5495 results for "*oma"

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• Integrative Multi-Omics and Drug Sensitivity Profiling Reveals Potential Predictive Biomarkers in Pediatric Solid Tumors from the INFORM Registry

  Cure rates for childhood malignancies using established therapy protocols have increased to an average of 80% but have reached a plateau. Moreover, survival rates are particularly low for some pediatric tumors (such as high-risk Group3 medulloblastomas, osteosarcomas, Ewing sarcomas, high-risk neuroblastomas and high-grade gliomas) and dismal for patients with relapsed malignancies. A functional drug response profiling platform for pediatric solid and brain tumors has been established within the INFORM program to identify patient-specific vulnerabilities, biomarkers and unravel molecular mechanisms associated with drug response profiles for clinical translation. Here, we perform a multi-omics analysis using drug sensitivity profiles, genomic, and transcriptomic data of 81 pediatric solid tumor samples. The integrative analysis revealed two multi-omics signatures with high drug sensitivity predictivity. One signature highlighted neuroblastoma samples with sensitivity to navitoclax (a BCL-2 family inhibitor). A second signature was significantly specific to a subset of Wilms tumors harboring the SIX1 (Q177R) hotspot mutation, which had high expression of MGAM, PTPN14, STAT4 and KDM2B and high sensitivity to MEK inhibitors. A patient-specific causal interaction network analysis elucidated the potential biological mechanism of action between MEK inhibitors and the SIX1 mutation in n = 6 Wilms tumor samples.

  Study EGAS00001008249

• Whole exome sequencing data for paired non-serous endometrial and ovarian carcinomas from 27 patients with concurrent tumours.

  Introduction: Concurrent non-serous endometrial and ovarian tumours are often managed clinically as two separate primary tumours, but almost all exhibit evidence of a genomic relationship. Methodology: This study investigates the extent of relatedness using whole exome sequencing, which was performed on paired non-serous endometrial and ovarian carcinomas from 27 patients with concurrent tumours in a cohort with detailed clinicopathological annotation. Four whole exome sequencing-derived parameters (mutation, mutational burden, mutational signatures and mutant allele tumour heterogeneity scores) were used to develop a novel unsupervised model for the assessment of genomic similarity to infer genomic relatedness of paired tumours. Results: This novel model demonstrated genomic relatedness across all four parameters in all tumour pairs. Mutations in PTEN, ARID1A, CTNNB1, KMT2D and PIK3CA occurred most frequently and 24 of 27 (89 %) tumour pairs shared identical mutations in at least one of these genes, with all pairs sharing mutations in a number of other genes. Ovarian endometriosis, CTNNB1 exon 3 mutation, and progression and death from disease were present across the similarity ranking. Mismatch repair deficiency was associated with less genomically similar pairs. Discussion: Although there was diversity across the cohort, the presence of genomic similarity in all paired tumours supports the hypothesis that concurrent non-serous endometrial and ovarian carcinomas are genomically related and may have arisen from a common origin. Keywords: Co-existing; Concurrent; Endometrial carcinoma; Genomics; Mutation; Ovarian carcinoma; Paired tumours; Tumour mutational burden.

  Study EGAS00001008259

• Patient-derived pediatric brain tumor organoids faithfully recapitulate primary tumors

