6048 results for "canc*"

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• Trial of Activity for Adolescent Girls (TAAG-BioLINCC)

  Data Access NOTE: Please refer to the "Authorized Access" section below for information about how access to the data from this accession differs from many other dbGaP accessions.ObjectivesThe purpose of the multicenter randomized trial was to test the effectiveness of a multicomponent school-based and community-linked intervention in preventing the decline in physical activity levels and cardiovascular fitness in middle school girls (i.e., in grades 6-8).BackgroundThe Report of the Surgeon General on Physical Activity and Health (USDHHS, 1996) emphasized that regular physical activity has important health benefits including reducing the risk of heart disease, and helping to treat and prevent high blood pressure, high cholesterol, and diabetes, and to prevent osteoporosis and colon cancer. In addition, physical activity helps control weight, reduces feelings of depression and anxiety, and promotes psychological well being. Inactivity increases with age and is more common among women than men and among those with lower income, less education, and in minorities (USDHHS, 1996). Even though adolescents are more active than adults, many do not engage in recommended levels of physical activity, and participation declines with age throughout adolescence, especially in girls (USDHHS, 1996; CDC, 1997). Fourteen percent of teenage girls get no regular exercise, twice the percentage as for boys. The proportion of adolescent girls who participate in regular vigorous physical activity declines dramatically each year they are in high school, from 61 percent among 9th graders to 41percent among 12th grade girls. In high school, enrollment for girls in daily physical education classes dropped from 41 percent in 1991 to 25 percent in 1995. Both the CDC report (1997) and the Surgeon General's Report (USDHHS, 1996) recommended the need for research testing the effectiveness of a coordinated school-based physical activity intervention linked to community agency programs to increase physical activity by adolescent girls.ParticipantsMiddle school girls with English-speaking skills and no conditions to prevent participation in physical activity in 36 schools in six geographically diverse areas of the United States. Random, cross-sectional samples were drawn within schools: 6th graders in 2003 (n 1721) and 8th graders in 2005 (n 3504) and 2006 (n 3502).Researchers receiving the TAAG data are encouraged to contact study investigators that have previously published TAAG data.ConclusionsA school-based, community-linked intervention modestly improved physical activity in girls.

  Study phs004741

• NCTN: CHAARTED: ChemoHormonal Therapy Versus Androgen Ablation Randomized Trial for Extensive Disease in Prostate Cancer (E3805)

