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News Article | May 8, 2017
Site: www.scientificcomputing.com

Product developers talk about time to market. Web service providers measure time to first byte. For James Lowey, the key metric is time to life. Lowey is CIO at the Translational Genomics Research Institute (TGen), a nonprofit focused on turning genomics insights into faster diagnostics and treatments that are more effective. TGen’s genetics research is being applied to rare childhood diseases, cancer, neurological disorders, diabetes and others. “We’ve got patients waiting,” Lowey told the panel audience. “We need to diagnose and treat them. They need results now, not in weeks or months. We’re working to accelerate the movement of insights from the bench to the bedside.” It’s no surprise that each new generation of processors helps organizations like TGen deliver genetic results—and clinical answers—more quickly. Lowey described TGen’s farm of Intel Xeon processor E5 v3 based Dell blade servers based on Intel Scalable System Framework (Intel SSF). Using the blade servers, TGen has reduced processing time for critical genomics processing tasks from two weeks to seven hours, making it fast enough to be clinically relevant. Digital imaging is another area where HPC-enabled speedups are advancing clinical care. Panelist Simon K. Warfield described innovative imaging techniques his team is applying to increase understanding of the brain’s complex circuitry. Dr. Warfield is the Thorne Griscom Professor of Radiology at Harvard Medical School and the founder and director of the Computational Radiology Lab (CRL) at Boston Children's Hospital. CRL is an Intel Parallel Computing Center that is modernizing the algorithms and data structures of medical image computing on Intel Xeon and Intel Xeon Phi processors. The lab is improving cache performance, vectorization performance and multi-threading performance, as well as creating more sophisticated imaging and modeling strategies. CRL can contribute to improved diagnosis and treatment of brain injuries, multiple sclerosis, depression, Alzheimer’s and many other conditions. Consider the novel technique CRL has developed to show more clearly water’s diffusion through the brain—and pinpoint hindrances and restrictions to its flow. In contrast to traditional image processing approaches, CRL’s diffusion-weighted imaging infers new parametric maps from data measurements. Its computational model includes tens or hundreds of 3D images—each up to 10 million pixels each—as its inputs. “This type of analysis is very computationally intensive,” Warfield said. “With the accelerated algorithm and the Intel Xeon Phi processors, we reduced the time needed from 48 hours to 15 minutes of calculations.” That speedup can translate to immediate benefits in for critically ill patients facing brain surgery. That’s because, as Warfield put it, “When you’re talking about surgical planning, life is a matter of time.” Recently, one of the hospital’s neurosurgery teams realized on a Friday that their patient’s conventional magnetic resonance scan was not clear enough to allow them to proceed with a planned brain resection. With the surgery-planning meeting scheduled for Monday, they requested emergency use of CRL’s diffusion imaging algorithm. The patient had a new scan Saturday evening, the data was processed on Sunday, and the information was ready for the team’s decision on Monday. The panel also highlighted precision medicine’s global reach—and its big data challenges. Fang Lin, Director of the Bioinformatics Center at BGI, described BGI’s use of the Lustre file system to help maintain storage performance as its data volumes grow. BGI is a global research leader as well as a provider of genetic testing products. It also operates the China National Genebank, putting it on the forefront of China’s five-year. BGI cranks 20 terabytes of sequencing data every day. The institute stores13petabytes of genomic data and uses a 10 petabyte file system comprising Intel Enterprise Edition for Lustre Software and open source technologies. Dr. David Torrents, a molecular biologist and research professor at the Barcelona Supercomputing Center, shone a spotlight on the importance of collaboration in advancing precision medicine. BSC provides resources to a variety of international centers and consortia. In addition, the institute conducts its own multidisciplinary research in computational biomedicine and related fields. BSC’s alliances also encompass a range of hospitals and medical centers, enabling it to validate and test its models and tools with data from clinical institutions. “We’re at an exciting moment,” Torrents said. “We are not just developing new solutions for personalized medicine, but now are beginning a pilot program in January 2017 to bring them together and apply them in clinical settings, beginning in Catalonia and then throughout Spain.” The panelists say continued leaps forward in precision medicine will come from faster and more sophisticated analysis of larger volumes of more varied data types. “What we want is a more holistic picture, and for that, it’s becoming absolutely critical to combine many diverse data types together for analysis,” said Lowey. To achieve that holistic picture, researchers want to use deep learning and other forms of artificial intelligence. They also want to apply those AI methods to genomic data in combination with imaging data, lifelong clinical records, population studies, environmental studies, and much more. Different aspects of the precision medicine workflow will have varying processing and storage requirements. So the push continues for faster performance with agile or heterogeneous platform architectures rather than a single “silver bullet” approach. The processors will continue as the primary workhorses, supplemented by embedded resources and FPGA accelerators for parts of the workflow. Distributed compute and storage resources will remain crucial, along with advances in applications and tools. As to the clinical impact of these holistic approaches, look no further than Boston Children’s Hospital. Noninvasive prenatal genomic testing can indicate whether a fetus has the risk factors that predispose it to be born with a malformed heart. If genetic testing shows these factors are present, data-intensive digital imaging can reveal whether the heart is actually deformed. By combining genomic with other medical data in this way, clinicians can provide peace of mind for worried parents-to-be, or help them plan for their child’s future. “We’re starting to connect the genetics that predisposes an individual to heart disease, with the imaging to see if the defect is present, and use that information to influence current treatment,” said Warfield. “That information can also help us plan for the child’s longer-term future. We can predict how they’ll do as teenagers and begin to plan accordingly.” Precision medicine is one of the most promising and meaningful applications of high-performance computing today. “It’s still early days, but we’re moving toward an exciting new era of predictive biology and personalized medicine,” said McManus. “Our panelists gave us a great taste of what’s on the horizon. With continued advances in platform technologies, artificial intelligence, and other areas, we create significant opportunities to increase the science of medicine and ultimately improve human health. Intel is excited to empower scientists and clinicians with technology innovations, resources and expertise as we collaborate to make this new era a reality.” Jan Rowell writes about technology trends in HPC, healthcare, life sciences, and other industries.


