Diagnostic Radiology

Cleveland, OH, United States

Diagnostic Radiology

Cleveland, OH, United States
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News Article | May 23, 2017
Site: www.prweb.com

Radsource, a leader in MRI interpretation services and provider of Picture Archiving and Communication Systems (ProtonPACS), is pleased to announce the addition of its latest radiologist, Benjamin A. Eyer, M.D. Dr. Eyer is a highly skilled radiologist who specializes in musculoskeletal and spine imaging. He graduated Magna Cum Laude from the University of San Diego and went on to earn his medical degree at the Medical College of Wisconsin. Dr. Eyer’s post-graduate training included an internship in preliminary medicine at Weiss Memorial Hospital, a University of Chicago-affiliated program. He then completed his residency in Diagnostic Radiology at the University of Southern California. After his residency, he completed a fellowship in Musculoskeletal and Spine Imaging with Dr. John Crues of Radnet. Subsequently, Dr. Eyer worked at Radnet for seven years as a musculoskeletal radiologist, including serving as Medical Director of one of their imaging centers in the Los Angeles area. Dr. Eyer is the recipient of numerous academic honors, including membership in the Alpha Omega Alpha Honor Medical Society, the Medical College of Wisconsin Academic Achievement Scholarship, and the Society of Thoracic Radiology President’s Award for best scientific paper. He has contributed to the radiology literature with numerous textbook chapters and articles in peer-reviewed journals, and has provided multiple presentations at national radiology meetings. Dr. Eyer lives in Manhattan Beach, California with his wife, who is also a diagnostic radiologist. When not practicing radiology, he enjoys outdoor activities including skiing, surfing and golf, and spending time with their two children. About Radsource Founded in 2001, Radsource has become one of the largest and most respected providers of subspecialized MRI interpretations to the outpatient orthopaedic and neurological markets. Based on our success in subspecialized interpretation, Radsource has developed a unique understanding of the functional and operational needs of PACS. The result is ProtonPACS, our advanced, full service solution for picture archiving and communication.


HOUSTON - Select breast cancer patients who achieved pathologic complete response (pCR) after chemotherapy may be able to avoid follow-up breast and lymph node, or axillary, surgery, according to new findings from researchers at The University of Texas MD Anderson Cancer Center. The study, published today in JAMA Surgery, identifies the exceptional responders who are at lowest risk for local metastases and thereby are candidates for less invasive treatment options. Worldwide, triple negative (TN) and HER-2 positive breast cancers account for about 370,000 women diagnosed annually, explains Henry Kuerer, M.D., Ph.D., professor of Breast Surgical Oncology and the study's principal investigator. In as many as 60 percent of these patients, neoadjuvant chemotherapy (NCT), given as the primary treatment, can result in pCR, or absence of residual disease, in both the breast and axillary lymph nodes. "This high rate of pCR naturally raises the question of whether breast surgery is required for all patients, particularly those who will receive adjuvant radiation," said Kuerer. "An important secondary question in these exceptional responders is whether we can also omit axillary surgery to remove lymph nodes." In order to determine those patients for whom surgery may be avoided, it is necessary to accurately identify those with a pCR following NCT. However, standard breast imaging techniques were not capable of accurately predicting residual disease. Recently Kuerer completed a clinical feasibility trial investigating the utility of image-guided biopsies to predict breast pCR. The preliminary results of that study, originally presented at the 2016 San Antonio Breast Cancer Symposium, revealed the technique to have 100 percent accuracy and 100 percent predictive value for determining residual disease following NCT. "By doing the same image-guided, percutaneous needle biopsies after NCT that we do at time of diagnosis, our preliminary research revealed we can accurately predict which women will have a complete response," said Kuerer. "With that knowledge, there's an obligation to test whether no surgery, or 'ultimate breast conserving therapy,' is safe." The current study sought to determine if patients achieving a pCR following NCT also may avoid axillary surgery for nodal metastases in addition to breast surgery. The prospective single-institution cohort study enrolled 527 women with T1-T2/N0-N1 stage triple negative (264) or HER-2 positive (263) breast cancer treated at MD Anderson between January 2010 and December 2014. All participants received NCT followed by standard breast and nodal surgery. Clinical staging was determined prior to NCT by core biopsy or fine-needle aspiration, followed by clinical examination, mammography and ultrasound of the breast and axilla. Breast pCR was defined as no residual disease at the time of surgery. Axillary pCR was defined as no evidence of metastatic carcinoma. Overall, 36.6 percent of patients achieved a breast pCR, with a slightly higher rate among TN (37.5 percent) than HER-2 positive (35.7 percent) patients. Of patients presenting with N1 disease, 77 (32.5 percent) achieved a breast pCR compared to 116 of those with N0 stage disease (40 percent). All 116 N0 stage patients with a breast pCR also achieved axillary pCR. Similarly, 89.6 percent of patients with N1 disease and a breast pCR were also free of nodal metastases. Overall, there were no significant differences between patients with TN and HER-2 positive breast cancers. "In our study, patients achieving a breast pCR were more than seven times less likely