Cell-Free DNA: Hope and Potential Application in Cancer

Yan, Yanyan; Guo, Qiaoru; Wang, Fenghua; Adhikari, Rameshwar; Zhu, Zhuangyan; Zhang, Haiyan; Zhou, Wenmin; Yu, Hua; Li, Jingquan; Zhang, Jianye

doi:10.3389/fcell.2021.639233

Cited by 79 publications

(72 citation statements)

References 128 publications

(58 reference statements)

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“…The quantification by ddPCR was more in line with yields obtained by qPCR, which seem to suggest the fluorimetric overestimation, but has also allowed for detection of samples which were inhibited in the qPCR analysis, most notably samples TIM-1 and TIM-5. This could be of importance for highly valuable, low-volume samples or those with the presence of inhibitors, giving ddPCR a supplementary role to qPCR cfDNA quantification, which is currently the gold standard ( Streleckiene et al, 2019 ; Yan et al, 2021 ). Quantification of cfDNA samples by capillary electrophoresis has shown yields more similar to the ones obtained by fluorometric analysis.…”

Section: Discussionmentioning

confidence: 99%

Impact of Preanalytical and Analytical Methods on Cell-Free DNA Diagnostics

Krasić

Abramović

Vrtarić

et al. 2021

Front. Cell Dev. Biol.

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Section: Discussionmentioning

confidence: 99%

Impact of Preanalytical and Analytical Methods on Cell-Free DNA Diagnostics

Krasić

Abramović

Vrtarić

et al. 2021

Front. Cell Dev. Biol.

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“…In brain cancer diagnosis, peripheral blood and CSF are the most popular materials (Figure 1 and Table 1; Siravegna et al, 2017b;Fontanilles et al, 2018;Yan et al, 2021). Circulating tumor DNA isolated from peripheral blood is effective for diagnosis and subtyping of brain cancer.…”

Section: Peripheral Blood and Cerebrospinal Fluidmentioning

confidence: 99%

Recent Advances in Liquid Biopsy of Brain Cancers

Fan

Jiang

et al. 2021

Front. Genet.

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Brain cancers are among the top causes of death worldwide. Although, the survival rates vary widely depending on the type of the tumor, early diagnosis could generally benefit in better prognosis outcomes of the brain cancer patients. Conventionally, neuroimaging and biopsy are the most widely used approaches in diagnosis, subtyping, and prognosis monitoring of brain cancers, while emerging liquid biopsy assays using peripheral blood or cerebrospinal fluid have demonstrated many favorable characteristics in this task, especially due to their minimally invasive and easiness in sampling nature. Here, we review the recent studies in the liquid biopsy of brain cancers. We discuss the methodologies and performances of various assays on diagnosis, tumor subtyping, relapse prediction as well as prognosis monitoring in brain cancers, which approaches have made a big step toward clinical benefits of brain cancer patients.

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“…Moreover, various research findings show that DNA methylation-based biomarkers are more consistent in comparison to those based on mutational profiles [7] , [8] . Detection of lung cancer with the help of EGFR mutation test V2 (Roche Molecular Diagnostics) and Epi procolon (Epigenomics AG) for colorectal cancer are some examples of cfDNA based FDA-approved tests [9] .…”

Section: Introductionmentioning

confidence: 99%

Computational challenges in detection of cancer using cell-free DNA methylation

Sharma

Verma

Kumar

et al. 2022

Computational and Structural Biotechnology Journal

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Cell-free DNA(cfDNA) methylation profiling is considered promising and potentially reliable for liquid biopsy to study progress of diseases and develop reliable and consistent diagnostic and prognostic biomarkers. There are several different mechanisms responsible for the release of cfDNA in blood plasma, and henceforth it can provide information regarding dynamic changes in the human body. Due to the fragmented nature, low concentration of cfDNA, and high background noise, there are several challenges in its analysis for regular use in diagnosis of cancer. Such challenges in the analysis of the methylation profile of cfDNA are further aggravated due to heterogeneity, biomarker sensitivity, platform biases, and batch effects. This review delineates the origin of cfDNA methylation, its profiling, and associated computational problems in analysis for diagnosis. Here we also contemplate upon the multi-marker approach to handle the scenario of cancer heterogeneity and explore the utility of markers for 5hmC based cfDNA methylation pattern. Further, we provide a critical overview of deconvolution and machine learning methods for cfDNA methylation analysis. Our review of current methods reveals the potential for further improvement in analysis strategies for detecting early cancer using cfDNA methylation.

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Cell-Free DNA: Hope and Potential Application in Cancer

Cited by 79 publications

References 128 publications

Impact of Preanalytical and Analytical Methods on Cell-Free DNA Diagnostics

Impact of Preanalytical and Analytical Methods on Cell-Free DNA Diagnostics

Recent Advances in Liquid Biopsy of Brain Cancers

Computational challenges in detection of cancer using cell-free DNA methylation

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