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  • richardmitnick 9:45 am on February 19, 2015 Permalink | Reply
    Tags: , Cancer,   

    From U Washington: “Tumor genetics traces cancer cells’ origins” 

    U Washington

    University of Washington

    02.18.2015
    Brigham and Women’s Hospital
    Haley Bridger
    617-525-6383, hbridger@partners.org

    University of Washington
    Leila Gray
    206-685-0381, leilag@uw.edu

    1
    An artists conception of the chromatin packing of DNA (Mary Jo Chmielewski/CellsSixthGrade)

    New possibilities for tracing cancer of unknown origin back to the type of cell in which it began are reported today.

    The approach benefits from the wealth of information being gleaned from epigenomes. The epigenome consists of all the chemical packaging and tags attached to genes in an individual’s complete DNA sequence. While these compounds may regulate gene activity, they do not alter the DNA code.

    By leveraging the epigenome maps produced by the Roadmap Epigenomics Program – a resource of data collected from over 100 cell types – a multi-instutional research team found that the unique genetic landscape of a particular tumor could be used to predict that tumor’s cell type of origin.

    The study provides new insights into the early events that shape a cancer. It also could have important implications for the many patients for whom the originating site of their cancer is unknown.

    The paper, Cell-of-origin chromatin organization shapes the mutational landscape of cancer, is one of several published today in Nature as part of collection reporting the latest advances epigenomics.

    “When people planned the Roadmap Epigenomics Project as a resource focusing on normal cells and tissues, nobody thought about cancer mutations and predicting a cancer’s cell of origin – this wasn’t on anyone’s radar,” said co-senior author Shamil Sunyaev, a research geneticist at Boston’s Brigham and Women’s Hospital, a teaching affiliate of Harvard Medical School. “Our study suggests that we can now predict, specifically for different cancer types, where mutations will happen in a given cancer and what was that cancer’s likely cell of origin based on genomic sequence.”

    Mutations are the driving force behind cancer, but they are not distributed evenly across a cancer cell’s genome. The researchers, made up of a team from the Broad Institute of MIT and Harvard and the University of Washington in Seattle, hypothesized that this variation in the “mutational landscape” might be influenced by chromatin structure, or the way that DNA is packaged, which varies widely from cell type to cell type.

    The National Institutes of Health Common Fund’s Roadmap Epigenomics Program, which set out to chart chromatin features from a variety of tissue types and cell types, gave the researchers a means to test this hypothesis. They looked to see how the genomic sequence of cancer cells corresponded with the chromatin structure of different normal cell types, which is highly characteristic for each cell type. The research team investigated samples from a diverse range of cancer types including myeloma, colon cancer, brain cancer and more. What they found was unexpected: the variation in the cancer mutational landscape was very strongly tied to chromatin structure, and because the chromatin structure patterns of cells are so unique, they could use a cancer’s mutation patterns to predict the likely cell type from which it originated.

    About 2% to 5% percent of cancer patients have a cancer whose primary site remains unknown. Cancer of unknown primary origin can pose challenges for treatment decisions, which are often influenced or based on the origin site of cancer.

    “This work could have implications for treatment – frequently, we’re confronted in the clinic with individuals that present with metastatic cancer from an unknown primary site, which makes it very difficult to choose the right initial treatment regimen,” said co-senior author John Stamatoyannopoulos, UW associate professor of genome sciences and medicine, Division of Oncology. “Our finding that the pattern of mutations in the cancer’s genomic sequence is such a strong predictor of its originating cell type thus might help guide such treatment decisions, and could be increasingly feasible as cancer genome sequencing becomes more routine.”

    Combining epigenomic resources and cancer genomic information may also give researchers insights into an early time period in cancer’s development for which little information is currently available. Understanding how chromatin structure shapes the landscape of mutations in a cancer cell could inform researchers’ understanding of the events that first give rise to cancer, as well as how cancers evolve over time.

    “This provides a window into these early, unseen events we never had access to before,” said Sunyaev, who is also an associate member of the Broad Institute and professor at Harvard Medical School. “We can now take advantage of the data that was hidden in these mutational patterns – we don’t fully know how to mine all of that data yet, but it’s likely to hold even more information than what we’ve figured out already.”

    This work was supported by NIH R01 MH101244, U54, CA143874, U01 ES017156, P01 HL53750, U54 HG007010, the Integra-Life Seventh Framework Program (grant number
    315997) and the EMBO Young Investigator Program (Installation grant 1431/2006).

    See the full article here.

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    The University of Washington is one of the world’s preeminent public universities. Our impact on individuals, on our region, and on the world is profound — whether we are launching young people into a boundless future or confronting the grand challenges of our time through undaunted research and scholarship. Ranked number 10 in the world in Shanghai Jiao Tong University rankings and educating more than 54,000 students annually, our students and faculty work together to turn ideas into impact and in the process transform lives and our world. For more about our impact on the world, every day.

    So what defines us — the students, faculty and community members at the University of Washington? Above all, it’s our belief in possibility and our unshakable optimism. It’s a connection to others, both near and far. It’s a hunger that pushes us to tackle challenges and pursue progress. It’s the conviction that together we can create a world of good. Join us on the journey.

     
  • richardmitnick 5:34 am on February 13, 2015 Permalink | Reply
    Tags: , Cancer, , , ,   

    From phys.org: “Gold nanotubes launch a three-pronged attack on cancer cells” 

    physdotorg
    phys.org

    Feb 13, 2015

    1
    Pulsed near infrared light (shown in red) is shone onto a tumour (shown in white) that is encased in blood vessels. The tumour is imaged by multispectral optoacoustic tomography via the ultrasound emission (shown in blue) from the gold nanotubes. Credit: Jing Claussen (Ithera Medical, Germany)

    Scientists have shown that gold nanotubes have many applications in fighting cancer: internal nanoprobes for high-resolution imaging; drug delivery vehicles; and agents for destroying cancer cells.

    The study, published today in the journal Advanced Functional Materials, details the first successful demonstration of the biomedical use of gold nanotubes in a mouse model of human cancer.

