11925 results for "cancer rna-seq"

in 51.01 milliseconds.

• Whole genome sequencing with linked reads of pediatric glioblastoma samples

  Pediatric glioblastoma (pGBM) is a lethal cancer with no effective therapies. To understand mechanisms of tumor evolution in this cancer, we performed whole genome sequencing with linked reads on longitudinally resected pGBM samples. Our analyses showed that all diagnostic and recurrent samples were collections of genetically diverse subclones. Clonal composition rapidly evolved at recurrence, with less than 8% of non-synonymous single nucleotide variants being shared in diagnostic-recurrent pairs. In order to track the origins of the mutational events we observed in pGBM, we generated whole genome datasets for two patients and their parents. These trios showed that genetic variants could be (i) somatic, (ii) inherited from a healthy parent, or (iii) arose de novo in the germlines of pGBM patients. Analysis of variant allele frequencies supported a model of tumor growth involving slow-cycling cancer stem cells that give rise to fast-proliferating progenitor-like cells and to non-dividing cells. Interestingly, radiation and anti-mitotic chemotherapeutics did not increase overall tumor burden upon recurrence. These findings support an important role for slow-cycling stem cell populations in contributing to recurrences, since slow-cycling cell populations are expected to be less prone to genotoxic stress induced by these treatments and to accumulate few mutations. Our results highlight the need for new targeted treatments that account for the complex functional hierarchies and genomic heterogeneity of pGBM.

  Study EGAS00001003432

• Partner-independent fusion gene detection by multiplexed CRISPR/Cas9 enrichment and long-read Nanopore sequencing

  Fusion genes are hallmarks of various cancer types and important determinants for diagnosis, prognosis and treatment possibilities. The promiscuity of fusion genes with respect to partner choice and exact breakpoint-positions restricts their detection in the diagnostic setting, even for known and recurrent fusion gene configurations. To accurately identify these gene fusions in an unbiased manner, we developed FUDGE: a FUsion gene Detection assay from Gene Enrichment. FUDGE couples target-selected and strand-specific CRISPR/Cas9 activity for enrichment and detection of fusion gene drivers (e.g. BRAF, EWSR1, KMT2A/MLL) - without prior knowledge of fusion partner or breakpoint-location - to long-read Nanopore sequencing. FUDGE encompasses a dedicated bioinformatics approach (NanoFG) to detect fusion genes from Nanopore sequencing data. Our strategy is flexible with respect to target choice and enables multiplexed enrichment for simultaneous analysis of several genes in multiple samples in a single sequencing run. We observe on average a 508-fold on-target enrichment and identify fusion breakpoints at nucleotide resolution - all within two days. We demonstrate that FUDGE effectively identifies fusion genes in cancer cell lines, tumor samples and on whole genome amplified DNA irrespective of partner gene or breakpoint-position in 100% of cases. Furthermore, we show that FUDGE is superior to routine diagnostic methods for fusion gene detection. In summary, we have developed a rapid and versatile fusion gene detection assay, providing an unparalleled opportunity for pan-cancer detection of fusion genes in routine diagnostics.

  Study EGAS00001003964

• scATAC-seq of CD4+ T cells from blood and tumor of NSCLC patients

  This study explore the CD4+ T cells diversity in paired blood and tumor of 2 different NSCLC patients. After FACS-sorted of Tregs (DAPI- CD45+ CD4+ CD25hi CD127lo) and Tconvs (DAPI- CD45+ CD4+CD25lo CD127lo/hi), cells were mixed in equal proportion (fifty/fifty ratio) and procesed with 10X Chromium (10X Genomics) scATAC kit and sequenced using Illumina platforms.

  Study EGAS50000000294

• Integration of T Cell Repertoire, CyTOF, genotyping and symptomatology data reveals subphenotypic variability in COVID-19 Patients

  A total of 61 patients (33 mild and 28 severe) with a median age of 51 years who recovered from COVID-19 were included in this study (Table 1). All collected samples were confirmed in diagnosis of COVID-19 by RT-PCR and positive IgG serolog. For the 61 patients, TCR-seq, CyTOF, and genotyping data were generated and analyzed in separate studies, as part of larger cohorts. In total, there are 143 variables, with 129 being quantitative (TCRseq and CyTOF metrics) and 13 being qualitative (symptomatology and genotyping). For more information about cohort characteristics, data adquisition an pre-processing, please visit PMID: 39227859, 36969980 and 37287057.

