Search Results - EGA European Genome-Phenome Archive

Blood and Marrow Transplant Clinical Trials Network - A Phase II Multicenter Trial of Single Autologous Hematopoietic Cell Transplant Followed by Lenalidomide Maintenance for Multiple Myeloma with or without Vaccination with Dendritic Cell/Myeloma Fusions (BMT CTN-1401-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 response at one year post transplant between participants receiving dendritic cell/myeloma vaccine along with granulocyte macrophage colony-stimulating factor (GM-CSF) and lenalidomide maintenance therapy to those receiving lenalidomide maintenance therapy with or without GM-CSF.Background: The advent of combination biologic therapy for multiple myeloma (MM) has significantly improved patient outcomes. Induction therapy followed by consolidation with autologous hematopoietic stem cell transplantation (auto-HCT) prolongs progression-free survival in patients with MM. The addition of post-transplant lenalidomide maintenance therapy further extends the duration of remission. However, the vast majority of patients ultimately experience disease progression due to the emergence of resistant disease. The development of strategies to enhance the durability of post-transplant response remains a major unmet need in the field. Since MM is associated with immune suppression, the development of cancer vaccines is being investigated in MM with the goal of stimulating tumor-specific immunity. Dendritic cells (DC) are the most potent antigen-presenting cells that prominently express costimulatory signaling necessary for optimal T-cell activation, cross-presentation of antigen to reactive CD8 T cells, and the development of primary immunity. The BMT CTN developed a personalized cancer vaccine in which patient-derived tumor cells are fused with autologous monocyte-derived DCs. The BMT CTN-1401 study examined the efficacy of the DC/MM fusion vaccine in conjunction with lenalidomide maintenance therapy after auto-HCT, compared with maintenance alone.Participants: Participants with symptomatic MM were eligible if they were 18-70 years old, were candidates for auto-HCT, had a Karnofsky Performance status of ≥70%, had >20% plasma cells in the bone marrow aspirate differential A total of 140 participants were randomized. 68 participants were randomized to the vaccine arm, 37 to the lenalidomide plus GM-CSF arm, and 35 to the lenalidomide alone arm.Design: BMT CTN-1401 was a phase II, multicenter, open label trial. All participants underwent bone marrow aspiration following enrollment. Myeloma cells were isolated, preserved, and for participants randomized to the vaccine arm, used for vaccine generation. All participants received standard-of-care induction therapy and auto-HCT conditioned with melphalan. Participants were randomized approximately 2 months post-transplant. Participants were randomized in a 2:1:1 ratio to the vaccine arm (DC/MM vaccine, GM-CSF, plus lenalidomide), or one of two control arms (lenalidomide plus GM-CSF or lenalidomide alone). All participants began maintenance lenalidomide between day 90 and 100 post-transplant at a dose of 10 mg a day for 28 days of a 28-day cycle. On day 1 of cycles 2, 3, and 4 of lenalidomide maintenance, patients assigned to the vaccine arm underwent subcutaneous administration of the DC/MM fusion vaccine along with 100 μg GM-CSF administered subcutaneously adjacent to the vaccine site on days 1 to 4. Participants randomized to the control arms received either lenalidomide alone or lenalidomide with GM-CSF at the same dose and schedule as the vaccine arm.The primary outcome was a comparison of participants in complete response (CR)/stringent CR (sCR) at 1-year post-transplant between the vaccine and control arms. The primary immunologic endpoint of the study was a comparison of the percentage of circulating multiple myeloma–reactive T cells between participants in the vaccine and control arms. PFS (progression-free survival) and OS (overall survival) were secondary endpoints of the study.Conclusions: There was not a statistically significant difference in the percentage of participants achieving complete response 1-year post-transplant in the vaccine arm compared to the control arms.

