11802 results for "cancer rna-seq"

in 15.01 milliseconds.

• Identification of genomic aberrations in low-grade serous ovarian cancer

  Low-grade serous ovarian cancer (LGSOC) is a rare disease that occurs more frequently in younger women compared with high-grade disease. The current treatment is suboptimal, and better understanding of molecular pathogenesis of this disease is needed. In this study, we compared the whole genome sequences of LGSOCs from short-term and long-term survivors (defined as <40 and >60 months, respectively). Our goal was to identify novel genomic aberrations in LGSOC, especially in short-term survivors.

  Study EGAS00001006679

• PELICAN33 Phenomic Dataset

  To better understand variation in metastatic prostate cancer behaviour, we assembled and analyzed longitudinal clinical and autopsy records in 33 men. The dataset is contained in a self-explanatory Excel Workbook, with each patient identified as A1, A2, etc. as listed in the "Combined longitudinal clinical and autopsy phenomic assessment in lethal metastatic prostate cancer: recommendations for advancing precision medicine" publication in European Urology Open Science. Please see Jasu J, Tolonen T, Antonarakis ES, Beltran H, Halabi S, Eisenberger MA, Carducci MA, Loriot Y, Van der Eecken K, Lolkema M, Ryan CJ, Taavitsainen S, Gillessen S, Högnäs G, Talvitie T, Taylor RJ, Koskenalho A, Ost P, Murtola TJ, Rinta-Kiikka I, Tammela T, Auvinen A, Kujala P, Smith TJ, Kellokumpu-Lehtinen PL, Isaacs WB, Nykter M, Kesseli J, Bova GS. Combined Longitudinal Clinical and Autopsy Phenomic Assessment in Lethal Metastatic Prostate Cancer: Recommendations for Advancing Precision Medicine. Eur Urol Open Sci. 2021 Jul 2;30:47-62. doi: 10.1016/j.euros.2021.05.011. PMID: 34337548; PMCID: PMC8317817. for more details.

  Dataset EGAD00001007800

• Tumour evolvability metrics predict recurrence in advanced localised prostate cancer (tumour data)

  There is a need for quantitative measurements of evolutionary metrics in controlled clinical trials with long term follow-up information. This is particularly true in advanced localised prostate cancer, which can recur more than a decade after diagnosis. Here we mapped genomic intra-tumour heterogeneity in 642 tumour samples from 114 patients who took part in the IMRT and DELINEATE clinical trials, for which full clinical information and 12y median follow-up was available. We concomitantly assessed phenotypic (morphological) heterogeneity using Deep Learning in 1,923 histological sections from 250 IMRT patients (fully overlapping with the genetic set). This study shows that combining genomics with AI-aided histopathology in clinical trials leads to novel clinical biomarkers. This EGA repository contains data produced from tumour samples using low coverage whole genome sequencing and a prostate cancer specific gene panel data following compression of unique molecular identifiers.

  Dataset EGAD00001010274

• Tumour evolvability metrics predict recurrence in advanced localised prostate cancer (normal data)

  There is a need for quantitative measurements of evolutionary metrics in controlled clinical trials with long term follow-up information. This is particularly true in advanced localised prostate cancer, which can recur more than a decade after diagnosis. Here we mapped genomic intra-tumour heterogeneity in 642 tumour samples from 114 patients who took part in the IMRT and DELINEATE clinical trials, for which full clinical information and 12y median follow-up was available. We concomitantly assessed phenotypic (morphological) heterogeneity using Deep Learning in 1,923 histological sections from 250 IMRT patients (fully overlapping with the genetic set). This study shows that combining genomics with AI-aided histopathology in clinical trials leads to novel clinical biomarkers. This EGA repository contains data produced from tumour samples using low coverage whole genome sequencing and a prostate cancer specific gene panel data following compression of unique molecular identifiers.

