NOCC To Host 6th Annual “Walk To Break The Silence On Ovarian Cancer” In Washington, D.C. Area

The National Ovarian Cancer Coalition (NOCC) Central Maryland Chapter announces its 6th Annual “Walk to Break the Silence on Ovarian Cancer” to be held on Sunday, September 12, 2010 at Quiet Waters Park, located in Annapolis, Maryland.

Pureology is the Premier Sponsor of the NOCC 6th Annual "Walk To Break The Silence On Ovarian Cancer" Event

The National Ovarian Cancer Coalition (NOCC) Central Maryland Chapter announces its 6th Annual “Walk to Break the Silence on Ovarian Cancer” to be held on Sunday, September 12, 2010 at Quiet Waters Park, located in Annapolis, Maryland.

Registration will open at 8:00 am, and the 5K Run will begin at 9:00 am. The 3K Walk is scheduled to kick off at 9:05 am. To view a complete schedule of events, click here. To view the event brochure, click here.

September is Ovarian Cancer and Gynecologic Cancer Awareness Month. “We walk and run to raise funds but just as importantly, we walk and run to raise awareness,” said Nancy Long, NOCC Central Maryland Chapter’s Co-President. “There is no early detection test for ovarian cancer. That is why education and awareness are currently our best defense against this disease.”

Special events will include a survivor’s area with prizes and gifts available for ovarian cancer survivors. Refreshments will be provided, as well as face painting for the kids, big and small, and a table to make a flag in honor of or in memory of a loved one.

All participants will receive a T-shirt and a Pureology gift pack containing Pureology Hydrate Shampoo and Pureology Hydrate Conditioner. Pureology is the premier sponsor of the NOCC’s “Walk to Break the Silence on Ovarian Cancer.”

Quiet Waters Park - South River Overlook, Annapolis, Maryland

Quiet Waters Park - Bridge & Fountain, Annapolis, Maryland

More than 20,000 women are diagnosed with ovarian cancer each year, and approximately 15,000 women die from the disease annually. Unfortunately, most cases are diagnosed in their later stages when the prognosis is poor.  However, if diagnosed and treated early, when the cancer is confined to the ovary, the five-year survival rate is over 90 percent. There is currently no early detection test for ovarian cancer, and Pap tests do not detect the disease.  That is why it is imperative that the early signs and symptoms of the disease are recognized, not only by women, but also by their families and the medical community.

Symptoms of ovarian cancer may include bloating, pelvic or abdominal pain, trouble eating or feeling full quickly, and feeling the need to urinate urgently or often. Other symptoms of ovarian cancer may include fatigue, upset stomach or heartburn, back pain, pain during intercourse, constipation, and menstrual changes. Women who experience these symptoms for longer than two weeks, especially if these symptoms are new to them, are encouraged to visit their health care provider.

Many women attending this event are anxious and willing to tell their stories of, or related to, diagnosis, misdiagnosis, the hardships of treatment, the potential for inherited genetic mutations, and the fears and joys of being a survivor.

To register for the NOCC Central Maryland Chapter’s “Walk to Break the Silence on Ovarian Cancer,” please call 443-433-2597 or visit www.nocc.kintera.org/mdcentral

About the National Ovarian Cancer Coalition

The mission of the National Ovarian Cancer Coalition, a 501 (c)(3) charitable organization, is to raise awareness and promote education about ovarian cancer. The Coalition carries out its mission through a toll-free Help Line, local NOCC Chapters, a comprehensive website, peer support, written publications, and awareness/educational programs. The Coalition is committed to improving the survival rate and quality of life for women with ovarian cancer. If you would like more information on the “Break the Silence” campaign, or wish to contact one of the local NOCC Chapters, visit www.ovarian.org or call 1-888-OVARIAN (1-888-682-7426).

Source: NOCC Central MD Announces the 6th Annual Walk/Run To Break the Silence on Ovarian Cancer, National Ovarian Cancer Coalition, Central Maryland Chapter, Press Release, July 2, 2010.

The Cancer Biomarker Conundrum: Too Many False Discoveries

The boom in cancer [including ovarian] biomarker investments over the past 25 years has not translated into major clinical success. The reasons for biomarker failures include problems with study design and interpretation, as well as statistical deficiencies, according to an article published online August 12 in The Journal of the National Cancer Institute.

