The QIAGEN team is about to get its barbecue on. That’s right, this week we’re heading to San Antonio, Texas, for the 57^th annual meeting of the Society of Toxicology! We’ll also be participating in ToxExpo, the meeting’s exhibit hall. If you’ll be attending, please visit us in booth #1564. We’d love to get a chance to show you how QIAGEN bioinformatics tools are being used in this exciting space.

The SOT meeting attracts more than 6500 attendees from toxicology-related and biomedical organizations. It’s a great gathering of experts who study adverse effects of chemical or biological agents, with discussions around the latest science and regulations along with plenty of continuing education. This year, poster sessions will last all day to give attendees more time to browse the newest innovations and findings.

Here at QIAGEN, our bioinformatics solutions are deployed by many scientists for in-depth toxicology analysis. QIAGEN’s OmicSoft tools are broadly used across pharmaceutical and biotech companies for toxicology research, while our Ingenuity Pathway Analysis tool helps scientists examine and interpret toxicological effects on gene expression, proteomics and metabolomics. We are humbled to see how researchers have adopted these tools for meaningful studies that will ultimately keep our society safer.

We hope to see you in San Antonio!

We’re always on the lookout for new and interesting ways in which researchers are using our solutions. Here is a quick recap of a few recent papers that included gene expression data analysis from our Ingenuity^® Pathway Analysis^™ (IPA) customers.

Network Topology Analysis of Post-Mortem Brain Microarrays Identifies More Alzheimer’s Related Genes and MicroRNAs and Points to Novel Routes for Fighting with the Disease
First author: Sreedevi Chandrasekaran

PLoS One recently published new findings about the battle against Alzheimer’s disease from a research team based at Virginia Commonwealth University. This study is part of a larger effort to understand neurodegenerative disorders, including Parkinson’s and Huntington’s, with the aim of identifying a unified underlying molecular mechanism for all three diseases. Using what may be the first-ever network-based approach to study Alzheimer’s, the team attempted to single out new drug targets by using IPA core analysis in one stage of gene expression to delve into the underlying cellular mechanisms and molecular factors of the disease. They looked at deregulated genes, biological processes, and the interactions between them to decipher the complexity of the condition, enabling them to identify patterns and heterogeneous datasets.

Blood Genome-Wide Transcriptional Profiles of HER2 Negative Breast Cancer Patients
First author: Ovidiu Balacescu

A Romanian research team recently reported using IPA to identify which biological processes and pathways were affected by gene expression changes in triple-negative breast cancer, which is also known as TNBC/ER−PR−HER2−. Triple-negative breast cancer is currently only treated with chemotherapy. Unlike ER+ and HER2+ tumors, it does not have a validated target therapy, which means that it typically has a poor clinical outcome as well as greater risk of recurrence and distant metastasis. The study showed that targeted immunotherapy could feasibly be used in conjunction with chemotherapy to treat triple-negative breast cancer and improve clinical outcomes.

Transcriptome Profiling of Musculus Longissimus Dorsi in Two Cattle Breeds with Different Intramuscular Fat Deposition
First author: Elke Albrecht

Agricultural genomics is a significant topic for today’s science community, and this paper in Genomics Data sheds new light on potential paths to improve meat quality. The authors discuss how gene expression provides details about the different intramuscular fat depositions — also known as marbling, which dictates quality and flavor — in two cattle breeds. The team compared transcriptomes of muscle cells in both breeds, identifying 569 differentially expressed genes in Japanese Black cattle. They then used IPA to locate a gene network that links parameters of cell morphology and maintenance with lipid metabolism.

Transcriptomic Sequencing Reveals a Set of Unique Genes Activated by Butyrate-Induced Histone Modification
First author: Cong-Jun Li

In this paper published by the NIH’s Gene Regulation and Systems Biology journal, a research team studied the role of butyrate, a mammalian nutritional element produced by bacterial fermentation of dietary fibers. Using normal bovine cells, the team used IPA to analyze genetic networks of differentially expressed genes as well as molecular processes and functions, ultimately discovering butyrate-induced differential expression of genes and unique genes, which are related to major cellular functions. This is a step toward understanding epigenomic regulation at the molecular level.

Post-weaning Blood Transcriptomic Differences between Yorkshire Pigs Divergently Selected for Residual Feed Intake
First author: Haibo Liu

In this BMC Genomics study, researchers from Iowa State University used IPA to help them understand variations of global gene expression in the blood transcriptome of two separate lines of recently-weaned pigs to potentially inform the development of predictive biomarkers for residual feed intake, or RFI — a standard measure for feed efficiency. The team found a difference between the low and high RFI classifications of pigs, potentially leading to improved feed efficiency through genetic selection.

To try Ingenuity Pathway Analysis, please request a trial. If you’re working on something interesting with a QIAGEN Bioinformatics solution, let us know … you could be featured on our blog!

Webinar: Transcriptome analysis of pancreatic cancer exosomes involved in metastatic progression

Pancreatic cancer is one of the most lethal malignancies with a poor prognosis. Liquid biopsies are non-invasive methods for diagnostics to detect early stage cancer resulting in more successful treatment. One liquid biopsy technique is the detection of RNA from tumor-derived exosomes.

In this webinar you can learn how bioinformatics solutions can be used to analyze and interpret RNA-sequencing results from these exosome experiments, providing additional hypothesis on regulatory networks and potential isoforms of biological significance. We’ll examine the transcriptome of pancreatic tumor-derived exosomes that induce the formation of a liver metastatic niche, and demonstrate how our solutions can provide deep biological understanding in this process.

Find out how to:

• Streamline RNA-sequencing alignment and analysis using configured workflows for the fast track to biological interpretation
• Analyze exosome gene expression signatures to pinpoint significant genes associated with early detection of pancreatic cancer
• Identify significantly differentially expressed isoforms and their association to pancreatic cancer
• Generate novel regulatory networks as hypotheses suggesting drivers of the expression changes observed in these tumor producing exosomes to better understand pancreatic cancer drivers