|1.||Dr. David Jackson||LIFE Biosystems||Germany||2013-04-26||Variant Characterization for Prediction of Drug Responsiveness||A crucial step towards the personalization of cancer medicine involves the marriage of molecular information and biomedical knowledge with patient specific clinico-molecular data. Effective cancer treatment is dependent on such an approach, since often patients respond very differently to treatment despite sharing the same cancer type. The key to understanding treatment response or resistance lies in deciphering the complex interplay of individual molecular variability in the tumor and the rest of a patient’s body. The aim of our project is to use the ICGC data as a reference to compare to patient-specific information with molecular information about drug mode of action and the functional implications of gene variants. This will make personalized cancer treatment decision support feasible and will help to bring the benefit of molecular disease data to the clinic and treating physician. |
|2.||Dr. Stephen Friend||Sage Bionetworks||United States||2013-05-15||Network Modeling of Cancer||Cancer represents one of the most complex diseases because the groups of genetic mutations that can result in tumor progression can vary widely across individuals. The goal of our research is to use mathematical models based on genomic and clinical data donated from patients around the world to provide a model of cancer pathology that can be used to understand the complex biology that underlies tumorigenesis (the biological process involved in generation of tumors). The goal of this effort is to predict clinical outcomes and, ultimately, to guide the production of more effective therapies for future generations of cancer patients. |
|3.||Dr. Michael Heuser||Hannover Medical School||Germany||2012-07-06||Characterization of novel mutations in AML for their effects on myeloid differentiation.||Acute myeloid leukemia is a very aggressive disease of the white blood cells, and novel treatments are needed. All-trans retinoic acid (ATRA) is an agent that has already been shown to be effective in one special form of leukaemia (acute promyeloic leukaemia). Whether ATRA is effective in other types of AML is a matter of current investigations. We are interested in identifying novel mutations that may be responsible for the fact that many leukemia patients don’t benefit from ATRA treatment. Genes of primary interest will be members of the retinoic acid receptor pathway. If mutations in these genes can be identified they will be functionally evaluated for their effect on ATRA sensitivity and leukemia development in vivo. Targeting these mutated proteins with new drugs may improve treatment of AML patients.
|4.||Mark Gerstein||Yale University||United States||2013-01-10||Dysregulation of Regulatory Networks in Cancer||We would like to investigate changes to the genome that occur in cancer, and how those changes affect the coordinated activity of genes (gene networks and pathways), as well as the functioning of pathways important to the healthy operation of a human cell. We hope this will reveal insights into how cancer cells function differently from healthy cells, and help us better classify cancer types and subtypes. |
|5.||Robert Bradley||Fred Hutchinson Cancer Research Center||United States||2013-03-19||Dysregulation of gene expression in tumors||The improper regulation or expression of particular genes is known to play important roles in cancer development. Recent technological developments have enabled individual laboratories, as well as large collaborations, to study the expression levels of hundreds or thousands of genes simultaneously in samples from cancer patients as well as healthy individuals. These studies will allow us to greatly increase our understanding of how cancers form and grow. In order to identify genes that are important for cancer development, we create computational methods to analyze these "gene expression datasets," thereby identifying potential future therapeutic targets. |
|6.||Jason Lu||OmicSoft Corporation||United States||2013-02-18||Systematic identification of genome alterations in cancer||Cancer cells have changes in DNA sequences which play a fundamental role in maintaining cell growth and other normal functions. Identifying these genome alterations is essential for understanding the initiation of cancer, how a tumor progresses, and why a treatment is effective for some patients but not for others. We aim to develop computational methods and tools to identify genome changes specifically occurring in each patient, providing the basis for developing targeted therapy for cancer. |
|7.||Dr. Steven J Jones||BC Cancer Agency - Michael Smith Genome Sciences Centre||Canada||2012-12-13||Comparison of the somatic mutational spectrum of medulloblastomas with other cancer types||To evaluate the relevance of changes found in the genetic make up of pediatric brain cancer patients, these changes have will be compared to information available from other cancer types. This cross comparison will potentially enable the identification of disease specific, novel or existing approaches to treatment. |
|8.||John McPherson||Ontario Institute for Cancer Research||Canada||2013-04-10||International Cancer Genome Consortium (ICGC): Pancreatic Cancer Project.||Cancer can result from changes in a person's genetic material (DNA). By studying the genetic changes, researchers can learn what causes cancer. This will lead to new ways to prevent, detect and treat cancer. The International Cancer Genome Consortium (ICGC) was created to coordinate a large number of research projects. The ICGC will develop a comprehensive catalogue of the genetic changes in cancer.
