Abstract

The molecular mechanism of nasopharyngeal carcinoma (NPC) is poorly understood and effective therapeutic approaches are needed. This research aimed to excavate the attractor modules involved in the progression of NPC and provide further understanding of the underlying mechanism of NPC. Based on the gene expression data of NPC, two specific protein-protein interaction networks for NPC and control conditions were re-weighted using Pearson correlation coefficient. Then, a systematic tracking of candidate modules was conducted on the re-weighted networks via cliques algorithm, and a total of 19 and 38 modules were separately identified from NPC and control networks, respectively. Among them, 8 pairs of modules with similar gene composition were selected, and 2 attractor modules were identified via the attract method. Functional analysis indicated that these two attractor modules participate in one common bioprocess of cell division. Based on the strategy of integrating systemic module inference with the attract method, we successfully identified 2 attractor modules. These attractor modules might play important roles in the molecular pathogenesis of NPC via affecting the bioprocess of cell division in a conjunct way. Further research is needed to explore the correlations between cell division and NPC.

Highlights

  • Nasopharyngeal carcinoma (NPC), a malignant tumor of the nasopharynx, has a strong geographical distribution with a high incidence in Southern China [1]

  • protein-protein interaction (PPI) network re-weighting To determine the significant biomarkers for NPC, first the data of gene expression profile of NPC and PPI data were recruited and preprocessed

  • To further assess the reliability of protein interactions, the PPI network re-weighting was conducted on the original network, and the absolute Pearson correlation coefficient (PCC) values for each interaction was used as the re-weighted PPI network value

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Summary

Introduction

Nasopharyngeal carcinoma (NPC), a malignant tumor of the nasopharynx, has a strong geographical distribution with a high incidence in Southern China [1]. The understanding of NPC at the genetic level is poor and effective therapeutic approaches are needed. Complex human diseases, such as cancers, are caused by dysregulations of biological networks [4]. The established methods begin with identifying differentially expressed genes (DEGs) between two conditions, and performing a functional analysis to identify the disease-related genes [8]. This often restricts the analyses to well-annotated biological processes

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