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• CALGB 40601: Randomized Phase III Trial of Paclitaxel Combined With Trastuzumab, Lapatinib, or Both As Neoadjuvant Treatment of HER2-Positive Primary Breast Cancer

  This randomized phase III trial studies paclitaxel and trastuzumab with or without lapatinib to see how well they work in treating patients with stage II or stage III breast cancer that can be removed by surgery. Drugs used in chemotherapy, such as paclitaxel, work in different ways to stop the growth of tumor cells, either by killing the cells, by stopping them from dividing, or by stopping them from spreading. Monoclonal antibodies, such as trastuzumab, can block tumor growth in different ways. Some block the ability of tumor cells to grow and spread. Others find tumor cells and help kill them or carry tumor-killing substances to them. Lapatinib may stop the growth of tumor cells by blocking some of the enzymes needed for cell growth. Giving paclitaxel with trastuzumab and/or lapatinib before surgery may make the tumor smaller and reduce the amount of normal tissue that needs to be removed. It is not yet known which regimen is more effective in treating patients with breast cancer.

  Study phs001570

• Acquiring and sequencing of all 24 single human chromosomes

  Haplotype phased whole genome sequencing of individuals is a technical challenge when family members are unavailable for determining chromosome of origin and variant linkage. Completely phasing genome sequences with single chromosomes has been shown to be feasible however amplifying all the single chromosomes for subsequent whole genome sequencing has been proposed but not performed to date. We acquired single chromosome of one of each of the autosomes and sex chromosomes to assess the feasibility of this sequencing library template preparation process.

  Study EGAS00001003300

• Local In Time Statistics for processual research

  Background: Functional genomics in a processual analysis cover the time-dependent changes in transcriptomics and epigenetics before diagnosis of a disease, reflecting the changes in both life style and disease processes. The aim of this paper is to explore the dynamic, time-dependent mechanisms of the metastatic processes, using blood transcriptomics and including time in a continuous manner. For achieving this goal we develop new statistical methods based on statistics that are local in time. Methods: The new statistical method, Local In Time Statistics (LITS), is based on calculating statistics in moving windows and randomization. The method has been tested for the analysis of a dataset that collectively provides information on the blood transcriptome up to eight years before breast cancer diagnosis. The dataset from the NOWAC Post-genome Cohort consists of 467 case-control pairs matched on birth year and time of blood sampling. The data for a pair is the difference in log2 gene expression between the case and control. The stratified analyses are based on important biological differences like metastatic versus non-metastatic cancer, and the mode of cancer detection, i.e. screening detected versus clinically detected cancers. The dataset was used for examining whether the gene expression profile varies between cases and controls, with time, or between cases with and without metastases. Results: The null hypotheses of no differences between cases and controls, no time-dependent changes, and no differences between different strata were all rejected. For screening detected cancers the probability of correct prediction of metastasis status was best in year 1 before diagnosis compared to year 3 and 4 before diagnosis for clinically detected cancers. The predictor was not very sensitive to the number of genes included.Conclusions: Using a new statistical method, LITS, we have demonstrated time-dependent changes of the blood transcriptome up to eight years before breast cancer diagnosis.

  Study EGAS00001002520

• Characterizing the Neurobehavioral Phenotype(s) in MPS III (Pilot Study)

  Mucopolysaccharidosis III (MPSIII) syndrome is characterized by a severe cognitive decline ending in dementia and death. MPSIII is also associated with a range of abnormal and disruptive behaviors that can include, but go well beyond, childhood noncompliance and oppositionality. The purpose of this study is to conduct a cross-sectional investigation to identify the behavioral phenotype and its neural basis in MPSIII. An overall goal of this research is to develop easily administered, sensitive and specific neurobehavioral markers to characterize the behavioral phenotype(s) of MPSIII, track their progression, and to delineate their possible neural substrates. The study looks to develop develop a sensitive and specific behavioral rating of disease progression in MPS III which can be used for clinical outcome studies. The research objectives are: Develop a measure for the use of health professionals to use in tracking MPSIII phenotypes and disease progression. Test our model of MPSIII with objectively recorded behaviors in a well-defined experimental setting. Elucidate the neural bases of MPSIII by correlating behavioral profiles with changes in brain structures through quantitative neuroimaging. Determine the relationship between the loss of cognitive functions and development of behavioral abnormalities in MPSIII. This is an observational pilot study that will enroll 45 individuals with MPS III Type A or B. Those participating in the study will be evaluated during a one-day assessment and chart review.

