Search Results - EGA European Genome-Phenome Archive

Genome and transcriptome sequence data from an alveolar soft part sarcoma patient

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

Dataset EGAD00001005909

Multiregional single cell RNA sequencing of human renal cell carcinoma

The dataset comprises of 5' single cell RNA sequencing with TCR enrichment with 10x Genomics' Chromium technology of multiregional biopsies of human renal cell carcinomas. Biopsies from different tumour regions, the tumour-normal interface, normal kidney, normal adrenal, metastatic regions, peri-nephric fat, and peripheral blood were sequenced from 12 patients with kidney tumours.

Dataset EGAD00001008030

Whole transcriptome profiling of osteosarcoma

This dataset contains 86 osteosarcoma samples and their matched normals that underwent RNA sequencing using size fractionation, NuGEN Ovation Ultralow Library System V2 preparation, and paired-end sequencing on Illumina HiSeq 2000.

Dataset EGAD00001008436

pancreatic ductal adenocarcinoma exomes in study: Pro-immunogenic Impact of MEK inhibition combined with an anti-CD40 immunostimulatory antibody

This dataset contains 3 pairs of exomes, germline (from whole blood) and patient-derived xenograft (PDX), from human pancreatic durctal adenocarcinoma patients. The data is referred to in the publication: "Pro-immunogenic impact of MEK inhibition synergizes with agonist anti-CD40 immunostimulatory antibodies in tumor therapy" (Nature Communications, 2020) Abstract: Cancer types with lower mutational load and a non-permissive tumor microenvironment are intrinsically resistant to immune checkpoint blockade. While the combination of cytostatic drugs and immunostimulatory antibodies constitutes an attractive concept for overcoming this refractoriness, suppression of immune cell function by cytostatic drugs may limit therapeutic efficacy. Here we show that targeted inhibition of mitogen-activated protein kinase (MAPK) kinase (MEK) does not impair dendritic cell-mediated T-cell priming and activation. Accordingly, combining MEK inhibitors (MEKi) with agonist antibodies (Abs) targeting the immunostimulatory CD40 receptor resulted in potent synergistic anti-tumor efficacy. Detailed analysis of the mechanism of action of MEKi GDC-0623 by means of flow cytometric analysis of the tumor immune infiltrate and whole tumor transcriptomics showed that, in addition to its cytostatic impact on tumor cells, this drug exerts multiple pro-immunogenic effects, including the suppression of M2-type macrophages, myeloid derived suppressor cells and CD4+ T-regulatory cells. In addition, MEKi was found to induce tumor-cell intrinsic interferon signaling, which contributed to antigen presentation by tumor cells. Finally, the tumoridical impact of MEKi involves the activation of multiple pro-inflammatory pathways involved in immune cell effector function in the tumor microenvironment. Our data therefore indicate that the combination of MEK inhibition with agonist anti-CD40 Ab is a promising therapeutic concept, especially for the treatment of mutant Kras-driven tumors such as pancreatic ductal adenocarcinoma.

Dataset EGAD00001005938

Genome and transcriptome sequence data from a pancreatic adenocarcinoma patient

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

Dataset EGAD00001010318

Multiple myeloma follow-up Dataset

77 samples collected from 35 multiple myeloma patients. Each patient provided one healthy sample and one primary tumor sample and, in some cases, also samples collected after the progression of the disease.

Dataset EGAD00001010161

RNA-Seq data on multiple myeloma CD138positive bone marrow plasma cells

RNA-Seq data on multiple myeloma CD138positive bone marrow plasma cells, 11 samples, sequenced on HiSeq 4000 and HiSeq X-Ten, using mostly the TruSeq stranded mRNA Kit.

Dataset EGAD00001008619

WGS of primary mesothelioma cell lines

Mesothelioma is an aggressive cancer associated with previous exposure to asbestos and dismal prognosis. Since a pemetrexed/cisplatin combination was introduced for treatment of mesothelioma, no new first- or second-line therapies have been discovered. Thus, to better understand what drives mesothelioma carcinogenesis and to identify potential targets for therapy, in this project we aim at performing WGS analysis of a panel of mesothelioma cells lines.

