Announcing Travel Grant recipients!

Autism, entomology and microRNAs in cancer may not have much in common, but three enthusiastic researchers studying these areas are the recipients of NextBio travel grants this month: Congratulations Catarina Correia, Malay Bhattacharyya and Stephanie Weldon!

Stephanie is a graduate student in entomology at the University of Georgia, studying symbiotic interactions in insects and bacteria. We were excited to learn how she used NextBio in her studies of Shiga toxins. As she describes her research:

“I study insect-bacterium symbioses and associated mobile genetic elements, where the lateral transfer of both infectious agent and genetic material requires me to cross-reference very diverse data sets, a circumstance that makes NextBio’s search apps very appealing. Sorted results, rather than restricted results, allow researchers to quickly take in large amounts of data without artificially limiting the potential for productive cross-fertilization from more distant sources.”

Tied with Stephanie for second place is Malay Bhattacharyya, a computer scientist turned biologist at the Indian Statistical Institute. As part of his graduate research in machine intelligence, he uses in silico approaches to demonstrate the involvement of two oncogenic miRNAs in leukemia and prostate cancer. Though he found “no earlier databases validating (his) hypothesis”, Malay adds that he found NextBio’s detailed statistics helpful:

“NextBio provides the results in Disease Atlas together with p-values, fold changes, copy number changes and z-scores. The ranking by statistical significance make the results very much practical to the researchers. It strengthens the results and makes it more justifiable.”

We were thrilled to hear that these statistics on his data supported Malay’s research!

Catarina Correia is a post-doctoral researcher in computational genomics and neurogenetics at the Instituto Gulbenkian de Ciência who works on protein networks in autism spectrum disorders. Catarina’s essay describes the importance of aggregate analysis of disease-linked gene variants to identify groups of affected pathways or biological processes. Her essay outlines how she used NextBio to identify protein sub-networks potentially important in autism and combine data from GWAS, expression profiles, CNV and mutation screenings. As she describes her analysis of public datasets:

“Information from several apps, especially Knockdown Atlas have elucidated possible mechanisms by which this gene can be implicated in autism, most of them required analysis of public datasets and are not fully described in the papers, helping us in the design of follow up studies.”

We will share the winning essays in this space over the next few weeks, so check back to hear more about these exciting research areas. We will be announcing the next round of travel grants soon, so keep an eye on this space as well!

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Sorting through omics data for cancer biomarkers

Going to the AACR Annual Meeting? Visit our poster to find out more about a novel biomarker candidate for cancer!

The genome of a healthy person is constantly interacting with external signals and internal cues to adapt to a changing environment. Similarly, tumors also respond to the therapies aimed at removing them; chemotherapy and targeted molecular therapies can occasionally induce additional mutations or gene expression changes in tumor genomes. These secondary genetic changes are associated with increased drug resistance, recurrent forms of cancer and poorer chances of survival for patients.

Our presentation at the AACR Annual Meeting next week focuses on the correlations we identified for one such gene, sorting nexin 9 (SNX9). NextBio analysis of data correlations to SNX9 revealed several correlations of the gene to multiple types of cancer, including breast, prostate and other cancers. Read more…

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Finding MARS mutants in the human exome

Talks at the Sanford-Burnham Rare Disease Day Symposium highlight the “transformative potential of exome sequencing” for rare Mendelian diseases

Individually rare yet collectively common, ‘orphan’ or rare diseases affect nearly 30 million Americans every year. Despite the current explosion in genomic data and personalized medicine strategies, little is known about what causes these rare genetic disorders, how they progress or options for treatment. Marking Rare Disease Day, a one-day symposium at the Sanford Burnham Medical Research Institute in La Jolla, CA featured talks by several researchers studying disorders of glycosylation, especially in children. Several of these discussions highlighted how studying rare conditions can enhance the ways we detect, diagnose or research relatively more common diseases. Read more…

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Moving sequencing into the clinic takes more than just big data

Recent news articles discuss how NextBio scales technology to handle  genomics data

As genomic data makes its way from specialized laboratories into routine healthcare evaluations, it is perhaps appropriate that announcements of the latest sequencers were made at the Consumer Electronics Show in Las Vegas rather than the  upcoming Advances in Genome Biology and Technology conference.

