Expressional profiling of prostate cancer risk SNPs at 11q13.5 identifiesDGAT2as a new target gene

Comprehensive Genetic Analysis of DGAT2 Mutations and Gene Expression Patterns in Human Cancers

DGAT2 is a transmembrane protein encoded by the DGAT2 gene that functions in lipid metabolism, triacylglycerol synthesis, and lipid droplet regulation. Cancer cells exhibit altered lipid metabolism and mutations in DGAT2 may contribute to this state. Using data from the Catalogue of Somatic Mutations in Cancer (COSMIC), we analyzed all cancer genetic DGAT2 alterations, including mutations, copy number variations and gene expression. We find that several DGAT2 mutations fall within the catalytic site of the enzyme. Using the Variant Effect Scoring Tool (VEST), we identify multiple mutations with a high likelihood of contributing to cellular transformation. We also found that D222V is a mutation hotspot neighboring a previously discovered Y223H mutation that causes Axonal Charcot-Marie-Tooth disease. Remarkably, Y223H has not been detected in cancers, suggesting that it is inhibitory to cancer progression. We also identify several single nucleotide polymorphisms (SNP) with high VEST scores, indicating that certain alleles in human populations have a pathogenic predisposition. Most mutations do not correlate with a change in gene expression, nor is gene expression dependent on high allele copy number. However, we did identify eight alleles with high expression levels, suggesting that at least in certain cases, the excess DGAT2 gene product is not inhibitory to cellular proliferation. This work uncovers unknown functions of DGAT2 in cancers and suggests that its role may be more complex than previously appreciated.

Identification of gene co-expression modules and hub genes associated with the invasiveness of pituitary adenoma

In pituitary adenoma (PA), invasiveness is the main cause of recurrence and poor prognosis. Thus, identifying specific biomarkers for diagnosis and effective treatment of invasive PAs is of great clinical significance. In this study, from the Gene Expression Omnibus database, we obtained and combined several microarrays of PA by the "sva" R package. Weighted gene co-expression network analysis was performed to construct a scale-free topology model and analyze the relationships between the modules and clinical traits. Our analysis results indicated that three key modules (dark turquoise, saddle brown, and steel blue) were associated with the invasiveness of PA. Kyoto Encyclopedia of Genes and Genomes pathway enrichment analysis and Gene Ontology analysis were performed for the functional annotation of the key modules. In addition, the hub genes in the three modules were identified and screened by differential expression analysis between normal samples and PA samples. Three upregulated differentially expressed genes (DGAT2, PIGZ, and DHRS2) were identified. The Fisher's exact test and receiver operating characteristic curve were used to validate the capability of these genes to distinguish invasive traits, and transcription factor interaction networks were used to further explore the underlying mechanisms of the three genes. Moreover, a lower expression level of DGAT2 in invasive PA tissue than in noninvasive PA tissue was validated by quantitative reverse transcription-polymerase chain reaction. In general, this study contributes to potential molecular biomarkers of invasive PAs and provides a broader perspective for diagnosis and new therapeutic targets for the invasive PAs.

DGUOK-AS1 promotes cell proliferation in cervical cancer via acting as a ceRNA of miR-653-5p

Cervical cancer (CC) holds the second highest incidence and is the fourth dominating cause of cancer-induced death in women. It has been widely accepted that long noncoding RNAs (lncRNAs) are implicated in pathological and physiological activities of CC. However, the research of lncRNAs is still in the initial stage. The biological function of lncRNA deoxyguanosine kinase antisense RNA 1 (DGUOK-AS1) in human cancers has not been reported yet. We found that DGUOK-AS1 was aberrantly upregulated in cervical squamous cell carcinoma and endocervical adenocarcinoma (CESC) tissues through TCGA database. Real-time quantitative polymerase chain reaction (RT-qPCR) also verified the high expression of DGUOK-AS1 in CC cell lines. Loss-of-function assays indicated that DGUOK-AS1 silence repressed CC cell growth. In addition, dual-luciferase reporter and RNA immunoprecipitation (RIP) experiments validated the binding relation between miR-653-5p and DGUOK-AS1 or EMSY. Results of the rescue assays elucidated that EMSY overexpression or miR-653-5p downregulation reversed the suppressive function of DGUOK-AS1 knockdown on cell growth and DNA repair in CC. To sum up, this research highlighted that DGUOK-AS1 could promote CC cell proliferation via serving as a ceRNA of miR-653-5p to release EMSY, which might inspire us to discover novel strategies for CC treatment. SIGNIFICANCE OF THE STUDY: DGUOK-AS1 knockdown hinders proliferation of CC cells. DGUOK-AS1 sequesters miR-653-5p to elevate EMSY in CC. EMSY is required for DGUOK-AS1 to induce cell proliferation and repress DNA damage in CC.

Metabolic reprogramming-associated genes predict overall survival for rectal cancer

Metabolic reprogramming has become a hot topic recently in the regulation of tumour biology. Although hundreds of altered metabolic genes have been reported to be associated with tumour development and progression, the important prognostic role of these metabolic genes remains unknown. We downloaded messenger RNA expression profiles and clinicopathological data from The Cancer Genome Atlas and the Gene Expression Omnibus database to uncover the prognostic role of these metabolic genes. Univariate Cox regression analysis and lasso Cox regression model were utilized in this study to screen prognostic associated metabolic genes. Patients with high‐risk demonstrated significantly poorer survival outcomes than patients with low‐risk in the TCGA database. Also, patients with high‐risk still showed significantly poorer survival outcomes than patients with low‐risk in the GEO database. What is more, gene set enrichment analyses were performed in this study to uncover significantly enriched GO terms and pathways in order to help identify potential underlying mechanisms. Our study identified some survival‐related metabolic genes for rectal cancer prognosis prediction. These genes might play essential roles in the regulation of metabolic microenvironment and in providing significant potential biomarkers in metabolic treatment.