CANCER RISKS IN MULTI-ETHNIC CARRIERS OF UNCLASSIFIED BRCA1 VARIANTS
Alice Whittemore
Stanford University, 340 Panama Street, Stanford, Ca 94305-6203
Grant 5R03CA132155-02 from National Cancer Institute
Abstract: Project Protein inactivating mutations of the BRCA1 gene are associated with elevated breast and ovarian cancer risks. However there is considerable uncertainty about the effects of other BRCA1 variants, particularly the single base changes that alter amino acids of the protein, termed nonsynonymous unclassified variants (ns UCVs). Because these variants are rare, no single source of data is sufficiently informative to unambiguously classify them as either neutral or pathogenic. Our goal is to assess the feasibility of adding useful new information about the risks of ns UCVs of BRCA1 by assessing cancer incidence in first-degree (FD) relatives of a population-based multi-ethnic series of incident breast cancer cases with and without ns UCVs. Our specific aims are 1) to compare the prevalence and types of ns UCVs detected among Hispanic, Asian- American, African-American and non-Hispanic white (NHW) breast cancer cases ascertained from the Northern California component of the Breast Cancer Family Registry (Breast CFR); 2) to estimate risk ratios and standardized residuals for BRCA1-related cancers among FD relatives of 66 cases who carry ns UCVs, compared to those of 1729 cases who carry at most neutral polymorphisms; 3) to combine results of Aim 2 with available pathogenicity scores of the variants to classify them as benign or deleterious; and 4) to evaluate agreement between this classification and one obtained using a function-based statistical learning algorithm. Our ultimate goal is to assess the potential of using cancer incidence in relatives of carriers to help classify other variants in disease-susceptibility genes. If we find that the results of this feasibility study are promising, we will seek separate funding to extend it to other UCVs of BRCA1 and BRCA2, using a larger series of population-based families from the Breast CFR and other population-based breast and ovarian cancer family registries. The risks associated with unclassified variants of established disease-susceptibility genes have important clinical implications, particularly for Hispanic and nonwhite populations, whose risks have not been extensively studied. This study will examine the feasibility of adding new information about these risks using cancer data from relatives of variant carriers
Keywords: African American; Afro American; Afroamerican; Agreement; Algorithms; Amino Acids; Asian Americans; BRCA1; BRCA1 Mutation; BRCA1 gene; BRCA2; BRCA2 gene; Benign; Black Populations; Black or African American; Breast; Breast Cancer 1 Gene; Breast Cancer 1, Early Onset Gene; Breast Cancer 2 Gene; Breast Cancer 2, Early Onset Gene; Breast Cancer Type 1 Susceptibility Gene; Breast Cancer Type 2 Susceptibility Gene; California; Cancer Family; Cancer Genes; Cancer of Breast; Cancer of the Ovary; Cancer-Promoting Gene; Cancers; Cell Function; Cell Process; Cell physiology; Cellular Function; Cellular Physiology; Cellular Process; Classification; Clinical; Colon Cancer; Colon Carcinoma; Colonic Carcinoma; Cross-Product Ratio; DNA Alteration; DNA mutation; Data; Data Sources; Diathesis; Disease; Disease regression; Disease susceptibility; Disorder; Epidemiology, Family Medical History; Exons; FANCB; FANCD1; Family; Family Medical History; Family history of; Family-Based Registry; Feasibility Studies; First Degree Relative; Frequencies (time pattern); Frequency; Funding; Gene Alteration; Gene Mutation; Genes; Genetic Alteration; Genetic Change; Genetic Polymorphism; Genetic defect; Genetic mutation; Glossary; Goals; Hereditary Breast Cancer 1; Hereditary Breast Cancer 2; Hispanic Populations; Hispanics; Hispanics or Latinos; Incidence; Latino Population; Learning, Machine; MMR; Machine Learning; Malignant Neoplasms; Malignant Ovarian Neoplasm; Malignant Ovarian Tumor; Malignant Tumor; Malignant Tumor of the Breast; Malignant Tumor of the Ovary; Malignant neoplasm of breast; Malignant neoplasm of ovary; Methods; Mismatch Repair; Mutation; Mutation of the BRCA1 Gene; Nature; Non-Hispanic; Normal Cell; Not Hispanic or Latino; Odds Ratio; Oncogenes; PSCP; Pathogenicity; Polymorphism (Genetics); Polymorphism, Genetic; Population; Post-Replication Mismatch Repair; Predisposition gene; Prevalence; Proteins; Questionnaires; RNF53; Rate; Regression; Relative; Relative (related person); Relative Odds; Residual; Residual state; Risk; Risk Ratio; SEER Program; SEER Program (National Cancer Institute (U.S.)); SEER-Surveillance, Epidemiology, and End Results; Score; Sequence Alteration; Series; Severities; Spanish Origin; Subcellular Process; Surveillance, Epidemiology, and End Results Program; Susceptibility Gene; Systematics; Transforming Genes; Uncertainty; Variant; Variation; ing; aminoacid; base; black American; brca 1 gene; brca 2 gene; breast cancer family; cancer risk; case control; disease/disorder; disease/disorder proneness/risk; doubt; family registry; gene product; genome mutation; hispanic community; kernel methods; liability to disease; malignancy; malignant breast neoplasm; neoplasm/cancer; ovarian cancer; polymorphism; predisposing gene; statistical learning; support vector machine
Project start date: 2007-09-24
Project end date: 2010-08-31
Budget start date: 1-SEP-2008
Budget end date: 31-AUG-2010
PFA/PA: PAR-06-294
5R03CA132155-02 (2008): $0
Sponsored Links Excellgen http://Excellgen.com
Grants awarded to Alice Whittemore
GENETIC EPIDEMIOLOGY OF PROSTATE CANCER
Alice Whittemore
Stanford University, 340 Panama Street, Stanford, Ca 94305-6203
Grant 5R01CA067044-10 from National Cancer Institute
Abstract: We have obtained pedigree data, blood and archived tissue from members of 98 families containing three or more confirmed cases of prostate cancer. We have typed these families for 437 autosomal markers and have analyzed the data for linkage. Although no single chromosomal region met the genome-wide criteria for statistically significant excess allele sharing, our strongest signal on the distal end of chromosome 19p has been replicated independently by a study of multiple-case prostate cancer families in Sweden (Wiklund et al. 2003). In this competing renewal application we request funds to test the hypothesis that region 19p13.3 harbors a prostate cancer susceptibility gene. Our objectives are to 1) narrow the region by tripling the number of markers and perform linkage analysis to exclude subregions with low lod scores, using statistical methods that accommodate both individual-specific and family-specific covariates that may account for genetic heterogeneity across families; 2a) rank the 92 known genes and 61 transcripts of unknown genes in the (narrowed) region with respect to their potential involvement in prostate cancer, and 2b) identify polymorphisms in the more promising genes; 3a) investigate associations between prostate cancer risk and the variant alleles in the identified polymorphisms by genotyping 750 African-American and 750 Caucasian case-control pairs in a casecontrol study nested within the Hawaii/Los Angeles multiethnic cohort (MEC); 3b) when warranted, investigate the functional significance of these variants. The NCI-funded International Consortium for Prostate Cancer Genetics (ICPCG) is a resource of more than 1,500 multiple-case prostate cancer families. As members of the ICPCG, our long-term aim is to pursue with this group any promising leads identified in this project
Keywords: 1, 25-Dihydroxycholecalciferol Receptors; 1, 25-Dihydroxyvitamin D3 Receptors; 17beta-Hydroxy-5alpha-Androstan-3-One; 19p; 19p13.3; 5 alpha-Dihydrotestosterone; 5-alpha-DHT; Abbreviations; Accounting; African American; Afro American; Afroamerican; Alleles; Allelomorphs; Analysis, Data; Androgen Receptor; Androstan-3-one, 17-hydroxy-, (5alpha, 17beta)-; Androstanolone; Archives; Assay; Bioassay; Biochemical; Biologic Assays; Biological Assay; Biotechnology; Black Populations; Black or African American; Blood; Blotting, Northern; Body Tissues; California; Cancer Family; Cancer Susceptibility Gene; Cancer of Prostate; Cancer-Predisposing Gene; Caucasian; Caucasian Race; Caucasians; Caucasoid; Caucasoid Race; Cell Communication and Signaling; Cell Signaling; Cholecalciferol Receptors; Chromosome 19 Proximal Arm; Chromosome 19 Short Arm; Chromosomes; DHT; Data; Data Analyses; Data Banks; Data Bases; Data Linkages; Databank, Electronic; Databanks; Database, Electronic; Databases; Dihydrotestosterone; Distal; EC 3.4.21.34; ESTs; Expressed Sequence Tags; Family; Fletcher Factor; Funding; GWAS; Genes; Genetic Heterogeneity; Genetic Polymorphism; Genome; Genomics; Genotype; Hawaii; Human Genome; Individual; International; Intracellular Communication and Signaling; Investigators; KLK3; Kallikrein 3; Linkage Analysis; Linkages, Data; Lod Score; Los Angeles; Malignant Tumor of the Prostate; Malignant