to have residual nodal disease, with even more pronounced differences among patients presenting with N0 stage disease," said Audree Tadros, M.D., fellow in Breast Surgical Oncology and the study's lead author. "Based upon these findings, we anticipate women with initial node-negative disease may avoid breast and axillary surgery if they achieve a pCR after NCT and move on to standard radiotherapy." To investigate the efficacy and safety of this approach, MD Anderson's Institutional Review Board has approved a Phase II clinical trial, which is now open at MD Anderson and will soon open within the MD Anderson Cancer Network®. The study is enrolling women with Stage I and II HER2-positive and TN breast cancer. Study participants who achieve image-guided, biopsy-proved pCR after NCT will undergo whole-breast radiation, without surgery. In those with initial, ultrasound-proven node-negative disease, axillary surgery will also be avoided. The trial will be the first using image-guided biopsies in this setting and not include surgery. "There is an urgency to test whether surgery is needed. In conversations with my patients, many express concerns about overtreatment. They want the most personalized care with as minimal treatment as possible," said Kuerer. "If some women are able to avoid unnecessary surgery, it would be groundbreaking for patients - both physically and psychologically." Additional authors on the all-MD Anderson study include: Dalliah M. Black, M.D., Anthony Lucci Jr., M.D., Abigail S. Caudle, M.D., Sara M. DeSnyder, M.D., Mediget Teshomem, M.D., Makesha Miggins, M.D., Rosa F. Hwang, M.D., and Kelly K. Hunt, M.D., all of Breast Surgical Oncology; Wei T. Yang, M.D, Gaiane M. Rauch, M.D., Ph.D., Beatriz E. Adrada, M.D., and Tanya Moseley, M.D., all of Diagnostic Radiology; Savitri Krishnamurthy, M.D., Pathology; Benjamin D. Smith, M.D., Radiation Oncology; and Vicente Valero, M.D., and Carlos H. Barcenas, M.D., Breast Medical Oncology. The study was financially supported by the PH and Fay Etta Robinson Distinguished Professorship in Cancer Research and a Cancer Center Support Grant from the National Institutes of Health (CA16672).


Immunotherapy fights cancer by supercharging the immune system's natural defenses or contributing additional immune elements that can help the body kill cancer cells. In recent decades, immunotherapy has become an important tool in treating a wide range of cancers, including breast cancer, melanoma and leukemia. But alongside its successes, scientists have discovered that immunotherapy sometimes has powerful—even fatal—side-effects. Much still needs to be learned about how the immune system fights cancer, and in this area, supercomputers play an important role. Not every immune therapy works the same on every patient. Differences in an individual's immune system may mean one treatment is more appropriate than another. Furthermore, tweaking one's system might heighten the efficacy of certain treatments. Researchers from Wake Forest School of Medicine and Zhejiang University in China developed a novel mathematical model to explore the interactions between prostate tumors and common immunotherapy approaches, individually and in combination. In a study published in February 2016 in Nature Scientific Reports, they used their model to predict how prostate cancer would react to four common immunotherapies: - Androgen deprivation therapy—used to control prostate cancer cell growth by suppressing or blocking the production and action the hormone androgen in men; - Vaccines—which train the immune system to recognize and destroy harmful substances; - Treg depletion—where the subpopulation of T cells, which modulate the immune system, are reduced to increase the efficacy of immunotherapy treatments; and - IL-2 neutralization—which disables interleukin, a type of signaling molecule in the immune system. To study the systematic effects of these four treatments, the researchers incorporated data from animal studies into their complex mathematical models and simulated tumor responses to the treatments using the Stampede supercomputer at the Texas Advanced Computing Center (TACC). "We do a lot of modeling which relies on millions of simulations," said Jing Su, a researcher at the Center for Bioinformatics and Systems Biology at Wake Forest School of Medicine and assistant professor in the Department of Diagnostic Radiology. "To get a reliable result, we have to repeat each computation at least 100 times. We want to explore the combinations and effects and different conditions and their results." The researchers found that the depletion of T Cells and the neutralization of Interleukin 2 can have a stronger effect when combined with androgen deprivation therapy and vaccines. The study highlights a potential therapeutic strategy that may manage prostate tumor growth more effectively. It also provides a framework for studying tumor-related immune mechanisms and the selection of therapeutic regimens in other types of cancer. In separate work published in Nature Scientific Reports in April 2017, Zhou and collaborators from Wake Forest School of Medicine used TACC's high performance computing resources to predict how ribonucleic acids (RNA) and proteins interact with greater accuracy than previous methods. RNA-protein interactions are import to the function of RNAs, especially in the case of long noncoding RNAs (lncRNAs), which play essential roles in a variety of biological processes, including cancer development. In their study, they first performed an analysis of 1,342 RNA-protein interacting complexes from the Nucleic Acid Database and identified diverse interface properties between them, including both binding and non-binding sites. They then used a three-step method to predict the interacting regions between them using both the sequences and structures of the proteins and RNAs. Compared with existing methods, which use only