Ingenuity^{\u00ae<\/sup> Pathway Analysis (IPA\u00ae<\/sup>) is a powerful analysis and interpretation tool for uncovering network interactions and identifying new targets or candidate biomarkers within the context of biological systems. Here, we\u2019ve rounded up a handful of the most interesting recent papers that have cited its use.<\/p>\n}

Site-Specific Gene Expression Profiling as a Novel Strategy for Unravelling Keloid Disease Pathobiology
\nFirst author: N. Jumper<\/h4>\n

A University of Manchester-based research team developed this report<\/a> on better understanding the pathology of keloid disease, an aggressive, locally invasive form of tumor. With the intention to apply a novel, three-method approach to this disease, the team used IPA to enrich the intersecting data. \u201cIPA was chosen as the primary mode of enrichment analysis as all pathways, ontologies and interactions are manually curated and have supporting literature data behind them, thus providing a very robust and standardised platform for interpreting differential gene lists from transcriptomic studies,\u201d the authors wrote. The team concluded that this research will not only provide an investigative starting point for other heterogeneous dermatological conditions, but also that it may have clinical implications for the future management of keloid disease.<\/p>\n

TMPRSS2:ERG\u00a0Gene Fusion Variants Induce TGF-\u03b2 Signaling and Epithelial to Mesenchymal Transition in Human Prostate Cancer Cells
\nFirst author: Leonie Ratz<\/h4>\n

The April issue of Oncotarget included a compelling report<\/a> on advances in prostate cancer research. Prostate cancer is common among men from Western countries and is a major contributor to cancer-related deaths. Compiled by a German team, the report detailed a study of TMPRSS2:ERG\u00a0 (T\/E) gene fusion variants, which are present in 50% of tumors and are the most frequent somatic alteration. They used IPA and the underlying QIAGEN\u00a0Knowledge Base<\/strong> for functional annotation and pathway enrichment of differentially regulated genes, finding important signaling pathways. This research enabled the team to confirm the value of using ALK1-blocking agents to stall progress of certain prostate cancers.<\/p>\n

Nrf2 Regulates Gene-Environment Interactions in an Animal Model of Intrauterine Inflammation: Implications for Preterm Birth and Prematurity
\nFirst author: Thomas E. Sussan<\/h4>\n

Typically caused by intrauterine inflammation, preterm birth is a leading cause of neonatal mortality. Infants who survive have an increased risk for lifelong disabilities. A Baltimore-based team used the established mouse model of intrauterine inflammation-induced preterm birth and deployed IPA to analyze the transcription profiles, which helped identify Nuclear erythroid 2-related factor 2 (Nrf2) as a prominent upstream regulator. The scientists determined that Nrf2 \u2014 a transcription factor that regulates the response to oxidative and inflammatory stress \u2014 was a contributor to susceptibility for not only preterm birth but also a variety of environmental diseases, ranging from cigarette smoke-induced emphysema to allergen-induced asthma and polymicrobial sepsis. Their paper<\/a> ran in Scientific Reports<\/em> and urges future human studies to confirm the theory that pharmacological activation of Nrf2 might reduce inflammation and oxidative stress, the leading indicators of preterm birth.<\/p>\n

Discovery of New Candidate Genes for Rheumatoid Arthritis Through Integration of Genetic Association Data with Expression Pathway Analysis
\nFirst author: Klementy Shchetynsky<\/h4>\n

Arthritis Research and Therapy<\/em> recently ran a study<\/a> focused on candidate genes for rheumatoid arthritis from a group of researchers at the Karolinska Institutet\/University Hospital in Solna, Sweden. The report detailed the team\u2019s process to identify new candidate genes and molecular pathways that are potentially involved in rheumatoid arthritis pathogenesis and which might be tested in the future as drug targets. The scientists used IPA\u2019s experimental evidence database (human, mouse, and rat) for network construction and analysis, finding that out of 377 genes from rheumatoid arthritis-associated loci, 22 were differentially expressed, suggesting that at least three new candidate genes are involved in disease development: ERBB2, TP53<\/em> and HTOP1<\/em>.<\/p>\n

A Transcriptome Multi-tissue Analysis Identifies Biological Pathways and Genes Associated with Variations in Feed Efficiency of Growing Pigs
\nFirst author: Florence Gondret<\/h4>\n

A French team looked at ways in which the meat industry might trim feed costs for pig meat production, aiming to describe shared and specific molecular responses in different tissues of pigs for residual feed intake. They used IPA to visualize plausible regulatory networks that included expression changes and to generate functional hypotheses and identify central molecules in small sub-networks. The team found that non-productive functions in metabolic tissues are likely important processes for feed efficiency \u2014 so dietary compounds with both anti-inflammatory and anti-oxidant activities might improve feed efficiency for pigs. They published their findings<\/a> in BMC Genomics<\/em>.<\/p>\n

If you\u2019re willing to share how you are using QIAGEN Bioinformatics tools in your workflow, we\u2019d love to hear about it! Please contact us here<\/a>; we\u2019d also be happy to arrange a trial<\/a> of Ingenuity Pathway Analysis.<\/p>\n

 <\/p>\n

 <\/p>\n","protected":false},"excerpt":{"rendered":"Ingenuity\u00ae Pathway Analysis (IPA\u00ae) is a powerful analysis and interpretation tool for uncovering network interactions and identifying new targets or candidate biomarkers within the context of biological systems. Here, we\u2019ve […]","protected":false},"author":5,"featured_media":151957,"comment_status":"closed","ping_status":"closed","sticky":false,"template":"","format":"standard","meta":{"_acf_changed":false,"ct_builder_shortcodes":"","ct_template_type":"","ct_parent_template":0,"_EventAllDay":false,"_EventTimezone":"","_EventStartDate":"","_EventEndDate":"","_EventStartDateUTC":"","_EventEndDateUTC":"","_EventShowMap":false,"_EventShowMapLink":false,"_EventURL":"","_EventCost":"","_EventCostDescription":"","_EventCurrencySymbol":"","_EventCurrencyCode":"","_EventCurrencyPosition":"","_EventDateTimeSeparator":"","_EventTimeRangeSeparator":"","_EventOrganizerID":[],"_EventVenueID":[],"_OrganizerEmail":"","_OrganizerPhone":"","_OrganizerWebsite":"","_VenueAddress":"","_VenueCity":"","_VenueCountry":"","_VenueProvince":"","_VenueState":"","_VenueZip":"","_VenuePhone":"","_VenueURL":"","_VenueStateProvince":"","_VenueLat":"","_VenueLng":"","_VenueShowMap":false,"_VenueShowMapLink":false,"_tribe_blocks_recurrence_rules":"","_tribe_blocks_recurrence_description":"","_tribe_blocks_recurrence_exclusions":"","footnotes":""},"categories":[10956],"tags":[11382,11181,11383,10988,11384,24,11385,11386,11387,11111,11388,11224],"class_list":["post-15964","post","type-post","status-publish","format-standard","has-post-thumbnail","hentry","category-discovery","tag-expression-pathway-analysis","tag-gene-expression-profiling","tag-genetic-association-data","tag-ingenuity-pathway-analysis","tag-intrauterine-inflammation","tag-ipa","tag-keloid-disease","tag-pathobiology","tag-pigs","tag-prostate-cancer","tag-rheumatoid-arthritis","tag-transcriptome"],"acf":[],"yoast_head":"\n