4955 results for "*oma"

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• Sequencing data for ICGC Oesophageal Adenocarcinoma tissue samples - side_cases_barretts

  Dataset EGAD00001001379

• Whole-Genome Bisulfite Sequencing of a paired initial and recurrent glioma

  Dataset EGAD00001001616

• Carcinoma of the oral tongue (OTSCC) genomic landscape characterisation

  18 Exomes for discovery set and 60 Targeted panel for prevalence set

  Dataset EGAD00001001465

• Transcriptional regulatory networks of tumor-associated macrophages that drive malignancy in mesenchymal glioblastoma

  Dataset EGAD00001003324

• Targeted resequencing of coding regions of ribosomal protein genes in multiple myeloma samples

  Dataset EGAD00001003302

• Pseudomyxoma peritonei exome sequencing vcf-files

  Dataset EGAD00001003297

• Ewing sarcoma genome sequencing

  Dataset EGAD00001001051

• BAM files from Cholangiocarcinoma exome sequencing

  Dataset EGAD00001001220

• Lengthening and shortening of plasma DNA in hepatocellular carcinoma patients

  Dataset EGAD00001001275

• Integrated molecular analysis of clear cell renal cell carcinoma

  Dataset EGAD00001000597

• Pilocytic Astrocytoma ICGC PedBrain RNA sequencing

  Pilocytic Astrocytoma ICGC PedBrain RNA sequencing

  Dataset EGAD00001000617

• Angiosarcoma follow up study

  A bespoke targeted pulldown experiment will be performed on patients with Angiosarcoma. the resulting products will be sequenced to determine the prevalence of previously found mutations in these patients.

  Dataset EGAD00001000620

• Sequencing data for ICGC Oesophageal Adenocarcinoma tissue samples - pilot normal and pre/post-chemo

  Dataset EGAD00001000704

• DIPG_ICR_WES

  Whole exome sequencing of 6 tumour and normal pairs of diffuse intrinsic pontine glioma (DIPG)

  Dataset EGAD00001000706

• Discovery of resistance mechanisms to the BRAF inhibitor vemurafenib in metastatic BRAF mutant melanoma

  Discovery of resistance mechanisms to the BRAF inhibitor vemurafenib in metastatic BRAF mutant melanoma by massively-parallel sequencing of tumour samples. Comparison of genomic characteristics of pretreatment 'sensitive' to recurrence 'resistant' tumours to identify the genetics of drug resistance.

  Dataset EGAD00001000707

• The UCSF Low Grade Glioma Genome Project #1

  Dataset EGAD00001000714

• Angiosarcoma whole exome

  Extension of angiosarcoma whole genome sequencing study

  Dataset EGAD00001000722

• Matched tumour/normal .bam files generated by QCMG at University of Queensland from HiSeq whole genome sequencing of oesophageal adenocarcinoma cases

  Dataset EGAD00001000845

• HCC.GNE RNA-Seq

  RNA-Sequencing data (raw read sequences) for 23 samples, from 12 patients, for the study "Diverse modes of genomic alterations in Hepatocellular Carcinoma"

  Dataset EGAD00001000886

• Mantle Cell Lymphoma Dataset

  Dataset EGAD00001000667

• Whole exome sequencing of peripheral T-cell lymphoma (PTCL)

  Dataset EGAD00001000659

• Novel driver variants in the histone 3.3 genes, H3F3A and H3F3B, define bone and cartilage cancer sub-types

  A selection of human cancers harbours somatic driver mutations in genes encoding histones, most notably childhood brain tumours with K27M substitutions of the histone 3.3 gene, H3F3A. We performed whole genome sequencing of the benign cartilage tumour, chondroblastoma, and targeted sequencing of histone 3.3 genes, H3F3A and H3F3B, in seven further skeletal tumour types. We identified an exceptionally high prevalence of novel histone 3.3 driver mutations at glycine 34 and at lysine 36. Histone 3.3 gene mutations were found in 91% in giant cell tumours of bone (48/53), mainly H3F3A G34W variants, and in 92% of chondroblastoma (73/79), predominantly K36M mutations in H3F3B. H3F3B is paralogous to the cancer gene H3F3A. However, H3F3B driver variants have not previously been reported in human cancer. Our observation demonstrate remarkable tumour-specificity of mutations, with respect to which histone 3.3 gene and residue is mutated, indicating that the advantage these mutations confer is tumour dependent. Moreover, tumour-specific mutation of H3F3A and H3F3B suggests, that although both genes encode identical proteins, they are likely non-redundant and employed differentially during skeletal development.

  Dataset EGAD00001000646

• Exome sequencing of patients with Ewings sarcoma

  Cancer is driven by mutations in the genome. We will uncover the mutations that give rise to Ewing's sarcoma, a bone tumour that largely affects children. We will use second generation Illumina massively parallel sequencing, and bespoke software, to characterise the genomes and transcriptomes of Ewing,s sarcoma tumours.

  Dataset EGAD00001000333

• Somatic mutations, clonal architecture and genomic evolution in multiple myeloma

  Multiple myeloma is an incurable plasma cell malignancy whose molecular pathogenesis is incompletely understood. We used whole exome sequencing, copy number profiling and cytogenetic to analyses 84 samples from 67 patients with myeloma. In addition to known myeloma genes, we identify new candidate genes, including truncations of SP140, ROBO1 and FAT3 and clustered missense mutations in EGR1. We find oncogenic mutations in cancer genes not previously implicated in myeloma, including SF3B1, PI3KCA and PTEN. We define diverse processes contributing to the mutational repertoire, including kataegis and somatic hypermutation. Most cases have at least one cluster of subclonal variants, including subclonal driver mutations, implying on-going tumor evolution. Serial samples revealed diverse patterns of clonal evolution, including linear evolution, differential clonal response and branching evolution. Our findings reveal the myeloma genome to be heterogeneous across patients and, within individual patients, to exhibit diversity in clonal admixture and dynamics in response to therapy.