sequences, the model was found to be more accurate and outperformed the leading current method by 20 percent. The computationally-intensive work represents the first approach that uses local conformations to analyze and predict the binding sites of protein, RNA and RNA-protein interacting pairs. "TACC provides an important assistance for discovering clinically meaningful and actionable knowledge across highly heterogeneous biomedical big data sets," Zhou said. [The research was supported by the National Institutes of Health (U01HL111560 and R01LM010185).] Biological agents used in immunotherapy—including those that target a specific tumor pathway, aim for DNA repair, or stimulate the immune system to attack a tumor—function differently from radiation and chemotherapy. Whereas toxicity and efficacy typically increase with the dose level for cell-destroying chemicals or x-rays, this relationship may not be true for biological agents. Specifically, toxicity may increase at low dose levels and then plateau at higher dose levels when the biological agent has reached a saturation level in the body. Efficacy may even decrease at higher dose levels. Because traditional dose-finding designs, which focus on identifying the maximum tolerated dose, are not suitable for trials of biological agents, novel designs that consider both the toxicity and efficacy of these agents are imperative. Chunyan Cai, assistant professor of biostatistics at UT Health Science Center (UTHSC)'s McGovern Medical School, uses TACC systems to design new kinds of dose-finding trials for combinations of immunotherapies. Writing in the Journal of the Royal Statistics Society Series C (Applied Statistics), Cai and her collaborators, Ying Yuan, and Yuan Ji, described efforts to identify biologically optimal dose combinations (BODC) for agents that target the PI3K/AKT/mTOR signaling pathway, which has been associated with several genetic aberrations related to the promotion of cancer. "Our research is motivated by a drug combination trial at the MD Anderson Cancer Center for patients diagnosed with relapsed lymphoma," Cai said. "The trial combined two novel biological agents that target two different components in the PI3K/AKT/mTOR signaling pathway." Both agents individually demonstrated the ability to partially inhibit the signaling pathway and provide therapeutic value. By combining these two agents, the investigators expected to obtain a more complete inhibition of the PI3K/AKT/mTOR pathway, and thereby achieve better treatment responses. The trial investigated the combinations of four dose levels of agent A with four dose levels of agent B, resulting in 16 dose combinations. The goal was to find the biologically optimal dose combination among those possibilities. Cai and her colleagues introduced a dose-finding trial design that explicitly accounted for the unique properties of biological agents. "Our design is conducted in two stages," she said. "In stage one, we escalate doses along the diagonal of the dose combination matrix as a fast exploration of the dosing space. In stage two, on the basis of the observed toxicity and efficacy data from stages one, we continuously update the posterior estimates of toxicity and efficacy and assign patients to the most appropriate dose combination." They investigated six different dose-toxicity and dose-efficacy scenarios and carried out 2,000 simulated trials for each of the designs using the Lonestar supercomputer at TACC. The simulations compared the percentage of the biologically optimal dose combination (BODC), the percentage of patients allocated to the BODC, the average efficacy rate, the number of patients assigned to over-toxic doses, and the total numbers of patients assigned in stage I and stage II of the trial. The optimal dose-finding design, they discovered, gives higher priority to trying new doses in the early stage of the trial, and toward the end of the trial assigns patients to the most effective dose that is safe. "Extensive simulation studies show that the design proposed has desirable operating characteristics in identifying the biologically optimal dose combination under various patterns of dose-toxicity and dose-efficacy relationships," she concluded. [The research was supported by the National Cancer Institute (Award Number R01 CA154591) and the National Institutes of Health's Clinical and Translational Science Award grant (UL1 TR000371).] Data-driven research and clinical dosing studies are essential for understanding how the immune system responds to treatments and determining the proper doses of biological agents. Also, critical, however, are mechanisms that bring together the research of a whole community—to share, compare and integrate disparate research findings. The VDJServer, which launched last year, serves as such a resource. The server enables researchers to analyze high-throughput immune repertoire sequencing data over the web using the high-performance computing resources available at TACC. Repertoire sequencing investigates the collection of trans-membrane antigen-receptor proteins located on the surface of T and B cells—white blood cells that play a key role in the human immune response. A form of next-generation genetic analysis, repertoire sequencing has transformed the field of immunotherapy, enabling quantitative analyses that help scientists understand the function of immunity in health and disease. VDJServer was developed by bioinformaticians and immunologists from UT Southwestern Medical Center, J. Craig Venter Institute and Yale University in partnership with computational experts at TACC. "VDJServer provides access to sophisticated analysis software and TACC's high-performance computing resources through an intuitive interface designed for users who are primarily biologists and clinicians," said project leader Lindsay Cowell, an associate professor of Clinical Sciences at UT Southwestern Medical Center, whose