Downregulation of Enteroendocrine Genes Predicts Survival in Colon Cancer: A Bioinformatics-Based Analysis

肠内分泌基因下调可预测结肠癌患者的生存期:一项基于生物信息学的分析

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Abstract

Colorectal cancer (CRC) is the fourth most common and the third mostly deadly cancer globally. Even with alternative therapies, some patients do not respond to treatment. Identifying modulations in the tumor microenvironment (TME) of CRC is a significant challenge due to the complex and dynamic nature of the TME. The intestinal epithelium comprises different types of secretory lineage cells, including goblet, tuft, Paneth, and enteroendocrine cells (EECs). Yet the relevance of each subtype of secretory intestinal epithelial cell (IEC) within the TME is still debated. This study investigated the involvement of IECs in CRC development through an integrative bioinformatics analysis. We used publicly available datasets from the National Center for Biotechnology Information, the Cancer Genome Atlas Program, and the National Cancer Institute's Proteomics Tumor Analysis Consortium, encompassing both human and mouse CRC samples. Our findings reveal a CRC microenvironment characterized by elevated expression levels of genes associated with WNT pathway activity. Remarkably, there was increased expression of Paneth cell-associated markers and transcription factors, such as WISP1, LYZ, SOX9, and DEFA1. Conversely, EEC-specific gene markers, such as GCG (encoding glucagon-like peptide-1) and CHGA exhibited significant downregulation in CRC tissue compared with healthy tissue, partially due to Paneth cell activity. Gene ontology analysis showed species-conserved downregulation in hormone/peptide secretion-related pathways in both mouse and human CRC. Of note, lower levels of GCG and CHGA correlated with reduced overall survival and demonstrated a correlation with the cell cycle, apoptosis, and proliferation. These results suggest that the disruption of enteroendocrine cell signaling is a hallmark of CRC development and may hold prognostic and therapeutic value in treating CRC patients.

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