Study phs004718

NCTN: A Randomized Phase III Post-operative Trial of Platinum Based Chemotherapy vs. Capecitabine in Patients with Residual Triple-Negative Basal-Like Breast Cancer following Neoadjuvant Chemotherapy (EA1131)

Study ID: EA1131 NCT Number: NCT02445391 ECOG-ACRIN Cancer Research Group Submitted in collaboration with the NCTN/NCORP Data Archive Trial Title: NCTN: A Randomized Phase III Post-operative Trial of Platinum Based Chemotherapy vs. Capecitabine in Patients with Residual Triple-Negative Basal-Like Breast Cancer following Neoadjuvant Chemotherapy (EA1131) Trial Description: This randomized phase III trial studies how well cisplatin or carboplatin (platinum based chemotherapy) works compared to capecitabine in treating patients with remaining (residual) basal-like triple-negative breast cancer following chemotherapy after surgery (neoadjuvant). Drugs used in chemotherapy, such as cisplatin, carboplatin and capecitabine, 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. It is not yet known whether cisplatin or carboplatin is more effective than capecitabine in treating patients with residual triple negative basal-like breast cancer. Clinical data presented in the following publication(s): PMID 34092112 Disease type(s): Breast Neoplasm - Breast Cancer - Invasive Clinical dataset(s) included: NCT02445391-D1 (PMID 34092112): There are three datasets for PMID 34092112. This dataset, NCT02445391-D1, contains baseline characteristics, stratification factors, treatment, second primary cancer, cause of death and efficacy data. The data reflect the study database as of April 7, 2021. All patients who were randomized to one of the three arms were included in the database (NCT02445391-D1). Accrual was open to arm A (observation) and arm B (platinum) prior to Amendment #3, and accrual to arm A was permanently closed and accrual to arm C (capecitabine) was opened in Amendment #3. NCT02445391-D2 (PMID 34092112): There are three datasets for PMID 34092112. This dataset, NCT02445391-D2 contains data on dose modification. The data reflect the study database as of April 7, 2021. NCT02445391-D3 (PMID 34092112): There are three datasets for PMID 34092112. This dataset, NCT02445391-D3, contains toxicity data. The data reflect the study database as of April 7, 2021. All treatment-related AEs were included in the database, and only the worst degree was reported in the paper. 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 phs004236

A Phase 1-2 Study of the Combination of Olaparib and Tremelimumab in BRCA1 and BRCA2 Mutation Carriers with Recurrent Ovarian Cancer (NCT02571725)

