Bioinformatics Analysis for Circulating Cell-Free DNA in Cancer.

Chiang-Ching Huang,Meijun Du,Liang Wang

doi:10.3390/cancers11060805

Chiang-Ching Huang, Meijun Du + Show 1 more

Open Access

https://doi.org/10.3390/cancers11060805

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Abstract

Molecular analysis of cell-free DNA (cfDNA) that circulates in plasma and other body fluids represents a “liquid biopsy” approach for non-invasive cancer screening or monitoring. The rapid development of sequencing technologies has made cfDNA a promising source to study cancer development and progression. Specific genetic and epigenetic alterations have been found in plasma, serum, and urine cfDNA and could potentially be used as diagnostic or prognostic biomarkers in various cancer types. In this review, we will discuss the molecular characteristics of cancer cfDNA and major bioinformatics approaches involved in the analysis of cfDNA sequencing data for detecting genetic mutation, copy number alteration, methylation change, and nucleosome positioning variation. We highlight specific challenges in sensitivity to detect genetic aberrations and robustness of statistical analysis. Finally, we provide perspectives regarding the standard and continuing development of bioinformatics analysis to move this promising screening tool into clinical practice.

Highlights

To date, tissue biopsy samples are widely used to characterize tumors
Attention is turning to liquid biopsies, which enable the analysis of tumor components, including circulating tumor cells (CTC) [2] and circulating tumor nucleic acids from various biological fluids, mostly blood and other accessible fluids such as urine [3]
Direction cell-free DNA (cfDNA) molecules have emerged as promising biomarkers for cancer detection and monitoring

Summary

Introduction

Tissue biopsy samples are widely used to characterize tumors. tissues allow the histological definition of the disease and can reveal details of the genetic profile of the tumor, enabling prediction of disease progression and response to therapies, the applications are limited on tissue availability, sampling frequency, and their genetic heterogeneity [1]. The requirement for such a high degree of sensitivity can lead to false positive results due to potential errors of PCR amplification and sequencing To address this challenge, new data analysis approaches have been developed, among which is a new unique molecular identifier (UMI) strategy [36]. By physically extracting and individually amplifying the DNA clones of erroneous reads, another barcoding-free method is reported to distinguish true variants of frequency >0.003% from the systematic NGS error This method uses 10 times less sequencing reads compared to those from previous studies and achieved a PCR-induced error rate of 2.5 × 10−6 per base per doubling event [59]

Detection of DNA Copy Number Alterations

Identification of DNA Methylation Changes from cfDNA

Findings

Conclusions and Future