Abstract

A cell-free DNA (cfDNA) assay would be a promising approach to early cancer diagnosis, especially for patients with dense tissues. Consistent cfDNA signatures have been observed for many carcinogens. Recently, investigations of cfDNA as a reliable early detection bioassay have presented a powerful opportunity for detecting dense tissue screening complications early. We performed a prospective study to evaluate the potential of characterizing cfDNA as a central element in the early detection of dense tissue breast cancer (BC). Plasma samples were collected from 32 consenting subjects with dense tissue and positive mammograms, 20 with positive biopsies and 12 with negative biopsies. After screening and before biopsy, cfDNA was extracted, and whole-genome next-generation sequencing (NGS) was performed on all samples. Copy number alteration (CNA) and single nucleotide polymorphism (SNP)/insertion/deletion (Indel) analyses were performed to characterize cfDNA. In the positive-positive subjects (cases), a total of 5 CNAs overlapped with 5 previously reported BC-related oncogenes (KSR2, MAP2K4, MSI2, CANT1 and MSI2). In addition, 1 SNP was detected in KMT2C, a BC oncogene, and 9 others were detected in or near 10 genes (SERAC1, DAGLB, MACF1, NVL, FBXW4, FANK1, KCTD4, CAVIN1; ATP6V0A1 and ZBTB20-AS1) previously associated with non-BC cancers. For the positive–negative subjects (screening), 3 CNAs were detected in BC genes (ACVR2A, CUL3 and PIK3R1), and 5 SNPs were identified in 6 non-BC cancer genes (SNIP1, TBC1D10B, PANK1, PRKCA and RUNX2; SUPT3H). This study presents evidence of the potential of using cfDNA somatic variants as dense tissue BC biomarkers from a noninvasive liquid bioassay for early cancer detection.

Details

Title
Evaluation of cfDNA as an early detection assay for dense tissue breast cancer
Author
Mouadh, Barbirou 1 ; Miller, Amanda A 2 ; Gafni, Erik 3 ; Mezlini Amel 4 ; Zidi Asma 4 ; Boley, Nathan 5 ; Tonellato, Peter J 2 

 University of Missouri, Department of Health Management and Informatics, Center for Biomedical Informatics, School of Medicine, Columbia, USA (GRID:grid.134936.a) (ISNI:0000 0001 2162 3504); University of Tunis El Manar, Medical School of Tunis, Tunis, Tunisia (GRID:grid.12574.35) (ISNI:0000000122959819) 
 University of Missouri, Department of Health Management and Informatics, Center for Biomedical Informatics, School of Medicine, Columbia, USA (GRID:grid.134936.a) (ISNI:0000 0001 2162 3504) 
 Ravel Biotechnology Inc, San Francisco, USA (GRID:grid.134936.a) 
 University of Tunis El Manar, Medical Oncology Division, Salah Azeiz Oncology Institute, Tunis, Tunisia (GRID:grid.12574.35) (ISNI:0000000122959819) 
 Ravel Biotechnology Inc, San Francisco, USA (GRID:grid.12574.35) 
Publication year
2022
Publication date
2022
Publisher
Nature Publishing Group
e-ISSN
20452322
Source type
Scholarly Journal
Language of publication
English
ProQuest document ID
2666718654
Copyright
© The Author(s) 2022. This work is published under http://creativecommons.org/licenses/by/4.0/ (the “License”). Notwithstanding the ProQuest Terms and Conditions, you may use this content in accordance with the terms of the License.