International Journal of Molecular Medical Science, 2024, Vol.14, No.4, 239-251 http://medscipublisher.com/index.php/ijmms 239 Feature Review Open Access Unveiling Cellular Heterogeneity in Colorectal Cancer Through Single-Cell Sequencing Jiahao Zhu, Jie Lian, Haibo Lu Department of Outpatient Chemotherapy, Harbin Medical University Cancer Hospital, Harbin, 150081, Heilongjiang, China Corresponding author: luhaibo@hrbmu.edu.cn International Journal of Molecular Medical Science, 2024, Vol.14, No.4 doi: 10.5376/ijmms.2024.14.0026 Received: 25 Jun., 2024 Accepted: 29 Jul., 2024 Published: 12 Aug., 2024 Copyright © 2024 Zhu et al., This is an open access article published under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. Preferred citation for this article: Zhu J.H., Lian J., and Lu H.B., 2024, Unveiling cellular heterogeneity in colorectal cancer through single-cell sequencing, International Journal of Molecular Medical Science, 14(4): 239-251 (doi: 10.5376/ijmms.2024.14.0026) Abstract Intratumoral heterogeneity poses a significant challenge in the treatment and understanding of colorectal cancer. Recent advancements in single-cell sequencing technologies have provided unprecedented insights into the cellular diversity within colorectal tumors. This study explores the application of single-cell RNA sequencing (scRNA-seq) and multiomics approaches to dissect the complex heterogeneity of colon cancer at a single-cell resolution. By analyzing individual tumor cells, researchers have identified distinct subtypes of cancer-associated fibroblasts, cancer stem cells, and immune cell populations, each contributing uniquely to tumor progression and therapeutic resistance. The integration of transcriptomic, genomic, and epigenomic data has revealed the dynamic interplay between genetic mutations, epigenetic modifications, and gene expression patterns, offering a comprehensive understanding of tumor evolution and metastasis. Furthermore, computational tools and algorithms have been developed to enhance the clustering accuracy and interpret the high-dimensional data generated from single-cell analyses. These advancements underscore the potential of single-cell sequencing to inform personalized treatment strategies and improve clinical outcomes for colon cancer patients. Keywords Intratumoral heterogeneity; Single-cell RNA sequencing; Colorectal cancer; Cancer stem cells; Tumor microenvironment 1 Introduction Colorectal cancer (CRC) is one of the most common malignancies worldwide. It arises from the epithelial cells lining the colon or rectum and is characterized by a series of genetic and epigenetic alterations that drive the transformation of normal colonic epithelium into adenocarcinoma. The progression of CRC typically follows a well-defined sequence from benign adenomatous polyps to invasive cancer, often influenced by both hereditary and environmental factors (Punt et al., 2017; Bian et al., 2018). Advances in molecular biology have significantly enhanced our understanding of CRC, leading to the identification of key genetic mutations and pathways involved in its pathogenesis, such as the Wnt/β-catenin, TGF-β, and p53 signaling pathways (Chen et al., 2016; Punt et al., 2017). Cellular heterogeneity within tumors is a critical factor influencing cancer progression and prognosis. This heterogeneity arises from genetic, epigenetic, and phenotypic variations among cancer cells, leading to diverse subpopulations within a single tumor. Understanding this complexity is essential for developing effective therapeutic strategies. Single-cell sequencing technologies have revolutionized our ability to dissect this heterogeneity at an unprecedented resolution, providing insights into the distinct cellular populations and their roles in tumor biology. Recent advancements in single-cell sequencing have enabled the simultaneous analysis of multiple omics layers, such as the genome, transcriptome, and epigenome, within individual cancer cells. For instance, Bian et al. (2018) utilized single-cell triple omics sequencing (scTrio-seq) to examine mutations, transcriptomes, and methylomes in colorectal cancer, revealing consistent DNA methylation patterns within genetic sublineages and substantial differences among clones. Similarly, single-cell RNA sequencing (scRNA-seq) has been employed to uncover transcriptional heterogeneity in various cancers, including glioblastoma and ovarian cancer, highlighting the presence of diverse cellular subpopulations with distinct gene expression profiles (Patel et al., 2014; Winterhoff et al., 2020).
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