12004 results for "cancer rna-seq"

in 30.69 milliseconds.

• Biological and Therapeutic Implications of a Unique Subtype of NPM1 Mutated AML

  Study EGAS00001004872

• Minor intron splicing efficiency increases with the development of lethal prostate cancer

  Study EGAS00001005546

• Serum Proteome Profiling Identifies Early Markers of Therapeutic Response to Neoadjuvant Chemotherapy of Breast Cancer

  Study EGAS00001006228

• Genomics characterization of BRAF-V600E colorectal cancer patients treated with anti-BRAF/EGFR

  Study EGAS00001006247

• PCF SELECT data on liquid biopsy samples from 3 clinical studies on prostate cancer patients

  Dac EGAC50000000758

• Induction Failure in Childhood and Young Adult T-cell Acute Lymphoblastic Leukemia

  Study EGAS00001006411

• 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_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

• 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

• 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

• 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

• Lobular Carcinomas In Situ Display Intra-Lesion Genetic Heterogeneity and Clonal Evolution in the Progression to Invasive Disease

  This study comprises prospectively accrued, microdissected fresh frozen samples of multifocal lobular carcinoma in situ (LCIS), ductal carcinoma in situ (DCIS), invasive lobular carcinoma and invasive ductal carcinoma from patients undergoing prophylactic or therapeutic mastectomies after a diagnosis on LCIS diagnosed and managed at Memorial Sloan Kettering Cancer Center (MSKCC). Microdissected samples were subjected to paired-end whole exome sequencing on an Illumina HiSeq 2000. The data generated were used to define the landscape of somatic genetic alterations of LCIS, DCIS, invasive lobular carcinoma and invasive ductal carcinoma, to define clonal relatedness of these lesions and to investigate the clonal shifts in the progression from in situ to invasive breast cancer.

  Study phs001006

• A comprehensive proteogenomic pipeline for neoantigen discovery to advance personalized cancer immunotherapy

  The accurate identification and prioritization of antigenic peptides is crucial for the development of personalized cancer immunotherapies. Publicly available pipelines to predict clinical neoantigens do not allow direct integration of mass spectrometry immunopeptidomics data, which can uncover antigenic peptides derived from various canonical and non-canonical sources. To address this, we present an end-to-end clinical proteogenomic pipeline, called NeoDisc, that combines state-of-the-art publicly available and in-house software for immunopeptidomics, genomics and transcriptomics with in-silico tools for the identification, prediction, and prioritization of tumor-specific and immunogenic antigens from multiple sources, including neoantigens, viral antigens and high-confidence tumor-specific antigens.

  Study EGAS50000000228

• Fragmentomics analyses of urinary cell-free DNA permit multi-urologic cancer detection and reduction in tissue biopsies for prostate cancer

  This study demonstrated the close association between urinary cell-free DNA (cfDNA) methylation status and the fragmentation patterns in healthy controls and patients with various diseases. Fragmentomics-based methylation analysis (FRAGMA) enables accurate estimation of methylation levels in urinary cfDNA, which is proved by paired bisulfite sequencing and non-bisulfite sequencing data. FRAGMA showed high accuracy in deducing tissue-of-origin of urinary cfDNA in transplantation patients and pregnant women. Moreover, FRAGMA showed great potential in the detection and classification of multiple cancers from the urinary system, including bladder, kidney, and prostate cancer. This study demonstrated that FRAGMA could be applied to improve current diagnostic strategies based on urine samples.

  Study EGAS50000001431

• TRACERx 100: RRBS data from a subset of the first 100 TRACERx tumours

  TRACERx (TRAcking Cancer Evolution through therapy (Rx)) is a prospective cohort study designed to investigate intratumor heterogeneity (ITH) in relation to clinical outcome, and to determine the clonal nature of driver events and evolutionary processes in early stage non-small cell lung cancer (NSCLC). This study looks at multi-region RRBS data from the TRACERx100 cohort selected for quantity of material available and high tumour purity. RRBS data was collected for 122 tumour regions across 36 patients each with matched normal. A subset of this cohort was used in a sister study looking at tumour neo-antigen promoter methylation status in NSCLC (71 tumour regions across 28 patients for a total of 99 samples).

