# Pre-analytical factors affecting ctDNA analysis in early and locally advanced breast cancer

> **NIH NIH U01** · UNIVERSITY OF WISCONSIN-MADISON · 2022 · $349,281

## Abstract

PROJECT SUMMARY
Circulating tumor DNA (ctDNA) analysis has enabled noninvasive tumor genotyping for patients with advanced
metastatic cancers. There is now growing interest in replicating this success in patients with early stage
cancers. ctDNA analysis could enable blood-based minimal residual disease detection in patients receiving
treatment and early detection of cancers in pre-symptomatic individuals. However, ctDNA levels are 10s-100s
fold lower in localized cancers than in metastatic cancers, limiting the sensitivity of current assays. This is
further confounded by pre-analytical variability such as differences in blood collection and processing and DNA
extraction. For example, inappropriate or delayed blood processing can cause peripheral cell lysis and dilute
ctDNA fraction in blood samples. In early stage cancer patients where ctDNA levels are already quite low, this
can cause false-negative results. The effects of pre-analytical factors on ctDNA detection in patients with
localized cancers are not well understood.
To address this gap, we propose a study of 180 patients with early and locally advanced breast cancer to
investigate three aspects of pre-analytical variation: 1) DNA extraction methods (Aim 1), 2) blood collection
tubes and processing protocols (Aim 2) and 3) long-term storage of plasma and extracted DNA (Aim 3). We
will investigate these factors using two assays we have recently developed: 1) a quality assessment assay that
measures total cell-free DNA concentration and fragment size and 2) TARgeted DIgital Sequencing (TARDIS),
an assay that simultaneously measures up to 30 patient-specific founder mutations in plasma DNA to quantify
ctDNA levels. By leveraging multiple mutations for each patient, improving error suppression and minimizing
loss of input DNA material, TARDIS enables sensitive detection and precise quantification of ctDNA in patients
with localized cancers and improves limit of detection by 10-100 fold over current assays.
Minimal residual disease detection and early detection using ctDNA analysis hold tremendous promise to
individualize cancer treatment and to improve outcomes. Our study will clarify pre-analytical factors that could
be critical to the success of future clinical studies across localized cancers of multiple subtypes.

## Key facts

- **NIH application ID:** 10246983
- **Project number:** 5U01CA243078-04
- **Recipient organization:** UNIVERSITY OF WISCONSIN-MADISON
- **Principal Investigator:** Muhammed Murtaza
- **Activity code:** U01 (R01, R21, SBIR, etc.)
- **Funding institute:** NIH
- **Fiscal year:** 2022
- **Award amount:** $349,281
- **Award type:** 5
- **Project period:** 2019-09-18 → 2024-08-31

## Primary source

NIH RePORTER: https://reporter.nih.gov/project-details/10246983

## Citation

> US National Institutes of Health, RePORTER application 10246983, Pre-analytical factors affecting ctDNA analysis in early and locally advanced breast cancer (5U01CA243078-04). Retrieved via AI Analytics 2026-05-22 from https://api.ai-analytics.org/grant/nih/10246983. Licensed CC0.

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