  Extensive molecular analysis by many groups has revealed a heterogeneous landscape of embryonal brain tumors, including medulloblastoma (MB) and atypical teratoid/rhabdoid tumor (ATRT). MB, the most common malignant pediatric brain tumor, is comprised of four molecularly distinct subgroups: Wingless (WNT), Sonic Hedgehog (SHH), Group 3 (G3), and Group 4 (G4). Among these, MB-SHH harboring MYCN amplification and TP53 mutation and MB-G3 with MYC overexpression or amplification constitute the most aggressive tumors, have the poorest clinical outcomes, and lack effective therapeutic options for recurrent disease. Here we describe the establishment of tumor organoid (TO) models from patient-derived orthotopic xenografts (PDOX) of MYCN-amplified and TP53-mutant MB-SHH, MYC-amplified MB-G3 and two ATRT which all grew in mice when reimplanted into the cortices of naïve recipient animals (TOX). Methylation, bulk and single-cell RNA sequencing, and whole genome sequencing demonstrated that TOs and TOXs faithfully recapitulated the molecular landscape and heterogeneity of PDOXs and primary patient tumors compared to established cell lines. The development of TOs will facilitate in vitro high-throughput drug or CRISPR screens without the need for use tumor-bearing mice. This will also accelerate the identification and validation of new vulnerabilities and in vivo preclinical testing toward clinical trials.

  Study EGAS00001008305

• Transcriptional and translational alterations induced by BET protein inhibition and its combination with Omaveloxolone in acute myeloid leukemia

  The inhibition of bromodomain and extra-terminal domain (BET) protein family achieved promising preclinical results as epigenetic therapy in acute myeloid leukemia (AML). However, clinical data showed a limited activity of bromodomain inhibitor (BETi) as single agent. We aimed to investigate the role of hypoxia in the response of AML cells to BET inhibition in order to identify a novel therapeutic combination targeting leukemia stem-progenitor cells (LSPCs) in their niche. BETi maintained an anti-proliferative and pro-apoptotic activity at low oxygen concentration by modulating the leukemic transcriptional, translational and metabolic programs towards reduced ribosome biogenesis, altered polyamine metabolism and activation of a TNF- via NF-B signature at translational level, especially in hypoxic conditions. Accordingly, Omaveloxolone, a clinical-stage NF-B inhibitor and NFR2 activator approved for Friedreich’s ataxia, significantly enhanced the efficacy of BETi against AML cell lines in hypoxia and normoxia by reducing cell viability and enhancing apoptosis. At molecular level, the drug combination converged to the downregulation of MYC, the DNA replication and oxidative phosphorylation signatures while forcing the expression of antioxidant genes. Overall, the combination of BETi and Oma disrupts key metabolic and transcriptional programs essential to AML cell survival and LSPC maintenance in the hypoxic microenvironment.

  Study EGAS00001008404

• Sensitive detection of MYCN amplified neuroblastoma in blood samples with structural variants using whole genome sequencing

  MYCN high amplification in neuroblastoma indicates a high-risk diagnosis. Although this feature is routinely detected using tumor whole genome sequencing followed by copy number analysis, it remains unclear whether MYCN amplification can be detected in blood samples. Leveraging on recent progress in the error profiling of structural alterations (SVs), we hypothesize that copy number analysis coupled with SV detection can enable sensitive detection of MYCN amplification in blood samples. By using childhood neuroblastoma cohorts from three institutions, we demonstrate that standard whole genome sequencing (30-100X) of blood samples enables detection of MYCN amplification in 64% of cases with limit of detection as low as 0.01% and SV markers are superior to conventional copy number markers. Further, we demonstrate that buccal samples collected at diagnosis are less affected by circulating tumor DNAs for MYCN amplified neuroblastoma. Together, our findings indicate the power of SV analysis in liquid biopsies to ascertain high risk MYCN amplified neuroblastoma.

  Study EGAS00001008441

• Single-nucleus sequencing of fresh-frozen large cell neuroendocrine carcinoma

  High-grade pancreatic neuroendocrine carcinoma (panNEC) is a rare, aggressive cancer with limited tissue availability. Single-nucleus transcriptomics of five large-cell panNECs revealed two interesting neuroendocrine cell states: one highly proliferative with an aberrant brain-specific neuronal differentiation program and another stress-responsive state enriched for heat stress, hypoxia, and glycolysis. Our findings suggest potential therapeutic vulnerabilities, highlighting the need to evaluate the efficacy of combination therapies.