The boom in cancer [including ovarian] biomarker investments over the past 25 years has not translated into major clinical success. The reasons for biomarker failures include problems with study design and interpretation, as well as statistical deficiencies, according to an article published online August 12 in The Journal of the National Cancer Institute.

The National Institutes of Health defines a biomarker as “a characteristic that is objectively measured and evaluated as an indicator of normal biologic processes, pathogenic processes, or pharmacologic responses to a therapeutic intervention.” In the past decade, there have been numerous biomarker discoveries, but most initially promising biomarkers have not been validated for clinical use.

Eleftherios P. Diamandis, M.D., Ph.D., Head, Section of Clinical Biochemistry, Department of Pathology and Laboratory Medicine, Mount Sinai Hospital, Toronto, Ontario, Canada

To understand why so-called biomarker “breakthroughs” have not made it to the clinic, Eleftherios P. Diamandis, M.D., Ph.D., professor of pathology and laboratory medicine at Mount Sinai Hospital in Toronto and associate scientist at the Samuel Lunenfeld Research Institute of Mount Sinai Hospital, reviewed some biomarkers initially hailed as breakthroughs and their subsequent failings.

Diamandis first describes the requirements for biomarkers to be approved for clinical use: A biomarker must be released into circulation in easily detectable amounts by a small asymptomatic tumor or its micro-environment; and it should preferably be specific for the tissue of origin. Also, if the biomarker is affected by a non-cancer disease, its utility for cancer detection may be compromised. For example, the prostate-specific antigen (PSA) biomarker, which is used to detect prostate cancer, is also elevated in benign prostatic hyperplasia.

Diamandis looks at seven biomarkers that have emerged in the past 25 years, all of which were considered promising when they were first described. These include nuclear magnetic resonance of serum for cancer diagnosis; lysophosphatidic acid for ovarian cancer; four- and six-parameter diagnostic panels for ovarian cancer; osteopontin for ovarian cancer; early prostate cancer antigen-2 (EPCA-2) for prostate cancer detection; proteomic profiling of serum by mass spectrometry for ovarian cancer diagnosis; and peptidomic patterns for cancer diagnosis. Problems ranged from inappropriate statistical analysis to biases in case patient and control subject selection. For example, the problems with EPCA-2 included reporting values that were beyond the detection limit of the assay and using inappropriate reagents to test EPCA-2, such as solid surfaces coated with undiluted serum.

Diamandis concludes that “problems with pre-analytical, analytical, and post-analytical study design could lead to the generation of data that could be highly misleading.”

Sources:

The Cancer Biomarker Conundrum: Too Many False Discoveries, Journal of the National Cancer Institute Advance Access,  published on August 12, 2010, DOI 10.1093/jnci/djq335.

Eleftherios P. Diamandis. Cancer Biomarkers: Can We Turn Recent Failures into Success? Commentary, Journal of the National Cancer Institute Advance Access published on August 12, 2010, DOI 10.1093/jnci/djq306.

Georgia Tech’s Ovarian Cancer Early Detection Blood Test Exhibits High Accuracy in Small Study; Larger Study Planned

Scientists at the Georgia Institute of Technology have attained very promising results on their initial investigations of a new test for ovarian cancer. Using a new technique involving mass spectrometry of a single drop of blood serum, the test correctly identified women with ovarian cancer in 100 percent of the 94 patients tested. Because of the extremely low prevalence of ovarian cancer in the general population (∼0.04%), extensive prospective testing will be required to evaluate the test’s potential utility in general screening applications.

Scientists at the Georgia Institute of Technology have attained very promising results on their initial investigations of a new test for ovarian cancer. Using a new technique involving mass spectrometry of a single drop of blood serum, the test correctly identified women with ovarian cancer in 100 percent of the 94 patients tested. The results can be found online in the journal Cancer Epidemiology, Biomarkers, & Prevention Research.

John McDonald, Ph.D., Professor, Associate Dean for Biology Program Development, Georgia Institute of Technology; Chief Science Officer, Ovarian Cancer Institute

Facundo Fernandez, Ph.D., Associate Professor, School of Chemistry & Biochemistry, Georgia Institute of Technology

“Because ovarian cancer is a disease of relatively low prevalence, it’s essential that tests for it be extremely accurate. We believe we may have developed such a test,” said John McDonald, chief research scientist at the Ovarian Cancer Institute (Atlanta) and professor of biology at Georgia Tech.

