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Colorectal Cancer Cell Surface Protein Profiling Using an Antibody Microarray and Fluorescence Multiplexing
Published on: September 25, 2011
Spatial and single-cell transcriptomic analysis reveals fibroblasts dependent immune environment in colorectal cancer
Hang Jia1, Xianglin Liu1, Guimin Wang1
1Department of Colorectal Surgery, Changhai Hospital, Naval Medical University, Shanghai, China.
Abstract:
Colorectal cancer (CRC) exhibits a complex tumor microenvironment with significant cellular heterogeneity, particularly involving cancer-associated fibroblasts that influence tumor behavior and metastasis. This study integrated single-cell RNA sequencing and spatial transcriptomics to dissect fibroblast heterogeneity in CRC. Data processing employed Seurat for quality control, principal component analysis for dimensionality reduction, and t-Distributed Stochastic Neighbor Embedding for visualization. Differentially expressed genes were identified using DESeq2. Immune infiltration was assessed via Single-Sample Gene Set Enrichment Analysis, CIBERSORT, and xCell algorithms. Prognostic genes were identified through univariate Cox regression, followed by consensus clustering and survival analysis. Metabolic pathways were explored using scMetabolism. Experimental validation involved CCK8, scratch, and Transwell assays to evaluate the roles of key genes BGN and CERCAM in CRC cell proliferation and metastasis. Machine learning-driven analysis identified four fibroblast-associated genes (TRIP6, TIMP1, BGN, and CERCAM) demonstrating significant prognostic relevance in CRC. Consensus clustering based on these biomarkers stratified CRC patients into three distinct molecular subtypes (Clusters A-C). Notably, Cluster C exhibited the most unfavorable clinical outcomes coupled with marked upregulation of all four fibroblast-related genes. Comprehensive immune profiling revealed paradoxical features in Cluster C: heightened global immune activation (characterized by substantial leukocyte infiltration) coexisted with specific immunosuppressive elements, including significant enrichment of pro-tumorigenic M0 macrophages, depletion of anti-tumor plasma cells, and resting memory CD4+ T cells, along with coordinated upregulation of multiple immune checkpoint molecules. Computational prediction using the TIDE platform suggested enhanced immunotherapy responsiveness in Cluster C patients. Functional validation demonstrated that knockdown of BGN or CERCAM significantly impaired malignant phenotypes, reducing proliferative capacity, migration potential, and invasive ability. Fibroblasts demonstrate significant heterogeneity within the CRC immune microenvironment, impacting prognosis and therapeutic responses. Key genes BGN and CERCAM emerge as potential immunotherapeutic targets, offering new strategies for precision treatment of CRC.
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