5624 results for "canc*"

in 18.52 milliseconds.

• The genomic complexity of sporadic and inherited retinoblastoma with a matched orthotopic xenograft

  Retinoblastoma is a pediatric cancer of the developing retina. All retinoblastomas are believed to initiate with biallelic inactivation of the RB1 gene. To identify subsequent genetic lesions in retinoblastoma, we performed whole genome sequencing of tumor and normal DNA of 4 children with retinoblastoma and one matched orthotopic xenograft. Both alleles of RB1 were inactivated in the tumor samples. 3 of the patients had sporadic retinoblastoma and one patient had inherited retinoblastoma. Overall, there were few single nucleotide changes in coding regions of the genome and some of the tumors had few chromosomal lesions. There were very few new genetic lesions in the xenograft compared to the primary tumor. These data suggest that the genome in retinoblastoma is more stable than previously believed and there are relatively few recurrent genetic lesions in known cancer pathways other than the RB1 pathway.

  Study phs000352

• Genome-Wide Association Studies in Upper Gastrointestinal Cancers (Asian)

  This project aims to conduct genome-wide association studies (GWAS) in two anatomically different upper gastrointestinal (UGI) cancer sites in two populations with distinctly different disease rates and genetic profiles. One population has very high rates for both esophageal squamous cell carcinomas (ESCCs) and gastric cancers (GCs) and is comprised of Asians (the "Asian UGI GWAS"), while the other population has low rates of ESCC and GC and includes non-Asians from the Americas, Europe, and Australia (the "Non-Asian UGI GWAS"). Study participants for the Asian UGI GWAS reported here (Illumina 660W Quad chip) were drawn from 2 studies, the Shanxi Upper Gastrointestinal Cancer Genetics Project (Shanxi) and the Linxian Nutrition Intervention Trial (NIT), a prospective cohort, and included a total of 1898 ESCCs, 1625 GCs, and 2100 controls. For the 2nd phase (8 TaqMan SNPs), additional subjects from Shanxi and NIT as well as subjects from the Shanghai Men's Health Study (SMHS), the Shanghai Women's Health Study (SWHS), and the Singapore Chinese Health Study (SCHS) were also included (217 ESCCs, 615 GCs, 1202 controls). Altogether 2115 ESCCs, 2240 GCs, and 3302 controls were genotyped in this study.

