Downregulation of ST6GALNAC1 is associated with esophageal squamous cell carcinoma development

Sialyltransferases and Neuraminidases: Potential Targets for Cancer Treatment

Cancers are the leading cause of death, causing around 10 million deaths annually by 2020. The most common cancers are those affecting the breast, lungs, colon, and rectum. However, it has been noted that cancer metastasis is more lethal than just cancer incidence and accounts for more than 90% of cancer deaths. Thus, early detection and prevention of cancer metastasis have the capability to save millions of lives. Finding novel biomarkers and targets for screening, determination of prognosis, targeted therapies, etc., are ways of doing so. In this review, we propose various sialyltransferases and neuraminidases as potential therapeutic targets for the treatment of the most common cancers, along with a few rare ones, on the basis of existing experimental and in silico data. This compilation of available cancer studies aiming at sialyltransferases and neuraminidases will serve as a guide for scientists and researchers working on possible targets for various cancers and will also provide data about the existing drugs which inhibit the action of these enzymes.

Bioinformatics Characterization of Candidate Genes Associated with Gene Network and miRNA Regulation in Esophageal Squamous Cell Carcinoma Patients

The present study aimed to identify potential therapeutic targets for esophageal squamous cell carcinoma (ESCC). The gene expression profile GSE161533 contained 84 samples, in that 28 tumor tissues and 28 normal tissues encoded as ESCC patients were retrieved from the Gene Expression Omnibus database. The obtained data were validated and screened for differentially expressed genes (DEGs) between normal and tumor tissues with the GEO2R tool. Next, the protein–protein network (PPI) was constructed using the (STRING 2.0) and reconstructed with Cytoscape 3.8.2, and the top ten hub genes (HGsT10) were predicted using the Maximal Clique Centrality (MCC) algorithm of the CytoHubba plugin. The identified hub genes were mapped in GSE161533, and their expression was determined and compared with The Cancer Genome Atlas (TCGA.) ESCC patient’s samples. The overall survival rate for HGsT10 wild and mutated types was analyzed with the Gene Expression Profiling Interactive Analysis2 (GEPIA2) server and UCSC Xena database. The functional and pathway enrichment analysis was performed using the WebGestalt database with the reference gene from lumina human ref 8.v3.0 version. The promoter methylation for the HGsT10 was identified using the UALCAN server. Additionally, the miRNA-HGsT10 regulatory network was constructed to identify the top ten hub miRNAs (miRT10). Finally, we identified the top ten novel driving genes from the DEGs of GSE161533 ESCC patient’s sample using a multi-omics approach. It may provide new insights into the diagnosis and treatment for the ESCC affected patients early in the future.

The Distinct Roles of Sialyltransferases in Cancer Biology and Onco-Immunology

Aberrant glycosylation is a key feature of malignant transformation. Hypersialylation, the enhanced expression of sialic acid-terminated glycoconjugates on the cell surface, has been linked to immune evasion and metastatic spread, eventually by interaction with sialoglycan-binding lectins, including Siglecs and selectins. The biosynthesis of tumor-associated sialoglycans involves sialyltransferases, which are differentially expressed in cancer cells. In this review article, we provide an overview of the twenty human sialyltransferases and their roles in cancer biology and immunity. A better understanding of the individual contribution of select sialyltransferases to the tumor sialome may lead to more personalized strategies for the treatment of cancer.

Aberrant Whole Blood Gene Expression in the Lumen of Human Intracranial Aneurysms

The rupture of an intracranial aneurysm (IA) causes devastating hemorrhagic strokes. Yet, most IAs remain asymptomatic and undetected until they rupture. In the search for circulating biomarkers of unruptured IAs, we previously performed transcriptome profiling on whole blood and identified an IA-associated panel of 18 genes. In this study, we seek to determine if these genes are also differentially expressed within the IA lumen, which could provide a mechanistic link between the disease and the observed circulating gene expression patterns. To this end, we collected blood from the lumen of 37 IAs and their proximal parent vessels in 31 patients. The expression levels of 18 genes in the lumen and proximal vessel were then measured by quantitative polymerase chain reaction. This analysis revealed that the expression of 6/18 genes (CBWD6, MT2A, MZT2B, PIM3, SLC37A3, and TNFRSF4) was significantly higher in intraluminal blood, while the expression of 3/18 genes (ST6GALNAC1, TCN2, and UFSP1) was significantly lower. There was a significant, positive correlation between intraluminal and proximal expression of CXCL10, MT2A, and MZT2B, suggesting local increases of these genes is reflected in the periphery. Expression of ST6GALNAC1 and TIFAB was significantly positively correlated with IA size, while expression of CCDC85B was significantly positively correlated with IA enhancement on post-contrast MRI, a metric of IA instability and risk. In conclusion, intraluminal expression differences in half of the IA-associated genes observed in this study provide evidence for IA tissue-mediated transcriptional changes in whole blood. Additionally, some genes may be informative in assessing IA risk, as their intraluminal expression was correlated to IA size and aneurysmal wall enhancement.