  Study ID: E3805 NCT Number: NCT00309985ECOG-ACRIN Cancer Research GroupSubmitted in collaboration with the NCTN/NCORP Data ArchiveTrial Title: NCTN: CHAARTED: ChemoHormonal Therapy versus Androgen Ablation Randomized Trial for Extensive Disease in Prostate Cancer Trial Description: RATIONALE: Androgens can cause the growth of prostate cancer cells. Androgen ablation therapy may stop the adrenal glands from making androgens. Drugs used in chemotherapy, such as docetaxel, work in different ways to stop the growth of tumor cells, either by killing the cells or by stopping them from dividing. It is not yet known whether androgen-ablation therapy is more effective with or without docetaxel in treating metastatic prostate cancer. PURPOSE: This randomized phase III trial is studying androgen-ablation therapy and chemotherapy to see how well they work compared to androgen-ablation therapy alone in treating patients with metastatic prostate cancer.Data presented in the following publication(s):PMID 26244877PMID 29384722PMID 34129855Additional unpublished data from E3805Disease type(s): Reproductive System Neoplasm, Male - Prostate Cancer Dataset(s) included: NCT00309985-D1 (PMID 26244877): There are 2 datasets (NCT00309985-D1 and -D2) associated with E3805's primary publication (PMID 26244877). This dataset, NCT00309985-D1, contains baseline characteristics (e.g., age, baseline PSA value, Gleason score, etc.), stratification factors, follow-up data, progression data (e.g., post-progression treatment), dose modification information, and outcome data (overall survival, progression-free survival, PSA complete response).NCT00309985-D2 (PMID 26244877): There are 2 datasets (NCT00309985-D1 and -D2) associated with E3805's primary publication (PMID 26244877). This dataset, NCT00309985-D2, contains treatment-related toxicity data.NCT00309985-D3 (PMID 29384722): There are two datasets (NCT00309985-D3 and -D4) associated with PMID 29384722, a publication analyzing the long-term follow-up of ECOG-ACRIN trial E3805. This dataset, NCT00309985-D3, contains updated outcome data. Data that are identical to those presented in NCT00309985-D1 are not duplicated in this dataset.NCT00309985-D4 (PMID 29384722): There are two datasets (NCT00309985-D3 and -D4) associated with PMID 29384722, a publication analyzing the long-term follow-up of ECOG-ACRIN trial E3805. This dataset, NCT00309985-D4, contains data describing the reasons patients never started protocol treatment. Data that are identical to those presented in NCT00309985-D1 are not duplicated in this dataset.NCT00309985-D5 (Unpublished data): This dataset, NCT00309985-D5, contains data collected on ECOG-ACRIN trial E3805, which are not published in the primary, long-term follow-up, or gene expression publication for the trial. NCT00309985-D5 contains unpublished baseline data (including prior treatments, patient characteristics and disease factors), treatment data, and PSA progression data.NCT00309985-D6 (Unpublished data): This dataset, NCT00309985-D6, contains data collected on ECOG-ACRIN trial E3805, which are not published in the primary, long-term follow-up, or gene expression publication for the trial. NCT00309985-D6 contains longitudinal PSA data. NCT00309985-D7 (Unpublished data): This dataset, NCT00309985-D7, contains data collected on ECOG-ACRIN trial E3805, which are not published in the primary, long-term follow-up, or gene expression publication for the trial. NCT00309985-D7 contains chemotherapy total dose data. NCT00309985-D8 (Unpublished data): This dataset, NCT00309985-D8 contains data collected on ECOG-ACRIN trial E3805, which are not published in the primary, long-term follow-up, or gene expression publication for the trial. NCT00309985-D8 contains the year of randomization for each patient. NCT00309985-D9 (Unpublished data): This dataset, NCT00309985-D9, contains data collected on ECOG-ACRIN trial E3805, which are not published in the primary, long-term follow-up, or gene expression publication for the trial. NCT00309985-D9 contains more baseline data (including pathologic stage, PSA, prior treatments, etc.) and non-protocol treatment data.NCT00309985-D10 (Unpublished data): This dataset, NCT00309985-D10, contains data collected on ECOG-ACRIN trial E3805, which are not published in the primary, long-term follow-up, or gene expression publication for the trial. NCT00309985-D10 contains testosterone data.NCT00309985-D11 (Unpublished data): This dataset, NCT00309985-D11, contains data collected on ECOG-ACRIN trial E3805, which are not published in the primary, long-term follow-up, or gene expression publication for the trial. NCT00309985-D11 contains fasting AM glucose and HDL data.NCT00309985-D12 (PMID 34129855): This dataset, NCT00309985-D12, contains gene expression data reported in PMID 34129855, a secondary publication of E3805 presenting transcriptional profiling associations with clinical outcomes.You are encouraged to view the PDF data dictionaries found in the "Documents" tab of the dbGaP study page, which may contain additional information regarding the data or the associated publication(s).

  Study phs004201

• Uncovering Principles of Adaptive Regulation in Cancer Resistance Through Deep Evolutionary Profiling

  A comprehensive understanding of the emergence of therapy resistance in cancer requires new approaches capable of generating and characterizing drug resistant cell lines at scale. Here, we present the EVolution Of Lineages in Vitro (EVOLV) platform, a high-throughput approach for generating diverse libraries of viable, drug-resistant cell lines from a common progenitor. EVOLV enables deeper insights into the genomics of drug resistance as well as into the complex interplay among genomic, transcriptomic, and functional layers during cancer evolution.

