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Role of Histone Methyltransferase in Breast Cancer
Published in Meenu Gupta, Rachna Jain, Arun Solanki, Fadi Al-Turjman, Cancer Prediction for Industrial IoT 4.0: A Machine Learning Perspective, 2021
Surekha Manhas, Zaved Ahmed Khan
However, G9a displays its action as histone protein, such as lysine methyltransferase. Numerous studies have described G9a as also having the potential to methylate various other non-protein targets, which include G9a itself, p53, SIRT1, p21, Reptin, MyoD, WIZ and ACINUS, CDYL1, C/EBPβ, and range of numerous non-histone based targets, such as G9a itself [110], CDYL1, ACINUS, C/EBPβ, WIZ histone deacetylase (HDAC)1, CSB, KLF12, and mAM [118]. Moreover, the precise posttranslational methylation role on the protein’s function remains unclear; non-histone protein methylation might affect protein-based interactions, protein stability, subcellular localization, and subcellular function [119].
Regulation of Human CYP2D6
Published in Shufeng Zhou, Cytochrome P450 2D6, 2018
Jiang et al. (2013) have developed a novel mediation analysis approach to identify new expression quantitative trait loci (eQTLs) driving CYP2D6 activity by combining genotype, gene expression, and enzyme activity data. The authors have found 389,573 and 1,214,416 SNP–transcript–CYP2D6 activity trios that are strongly associated for two different genotype platforms, namely, Affymetrix and Illumina, respectively. In the Affymetrix data set, 295 SNPs correlate with at least 20 genes, which are used to check for overlapping with the results of mediation analysis. A total of 289 eQTL hotspots are found to correlate with 1542 gene expression profiles. The Illumina data set has found that 724 SNPs correlate with at least 20 genes, and 719 of the hotspots are significantly correlated with 2444 genes in mediation analysis. Nine hundred thirty-nine and 1420 genes are successfully mapped in the Ingenuity database for two platforms. The majority of eQTLs are trans-SNPs. Five (CCL16, CCL20, CMTM5, IL-6, and SPP1) and 7 (CCL16, CCL20, CKLF, CKLFSF5, EPO, FAM3C, and SPP1) cytokines, 5 (AR, NR1I2/PXR, NR1I3/CAR, NR2F6, and PPARα) and 7 (AR, ESR1, NR1I2/PXR, NR1I3/CAR, PPARα, RORα/NR1F1, and RORγ) nuclear receptors, and 80 and 113 transcription regulators are found to mediate the relationship between genetic variant and CYP2D6 activity for Affymetrix and Illumina data sets. Overlapped eQTL hotspots with the mediators lead to the identification of 64 transcription factors that can regulate CYP2D6 (Jiang et al. 2013). These transcription factors include AATF, ALYREF, ARHGAP35, ASB8, ATF4, CBX4, CEBPG, CSDA, DDIT3, E2F5, ETV7, FOXN3, FOXN3, FUBP1, GPS2, HDAC10, HMGN1, ID1, INVS, IRF9, KANK1, KAT2B, KHDRBS1, KLF12, MAF, MAML2, MEIS2, MLXIPL, MXD4, MYBBP1A, MYCL1, NCOA7, NCOR1, NFIA, NFKB2, NFYA, NOLC1, NPM1, PEX14, PYCARD, SAP18, SATB1, SIM2, SLC2A4RG, SMARCC1, SNAI3, SNW1, SOX5, TCERG1, TCF7L2, TEAD3, TEAD4, TFDP2, TFEB, TOB1, p53, YWHAB, YY1, ZGPAT, ZHX3, ZKSCAN1, ZNF132, ZNF256, and ZNF263 (Jiang et al. 2013). Among them, YY1 has been reported to putatively bind to human CYP2D6 or rat Cyp2d4 promoter and regulate the expression of CYP2D6 (Gong et al. 2013) and Cyp2d4 (Mizuno et al. 2003). This study has provided new insights into the complex regulatory network for hepatic CYP2D6. Addition of the p53 inhibitor cyclic PFT-α in HepG2 cells dose-dependently enhances CYP2D6 and 3A4 activity, whereas addition of the p53 activator NSC 66811 dose-dependently inhibits CYP2D6 and 3A4 activity (Xiao et al. 2015). Further functional and validation studies are certainly needed to verify the regulation of CYP2D6 by these genes.
