Proteomic Data Analyses Using IPA

Often, it is very challenging to analyze and interpret the large data generated by techniques such as microarray and mass spectrometry. To overcome this issue, there have been few bioinformatics tools such as Ingenuity Pathway Analysis (IPA) developed that use the information already available in the literature to map the set of experimental data to known canonical pathways, networks, disease and drugs.
IPA is a web-based functional analysis tool that is widely used to analyze comprehensive omic data including proteomics, metabolomics and genomics. Through navigating the curated literature database, the IPA system not only identifies the most relevant signaling and metabolic pathways, molecular networks, and biological functions for list of genes and proteins, but it also predicts the upstream regulators as well as predicting the direction of downstream effects on biological and disease processes. In addition, IPA allows comparing and contrasting affected pathways and phenotypes across multiple testing conditions.
We have been recently using IPA system to analyze the proteomics data we have collected from the mass spectrometry analyses of cutaneous squamous cell carcinoma (cSCC). Following the statistical analyses, we have been uploading the list of proteins showing significant difference in their abundance between the tumour and normal tissues onto the IPA for further analyses. IPA will help us understand the significance of these differentially regulated proteins in the context of larger biological or chemical systems which would eventually lead to the identification of potential cSCC biomarkers.
Written by Ali Azimi