  Dataset EGAD50000000840

• Targeted long-read snIso-Seq of the human brain in neurodegenerative diseases

  Nuclei were extracted from postmortem human brain, and cDNA libraries were generated using the 10X Genomics 3' v3.1 kit. Prior to fragmentation, 75% of the library was reserved for long-read sequencing. This unfragmented library was used for target enrichment with a custom 50 gene probe panel from Twist Biosciences. The resulting amplified cDNA libraries were sequenced on a Sequel II. The files provided have undergone CCS generation, and we recommend following the guidelines in https://isoseq.how/ for further analysis starting with removal of primers using lima. The primer sequences that should be supplied are the Read 1 and TSO primers from the 10X Genomics kit.

  Dataset EGAD50000000179

• WGBS Discovery Samples

  The dataset contains valuable genomic data from a discovery cohort consisting of 29 individuals. This cohort is comprised of 8 healthy individuals (control), 8 patients with ST-segment elevation myocardial infarction (STEMI), 7 patients with non-ST-segment elevation myocardial infarction (NSTEMI), and 6 patients with unstable angina (UA). The genomic data was obtained by isolating cell-free circulating DNA (ccfDNA) and subjecting it to bisulfite conversion using a low-input BS-seq (PBAT) protocol. Sequencing was done on the Novaseq 6000 platform.

  Dataset EGAD00001010935

• LLD PhIPSeq

  LLD PhIP-Seq reads. Oligopeptides were designed at Eran's Segal group at Weizmann Institute of Science. Dataset include 1,783 plasma samples. In 340 participants, a second time point was taken after a 4-year follow-up.

  Dataset EGAD00001010104

• DPY30 ChIP-seq

  H9 human embryonic stem cells (hESCs) were cultured in feeder-free chemically-defined conditions in medium containing 10ng/ml Activin A and 12ng/ml FGF2 (Vallier L. 2011, Methods in Molecular Biology, 690: 57-66). Chromatin immunoprecipitation was performed as described in Brown S. et al. 2011. Stem Cells 29: 1176-85 by using 5ug of anti-DPY30 antibody (Sigma, cat. number HPA043761). This protocol was performed in control hESCs (expressing a scrambled shRNA) and in hESCs stably expressing an shRNA against DPY30 (Sigma, clone n. TRCN0000131112).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 EGAD00001001268

• Data Access Committee of divisions B060 and B062, German Cancer Research Center (DKFZ)

  Dac EGAC00001000219

• EGAD00010000644

  Affymetrix SNP6.0 cancer cell line exome sequencing data

  Dataset EGAD00010000644

• Genentech_cell_line_SNP

  SNP array data for 668 cancer cell lines

  Dataset EGAD00010000951

• FunGeST - Functional Genomics from cancer research to personalized medicine

  Dac EGAC00001002924

• Rucaparib in patients presenting a metastatic breast cancer with Homologous Recombination Deficiency, without germline BRCA1/2 mutation, pronostic value of high LOH genomic score and predictive value of HRDetect (WGS)

  Study EGAS00001004756

• Point-of-care monitoring of head and neck cancer treatment response and recurrence development using nanopore-based ctDNA consensus sequencing

  Study EGAS00001007090

• UCL Translation Uro-Oncology Data Access Committee will govern access to data generated from the Translation Uro-Oncology groups of the UCL Cancer Institute and UCL Division of Surgery & Interventional Science

  Dac EGAC00001000471

• V4_Colorectal_panel_test

  Targeted gene screen of cell line tumours for testing the new V4 Colorectal gene panel.