As a contributing member of the ICGC, the OICR will generate a comprehensive catalogue of genomic abnormalities found in pancreatic tumours. Our target is to collect the requisite 500 independent tumours and their matched controls and fully characterize 350 of these.
The main goal of the ICGC collaboration will allow members from sites world wide to advance cancer research by analysis of a large number of genomes through the comparison of genes involved in multiple cancer types. |
|9.||Ming Tsao||University Health Network||Canada||2012-07-03||International Cancer Genome Consortium (ICGC): Pancreatic Cancer Proejct||Cancer can result from changes in a person's genetic material (DNA). By studying the genetic changes, researchers can learn what causes cancer. This will lead to new ways to prevent, detect and treat cancer. The International Cancer Genome Consortium (ICGC) was created to coordinate a large number of research projects. The ICGC will develop a comprehensive catalogue of the genetic changes in cancer. As a contributing member of the ICGC, the OICR will generate a comprehensive catalogue of genomic abnormalities found in pancreatic tumours. The target is to collect the requisite 500 independent tumours and their matched controls and fully characterize 350 of these. The main goal of the ICGC collaboration (OICR, University Health Network, University of Toronto) will allow members from sites world wide to advance cancer research by analysis of a large number of genomes through the comparison of genes involved in multiple cancer types. |
|10.||Sachdev Sidhu||University of Toronto||Canada||2012-07-26||International Cancer Genome Consortium (ICGC): Pancreatic Cancer Project
http://www.icgc.org/||Cancer can result from changes in a person's genetic material (DNA). By studying the genetic changes, researchers can learn what causes cancer. This will lead to new ways to prevent, detect and treat cancer. The International Cancer Genome Consortium (ICGC) was created to coordinate a large number of research projects. The ICGC will develop a comprehensive catalogue of the genetic changes in cancer. As a contributing member of the ICGC, the OICR will generate a comprehensive catalogue of genomic abnormalities found in pancreatic tumours. The target is to collect the requisite 500 independent tumours and their matched controls and fully characterize 350 of these. The main goal of the ICGC collaboration (OICR, University Hospital Network, University of Toronto) will allow members from sites world wide to advance cancer research by analysis of a large number of genomes through the comparison of genes involved in multiple cancer types. |
|11.||Dan Rhodes||Compendia Biosciences, Inc.||United States||2012-12-20||Integrative analysis of cancer genomes||We aim to study the relationships among different genetic events in cancer. It is our goal to establish an improved molecular sub-classification of cancer that could be useful in cancer diagnosis and treatment. |
|12.||xiaosong wang||Baylor College Of Medicine||United States||2012-11-16||Genome-wide detection of driving genetic aberrations and drug targets in epithelial tumors using an integrative genomics approach||This proposal seeks to employ a robust integrative genomics approach to discover driving genomic alternations and drug targets in epithelial tumors. This approach looks for oncogenes and therapeutic targets using evidence from different levels of cancer genome sequencing and profiling datasets. We will integrate data from multiple projects, such as International Cancer Genome Project, The Cancer Genome Atlas Project, Tumor Sequencing Project, Genome-Wide Association Studies, etc. We will focus our discovery in breast and lung cancers; a priority will be given to recurrent structural or numerical chromosome rearrangements or deregulated oncogenes that can be inhibited by small molecule drugs. |
|13.||Bernard Fox||Providence Cancer Center, Earle A. Chiles Research Institute||United States||2013-03-26||Analysis of Genomic Prostate Cancer Profiles from the International Cancer Genome Consortium for Correlations with Patient’s Phenotypes in a Prostate Cancer Immunotherapy Research Study||Comparison of matched normal and prostate cancer genomes has given insights to genomic variations which we propose to examine for correlations with protein, gene expression, and clinical data in our prostate cancer immunotherapy research participants. |
|14.||Mamatha Shekar (Mahadevappa)||NextBio||United States||2013-01-15||Integration and analysis of cancer genomic data||We have developed an online database that integrates a large number of diverse biological datasets to build models of different cancer types. We will use the datasets from ICGC to complement the current models providing researchers with a comprehensive list of genes and mutations that may underlie different cancer types and various clinical phases within a given cancer. |