  Dataset EGAD00001000339

• Frequent mutation of the major cartilage collagen gene, COL2A1, in chondrosarcoma

  Chondrosarcoma (CHS) is a heterogeneous collection of malignant bone tumours and is the second most common primary malignancy of bone after osteosarcoma. Recent work has identified frequent, recurrent mutations in IDH1/2 in nearly half of central CHS. However, there has been little systematic genomic analysis of this tumour type and thus the contribution of other genes is unclear. Here we report comprehensive genomic analyses of 49 cases of CHS. We identified hypermutability of the major cartilage collagen COL2A1 with insertions, deletions and rearrangements identified in 37% of cases. The patterns of mutation were consistent with selection for variants likely to impair normal collagen biosynthesis. In addition we identified mutations in IDH1/2 (59%), TP53 (20%), the RB1 pathway (27%) and hedgehog signaling (22%).

  Dataset EGAD00001000358

• The genomic architecture of mesothelioma

  The genome-wide landscape of somatically acquired mutations in mesothelioma has not been deeply characterised to date, but advances in DNA sequencing technology now allow this to be addressed comprehensively. Harnessing massively parallel DNA sequencing platforms, we will identify somatically acquired point mutations in all coding regions of the genome from patients with mesothelioma. In addition, using paired-end sequencing, we will map copy number changes and genomic rearrangements from the same patients.

  Dataset EGAD00001000360

• Targeted gene fusion sequencing (Fus-seq) in mesothelioma

  This is a small pilot data set to test the feasibility of cDNA exomes across 1200 cancer cell line panel. cDNA exomes or Fus-seq is further explained in this studies Abstract.

  Dataset EGAD00001000361

• A common single nucleotide variant in T is strongly associated with chordoma

  Chordoma is a rare malignant bone tumor that expresses the transcription factor T. We conducted an association study of 40 patients with chordoma and 358 ancestry-matched, unaffected individuals with replication in an independent cohort. Whole-exome and Sanger sequencing of T exons reveals a strong risk association ( allelic odds ratio (OR) = 4.9, P = 3.3x10-11, CI= 2.9-8.1) with the common (minor allelic frequency >5%) non-synonymous SNP rs2305089 in chordoma, which is exceptional in cancer genetics.

  Dataset EGAD00001000226

• Melanoma-TIL Study Exomes

  Melanoma-TIL Study Exomes

  Dataset EGAD00001000243

• Integrative Oncogenomics of multiple myeloma

  Integrative Oncogenomics of multiple myeloma

  Dataset EGAD00001000246

• Integrative Oncogenomics of multiple myeloma

  Integrative Oncogenomics of multiple myeloma

  Dataset EGAD00001000247

• DATA FILES FOR SJRB

  Retinoblastoma whole genome sequencing

  Dataset EGAD00001000261

• Chondrosarcoma Targeted Sequencing Study

  This Study uses a focused bespoke bait pull down library method to target findings of Chondrosarcoma whole genome and whole exome sequencing studies in order to validate findings. This method will also be used on a larger set of tumour only samples in order to find precedence of these findings in a larger set of patient samples.

  Dataset EGAD00001000265

• Osteosarcoma Targeted Sequencing Study

  This Study uses a focused bespoke bait pull down library method to target findings of Osteosarcoma whole genome and whole exome sequencing studies in order to validate findings. This method will also be used on a larger set of tumour only samples in order to find precedence of these findings in a larger set of patient samples.

  Dataset EGAD00001000266

• Chordoma Targeted Sequencing Study

  This Study uses a focused bespoke bait pull down library method to target findings of Chordoma whole genome and whole exome sequencing studies in order to validate findings. This method will also be used on a larger set of tumour only samples in order to find precedence of these findings in a larger set of patient samples.

  Dataset EGAD00001000267

• Pilot study Pilocytic Astrocytoma ICGC PedBrain, whole genome sequencing of 5 tumors and matched blood

  Pilot study Pilocytic Astrocytoma ICGC PedBrain, whole genome sequencing of 5 tumors and matched blood

  Dataset EGAD00001000271

• Meningioma Targeted Sequencing Study

  This Study uses a focused bespoke bait pull down library method to target findings of Meningioma whole genome and whole exome sequencing studies in order to validate findings. This method will also be used on a larger set of tumour only samples in order to find precedence of these findings in a larger set of patient samples.

  Dataset EGAD00001000273

• Identifying Novel Fusion Genes in Myeloma

  Identifying Novel Fusion Genes in Myeloma

  Dataset EGAD00001000112

• Osteosarcoma Exome Sequencing

  Osteosarcoma Exome Sequencing

  Dataset EGAD00001000118

• Chordoma Exome Sequencing

  Chordoma Exome Sequencing

  Dataset EGAD00001000119

• DATA_SET_ICGC_PedBrainTumor_Medulloblastoma

  DATA_SET_ICGC_PedBrainTumor_Medulloblastoma

  Dataset EGAD00001000122

• Chondrosarcoma Exome

  Chondrosarcoma Exome

  Dataset EGAD00001000125

• Burden of Disease in Sarcoma

  Burden of Disease in Sarcoma

  Dataset EGAD00001000127

• Genetic landscape of hepatocellular carcinoma

  Genetic landscape of hepatocellular carcinoma

  Dataset EGAD00001000131

• Driver mutations in histone H3.3 and chromatin remodelling genes in paediatric glioblastoma

  Sequence reads for pediatric GBM samples for manuscript: Driver mutations in histone H3.3 and chromatin remodelling genes in paediatric glioblastoma

  Dataset EGAD00001000134

• DATA FILES FOR NBL

  Neuroblastoma whole genome sequencing

  Dataset EGAD00001000135

• Tumor sample of a serious ovarian carcinoma

  Tumor sample of a serious ovarian carcinoma

  Dataset EGAD00001000139

• Blood sample of serious ovarian carcinoma patient

  Blood sample of serious ovarian carcinoma patient

  Dataset EGAD00001000140

• Osteosarcoma Whole Genome

  Osteosarcoma Whole Genome

  Dataset EGAD00001000147

• Subgroup-specific structural variation across 1,000 medulloblastoma genomes

  Subgroup-specific structural variation across 1,000 medulloblastoma genomes

  Dataset EGAD00001000158

• Whole Genome Sequencing accompanying Genetic landscape of pediatric Rhabdomyosarcoma

  Whole Genome Sequencing accompanying Genetic landscape of pediatric Rhabdomyosarcoma.

