Performing Data Mining And Integrative Analysis Of Biomarker in Breast Cancer Using Multiple Publicly Accessible Databases

Summary

Here, we present a protocol to explore the biomarker and survival predictor of breast cancer based on the comprehensive analysis of pooled clinical datasets derived from a variety of publicly accessible databases, using the strategy of expression, correlation and survival analysis step by step.

Abstract

In recent years, emerging databases were designed to lower the barriers for approaching the intricate cancer genomic datasets, thereby, facilitating investigators to analyze and interpret genes, samples and clinical data across different types of cancer. Herein, we describe a practical operation procedure, taking ID1 (Inhibitor of DNA binding proteins 1) as an example, to characterize the expression patterns of biomarker and survival predictors of breast cancer based on pooled clinical datasets derived from online accessible databases, including ONCOMINE, bcGenExMiner v4.0 (Breast cancer gene-expression miner v4.0), GOBO (Gene expression-based Outcome for Breast cancer Online), HPA (The human protein atlas), and Kaplan-Meier plotter. The analysis began with querying the expression pattern of the gene of interest (e.g., ID1) in cancerous samples vs. normal samples. Then, the correlation analysis between ID1 and clinicopathological characteristics in breast cancer was performed. Next, the expression profiles of ID1 was stratified according to different subgroups. Finally, the association between ID1 expression and survival outcome was analyzed. The operation procedure simplifies the concept to integrate multidimensional data types at the gene level from different databases and test hypotheses regarding recurrence and genomic context of gene alteration events in breast cancer. This method can improve the credibility and representativeness of the conclusions, thereby, present informative perspective on a gene of interest.

Introduction

Breast cancer is a heterogeneous disease with diverse prognosis and treatment strategies in different molecular subtypes, in which the pathogenesis and development are probably associated with disparate molecular mechanisms^1,2,3. However, identifying a therapeutic target usually takes years, or even decades, from initial discovery in basic research to clinical use⁴. Genome wide application of high-throughput sequencing technology for cancer genome has greatly advanced the process of searching for valuable biomarkers or therapeutic targets

Protocol

1. Expression Pattern Analysis

1. Go to the ONCOMINE web interface²⁶.
2. Obtain the relative expression levels of gene ID1 in various types of malignancies by typing ID1 to the Search Box.
3. Select Analysis Type from the Primary Filters menu. Then, select Cancer vs. Normal Analysis, Breast Cancer vs. Normal Analysis.
4. Select Gene Summary View from the OTHER VIEWS menu. Set the threshold of P-value at 0.01. Download the figures.
   NOTE: The threshold of fol....

Results

A representative result of data mining and integrative analysis of breast cancer biomarker was performed using ID1, one of the inhibitors of DNA-binding family members, which have been reported in the previous study ²⁵.

As demonstrated in Figure 2, the differences of ID1 mRNA expression between tumor and normal tissues in multiple types of cancer were analyzed using the ONCOM.......

Discussion

Comprehensive analysis of public databases may indicate the underlying function of the gene of interest and reveal the potential link between this gene and clinicopathological parameters in specific cancer^27,31. The exploration and analysis based on one single database might provide limited or isolated perspectives due to the potential selection bias, or in a certain extent, possibly due to the variety of data quality, including data collection and the analytical.......

Materials

List of materials used in this article

Name	Company	Catalog Number	Comments
A personal computer or computing device with an Internet browser with Javascript enabled	Microsoft	051690762553	We support and test the following browsers: Google Chrome, Firefox 3.0 and above, Safari, and Internet Explorer 9.0 and above
Adobe Flash player	Adobe Systems Inc.	It can be freely downloaded from http://get.adobe.com/flashplayer/.	This browser plug-in is required for visualizing networks on the network analysis tab.
Chrome Broswer	Google Inc.	It can be freely downloaded from https://www.google.cn/chrome/	This is necessary for viewing PDF files including the Pathology Reports and many of the downloadable files.
Java Runtime Environment	Oracle Corporation	It can be downloaded from http://www.java.com/getjava/.
Office 365 ProPlus for Faculty	Microsoft	2003BFFD8117EA68	This is necessary for viewing the Pathology Reports and for viewing many of the downloadable files.
Vectr Online	Vectr Labs Inc.	It can be freely used from https://vectr.com/new	This is necessary for visualizing and editing many of the downloadable files and pictures.