|15.||Martin Vingron||Max Planck Institute for Molecular Genetics||Germany||2012-11-27||CancerEpiSys - Integrative analysis of epigenetic networks that determine the chronic lymphocytic leukemia disease state||CancerEpiSys is a BMBF funded research project with the CancerSys program that dissects the epigenetic networks associated with chronic lymphocytic leukemia (CLL) to develop novel diagnostic and therapeutic approaches for the disease. It has been initiated based on the emerging view that signals encoded in the DNA sequence, epigenetic modifications (e.g. DNA methylation, histone modifications), and other regulatory factors are not independently regulated properties. Rather, these factors are governed by an interconnected network of molecular processes that determine the cellular gene expression program. Any errors that occur in the interplay of these factors can lead to aberrant gene regulation associated with cancer. To rationalize the mode of action of novel ‘epigenetic’ drugs in cancer therapy that change properties of this network, we will dissect experimentally and mathematically the interdependence of these processes, focusing on CLL. |
|16.||Mark Daly||Broad Institute||United States||2012-07-26||Identification of Rare Variants Causing Drug-Induced Liver Injury||We are searching for genetic difference that explain why a very rare segment of the population has severe, unpredictable, and potentially life-threatening adverse reactions to routine medication use of prescribed dosage. Understanding the genetic susceptibilities may lead to genetic testing so that alternate drugs may be prescribed to specific individuals or that an additional drug can be added to avoid the reaction in such individuals. |
|17.||Dongwan Hong||National Cancer Center||South Korea||2013-05-14||An accurate approach to identifying somatic mutations from cancer genome sequencing||Recently, next generation sequencing (NGS) has been used to study cancer affecting specific tissues and organs because it has several advantages over previous methods. NGS data analysis methods and software have been used to characterize cancer genomes and identify various types of somatic variants driving cancer progression. Although there are many computational tools for NGS data analysis, most of these methods don't take into account the nature of cancer so that critical steps and considerations for cancer genome analysis are overlooked. Therefore, cancer-specific NGS methods and software are needed to improve early cancer diagnosis, prediction of patient prognosis, patient cancer sub-type classification, and personalized treatments. The goal of our project is to develop an accurate analysis method to detect all types of somatic variants and annotate them in a cancer specific manner. |
|18.||Heidi Okamura||Aveo Pharmaceuticals||United States||2012-07-10||Identification of predictive biomarkers for targeted cancer therapeutics||One of the major challenges of targeted therapies is to identify the patient population most likely to benefit from a particular drug, since cancer is such a complex collection of heterogeneous diseases. The aim of our project is to determine a molecular “signature”, or pattern of gene expression, that would identify tumors dependent on a particular group of proteins that work together to control functions like cell growth or survival. This molecular signature could then be used to identify patients in the clinic that are more likely to respond to inhibitors of that particular cell growth or survival pathway, potentially resulting in more effective therapies. |
|19.||David Adams||Wellcome Trust Sanger Institute||United Kingdom||2013-04-25||Integration and Validation of Bioinformatics Software Tools on Cancer Genomes||We are interested in identifying DNA changes in a broad range of cancer tumours that give rise to and drive the development of the cancers themselves. To do this we are using a number of scientific software programs to perform complex computational analyses. We are taking the ‘two-heads-are-better-than-one’ approach, i.e. by overlapping results from many software programs we seek to obtain better and more reliable results in terms of revealing differences in cancer tumour DNA. Our aim in using the ICGC data is to provide gold standard data sets of known DNA changes reported from laboratory experiments, against which we can evaluate how well the scientific software programs are performing and how well the ‘two-heads-are-better-than-one’ approach works. |
|20.||Kelly Frazer||University of California, San Diego||United States||2013-05-02||Cancer Genetics||Most cancers have a strong genetic component. Genetic association studies have demonstrated that some patients can inherit a higher genetic risk of specific cancers. The tumor itself is believed to develop from benign to malignant as a consequence of an accumulation of mutation events in genes important for cancer, leading to uncontrollable cell proliferation. By analyzing tumor and matched normal genomic profiles, we seek to identify biomarkers for cancer susceptibility, cancer progression, and genetic changes responsible for tumor growth. By establishing a refined genetic landscape of cancer, we can improve diagnosis and prognosis, classify tumors, open new pathways for drug discovery, and help physicians select the optimal therapeutic option for each individual patient. We would like to use the ICGC as reference data sets to test bioinformatic algorithmdevelopment, and to compare expression and mutational profiles to our own tumor collections. |