  Study EGAS00001008449

• Whole-blood RNA-seq in AtezoBev-treated HCC

  This dataset contains RNA-sequencing BAM files generated from paired whole-blood RNA samples collected from patients with advanced hepatocellular carcinoma treated with first-line atezolizumab–bevacizumab immunotherapy. Samples were collected at baseline before the first infusion (T0) and immediately prior to the second infusion (T1). The dataset includes paired longitudinal samples from 24 patients, comprising 13 responders and 11 progressors. RNA sequencing was performed by Novogene using a GlobinClear-based non-directional mRNA library preparation strategy. These data support transcriptomic analyses of circulating immune activation, treatment response and resistance mechanisms under atezolizumab–bevacizumab therapy.

  Study EGAS00001008486

• Preclinical trial supports dual inhibition of BCL2 and aurora kinase for MYCN-amplified high-risk neuroblastoma

  Half of all children with high-risk neuroblastoma experience relapse or have refractory disease. These children lack effective options, and few survive beyond 5 years. The BCL2 inhibitor venetoclax, combined with cyclophosphamide/topotecan, has clinical activity in relapsed and refractory neuroblastoma, however with severe treatment-emergent adverse events. Combination drug screening in patient-derived models identified approved drugs synergistic with venetoclax, including the aurora kinase inhibitor alisertib. We assessed venetoclax-alisertib in 22 diverse neuroblastoma PDX models using an n=1 clinical trial-like design. Venetoclax-alisertib induced objective response in all models but was particularly effective in models of MYCN-amplified disease (n=12), doubling median survival time compared to cyclophosphamide/topotecan, and outperforming venetoclax/cyclophosphamide/topotecan. The efficacy of venetoclax-alisertib was maintained with discontinuous schedules, minimizing hematological toxicity without substantially compromising activity. Venetoclax-alisertib was strikingly effective with anti-GD2 immunotherapy, allowing long-term survival of PDX-engrafted animals. Our findings support advancement of venetoclax-alisertib to clinical trial for neuroblastoma with or without anti-GD2 immunotherapy.

  Study EGAS00001008494

• Spatial Omics Resolves Adrenergic and Mesenchymal Cell States in Neuroblastoma

  Neuroblastoma is a pediatric cancer arising from the developing sympathoadrenal lineage. Although cell lines derived from neuroblastoma patients have features of either adrenergic (ADRN) or mesenchymal (MES) cells, identifying MES cells in patient tumors is challenging and controversial. Here, to characterize intra- and inter-patient cellular heterogeneity, we analyze 54 neuroblastoma tumors spanning broad clinical, genetic, and histologic features using single-cell/single-nucleus RNA-sequencing (sc/snRNA-seq), bulk RNA-sequencing, spatial transcriptomics, and spatial proteomics. We show that tumor cells occupy distinct cellular neighborhoods separated from nonmalignant immune and stromal cells, yet established cell line-derived gene expression signatures fail to identify MES neuroblastoma cells. We therefore develop ADRN/MES signatures from early passage orthotopic patient-derived xenografts, enabling identification of MES tumor cells, validated by transcriptomic, epigenomic, proteomic, ultrastructural and functional assays. In patients, high MES gene expression correlates with worse event-free and overall survival. Together, this study provides a framework for defining clinically relevant neuroblastoma cell states.

