Functional metabolome profiling may improve individual outcomes in colorectal cancer management implementing concepts of predictive, preventive, and personalized medical approach

Abstract

Objectives: Colorectal cancer (CRC) is one of the most common solid tumors worldwide, but its diagnosis and treatment are limited. The objectives of our study were to compare the metabolic differences between CRC patients and healthy controls (HC), and to identify potential biomarkers in the serum that can be used for early diagnosis and as effective therapeutic targets. The aim was to provide a new direction for CRC predictive, preventive, and personalized medicine (PPPM).

Methods: In this study, CRC patients (n = 30) and HC (n = 30) were recruited. Serum metabolites were assayed using an ultra-performance liquid chromatography coupled with quadrupole time-of-flight mass spectrometry (UPLC-Q-TOF/MS) technology. Subsequently, CRC cell lines (HCT116 and HCT8) were treated with metabolites to verify their function. Key targets were identified by molecular docking, thermal shift assay, and protein overexpression/inhibition experiments. The inhibitory effect of celastrol on tumor growth was also assessed, which included IC50 analysis, nude mice xenografting, molecular docking, protein overexpression/inhibition experiments, and network pharmacology technology.

Results: In the CRC group, 15 serum metabolites were significantly different in comparison with the HC group. The level of glycodeoxycholic acid (GDCA) was positively correlated with CRC and showed high sensitivity and specificity for the clinical diagnostic reference (AUC = 0.825). In vitro findings showed that GDCA promoted the proliferation and migration of CRC cell lines (HCT116 and HCT8), and Poly(ADP-ribose) polymerase-1 (PARP-1) was identified as one of the key targets of GDCA. The IC50 of celastrol in HCT116 cells was 121.1 nM, and the anticancer effect of celastrol was supported by in vivo experiments. Based on the potential of GDCA in PPPM, PARP-1 was found to be significantly correlated with the anticancer functions of celastrol.

Conclusion: These findings suggest that GDCA is an abnormally produced metabolite of CRC, which may provide an innovative molecular biomarker for the predictive identification and targeted prevention of CRC. In addition, PARP-1 was found to be an important target of GDCA that promotes CRC; therefore, celastrol may be a potential targeted therapy for CRC via its effects on PARP-1. Taken together, the pathophysiology and progress of tumor molecules mediated by changes in metabolite content provide a new perspective for predictive, preventive, and personalized medical of clinical cancer patients based on the target of metabolites in vivo.Clinical trials registration number: ChiCTR2000039410.

Supplementary information: The online version contains supplementary material available at 10.1007/s13167-021-00269-8.

Keywords: Celastrol; Colorectal cancer; Glycodeoxycholic acid; Metabolomics; Poly(ADP-ribose) polymerase-1; Predictive preventive personalized medicine; Serum; Therapeutic targets; UPLC-Q-TOF/MS.

Fig. 1

Non-targeted metabolomics profiling analysis for human serum. A PCA score plot; B OPLS-DA score plot; C permutation test (n = 200) of the OPLS-DA model; D validation plots

Fig. 2

Identification of the differential metabolomics profiles by clustering, correlation and pathways analysis. A Heatmap of differentially expressed metabolites; B correlation analysis of metabolites; C metabolic pathways of 15 different metabolites

Fig. 3

ROC curve of 15 differential metabolites for distinguishing the CRC group from the healthy group

Fig. 4

GDCA can promote the proliferation of CRC cells. A–B GDCA promotes CRC cell lines (HCT116 and HCT8) proliferation; C–D GDCA strongly promotes clonogenicity of HCT116 cells; E GDCA promoted cell migration of HCT116 cell line. Three independent experiments were conducted for each assay (*p < 0.05, **p < 0.01, ***p < 0.001)

Fig. 5

The expression of PARP-1 played a key role in the promotion of CRC cell proliferation by GDCA. A Intersection analysis between GDCA and CRC targets; B molecular docking results of GDCA with PARP-1; C–F thermal shift assay was measured the combination effect of GDCA and PARP-1; G–H sensitivity of PARP-1 overexpression/knockdown cells to GDCA treatment. Three independent experiments were conducted for each assay (*p < 0.05,**p < 0.01, ***p < 0.001)

Fig. 6

Celastrol may become a new therapeutic agent for CRC. A The IC50 of celastrol; B molecular docking results of Celastrol with PARP-1; C–D sensitivity of PARP-1 overexpression/knockdown cells to celastrol treatment; E attenuated tumor growth in celastrol treated mice; F–G the overall size and weight of the tumors in nude mice. Three independent experiments were conducted for each assay (*p < 0.05, **p < 0.01, ***p < 0.001)

Fig. 7

The mechanisms of celastrol therapy for CRC. A The target interaction network for 66 targets; B GO functional enrichment analysis; C KEGG enrichment analysis