INST1419: A phase 1-2 study of the combination of olaparib and tremelimumab in BRCA1 and BRCA2 mutation carriers with recurrent ovarian cancer (NCT02571725) was designed to evaluate the safety and efficacy of combined treatment with the PARP inhibitor olaparib and the CTLA4 immune checkpoint inhibitor tremelimumab in women with recurrent ovarian cancer and a germline BRCA1 or BRCA2 mutation. This was a multi-site single-arm open-label study that enrolled 50 subjects with recurrent epithelial ovarian, fallopian tube, or primary peritoneal cancer between 2016 and 2020. Treatment efficacy was assessed using best overall response by modified WHO (mWHO) criteria, and secondary endpoints included disease control rate, duration of response, and progression-free and overall survival. The median age was 56 (range 39-78). All patients had measurable disease and pathogenic germline mutations in BRCA1 (72%) or BRCA2 (28%). Subjects received 300mg of olaparib by mouth, twice daily, and tremelimumab at 10mg/kg IV every four weeks for 6 doses, and then every 12 weeks for up to 24 months. Following an interim data safety monitoring review in 2018, the protocol was modified to reduce the frequency of tremelimumab infusions to 10mg/kg IV every four weeks for 4 doses, followed by infusions every 12 weeks. Exploratory biomarker assessments were performed using archived formalin-fixed paraffin-embedded (FFPE) tumor samples collected at the time of initial cytoreductive surgery from 33 subjects. Clinical characteristics and outcomes for the biomarker cohort were similar to the overall and response cohorts. Candidate biomarkers were identified based on differential gene expression in samples from patients with clinical benefit from treatment, defined as disease control for at least 12 weeks, versus those with progressive disease. For RNAseq, sample integrity was assessed using Agilent Tapestation, to ensure the DV200 was greater than or equal to 30. Sequencing was done on the Illumina NovaSeq instrument by Personalis. Gene expression used in this analysis was the normalized measure defined as transcripts per million (TPM) total RNA molecules. Welch's t-test was used to assess whether there was a difference in gene expression based on clinical benefit. The area under the receiver operating characteristic curve (AUC) was also computed for TPM gene expression based on clinical benefit. The AUC, as determined by the trapezoidal rule, was estimated by the concordance index (SAS 9.4 LOGISTIC procedure). DNA quality was confirmed if the DNA integrity number was greater than or equal to 3. Exome enrichment was performed using the Accuracy and Content Enhanced (ACE) version 4 (ACE ImmunoID NeXT) enrichment platform of Personalis. Briefly, DNA from tumor and cryopreserved PBMC samples were used to construct whole-exome capture libraries, and additional custom probes and optimized chemistry improved uniformity of coverage in sequence regions of high G-C content across the exome using ACE technology. Sequencing was performed at 20 Gigabase (G) sequencing depth for normal samples and 35G sequencing depth for tumor samples. All DNA and RNA reads were aligned to the hs37d5 reference genome built in accordance with the Personalis ACE Cancer Exome Analysis Pipeline, duplicate reads were removed, and the Genome Analysis toolkit was used to correct base quality scores and improve sequence alignment. Mutational burdens were generated using tumor-specific genomic events (SNVs, indels and fusions) of at least 5% allelic fraction that were verified using transcriptomic data. All potential neoepitopes were created for each mutation and tested for presentation, and considered putative neoepitopes if they were predicted to bind to any patient-specific alleles. The Xenium platform was used for spatial transcriptomic analyses using Xenium slides and sample prep reagents (10x Genomics). The immune panel was augmented with custom-ordered genes. Initial preprocessing included quality control, normalization, batch correction, and clustering. Cells with fewer than 20 detected features were excluded as low-quality. High-quality cell-by-gene count matrices were processed using Seurat 5.3.0, with normalization performed using SCTransform. Batch correction was carried out using Harmony integration, following standard preprocessing: individual dataset normalization, merging, PCA (RunPCA), and integration via RunHarmony. Clustering was performed on the Harmony-corrected embeddings using FindNeighbors and FindClusters (resolution = 0.03), and visualized with UMAP (RunUMAP). Cell types were initially assigned using SingleR with the HPCA reference dataset. To resolve cellular heterogeneity, subclustering was performed on select clusters using the FindSubCluster function in Seurat. Canonical marker genes used for cell type identification included CD3E for T cells, MS4A1 for B cells and EPCAM for epithelial and DCN for fibroblasts. Results from this trial demonstrated grade 3 or 4 non-hematologic toxicity in 57% of subjects. The overall response rate was 32.7% (95% CI 19.5-45.8%), with a disease control rate of 47.7% (95% CI 33.0-62.5%). In exploratory biomarker analyses, low VSTM5 or IFIT1B expression predicted treatment benefit and progression-free survival (pData available through dbGaP include RNAseq, whole exome sequencing, and Xenium spatial transcriptomic data.

Study phs004512

The Electronic Medical Records and GEnomics Network Genomic Risk Assessment (eMERGE IV)