  Study EGAS00001001807

• sWGS of non-cancer controls

  Paired end shallow whole genome sequencing (sWGS) data of cell-free DNA from plasma from self-reporting healthy individuals (MonRec Cohort)

  Dataset EGAD00001005805

• RBWES

  Retinoblastoma is a rare childhood cancer of the retina. We studied retinoblastoma by Whole-Exome-Sequencing.

  Dataset EGAD00001007591

• Osteosarcoma RNAseq

  We propose to definitively characterise the somatic genetics of Osteosarcoma cancer through generation of comprehensive catalogues of somatic mutations by high coverage genome and transcriptome sequencing.

  Dataset EGAD00001000826

• Multiple_myeloma_precursor_genomics

  Whole genome sequencing of up to 45 multiple myeloma precursor samples and matched normals pairs.

  Study EGAS00001006312

• Mutational_signatures_and_clonal_dynamics_in_normal_human_tissues

  Somatic mutations (burdens and signatures) and clonal dynamics in normal human tissues

  Study EGAS00001002471

• NSCCG CRC WES

  1006 Familial early onset gemrline CRC patients sequenced by the Molecular and Population Genetics group of the Institute of Cancer Research

  Dataset EGAD00001002204

• Involvement of the FGF8/FGF Receptor Signaling Pathway in the Maintenance and Progression of Fusion-Positive Rhabdomyosarcoma

  In our previous work, we used a myoblast model of fusion-positive rhabdomyosarcoma (FP-RMS) to demonstrate that FGF8, a target of the PAX3-FOXO1 (P3F) transcription factor, is essential for tumorigenicity driven by P3F. When aberrantly expressed, FGF8 can also sustain tumorigenicity in recurrent tumors that are independent of P3F. In this study, we report that FGF8, along with its receptors FGFR1 and FGFR4, is often highly expressed in FP-RMS tumors. We found that high levels of FGF8 expression in FP-RMS cells correlate with increased sensitivity to an FGFR4 inhibitor and a pan-FGFR inhibitor. Conversely, downregulating FGF8 led to a loss of sensitivity to these inhibitors. Interestingly, when FGF8 was upregulated in myoblasts, it resulted in decreased FGFR4 expression and sensitized the cells to an FGFR1 inhibitor and a pan-FGFR inhibitor. The downregulation of FGFR4 expression mediated by FGF8 could be reversed by inhibiting FGFR1, MEK, or ERK, thereby defining a signaling pathway through which FGF8 exerts its regulatory effects. Additionally, we discovered that high FGF8 expression in P3F-independent recurrent tumors is due to a rearrangement of viral long terminal repeat (LTR) sequences into the 3' untranslated region (UTR) of FGF8, leading to increased stability of FGF8 mRNA. These findings indicate that FGF8 plays an oncogenic role in FP-RMS through FGFR4 and may also exert oncogenic effects in P3F-independent relapses via FGFR1. Our study highlights the functional significance of FGF8 in FP-RMS and supports the rationale for preclinical investigations of FGFR inhibitors in treating this type of cancer.

