14977 results for "cancer studies using rna-seq"

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• Metastatic Prostate Follow Up

  Validation/deeper sequencing for metastatic prostate cancer samples

  Dataset EGAD00001000988

• Chordoma Extension (known cancer genes)

  Extension analysis to pursue candidate genes of interest in chordoma

  Dataset EGAD00001001239

• CPC-GENE Prostate Cancer Heterogeneity Study

  Raw sequence data, fastq format

  Dataset EGAD00001002885

• Evolution_of_the_cancer_epigenome_in_myeloproliferative_neoplasms_2

  Whole genome sequencing and bisulphite sequencing of haematopoietic colonies

  Study EGAS00001002372

• Kings_Hepatoblastoma_Behjati_RNA_Managed_Access

  A study of the development of liver based tumours.

  Study EGAS00001006876

• Global Anaplastic Thyroid Cancer Initiative

  Raw exome sequence data(fastq) for the GATCI project

  Dataset EGAD00001003235

• How to encrypt files with Crypt4gh

  File preparation Due to the processes used at the EGA for file archival the use of non-alphanumeric characters in a filename will cause issues in archival. By convention whitespaces in filenames are to be avoided and should be replaced with the underscore character (_). Before encrypting your files please make sure that any files that will be uploaded to EGA do not use special characters such as # ? ( ) [ ] / \ = + < > : ; " ' , * ^ | & Crypt4gh EGACryptor Files encrypted with Crypt4gh must be uploaded via INBOX Before uploading If you are not a registered EGA user, you will first need an EGA user account. Please note that it may take a few days for your account to be activated, as it needs to be vouched for by the EGA Helpdesk. Once your account is validated you will be able to request a submitter role. Meanwhile, you can create and add your public key to your EGA account profile. This option is not available for old submission accounts (e.g. ega-box-NNN). As soon as you have been granted a submitter role, you will be able to connect with your username and password to the EGA inbox using the SFTP protocol. If you have also registered a public key in your profile, you can also connect using this key. Encrypting your files Please note that you can also encrypt your files by uploading them directly to the "to-encrypt" folder in your upload area If your connection is unstable, please encrypt them using Crypt4gh The EGA encryption of this inbox is based on Crypt4GH. You can install a python implementation of it, with pip install crypt4gh or directly from the Github repository pip install git+https://github.com/EGA-archive/crypt4gh.git Save now the following Crypt4GH public key, into a file, say ingestion.pubkey. __EGA_INGESTION_PUBKEY__ Encrypt a given file with the following command: crypt4gh encrypt --recipient_pk ingestion.pubkey < file_to_encrypt > encrypted_file.c4gh The command reads the file from stdin (with < ) and output the encrypted version to stdout (with > ). Replace file_to_encrypt and encrypted_file.c4gh with the appropriate filenames but make sure to not use the same filename for both reading and writing because your SHELL would then truncate both files before you even read or write.

  Documentation submission/data/file-preparation/crypt4gh

• WGS of 32 paired SRCC samples

  Signet-ring cell carcinoma (SRCC) has specific epidemiology and oncogenesis in gastric cancer, however with no systematical investigation for prognostic genomic features. We systematically investigated the clinical characteristics of 1,868 Chinese gastric cancer patients, and found that signet-ring cell content was significantly related to multiple clinical characteristics and treatment outcomes. Next, we performed whole genome sequencing for 32 SRCC patients with &gt; 80% signet-ring cells in tumor, and identified frequent5 CLDN18-ARHGAP26/6 fusion (25%). With additional 797 patients for validation, we notice that prevalence of CLDN18-ARHGAP26/6 fusion is positively associated with signet-ring cell content (P = 4.1 x 10 -9 ), younger age at diagnosis (P = 4.2 x 10 -10 ), female/male ratio (P = 1.7 x 10 -9 ), and advanced TNM stage (P = 1.7 x 10 -5 ). Importantly, patients with CLDN18-ARHGAP26/6 fusion had a worse survival outcomes (P = 0.03), and got no benefit0 from platinum/fluoropyrimidines based chemotherapy (P = 0.92) compared to fusion-free patients (P = 0.001), which is consistent with the fact of oxaliplatin/fluoropyrimidine resistance acquired in CLDN18-ARHGAP26 introduced gastric cancer cell lines. Overall, this study provides new insights into the clinical and genomic features of SRCC, and highlights the importance of frequent CLDN18-ARHGAP26/6 fusions in chemotherapy response for SRCC.