    Study lead author Dr Sunjie Ye, who is based in both the School of Physics and Astronomy and the Leeds Institute for Biomedical and Clinical Sciences at the University of Leeds, said: “High recurrence rates of tumours after surgical removal remain a formidable challenge in cancer therapy. Chemo- or radiotherapy is often given following surgery to prevent this, but these treatments cause serious side effects.

    Gold nanotubes – that is, gold nanoparticles with tubular structures that resemble tiny drinking straws – have the potential to enhance the efficacy of these conventional treatments by integrating diagnosis and therapy in one single system.”

    The researchers say that a new technique to control the length of nanotubes underpins the research. By controlling the length, the researchers were able to produce gold nanotubes with the right dimensions to absorb a type of light called ‘near infrared’.

    The study’s corresponding author Professor Steve Evans, from the School of Physics and Astronomy at the University of Leeds, said: “Human tissue is transparent for certain frequencies of light – in the red/infrared region. This is why parts of your hand appear red when a torch is shone through it.

    “When the gold nanotubes travel through the body, if light of the right frequency is shone on them they absorb the light. This light energy is converted to heat, rather like the warmth generated by the Sun on skin. Using a pulsed laser beam, we were able to rapidly raise the temperature in the vicinity of the nanotubes so that it was high enough to destroy cancer cells.”

    In cell-based studies, by adjusting the brightness of the laser pulse, the researchers say they were able to control whether the gold nanotubes were in cancer-destruction mode, or ready to image tumours.

    In order to see the gold nanotubes in the body, the researchers used a new type of imaging technique called ‘multispectral optoacoustic tomography’ (MSOT) to detect the gold nanotubes in mice, in which gold nanotubes had been injected intravenously. It is the first biomedical application of gold nanotubes within a living organism. It was also shown that gold nanotubes were excreted from the body and therefore are unlikely to cause problems in terms of toxicity, an important consideration when developing nanoparticles for clinical use.

    Study co-author Dr James McLaughlan, from the School of Electronic & Electrical Engineering at the University of Leeds, said: “This is the first demonstration of the production, and use for imaging and cancer therapy, of gold nanotubes that strongly absorb light within the ‘optical window’ of biological tissue.

    “The nanotubes can be tumour-targeted and have a central ‘hollow’ core that can be loaded with a therapeutic payload. This combination of targeting and localised release of a therapeutic agent could, in this age of personalised medicine, be used to identify and treat cancer with minimal toxicity to patients.”

    The use of gold nanotubes in imaging and other biomedical applications is currently progressing through trial stages towards early clinical studies.

    See the full article here.

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    About Phys.org in 100 Words

    Phys.org™ (formerly Physorg.com) is a leading web-based science, research and technology news service which covers a full range of topics. These include physics, earth science, medicine, nanotechnology, electronics, space, biology, chemistry, computer sciences, engineering, mathematics and other sciences and technologies. Launched in 2004, Phys.org’s readership has grown steadily to include 1.75 million scientists, researchers, and engineers every month. Phys.org publishes approximately 100 quality articles every day, offering some of the most comprehensive coverage of sci-tech developments world-wide. Quancast 2009 includes Phys.org in its list of the Global Top 2,000 Websites. Phys.org community members enjoy access to many personalized features such as social networking, a personal home page set-up, RSS/XML feeds, article comments and ranking, the ability to save favorite articles, a daily newsletter, and other options.

     
  • richardmitnick 5:49 am on February 12, 2015 Permalink | Reply
    Tags: , Cancer, ,   

    From Rutgers: “Ingredient in Olive Oil Looks Promising in the Fight Against Cancer” 

    Rutgers University
    Rutgers University

    February 12, 2015
    Ken Branson

    1
    Extra-virgin olive oil contains an ingredient, oleocanthal, that kills cancer cells without harming healthy cells, researchers have found.

    A Rutgers nutritional scientist and two cancer biologists at New York City’s Hunter College have found that an ingredient in extra-virgin olive oil kills a variety of human cancer cells without harming healthy cells.

    The ingredient is oleocanthal, a compound that ruptures a part of the cancerous cell, releasing enzymes that cause cell death.

    Paul Breslin, professor of nutritional sciences in the School of Environmental and Biological Sciences, and David Foster and Onica LeGendre of Hunter College, report that oleocanthal kills cancerous cells in the laboratory by rupturing vesicles that store the cell’s waste. LeGendre, the first author, Foster, the senior author, and Breslin have published their findings in Molecular and Cellular Oncology.

    According to the World Health Organization’s World Cancer Report 2014, there were more than 14 million new cases of cancer in 2012 and more than 8 million deaths.

    Scientists knew that oleocanthal killed some cancer cells, but no one really understood how this occurred. Breslin believed that oleocanthal might be targeting a key protein in cancer cells that triggers a programmed cell death, known as apoptosis, and worked with Foster and Legendre to test his hypothesis after meeting David Foster at a seminar he gave at Rutgers.

    “We needed to determine if oleocanthal was targeting that protein and causing the cells to die,” Breslin said.

    After applying oleocanthal to the cancer cells, Foster and LeGendre discovered that the cancer cells were dying very quickly – within 30 minutes to an hour. Since programmed cell death takes between 16 and 24 hours, the scientists realized that something else had to be causing the cancer cells to break down and die.

    LeGendre, a chemist, provided the answer: The cancer cells were being killed by their own enzymes. The oleocanthal was puncturing the vesicles inside the cancer cells that store the cell’s waste – the cell’s “dumpster,” as Breslin called it, or “recycling center,” as Foster refers to it. These vesicles, known as lysosomes are larger in cancer cells than in healthy cells, and they contain a lot of waste. “Once you open one of those things, all hell breaks loose,” Breslin said.

    But oleocanthal didn’t harm healthy cells, the researchers found. It merely stopped their life cycles temporarily – “put them to sleep,” Breslin said. After a day, the healthy cells resumed their cycles.

