Prognostic significance of interferon regulating factor 4 in esophageal squamous cell carcinoma

Comparison of single and module-based methods for modeling gene regulatory networks

MOTIVATION

Gene regulatory networks describe the regulatory relationships among genes, and developing methods for reverse engineering these networks is an ongoing challenge in computational biology. The majority of the initially proposed methods for gene regulatory network discovery create a network of genes and then mine it in order to uncover previously unknown regulatory processes. More recent approaches have focused on inferring modules of co-regulated genes, linking these modules with regulatory genes and then mining them to discover new molecular biology.

RESULTS

In this work we analyze module-based network approaches to build gene regulatory networks, and compare their performance to single gene network approaches. In the process, we propose a novel approach to estimate gene regulatory networks drawing from the module-based methods. We show that generating modules of co-expressed genes which are predicted by a sparse set of regulators using a variational Bayes method, and then building a bipartite graph on the generated modules using sparse regression, yields more informative networks than previous single and module-based network approaches as measured by: (i) the rate of enriched gene sets, (ii) a network topology assessment, (iii) ChIP-Seq evidence and (iv) the KnowEnG Knowledge Network collection of previously characterized gene-gene interactions.

AVAILABILITY AND IMPLEMENTATION

The code is written in R and can be downloaded from https://github.com/mikelhernaez/linker.

SUPPLEMENTARY INFORMATION

Supplementary data are available at Bioinformatics online.

SLC39A4 as a Novel Prognosis Marker Promotes Tumor Progression in Esophageal Squamous Cell Carcinoma

Background

Solute carrier family 39 member 4 (SLC39A4) has been reported to play an oncogenic role in several cancers. However, the role of SLC39A4 in esophageal squamous cell carcinoma (ESCC) remains unclear. In this study, we aimed to explore the clinical significance and function of SLC39A4 in ESCC.

Methods

The Cancer Genome Atlas and Gene Expression Omnibus databases were analyzed to assess the level of SLC39A4 in ESCC. The expression level of SLC39A4 was measured by RT-qPCR and immunohistochemistry in a cohort of 73 patients aged 45-65 years with ESCC. Kaplan-Meier analysis was used to identify the correlation between SLC39A4 and the prognosis of ESCC patients. In vitro experiments were conducted to explore the biological function of SLC39A4 in ESCC cell line TE-1 and TE-10.

Results

The mRNA level of SLC39A4 was significantly enhanced in ESCC specimens, which was in line with the outcome of online databases analysis. Moreover, the aberrant expression of SLC39A4 was positively correlated with clinical stage, T categories and lymph node metastasis. Kaplan-Meier analysis indicated that elevated SLC39A4 expression predicted poor prognosis of patients with ESCC. Furthermore, the in vitro experiments showed that SLC39A4 knockdown not only impaired the proliferation and motility capacities of ESCC cells but also enhanced the sensitivity to cisplatin treatment.

Conclusion

Our findings suggest that SLC39A4 could serve as a novel prognosis biomarker to promote ESCC progression; however, the mechanism of SLC39A4 in ESCC remains to be further explored.