  Study EGAS00001008537

• The ITCC-P4 PDX platform of pediatric cancers for preclinical testing

  Cancer is the leading cause of disease-related deaths among children in high-income countries. Tumor heterogeneity and lack of mechanism-of-action-based therapeutic options are key challenges to overcome in order to improve pediatric cancer patients’ survival. Here, we report the EU-IMI-2 funded public-private partnership “ITCC-Pediatric Preclinical Proof-of-Concept Platform” (ITCC-P4), which has built a large repertoire of patient-derived xenograft (PDX) models, representing all major solid pediatric cancer types, for in vivo drug testing. Three-hundred-fifty-three PDX models from diagnostic and relapsed pediatric cancers have been established and molecularly characterized, together with matched germline/tumor samples. As proof-of-concept, we present in vivo drug screening data in neuroblastoma and rhabdomyosarcoma models. PDX data, accessible at http://r2platform.com/itcc-p4, allow the selection of models based on oncogenic drivers and/or potential biomarkers for preclinical testing. Operated by a non-profit entity (www.itccp4.com), this sustainable platform aids academic and industrial researchers in developing and prioritizing innovative therapies for pediatric cancer.

  Study EGAS00001008330

• Single-cell characterization of anti-LAG3+anti-PD1 treatment in melanoma patients

  Study EGAS00001005580

• Single-cell study of 14 childhood medulloblastoma patients

  Study EGAS00001006392

• Targeted Sequencing of Tumor-Normal pairs from advanced Melanoma

  Aligned BAM files from NextSeq500 tageted panel sequencing of 84 samples from matched tumour-normal pairs of 42 melanoma patients. The dataset consists of 30 non-responders and 12 responders to ICB.

  Dataset EGAD00001005778

• Mutation analysis of 10 genes in plasma DNA of RCC patients

  Mutation analysis of 10 frequently mutated genes in renal cell carcinoma (BAP1, KDM5C, MET, MTOR, PBRM1, PIK3CA, PTEN, SETD2, TP53, VHL) in plasma DNA of RCC patients using a custom QIASeq panel (MonRec Cohort)

  Dataset EGAD00001005806

• Chromatin run-on and transcriptome sequencing of fibrolamellar carcinoma

  Fastq files of chromatin run-on (14 fibrolamellar carcinoma, 3 non-malignant liver; single-end) and transcriptome (23 fibrolamellar carcinoma, 2 non-malignant liver; paired-end) sequencing of fibrolamellar carcinoma

  Dataset EGAD00001005797

• JAK and STAT alterations in CD30 positive LPD

  JAK and STAT alterations in CD30 positive LPD, panel sequencing, 12 cutaneous lymphoma patients, 40 samples

  Dataset EGAD00001005801

• sWGS of RCC patients

  Paired end shallow whole genome sequencing (sWGS) data for the identification of somatic copy number alterations (SCNA) and the estimation of tumor fractions in plasma DNA of renal cell carcinoma (RCC) patients (MonRec Cohort)

  Dataset EGAD00001005804

• Spatial whole exome sequencing of metastatic melanoma

  We performed whole exome sequencing of 8 samples derived from a patient with metastatic melanoma. These represent six different regions of a metastatic melanoma biopsy that was treated with anti-PD-1 inhibitor, one pre-treatment biopsy that was treatment naive and one post-PD-1 inhibitor treated lesion. Exome sequencing data was generated using methods as previously described, including library preparation using the Agilent SureSelect XT Target Enrichment protocol (#5190-8646) prior to sequencing on an Illumina HiSeq 2000/2500 v3 system using 76bp paired-end reads. Raw sequencing data was then processed using Saturn V, the next generation sequencing data processing and analysis pipeline developed by the Department of Genomic Medicine at the UT MD Anderson Cancer Center.

  Dataset EGAD00001005819

• Spatial RNA-sequencing of metastatic melanoma

  We performed RNA sequencing of 48 different regions sub-sampled from a metastatic melanoma biopsy that was treated with anti-PD-1 inhibitor. RNAseq was performed on samples with a minimum RNA integrity number (RIN) of 5.5 except for two cases (6A10 and 8A3) with RINs greater than 3. A minimum of 700ng of RNA were required for all samples undergoing RNAseq. Paired-end transcriptome reads were aligned using TopHat2, to the UCSC hg19 reference genome.