  Study phs004009

• California Pacific Medical Center Research Breast Health Cohort

  Description of Cohort: The California Pacific Medical Center (CPMC) Breast Health Cohort is a cohort study based at CPMC and is linked to the San Francisco Mammography Registry, one of the sites of the NCI-funded Breast Cancer Screening Consortium (U01CA063740). CPMC is a community hospital in San Francisco, which has one of the highest volumes for mammography in San Francisco. Between September 2004 and June 2007, >90,000 mammograms were performed at CPMC. The CPMC breast health cohort collects demographic and risk factor data on women receiving mammography through participation in the San Francisco Mammography Registry, as part of the Breast Cancer Screening Consortium (U01CA063740). The SFMR database collects information from all sources, including a questionnaire on demographic and risk factor information, the clinical results of the breast examination, the measures of breast density by Dr. John Shepherd and the women who agreed to donate a blood sample. By merging these various sources of information we have very efficiently developed a large sample of women who have donated blood and have had a measure of mamographic density. Blood Collection: Dr. Steve Cummings is leading an effort to collect and archive blood samples from women who are receiving mammography screening. All women who are sent for a screening mammogram at CPMC are considered eligible. Since the cohort began collecting blood samples in July 2004 until June 2007, samples have been collected from over 11,000 women. Measurement of Breast Density: Dr. John Shepherd is currently measuring breast density in a large fraction of the cohort using an automated approach with single X-ray absorptiometry. Dr. Shepherd has established a link with the CPMC mammography center that allows him to collect routine digital mammography information. Using the data from the mammogram, Dr. Shepherd and his group have developed the single X-ray absorptiometry (SXA) technique for measuring density which is described in more detail below. The table demonstrates the distribution of demographic variables and some breast cancer risk factors of women who donated blood and had a breast density measurement in the CPMC breast health cohort. Nearly 80% of the participants are Caucasian and most of the women are post-menopausal with a median age of ~52. Since it will be difficult to accrue a large enough sample from each ethnic group, our study will focus only on Caucasian women. Table: Demographic variables, reproductive history and family history of breast cancer among 2962 women participating in the CPMC cohort study who contributed blood samples between 1994-1997. Variable Median/Percentage Age (Median/IQR) 52 (46-59) Ethnicity Caucasian/White 0.76 Asian/Pacific Islander 0.141 Hispanic 0.029 Mixed Race/Ethnicity 0.039 African American/Black 0.022 American Indian 0.001 Other 0.009 First degree relative with breast cancer 0.17 Age at first birth Nulliparous 0.39 Age<20 0.043 Age>40 0.032 Age<30, ≥20 0.251 Age>30, ≤40 0.282 Measurement of Breast Density in Cohort: Measurement of breast density is accomplished using an automated technique for all mammograms obtained by Dr. Shepherd using Single X-Ray absorptiometry (SXA). SXA measurement of breast density is done on approximately 30% of all screening mammograms. Below we describe the method for measurement of breast density by SXA by Dr. Shepherd's group and its validation and association with breast cancer. As we demonstrate below, breast density, as measured by SXA, is an automated, highly reproducible measure of the density of breast tissue and is associated with breast cancer risk. SXA for Quantifying Breast Density: Single x-ray absorptiometry (SXA) was initially developed for measuring bone density. SXA can determine the fraction of each of two densities simultaneously using the fact the sample is a constant thickness, the thickness in known, and the total attenuation is known. In applying this technique to breast density, we assume a two compartment model: fat and non-fatty (fibroglandular tissue). We use a reference material composed of various concentrations of two materials: one which is the same density as fat and another which is the same density as fibroglandular tissue. The reference material (phantom) is placed in the X-ray field with each mammogram. We have been able to implement this in a way that is unintrusive to the patient and technologist at CPMC. Assuming this two-compartment model and a constant known breast thickness, we can then calculate the percent density at any region of the breast based on the assumption that % pixel grey-scale is proportion to the mass fractions of breast fat and lean tissue. If reference materials (a phantom) of fat and fibroglandular tissue are imaged with the patient's breast and the reference materials have the same thickness as the patient's breast, then the breast's grey-scale values can be converted to fat/fibroglandular mass fractions by interpolating between those two references. The total percent density is found by averaging the volume fraction over all breast pixels. The phantom being used for breast density assessment at CPMC began to be used in September 2004. The phantom does not have to be manipulated by the technologist and stays attached on the mammography device during standard craniocaudal (CC) views. Thus it creates minimal to no interference with the clinical mammogram. Reproducibility of breast density measures: Traditional measures of mammographic density require some human interpretation. A human reader outlines the area perceived to be dense and a computer then calculates the percent area outlined as a percent of the entire image. Thus, while traditional mammographic density is associated with breast cancer risk, it has some limitations. In a study by Drs. Shepherd, Kerlikowske, et al., the correlation coefficient (Pearson's R) between different readers was 0.8-0.9. In contrast to the traditional mammographic density measurement, the SXA measurement is fully automated and, therefore, the reproducibility of the measurement is higher. Dr. Shepherd and colleagues have performed a replication study of SXA as a measurement of breast density. They have estimated the correlation coefficient of the SXA measurement of breast density to be >0.98. Thus, as expected for an automated measure, SXA is a highly reproducible measure of mammographic breast density. Drs. Shepherd and Kerlikowske have recently analyzed the association between breast cancer risk and breast density as measured by SXA (Shepherd et al., Cancer Epi Biomarkers and Prev, 2011, PMID: 21610220). They found that women in the highest quintile of % volumetric density had an odds ratio of 4.1 (95% CI: 2.3 - 7.2) for breast cancer risk compared to women in the lowest quintile of volumetric density. Thus volumetric density appears to be a highly reproducible, automated measure of breast cancer.