The measurement step in the test, developed by the research group of Facundo Fernandez, associate professor in the School of Chemistry and Biochemistry at Tech, uses a single drop of blood serum, which is vaporized by hot helium plasma. As the molecules from the serum become electrically charged, a mass spectrometer is used to measure their relative abundance. The test looks at the small molecules involved in metabolism that are in the serum, known as metabolites. Machine learning techniques developed by Alex Gray, assistant professor in the College of Computing and the Center for the Study of Systems Biology, were then used to sort the sets of metabolites that were found in cancerous plasma from the ones found in healthy samples. Then, McDonald’s lab mapped the results between the metabolites found in both sets of tissue to discover the biological meaning of these metabolic changes.

The assay did extremely well in initial tests involving 94 subjects. In addition to being able to generate results using only a drop of blood serum, the test proved to be 100 percent accurate in distinguishing sera from women with ovarian cancer from normal controls. In addition it registered neither a single false positive nor a false negative

The group is currently in the midst of conducting the next set of assays, this time with 500 patients.

“The caveat is we don’t currently have 500 patients with the same type of ovarian cancer, so we’re going to look at other types of ovarian cancer,” said Fernandez. “It’s possible that there are also signatures for other cancers, not just ovarian, so we’re also going to be using the same approach to look at other types of cancers. We’ll be working with collaborators in Atlanta and elsewhere.”

In addition to having a relatively low prevalence, ovarian cancer is also asymptomatic in the early stages. Therefore, if further testing confirms the ability to accurately detect ovarian cancer by analyzing metabolites in the serum of women, doctors will be able detect the disease early and save many lives.

Libby’s H*O*P*E*™ Comment:

Alex Gray, Ph.D., Assistant Professor, College of Computing & Center for the Study of Systems Biology, Georgia Institute of Technology

This study involved testing the metabolite levels in blood sera from 44 women diagnosed with serous papillary ovarian cancer (stages I-IV) and 50 healthy women or women with benign conditions.  The assay distinguished between the cancer and control groups with an unprecedented 99% to 100% accuracy. The method possesses significant clinical potential as a cancer diagnostic tool.  Because of the extremely low prevalence of ovarian cancer in the general population (∼0.04%), extensive prospective testing will be required to evaluate the test’s potential utility in general screening applications.

Sources:

Initial Trials On New Ovarain Cancer Tests Exhibit Extremely High Accuracy, News Release, Georgia Institute of Technology, August 11, 2010.

Zhou M,Guan W, Walker LD, et. al. Rapid Mass Spectrometric Metabolic Profiling of Blood Sera Detects Ovarian Cancer with High Accuracy. Cancer Epidemiol Biomarkers Prev 1055-9965.EPI-10-0126; Published OnlineFirst August 10, 2010; doi:10.1158/1055-9965.EPI-10-0126

Largest Study Matching Genomes To Potential Anticancer Treatments Releases Initial Results

The largest study to correlate genetics with response to anticancer drugs released its first results on July 15. The researchers behind the study, based at Massachusetts General Hospital Cancer Center and the Wellcome Trust Sanger Institute, describe in this initial dataset the responses of 350 cancer samples (including ovarian cancer) to 18 anticancer therapeutics.

U.K.–U.S. Collaboration Builds a Database For “Personalized” Cancer Treatment

The Genomics of Drug Sensitivity in Cancer project released its first results on July 15th. Researchers released a first dataset from a study that will expose 1,000 cancer cell lines (including ovarian) to 400 anticancer treatments.

The largest study to correlate genetics with response to anticancer drugs released its first results on July 15. The researchers behind the study, based at Massachusetts General Hospital Cancer Center and the Wellcome Trust Sanger Institute, describe in this initial dataset the responses of 350 cancer samples (including ovarian cancer) to 18 anticancer therapeutics.

These first results, made freely available on the Genomics of Drug Sensitivity in Cancer website, will help cancer researchers around the world to obtain a better understanding of cancer genetics and could help to improve treatment regimens.

Dr. Andy Futreal, co-leader of the Cancer Genome Project at the Wellcome Trust Sanger Institute, said:

Today is our first glimpse of this complex interface, where genomes meet cancer medicine. We will, over the course of this work, add to this picture, identifying genetic changes that can inform clinical decisions, with the hope of improving treatment.  By producing a carefully curated set of data to serve the cancer research community, we hope to produce a database for improving patient response during cancer treatment.