  Study EGAS00001003484

• Integration of intra-sample contextual error modeling for improved detection of somatic mutations

  Study EGAS00001003806

• IRCCS Istituto Romagnolo per lo Studio dei Tumori "Dino Amadori" Italian Cancer Center Data Access Committee

  Dac EGAC00001003223

• IRCCS Istituto Romagnolo per lo Studio dei Tumori "Dino Amadori" Italian Cancer Center Data Access Committee

  Dac EGAC00001003227

• St. Jude Children’s Research Hospital – Washington University Pediatric Cancer Genome Project Steering Committee

  Dac EGAC00001000045

• Data access policy for PDTX Breast Cancer data from Bruna et al (2016), Cell.

  Dac EGAC00001000540

• DAC for "A Functional Network of Gastric-Cancer-Associated Splicing Events Controlled by Dysregulated Splicing Factors"

  Dac EGAC00001000675

• DAC for study: "Circulating tumour DNA abundance and potential utility in de novo metastatic prostate cancer"

  Dac EGAC00001001099

• The University of Hong Kong Colon Cancer Organoids Genomics Study Data Access Committee

  Dac EGAC00001001405

• The data access committee for Detection and characterization of lung cancer using cell-free DNA fragmentomes

  Dac EGAC00001002184

• Treatment-mediated selection of lethal prostate cancer clones defined by copy number architectures

  Dac EGAC00001002865

• Whole exome sequencing of metastatic breast cancer

  Dataset EGAD00001000836

• Nanostring_nCounter_BreastCancer360

  hormone receptor-positive early breast cancer by Nanostring BC360 panel

  Dataset EGAD00010001994

• Cancer-Unknown-Primary-Array-Methylation-H021

  CUP samples using 850k

  Dataset EGAD00010002036

• Single cell sequencing: Capturing the origin and dynamics of chromosomal copy-number heterogeneity

  Study EGAS00001003812

• STM4 - Mouliere et al, 2018. Enhanced detection of circulating tumor DNA by fragment size analysis

  Study EGAS00001004418

• BRCA2, ATM, and CDK12 defects differentially shape prostate tumor driver genomics and clinical aggression

  Study EGAS00001004800

• Genomic Analysis of Focal Nodular Hyperplasia with Associated Hepatocellular Carcinoma Unveils its Malignant Potential

  Study EGAS00001005313

• Evaluating CRISPR-based Prime Editing for cancer modeling and CFTR repair in organoids

  Study EGAS00001005358

• Genomic profiling of metastatic basal cell carcinoma reveals candidate drivers of disease and therapeutic targets

  Study EGAS00001006148

• Mechanism of action and resistance to Trastuzumab Deruxtecan in patients with metastatic breast cancer

  Study EGAS00001007372

• CUPiD, a cfDNA methylation-based tissue-of-origin classifier for Cancers of Unknown Primary

  Study EGAS00001007445

• The WID-EC test for the detection and risk prediction of endometrial cancer

  Study EGAS00001005033

• The DNA methylome of cervical cells and risk of ovarian cancer

  Study EGAS00001005045

• Characterization of UV DNA damage in B-cell precursor acute lymphoblastic leukemia

  Study EGAS00001008128

• The data access committee for "Validation of cfDNA fragmentome analyses for early detection of liver cancer"

  Dac EGAC00001003543

• An Integrated Approach to Patient Stratification and Therapy Selection in Acute Myeloid Leukemia

  Study EGAS00001004655

• A renal cell carcinoma tumorgraft platform to advance precision medicine

  Study EGAS00001005516

• Subgroup-specific gene expression profiles and mixed epistasis in chronic lymphocytic leukemia (HIPO, H005)

  Study EGAS00001006361

• FFPE_whole_genome_pilot

  To assess feasibility of whole genome sequencing

  Study EGAS00001001967

• Angiosarcoma_whole_exome

  Extension of angiosarcoma whole genome sequencing study

  Study EGAS00001000588

• Angiosarcoma_RNA_sequencing

  Extension of angiosarcoma whole genome sequencing study

  Study EGAS00001000590

• Angiosarcoma_targeted_pulldown_cancer_gene_panel

  Extension of angiosarcoma whole genome sequencing study

  Study EGAS00001000589

• Deep_sequencing_of_melanoma_for_driver_mutations

  Deep sequencing of melanoma for driver mutations

  Study EGAS00001000857