Search Results - EGA European Genome-Phenome Archive

Identification of Targetable FGFR Gene Fusions in Diverse Cancers

In this study, patients with advanced cancer across all histologies were enrolled in our IRB approved clinical sequencing program, called MI-ONCOSEQ, to go through an integrative sequencing which includes whole exome sequencing of the tumor and matched normal, and transcriptome sequencing. Four index cases were identified which harbor gene rearrangements of FGFR2 including two cholangiocarcinoma cases, a metastatic breast cancer case, and a metastatic prostate cancer case. After extending our assessment of FGFR rearrangements across multiple tumor cohorts, including TCGA, we identified FGFR gene fusions with intact kinase domains of FGFR1, FGFR2, or FGFR3 in cholangiocarcinoma, breast cancer, prostate cancer, lung squamous cell cancer, bladder cancer, thyroid cancer, oral cancer, glioblastoma, and head and neck squamous cell cancer. All FGFR fusion partners tested exhibit oligomerization capability, suggesting a shared mode of kinase activation. Overexpression of FGFR fusion proteins in vitro induced cell proliferation, and bladder cancer cell lines that harbors FGFR3 fusion proteins exhibited enhanced susceptibility to pharmacologic inhibition in vitro and in vivo. Due to the combinatorial possibilities of FGFR family fusion to a variety of oligomerization partners, clinical sequencing efforts which incorporate transcriptome analysis for gene fusions are poised to identify rare, targetable FGFR fusions across diverse cancer types.

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Whole Genome Comparisons of Breast Cancers and their Xenotransplants

Early passage breast cancer xenografts have been proposed as alternatives to cell lines as model systems for studying the basic biology of tumors and for advancing therapy development. This study explores the relatedness of primary disease genomes to their matched xenotransplants. Using paired-end massively parallel sequencing 17 matched progenitor tumor, xenograft and normal trios were sequenced to at least 30-fold coverage with diploid coverage of at least 95% of the genome as determined by SNP array concordance. RNA sequence was generated from the xenograft tumors. The xenografts were derived from a spectrum of tumor samples from patients with both early and advanced breast cancer.

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University of North Carolina at Chapel Hill (UNC) Hepatocellular Carcinoma Study by Exome Sequencing (HCCSES)

Genetic alterations in specific driver genes lead to disruption of cellular pathways and are critical events in the instigation and progression of hepatocellular carcinoma. As a prerequisite for individualized cancer treatment, we sought to characterize the landscape of recurrent somatic mutations in hepatocellular carcinoma. We performed whole exome sequencing on 87 hepatocellular carcinomas and matched normal adjacent tissues to an average coverage of 59x. The overall mutation rate was roughly 2 mutations per Mb, with a median of 45 non-synonymous mutations that altered the amino acid sequence (range 2 to 381). We found recurrent mutations in several genes with high transcript levels: TP53 (18%), CTNNB1 (10%), KEAP1 (8%), C16orf62 (8%), MLL4 (7%) and RAC2 (5%). Significantly affected gene families include the nucleotide-binding domain and leucine rich repeat containing family, calcium channel subunits, and histone methyltransferases. In particular, the MLL family methyltransferases for histone H3 lysine 4 were mutated in 20% of tumors. Conclusion: The NFE2L2-KEAP1 and MLL pathways are recurrently mutated in multiple cohorts of hepatocellular carcinoma.

Study phs000627

Characterization of a Metastatic Cervical Cancer Patient and HPV18 Integration Using Next Generation Sequencing

In this study, we used shallow whole genome, exome, and RNA sequencing to genomically and transcriptomically characterize a cervical squamous carcinoma lesion metastatic to the lung and to detect and analyze HPV infection in the same sample.

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Genetic Epidemiology of Lung Cancer Consortium GWAS of Familial Lung Cancer

Familial lung cancer cases were collected by the Genetic Epidemiology of Lung Cancer Consortium (GELCC) recruitment sites: University of Cincinnati, Karmanos Cancer Institute at Wayne State University, Louisiana State University Health Sciences Center-New Orleans, Mayo Clinic, and Medical College of Ohio. Familial cases for this study came from three sources: 1) one case each from families (at least 3 affected lung cancer cases in the family) included in the linkage analysis; 2) one case from linkage-eligible families (at least 3 affected lung cancer cases in the family) but where there were insufficient biospecimens available to make them informative for linkage analysis; and 3) one case from families not eligible for the linkage study with a family history of at least one first or second degree relative affected with lung cancer. Unrelated controls were selected from 1) among the spouses of family members, thus matching on socio-economic status (SES) and ethnicity (typically) of the cases or 2) from case-control studies of lung cancer conducted in the same location in which the linkage families were collected and matched on age, sex, and race. All cases and controls self-reported as European American. Biospecimens used for normal DNA extraction included blood, saliva or mouthwash. Some samples underwent whole genome amplication.

