3290 results for "ovarian cancer"

in 6.58 milliseconds.

• Metastatic_Breast_Cancer_Validation

  Validation of point mutations and small insertions and deletions in primary and associated metastatic breast cancer samples with matched normal tissues.

  Study EGAS00001001968

• Metastatic_breast_cancer_targeted_gene_screen

  The samples will be sequenced for a targeted panel of cancer relevant genes (n ~ 370) and analysed for somatic mutations.

  Study EGAS00001000704

• Epi_Tax_targeted_sequencing

  Sequencing of 350 cancer genes in BC samples from patients treated with either Epirubicin or Paclitaxel monotherapy in the neoadjuvant setting.

  Study EGAS00001000587

• The patterns and dynamics of genomic instability in metastatic pancreatic cancer

  Pancreatic cancer is an aggressive malignancy with a five-year mortality of 97–98%, usually due to widespread metastatic disease. Previous studies indicate that this disease has a complex genomic landscape, with frequent copy number changes and point mutations, but genomic rearrangements have not been characterized in detail. Despite the clinical importance of metastasis, there remain fundamental questions about the clonal structures of metastatic tumours, including phylogenetic relationships among metastases, the scale of ongoing parallel evolution in metastatic and primary sites, and how the tumour disseminates. Here we harness advances in DNA sequencing to annotate genomic rearrangements in 13 patients with pancreatic cancer and explore clonal relationships among metastases. We find that pancreatic cancer acquires rearrangements indicative of telomere dysfunction and abnormal cell-cycle control, namely dysregulated G1-to-S-phase transition with intact G2–M checkpoint. These initiate amplification of cancer genes and occur predominantly in early cancer development rather than the later stages of the disease. Genomic instability frequently persists after cancer dissemination, resulting in ongoing, parallel and even convergent evolution among different metastases. We find evidence that there is genetic heterogeneity among metastasis-initiating cells, that seeding metastasis may require driver mutations beyond those required for primary tumours, and that phylogenetic trees across metastases show organ-specific branches. These data attest to the richness of genetic variation in cancer, brought about by the tandem forces of genomic instability and evolutionary selection.

  Study EGAS00000000064

• Machine learning to detect the SINEs of cancer

  We previously described an approach called RealSeqS to evaluate aneuploidy in plasma cell-free DNA (cfDNA) through the amplification of ~350,000 repeated elements with a single primer. We hypothesized that an unbiased evaluation of the large amount of sequencing data obtained with RealSeqS might reveal other differences between plasma samples from patients with and without cancer. This hypothesis was tested through the development of a novel machine-learning approach called Alu Profile Learning Using Sequencing (A-PLUS) and its application to samples from 5108 individuals, 2037 with cancer and the remainder without cancer. Samples from cancer patients and controls were pre-specified into four cohorts used for: 1) model training, 2) analyte integration and threshold determination, 3) validation, and 4) reproducibility. A-PLUS alone provided a sensitivity of 40.5% across 11 different cancer types in the Validation Cohort, at a specificity of 98.5%. Combining A-PLUS with aneuploidy and 8 common protein biomarkers detected 51% of 1167 cancers at 98.9% specificity. We found that part of the power of A-PLUS could be ascribed to a single feature – the global reduction of AluS sub-family elements in the circulating DNA of cancer patients. We confirmed this reduction through the analysis of another independent dataset obtained with a very different approach (whole genome sequencing). The evaluation of Alu elements therefore has the potential to enhance the performance of several methods designed for the earlier detection of cancer.

  Study EGAS00001007169

• Genomics of Prostate Cancer

  This dataset includes genomic data from patients with prostate cancer. Specimens include archival active surveillance biopsies, radical prostatectomy specimens selected based on evidence of PD-L1 expression and/or T lymphocyte infiltrates, and rapid autopsy material from patients deceased of prostate cancer. These data include low pass whole genome sequencing and targeted sequencing with matched normal.

  Study phs002398

• Identifying and Reducing Disparities in Patient-Reported Outcomes Among African American Prostate Cancer Survivors

  This research study aimed to identify disparities in prostate cancer symptom burden and their contributors among African American, Hispanic, and non-Hispanic White prostate cancer survivors. We collected patient-reported outcomes data, focusing on various aspects of the survivors' health and well-being, clinical data, demographics data, and germline genomic data.

  Study phs003745

• Pilot study towards the development of a Companion/Complimentary Diagnosis platform using liquid biopsy with cfDNA for immune checkpoint inhibitor therapy in advanced urothelial cancer

  Preliminary analysis was conducted to develop a cfDNA-based platform capable of predicting gene mutation profiles, TMB, gene expression profiles (molecular subtype diagnosis), and immunohistochemical findings (PD-L1 expression) using the primary lesion tissue of bladder cancer and upper urinary tract epithelial cancer, verifying the feasibility of such development.

  Study JGAS000714

• Target sequencing of 11 hereditary breast cancer genes in Japanese

  We performed a case control association study for variants in coding regions of 11 hereditary breast cancer genes in 7,051 female unselected breast cancer patients, 11,241 female controls, 53 male patients, and 12,490 male controls of Japanese ancestry. The 11 genes were ATM, BRCA1, BRCA2, CDH1, CHEK2, NBN, NF1, PALB2, PTEN, STK11, and TP53.

  Study JGAS000140

• Cell_Line_Sub_Clone_Rearrangement_Screen

  Genomic libraries (500 bps) will be generated from total genomic DNA cancer samples and subjected to paired end sequencing on the llumina GA. Paired reads will be mapped to build 37 of the human reference genome to facilitate the generation of genome wide copy number information, and the identification of novel rearranged cancer genes and gene fusions.

  Study EGAS00001000178