  Dataset EGAD00001000164

• Exome sequencing identifies frequent mutation of the SWI/SNF complex gene PBRM1 in renal carcinoma

  Exome sequencing identifies frequent mutation of the SWI/SNF complex gene PBRM1 in renal carcinoma

  Dataset EGAD00001000001

• Osteosarcoma Sequencing

  Osteosarcoma Sequencing

  Dataset EGAD00001000007

• Familial Melanoma Sequencing

  Familial Melanoma Sequencing

  Dataset EGAD00001000016

• ICGC Germany PedBrain Medulloblastoma Pilot_2_LM

  ICGC Germany PedBrain Medulloblastoma Pilot_2_LM

  Dataset EGAD00001000027

• Pancreatic adenocarcinoma QCMG 20110901

  Pancreatic adenocarcinoma QCMG 20110901

  Dataset EGAD00001000049

• UK10K_RARE_COLOBOMA REL-2012-11-27

  UK10K_RARE_COLOBOMA REL-2012-11-27

  Dataset EGAD00001000307

• Whole genome sequencing of matched germline-tumour samples in follicular lymphoma

  Whole genome sequencing analysis was performed on 6 patients within matched germline, follicular lymphoma and transformed follicular lymphoma.

  Dataset EGAD00001000292

• Molecular characterization of invasive lobular carcinoma

  Invasive lobular carcinoma (ILC) is the second most common histological subtype of breast cancer accounting for 10-15% of cases. ILC differs from invasive ductal carcinoma (IDC)with respect to epidemiology, histology, and clinical presentation. Moreover, ILC is lesssensitive to chemotherapy, more frequently bilateral, and more prone to form gastrointestinal, peritoneal, and ovarian metastases than IDCs. In contrast to IDC, the prognostic value ofhistological grade (HG) in ILC is controversial. One of the three major components of histological grading (tubule formation) is missing in ILC which hinders the process of gradingin this histological subtype and results in the classification of approximately two thirds of ILC as HG 2.Over the last decade, a number of gene expression signatures have shed light onto breast cancer classification, allowing breast cancer care to become more personalized. Withrespect to the management of estrogen receptor (ER)-positive breast cancer, several gene expression signatures provide prognostic and/or predictive information beyond what is possible with current classical clinico-pathological parameters alone. Nevertheless, most studies using gene expression signature have not considered different histologic subtypesseparately. Recently, a comprehensive research program has elucidated some of the biological underpinnings of invasive lobular carcinoma. Genetic material extracted from 200 ILC tumor samples were studied using gene expression profiling and identified ILCmolecular subtypes. These proliferation-driven gene signatures of ILC appear to have prognostic significance. In particular, the Genomic Grade (GG) gene signature improved upon HG in ILC and added prognostic value to classic clinico-pathologic factors. In addition this study demonstrated that most ILC are molecularly characterized as luminal-A (~75%)followed by luminal-B (~20%) and HER2-positve tumors (~5%). Moreover, we investigated the prognostic value of known gene signatures/ gene modules in the same cohort of ILC. As a second step within the scope of this project, we aim to investigate the interactionsbetween somatic ILC tumor mutations to observed transcriptome findings. To this end, we aim to perform somatic mutation analysis for the ILC tumors for which Affymetrix gene expression profiling is available. To this end, we will use a gene screen assay, which specifically interrogates the mutational status of a few hundreds of cancer genes. We believe that this pioneering effort will be fundamental for a tailored treatment of ILC withimprovement in patients' outcome.

  Dataset EGAD00001000288

• Whole genome analyses of the childhood cancer neuroblastoma

  Neuroblastomas are tumors of peripheral sympathetic neurons and are the most common solid tumor in children. To determine the genetic basis for neuroblastoma we performed whole-genome sequencing (6 cases), exome sequencing (16 cases), genome-wide rearrangement analyses (32 cases), and targeted analyses of specific genomic loci (40 cases) using massively parallel sequencing. On average each tumor had 19 somatic alterations in coding genes (range, 3-70). Among genes not previously known to be involved in neuroblastoma, chromosomal deletions and sequence alterations of chromatin remodeling genes, ARID1A and ARID1B, were identified in 8 of 71 tumors (11%) and were associated with early treatment failure and decreased survival. Using tumor-specific structural alterations, we developed an approach to identify rearranged DNA fragments in sera, providing personalized biomarkers for minimal residual disease detection and monitoring. These results highlight dysregulation of chromatin remodeling in pediatric tumorigenesis and provide new approaches for the management of neuroblastoma patients.

  Dataset EGAD00001000282

• SCAT_Osteosarcoma_Validation

  This experiment is to validate putative somatic substitutions and indels identified in an exome screen of ~50 osteosarcoma tumour/normal pairs. It is the first stage in our ICGC commitment to study osteosarcoma. The validation process is an important component of our analysis to clarify the data prior to looking for evidence of new cancer genes, or subverted pathways important in the development of cancer. This data is part of a pre-publication release. For information on the proper use of pre-publication data shared by the Wellcome Trust Sanger Institute (including details of any publication moratoria), please see http://www.sanger.ac.uk/datasharing/

  Dataset EGAD00001000280

• Data set for Whole-genome-Sequencing of adult medulloblastoma

  Data set for Whole-genome-Sequencing of adult medulloblastoma

  Dataset EGAD00001000275

• UK10K_RARE_COLOBOMA REL-2012-07-05

  UK10K_RARE_COLOBOMA REL-2012-07-05

  Dataset EGAD00001000206

• Neuroblastoma samples (Analyses_vcf files)

  Neuroblastoma samples (Analyses_vcf files)

  Dataset EGAD00001000202

• Neuroblastoma samples

  Neuroblastoma samples

  Dataset EGAD00001000196

• UK10K_RARE_COLOBOMA REL-2012-01-13

  UK10K_RARE_COLOBOMA REL-2012-01-13

  Dataset EGAD00001000179

• Identification of SPEN as a novel cancer gene and FGFR2 as a potential therapeutic target in adenoid cystic carcinoma