group developed the software at the core of VDJServer. "In addition, we provide platforms for sharing data, analysis results, and analysis pipelines," she said. "Access to these analyses and resource-sharing accelerates research and enables insights that wouldn't be possible without the opportunity for data integration." Researchers can upload B- and T-cell-receptor data and tap into TACC's computing power through the site to perform data-driven studies. Immune repertoire analysis is relevant in many contexts, including cancer immunology. One example of this type of research is a collaboration between the Cowell group and Marco Davila, a cancer researcher at the Moffitt Cancer Center. Together they are developing chimeric antigen receptors - genetically engineered receptors enabling T-cells to express receptors with the antigen specificity of an antibody. These receptors would allow the T-cells to recognize and kill cancer cells. "The team is using VDJServer to perform bioinformatics analyses to identify appropriate antibodies that may target specific cancer types," explained Cowell. "That's followed up with experimental validation to determine that the antibodies are appropriate." VDJServer speeds up scientists' understanding of the immune system and help cultivate reproducible findings, according to Matt Vaughn, TACC's Director of Life Science Computing. "Immunotherapy is a relatively young field and the computational tools are emerging alongside with knowledge of the domain," Vaughn said. "Community-oriented efforts like VDJServer are important because they provide a centralized workbench where best of breed algorithms and workflows can be used much more quickly than if they were released just as source code and at the end of a long publication cycle. They're also available democratically: anyone can use software at VDJServer regardless of how computationally experienced they are." Whether in support of population-level immune response studies, clinical dosing trials or community-wide efforts like VDJServer, TACC's advanced computing resources are helping scientists put the immune system to work to better fight cancer. Explore further: Immunotherapy for glioblastoma well tolerated; survival gains observed More information: Jiesi Luo et al, RPI-Bind: a structure-based method for accurate identification of RNA-protein binding sites, Scientific Reports (2017). DOI: 10.1038/s41598-017-00795-4 Huaidong Chen et al. Relational Network for Knowledge Discovery through Heterogeneous Biomedical and Clinical Features, Scientific Reports (2016). DOI: 10.1038/srep29915


News Article | May 17, 2017
Site: www.sciencedaily.com

The body has a natural way of fighting cancer -- it's called the immune system, and it is tuned to defend our cells against outside infections and internal disorder. But occasionally, it needs a helping hand. Immunotherapy fights cancer by supercharging the immune system's natural defenses or contributing additional immune elements that can help the body kill cancer cells. In recent decades, immunotherapy has become an important tool in treating a wide range of cancers, including breast cancer, melanoma and leukemia. But alongside its successes, scientists have discovered that immunotherapy sometimes has powerful -- even fatal -- side-effects. Much still needs to be learned about how the immune system fights cancer, and in this area, supercomputers play an important role. Not every immune therapy works the same on every patient. Differences in an individual's immune system may mean one treatment is more appropriate than another. Furthermore, tweaking one's system might heighten the efficacy of certain treatments. Researchers from Wake Forest School of Medicine and Zhejiang University in China developed a novel mathematical model to explore the interactions between prostate tumors and common immunotherapy approaches, individually and in combination. In a study published in February 2016 in Nature Scientific Reports, they used their model to predict how prostate cancer would react to four common immunotherapies: To study the systematic effects of these four treatments, the researchers incorporated data from animal studies into their complex mathematical models and simulated tumor responses to the treatments using the Stampede supercomputer at the Texas Advanced Computing Center (TACC). "We do a lot of modeling which relies on millions of simulations," said Jing Su, a researcher at the Center for Bioinformatics and Systems Biology at Wake Forest School of Medicine and assistant professor in the Department of Diagnostic Radiology. "To get a reliable result, we have to repeat each computation at least 100 times. We want to explore the combinations and effects and different conditions and their results." The researchers found that the depletion of T Cells and the neutralization of Interleukin 2 can have a stronger effect when combined with androgen deprivation therapy and vaccines. The study highlights a potential therapeutic strategy that may manage prostate tumor growth more effectively. It also provides a framework for studying tumor-related immune mechanisms and the selection of therapeutic regimens in other types of cancer. In separate work published in Nature Scientific Reports in April 2017, Zhou and collaborators from Wake Forest School of Medicine used TACC's high performance computing resources to predict how ribonucleic acids (RNA) and proteins interact with greater accuracy than previous methods. RNA-protein interactions are import to the function of RNAs, especially in the case of long noncoding RNAs (lncRNAs), which play essential roles in a variety of biological processes, including cancer development. In their study, they first performed an analysis of 1,342 RNA-protein interacting complexes from the Nucleic Acid Database and identified diverse interface properties between them, including both binding and non-binding sites. They