  Dataset EGAD00001005820

• Spatial targeted gene sequencing of metastatic melanoma

  We performed deep targeted DNA sequencing for a panel of 265 cancer-related genes. This included subsampling 35 different regions of a metastatic melanoma biopsy that was treated with anti-PD-1 inhibitor. Samples with cancer cell purity greater than 80% based on pathologic assessment were used for cancer gene panel DNA sequencing. Mean sequencing coverage was 861x and paired-end reads in FASTQ format were generated by the Illumina pipeline and aligned to the reference human genome hg19 build using the Burrows-Wheeler Alignment Tool (BWA, v0.7.5) with default settings. Aligned reads were further processed using GATK with best practices for removing duplicates, indel removal and recalibration.

  Dataset EGAD00001005821

• Genome and transcriptome sequence data from a breast ductal carcinoma patient

  Genome and transcriptome sequence data from a breast ductal carcinoma patient, generated as part of the BC Cancer Agency's Personalized OncoGenomics (POG) study

  Dataset EGAD00001005823

• Genome and transcriptome sequence data from an uveal melanoma patient

  Genome and transcriptome sequence data from an uveal melanoma patient, generated as part of the BC Cancer Agency's Personalized OncoGenomics (POG) study

  Dataset EGAD00001005824

• Genome and transcriptome sequence data from a metastatic rectal carcinoma patient

  Genome and transcriptome sequence data from a metastatic rectal carcinoma patient, generated as part of the BC Cancer Agency's Personalized OncoGenomics (POG) study

  Dataset EGAD00001005825

• Genome and transcriptome sequence data from a metastatic choroidal melanoma patient

  Genome and transcriptome sequence data from a metastatic choroidal melanoma patient, generated as part of the BC Cancer Agency's Personalized OncoGenomics (POG) study

  Dataset EGAD00001005828

• preinvasive LUAD

  Whole-exome sequencing coupled with RNA-seq of preinvasive (n=98) and invasive (n=99) lung adenocarcinoma samples.

  Dataset EGAD00001005479

• Melanoma multi site metastases

  These are caveman, pindel, battenberg and brass calls for index patients' metastatic melanoma genomes within this study.

  Dataset EGAD00001005483

• WXS files for Zhang PanNBL

  WXS files for Zhang PanNBL paper titled "Pan-neuroblastoma analysis reveals age- and signature-associated driver alterations"

  Dataset EGAD00001005484

• Melanoma multi site metastases

  These are caveman, pindel and sequenza calls for the metastatic melanoma exomes within this study.

  Dataset EGAD00001005487

• Berlin Neuroblastoma Dataset

  Paired tumor/normal WGS and RNA-seq of primary neuroblastoma.

  Dataset EGAD00001005488

• Myeloma XI trial data

  The dataset contains WGS and RNA-seq from Myeloma XI trial

  Dataset EGAD00001005491

• Reconstruction of complex rearrangement patterns causing the initiation of clear cell renal cell carcinoma.

  The genomic hallmark of clear cell renal cell carcinoma is the loss of the short arm of chromosome three. This appears to be the earliest genomic event in the formation of these cancers. Often chromosome 3 is lost at the same time as part of chromosome 5 is duplicated via an unbalanced translocation, often with features consistent with focal chromothripsis. In this study, we sought to reconstruct the chromothriptic event that underlies the initiation of kidney cancer. We used long read sequencing (promethION, Oxford Nanopore Technologies) of patient tumour-derived DNA to elucidate how a single cell division error can generate cancer genome complexity.

