TOX3 Promotes Ovarian Estrogen Synthesis: An RNA-Sequencing and Network Study

Unique features of KGN granulosa-like tumour cells in the regulation of steroidogenic and antioxidant genes

The ovarian KGN granulosa-like tumour cell line is commonly used as a model for human granulosa cells, especially since it produces steroid hormones. To explore this further, we identified genes that were differentially expressed by KGN cells compared to primary human granulosa cells using three public RNA sequence datasets. Of significance, we identified that the expression of the antioxidant gene TXNRD1 (thioredoxin reductase 1) was extremely high in KGN cells. This is ominous since cytochrome P450 enzymes leak electrons and produce reactive oxygen species during the biosynthesis of steroid hormones. Gene Ontology (GO) analysis identified steroid biosynthetic and cholesterol metabolic processes were more active in primary granulosa cells, whilst in KGN cells, DNA processing, chromosome segregation and kinetochore pathways were more prominent. Expression of cytochrome P450 cholesterol side-chain cleavage (CYP11A1) and cytochrome P450 aromatase (CYP19A1), which are important for the biosynthesis of the steroid hormones progesterone and oestrogen, plus their electron transport chain members (FDXR, FDX1, POR) were measured in cultured KGN cells. KGN cells were treated with 1 mM dibutyryl cAMP (dbcAMP) or 10 μM forskolin, with or without siRNA knockdown of TXNRD1. We also examined expression of antioxidant genes, H2O2 production by Amplex Red assay and DNA damage by γH2Ax staining. Significant increases in CYP11A1 and CYP19A1 were observed by either dbcAMP or forskolin treatments. However, no significant changes in H2O2 levels or DNA damage were found. Knockdown of expression of TXNRD1 by siRNA blocked the stimulation of expression of CYP11A1 and CYP19A1 by dbcAMP. Thus, with TXNRD1 playing such a pivotal role in steroidogenesis in the KGN cells and it being so highly overexpressed, we conclude that KGN cells might not be the most appropriate model of primary granulosa cells for studying the interplay between ovarian steroidogenesis, reactive oxygen species and antioxidants.

Genetic Variants of Steroidogenesis and Gonadotropin Pathways and Polycystic Ovary Syndrome Susceptibility: A Systematic Review and Meta-analysis

Genetic variants are predisposing factors to polycystic ovary syndrome (PCOS), a multifactorial condition that often gets triggered due to various environmental factors. The study investigates the association of the variants of genes that are involved in the steroidogenesis pathway or gonadotropin pathway with the risk of PCOS. Appropriate keywords for predetermined genes were used to search in PubMed, Google Scholar, Science Direct, and Central Cochrane Library up to January 11, 2023. PROSPERO (CRD42022275425). Inclusion criteria: (a) case-control study; (b) genotype or allelic data. Exclusion criteria were: (a) duplicate studies; (b) clinical trials, systematic reviews, meta-analysis or conference abstract, case reports; (c) other than the English language; (d) having insufficient data; e) genetic variants for which meta-analysis has been reported recently and does not have a scope of the update. Various genetic models were applied as per data availability. Overall 12 variants of 7 genes were selected for the analysis. Relevant data were extracted from 47 studies which include 10,584 PCOS subjects and 16,150 healthy controls. Meta-analysis indicates a significant association between TOX3 rs4784165 [ORs = 1.08, 95% CI (1.00-1.16)], HMGA2 rs2272046 [ORs = 2.73, 95% CI (1.97-3.78)], YAP1 rs1894116 [OR = 1.22, 95% CI (1.13-1.33)] and increased risk of PCOS. Whereas FSHR rs2268361 [ORs = 0.84, 95% CI (0.78-0.89)] is associated with decreased PCOS risk. When sensitivity analysis was carried out, the association became significant for CYP19 rs700519 and FSHR rs6165 under an additive model. In addition, C9Orf3 rs3802457 became significantly associated with decreased PCOS risk with the removal of one study. Insignificant association was observed for CYP19A (rs2470152), FSHR (rs2349415, rs6166), C9Orf3 (rs4385527), GnRH1 (rs6185) and risk of PCOS. Our findings suggest association of CYP19A (rs700519), TOX3 (rs4784165), HMGA2 (rs2272046), FSHR (rs6165, rs2268361), C9orf3 (rs3802457), and YAP1 (rs1894116) with risk for PCOS.

