Therapeutic potential of Xihuang Pill in colorectal cancer: Metabolomic and microbiome-driven approaches

Abstract

Introduction: The Xihuang Pill (XHP), a venerated traditional Chinese medicine, has demonstrated significant anti-cancer capabilities. Despite its proven efficacy, the scarcity of comprehensive pharmacological studies limits the widespread application of XHP. This research endeavor seeks to demystify the therapeutic underpinnings of XHP, particularly in the realm of colorectal cancer (CRC) therapy.

Methods: In this study, mice harboring CT26 tumors were divided into four groups, each administered with either XHP monotherapy, 5-fluorouracil (5-FU), or a combination of both. The tumor growth trajectory was closely monitored to evaluate the effectiveness of these anti-neoplastic interventions. Advanced techniques, including 16S-rDNA gene sequencing and ultra-high performance liquid chromatography-tandem mass spectrometry (UHPLC-MS/MS), were harnessed to scrutinize the gut microbiota and serum metabolite profiles. Immunohistochemical assays were employed to gauge the expression levels of CD4, CD8, and Foxp3, thereby providing insights into the dynamics of tumor-infiltrating lymphocytes within the tumor microenvironment.

Results: Our findings indicate that XHP effectively suppresses the initiation and progression of colorectal tumors. The combinatorial therapy of XHP with 5-FU exhibited an enhanced inhibitory effect on tumor growth. Metabolic profiling revealed that XHP induced notable metabolic shifts, particularly impacting pathways such as steroid hormone synthesis, arachidonic acid metabolism, purine biosynthesis, and renin secretion. Notably, 17α-ethinyl estradiol and α-ergocryptine were identified as serum metabolites with the most substantial increase following XHP administration. Analysis of the gut microbiome suggested that XHP promoted the expansion of specific bacterial taxa, including Lachnospiraceae_NK4A136_group, Clostridiales, Desulfovibrionaceae, and Anaerotignum_sp., while suppressing the proliferation of others such as Ligilactobacilus, Lactobacillus_taiwanensis, and Candidatus_saccharimonas. Immunohistochemical staining indicated an upregulation of CD4 and CD8 post-XHP treatment.

Conclusion: This study delineates a potential mechanism by which XHP inhibits CRC tumorigenesis through modulating the gut microbiota, serum metabolites, and reshaping the tumor immune microenvironment in a murine CRC model. These findings contribute to a more profound understanding and potentially broaden the clinical utility of XHP in oncology.

Keywords: 5-fu (5-fluorouracil); Xihuang Pill; colorectal cacner; gut micobiota; untarget metabolomics.

FIGURE 1

Total Ion Chromatogram (TIC) analysis of Xihuang Pill (XHP). (A) TIC of XHP in positive ion mode, with identified compounds: 1. Betaine, 2. Tetrahydrocortisone, 3. Dehydrotumulosic acid, 4. D-(+)-Camphor, 5. Ursolic acid, 6. Acetyl-11-keto-β-boswellic acid. (B) TIC of XHP in negative ion mode, with identified compounds: 1. Maltotetrose, 2. Azelaic acid, 3. ST 24:1; O4; T, 4. Cholic acid. Abbreviations: XHP, Xihuang Pill; RT, Retention Time..

FIGURE 2

Xihuang Pill (XHP) inhibits colorectal tumorigenesis in the CT26 murine model. (A) Pre-treatment body weight of mice across four groups (n = 8). (B) Initial tumor volume in the four groups (n = 8). (C) Tumor growth trajectories of the four groups (n = 8). (D) Final body weight of mice in the four groups at the experiment endpoint (n = 8). (E) Final tumor weight in the four groups at the experiment endpoint (n = 8). (F) Tumors harvested from the four groups at the experiment endpoint (n = 8). * Represents p < 0.05.

FIGURE 3

Metabolomic profiling of vehicle and Xihuang Pill (XHP) groups via ultra-high performance liquid chromatography-tandem mass spectrometry (UHPLC-MS/MS) positive electrospray ionization (ESI+) Mode. (A) A pie chart depicting the classification of metabolites. (B) Principal Component Analysis (PCA) score plots illustrating the distribution of metabolomic data. (C) Orthogonal Partial Least Squares-Discriminant Analysis (OPLS-DA) score plots showcasing the metabolite discrimination between groups. (D) Volcano plots highlighting the differential metabolites between the vehicle and XHP groups. (E) A heatmap representing the differential metabolites between the vehicle and XHP groups.

FIGURE 4

Metabolomic profiling of vehicle and Xihuang Pill (XHP) groups via ultra-high performance liquid chromatography-tandem mass spectrometry (UHPLC-MS/MS) negative electrospray ionization (ESI-) Mode. (A) A pie chart depicting the classification of metabolites. (B) Principal Component Analysis (PCA) score plots illustrating the distribution of metabolomic data. (C) Orthogonal Partial Least Squares-Discriminant Analysis (OPLS-DA) score plots showcasing the metabolite discrimination between groups. (D) Volcano plots highlighting the differential metabolites between the vehicle and XHP groups. (E) A heatmap representing the differential metabolites between the vehicle and XHP groups.

FIGURE 5

(A) Matchstick plots illustrating the top 20 representative metabolites that exhibit significant changes following XHP treatment. (B) KEGG enrichment analysis of the differential metabolites between the vehicle and XHP groups. (C) Quantitative analysis of the 17alpha-Ethinyl estradiol levels in both the vehicle and XHP groups. (D) Quantitative assessment of α-ergocryptine levels in the vehicle and XHP groups.

FIGURE 6

Matchstick plots illustrating the top 20 representative metabolites that exhibit significant changes following XHP treatment. (B) KEGG enrichment analysis of the differential metabolites between the vehicle and XHP groups. (C) Quantitative analysis of biocytin levels in both the vehicle and XHP groups. (D) Quantitative assessment of biopterin levels in the vehicle and XHP groups.

FIGURE 7

XHP administration remodels microbial dysbiosis. (A) Comparative analysis of observed bacterial species in the vehicle and XHP groups. (B) Evaluation of the Chao1 index for the vehicle and XHP groups. (C) Assessment of the Shannon index for the vehicle and XHP groups. (D) Principal Coordinate Analysis (PCoA) score plots. (E) Nonmetric Multidimensional Scaling (NMDS) score plots. (F) Analysis of bacterial taxa differences at the phylum level between the vehicle and XHP groups. (G, H) Analysis of bacterial taxa differences at the species level between the vehicle and XHP groups. (I) Analysis of bacterial taxa differences between the vehicle and XHP groups using Linear Discriminant Analysis Effect Size (LEfSe).

FIGURE 8

Spearman’s correlation analysis of metabolites and gut bacteria.

FIGURE 9

Representative photographs were obtained using the Caseviewer 2.4 imaging system. Tumor sections from all four groups, immunolabeled for Ki-67, CD8, CD4, and FoxP3, were scanned with the Caseviewer 2.4 imaging system. Semi-quantitative analyses were conducted using Image Pro Plus 6.0.