The eMERGE (electronic MEdical Records and GEnomics) network enrolled ~25,000 individuals not typically involved in research in a prospective cohort study across 10 sites. The network developed methods to return cross-ancestry polygenic risk scores, monogenic risks, family history, and clinical risk assessments via a genome-informed risk assessment (GIRA) report along with recommended actions. The GIRAs include summary care recommendations for 11 conditions, education pages, and clinical laboratory reports and was returned to participants, their providers, and their EHR. The network is examining the uptake of care recommendations after return of results.Children's Hospital of Philadelphia (CHOP)The Center for Applied Genomics (CAG) is a specialized Center of Emphasis at the Children's Hospital of Philadelphia (CHOP) with the primary goal of translating basic research findings to medical innovations. The mission of CAG is to develop new and better ways to diagnose and treat children affected by rare and complex medical disorders. We aim to discover genetic causes for the most prevalent diseases of childhood including ADHD, asthma, autism, diabetes, epilepsy, obesity, schizophrenia, pediatric cancer, and a range of rare diseases. Ultimately, our objective is to generate new diagnostic tests and to guide physicians to the most appropriate therapies. Our participants are recruited from the CHOP Health Care Network, which includes over 50 sites throughout Pennsylvania and New Jersey, 100% of which use Epic EMR system. This constitutes the country's largest pediatric integrated delivery system, supporting >1.1 million visits/year within the primary and specialty care networks, community-based inpatient pediatric and neonatal programs, a rehabilitation hospital, and a home care service. It provides acute- and well-care to patients in urban, rural, and suburban settings.Cincinnati Children's Hospital Medical Center (CCHMC)CCHMC has proposed ambitious initiatives for eMERGE IV. The major goals are to generate, return as appropriate along with clinical recommendations, individualized genomic risk assessments that include polygenic risk scores for 2500 minority participants ascertained on dyads (mother/child) and extended to families (dyad + biologic father, siblings). The informatics initiatives include integration of electronic medical records and development, implementation and evaluation of clinical decision support at two different hospital systems, one pediatric and one adult. Participant preferences, education needs, and ethical and social implications will be studied throughout the 5 year period. Columbia UniversityColumbia University in partnership with the New York-Presbyterian hospital has a long and strong tradition of patient-centered research and community engagement in the urban, medically underserved communities of Washington Heights and Harlem in Northern Manhattan, and has established Precision Medicine as a major university-wide initiative (PMI), of which eMERGE is a vital program. We possess broad and deep expertise in clinical genetics, genomics, informatics, EHR phenotyping, systems biology, public health, and ELSI, including return of genetic results and secondary findings to diverse patients. Columbia will share lessons learned in linking EHR and sequence data for genomic decision support, developing scalable genomic education methods and assessing the impact of returning genetic results on patients, families, and clinicians. We are poised to contribute novel comprehensive risk prediction and management solutions for diverse patients as part of eMERGE IV efforts.Icahn School of Medicine at Mt. Sinai (Mt. Sinai)Mt. Sinai investigators have been at the center of many NHGRI-led genomic research (GSP, PAGE) and genomic medicine (eMERGE, CSER, IGNITE) consortia. Building on our decade-long track record in genomic research, clinical trials, and genomic medicine in diverse, underserved patients from New York City, we propose to develop new frameworks to bring genomic risk into clinical care to promote health equity. In addition to genomic discovery and risk prediction, we are creating analytical and data resources, and digital health applications tailored to diverse populations, as part of the eMERGE IV Network. The Mt. Sinai team is composed of clinicians and scientists who work closely with community members and industry partners to develop flexible and innovative strategies to bring leading-edge research into clinical care. Having recently announced a large institutional investment to scale the integration of genomics and artificial intelligence into patient care, Mt. Sinai is poised to contribute to eMERGE IV's mission to implement and learn from genomic risk assessment in clinical care. Mt. Sinai's team will contribute to progress in multiple areas across eMERGE, including developing and deploying electronic phenotypes; discovering new genotype-phenotype associations; and facilitating the communication of genomic results to patients and their healthcare providers.Mass General BrighamThe eMERGE IV Clinical Center at Mass General Brigham leverages a large biobank, clinical data in the electronic health records (EHR) for >6 million patients from the largest integrated health care provider in New England, advanced bioinformatics expertise, prior leadership in PRS development, established expertise in returning genomics results, and experience using information technology to transform clinical processes and assess medical, behavioral and economic outcomes. We have developed highly specific machine learning algorithms for e-phenotypes and implemented eMERGE algorithms for multiple phenotypes