# Annotation of cell types in human colon tissue using Boolean analysis

> **NIH NIH R01** · UNIVERSITY OF CALIFORNIA, SAN DIEGO · 2020 · $354,375

## Abstract

Title: Annotation of cell types in human colon tissue using Boolean analysis
Abstract: Despite 50 years of extensive investigations to characterize the stem cell population in human colon
crypts, we still do not have a clear definition of cells that maintain the colon crypts. Identification of specific
markers of stem and progenitor cells in human colon tissue not only contribute to the field of (intestinal) stem cell
biology but also provides insight into colon cancer, adenoma and other diseases of the colon tissue. We have a
new method that has the ability to predict differentiation hierarchy using unbiased systems biology perspective
and mathematical models of large patient-derived gene expression datasets. We have mathematical models that
can predict the terminally-differentiated cells. The mathematical principle we use is based on Boolean implication
logic that has not been commonly applied to study tissue cell populations. The Boolean analysis assigns a
parameter (e.g. RNA level of a gene) with only two values, i.e., high/low, 1/0, or positive/negative. Applying the
Boolean principle, it is possible to determine the relationship between the expression levels of any pair of genes.1
As shown in Fig 2, the Boolean principle dictates only six different relationships: two are symmetric (equivalent
or opposite) (Fig. 2A, B) and four are asymmetric (low => low, high => low, low => high, and high => high)(Fig.
2C-F). Preliminary work based on Boolean implication has been shown to produce results in B cell differentiation,
bladder cancer and colon cancer. Boolean analysis was used to search for biomarkers of colon epithelial
differentiation across gene-expression arrays by identifying genes that have relationship with the activated
leukocyte-cell adhesion molecule (ALCAM/CD166) and fulfilled the “X low => ALCAM high” Boolean implication.
ALCAM is a marker of immature colon epithelial cells that is preferentially expressed at the bottom of colon
crypts2,3 and on human colon-cancer cells with enriched tumorigenic capacity in mouse xenotransplantation
models.4 The search yield 16 genes that includes CDX2, for which clinical grade diagnostic assays were readily
available. In large pooled database of randomized-adjuvant therapy trials CDX2 low stage II tumors responded
favorably when they are treated.5
 The primary goal of this proposal is to use Boolean implication relationships to decode the tissue
organization of human colon. Based on our preliminary data the overall hypothesis is that Boolean principles
can be used to specifically characterize the population of cell types in human colon tissue.
 These studies are expected to yield information about markers of specific cell types in the colon tissue,
cell differentiation, diagnostic and prognostic biomarkers. Consequently, they have the potential to impact current
guidelines about how to treat and manage colon cancer patients and even help identify potential future
therapeutic targets.

## Key facts

- **NIH application ID:** 9974241
- **Project number:** 1R01GM138385-01A1
- **Recipient organization:** UNIVERSITY OF CALIFORNIA, SAN DIEGO
- **Principal Investigator:** Debashis Sahoo
- **Activity code:** R01 (R01, R21, SBIR, etc.)
- **Funding institute:** NIH
- **Fiscal year:** 2020
- **Award amount:** $354,375
- **Award type:** 1
- **Project period:** 2020-06-01 → 2024-05-31

## Primary source

NIH RePORTER: https://reporter.nih.gov/project-details/9974241

## Citation

> US National Institutes of Health, RePORTER application 9974241, Annotation of cell types in human colon tissue using Boolean analysis (1R01GM138385-01A1). Retrieved via AI Analytics 2026-05-24 from https://api.ai-analytics.org/grant/nih/9974241. Licensed CC0.

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