3773 results for "*oma"

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• noninvasive lung cancer subtyping

  Accurate diagnosis of lung cancer is important for treatment decision-making. Currently, the gold standard for diagnosing histological subtypes of lung cancer relies on tumor biopsies. Recently, liquid biopsy, particularly cell-free DNA (cfDNA), has shown promising results in cancer detection and classification. In this study, we investigated the potential of cfDNA methylome for the noninvasive classification of lung cancer histological subtypes. Specifically, we focused on the two most prevalent lung cancer subtypes, lung adenocarcinoma and lung squamous cell carcinoma. Using a fragment-based marker discovery approach, we identified robust subtype-specific methylation markers from tumor samples. These markers were successfully validated in independent cohorts and associated with subtype-specific transcription activity. Leveraging these markers, we constructed a subtype classification model using cfDNA methylation profiles, achieving an AUC of 0.808 in the cross-validation and an AUC of 0.747 in the independent validation. Additionally, tumor copy number variations inferred from cfDNA methylome analysis revealed potential implications for treatment selection. In summary, our study demonstrates the potential of cfDNA methylome analysis for noninvasively lung cancer subtyping, offering insights for cancer monitoring and early detection.

  Study EGAS00001007717

• Oesophageal adenocarcinoma RNAseq from LUD2015-005 study (NCT02735239, EudraCT 2015-005298-19)

  This dataset contains bulk transcriptomes from the inoperable cohorts of the LUD2015-005 study (NCT02735239, EudraCT 2015-005298-19). Transcriptomes were prepared from pre-treatment oesophageal tumour biopsies using a ribodepletion approach in order to assess both previously reported (e.g. PD-L1 expression) and novel predictive expression-based biomarkers for immunochemotherapy treatment in this setting. On-treatment and post-treatment biopsies were generated as well to characterize response to therapy, and samples were also prepared from paired normal GI tissues for a subset of patients. scRNA-seq based deconvolution was also applied to bulk transcriptomes in this study to estimate the cell composition of tumour biopsies and assess the link between the presence of specific cell types with immunochemotherapy outcomes.

  Dataset EGAD00001009399

• Oesophageal adenocarcinoma WGS from LUD2015-005 study (NCT02735239, EudraCT 2015-005298-19)

  This dataset contains whole genome sequencing (WGS) generated from the inoperable cohorts of the LUD2015-005 study (NCT02735239, EudraCT 2015-005298-19). WGS data were generated with the aim to assess previously reported (e.g. tumour mutational burden) and novel predictive genomic markers for immunochemotherapy treatment in this setting. Using these data, mutation and copy number profiles were generated for the LUD2015-005 study, which were assessed for correlation with patient outcomes from this trial.

  Dataset EGAD00001009400

• A Risk Score Incorporating Low Pass Whole Genome Sequencing of Cell Free DNA from Patients Receiving CD19 CAR T-Cell Therapy for Large B-Cell Lymphoma

  Study EGAS00001006308

• Low Pass Whole Genome Sequencing of Cell Free DNA from Patients Receiving CD19 CAR T-Cell Therapy for Large B-Cell Lymphoma

  Low Pass Whole Genome Sequencing of Cell Free DNA from Patients Receiving CD19 CAR T-Cell Therapy for Large B-Cell Lymphoma consisting of 123 samples with FASTQs with hg19 aligned BAM/BAI files.

  Dataset EGAD00001009175

• MD Anderson Lymphoma & Myeloma Data Access Committee

  Dac EGAC00001002706

• Machine learning guided signal enrichment for ultrasensitive plasma tumor burden monitoring