and have considerable experience in developing decision support tools and analyzing outcomes that can be leveraged to study the integration of PRS data into clinical practice. We will test the hypothesis that PRS will allow us to stratify eMERGE participants based on genetic risk for common complex traits. We will focus on coronary artery disease, atrial fibrillation, type 2 diabetes, colorectal cancer and depression in GWAS populations and validate multi-ethnic PRS in the Mass General Brigham Biobank and eMERGE III dataset. We will conduct an analysis of the effect of disclosing results to high risk participants to determine how personalized results changed patient outcomes in laboratory values, risk reduction behaviors, or health care utilization.Mayo Clinic (Mayo)The goal of Mayo eMERGE investigators is to leverage the electronic health record (EHR) for genomic discovery and to implement genomic medicine to improve health care outcomes, working closely with other eMERGE sites and the Mayo Center for Individualized Medicine. In eMERGE I we used genotype data and electronic phenotyping algorithms for genomic discovery. In eMERGE II we conducted a clinical trial of disclosing a polygenic risk score (PRS) for coronary heart disease (CHD) and placed pharmacogenomic variants in the EHR with linkage to clinical decision support (CDS). In eMERGE III, we returned actionable findings from targeted sequencing of 68 genes and collaborated with a Federally Qualified Health Center (FQHC) to bring genomic medicine to an under-represented population. In eMERGE IV, as part of the Genomic Risk Assessment & Management Network, we will test the hypothesis that individuals at high polygenic risk for common diseases will have a higher uptake of risk reduction measures than those at lower risk. We will build on our prior work in genomic discovery, EHR integration and return of results (RoR) to develop and validate PRS and combine these with clinical risk scores and family history to compute comprehensive risk profiles for 2500 individuals. Our prior work in disclosing a PRS for CHD to research participants as part of a comprehensive risk profile enables us to efficiently expand the approach to other common diseases that pose a significant public health burden. To assess the utility of PRSs, we will recruit 1800 adults and 200 adolescents from Rochester MN and 500 adults from Phoenix AZ. DNA will be sent for CLIA-certified genomic testing and we will calculate ancestry specific PRSs for each participant. Individualized risk estimates will be reported to participants and health care providers (HCPs) and placed in the EHR with linkage to CDS that includes guideline-based risk-management information. For participants who are at significantly higher polygenic risk of developing at least 1 of the diseases, results will be disclosed in-person by a HCP followed by assessment of outcomes including new tests ordered, risk reduction measures, and changes in modifiable risk factors. We will examine the economic, behavioral and psychosocial implications of returning PRS. Our focus on PRS for common cardiovascular diseases brings genomic medicine to the population. We will continue our partnership with Mountain Park Health Center, a FQHC serving low-income, minority communities in Phoenix AZ, to address concerns about health disparities in the context of genomic medicine.Northwestern University (NU)Northwestern University is dedicated to translational genomics, with a strong focus on unified, interdisciplinary research bridging the informatics, clinical, basic science, and bioethics domains. Over the phases of eMERGE, Northwestern has applied this interdisciplinary approach to study the feasibility, utility, outcomes, and effectiveness of EHR-linked genomic information as a member of the network. Particular areas of focus include: novel informatics approaches to integrate genomic results into EHR systems; development of open-source, EHR-based phenotyping algorithms to empower translational research across a variety of clinical domains; and studies of participant, patient, and provider interaction with EHR-based genomic results. In phase IV of eMERGE, Northwestern is building on this expertise to develop, deploy, and evaluate systems of EHR-based, genomics-guided clinical risk assessment and management tools across a variety of common, impactful conditions. Northwestern's cross-disciplinary approach to this work is empowered by an innovative smartphone app to consolidate outreach, enrollment, engagement, return of results, and dissemination of health education materials surrounding genetic risk and risk management. Focusing recruitment on community-based clinics, Northwestern aims to engage participants from communities that, though not traditionally included in academic research settings, could benefit significantly from these risk management approaches. By combining expertise in informatics and EHR integration with innovative return-of-results strategies rooted in behavior theory, Northwestern aims to provide valuable data on accuracy, utility, and uptake of genetic risk assessment as the field moves towards integrating genetic risk scores into clinical practice.University of Alabama at Birmingham (UAB)Our eMERGE team aims to bring our experience and expertise in research with medically underserved (>75%) populations to identify genomic signatures of common diseases, conduct genomic risk assessments within the clinical workflow and where appropriate, pre-treat at-risk patients with common diseases including diabetes, chronic obstructive pulmonary disease, obesity, coronary artery disease and prostate cancer. Our aims will also allow