neoplasm of prostate; Malignant prostatic tumor; Molecular; Molecular Configuration; Molecular Conformation; Molecular Stereochemistry; NCI; NCI Organization; NIH RFA; National Cancer Institute; Northern Blotting; Northern Blottings; Numbers; Occidental; P-30 Antigen; PCR; Participant; Pedigree; Plasma Kallikrein Precursor; Plasma Prekallikrein; Polymerase Chain Reaction; Polymorphism (Genetics); Polymorphism, Genetic; Polymorphism, Single Base; Prostate CA; Prostate Cancer; Prostate Specific Antigen Preproprotein; Prostate-Specific Antigen; Prostatic Cancer; RNA blot analysis; RNA blotting; RT-PCR; RTPCR; Receptors, 1, 25-Dihydroxyvitamin D 3; Receptors, Calcitriol; Record Linkage Study; Request for Applications; Research Institute; Research Personnel; Research Resources; Researchers; Resources; Reticuloendothelial System, Blood; Reverse Transcriptase Polymerase Chain Reaction; Reverse Transcription; SNP; SNPs; SSCP; Scanning; Second Degree Relative; Semenogelase; Seminin; Signal Transduction; Signal Transduction Systems; Signaling; Single Nucleotide Polymorphism; Single-Stranded Conformational Polymorphism; Stanolone; Statistical Methods; Statistically Significant; Sweden; Testing; Therapeutic Androstanolone; Tissues; Transcript; VDR; Variant; Variation; Vitamin D 3 Receptors; Vitamin D Receptors; Vitamin D3 Receptor; base; biological signal transduction; black American; cancer genetics; cancer risk; case control; clinical data repository; clinical data warehouse; cohort; conformation; conformational state; data repository; family based linkage study; gamma-Seminoprotein; gel electrophoresis; genetic epidemiology; genetic linkage analyses; genetic linkage analysis; genetic pedigree; genetic resource; genetic variant; genome wide association scan; genome wide association studies; genome wide association study; genome-wide linkage; genome-wide scan; genomewide association scan; genomewide association studies; genomewide association study; genomewide scan; hK3 Kallikrein; kininogenin; linkage analyses; member; pedigree structure; polymorphism; relational database; reverse transcriptase PCR; single strand conformation polymorphism; white race; whole genome association studies; whole genome association study
Project start date: 1995-04-01
Project end date: 2011-04-30
Budget start date: 1-MAY-2008
Budget end date: 30-APR-2011
5R01CA067044-10 (2008): $0
VALIDATING CANCER RISK MODELS: A PILOT STUDY TO EVALUATE COST-EFFICIENT METHODS
Alice Whittemore
Stanford University, 340 Panama Street, Stanford, Ca 94305-6203
Grant 1R03CA150136-01 from National Cancer Institute
Abstract: Validating Cancer Risk Models a Pilot Study to Evaluate Cost-efficient Methods To facilitate targeted cancer prevention strategies and help patients weigh the costs and benefits of genetically tailored interventions, we need statistical models that provide accurate and precise projections of a person´s risk of developing a given adverse outcome. Such models must be evaluated using cohort data on individuals at risk of the outcome. The ideal evaluation would genotype all subjects in a large cohort, use the genotypes to assign risks to all cohort members, and then relate assigned risks to subsequent outcomes. However such complete genotyping is too costly to be feasible. Our goal here is to test two new cost-effective methods for evaluating the added value of genetic covariates. The first is a case-cohort design that genotypes only a subset of the cohort members. The second uses case-control data and Bayes Rule to estimate the amount of increased precision gained with genotyping. Our goal is to use cohort data from the California Teachers Study (CTS) and population-based case-control data to test the two methods. We will do so by evaluating existing risk models for cancers of the ovary and breast using data from a) all CTS subjects; b) a subset of CTS subjects in a case- cohort design; and c) subjects from a case-control study. We will use BRCAPRO scores as surrogates for pathogenic mutations of BRCA1 and BRCA2. This will allow us to compare inferences using (b) and (c) with those from (a), which will form the gold standard. To facilitate targeted cancer prevention strategies and help patients weigh the costs and benefits of genetically tailored interventions, we need statistical models that provide accurate and precise projections of a person´s risk of developing a given adverse outcome. The goal of this project is to test two new cost-effective methods for evaluating the value of adding genetic covariates to these models using data from studies of cancers of the breast and ovary