  In solid tumor oncology, circulating tumor DNA (ctDNA) is poised to transform care through accurate assessment of minimal residual disease (MRD) and therapeutic response monitoring. To overcome the sparsity of ctDNA fragments in low tumor fraction (TF) settings and increase MRD sensitivity, we previously leveraged genome-wide mutational integration through plasma whole genome sequencing (WGS). We now introduce MRD-EDGE, a composite machine learning-guided WGS ctDNA single nucleotide variant (SNV) and copy number variant (CNV) detection platform designed to increase signal enrichment. MRD-EDGESNV uses deep learning and a ctDNA-specific feature space to increase SNV signal-to-noise enrichment in WGS by 300X compared to previous WGS error suppression. MRD-EDGECNV also reduces the degree of aneuploidy needed for ultrasensitive CNV detection through WGS from 1 Gb to 200 Mb, thereby expanding its applicability to a wider range of solid tumors. We harness the improved performance to identify MRD following surgery in multiple cancer types, track changes in tumor burden in response to neoadjuvant immunotherapy in non-small cell lung cancer (NSCLC) and demonstrate ctDNA shedding in precancerous colorectal adenomas. Finally, the radical signal-to-noise enrichment in MRD-EDGESNV enables de novo mutation calling in melanoma and small cell lung cancer (SCLC) without matched tumor, yielding clinically informative TF monitoring for patients on immune checkpoint inhibition (ICI).

  Study EGAS00001007545

• Machine Learning Signal Enrichment for Ultrasensitive Plasma Tumor Burden Monitoring

  In solid tumor oncology, circulating tumor DNA (ctDNA) is poised to transform care through accurate assessment of minimal residual disease (MRD) and therapeutic response monitoring. To overcome the sparsity of ctDNA fragments in low tumor fraction (TF) settings and increase MRD sensitivity, we previously leveraged genome-wide mutational integration through plasma whole genome sequencing (WGS). We now introduce MRD-EDGE, a composite machine learning-guided WGS ctDNA single nucleotide variant (SNV) and copy number variant (CNV) detection platform designed to increase signal enrichment. MRD-EDGESNV uses deep learning and a ctDNA-specific feature space to increase SNV signal-to-noise enrichment in WGS by 300X compared to previous WGS error suppression. MRD-EDGECNV also reduces the degree of aneuploidy needed for ultrasensitive CNV detection through WGS from 1 Gb to 200 Mb, thereby expanding its applicability to a wider range of solid tumors. We harness the improved performance to identify MRD following surgery in multiple cancer types, track changes in tumor burden in response to neoadjuvant immunotherapy in non-small cell lung cancer (NSCLC) and demonstrate ctDNA shedding in precancerous colorectal adenomas. Finally, the radical signal-to-noise enrichment in MRD-EDGESNV enables de novo mutation calling in melanoma and small cell lung cancer (SCLC) without matched tumor, yielding clinically informative TF monitoring for patients on immune checkpoint inhibition (ICI).

  Study EGAS00001007451

• Biomarker Screen for Efficacy of Oncolytic Virotherapy in Patient-derived Pancreatic Cancer Cultures

  Pancreatic ductal adenocarcinoma (PDAC) is a tumour entity with unmet medical need. To assess the therapeutic potential of oncolytic virotherapy (OVT) against PDAC, different oncolytic viruses (OVs) are currently investigated in clinical trials. However, systematic comparisons of these different OVs in terms of efficacy against PDAC and biomarkers predicting therapeutic response are lacking. We screened fourteen patient-derived PDAC cultures for their sensitivity to five clinically relevant OVs, namely serotype 5 adenovirus Ad5-hTERT, herpes virus T-VEC, measles vaccine strain MV-NIS, reovirus jin-3, and protoparvovirus H 1PV using live cell analysis, quantification of viral genome/gene expression, cell viability as well as cytotoxicity assays. Sensitivity was correlated with transcriptome profiles to identify potential predictive biomarkers for response to OVT. Patient-derived PDAC cultures showed individual response patterns to OV treatment. Twelve of fourteen cultures were responsive to at least one OV, with no single OV proving superior or inferior across all cultures. Known host factors for distinct viruses were retrieved as potential biomarkers. Compared to the basal-like molecular subtype, the quasi-mesenchymal subtype of PDAC was more sensitive to H-1PV, jin-3, and T-VEC. Expression of viral entry receptors did not correlate with sensitivity to OV treatment. Rather, cellular pathways controlling immunological, metabolic, and proliferative signalling appeared to determine outcome. For instance, high baseline expression of interferon-stimulated genes (ISGs) correlated with relative resistance to oncolytic measles virus, whereas cGAS expression was associated with exceptional response. Combination treatment of MV-NIS with a cGAS inhibitor improved tumour cell killing in several PDAC cultures.

