14970 results for "cancer studies using rna-seq"

in 20.70 milliseconds.

• Rapid brain tumor classification from sparse epigenomic data

  Although the intraoperative, molecular differential diagnosis of the approximately one hundred different brain tumor entities described to date has been a goal of neuropathology in the last decade, this has not yet been achieved in a clinically relevant time frame of less than one hour after biopsy collection. Recent advances in third-generation sequencing technologies have brought this once-elusive goal within reach. However, established machine learning techniques rely on concepts and methods, impractical for live diagnostic workflows in clinical applications. Here, we present MethyLYZR, a Naïve Bayesian framework enabling fully tractable live classification of cancer epigenomes. MethyLYZR can be run in parallel with an ongoing Nanopore experiment with negligible computational cost and provides clinically relevant and accurate cancer classification results within 15 minutes of sequencing. Therefore, only the time required for DNA extraction and the Nanopore sequencer's maximum parallel throughput remain limiting factors for even faster time-to-results. We demonstrate the potential utility of the MethyLYZR framework not only for the neurosurgical intraoperative use case but also for other oncologic indications and cell-free DNA from liquid biopsies.

  Study EGAS50000000559

• Final results and ctDNA analyses from the randomized phase 3 IMpassion031 trial evaluating peri-operative atezolizumab for early-stage triple-negative breast cancer

  In IMpassion031, adding atezolizumab to neoadjuvant chemotherapy significantly improved pathologic complete response (pCR) rate (primary endpoint) for stage II/III triple-negative breast cancer (TNBC). Patients with stage II/III TNBC were randomized 1:1 to neoadjuvant chemotherapy plus peri-operative atezolizumab or pre-operative placebo. Descriptive secondary endpoints included event-free, disease-free, and overall survival. Long-term outcomes favored the atezolizumab group (event-free survival HR 0.76, 95% CI: 0.47–1.21). Among patients without pCR, 14/70 (20%) atezolizumab-treated and 33/99 (33%) placebo-treated patients received additional adjuvant therapy, frequently capecitabine. In exploratory analyses, pCR was prognostic for long-term outcome. Patients with baseline ctDNA-negative status (6%) had excellent long-term outcomes. Most patients (87%) had cleared ctDNA at surgery. ctDNA-positive status at surgery identified a subset of non-pCR patients with poorest prognosis. Long-term safety was consistent with primary results. Adding atezolizumab to chemotherapy for stage II/III TNBC is associated with more favorable long-term outcomes. ctDNA dynamics provide prognostic value beyond pCR. ClinicalTrials.gov identifier: NCT03197935

  Study EGAS50000000974

• Error-corrected flow-based sequencing at whole genome scale and its application to circulating cell-free DNA profiling

  Differentiating sequencing errors from true variants is a central genomics challenge calling for error suppression strategies that balance costs when sparse material or ultra-rare variants require high-accuracy methods. For example, circulating cell-free DNA (ccfDNA) sequencing for cancer monitoring is limited by sparsity of circulating tumor DNA (ctDNA), abundance of genomic material in samples, library preparation error rates and sequencing errors. Whole-genome sequencing (WGS) can overcome the low abundance of ccfDNA by integrating signal across the mutation landscape, but higher cost limits adoption compared with targeted panels, where ccfDNA abundance limits maximal coverage depths. Here we applied deep (~120x) lower-cost WGS (Ultima Genomics) with analytic error correction for tumor-informed ctDNA detection within the part-per-million range. We further developed high-coverage duplex error-corrected WGS of ccfDNA, achieving 7.7x10-8 error rates, to assess disease burden in melanoma and urothelial cancer patients without matched tumor sequencing. Together, we show that deeply sequenced error-corrected WGS accurately calls somatic variants, demonstrating the feasibility of WGS for tumor-informed and tumor-agnostic ctDNA detection.

  Study EGAS50000000844

• We performed whole-exome sequencing of 20 samples (10 actinic keratosis and 10 cutaneous squamous cell carcinoma) to investigate a potential relationship between DNA methylation-based subtypes and genetic mutation patterns (Rodriguez-Paredes et al., Nat Commun 2017)

  Cutaneous squamous cell carcinoma (cSCC) is the second most common skin cancer type and arises from keratinocytes. Most cSCC progress from a UV-induced precancerous lesion termed actinic keratosis (AK). Despite various efforts to characterize these lesions molecularly, the etiology of AK and its progression to cSCC remain only partially understood. Here we have used Infinium MethylationEPIC BeadChips to interrogate the DNA methylation status of about 850.000 CpGs in epidermal preparations from healthy skin, AK and cSCC. Importantly, we found that the premalignant AK samples displayed classical features of cancer methylomes and were highly similar to cSCC methylomes. Further analysis identified typical features of stem cell methylomes, such as a reduced DNA methylation age, non-CpG methylation and stem cell-related keratin and enhancer methylation patterns. Interestingly, this signature was detected only in one half of the AK and cSCC samples, while the other half showed keratin and enhancer methylation patterns that were more closely related to the control epidermis. These findings suggest the existence of two distinct subclasses of AK and cSCC that originate from distinct keratinocyte differentiation stages.

