenge for detection of cancer at early stages. In this work, we will discuss several other challenges that are necessary to address for developing a practical and high-quality screening application for early-stage detection of cancer. We will also provide a framework in which much of these challenges can be addressed. While a reasonable sensitivity is needed for such test to be of value, the most prominent matter regarding screening for cancer is specificity. Due to low prevalence of cancer, what may appear as a high specificity (e.g., 99%) could actually be insufficient, as it translates to a low positive predictive value (PPV) (e.g., in the 10% range). A low PPV would result in a large number of false positives in the test. These false positives would cause follow-up tests that are not only costly, but also could trigger unnecessary anxiety for the patients. A comprehensive validation process is another critical element in early detection. While it is tempting to perform validation based, solely, on groups of Healthy and Cancer patients, it can be shown that some signals caused by Benign conditions could highly resemble those of Cancer patients, and therefore result in false positives. We will show that distinguishing Benign from Cancer necessitates detection of more complex patterns, as opposed to simplistic measures such as genome-wide copy number variation (CNV). Yet another challenge in a liquid biopsy test is identification of the tissue-of-origin. Due to the mixed-signal problem inherent in ctDNA-based technologies, we argue that they face a higher challenge, as compared to CTC-based counterparts, for obtaining this goal. In conclusion, we will show how a system based on CTCs, whole genome sequencing (WGS), and artificial intelligence (AI) could provide an appropriate framework for addressing much of the challenges in early detection of cancer for a true screening application with the specificity in the 99.99% range. Citation Format: Bahram G. Kermani, Sarah Huecker, Stefan Kirsch, Bernhard Polzer. Challenges of screening applications for early detection of cancer using liquid biopsy [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2019; 2019 Mar 29-Apr 3; Atlanta, GA. Philadelphia (PA): AACR; Cancer Res 2019;79(13 Suppl):Abstract nr 1625.
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