  Study phs003851

• NCTN: TAILORx: Program for the Assessment of Clinical Cancer Tests: Trial Assigning Individualized Options for Treatment (PACCT-1)

  Study ID: PACCT-1NCT Number: NCT00310180Trial Title: NCTN: Program for the Assessment of Clinical Cancer Tests (PACCT-1): Trial Assigning Individualized Options for Treatment: The TAILORx TrialTrial Description:This randomized phase III trial studies the best individual therapy for women who have node-negative, estrogen-receptor positive breast cancer by using a special test (Oncotype DX), and whether hormone therapy alone or hormone therapy together with combination chemotherapy is better for women who have an Oncotype DX recurrence score of 11-25. Estrogen can cause the growth of breast cancer cells. Hormone therapy may fight breast cancer by blocking the use of estrogen by the tumor cells or by lowering the amount of estrogen the body makes. Drugs used in chemotherapy 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. Giving hormone therapy together with more than one chemotherapy drug (combination chemotherapy) has been shown to reduce the chance of breast cancer recurrence, but the benefit of adding chemotherapy to hormone therapy for women with node-negative, estrogen-receptor positive breast cancer is small. New tests may provide information about which patients are more likely to benefit from chemotherapy. You are encouraged to view the PDF data dictionaries found in the "Documents" tab of the dbGaP study page, which may contain additional information regarding the data or the associated publication.ECOG-ACRIN Cancer Research GroupSubmitted in collaboration with the NCTN/NCORP Data ArchiveData presented in the following publication(s):PMID 29860917PMID 32271671Disease type(s): Breast Neoplasm - Breast Cancer - InvasiveAvailable Dataset(s):NCT00310180-D1 (PMID 29860917): This dataset contains the data published in the primary results publication for TAILORx (PACCT-1; NCT00310180; PMID 29860917). The dataset includes patient characteristics, OncoType Recurrence Score values, survival outcomes, and stratification variables used in the analyses presented in the publication. The data reflect the study database as of March 2, 2018. All patients who were registered to one of the arms are included.NCT00310180-D4 (PMID 32271671): There are three separate submissions for PMID 32271671, a publication analyzing the cognitive function among women with early breast cancer on ECOG-ACRIN trial PACCT-1. This dataset submission, NCT00310180-D4, contains additional clinical data in addition to those submitted in NCT00310180-D1 (for the trial's primary publication with PMID 29860917). Dataset NCT00310180-D5 contains the FACT-COG data. Dataset NCT00310180-D6 contains the FACT-G data. The data contained within variables identical to those presented in NCT00310180-D1 are not duplicated in this submission.NCT00310180-D5 (PMID 32271671): There are three separate submissions for PMID 32271671, a publication analyzing the cognitive function among women with early breast cancer on ECOG-ACRIN trial PACCT-1. This dataset submission, NCT00310180-D5, contains the FACT-COG data. Dataset NCT00310180-D4 contains additional clinical data in addition to those submitted in NCT00310180-D1 (for the trial's primary publication with PMID 29860917). Dataset NCT00310180-D6 contains the FACT-G data. The data contained within variables identical to those presented in NCT00310180-D1 are not duplicated in this submission.NCT00310180-D6 (PMID 32271671): There are three separate submissions for PMID 32271671, a publication analyzing the cognitive function among women with early breast cancer on ECOG-ACRIN trial PACCT-1. This dataset submission, NCT00310180-D6, contains the FACT-G data. Dataset NCT00310180-D4 contains additional clinical data in addition to those submitted in NCT00310180-D1 (for the trial's primary publication with PMID 29860917). Dataset NCT00310180-D5 contains the FACT-COG data. The data contained within variables identical to those presented in NCT00310180-D1 are not duplicated in this submission.Forthcoming Dataset(s): NCT00310180-D2, NCT00310180-D3

  Study phs004260

• Blood and Marrow Transplant Clinical Trials Network A Trial of Single Autologous Transplant With or Without Consolidation Therapy Versus Tandem Autologous Transplant With Lenalidomide Maintenance for Patients With Multiple Myeloma (BMT CTN-0702-BioLINCC)