Dataset EGAD00001009641

RNAseq of primary mesothelioma cell lines

Mesothelioma is an aggressive cancer associated with previous exposure to asbestos and dismal prognosis. Since a pemetrexed/cisplatin combination was introduced for treatment of mesothelioma, no new first- or second-line therapies have been discovered. Thus, to better understand what drives mesothelioma carcinogenesis and to identify potential targets for therapy, in this project we aim at performing RNAseq analysis of a panel of mesothelioma cells lines.

Dataset EGAD00001009642

Single cell atlas of neuroblastoma and the human fetal adrenal gland

Using the chromium 3' expression assay, we generated an atlas of neuroblastoma and the human fetal adrenal gland. These data were complemented with whole genome sequencing of normal and tumour DNA from the neuroblastoma samples.

Dataset EGAD00001008345

MutWP1: CRUK Grand Challenge Mutographs of Cancer: Colorectal_LCM (2020-02-20)

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. . This dataset contains all the data available for this study on 2020-02-20.

Dataset EGAD00001005994

WGS data for manuscript titled: Multi-omic features of oesophageal adenocarcinoma in patients treated with preoperative neoadjuvant therapy

Dataset EGAD00001008646

Whole transcriptome sequencing of 38 follicular lymphoma tumours.

This data set includes RNAseq from 38 follicular lymphoma tumours. All tumours were fresh frozen. Libraries were constructed by enriching for poly-A transcripts and sequenced as 75bp paired end reads on an Illumina HiSeq 2500 instrument.

Dataset EGAD00001009650

Single cell sequencing of a post-PD-1 inhibitor metastatic melanoma mass

Three technical replicates of FACS-sorted T cells (CD45+CD3+) and one replicate of FACS-sorted tumor cells (MCSP+) were loaded to a targeted 10,000 cells per lane on the 10X Genomics Chromium Controler with the single cell 5’ Immune Repertoire and Gene Expression profiling kit. In total, we loaded ~30,000 individual tumor infiltrating lymphocytes (TILs) and ~10,000 melanoma cells on the 10X platform (10X Genomics, CA, USA). Reverse transcription, TCR enrichment, and library preparations were performed according to the 10X Genomics 5’ V(D)J protocol revision C. Transcriptome libraries were pooled and sequenced on the Illumina NovaSeq 6000 S2 flow cell with 26 R1, 8 i7, and 91 R2 cycles respectively. The TCR libraries were pooled and sequenced on the Illumina MiSeq V2 150 cycles paired-end. Single cell transcriptomic and TCR data was processed with the 10X Genomics Cell Ranger Pipeline version 2.2.0 with the software-provided GRCh38 reference transcriptomes. After quality control, there was RNAseq profile data available from 6267 immune and 4303 melanoma cells. Downstream processing and visualization was encompassed through Seurat and tSNE plots.

Dataset EGAD00001006013

Interplay of somatic alterations and immune infiltration modulates response to PD-1 blockade in advanced clear cell renal cell carcinoma -- CA209-010

Immune checkpoint inhibitors targeting the PD-1 pathway have transformed the management of many advanced malignancies, including clear cell renal cell carcinoma (ccRCC), but the drivers and resistors of PD-1 response remain incompletely elucidated. Here, we analyzed 592 tumors collected from advanced ccRCC patients enrolled in prospective clinical trials of treatment with PD-1 blockade (or mTOR inhibition as control arm) by whole-exome and RNA-sequencing, integrated with immunofluorescence analysis, to define the somatic alteration landscape of late-stage ccRCC and to uncover the immunogenomic determinants of therapeutic response. While conventional genomic markers (tumor mutation burden, neoantigen load) and degree of CD8+ T cell infiltration were not associated with clinical response, we discovered numerous chromosomal alterations in advanced ccRCC associated with response or resistance to PD-1 blockade. These advanced tumors were highly CD8+ T cell infiltrated, with only 22% and 5% with an immune desert and immune excluded phenotype, respectively. Our analysis revealed that CD8+ infiltrated tumors are depleted of favorable PBRM1 mutations and are enriched for unfavorable chromosomal losses of 9p21.3 when compared to non-infiltrated tumors. These data demonstrate how the interplay of somatic alterations and immunophenotypes impacts therapeutic efficacy.