New machines from Illumina and Life Technologies only strengthen the idea that 2012 is, in fact, the year of the $1000 genome. Led by a trickle of individual success stories, genome sequencing appears to be on the verge of altering the clinical landscape. While the FDA and regulatory bodies resolve the consumer issues of reimbursement and regulation crucial to patients, here at NextBio we tackle an intermediate problem: Making sense of the data. Read more…

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Predicting drug responses: Clinical Trials and Meta-analysis in NextBio

In part IV of the NextBio tutorials, we use the Clinical Trials and Meta-analysis apps to explore the effects of the drug tibolone

High through-put technology is churning out data faster than human beings can process and sift through this abundance of information. However, not all of the results obtained are included in the finished product of a study. A recent paper by Lisa Bero and her colleagues investigates the effect of omitted trial outcome data from the Food and Drug Administration. By examining studies included in the Cochrane reviews, the researchers found that approximately half of these clinical trials exclude data. Meta-analyses and systemic reviews based on partial data may overestimate the efficacy of the drug, a practice that can be harmful to patients. Bero and her colleagues found that 19 out of 41 trials included in their reanalysis showed decreased efficacy with the addition of unpublished data. Read more…

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Query curiosity: NextBio queries using biosets

In Part III of the NextBio tutorials, we demo bioset queries with the Curated Studies, Biogroups and Genome Browser apps

Incorporating different kinds of data into a single system means that every experiment included has to be normalized and compared with other curated studies in the NextBio platform. One way we accomplish this is by standardizing different kinds of results into biosets.

A bioset usually represents the results from a single experiment. For this tutorial video, we used a bioset that compares colon cancer cells that have metastasized to the liver to normal liver tissue.  The tutorial walks you through using this bioset to query Biogroups, which shows groups of genes or pathways that are enriched in this particular comparison.   Read more…

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Epigenetic changes mark up ovarian cancer cells

A genome wide methylation screen finds a potential new biomarker for ovarian cancer

In the forty years since the ‘War on Cancer’ was declared, ovarian cancer is the only form of the disease where mortality rates remain unchanged, in part due to a lack of early detection tests and specific treatments. In 2011, an estimated 15,000 women in the U.S will die of ovarian cancer.

A recent study in PLoS One by Campan et al. describes the identification of a new candidate biomarker, IFFO1, in a genome-wide DNA methylation screen of blood samples from ovarian cancer patients. Less invasive than tests that require tissue samples, and chemically and biologically more stable than RNA markers for gene expression, DNA methylation changes that can be tracked in blood samples are promising biomarkers for cancer detection and treatment. Read more…

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NextBio Public Tutorials: Exploring the experimental details behind NextBio results

In part II of the NextBio Public tutorials, we show you how to find the experimental details underlying your NextBio query results.

Critics of GWAS are quick to point out that the genetic associations identified in such studies rarely reach clinical significance. However, integrating associations identified in genome-wide studies with evidence from more directed experiments can speed up the process of taking genomic variants from the bench to the clinic. Watch our tutorial to find out how to dig down into the experimental results associated with a gene query in NextBio, or read on to learn more about our study* on one particular gene, POU5F1B. Read more…

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Tumor suppressor or oncogene? The argument continues…

Integrated approaches identify a new tumor suppressor function for soluble EPHA7 in follicular lymphoma

Scanning the whole genome for tumor-associated mutations has the potential to reveal new drug targets or diagnostic biomarkers that could help personalize therapy for patients. However, the complex patterns of genetic disruptions in cancer frequently prevent such candidate genes from reaching clinical significance. Combining tumor genomics with functional genetic screens and experimental models can increase the pace at which genome-wide findings are translated into clinically relevant applications.

A recent paper in Cell describes the identification of a novel tumor suppressor, EPHA7, in a genome-wide screen of follicular lymphoma samples. Supporting this finding with experimental results from animal models and cancer cell lines, the researchers also demonstrated that the gene product, a soluble protein, had the potential to dramatically improve tumor clearance in mice. Read more…

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