us to develop genomic risk assessments, and address challenges involved in bringing genomic medicine into routine medical care. Working with the eMERGE network, we will select the eleven diseases of public health impact and select polygenic risk scores for clinical implementation. We will conduct an ethical legal social implications (ELSI) study, to explore patient perspectives on the use of family history and polygenic risk scores for estimating disease risk among Alabama Genomic Health Initiative (a statewide cohort) participants. The results will inform the development of consent, educational materials, and a communication strategy to enhance recruitment and retention of eMERGE participants. Recruiting over 75% of patients from medically underserved communities, we will incorporate genomic risk, family history, and clinical data to identify high-risk patients, recommending risk reduction recommendations in concordance with practice guidelines. For high-risk patients, we will deploy clinical decision support and present the genomic risk assessments and risk reduction recommendations. We will assess three outcomes: uptake of recommendations (implementation outcome), adherence to clinic visits (engagement outcome), and surrogates of disease/control (clinical outcome; e.g. blood sugar, cholesterol). We bring our expertise and experience to collaborate with the eMERGE investigative team to leverage the power of genomics to prevent disease.University of Washington (UW)The eMERGE IV Northwest partnership includes clinicians, scientists, and professionals in other fields from University of Washington (UW) Medicine, UW Health Sciences, the Fred Hutchinson Cancer Research Center, and the Brotman Baty Institute for Precision Medicine. The eMERGE IV Northwest partnership aims to evaluate the use of genomic information in the health care of diverse participants at the University of UW. Our site is expected to lead work on the prediction of colon cancer, glaucoma, and cardiovascular disease; other conditions expected to be studied include diabetes, liver disease, high cholesterol, and osteoporosis. Working with our eMERGE colleagues, we will aggregate, into a single score that informs about the risk of a disease, a participant's polygenic test information, which looks at variants from across the genome, as well as other known risk factors, such as personal and family medical history, environmental and social determinants, and physical and lab results. This score would let clinicians know which patients might benefit from screenings or other interventions to reduce the risk of disease or make an early diagnosis. In addition to experts specializing in each of the medical conditions that are the focus of the Northwest site, leaders in health economics, and in the ethical and societal aspects of genomics and health care will also be part of the research team. Medical, as well as economic, outcomes will be measured. Stakeholder engagement will be encouraged to obtain comments from participants and their families.Vanderbilt University Medical Center (VUMC)Vanderbilt University Medical Center has embraced Personalized Health and Healthcare as a key pillar of our Research Strategic Plan. This institutional commitment has taken multiple forms including the development of key infrastructure resources (the institutional Biobank (BioVU); the program in preemptive pharmacogenetic testing; the genotyping and sequencing core) and support of faculty in key disciplines such as genomics, informatics, ethics, privacy science, and clinical pharmacology. VUMC's team has contributed importantly to progress in multiple areas across eMERGE, including developing and deploying phenotype algorithms; developing and managing the genotype quality control pipeline for the network (eMERGE I); discovering new genotype-phenotype relations in VUMC and cross-network datasets; actively participating in the PGx clinical implementation project, community consultation, and return of results initiatives; developing methods to resolve tensions between data access and individual privacy; developing sampling methodology for the CERC survey; and developing new software tools for the field, including for developing and validating phenotypes, de-identification and for the phenome-wide association study paradigm (“PheWAS”)eMERGE Network Coordinating Center (CC)Vanderbilt University Medical Center has been the coordinating center of the eMERGE Network since inception. During this phase of eMERGE we have partnered with the Broad Institute to to add expertise in large-scale genotyping, cloud computing, and genomic data analysis and management, and with Duke University to leverage its proficiency in the implementation of patient-oriented family history tools and delivery of risk assessments. To meet the needs of the Network, the CC continues to serve NHGRI, the Network, and its members in all coordination, communication, and collaboration functions while providing a nationally visible home for eMERGE authored tools and scientific productivity. The CC is also assisting the Network with selecting and validating polygenic risk scores (PRS) for approximately eleven complex diseases and developing genomic risk assessments (GRAs) which combine the PRS with other clinical risks, family history, and monogenic risks. Finally, The CC will coordinate a prospective study for 25,000 participants which calculates clinical and genomic risks for participants and their providers. In addition to providing the genotyping and PRS reporting services, we will develop with the Network scalable EHR-based methods to assess uptake of risk-reduction recommendations and clinical impact.