    The researchers say the logical next step is to go beyond laboratory conditions and show that oleocanthal can kill cancer cells and shrink tumors in living animals. “We also need to understand why it is that cancerous cells are more sensitive to oleocanthal than non-cancerous cells,” Foster said.

    See the full article here.

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    Rutgers, The State University of New Jersey, is a leading national research university and the state’s preeminent, comprehensive public institution of higher education. Rutgers is dedicated to teaching that meets the highest standards of excellence; to conducting research that breaks new ground; and to providing services, solutions, and clinical care that help individuals and the local, national, and global communities where they live.

    Founded in 1766, Rutgers teaches across the full educational spectrum: preschool to precollege; undergraduate to graduate; postdoctoral fellowships to residencies; and continuing education for professional and personal advancement.

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  • richardmitnick 3:10 pm on February 5, 2015 Permalink | Reply
    Tags: , Cancer, ,   

    From NOVA: “Electric Fields Carrying Chemo Could Destroy Intractable Tumors” 

    PBS NOVA

    NOVA

    05 Feb 2015
    Tim De Chant

    There’s no “good” cancer, but some are certainly worse than others when it comes to prognosis. Pancreatic cancer, for example, has a dismal survival rate. It’s inoperable in many cases, and in general it’s hard to deliver chemo to the tumor because its internal pressure keeps drugs at bay.

    Researchers have been devising strategies to concentrate chemo in the most recalcitrant tumors, from injecting drugs directly into tumors themselves to directing chemo-coated magnetic particles to the site. The latest takes some of these ideas a step further while using existing drugs, a time-saving step. It comes in the form of a device that stores chemo and produces electric fields that carry the drugs directly into the tumor. Because many existing drugs are polar molecules, they are carried along with the electric current.

    1
    Pancreatic cancer cells, seen here through a powerful microscope, are targeted by the new treatment.

    Inventors Joseph DeSimone, a professor of chemistry at the University of North Carolina, Chapel Hill, and his team have tested their device on mice and dogs, and the approach shows promise. Here’s Robert F. Service, reporting for Science:

    The team got several promising results. In one experiment, the researchers started with mice that had been implanted with human pancreatic cancer tumors. One group of mice was then implanted with the electrode setup and administered an anticancer drug called gemcitabine twice a week for 7 weeks. Control animals received either saline through the same electrode setup or intravenous (IV) doses of saline or gemcitabine. The researchers report online today in Science Translational Medicine that the animals in the experimental group had far higher gemcitabine concentrations in their tumors compared with mice that received the IV drug. That caused the tumors to shrink dramatically in the experimental animals, whereas tumors in mice that received IV gemcitabine or saline continued to grow.

    Another advantage of the approach is that it limits the distribution of chemo within the body. Though the drugs are highly toxic to cancer cells, they also are taxing to healthy cells, making treatment regimens grueling affairs.

    DeSimone and his team have yet to move the device into clinical trials involving humans, an often unsuccessful transition for many would-be cancer treatments. Still, the fact that the device relies on delivering known, existing drugs more directly to a tumor site should reduce some uncertainty.

    See the full article here.

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    NOVA is the highest rated science series on television and the most watched documentary series on public television. It is also one of television’s most acclaimed series, having won every major television award, most of them many times over.

     
  • richardmitnick 2:37 pm on January 6, 2015 Permalink | Reply
    Tags: , , Cancer, ,   

    From UCSD: “Sugar Molecule Links Red Meat Consumption and Elevated Cancer Risk in Mice” 

    UC San Diego bloc

    UC San Diego

    December 29, 2014
    Heather Buschman, PhD

    While people who eat a lot of red meat are known to be at higher risk for certain cancers, other carnivores are not, prompting researchers at the University of California, San Diego School of Medicine to investigate the possible tumor-forming role of a sugar called Neu5Gc, which is naturally found in most mammals but not in humans.

    s
    N-Glycolylneuraminic acid
    Other names: GcNeu; NGNA; NeuNGl; Neu5Gc

    In a study published in the Dec. 29 online early edition of the Proceedings of the National Academy of Sciences, the scientists found that feeding Neu5Gc to mice engineered to be deficient in the sugar (like humans) significantly promoted spontaneous cancers. The study did not involve exposure to carcinogens or artificially inducing cancers, further implicating Neu5Gc as a key link between red meat consumption and cancer.

    “Until now, all of our evidence linking Neu5Gc to cancer was circumstantial or indirectly predicted from somewhat artificial experimental setups,” said principal investigator Ajit Varki, MD, Distinguished Professor of Medicine and Cellular and Molecular Medicine and member of the UC San Diego Moores Cancer Center. “This is the first time we have directly shown that mimicking the exact situation in humans — feeding non-human Neu5Gc and inducing anti-Neu5Gc antibodies — increases spontaneous cancers in mice.”

    Red meat is rich in Neu5Gc, a non-human sugar found to promote inflammation and cancer progression in rodents.

    Varki’s team first conducted a systematic survey of common foods. They found that red meats (beef, pork and lamb) are rich in Neu5Gc, affirming that foods of mammalian origin such as these are the primary sources of Neu5Gc in the human diet. The molecule was found to be bio-available, too, meaning it can be distributed to tissues throughout the body via the bloodstream.

    The researchers had previously discovered that animal Neu5Gc can be absorbed into human tissues. In this study, they hypothesized that eating red meat could lead to inflammation if the body’s immune system is constantly generating antibodies against consumed animal Neu5Gc, a foreign molecule. Chronic inflammation is known to promote tumor formation.

    To test this hypothesis, the team engineered mice to mimic humans in that they lacked their own Neu5Gc and produced antibodies against it. When these mice were fed Neu5Gc, they developed systemic inflammation. Spontaneous tumor formation increased fivefold and Neu5Gc accumulated in the tumors.

    “The final proof in humans will be much harder to come by,” Varki said. “But on a more general note, this work may also help explain potential connections of red meat consumption to other diseases exacerbated by chronic inflammation, such as atherosclerosis and type 2 diabetes.