Dataset EGAD00001006026

Neuroblastoma patient WGS data

Paired tumor and normal WGS of primary neuroblastomas. This is an update of the „Berlin Neuroblastoma Dataset” (EGAS00001004022). This data was used for the analysis of circular RNA expression and regulation in neuroblastoma.

Dataset EGAD00001008123

Processed RNA-seq data for clinical efficacy and biomarker analysis of neoadjuvant atezolizumab in operable urothelial carcinoma in the ABACUS trial

ABACUS is a single arm phase 2 study that investigated 2 cycles of atezolizumab (1200mg Q3) prior to cystectomy in 95 patients with muscle invasive transitional cell cancer (T2-4N0M0). Pathological complete response (pCR) occurring in ≥20% of patients was the primary endpoint. Biomarker analysis on sequential tissue was a co-primary endpoint. This dataset includes the TPM and raw counts tables.

Dataset EGAD00001006199

Whole exome data from PMID27216186

This dataset comprises complete exome data from from the study PMID27216186 (Harbst & Lauss et al, Cancer Research 2016). These data are from 49 samples (tumor and matched normal) from 8 patients representing multi-region sequencing of human melanoma. Files are in the BAM format and contain aligned and processed data used for e.g. somatic variant calling. The sequencing libraries were constructed using SureSelect target enrichment with Clinical Research Exome Panel (Agilent) and sequenced on a HiSeq2500 (Illumina).

Dataset EGAD00001008149

RNA data for Glioblastoma (EGAS00001003953, H016)

RNA data for human glioblastoma patients, EGAS00001003953. 64 human samples, 2 cell lines (LN229, ZH487).

Dataset EGAD00001006547

Transcriptome sequencing of hepatocellular carcinoma biopsies (TACE study)

Illumina-based RNA-Seq analysis of 93 liver samples. Biopsies of tumors and non-tumor tissues are included. Samples are stratified by response and non-response to TACE treatment.

Dataset EGAD00001008158

Whole-exome sequencing of hepatocellular carcinoma biopsies

All 122 HCC biopsies and 115 non-tumoral tissues from 114 patients were subjected to whole-exome sequencing. Whole-exome capture was performed using the SureSelectXT Clinical Research Exome (Agilent Technologies) or SureSelect Human All Exon V6+COSMIC (Agilent Technologies) platforms according to the manufacturer’s guidelines. Sequencing was performed on an Illumina HiSeq 2500 at the Genomics Facility Basel according to the manufacturer’s guidelines. Paired-end 101-bp reads were generated.

Dataset EGAD00001008182

PDX RNA

RNAseq from PDX tumours under treatment with dpbs or eribulin. Sarcomatous or mixed sarcoma/carcinoma. 6 PDX tumours each with 2 treatments gave 12 pairs of fastq files.

Dataset EGAD00001009658

Interplay of somatic alterations and immune infiltration modulates response to PD-1 blockade in advanced clear cell renal cell carcinoma -- CA209-025

Immune checkpoint inhibitors targeting the PD-1 pathway have transformed the management of many advanced malignancies, including clear cell renal cell carcinoma (ccRCC), but the drivers and resistors of PD-1 response remain incompletely elucidated. Here, we analyzed 592 tumors collected from advanced ccRCC patients enrolled in prospective clinical trials of treatment with PD-1 blockade (or mTOR inhibition as control arm) by whole-exome and RNA-sequencing, integrated with immunofluorescence analysis, to define the somatic alteration landscape of late-stage ccRCC and to uncover the immunogenomic determinants of therapeutic response. While conventional genomic markers (tumor mutation burden, neoantigen load) and degree of CD8+ T cell infiltration were not associated with clinical response, we discovered numerous chromosomal alterations in advanced ccRCC associated with response or resistance to PD-1 blockade. These advanced tumors were highly CD8+ T cell infiltrated, with only 22% and 5% with an immune desert and immune excluded phenotype, respectively. Our analysis revealed that CD8+ infiltrated tumors are depleted of favorable PBRM1 mutations and are enriched for unfavorable chromosomal losses of 9p21.3 when compared to non-infiltrated tumors. These data demonstrate how the interplay of somatic alterations and immunophenotypes impacts therapeutic efficacy.

