Initial characterization of human DHRS1 (SDR19C1), a member of the short-chain dehydrogenase/reductase superfamily

Multi-omics and bioinformatics for the investigation of therapeutic mechanism of roucongrong pill against postmenopausal osteoporosis

ETHNOPHARMACOLOGICAL RELEVANCE

The Roucongrong Pill (RCRP), originating from the historical General Medical Collection of Royal Benevolence, is frequently used to treat postmenopausal osteoporosis (PMOP). Despite its prevalent application, the specific anti-osteoporotic mechanisms of RCRP remain to be elucidated.

AIM OF THE STUDY

This study aims to elucidate the therapeutic mechanism of RCRP in the context of ovariectomy (OVX)-induced PMOP in rats. By employing an integrative approach, the research combines medicinal chemistry, gut microbiota (GM) profiling, metabolomics, MetOrigin traceability, network pharmacology, molecular docking, and molecular dynamics simulations to deliver a comprehensive analysis.

MATERIALS AND METHODS

Sprague-Dawley (SD) rats underwent bilateral OVX to establish a PMOP model. The therapeutic efficacy of RCRP was evaluated through bone metrics (BMD, bone strength, BV/TV, Tb.Sp), hematoxylin and eosin (H&E) histological assessment, and bone metabolism markers (OPG, BALP, TRACP-5b, β-CTX, RANKL). Fecal metabolomics and 16S rDNA sequencing were employed to assess the influence of RCRP on GM and metabolite profiles. Furthermore, MetOrigin facilitated the traceability analysis of relevant metabolites. Molecular docking identified potential RCRP compounds with anti-PMOP activity, while their stability and protein interactions were assessed through molecular dynamics simulations. Network pharmacology further confirms the targets of action.

RESULTS

RCRP alleviated PMOP in rats, enhancing bone strength, cortical and trabecular BMD, BV/TV, and serum OPG levels, while reducing Tb.Sp, serum BALP, TRACP-5b, β-CTX, and RANKL concentrations. A total of twenty-six distinct metabolites were identified, of which ten-tribufos, sulfoacetic acid, betamethasone dipropionate, 9-oxooctadeca-10,12,15-trienoic acid, menatetrenone, piperlongumine, maltopentaose, enol-phenylpyruvate, catechol, pentaacetate, and (+)-2-methylpropanoic acid-exhibited correlations with six GM species: Turicibacter, Roseburia, Colidextribacter, Helicobacter, Odoribacter, and Lachnoclostridium, as determined by Spearman's correlation analysis. Notably, MetOrigin revealed the microbial metabolism of taurine and hypotaurine, along with host-specific steroid hormone synthesis. Computational docking studies demonstrated robust interactions between five RCRP-derived steroids (hydroxyecdysone, corticosterone, trilostane, 5α-androstan-3,6,17-trione, and cortisol) and key enzymes (estradiol 17α-dehydrogenase and UDP-glucuronosyltransferase), suggesting a potential enhancement of therapeutic efficacy against PMOP. Furthermore, molecular dynamics simulations indicated stable interactions between hydroxyecdysone and two proteins, with binding free energies of -67.427 kJ/mol and -156.948 kJ/mol, respectively. Through network pharmacology and molecular docking approaches, potential targets of these metabolites were identified, including estrogen receptors ESR1 and ESR2, dual specificity phosphatase 6 (DUSP6), sex hormone-binding globulin (SHBG), prostaglandin E receptor 4 (PTGER4), cannabinoid receptor 2 (CNR2), cathepsin K (CTSK), and androgen receptor (AR).

CONCLUSIONS

RCRP effectively mitigates OVX-induced bone loss in PMOP rats by modulating GM and associated metabolites, along with their potential targets and key metabolic pathways, including taurine and hypotaurine metabolism, as well as steroid hormone biosynthesis. These findings offer new insights into the therapeutic mechanisms by which RCRP may alleviate PMOP.

Construction and validation of a immune-related prognostic gene DHRS1 in hepatocellular carcinoma based on bioinformatic analysis

A member of the short-chain dehydrogenase/reductase superfamily (DHRS1, SDR19C1) is a member of the short-chain dehydrogenase/reductase superfamily and a potential predictor of hepatocellular carcinoma (HCC). However, the role of DHRS1 in HCC immunity remains unclear. We systematically analyzed the association between DHRS1 and HCC immunity with transcriptional and clinical data from the Tumor Immune Estimation Resource, an integrated repository portal for tumor immune system interactions, and cBioPortal databases. Six DHRS1-associated immunomodulators strongly correlated with survival and were uncovered by exploiting univariate and multivariate Cox analyses. We created a risk score for each patient by adding the points from each immunomodulator and then classified them into high and low risk categories. Survival analysis were used to compare the overall survival between the 2 groups, and the receiver operating characteristic curve was applied to assess the accuracy of the risk score. Data from our center were adopted as the external validation set, the risk score was calculated using the risk coefficient of the 6 genes in the training cohort, and survival analysis were executed to verify the experimental group results. A nomogram was ultimately constructed with the R package. Our data revealed a correlation between the levels of immune cell infiltration and either the DHRS1 gene copy numbers or mRNA levels in HCC. Second, we generated a signature based on the 6 DHRS1-related immunomodulators (KDR, TNFRSF4, CD276, TNFSF4, SLAMF6, and SIGLEC9). We postulate that the generated risk scores would serve as an independent indicator of HCC prognosis, with an area under the receiver operating characteristic curve for the risk score of 0.743. We further established external validation sets to reconfirm the predictive validity of the risk score. Finally, a prognostic nomogram and calibration curve were created. The DHRS1 gene may exert an impact on HCC immunity. We posit that the nominated immune signature based on DHRS1-associated immunomodulators could constitute a promising prognostic biomarker in HCC.

