Identification of osalmid metabolic profile and active metabolites with anti-tumor activity in human hepatocellular carcinoma cells

Ribonucleotide reductase M2 (RRM2): Regulation, function and targeting strategy in human cancer

Ribonucleotide reductase M2 (RRM2) is a small subunit in ribonucleotide reductases, which participate in nucleotide metabolism and catalyze the conversion of nucleotides to deoxynucleotides, maintaining the dNTP pools for DNA biosynthesis, repair, and replication. RRM2 performs a critical role in the malignant biological behaviors of cancers. The structure, regulation, and function of RRM2 and its inhibitors were discussed. RRM2 gene can produce two transcripts encoding the same ORF. RRM2 expression is regulated at multiple levels during the processes from transcription to translation. Moreover, this gene is associated with resistance, regulated cell death, and tumor immunity. In order to develop and design inhibitors of RRM2, appropriate strategies can be adopted based on different mechanisms. Thus, a greater appreciation of the characteristics of RRM2 is a benefit for understanding tumorigenesis, resistance in cancer, and tumor microenvironment. Moreover, RRM2-targeted therapy will be more attention in future therapeutic approaches for enhancement of treatment effects and amelioration of the dismal prognosis.

Identification of novel biomarkers of ferroptosis involved in keloid based on bioinformatics analysis

Keloid is a fibroproliferative disease of unknown aetiology, which has a significant impact the quality of life of patients. Ferroptosis plays an important role in the occurrence and development of fibrosis, but there is still a lack of research related to keloids. The objective of this work was to identify the hub genes related to ferroptosis in keloid to better understand the keloid process. The microarray data (GSE7890 GSE145725, and GSE44270) (23 keloid and 22 normal fibroblast) were analysed via the gene expression comprehensive database (GEO). Only GSE7890 met the FerrDB database. Cell cycle and pathway analysis were performed with gene ontology (GO) and the Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway analysis was performed to differentially expressed genes (DEG). The differential genes were confirmed in other GEO datasets (GSE145725 and GSE44270), and multi-fibrosis-gene correlation analysed. To validate these hub genes, quantitative real-time PCR (qRT-PCR) was conducted. A total of 581 DEGs were screened, with 417 genes down-regulated and 164 genes up-regulated, with 11 ferroptosis genes significantly up-regulated in both keloid and normal tissue, and 6 genes are consistent with our findings and are associated with multiple fibrosis genes. The qRT-PCR results and tissues of normal skin and keloid agreed with our predictions. Our findings provide new evidence for the ferroptosis-related molecular pathways and biomarker of keloid.

Association analysis of hepatocellular carcinoma-related hub proteins and hub genes

PURPOSE

Hepatocellular carcinoma (HCC) is one of the most common cancers worldwide. The occurrence and development of HCC are closely related to epigenetic modifications. Epigenetic modifications can regulate gene expression and related functions through DNA methylation. This paper presents an association analysis method of HCC-related hub proteins and hub genes.

EXPERIMENTAL DESIGN

Bioinformatics analysis of HCC-related DNA methylation data is carried out to clarify the molecular mechanism of HCC-related genes and to find hub genes (genes with more connections in the network) by constructing in the gene interaction network. This paper proposes an accurate prediction method of protein-protein interaction (PPI) based on deep learning model DeepSG2PPI. The trained DeepSG2PPI model predicts the interaction relationship between the synthetic proteins regulated by HCC-related genes.

RESULTS

This paper finds that four genes are the intersection of hub genes and hub proteins. The four genes are: FBL, CCNB2, ALDH18A1, and RPLP0. The association of RPLP0 gene with HCC is a new finding of this study. RPLP0 is expected to become a new biomarker for the treatment, diagnosis, and prognosis of HCC. The four proteins corresponding to the four genes are: ENSP00000221801, ENSP00000288207, ENSP00000360268, and ENSP00000449328.

CONCLUSIONS AND CLINICAL RELEVANCE

The association between the hub genes with the hub proteins is analyzed. The mutual verification of the hub genes and the hub proteins can obtain more credible HCC-related genes and proteins, which is helpful for the diagnosis, treatment, and drug development of HCC.