  Study phs000395

• EGAD00010000268

  Metabric breast cancer samples (Expression raw data)

  Dataset EGAD00010000268

• ParityImmune

  Blood transcriptome from women participating in the Norwegian Women and Cancer study (NOWAC)

  Dataset EGAD00010001412

• BROCA cancer panel sequencing for 15 samples

  BROCA panel sequencing using the BROCA-HR v8 and BROCA-GO v1 versions of the gene panel

  Dataset EGAD50000000035

• Tumor Normal WES dataset

  This dataset contains tumor-normal WES data in BAM files aqcuired from patients with renal cancer tumors and treated with Sunitinib

  Dataset EGAD50000001174

• Illumina_WXS_MET-CELL

  Whole-exome sequencing on Illumina HiSeq2000/2500 of PDO culture derived from colorectal cancer metastasis sample

  Dataset EGAD00001002096

• EPO2_Illumina_WXS_XEN

  Whole-exome sequencing on Illumina HiSeq2000/2500 of Patient-derived xenograft derived from colorectal cancer primary tumor sample (EPO2_cohort)

  Dataset EGAD00001003363

• Organoid Derivation Project WGS: Release 2

  Sequencing of tissue samples and their derived organoids from oesophageal, pancreatic and colorectal cancer patients.

  Dataset EGAD00001005955

• Organoid Derivation Project TGS: Release 2

  Sequencing of tissue samples and their derived organoids from oesophageal, pancreatic and colorectal cancer patients.

  Dataset EGAD00001004999

• Organoid Derivation Project WGS: Release 1

  Sequencing of tissue samples and their derived organoids from oesophageal, pancreatic and colorectal cancer patients.

  Dataset EGAD00001005000

• Organoid Derivation Project TGS: Release 3

  Sequencing of tissue samples and their derived organoids from oesophageal, pancreatic and colorectal cancer patients.

  Dataset EGAD00001005958

• Genomic Resistance Patterns to Second Generation Androgen Blockade in Paired Tumor Biopsies of Metastatic Castrate-Resistant Prostate Cancer

  We examined genetic resistance to second generation androgen targeting therapies (abiraterone acetate or enzalutamide) by analyzing whole exome sequencing of patient-matched pre-treatment and post-resistance tumors from a series of castrate-resistant prostate cancer (CRPC) patients. Abiraterone resistant tumors harbored alterations in AR and MYC, whereas patients treated with enzalutamide had acquired alterations in the cell cycle pathway. We experimentally confirmed expression of cell-cycle kinases sufficed to drive enzalutamide resistance, which was mitigated through CDK4/6 blockade. These observations link genetic resistance to specific therapeutic agents to inform strategies in genomically selected advanced CRPC.

  Study phs001447

• Radiation-Related Genomic Profile of Papillary Thyroid Cancer after the Chernobyl Accident

  The April 26, 1986 accident at the Chernobyl nuclear power plant in northern Ukraine resulted in the release of radioactive contaminants, which were deposited in the surrounding areas in Ukraine, Belarus, and Russia. The main radiation-related health effect resulting from these exposures is the increased occurrence of thyroid cancer among individuals who were children at the time of the accident or born shortly thereafter. The purpose of this study was to conduct a comprehensive genomic landscape analysis of papillary thyroid tumors arising in individuals who were exposed as children to radioactive iodine (I-131) from the Chernobyl nuclear power plant accident.