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NHLBI GO-ESP: Family Studies (Hematological Cancers)

The NHLBI "Grand Opportunity" Exome Sequencing Project (GO-ESP), a signature project of the NHLBI Recovery Act investment, was designed to identify genetic variants in coding regions (exons) of the human genome (the "exome") that are associated with heart, lung and blood diseases. These and related diseases that are of high impact to public health and individuals from diverse racial and ethnic groups will be studied. These data may help researchers understand the causes of disease, contributing to better ways to prevent, diagnose, and treat diseases, as well as determine whether to tailor prevention and treatments to specific populations. This could lead to more effective treatments and reduce the likelihood of side effects. GO-ESP is comprised of five collaborative components: 3 cohort consortia - HeartGO, LungGO, and WHISP - and 2 sequencing centers - BroadGO and SeattleGO. Two major goals in the study of human malignancies are (i) to understand the genetic basis that underlies the predisposition of certain individuals to develop cancer and (ii) to identify the full spectrum of acquired mutations that occur in human cancers. There has been some progress in both of these areas with respect to hematologic malignancies but much remains to be discovered. As a result of recent advantages in sequencing technologies it is now feasible to sequence multiple individual whole exomes at reasonable cost. Such technologies provide a unique opportunity to transform our understanding of the biological basis of human cancer and to identify inherited genetic variants that predispose individuals to the development of hematologic malignancies. Myeloproliferative neoplasms (MPN), myelodysplastic syndrome (MDS) and acute leukemia are clonal disorders of hematopoieis. Our study involves performing whole exome sequencing of individuals with these disorders for the purpose of identifying (i) novel inherited genetic variants associated with the risk of developing of MPN/MDS/acute leukemia and (ii) novel acquired mutations associated with the development of MPN/MDS/acute leukemia.

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National Cancer Institute (NCI) Genome Wide Association Study (GWAS) of Lung Cancer in Never Smokers

A genomewide study of lung cancer in never smokers Abstract and specific aims In the United States, lung cancer incidence and mortality rates have been steadily declining over the past decade, following decline in the prevalence of tobacco smoking. However, lung cancer remains the leading cause of cancer death, killing more patients than breast, colon, and prostate cancers combined. Although tobacco smoke is the predominant risk factor for development of lung cancer, some patients develop the disease without a history of tobacco smoking. About 10 - 15% of all lung cancers occur in lilfetime never smokers. This figure will increase as the proportion of never smokers increases in the population. Even at present rates, lung cancer in never smokers, if considered a separate disease, is 6th to 8th top cause of cancer death. The growing number of never smokers in the USA and other countries emphasizes the importance of understanding the epidemiology and biology underlying lung cancer in this group. Genetic polymorphisms associated with the risk of lung cancer in never smokers are expected to overlap with those associated with the risk of lung cancer in ever smokers only partially. Epidemiological, molecular and clinical data suggest that molecular mechanisms of LC may differ in smokers and non-smokers, implying that lung cancer in never smokers is a different disease compared to the lung cancer in smokers. One can expect that there should be stronger genetic component in the control lung cancer in never smokers because effects of the genetic factors in never smokers are unmasked by the lack of tobacco smoke exposure. The genetic epidemiology of lung cancer in never smokers has not been well explored, largely because of difficulties in accruing the needed sample size for association studies. We propose a multicenter (total 14 sites from the US and Europe) genomewide association study of lung cancer in never smokers with the following specific aims: Aim 1: To identify candidate SNPs influencing risk for lung cancer in never smokers using Discovery sample. In the Discovery phase we will genotype 1256 Caucasian cases and 1365 age- and gender-matched never smoker controls using the Illumina Human660W-Quad platform. In addition, we will include in the analysis 284 cases and 175 matched controls already genotyped on the 610Quad platform. In this phase we will only include the study sites that have collected blood specimens (MDACC, Mayo Clinic, Karmanos Cancer Institute, The University of Liverpool Cancer research Centre, Institute of Cancer Research in Sutton, and Lunenfeld Research Institute in Toronto, Canada). All the samples will be sent to the independent lab for genotyping, to reduce site-specific technical artifacts. The final sample will consist of 1540 cases and 1540 controls matched by study site. Aim 2: To perform the second phase (validation) analysis of significant SNPs identified in aim 1 using an independent set of cases and controls. SNPs associated with risk at the significance level of 0.01 or below in the discovery set will be included in the replication phase. The proposed threshold guarantees an adequate power to retain SNPs with the typical effect size of 1.3. We plan to carry 6000-7000 SNPs for validation. The independent replication set will include 800 cases and 800 controls, mostly from sites that collected tissue (Mayo Clinic, Karmanos Cancer Institute, UT Southwestern) or buccal specimens (UCLA), but also blood samples (Imperial College London, University of Pennsylvana, German Cancer Research Center, Heidelberg, National Research Center for Environment and Health, Neuherberg, Carmel Medical Center, Haifa). We will then perform a joint analysis to test the significance of the SNPs identified in the first stage using a stringent critical p-value of 10-7. There will be 2340 cases and 2340 controls in the joint set. Based on our experience with GWAS in smokers and assuming that genetic component in lung cancer risk in never smokers can be higher than genetic component in smokers, we expect to identify about 5-10 candidate regions associated with lung cancer risk in never smokers. Aim 3: To identify and explore pathways associated with the risk of lung cancer in never smokers. Results of the number of studies on the molecular mechanisms and drug response suggest that lung cancer in never smokers is a different disease and different pathways will be associated with lung cancer risk in non-smokers and smokers. To identify pathways and molecular functions associated with lung cancer risk in never smokers we will apply Ingenuity and DAVID bioinformatics tools. We will use at least 300 top candidate genes identified in joint and discovery analysis. The reason why we select rather large number of candidate genes for functional annotation is two-fold: 1. Both algorithms are looking for enrichment of pathways and function by most significant genes and they produce statistically robust results only when number of genes is relatively high. 2. Despite the fact that this study will be largest possible for never smokers we still are underpowered to detect SNPs with relatively small effect size. But though those SNPs will not reach genome wide level of significance they will tend to be on the top of the list. In other words genes from the gray zone (significant on individual level and non-significant for genome wide level) are expected to be enriched by true discoveries. True discoveries are likely to be associated with limited number of pathways / functions while false positives are expected to be uniformly distributed across functions and pathways. Therefore significant clustering of the gene to a given function will suggest that that those genes are true discoveries. This is the first GWAS aiming at identifying the genetic control of susceptibility to lung cancer in Caucasian never smokers. We will combine the available resources from the multiple sites to achieve the sample size sufficient for this study. The study will identify genetic architecture of the predisposition to the lung cancer in never smokers.