|21.||Jan Korbel||European Molecular Biology Laboratory||Germany||2012-09-06||Dissecting genetic determinants for complex genomic DNA alterations in cancer||Until recently, researchers have thought that cancer generally occurs in patients as the result of the action of multiple subsequent mutations. We and others, have, however, recently found evidence for an alternative mechanism, which involves massive chromosome rearrangements resulting from a single, one-step catastrophic event, termed 'chromothripsis'. We recently discovered that chromothripsis is particularly abundant in childhood brain tumor patients carrying a hereditary mutation in the p53 gene, a finding that was important for understanding this particular cancer development phenomenon. We will, in addition to p53, try to find whether mutations in other cancer genes are occurring in connection with chromothripsis, to further understand the molecular basis of this phenomenon (and related phenomena) in cancer. |
|22.||Gad Getz||Broad Institute||United States||2012-09-13||Genetic characterization of chronic lymphocytic leukemia||Chronic lymphocytic leukemia (CLL) is the most common leukemia in the western hemisphere. It remains incurable and its highly variable course is difficult to predict. Through advanced genetic research technologies, we will characterize the genetic landscape in CLL and its implications on the causes of CLL .
We performed an analysis of the all genes that encode proteins of 135 samples of CLL, detecting commonly occurring genetic alterations. The increased size of the patient group allows for detection of genetic events that occur in a small proportion of cases as well as the alterations that affect large proportion of cases.
We aim to perform an analysis combining these data as well as publicly available data (e.g from the International Cancer Genome Consortium), to better assess the identity and the proportion of cases affected by recurrently mutated genes. |
|23.||Charles Vaske||Five3 Genomics||United States||2012-09-13||Association of pathway signatures with mutational spectrum in cancer||Each gene in the genome interacts with other genes in two ways: a gene's activity is regulated by others, and the biological activity of a gene in a cell may require the coordination of other gene's. In tumors, mutations will aberrantly turn genes on or off, resulting in the abnormal behaviors of tumor cells. We will map each tumor's mutations onto the set of genes, and then the corresponding interactions, in an attempt to explain tumor cell's behavior in terms of how these regulatory interactions have been modified. We will provide an overview of what sets of interactions are most often modified together, in order to better understand what biological processes must be co-regulated in cancer. |
|24.||Geoffrey Faulkner||Mater Medical Research Institute||Australia||2012-10-05||Endogenous L1 mobilisation in human hepatocellular carcinoma
http://research.mater.org.au/Research/Understanding-and-Preventing-Disease/Cancer-Biology-Program/Genome-Plasticity-and-Disease-Group.aspx||This project intends to screen DNA sequences produced by ICGC for unusual mutations that occur in tumors. In particular, we will search for regions of DNA that have been rearranged in tumor cells but not in the normal cells of the body. These rearrangements can occur in genes that are essential to stopping normal cells changing to tumor cells and are therefore of high interest in understanding how a tumor starts to form. |
|25.||Alex Ramos||H3 Biomedicine||United States||2012-11-09||Mining ICGC data for target identification and patient selection biomarker discovery|| Cancer is caused by genetic changes in the genome that lead to deregulation of key cancer “driver” genes. We aim to analyze patterns of genetic changes across tumor samples derived from multiple tissue sites to identify new driver genes. Characterization of cancer genomes from such analyses will be a tremendous aid to our understanding of cancer biology and could ultimately lead to novel therapeutic approaches in genetically-defined populations of cancer patients. |
|26.||Dan Simovici||University of Massachusetts Boston||United States||2012-10-17||An Algorithm to Detect Copy Number Variations Corresponding to Driver Mutations in Cancer using Compression||Human DNA contains approximately three billion letters, A, C, G, and
T, arranged in specific sequences. Occasionally, large blocks of
these letters duplicate or rearrange, which not only can cause cancer,
but also make the treatment of cancer extremely challenging.
