3995 results for "*geneti*"

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• RNA sequencing data of pediatric B-other acute lymphoblastic leukemia

  For a long time, approximately 70% of childhood B-ALL cases could be classified routinely, and the remaining 30% were classified into the “B-other” group lacking the known genetic features. However, more recently, new genomic tools have uncovered new subtypes among the B-other groups. Approximately 10% of B-ALL cases lack the recurrent genetic abnormalities, and are referred as "B-other". They are typically more heterogeneous than other subtypes of B-ALL, and their prognoses are more variable. In a more recent update of the B-ALL classification, 27 subtypes were identified (Arber et al., 2022). The identification of some of these subtypes is dependent on NGS methods, such as RNA sequencing, which are not routinely used in all clinical laboratories. For example, ETV6::RUNX1-like and DUX4-rearranged subtypes have been identified using RNA sequencing. For this study, subtype predictions for some of the cases were acquired by using the ALLIUM (Krali et al., NPJ Precis Oncol., 2023) and ALLCatchR (Beder et al., Blood, 2022) tools for the RNA sequencing data.

  Study EGAS50000001803

• RNA sequencing data of pediatric hypodiploid acute lymphoblastic leukemia

  Hypodiploid acute lymphoblastic leukemia (ALL) is a rare subtype of B-cell ALL characterized by chromosome number < 45 , encompassing near-haploid (24–29 chromosomes) and low-hypodiploid (30–39 chromosomes) subgroups. These subgroups display distinct genetic landscapes, including Ras and receptor tyrosine kinase pathway alterations in near-haploid ALL, and frequent IKZF2, RB1, and germline TP53 alterations in low-hypodiploid ALL. Clinically, hypodiploid ALL is associated with dismal prognosis, with 5-year overall survival rates often between 50-70% in children and markedly worse in adults. Despite advances in risk stratification and MRD-guided therapy, allogeneic stem cell transplantation remains the current standard recommendation for affected patients.

  Study EGAS50000001806

• Large deletion predisposes to familial melanoma

  Mutations in CDKN2A and CDK4 account for ~40% of multi-case melanoma families, with another ~10% attributable to BAP1 and genes associated with telomere maintenance. Thus, a substantial proportion of the genetic risk underlying familial melanoma remains unexplained.

  Study EGAS50000001496

• Predictive value of genomic, transcriptomic and epigenetic biomarkers in patients with recurrent and/or metastatic HNSC treated with PD-1/PD-L1 inhibitors

  Immune checkpoint inhibitors have improved survival in several solid tumors, including head and neck squamous cell carcinoma (HNSCC). However, current use of PD-1/PD-L1 inhibitors relies on PD-L1 expression, which does not reliably predict patient response. Therefore, better predictive biomarkers are needed to identify which patients benefit from immunotherapy. Previous studies suggest that genomic and transcriptomic features may help predict treatment response. This study aims to integrate genomic, transcriptomic, and methylomic data from 31 patients with recurrent/metastatic HNSCC to identify new biomarkers of resistance to anti-PD-1/PD-L1 therapy.

  Study EGAS50000001746

• scATAC-seq of CD4+ T cells from blood, lymph nodes and tumors of NSCLC patients

  This study explore the CD4+ T cells diversity in paired blood, lymph nodes and tumors of 2 different NSCLC patients. After FACS-sorted of Tregs (DAPI- CD45+ CD4+ CD25hi CD127lo) and Tconvs (DAPI- CD45+ CD4+CD25lo CD127lo/hi), cells were mixed in equal proportion (fifty/fifty ratio) and procesed with 10X Chromium (10X Genomics) scATAC kit and sequenced using Illumina platforms.

  Study EGAS50000000294

• ecDNA copy number heterogeneity

  Neuroblastoma exhibits significant inter- and intra-tumour genetic heterogeneity and varying clinical outcomes. Here, we used DNA and RNA sequencing from the same single cells in cell lines and neuroblastoma patients to investigate these effects. We reveal extensive intercellular ecDNA copy number heterogeneity. We also provide direct evidence of how this heterogeneity influences the expression of cargo genes, including MYCN and its downstream targets, and the overall transcriptional state of neuroblastoma cells.

  Study EGAS50000000509

• Methylation sequencing of CSF-derived cell free DNA

  We sequenced and enzymatically converted cell free DNA from 268 samples from 157 patients with brain tumors and 58 control CSF patients.

  Study EGAS50000001365

• cell-free DNA Target sequencing from primary and recurrent/metastatic breast cancer patients

  Breast cancer is one of the most common cancers occurring worldwide in women. Even after curative treatment based on clinical subtypes according to molecular features, the risk of relapse still remains. Cell-free DNA (cfDNA) is an emerging tool for clinical cancer detection to monitor the risk of recurrence, therapeutic efficacy and tumor progression. In occurrence of relapse, genomic, transcriptomic and epigenetic profiles are altered, and reflected in cfDNA fragmentation patterns. In this study, we focus on the transcriptionally dynamic loci associated with therapy resistance in breast cancer, and develop the target sequencing approach using cfDNAs to detect individuals with recurrent/metastatic breast cancer.

  Study JGAS000812

• Whole-genome sequencing of the parental tumor and established organoids from a patient with gastric-type cervical adenocarcinoma

  This study aims to evaluate the genetic characteristics of patient-derived organoids established from gastric-type cervical adenocarcinoma and to assess their similarity to the parental tumors using whole-genome sequencing.

  Study JGAS000796

• Smoking-dependent expression alterations in nasal epithelium reveal immune impairment linked to germline variation and lung cancer risk.

  Lung cancer is the leading cause of cancer-related death in the world. In contrast to many other cancers, a direct connection to lifestyle risk in the form of cigarette smoke has long been established. More than 50% of all smoking-related lung cancers occur in former smokers, often many years after smoking cessation. Despite extensive research, the molecular processes for persistent lung cancer risk are unclear. CT screening of current and former smokers has been shown to reduce lung cancer mortality by up to 26%. To examine whether clinical risk stratification can be improved upon by the addition of genetic data, and to explore the mechanisms of the persisting risk in former smokers, we have analyzed transcriptomic data from accessible airway tissues of 487 subjects. We developed a model to assess smoking associated gene expression changes and their reversibility after smoking is stopped, in both healthy subjects and clinic patients. We find persistent smoking associated immune alterations to be a hallmark of the clinic patients. Integrating previous GWAS data using a transcriptional network approach, we demonstrate that the same immune and interferon related pathways are strongly enriched for genes linked to known genetic risk factors, demonstrating a causal relationship between immune alteration and lung cancer risk. Finally, we used accessible airway transcriptomic data to derive a non-invasive lung cancer risk classifier. Our results provide initial evidence for germline-mediated personalised smoke injury response and risk in the general population, with potential implications for managing long-term lung cancer incidence and mortality.

  Dac EGAC50000000169