    “Of course, moderate amounts of red meat can be a source of good nutrition for young people. We hope that our work will eventually lead the way to practical solutions for this catch-22.”

    Study co-authors include Annie N. Samraj, Oliver M. T. Pearce, Heinz Läubli, Alyssa N. Crittenden, Anne K. Bergfeld, Kalyan Banda, Christopher J. Gregg, Andrea E. Bingman, Patrick Secrest, Sandra L. Diaz and Nissi M. Varki, all at UC San Diego School of Medicine.

    This research was funded, in part, by the Ellison Medical Foundation, the National Cancer Institute (grant R01CA38701), a Samuel and Ruth Engelberg Fellowship from the Cancer Research Institute and a Swiss National Science Foundation Fellowship.

    Disclosure: Ajit Varki and Nissi Varki are co-founders and have equity interest in SiaMab Therapeutics, Inc., a biotech company with an interest in Neu5Gc and anti-Neu5Gc antibodies. In addition, Ajit Varki is a member of SiaMab Therapeutics, Inc.’s Board of Directors and is a Scientific Advisor to the company. The terms of this arrangement have been reviewed and approved by the University of California, San Diego in accordance with its conflict of interest policies.

    See the full article here.

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    The University of California, San Diego (also referred to as UC San Diego or UCSD), is a public research university located in the La Jolla area of San Diego, California, in the United States.[12] The university occupies 2,141 acres (866 ha) near the coast of the Pacific Ocean with the main campus resting on approximately 1,152 acres (466 ha).[13] Established in 1960 near the pre-existing Scripps Institution of Oceanography, UC San Diego is the seventh oldest of the 10 University of California campuses and offers over 200 undergraduate and graduate degree programs, enrolling about 22,700 undergraduate and 6,300 graduate students. UC San Diego is one of America’s Public Ivy universities, which recognizes top public research universities in the United States. UC San Diego was ranked 8th among public universities and 37th among all universities in the United States, and rated the 18th Top World University by U.S. News & World Report ‘s 2015 rankings.

     
  • richardmitnick 8:49 am on January 6, 2015 Permalink | Reply
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    From NYT: “Cancer’s Random Assault” 

    New York Times

    The New York Times

    JAN. 5, 2015
    DENISE GRADY

    It may sound flippant to say that many cases of cancer are caused by bad luck, but that is what two scientists suggested in an article published last week in the journal Science. The bad luck comes in the form of random genetic mistakes, or It may sound flippant to say that many cases of cancer are caused by bad luck, but that is what two scientists suggested in an article published last week in the journal Science. The bad luck comes in the form of random genetic mistakes, or mutations, that happen when healthy cells divide.

    Random mutations may account for two-thirds of the risk of getting many types of cancer, leaving the usual suspects — heredity and environmental factors — to account for only one-third, say the authors, Cristian Tomasetti and Dr. Bert Vogelstein, of Johns Hopkins University School of Medicine. “We do think this is a fundamental mechanism, and this is the first time there’s been a measure of it,” said Dr. Tomasetti, an applied mathematician.

    Though the researchers suspected that chance had a role, they were surprised at how big it turned out to be.

    c

    “This was definitely beyond my expectations,” Dr. Tomasetti said. “It’s about double what I would have thought.”

    The finding may be good news to some people, bad news to others, he added.

    Smoking greatly increases the risk of lung cancer, but for other cancers, the causes are not clear. And yet many patients wonder if they did something to bring the disease on themselves, or if they could have done something to prevent it.

    “For the average cancer patient, I think this is good news,” Dr. Tomasetti said. “Knowing that over all, a lot of it is just bad luck, I think in a sense it’s comforting.”

    Among people who do not have cancer, Dr. Tomasetti said he expected there to be two camps.

    “There are those who would like to control every single thing happening in their lives, and for those, this may be very scary,” he said. “ ‘There is a big component of cancer I can just do nothing about.’

    “For the other part of the population, it’s actually good news. ‘I’m happy. I can of course do all I know that’s important to not increase my risk of cancer, like a good diet, exercise, avoiding smoking, but on the other side, I don’t want to stress out about every single thing or every action I take in my life, or everything I touch or eat.’ ” Dr. Vogelstein said the question of causation had haunted him for decades, since he was an intern and his first patient was a 4-year-old girl with leukemia. Her parents were distraught and wanted to know what had caused the disease. He had no answer, but time and time again heard the same question from patients and their families, particularly parents of children with cancer.

    “They think they passed on a bad gene or gave them the wrong foods or exposed them to paint in the garage,” he said. “And it’s just wrong. It gave them a lot of guilt.”

    Dr. Tomasetti and Dr. Vogelstein said the finding that so many cases of cancer occur from random genetic accidents means that it may not be possible to prevent them, and that there should be more of an emphasis on developing better tests to find cancers early enough to cure them.

    “Cancer leaves signals of its presence, so we just have to basically get smarter about how to find them,” Dr. Tomasetti said.

    Their conclusion comes from a statistical model they developed using data in the medical literature on rates of cell division in 31 types of tissue. They looked specifically at stem cells, which are a small, specialized population in each organ or tissue that divide to provide replacements for cells that wear out.

    Dividing cells must make copies of their DNA, and errors in the process can set off the uncontrolled growth that leads to cancer.

    The researchers wondered if higher rates of stem-cell division might increase the risk of cancer simply by providing more chances for mistakes.

    Dr. Vogelstein said research of this type became possible only in recent years, because of advances in the understanding of stem-cell biology.

    The analysis did not include breast or prostate cancers, because there was not enough data on rates of stem-cell division in those tissues.

    A starting point for their research was an observation made more than 100 years ago but never really explained: Some tissues are far more cancer-prone than others. In the large intestine, for instance, the lifetime cancer risk is 4.8 percent — 24 times higher than in the small intestine, where it is 0.2 percent.

    The scientists found that the large intestine has many more stem cells than the small intestine, and that they divide more often: 73 times a year, compared with 24 times. In many other tissues, rates of stem cell division also correlated strongly with cancer risk.