  Study EGAS00001002668

• Regulatory T cell transcriptomic reprogramming characterizes adverse events by checkpoint inhibitors in solid tumors

  Immune checkpoint inhibitors (ICI), which target immune regulatory pathways to unleash antitumor responses, have revolutionized cancer immunotherapy. Despite the remarkable success of ICI immunotherapy, a significant proportion of patients whose tumors respond to these treatments develop immune-related adverse events (irAEs) resembling autoimmune diseases. Although the clinical spectrum of irAEs is well characterized, their successful management remains empiric. This is in part because the pathogenic mechanisms involved in the break-down of peripheral tolerance and induction of irAEs remain elusive. Herein, we focused on regulatory T cells (Tregs) in individuals with irAEs because these cells are vital for maintenance of peripheral tolerance, appear expanded in the peripheral blood of individuals with cancer and abundantly express checkpoint molecules, hence representing direct targets of ICI immunotherapy. Our data demonstrate an intense transcriptomic reprogramming of CD4+CD25+CD127– Tregs in the blood of individuals with advanced metastatic melanoma who develop irAEs following ICI immunotherapy, with a characteristic inflammatory, apoptotic and metabolic signature. This inflammatory signature was shared by Tregs from individuals with different types of cancer developing irAEs and individuals with autoimmune diseases. Our findings propose an inflammatory Treg reprogramming as a feature of immunotherapy-induced irAEs, that may facilitate translational approaches aiming to induce robust antitumor immunity without disturbing peripheral tolerance.

  Study EGAS00001004694

• Proteogenomics of chronic lymphocytic leukemia

  Cancer heterogeneity at the proteome level may explain differences in therapy response and prognosis beyond the currently established genomic and transcriptomic based diagnostics. The relevance of proteomics for disease classifications remains to be established in clinically heterogeneous cancer entities such as chronic lymphocytic leukemia (CLL). Here, we characterized the proteome and transcriptome in-depth alongside genetic and ex-vivo drug response profiling in a clinically well annotated CLL discovery cohort (n= 68). Unsupervised clustering of the proteome data revealed six subgroups. Five of these proteomic groups were associated with genetic features, while one group was only detectable at the proteome level. This new group was characterized by accelerated disease progression, high spliceosomal protein abundances associated with aberrant splicing, and low B cell receptor signaling protein abundances (ASB-CLL). We developed classifiers to identify ASB-CLL based on its characteristic proteome or splicing signature in two independent cohorts (n= 165, n= 169) and confirmed that ASB-CLL comprises about 20 % of CLL patients. The inferior overall survival observed in ASB-CLL was independent of both TP53- and IGHV mutation status. Our multi-omics analysis refines the classification of CLL and highlights the potential of proteomics to improve cancer patient stratification beyond genetic and transcriptomic profiling. This is the transcriptomics data of the discovery cohort.

  Study EGAS00001005746

• Identification of biomarkers of response to preoperative talazoparib monotherapy in treatment naïve gBRCA+ breast cancers

  Germline mutations in BRCA1 or BRCA2 exist in ~2-7% of breast cancer patients, which has led to the approval of PARP inhibitors in the advanced setting. We have previously reported a phase II neoadjuvant trial of single agent talazoparib for patients with germline BRCA pathogenic variants with a pathologic complete response (pCR) rate of 53%. As nearly half of the patients treated did not have pCR, better strategies are needed to overcome treatment resistance. To this end, we conducted multi-omic analysis of 13 treatment naïve breast cancer tumors from patients that went on to receive single-agent neoadjuvant talazoparib. We looked for biomarkers that were predictive of response (assessed by residual cancer burden) after 6 months of therapy. We found that all resistant tumors exhibited either the loss of SHLD2, expression of a hypoxia signature, or expression of a stem cell signature. These results indicate that the deep analysis of pre-treatment tumors can identify biomarkers that are predictive of response to talazoparib and potentially other PARP inhibitors, and provides a framework that will allow for better selection of patients for treatment, as well as a roadmap for the development of novel combination therapies to prevent emergence of resistance.

  Study EGAS00001005676

• The data access committee for Single molecule genome-wide mutation profiles of cell-free DNA for non-invasive detection of cancer

  Dac EGAC00001003253

• Expression-Based Subtypes Define Pathologic Response to Neoadjuvant Immune-Checkpoint Inhibitors in Muscle-Invasive Bladder Cancer

  Dac EGAC00001002276

• EGAD00010000474

  blood-based gene expression from breast cancer cases and age-matched controls in case-control serie 2 (CC2)

  Dataset EGAD00010000474

• EGAD00010000476

  blood-based gene expression from breast cancer cases and age-matched controls in case-control serie 1 (CC1)

  Dataset EGAD00010000476