News Article | May 8, 2017
Site: www.scientificcomputing.com

Product developers talk about time to market. Web service providers measure time to first byte. For James Lowey, the key metric is time to life. Lowey is CIO at the Translational Genomics Research Institute (TGen), a nonprofit focused on turning genomics insights into faster diagnostics and treatments that are more effective. TGen’s genetics research is being applied to rare childhood diseases, cancer, neurological disorders, diabetes and others. “We’ve got patients waiting,” Lowey told the panel audience. “We need to diagnose and treat them. They need results now, not in weeks or months. We’re working to accelerate the movement of insights from the bench to the bedside.” It’s no surprise that each new generation of processors helps organizations like TGen deliver genetic results—and clinical answers—more quickly. Lowey described TGen’s farm of Intel Xeon processor E5 v3 based Dell blade servers based on Intel Scalable System Framework (Intel SSF). Using the blade servers, TGen has reduced processing time for critical genomics processing tasks from two weeks to seven hours, making it fast enough to be clinically relevant. Digital imaging is another area where HPC-enabled speedups are advancing clinical care. Panelist Simon K. Warfield described innovative imaging techniques his team is applying to increase understanding of the brain’s complex circuitry. Dr. Warfield is the Thorne Griscom Professor of Radiology at Harvard Medical School and the founder and director of the Computational Radiology Lab (CRL) at Boston Children's Hospital. CRL is an Intel Parallel Computing Center that is modernizing the algorithms and data structures of medical image computing on Intel Xeon and Intel Xeon Phi processors. The lab is improving cache performance, vectorization performance and multi-threading performance, as well as creating more sophisticated imaging and modeling strategies. CRL can contribute to improved diagnosis and treatment of brain injuries, multiple sclerosis, depression, Alzheimer’s and many other conditions. Consider the novel technique CRL has developed to show more clearly water’s diffusion through the brain—and pinpoint hindrances and restrictions to its flow. In contrast to traditional image processing approaches, CRL’s diffusion-weighted imaging infers new parametric maps from data measurements. Its computational model includes tens or hundreds of 3D images—each up to 10 million pixels each—as its inputs. “This type of analysis is very computationally intensive,” Warfield said. “With the accelerated algorithm and the Intel Xeon Phi processors, we reduced the time needed from 48 hours to 15 minutes of calculations.” That speedup can translate to immediate benefits in for critically ill patients facing brain surgery. That’s because, as Warfield put it, “When you’re talking about surgical planning, life is a matter of time.” Recently, one of the hospital’s neurosurgery teams realized on a Friday that their patient’s conventional magnetic resonance scan was not clear enough to allow them to proceed with a planned brain resection. With the surgery-planning meeting scheduled for Monday, they requested emergency use of CRL’s diffusion imaging algorithm. The patient had a new scan Saturday evening, the data was processed on Sunday, and the information was ready for the team’s decision on Monday. The panel also highlighted precision medicine’s global reach—and its big data challenges. Fang Lin, Director of the Bioinformatics Center at BGI, described BGI’s use of the Lustre file system to help maintain storage performance as its data volumes grow. BGI is a global research leader as well as a provider of genetic testing products. It also operates the China National Genebank, putting it on the forefront of China’s five-year. BGI cranks 20 terabytes of sequencing data every day. The institute stores13petabytes of genomic data and uses a 10 petabyte file system comprising Intel Enterprise Edition for Lustre Software and open source technologies. Dr. David Torrents, a molecular biologist and research professor at the Barcelona Supercomputing Center, shone a spotlight on the importance of collaboration in advancing precision medicine. BSC provides resources to a variety of international centers and consortia. In addition, the institute conducts its own multidisciplinary research in computational biomedicine and related fields. BSC’s alliances also encompass a range of hospitals and medical centers, enabling it to validate and test its models and tools with data from clinical institutions. “We’re at an exciting moment,” Torrents said. “We are not just developing new solutions for personalized medicine, but now are beginning a pilot program in January 2017 to bring them together and apply them in clinical settings, beginning in Catalonia and then throughout Spain.” The panelists say continued leaps forward in precision medicine will come from faster and more sophisticated analysis of larger volumes of more varied data types. “What we want is a more holistic picture, and for that, it’s becoming absolutely critical to combine many diverse data types together for analysis,” said Lowey. To achieve that holistic picture, researchers want to use deep learning and other forms of artificial intelligence. They also want to apply those AI methods to genomic data in combination with imaging data, lifelong clinical records, population studies, environmental studies, and much more. Different aspects of the precision medicine workflow will have varying processing and storage requirements. So the push continues for faster performance with agile or heterogeneous platform architectures rather than a single “silver bullet” approach. The processors will continue as the primary workhorses, supplemented by embedded resources and FPGA accelerators for parts of the workflow. Distributed compute and storage resources will remain crucial, along with advances in applications and tools. As to the clinical impact of these holistic approaches, look no further than Boston Children’s Hospital. Noninvasive prenatal genomic testing can indicate whether a fetus has the risk factors that predispose it to be born with a malformed heart. If genetic testing shows these factors are present, data-intensive digital imaging can reveal whether the heart is actually deformed. By combining genomic with other medical data in this way, clinicians can provide peace of mind for worried parents-to-be, or help them plan for their child’s future. “We’re starting to connect the genetics that predisposes an individual to heart disease, with the imaging to see if the defect is present, and use that information to influence current treatment,” said Warfield. “That information can also help us plan for the child’s longer-term future. We can predict how they’ll do as teenagers and begin to plan accordingly.” Precision medicine is one of the most promising and meaningful applications of high-performance computing today. “It’s still early days, but we’re moving toward an exciting new era of predictive biology and personalized medicine,” said McManus. “Our panelists gave us a great taste of what’s on the horizon. With continued advances in platform technologies, artificial intelligence, and other areas, we create significant opportunities to increase the science of medicine and ultimately improve human health. Intel is excited to empower scientists and clinicians with technology innovations, resources and expertise as we collaborate to make this new era a reality.” Jan Rowell writes about technology trends in HPC, healthcare, life sciences, and other industries.