How a patient responds to anticancer treatment is determined in large part by the combination of gene mutations in her or his cancer cells. The better this relationship is understood, the better treatment can be targeted to the particular tumor.

The aim of the five-year, international drug-sensitivity study is to find the best combinations of treatments for a wide range of cancer types: roughly 1000 cancer cell lines will be exposed to 400 anticancer treatments, alone or in combination, to determine the most effective drug or combination of drugs in the lab.

The therapies include known anticancer drugs as well as others in preclinical development.

To make the study as comprehensive as possible, the researchers have selected 1000 genetically characterized cell lines that include common cancers such as breast, colorectal and lung. Each cell line has been genetically fingerprinted and this data will also be publicly available on the website. Importantly, the researchers will take promising leads from the cancer samples in the lab to be verified in clinical specimens: the findings will be used to design clinical studies in which treatment will be selected based on a patient’s cancer mutation spectrum.

The new data released today draws on large-scale analyses of cancer genomes to identify genomic markers of sensitivity to anticancer drugs.

The first data release confirms several genes that predict therapeutic response in different cancer types. These include sensitivity of melanoma, a deadly form of skin cancer, with activating mutations in the gene BRAF to molecular therapeutics targeting this protein, a therapeutic strategy that is currently being exploited in the clinical setting. These first results provide a striking example of the power of this approach to identify genetic factors that determine drug response.

Dr. Ultan McDermott, Faculty Investigator at the Wellcome Trust Sanger Institute, said:

It is very encouraging that we are able to clearly identify drug–gene interactions that are known to have clinical impact at an early stage in the study. It suggests that we will discover many novel interactions even before we have the full complement of cancer cell lines and drugs screened. We have already studied more gene mutation-drug interactions than any previous work but, more importantly, we are putting in place a mechanism to ensure rapid dissemination of our results to enable worldwide collaborative research. By ensuring that all the drug sensitivity data and correlative analysis is freely available in an easy-to-use website, we hope to enable and support the important work of the wider community of cancer researchers.

Further results from this study should, over its five-year term, identify interactions between mutations and drug sensitivities most likely to translate into benefit for patients: at the moment we do not have sufficient understanding of the complexity of cancer drug response to optimize treatment based on a person’s genome.

Professor Daniel Haber, Director of the Cancer Center at Massachusetts General Hospital and Harvard Medical School, said:

We need better information linking tumor genotypes to drug sensitivities across the broad spectrum of cancer heterogeneity, and then we need to be in position to apply that research foundation to improve patient care.  The effectiveness of novel targeted cancer agents could be substantially improved by directing treatment towards those patients that genetic study suggests are most likely to benefit, thus “personalizing” cancer treatment.

The comprehensive results include correlating drug sensitivity with measurements of mutations in key cancer genes, structural changes in the cancer cells (copy number information) and differences in gene activity, making this the largest project of its type and a unique resource for cancer researchers around the world.

Professor Michael Stratton, co-leader of the Cancer Genome Project and Director of the Wellcome Trust Sanger Institute, said:

“This is one of the Sanger Institute’s first large-scale explorations into the therapeutics of human disease.  I am delighted to see the early results from our partnership with the team at Massachusetts General Hospital. Collaboration is essential in cancer research: this important project is part of wider efforts to bring international expertise to bear on cancer.”

Ovarian Cancer Sample Gene Mutation Prevalence

As part of the Cancer Genome Project, researchers identified gene mutations found in 20 ovarian cancer cell lines and the associated prevalence of such mutations within the sample population tested. For purposes of this project, a mutation — referred to by researchers as a “genetic event” in the project analyses description — is defined as (i) a coding sequence variant in a cancer gene, or (ii) a gene copy number equal to zero (i.e., a gene deletion) or greater than or equal to 8 (i.e., gene amplification).  The ovarian cancer sample analysis thus far, indicates the presence of mutations in twelve genes. The genes that are mutated and the accompanying mutation prevalence percentage are as follows:  APC (5%), CDKN2A (24%), CTNNB1 (5%), ERBB2/HER-2 (5%), KRAS (10% ), MAP2K4 (5%), MSH2 (5%), NRAS (10%), PIK3CA (10%), PTEN (14%), STK11 (5%), and TP53 (62%). Accordingly, as of date, the top five ovarian cancer gene mutations occurred in TP53, CDKN2A, CDKN2a(p14)(see below), PTEN, and KRAS.

