Recent literatures indicate that maternal hormone exposure is a risk factor for autism spectrum disorder (ASD). We hypothesize that prenatal progestin exposure may counteract the neuroprotective effect of estrogen and contribute to ASD development, and we aim to develop a method to ameliorate prenatal progestin exposure-induced autism-like behavior. Experiment 1: Prenatal progestin exposure-induced offspring are treated with resveratrol (RSV) through either prenatal or postnatal exposure and then used for autism-like behavior testing and other biomedical analyses. Experiment 2: Prenatal norethindrone (NET) exposure-induced offspring are treated with ERβ knockdown lentivirus together with RSV for further testing. Experiment 3: Pregnant dams are treated with prenatal NET exposure together with RSV, and the offspring are used for further testing. Eight kinds of clinically relevant progestins were used for prenatal exposure in pregnant dams, and the offspring showed decreased ERβ expression in the amygdala with autism-like behavior. Oral administration of either postnatal or prenatal RSV treatment significantly reversed this effect with ERβ activation and ameliorated autism-like behavior. Further investigation showed that RSV activates ERβ and its target genes by demethylation of DNA and histone on the ERβ promoter, and then minimizes progestin-induced oxidative stress as well as the dysfunction of mitochondria and lipid metabolism in the brain, subsequently ameliorating autism-like behavior. We conclude that resveratrol ameliorates prenatal progestin exposure-induced autism-like behavior through ERβ activation. Our data suggest that prenatal progestin exposure is a strong risk factor for autism-like behavior. Many potential clinical progestin applications, including oral contraceptive pills, preterm birth drugs, and progestin-contaminated drinking water or seafood, may be risk factors for ASD. In addition, RSV may be a good candidate for clinically rescuing or preventing ASD symptoms in humans, while high doses of resveratrol used in the animals may be a potential limitation for human application.

Multiple myeloma (MM) is an incurable hematologic malignancy due to inevitable relapse and chemoresistance development. Our preliminary data show that MM cells express high levels of PGC1β and LDHA. In this study, we investigated the mechanism behind PGC1β‐mediated LDHA expression and its contribution to tumorigenesis, to aid in the development of novel therapeutic approaches for MM. Real‐time PCR and western blotting were first used to evaluate gene expression of PGC1β and LDHA in different MM cells, and then, luciferase reporter assay, chromatin immunoprecipitation, LDHA deletion report vectors, and siRNA techniques were used to investigate the mechanism underlying PGC1β‐induced LDHA expression. Furthermore, knockdown cell lines and lines stably overexpressing PGC1β or LDHA lentivirus were established to evaluate in vitro glycolysis metabolism, mitochondrial function, reactive oxygen species (ROS) formation, and cell proliferation. In addition, in vivo xenograft tumor development studies were performed to investigate the effect of PGC1β or LDHA expression on tumor growth and mouse survival. We found that PGC1β and LDHA are highly expressed in different MM cells and LDHA is upregulated by PGC1β through the PGC1β/RXRβ axis acting on the LDHA promoter. Overexpression of PGC1β or LDHA significantly potentiated glycolysis metabolism with increased cell proliferation and tumor growth. On the other hand, knockdown of PGC1β or LDHA largely suppressed glycolysis metabolism with increased ROS formation and apoptosis rate, in addition to suppressing tumor growth and enhancing mouse survival. This is the first time the mechanism underlying PGC1β‐mediated LDHA expression in multiple myeloma has been identified. We conclude that PGC1β regulates multiple myeloma tumor growth through LDHA‐mediated glycolytic metabolism. Targeting the PGC1β/LDHA pathway may be a novel therapeutic strategy for multiple myeloma treatment.

Combination of betulinic acid and chidamide inhibits acute myeloid leukemia by suppression of the HIF1 pathway and generation of reactive oxygen species Combination of betulinic acid and chidamide inhibits acute myeloid leukemia by suppression of the HIF1α pathway and generation of reactive oxygen species

