12345 results for "cancer rna-seq"

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• Whole genome sequencing of tumour and matched normal from patients with family history of breast cancer

  Analysis of whole genome sequencing of tumour and matched normal from familial breast cancer patients who had previously undergone clinical germline testing for variation in the BRCA1 and BRCA2 genes. The patients were either carriers of BRCA1 or BRCA2 germline pathogenic variants or non-carriers high-risk individuals (non-BRCA1/2). Somatic mutational signatures were used to study tumour aetiology of these individuals.

  Study EGAS00001003305

• Targeted sequencing of 72 prostate cancer driver in 712 plasma cell free DNA samples

  Dataset contains targeted sequencing data of 712 plasma cell free DNA samples and 428 white blood cell samples collected from 428 men with metastatic prostate cancer. Target capture was performed using a hydridization-based custom Roche SeqCap EZ Choice kit, designed to capture all exons of 72 prostate cancer driver genes. Cell free DNA was extracted from 10 mL blood samples. Libraries were sequenced using Illumina HiSeq 2500 or Illumina MiSeq instruments to a median coverage of 750x. 62% of samples had ctDNA fraction above 2% of total cfDNA. Note that "Dataset type" is erroneously listed as "Amplicon sequencing", because "Captured-based targeted sequencing" or "Hybridization-based targeted sequencing" were not available options in EGA at the time of submission.

  Dataset EGAD00001004208

• Genomic Evolution of Breast Cancer Metastasis and Relapse

  Recurrent breast cancer is almost universally fatal. We characterize 170 patients locally relapsed or distant metastatic cancers using massively parallel sequencing. We identify that the relapse-seeding clone disseminates late from the primary tumor. TP53 and AKT1 appear to be enriched in ER-positive cancers predisposed to relapse. Mutation acquisition continues at relapse as the same mutation signatures continue to operate and new signatures, such as that caused by radiotherapy appear de novo. In 49% of cases we identify drivers mutations private to the relapse and these are sampled from a wider range of cancer genes, including SWI-SNF complex and JAK-STAT signaling.

  Dataset EGAD00001002698

• 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

• Broad utility of ultrasensitive analysis of ctDNA dynamics across solid tumors treated with immunotherapy

  Prior studies have suggested the biomarker potential of plasma circulating tumor DNA (ctDNA) in cancer patients treated with immune checkpoint inhibitors (ICIs). In order to characterize the potential role of ultrasensitive ctDNA detection in the management of these patients we have performed tumor whole-genome-informed, ultrasensitive ctDNA analysis—tracking approximately 1,800 tumor-specific mutations per patient—in a retrospective cohort (n=136) and a prospective validation cohort (n=66) across 24 cancer types treated with ICIs alone or in combination with bispecific antibodies or immune cell engagers. Analyzing 1,455 longitudinal samples, we found that ctDNA molecular response measured as early as 3 weeks after treatment initiation correlated with improved progression-free and overall survival, while ctDNA clearance at any time strongly correlated with radiological response and prolonged survival. Additionally, ctDNA dynamics distinguished true progression from pseudoprogression and predicted outcomes in patients receiving continued immunotherapy beyond initial progression. This study highlights the broader applicability of ultrasensitive ctDNA as a biomarker across cancer types and immunotherapy modalities.

  Study EGAS50000001333

• 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

• Long-read sequencing of diagnosis and post-therapy medulloblastoma reveals complex rearrangement patterns and epigenetic signatures

  Cancer genomes harbor a broad spectrum of structural variants (SV) driving tumorigenesis, a relevant subset of which are likely to escape discovery in short reads. We employed Oxford Nanopore Technologies (ONT) sequencing in a paired diagnostic and post-therapy medulloblastoma to unravel the haplotype-resolved somatic genetic and epigenetic landscape. We assemble complex rearrangements and such associated with telomeric sequences, including a 1.55 Megabasepair chromothripsis event. We uncover a complex SV pattern termed "templated insertion thread", characterized by short (mostly less than 1kb) insertions showing prevalent self-concatenation into highly amplified structures of up to 50kbp in size. Templated insertion threads occur in 3% of cancers, with a prevalence ranging to 74% in liposarcoma, and frequent colocalization with chromothripsis. We also perform long-read based methylome profiling and discover allele-specific methylation (ASM) effects, complex rearrangements exhibiting differential methylation, and differential promoter methylation in seven cancer-driver genes. Our study shows the potential of long-read sequencing in cancer.

