12312 results for "cancer rna-seq"

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• Zero Childhood Cancer

  Dac EGAC00001001683

• Whole Exome Sequencing of Mixed Histology Lung Cancer at MDACC

  Dac EGAC00001002034

• Peter MacCallum Cancer Centre Research Data Access Committee

  Dac EGAC00001002510

• Garvan/St Vincent’s Prostate Cancer Tissue and Data Access Committee

  Dac EGAC00001002769

• Hoag Family Cancer Institute Carcinoid Multiomic Study Data Access Committee

  Dac EGAC00001003084

• TCR sequencing of TIL in breast cancer data access committee

  Dac EGAC00001003173

• Human Throid Cancer and CDK4/6 inhibition Data Access Commitee

  Dac EGAC00001003446

• Netherlands Cancer Institute (NKI) - Wilbert Zwart Group

  Dac EGAC00001003257

• Unraveling the genetics of transformed splenic marginal zone lymphoma

  Study EGAS00001006389

• Mechanisms of duodenal adenoma development in familial polyposis syndromes

  Study EGAS00001006561

• University of Melbourne Centre for Cancer Research (UMCCR) Data Access Committee

  Dac EGAC00001003567

• Resident memory CD8 T cell in human lung cancer

  Study EGAS00001004707

• Single cell RNAseq of PBMC from bladder cancer patients

  Study EGAS00001004458

• Genomic Analysis of a Metastatic Fusion-negative Embryonal Rhabdomyosarcoma

  Study EGAS00001006946

• OvCan2

  Digital images of ovarian cancer metastases

  Dataset EGAD00010001099

• EGAD00010000556

  SNP 6.0 arrays of small cell lung cancer

  Dataset EGAD00010000556

• EGAD00010000554

  SNP 6.0 arrays of small cell lung cancer

  Dataset EGAD00010000554

• Germline and Somatic Genetic Landscape of Pediatric Rhabdomyosarcoma

  Dynamic approaches that integrate population-based research and molecular biology are needed to explain the mechanisms underlying pediatric rhabdomyosarcoma (RMS) and to determine novel prevention strategies. RMS, the most common soft-tissue sarcoma in children and adolescents, has one of the poorest 5-year survival rates among all pediatric cancers (less than 65%). One of the strongest risk factors for RMS is having a cancer predisposition syndrome. The syndromes that are most commonly seen among those with RMS are Li-Fraumeni, neurofibromatosis type 1, Costello, Noonan, and DICER1. Based on smaller clinic-based studies, only about 7% of RMS cases are thought to be associated with the genes responsible for these syndromes. However, there have been no population-based assessments to support this estimate. Even in the most recent large-scale evaluations of germline mutations in predisposition genes among children with cancer, very few RMS cases were included (43 cases). Furthermore, no distinctions were made between the major histologic subtypes of RMS: embryonal (eRMS) and alveolar (aRMS), which display differences in terms of age distribution, incidence, and cytogenetics. For instance, nearly 80% of alveolar cases are driven by a chromosomal translocation between either PAX3 or PAX7 and FOXO1, whereas these fusions are not seen in embryonal cases. In fact, RMS research is shifting from categorization based on histology to fusion status (eRMS is overwhelmingly fusion-negative). Another limitation in previous studies has been the inability to evaluate the frequency of de novo germline mutations (DNMs) in cancer predisposition genes due to the absence of any well-characterized cohorts of RMS case-parent trios. Therefore, a major gap in our understanding of the role of cancer predisposition in pediatric RMS that limit translational impact is there have been no population-based assessments to determine the true impact of these mutations on pediatric RMS, which limits clinical sequencing guidelines and surveillance protocols in these children.Overall Project Strategy: The objective of this project is to advance our understanding of the relationship between cancer predisposition genes and pediatric RMS. Our central hypotheses are: 1) mutations in cancer predisposition genes are more common than expected in children with RMS; and 2) children with fusion-negative tumors have a higher burden of germline mutations than those with fusion-positive tumors. The framework for this study relies on >600 well annotated samples collected from newly diagnosed RMS patients and stored in the Children’s Oncology Group (COG) Biopathology Center.

  Study phs002304

• Sequencing to Guide Cancer Care (CanSeq)

  The overall goal of the CanSeq U01 project is to study the impact of whole-exome sequencing (WES) on the clinical care of cancer patients and oncology provider practices. The aims of Project 1 are to implement and establish the feasibility of germline and somatic WES in patients with advanced solid tumors (lung and colon); to develop a framework for interpreting and reporting for exome sequencing data; to determine the proportion of patients with "actionable items" compared to existing technologies; and to report on the percentage of patients in whom unique WES findings led to a clinical action. The aims of Project 2 are to implement a production-scale platform for WES from archival (FFPE) material; to identify biologically relevant somatic and germline alterations existing in tumor/normal DNA from individual patients; to produce an evidence-based list of clinically "actionable" genetic alterations; and to develop inferential models that predict the utility of tumor genomic data within the larger clinical context. The goals of Project 3 are to describe the impact of information derived through WES on cancer patients; to test the hypothesis that patients will want to receive information about all potentially informative somatic and germline variants; to study patients' understanding of disclosed genomic information; and to describe the experiences of oncology providers as they implement WES into cancer care delivery.

