# Pre-Clinical Core

> **NIH NIH P01** · H. LEE MOFFITT CANCER CTR & RES INST · 2021 · $332,297

## Abstract

CORE 2 PROJECT SUMMARY
PRECLINICAL MODELS AND PATHOLOGY CORE
The Preclinical Core (Core #2) leverages the knowledge and expertise from several Moffitt investigators and
core facilities and will pursue three aims that systematically support the Program Projects at three critical
stages; 1) model development, 2) measurement and analysis of outcome, and 3) validation in human cohorts
and organoid models. In the Aim 1, Core #2 is tasked with mouse model generation and characterization. The
Core will use the embryonic stem cell-genetically engineered mouse model (ESC-GEMM) approach to enable
the rapid generation of lung cancer mouse models. To this end, ESCs will be established from existing lung
cancer GEMMs that also harbor regulatory alleles for efficient targeting of ESCs and control of gene
expression. ESCs will be targeted with inducible expression cassettes, followed by injection into blastocysts to
generate chimeric animals. ESC-derived lung cells in such chimeras carry the alleles necessary to induce lung
tumorigenesis, and chimeras will be used as experimental animals without further breeding. This approach
allows for the very rapid generation of lung cancer models having modulated expression or activity of metabolic
enzymes of interest. In Aim 2, Core #2 will streamline the quantification of tumor burden in these mouse
models by providing digital pathological (DP) analysis of murine lung cancer models. As input, histology slides
are imaged at multiple magnifications using automated slide scanners. The resulting high-resolution images
are processed and analyzed using innovative machine learning algorithms we have developed. The platform
allows for the identification, characterization, and quantification of lung tumors and individual cells within whole
lung sections. Deep learning methods will be applied to provide a comprehensive characterization of lung
tumors, including tumor grading and the assessment of immune cell infiltration. Histology samples and
datasets created by the program projects will be used to create training libraries for new algorithm
development. The DP platform allows for highly accurate and rapid image analysis, accelerating the
characterization of lung tumor models. In Aim 3, Core #2 will provide resources and expertise to validate
outcomes from the mouse studies of the first two Aims. The Core will provide large, well-annotated human
cohorts represented by tissue microarrays and a centralized workflow for the generation of organoid models.
The Core will assist with project planning and method development, diagnostic consultation, biomarker scoring,
result interpretation, and manuscript writing. Additional pathology resources will include microscopic evaluation
of animal and human tissues for adequacy and diagnosis, antibody selection guidance, optimization for
immunohistochemistry (IHC), and multiplexed immunofluorescence imaging.

## Key facts

- **NIH application ID:** 10171104
- **Project number:** 1P01CA250984-01A1
- **Recipient organization:** H. LEE MOFFITT CANCER CTR & RES INST
- **Principal Investigator:** William Douglas Cress
- **Activity code:** P01 (R01, R21, SBIR, etc.)
- **Funding institute:** NIH
- **Fiscal year:** 2021
- **Award amount:** $332,297
- **Award type:** 1
- **Project period:** 2021-06-25 → 2026-05-31

## Primary source

NIH RePORTER: https://reporter.nih.gov/project-details/10171104

## Citation

> US National Institutes of Health, RePORTER application 10171104, Pre-Clinical Core (1P01CA250984-01A1). Retrieved via AI Analytics 2026-05-22 from https://api.ai-analytics.org/grant/nih/10171104. Licensed CC0.

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