then used a three-step method to predict the interacting regions between them using both the sequences and structures of the proteins and RNAs. Compared with existing methods, which use only sequences, the model was found to be more accurate and outperformed the leading current method by 20 percent. The computationally-intensive work represents the first approach that uses local conformations to analyze and predict the binding sites of protein, RNA and RNA-protein interacting pairs. "TACC provides an important assistance for discovering clinically meaningful and actionable knowledge across highly heterogeneous biomedical big data sets," Zhou said. [The research was supported by the National Institutes of Health (U01HL111560 and R01LM010185).] Biological agents used in immunotherapy -- including those that target a specific tumor pathway, aim for DNA repair, or stimulate the immune system to attack a tumor -- function differently from radiation and chemotherapy. Whereas toxicity and efficacy typically increase with the dose level for cell-destroying chemicals or x-rays, this relationship may not be true for biological agents. Specifically, toxicity may increase at low dose levels and then plateau at higher dose levels when the biological agent has reached a saturation level in the body. Efficacy may even decrease at higher dose levels. Because traditional dose-finding designs, which focus on identifying the maximum tolerated dose, are not suitable for trials of biological agents, novel designs that consider both the toxicity and efficacy of these agents are imperative. Chunyan Cai, assistant professor of biostatistics at UT Health Science Center (UTHSC)'s McGovern Medical School, uses TACC systems to design new kinds of dose-finding trials for combinations of immunotherapies. Writing in the Journal of the Royal Statistics Society Series C (Applied Statistics), Cai and her collaborators, Ying Yuan, and Yuan Ji, described efforts to identify biologically optimal dose combinations (BODC) for agents that target the PI3K/AKT/mTOR signaling pathway, which has been associated with several genetic aberrations related to the promotion of cancer. "Our research is motivated by a drug combination trial at the MD Anderson Cancer Center for patients diagnosed with relapsed lymphoma," Cai said. "The trial combined two novel biological agents that target two different components in the PI3K/AKT/mTOR signaling pathway." Both agents individually demonstrated the ability to partially inhibit the signaling pathway and provide therapeutic value. By combining these two agents, the investigators expected to obtain a more complete inhibition of the PI3K/AKT/mTOR pathway, and thereby achieve better treatment responses. The trial investigated the combinations of four dose levels of agent A with four dose levels of agent B, resulting in 16 dose combinations. The goal was to find the biologically optimal dose combination among those possibilities. Cai and her colleagues introduced a dose-finding trial design that explicitly accounted for the unique properties of biological agents. "Our design is conducted in two stages," she said. "In stage one, we escalate doses along the diagonal of the dose combination matrix as a fast exploration of the dosing space. In stage two, on the basis of the observed toxicity and efficacy data from stages one, we continuously update the posterior estimates of toxicity and efficacy and assign patients to the most appropriate dose combination." They investigated six different dose-toxicity and dose-efficacy scenarios and carried out 2,000 simulated trials for each of the designs using the Lonestar supercomputer at TACC. The simulations compared the percentage of the biologically optimal dose combination (BODC), the percentage of patients allocated to the BODC, the average efficacy rate, the number of patients assigned to over-toxic doses, and the total numbers of patients assigned in stage I and stage II of the trial. The optimal dose-finding design, they discovered, gives higher priority to trying new doses in the early stage of the trial, and toward the end of the trial assigns patients to the most effective dose that is safe. "Extensive simulation studies show that the design proposed has desirable operating characteristics in identifying the biologically optimal dose combination under various patterns of dose-toxicity and dose-efficacy relationships," she concluded. [The research was supported by the National Cancer Institute (Award Number R01 CA154591) and the National Institutes of Health's Clinical and Translational Science Award grant (UL1 TR000371).] Data-driven research and clinical dosing studies are essential for understanding how the immune system responds to treatments and determining the proper doses of biological agents. Also, critical, however, are mechanisms that bring together the research of a whole community -- to share, compare and integrate disparate research findings. The VDJServer, which launched last year, serves as such a resource. The server enables researchers to analyze high-throughput immune repertoire sequencing data over the web using the high-performance computing resources available at TACC. Repertoire sequencing investigates the collection of trans-membrane antigen-receptor proteins located on the surface of T and B cells -- white blood cells that play a key role in the human immune response. A form of next-generation genetic analysis, repertoire sequencing has transformed the field of immunotherapy, enabling quantitative analyses that help scientists understand the function of immunity in health and disease. VDJServer was developed by bioinformaticians and immunologists from UT Southwestern Medical Center, J. Craig Venter Institute and Yale University in partnership with computational experts at TACC. "VDJServer provides access to sophisticated analysis software and TACC's high-performance computing resources