  Study phs000361

• California Pacific Medical Center Research Breast Health Cohort

  Description of Cohort: The California Pacific Medical Center (CPMC) Breast Health Cohort is a cohort study based at CPMC and is linked to the San Francisco Mammography Registry, one of the sites of the NCI-funded Breast Cancer Screening Consortium (U01CA063740). CPMC is a community hospital in San Francisco, which has one of the highest volumes for mammography in San Francisco. Between September 2004 and June 2007, >90,000 mammograms were performed at CPMC. The CPMC breast health cohort collects demographic and risk factor data on women receiving mammography through participation in the San Francisco Mammography Registry, as part of the Breast Cancer Screening Consortium (U01CA063740). The SFMR database collects information from all sources, including a questionnaire on demographic and risk factor information, the clinical results of the breast examination, the measures of breast density by Dr. John Shepherd and the women who agreed to donate a blood sample. By merging these various sources of information we have very efficiently developed a large sample of women who have donated blood and have had a measure of mamographic density. Blood Collection: Dr. Steve Cummings is leading an effort to collect and archive blood samples from women who are receiving mammography screening. All women who are sent for a screening mammogram at CPMC are considered eligible. Since the cohort began collecting blood samples in July 2004 until June 2007, samples have been collected from over 11,000 women. Measurement of Breast Density: Dr. John Shepherd is currently measuring breast density in a large fraction of the cohort using an automated approach with single X-ray absorptiometry. Dr. Shepherd has established a link with the CPMC mammography center that allows him to collect routine digital mammography information. Using the data from the mammogram, Dr. Shepherd and his group have developed the single X-ray absorptiometry (SXA) technique for measuring density which is described in more detail below. The table demonstrates the distribution of demographic variables and some breast cancer risk factors of women who donated blood and had a breast density measurement in the CPMC breast health cohort. Nearly 80% of the participants are Caucasian and most of the women are post-menopausal with a median age of ~52. Since it will be difficult to accrue a large enough sample from each ethnic group, our study will focus only on Caucasian women. Table: Demographic variables, reproductive history and family history of breast cancer among 2962 women participating in the CPMC cohort study who contributed blood samples between 1994-1997. Variable Median/Percentage Age (Median/IQR) 52 (46-59) Ethnicity Caucasian/White 0.76 Asian/Pacific Islander 0.141 Hispanic 0.029 Mixed Race/Ethnicity 0.039 African American/Black 0.022 American Indian 0.001 Other 0.009 First degree relative with breast cancer 0.17 Age at first birth Nulliparous 0.39 Age<20 0.043 Age>40 0.032 Age<30, ≥20 0.251 Age>30, ≤40 0.282 Measurement of Breast Density in Cohort: Measurement of breast density is accomplished using an automated technique for all mammograms obtained by Dr. Shepherd using Single X-Ray absorptiometry (SXA). SXA measurement of breast density is done on approximately 30% of all screening mammograms. Below we describe the method for measurement of breast density by SXA by Dr. Shepherd's group and its validation and association with breast cancer. As we demonstrate below, breast density, as measured by SXA, is an automated, highly reproducible measure of the density of breast tissue and is associated with breast cancer risk. SXA for Quantifying Breast Density: Single x-ray absorptiometry (SXA) was initially developed for measuring bone density. SXA can determine the fraction of each of two densities simultaneously using the fact the sample is a constant thickness, the thickness in known, and the total attenuation is known. In applying this technique to breast density, we assume a two compartment model: fat and non-fatty (fibroglandular tissue). We use a reference material composed of various concentrations of two materials: one which is the same density as fat and another which is the same density as fibroglandular tissue. The reference material (phantom) is placed in the X-ray field with each mammogram. We have been able to implement this in a way that is unintrusive to the patient and technologist at CPMC. Assuming this two-compartment model and a constant known breast thickness, we can then calculate the percent density at any region of the breast based on the assumption that % pixel grey-scale is proportion to the mass fractions of breast fat and lean tissue. If reference materials (a phantom) of fat and fibroglandular tissue are imaged with the patient's breast and the reference materials have the same thickness as the patient's breast, then the breast's grey-scale values can be converted to fat/fibroglandular mass fractions by interpolating between those two references. The total percent density is found by averaging the volume fraction over all breast pixels. The phantom being used for breast density assessment at CPMC began to be used in September 2004. The phantom does not have to be manipulated by the technologist and stays attached on the mammography device during standard craniocaudal (CC) views. Thus it creates minimal to no interference with the clinical mammogram. Reproducibility of breast density measures: Traditional measures of mammographic density require some human interpretation. A human reader outlines the area perceived to be dense and a computer then calculates the percent area outlined as a percent of the entire image. Thus, while traditional mammographic density is associated with breast cancer risk, it has some limitations. In a study by Drs. Shepherd, Kerlikowske, et al., the correlation coefficient (Pearson's R) between different readers was 0.8-0.9. In contrast to the traditional mammographic density measurement, the SXA measurement is fully automated and, therefore, the reproducibility of the measurement is higher. Dr. Shepherd and colleagues have performed a replication study of SXA as a measurement of breast density. They have estimated the correlation coefficient of the SXA measurement of breast density to be >0.98. Thus, as expected for an automated measure, SXA is a highly reproducible measure of mammographic breast density. Drs. Shepherd and Kerlikowske have recently analyzed the association between breast cancer risk and breast density as measured by SXA (Shepherd et al., Cancer Epi Biomarkers and Prev, 2011, PMID: 21610220). They found that women in the highest quintile of % volumetric density had an odds ratio of 4.1 (95% CI: 2.3 - 7.2) for breast cancer risk compared to women in the lowest quintile of volumetric density. Thus volumetric density appears to be a highly reproducible, automated measure of breast cancer.

