# A Comprehensive Protocol for Tissue of Origin Prediction in Circulating Cell-Free DNA

> **NIH NIH F31** · UNIVERSITY OF CALIFORNIA LOS ANGELES · 2022 · $38,569

## Abstract

PROJECT ABSTRACT
 Circulating cell-free DNA (cfDNA) in the bloodstream originates from dying cells and is a promising non-
invasive biomarker for cell death. Recent studies have demonstrated that cfDNA levels are correlated with
cancer, tissue trauma, autoimmune disease, and organ transplants, indicating the potential clinical utility of
cfDNA. CfDNA, however, can originate from any number of tissues throughout the body, and some of the cfDNA
present in an individual at a given moment is likely originating from healthy cell turnover. To better understand
tissue degeneration, especially in the context of disease, a reliable estimate of the tissue of origin of cfDNA is
needed. Identifying the tissue of origin of cfDNA will have direct impact on disease diagnosis and monitoring,
and in quantitative biomarker discovery.
 Pre-existing methods for tissue of origin decomposition are inadequate for cfDNA. Firstly, cDNA is only
present in a small amount in the blood. Current decomposition methods generally rely on array-based platforms
that require an onerous amount of patient blood, which may not be clinically applicable. An alternative is whole
genome bisulfite sequencing data, which requires lower input cfDNA, but is noisy. This data is not addressed
with previous methods. Finally, accurately decomposing cfDNA mixtures requires a robust understanding of all
possible tissue types that could potentially contribute to the mixture. This robust reference, however, is nearly
impossible to assemble, as there are hundreds of distinct tissue types, and because the methylation state for a
CpG in a tissue can vary. This could lead to biases in the decomposition results of previous methods.
 In this proposal, we aim to address the limitations of previous methods by developing a comprehensive
workflow for cfDNA tissue-of-origin prediction. We will develop a statistical method for predicting the tissue of
origin of cfDNA, allowing for low read count data and unknown tissue types (Aim 1). We hypothesize that this
will reduce bias in decomposition estimates and allow our method to be more widely used than previous methods.
Additionally, we propose developing a capture protocol that will enrich for cfDNA fragments that are informative
of tissue or disease status. This protocol will be designed to use with only small amounts of input cfDNA (Aim
2). We hypothesize that a capture panel approach will vastly reduce sequencing costs and, thus, increase the
clinical utility of our approach. Lastly, we propose applying our method to a large cohort of ALS patients and age
matched controls (Aim 3). If successful, this biomarker will have substantial impact on the treatment of
and drug development for ALS and other degenerative diseases.

## Key facts

- **NIH application ID:** 10373970
- **Project number:** 5F31NS122538-02
- **Recipient organization:** UNIVERSITY OF CALIFORNIA LOS ANGELES
- **Principal Investigator:** Christa Caggiano
- **Activity code:** F31 (R01, R21, SBIR, etc.)
- **Funding institute:** NIH
- **Fiscal year:** 2022
- **Award amount:** $38,569
- **Award type:** 5
- **Project period:** 2021-04-01 → 2023-03-31

## Primary source

NIH RePORTER: https://reporter.nih.gov/project-details/10373970

## Citation

> US National Institutes of Health, RePORTER application 10373970, A Comprehensive Protocol for Tissue of Origin Prediction in Circulating Cell-Free DNA (5F31NS122538-02). Retrieved via AI Analytics 2026-05-24 from https://api.ai-analytics.org/grant/nih/10373970. Licensed CC0.

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