  Study phs001134

• Sensitive urothelial cancer detection via high volume urine DNA analysis

  Cystoscopy and imaging are the gold standard for urothelial cancer (UC) detection and surveillance, but cystoscopy is an uncomfortable procedure associated with adverse effects and a low diagnostic yield as only 10% of hematuria patients have UC. Urine tumor DNA (utDNA) is a non-invasive UC biomarker that has suffered from poor sensitivity for Ta stage tumors (<80%). We hypothesized that high urine volume analysis with a multi-gene panel could overcome these limitations, and developed a 100 mL utDNA laboratory platform (UroScout) that analyzes 25 commonly mutated UC genes and 8 copy number-altered loci for somatic alterations to detect UC.

  Study EGAS50000000630

• plasma DNA LINE-1 targeted bisulfite sequencing: a new non-invasive multi-cancer detection marker

  The detection of circulating tumor DNA, which allows non-invasive tumor molecular profiling and disease follow-up, promises optimal and individualized management of patients with cancer. However, detecting small fractions of tumor DNA released when the tumor burden is reduced remains a challenge. We developed a PCR-based targeted bisulfite method coupled to deep sequencing to detect methylation patterns of L1PA elements,which we named DIAMOND (for Detection of Long Interspersed Nuclear Element Altered Methylation ON plasma DNA). We used sodium bisulfite chemical conversion to achieve base-pair resolution analysis and designed a multiplexed PCR based on 8 amplicons covering L1PAs .

  Study EGAS50000000446

• scRNAseq analysis of CD8 T cells infiltrating the bladder and tumor of 4 non-muscle-invasive bladder cancer patients, before and after BCG treatment.

  We performed scRNAseq analysis of CD8 T cells infiltrating the bladder and tumor of 4 non-muscle-invasive bladder cancer patients, before and after BCG treatment. In order to identify tumor-specific T cells, we selected CD8 T cells that were enriched in the tumor of the patient. We also selected CD8 T cells appearing in the bladder after BCG treatment, with the hypothesis that BCG treatment stimulates tumor-specific CD8 T cells. Next, we cloned the TCR of these T cells in a Jurkat cell line and tested these TCR for recognition of tumor-specific antigens.

  Study EGAS50000001384

• Use_of_Deep_Sequencing_to_Dectect_Clonal_Mutations_In_Sun_Exposed_Skin_Epidermis

  This study aims to define the landscape of somatic mutations in sun exposed human skin by deep sequencing, analyse their frequency and use the data to infer the effect of mutations on proliferating cell behaviour. The frequency of each mutation will reflect the size of the clone of cells in the tissue sample. By analyzing small samples, clones with as few as 100 cells will be detectable. Allele frequency distributions for each mutation will be used to infer cell fate using published methods (Klein et al. 2010). This study will shed unprecedented light on the early clonal events that lead to the emergence of cancer.

  Study EGAS00001000515

• Inter and intra - tumor heterogeneity in Colorectal Cancer

  We used high depth massive parallel sequencing analyses to study 27 CRC (colorectal cancer) patients, with a total of 97 tumors (both primary and matched metastases) in addition to healthy control samples. We found inter-tumor concordance for coding mutations; in contrast, gene copy numbers were found to be highly discordant between primary tumors and metastases as validated by fluorescent in-situ hybridization. in a further step, we dissected a single tumor into 68 spatially defined samples and sequenced them separately. Here we identify evenly distributed coding mutations in APC and TP53 in all tumor areas, yet highly variable gene copy numbers in numerous genes.

  Study EGAS00001002150

• Use_of_Deep_Sequencing_to_Dectect_Clonal_Mutations_In_Sun_Exposed_Skin_Epidermis_PART2

  This study aims to define the landscape of somatic mutations in sun exposed human skin by deep sequencing, analyse their frequency and use the data to infer the effect of mutations on proliferating cell behaviour. The frequency of each mutation will reflect the size of the clone of cells in the tissue sample. By analyzing small samples, clones with as few as 100 cells will be detectable. Allele frequency distributions for each mutation will be used to infer cell fate using published methods (Klein et al. 2010). This study will shed unprecedented light on the early clonal events that lead to the emergence of cancer.