Development of an Eight-gene Prognostic Model for Overall Survival Prediction in Patients with Hepatocellular Carcinoma

BACKGROUND AND AIMS

The overall survival (OS) of hepatocellular carcinoma (HCC) remains dismal. Bioinformatic analysis of transcriptome data could identify patients with poor OS and may facilitate clinical decision. This study aimed to develop a prognostic gene model for HCC.

METHODS

GSE14520 was retrieved as a training set to identify differential expressed genes (DEGs) between tumor and adjacent liver tissues in HCC patients with different OS. A DEG-based prognostic model was then constructed and the TCGA-LIHC and ICGC-LIRI datasets were used to validate the model. The area under the receiver operating characteristic curve (AUC) and hazard ratio (HR) of the model for OS were calculated. A model-based nomogram was established and verified.

RESULTS

In the training set, differential expression analysis identified 80 genes dysregulated in oxidation-reduction and metabolism regulation. After univariate Cox and LASSO regression, eight genes (LPCAT1, DHRS1, SORBS2, ALDH5A1, SULT1C2, SPP1, HEY1 and GOLM1) were selected to build the prognostic model. The AUC for 1-, 3- and 5-year OS were 0.779, 0.736, 0.754 in training set and 0.693, 0.689, 0.693 in the TCGA-LIHC validation set, respectively. The AUC for 1- and 3-year OS were 0.767 and 0.705 in the ICGC-LIRI validation set. Multivariate analysis confirmed the model was an independent prognostic factor (training set: HR=4.422, p<0.001; TCGA-LIHC validation set: HR=2.561, p<0.001; ICGC-LIRI validation set: HR=3.931, p<0.001). Furthermore, a nomogram combining the model and AJCC stage was established and validated, showing increased OS predictive efficacy compared with the prognostic model (p=0.035) or AJCC stage (p<0.001).

CONCLUSIONS

Our eight-gene prognostic model and the related nomogram represent as reliable prognostic tools for OS prediction in HCC patients.

Oral enzymatic detoxification system: Insights obtained from proteome analysis to understand its potential impact on aroma metabolization

The oral cavity is an entry path into the body, enabling the intake of nutrients but also leading to the ingestion of harmful substances. Thus, saliva and oral tissues contain enzyme systems that enable the early neutralization of xenobiotics as soon as they enter the body. Based on recently published oral proteomic data from several research groups, this review identifies and compiles the primary detoxification enzymes (also known as xenobiotic-metabolizing enzymes) present in saliva and the oral epithelium. The functions and the metabolic activity of these enzymes are presented. Then, the activity of these enzymes in saliva, which is an extracellular fluid, is discussed with regard to the salivary parameters. The next part of the review presents research evidencing oral metabolization of aroma compounds and the putative involved enzymes. The last part discusses the potential role of these enzymatic reactions on the perception of aroma compounds in light of recent pieces of evidence of in vivo oral metabolization of aroma compounds affecting their release in mouth and their perception. Thus, this review highlights different enzymes appearing as relevant to explain aroma metabolism in the oral cavity. It also points out that further works are needed to unravel the effect of the oral enzymatic detoxification system on the perception of food flavor in the context of the consumption of complex food matrices, while considering the impact of food oral processing. Thus, it constitutes a basis to explore these biochemical mechanisms and their impact on flavor perception.

Decreased DHRS1 expression is a novel predictor of poor survival in patients with hepatocellular carcinoma

Aim: To investigate the effect of aberrant expression of DHRS1 on hepatocellular carcinoma (HCC). Materials & methods: Kaplan-Meier and Cox regression analyses were performed to evaluate the correlation between DHRS1 and overall survival. Gene set enrichment analysis was performed to explore the potential function of DHRS1 in HCC. Results: Multiple data analysis revealed that DHRS1 mRNA and protein expression level were remarkably lower in HCC than that in normal tissues. In survival analysis, patients with low DHRS1 expression presented a poorer prognosis, and was an independent risk factor for HCC. Conclusion: Decreased DHRS1 expression may be a potential predictor of poor prognosis in HCC.