Protocol for spatial characterization of ECM collagen-GAG in colorectal cancer tumor microenvironment
Libby A. Boykin, Sneha Jayashankar, Khidr Kishan K. BudhwaniiD, Brahma Mubarak K. BudhwaniiD, Diya Samal, Chelsea L. Crawford, Allan TsungiD, Karim I. BudhwaniiD
Abstract
The extracellular matrix (ECM) plays a critical role in colorectal cancer (CRC) progression and therapeutic resistance. Accurate characterization of ECM composition and architecture is essential for understanding how CRC evades therapy, yet most protocols either assess ECM components in isolation or remain technically challenging. Here we present a robust yet simple protocol for spatial characterization of collagen and glycosaminoglycan (GAG) organization within the CRC tumor microenvironment (TME). Our method combines Alcian Blue and Picrosirius Red staining procedures with standardized tissue processing and imaging protocols. The protocol enables simultaneous visualization, assessment, and quantification of collagen and GAG distribution patterns in formalin-fixed, paraffin-embedded tissue sections. Key methodological advances include optimized dual-staining approach with distinct blue-red coloration for straightforward spectral separation on digital imaging systems, standardized reagent preparations, and validated imaging parameters. The complementary wavelengths facilitate both visual interpretation and potential digital separation, offering advantages over multi-component stains with overlapping spectral ranges. Validation across multiple CRC patient specimens demonstrates excellent reproducibility with consistent staining intensity using standard histology equipment. Because the resulting spatial maps can be compared directly with engineered or ex vivo tumor models, the protocol also provides a practical benchmark for microenvironment validation. This standardized approach to ECM visualization will advance TME research, support morphological studies, and enable comparative analyses across CRC subtypes. The methodology can be adapted to other solid tumor types and integrated with complementary techniques including digital pathology workflows for comprehensive microenvironment characterization and enhanced analysis capabilities.
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