  Identification of SPEN as a novel cancer gene and FGFR2 as a potential therapeutic target in adenoid cystic carcinoma

  Dataset EGAD00001000175

• UK10K_RARE_COLOBOMA REL-2012-02-22

  UK10K_RARE_COLOBOMA REL-2012-02-22

  Dataset EGAD00001000185

• SCAT osteosarcoma sequencing

  SCAT osteosarcoma sequencing

  Dataset EGAD00001000107

• Meningioma Exome

  Meningioma Exome

  Dataset EGAD00001000099

• Pancreatic adenocarcinoma QCMG 20120201

  Pancreatic adenocarcinoma QCMG 20120201

  Dataset EGAD00001000096

• Glioma cell lines rearrangement screen

  Glioma cell lines rearrangement screen

  Dataset EGAD00001000090

• Splenic Marginal Zone Lymphoma with villous lymphocytes exome sequencing

  Splenic Marginal Zone Lymphoma with villous lymphocytes exome sequencing

  Dataset EGAD00001000081

• Integrative Oncogenomics of Multiple Myeloma

  Integrative Oncogenomics of Multiple Myeloma

  Dataset EGAD00001000074

• Kaposi sarcoma exome

  Kaposi sarcoma exome

  Dataset EGAD00001000071

• Acral melanoma study whole genomes

  Acral melanoma study whole genomes

  Dataset EGAD00001000060

• Acral melanoma study whole exomes

  Acral melanoma study whole exomes

  Dataset EGAD00001000061

• EGAD00000000119

  Genotypes from cell lines derived from breast carcinoma tissue

  Dataset EGAD00000000119

• EGAD00000000114

  Whole transcriptome sequence data from 18 ovarian clear-cell carcinoma samples and one TOV21G ovarian clear-cell carcinoma cell line

  Dataset EGAD00000000114

• EGAD00000000052

  Sequencing data from natching Pancreatic Carcinoma samples

  Dataset EGAD00000000052

• EGAD00000000051

  Sequencing data from matching Renal Carcinoma samples

  Dataset EGAD00000000051

• Identification of gene mutations and fusion genes in patients with Sézary Syndrome

  Sezary syndrome (SS) is a leukemic form of cutaneous T-cell lymphoma (CTCL) with an aggressive clinical course. The goal of our study is to understand the genetic basis of the disease by looking for driver gene mutations and fusion genes in 15 erythrodermic patients with circulating Sezary cels, fourteen of them fulfilling the diagnostic criteria of SS. Peripheral blood samples were collected for each patient and CD4+ T-lymphocytes and Granulocytes were isolated. DNA and RNA was extracted for matched normal and tumor materials. Whole exome sequencing was performed on matched normal and tumor tissues of 12 patients and RNA sequencing was performed on 10 patients. For 7 of these patients, we have both exome as well as RNA sequencing data. In this study, we present a complex genomic landscape of Sezary syndrome with several point mutations, copy number variations and fusion events which could contribute to the pathogenesis of SS.

  Study EGAS00001001706

• Prognostic relevance of microenvironmental factors CD163 and CD8 combined with EZH2 and chromosome 18 gain in a validation cohort of follicular lymphoma patients of the Lunenburg Lymphoma Biomarker Consortium

  Background: In follicular lymphoma (FL), studies addressing the prognostic value of microenvironment-related immunohistochemical (IHC) markers and tumor cell-related genetic markers have yielded conflicting results, precluding implementation in practice. Therefore, the Lunenburg Lymphoma Biomarker Consortium (LLBC) performed a validation study for published markers. Methods: To maximize sensitivity, an end-of-spectrum design was applied for 122 uniformly immunochemotherapy-treated FL patients retrieved from international trials and registries; early failure (EF): progression or lymphoma-related death <2 years versus long remission: response duration of >5 years. IHC staining for T-cells and macrophages was performed on tissue microarrays from initial biopsy and scored with a validated computer-assisted protocol. Shallow whole-genome and deep targeted sequencing was performed on the same samples. Results: 96/122 cases with complete molecular and immunohistochemical data were included in the analysis. EZH2 wild-type (p=0.006), gain of chromosome 18 (p=0.002), low percentages of CD8+ cells (p=0.011) and CD163+ areas (p=0.038) were associated with EF. No significant differences in other markers were observed, thereby refuting previous claims on their prognostic significance. Conclusion: Using an optimized study design, this LLBC study validates wild-type EZH2 status, gain of chromosome 18, low percentages of CD8+ cells and CD163+ area as predictors of EF to immunochemotherapy in FL.

  Study EGAS00001002049

• MutWP1__CRUK_Grand_Challenge_Mutographs_of_Cancer__clear_cell_renal_cell_carcinoma

  The Mutographs project aims to advance our understanding of the causes of cancer through studies of mutational signatures. Led by Mike Stratton, together with Paul Brennan, Ludmil Alexandrov, Allan Balmain, David Phillips and Peter Campbell, this large-scale international research endeavour was awarded a Cancer Research UK Grand Challenge. Different patterns of somatic mutation are generated by the different environmental, lifestyle and genetic factors that cause cancer, many of them are still unknown. Within Mutographs, the International Agency for Research on Cancer is coordinating the recruitment of 5000 individuals with cancer (colorectal, renal, pancreatic, oesophageal adenocarcinoma or oesophageal squamous cancers) across 5 continents to explore whether different mutational signatures explain marked variation in incidence. In brief, through an international network of collaborators around the world, biological materials are collected, along with demographic, histological, clinical and questionnaire data. Whole genome sequences of tumour-germline DNA pairs are generated at the Wellcome Trust Sanger Institute. Somatic mutational signatures are subsequently extracted by non-negative matrix factorisation methods and correlated with risk factors data. Through an enhanced understanding of cancer aetiology, Mutographs unprecedented effort is anticipated to outline modifiable risk factors, lead to new approaches to prevent cancer, and provide opportunities to empower early detection, refine high-risk groups and contribute to further therapeutic development.

