Single-cell transcriptomic analysis reveals cellular heterogeneity and prognostic subtypes in colorectal cancer
Huizhen Han1, Yuan Gao1, Yuxing Zhao1
1Anorectal Center, Inner Mongolia Autonomous Region Hospital of Traditional Chinese Medicine, No. 11 Jiankang Street, Xincheng District, Hohhot, 010020, Inner Mongolia, China.
Background:
Colorectal cancer (CRC) exhibits substantial heterogeneity within the tumor microenvironment (TME), which complicates both diagnosis and treatment.
Objective:
This study aimed to explore the cellular composition of CRC through single-cell RNA sequencing (scRNA-seq) and integrate this data with bulk RNA-seq to identify prognostic markers and characterize tumor heterogeneity.
Methods:
scRNA-seq data from 17 CRC samples were analyzed to identify distinct cell clusters and infer cellular trajectories using computational approaches. Bulk RNA-seq data from 566 CRC samples were subsequently employed to genotype patients based on marker genes identified from the single-cell analysis. Survival and clinical correlation analyses were conducted to assess the prognostic relevance of the identified molecular subtypes.
Results:
Single-cell analysis identified 14 distinct cell clusters, including epithelial, immune, and stromal cells, highlighting the TME's complexity. Trajectory inference revealed three major cellular states, with epithelial cells predominantly representing an early-stage phenotype. Genotyping of patients using bulk RNA-seq data delineated three prognostic clusters, with cluster 2 showing significantly poorer survival and an association with advanced tumor stages.
Conclusion:
This study offers a detailed characterization of CRC heterogeneity, identifying key cellular subpopulations and prognostic molecular subtypes. The integration of single-cell and bulk transcriptomic data provides valuable insights into CRC biology and potential prognostic markers. Further functional validation is required to fully understand the clinical implications of these findings.
