Understanding cell‐cell communication and signaling in the colorectal cancer microenvironment

• Published in: Clinical and translational medicine 2021-02, Vol.11 (2), p.e308-n/a
• Main Authors: AlMusawi, Shaikha, Ahmed, Mehreen, Nateri, Abdolrahman S.
• Format: Article
• Language: English
• Subjects: Animals; Apoptosis; Cell Communication - physiology; Cell Culture Techniques; CellPhoneDB; CITE‐seq; Clinical medicine; Colorectal cancer; Colorectal cancer (CRC); Colorectal Neoplasms - pathology; Communication; Communications networks; Consortia; CyTOF; Drosophila; Epigenetics; Fibroblasts; Gene expression; Genomes; Genotype & phenotype; Homeostasis; Humans; Medical research; Metabolism; Metastasis; Mice; Mortality; Mutation; Ordinary differential equations; patient‐derived explant (PDE); patient‐derived organoid (PDO); patient‐derived xenografts (PDX); Physiology; Review; Reviews; scRNA‐seq; Signal Transduction - physiology; Tumor Microenvironment - physiology; Tumor microenvironments (TME); Tumors
• ISSN: 2001-1326; 2001-1326
• DOI: 10.1002/ctm2.308

Carcinomas are complex heterocellular systems containing epithelial cancer cells, stromal fibroblasts, and multiple immune cell‐types. Cell‐cell communication between these tumor microenvironments (TME) and cells drives cancer progression and influences response to existing therapies. In order to provide better treatments for patients, we must understand how various cell‐types collaborate within the TME to drive cancer and consider the multiple signals present between and within different cancer types. To investigate how tissues function, we need a model to measure both how signals are transferred between cells and how that information is processed within cells. The interplay of collaboration between different cell‐types requires cell‐cell communication. This article aims to review the current in vitro and in vivo mono‐cellular and multi‐cellular cultures models of colorectal cancer (CRC), and to explore how they can be used for single‐cell multi‐omics approaches for isolating multiple types of molecules from a single‐cell required for cell‐cell communication to distinguish cancer cells from normal cells. Integrating the existing single‐cell signaling measurements and models, and through understanding the cell identity and how different cell types communicate, will help predict drug sensitivities in tumor cells and between‐ and within‐patients responses. Graphical Headlights: 1. Multi‐cellular patient‐derived platform models intra‐/inter‐tumoral heterogeneity, and recapitulate human tumors’ complexity and microenvironment. 2. Simultaneous integration of multi‐omics data using multi‐cellular models enables identifying and comparing heterocellular cell‐cell communication in tumor vs normal tissues. 3. Multiple types of endpoint analysis using multi‐cellular patient‐derived models provide valuable insights for developing personalized cancer medicine, biomarkers and new therapies.