  Study EGAS00001006576

• Analysis of DNA methylation in normal B cells and chronic lymphocytic leukemia

  Charting differences between tumors and normal tissue is a mainstay of cancer research. However, clonal tumor expansion from complex normal tissue architectures potentially obscures cancer-specific events, including divergent epigenetic patterns. Using whole-genome bisulfite sequencing of normal B cell subsets, we observed broad epigenetic programming of selective transcription factor binding sites coincident with the degree of B cell maturation. By comparing normal B cells to malignant B cells from 268 patients with chronic lymphocytic leukemia (CLL), we showed that tumors derive largely from a continuum of maturation states reflected in normal developmental stages. Epigenetic maturation in CLL was associated with an indolent gene expression pattern and increasingly favorable clinical outcomes.As second study using these samples focued on evolution and resulting intra-tumor heterogeneity in CLL. We used 450k bead-chip arrays to study DNA methylomes in 68 chronic lymphocytic leukemia (CLL) cases, including 28 serial cases. The result establishs linked evolution of epigenetic and genetic alterations in progressive disease, revealing an important aspect of the biology of epigenetics in cancer.

  Study EGAS00001000534

• MED12L Gene Alterations Define Aggressive BRCA2-Mutant Prostate Cancers

  Germline mutation of BRCA2 increases the lifetime risk of developing prostate cancer (PCa) by over 700%. BRCA2-mutant PCa have poorer prognosis than sporadic PCa, with rapid development of metastatic, castrate-resistant prostate cancer (mCRPC) and 5-year cancer-specific survival rates of ~50-60%1-4. Despite this, unique genomic driver events that explain the aggressiveness of localized BRCA2-mutant PCa are lacking. We used whole-genome sequencing to fully characterize 14 BRCA2-mutant PCa and demonstrate that BRCA2-mutant PCa is associated with increased genetic instability and a mutually exclusive mutational burden when compared to sporadic PCa. Importantly, BRCA2-mutated cancers are defined by unique copy number gains and hypomethylation events, including alterations in the MED12L/MED12 axis, which are found solely in mCRPC and are enriched in PCa tumours harbouring aggressive intraductal carcinoma (IDC-P) pathologic sub-types. Our findings begin to explain the clinical entity of BRCA2-mutated PCa as these tumours have a unique and aggressive genotype de novo, associated with IDC-P and mCRPC, even in the hormone-naive setting.

  Study EGAS00001001615

• METABRIC: Data from Pereira et al (2016), The somatic mutation profiles of 2433 breast cancers refine their genomic and transcriptomic landscapes. Nat Comms 7.

  The genomic landscape of breast cancer is complex, and inter- and intra-tumour heterogeneity are important challenges in treating the disease. In this study, we sequence 173 genes in 2433 primary breast tumours that have copy number aberration (CNA), gene expression, and long-term clinical follow-up data. We identify 40 mutation-driver (Mut-driver) genes, and determine associations between mutations, driver CNA profiles, clinical-pathological parameters, and survival. We assess the clonal states of Mut-driver mutations, and estimate levels of intratumour heterogeneity using mutant allele fractions. Associations between PIK3CA mutations and reduced survival are identified in three subgroups of ER-positive cancer (defined by amplification of 17q23, 11q13-14 or 8q24). High levels of intratumour heterogeneity are in general associated with worse outcome, but highly aggressive tumours with 11q13-14 amplification have low levels of intratumour heterogeneity. These results emphasise the importance of genome-based stratification of breast cancer, and have important implications for designing therapeutic strategies.

  Study EGAS00001001753