MYC and MXI1 protein expression: potential prognostic significance in women with breast cancer in China

Identification of a Novel Glycolysis-Related Gene Signature for Predicting Breast Cancer Survival

To identify a glycolysis-related gene signature for the evaluation of prognosis in patients with breast cancer, we analyzed the data of a training set from TCGA database and four validation cohorts from the GEO and ICGC databases which included 1,632 patients with breast cancer. We conducted GSEA, univariate Cox regression, LASSO, and multiple Cox regression analysis. Finally, an 11-gene signature related to glycolysis for predicting survival in patients with breast cancer was developed. And Kaplan–Meier analysis and ROC analyses suggested that the signature showed a good prognostic ability for BC in the TCGA, ICGC, and GEO datasets. The analyses of univariate Cox regression and multivariate Cox regression revealed that it’s an important prognostic factor independent of multiple clinical features. Moreover, a prognostic nomogram, combining the gene signature and clinical characteristics of patients, was constructed. These findings provide insights into the identification of breast cancer patients with a poor prognosis.

FTO Inhibition Enhances the Antitumor Effect of Temozolomide by Targeting MYC-miR-155/23a Cluster-MXI1 Feedback Circuit in Glioma

Malignant glioma constitutes one of the fatal primary brain tumors in adults. Such poor prognosis calls for a better understanding of cancer-related signaling pathways of this disease. Here we elucidate a MYC-miRNA-MXI1 feedback loop that regulates proliferation and tumorigenesis in glioma. MYC suppressed MXI1 expression via microRNA-155 (miR-155) and the microRNA-23a∼27a∼24-2 cluster (miR-23a cluster), whereas MXI1, in turn, inhibited MYC expression by binding to its promoter. Overexpression of miR-155 and the miR-23a cluster promoted tumorigenesis in U87 glioma cells. Furthermore, fat mass and obesity-associated protein (FTO), an N⁶-methyladenosine (m⁶A) RNA demethylase, regulated the loop by targeting MYC. The ethyl ester form of meclofenamic acid (MA2) inhibited FTO and enhanced the effect of the chemotherapy drug temozolomide on suppressing proliferation of glioma cells and negatively regulated the loop. These data collectively highlight a key regulatory circuit in glioma and provide potential targets for clinical treatment. SIGNIFICANCE: These findings elucidate a novel feedback loop that regulates proliferation in glioma and can be targeted via inhibition of FTO to enhance the efficacy of temozolomide.

REPA: Applying Pathway Analysis to Genome-Wide Transcription Factor Binding Data

Pathway analysis has been extensively applied to aid in the interpretation of the results of genome-wide transcription profiling studies, and has been shown to successfully find associations between the biological phenomena under study and biological pathways. There are two widely used approaches of pathway analysis: over-representation analysis, and gene set analysis. Recently genome-wide transcription factor binding data has become widely available allowing for the application of pathway analysis to this type of data. In this work, we developed regulatory enrichment pathway analysis (REPA) to apply gene set analysis to genome-wide transcription factor binding data to infer associations between transcription factors and biological pathways. We used the transcription factor binding data generated by the ENCODE project, and gene sets from the Molecular Signatures and KEGG databases. Our results showed that 54 percent of the predictions examined have literature support and that REPA's recall is roughly 54 percent. This level of precision is promising as several of REPA's predictions are expected to be novel and can be used to guide new research avenues. In addition, the results of our case studies showed that REPA enhances the interpretation of genome-wide transcription profiling studies by suggesting putative regulators behind the observed transcriptional responses.

Association between the ornithine decarboxylase G316A polymorphism and breast cancer survival

Ornithine decarboxylase (ODC) is a significant rate-limiting enzyme in polyamine synthesis, required for normal cell growth, and is highly expressed in various malignancies, including colorectal and breast cancer. In the present study, the associations between the ODC G316A single nucleotide polymorphism (SNP) and breast cancer-specific survival were investigated. In addition, the functional effects of this SNP were examined in the MCF-7 human breast cancer cell line. The present study recruited 300 stage I-III breast cancer cases, which were diagnosed at the Affiliated Cancer Hospital of Zhengzhou University (Zhengzhou, China) between 2002 and 2003, with follow-up visits conducted until May 2013. ODC G316A was genotyped (ODC GG vs. ODC AG/AA) in the 300 cases and the association of the genotypes with cancer-specific survival was analyzed. In the MCF-7 cell line, the ODC allele-specific binding of E-box transcription factors was determined using western blot and chromatin immunoprecipitation assays. Survival differences were observed between the two genotypes: Compared with the ODC GG genotype, patients with ODC GA/AA exhibited significantly higher survival rates (P<0.05). In cultured cells, the ODC SNP, which is flanked by two E-boxes, appeared to predict ODC promoter activity. Furthermore, the E-box activator c-MYC and repressor MAX interactor 1 were found to preferentially bind to ODC minor A-alleles compared with major G-alleles, in cultured MCF-7 cells. In conclusion, the results of the current study suggest that the regulation of ODC may affect survival in breast cancer patients and indicate a model in which the ODC SNP may be protective for breast adenoma recurrence and detrimental for survival following a diagnosis of breast cancer.