Category Archives: Genetic Medicine

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WHAT The team of parents, genetic and translational medicine scientists and pediatric oncologists trailblazing personalized medicine in the treatment of deadly pediatric cancers is convening in Austin to discuss the status of the worlds first personalized medicine clinical trial for pediatric cancer and plan next steps at the NMTRC Symposium 2012. Neuroblastoma affects 1 in 100,000 children and is responsible for 1 in 7 pediatric cancer deaths.

WHO Parents, advocates, oncologists from the Neuroblastoma and Medulloblastoma Translational Research Consortium (NMTRC) and biomedical researchers from the Translational Genomics Research Institute (TGen), who are using high performance computing and cloud technology from Dell to identify targeted treatments based on the specific genetic vulnerabilities of each childs tumoran approach that could be used to treat all pediatric and adult cancers in the future.

WHY Personalized medicinetreatment based on the specific vulnerabilities of each tumor is overcoming longstanding barriers to treatment of pediatric cancer. There has been only one new treatment for pediatric cancer approved by the FDA since the 1980s, compared to 50 treatments approved for adult cancer in this same timeframe. As a result, pediatric oncologists use treatments designed for adults to treat children, with toxic side effects that are frequently as physically detrimental to the child as the cancer itself.

WHEN The following events will be available via live-stream: May 16 1-2 pm CT: Keynote: Molecular-Profiling for Optimized Precision Therapy, Dr. Timothy Triche, University of Southern California/ Childrens Hospital Los Angeles

2-4 pm CT: Panel Discussion: Kids Cloud: Access to Data Boundaries Dr. Melinda Merchant - National Cancer Institute Dr. Gary Marchant - Arizona State University Nancy Goodman - Kids V. Cancer Foundation Patrick Lacey - Friends of Will Foundation Andy Mikulak - Maxs Ring of Fire Foundation Dr. Giselle Sholler - Van Andel Institute Dr. Spyro Mousses - Translational Genomics Research Institute Dr. James Coffin - Dell

WHERE Participate and join the conversation via the #HealthCloud hashtag on Twitter. Tune in via Live-Stream here: http://www.fittotweet.com/live/nmtrc/.

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Innovators in Pediatric Cancer to Share Progress on Ground-Breaking Personalized Medicine Clinical Trial

Public release date: 7-May-2012 [ | E-mail | Share ]

Contact: David Sampson ajpmedia@elsevier.com 215-239-3171 Elsevier Health Sciences

Philadelphia, PA, May 7, 2012 While active monitoring of serum prostate specific antigen (PSA) levels in men over 50 has greatly improved early detection of prostate cancer, prediction of clinical outcomes after diagnosis remains a major challenge. Researchers from the University of Pittsburgh School of Medicine have found that a genetic abnormality known as copy number variation (CNV) in prostate cancer tumors, as well as in the benign prostate tissues adjacent to the tumor and in the blood of patients with prostate cancer, can predict whether a patient will experience a relapse, and the nature of the relapse aggressive or indolent. Their report is published in the June issue of The American Journal of Pathology.

Copy number variations are large areas of the genome with either duplicated or missing sections of DNA. "Our analysis indicates that CNV occurred in both cancer and non-cancer tissues, and CNV of these tissues predicts prostate cancer progression," says lead investigator Jian-Hua Luo, MD, PhD, associate professor in the Divisions of Molecular and Cellular Pathology, and Anatomic Molecular Pathology, Department of Pathology, University of Pittsburgh School of Medicine. "Prediction models of prostate cancer relapse, or of the rate of PSA level increase after surgery, were generated from specific CNV patterns in tumor or benign prostate tissues adjacent to cancer samples."

To detect the abnormalities, scientists conducted a comprehensive genome analysis on 238 samples obtained from men undergoing radical prostatectomy: 104 prostate tumor samples, 85 blood samples from patients with prostate cancer, and 49 samples of benign prostate tissues adjacent to a tumor. A third of the samples were from patients exhibiting recurrence with a PSA level increasing at a rapid rate, doubling in less than four months (rapid increases are associated with lethal prostate cancer); a third from patients exhibiting recurrence with a PSA level increasing at a slow rate, doubling time greater than 15 months; and a third with no relapse more than five years after surgery. Three commercially available prostate cancer cell lines were also tested to validate the results.

Deletions of large segments of specific chromosomes occurred with high frequency, whereas amplification of other chromosomes occurred in only a subset of prostate cancer samples. Similar amplification and deletion of the same regions also occurred in benign prostate tissue samples adjacent to the cancer. Prostate cancer patients' blood was found to contain significant CNVs. Most were not unique and overlapped with those of prostate cancer samples.

Using gene-specific CNV from tumor, the model correctly predicted 73% of cases for relapse and 75% of cases for short PSA doubling time. The CNV model from tissue adjacent to the prostate tumor correctly predicted 67% of cases for relapse and 77% of cases for short PSA doubling time. Using median-size CNV from blood, the genome model correctly predicted 81% of the cases for relapse and 69% of the cases for short PSA doubling time.

Dr. Luo notes that there are several potential clinical applications using CNV tests. "For a patient diagnosed with prostate cancer, CNV analysis done on blood or normal tissues would eliminate the need for additional invasive procedures to decide a treatment mode. For a patient already having a radical prostatectomy, CNV analysis on the tumor or blood sample may help to decide whether additional treatment is warranted to prevent relapse. Despite some limitations, including the need for high quality genome DNA, CNV analysis on the genome of blood, normal prostate, or tumor tissues holds promise to become a more efficient and accurate way to predict the behavior of prostate cancer."