Dataset EGAD00001006029

WGS data for Glioblastoma (EGAS00001003953, H016)

Whole genome sequencing data for 20 human glioblastoma patients.

Dataset EGAD00001006545

WGBS data for Glioblastoma (EGAS00001003953, H016)

Whole Genome Bisulfite data for human glioblastoma patients, EGAS00001003953. 68 human samples

Dataset EGAD00001006546

RNAseq of neuroblastoma PDX and cell lines

This dataset contains 72 RNAseq (BAM and Fastq files are available for each sample).

Dataset EGAD00001006558

Somatic mutations in facial skin from countries of contrasting skin cancer risk

The incidence of non-melanoma skin cancer is 17-fold lower in Singapore compared to the UK1, despite Singapore receiving 2-3 times more year-round ultraviolet radiation (UV)2,3. The ageing epidermis of the skin comprises competing somatic mutant clones4,5, from which such cancers develop. We question if differences in keratinocyte skin cancer incidence are reflected in the mutational landscape by comparing ageing facial epidermis from donors of Singapore and the UK. We find UK skin to be a highly competitive, densely mutated landscape with 4-fold greater mutation burden compared to Singaporean skin and differences in clonal selection by country. We disproportionately observe multiple features common to keratinocyte skin cancers6,7,8 in UK skin, such as UV mutagenesis, copy number aberration and hotspot mutations (in particular TP53 R248W). We conclude that keratinocyte skin cancer incidence is reflected in the somatic clones of non-cancerous epidermis. Finally, we re-analyse squamous cell carcinoma exomes from Korea9 to show, even in low incidence populations, carcinogenesis is driven by UV damage.

Dataset EGAD00001009666

Orthotopic murine Group 3 medulloblastoma in C57Bl/6 mice treated with sham or craniospinal irradiation

Mice with medulloblastoma (Group 3) were treated with sham (isofluorane and imaging xray) or CSI as described by Abbas et al (2022). Total RNA was isolated with RNeasy Plus Mini Kit (Qiagen), library preparation (SureSelect, Agilent), rRNA depletion (Ribo-Zero Plus, Illumina) and sequencing were carried out by GenomicsWA or Australian Genome Research Facility. Libraries were sequenced on NovaSeq 6000 S1 flow cells as paired-end 150bp reads (Illumina).

Dataset EGAD00001008510

MutWP1: CRUK Grand Challenge Mutographs of Cancer: Oesophageal adenocarcinoma

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 (40X and 20X depth respectively). 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. This dataset contains all the data available for this study on 2021-09-27.

Dataset EGAD00001006083

SF4007

Oligodendroglioma (WHO gr. 2

Dataset EGAD00001008300

DNA methylation-based classification of sinonasal tumors [DNA sequencing]

This dataset contains raw exome sequencing data from nine sinonasal undifferentiated carcinoma FFPE samples and matched normal tissue that were assigned to a shared epigenetic class using DNA methylation-based classification. They were analyzed using the Twist Human Core Exome Plus Kit (Twist Bioscience) on a NovaSeq 6000 sequencer.

Dataset EGAD00001009668

Whole exome sequencing of a sinonasal glomangiopericytoma case

The is dataset includes the whole exome sequencing of the tumor from a sinonasal glomangiopericytoma case together with the matching blood. The whole exome sequencing revealed somatic PIK3CA and CTNNB1 mutations.

Dataset EGAD00001008291

Paired RNA sequencing of 30 samples RRMM (multiple myeloma)

Paired RNA sequencing of 30 samples RRMM using Illumina TruSeq stranded mRNA kit and either HiSeq2000 or HiSeq X Ten for sequencing.

