Traditional chinese medicine syndromes classification associates with tumor cell and microenvironment heterogeneity in colorectal cancer: a single cell RNA sequencing analysis

Abstract

Background: Colorectal cancer (CRC) is one of the common gastrointestinal malignancies, tumor heterogeneity is the main cause of refractory CRC. Syndrome differentiation is the premise of individualized treatment of traditional Chinese medicine (TCM), but TCM syndrome lacks objective identification in CRC. This study is to investigate the correlation and significance of tumor heterogeneity and TCM syndromes classification in CRC.

Methods: In this study, we using scRNA-seq technology, investigate the significance of tumor heterogeneity in TCM syndromes classification on CRC.

Results: The results showed that 662 cells isolated from 11 primary CRC tumors are divided into 14 different cell clusters, and each cell subtype and its genes have different functions and signal transduction pathways, indicating significant heterogeneity. CRC tumor cell clusters have different proportions in Excess, Deficiency and Deficiency-Excess syndromes, and have their own characteristic genes, gene co-expression networks, gene functional interpretations as well as monocle functional evolution. Moreover, there were significant differences between the high expressions of MUC2, REG4, COL1A2, POSTN, SDPR, GPX1, ELF3, KRT8, KRT18, KRT19, FN1, SERPINE1, TCF4 and ZEB1 genes in Excess and Deficiency syndrome classification in CRC (P < 0.01).

Conclusions: The Excess and Deficiency syndromes classification may be related to tumor heterogeneity and its microenvironment in CRC.

Keywords: Colorectal cancer; Excess and Deficiency syndromes classification; Single cell RNA sequencing; Tumor heterogeneity; Tumor microcirculation.

Fig. 1

TSNE distribution of cell subpopulation and the proportion in CRC with Excess syndrome (ES), Deficiency syndrome (DS) and Excess-Deficiency syndrome (DES). A tSNE distribution of cell subpopulations; B the proportion of the three syndromes; C columnar graphic of cell subpopulations tSNE distribution and the three syndromes proportion

Fig. 2

DEGs and functional annotations of tumor cells in CRC with Excess syndrome (ES), Deficiency syndrome (DS) and Excess-Deficiency syndrome (DES). A Top30 heat map of DEGs, in the expression level, yellower color was higher and redder color was lower; B GO/BP enrichment analysis; C KEGG signal pathway enrichment analysis

Fig. 3

The high-expressed gene co-expression network in CRC with TCM syndromes. A Excess syndrome (ES); B Deficiency syndrome (DS); C Deficiency-Excess syndrome (DES). Pink ovals indicated highly expressed genes, and blue squares indicated TF. The lighter line color indicated lower correlation, and the thicker line indicated smaller p-value

Fig. 4

Correlation of ELF3, KRT8, KRT18, KRT19, FN1, SERPINE1, TCF4 and ZEB1 with Excess syndrome (ES), Deficiency syndrome (DS) and Excess-Deficiency syndrome (DES) in CRC. Analysis of variance, Wilcox test, *P < 0.05; **P < 0.01; ***P < 0.001; NS, no statistical significance

Fig. 5

Monocle pseudotime analysis of tumor cell subpopulation evolution in CRC with TCM syndromes. A The evolutionary trajectory of CEACAM5 + , EPCAM + , KRT18 + and MUC1 + tumor cell subpopulations; B the distribution of Evidence (ES), Deficiency Syndrome (DS), and Deficiency and Excessive Syndrome (DES) on the evolutionary trajectory of tumor cell subpopulations; C the pseudotime trajectory of tumor cell subgroup evolution. The darker color is 'earlier', the pseudotime is 0; the lighter color is the more ‘late’, the pseudotime is greater