Study phs003905

NCTN: A Randomized Phase III Trial of Oxaliplatin (OXAL) Plus 5-Fluorouracil (5-FU)/Leucovorin (CF) With or Without Cetuximab (C225) After Curative Resection for Patients With Stage III Colon Cancer (N0147)

Study ID: N0147NCT Number: NCT00079274Trial Title: NCTN: A Randomized Phase III Trial of Oxaliplatin (OXAL) plus 5-Fluorouracil (5-FU)/Leucovorin (CF) with or without Cetuximab (C225) after Curative Resection for Patients with Stage III Colon Cancer (N0147)Alliance for Clinical Trials in OncologySubmitted in collaboration with the NCTN/NCORP Data ArchiveTrial Description: This randomized phase III trial was originally designed to compare three different combination chemotherapy regimens to see how well they work. As of September 1, 2004, the study was expanded to a total of 6 arms (the original 3 arms (A, B, C) and 3 additional arms which were the same as the first 3 but with cetuximab) in treating patients who have undergone surgery for stage III colon cancer. Drugs used in chemotherapy, such as irinotecan hydrochloride, fluorouracil, leucovorin calcium, and oxaliplatin, work in different ways to stop tumor cells from dividing so they stop growing or die. Monoclonal antibodies such as cetuximab can locate tumor cells and either kill them or deliver tumor-killing substances to them without harming normal cells. Combining more than one chemotherapy drug with monoclonal antibody therapy and giving them after surgery may kill any remaining tumor cells. It was not known at the time this study was developed which combination chemotherapy regimen is more effective after surgery in treating colon cancer. This study had several key changes, based on the results of other phase III trials. As of 6/1/2005, patients no longer received irinotecan on this study and treatment arms B, C, E, and F were discontinued. Patients on arms B and C crossed to arm A. Patients on arms E and F crossed to arm D. Patients on arms C and F who had not gotten to irinotecan continued on arms A and D, respectively. As of 8/18/2008, pre-screening for Kirsten rat sarcoma (KRAS) status was added with mutant KRAS (or KRAS not evaluable) patients put on arm G and wild-type KRAS patients randomized between arm A and arm D. Patients on arm G were treated per physician discretion and followed for disease and survival status. KRAS was determined in a central laboratory and was process for all patients on this study. The primary endpoint of this study was modified on 8/18/2008 to focus on patients having wild-type KRAS tumors. All modifications were approved by the Central Institution Review Board, local Institutional Review Boards, NCI, and the NCCTG Data Safety Monitoring Board.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.Clinical Data presented in the following publication(s): PMID 22474202Disease type(s): Gastrointestinal Neoplasm - Colorectal CancerClinical Dataset(s) included:NCT00079274-D1 (PMID 22474202): The NCT00079274_D1.txt dataset is one of 3 datasets associated with PubMed ID 22474202. This dataset contains information on baseline characteristics (e.g., age, race, etc.), eligibility (e.g. tumor staging, etc.), follow-up status (e.g., reason treatment ended, days from randomization until last protocol therapy, etc.), response status, and KRAS status.NCT00079274-D2 (PMID 22474202): The NCT00079274_D2.txt dataset is one of 3 datasets associated with PubMed ID 22474202. This dataset contains information on overall survival, disease free survival and time to recurrence analyses.NCT00079274-D3 (PMID 22474202): The NCT00079274_D3.txt dataset is one of 3 datasets associated with PubMed ID 22474202. This dataset contains information on grade 3 or higher reported toxicity.Additional genomic data are available for this trial under phs001290.

Study phs004241

Sequencing Data from Patient-Derived Models of Pediatric Cancer

Pediatric cancer can take decades of life from patients and devastate families. To design improved treatments we must understand the pathogenesis and molecular mechanisms underlying development of these diseases. Tumor samples from patients are precious resources that give unique biological insights. To extend the utility of these samples, we utilize patient derived xenograft (PDX) models. These models are created by growing patient tumor samples in immune compromised mice. This increases the volume of samples available for study and enables in vivo testing. We generated single cell RNAseq data from pediatric PDX models to characterize the tumor, explore microenvironmental interactions and test treatments. This study aims to provide a warehouse for data generated from PDX models. Additional data will be added as it becomes available and is published.