    Some cancers, including certain lung and skin cancers, are more common than would be expected just from their rates of stem-cell division — which matches up with the known importance of environmental factors like smoking and sun exposure in those diseases. Others more common than expected were linked to cancer-causing genes. To help explain the findings, Dr. Tomasetti cited the risks of a car accident. In general, the longer the trip, the higher the odds of a crash. Environmental factors like bad weather can add to the basic risk, and so can defects in the car.

    “This is a good picture of how I see cancer,” he said. “It’s really the combination of inherited factors, environment and chance. At the base, there is the chance of mutations, to which we add, either because of things we inherited or the environment, our lifestyle.”

    Dr. Kenneth Offit, chief of the clinical genetics service at Memorial Sloan Kettering Cancer Center in Manhattan, called the article “an elegant biological explanation of the complex pattern of cancers observed in different human tissues.”

    He said the hypothesis “appears to be correct,” but added that it is “just a first approximation,” and he noted that certain types of cancer did not fit the model. One form of thyroid cancer, for instance, has a much bigger hereditary component than the model would suggest, he said.

    Although the article focused on factors in cancer beyond people’s control, Dr. Offit said that about half of cancer deaths could be avoided.

    “So one would not want to dilute the important public health message that although most cancer is likely due to random events (affecting DNA replication) at the cellular level, at the population level, the most powerful interventions to decrease the burden of cancer are to stop smoking, know your family history and aim for ideal weight,” he said.

    See the full article here.

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  • richardmitnick 7:51 pm on December 17, 2014 Permalink | Reply
    Tags: , Cancer,   

    From HCC at WCG: “New imaging tools accelerate cancer research” 

    New WCG Logo

    15 Dec 2014
    Help Conquer Cancer research team

    Summary
    The Help Conquer Cancer research team at the Ontario Cancer Institute continues to analyze the millions of protein-crystallization images processed by World Community Grid volunteers, by building new classifiers based on a combination of Grid-processed image features, and deep features learned directly from image pixels. Improvements in image classification, along with new data provided by our collaborators increase possibilities for discovering useful and interesting patterns in protein crystallization.

    Dear World Community Grid volunteers,

    Since our last Help Conquer Cancer (HCC) project update, we have continued to analyze the results that you generated. Here, we provide an update on that analysis work, and new research directions the project is taking.

    Analyzing HCC Results

    Volunteers for the HCC project received raw protein crystallization images and processed each image into a set of over 12,000 numeric image features. These features were implemented by a combination of image-processing algorithms, and refined over several generations of image-processing research leading up to the launch of HCC. The features (HCC-processed images) were then used to train a classifier that would convert each image’s features into a label describing the crystallization reaction captured in the image.

    Importantly, these thousands of features were human-designed. Most protein crystals have straight edges, for example, and so certain features were incorporated into HCC that search for straight lines. This traditional method of building an image classifier involves two types of learning: the crystallographer or image-processing expert (human), who studies the image and designs features, and the classifier (computer model), that learns to predict image labels from the designed features. The image classifier itself never sees the pixels; any improvements to the feature design must come from the human expert.

    More recently, we have applied a powerful computer-vision/machine-learning technology that improves this process by closing the feedback loop between pixels, features and the classifier: deep convolutional neural networks (CNNs). These models learn their own features directly from the image pixels; thus, they could complement human-designed features.

    CrystalNet

    We call our deep convolutional neural networks [CNN] CrystalNet. Our preliminary results suggest that it is an accurate and efficient classifier for protein crystallization images.

    In a CNN, multiple filters act like pattern detectors that are applied across the input image. A single map of the layer 1 feature maps shows the activation responses from a single filter. Deep CNNs refers to CNNs with many layers: higher-level filters stacked upon lower-level filters. Information from image pixels at the bottom of the network rises upwards through layers of filters until the “deep” features emerge from the top. Although the example shown in Figure 1 (below) has only 6 layers, more layers can be easily added. Including other image preprocessing and normalization layers, CrystalNet has 13 layers in total.

    1
    Fig. 1: Diagram of the standard convolutional neural network. For a single feature map, the convolution operation applies inner product of the same filter across the input image. 2D topography is preserved in the feature map representation. Spatial pooling performs image down-sampling of the feature maps by a factor of 2. Fully connected layers are the same as standard neural network layers. Outputs are discrete random variables or “1-of-K” codes. Element-wise nonlinearity is applied at every layer of the network.

    2
    After training, Figure 2 shows examples of the first layer filters. These filters extract interesting features useful for protein crystallography classification. Note that some of these filters look like segments of straight lines. Others resemble microcrystal-detecting filters previously designed for HCC.
    Fig. 2: Selected examples of the first-layer filters learned by our deep convolutional neural net. These filters have resemblances to human-designed feature extractors such as edge (top row), microcrystal (bottom), texture, and other detectors from HCC and computer vision generally.

    3
    Figure 3 shows CrystalNet’s crystal-detection performance across 10 image classes in the test set. CrystalNet produces an area under curve (AUC) 0.9894 for crystal class classification. At 5% false positive rate, our model can accurately detect 98% of the positive cases.

    CrystalNet can provide labels for images generated during the high-throughput process effectively, with a low miss rate and high precision for crystal detection. Moreover, CrystalNet operates in real-time, where labeling 1,536 images from a single plate only requires approximately 2 seconds. The combination of accuracy and efficiency makes a fully automated high-throughput crystallography pipeline possible, substantially reducing labor-intensive screening.

    New data from collaborators

    Our collaborators at the High-Throughput Screening Lab at the Hauptman-Woodward Medical Research Institute (HWI) supplied the original protein-crystallization image data. They continue to generate more, and are using versions of the image classifiers derived from the HCC project.

    Our research on the predictive science of protein crystallization has been limited by the information we have about the proteins being crystallized. Our research partners at HWI run crystallization trials on proteins supplied by labs all over the world. Often, protein samples are missing the identifying information that allows us to link these samples to global protein databases (e.g., Uniprot). Missing protein identifiers prevent us from integrating these samples into our data-mining system, and thereby linking the protein’s physical and chemical properties to each cocktail and corresponding crystallization response.