  Study EGAS00001007001

• Exploring the driver events of eccrine poromas and porocarcinomas: A retrospective, cross-institutional study of 90 cases

  Eccrine poroma (EP) and porocarcinoma (EPC) are rare benign and malignant adnexal neoplasms of the terminal sweat gland duct, respectively. Both can arise de novo, however, EPCs can also arise from a pre-existing EP. To-date, genetic investigation of these tumors has involved studies with small sample sizes and/or limited analyses. To comprehensively compare the driver events and mutational landscape of these tumors, we performed a retrospective multi-institutional whole-exome sequencing and RNA sequencing study on the largest cohort of EPs and EPCs to-date (n=90). We uncovered novel events and delineated different pathways of tumorigenesis underlying these tumors, with EPs driven largely by fusion genes, and EPCs driven largely by somatic mutations, with rare YAP1 and frequent PAK gene novel fusions.

  Dataset EGAD00001015376

• Exploring the driver events of eccrine poromas and porocarcinomas: A retrospective, cross-institutional study of 90 cases

  Eccrine poroma (EP) and porocarcinoma (EPC) are rare benign and malignant adnexal neoplasms of the terminal sweat gland duct, respectively. Both can arise de novo, however, EPCs can also arise from a pre-existing EP. To-date, genetic investigation of these tumors has involved studies with small sample sizes and/or limited analyses. To comprehensively compare the driver events and mutational landscape of these tumors, we performed a retrospective multi-institutional whole-exome sequencing and RNA sequencing study on the largest cohort of EPs and EPCs to-date (n=90). We uncovered novel events and delineated different pathways of tumorigenesis underlying these tumors, with EPs driven largely by fusion genes, and EPCs driven largely by somatic mutations, with rare YAP1 and frequent PAK gene novel fusions.

  Dataset EGAD00001015377

• Exploring the driver events of eccrine poromas and porocarcinomas: A retrospective, cross-institutional study of 90 cases

  Eccrine poroma (EP) and porocarcinoma (EPC) are rare benign and malignant adnexal neoplasms of the terminal sweat gland duct, respectively. Both can arise de novo, however, EPCs can also arise from a pre-existing EP. To-date, genetic investigation of these tumors has involved studies with small sample sizes and/or limited analyses. To comprehensively compare the driver events and mutational landscape of these tumors, we performed a retrospective multi-institutional whole-exome sequencing and RNA sequencing study on the largest cohort of EPs and EPCs to-date (n=90). We uncovered novel events and delineated different pathways of tumorigenesis underlying these tumors, with EPs driven largely by fusion genes, and EPCs driven largely by somatic mutations, with rare YAP1 and frequent PAK gene novel fusions.

  Dataset EGAD00001015378

• Exploring the driver events of eccrine poromas and porocarcinomas: A retrospective, cross-institutional study of 90 cases

  Eccrine poroma (EP) and porocarcinoma (EPC) are rare benign and malignant adnexal neoplasms of the terminal sweat gland duct, respectively. Both can arise de novo, however, EPCs can also arise from a pre-existing EP. To-date, genetic investigation of these tumors has involved studies with small sample sizes and/or limited analyses. To comprehensively compare the driver events and mutational landscape of these tumors, we performed a retrospective multi-institutional whole-exome sequencing and RNA sequencing study on the largest cohort of EPs and EPCs to-date (n=90). We uncovered novel events and delineated different pathways of tumorigenesis underlying these tumors, with EPs driven largely by fusion genes, and EPCs driven largely by somatic mutations, with rare YAP1 and frequent PAK gene novel fusions.