Screening of traditional Chinese medicine monomers as ribonucleotide reductase M2 inhibitors for tumor treatment

BACKGROUND

Ribonucleotide reductase (RR) is a key enzyme in tumor proliferation, especially its subunit-RRM2. Although there are multiple therapeutics for tumors, they all have certain limitations. Given their advantages, traditional Chinese medicine (TCM) monomers have become an important source of anti-tumor drugs. Therefore, screening and analysis of TCM monomers with RRM2 inhibition can provide a reference for further anti-tumor drug development.

AIM

To screen and analyze potential anti-tumor TCM monomers with a good binding capacity to RRM2.

METHODS

The Gene Expression Profiling Interactive Analysis database was used to analyze the level of RRM2 gene expression in normal and tumor tissues as well as RRM2's effect on the overall survival rate of tumor patients. TCM monomers that potentially act on RRM2 were screened via literature mining. Using AutoDock software, the screened monomers were docked with the RRM2 protein.

RESULTS

The expression of RRM2 mRNA in multiple tumor tissues was significantly higher than that in normal tissues, and it was negatively correlated with the overall survival rate of patients with the majority of tumor types. Through literature mining, we discovered that berberine, ursolic acid, gambogic acid, cinobufagin, quercetin, daphnetin, and osalmide have inhibitory effects on RRM2. The results of molecular docking identified that the above TCM monomers have a strong binding capacity with RRM2 protein, which mainly interacted through hydrogen bonds and hydrophobic force. The main binding sites were Arg330, Tyr323, Ser263, and Met350.

CONCLUSION

RRM2 is an important tumor therapeutic target. The TCM monomers screened have a good binding capacity with the RRM2 protein.

Kinetic Characteristics of Curcumin and Germacrone in Rat and Human Liver Microsomes: Involvement of CYP Enzymes

Curcumin and germacrone, natural products present in the Zingiberaceae family of plants, have several biological properties. Among these properties, the anti-NSCLC cancer action is noteworthy. In this paper, kinetics of the two compounds in rat liver microsomes (RLMs), human liver microsomes (HLMs), and cytochrome P450 (CYP) enzymes (CYP3A4, 1A2, 2E1, and 2C19) in an NADPH-generating system in vitro were evaluated by UP-HPLC–MS/MS (ultrahigh-pressure liquid chromatography–tandem mass spectrometry). The contents of four cytochrome P450 (CYP) enzymes, adjusting by the compounds were detected using Western blotting in vitro and in vivo. The t1/2 of curcumin was 22.35 min in RLMs and 173.28 min in HLMs, while 18.02 and 16.37 min were gained for germacrone. The Vmax of curcumin in RLMs was about 4-fold in HLMs, meanwhile, the Vmax of germacrone in RLMs was similar to that of HLMs. The single enzyme t1/2 of curcumin was 38.51 min in CYP3A4, 301.4 min in 1A2, 69.31 min in 2E1, 63.01 min in 2C19; besides, as to the same enzymes, t1/2 of germacrone was 36.48 min, 86.64 min, 69.31 min, and 57.76 min. The dynamic curves were obtained by reasonable experimental design and the metabolism of curcumin and germacrone were selected in RLMs/HLMs. The selectivities in the two liver microsomes differed in degradation performance. These results meant that we should pay more attention to drugs in clinical medication–drug and drug–enzyme interactions.

Preclinical validation and phase I trial of 4-hydroxysalicylanilide, targeting ribonucleotide reductase mediated dNTP synthesis in multiple myeloma

Background

Aberrant DNA repair pathways contribute to malignant transformation or disease progression and the acquisition of drug resistance in multiple myeloma (MM); therefore, these pathways could be therapeutically exploited. Ribonucleotide reductase (RNR) is the rate-limiting enzyme for the biosynthesis of deoxyribonucleotides (dNTPs), which are essential for DNA replication and DNA damage repair. In this study, we explored the efficacy of the novel RNR inhibitor, 4-hydroxysalicylanilide (HDS), in myeloma cells and xenograft model. In addition, we assessed the clinical activity and safety of HDS in patients with MM.