  Study phs000395

• Sequence Analysis of Mutations and Translocations Across Breast Cancer Subtypes

  This study combined whole exome (103 samples) and whole genome (22 samples) sequencing over a total of 108 breast tumors and matched normal DNA to identify novel mutations and translocations. Samples were subjected to paired-end Illumina sequencing with goal of 30x coverage of tumor/normal for whole genomes and 100x tumor/normal coverage for whole exomes. From these sequences, we used various computational techniques to identify somatic point mutations, insertion/deletions and structural rearrangements in these tumors. From these data, we identified new insights into the rates of background mutations in these cancers, novel recurrent mutated genes, and multiple gene rearrangements. One of these rearrangements appears to be a recurrent event in breast cancer.

  Study phs000369

• The Mutational Landscape of Head and Neck Squamous Cell Carcinoma

  This study was the first-known large-scale effort to uncover the mutational spectrum of head and neck cancers. We analyzed whole-exome sequence from 92 tumor-normal pairs and retained 74 of them for significance analysis. The majority exhibited a mutational profile consistent with tobacco exposure; human papilloma virus sequence was detectable in 15% of cases. In addition to identifying previously known HNSCC genes (TP53, CDKN2A, PTEN, PIK3CA, and HRAS), the analysis revealed many genes not previously implicated in this malignancy. At least 30% of cases harbor mutations in genes (such as NOTCH1, IRF6, TP63) that regulate squamous differentiation, implicating alterations in this process as a major driver of HNSCC carcinogenesis. Altogether, the results suggest that large-scale exome sequencing may illuminate fundamental tumorigenic mechanisms with important therapeutic implications.

  Study phs000370

• Whole Genomic Sequencing of Nine Primary Colorectal Adenocarcinoma Tumor/Germline Pairs

  This study was the first-known effort to complete the complete genome sequencing of primary colorectal adenocarcinomas and the matched germline genome. Nine colorectal adenocarcinomas selected on the basis of having chromosomal instability were subjected to 'shotgun' Illumina sequencing with 101-bp paired end reads to an approximate goal of 30x coverage of tumor and of normal. From these sequences, we used various computational techniques to identify somatic point mutations, insertion/deletions and structural rearrangements in these tumors. From these data, we identified new insights into the rates of background mutations in these cancers, new spectrums of structural alterations including the identification of a novel in-frame fusion gene.

  Study phs000374

• Genome-Wide Association Study of Breast Cancer in the African Diaspora - the ROOT study

  The paucity of data on the genetic epidemiology of breast cancer for racial/ethnic groups other than those of European ancestry hinders the development of innovative interventions to reduce health disparities. Women in the African Diaspora experience a disproportionate burden of pre-menopausal breast cancer in comparison to all other races for reasons that remain unknown and understudied. This higher proportion of early-onset breast cancer might suggest a stronger genetic component in these populations. Genome-wide association studies (GWAS) have revealed several genetic loci that confer risk of breast cancer. Because all GWAS started the discovery stage in women of European ancestry and replicated mainly in women of European ancestry, we propose a novel approach for a GWAS in indigenous African women to identify alleles associated with breast cancer risk which will then be replicated in other populations. This innovative design builds on our current understanding of the etiologic heterogeneity in breast cancer and the distribution of breast cancer molecular subtypes which differ between women of African ancestry and women of European ancestry. The major objective of the proposed studies is to get to the "root" causes of breast cancer by identifying breast cancer risk alleles in a pooled sample of women of African ancestry and to replicate our findings in other populations. To achieve this objective, we conducted a case control study of breast cancer in women of African ancestry, including Africans living in Nigeria, African Americans and African Barbadians. We will genotype ~3800 individuals using the Illumina HumanOmni2.5-Quad platform. We will conduct both standard and novel genetic analyses of the data to map genes associated with breast cancer susceptibility, verify genotyping and carry out fine-mapping studies in genes or regions showing association with breast cancer risk, and replicate in other African American and non-African American populations. By pooling unique resources from studies throughout the African Diaspora, this study has the potential to identify risk alleles in several genes that contribute to increased breast cancer risk and may have implications for early detection, prognosis and treatment of breast cancer in ALL women. This should ultimately lead to improved outcomes for those who suffer a disproportionate burden of early-onset breast cancer.