Study phs004719

Cancer Associated Fibroblasts Drive Epithelial to Mesenchymal Transition and Classical to Basal Change in Pancreatic Cancer Cells with Loss of IL-8 Expression

We examined the transcriptional changes induced by cancer associated fibroblasts in pancreatic ductal adenocarcinoma patient-derived tumor organoids. We hypothesized that cancer associated fibroblasts (CAFs) impacted tumor cell transcriptional phenotypes to promote more tumorigenic behavior. Using patient-matched cells from 8 patients, we compared the transcriptional profiles of patient-derived organoids in monoculture to patient-derived organoids co-cultured with autologous CAFs. Similarly, we looked at the transcriptional changes in matched patient-derived CAFs grown in monoculture or co-cultured with patient-derived organoids. With a focus on intercellular crosstalk, we identified crosstalk between CAFs and patient-derived organoids through changes in tumor cell classification (classical vs basal) and a phenotype of more prominent epithelial to mesenchymal transition. We also identified IL8 as a regulator for maintaining a classical tumor cell phenotype. This was identified by bulk RNA sequencing and examined dynamically in organoid-CAF co-culture. This dbGaP deposit is the bulk RNA sequencing data for these 8 patients. The deposit for 3 additional patients from this cohort who did not receive neoadjuvant chemotherapy can be found at: phs003563.

Study phs004499

Childhood Cancer Data Initiative (CCDI): CCDI Pediatric In Vivo Testing Program - Orthotopic CNS Tumors

The goal of this project is to advance the development of effective therapies for pediatric brain cancers through preclinical in vivo testing of novel agents. We utilize a well-characterized panel of approximately 150 patient-derived orthotopic xenograft (PDOX) models that replicate the histopathologic and molecular features of the original patient tumors. These models represent multiple pediatric CNS tumor types, including high-grade glioma, medulloblastoma, ependymoma, diffuse intrinsic pontine glioma (DIPG), and atypical teratoid/rhabdoid tumor (ATRT), across diverse disease stages and molecular subtypes. As part of this effort, the PDOX models are being molecularly characterized to identify promising therapeutic candidates. Molecular profiling includes whole exome sequencing (WES), RNA-seq, MethylEPIC array, CytoSNP array, and DNA fingerprinting for quality control. Demographic and clinical data (e.g., diagnosis, disease site, disease status) are also shared.

Study phs003162

Radiology Imaging Data Containing Faces from The Cancer Imaging Archive

Effective January 6, 2022, all radiology datasets containing images that could be used to reconstruct a 3D volume resembling a human face were put behind a controlled-access request system to mitigate potential re-identification risks emerging from advances in facial recognition tools.

Study phs004225

Impact of HLA Aberrations on Tumor Neoepitope Presentation

TP53 mutations may encode tumor-specific truncal neoantigens for targeting cytotoxic T lymphocyte (CTL). Using mass spectrometry followed by X-ray crystallographic analysis of HLA-bound p53 neoantigens, clinical tumor database analyses, and functional studies of neoantigen-directed T cell receptors (TCRs), we have built a comprehensive p53 immunopeptidome. As a component of this study, we noted that tumors with neoantigens displayable on HLA-A*02:01 or HLA-B*07:02, and structurally divergent from p53 wild-type peptide-HLA complexes, may exploit an allele's absence for growth in patients. The data deposited highlights that in brain metastasis of an ovarian cancer, that a damaged HLA-A*02:01 allele resulted in inability to present the p53 I195F neoepitope (GLAPPQHLFRV). Conversely, a simultaneously processed glioblastoma sample, sequenced as a control (and bearing a p53 R248W mutation on an A*24:02/A*32:01 background), revealed full exome genomic reads and transcript reads of the HLA-A locus. This indicated that biallelic HLA-A loss in the 10-417-1023 tumor was not a technical issue but represented damage to the 5' encoding exons of HLA-A.

Study phs004529

8432 results for "canc*"

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