  Data Access NOTE: Please refer to the “Authorized Access” section below for information about how access to the data from this accession differs from many other dbGaP accessions.Objectives: To compare the use of tandem autologous hematopoietic cell transplantation (AHCT) followed by lenalidomide maintenance, AHCT plus four cycles of lenalidomide, bortezomib, and dexamethasone (RVD) followed by lenalidomide, and AHCT and lenalidomide only in improving outcomes for patients with active multiple myeloma (MM).Background: At the time of this trial, initial myeloma reductive therapy followed by high-dose melphalan plus AHCT with long-term lenalidomide was the standard of care for patients newly diagnosed with MM in the United States. Despite substantive improvements in outcomes with the addition of lenalidomide, most patients still experienced disease progression and ultimately died as a result of the disease. Several approaches to further improve outcome after initial AHCT have been investigated but incremental benefit compared with maintenance therapy remains to be determined. This trial was initiated to assess whether the additional interventions of second AHCT or RVD consolidation to AHCT and lenalidomide further improve outcomes.Participants: Patients with symptomatic MM who were 70 years old or younger, had a Karnofsky score equal to or greater than 70, received at least two cycles of any regimen as initial systemic therapy without disease progression, and were within 2 to 12 months of the first dose of initial therapy were eligible.758 patients were enrolled. 247 patients were randomly assigned to the AHCT/AHCT + lenalidomide arm, 254 patients to the AHCT + RVD + lenalidomide arm, and 257 patients to the AHCT + lenalidomide arm.Design: The BMT CTN-0702 study was a Phase III multicenter trial. All patients were randomly assigned in a 1:1:1 manner at the time of enrollment, which occurred within 7 days before the first high-dose melphalan conditioning regimen. Random assignment was stratified by disease risk and transplantation center. High-risk MM was defined by presence of high β2-microglobulin, presence of cytogenetic abnormalities, or aneuploidy. Patients without cytogenetic analysis available and low β2-microglobulin level (≤5.5 mg/L) or with deletion 13 detected by fluorescence in situ hybridization were classified as standard risk.All enrolled patients were to receive high-dose melphalan (200 mg/m2) followed by mobilized autologous peripheral-blood stem-cell infusion (minimum 2 × 106 CD34+ cells/kg). Subsequent therapy was based on random assignment at the time of enrollment. The second phase of therapy started between 60 and 120 days after the first AHCT, once patients had sufficiently recovered. Patients randomly assigned to a second transplantation received high-dose melphalan (200 mg/m2) followed by autologous peripheral-blood stem-cell infusion. Patients randomly assigned to RVD consolidation received four cycles of lenalidomide 15 mg/d on days 1 to 14; bortezomib 1.3 mg/m2 on days 1, 4, 8, and 11 of every 21-day cycle; and dexamethasone 40 mg per day on days 1, 8, and 15. After their initial interventions, all patients received lenalidomide starting at 10 mg per day for 3 months and increasing to 15 mg per day. Dose adjustments for toxicity were permitted. Maintenance therapy was initially designed to be given for 3 years to all patients. An amendment expanded use of lenalidomide to continue until toxicity, disease progression, or withdrawal of consent.Quality of life was assessed using the Short Form 36 and Functional Assessment of Cancer Therapy-Bone Marrow Transplant at baseline and yearly.The primary study end point was progression free survival at 38 months.Conclusions: Second AHCT or RVD consolidation as post-AHCT interventions for the up-front treatment of transplantation-eligible patients with multiple myeloma did not improve progression free survival or overall survival. Single AHCT and lenalidomide should remain as the standard approach for this population.

  Study phs004692

• NCI Cancer Model Development for the Human Cancer Model Initiative (HCMI)

  The Cancer Model Development Center (CMDC) project is part of the Human Cancer Model Initiative (HCMI) and is managed by the Office of Cancer Genomics within the Center for Cancer Genomics at the National Cancer Institute (NCI). The goal of the HCMI is to generate approximately 1000 novel human "next generation" tumor-derived models as a community resource. The models aim to faithfully recapitulate the cellular complexity and heterogeneity of human tumors. The CMDCs are tasked by the NCI with producing a proportion of the cancer models. Wellcome Sanger Institute (WSI) is a contributing member of the HCMI. Models developed by HCMI are being derived from a number of tumor types and subtypes (see below), including rare adult, pediatric and understudied cancers. The number of models and the clinical sites from which patient samples are acquired is increasing. Normal tissue, originating tumor, and tumor-derived models are sequenced. The next generation cancer models are associated with rich clinical and genomic data through the NCI Genomic Data Commons for all researchers to advance cancer research. The CMDC and HCMI models will serve as excellent tools in research to provide insight into the pathways that influence tumor growth and progression, how tumors respond to therapy, etc. Ultimately, the data generated using these models will support the development of personalized oncology. There is a delay between registered IDs and model availability. The current model count is found in The HCMI Searchable Catalog which is updated when new models are available for distribution to the research community.