Dataset EGAD00001009680

Paired WGS data of 45 samples and 2 paired WES sample of RRMM (multiple myeloma)

Here is mostly paired WGS data of RRMM, 45 samples (tumors and controls) in 86 runs. This data was produced by using Illumina TruSeq Nano DNA and NovaSeq6000 or HiSeq X Ten for sequencing. One tumor/control pair is WES data using Agilent SureSelect V5+UTRs and NovaSeq6000 for sequencing.

Dataset EGAD00001009682

scATAC sequence runs of 29 samples of RRMM (multiple myeloma) tumors

scATAC sequencing was performed of 29 samples of RRMM tumors using 10xGenomics for the preparation and NovaSeq6000 for sequencing.

Dataset EGAD00001009683

Pediatric Glioblastoma with Persistent STAG2 Mutation

This case represented the genomic findings of a pediatric glioblastoma patient who underwent multiple surgical resections and treated with standard chemoradiation, as well as a novel recombinant poliovirus vaccine therapy. The results present the preservation of a STAG2 mutated clone, besides elimination and emergence of other clones with oncogenic mutations through disease progression under different treatment modalities. Although STAG2 deficiency comprises only a small subset of gliomas, this case adds clinical evidence to existing preclinical data supporting a role for STAG2 mutations in gliomagenesis and resistance to standard therapies.

Dataset EGAD00001006202

WGS,RNA data of patients with multiple myeloma (MM) refractory to immunomodulatory agents (IMiDs) and proteasome inhibitors (PIs)

Paired WGS and RNA-Seq data of patients with multiple myeloma (MM) refractory to immunomodulatory agents (IMiDs) and proteasome inhibitors (PIs). We performed whole genome and transcriptome sequencing of 39 heavily pretreated RRMM patients with at least double refractoriness revealing complex structural changes and a high mutational load.

Dataset EGAD00001006189

Fastq files for the single cell RNAseq data of Follicular lymphoma study

Fastq files for the single cell RNAseq data of Follicular lymphoma study. This dataset includes the paired single cell RNA sequencing data for 23 samples.

Dataset EGAD00001008595

rna-seq data of multiple myeloma patients

6 samples from individuals with multiple myeloma with selective elimination of immunosuppressive T cells, rna sequencing

Dataset EGAD00001006866

Single circulating tumor cells in hepatocellular carcinoma

We determined intra- and inter-vascular transcriptional heterogeneity within the circulatory system using single-cell RNA-sequencing of 113 CTCs isolated from four key vascular sites along their dissemination route in ten HCC patients. The dataset consists of 146 paired-end fastq files from 113 sigle CTCs, HuH-7 cell line, Hep3B cellline, white blood cell, tumor and normal bulk tissue.

Dataset EGAD00001007642

DKFZ-St.Jude Medulloblastoma - 225 clinical cases, control exomes with some paired tumor.

225 clinical cases, control exomes with some paired tumor data, sequenced on Illumina machines from the paper "Germline Elongator mutations in Sonic Hedgehog medulloblastoma" (Waszak et al. 2020 Nature).

Dataset EGAD00001006665

Distribution of ctDNA levels in plasma of early-stage non-small cell lung cancer patients measured using personalised ctDNA analysis

Blood-based assays have shown increasing ability to detect circulating tumour DNA (ctDNA) in patients with early-stage cancer. However, detection of ctDNA in patients with non-small cell lung cancer (NSCLC) has continued to prove challenging. We performed retrospective analysis to quantify ctDNA levels in a cohort of 100 patients with early-stage NSCLC prior to treatment with curative intent. Where tumour tissue was available for whole exome sequencing, mutations identified were used to define patient-specific sequencing assays. For those 90 patients, plasma cell-free DNA was sequenced to high depth across capture panels targeting a median of 328 mutations specific to each patient. Data was analysed using Integration of Variant Reads (INVAR), detecting ctDNA in 66.7% of patients, including 52.7% (29 of 55) patients with stage I disease and >88% detection for patients with stage II and III disease (16/18 and 15/17). ctDNA was detected in plasma at fractional concentrations as low as 9.1x10-6, and in patients with tumour volumes as low as 0.23 cm3. A 36-gene sequencing panel (InVisionFirst-LungTM) was used to analyse plasma DNA in 27 samples including the 10 cases without tumour exome data, and detected ctDNA in 59% of samples tested (16 of 27). Across the entire cohort, detection rates were higher in squamous cell carcinoma patients compared to adenocarcinoma patients (81% vs. 59%). Detection of ctDNA prior to treatment was associated with significantly shorter time free from relapse, across all patients and in patient subgroups, with Hazard Ratios ranging from 2.25 to >11. Our analysis indicates that for patients with stage I NSCLC, the median ctDNA fraction in plasma is approx. 12 parts per million (0.0012%). This indicates the limits of detection that would be required for ctDNA-based liquid biopsies to detect ctDNA in the majority of patients with early-stage NSCLC.

