# Harnessing Induced Human Intestinal Organoids (iHIOs) and Metagenomics to Unravel Host Immune-microbiota Interactions During Cancer Chemotherapy-associated Clostridium difficile Infections

> **NIH NIH K08** · UNIVERSITY OF CINCINNATI · 2020 · $233,957

## Abstract

Cancer-chemotherapy associated Clostridium difficile infection (CDI) has an adverse effect on
treatment outcomes in cancer patients. It leads to treatment interruptions and/or dose intensity reduction with
calamitous effects on tumor regression. Unfortunately, efforts at reducing CDI incidence in cancer patients
have been hampered by limited understanding of CDI pathophysiology and poor performance of established
predictors particularly in cytoreductive cancer chemotherapy (CCC) treated patients. Until more reliable
predictors of CDI in CCC patients are identified and the basic science of CDI development is understood,
efforts to curtail incidence and improve treatment strategies will remain inadequate. The research aims of this
proposal are focused on preventing CDI in CCC-treated patients while providing the training scaffold for Dr.
Apewokin's transition to becoming an independent physician-scientist with a focus on cancer supportive care.
 Protection against gastrointestinal infections in the normal host is mediated by many processes.
Immunoglobulins provide humoral protection while the endogenous gut microbial community structure favors
resistance to pathogenic organism colonization. We have demonstrated in pilot studies that cytoreductive
cancer chemotherapy modifies these factors and leads to reduction of CDI-specific immunoglobulins and gut
microbial diversity. We propose a conceptual model of CCC-associated CDI that captures these processes and
accordingly hypothesize that CCC-induced loss of CD-specific humoral protection and microbial diversity
transforms CD colonization to infection. To test this conceptual model we will establish that AIM #1,
CCC patients who develop CDI (cases) have lower CD-specific humoral protection. In AIM #2, CCC patients
who develop CDI (cases) have lower gut microbial diversity, and AIM#3, CCC patients who develop CDI
undergo clonal expansion of existing CD organisms during CCC. We will conduct a case-control study of 16
CDI-positive cases and 16 CDI-negative controls. We will use metagenomics and induced human intestinal
organoid models (iHIOs) as a model system to interrogate CDI development in CCC patients. iHIOs
recapitulate human physiology and disease pathology, and incorporate components critical to disease and
human host response. We will also employ shotgun sequencing to evaluate microbial factors contributing to
CDI during CCC. Integrating these state-of-the-art methodologies with collaborative synergistic research
approaches will allow us to characterize CDI pathophysiology and elucidate mechanisms that could not be
performed by traditional methods and models.Training in 1) protein toxin biology and quantification techniques,
2) molecular biology and metagenomics, 3) biostatistics and immunogenetics, and 4) clinical trial design will
serve as a vehicle for Dr.Apewokin to transition to become an independent physician-scientist competitive
for external R type awards. A mentoring team consisting of co...

## Key facts

- **NIH application ID:** 9976757
- **Project number:** 1K08CA237735-01A1
- **Recipient organization:** UNIVERSITY OF CINCINNATI
- **Principal Investigator:** Senu Apewokin
- **Activity code:** K08 (R01, R21, SBIR, etc.)
- **Funding institute:** NIH
- **Fiscal year:** 2020
- **Award amount:** $233,957
- **Award type:** 1
- **Project period:** 2020-06-01 → 2025-05-31

## Primary source

NIH RePORTER: https://reporter.nih.gov/project-details/9976757

## Citation

> US National Institutes of Health, RePORTER application 9976757, Harnessing Induced Human Intestinal Organoids (iHIOs) and Metagenomics to Unravel Host Immune-microbiota Interactions During Cancer Chemotherapy-associated Clostridium difficile Infections (1K08CA237735-01A1). Retrieved via AI Analytics 2026-05-23 from https://api.ai-analytics.org/grant/nih/9976757. Licensed CC0.

---

*[NIH grants dataset](/datasets/nih-grants) · CC0 1.0*