  Study EGAS00001000603

• Field effect of healthy and diseased livers (2019-04-08)

  Recent work in the Campbell group has revealed somatic mutations present in normal, non-cancerous human skin. A subset of the mutations conferred selective advantages to the host cells, leading to clonal expansions and raising the risk for future cancer development. Capturing such somatic mutations in normal tissue is important to advance our understanding about carcinogenesis and could provide prospective medical insights. In this project, our goal is to detect somatic mutations in normal (pre-cancerous) liver tissue. Using Laser Microdissection technology, we will dissect individual liver lobules from patient samples and submit these to sequencing. For each patient sample, we aim to sequence multiple lobules to characterise the mutagenic burden. Samples will be taken from patients with different liver disease aetiologies, including alcoholism and obesity, with a view on distinguishing the prevalent mutation types occurring in each disease context. We will perform targeted sequencing, initially using the WTSI cancer panel. Later we aim to use a novel bait set that captures both cancer genes as well as genes relevant to the non-cancerous samples (ie. genes implicated in hereditary disorders, immune sequences). . This dataset contains all the data available for this study on 2019-04-08.

  Dataset EGAD00001004941

• BAM files of targeted next-generation DNA sequencing data of 13 chordoid gliomas of the third ventricle

  BAM files of targeted next-generation DNA sequencing data of 13 chordoid gliomas of the third ventricle (2 paired tumor-normal samples and 11 tumor-only samples). Genomic DNA was extracted from formalin-fixed, paraffin-embedded blocks of tumor tissue from 13 patients with chordoid glioma of the third ventricle using the QIAamp DNA FFPE Tissue Kit (Qiagen). Genomic DNA was also extracted from leukocytes in a peripheral blood sample from one of the patients and a non-neoplastic gastric biopsy specimen from one of the patients. 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 approximately 500 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 EGAD00001003818

• Partner independent fusion gene detection by multiplexed CRISPR Cas9 enrichment and long read Nanopore sequencing (FUDGE)

  Targeted long-read nanopore sequencing. Abstract: Fusion genes are hallmarks of various cancer types and important determinants for diagnosis, prognosis and treatment. Fusion gene partner choice and breakpoint-position promiscuity restricts diagnostic detection, even for known and recurrent configurations. To accurately and impartially identify fusions, we developed FUDGE: FUsion Detection from Gene Enrichment. FUDGE couples target-selected and strand-specific CRISPR/Cas9 activity for fusion gene driver enrichment - without prior knowledge of fusion partner or breakpoint-location – to long-read Nanopore sequencing with the bioinformatics pipeline NanoFG. FUDGE has flexible target-loci choices and enables multiplexed enrichment for simultaneous analysis of several genes in multiple samples in one sequencing run. We observe on-average 665 fold breakpoint-site enrichment and identify nucleotide resolution fusion breakpoints - within two days. The assay identifies cancer cell line and tumor sample fusions irrespective of partner gene or breakpoint-position. FUDGE is a rapid and versatile fusion detection assay, providing unparalleled opportunity for diagnostic pan-cancer fusion detection.

  Dataset EGAD00001006111

• Ovarian Cancer Organoid Biobank

  WGS of ovarian cancer organoids, tumor samples and blood references. Ovarian cancer (OC) is a heterogeneous disease usually diagnosed at a late stage. Experimental in vitro models that faithfully capture the hallmarks and tumor heterogeneity of OC are limited and hard to establish. We present a novel protocol that enables efficient derivation and long-term expansion of OC organoids. Utilizing this protocol, we have established 56 organoid lines from 32 patients, representing the spectrum of ovarian neoplasms, including non-malignant borderline tumors, as well as mucinous, clear-cell, endometrioid, low- and high-grade serous carcinomas. OC organoids recapitulate histological and genomic features of the pertinent lesion from which they were derived, illustrating intra- and inter-patient heterogeneity, and can be genetically modified. We show that OC organoids can be used for drug screening assays and capture different tumor subtype responses to the gold standard platinum-based chemotherapy, including acquisition of chemoresistance in recurrent disease. Finally, OC organoids can be xenografted, enabling in vivo drug sensitivity assays. Taken together, this demonstrates their potential application for research and personalized medicine.