  Study phs001075

• MSK SPECTRUM - SPatiotemporal Evolution of Cancer Traced Using Multimodalities

  MSK SPECTRUM is a multi-modal, interdisciplinary prospective study of spatiotemporal determinants of high-grade serous ovarian cancer (HGSOC) evolution, treatment and response. Accounting for ~80% of ovarian cancers, HGSOC is the most lethal gynecological malignancy and is a cancer of major unmet clinical need. Challenges in disease management relate to several unresolved questions about disease biology and diagnostic modalities. Prospective longitudinal collection of tissues and blood from laparoscopic biopsies and debulking surgeries enable multi-modal molecular measurements. The program brings together formidable expertise at Memorial Sloan Kettering Cancer Center (MSKCC) across the disciplines of high-resolution genomics and computer science, radiology and radiomics, surgery, tissue banking and sample preparation, medical oncology, immuno-oncology and high-resolution tissue profiling to generate a comprehensive and integrative dataset that will allow us to address the following major aims: i) characterize malignant and immune diversity at diagnosis, ii) survey the co-evolution of malignant cells and the immune response, and iii) stratify patients on standard-of-care and investigational compounds based on their genomic and transcriptomic signatures and changes to relevant genes (TP53, CCNE1, BRCA1/2, CDK12). The goal is to create a framework to utilize integrated multi-modal data as a route to advanced diagnostics and to ultimately establish a proof-of-concept for integrated diagnostics.

  Study phs002857

• Genomics to select patients with metastatic breast cancer for targeted therapy (microarray_cytoscan)

  Cancer progression is driven in part by genomic alterations located in oncogenes or tumor suppressor genes. The genomic characterization of cancers has shown a large interpatient heterogeneity regarding the driver alterations, leading to the concept that generating a genomic profiling by multigene sequencing in patients with cancer could allow selecting effective targeted therapies. While this concept has been broadly implemented in daily practice, there is no evidence that such approach improves patient outcome, and how to optimally select the therapy to administer. A genomic profiling using next generation sequencing and copy number analyses was performed 1462 patients with Her2-non overexpressing metastatic breast cancer included in SAFIR02 Breast trial. 238 of these patients were randomized in two trials between a targeted therapy matched to genomic alteration and a maintenance chemotherapy. The trial shows that targeted therapies matched to genomics improves progression free survival (PFS) when genomic alterations are classified level I/II according to ESMO Scale for Clinical Actionability of Molecular Targets (ESCAT) (adjusted HR: 0.41, 90% CI: 0.27-0.61, p<0.001), but not when alterations are classified beyond level II (unadjusted HR: 1.15, 95% CI: 0.76-1.75). This trial provides evidence that the treatment decision led by genomics should be driven by a framework of target actionability in patients with mBC.

  Study EGAS00001005584

• Genomics to select patients with metastatic breast cancer for targeted therapy (microarray_agilent)

  Cancer progression is driven in part by genomic alterations located in oncogenes or tumor suppressor genes. The genomic characterization of cancers has shown a large interpatient heterogeneity regarding the driver alterations, leading to the concept that generating a genomic profiling by multigene sequencing in patients with cancer could allow selecting effective targeted therapies. While this concept has been broadly implemented in daily practice, there is no evidence that such approach improves patient outcome, and how to optimally select the therapy to administer. A genomic profiling using next generation sequencing and copy number analyses was performed 1462 patients with Her2-non overexpressing metastatic breast cancer included in SAFIR02 Breast trial. 238 of these patients were randomized in two trials between a targeted therapy matched to genomic alteration and a maintenance chemotherapy. The trial shows that targeted therapies matched to genomics improves progression free survival (PFS) when genomic alterations are classified level I/II according to ESMO Scale for Clinical Actionability of Molecular Targets (ESCAT) (adjusted HR: 0.41, 90% CI: 0.27-0.61, p<0.001), but not when alterations are classified beyond level II (unadjusted HR: 1.15, 95% CI: 0.76-1.75). This trial provides evidence that the treatment decision led by genomics should be driven by a framework of target actionability in patients with mBC.

