Improved Quantification of Circulating Tumor DNA in Translocation-Associated Myxoid Liposarcoma by Simultaneous Detection of Breakpoints and Single Nucleotide Variants

IF 2.9 2区医学 Q2 ONCOLOGY

Cancer Medicine Pub Date : 2025-02-20 DOI:10.1002/cam4.70704

A. Schmid, U. Lausch, A. Runkel, J. Kiefer, T. Pauli, M. Boerries, B. Bogner, S. U. Eisenhardt, D. Braig

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引用次数: 0

Abstract

Background

Myxoid liposarcomas (MLS) can exhibit a disseminated metastatic pattern, necessitating extensive diagnostics during follow-up. With no tumor markers available, early diagnosis of recurrences and tumor monitoring is difficult. The detection of circulating tumor DNA (ctDNA; liquid biopsy) in MLS with the characteristic translocations t(12;16) and t(12;22) can provide an additional diagnostic. However, due to the often very low tumor fraction, distinguishing actual tumor variants from sequencing artifacts remains a key challenge.

Methods

Using MLS as a model for translocation-driven tumors, this study evaluates a refined analytical approach for detecting both single nucleotide variants (SNVs) and structural variants (SVs) with the highest possible sensitivity and specificity. Different analysis pipelines using Unique Molecular Identifiers (UMIs) were compared in dilution series of tumor DNA from MLS patients (n = 11) and a cell line. The results were validated on plasma samples (n = 36) from two MLS patients and one patient with Synovial Sarcoma (SS).

Results

In dilution series, the use of UMIs significantly reduced false positive events in SNV analysis while maintaining high sensitivity without significant differences. In SV analysis, the effect of UMIs was not consistently detectable, as some dilution series exhibited no false positive events even without UMI correction. Additional filter criteria further improved specificity without significantly compromising assay sensitivity. Validation on patient plasma samples confirmed these findings, demonstrating the advantages of the differentiated analytical approach.

Conclusion

By integrating a refined analytical approach for SNVs and SVs, we achieved reliable ctDNA detection that corresponded with the clinical course of the patients’ disease. This method enables non-invasive tumor detection in translocation-driven tumors with low mutational burden and can easily be adapted into routine clinical diagnostics.

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来源期刊

Cancer Medicine ONCOLOGY-

CiteScore

5.50

自引率

2.50%

发文量

907

审稿时长

19 weeks

期刊介绍： Cancer Medicine is a peer-reviewed, open access, interdisciplinary journal providing rapid publication of research from global biomedical researchers across the cancer sciences. The journal will consider submissions from all oncologic specialties, including, but not limited to, the following areas: Clinical Cancer Research Translational research ∙ clinical trials ∙ chemotherapy ∙ radiation therapy ∙ surgical therapy ∙ clinical observations ∙ clinical guidelines ∙ genetic consultation ∙ ethical considerations Cancer Biology: Molecular biology ∙ cellular biology ∙ molecular genetics ∙ genomics ∙ immunology ∙ epigenetics ∙ metabolic studies ∙ proteomics ∙ cytopathology ∙ carcinogenesis ∙ drug discovery and delivery. Cancer Prevention: Behavioral science ∙ psychosocial studies ∙ screening ∙ nutrition ∙ epidemiology and prevention ∙ community outreach. Bioinformatics: Gene expressions profiles ∙ gene regulation networks ∙ genome bioinformatics ∙ pathwayanalysis ∙ prognostic biomarkers. Cancer Medicine publishes original research articles, systematic reviews, meta-analyses, and research methods papers, along with invited editorials and commentaries. Original research papers must report well-conducted research with conclusions supported by the data presented in the paper.