Dataset EGAD00001006230

NABUCCO cohort 1 (NCT03387761) - Neo-Adjuvant Bladder Urothelial Carcinoma COmbination-immunotherapy

NABUCCO cohort 1 sequencing data. The dataset includes: * Whole exome DNAseq pre-treatment on tumor samples (n=24) matched with blood samples (n=24) * RNAseq pre-treatment on tumor samples (n=18) * RNAseq post-treatment on tumor samples (n=18). Not all pre-treatment samples are linked with pre-treatment samples * High coverage Whole exome DNAseq on pre-treatment tumor samples (n=3) matched with post-treatment metastasized lymph nodes isolated with laser microdissection (n=3) * All samples are labelled with the response phenotype (Complete Responder or Non-Complete Responder)

Dataset EGAD00001006250

Convergent somatic mutations in effectors of insulin signalling in chronic liver disease

Chronic liver disease is associated with metabolic dysregulation, liver failure and hepatocellular carcinoma. We analysed somatic mutations from 1202 genomes across 32 liver samples, including normal controls, alcohol-related and non-alcoholic fatty liver disease. Five of 27 patients with liver disease carried hotspot driver mutations in FOXO1, the major transcription factor downstream of insulin signalling. FOXO1 mutations were independently acquired by up to 5 distinct clones within the same patient’s sample, and impaired insulin-mediated nuclear export of FOXO1. GPAM, which produces storage triacylglycerol from dietary calories, also had significant excess of mutations, similarly exhibiting convergent evolution within biopsies. Telomeres were shorter in diseased than normal liver, with attrition more pronounced in larger clones. Multiple independent acquisitions of drivers within one small liver sample imply that such mutations could affect hundreds of grams of tissue across the whole organ, potentially contributing to systemic metabolic dysfunction.

Dataset EGAD00001006255

Processed microarray gene expression data from NPC samples_Cohort 2

We retrospectively collected 150 non-metastatic, pretreatment, formalin-fixed, paraffin-embedded (FFPE) nasopharyngeal carcinoma (NPC) samples as validation cohort 1. Also, we prospectively collected 32 FFPE samples from NPC patients enrolled in a trial evaluating anti-PD-1 antibody as validation cohort 2. Total RNA was extracted and hybridised to an Affymetrix HTA 2.0 microarray. In this study, we investigated the immune status of the tumour microenvironment (TME) based on gene expression profiles to classify NPC into biologically distinct immune subtypes, and clarify their associations with prognosis and immunotherapy response.

Dataset EGAD00001006274

ctDNA monitoring using patient-specific sequencing and integration of variant reads - Breast cohort

Circulating tumor-derived DNA (ctDNA) can be used to monitor cancer dynamics noninvasively. Detection of ctDNA can be challenging in patients with low-volume or residual disease, where plasma contains very few tumor-derived DNA fragments. We show that sensitivity for ctDNA detection in plasma can be improved by analyzing hundreds to thousands of mutations that are first identified by tumor genotyping. We describe the INtegration of VAriant Reads (INVAR) pipeline, which combines custom error-suppression methods and signal-enrichment approaches based on biological features of ctDNA. With this approach, the detection limit in each sample can be estimated independently based on the number of informative reads sequenced across multiple patient-specific loci. We applied INVAR to custom hybrid-capture sequencing data from 176 plasma samples from 105 patients with melanoma, lung, renal, glioma, and breast cancer across both early and advanced disease. By integrating signal across a median of >105 informative reads, ctDNA was routinely quantified to 1 mutant molecule per 100,000, and in some cases with high tumor mutation burden and/or plasma input material, to individual parts per million. This resulted in median Area Under the Curve (AUC) values of 0.98 in advanced cancers, and 0.80 in early stage and challenging settings for ctDNA detection. We generalized this method to whole-exome and whole-genome sequencing, showing that the INVAR may be applied without requiring personalized sequencing panels, so long as a tumor mutation list is available. As tumor sequencing becomes increasingly performed, such methods for personalized cancer monitoring may enhance the sensitivity of cancer liquid biopsies.