Keywords: Address; Age; Au element; Australia; BRCA1 Mutation; BRCA2; BRCA2 gene; Breast; Breast Cancer 2 Gene; Breast Cancer 2, Early Onset Gene; Breast Cancer Gail Model; Breast Cancer Gail Model Risk Assessment Tool; Breast Cancer Risk Assessment Tool; Breast Cancer Type 2 Susceptibility Gene; California; Canada; Cancer Model; Cancer of Breast; Cancer of the Ovary; CancerModel; Cancers; Case-Base Studies; Case-Comparison Studies; Case-Compeer Studies; Case-Control Studies; Case-Referent Studies; Case-Referrent Studies; Cohort Studies; Concurrent Studies; Costs and Benefits; Data; Diathesis; Disease susceptibility; Esocidae; Evaluation; FANCB; FANCD1; Future; Gail model; Genetic; Genital System, Female, Ovary; Genotype; Goals; Gold; Guidelines; Hereditary Breast Cancer 2; Individual; Intervention; Intervention Strategies; Malignant Neoplasms; Malignant Ovarian Neoplasm; Malignant Ovarian Tumor; Malignant Tumor; Malignant Tumor of the Breast; Malignant Tumor of the Ovary; Malignant neoplasm of breast; Malignant neoplasm of ovary; Methods; Modeling; Models, Statistical; Mutation of the BRCA1 Gene; Outcome; Ovary; Persons; Pike; Pike fish; Pilot Projects; Population; Prevalence; Prevention strategy; Preventive strategy; Probabilistic Models; Risk; SUBGP; Site; Statistical Models; Study Subject; Subgroup; Testing; Variant; Variation; Weighing patient; Woman; ing; brca 2 gene; cancer location; cancer prevention; cancer risk; cancer site; case control; cohort; cost; design; designing; disease prevention; disease/disorder proneness/risk; disorder prevention; genetic variant; interventional strategy; liability to disease; malignancy; malignant breast neoplasm; member; model development; neoplasm/cancer; ovarian cancer; pilot study; population based; public health relevance; teacher
Relevance: To facilitate targeted cancer prevention strategies and help patients weigh the costs and benefits of genetically tailored interventions, we need statistical models that provide accurate and precise projections of a person´s risk of developing a given adverse outcome. The goal of this project is to test two new cost-effective methods for evaluating the value of adding genetic covariates to these models using data from studies of cancers of the breast and ovary
Project start date: 2010-03-06
Project end date: 2012-02-29
Budget start date: 6-MAR-2010
Budget end date: 28-FEB-2011
PFA/PA: PAR-08-237
1R03CA150136-01 (2010): $89742
Alice Whittemore
Stanford University, 340 Panama Street, Stanford, Ca 94305-6203
Abstract: The goal of the Cancer Epidemiology Program (CEP) is to improve our ability to prevent cancer and reduce its burden through new knowledge in surveillance, etiology, patterns of care, and survival, using an interdisciplinary approach. Special emphasis is placed on racial, ethnic, cultural, and other groups with an unequal burden of cancer. This research has been conducted primarily via large populationbased case-control and cohort studies in the ethnically diverse population of the San Francisco Bay Area, which includes Oakland and San Jose. Case-control studies typically collect demographic and exposure data, DNA from peripheral lymphocytes, and/or archived tumor samples. Cohort studies are based on follow-up of healthy individuals for cancer incidence (e.g., California Teachers Study), and of incident cases for cancer care, quality of life, and survival (e.g., CanCORS and Family Registries). Cancer sites of particular interest include breast, ovary, prostate, and lymphomas. This work has been facilitated and enhanced by the recent formal affiliation between Stanford University and the Northern California Cancer Center (NCCC). Some highlights of Program research include findings that oral contraceptive use is associated with reduced ovarian cancer risk and no elevation in breast cancer risk among carriers of BRCA1 mutations, that Helicobacter pylori infection is associated with reduced risk of esophageal cancer, that ethnic differences exist in use of alternative cancer therapies, and that choice of breastconserving surgery is related to socioeconomic status, immigration status and acculturation, and race/ethnicity. The Program adds value to the Cancer Center through its population-based study resources that provide a strong basis for developing important interdisciplinary collaborations and conducting translational