  Study EGAS00001002608

• Preferential infiltration of distinct Vγ9δ2 T cells into Glioblastoma multiforme

  Glioblastoma multiforme (GBM), the most fatal CNS cancer, is highly infiltrative as a result of phenotypic alteration of cancer cells mainly driven by a mutual interaction among cancer cells, tumor-associated macrophages (TAMs) and other stromal cells. This work aims at characterizing GBM-infiltrating γδ T cells that may regulate the GBM tumor microenvironment and cancer cell gene expression. V(D)J repertoires of tumor-infiltrating and blood circulating γδ T cells from 4 patients were analyzed by NGS-based TCR sequencing. RNA gene expression profiling and immunostaining of cancer tissues were performed as well.

  Study EGAS00001002790

• Pan-neuroblastoma analysis reveals age- and signature-associated driver alterations

  Neuroblastoma is a pediatric malignancy with heterogeneous clinical outcomes depending on age and other factors. To better understand neuroblastoma pathogenesis, here we analyze whole-genome, whole-exome and/or transcriptome sequencing data from 702 neuroblastoma samples, half of which are new data. Over 95% of samples harbor at least one recurrent driver alteration and most aberrations, including MYCN, ATRX, and TERT alterations, differ in frequency by age. MYCN alterations occur at median 2.3 years of age, TERT at 3.8 years, and ATRX at 5.6 years, suggesting age-specific susceptibility to genetic alterations. Mutational signature analysis shows that reactive oxygen-species (ROS)-induced mutations are the most common cause of single nucleotide variant (SNV) drivers in neuroblastoma, including most ALK and Ras pathway SNVs. ROS-induced mutagenesis is both an early event, as it causes truncal variants, and continuous as it also induces relapse-specific mutations. ROS-induced mutations are more abundant in neuroblastomas with MYCN amplification, 17q gains, and increased expression of mitochondrial ribosome genes. We observe recurrent FGFR1 N546K or internal tandem duplication variants in 6 patients and ALK N-terminal structural alterations in 5 samples, identifying additional patients amenable to precision therapy.

  Study EGAS00001003931

• Lindsey E. Jones et al. Patient-derived cells from recurrent tumors that model the evolution of IDH-mutant glioma. Neuro-Oncology Advances, 2020. We established robust, versatile, and well-characterized Patient Derived Cells (PDC) of an IDH1-mutant astrocytoma and an IDH1-mutant oligodendroglioma that represents defined evolutionary stages of chemotherapy-induced hypermutation. The PDCs retain tumor subtype defining features over time as well as classic hallmarks of cancer, including anchorage independent growth and cell immortality. The integrated phylogenies composed of PDCs,single-cell-derived PDCs, patient-derived xenografts, and corresponding spatiotemporal tumor tissue samples also provide new insight into the clonality, evolutionary pattern, and immense mutational load of hypermutated IDH mutant gliomas.

  IDH-mutant lower-grade gliomas can undergo malignant progression via temozolomide-driven hypermutation. Patient-derived cells (PDC) that model the genetically distinct hypermutated (HM) tumor subgroup are generally lacking, and few if any human brain tumor cell models are from defined evolutionary time points. Here, we characterize multiple PDC derived from independent surgical specimens of IDH1-mutant recurrences, including an ATRX and TP53-mutant astrocytoma and a 1p/19q co-deleted and TERT promoter-mutant oligodendroglioma. We determined the evolutionary time points represented by each PDC using exome sequencing and phylogenetic reconstruction, comparing the PDC and single cell clones of the PDC (scPDC) to multiple spatiotemporal tumor tissue samples, PDC-derived xenografts (PDX) and patient-matched blood. The tumor samples exhibited TMZ-induced mutagenesis and a branching pattern of evolution. We found clear evidence of two fully independent founder HM clones in the tumor tissue that are faithfully represented by independent PDC. The PDC, scPDC and PDX also shared the mutagenesis signature and represent the mid and later evolutionary time points of their corresponding tumors. The PDC maintained the tumor subtype-defining features over many passages, including heterozygosity of the IDH1 R132H mutation, production of 2-hydroxyglutarate (2-HG), and subtype-specific telomere maintenance mechanisms. The PDC from both tumors exhibited anchorage-independent growth in soft agar. The oligodendroglioma PDC formed infiltrative intracranial tumors with characteristic oligodendroglioma histology, initially with a long period to tumor formation. We conclude that the PDC, scPDC and PDX faithfully model the heterogeneous clonal origins of the corresponding tumor tissue. The multilevel analysis also provides new insight into the intratumoral heterogeneity and vast mutational load of HM glioma. The PDC from multiple evolutionary time points presented in the context of full clinical timelines may be useful to model evolution and intratumoral heterogeneity, important sources of therapeutic failure.

  Study EGAS00001003992

• The double-hit signature identifies double-hit diffuse large B-cell lymphoma with genetic events cryptic to FISH​

  High-grade B-cell lymphomas with MYC and BCL2 and/or BCL6 rearrangements (HGBL-DH/THs) include a group of diffuse large B-cell lymphomas (DLBCLs) with inferior outcomes after standard chemoimmunotherapy. We recently described a gene expression signature that identifies 27% of germinal center B-cell DLBCLs (GCB-DLBCLs) as having a double-hit-like expression pattern (DHITsig) and inferior outcomes; however, only half of these cases have both MYC and BCL2 translocations identifiable using standard breakapart fluorescence in situ hybridization (FISH). Here, 20 DHITsig+ GCB-DLBCLs apparently lacking MYC and/or BCL2 rearrangements underwent whole-genome sequencing. This revealed 6 tumors with MYC or BCL2 rearrangements that were cryptic to breakapart FISH. Copy-number analysis identified 3 tumors with MYC and 6 tumors with MIR17HG gains or amplifications, both of which may contribute to dysregulation of MYC and its downstream pathways. Focal deletions of the PVT1 promoter were observed exclusively among DHITsig+ tumors lacking MYC translocations; this may also contribute to MYC overexpression. These results highlight that FISH fails to identify all HGBL-DH/THs, while revealing a range of other genetic mechanisms potentially underlying MYC dysregulation in DHITsig+ DLBCL, suggesting that gene expression profiling is more sensitive for identifying the biology underlying poor outcomes in GCB-DLBCL.