Computers can search cancer patients' DNA sequences for these
duplications and rearrangements, but with three billion letters, the
task is daunting even for high-speed computers. Our computational
approach greatly accelerates this search by first distilling these
enormous DNA sequences down to much smaller fingerprints, and then
searching the smaller fingerprints for patterns found in cancer. We
are using the International Cancer Genome Consortium sequence data as
a benchmark, to develop and test our computational approach.
Ultimately, we anticipate that this research will be enormously
beneficial in clinical settings.
|27.||John Castle||TRON||Germany||2012-11-19||Individualized cancer combination therapy||Immunotherapies have the potential improve the outcome of cancer patients. Our institute is running clinical trials testing therapeutic RNA vaccines, in which a patient’s immune system is triggered to attack cancer cells. To trigger an immune response against cancer cells, we seek to identify those genes, including mutated genes, which are found only in the cancer cells. By profiling a collection of cancer samples, we can identify the frequency and co-occurrence of mutations and tumor-specific genes (antigens). We will select the most promising tumor-specific antigens and then proceed to make therapeutic RNA vaccines that encode for these cancer antigens, followed by clinical trials that hopefully demonstrate a benefit for the patient. |
|28.||Matthieu Schapira||University of Toronto||Canada||2012-11-09||Discovery of oncogenic gene fusion events involving chromatin regulators||Chromatin regulators are a class of proteins that control the expression of target genes. This control mechanism is often de-regulated in cancer. Gene fusion events involving chromatin regulators have been shown to be driving certain forms of cancer, and so far were found mostly in leukemia. For instance, fusions of the chromatin regulator MLL with other genes is driving 70 % of an acute form of leukemia in infants. These proteins are therefore biologically valid targets for cancer therapy. Here, we will look for new fusion events involving chromatin regulators from cancer patients, with a focus on non-leukemia cancer forms, such as breast, prostate or lung cancer. Our goal is to uncover novel gene fusions driving cancer, which will help prioritize drug discovery programs. |
|29.||Benedikt Brors||German Cancer Research Center||Germany||2013-03-06||Correlation between DNA methylation and other epigenetic changes in CLL||Cancer is a disease caused by acquired changes in the genome during lifetime. There is accumulating evidence that this is not entirely due to direct changes in the DNA (the 'genome material'), but also by changes in associated proteins, or by chemical modification of DNA called methylation. We are investigating such changes, which are called epigenetic since they are not directly inherited by copying of the DNA, in a disease called chronic lymphocytic leukemia (CLL). One of the ICGC networks has already investigated such changes in CLL and published the results in a scientific journal. We want to use these data to construct a map of typical patterns of DNA methylation in CLL. We will then use our own data on additional epigenetic changes to relate these to the findings that have been already published. |
|30.||Manish Gala (Independent Investigator Status)||Massachusetts General Hospital||United States||2013-02-18||Germline Mutations in Ras/Raf-initiated Carcinogenesis||Certain mutations occur with high frequency in cancers at multiple sites in the body. While these mutations can predispose someone to develop cancer from normal tissue, previous studies have demonstrated that additional mutations are required to overcome anti-cancer barriers. We hope to use the ICGC data and other data to help us develop novel computer algorithms to find these helper mutations. |
|31.||Tatsuaki Morokata||Astellas Pharma Inc.||Japan||2013-02-08||Investigation of innovative drug targets and biomarkers for cancer therapeutics.||Astellas Pharma Inc. is committed to providing highly effective drugs to oncology patients. We believe that understanding the complexity of cancer is absolutely necessary to the development of drugs with higher efficacy and fewer side effects, and that the data of the International Cancer Genome Consortium (ICGC) will provide us with a deep understanding of the genetic context of cancer cells and tissues. By applying computer analyses to the ICGC data, we will explore some genomic alterations specifically observed in some types of cancer. We will then combine the results with clinical information to identify mutated proteins which may cause cancer, and experimentally validate the ability to induce tumor formation. We believe that analyses such as these using the ICGC data will provide us the opportunity to find novel drug targets or biomarkers and make it possible to develop cancer medicines for defined patient populations with precise diagnoses. |
|32.||Carlos Martinez-A.||Centro Nacional Biotecnologia||Spain||2012-12-21||Study of the implications of the Dido locus in chromosome 20 (death inducer obliterator protein ) in hematological myelodysplasia||The aim of this research is to study the DNA coding regions of the Dido (death inducer-obliterator protein) gene, to identify its possible implication in the development of a type of cancers that affect the blood. We use the mouse as a model to study MDS/MPD diseases (myelodysplastic/ myeloproliferative diseases, a subgroup of blood cancers).