  Study phs000383

• Epigenetic Profiling of Human Colorectal Cancer

  DNA methylation, together with chromatin modifications, constitute the epigenome that functions to regulate gene expression and genome integrity. DNA methylation alterations are ubiquitous in human cancers, as many genes acquire DNA methylation in a cancer-specific manner. DNA methylation at these sites in the genome of cancer cells not only serves as a marker for tumor identification, but together with gene mutation and gene expression data, can also be used to describe subsets of tumors of the same organ source. We have previously shown distinct human colorectal cancer subtypes based on DNA methylation differences. Correlating these DNA methylation differences with clinical co-variates will serve to further understand how these distinct subtypes are generated. We have collected 100 colorectal tumor tissues (for which clinical information is known) and have obtained (unprotected) genome-wide DNA methylation and chromatin modification information for each sample for the purposes of identifying and classifying unique tumor subtypes of colorectal cancers. In addition, we have determined mutations of key genes relevant to colorectal cancer as well as gene expression profiles. We will use the clinical data for each de-identified sample to correlate with the DNA methylation, mutation and gene expression information so as to understand the driving forces behind these distinct colorectal subtypes. We have selected the most promising tumors for whole-genome bisulfite sequencing using next-generation sequencing technology to obtain complete maps of colon cancer methylomes. Researchers will be unable to identify the subjects because the samples and associated information have been de-identified and anonymized by the tissue source site. In addition, upon receipt by the USC Epigenome Center, we have assigned new random identifiers for each sample. The data generated using these new codes are not traceable to the patient identity.

  Study phs000385

• Division of Cancer Epidemiology and Genetics (DCEG) Imputation Reference Dataset

  We have built a new resource for imputation of SNPs for existing and future genome-wide association studies (GWAS), known as the Division of Cancer Epidemiology and Genetics (DCEG) Reference Set. The first build of the data set includes 728 cancer-free individuals of European descent from three large prospectively sampled studies, 98 African-American individuals from the Prostate, Lung, Colon, and Ovary Cancer Screening Trial (PLCO), 74 Chinese individuals from a Chinese clinical trial in Shanxi, China (SHNX), and 349 unrelated individuals from the HapMap Project (see Molecular Data Section for details on arrays used). The final harmonized dataset includes 2.8 million autosomal polymorphic SNPs on 1,249 subjects after rigorous quality control metrics were applied.