through an intuitive interface designed for users who are primarily biologists and clinicians," said project leader Lindsay Cowell, an associate professor of Clinical Sciences at UT Southwestern Medical Center, whose group developed the software at the core of VDJServer. "In addition, we provide platforms for sharing data, analysis results, and analysis pipelines," she said. "Access to these analyses and resource-sharing accelerates research and enables insights that wouldn't be possible without the opportunity for data integration." Researchers can upload B- and T-cell-receptor data and tap into TACC's computing power through the site to perform data-driven studies. Immune repertoire analysis is relevant in many contexts, including cancer immunology. One example of this type of research is a collaboration between the Cowell group and Marco Davila, a cancer researcher at the Moffitt Cancer Center. Together they are developing chimeric antigen receptors -- genetically engineered receptors enabling T-cells to express receptors with the antigen specificity of an antibody. These receptors would allow the T-cells to recognize and kill cancer cells. "The team is using VDJServer to perform bioinformatics analyses to identify appropriate antibodies that may target specific cancer types," explained Cowell. "That's followed up with experimental validation to determine that the antibodies are appropriate." VDJServer speeds up scientists' understanding of the immune system and help cultivate reproducible findings, according to Matt Vaughn, TACC's Director of Life Science Computing. "Immunotherapy is a relatively young field and the computational tools are emerging alongside with knowledge of the domain," Vaughn said. "Community-oriented efforts like VDJServer are important because they provide a centralized workbench where best of breed algorithms and workflows can be used much more quickly than if they were released just as source code and at the end of a long publication cycle. They're also available democratically: anyone can use software at VDJServer regardless of how computationally experienced they are." Whether in support of population-level immune response studies, clinical dosing trials or community-wide efforts like VDJServer, TACC's advanced computing resources are helping scientists put the immune system to work to better fight cancer. [VDJServer is supported by a National Institute of Allergy and Infectious Diseases research grant (#1R01A1097403)]


News Article | May 17, 2017
Site: www.eurekalert.org

The body has a natural way of fighting cancer - it's called the immune system, and it is tuned to defend our cells against outside infections and internal disorder. But occasionally, it needs a helping hand. Immunotherapy fights cancer by supercharging the immune system's natural defenses or contributing additional immune elements that can help the body kill cancer cells. In recent decades, immunotherapy has become an important tool in treating a wide range of cancers, including breast cancer, melanoma and leukemia. But alongside its successes, scientists have discovered that immunotherapy sometimes has powerful -- even fatal -- side-effects. Much still needs to be learned about how the immune system fights cancer, and in this area, supercomputers play an important role. Not every immune therapy works the same on every patient. Differences in an individual's immune system may mean one treatment is more appropriate than another. Furthermore, tweaking one's system might heighten the efficacy of certain treatments. Researchers from Wake Forest School of Medicine and Zhejiang University in China developed a novel mathematical model to explore the interactions between prostate tumors and common immunotherapy approaches, individually and in combination. In a study published in February 2016 in Nature Scientific Reports, they used their model to predict how prostate cancer would react to four common immunotherapies: To study the systematic effects of these four treatments, the researchers incorporated data from animal studies into their complex mathematical models and simulated tumor responses to the treatments using the Stampede supercomputer at the Texas Advanced Computing Center (TACC). "We do a lot of modeling which relies on millions of simulations," said Jing Su, a researcher at the Center for Bioinformatics and Systems Biology at Wake Forest School of Medicine and assistant professor in the Department of Diagnostic Radiology. "To get a reliable result, we have to repeat each computation at least 100 times. We want to explore the combinations and effects and different conditions and their results." The researchers found that the depletion of T Cells and the neutralization of Interleukin 2 can have a stronger effect when combined with androgen deprivation therapy and vaccines. The study highlights a potential therapeutic strategy that may manage prostate tumor growth more effectively. It also provides a framework for studying tumor-related immune mechanisms and the selection of therapeutic regimens in other types of cancer. In separate work published in Nature Scientific Reports in April 2017, Zhou and collaborators from Wake Forest School of Medicine used TACC's high performance computing resources to predict how ribonucleic acids (RNA) and proteins interact with greater accuracy than previous methods. RNA-protein interactions are import to the function of RNAs, especially in the case of long noncoding RNAs (lncRNAs), which play essential roles in a variety of biological processes, including cancer development. In their study, they first performed an analysis of 1,342 RNA-protein interacting complexes from the Nucleic Acid Database and identified diverse interface properties between them, including both binding and non-binding sites. They then used a three-step method to predict the interacting regions between them using both the sequences and structures