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colleagues found that 19 out of 41 trials included in their reanalysis showed decreased efficacy with the addition of unpublished data.
Past studies on the drug tibolone exhibit this missing data phenomenon. Tibolone, a synthetic estrogen analog, is prescribed to treat vasomotor symptoms of menopause and breast cancer. Vasomotor symptoms include hot flashes, night sweats, sweats, and flushes, all of which tend to difficult to relieve. A clinical trial in 2006 by the Women’s Clinic of Lincoln identified tibolone as a drug that successfully ameliorates these symptoms. Conversely, a study published three years later in The Lancet found that tibolone also increases the risk of relapse in breast cancer patients undergoing adjuvant systemic therapy from 10.7 to 15.2 percent. This study’s original objective was to show the advantage of using tibolone for hormone replacement therapy. However, out of 402 participating breast cancer patients, the majority of relapse occurred in those taking tibolone. This tutorial uses the Erasmus University Medical Center clinical trial on tibolone to demonstrate how NextBio’s Meta-analysis application can reveal obscure expression patterns, which can predict potential adverse side effects such as those found in the 2009 study.
NextBio’s Clinical Trials application allows users to quickly view specific details of clinical trials. All studies shown on the Clinical Trials app come from clinicaltrials.gov, but are tagged with keywords and organized so that the user can quickly choose a filter best suited to their search. Some options include filtering by biogroup, compound, or phenotype. Clinical Trials also includes links for key words in the trial description that opens an information box when moused over.
Meta-analysis makes it easy to reveal correlations and make connections using data from a single study, or across multiple studies. The results from curated clinical trials can be re-analyzed with Meta-Analysis to find correlations to existing data on disease prognosis or drug responses. Data from the tibolone study shows similar induced gene expression patterns to breast cancer, which may explain why tibolone treatment can increase the risk of relapse in breast cancer patients. For example, TOP2A (Topoisomerase (DNA) II alpha 170kDA), a gene that regulates cell division and is the target of several anti-cancer agents, is upregulated in women treated with tibolone and breast cancer tissue.
Additionally, viewing results by bioset allows users to develop new hypotheses by comparing expression patterns in biosets from the entire NextBio database. Biosets appear in order of relevance to the user’s chosen biosets. In the tutorial, we see that other cancers, aside from breast cancer, also have some similarities to tibolone-induced gene expression patterns in the body.
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