Comparative study on the anti-tumor effect of steroids derived from different organisms in H22 tumor-bearing mice and analysis of their mechanisms.

This study aimed to comparatively investigate the anti-tumor mechanisms of steroids including ergosterol, ß-sitosterol, cholesterol, and fucosterol. The model of H22 tumor-bearing mice was constructed based on histopathological data and biochemical parameters, while serums were subjected to metabolomics analysis to study the potential anti-tumor mechanisms. The results indicated that the four steroids exhibited different degrees of anti-tumor effects on H22 mice. The tumor inhibition rates were 63.25% for ergosterol, 56.41% for ß-sitosterol, 61.54% for cholesterol, and 72.65% for fucosterol. Metabolomic analyses revealed that 87, 71, and 129 differential metabolites were identified in ergosterol, cholesterol, and fucosterol treatment groups, respectively. The fucosterol treatment group had the highest number of differential metabolites. At the same time, it mainly inhibited purine and amino acid metabolism to exert anti-tumor effects. Ergosterol enhanced immunity and affected pyruvate metabolism, and cholesterol inhibited purine metabolism. The chemical structure difference among ergosterol, cholesterol, and fucosterol is mainly at the number and position of sterol double bonds and the number and length of side chain carbons. Therefore, there is a structure-activity relationship between the structure of steroid compounds and their efficacy. This study provides a key foundation for the exploitation of the anti-tumor effects of steroids derived from different organisms.

Genetic and molecular dissection of ginseng (Panax ginseng Mey.) germplasm using high-density genic SNP markers, secondary metabolites, and gene expressions.

Genetic and molecular knowledge of a species is crucial to its gene discovery and enhanced breeding. Here, we report the genetic and molecular dissection of ginseng, an important herb for healthy food and medicine. A mini-core collection consisting of 344 cultivars and landraces was developed for ginseng that represents the genetic variation of ginseng existing in its origin and diversity center. We sequenced the transcriptomes of all 344 cultivars and landraces; identified over 1.5 million genic SNPs, thereby revealing the genic diversity of ginseng; and analyzed them with 26,600 high-quality genic SNPs or a selection of them. Ginseng had a wide molecular diversity and was clustered into three subpopulations. Analysis of 16 ginsenosides, the major bioactive components for healthy food and medicine, showed that ginseng had a wide variation in the contents of all 16 ginsenosides and an extensive correlation of their contents, suggesting that they are synthesized through a single or multiple correlated pathways. Furthermore, we pair-wisely examined the relationships between the cultivars and landraces, revealing their relationships in gene expression, gene variation, and ginsenoside biosynthesis. These results provide new knowledge and new genetic and genic resources for advanced research and breeding of ginseng and related species.

Genome-wide characterization, evolutionary analysis, and expression pattern analysis of the trihelix transcription factor family and gene expression analysis under MeJA treatment in Panax ginseng.

Panax ginseng is a well-known medicinal plant with several pharmacological uses in China. The trihelix family transcription factors, also known as GT factors, can be involved in the regulation of growth and developmental processes in plants. There have been no in-depth reports or systematic studies about the trihelix transcription factor in ginseng. In this study, the structure, chromosomal localization, gene duplication, phylogeny, functional differentiation, expression patterns and coexpression interactions of trihelix transcripts were analysed using bioinformatics methods based on the ginseng transcriptome database. Thirty-two trihelix transcription factor genes were identified in ginseng, and these genes were alternatively spliced to obtain 218 transcripts. These transcripts were unevenly distributed on different chromosomes of ginseng, and phylogenetic analysis classified the PgGT transcripts into five subgroups. Gene Ontology (GO) analysis classified PgGT transcripts into eight functional subclasses, indicating that they are functionally diverse. The expression pattern analysis of 218 PgGT transcripts revealed that their expression was tissue-specific and spatiotemporally-specific in 14 different tissues of 4-year-old ginseng, 4 different ages of ginseng roots, and 42 farmers' cultivars of 4-year-old ginseng roots. Despite the differences in the expression patterns of these transcripts, coexpression network analysis revealed that these transcripts could be expressed synergistically in ginseng. In addition, two randomly selected PgGT transcripts in each of the five different subfamilies were subjected to methyl jasmonate treatment at different times, and PgGT was able to respond to the regulation of methy1 jasmonate. These results provide a theoretical basis and gene resources for an in-depth study of the function of trihelix genes in other plants.

Poor prognosis, hypomethylation, and immune infiltrates are associated with downregulation of INMT in head and neck squamous cell carcinoma.

Background: Indiolethylamine-N-methyltransferase (INMT) is a methyltransferase responsible for transferring methyl groups from methyl donor SAM to its substrate. S-adenosyl-l-methionine (SAM), obtained from the methionine cycle, is a naturally occurring sulfonium compound that is vital to cellular metabolism. The expression of INMT is down-regulated in many tumorous tissues, and it may contribute to tumor invasion and metastasis. Nevertheless, the expression of INMT and its relationship to methylation and immune infiltrates in head and neck squamous cell carcinoma (HNSC) remains a mystery. Thus, we evaluated expression, clinicopathological features, prognosis, several critical pathways, DNA methylation, and immune cell infiltration for the first time. Methods: Analysis of the clinicopathological characteristics of INMT expression, several tumor-related bioinformatics databases were utilized. In addition, the role of INMT expression was analyzed for prognosis. Several INMT-related pathways were enriched on the LinkedOmics website. In addition, we have analyzed the methylation of INMT in HNSC in detail by using several methylation databases. Lastly, the relationship between INMT gene expression and immune infiltration was analyzed with ssGSEA, Timer, and TISIDB. Results: In HNSC, mRNA and protein levels were significantly lower than in normal tissues. The low expression of INMT was statistically associated with T stage, histological grade, gender, smoking history, and alcohol consumption. HNSC patients with low INMT expression have a poorer OS (overall survival) compared to those with high levels of expression. In addition, the multivariate analysis revealed INMT expression to be a remarkable independent predictor of prognosis in HNSC patients. An analysis of gene enrichment showed that several pathways were enriched in INMT, including the Ras signaling pathway, the cGMP-PKG signaling pathway, and others. Moreover, methylation patterns of INMT detected in a variety of methylation databases are closely associated with mRNA expression and prognosis. Finally, INMT was significantly correlated with immune infiltration levels. Conclusion: HNSC with low levels of INMT exhibits poor survival, hypomethylation, and immune infiltration. For HNSC, this study presented evidence that INMT is both a biomarker of poor prognosis and a target of immunotherapy.