Click here to view the Ovary Tissue Overview.  Click here to download a Microsoft Excel spreadsheet listing the mutations in 52 cancer genes across tissue types. Based upon the Ovary Tissue Overview chart, the Microsoft Excel Chart has not been updated to include the following additional ovarian cancer sample mutations and associated prevalence percentages: CDKN2a(p14)(24%), FAM123B (5%), FBXW7 (5%), MLH1 (10%), MSH6 (5%).

18 AntiCancer Therapies Tested; Next 9 Therapies To Be Tested Identified

As presented in the initial study results, 18 drugs/preclinical compounds were tested against various cancer cell lines, including ovarian. The list of drugs/preclinical compounds that were tested for sensitivity are as follows:  imatinib (brand name: Gleevec),  AZ628 (C-Raf inhibitor)MG132 (proteasome inhibitor), TAE684 (ALK inhibitor), MK-0457 (Aurora kinase inhibitor)sorafenib (C-Raf kinase & angiogenesis inhibitor) (brand name: Nexavar), Go 6976 (protein kinase C (PKC) inhibitor), paclitaxel (brand name: Taxol), rapamycin (mTOR inhibitor)(brand name: Rapamune), erlotinib (EGFR inhibitor)(brand name: Tarceva), HKI-272 (a/k/a neratinib) (HER-2 inhibitor), Geldanamycin (Heat Shock Protein 90 inhibitor), cyclopamine (Hedgehog pathway inhibitor), AZD-0530 (Src and Abl inhibitor), sunitinib (angiogenesis & c-kit inhibitor)(brand name:  Sutent), PHA665752 (c-Met inhibitor), PF-2341066 (c-Met inhibitor), and PD173074 (FGFR1 & angiogenesis inhibitor).

Click here to view the project drug/preclinical compound sensitivity data chart.

The additional drugs/compounds that will be screened by researchers in the near future are metformin (insulin)(brand name:  Glucophage), AICAR (AMP inhibitor), docetaxel (platinum drug)(brand name: Taxotere), cisplatin (platinum drug)(brand name: Platinol), gefitinib (EGFR inhibitor)(brand name:  Iressa), BIBW 2992 (EGFR/HER-2 inhibitor)(brand name:  Tovok), PLX4720 (B-Raf [V600E] inhibitor), axitinib (angiogenesis inhibitor)(a/k/a AG-013736), and CI-1040 (PD184352)(MEK inhibitor).

Ovarian cancer cells dividing. (Source: ecancermedia)

Ovarian Cancer Therapy Sensitivity

Targeted molecular therapies that disrupt specific intracellular signaling pathways are increasingly used for the treatment of cancer. The rational for this approach is based on our ever increasing understanding of the genes that are causally implicated in cancer and the clinical observation that the genetic features of a cancer can be predictive of a patient’s response to targeted therapies. As noted above, the goal of the Cancer Genome Project is to discover new cancer biomarkers that define subsets of drug-sensitive patients. Towards this aim, the researchers are (i) screening a wide range of anti-cancer therapeutics against a large number of genetically characterized human cancer cell lines (including ovarian), and (ii) correlating drug sensitivity with extensive genetic data. This information can be used to determine the optimal clinical application of cancer drugs as well as the design of clinical trials involving investigational compounds being developed for the clinic.

When the researchers tested the 18 anticancer therapies against the 20 ovarian cancer cell lines, they determined that the samples were sensitive to many of the drugs/compounds. The initial results of this testing indicate that there are at least six ovarian cancer gene mutations that were sensitive to eight of the anticancer therapies, with such results rising to the level of statistical significance.  We should note that although most (but not all) of the ovarian cancer gene mutations were sensitive to several anticancer therapies, we listed below only those which were sensitive enough to be assigned a green (i.e., sensitive) heatmap code by the researchers.

Click here to download a Microsoft Excel spreadsheet showing the effect of each of the 51 genes on the 18 drugs tested. Statistically significant effects are highlighted in bold and the corresponding p values for each gene/drug interaction are displayed in an adjacent table.  A heatmap overlay for the effect of the gene on drug sensitivity was created, with the color red indicating drug resistance and the color green indicating drug sensitivity.

