Supplementary Material for: Advanced Minimal Residual Disease Detection Using a Novel Circulating Tumor DNA Assay: A Report of Two Cases

karger, figshare admin;G., Azzi;T., Slavin;J., Izaguirre-Carbonell;H.S., Sloane;D.L., Edelstein;C.X., Ma

Description

Introduction: Tumor-informed minimal residual disease (MRD) monitoring assays based on plasma circulating tumor DNA (ctDNA) are increasingly integrated into the clinical management of patients with cancer. In the post-surgical curative intent setting and as an adjunct to radiographic imaging for response assessment and surveillance, timely identification of MRD may better guide therapeutic decision-making. The increasing clinical adoption of MRD testing, supported by a growing body of evidence demonstrating its potential utility at critical decision points across diverse tumor histology, has brought attention to the variability in the analytical performance of available ctDNA assays. This variability is becoming increasingly appreciated as a key factor influencing clinical performance. Case Presentations: Here we report a case series in breast and rectal cancer involving treatment monitoring with a novel advanced MRD assay, illustrating its ability to identify subclinical metastasis and disease resolution below the validated limit of detection of a commercially available ctDNA assay in these cases.Conclusion: Results aided medical decision-making and underscored the need for highly sensitive assays in MRD detection. The differences in sensitivity, driven primarily by analytical variables, highlight the importance of selecting an assay that is not only analytically robust but also appropriately matched to the patient’s specific clinical context, to help ensure optimal utility and minimize the risk of misinterpretation.

Citations (0)

Mentions (0)

Metrics

Dataset Index

0.8

FAIR Score

85%

Citations

1

Mentions

0

Metrics Over Time

Publication Details

DOI

Publisher

Karger Publishers

License

Creative Commons Attribution 4.0 International

Assigned Domain

Subfield

Radiology, Nuclear Medicine and Imaging

Field

Medicine

Domain

Health Sciences

Confidence Score

58%

Source

Scholar Data Model

Keywords

Medicine

Normalization Factors

FT

63.46

CTw

1.00

MTw

1.00