  Dataset EGAD00001005495

• UCSF Pediatric Bithalamic Glioma Genome Project

  Targeted next-generation sequencing of 13 pediatric bithalamic diffuse gliomas. BAM files of targeted next-generation DNA sequencing data of 13 pediatric gliomas, with multi-region sequencing data from 2 of these cases (17 total tumor samples). Genomic DNA was extracted from formalin-fixed, paraffin-embedded blocks of tumor tissue from using the QIAamp DNA FFPE Tissue Kit (Qiagen). Capture-based next-generation DNA sequencing was performed at the University of California, San Francisco Clinical Cancer Genomics Laboratory, using an assay that targets all coding exons of 480 cancer-related genes, select introns of 47 genes, and TERT promoter with a total sequencing footprint of 2.8 Mb (UCSF500 Cancer Panel). Sequencing libraries were prepared from genomic DNA, and target enrichment was performed by hybrid capture using a custom oligonucleotide library (Nimblegen SeqCap EZ Choice). Captured libraries were sequenced as paired-end 100 bp reads on an Illumina HiSeq 2500 instrument. Duplicate sequencing reads were removed computationally to allow for accurate allele frequency determination and copy number calling.

  Dataset EGAD00001005499

• 20191008_EGA_MELA_Acral_WGS+RNASeq

  Illumina platform sequencing of whole genome libraries prepared from paired tumour/normal samples from 87 cases of melanoma Acral subtype. 63 cases also have RNASeq sequencing from the tumour sample.

  Dataset EGAD00001005500

• 20191008_EGA_MELA_Immunology

  Illumina RNASeq sequencing of tumour samples from 41 cases of melanoma

  Dataset EGAD00001005501

• ICGC_Pedbrain_WGBS_Pilocytic_Astrocytoma

  18 WGBS lanes for 9 samples of pilocytic astrocytoma.

  Dataset EGAD00001005504

• Cell type-specific transcriptomics of esophageal adenocarcinoma

  3' mRNA-Seq obtained from distinct isolated cell types (epithelia cells,immune cells, fibroblasts) of endoscopically obtained esophageal adenocarcinoma tissue as well as normal esophageal mucosa. Libraries for RNA-sequencing were prepared using the QuantSeq 3' mRNA-Seq Library Prep Kit FWD for Illumina according to the low input protocol. Libraries were sequenced on a HiSeq 4000 (Illumina) by 1x 50 bases.

  Dataset EGAD00001005508

• Sequencing files for "A Unifying Paradigm for Transcriptional Heterogeneity and Squamous Features in Pancreatic Ductal Adenocarcinoma."

  Files from DNA and RNA sequencing from primary tumors and metastases from pancreatic cancer patients along with matched normal tissues.

  Dataset EGAD00001005519

• A Protein Neddylation Inhibitor MLN4924 Suppresses Patient-Derived Glioblastoma Cells via Inhibition of ERK and AKT Signaling

  To identify what factors cause a different reactivity to MLN4924, 15 cells were categorized into high, intermediate, and low MLN4924 resistance groups based on the half-maximal inhibitory concentration (IC50) of MLN4924. PDC1, PCD2, PDC3, PDC4, and PDC5 showed high MLN4924 sensitivity, whereas PDC12, PDC13, PDC14, and PDC15 showed low MLN4924 sensitivity. Whole-transcriptome sequencing of these 9 patient-derived glioblastoma stem cells was performed.

  Dataset EGAD00001005709

• SF11215 snATAC Seq GBM

  High grade glioma sample, Gender Male Age 46. Single Nuclei ATAC seq data from high grade human glioma samples. NovaSeq6000 was used for ATAC seq. The files uploaded are bam files created with grch38 reference.

  Dataset EGAD00001005407

• SF11331 snATAC Seq Primary GBM Male

  SF11331 Primary GBM Male,55 Single Nuclei ATAC seq data from high grade human glioma sample. NovaSeq6000 was used for ATAC seq. The files uploaded are bam files created with grch38 reference.

  Dataset EGAD00001005408

• SF10022 snRNA-Seq Primary High-grade Glioma

  SF10022 single nuclei RNA-Seq Primary High-grade glioma. gender Male Age 65. Single Nuclei RNA seq from high grade primary glioma sample. NovaSeq6000 was used for RNA seq. The files uploaded are bam files created with grch38 reference

  Dataset EGAD00001005409

• SF12264 snRNA-Seq Primary GBM

  Single Nuclei RNA-Seq Primary GBM. Gender Female Age 51. Single Nuclei RNA seq from high grade primary glioma sample. NovaSeq6000 was used for RNA seq. The files uploaded are bam files created with grch38 reference.