News Article | April 25, 2017
Site: www.sciencedaily.com

Adding cisplatin to the standard gemcitabine/nab-paclitaxel drug treatment provided a very high rate of tumor shrinkage for patients with advanced pancreatic cancer, according to the results of a pilot clinical trial conducted by the HonorHealth Research Institute and the Translational Genomics Research Institute (TGen). These statistically significant and clinically meaningful improvements in overall response and survival rates resulted from a phase Ib/II clinical study performed at the HonorHealth Research Institute, a partnership of HonorHealth and TGen. The results were presented during the 2017 Gastrointestinal Cancers Symposium, sponsored by the American Society of Clinical Oncology, in San Francisco. Connecting a global network of more than 40,000 cancer professionals, the society serves as the leading resource for best practices in clinical oncology research and academic and community practices. "After just three treatment cycles, we saw tumor markers plummet and some patients' tumors shrink significantly in just nine weeks," said Gayle Jameson, nurse practitioner and principal investigator of the clinical trial, who is highly encouraged by the response. "After treatment, two patients had no evidence of disease and are alive over three years after starting this regimen. This is very rare with traditional chemotherapy." Dr. Daniel Von Hoff, TGen Distinguished Professor and Physician-in-Chief who devised the clinical trial, agreed: "Although a small study, the high response rate and landmark evolving median survival are very encouraging, and this regimen is being expanded for patients with stage IV pancreatic cancer." Dr. Von Hoff also is chief scientific officer at the HonorHealth Research Institute. Of the 24 evaluable patients (those whose response to a treatment could be measured because enough information was collected) who were enrolled in the study: This pilot clinical trial began in 2013 through a partnership between the HonorHealth Research Institute and TGen. It was funded by Stand Up To Cancer, Mattress Firm, the Arizona Diamondbacks, and the Scottsdale-based Seena Magowitz Foundation. Symptoms of pancreatic cancer usually do not appear until the disease progresses to its late stages, making it difficult to treat. Only about one in four patients survives more than a year after diagnosis, and fewer than 10 percent survive more than five years. Pancreatic cancer this year will take the lives of more than 43,000 Americans, making it the nation's third-leading cause of cancer-related death. The results of this trial are encouraging and deserve additional testing prior to becoming a standard of care for patients with advanced pancreatic cancer. Through research, the HonorHealth Research Institute and TGen aim to provide hope and a better chance for patients to live for years instead of months. The current standard of care for advanced pancreatic cancer -- a combination of nab-paclitaxel and gemcitabine -- was developed by TGen and the HonorHealth Research Institute, and approved by the U.S. Food and Drug Administration in 2013.