  Dataset EGAD00001015379

• Pediatric Low-Grade Glioma RNA and Targeted Sequencing

  Pediatric low-grade gliomas (pLGG) are frequently driven by genetic alterations in the RAS/MAPK pathway yet show unexplained variability in their clinical outcome. To address this, we characterized a cohort of >1,000 clinically annotated pLGG. 84% of cases harbored a driver alteration, while those without an identified alteration also often exhibited up-regulation of the RAS/MAPK pathway. pLGG could be broadly classified based on their alteration type. Rearrangement-driven tumors were diagnosed at a younger age, enriched for WHO grade I histology, infrequently progressed, and rarely resulted in death as compared to SNV-driven tumors. Further sub-classification of clinical-molecular correlates stratified pLGG into risk categories. These data highlight the biological and clinical differences between pLGG subtypes and opens avenues for future treatment refinement.

  Study EGAS00001004242

• Shot-gun stool metagenomics and colorectal cancer risk.

  This study aims to identify metagenomics biomarkers in colorectal cancer (CRC). The study includes 156 samples of shot-gun stool metagenomics, corresponding to 51 patients with CRC, 54 patients with high-risk adenoma, and 51 healthy controls. The sequencing libraries were prepared with 2 µg of total DNA using the Nextera XT DN Sample Prep Kit (Illumina, San Diego, CA, USA). Sequencing was performed at 150 nucleotides, paired-end, using an Illumina HiSeq 4000 platform.

  Study EGAS00001007025

• Multiple Myeloma follow-up sequencing study

  A total of 40 Multiple Myeloma (MM) patients at clinical relapse who progressed during Proteasome Inhibitors (PIs) or Immunomodulating Drugs (IMiDs)-based therapies and who are assigned to antiCD38-based salvage treatments, will be enrolled. We will collect bone marrow (BM) and peripheral blood (PB) samples from patients at specific timepoints: baseline (BM, PB and buccal swab) every 3 month (PB) achievement of response (≥ Very Good Partial Response (VGPR)) (BM and PB) relapse or refractory status to antiCD38-based treatments (BM and PB) Samples will be processed and stored in the "Hematological Laboratory" located in the University of Turin (Italy) for various proposed analyses: at specific time-points CD138+ (Plasma Cells-PCs) awill be immunomagnetically enriched from the BM mononuclear cells and frozen as viable cells in dimethyl sulfoxide (DMSO); PB mononuclear cells (PBMCs) will be isolated from whole blood by density-gradient centrifugation, and frozen as above; plasma fraction from PB and BM will be obtained by centrifugation and stored frozen; Neutrophils will be obtained at the time of enrollment as a source of control germline DNA and stored frozen.

  Study EGAS00001007092

• RNA sequencing of in vitro generated suppressive myeloid cells using parental and Sialidase expressing A549 cancer cell lines

  Fresh peripheral blood mononuclear cells of four human donors were cultured together with either lung adenocarcinoma A549 cancer cells or A549-expressing H1N1 Sialidase cancer cells. These treatments induced the differentiation of donor cells into immunosuppressive MDSC-like cells, which were further subjected to bulk RNA sequencing. RNA-seq TruSeq libraries were generated from polyA-enriched mRNA isolated from the samples, and sequenced in paired-end mode on 4 lanes of an Illumina NextSeq 500 flow-cell

  Dataset EGAD00001012437

• ISA Nutrition 2015

  Comprehensive data on lifestyle-related modifiable factors, sociodemographic, anthropometric, economic, biochemical, and genetic markers related to the occurrence of cardiometabolic diseases as part of the observational cross-sectional survey (2015 Health Survey of Sao Paulo with Focus on Nutrition (2015 ISA-Nutrition), a population-based study. Data of 805218 SNPs for 841 individuals was genotyped using the Axioma 2.0 Precision Medicine Research Array in the Thermo Fisher Scientific laboratory (Affymetrix Inc, Santa Clara, CA).