  Dataset EGAD00001005410

• SF11612 scRNA-Seq Recurrent oligodendroglioma

  Single Cell RNA seq from Recurrent oligodendroglioma sample. Gender Male Age 67. NovaSeq6000 was used for RNA seq. The files uploaded are bam files created with grch38 reference through Cellranger count (10xGenomics.)

  Dataset EGAD00001005411

• SF12090 snRNA-Seq IDHR132H Wild-type Primary GBM Male

  Single Nuclei RNA-Seq Primary IDHR132H Wild-type GBM. Male, 61. Single Nuclei RNA seq from high grade primary glioma sample. NovaSeq6000 was used for RNA seq. The files uploaded are bam files created with grch38 reference.

  Dataset EGAD00001005412

• SF11612 snATAC Seq Recurrent oligodendroglioma

  SF11612 Recurrent oligodendroglioma. Gender Male Age 67. Single Nuclei ATAC seq data from low grade human glioma samples. NovaSeq6000 was used for ATAC seq. The files uploaded are bam files created with grch38 reference.

  Dataset EGAD00001005413

• SF11964 snATAC Seq Low Grade Astrocytoma IDHR132H mutant

  Single Nuclei ATAC Seq IDHR132H mutant Astrocytoma . Male, 64. Single Nuclei ATAC seq data from low grade human glioma sample. NovaSeq6000 was used for ATAC seq. The files uploaded are bam files created with grch38 reference.

  Dataset EGAD00001005414

• SF4297 snRNA-Seq Primary GBM

  Single Nuclei RNA-Seq Primary High-grade Glioma. Gender male age 39. Single Nuclei RNA seq from high grade primary glioma sample. NovaSeq6000 was used for RNA seq. The files uploaded are bam files created with grch38 reference

  Dataset EGAD00001005415

• SF11979 snATAC seq IDHR132H Wildtype GBM Female

  SF11979 snATAC, IDHR132H WT GBM Female, 76 Single Nuclei ATAC seq data from high grade human glioma samples. NovaSeq6000 was used for ATAC seq. The files uploaded are bam files created with grch38 reference.

  Dataset EGAD00001005418

• CyTOF of 27 DLBCLs

  Diffuse large B-cell lymphoma (DLBCL) is the most common histologic subtype of non-Hodgkin lymphoma and is notorious for its clinical heterogeneity. Patient outcomes can be predicted by cell-of-origin (COO) classification, demonstrating that the underlying transcriptional signature of malignant B-cells informs biological behavior in the context of standard combination chemotherapy regimens. In the current study, we used mass cytometry (CyTOF) to examine tumor phenotypes at the protein level with single cell resolution in a collection of 27 diagnostic DLBCL biopsy specimens from treatment naïve patients. We found that malignant B-cells from each patient occupied unique regions in 37-dimensional phenotypic space with no apparent clustering of samples into discrete subtypes. Interestingly, variable MHC class II expression was found to be the greatest contributor to phenotypic diversity. Within individual tumors, a subset of cases showed multiple phenotypic subpopulations, and in one case we were able to demonstrate direct correspondence between protein-level phenotypic subsets and DNA mutation-defined subclones. In summary, CyTOF analysis can resolve both inter- and intra-tumoral heterogeneity among primary samples, and reveals that each case of DLBCL is unique and may be comprised of multiple, genetically distinct subclones.

  Dataset EGAD00001005419

• Melanoma post mortem analysis

  These are 21 metastatic melanoma exomes matched with 7 germlines from 7 multisite metastatic melanoma cases.

  Dataset EGAD00001005421