Dataset EGAD00001006293

H3K27ac/H3K27me3 landscape of medulloblastoma

We profiled 111 patient medulloblastoma primary tumor samples by bulk RNA-seq (19 samples), 27ac (98 samples) / 27me3 (61 samples) ChIP-Seq, WGS (4 samples) and 27ac hichip (8 samples). Submitted data consists of data generated from previously unpublished tumors as well as complementary data for data sets already published for identical medulloblastoma tumors (ex: 27me3 ChIP-Seq and RNA-Seq data submitted for a tumor with publicly available WGS data). The raw fastqs and hg19 aligned RNA-Seq bams are provided.

Dataset EGAD00001009709

10x Single Cell Gene Expression Library SCRNA10X_CS_CHIP0169_001

10x Single Cell Gene Expression library SCRNA10X_CS_CHIP0169_001 for Follicular lymphoma patient sample TFRIPAIR4_FL

Dataset EGAD00001010217

Genomic characterization (through whole-exome sequencing) of bone marrow clonal plasma cells before and after VRD treatment from multiple myeloma patients.

WES data from clonal pahtologic bone marrow plasma cells of multiple myeloma patients. From each patient there are three samples, pathologyc bone marrow plasma cells at diagnosis, pathologyc bone marrow plasma cells after VRD treatment and T lymphocytes as germline control. There are 14 patients in total

Dataset EGAD00001006302

Clinical Outcomes by Tumor Mutational Burden and Inflammatory Gene Expression With Combined Nivolumab and Ipilimumab or Monotherapy in Advanced Melanoma_CM67-RNASeq

Purpose Exploratory analyses of CheckMate 066 and 067 trials were conducted to investigate associations of tumor mutational burden (TMB), a 4-gene inflammatory gene expression signature, and BRAF mutation status with tumor response, progression-free survival (PFS), and overall survival (OS) in patients with advanced melanoma. Patients and Methods Patients with known programmed death ligand 1 (PD-L1) expression and BRAF mutation status received nivolumab (NIVO) or dacarbazine in CheckMate 066 and either NIVO, ipilimumab (IPI), or NIVO+IPI in CheckMate 067. Whole exome sequencing and RNA sequencing were used to determine TMB and inflammatory gene expression signature scores, respectively. These biomarkers were evaluated in terms of their association with PFS and OS. Results In the NIVO, NIVO+IPI, and IPI arms of CheckMate 067, longer survival was associated with high (> median) versus low (≤ median) TMB with hazard ratios (HRs) (95% confidence interval [CI]) for PFS of 0.45 (0.30–0.65), 0.55 (0.38–0.81), and 0.60 (0.43–0.82), and for OS of 0.46 (0.30–0.71), 0.53 (0.34–0.82), and 0.52 (0.36–0.74), respectively. For NIVO-treated patients, these results were confirmed in CheckMate 066. A survival benefit was observed with high TMB and absence of BRAF mutation. Survival was associated with high versus low inflammatory signature scores with HRs (95% CI) for PFS of 0.56 (0.34–0.94), 0.40 (0.23–0.72), and 0.43 (0.27–0.70), and for OS of 0.37 (0.20–0.66), 0.38 (0.19–0.74), and 0.46 (0.27–0.79), in the NIVO, NIVO+IPI, and IPI arms, respectively. Weak correlations were observed between PD-L1, TMB, and the inflammatory signature. Conclusions Combined assessment of TMB, inflammatory gene expression signature, and BRAF mutation status may be predictive for response to immunotherapy in advanced melanoma.

Dataset EGAD00001006306

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