    Recently, however, HWI crystallographers were able to compile and share with us a complete record of all crystallization-trial proteins produced by the North-Eastern Structural Genomics (NESG) group. This dataset represents approximately 25% of all proteins processed by HCC volunteers on World Community Grid. Now all our NESG protein records are complete with each protein’s Uniprot ID, amino-acid sequence, and domain signatures.

    With more complete protein/cocktail information, combined with more accurate image labels from improved deep neural-net image classifiers, we anticipate greater success mining our protein-crystallization database. Work is ongoing.

    See the full article here.

    Please help promote STEM in your local schools.
    STEM Icon

    Stem Education Coalition

    World Community Grid (WCG) brings people together from across the globe to create the largest non-profit computing grid benefiting humanity. It does this by pooling surplus computer processing power. We believe that innovation combined with visionary scientific research and large-scale volunteerism can help make the planet smarter. Our success depends on like-minded individuals – like you.”

    WCG projects run on BOINC software from UC Berkeley.

    BOINC is a leader in the field(s) of Distributed Computing, Grid Computing and Citizen Cyberscience.BOINC is more properly the Berkeley Open Infrastructure for Network Computing.

    CAN ONE PERSON MAKE A DIFFERENCE? YOU BETCHA!!

    “Download and install secure, free software that captures your computer’s spare power when it is on, but idle. You will then be a World Community Grid volunteer. It’s that simple!” You can download the software at either WCG or BOINC.

    Please visit the project pages-
    Outsmart Ebola together

    Outsmart Ebola Together

    Mapping Cancer Markers
    mappingcancermarkers2

    Uncovering Genome Mysteries
    Uncovering Genome Mysteries

    Say No to Schistosoma

    GO Fight Against Malaria

    Drug Search for Leishmaniasis

    Computing for Clean Water

    The Clean Energy Project

    Discovering Dengue Drugs – Together

    Help Cure Muscular Dystrophy

    Help Fight Childhood Cancer

    Help Conquer Cancer

    Human Proteome Folding

    FightAIDS@Home

    World Community Grid is a social initiative of IBM Corporation
    IBM Corporation
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    IBM – Smarter Planet
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  • richardmitnick 7:02 pm on November 24, 2014 Permalink | Reply
    Tags: , Cancer,   

    From LBL: “For Important Tumor-Suppressing Protein, Context is Key” 

    Berkeley Logo

    Berkeley Lab

    November 21, 2014
    Dan Krotz 510-486-4019

    Scientists from the US Department of Energy’s Lawrence Berkeley National Laboratory (Berkeley Lab) have learned new details about how an important tumor-suppressing protein, called p53, binds to the human genome. As with many things in life, they found that context makes a big difference.

    t.
    PDB rendering based on 1TUP: P53 complexed with DNA[1]

    The researchers mapped the places where p53 binds to the genome in a human cancer cell line. They compared this map to a previously obtained map of p53 binding sites in a normal human cell line. These binding patterns indicate how the protein mobilizes a network of genes that quell tumor growth.

    They found that p53 occupies various types of DNA sequences, among them are sequences that occur in many copies and at multiple places in the genome. These sequences, called repeats, make up about half of our genome, but their function is much less understood than the non-repeated parts of the genome that code for genes.

    It’s been known for some time that p53 binds to repeats, but the Berkeley Lab scientists discovered something new: The protein is much more enriched at repeats in cancer cells than in normal cells. The binding patterns in these cell lines are very different, despite the same experimental conditions. This is evidence, they conclude, that in response to the same stress signal, p53 binds to the human genome in a way that is selective and dependent on cell context—an idea that has been an open question for years.

    l
    Illustration of p53 binding to major categories of repeats in the human genome, such as LTR, SINE and LINE.

    The research is published online Nov. 21 in the journal PLOS ONE.

    “It is well established that p53 regulates specific sets of genes, depending on the cell type and the DNA damage type. But how that specificity is achieved, and whether p53 binds to the genome in a selective manner, has been a matter of debate. We show that p53 binding is indeed selective and dependent on cell context,” says Krassimira Botcheva of Berkeley Lab’s Life Sciences Division. She conducted the research with Sean McCorkle of Brookhaven National Laboratory.

    What exactly does cell context mean in this case? The DNA that makes up the genome is organized into chromatin, which is further packed into chromosomes. Different cell types differ by their chromatin state. Cancer can change chromatin in a way that doesn’t affect DNA sequences, a type of change that is called epigenetic. The new research indicates that epigenetic changes to chromatin may have a big impact on how p53 does its job.

    “To understand p53 tumor suppression functions that depend on DNA binding, we have to examine these functions in the context of the dynamic, cancer-associated epigenetic changes,” says Botcheva.

    Their finding is the latest insight into p53, one of the most studied human proteins. For the past 35 years, scientists have explored how the protein fights cancer. After DNA damage, p53 can initiate cell cycle arrest to allow time for DNA repair. The protein can promote senescence, which stops a cell from proliferating. It can also trigger cell death if the DNA damage is severe.

    Much of this research has focused on how p53 binds to the non-repeated part of the genome, where the genes are located. This latest research suggests that repeats deserve a lot of attention too.

    “Our research indicates that p53 binding at repeats could be essential for maintaining the genomic stability,” says Botcheva. “Repeats could have a significant impact on the way the entire p53 network is mobilized to ensure tumor suppression.”

    The research was supported by the U.S. Department of Energy’s Office of Science.

    See the full article here.

    Please help promote STEM in your local schools.

