Search Results - EGA European Genome-Phenome Archive

Identification of Somatic Changes in Tumors from Fanconi Anemia Patients

This study focused on the identification of genomic signatures present in tumors from Fanconi anemia patients. Fanconi anemia is a rare hereditary disease caused by defects in DNA interstrand crosslink repair. The primary patient phenotypes are bone marrow failure and cancer predisposition. We concentrated on squamous cell carcinomas and used whole genome Illumina sequencing (22 tumor samples and 12 normal samples) , whole exome sequencing (37 tumor samples and 33 normal samples), PacBio long-read whole-genome (nine tumor and four normal samples),10X linked-read whole-genome sequencing, 10x single-cell/nuclei 3’ RNA sequencing (three tumor samples), 10x Visium spatial transcriptomics (one tumor sample), EPIC 850K methylation array (six samples), and bulk RNAseq (six tumor samples) to identify somatic changes present in tumors. The study aimed to identify changes that drive tumorigenesis in Fanconi anemia, give insight into the early development and aggressive nature of these tumors, and suggest therapeutic avenues for these patients. Another goal was to compare the genomic changes identified in tumors from Fanconi anemia patients with sporadic head and neck cancers. This study demonstrated that the tumors from Fanconi anemia individuals are generally not driven by HPV. Instead, they acquire mutations in the p53 tumor suppressor. The main characteristic of the tumors is the presence of a high number of structural variants in the form of small deletions, unbalanced translocations, and fold-back inversions, which often form complex rearrangements. These rearrangements result in amplifications and deletions of a multitude of oncogenes and tumor suppressors, respectively. The study also shows that lack of the Fanconi anemia DNA repair pathway leads to an epithelial-to-mesenchymal transition in a mouse model and in human samples that may influence the behavior of tumors in Fanconi anemia. Finally, comparing genomic changes in Fanconi anemia and sporadic tumors of the head and neck, we propose that the structural variants present in sporadic cancer result in a functional deficiency of the Fanconi anemia DNA repair pathway.

Study phs002652

Automated machine-learning approach for next generation profiling of sequence alterations, mutation burden, microsatellite instability, and structural variants in human cancers

Sequence and structural alterations together with tumor mutation burden (TMB) and microsatellite instability (MSI) have been identified as biomarkers for the determination of response to targeted and immune checkpoint inhibitor therapies. However, widespread clinical adoption of these biomarkers has historically been limited due to barriers such as evidence of clinical utility and reimbursement. We have developed 2.2 Mb targeted NGS system and an automated machine-learning analysis approach (PGDx elio™ tissue complete, ETC) that has been FDA cleared for examination of 500+ cancer-related genes and 68 mononucleotide repeats for identification of sequence and structural alterations, TMB, and MSI in solid cancers in a clinical setting. We designed and trained this approach using sequence data from 4,174 cancers and &gt;124,000 in silico alterations and evaluated the methodology in &gt;2,550 tumor or non-cancerous normal samples. Independent analyses of ETC sequence changes in 440 formalin fixed paraffin embedded (FFPE) tumor or cell line samples using MSK-IMPACT™, FoundationOne®, and ddPCR revealed a positive percent agreement (PPA) &gt;97% with high sensitivity as low as 3% mutant allele fraction. We observed high concordance between panel-wide and whole-exome TMB for 307 pan-cancer FFPE tumors (Pearson r=0.95, p &lt; 0.0001) using samples with ≥20% tumor cellularity. Comparison of the mutation context and repeat-based MSI approach in ETC with a multiplex MSI PCR assay in 223 samples revealed a PPA of 99% and negative predictive agreement (NPA) &gt;99%. We confirmed the accuracy and precision of TMB and MSI measurements across three independent laboratories (CV of &lt;5% and average PPA &gt;99%, respectively). Finally, evaluation of amplifications and translocations against DNA and RNA-based approaches exhibited &gt;98% NPA and PPA of 86% and 82% respectively. These results demonstrate high analytical performance for determination of sequence and structural changes, TMB, and MSI using a targeted NGS panel and provide a scalable and facile approach for evaluating these biomarkers in a clinical laboratory.

Study EGAS00001005556

Renal_habitat_WXS

This project aims at correlating genetic diversity (as well as transcriptomic, metabolic and immune diversity) observed in multiple targeted tumour biopsies and circulating tumour DNA with heterogeneity on multiparametric MRI. To this end, 20 patients with RCC (15 patients with localised/locally advanced disease and 5 with mRCC) will undergo multiparametric MRI including metabolic assessment by 13C-MRSI as well as measurements of tumour perfusion, oxygenation and water diffusion. Based on unique combinations of these imaging parameters, tumour habitats will be defined through cluster mapping. Intra-operative biopsy and immediate freezing of tumour cores from different imaging habitats will be performed. Multiregional ex-vivo tumour biopsies will be spatially registered to the MR data by using 3D printed tumour moulds generated from high-resolution volumetric sequences. These moulds allow slicing tumour specimens in identical planes to the MR acquisition and increase the accuracy of tissue sampling. The biopsies will then undergo molecular profiling such as metabolomic and RNA sequencing (including mRNA immune profiling), as well as DNA sequencing to assess driver and clonal mutations in different tumour habitats and guide design of appropriate cfDNA probes. The targeted cfDNA capture panel will be employed to determine the ability of cfDNA to capture the full genetic diversity observed in the primary tumour and to relate cfDNA to various imaging habitats in both renal and pancreatic cancer. Data integration will be undertaken between imaging habitats and molecular profiles for each region.