Methods

We applied bioinformatic, genetic, and pharmacological approaches to demonstrate that HDS was an RNR inhibitor that directly bound to RNR subunit M2 (RRM2). The activity of HDS alone or in synergy with standard treatments was evaluated in vitro and in vivo. We also initiated a phase I clinical trial of single-agent HDS in MM patients (ClinicalTrials.gov: NCT03670173) to assess safety and efficacy.

Results

HDS inhibited the activity of RNR by directly targeting RRM2. HDS decreased the RNR-mediated dNTP synthesis and concomitantly inhibited DNA damage repair, resulting in the accumulation of endogenous unrepaired DNA double-strand breaks (DSBs), thus inhibiting MM cell proliferation and inducing apoptosis. Moreover, HDS overcame the protective effects of IL-6, IGF-1 and bone marrow stromal cells (BMSCs) on MM cells. HDS prolonged survival in a MM xenograft model and induced synergistic anti-myeloma activity in combination with melphalan and bortezomib. HDS also showed a favorable safety profile and demonstrated clinical activity against MM.

Conclusions

Our study provides a rationale for the clinical evaluation of HDS as an anti-myeloma agent, either alone or in combination with standard treatments for MM.

Trial registration: ClinicalTrials.gov, NCT03670173, Registered 12 September 2018.

Supplementary information

The online version contains supplementary material available at 10.1186/s12929-022-00813-2.

Brown Adipose Transplantation Improves Polycystic Ovary Syndrome-Involved Metabolome Remodeling

Polycystic ovary syndrome (PCOS) is a complex reproductive, endocrine, and metabolic disorder in reproductive-age women. In order to explore the active metabolites of brown adipose tissue (BAT) transplantation in improving the reproductive and metabolic phenotypes in a PCOS rat model, the metabolites in the recipient's BAT were explored using the liquid chromatography-mass spectrometry technique. In total, 9 upregulated and 13 downregulated metabolites were identified. They were roughly categorized into 12 distinct classes, mainly including glycerophosphoinositols, glycerophosphocholines, and sphingolipids. Ingenuity pathway analysis predicted that these differentially metabolites mainly target the PI3K/AKT, MAPK, and Wnt signaling pathways, which are closely associated with PCOS. Furthermore, one of these differential metabolites, sphingosine belonging to sphingolipids, was randomly selected for further experiments on a human granulosa-like tumor cell line (KGN). It significantly accelerated the apoptosis of KGN cells induced by dihydrotestosterone. Based on these findings, we speculated that metabolome changes are an important process for BAT transplantation in improving PCOS. It might be a novel therapeutic target for PCOS treatment.

A novel four-gene of iron metabolism-related and methylated for prognosis prediction of hepatocellular carcinoma

Hepatocellular carcinoma (HCC) is a liver disease with a complex underlying mechanism, and patients with HCC have low survival rates. Iron metabolism plays a crucial role in the pathogenesis of HCC; however, the prognostic value of iron metabolism-related and methylated genes for HCC needs to be further explored. In the present study, we identified differentially expressed genes (DEGs) that play a role in iron metabolism and DNA methylation in HCC from The Cancer Genome Atlas. Four of these DEGs, whose expression levels are correlated with HCC prognosis, namely, RRM2, FTCD, CYP2C9, and ATP6V1C1, were further used to construct a prognostic model for HCC, wherein the risk score was calculated using the gene expression of the four DEGs. This could be used to predict the overall survival of HCC patients for 1, 3, and 5 years. Results of a multivariate Cox regression analysis further indicated that the risk score was an independent variable correlated with the prognosis of HCC patients. The identified gene signature was further validated using an independent cohort of HCC patients from the International Cancer Genome Consortium. Weighted gene co-expression network analysis and gene set enrichment analysis were performed to identify potential regulatory mechanisms of the gene signature in HCC. Taken together, we identified key prognostic factors of iron metabolism-related and methylated genes for HCC, providing a potential treatment strategy for HCC.