As a researcher, it’s an enormous task to acquire knowledge and insight from the sea of biological data and complex interactions involved in a specific research topic. With QIAGEN Bioinformatics’ Ingenuity Pathway Analysis (IPA), we make it easier.
With the comprehensive, manually curated content of the Ingenuity Knowledge Base, combined with powerful algorithms, IPA provides advanced analysis capabilities to help scientists understand the biological context of expression analysis experiments. With IPA, you can identify the most significant pathways, and discover novel regulatory networks and causal relationships associated with your experimental data.
In the past several months there have been over 500 citations for Ingenuity Pathway Analysis, demonstrating how this tool helps put biological data in context to gain insight. Here, we round up just a few of them to offer a sense of the diverse research for which Ingenuity Pathway Analysis makes a difference.
Increasing evidence indicates that miR-301a is a potential oncogenic microRNA and that its genetic ablation reduces Kras-driven lung tumorigenesis in mice. A recent Molecular Cancer paper describes how researchers from China studied the role of miR-301a on host antitumor immunity.
After differentially expressed genes (DEGs) of two mouse models (with or without miR-301a) were identified from RNA-seq data, IPA was used to identify gene networks. The five most highly implicated IPA networks related to cell cycle and immune response were merged, and it was discovered that IFNG (INF-γ) and CTNNB1 (β-catenin) were in the core modules within the entire network. This discovery led to further investigation of these genes, which enabled the researchers to find that miR-301a deficiency recruits immune cells to the tumor microenvironment, resulting in higher IFN-γ expression in early lung tumorigenesis. Additionally, miR-301a directly targets Runx3 mRNA, a negative regulator of the β-catenin pathway. After further experiments, the authors conclude that miR-301a facilitates antitumor immunity in the tumor microenvironment via Runx3 suppression during lung tumorigenesis.
In a Nature Communications paper, scientists from the Broad Institute and the Worchester Polytechnic Institute looked into transcriptional dynamics of macrophages infected with Candida albicans. IPA was used to investigate biological relationships, canonical pathways and upstream regulators of differentially expressed genes in macrophages either exposed to or infected with C. albicans.
Using IPA, the group was able to assess the overlap between significantly DEGs and an extensively curated database of target genes for each of several hundred known regulatory proteins. The researchers found that transcriptomes of infected macrophages and phagocytosed C. albicans displayed tightly coordinated shifts in gene expression, and they established an approach for studying host-pathogen trajectories to resolve heterogeneity in dynamic populations.
A group of collaborating researchers from China recently published their findings on the signaling pathway network profile of human ovarian cancers. They used IPA to mine signaling pathway networks with nearly 1200 differentially expressed mitochondrial proteins, and they compared the pathway and network changes between ovarian cancers and controls. Their results were experimentally validated using qRT-PCR and Western blot. The scientific data generated in this study may lead to the discovery of pathway- and network-based disease and treatment biomarkers for ovarian cancers, and potentially novel molecular mechanisms and therapeutic targets for this disease.
Metal oxide nanoparticles (NPs) are widely used in industry despite little knowledge about the cellular pathways involved in their potential toxicity. Collaborating scientists from France and Ireland published in Cell Biology and Toxicology results of their gene expression study, showing expression changes in rat macrophages upon exposure to metal oxide NPs. IPA was used to identify top canonical pathways influenced by the exposure, notably eIF2 signaling involved in protein homeostasis.