research. Dr. Alice S. Whittemore and Dr. Esther M. John lead the Program, both senior cancer epidemiologists with extensive cancer research programs who have worked together for over 15 years. The CEP consists of 23 members, with direct cost funding of $20,220,819, including $6,463,763 in NCI funding. In the period from 2000 to the present, the average number of publications by Program members was 33 per year; of these, 40% were intra-programmatic and 14% were interprogrammatic. Future plans include expanding intra- and inter-programmatic interactions among investigators, identifying new research opportunities, and evaluating the feasibility of a data collection Shared Resource within the Cancer Center
Keywords: Affect; Area; Behavioral Genetics; Cancer Center; Cancer Patient; Cancer Treatment; Cancers; Causality; Cessation of life; Characteristics; Complex; Data; Data Quality; Death; Development; Diffusion; Environment; Epidemiologic Research; Epidemiologic Studies; Epidemiological Studies; Epidemiology Research; Etiology; Family; Genetic Determinants of Behavior; Genetics, Behavioral; Goals; History; Incidence; Investigators; Malignant Neoplasm Therapy; Malignant Neoplasm Treatment; Malignant Neoplasms; Malignant Tumor; Medical; Molecular Genetic; Molecular Genetics; Morbidity; Morbidity - disease rate; Mortality; Mortality Vital Statistics; Outcome; PROV; Patients; Pattern; Programs (PT); Programs [Publication Type]; Provider; QOL; Quality of life; Recording of previous events; Recurrence; Recurrent; Research; Research Personnel; Researchers; Scheme; System; System, LOINC Axis 4; Universities; Work; anticancer therapy; behavior genetics; cancer care; cancer epidemiology; cancer prevention; cancer progression; cancer risk; cancer therapy; disease causation; disease etiology; disease/disorder etiology; disorder etiology; improved; innovate; innovation; innovative; malignancy; member; multidisciplinary; neoplasm progression; neoplasm/cancer; neoplastic progression; new technology; programs; racial and ethnic; racial/ethnic; surveillance study; tumor progression
Budget start date: 1-SEP-2009
Budget end date: 31-AUG-2011
3P30CA124435-03S2_0009 (2009): $602
5P30CA124435-03_0009 (2009): $20912
"STATISTICAL METHODS FOR GENETIC EPIDEMIOLOGY"
Alice Whittemore
Stanford University, 340 Panama Street, Stanford, Ca 94305-6203
Grant 5R01CA094069-09 from National Cancer Institute
Abstract: The availability of high-dimensional single-nucleotide (SNP) data for large samples of individuals with and without disease presents unprecedented opportunities for genetic epidemiologists, but also many statistical challenges. Our ability to bring these opportunities to fruition depends on the development and application of sound and innovative statistical methods. Areas of particularly great need include methods for dealing with multiple hypothesis-testing problems (multiple comparison issues), and methods for combining data from multiple sources to achieve sharper inferences (data synthesis issues). The goals of this research are to develop new or improved methods for addressing these issues, and to apply them to data on cancers of the breast, ovary and prostate. To accomplish these goals, the investigators will build on more than 15 years of previous work. Specifically, in 1988 the National Cancer Institute (NCI) awarded an Outstanding Investigator Grant (OIG) to the Principle Investigator for the development and application of new and improved statistical methods for use in epidemiological research. In 1995 this grant was renewed until NCI terminated the program in 2001. The research was then funded by R01 CA94069 for the period January 2002 to December 2006. This competing renewal application requests funds to continue this work and to apply it to new areas of emerging importance. The specific aims are fourfold 1) to evaluate new and existing methods for controlling confounding and tail count variability in case-control genome-wide association (GWA) studies; 2) to evaluate risks associated with missense mutations of unknown significance in genes of established disease relevance; 3) to combine multiple independent sources of data in assessing the joint carcinogenic effects of groups of genes; and 4) to integrate data on tumor and patient characteristics for improved assessment of phenotype-specific etiology. We will evaluate the new methods by simulations, and we will illustrate them by application to existing data on cancers of the breast, ovary and