  Study EGAS00001004285

• Clinical relevance of somatic copy-number alterations in plasma circulating tumor DNA from advanced EGFR-mutated NSCLC patients treated with osimertinib

  Background: Somatic copy-number alterations (SCNAs) are associated with drug resistance in patients with advanced epidermal growth factor receptor (EGFR)-mutated non-small cell lung cancer (NSCLC) treated with EGFR-tyrosine kinase inhibitors (TKIs). The purpose of our study was to assess the clinical relevance and development of genome-wide SCNAs in plasma circulating tumor DNA (ctDNA) under osimertinib therapy.Methods: We included 43 patients with advanced EGFR T790M-positive lung adenocarcinoma who were treated with osimertinib after progression under previous EGFR-TKI therapy. We performed genomic profiling of ctDNA in plasma samples from each patient obtained pre-osimertinib and after patients developed resistance to osimertinib. SCNAs were detected by shallow whole-genome plasma sequencing and EGFR mutations were assessed by droplet digital PCR.Results: SCNAs in resistance-related genes (rrSCNAs) were detected in 10 out of 39 (25.6%) evaluable patients before start of osimertinib. The presence of rrSCNAs in plasma before initiation of osimertinib therapy was associated with a lower response rate to osimertinib (50% versus 86%, p=0.02) and was an independent predictor for shorter progression-free survival (adjusted HR 3.26, 95% CI 1.37-7.75, p=0.008) and overall survival (adjusted HR 2.41, 95% CI 1.09-5.34, p=0.03).Conclusions: Genomic profiling of plasma ctDNA is clinically relevant and affects the efficacy and clinical outcome of osimertinib. Our approach allows comprehensive assessment of SCNAs in plasma samples of lung adenocarcinoma patients and may help to guide genotype-specific therapeutic strategies in the future.

  Study EGAS00001004539

• OpACIN-neo – A Multicenter Phase 2 Study to identify the Optimal neo-Adjuvant Combination scheme of Ipilimumab and Nivolumab – Whole exome sequencing

  The outcome of patients with macroscopic stage III melanoma is poor. Neoadjuvant treatment with ipilimumab plus nivolumab at the standard dosing schedule induced pathological responses in a high proportion of patients in two small independent early-phase trials. However, toxicity of the standard ipilimumab plus nivolumab dosing schedule was high, preventing its broader clinical use. The aim of the OpACIN-neo study (NCT02977052) to identify a dosing schedule of ipilimumab plus nivolumab that is less toxic but equally effective. 86 patients with macroscopic stage III melanoma were randomised to one of three dosing schedules: arm A, two cycles of ipilimumab 3 mg/kg plus nivolumab 1 mg/kg once every 3 weeks; arm B, two cycles of ipilimumab 1 mg/kg plus nivolumab 3 mg/kg once every 3 weeks; or arm C, two cycles of ipilimumab 3 mg/kg once every 3 weeks directly followed by two cycles of nivolumab 3mg/kg once every 2 weeks. Within the first 12 weeks, grade 3–4 immune-related adverse events were observed in 12 (40%) of 30 patients in group A, six (20%) of 30 in group B, and 13 (50%) of 26 in group C. Pathological responses occurred in 24 (80%) patients in group A, 23 (77%) in group B, and 17 (65%) in group C. The 2-year estimated relapse-free survival was 84% for all patients, 97% for patients achieving a pathologic response and 36% for nonresponders (p<0.001). High tumor mutational burden (TMB) and high interferon-gamma-related gene expression signature score (IFN-γ score) were associated with pathologic response and low risk of relapse; pathologic response rate (pRR) was 100% in patients with high IFN-γ score/high TMB, patients with high IFN-γ score/low TMB or low IFN-γ score/high TMB had pRRs of 91% and 88%; while patients with low IFN-γ score/low TMB had a pRR of only 39%. These data demonstrate long-term benefit in patients with a pathologic response and show the predictive potential of TMB and IFN-γ score.

  Study EGAS00001004832

• OpACIN-neo – A Multicenter Phase 2 Study to identify the Optimal neo-Adjuvant Combination scheme of Ipilimumab and Nivolumab – RNA sequencing

  The outcome of patients with macroscopic stage III melanoma is poor. Neoadjuvant treatment with ipilimumab plus nivolumab at the standard dosing schedule induced pathological responses in a high proportion of patients in two small independent early-phase trials. However, toxicity of the standard ipilimumab plus nivolumab dosing schedule was high, preventing its broader clinical use. The aim of the OpACIN-neo study (NCT02977052) to identify a dosing schedule of ipilimumab plus nivolumab that is less toxic but equally effective. 86 patients with macroscopic stage III melanoma were randomised to one of three dosing schedules: arm A, two cycles of ipilimumab 3 mg/kg plus nivolumab 1 mg/kg once every 3 weeks; arm B, two cycles of ipilimumab 1 mg/kg plus nivolumab 3 mg/kg once every 3 weeks; or arm C, two cycles of ipilimumab 3 mg/kg once every 3 weeks directly followed by two cycles of nivolumab 3mg/kg once every 2 weeks. Within the first 12 weeks, grade 3–4 immune-related adverse events were observed in 12 (40%) of 30 patients in group A, six (20%) of 30 in group B, and 13 (50%) of 26 in group C. Pathological responses occurred in 24 (80%) patients in group A, 23 (77%) in group B, and 17 (65%) in group C. The 2-year estimated relapse-free survival was 84% for all patients, 97% for patients achieving a pathologic response and 36% for nonresponders (p<0.001). High tumor mutational burden (TMB) and high interferon-gamma-related gene expression signature score (IFN-γ score) were associated with pathologic response and low risk of relapse; pathologic response rate (pRR) was 100% in patients with high IFN-γ score/high TMB, patients with high IFN-γ score/low TMB or low IFN-γ score/high TMB had pRRs of 91% and 88%; while patients with low IFN-γ score/low TMB had a pRR of only 39%. These data demonstrate long-term benefit in patients with a pathologic response and show the predictive potential of TMB and IFN-γ score.