  Study EGAS00001002670

• Single cell whole genome sequencing of luminal breast epithelial cells from wildtype and BRCA mutation carriers

  Single cell whole genome sequencing was done using DLP+ (https://doi.org/10.1016/j.cell.2019.10.026) on luminal breast epithelial cells from wildtype and BRCA mutation carriers. Each BAM file is a merged BAM from single cells from a single sample, and the cells can be uniquely identified by their @RG group. Only high quality cells were kept, thus there are large differences in BAM sizes. The same sample/patient can be found across multiple BAM files to accumulate more cells, sometimes the same patient will have multiple FACS sorted cell types also split by BAMs.

  Dataset EGAD50000000883

• Long-read whole-genome sequencing-based concurrent haplotype phasing and aneuploidy profiling of single cells

  This dataset contains long-read whole-genome sequencing (lrWGS) data from 14 samples. Five lrWGS data are from single-cell (sc, sc_2, sc_3), multi-cell (mc, 10 cells), and bulk samples of HG002. The remaining nine lrWGS data are from two preimplantation genetic testing (PGT) families, including four from blood bulk DNA of the parental pairs and five from trophectoderm biopsies of two embryos from one family and three embryos from another family. The data are provided in raw FASTQ format and were generated using the PromethION device from Oxford Nanopore Technologies.

  Dataset EGAD50000000787

• Emirati Phased Diploid T2T Trio-Assembly of a Female Individual

  This dataset contains a telomere-to-telomere (T2T), trio-based genome assembly in FASTA format for a single female Emirati individual (proband) generated using parental information for accurate phasing. Sequencing data comprised PacBio HiFi (>60X per parent, >120X offspring), ONT ultra-long reads (>110X offspring), and Illumina short-read WGS (>100X for all three individuals). The offspring genome was assembled in a trio framework and finished with NTLink (initial scaffolding), RagTag (reference-guided refinement), and Quartett (gap filling). The resulting contiguous assembly serves as a high-quality, population-relevant reference suitable for downstream variant discovery and integration into the pangenome.

  Dataset EGAD50000001754

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

  This dataset contains all available targeted exon sequencing bam files from our study, "BRCA2, ATM, and CDK12 defects differentially shape prostate tumor driver genomics and clinical aggression". Patient identifiers are denoted by the first segment of the sample aliases (e.g. "P1"), and additional information is appended to reflect which sample is referenced. These include serial cfDNA samples ("-1", "-2", "-3", etc.), paired white blood cell or benign tissue control samples ("-Control"), or primary archival tissue samples derived from a diagnostic biopsy, prostatectomy, or transurethral resection of the prostate ("-Tissue"). All samples were sequenced using Illumina technology.

  Dataset EGAD00001006733

• COMPARE study: participants typed during UK Biobank version 2 array development phase

  The COMPARE study enrolled 29,066 British blood between donors between February 2016 and March 2017, the study aim is to find the optimum technology for haemoglobin screening (ISRCTN 90871183). All participants were at the time of recruitment active blood donors. The 4,796 participants in this dataset have consented to join the NIHR BioResource. Genotyping data was produced using the Thermo Fisher Scientific Axiom Genotyping platform. The UK Biobank version 2 array design was used, content on this array has been added to allow for accurate DNA based identification of human blood group antigens.

  Dataset EGAD00001005023

• Donor InSight III study: Participants typed during UK Biobank version 2 array development phase

  The Donor InSight III study, undertaken by Sanquin research, recruited 3,046 Dutch blood donors between 2015 and 2016. The purpose of the study was to gain more insight into characteristics of donors, their motivations and health. All participants were at the time of recruitment active blood donors. Genotyping data was produced using the Thermo Fisher Scientific Axiom Genotyping platform. The UK Biobank version 2 array design was used, content on this array has been added to allow for accurate DNA based identification of human blood group antigens.

  Dataset EGAD00001005026