Study EGAS00001003703

Single_cell_characterization_of_T_cell_lymphoma_

Lymphomas are types of blood cancer derived from lymphocytes, and can be classified into two main categories, Hodgkin's lymphomas (HL) and non-Hodgkin lymphomas (NHL). T-cell lymphoma is a type of NHL that develops from T lymphocytes and accounts for 10-15% of total NHL cases. As a rare disease, T-cell lymphoma is functionally, pathologically, and clinically complex and heterogeneous. The 2016 revision of the WHO classification has listed 29 subtypes of mature T/NK-cell neoplasms, among which over 25 are T lymphocyte in origin. These subtypes of T-cell lymphomas have different biological behaviours and clinical prognosis. Clinically, T-cell lymphoma ranges from indolent (slow-growing) to aggressive (fast-growing and spreading) disease. According to the guideline booklet provided by the Lymphoma Research Foundation (https://lymphoma.org/aboutlymphoma/nhl/), indolent T-cell lymphoma subtypes include adult T-cell leukaemia/lymphoma (ATLL), cutaneous T-cell lymphoma (CTCL), and mycosis fungoides (MF), while the aggressive subtypes include anaplastic large cell lymphoma (ALCL), angioimmunoblastic T-cell lymphoma (AITL), peripheral T-cell lymphoma (PTCL), and T lymphoblastic lymphoma (TLBL). PTCL and ALCL represent the most common subtypes of aggressive T-cell lymphoma whereas TLBL is a rare and aggressive subtype mostly diagnosed in children. In this study, we will use single cell RNA sequencing and single cell multiomic methods three aggressive T-cell lymphoma subtypes (ALCL, PTCL and TLBL) and try to gain a deeper insight into the genotypic and phenotypic features of these T-cell lymphomas.

Study EGAS00001005750

RNA-seq, WGS and WES of Hepatocellular carcinomas, enriched in fibrolamellar carcinomas

DNAJB1-PRKACA fusion is a specific driver event in fibrolamellar carcinoma (FLC), a rare subtype of hepatocellular carcinoma (HCC) occurring in adolescents and young adults. In older patients, molecular determinants of HCC with mixed histological features of HCC and FLC (mixed-FLC/HCC) remain to be discovered.This study aims to molecularly caracterize mixed fibrolamellar hepatocellular carcinoma (mixed FLC/HCC) within the molecular liver tumors diversity, in respect of pure FLC and different HCC subtypes. This study reunites WGS data (n=3, Tumoral/Non-Tumoral pairs), WES data (n=43, Tumoral/Non-Tumoral pairs) and RNAseq data (n=66, Tumoral only). On a trascriptomic level, most of the mixed-FLC/HCC RNAseq clustered in a robust subgroup of tumors all showing mutation or translocation inactivating BAP1 that codes for the BRCA1 associated protein-1.

Study EGAS00001003837

BLUEPRINT RNA-seq of Epigenetic programming during monocyte to macrophage differentiation and trained innate immunity

Monocyte differentiation into macrophages represents a cornerstone process for host defense. Concomitantly, immunological imprinting of either tolerance or trained immunity determines the functional fate of macrophages and susceptibility to secondary infections. Transcriptomes and epigenomes in four primary cell types: monocytes, in vitro differentiated naïve, tolerized and trained macrophages were characterized. Inflammatory and metabolic pathways were modulated in macrophages, including decreased inflammasome activation, and pathways functionally implicated in trained immunity were identified. Strikingly, β-glucan training elicits an exclusive epigenetic signature, revealing a complex network of enhancers and promoters. Analysis of transcription factor motifs in DNase I hypersensitive sites at cell-type specific epigenetic loci unveiled differentiation and treatment specific repertoires. Altogether, this study provides a resource to understand the epigenetic changes that underlie innate immunity in humans.

Study EGAS00001000953

Single cell eQTL map of T cell activation

We isolated naive and memory CD4+ T cells from 119 healthy individuals and stimulated the cells using anti-CD3/anti-CD28 coated beads. We profiled gene expression using single cell RNA-seq (10X-Genomics 3’ v2 kit) at resting state and three time points of activation (16h, 40h and 5 days post stimulation) and mapped expression quantitative trait loci.

Dataset EGAD00001008197

12086 results for "cancer rna-seq"

in 17.02 milliseconds.