  Study phs001486

• Melanoma Genome Sequencing Project

  Melanoma is the most prevalent cause of skin cancer morbidity and mortality. In order to characterize the full range of somatic mutations that may drive the growth of melanoma, we are sequencing tumor and normal DNA from a set of roughly 150 melanomas. For the majority of samples (approximately 90% of the cases), mutations in protein coding genes will be assessed in the exonic DNA of tumor-normal pairs using hybrid capture and paired-end DNA sequencing. For a few of DNA samples (approximately 10% of the cases), the entire genomes will be analyzed to assess the possible contribution of complex structural rearrangements contributing to oncogenesis. The sequencing data are supplemented by copy number profiling on the same tumors using high-density SNP arrays. Integration of these approaches will enable the unbiased and comprehensive characterization of both known and novel recurrent DNA alterations that arise in melanoma.Versions 1-4 contain whole exome and bulk RNA sequencing data for patients with melanoma.Version 5 - We compared somatic genomic profiles from matched pre-treatment and post-resistance tumor biopsies in patients with metastatic melanoma who exhibited heterogeneous responses to immune checkpoint inhibitors (ICIs). This version includes whole exome sequencing (WES) data from 14 patients.

  Study phs000452

• TIGER-LC High-Throughput Sequencing

  Intrahepatic cholangiocarcinoma (CCA) and hepatocellular carcinoma (HCC) are clinically disparate primary liver cancers with etiological and biological heterogeneity. We performed sequencing on multiple data levels of Thai CCA and HCC among the Thailand Initiative in Genomics and Expression Research for Liver Cancer (TIGER-LC) cohort using targeted OncoVar platform, whole exome, whole transcriptome, and whole genome metagenomic sequencing.

  Study phs001199

• Yale SPORE in Skin Cancer Project 2

  Understanding the relationship between tumor and peripheral immune environments could allow longitudinal immune monitoring in cancer. Here, we examined whether T cells that share the same TCRab and are found in both tumor and blood can be interrogated to gain insight into the ongoing tumor T cell response. Paired transcriptome and TCRab repertoire of circulating and tumor-infiltrating T cells were analyzed at the single cell level from matched tumor and blood from patients with metastatic melanoma. The data shared here consist of gene expression matrix and fastq files obtained from sequencing single-cell libraries generated with the Chromium (TM) 5' technique. For each of 18 immunotherapy naive and 11 previously treated melanoma patients, T cells (Live/CD45+/TcRab+) were FACS-sorted from PBMCs and freshly resected tumors. Metadata associated with each individual cell consist of Patient I.D., biological sex, immunotherapy status, amino acid and nucleotide CDR3 sequence of the TCR alpha and beta chain (obtained from matched VDJ region enriched libraries), and sequencing batch. Further details about previous treatment history and other clinical parameters can be found in the associated manuscripts (Lucca et al., 2021: PMID: 33651881; Lu et al., PMID: 39609626).

  Study phs002289

• Characterization of High-Grade Serous Ovarian Cancer Subtypes via Single-Cell and Spatial-Transcriptomics Profiling

  We measured gene expression in single-cell RNA sequencing samples from patients with high-grade serous ovarian cancer (HGSOC), for a study on improving HGSOC subtype definition by taking into account varying cell type proportions within tumors. The initial dataset (added October, 2020) contains 3 samples (3 individuals). The next dataset (added November, 2022) contains 34 samples from 8 individuals. The samples in the second dataset were sequenced in five different ways: 1) rRNA depletion and bulk RNA sequencing of tumor chunks, 2) rRNA depletion and bulk RNA sequencing of dissociated cells, 3) poly-A capture and bulk RNA sequencing of dissociated cells, 4) poly-A capture and scRNA sequencing of dissociated cells, 5) barcoding and pooling cells and scRNA sequencing (2 pools of 4 samples each). The third dataset (added June, 2024) contains data from one spatially resolved transcriptomics experiment (4 samples, one per Visium capture area, describing one tumor from one individual) and scRNA sequencing on 5 samples (5 individuals).

  Study phs002262