Biological background of the genomic variations of cf-DNA in healthy individuals

Abstract

Background: Cell-free DNA (cf-DNA)-based liquid biopsy is emerging as a revolutionary new method in individualized cancer treatment and prognosis monitoring, although detecting early-stage cancers using cf-DNA remains challenging, partially because of the undefined biological background of cf-DNA. Materials and methods: We investigated somatic mutations in the cf-DNA of 259 cancer-free individuals with a median age of 47 years using an endogenous barcoding duplex method with an ultralow base error rate (2 Â 10 À7) and compared the variant allele frequencies (VAFs) of these mutations between the cf-DNA and the corresponding blood cell DNA. Results: Sixty percent (155/259) of the samples showed at least one nonsynonymous mutation on either of two similar target panels covering 508 and 559 cancer-related genes. For individuals older than 50 years of age, the positive rate increased to 76%. Most cf-DNA mutations were also present at similar VAFs in the paired blood cell DNA. The most frequently mutated genes were driver genes of hematologic malignancies, including DNMT3A, TET2, AXSL1, and JAK2. However, the other 58.4% (192/329) of the mutations were likely 'passenger mutations' of clonal hematopoiesis, including mutations in NOTCH2, FAT3, EXT2, ERBB4, and ARID2, which are driver genes of solid tumors. Conclusion: Hematopoietic clone-derived mutations, including 'driver mutations' and 'passenger mutations', are prevalent in the cf-DNA of both healthy individuals and cancer patients and may be a potential source of false positives in the liquid biopsy. Our results also suggest the ineffectiveness for distinguishing clonal hematopoietic mutations of low VAF (0.1%) from tumorderived mutations using conventional next-generation sequencing of blood cell DNA. However, an error correction model with an ultralow error rate and high coverage depth is required for blood cell DNA sequencing, which is difficult and costly to achieve with current technologies.

White blood cell and cell-free DNA analyses for detection of residual disease in gastric cancer

“…As the majority of cfDNA typically arises from hematopoietic cells 49 , a major challenge for the development of MRD assays using noninvasive liquid biopsies is distinguishing tumor-specific mutations from background changes associated with biological variation. WBC-derived alterations that arise as a consequence of clonal hematopoiesis may confound liquid biopsy analyses that are based on characterization of cfDNA as these may occur in common cancer driver genes [38][39][40][41] . As we have shown here, cfDNA analyses without parallel analyses of WBC DNA would have been unable to appropriately identify patients that benefit from perioperative treatment in terms of event-free and overall survival.…”

“…However, blood-based deep sequencing approaches have raised concerns about detection and misclassification of white blood cell (WBC)-derived variants in cfDNA associated with clonal hematopoiesis of indeterminate potential 18,[35][36][37] . Such studies have typically assessed WBC DNA and cfDNA in patients with cancer at a single timepoint 18,[38][39][40] or in healthy individuals 41 , and did not attempt to evaluate these during the course of therapy to predict clinical outcome.…”

High-intensity sequencing reveals the sources of plasma circulating cell-free DNA variants

“…These somatic mutations may provide a fitness advantage to some HSCs and/or their descendant cells, resulting in their disproportionate expansion 8,[18][19][20] , or arise through neutral drift 21 . CH increases with age and occurs in up to 31% of older individuals 10,20,[22][23][24][25][26] , and can also be detected in cfDNA sequencing analysis 27 . In this context, it may confound the interpretation of cfDNA sequencing, particularly because a large proportion of the cfDNA fragments originate from hematopoietic cells 28 .…”

The evolutionary dynamics and fitness landscape of clonal haematopoiesis

“…Future directions. CH has associated risks with cardiovascular disease 7,48 and progression to blood cancers 7,8,14,18 , and has important consequences in the study of ctDNA 49,50 , aplastic anaemia 51 , response to chemotherapies 52,53 and bone marrow transplant 40,54,55 . A major challenge is to develop a predictive understanding of how variants and their VAFs affect disease risk.…”