Our recent research showed that alterations in Dido protein expression cause a transplantable disease whose symptoms and signs suggested myelodysplastic diseases. Our findings indicate that Dido might be one of the genes involved in the development of this group of diseases. With access to the International Cancer Genome Consortium (ICGC) datasets, we will study the DNA coding sequences of genes from patients with myelodysplastic diseases and compare them with sequences from healthy donors. With this study, we intend to gather sufficient information about Dido gene function to contribute to develop new treatments and diagnostic tools. |
|33.||Claude Chelala||Barts Cancer Institute, Queen Mary University of London||United Kingdom||2013-01-18||Integrated meta analysis of pancreatic ductal adenocarcinoma studies towards prognostic biomarker discovery||Pancreatic cancer is amongst the leading cause of cancer deaths in the world with an overall 5 year survival of less than 5%. Over the past decade, a number of research efforts aimed at studying gene expression profiles have identified patient groups (disease subtypes) that respond differently to the same treatment. We are compiling these studies for meta analysis in order to validate the reproducibility of disease subtypes across multiple studies. Moreover, the project aims to identify potentially new subtypes that are correlated with patient's clinical outcome, and subsequently test their robustness and reproducibility on independent patient cohorts. |
|34.||Sami Kilpinen||MediSapiens Ltd||Finland||2013-01-24||Next-generation of bioinformatic tools for personalized medicine||MediSapiens Ltd is developing innovative software tools for both drug development and personalized medicine. While modern technology allows rather efficient genetic analysis of individuals, the interpretation of the resulting information remains a considerable challenge. With proper tools one could use these existing large scale datasets to interpret data from individual patients. This would enable e.g. tailoring medical treatment to suit the patient and illness better. In drug development, the ability to visually explore and analyze complex and large datasets is essential for the development of effective new therapies for cancer. |
|35.||Parminder Mankoo||Sanofi Aventis||United States||2013-02-07||Identifying subtype-specific mechanisms and novel drug targets and biomarkers using ICGC genomic and clinical data||This project aims to further personalized medicine by identifying tumor-driving gene alterations and novel drug targets that are found only in specific cancer subtypes. We will achieve this goal by integrating multi ICGC data types along with clinical data correlation analyses. We will apply novel methods to identify patterns of correlation and mutual exclusivity defining different cancer subtypes. Secondly, we plan to correlate these identified cancer subtypes with clinical outcomes (for example, survival and progress-free survival). This research will improve understanding of the molecular mechanisms of cancers, support target identification, and facilitate patient stratification that will most benefit from subtype-specific therapy. Significant findings will be validated on cell lines and mouse models derived from human tumor, followed by subtype-specific drug development, potentially leading to better personalized patient cancer therapy. |
|36.||Jan Paul Medema||Academic Medical Center, University of Amsterdam||Netherlands||2012-12-13||Influence of the tumor microenvironment on cancer cell plasticity, behavior and clinical outcome
||Tumors consist not only of a bulk of malignant cells, but also contain a complex mixture of different cells that are not malignant, like blood vessels or immune cells, as well as molecules that surround tumor cells that together form the tumor stroma, also referred to as the tumor microenvironment. Only fairly recently has the importance been recognized of the interactions between the microenvironment and cancer (stem) cells for tumor development, progression and metastasis. Understanding how the crosstalk between these compartments is mediated could give important clues for the development of novel cancer treatments, which should prove very effective against cancers that depend on a strong stromal response. |
|37.||Kamalakar Gulukota||NorthShore University HealthSystem||United States||2013-01-09||Genomics of Pancreatic Cancer||Pancreatic cancer is a very aggressive tumor resulting in death in about a year in most cases. However, there are some patients who survive 5 years and more after diagnosis. Our project attempts to look at these patients in an attempt to determine the characteristics of these tumors. The goal is to provide a more reliable prognosis to patients' data on the basis of the molecular characterization of their tumor. |