prostate, and emerging data from GWA studies of breast and prostate cancer. The existing data have been collected either by the investigators and the consultants to this project, or as part of three collaborations in which the investigators participate the Breast Cancer Family Registry (Breast-CFR), the Ovarian Cancer Association Consortium (OCAC), and the International Consortium for Prostate Cancer Genetics (ICPCG). In summary, we need sound, reliable methods for analyzing the vast amounts of emerging genetic data from individuals with and without a given type of cancer. The goals of this research are to develop such methods, and thereby to help generate new knowledge useful for cancer prevention and treatment
Keywords: Address; Admixture; Area; Articulation; Award; BRCA1; BRCA1 gene; BRCA2; BRCA2 gene; Breast; Breast Cancer 1 Gene; Breast Cancer 1, Early Onset Gene; Breast Cancer 2 Gene; Breast Cancer 2, Early Onset Gene; Breast Cancer Type 1 Susceptibility Gene; Breast Cancer Type 2 Susceptibility Gene; Cancer of Breast; Cancer of Prostate; Cancer of the Ovary; Cancers; Case-Base Studies; Case-Comparison Studies; Case-Compeer Studies; Case-Control Studies; Case-Referent Studies; Case-Referrent Studies; Causality; Characteristics; Collaborations; Computer Programs and Programming; Critiques; Cross-Product Ratio; Data; Data Set; Data Sources; Dataset; Development; Disease; Disorder; Doctor of Philosophy; Environmental Factor; Environmental Risk Factor; Epidemiologist; Epidemiology; Etiology; FANCB; FANCD1; Family; Funding; GWAS; Genes; Genetic; Genetic Predisposition; Genetic Predisposition to Disease; Genetic Susceptibility; Genital System, Female, Ovary; Genital System, Male, Prostate; Genotype; Glossary; Goals; Grant; Hereditary Breast Cancer 1; Hereditary Breast Cancer 2; Human Prostate; Human Prostate Gland; Incidence; Individual; Inherited Predisposition; Inherited Susceptibility; International; Investigators; Joints; Knowledge; Learning, Machine; Life Style; Lifestyle; Linkage Disequilibrium; Linkage Disequilibriums; Machine Learning; Malignant Neoplasms; Malignant Ovarian Neoplasm; Malignant Ovarian Tumor; Malignant Tumor; Malignant Tumor of the Breast; Malignant Tumor of the Ovary; Malignant Tumor of the Prostate; Malignant neoplasm of breast; Malignant neoplasm of ovary; Malignant neoplasm of prostate; Malignant prostatic tumor; Methods; Methods and Techniques; Methods, Other; Missense Mutation; Modeling; Molecular; NCI; NCI Organization; NIH RFA; National Cancer Institute; Nucleotides; Odds Ratio; Output; Ovary; PSCP; Patients; Penetrance; Ph.D.; PhD; Phenotype; Polymorphism, Single Base; Population; Predisposition; Principal Investigator; Programs (PT); Programs [Publication Type]; Prostate; Prostate CA; Prostate Cancer; Prostate Gland; Prostatic Cancer; Prostatic Gland; RNF53; Registries; Relative Odds; Request for Applications; Research; Research Personnel; Researchers; Risk; Risk Ratio; SNP; SNPs; Sampling; Single Nucleotide Polymorphism; Site; Sound; Sound - physical agent; Source; Statistical Methods; Stratification; Study Section; Suggestion; Susceptibility; Tail; Techniques; Testing; Time; Training; Transmission; Universities; Variant; Variation; Work; acronyms; base; brca 1 gene; brca 2 gene; breast cancer family registry; cancer genetics; cancer prevention; cancer type; case control; computer program; computer programming; conditioning; disease causation; disease etiology; disease/disorder; disease/disorder etiology; disorder etiology; environmental risk; genetic epidemiology; genetic etiology; genetic mechanism of disease; genetic vulnerability; genome wide association scan; genome wide association studies; genome wide association study; genome-wide scan; genomewide association scan; genomewide association studies; genomewide association study; genomewide scan; improved; innovate; innovation; innovative; kernel methods; malignancy; malignant breast neoplasm; neoplasm/cancer; ovarian cancer; post-doctoral training; postdoctoral training; programs; response; simulation; sound; statistical learning; support vector machine; tool; transmission process; tumor; user-friendly; whole genome association studies; whole genome association study
Project start date: 2002-01-01
Project end date: 2012-07-31
Budget start date: 1-AUG-2010
Budget end date: 31-JUL-2011
5R01CA094069-09 (2010): $580133
5R01CA094069-08 (2009): $573074
Alice Whittemore
Stanford University
Project start date: 2002-01-01
Project end date: 2012-07-31