Genomic Variants and Worldwide Epidemiology of Breast Cancer: A Genome-Wide Association Studies Correlation Analysis

Breast cancer (BCa) is the most common cancer and leading cause of cancer death among women globally. This can be explained by the genetic factor of this disease. This article aims to correlate the epidemiological data, worldwide incidence, and mortality of BCa with the Single-Nucleotide Polymorphisms (SNPs) associated with the susceptibility and severity in different populations. Two hundred and forty genetic variants associated with BCa susceptibility/severity were selected from the literature through Genome-Wide Association Studies (GWAS). The allele frequencies were obtained from the 1000 Genomes Project, and the epidemiological data were obtained from the World Health Organization (WHO). The BCa incidence, mortality rates, and allele frequencies of the variants were evaluated using Pearson's correlation. Our study demonstrated that 11 SNPs (rs3817578, rs4843437, rs3754934, rs61764370, rs780092, rs2290203, rs10411161, rs6001930, rs16886165, rs8051542 and rs4973768) were significantly correlated with the epidemiological data in different ethnic groups. Seven polymorphisms (rs3817578, rs3754934, rs780092, rs2290203, rs10411161, rs6001930 and rs16886165) were inversely correlated with the incidence rate and four polymorphisms (rs4843437, rs61764370, rs8051542 and rs4973768) were directly correlated with the incidence rate. African and South-East Asian populations have a lower risk of developing BCa when evaluated in terms of genetic factors since they possess variants characterized as protective, as their higher incidence is associated with a lower frequency of BCa cases. The genetic variants investigated here are likely to predispose individuals to BCa. The genetic study described here is promising for implementing personalized strategies to screen for breast cancer in diverse populations.

Landscape genomics reveals adaptive divergence of indigenous sheep in different ecological environments of Xinjiang, China

Sheep are important livestock animals that have evolved under various ecological pressures. Xinjiang is a region with diverse and harsh environments that have shaped many local sheep breeds with unique characteristics and environmental adaptability. However, these breeds are losing ecological flexibility due to the promotion of intensive farming practices. Here we sequenced 14 local sheep breeds from Xinjiang and analyzed their genetic structure and gene flow with other sheep breeds from neighboring regions. The Tibetan Plateau was the geographic origin of Xinjiang native sheep evolution. We performed genome-environment association analysis and identified Bio9: Mean Temperature of Driest Quarter and Bio15: Precipitation Seasonality as the key environmental factors affecting Xinjiang local sheep and the key genes involved in their survival and adaptation. We classified Xinjiang native sheep breeds into six groups based on their differential genes by pairwise selective sweep analysis and Community Network Analysis. We analyzed transcriptome expression data of 832 sheep tissues and detected tissue-specific enrichment of six group-specific genes in different biological systems. Our results revealed the genetic basis of year-round estrus, drought tolerance, hypoxia resistance, and cold tolerance traits of Xinjiang sheep breeds. Moreover, we proposed conservation strategies for Xinjiang local sheep breeds and provided theoretical guidance for breeding new sheep breeds under global extreme environments.

Revealing the impact of TOX3 on osteoarthritis: insights from bioinformatics

Osteoarthritis, a prevalent long-term condition of the joints, primarily impacts older individuals, resulting in discomfort, restrictions in mobility, and a decrease in overall well-being. Although Osteoarthritis is widely spread, there is a lack of successful interventions to stop the advancement of the condition. Numerous signaling pathways have been emphasized in recent research on Osteoarthritis, yet the diagnostic significance of numerous genes has not been investigated. To identify genes that were expressed differently in osteoarthritis, we utilized the Gene Expression Omnibus database. To identify marker genes, we built machine learning models including Least Absolute Shrinkage and Selection Operator and Random Forest. We categorized Osteoarthritis samples and performed immune cell infiltration analysis based on the expression patterns of these characteristic genes. Both the Least Absolute Shrinkage and Selection Operator and Random Forest models selected six marker genes (TOX3, ARG1, CST7, RERGL, COL11A1, NCRNA00185) out of a total of 17 differentially expressed genes. The osteoarthritis samples were categorized into two groups, namely a high expression group and a low expression group, based on the median levels of TOX3 expression. Comparative analysis of these groups identified 85 differentially expressed genes, showing notable enrichment in pathways related to lipid metabolism in the group with high expression. Analysis of immune cell infiltration revealed noticeable differences in immune profiles among the two groups. The group with high expression of TOX3 showed a notable increase in Mast cells and Type II IFN Response, whereas B cells, Cytolytic activity, Inflammation-promoting cells, NK cells, pDCs, T cell co-inhibition, Th1 cells, and Th2 cells were significantly decreased. We constructed a ceRNA network for TOX3, revealing 57 lncRNAs and 18 miRNAs involved in 57 lncRNA-miRNA interactions, and 18 miRNA-mRNA interactions with TOX3. Validation of TOX3 expression was confirmed using an external dataset (GSE29746), revealing a notable increase in Osteoarthritis samples. In conclusion, our study presents a comprehensive analysis identifying TOX3 as a potential feature gene in Osteoarthritis. The distinct immune profiles and involvement in fat metabolism pathways associated with TOX3 expression suggest its significance in Osteoarthritis pathogenesis. The study establishes a basis for comprehending the intricate correlation between characteristic genes and Osteoarthritis, as well as for the formulation of individualized therapeutic approaches.

Synthesis, Regulatory Factors, and Signaling Pathways of Estrogen in the Ovary

New insights have been thrown for understanding the significant role of estrogen on various systems of humans. Increasing evidences have determined the significant roles of estrogen in female reproductive system. So, the normal synthesis and secretion of estrogen play important roles in maintaining the function of tissues and organs. The ovaries are the main synthetic organs of estrogen. In this review, we summarized the current knowledge of the estrogen synthesis in the ovaries. A series of factors and signaling pathways that regulate the synthesis of estrogen are expounded in detail. Understanding the regulating factors and potential mechanism related to estrogen synthesis will be beneficial for understanding estrogen disorder related diseases and may provide novel therapeutic targets.