  Study EGAS00001005587

• Genomics to select patients with metastatic breast cancer for targeted therapy (microarray_oncoscan)

  Cancer progression is driven in part by genomic alterations located in oncogenes or tumor suppressor genes. The genomic characterization of cancers has shown a large interpatient heterogeneity regarding the driver alterations, leading to the concept that generating a genomic profiling by multigene sequencing in patients with cancer could allow selecting effective targeted therapies. While this concept has been broadly implemented in daily practice, there is no evidence that such approach improves patient outcome, and how to optimally select the therapy to administer. A genomic profiling using next generation sequencing and copy number analyses was performed 1462 patients with Her2-non overexpressing metastatic breast cancer included in SAFIR02 Breast trial. 238 of these patients were randomized in two trials between a targeted therapy matched to genomic alteration and a maintenance chemotherapy. The trial shows that targeted therapies matched to genomics improves progression free survival (PFS) when genomic alterations are classified level I/II according to ESMO Scale for Clinical Actionability of Molecular Targets (ESCAT) (adjusted HR: 0.41, 90% CI: 0.27-0.61, p<0.001), but not when alterations are classified beyond level II (unadjusted HR: 1.15, 95% CI: 0.76-1.75). This trial provides evidence that the treatment decision led by genomics should be driven by a framework of target actionability in patients with mBC.

  Study EGAS00001005586

• Real-time analysis of the cancer genome and fragmentome from plasma and urine short and long cell-free DNA using Nanopore sequencing

  Cell-free DNA (cfDNA) can be isolated from blood and/or urine of cancer patients and analyzed with sequencing. Unfortunately, most conventional short-read sequencing methods are technically challenging, labor intensive and time consuming, requiring several days but more typically weeks to obtain interpretable data which are limited by a bias for short cfDNA fragments. Here, we demonstrate that with Oxford Nanopore Technologies sequencing  we can achieve economical and ultra-fast delivery of clinical data from liquid biopsies.   Our ‘ITSFASTR’ approach is able to deliver copy number aberrations, and cfDNA fragmentation profiles in less than 24 hours from sample collection. The tumor-derived cfDNA fraction calculated from lung cancer patient plasma and urine from bladder cancer patients was highly correlated (R=0.98) to the tumor fraction calculated from conventional short-read sequencing of the same samples. cfDNA size profile and fragmentation patterns in plasma and urine exhibited the typical cfDNA features yet with a significantly higher proportion of informative fragments that exceed 300bp, exhibiting similar tumor fraction than shorter size fragments. Notably, comprehensive fragment-end composition and nucleosome profiling near transcription start sites can be determined from the same data.  We propose that ITSFASTR is the first point-of-care solution for obtaining genomic and fragmentomic results from liquid biopsies.

  Study EGAS00001006591

• A Genome-Wide Association Study in Participants Experiencing Breast Cancer Events in High-Risk Postmenopausal Women Receiving Selective Estrogen Receptor Modulators on NSABP Trials P-1 and P-2. A Collaboration Between the NIH Pharmacogenetics Research Network and the RIKEN Yokohama Institute Center for Genomic Medicine

  The primary aim of this study is to identify genes related to the occurrence of breast events, defined as occurrence of invasive breast cancer or ductal carcinoma in situ (DCIS), in women at high risk of developing breast cancer who have received a Selective Estrogen Receptor Modulator (SERM - tamoxifen or raloxifene) on the National Surgical Adjuvant Breast and Bowel Project (NSABP) P-1 or P-2 trials. Cases and controls were selected from the tamoxifen arm in the P-1 and from the tamixifen and raloxifene arms in the P-2 trial. For the P-1 trial, cases and controls were required to be 50 years of age or older at time of entry. Cases were females who experienced an invasive breast cancer or DCIS on P-1 or P-2. Controls were females who did not experience an invasive breast cancer or DCIS. A nested matched case-control design was used, with matching on the following factors: 1) trial and treatment arm (P-1 tamoxifen, P-2 tamoxifen, P-2 raloxifene); 2) age at trial entry (when controls could not be exactly matched on age, we incremented the age of matching by +/- 1 year, in sequence until a match was obtained without exceeding +/- 5 years); 5-year predicted breast cancer risk based on the Gail model ( <2.00%, 2.01-3.00, 3.01-5.00, >5.01), 3) history of lobular carcinoma in situ (yes vs. no); 4) history of atypical hyperplasia in breast (yes vs. no); 5) time on study (controls must be on study at least as long as the time to diagnosis of the breast event for the case). Because 94.2% of the participants on P-1 and P-2 treated with tamoxifen or raloxifene were Caucasian, this study was restricted to only Caucasians. Two cases and two controls were randomly chosen as duplicates for quality control of genotype concordance. The DNA samples were plated into 96-well plates, with cases and controls randomly distributed across the plates. A Caucasian parent-child CEPH trio from the HapMap project was included to check for Mendelian transmission of alleles. Genotypes were determined by the RIKEN Center for Genomic Medicine with the Illumina Human610-Quad.

  Study phs000305