Autoencoded DNA methylation data to predict breast cancer recurrence: Machine learning models and gene-weight significance

Breast cancer is the most frequent cancer in women and the second most frequent overall after lung cancer. Although the 5-year survival rate of breast cancer is relatively high, recurrence is also common which often involves metastasis with its consequent threat for patients. DNA methylation-derived databases have become an interesting primary source for supervised knowledge extraction regarding breast cancer. Unfortunately, the study of DNA methylation involves the processing of hundreds of thousands of features for every patient. DNA methylation is featured by High Dimension Low Sample Size which has shown well-known issues regarding feature selection and generation. Autoencoders (AEs) appear as a specific technique for conducting nonlinear feature fusion. Our main objective in this work is to design a procedure to summarize DNA methylation by taking advantage of AEs. Our proposal is able to generate new features from the values of CpG sites of patients with and without recurrence. Then, a limited set of relevant genes to characterize breast cancer recurrence is proposed by the application of survival analysis and a pondered ranking of genes according to the distribution of their CpG sites. To test our proposal we have selected a dataset from The Cancer Genome Atlas data portal and an AE with a single-hidden layer. The literature and enrichment analysis (based on genomic context and functional annotation) conducted regarding the genes obtained with our experiment confirmed that all of these genes were related to breast cancer recurrence.

Stimulative role of ST6GALNAC1 in proliferation, migration and invasion of ovarian cancer stem cells via the Akt signaling pathway

Background

Ovarian cancer is known as one of the most common cancers in the world among women. ST6GALNAC1 is highly expressed in cancer stem cells (CSCs), which correlates to high tumor-initiating, self-renewal and differentiation abilities. This present study aims to investigate how ST6GALNAC1 affects ovarian cancer stem cells (OCSCs).

Methods

In order to identify the differentially expressed genes related to ovarian cancer, microarray-based gene expression profiling of ovarian cancer was used, and ST6GALANC1 was one of the identified targets. After that, levels of ST6GALNAC1 in OCSCs and ovarian cancer cells were examined. Subsequently, an Akt signaling pathway inhibitor LY294002 was introduced into the cluster of differentiation 90⁺ (CD90⁺) stem cells, and cell proliferation, migration and invasion, levels of CXCL16, EGFR, CD44, Nanog and Oct4, as well as tumorigenicity of OCSCs were examined.

Results

By using a comprehensive microarray analysis, it was determined that ST6GALNAC1 was highly expressed in ovarian cancer and it regulated the Akt signaling pathway. High levels of ST6GALNAC1 were observed in OCSCs and ovarian cancer cells. Silencing ST6GALNAC1 was shown to be able to reduce cell proliferation, migration, invasion, self-renewal ability, tumorigenicity of OCSCs. In accordance with these results, the effects of ST6GALNAC1 in OCSCs were dependent on the Akt signaling pathway.

Conclusions

When taken together, our findings defined the potential stimulative roles of ST6GALNAC1 in ovarian cancer and OCSCs, which relied on the Akt signaling pathway.

Epigenetic Bases of Aberrant Glycosylation in Cancer

In this review, the sugar portions of glycoproteins, glycolipids, and glycosaminoglycans constitute the glycome, and the genes involved in their biosynthesis, degradation, transport and recognition are referred to as “glycogenes“. The extreme complexity of the glycome requires the regulatory layer to be provided by the epigenetic mechanisms. Almost all types of cancers present glycosylation aberrations, giving rise to phenotypic changes and to the expression of tumor markers. In this review, we discuss how cancer-associated alterations of promoter methylation, histone methylation/acetylation, and miRNAs determine glycomic changes associated with the malignant phenotype. Usually, increased promoter methylation and miRNA expression induce glycogene silencing. However, treatment with demethylating agents sometimes results in silencing, rather than in a reactivation of glycogenes, suggesting the involvement of distant methylation-dependent regulatory elements. From a therapeutic perspective aimed at the normalization of the malignant glycome, it appears that miRNA targeting of cancer-deranged glycogenes can be a more specific and promising approach than the use of drugs, which broad target methylation/acetylation. A very specific type of glycosylation, the addition of GlcNAc to serine or threonine (O-GlcNAc), is not only regulated by epigenetic mechanisms, but is an epigenetic modifier of histones and transcription factors. Thus, glycosylation is both under the control of epigenetic mechanisms and is an integral part of the epigenetic code.