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• TIRE-seq: an Integrated Sample Extraction and Transcriptomics Workflow for High Throughput Perturbation Studies

  TIRE-seq is a novel RNA sequencing method that integrates mRNA purification directly into library preparation, eliminating separate RNA extraction. The technique demonstrated utility across three biological applications, including capturing transcriptional changes in human T cells, identifying genes driving murine dendritic cell differentiation, and analyzing the dose-response effects of temozolomide on patient-derived neurospheres. With its simplified approach and high sequencing efficiency, TIRE-seq offers a cost-effective solution for large-scale gene expression studies.

  Study EGAS50000000867

• NGS sequencing data of archival FFPE tumor tissue

  The aim of the study was to identify mutations in key ovarian cancer genes (BRCA1, BRCA2,TP53, PTEN, ATM, ATR, NF1) in archival fresh-frozen paraffin embedded (FFPE) tumor tissue from platinum-resistant ovarian cancer patients enrolled in the phase I/II GANNET53 clinical trial. From the enrolled 133 patients, archival FFPE tissue was available and DNA was extracted thereof. The DNA samples passing quality control (n=118) were NGS sequenced using the SureSeq™ Ovarian Cancer Panel and the NGS Library Preparation kit (Oxford Gene Technology), which covers all exons of 7 key ovarian cancer genes for single nucleotide variants (SNV) and indels, and the Illumina MiSeq platform. For the paired-end runs, one Read 1 (R1) and one Read 2 (R2) FASTQ file were created for each sample. FASTQ files were compressed and created with the extension \.fastq.gz.

  Dataset EGAD50000001371

• Allogeneic induced pluripotent stem (iPS) cell-derived cartilage transplantation for articular cartilage damage in knee joints: a phase I, first-in-human study

  Damaged articular cartilage seldom heals due to a limited capacity for self-repair, frequently leading to osteoarthritis. Regenerative interventions are expected to heal the damage. We have recently established a method to produce cartilage from induced pluripotent stem cells (iPSCs) in a clinically applicable process. The primary aim of this study was to evaluate the safety including tumorigenesis and the subsequence efficacy of allogeneic iPSC-derived cartilage transplantation into damaged areas of knee articular cartilage.

  Study EGAS50000001167

• Generation of hypoimmunogenic induced pluripotent stem cells by CRISPR-Cas9 system and detailed evaluation for clinical application

  We established hypoimmunogenic human induced pluripotent stem cells (iPSCs) to minimize the immune rejection caused by mismatches of HLA type. Here, we optimized the protocol for good manufacturing practice (GMP)-compatible CRISPR-Cas9 genome editing to deplete the three gene locus (HLA-A, HLA-B, and CIITA genes) simultaneously in HLA homozygous iPSCs. RNA-seq and flow cytometry analyses confirmed the successful depletion of HLAs, and lineage-specific differentiation into cardiomyocytes was verified.

  Study EGAS50000001194

• Integrated Methylation and Copy Number Analysis for Non-invasive Bladder Cancer Detection in Urine

  The molecular analysis of urine cell-free DNA (cfDNA) offers a non-invasive tool to advance bladder cancer (BC) management. Assessment of somatic copy number aberrations (SCNA) and DNA methylation, as singular or complementary analysis, have emerged as promising approaches for BC detection. Here, we developed an integrated analysis to assess both SCNA and targeted methylation changes from the same template molecules, named the iSECURE (integrated SEquencing-based Copy number and methylation analysis in URinE) method.

  Study EGAS50000001350

• ATAC-seq iPSC cells or smNPC cells for allelic imbalance

  In order to confirm the predicted impact of the PD-associated allele of rs144814361 on BAG3 promoter, we proceeded with genome editing of the TH-REP1 cell line by using prime editing to insert the “T” allele at the position chr10:119651405 in the BAG3 promoter. 3 replicates for each condition: 1) iPSC Wild Type 2) SNP-BAG3 variant in iPSC 3) SNP-BAG3 variant in smNPC. Allelic imbalance is further assessed using read counting at this specific position.

  Study EGAS50000001579

• Personalized analysis of ctDNA for detection of molecular residual disease and recurrence in a cohort of surgically treated patients with head and neck squamous cell carcinoma

  Despite advances in multimodal treatment, survival for patients with advanced head and neck squamous cell carcinoma (HNSCC) has improved only modestly. The recent advent of tumor-informed assays capable of detecting circulating cell-free tumor DNA (ctDNA) has enabled early detection of molecular residual disease (MRD) and recurrence following curative therapy. We assessed ctDNA in plasma from 76 and saliva from 54 HNSCC patients, respectively, who received primary curative-intent surgery.

  Study EGAS50000001018

• Fixative optimisation study for BRITROC project

  The British Translational Research Ovarian Cancer Collaborative (BriTROC), spanning more than 10 centres across UK, is a prospective observational project focused on relapsed high-grade serous ovarian cancer (HGSOC). The first study, as a part of the project, is the Fixative optimisation study, which analyses the utility for next-generation sequencing of UMFIX samples compared to NBF-fixed and fresh frozen samples. Various DNA and sequencing quality analyses were performed to compare fixation methods in bulk tumour and biopsy samples.

  Study EGAS00001001433

• Oral mucosa organoids as a potential model for personalized therapies

  Organoids were established from both tumor and matched wildtype tissue from patients diagnosed with head and neck squamous cell carcinoma (HNSCC). In order to confirm tumor status and identify oncogenic driver mutations, DNA derived of these organoids was sequenced. After validation of tumor identity, organoids were exposed to a range of (targeted) chemotherapeutics and radiotherapy. Differential responses to therapeutics were subsequently correlated to underlying genetic alterations to see if DNA mutation status could be predictive for responses to therapy.

  Study EGAS00001003628

• A Comparative Analysis of Algorithms for Somatic SNV Detection in Cancer

  Four recently published algorithms for the detection of somatic SNV sites in matched cancer-normal sequencing datasets are VarScan, SomaticSniper, JointSNVMix and Strelka. In this analysis, we apply these four SNV calling algorithms to cancer- normal Illumina exome sequencing of a chronic myeloid leukaemia (CML) patient. The candidate SNV sites returned by each algorithm are filtered to remove likely false positives, then characterised and compared to investigate the strengths and weaknesses of each SNV calling algorithm.

  Study EGAS00001000927