Integrative topological analysis of mass spectrometry data reveals molecular features with clinical relevance in esophageal squamous cell carcinoma

She Gan Gao, Rui Min Liu, Yun Gang Zhao, Pei Wang, Douglas G. Ward, Guang Chao Wang, Xiang Qian Guo, Juan Gu, Wan Bin Niu, Tian Zhang, Ashley Martin, Zhi Peng Guo, Xiao Shan Feng, Yi Jun Qi, Yuan Fang Ma

Research output: Contribution to journalArticlepeer-review

4 Citations (Scopus)

Abstract

Combining MS-based proteomic data with network and topological features of such network would identify more clinically relevant molecules and meaningfully expand the repertoire of proteins derived from MS analysis. The integrative topological indexes representing 95.96% information of seven individual topological measures of node proteins were calculated within a protein-protein interaction (PPI) network, built using 244 differentially expressed proteins (DEPs) identified by iTRAQ 2D-LC-MS/MS. Compared with DEPs, differentially expressed genes (DEGs) and comprehensive features (CFs), structurally dominant nodes (SDNs) based on integrative topological index distribution produced comparable classification performance in three different clinical settings using five independent gene expression data sets. The signature molecules of SDN-based classifier for distinction of early from late clinical TNM stages were enriched in biological traits of protein synthesis, intracellular localization and ribosome biogenesis, which suggests that ribosome biogenesis represents a promising therapeutic target for treating ESCC. In addition, ITGB1 expression selected exclusively by integrative topological measures correlated with clinical stages and prognosis, which was further validated with two independent cohorts of ESCC samples. Thus the integrative topological analysis of PPI networks proposed in this study provides an alternative approach to identify potential biomarkers and therapeutic targets from MS/MS data with functional insights in ESCC.

Original languageEnglish
Article number21586
JournalScientific Reports
Volume6
DOIs
Publication statusPublished - 22 Feb 2016

Bibliographical note

Funding Information:
This study was supported by National Natural Science Foundation of China (No. 30700366 & 81072039).

ASJC Scopus subject areas

  • General

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