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The Effect of the Menstrual Cycle on DNA Expression in the Normal Human Breast Epithelium

The Susan G. Komen for the Cure® Tissue Bank at the IU Simon Cancer Center [www.komentissuebank.iu.edu] (KTB) was established expressly for the prospective collection of normal, healthy breast tissue from volunteer donors. Blood is also obtained from donors at the time of donation and is processed for serum, plasma and peripheral blood leukocyte DNA. Specimens are annotated and data includes age, race, ethnicity, personal health history, family cancer history, medication usage at the time of donation, and breast cancer risk factors. Premenopausal donors to the KTB were identified by a query of the Bank's database. Hematoxylin and eosin stained sections of the formalin-fixed paraffin-embedded tissue of the identified donors were reviewed and tissue was graded on the basis of the abundance of epithelium within the section. Only tissue containing abundant epithelium was considered for this study. Based on dates, the specimens of nine women in the follicular phase of the menstrual cycle and five in the luteal phase were chosen. Six donors using hormonal contraception at the time of donation were also included. Whole blood obtained from 19 of the 20 donors at the time of tissue donation was available and it was processed for serum. Estradiol, estriol, luteinizing hormone and progesterone concentrations were determined by the Indiana University Health Pathology Laboratory using a Beckman Unicel DxI 800 Immunoassay System. The phase of the menstrual cycle was verified by serum progesterone concentration. The epithelium of these 20 specimens was microdissected from multiple 8 micron frozen tissue sections. Total RNA extracted from the tissue was subsequently depleted of rRNA via locked nucleic acid probes. This enabled profiling of both poly-A and non-poly-A RNA species. Barcoded cDNA libraries from the 20 normal breast epithelia were prepared and sequenced on an Applied Biosystems (AB) SOLiD3 or SOLiD 4 platform. RNA-seq reads for each sample were then mapped to the human genome (hg19) using the LifeScope software version 2.5.1 (Life Technologies, Foster City, CA) and BAM (Binary Alignment/Map) files generated. Read counts for each gene were derived from the output BAM files using the RefSeq database (UCSC Genome Brower) as the gene model.

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Breakpoint detection using long insert whole genome sequencing

In this study, we hypothesize that shallow long insert whole genome sequencing (LI-WGS) increases our power for detecting breakpoints compared to shallow short insert WGS. We performed a priori analyses to demonstrate the benefits of LI-WGS, developed a long insert library preparation protocol based off Illumina's protocol, and compared LI-WGS against short insert WGS on test samples. We then used long insert WGS to identify translocations and copy number changes in tumor and germline samples collected from cancer patients with different malignancies.

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Genetic Epidemiology of Chronic Lymphocytic Leukemia

Chronic lymphocytic leukemia (CLL) is a subtype of B-cell lymphoproliferative disorders (LPD), and is the most common form of adult leukemia in Caucasians in the United States. Small lymphocytic lymphoma (SLL) is also a B-cell LPD and is typically considered to be the same disease as CLL, based on pathology. We consider CLL and SLL as the same disease entity, and hereafter refer to both simply as "CLL". Using genealogical databases and cancer records, the familial clustering for CLL is one of the strongest for all cancer sites, strongly implicating germline genetic risk. We ascertained CLL cases and controls for a genomewide association study (GWAS) that was undertaken as part of the International Lymphoma Epidemiology (InterLymph) consortium GWAS. Some CLL cases are also part of extended high-risk CLLpedigrees.

Study phs001568

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