Journal article
Identifying the Common Cell-Free DNA Biomarkers across Seven Major Cancer Types
Biology, Vol.12(7), pp.1-12
2023
PMCID: PMC10376459
PMID: 37508365
Appears in Cancer Research Cluster Research Collection
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.
Details
- Title
- Identifying the Common Cell-Free DNA Biomarkers across Seven Major Cancer Types
- Authors
- Mingyu Luo - Univ Sunshine Coast, Sch Sci Technol & Engn, Sippy Downs, Qld 4558, AustraliaYining Liu - Guangzhou Medical UniversityMin Zhao (Corresponding Author) - University of the Sunshine Coast
- Publication details
- Biology, Vol.12(7), pp.1-12
- Publisher
- MDPI AG
- Date published
- 2023
- DOI
- 10.3390/biology12070934
- ISSN
- 2079-7737
- PMID
- 37508365; PMC10376459
- Copyright note
- © 2023 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://creativecommons.org/licenses/by/4.0/).
- Data Availability
- The raw data used were from public Sequence Read Archive (SRA) databases.
- Organisation Unit
- Cancer Research Cluster; School of Science, Technology and Engineering; Centre for Bioinnovation
- Language
- English
- Record Identifier
- 991261895702621
- Output Type
- Journal article
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