|38.||Pedro Galante||Hospital Sirio-Libanês||Brazil||2013-02-07||Study of retroposition events in cancer||A major set of cancers is caused by alterations in DNA. The identification of these alterations is essential for understand the initiation and progression of this disease. Recently, next generation DNA sequencing (NGS) has enabled us to better characterize various types of somatic variants, such as complex genomic variations involving chromosomal rearrangements and retrotransposable elements, such as LINEs and SINEs (Long/Short Interspersed Nuclear Elements, respectively). In general, the identification of these variations is based on comparisons between sequences from normal and tumor samples. Here, we aim to analyze the amazing set of tumor and normal sequences produced by ICGC to identify complex somatic variations. Our focuses are those variations involving retrotransposable elements, such as LINEs, SINEs and other retrocopied elements. We expected to find a small, but interesting set of somatic variations involving these elements in tumors. |
|39.||Lars Kaderali||University of Technology Dresden||Germany||2013-04-04||Non-coding RNAs in cancer development||While it is well known that mutations in our genomic information are associated with cancer, much less is known about how such mutations affect regulatory mechanisms in the cell. In this project, we focus on the role of alterations in regulatory regions of our genome (so-called noncoding RNA), and their role in cancer development. For this purpose, we will develop and apply novel bioinformatics tools to model cellular regulatory mechanisms, map noncoding RNA data to these networks, and analyze the role these networks play in tumor progression based on the sequencing data from the ICGC consortium. We hope that through this procedure we will not only get a clearer idea of the role of noncoding RNAs in cancer, but possibly also identify new points of attack to impede cancer progression. |
|40.||Keyue Ding||Chongqing Medical University||China||2013-04-19||Genetic mechanisms of virus-related hepatocellular carcinoma||Hepatocellular carcinoma (HCC) is the fifth most common cancer in men and the seventh in women. Major risk factors for HCC include infection with hepatitis B virus (HBV) or hepatitis C virus (HCV), alcoholic liver disease, and most probably nonalcoholic fatty liver disease. In the proposed study, we aim to use data from the ICGC data portal to systematically characterize mutation patterns in HCC with different causes. We will also sequence DNA from cancer tissues, adjacent normal tissues and immune system cells in ten patients with HBV-associated HCC. Using this data, we aim to identify "driver genes" involved in HCC development. |
|41.||Nicholas Shackel||Centenary Institute||Australia||2013-05-13||Discovering Novel Non-Invasive Diagnostic and Prognostic Markers in Hepatocellular Carcinoma||The aim of this research is to utilize available data to identify genome changes occurring in liver cancer and to determine their molecular “signatures”, in order to help determine both the cause of these genome changes together with the outcomes of patients with liver cancer. With access to the International Cancer Genome Consortium (ICGC) dataset, we will be able to screen DNA sequences for changes that occur in liver cancer and to compare them to our own data. |
|42.||Peter Campbell||Wellcome Trust Sanger Institute||United Kingdom||2013-03-11||Deciphering the mutational landscape and signatures of mutational processes active in the genomes and transcriptomes of human cancers||In this project, we will identify somatic (non-inherited) changes in the DNA sequence of cancer patients. These changes will be separated from germ-line (inherited) changes by comparing the patient's cancer DNA to that of their normal DNA. We will then record the distributions of these DNA rearrangements or changes across different cancer types, and we will study the genetic and genomic context in which they occur. We will further investigate and report the functional consequences of the somatic (non-inherited) genomic changes. We will also explore the relationships between different types of somatic changes such as DNA/gene rearrangements or DNA insertions and/or deletions. |
|43.||Sergi Castellvi-Bel||Institut D'Investigacions Biomediques August Pi i Sunyer (IDIBAPS)||Spain||2013-04-03||Identification of new genes for predisposition to colorectal cancer by exome sequencing||The main objective of this research project is the identification of new genes responsible for familial colorectal cancer (CRC) predisposition by sequencing the part of the human genome that codifies for proteins (whole-exome sequencing) in selected cases with familial aggregation but no alteration of genes involved in the known CRC hereditary forms (polyposis forms and Lynch syndrome).