    STEM Icon

    Stem Education Coalition

    A U.S. Department of Energy National Laboratory Operated by the University of California

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  • richardmitnick 10:18 am on November 11, 2014 Permalink | Reply
    Tags: , , Cancer, , ,   

    From SLAC: “Researchers Take Snapshots of Potential ‘Kill Switch’ for Cancer” 


    SLAC Lab

    November 10, 2014

    X-ray Study Shows Protein Switch for Programmed Cell Death in Motion

    A study conducted in part at the Department of Energy’s SLAC National Accelerator Laboratory has revealed how a key human protein switches from a form that protects cells to a form that kills them – a property that scientists hope to exploit as a “kill switch” for cancer.

    The protein, called cIAP1, shields cells from programmed cell death, or apoptosis – a naturally occurring crackdown on unhealthy cells and tissues. When a cell is in trouble, a signal activates cIAP1, which rapidly transforms into a state that allows apoptosis to take place.

    cell
    The structure of cellular inhibitor-of-apoptosis protein 1 (cIAP1) in its “closed” state. The protein is a key switch for apoptosis, or programmed cell death, and is composed of four distinct domains (color coded) that rearrange depending on the position of the switch. (Allyn Schoeffler/Genentech)

    “Cancer cells produce excess amounts of cIAP1 in an attempt to shut down apoptosis and evade death,” says senior staff scientist Thomas Weiss from SLAC’s Stanford Synchrotron Radiation Lightsource (SSRL), a DOE Office of Science User Facility, who participated in the study. “The search for drugs that would switch apoptosis back on to eradicate cancer is a very active research field.”

    The researchers used X-rays from SSRL to watch in real time how cIAP1 transitions from one state to another. The results are an important step towards becoming able to control the protein’s switching properties.

    “Our study closely ties cIAP1’s motions to its role as a switch,” says Allyn Schoeffler, a senior research associate at Genentech Inc. in South San Francisco and lead author of the study, published Nov. 10 in Nature Structural & Molecular Biology. “We now know why cIAP1 can act as a strictly controlled fail-safe for apoptosis and, at the same time, remain flexible enough to undergo rapid structural transitions.”

    Incomplete Static Model

    Earlier studies had given researchers a fairly good idea of cIAP1’s structure and general mechanism.

    In its “closed” state, which blocks apoptosis, the protein’s four parts, or domains, are tightly bound together in a rather rigid, compact structure.

    When a signal molecule binds to a specific site in cIAP1, the protein changes into its “open” state, in which the domains arrange in a more flexible, linear way. When two identical copies of this open structure partner up in what is known as a dimer, the assembly eventually self-destructs, removing the brake that blocks apoptosis and allowing cellular clean-up to carry on.

    “This model of cIAP1 action has largely been derived from static images of the protein,” Schoeffler says. “However, static pictures do not tell us the whole story.”

    Bringing Motion into the Equation

    To find out more, the research team first used a technique known as nuclear magnetic resonance spectroscopy, or NMR, to analyze how the protein domains move in the closed state, and followed up with studies at SSRL, where they observed how X-rays scatter off the transforming sample.

    scat
    Small-angle X-ray scattering models of different cIAP1 states. In its “closed” state, which blocks apoptosis, the domains are tightly bound together in a compact structure (left). Binding of a signal molecule for apoptosis switches the protein into its “open” state, in which the domains arrange in a more flexible linear way (center). When two identical copies of the open structure partner up in what is known as a dimer (right), the assembly eventually self-destructs, thereby allowing apoptosis to take place. (Allyn Schoeffler/Genentech)

    “The results showed that cIAP1 switches from ‘closed’ to ‘open’ extremely fast, within only 300 milliseconds, which we were able to determine using a technique called time-resolved small-angle X-ray scattering,” says Weiss. “The following dimer formation is even faster than that.”

    open
    Protein envelopes of cIAP1’s “open” and “closed” forms as determined by small-angle X-ray scattering (left) with detailed molecular structures modeled into them (right). For the first time, scientists have now monitored in real time how cIAP1 transitions from one state to another. (Allyn Schoeffler/Genentech)

    In addition, the scientists observed that the protein “breathes” rapidly in its closed form, with interfaces between domains opening and closing quickly.

    “The only region that is relatively rigid is the interaction site for the apoptosis signal,” says Schoeffler. “This well-defined site in the closed state allows nature to control cIAP1 very tightly. It is the critical latch that keeps the switch closed and makes sure that it does not open accidentally.”

    The rest of the protein, in contrast, is very flexible and allows cIAP1 to open instantaneously, like a spring-loaded trigger mechanism, when the proper signal is received. Once the trigger has been pulled, cell death becomes inevitable.

    Ties to Cancer Research

    The new insights could potentially benefit recent developments in cancer research. In fact, several studies are underway to explore the use of synthetic compounds that mimic nature’s signal molecules.

    “Natural and synthetic molecules are thought to interact with this protein the same way,” says Schoeffler. “Therefore, the mechanisms revealed by our study are likely to hold true in medically relevant molecules as well.”

    Research funding for the SSRL Structural Molecular Biology Program was provided by the DOE Office of Biological and Environmental Research and the National Institutes of Health, National Institute of General Medical Sciences.

    See the full article here.

    SLAC Campus
    SLAC is a multi-program laboratory exploring frontier questions in photon science, astrophysics, particle physics and accelerator research. Located in Menlo Park, California, SLAC is operated by Stanford University for the DOE’s Office of Science.
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  • richardmitnick 3:13 pm on November 7, 2014 Permalink | Reply
    Tags: , , , Cancer, ,   

    From WCG: “Decade of discovery: New precision tools to diagnose and treat cancer” 

    New WCG Logo

    3 Nov 2014
    By: Dr. David J. Foran, PhD
    Rutgers Cancer Institute of New Jersey

    Summary
    It’s week four of our 10th anniversary celebrations, and we’re following up last week’s childhood cancer feature by spotlighting another cancer project that’s helped researchers develop powerful new tools to diagnose cancer and tailor treatments to individual patients, using big data and analytics.

    no

    When it comes to cancer, a doctor’s diagnosis affects how aggressively a patient is treated, which medications might be appropriate and what levels of risk are justified. New precision medicine techniques are enabling physicians and scientists to refine diagnoses by identifying changes and patterns in individual cancers at unprecedented levels of granularity – ultimately improving treatment outcomes for patients.

