# Three-dimensional maps of senescence in the human pancreas

> **NIH NIH UG3** · JOHNS HOPKINS UNIVERSITY · 2022 · $550,000

## Abstract

Summary
The hallmark of cellular senescence is the inability of cells to progress through the cell cycle. With increasing
age, senescent cells accumulate in multiple tissues; their abundance increases in aging and several age-related
diseases such as atherosclerosis, diabetes, lung disease, and many others. Senescence is both a physiologically
fundamental and pathologically relevant program, with its role depending on the context and the specific
situation. Evidence linking senescence to common age-associated human diseases has emerged. Despite these
advances, little is known about the abundance, spatial distribution, precise nature, and functional relevance of
senescent cells in human tissues. The main challenge is paused by the extraordinarily complex heterogeneity of
the 3D architecture of tissues like the pancreas, even in non-diseased conditions, which greatly complicates the
spatially resolved identification of senescent cells. In this project, we will use the pancreas as a testbed and will
expand our 3D spatial analysis of cellular senescence to the human breast and ovaries of similar complex
heterogeneity. The development of spatial -omics approaches such as spatial transcriptomics/proteomics may
help overcome the challenge paused by 3D tissue heterogeneity. But these approaches only provide high-
content molecular information in a spatially resolved manner in 2D tissue sections. Here, we propose to establish
a new integrated 3D imaging platform that can map both the 3D architecture of large volumes (> 1cm3) of tissues
and can determine the location of senescent cells within a 3D tissue sample. Given its versatility, our proposed
integrated platform could readily be used to study spatial senescence in other tissues (besides the pancreas,
breast, and ovaries studied here) and to incorporate protein-based and RNA-based senescence signatures that
will be discovered by other centers and projects of the SenNet network. To produce the first comprehensive 3D
multiscale senescence atlas of tissues across ages, we propose the following aims in the UG3 and the UH3
phases. In the UG3 phase, in a small set of pancreatic and breast tissues, we will first integrate our new AI-
based 3D tissue reconstruction platform CODA with immunofluorescence (the CODA+IF platform) for multiple
labeling of senescence markers in FFPE tissue samples of non-diseased human pancreas and breast. We will
then integrate CODA with DBiT-seq (the CODA+DBiT-seq platform) and apply this integrated platform in regions
of the tissue sample that are poor and rich in cellular senescence, as identified by CODA+IF. In the UH3 phase,
we will apply these 3D cellular senescence mapping methods to large cohorts of pancreatic, breast, and ovarian
tissue. We will measure the distribution and variability and associated molecular signatures of senescent cells
within different tissue compartments in non-diseased tissue volumes as a function of age.

## Key facts

- **NIH application ID:** 10552336
- **Project number:** 1UG3CA275681-01
- **Recipient organization:** JOHNS HOPKINS UNIVERSITY
- **Principal Investigator:** Pei-Hsun wu
- **Activity code:** UG3 (R01, R21, SBIR, etc.)
- **Funding institute:** NIH
- **Fiscal year:** 2022
- **Award amount:** $550,000
- **Award type:** 1
- **Project period:** 2022-08-05 → 2024-07-31

## Primary source

NIH RePORTER: https://reporter.nih.gov/project-details/10552336

## Citation

> US National Institutes of Health, RePORTER application 10552336, Three-dimensional maps of senescence in the human pancreas (1UG3CA275681-01). Retrieved via AI Analytics 2026-05-25 from https://api.ai-analytics.org/grant/nih/10552336. Licensed CC0.

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