  Dataset EGAD00010002678

• Molecular profiling of acinar cell carcinoma of the salivary glands

  Samples of acinar cell carcinoma (AciCC) of the salivary glands and paired normal salivary gland tissue were analyzed by whole transcriptome RNA-seq (n=10), whole genome sequencing (n=6), whole genome bisulfite sequencing (n=3) and ChIP-seq (H3K27ac, H3K4me3, H3K27me3, NR4A3, CTCF).

  Study EGAS00001002795

• Whole genome sequencing and somatic mutation profiles and whole genome transcription files of pediatric medulloblastoma

  Fastq, Mutect (SNVs), Platypus (indels), and InfoGenomeR (SVs and CNAs) calls from whole genome sequencing data and fastq files of whole genome transcription data of five patients with pediatric medulloblastoma.

  Dataset EGAD00001009507

• H3.3G34R/V-transformed interneuron progenitors co-opt PDGFRA for gliomagenesis

  Histone H3.3 glycine 34 to arginine/valine (H3.3G34R/V) mutations occur in deadly hemispheric high-grade gliomas. These tumors show exquisite regional and temporal specificity, suggesting a developmental context permissive to the effects of G34R/V mutations. Here we present the molecular landscape of G34R/V gliomas (n=85) and show that 50% bear activating mutations in PDGFRA, with strong selection pressure for PDGFRAMUT clones at recurrence. We show that G34R/V tumors arise in interneuron progenitors of the foetal ventral forebrain expressing GSX2 and the DLX family of homeobox transcription factors, where terminal neuronal differentiation is impaired through aberrant G34R/V-mediated H3K27me3. Frequent co-occurrence of G34R/V & PDGFRAMUT is facilitated in this interneuron lineage-of-origin as PDGFRA forms an aberrant chromatin loop with the adjacent GSX2, hijacking its active chromatin conformation. At the single-cell level, G34R/V tumours entirely lack oligodendroglial transcriptional programs prominent in other glioma entities, and instead harbour dual neuronal and astroglial compartments. CRISPR-removal of H3.3G34R/V does not impact tumorigenicity suggesting this mutation becomes dispensable, while PDGFRAMUT are potently oncogenic regardless of G34 mutation. Collectively, our results suggest that G34R/V gliomas arise in foetal interneuron progenitors unable to undergo terminal differentiation, enabling co-option of PDGFRA through inappropriate expression and activating mutations to promote gliogenesis and oncogenicity. Reliance on PDGFRA for oncogenesis may be of therapeutic opportunity in G34R/V glioma.

  Study EGAS00001004301

• NanoString Cancer

  RCC files of 17 Cartridges from metastatic melanoma

  Dataset EGAD00010002432

• 3D-GSC_expression_profiles

  In this study, we used RNA-sequencing gene expression profiling in order to characterize specific phenotypic traits in DIPG-derived glioma stem cell (GSC) models. Twenty-two primary GSC models derived from biopsies collected at diagnosis were cultured in an ECM-mimicking compound before for RNA extraction and subsequent rRNA-depletion and sequencing .

  Study EGAS00001007182

• 3D-GSC_expression_profiles

  In this study, we used RNA-sequencing gene expression profiling in order to characterize specific phenotypic traits in DIPG-derived glioma stem cell (GSC) models. Twenty-two primary GSC models derived from biopsies collected at diagnosis were cultured in an ECM-mimicking compound before for RNA extraction and subsequent rRNA-depletion and sequencing .

  Dataset EGAD00001011079

• Whole exome sequencing data of Hispanic hepatocellular carcinoma

  The paired-end reads were aligned to the human reference genome (hg19) with decoy sequences (as used in the 1000 Genomes Project) using BWA (v0.7.5a) software. The duplicate reads were marked and subsequently removed using Picard (v1.140) (https://broadinstitute.github.io/picard/) and SAMtools (v0.1.19), respectively. Local realignment around insertions/deletions (indels) and base quality recalibration were performed using GATK (v3.6).

  Dataset EGAD00001011158