  Study phs000396

• The Genetic Architecture of Smoking and Smoking Cessation

  This study includes samples from two projects: Collaborative Genetic Study of Nicotine Dependence (COGEND; PI: Laura Bierut) and University of Wisconsin Transdisciplinary Tobacco Use Research Center (UW-TTURC; PI: Timothy Baker). Data are available for an additional 1420 COGEND subjects through the Study of Addiction: Genetics and Environment (SAGE), dbGaP study accession phs000092. The majority of these subjects are independent from the current study, but there is a small amount of overlap between the two samples (n=29 subjects) for quality control purposes. It should be noted that the case definition in the SAGE study is DSM-IV alcohol dependence. The case definition in the current study is nicotine dependence by a current score of 4 or greater on the Fagerström Test for Nicotine Dependence (FTND). The overall goal of this project is to identify and characterize genetic variants that contribute to the development of nicotine dependence, related smoking behaviors, and smoking cessation. The COGEND sample includes unrelated cases and controls for a genetic association study of nicotine dependence. Cases are defined by a commonly used definition of nicotine dependence, a current score of 4 or more (maximum score of 10) on the Fagerström Test for Nicotine Dependence (FTND). Control status is defined as an individual who smoked at least 100 cigarettes during their lifetime, yet never became dependent (lifetime FTND=0). By selecting controls who smoked, those genetic effects that are specific to nicotine dependence can be examined. The UW-TTURC sample includes nicotine dependent smokers from three smoking cessation studies. Subjects had to smoke at least 10 cigarettes per day (confirmed smoking by an alveolar carbon monoxide (CO) level greater than 9) and report being motivated to quit smoking. Participants were excluded based on evidence of psychosis history, clinically significant depression symptoms, other severe mental illness, or contraindications to smoking cessation medications. COGEND: COGEND was initiated in 2001 as a three-part program project grant funded through the National Cancer Institute (NCI; PI: Laura Bierut). The three projects included a study of the familial transmission of nicotine dependence, a genetic study of nicotine dependence, and a study of the relationship of nicotine dependence with nicotine metabolism. The primary goal is to detect, localize, and characterize genes that predispose or protect an individual with respect to heavy tobacco consumption, nicotine dependence, and related phenotypes and to integrate these findings with the family transmission and nicotine metabolism findings. The primary design is a community based case-control family study. Nicotine dependent cases and non-dependent, smoking controls were identified and recruited from Detroit and St. Louis. In addition, one sibling for each case and control subject was recruited in a subset of the sample. More than 54,000 subjects aged 25-44 years were screened by telephone; more than 3,100 subjects were personally interviewed; and more than 2,900 subjects donated blood samples for genetic studies. UW-TTURC: The UW-TTURC was initiated in 2001 as a study of nicotine dependence and smoking cessation treatment. The second round of UW-TTURC was initiated in 2005 as a study of efficacy of smoking cessation and long term outcomes. Nicotine dependent smokers seeking cessation treatment were identified and recruited from Madison and Milwaukee, WI. Over 9,000 adult smokers were screened by telephone; 2,575 individuals were enrolled and randomized to treatment conditions that involved use of different smoking cessation medications. Participants from the UW-TTURC smoking cessation clinical trials had the option of participating in a genetic substudy, and approximately 2,000 donated blood samples for genetic studies. The goal of the genetic studies of smokers seeking cessation treatment is to detect, localize, and characterize genes that predispose or protect an individual with respect to heavy tobacco consumption, nicotine dependence, and related phenotypes including cessation, withdrawal, and relapse. Both studies (COGEND and UW-TTURC) include measures of basic socio-demographic variables, including age, sex, race/ethnicity, family income, and educational attainment. Information on nicotine dependence, as assessed by the Fagerström Test for Nicotine Dependence (FTND) is available for all subjects. In addition, participants also completed the Nicotine Dependence Syndrome Scale (NDSS; Shiffman et al., 2004) and the Wisconsin Inventory of Smoking Dependence Motives (WISDM-68; Piper et al, 2004). Coding for both individual variables and indices has been standardized across studies. All subjects were assessed in person by trained research assistants. This study is part of the Gene Environment Association Studies initiative (GENEVA, http://www.genevastudy.org) funded by the trans-NIH Genes, Environment, and Health Initiative (GEI). The overarching goal is to identify novel genetic factors that contribute to the genetic architecture of smoking through large-scale genome-wide association studies of two well-characterized cohorts. Genotyping was performed at the Johns Hopkins University Center for Inherited Disease Research (CIDR). Data cleaning and harmonization were done at the GEI-funded GENEVA Coordinating Center at the University of Washington.

  Study phs000404