4913 results for "*oma"

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• Diversity of U1 small nuclear RNAs and Evaluation of Diagnostic Methods for their Mutations

  U1 small nuclear RNA (snRNA) mutations are recurrent non-coding alterations found in various malignancies, including medulloblastoma, yet their identification has proven challenging due to their repetitive nature. To establish a robust DNA-based, and RNA-based method for detecting U1 snRNA mutations, we performed targeted DNA sequencing using our original gene panel for medulloblastoma and RNA-sequencing. As an RNA-based method, we developed a random forest classifier employing splicing patterns which were massively altered as a result of U1 snRNA mutations. By using both methods, we successfully detected U1 snRNA mutation in five DNA samples and four RNA samples.

  Study EGAS50000000693

• SCANDARE HNSCC

  Prospective biobanking study in SCANDARE HNSCC (Head and Neck Squamous Cell Carcinoma) patients aiming at better understand the link between the molecular alterations of the tumor itself, its microenvironment and immune response.

  Study EGAS50000001158

• SCANDARE ovarian WES data

  SCANDARE (NCT03017573) is a multicentric biobanking study, enrolling adult patients with newly diagnosed head and neck squamous cell carcinoma (HNSCC), triple negative breast cancer (TNBC), ovarian and cervical cancer. Tumor tissue and blood samples are collected at several time points during patient's journey, including at diagnosis, post-neoadjuvant chemotherapy in case of neoadjuvant treatment, at surgery, at recurrence and at disease progression following treatment initiated at recurrence. Since its launch in 2017 at Institut Curie, SCANDARE has enabled the longitudinal collection and preservation of samples for in-depth analyses. Here, we describe molecular alterations in 91 frozen samples (n = 53 at baseline, n = 31 Post-NAC, n= 7 Recurrence, and n = 62 germline DNA) from 64 ovarian cancer patients using WES technology, with FASTQ files deposited in the dataset.

  Dataset EGAD50000001658

• Sequenced IDH wildtype, untreated, human glioblastoma samples (GB-UK cohort)

  BAM files for 42 IDH wildtype, untreated, human glioblastoma samples from the GB-UK cohort, published in Noorani & Haughey et al. Cancer Discovery (2025).

  Dataset EGAD50000001649

• Aberrant EZHIP Expression Drives Tumorigenesis in Osteosarcoma

  Study EGAS00001007531

• Whole genome sequencing data of cfDNA and WBC from 5 patients with mUC

  Whole genome Illunima sequencing of cfDNA of 5 metastatic urothelial carcinoma patients. White blood cell (WBC) samples are used as patient matched germline samples (n=5). All files are in paired-end fastq format.

  Dataset EGAD50000001570

• Targeted sequencing data of cfDNA, archival tissue, and WBC from 226 patients with mUC

  Targeted tissue (n=210), cfDNA (n=402), and WBC (n=245) Illumina sequencing of metastatic urothelial carcinoma patients. All cfDNA is collected in the metastatic setting, while archival tissue is from across the disease course. White blood cell (WBC) samples are used as patient matched germline samples. All files are in paired-end fastq format.

  Dataset EGAD50000001571

• Single-Cell RNA-Sequencing of Bone Marrow and Circulating Tumor Cells from Patients with Multiple Myeloma and its Precursor Conditions

  We performed single-cell RNA and V(D)J-sequencing of tumor cells from bone marrow and peripheral blood specimens and patients with Monoclonal Gammopathy of Undetermined Significance (MGUS), Smoldering Multiple Myeloma (SMM), and Multiple Myeloma (MM), as well as healthy donors. In this study we aimed to shed light on the mechanisms underlying tumor cell circulatory capacity and dissemination.

  Study phs003855

• National Cancer Institute (NCI) Early Onset Malignancies Initiative (EOMI): Molecular profiling of Breast, Colon, Kidney, Liver, Multiple Myeloma, and Prostate among Racially and Ethnically Diverse Populations

  The Early Onset Malignancies Initiative (EOMI) is focused on collecting specimens from racially and ethnically diverse population groups with six different types of cancer (breast, prostate, colon, liver, kidney, and multiple myeloma). This initiative is a partnership between the Center for Research Strategy, the Center for Cancer Genomics and the Division of Cancer (DCP). DCP's NCI Community Oncology Research Program (NCORP) is a critical partner. The acquisition of the cancer and matching normal biospecimens in this initiative are from newly diagnosed early onset cancer patients who identify as Non-Hispanic Black, Hispanic, American Indian or Alaska Native, or Non-Hispanic White. The Minority/Underserved NCORPs sites will collect the samples for this project. By carrying out this initiative in the NCORP's national network of investigators, cancer care providers, and research institutions, the EOMI will harness the community-based partnerships to improve participation among these racial/ethnic groups. The NCORP investigators, as participants in NCI's clinical trials network, will annotate the biologic samples with clinical information that will enhance the ability to answer questions about molecular determinants of early disease, treatment response, and/or prognosis. The EOMI will be a step forward in addressing racial/ethnic disparities and in understanding cancer in underserved populations.

  Study phs001952

• scRNA seq and scTCR seq data from 5 melanoma patients

  The Chromium Controller and Chromium X platfor of 10X Genomics were used for single cell partitioning and barcoding. Each cell's transcriptome was barcoded during reverse transcription, pooled cDNA was amplified and Single Cell 5' Gene Expression (GEX), V(D)J and Feature Barcode (FB) Libraries were prepared according to the manufacturer's protocols (CG000330 and CG000331, 10X Genomics). All libraries were quantified and normalized on library QC data generated on the Bioanalyzer system according to manufacturer's protocols (G2938-90321 and G2938-90024, Agilent Technologies). Based on the expected target cell counts, a balanced library sub-pool of samples was compsed for SC5'GEX, V(D)J and FB libraries. Library sub-pools were quantified by qPCR, accodring to the KAPA Library Quantification Kit Illumina(R) Platforms protocol (KR0405, KAPA Biosystems). Based on qPCR results a final sequencing pool was composed. Paired end sequencing was performed on a NovaSeq 6000 Instrument (Illumina) using NovaSeq 6000 Reagent Kits v1.5 100 cycles (cat. no. 20028401, 20028319, 20028316 Illumina), using 28 cycles for Read 1, 10 cycles for Read i7, 10 cycles for Read i5 and 90 cycles for Read 2.

  Dataset EGAD50000001155