  Study phs001330

• Genetics of Mammographic Density in Ashkenazi Jews

  Mammographic density (MD) is a strong risk factor for breast cancer and is also a highly heritable trait with ~60-70% of the variance due to genetic factors, based on twin studies. MD is also higher in families with a strong history of breast cancer. Genome-wide association studies (GWAS), which focus on common genetic variants, have identified several single nucleotide polymorphisms (SNPs) associated with MD. However, these SNPs explain a very small fraction of the variance of MD, suggesting many other genes are involved. Thus, the vast majority of the heritability of mammographic density remains unexplained and may be explained, at least in part, by rare variants. Ashkenazi Jewish women are a founder population; founder populations frequently have alleles affecting phenotypes which may be unique and/or extremely rare in other populations. Prior reports have identified an association between higher mammographic density and Ashkenazi Jewish ancestry. Therefore, we developed a study of mammographic density in AJ women. We combined datasets from several different cohorts including (a) the California Pacific Medical Center Research Institute (b) the Athena Breast Health Cohort and (c) the Marin Women's study. In each study, we identified women who reported AJ ancestry (determined by self-report or by genetic analysis). We identified mammograms by linking the women to the San Francisco Mammography Registry. We retrieved digital mammographic results and used software to infer volumetric density and percent volumetric density for each woman. We then performed genome-wide genotyping of the samples using the Illumina MEGA array.

  Study phs001857

• SU2C-MARK Lung Cancer Consortium - Checkpoint Blockade Response Project

  Immune checkpoint inhibitors have become a critical part of the armamentarium against advanced Non-Small Cell Lung Cancer (NSCLC). While early studies have identified Tumor Mutation Burden (TMB) and PD-L1 staining as important biomarkers of response, they remain imperfect predictors. Here we describe a multi-institutional effort as part of the SU2C-MARK Lung Cancer Consortium in which Whole Exome Sequencing (WES) - and in select cases, RNA sequencing – was performed on a large collection of NSCLC samples prior to immune checkpoint blockade therapy, along with matched clinical response data following therapy. (Profiling of a small number of on- or post-treatment samples was also performed.) We anticipate this dataset to be of high value for the development of a deep understanding of the molecular determinants of immune checkpoint blockade response as well as the discovery of novel biomarkers.

  Study phs002822

• SIGi001-A-13 / SAMEA104386250 WGS data

  The iPSC line SIGi001-A-13 / SAMEA104386250 has undergone whole genome sequencing. Whole genome sequencing was done using Illumina HiSeq X Five platform with a reference genome of GRCh38. Raw data as FASTQ files and analysed data as CRAM files are available for this sample, in this dataset. The iPSC line SIGi001-A-13 is available for research use at www.EBiSC.org.

  Dataset EGAD50000001031

• SIGi001-A-3 / SAMEA4448571 WGS data

  The iPSC line SIGi001-A-3 / SAMEA4448571 has undergone whole genome sequencing. Whole genome sequencing was done using Illumina HiSeq X Five platform with a reference genome of GRCh38. Raw data as FASTQ files and analysed data as CRAM files are available for this sample, in this dataset. The iPSC line SIGi001-A-3 is available for research use at www.EBiSC.org.

  Dataset EGAD50000001041

• EDi014-A / SAMEA4459369 WGS data

  The iPSC line EDi014-A / SAMEA4459369 has undergone whole genome sequencing. Whole genome sequencing was done using Illumina HiSeq X Five platform with a reference genome of GRCh38. Raw data as FASTQ files and analysed data as CRAM files are available for this sample, in this dataset. The iPSC line EDi014-A is available for research use at www.EBiSC.org.

  Dataset EGAD50000001051

• SIGi001-A-9 / SAMEA4447499 WGS data

  The iPSC line SIGi001-A-9 / SAMEA4447499 has undergone whole genome sequencing. Whole genome sequencing was done using Illumina HiSeq X Five platform with a reference genome of GRCh38. Raw data as FASTQ files and analysed data as CRAM files are available for this sample, in this dataset. The iPSC line SIGi001-A-9 is available for research use at www.EBiSC.org.

  Dataset EGAD50000001095