  Dataset EGAD00001010295

• Whole-genome sequencing in 14 cases and whole-exome sequencing in 90 cases of Chinese ESCC

  Esophageal cancer is one of the most aggressive cancers and the sixth leading cause of cancer death worldwide1. Approximately 70% of the global esophageal cancers occur in China and over 90% histopathological forms of this disease are esophageal squamous cell carcinoma (ESCC)2-3. Currently, there are limited clinical approaches for early diagnosis and treatment for ESCC, resulting in a 10% 5-year survival rate for the patients. Meanwhile, the full repertoire of genomic events leading to the pathogenesis of ESCC remains unclear. Here we show a comprehensive genomic analysis in 158 ESCC cases, as part of the International Cancer Genome Consortium (ICGC) Research Projects (http://icgc.org/icgc/cgp/72/371/1001734). We conducted whole-genome sequencing in 14 ESCC cases and whole-exome sequencing in 90 cases.

  Dataset EGAD00001001691

• Subclonal diversification of primary breast cancer

  Cancers are ecosystems of genetically related clones, competing across space and time for limited resources. To understand the clonal structure of primary breast cancer, we applied genome and targeted sequencing to 295 samples from 49 patients’ tumors. The extent of subclonal diversification varied considerably among patients and encompassed many spatial patterns, including local growth, intraductal dissemination and clonal intermixture. Landmarks of disease progression, such as acquiring invasive or metastatic potential, arose within detectable subclones of antecedent lesions, suggesting that subclonal mutations could be relevant if actionable. No defined temporal order of mutation was evident, with the commonest genes, including PIK3CA, TP53, BRCA2, PTEN and MYC, mutated early in some, late in others, often exhibiting parallel evolution across subclones. Signatures of homologous recombination deficiency correlated with response to neoadjuvant chemotherapy. Thus, the interplay of mutation, growth and competition drives clonal structures of breast cancer that are complex, variable across patients and clinically relevant.

  Dataset EGAD00001000965

• The evolving mutational landscape of normal human esophagus

  The extent to which cells in normal tissues accumulate mutations during life is poorly understood. Some mutant cells expand into clones that can be detected by genome sequencing. We mapped mutant clones in normal esophageal epithelium from nine donors aged 20-75. Somatic mutations accumulate with age and are mainly caused by intrinsic mutational processes. We found strong Darwinian selection of clones carrying mutations in 14 cancer genes, with tens to hundreds of such clones per square centimeter. By middle age, clones with cancer-associated mutations cover most of the epithelium, with NOTCH1 and TP53 mutations affecting 40% and 10% of all cells, respectively. Remarkably, the prevalence of NOTCH1 mutations in normal esophagus is several times higher than in esophageal cancers. The esophagus emerges as an evolving patchwork of mutant clones that colonize the majority of the epithelium, with implications for our understanding of cancer and ageing.

  Dataset EGAD00001004158

• The evolving mutational landscape of normal human esophagus

  The extent to which cells in normal tissues accumulate mutations during life is poorly understood. Some mutant cells expand into clones that can be detected by genome sequencing. We mapped mutant clones in normal esophageal epithelium from nine donors aged 20-75. Somatic mutations accumulate with age and are mainly caused by intrinsic mutational processes. We found strong Darwinian selection of clones carrying mutations in 14 cancer genes, with tens to hundreds of such clones per square centimeter. By middle age, clones with cancer-associated mutations cover most of the epithelium, with NOTCH1 and TP53 mutations affecting 40% and 10% of all cells, respectively. Remarkably, the prevalence of NOTCH1 mutations in normal esophagus is several times higher than in esophageal cancers. The esophagus emerges as an evolving patchwork of mutant clones that colonize the majority of the epithelium, with implications for our understanding of cancer and ageing.

  Dataset EGAD00001004159

• TRACERx Non-small cell lung cancer

  Dac EGAC00001000632

• Barts Cancer Institute - Follicular Lymphoma Whole Genome Sequencing Project Data Access Committee

  Dac EGAC00001000086