    A key tool for precision medicine is tissue microarray analysis. This enables investigators to analyze large batches of tissue sample images simultaneously, so they can look for patterns and identify cancer signatures. It also provides them with a deeper understanding of cancer biology and uncovers new sub-classifications of cancer and likely patient responses – all of which influence new courses of treatment and future drug design.

    Tissue microarray analysis shows great promise, but it is not without its limitations. Pathologists typically examine the specimens visually, resulting in subjective interpretations and variations in diagnoses.

    We realized that if this method of analysis could be automated using digital pattern recognition algorithms, we could improve accuracy and reveal new patterns across large sets of data. This would make it possible for researchers to determine a patient’s type and stage of cancer more precisely, meaning they can prescribe therapies or combinations of treatments that are most likely to be effective.

    To study the feasibility of automating tissue microarray analysis, we partnered with IBM’s World Community Grid in 2006 to launch the Help Defeat Cancer project. At the time, we were pioneering a new approach that nobody else was investigating, and it was met with tremendous skepticism by many of our colleagues.

    However, with the support of more than 200,000 World Community Grid volunteers from around the globe who donated over 2,900 years of their computing time, we were able to study over 100,000 patient tissue samples to search for cancer signatures.

    Access to this vast computing power enabled our team to rapidly conduct this research under a much wider range of environmental conditions and to perform specimen analysis at much greater degrees of sensitivity.

    Thanks to World Community Grid and the Help Defeat Cancer project, we demonstrated the success of using computer-based analysis to automatically investigate and classify cancer specimens based on expression signature patterns. We were able to develop a reference library of cancer signatures that can be used to systematically analyze and compare tissue samples across large patient cohorts.

    Leveraging these experimental results, our team secured competitive funding from the National Institutes of Health (NIH) to build a clinical decision support system to automatically analyze and classify cancer specimens with improved diagnostic and prognostic accuracy. We used the core reference library of expression signatures generated through the Help Defeat Cancer project to demonstrate the proof-of-concept for the system.

    These decision support tools are now being tested and refined by investigators from the Rutgers Cancer Institute of New Jersey, Stony Brook University School of Medicine, University of Pittsburgh Medical Center and Emory University. They are exploring how the tools can aid clinical decision-making, plus are pursuing further investigative research. Together, our ultimate aim is to refine these tools sufficiently so they can be certified for routine clinical use in diagnosing and treating patients.

    Although the Help Defeat Cancer project has completed its research on World Community Grid, we continue to investigate the findings and they have contributed to some significant new beginnings. At Rutgers Cancer Institute of New Jersey, physicians and scientists – aided by high-performance computing resources – are analyzing genomes and human tissues, and identifying cancer patterns, faster than ever before.

    In collaboration with our research partners at the Rutgers Discovery Informatics Institute (RDI2) and RUCDR Infinite Biologics (the world’s largest university-based biorepository, located within the Human Genetics Institute of New Jersey), the Rutgers Cancer Institute is shaping a revolution in how best to determine cancer therapy for patients – a vast improvement from the time-intensive, trial-and-error approach that doctors have faced for years. To date, only a fraction of known cancer biomarkers have been examined. The long-term goal is to create a library of biomarkers and their expression patterns so that, in the future, physicians can consult the library to help diagnose cancer patients and provide them with the most effective treatment.

    I would like to express my gratitude to Stanley Litow, Robin Willner, and Jen Crozier from IBM and to World Community Grid’s Advisory Board for supporting the Help Defeat Cancer project. I’d also like to extend my special thanks to the IBM World Community Grid team members who contributed to the success of the project – I hope to have the opportunity to work with them again in the near future.

    Additionally, I would like to acknowledge the NIH, Department of Defense and IBM for supporting this research – and give credit to those individuals from my laboratory and partnering institutions who were involved in the early experiments and the initial design and development of the imaging and computational tools, which we then used throughout the project. And, of course, a very big thank you to all the World Community Grid volunteers – without their support, our accomplishments with Help Defeat Cancer would not have been possible.

    The Help Defeat Cancer project has completed its analysis on World Community Grid – but another innovative project, Mapping Cancer Markers, is currently running and needs your help. Help us celebrate a decade of discovery on World Community Grid by sharing this story and encouraging your friends to donate their unused computing power to cutting-edge cancer research.

    Here’s to another decade of discovery.

    See the full article here.

    World Community Grid (WCG) brings people together from across the globe to create the largest non-profit computing grid benefiting humanity. It does this by pooling surplus computer processing power. We believe that innovation combined with visionary scientific research and large-scale volunteerism can help make the planet smarter. Our success depends on like-minded individuals – like you.”

    WCG projects run on BOINC software from UC Berkeley.

    BOINC is a leader in the field(s) of Distributed Computing, Grid Computing and Citizen Cyberscience.BOINC is more properly the Berkeley Open Infrastructure for Network Computing.

    CAN ONE PERSON MAKE A DIFFERENCE? YOU BETCHA!!

    “Download and install secure, free software that captures your computer’s spare power when it is on, but idle. You will then be a World Community Grid volunteer. It’s that simple!” You can download the software at either WCG or BOINC.

    Please visit the project pages-

    Mapping Cancer Markers
    mappingcancermarkers2

    Uncovering Genome Mysteries
    Uncovering Genome Mysteries

    Say No to Schistosoma

    GO Fight Against Malaria

    Drug Search for Leishmaniasis

    Computing for Clean Water

    The Clean Energy Project

    Discovering Dengue Drugs – Together

    Help Cure Muscular Dystrophy

    Help Fight Childhood Cancer

    Help Conquer Cancer

    Human Proteome Folding

    FightAIDS@Home

    World Community Grid is a social initiative of IBM Corporation
    IBM Corporation
    ibm

    IBM – Smarter Planet
    sp

    ScienceSprings relies on technology from

    MAINGEAR computers

    Lenovo
    Lenovo

    Dell
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