A multilevel data integration resource for breast cancer study

Abstract

BackgroundBreast cancer is one of the most common cancer types. Due to the complexity of this disease, it is important to face its study with an integrated and multilevel approach, from genes, transcripts and proteins to molecular networks, cell populations and tissues. According to the systems biology perspective, the biological functions arise from complex networks: in this context, concepts like molecular pathways, protein-protein interactions (PPIs), mathematical models and ontologies play an important role for dissecting such complexity.ResultsIn this work we present the Genes-to-Systems Breast Cancer (G2SBC) Database, a resource which integrates data about genes, transcripts and proteins reported in literature as altered in breast cancer cells. Beside the data integration, we provide an ontology based query system and analysis tools related to intracellular pathways, PPIs, protein structure and systems modelling, in order to facilitate the study of breast cancer using a multilevel perspective. The resource is available at the URL http://www.itb.cnr.it/breastcancer.ConclusionsThe G2SBC Database represents a systems biology oriented data integration approach devoted to breast cancer. By means of the analysis capabilities provided by the web interface, it is possible to overcome the limits of reductionist resources, enabling predictions that can lead to new experiments.

Large Scale Statistical Analysis of GEO Datasets

“…Among the 20 genes found most significantly overexpressed in breast tumors by our test, 11 were inside genesets of C2 relative to breast cancers, and outside all genesets relative to lung tumors: EFHD1, IRX5, MUCL1, PRLR, PTGER3, RGL2, TRIL, TRPS1, VAV3, WWP1, ZG16B. Seven of these genes can be found in the G2SBC database [48] and for 10 out of 11, we have found at least one reference relating it to breast cancer. Conversely, among the most significant genes for lung tumor, the following were found in C2 genesets related to lung and not in those related to breast: ALDH3B1, DARS, PRPSAP2, FAM96B, MBIP, LRRC20.…”

The interplay of HuR and miR-3134 in regulation of AU rich transcriptome

“…Since we used a breast cancer cell line, we compared the list of genes modulated by miR-3134 with those commonly mis-regulated in breast cancer using the G2SBC (The Genes-to-Systems Breast Cancer (G2SBC) Database) database and found that 50 out of 220 genes (22.7%) are shared between the two lists. 19 These observations hint that miR-3134 regulated ARE transcriptome subset and, thus, levels of several cancer related genes may lead to breast cancer development/progression (Fig. 2C).…”

Oral Cancer Biomarkers - as Powerful Diagnostic and Prognostic Tools

“…All of this data regarding the ZNF expression level suggest the importance of ZNF as a biomarker candidate in different tumor types. ZNF 510 has been a well-known biomarker for breast cancer as suggested in a studies conducted in the year 2010 and 2011 [88,89]. A recent study (2011) for the first time reported the role of ZNF 510 as a potential biomarker for OSCC by comparing the salivary proteomic profiles of OSCC patients with the control group.…”