Identification of potential candidate genes and regulatory pathways related to reproductive capacity in hypothalamus and pituitarium of male ducks (Anas platyrhynchos) by differential transcriptome analysis

The improvement of reproductive capacity of poultry is important for the poultry industry. The existing studies on reproductive capacity mainly focus on the testis tissue, but few reports on regulationary effect of brain neuroendocrime on reproductive capacity have been available. The hypothalamus-pituitarium-gonad (HPG) axis is an important pathway regulating spermatogenesis and sexual behavior. This study analyzed the gene expression in the hypothalamus and pituitary tissues of male ducks in high-semen-quality group (DH), low-semen-quality group (DL), and non-response group (DN) by RNA-sequencing. A total of 1980 differentially expressed genes (DEGs) were identified, and significantly less DEGs were found in pituitary gland than in hypothalamus. Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) analyses showed that these DEGs were mainly enriched in nerve-related and synapse-related biological processes, mitochondrial inner membrane formation pathway, and ribosome structure pathway. Notably, the neuroactive ligand-receptor interaction pathway significantly enriched in all three comparisons (DH vs. DL, DH vs. DN, and DL vs. DN) was related to different reproductive performance such as semen quality and sexual response. Furthermore, six genes, including POMC, CPLX2, HAPLN2, EGR4, TOX3, and MSH4, were identified as candidate genes regulating reproductive capacity. Our findings provide new insights into the regulation mechanisms underlying the reproductive performance of male poultry, and offer a valuable reference for duck breeding programs aimed at promoting reproductive capacity.

A Swedish Genome-Wide Haplotype Association Analysis Identifies a Novel Breast Cancer Susceptibility Locus in 8p21.2 and Characterizes Three Loci on Chromosomes 10, 11 and 16

(1) Background: The heritability of breast cancer is partly explained but much of the genetic contribution remains to be identified. Haplotypes are often used as markers of ethnicity as they are preserved through generations. We have previously demonstrated that haplotype analysis, in addition to standard SNP association studies, could give novel and more detailed information on genetic cancer susceptibility. (2) Methods: In order to examine the association of a SNP or a haplotype to breast cancer risk, we performed a genome wide haplotype association study, using sliding window analysis of window sizes 1−25 and 50 SNPs, in 3200 Swedish breast cancer cases and 5021 controls. (3) Results: We identified a novel breast cancer susceptibility locus in 8p21.1 (OR 2.08; p 3.92 × 10−8), confirmed three known loci in 10q26.13, 11q13.3, 16q12.1-2 and further identified novel subloci within these three loci. Altogether 76 risk SNPs, 3302 risk haplotypes of window size 2−25 and 113 risk haplotypes of window size 50 at p < 5 × 10−8 on chromosomes 8, 10, 11 and 16 were identified. In the known loci haplotype analysis reached an OR of 1.48 in overall breast cancer and in familial cases OR 1.68. (4) Conclusions: Analyzing haplotypes, rather than single variants, could detect novel susceptibility loci even in small study populations but the method requires a fairly homogenous study population.

Identification and Mechanism of the PD-1/PD-L1 Genomic Signature SORL1 as Protective Factor in Bladder Cancer

Background: Immunotherapy has recently shown remarkable efficacy for advanced bladder cancer patients. Accordingly, identifying a biomarker associated with the programmed cell death protein 1 (PD-1)/its ligand (PD-L1) genomic signature to predict patient prognosis is necessary.

Methods: In this study, we used mutation data and RNA-seq data of bladder cancer samples acquired from The Cancer Genome Atlas (TCGA) database to combine PD-1/PD-L1-associated mutational signatures with PD-1/PD-L1-associated differentially expressed genes (DEGs). Then, we performed a Kaplan-Meier analysis on the corresponding clinical data of the TCGA bladder urothelial carcinoma (BLCA) cohort to identify prognostic genes, and the results were validated using the GSE48075 cohort. The online platform UCSC Xena was used to analyze the relationship between the candidate genes and clinical parameters. We utilized the Human Protein Atlas (HPA) database to validate the protein expression levels. Then, correlation analysis, cell-type identification by estimating relative subsets of RNA transcripts (CIBERSORT) analysis, and gene set enrichment analysis (GSEA) were used to clarify the mechanism.

Results: We identified one prognostic gene, sortilin related receptor 1 (SORL1), whose downregulation was associated with a comparatively advanced BLCA stage. While further exploring this finding, we found that SORL1 expression was negatively correlated with PD-1/PD-L1 expression and M2 macrophage levels. Furthermore, we found that the downregulation of SORL1 expression was significantly associated with a higher epithelial-mesenchymal transition (EMT) score.

Conclusion: We described a novel PD-1/PD-L1-associated signature, SORL1, that predicts favorable outcomes in bladder cancer. SORL1 might reduce immune suppression and inhibit the M2 macrophage-induced EMT phenotype of tumor cells.