Access to sequencing data files corresponding to the germline coding genome of 105 cases from the Chronic Lymphocytic Leukemia (CLL) ICGC project will permit to perform a control of the filtering and prioritization strategy used in our dataset in an independent dataset. Those variants shared in the CRC and CLL datasets will be most probably false positives findings, not likely to be involved in CRC genetic predisposition. |
|44.||Trey Ideker||University of California, San Diego||United States||2013-04-30||Network analysis and classification of cancer||Emerging evidence shows that cancer is not a disease of single genes but of entire cellular pathways and networks. Analysis of massive, genome-scale datasets across large patient cohorts presents unique challenges from both the perspective of data integration and the development of tools for use in the clinical community. Our project aims to combine multiple types of genome scale data, such as mRNA expression and DNA mutations, in meaningful ways. We will make use of cellular pathway models in order to improve diagnostic and prognostic prediction tools, highlight potential drug targets, and characterize cellular pathways that play active roles in cancer progression. |
|45.||David Torrents||BSC-IRB Research Programme in Computational Biology||Spain||2013-05-03||Validation and discovery of new structural rearrangements in human Medulloblastoma||Cancer is an unfortunately prevalent disease affecting millions of people. Finding adequate therapies is made difficult by the fact that different cancers show different alterations of the information encoded by the genetic material. Moreover these alterations are also quite different between patients affected by the same cancer type.
In order to develop successful therapies, researchers need to understand how cancer evolve from normal cells, how it progresses, and what biological features can point to a particular clinical outcome. This is why the main effort in cancer research is now addressed by sequencing genetic material of many affected patients and for many different cancer types.
Our project is to apply the computational tools we have developed on these large datasets, in order to find new genetic modifications that can lead to cancer and can be targeted by therapy. |
|46.||George Bova||University of Tampere Institute of Biomedical Technology||Finland||2013-04-26||Integrated Studies of Cancer Genomics||The University of Tampere, Finland Institute of Biomedical Technology (IBT) is a collaborator in the ongoing ICGC Prostate Cancer-UK project, whose principal aim is to define the genomic basis of prostate cancer, and to use this information to improve prevention, diagnosis, and therapy of this common disease. Prof. Bova is a PI in the prostate cancer-UK project group, and he is mainly focused on analysis of metastatic prostate cancer samples which are a critical component of the ICGC Prostate Cancer-UK project. At IBT, working together with Prof. Visakorpi and Nykter and team members, we will use a combination of the ICGC data and data generated locally to build models to support the development of a system to enable effective prevention, diagnosis, and treatment of cancer tailored to each patient and their unique characteristics. |
|47.||John McPherson||Ontario Institute for Cancer Research||Canada||2013-05-13||International Cancer Genome Consortium (ICGC): Pancreatic Cancer Project||Cancer can result from changes in a person's genetic material (DNA). By studying the genetic changes, researchers can learn what causes cancer. This will lead to new ways to prevent, detect and treat cancer. The International Cancer Genome Consortium (ICGC) was created to coordinate a large number of research projects. The ICGC will develop a comprehensive catalogue of the genetic changes in cancer.
As a contributing member of the ICGC, the Ontario Institute for Cancer Research will generate a comprehensive catalogue of genomic abnormalities found in pancreatic tumours. Our target is to collect the requisite 500 independent tumours and their matched controls and to fully study and describe 350 of these.
The ICGC collaboration will allow members world wide to advance cancer research through analysis of a large number of genomes from multiple cancer types. |