Skip to main content
. 2021 Feb 22;9:639233. doi: 10.3389/fcell.2021.639233

Table 2.

Summary of cfDNA-based cancer liquid biopsy studies.

Cancer type Marker(s) Technical method Clinical significance Sample References
Hematological malignancies Copies of circulating NPM mutation A (NPM mut.A) DNA; TP53 mutations; MYD88 p.L265P mutation RT-PCR and sequencing analysis; direct sequencing and a PCR-restriction digestion analysis (RFLP); droplet digital PCR (ddPCR) Diagnosis Plasma; serum; cerebrospinal fluid (CSF) Hosny et al., 2009; Quan et al., 2015; Zorofchian et al., 2018
Thyroid cancer Cell-free DNA quantity and integrity index 180/67 Quantitative real-time PCR (qPCR) Diagnosis Plasma Salvianti et al., 2017
Colorectal cancer ALU115; dozens of DNA hypermethylation markers (e.g., SEPT9 and IKZF1, EMBP1, KCNQ5, CHST11, APBB1IP, and TJP2) qPCR; methylated CpG tandem amplification and sequencing (MCTA-Seq) Diagnosis Plasma Bhangu et al., 2017; Li et al., 2019
High cfDNA and ctDNA levels; methylated circulating DNA biomarkers (EYA4, GRIA4, ITGA4, MAP3K14-AS1, MSC) ddPCR Predicting response to therapy Plasma Barault et al., 2018; Lyskjaer et al., 2019
High cfDNA levels; methylation levels of HLTF, HPP1/TPEF, hMLH1, TAC1, and SEPT9 ddPCR; quantitative methylation-specific PCR Indicating prognosis Plasma; serum Wallner et al., 2006; Tham et al., 2014; Hamfjord et al., 2019
Gastric cancer Mutations of cadherin (CDH1), phosphatidylinositol-4,5-bisphosphate 3-kinase catalytic subunit alpha (PIK3CA), ARID1A (AT-rich interactive domain 1A), epidermal growth factor receptor (EGFR), and phosphatase and tensin homolog deleted on chromosome 10 (PTEN); 5-hydroxymethylcytosine (5hmC) Bidirectional sequencing; 5 hmC quantification Diagnosis Plasma Samuels et al., 2004; Li et al., 2005, 2017; Velho et al., 2005; Kaurah et al., 2007; Heald et al., 2010; Wen et al., 2010; Corso et al., 2011, 2012; Liu et al., 2011; Lee et al., 2012; Zang et al., 2012; Chen et al., 2013
Hepatocellular carcinoma RASSF1A promoter hypermethylation Methylation-specific PCR Diagnosis Serum Chan et al., 2008
Post-radiotherapy (RT) cfDNA levels; mutation of BAX, CYP2B6 and HNF1A RT-PCR; NGS Predicting response to therapy Plasma Park et al., 2018; Alunni-Fabbroni et al., 2019
Methylation of insulin-like growth factor-binding protein 7 (IGFBP7); higher level of circulating DNA RT-PCR Indicating prognosis Serum; plasma Ren et al., 2006; Li et al., 2018
HPV-positive metastatic cervical cancer HPV cfDNA Duplex digital droplet PCR (ddPCR) Diagnosis; predicting response to therapy Serum Kang et al., 2017
Nasopharyngeal carcinoma Epstein–Barr virus (EBV) DNA PCR Diagnosis Plasma Chan et al., 2017
Lung cancer act-EGFR mutant allele frequency (MAF) and T790M/act-EGFR MAF ratio; 36 cancer-related genes; TP53, RB1, BRAF, KIT, NOTCH1–4, PIK3CA, PTEN, FGFR1, MYC, MYCL1, and MYCN ddPCR; NGS Predicting response to therapy Plasma Almodovar et al., 2018; Del Re et al., 2018; Guibert et al., 2019
EGFR19del, L858R, and T790M; cfDNA concentration; KRAS mutation ddPCR; RFLP-PCR; mutant-enriched PCR Indicating prognosis Plasma or serum Ai et al., 2016; Yanagita et al., 2016
Prostate cancer Androgen receptor gene (AR) copy numbers (CN) and mutations; cfDNA concentration and mutations (BRCA2, PALB2); AR amplification, TMPRSS2-ERG fusion, PTEN gene deletion, NOTCH1 locus amplification along with genomic amplifications dPCR and target sequencing; targeted cfDNA sequencing; whole-genome sequencing (WGS) Predicting response to therapy Plasma, urine Xia et al., 2016; Goodall et al., 2017; Sumiyoshi et al., 2019
Hypermethylation patterns of two genes (GSTP1 and APC) Methylation-specific PCR Indicating prognosis Plasma Hendriks et al., 2018
Breast cancer ESR1 mutation Digital PCR Predicting response to therapy Plasma Beije et al., 2018
cfDNA concentration and cfDNA integrity (cfDI); ALU-247, ALU-115, and cfDNA Integrity; methylation of KLK10, SOX17, WNT5A, MSH2, GATA3 RT-qPCR; quantitative methylation-specific PCR Indicating prognosis Plasma Cheng et al., 2018; Hussein et al., 2019; Panagopoulou et al., 2019
Cervical cancer Increased cfDNA allele fraction deviation (AFD) Targeted deep sequencing Predicting response to therapy Plasma Tian et al., 2019
Bladder carcinoma Presence and dynamics of ctDNA Ultra-deep multiplex polymerase chain reaction–based next-generation sequencing Predicting response to therapy Plasma Christensen et al., 2019
Pancreatic cancer ABL1, ATM, DNMT3A, FLT3, HNF1A, NRAS, and SMAD4 NGS; Library Preparation Kit Predicting response to therapy Plasma Vietsch et al., 2017
Pretreatment cfDNA fragment size of ≤167 bp (mode) and high pre-treatment cfDNA levels Agilent 2100 Bioanalyzer and the Agilent High Sensitivity DNA chip Indicating prognosis Plasma Lapin et al., 2018
Esophageal cancer Mutations of TP53, PIK3CA, ERBB2 NGS; ddPCR Predicting response to therapy Plasma Pasternack et al., 2018
Oral squamous cell carcinoma Higher cfDNA levels Quantitative spectrometry Indicating prognosis Plasma Lin et al., 2018
Metastatic melanoma Baseline cfDNA concentration ddPCR Indicating prognosis Plasma Valpione et al., 2018