of the proteins and RNAs. Compared with existing methods, which use only sequences, the model was found to be more accurate and outperformed the leading current method by 20 percent. The computationally-intensive work represents the first approach that uses local conformations to analyze and predict the binding sites of protein, RNA and RNA-protein interacting pairs. "TACC provides an important assistance for discovering clinically meaningful and actionable knowledge across highly heterogeneous biomedical big data sets," Zhou said. [The research was supported by the National Institutes of Health (U01HL111560 and R01LM010185).] Biological agents used in immunotherapy -- including those that target a specific tumor pathway, aim for DNA repair, or stimulate the immune system to attack a tumor -- function differently from radiation and chemotherapy. Whereas toxicity and efficacy typically increase with the dose level for cell-destroying chemicals or x-rays, this relationship may not be true for biological agents. Specifically, toxicity may increase at low dose levels and then plateau at higher dose levels when the biological agent has reached a saturation level in the body. Efficacy may even decrease at higher dose levels. Because traditional dose-finding designs, which focus on identifying the maximum tolerated dose, are not suitable for trials of biological agents, novel designs that consider both the toxicity and efficacy of these agents are imperative. Chunyan Cai, assistant professor of biostatistics at UT Health Science Center (UTHSC)'s McGovern Medical School, uses TACC systems to design new kinds of dose-finding trials for combinations of immunotherapies. Writing in the Journal of the Royal Statistics Society Series C (Applied Statistics), Cai and her collaborators, Ying Yuan, and Yuan Ji, described efforts to identify biologically optimal dose combinations (BODC) for agents that target the PI3K/AKT/mTOR signaling pathway, which has been associated with several genetic aberrations related to the promotion of cancer. "Our research is motivated by a drug combination trial at the MD Anderson Cancer Center for patients diagnosed with relapsed lymphoma," Cai said. "The trial combined two novel biological agents that target two different components in the PI3K/AKT/mTOR signaling pathway." Both agents individually demonstrated the ability to partially inhibit the signaling pathway and provide therapeutic value. By combining these two agents, the investigators expected to obtain a more complete inhibition of the PI3K/AKT/mTOR pathway, and thereby achieve better treatment responses. The trial investigated the combinations of four dose levels of agent A with four dose levels of agent B, resulting in 16 dose combinations. The goal was to find the biologically optimal dose combination among those possibilities. Cai and her colleagues introduced a dose-finding trial design that explicitly accounted for the unique properties of biological agents. "Our design is conducted in two stages," she said. "In stage one, we escalate doses along the diagonal of the dose combination matrix as a fast exploration of the dosing space. In stage two, on the basis of the observed toxicity and efficacy data from stages one, we continuously update the posterior estimates of toxicity and efficacy and assign patients to the most appropriate dose combination." They investigated six different dose-toxicity and dose-efficacy scenarios and carried out 2,000 simulated trials for each of the designs using the Lonestar supercomputer at TACC. The simulations compared the percentage of the biologically optimal dose combination (BODC), the percentage of patients allocated to the BODC, the average efficacy rate, the number of patients assigned to over-toxic doses, and the total numbers of patients assigned in stage I and stage II of the trial. The optimal dose-finding design, they discovered, gives higher priority to trying new doses in the early stage of the trial, and toward the end of the trial assigns patients to the most effective dose that is safe. "Extensive simulation studies show that the design proposed has desirable operating characteristics in identifying the biologically optimal dose combination under various patterns of dose-toxicity and dose-efficacy relationships," she concluded. [The research was supported by the National Cancer Institute (Award Number R01 CA154591) and the National Institutes of Health's Clinical and Translational Science Award grant (UL1 TR000371).] Data-driven research and clinical dosing studies are essential for understanding how the immune system responds to treatments and determining the proper doses of biological agents. Also, critical, however, are mechanisms that bring together the research of a whole community -- to share, compare and integrate disparate research findings. The VDJServer, which launched last year, serves as such a resource. The server enables researchers to analyze high-throughput immune repertoire sequencing data over the web using the high-performance computing resources available at TACC. Repertoire sequencing investigates the collection of trans-membrane antigen-receptor proteins located on the surface of T and B cells -- white blood cells that play a key role in the human immune response. A form of next-generation genetic analysis, repertoire sequencing has transformed the field of immunotherapy, enabling quantitative analyses that help scientists understand the function of immunity in health and disease. VDJServer was developed by bioinformaticians and immunologists from UT Southwestern Medical Center, J. Craig Venter Institute and Yale University in partnership with computational experts at TACC. "VDJServer provides access to sophisticated analysis software and TACC's high-performance computing resources through an intuitive interface designed for users who are primarily biologists and clinicians," said project leader