Patent
Mayo Foundation For Medical Education And Research and Translational Genomics Research Institute | Date: 2015-02-04

The present invention provides a method of characterizing a cancer by obtaining a sample from a subject suspected of having cancer; and determining whether a fibroblast growth factor receptor (FGFR) fusion is present in the sample, wherein the FGFR fusion comprises a FGFR locus, thereby characterizing the cancer based on the presence or absence of the FGFR fusion.


Patent
Van Andel Research Institute and Translational Genomics Research Institute | Date: 2014-12-05

The present invention relates to compounds of Formula III, Formula 111(a), Formula V, Formula V(a), Formula A, Formula A 1, Formula A2, Formula A 3, or a pharmaceutically acceptable salt thereof that are useful as pharmaceutical agents, individually and/or in a combination with a chemotherapeutic agent: PLX-4032 (vemurafenib), or the catalytic mTOR inhibitor AZD8055, to treat a cancer and/or a cancer metastasis, for example a cancer harboring a BRAF protein kinase mutation and/or a HRAS protein mutation. Also, a method of treating and/or preventing malaria in a subject, the method comprising administering a therapeutically effective amount of a compound of Formula A, Formula A 1, Formula A2, Formula A 3, or a pharmaceutically acceptable salt thereof to the subject in need.


Patent
Van Andel Research Institute and Translational Genomics Research Institute | Date: 2015-11-19

The present invention relates to compounds of formulas III and V that are useful as pharmaceutical agents, particularly as autophagy inhibitors.


Baker A.,Translational Genomics Research Institute
Blood | Year: 2013

Epidemiological data have suggested that African American (AA) persons are twice as likely to be diagnosed with multiple myeloma (MM) compared with European American (EA) persons. Here, we have analyzed a set of cytogenetic and genomic data derived from AA and EA MM patients. We have compared the frequency of IgH translocations in a series of data from 115 AA patients from 3 studies and 353 EA patients from the Eastern Cooperative Oncology Group (ECOG) studies E4A03 and E9487. We have also interrogated tumors from 45 AA and 196 EA MM patients for somatic copy number abnormalities associated with poor outcome. In addition, 35 AA and 178 EA patients were investigated for a transcriptional profile associated with high-risk disease. Overall, based on this cohort, genetic profiles were similar except for a significantly lower frequency of IgH translocations (40% vs 52%; P = .032) in AA patients. Frequency differences of somatic copy number aberrations were not significant after correction for multiple testing. There was also no significant difference in the frequency of high-risk disease based on gene expression profiling. Our study represents the first comprehensive comparisons of the frequency and distribution of molecular alterations in MM tumors between AA and EA patients. ECOG E4A03 is registered with ClinicalTrials.gov, number NCT00098475. ECOG E9487 is a companion validation set to the ECOG study E9486 and is registered with the National Institutes of Health, National Cancer Institute, Clinical Trials (PDQ), number EST-9486.


Byron S.A.,Translational Genomics Research Institute
Nature Reviews Genetics | Year: 2016

With the emergence of RNA sequencing (RNA-seq) technologies, RNA-based biomolecules hold expanded promise for their diagnostic, prognostic and therapeutic applicability in various diseases, including cancers and infectious diseases. Detection of gene fusions and differential expression of known disease-causing transcripts by RNA-seq represent some of the most immediate opportunities. However, it is the diversity of RNA species detected through RNA-seq that holds new promise for the multi-faceted clinical applicability of RNA-based measures, including the potential of extracellular RNAs as non-invasive diagnostic indicators of disease. Ongoing efforts towards the establishment of benchmark standards, assay optimization for clinical conditions and demonstration of assay reproducibility are required to expand the clinical utility of RNA-seq. © 2016 Nature Publishing Group, a division of Macmillan Publishers Limited. All Rights Reserved.


Patent
Translational Genomics Research Institute | Date: 2013-05-07

This disclosure provides tyrosine kinase protein and nucleic acid variants, particularly FGFR2 variants, which are linked to drug resistance. The disclosure further provides methods of diagnosis and theranosis, using these molecules and fragments thereof, and kits for employing these methods and compositions.


Patent
Translational Genomics Research Institute | Date: 2014-03-14

The invention encompasses methods and kits used in the identification of invasive glioblastoma based upon the expression of Akt1, Akt2, and Akt3. The methods and kits also allow prediction of disease outcome and staging of patients with regard to therapy.

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