Mevalonate diphosphate decarboxylase MVD/Erg19 is required for ergosterol biosynthesis, growth, sporulation, and stress tolerance in Aspergillus oryzae. In this study, RNA-seq was used to analyze the gene transcription profile in AoErg19 overexpression (OE) and RNAi strains. There were 256 and 74 differentially expressed genes (DEGs) in AoErg19 OE and RNAi strains, respectively, compared with the control strain (CK). The most common DEGs were transport- and metabolism-related genes. Only 22 DEGs were obtained that were regulated in both OE and RNAi strains. The transcriptomic comparison between CK and AoErg19 overexpression strain (CK vs. OE), and between CK and AoErg19 RNAi strain (CK vs. RNAi) revealed that the greatest difference existed in the number of genes belonging to the cytochrome P450 family; 12 were found in CK vs. OE, whereas 1 was found in CK vs. RNAi. The expression patterns of lipid biosynthesis and metabolism related genes were altered in OE and RNAi strains, either by gene induction or suppression. Moreover, the total fatty acid content in the RNAi strain was 12.1% greater than the control strain, but no difference in total acid content was found between the overexpression strain and the control strain. Therefore, this study highlights the gene expression regulation within mevalonate (MVA), ergosterol biosynthesis, and fatty acid biosynthesis pathways.
Adrenocortical carcinoma is an invasive malignancy with poor prognosis, high recurrence rate and limited therapeutic options. Therefore, it is necessary to establish an effective method to diagnose and evaluate the prognosis of patients, so as to realize individualized treatment and improve their survival rate.This study investigated metabolic genes that may be potential therapeutic targets for Adrenocortical carcinoma (ACC). Level 3 gene expression data from the ACC cohort and the relevant clinical information were obtained from The Cancer Genome Atlas (TCGA) database. To verify, other ACC datasets (GSE76021, GSE19750) were downloaded from the Gene Expression Omnibus (GEO) database. The ACC datasets from TCGA and GEO were used to screen metabolic genes through the Molecular Signatures Database using gene set enrichment analysis. Then, the overlapping metabolic genes of the 2 datasets were identified.A signature of five metabolic genes (CYP11B1, GSTM2, IRF9, RPL31, and UBE2C) was identified in patients with ACC. The signature could be used to divide the patients with ACC into high-and low-risk groups based on their median risk score. Multivariate Cox regression analysis was performed to determine the independent prognostic factors of ACC. Time-dependent receiver operating characteristic (ROC) curve analysis was conducted to assess the prediction accuracy of the prognostic signature. Last, a nomogram was established to assess the individualized prognosis prediction model.The results indicated that the signature of 5 metabolic genes had excellent predictive value for ACC. These findings might help improve personalized treatment and medical decisions.Abbreviations: ACC = adrenocortical carcinoma, GO = gene oncology, HR = hazard ratio, KEGG = Kyoto Encyclopedia of Genes and Genomes, OS = overall survival, ROC = receiver operating characteristic, TCGA = the cancer genome atlas.
Background Wolfram syndrome (WFS) is a rare autosomal recessive genetic disease whose main cause is mutations in the WFS1 and CISD2 genes. Its characteristic clinical manifestations are diabetes insipidus, diabetes mellitus, optic atrophy and deafness. Methods In this study, two patients from this particular family underwent complete routine biochemical and ophthalmic tests. Blood, urine, routine stool test, visual acuity (VA) examination, visual field assessment, funduscope, optical coherence tomography and periorbital magnetic resonance imaging (MRI) scans were performed for each patient to evaluate whether the nerve fiber layer around the optic nerve head was atrophied and next-generation sequencing of target genes was performed in two patients. Results When the patients were diagnosed with Wolfram syndrome, their genetic analyses suggested unique three-site compound heterozygous mutations (c.2314C > T + c.2194C > T + c.2171C > T) in exon 8 of both patients’ chromosome 4. One mutation (c.2314C > T) was a novel mutation in the known reports of Wolfram syndrome. As a degenerative genetic disease, the types of gene mutations in the Chinese population are generally homozygous mutations at the unit point or compound heterozygous mutations at two nucleotide change sites. However, the two patients reported in this study are the first known cases of compound heterozygous mutations with three mutation sites coexisting on the WFS1 gene in China or even globally. Conclusions This study expands the phenotypic spectrum of Wolfram syndrome and may reveal a novel mutation pattern of pathogenesis of Wolfram syndrome. The implications of this discovery are valuable in the clinical diagnosis, prognosis, and treatment of patients with WFS1.
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