Progress of oxidative stress in endometrium decidualization
Published in Journal of Obstetrics and Gynaecology, 2022
Wenxin Gao, Fei Feng, Xiaoling Ma, Rui Zhang, Lifei Li, Feng Yue, Meng Lv, Lin Liu
RIF refers to the failure of embryo implantation in three or more consecutive cycles of in vitro fertilisation and embryo transfer (IVF-ET), and there are one to two high quality embryos in per cycle (Bashiri et al.2018). The occurrence of RIF may be related to many factors, including abnormal anatomical structure of uterus, genetic defects of embryo, disorder of hormone and metabolism, infection, immune factors and so on (Timeva et al.2014). Transcription factor FOXOs family is the key regulator of decidualization (Brosens et al.2009). There was confirmed that the expression of KLF12, a negative regulator of decidualization, increased in the endometrium of patients with RIF, and directly combined with the FOXO1 promoter region and inhibited its expression in ESCs, resulting in decidualization disorder (Zhang et al.2015). This result indicates that there is a certain degree of decidual disorder in patients with RIF. HOXA10 is also an important regulator of decidualization of human endometrium (Taylor et al.1998). It has been shown that HOXA10 can be ubiquitin-modified on lysine 164residues, and the resulting SUMO1-HOXA10 may lead to decidualization defects and then affect embryo implantation. The level of SUMO1-HOXA10 in secretory endometrium of RIF patients was significantly higher than that of normal women of childbearing age (Jiang et al.2017), which further confirmed that decidualization defect could lead to RIF.
Liver transcriptome analysis reveals biological pathways and transcription factors in response to high ammonia exposure
Published in Inhalation Toxicology, 2022
Daojie Li, Shuangzhao Chen, Chun Liu, Baoxing Wei, Xiaoping Li
TFs can regulate the expression levels of target genes by binding to corresponding regulatory elements. Therefore, we further identified TF encoding genes in DEGs. Interestingly, 54 DEGs were identified to be TF coding genes, with 44 up-regulated and 10 down-regulated (Table 2). Top 20 differentially expressed TF coding genes with higher log2(fold change) were highlighted in the volcano plot, including FOS, NR4A2, NR1D2, ATF3, KLF4, PROX1, JUNB, NR4A3, ATOH8, RORA, CSRNP1, NFE2L3, KLF12, REL, SOX5, MESP2, ZBTB10, ONECUT1, ZKSCAN8, and MGA (Figure 2). And among these TF coding genes, only ATOH8 and MESP2 showed decreased expression in the ammonia group.
microRNAs as biomarkers of ovarian cancer
Published in Expert Review of Anticancer Therapy, 2020
miR-141, a member of the miR-200 family, was markedly upregulated in patients at advanced stage and metastatic OC cells. It can promote metastasis and progression of OC in vivo and in vitro by suppressing anoikis via targeting the KLF12/Sp1/survivin axis [93]. miR-134 could activate JNK and ERK signaling by suppressing SDS22. The expression level of miR-134 was found to be positively correlated with metastasis and chemoresistance in OC patients [87]. In combination with chemotherapy, glucocorticoids could inhibit OC metastasis by upregulating miR-708, which had effects on downstream target Rap1B. Moreover, OC patients with high miR-708 expression showed obviously better clinical outcomes [94]. Besides, downregulation of miR-138 was associated with metastasis and short survival time in OC patients. miR-138 suppressed metastasis in xenograft tumors and tail-vein metastasis model in mice by inhibiting Slug and EGFR related pathways via directly binding with SRY-related high mobility group box 4 (SOX4) and hypoxia-inducible factor-1α (HIF-1α) [95]. Similarly, miR-199a overexpression could inhibit cell migration in vitro and impeded peritoneal seeding and growth of tumors in vivo by downregulating HIF-1α and HIF-2α [96]. miR-148a and miR-598 regulated OC metastasis through targeting sphingosine-1-phosphate receptor 1 (S1PR1) and URI, respectively [97,98].