Identifying the Common Cell-Free DNA Biomarkers across Seven Major Cancer Types

SIMPLE SUMMARY: Blood-based circulating cell-free DNA (cfDNA) biomarkers are important for cancer detection because they can provide a less invasive and more cost-effective way of detecting cancer and offer the possibility of screening large populations at risk for the early detection of multiple cancers. However, highly sensitive techniques are needed to detect circulating tumour DNA (ctDNA), and further optimization and standardization of pre-analytical and analytical steps are required to harness the full potential of cfDNA analysis. ABSTRACT: Blood-based detection of circulating cell-free DNA (cfDNA) is a non-invasive and easily accessible method for early cancer detection. Despite the extensive utility of cfDNA, there are still many challenges to developing clinical biomarkers. For example, cfDNA with genetic alterations often composes a small portion of the DNA circulating in plasma, which can be confounded by cfDNA contributed by normal cells. Therefore, filtering out the potential false-positive cfDNA mutations from healthy populations will be important for cancer-based biomarkers. Additionally, many low-frequency genetic alterations are easily overlooked in a small number of cfDNA-based cancer tests. We hypothesize that the combination of diverse types of cancer studies on cfDNA will provide us with a new perspective on the identification of low-frequency genetic variants across cancer types for promoting early diagnosis. By building a standardized computational pipeline for 1358 cfDNA samples across seven cancer types, we prioritized 129 shard genetic variants in the major cancer types. Further functional analysis of the 129 variants found that they are mainly enriched in ribosome pathways such as cotranslational protein targeting the membrane, some of which are tumour suppressors, oncogenes, and genes related to cancer initiation. In summary, our integrative analysis revealed the important roles of ribosome proteins as common biomarkers in early cancer diagnosis.