The mutated genes present within the 20 ovarian cancer cell line sample that were sensitive to anticancer therapies are listed below.  Again, only statistically significant sensitivities are provided.

  • CDKN2A gene mutation was sensitive to TAE684, MK-0457, paclitaxel, and PHA665752.
  • CTNNB1 gene mutation was sensitive to MK-0457.
  • ERBB2/HER-2 gene mutation was sensitive to HKI-272.
  • KRAS gene mutation was sensitive to AZ628.
  • MSH2 gene mutation was sensitive to AZD0530.
  • NRAS gene mutation was sensitive to AZ628.

We will provide you with future updates regarding additional ovarian cancer gene mutation findings, and new anticancer therapies tested, pursuant to the ongoing Cancer Genome Project.

Sources:

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About The Genomics of Drug Sensitivity In Cancer Project

The Genomics of Drug Sensitivity In Cancer Project was launched in December 2008 with funding from a five-year Wellcome Trust strategic award. The U.K.–U.S. collaboration harnesses the experience in experimental molecular therapeutics at Massachusetts General Hospital Cancer Center and the expertise in large scale genomics, sequencing and informatics at the Wellcome Trust Sanger Institute. The scientists will use their skills in high-throughput research to test the sensitivity of 1000 cancer cell samples to hundreds of known and novel molecular anticancer treatments and correlate these responses to the genes known to be driving the cancers. The study makes use of a very large collection of genetically defined cancer cell lines to identify genetic events that predict response to cancer drugs. The results will give a catalogue of the most promising treatments or combinations of treatments for each of the cancer types based on the specific genetic alterations in these cancers. This information will then be used to empower more informative clinical trials thus aiding the use of targeted agents in the clinic and ultimately improvements in patient care.

Project leadership includes Professor Daniel Haber and Dr. Cyril Benes at Massachusetts General Hospital Cancer Center and Professor Mike Stratton and Drs. Andy Futreal and Ultan McDermott at the Wellcome Trust Sanger Institute.

About Massachusetts General Hospital

Massachusetts General Hospital (MGH), established in 1811, is the original and largest teaching hospital of Harvard Medical School. The MGH conducts the largest hospital-based research program in the United States, with an annual research budget of more than $600 million and major research centers in AIDS, cardiovascular research, cancer, computational and integrative biology, cutaneous biology, human genetics, medical imaging, neurodegenerative disorders, regenerative medicine, systems biology, transplantation biology and photomedicine.

About The Wellcome Trust Sanger Institute

The Wellcome Trust Sanger Institute, which receives the majority of its funding from the Wellcome Trust, was founded in 1992 as the focus for U.K. gene sequencing efforts. The Institute is responsible for the completion of the sequence of approximately one-third of the human genome as well as genomes of model organisms such as mouse and zebrafish, and more than 90 pathogen genomes. In October 2005, new funding was awarded by the Wellcome Trust to enable the Institute to build on its world-class scientific achievements and exploit the wealth of genome data now available to answer important questions about health and disease. These programs are built around a Faculty of more than 30 senior researchers. The Wellcome Trust Sanger Institute is based in Hinxton, Cambridge, U.K.

About The Wellcome Trust

The Wellcome Trust is a global charity dedicated to achieving extraordinary improvements in human and animal health. It supports the brightest minds in biomedical research and the medical humanities. The Trust’s breadth of support includes public engagement, education, and the application of research to improve health. It is independent of both political and commercial interests.

Required Cancer Genome Project Disclaimer:

The data above was obtained from the Wellcome Trust Sanger Institute Cancer Genome Project web site, http://www.sanger.ac.uk/genetics/CGP. The data is made available before scientific publication with the understanding that the Wellcom Trust Sanger Institute intends to publish the initial large-scale analysis of the dataset. This publication will include a summary detailing the curated data and its key features.  Any redistribution of the original data should carry this notice: Please ensure that you use the latest available version of the data as it is being continually updated.  If you have any questions regarding the sequence or mutation data or their use in publications, please contact cosmic@sanger.ac.uk so as to obtain any updated or additional data.  The Wellcome Trust Sanger Institute provides this data in good faith, but makes no warranty, express or implied, nor assumes any legal liability or responsibility for any purpose for which the data are used.