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Genetic abnormalities in benign or malignant tissues predict relapse of prostate cancer

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Free text in electronic health records, with the help of natural language processing (NLP) technology, can be used to create accurate clinical decision support (CDS) tools, according to a study published this week in the Journal of the American Medical Informatics Association

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Read about why a Qualcomm Life executive says mobile health doesn’t yet have an Instagram, and why it eventually will.

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DUBLIN--(BUSINESS WIRE)--

Dublin - Research and Markets (http://www.researchandmarkets.com/research/vw2h92/personalized_medic) has announced the addition of the "Personalized Medicine: Companies, Trends and World Market" report to their offering.

This broad, high-level report analyzes the expanding Personalized Medicine market. This world market includes important core medical product areas that will continue to have a powerful impact on current and future healthcare delivery. This business report examines key market segments such as targeted drugs and key personalized medicine diagnostics, including companion diagnostic IVDs, LDTs, diagnostic services and related tools or technologies.

Many people already know about DNA, genes and the human genome. The science driving personalized medicine includes pharmacogenetics, pharmacoproteomics and pharmacometabalomix. Personalized medicine uses a targeted drug that depends on the patient information identified by a companion diagnostic (genetic biomarker test). The companion diagnostic identifies which patients would likely benefit from a particular therapy or those who might suffer from a bad side effect. The test information enables doctors to select the drug therapy that would benefit the patient. Drug developers in clinical trials could use a companion diagnostic to select patents that would benefit from a targeted drug.

The report discusses important technologies, including microarray, next-generation sequencing, PCR, bioinformatics, nanotechnology and other platforms. This section highlights key platforms and selected vendors. For example, the field of clinical next generation sequencing is expected to have an impact on personalized medicine.

The report covers subjects including important personalized medicine concepts. The study discusses key biomarkers, commercial diagnostics and therapeutics that drive personalized medicine. The study highlights new personalized diagnostics. This research examines the current targeted therapeutics on the market and drugs in the clinical pipeline.

The report highlights major government regulatory activities that involve personalized medicine in the US and Europe. The US FDA and the European EMA have drafted guidance papers to help drug makers and diagnostic firms develop future targeted therapies guided by companion diagnostics. The recent FDA approvals of Pfizer's Xalkori for lung cancer and Roche's Zelboraf for melanoma demonstrate that a surge in new targeted drugs is happening.

This report is in an interactive PDF format. The interactive feature uses hyperlinks that enable the reader to click the mouse to jump from Table of Contents items to sections inside the report. The hyperlinks also allow the reader to click on links to Internet information.

This study discusses important personalized medicine topics and provides the reader with key findings. The report estimates that the world personalized medicine market value will reach multi-billions of dollars in 2012, with a strong double-digit growth rate. This study reviews the activities of 31 companies.

The report uses 71 figures and tables to help the reader scan the details of major trends, market segmentation, forecast, M&As, partnerships, grant funding, patents and so on. This must-have report would benefit people with job titles including CEO, VPs, Director of Business Development, Research Directors, Entrepreneurs, Venture Capitalists, Investment Planners, Research Scientists, Consultants or Industry Analysts.

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Research and Markets: Personalized Medicine: Companies, Trends and World Market

Public release date: 1-May-2012 [ | E-mail | Share ]

Contact: Doug Dusik ddusik@aasmnet.org 630-737-9700 American Academy of Sleep Medicine

DARIEN, IL Toss out another old wives' tale: Sleeping too much does not make you fat. Quite the opposite, according to a new study examining sleep and body mass index (BMI) in twins, which found that sleeping more than nine hours a night may actually suppress genetic influences on body weight.

The study looked at 1,088 pairs of twins and found that sleeping less than seven hours a night was associated with both increased BMI and greater genetic influences on BMI. Previous research has shown that genetic influences include things like glucose metabolism, energy use, fatty acid storage and satiety. In this study, the heritability of BMI was twice as high for the short sleepers than for twins who slept longer than nine hours a night.

"The results suggest that shorter sleep provides a more permissive environment for the expression of obesity related genes," said principal investigator Nathaniel Watson, MD, MSc, of the University of Washington. "Or it may be that extended sleep is protective by suppressing expression of obesity genes."

Watson and colleagues determined that for twins sleeping less than seven hours, genetic influences accounted for 70 percent of the differences in BMI, with common environment accounting for just 4 percent and unique environment 26 percent. For twins averaging more than nine hours of sleep, genetic factors were attributed to 32 percent of weight variations, with common environment accounting for 51 percent and unique environment 17 percent.

More research is needed, Watson said, but these preliminary results may suggest that behavioral weight loss measures would be most effective when genetic drivers of body weight are mitigated through sleep extension.

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For a copy of the study, "Sleep Duration and Body Mass Index in Twins: A Gene-Environment Interaction," or to arrange an interview with an AASM spokesperson, please contact PR Coordinator Doug Dusik at 630-737-9700, ext. 9364, or ddusik@aasmnet.org.

The monthly, peer-reviewed, scientific journal SLEEP is published online by the Associated Professional Sleep Societies LLC, a joint venture of the American Academy of Sleep Medicine and the Sleep Research Society. The AASM is a professional membership society that is the leader in setting standards and promoting excellence in sleep medicine health care, education and research (www.aasmnet.org).

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Longer sleep times may counteract genetic factors related to weight gain