  Study EGAS00001004833

• Assessment of cannabidiol and Δ9-tetrahydrocannabiol in mouse models of medulloblastoma

  Phytocannabinoids Δ9-tetrahydrocannabinol (THC) and cannabidiol (CBD) have been demonstrated to exhibit anti-cancer activity in preclinical models of brain cancer leading to new clinical trials for adults with glioblastoma. We describe here the first report that has investigated a role for THC and CBD in paediatric brain cancer. Cannabinoids had cytotoxic activity against medulloblastoma and ependymoma cells in vitro, functioning in part through the inhibition of cell cycle progression and the induction of autophagy. Despite these effects in vitro, when tested in orthotopic mouse models of medulloblastoma or ependymoma, no impact on animal survival was observed. Furthermore, cannabinoids neither enhanced nor impaired conventional chemotherapy in a medulloblastoma mouse model. These data show that while THC and CBD do have some effects on medulloblastoma and ependymoma cells, are well tolerated and have minimal adverse effects, they do not appear to elicit any survival benefit in preclinical models of paediatric brain cancer.

  Study EGAS00001004963

• Molecular characterization of Barrett’s esophagus at single cell resolution

  Backgrounds & Aims: Patient with Barrett’s esophagus (BE) have an increased risk to develop esophageal adenocarcinoma and are under periodical endoscopic surveillance for malignant transformation. Pathologists distinguish between different BE stages to identify high-risk patients, but this process remains difficult as stage-specific markers are still missing. We established BE organoid cultures, applied single cell sequencing approaches to identify differences in gene expression and genomic alterations, and validated candidate genes for their predictive value on histological sections. Methods: We collected 43 epithelial biopsies from 21 patients, established organoids for the clonal expansion of matching healthy and diseased tissue from two patients to identify genomic alterations by whole genome sequencing (WGS). We performed single cell DNA-sequencing (scDNAseq) to analyse DNA alterations within biopsies from 8 patients and single cell RNA-sequencing (scRNAseq) to identify gene expression differences between BE stages from 19 patients. Candidate marker genes were then validated by RNA in situ hybridization experiments on histological resection specimen. Results: Most BE biopsies were chromosomal stable (CS) and their single base substitution (SBS) signatures were indistinguishable from the healthy control tissues. Dysplastic BE cells contained areas of chromosomal instabilities (CIN), which differed by the presence of the SBS17 signatures from biopsy-matching CS cells or patient-matching healthy control cells. Such CIN areas affected efficient clustering of the scRNAseq data. We identified two sets of marker genes (SLC5A5, PSCA, LIPF and ANPEP, CEACAM6, REG4), which distinguish columnar BE epithelium from non-dysplastic/dysplastic stages. CLDN2 allowed the distinction between dysplastic and more advanced stages as its expression level increased and spread in dysplastic BE glands. Conclusions: Molecular characterization of BE samples identified a correlation between the presence of CIN and COSMIC signature 17, and we report seven marker genes that help in distinguishing different BE stages.

  Study EGAS00001005221

• Sequential single-cell transcriptional and protein marker profiling reveals TIGIT as a marker of CD19 CAR-T cell dysfunction in patients with non-Hodgkin’s lymphoma

  Employed single cell RNA sequencing and protein surface marker profiling of serialCAR-T cell samples from patients with non-Hodgkin’s lymphoma (NHL) to reveal CAR-T cell evolution, identify biomarkers of response, and test for evidence of exhaustion inCAR-T cells of poor responders. At the transcriptional and protein levels, we note the evolution of CAR-T cells toward a non-proliferative, highly-differentiated, andexhausted state that is enriched in CAR-T cells of patients with poor response.Furthermore, we identified the checkpoint receptor TIGIT as a novel prognosticbiomarker and potential driver of CAR-T cell exhaustion.

  Study EGAS00001005356

• Genome-wide cell-free DNA termini in patients with cancer

  The structure, fragmentation pattern, length and terminal sequence of cell-free DNA (cfDNA) is under the influence of nucleases present in the blood. We hypothesized that differences in the diversity of bases at the end of cfDNA fragments can be leveraged on a genome-wide scale to enhance the sensitivity for detecting the presence of tumor signals in plasma. We surveyed the cfDNA termini in 72 plasma samples from 319 patients with 18 different cancer types using low-coverage whole genome sequencing. The fragment-end sequence and diversity were altered in all cancer types in comparison to 76 healthy controls. We converted the fragment end sequences into a quantitative metric and observed that this correlates with circulating tumor DNA tumor fraction (R = 0.58, p < 0.001, Spearman). Using these metrics, we were able to classify cancer samples from control at a low tumor content (AUROC of 91% at 1% tumor fraction) and shallow sequencing coverage (mean AUROC = 0.99 at >1M fragments). Combining fragment-end sequences and diversity using machine learning, we classified cancer from healthy controls (mean AUROC = 0.99, SD = 0.01). Using unsupervised clustering we showed that early-stage lung cancer can be classified from control or later stages based on fragment-end sequences. We observed that fragment-end sequences can be used for prognostication (hazard ratio: 0.49) and residual disease detection inresectable esophageal adenocarcinoma patients, moving fragmentomics toward a greater clinical implementation.

