15169 results for "cancer studies using rna-seq"

in 37.55 milliseconds.

• DAC for integrated genomics of metastatic prostate cancer

  Dac EGAC00001000230

• The NOWAC blood-breast cancer commitee data access agreement

  Dac EGAC00001000684

• Ludwig Data Access Committee for the Study of Oesophageal Cancer

  Dac EGAC00001000978

• Children's Cancer Therapy Development Institute Data Access Commitee

  Dac EGAC00001001160

• Latency and interval therapy affect the evolution in metastatic colorectal cancer.

  Dac EGAC00001001198

• 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

• EGAD00010000554

  SNP 6.0 arrays of small cell lung cancer

  Dataset EGAD00010000554

• EGAD00010000556

  SNP 6.0 arrays of small cell lung cancer

  Dataset EGAD00010000556

• OvCan2

  Digital images of ovarian cancer metastases

  Dataset EGAD00010001099

• 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

• 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

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

  Dac EGAC00001003567

• CPTAC: Microscaled Proteogenomic Methods for Precision Oncology

  Cancer proteogenomics combines genomics, transcriptomics and mass spectrometry-based proteomics to gain insights into cancer biology and treatment outcomes. To promote clinical investigation, we developed a "microscaled" proteogenomics approach for tumor-rich frozen core needle biopsies. Tissue-sparing specimen processing ("Biopsy Trifecta EXTraction", BioTExt) and microscaled proteomics (MiProt) generated deep-scale proteogenomics datasets. As a proofof- concept, biopsies were accrued from ERBB2 positive (ERBB2+) breast cancers before and 48 to 72 hours after the first dose of neoadjuvant trastuzumab-based chemotherapy. Multi-omics comparisons were conducted between samples associated with residual disease versus complete pathological response (pCR). Integrated analyses diagnosed diverse molecular causes of treatmentresistance including: 1) absence of ERBB2 amplification (false-ERBB2&#43); 2) insufficient ERBB2 activity for therapeutic sensitivity despite ERBB2 amplification (pseudo-ERBB2&#43); 3) resistance features in true-ERBB2+ cases including androgen receptor signaling, mucin expression and an inactive immune microenvironment; 4) lack of acute phospho-ERBB2 down-regulation in nonpCR cases. We conclude microscaled cancer proteogenomics could improve diagnostic precision.

  Study phs001907

• Liquid biopsy-based minimal residual disease monitoring for early risk stratification and decision-making in advanced non-small cell lung cancer

  Circulating tumor DNA (ctDNA)-based minimal residual disease (MRD) monitoring shows promise for risk stratification and decision-making in cancer patients. However, factors like background noise from non-tumor DNA, clonal haematopoiesis, and non-shedding tumors may complicate manual interpretation and limit its clinical application. In this proof-of-concept study in advanced non-small cell lung cancer (NSCLC) patients treated with immune checkpoint inhibitors (ICIs), we developed an algorithm that automatically classifies serial cell-free DNA (cfDNA) samples, thereby enabling reliable and reproducible interpretation, and preventing time-consuming manual interpretation in approximately 75% of patients. Importantly, application of the algorithm allowed early risk stratification and decision-making, specifically identifying approximately 35% of patients with short-term clinical benefit and approximately 25% of patients who may potentially benefit from treatment escalation. Simultaneous serum tumor marker (STM) monitoring further improved risk stratification and decision-making in our study, enabling accurate identification of all patients with a clinical benefit of at least one year.

  Study EGAS50000001554

• Sequencing of an organoid biobank for childhood kidney cancers that captures disease and tissue heterogeneity.

  Kidney tumors are among the most common solid tumors in children, comprising several distinct subtypes differing in many aspects, including cell-of-origin, genetics, and pathology. Pre-clinical cell models capturing the disease heterogeneity are currently lacking. Here, we describe the first pediatric cancer organoid biobank. It contains tumor and matching normal organoids from over 50 children with different subtypes of kidney cancer, including Wilms tumors, malignant rhabdoid tumors, renal cell carcinomas, and congenital mesoblastic nephromas. The malignant rhabdoid tumor organoids represent the first organoid model for tumors of non-epithelial origin. The tumor organoids retain key properties of native tumors, useful for revealing patient specific drug vulnerabilities. We further demonstrate that organoid cultures derived from Wilms tumors consist of multiple different cell types, including epithelial, stromal and blastemal-like. Our organoid biobank captures the cellular heterogeneity of pediatric kidney tumors, providing a representative collection of well-characterized models for basic cancer research, drug-screening, and personalized medicine.

  Study EGAS00001003853