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.

Public Health Relevance

This study will help in improving our understanding of the cellular diversity, sub population of cells and their composition in human colon normal and disease tissue. Knowledge about these cells will play a pivotal role in developing better ways to combat human diseases. These studies have the potential for delivering diagnostic and prognostic biomarkers and therapeutic targets for inflammatory bowel disease and colon cancer.

National Institute of Health (NIH)
National Institute of General Medical Sciences (NIGMS)
Research Project (R01)
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Biodata Management and Analysis Study Section (BDMA)
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Ravichandran, Veerasamy
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University of California, San Diego
Schools of Medicine
La Jolla
United States
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