# Epigenomic Mechanisms & STAT Networks in Persistent CA Candidemia

> **NIH NIH U19** · LUNDQUIST INSTITUTE FOR BIOMEDICAL INNOVATION AT HARBOR-UCLA MEDICAL CENTER · 2024 · $384,977

## Abstract

PROJECT SUMMARY/ABSTRACT
In hospitalized patients, the fungus Candida albicans invades the bloodstream and causes hematogenously
disseminated candidiasis (HDC). The mortality associated with this infection approaches 40%, even with
antifungal current antifungal therapy. Because Candida spp. constitute the third most common cause of
nosocomial blood stream infections, HDC is a serious public health challenge of increasing medical and
socioeconomic importance. A better understanding of both the fungus and the host is required to develop new
approaches to diagnose, prevent, and treat HDC. Characteristics of both the fungus and the host determine
which patients develop HDC, and among those, which ones develop persistent candidemia and/or succumb to
infection. However, these characteristics are incompletely understood. To address this fundamental gap in
knowledge, we propose to analyze an existing biorepository of host and fungal samples selected from a cohort
of 300 patients with candidemia. We will compare samples from 35 patients with candidemia who died with those
from 35 matched candidemic patients who survived. We will also analyze serial isolates from selected patients
with persistent candidemia. Using this biorepository and associated clinical information, we will link fungal
genotype/phenotype, and host epigenetics, immune responses, and signaling pathways to patient outcome.
Specifically, we will 1) determine C. albicans genomic, epigenetic, transcriptomic, and phenotypic signatures
associated with lethality and persistence during candidemia and 2) determine the host response to lethal vs.
non-lethal and persisting vs. resolving C. albicans clinical isolates, with a focus on signal transducer and activator
of transcription (STAT) molecules. The data generated by the project will be compiled by the Bioinformatics and
Data Monitoring (BDM) core and analyzed by the Computation and Predictive Modeling (CPM) core to identify
both fungal and host signatures that are associated with persistent and lethal candidemia. These signatures will
then be tested by mutational and gene silencing approaches to refine the models and generate new hypotheses
that will be tested in an iterative fashion. The results of this comprehensive analysis hold promise to lead to new
approaches to predict, prevent, and treat HDC.

## Key facts

- **NIH application ID:** 10904644
- **Project number:** 5U19AI172713-02
- **Recipient organization:** LUNDQUIST INSTITUTE FOR BIOMEDICAL INNOVATION AT HARBOR-UCLA MEDICAL CENTER
- **Principal Investigator:** Scott G Filler
- **Activity code:** U19 (R01, R21, SBIR, etc.)
- **Funding institute:** NIH
- **Fiscal year:** 2024
- **Award amount:** $384,977
- **Award type:** 5
- **Project period:** 2023-08-10 → 2028-05-31

## Primary source

NIH RePORTER: https://reporter.nih.gov/project-details/10904644

## Citation

> US National Institutes of Health, RePORTER application 10904644, Epigenomic Mechanisms & STAT Networks in Persistent CA Candidemia (5U19AI172713-02). Retrieved via AI Analytics 2026-05-21 from https://api.ai-analytics.org/grant/nih/10904644. Licensed CC0.

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