Background: Central precocious puberty (CPP) is a common disease in prepubertal children and results mainly from disorders in the endocrine system. Emerging evidence has highlighted the involvement of gut microbes in hormone secretion, but their roles and downstream metabolic pathways in CPP remain unknown. Methods: To explore the gut microbes and metabolism alterations in CPP, we performed the 16S rRNA sequencing and untargeted metabolomics profiling for 91 CPP patients and 59 healthy controls. Bioinformatics and statistical analyses, including the comparisons of alpha and beta diversity, abundances of microbes, were undertaken on the 16S rRNA gene sequences and metabolism profiling. Classifiers were constructed based on the microorganisms and metabolites. Functional and pathway enrichment analyses were performed for identification of the altered microorganisms and metabolites in CPP. Results: We integrated a multi-omics approach to investigate the alterations and functional characteristics of gut microbes and metabolites in CPP patients. The fecal microbiome profiles and fecal and blood metabolite profiles for 91 CPP patients and 59 healthy controls were generated and compared. We identified the altered microorganisms and metabolites during the development of CPP and constructed a machine learning-based classifier for distinguishing CPP. The Area Under Curves (AUCs) of the classifies were ranged from 0.832 to 1.00. In addition, functional analysis of the gut microbiota revealed that the nitric oxide synthesis was closely associated with the progression of CPP. Finally, we investigated the metabolic potential of gut microbes and discovered the genus Streptococcus could be a candidate molecular marker for CPP treatment. Conclusions: Overall, we utilized multi-omics data from microorganisms and metabolites to build a classifier for discriminating CPP patients from the common populations and recognized potential therapeutic molecular markers for CPP through comprehensive analyses.

Systematic analysis of cancer gene-expression patterns using high-throughput transcriptional profiling technologies has led to the discovery and publication of hundreds of gene-expression signatures. However, few public signature values have been cross-validated over multiple studies for the prediction of cancer prognosis and chemosensitivity in the neoadjuvant setting. To analyze the prognostic and predictive values of publicly available signatures, we have implemented a systematic method for high-throughput and efficient validation of a large number of datasets and gene-expression signatures. Using this method, we performed a meta-analysis including 351 publicly available signatures, 37,000 random signatures, and 31 breast cancer datasets. Survival analyses and pathologic responses were used to assess prediction of prognosis, chemoresponsiveness, and chemo-drug sensitivity. Among 31 breast cancer datasets and 351 public signatures, we identified 22 validation datasets, two robust prognostic signatures (BRmet50 and PMID18271932Sig33) in breast cancer and one signature (PMID20813035Sig137) specific for prognosis prediction in patients with ER-negative tumors. The 22 validation datasets demonstrated enhanced ability to distinguish cancer gene profiles from random gene profiles. Both prognostic signatures are composed of genes associated with TP53 mutations and were able to stratify the good and poor prognostic groups successfully in 82%and 68% of the 22 validation datasets, respectively. We then assessed the abilities of the two signatures to predict treatment responses of breast cancer patients treated with commonly used chemotherapeutic regimens. Both BRmet50 and PMID18271932Sig33 retrospectively identified those patients with an insensitive response to neoadjuvant chemotherapy (mean positive predictive values 85%-88%). Among those patients predicted to be treatment sensitive, distant relapse-free survival (DRFS) was improved (negative predictive values 87%-88%). BRmet50 was further shown to prospectively predict taxane-anthracycline sensitivity in patients with HER2-negative (HER2-) breast cancer. We have developed and applied a high-throughput screening method for public cancer signature validation. Using this method, we identified appropriate datasets for cross-validation and two robust signatures that differentiate TP53 mutation status and have prognostic and predictive value for breast cancer patients.

Purpose: To investigate the association between DNA methylation and childhood simple obesity. Methods: Genome-wide analysis of DNA methylation was conducted on peripheral blood samples from 41 children with simple obesity and 31 normal controls to identify differentially methylated sites (DMS). Subsequently, gene functional analysis of differentially methylated genes (DMGs) was carried out. After screening the characteristic DMGs based on specific conditions, the methylated levels of these DMS were evaluated and verified by pyrosequencing. Receiver operating characteristic (ROC) curve analysis assessed the predictive efficacy of corresponding DMGs. Finally, Pearson correlation analysis revealed the correlation between specific DMS and clinical data. Results: The overall DNA methylation level in the obesity group was significantly lower than in normal. A total of 241 DMS were identified. Functional pathway analysis revealed that DMGs were primarily involved in lipid metabolism, carbohydrate metabolism, amino acid metabolism, human diseases, among other pathways. The characteristic DMS within the genes Transcription factor A mitochondrial (TFAM) and Piezo type mechanosensitive ion channel component 1(PIEZO1) were recognized as CpG-cg05831083 and CpG-cg14926485, respectively. Furthermore, the methylation level of CpG-cg05831083 significantly correlated with body mass index (BMI) and vitamin D. Conclusions: Abnormal DNA methylation is closely related to childhood simple obesity. The altered methylation of CpG-cg05831083 and CpG-cg14926485 could potentially serve as biomarkers for childhood simple obesity.