Lindsay Cowell, an associate professor of Clinical Sciences at UT Southwestern Medical Center, whose group developed the software at the core of VDJServer. "In addition, we provide platforms for sharing data, analysis results, and analysis pipelines," she said. "Access to these analyses and resource-sharing accelerates research and enables insights that wouldn't be possible without the opportunity for data integration." Researchers can upload B- and T-cell-receptor data and tap into TACC's computing power through the site to perform data-driven studies. Immune repertoire analysis is relevant in many contexts, including cancer immunology. One example of this type of research is a collaboration between the Cowell group and Marco Davila, a cancer researcher at the Moffitt Cancer Center. Together they are developing chimeric antigen receptors - genetically engineered receptors enabling T-cells to express receptors with the antigen specificity of an antibody. These receptors would allow the T-cells to recognize and kill cancer cells. "The team is using VDJServer to perform bioinformatics analyses to identify appropriate antibodies that may target specific cancer types," explained Cowell. "That's followed up with experimental validation to determine that the antibodies are appropriate." VDJServer speeds up scientists' understanding of the immune system and help cultivate reproducible findings, according to Matt Vaughn, TACC's Director of Life Science Computing. "Immunotherapy is a relatively young field and the computational tools are emerging alongside with knowledge of the domain," Vaughn said. "Community-oriented efforts like VDJServer are important because they provide a centralized workbench where best of breed algorithms and workflows can be used much more quickly than if they were released just as source code and at the end of a long publication cycle. They're also available democratically: anyone can use software at VDJServer regardless of how computationally experienced they are." Whether in support of population-level immune response studies, clinical dosing trials or community-wide efforts like VDJServer, TACC's advanced computing resources are helping scientists put the immune system to work to better fight cancer. [VDJServer is supported by a National Institute of Allergy and Infectious Diseases research grant (#1R01A1097403)]


News Article | May 23, 2017
Site: www.eurekalert.org

Washington, D.C. - According to a study presented at the American College of Radiology annual meeting, the use of follow-up imaging is significantly less when initial emergency department (ED) ultrasound examinations are interpreted by a radiologist than a nonradiologist. The work, conducted by researchers at the Harvey L. Neiman Health Policy Institute, was named an ACR 2017 Gold Merit Abstract Award recipient in the Advocacy, Economics and Health Policy category. The researchers used 5 percent Medicare data files from 2009 through 2014 to identify patients in the ED setting where the patient underwent an initial ultrasound examination. They determined whether the initial ultrasound was interpreted by a radiologist or a nonradiologist and then summed all additional imaging events occurring within 7, 14 and 30 days of each initial ED ultrasound. The differences in the mean number of downstream imaging procedures for radiologists and nonradiologists were calculated. "We found that radiologists still interpret that vast majority of ED US. Of 200,357 ED ultrasound events, 81.6 percent were interpreted by radiologists and 36,788 by nonradiologists," said Van Carroll, MD, MPH, a radiology resident at the Brookwood Baptist Health Diagnostic Radiology Residency Program. Carroll and his colleagues discovered that across all study years, ED patients with ultrasounds interpreted by nonradiologists underwent 1.08 more imaging studies within seven days, 1.22 more imaging studies within 14 days, and 1.34 within 30 days of the initial ED ultrasound event. For both radiologists and nonradiologists, the volume of subsequent imaging decreased over time. Despite that decline, differences in follow-up imaging between radiologists and nonradiologists persisted over time. "While the causes of this difference are not clear, the previously documented higher use of limited ultrasound examinations by nonradiologists or a lack of confidence in the interpretations of nonradiologists may potentially explain this increase in follow-up imaging examinations," said Bibb Allen Jr., MD, FACR, a co-author and chair of the Neiman Institute advisory board. Allen added that further analysis will be necessary to fully elucidate the causes of the discrepancy since resource use will be a critical metric in federal health care reform. "Since emerging federal health reform includes cost and resource use as part of the Medicare Quality Payment Program, emerging patterns of care such as point of care ultrasound should include resource use in outcomes evaluation. Efforts toward improving documentation of findings and archiving of images as well as development of more robust quality assurance programs could all be beneficial." ACR 2017 - The Crossroads of Radiology is taking place through May 25 at the Washington Marriott Wardman Park Hotel in Washington, D.C. Visit the ACR 2017 website to view the full abstract. To arrange an interview with a Neiman Institute spokesperson, contact Nicole Racadag at (703) 716-7559 or nracadag@neimanhpi.org. The Harvey L. Neiman Health Policy Institute is one of the nation's leading medical imaging socioeconomic research organizations. The Neiman Institute studies the role and value of radiology and radiologists in evolving health care delivery and payment systems and the impact of medical imaging on the cost, quality, safety and efficiency of health care. Visit us at http://www. and follow us on Twitter, LinkedIn and Facebook.

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