Network Pharmacology and Transcriptomic Sequencing Analyses Reveal the Molecular Mechanism of Sanguisorba officinalis Against Colorectal Cancer

Chemical component of differences in the endosperm of Gleditsia species seeds revealed based on comparative metabolomics

To investigate the chemical composition and interfunctional differences among the endosperm of Gleditsia species seeds (EGS), this study was conducted to determine the metabolic profiles in three EGSs based on the metabolomics approach of UPLC-ESI-MS/MS. A total of 505 metabolites were identified, of which 156 metabolites of EGS were annotated as pharmaceutical ingredients for six human diseases. A total of 110, 146, and 104 metabolites showed different accumulation patterns in the three control groups, LEGS vs. MEGS, LEGS vs. SEGS, and MEGS vs. SEGS, respectively. The metabolic profiles of EGSs differed significantly, and KEGG annotation and enrichment analyses indicated aminoacyl-tRNA biosynthesis as the key metabolic pathway of EGSs. This study enriches the understanding of the chemical composition of EGSs and provides theoretical support for the development and application of EGSs.

Liquid chromatography-tandem mass spectrometry analysis of a ratio-optimized drug pair of Sophora flavescens Aiton and Coptis chinensis Franch and study on the mechanism of anti-colorectal cancer effect of two alkaloids thereof

The drug pair consisting of Sophora flavescens Aiton (Sophorae flavescentis radix, Kushen) and Coptis chinensis Franch. (Coptidis rhizoma, Huanglian), as described in Prescriptions for Universal Relief (Pujifang), is widely used to treat laxation. Matrine and berberine are the major active components of Kushen and Huanglian, respectively. These agents have shown remarkable anti-cancer and anti-inflammatory effects. A mouse model of colorectal cancer was used to determine the most effective combination of Kushen and Huanglian against anti-colorectal cancer. The results showed that the combination of Kushen and Huanglian at a 1:1 ratio exerted the best anti-colorectal cancer effect versus other ratios. Moreover, the anti-colorectal cancer effect and potential mechanism underlying the effects of matrine and berberine were evaluated by the analysis of combination treatment or monotherapy. In addition, the chemical constituents of Kushen and Huanglian were identified and quantified by liquid chromatography-tandem mass spectrometry (LC-MS/MS). A total of 67 chemical components were identified from the Kushen-Huanglian drug pair (water extraction), and the levels of matrine and berberine were 129 and 232 µg/g, respectively. Matrine and berberine reduced the growth of colorectal cancer and relieved the pathological conditions in mice. In addition, the combination of matrine and berberine displayed better anti-colorectal cancer efficacy than monotherapy. Moreover, matrine and berberine reduced the relative abundance of Bacteroidota and Campilobacterota at phylum level and that of Helicobacter, Lachnospiraceae_NK4A136_group, Candidatus_Arthromitus, norank_f_Lachnospiraceae, Rikenella, Odoribacter, Streptococcus, norank_f_Ruminococcaceae, and Anaerotruncus at the genus level. Western blotting results demonstrated that treatment with matrine and berberine decreased the protein expressions of c-MYC and RAS, whereas it increased that of sirtuin 3 (Sirt3). The findings indicated that the combination of matrine and berberine was more effective in inhibiting colorectal cancer than monotherapy. This beneficial effect might depend on the improvement of intestinal microbiota structure and regulation of the RAS/MEK/ERK-c-MYC-Sirt3 signaling axis.

Prognosis and Novel Drug Targets for Key lncRNAs of Epigenetic Modification in Colorectal Cancer

Background

Colorectal cancer (CRC) has been the 3rd most commonly malignant tumor of the gastrointestinal tract in the world. 5-Methylcytosine (m⁵C) and long noncoding RNAs (lncRNAs) have an essential role in predicting the prognosis and immune response for CRC patients. Therefore, we built a m⁵C-related lncRNA (m⁵CRlncRNA) model to investigate the prognosis and treatment methods for CRC patients.

Methods

Firstly, we secured the transcriptome and clinical data for CRC from The Cancer Genome Atlas (TCGA). Then, m⁵CRlncRNAs were recognized by coexpression analysis. Then, univariate Cox, least absolute shrinkage and selection operator (LASSO), and multivariate Cox regression analyses were utilized to build m⁵C-related prognostic characteristics. Besides, Kaplan-Meier analysis, ROC, PCA, C-index, enrichment analysis, and nomogram were performed to investigate the model. Additionally, immunotherapy responses and antitumor medicines were explored for CRC patients.

Results

A total of 8 m⁵C-related lncRNAs (AC093157.1, LINC00513, AC025171.4, AC090948.2, ZEB1-AS1, AC109449.1, AC009041.3, and LINC02516) were adopted to construct a risk model to investigate survival and prognosis for CRC patients. CRC samples were separated into low- and high-risk groups, with the latter having a worse prognosis. The m⁵C-related lncRNA model helps us to better distinguish immunotherapy responses and IC50 of antitumor medicines in different groups of CRC patients.

Conclusion

The research may give new perspectives on tailored therapy approaches as well as novel theories for forecasting the prognosis of CRC patients.