  Study EGAS00001005738

• Genome-wide cell-free DNA termini in patients with cancer

  The structure, fragmentation pattern, length and terminal sequence of cell-free DNA (cfDNA) is under the influence of nucleases present in the blood. We hypothesized that differences in the diversity of bases at the end of cfDNA fragments can be leveraged on a genome-wide scale to enhance the sensitivity for detecting the presence of tumor signals in plasma. We surveyed the cfDNA termini in 72 plasma samples from 319 patients with 18 different cancer types using low-coverage whole genome sequencing. The fragment-end sequence and diversity were altered in all cancer types in comparison to 76 healthy controls. We converted the fragment end sequences into a quantitative metric and observed that this correlates with circulating tumor DNA tumor fraction (R = 0.58, p < 0.001, Spearman). Using these metrics, we were able to classify cancer samples from control at a low tumor content (AUROC of 91% at 1% tumor fraction) and shallow sequencing coverage (mean AUROC = 0.99 at >1M fragments). Combining fragment-end sequences and diversity using machine learning, we classified cancer from healthy controls (mean AUROC = 0.99, SD = 0.01). Using unsupervised clustering we showed that early-stage lung cancer can be classified from control or later stages based on fragment-end sequences. We observed that fragment-end sequences can be used for prognostication (hazard ratio: 0.49) and residual disease detection inresectable esophageal adenocarcinoma patients, moving fragmentomics toward a greater clinical implementation.

  Study EGAS00001005747

• Combination of ribociclib and gemcitabine for the treatment of medulloblastoma

  Group 3 (G3) medulloblastoma (MB) is one of the deadliest forms of the disease for which novel treatment is desperately needed. Here we evaluate ribociclib, a highly selective CDK4/6 inhibitor, with gemcitabine in mouse and human G3 MBs. Ribociclib CNS penetration was assessed by in vivo microdialysis and by immunohistochemistry and gene expression studies. Survival studies to determine the efficacy of ribociclib and gemcitabine combination were performed on mice orthotopically implanted with luciferase labelled mouse and human G3 MB. Pharmacokinetic-pharmacodynamic outcomes and univariable survival models were analyzed to estimate survival. Gene activity inference using NetBID and tumor differentiation analysis investigated the effects of the combination after short and long-term treatments. Tumors from mice treated with oral ribociclib displayed inhibited RB phosphorylation, downregulated E2F target genes, and decreased proliferation. Treatment of mice with the combination of ribociclib and gemcitabine was well tolerated, slowed tumor progression and metastatic spread, and increased survival. Molecular analysis of treated versus untreated tumors showed a significant decrease in the activity and expression of genes involved in cell cycle progression and DNA damage response, and an increase in activity and expression of genes implicated in neuronal identity and neuronal differentiation. Ribociclib is CNS-penetrant. When administered/combined with gemcitabine in orthotopic G3 MB models resulted in improved survival. Our findings, with both mouse and human patient-derived-orthotopic xenograft models, suggest that this combination therapy has promise for children with G3 MB and may represent an effective treatment strategy for other CNS malignancies.

  Study EGAS00001006001

• early-stage ESCC sequencing study

  We performed a comprehensive multi-omics analysis of 786 trace-tumor-samples from 154 esophageal squamous cell carcinoma phase (ESCC) patients, covering 9 histopathological stages in 3 phases as nontumor phase (NT phase), intraepithelial neoplasia phase (IEN phase), and ESCC phase. Proteogenomics elucidated the stage-specific molecular characterization and defined the cancer-driving waves along with the mutation accumulation in EC progression. The integrated multi-omics uncovered the chromosome 3q gain was the key event in the transmit from the NT to IEN phase, disclosed the top mutation of TP53 enhanced cell cycle and DNA replication in the IEN phase, and revealed the ESCC phase mutations of AKAP9 and MCAF1 elevated glycolysis and Wnt signaling, respectively. Furthermore, the trajectory analysis identified 6 major tracks related to different clinical features during ESCC progression. Growingly enhanced and hyperphosphorylated phosphoglycerate kinase 1 (PGK1, S203) was detected and considered as a drug target in ESCC progression. Collectively, this study provides insight into the understanding of ESCC molecular mechanism and a valuable resource for the development of therapeutic targets.

  Study EGAS00001006126

• Genome-wide cell-free DNA termini in patients with cancer

  The structure, fragmentation patterns and terminal sequences of cell-free DNA (cfDNA) are altered by nucleases and biological mechanisms in the blood of cancer patients. The cfDNA fragment-end composition recovered from low coverage WGS (<1 fold coverage) using a bespoke software (FrEIA) is aberrant in the plasma from cancer patient (n = 418, 655 samples) compared to controls (n = 117). As a standalone test FrEIA allows detection down to ~0.2% tumor fraction in vitro and in silico at 95% specificity, leading to a sensitivity of ~71% for detecting lung cancer (14/22 stage I-II, 27/38 stage III, 92/127 stage IV) and ~68% for detecting esophageal adenocarcinoma (26/44 stage II, 46/62 stage III). Additional cfDNA biological patterns can be combined with FrEIA increasing the diagnostic potential of low coverage WGS at minimal cost (mean AUROC = 0.96). Integrating multiple cfDNA biological signal augments the diagnostic performance of liquid biopsy.

  Study EGAS00001006142

• Multi-organ landscape of therapy-resistant melanoma

  Metastasis and failure of present-day therapies represent the most common causes of mortality in patients with cutaneous melanoma. To identify the underlying genetic and transcriptomic landscapes, here we analyzed multi-organ metastases and tumor-adjacent tissues from eleven rapid autopsies after treatment with MAPK inhibitor (MAPKi) and/or immune checkpoint blockade (ICB) and death due to acquired resistance. Either treatment elicits shared genetic alterations that suggest immune-evasive, cross-therapy resistance mechanisms. Large, non-clustered deletions, inversions, and inter-chromosomal translocations dominate rearrangements. Using 345 therapy-naïve TCGA melanoma and 131 patient-matched melanoma pre-and-post acquired resistance to only either treatment, we performed cross-cohort analyses to identify MAPKi and ICB as respective contributors to gene amplifications and deletions enriched in autopsy versus therapy-naïve tumors. Private/late mutations and structural variants display shifted mutational and rearrangement signatures, with MAPKi specifically selecting for signatures of defective homologous-recombination, mismatch, and base-excision repair. Transcriptomic signatures and cross-talks with tumor-adjacent macroenvironments nominate organ-specific adaptive pathways. An immune-desert, CD8+-macrophage-biased archetype, T-cell exhaustion, and type-2 immunity characterize the immune contexture. This multi-organ analysis of lethal, therapy-resistant melanoma presents preliminary insights with potential to improve therapeutic strategies.

  Study EGAS00001006644