  Dataset EGAD00001004387

• Combination Therapies for Personalised Cancer Medicine in 11-18

  This study involves mutagenizing 11-18 with ENU to identify those mutations which engender resistance to targeted treatment. In the last decade we have begun to move towards the use of targeted therapeutics in the clinic, often resulting in dramatic response rates in cancer patients. However, clinical experience has demonstrated time and time again that such responses are invariably followed by the development of drug resistance. Identification of the underlying mechanisms may enable us to reverse such resistance. Traditional methods of modelling this resistance in vitro can lead to a plethora of potential resistance mechanisms that can be difficult to decipher.

  Study EGAS00001002579

• Exome array analysis of adverse reactions to fluoropyrimidine-based therapy for gastrointestinal cancer

  Fluoropyrimidines, including 5-fluororacil (5FU) and its pro-drug Capecitabine, are the common treatment for colorectal, breast, neck and head cancers – either as monotherapy or in combination therapy. Adverse reactions (ADRs) to the treatment are common and often result in treatment discontinuation or dose reduction. Factors contributing to ADRs, including genetic variation, are poorly characterized. We performed exome array analysis to identify genetic variants that contribute to adverse reactions.Our final dataset consisted of 504 European ancestry individuals undergoing fluoropyrimidine-based therapy for gastrointestinal cancer. A subset of 254 of these were treated with Capecitabine. All individuals were genotyped on the Illumina HumanExome Array.

  Study EGAS00001002763

• MutWP5__CRUK_Mutographs_of_Cancer__Lung__PD38234__Targeted_

  Sequencing of LCM-derived microbiopsies from explanted lung from pulmonary fibrosis patient. Goal to assess the mutational burden, spectrum, and clonal dynamics within the tissue. Deep sampling throughout multiple regions of the lung will determine whether there are differences in smoking-related mutation burden in different portions of the lung. Targeted sequencing will be conducted on samples to identify drivers of interest and clonality of the samples, well-performing samples will be sent for subsequent whole-genome sequencing. Results from this portion of the study will be compared to other individuals with smoking-related diseases (COPD, pulmonary fibrosis, lung cancer), and normal, non-smoking lungs.

  Study EGAS00001003325

• Identification of cis-regulatory mutations generating de novo edges in personalized cancer gene regulatory networks

  The identification of functional non-coding mutations is a key challenge in the field of genomics. Here we introduce μ-cisTarget to filter, annotate and prioritize cis-regulatory mutations based on their putative effect on the underlying ‘personal’ gene regulatory network. We validated μ-cisTarget by re-analyzing the TAL1 and LMO1 enhancer mutations in T-ALL, and the TERT promoter mutation in melanoma. Next, we re-sequenced the full genome of ten cancer cell lines and used matched transcriptome data and motif discovery to identify master regulators with de novo binding sites that result in the up-regulation of nearby oncogenic drivers.

  Study EGAS00001002571

• Rapid response of APC/TP53/KRAS mutated stage IV colorectal cancer under FOLFIRI + Bevacizumab detected by liquid biopsy: a case report

  In our non-interventional liquid biopsy study, a male patient in his fifties diagnosed with stage IV colorectal cancer and polytope liver metastases rapidly progressed after completing chemotherapy and deceased 8 months after diagnosis. Retrospective cell free DNA testing showed that the APC/TP53/KRAS major clone responded quickly after 3 cycles of FOLFIRI + Bevacizumab. Retrospective exome sequencing of pre-chemotherapy and post-chemotherapy tissue samples including metastases confirmed that the APC/TP53/KRAS and other major clonal mutations (GPR50, SLC5A, ZIC3, SF3A1 and others) were present in all samples. After the last chemotherapy cycle,

  Study EGAS00001004088

• Mutational signatures in head and neck cancer (H019)

  Genomic alterations are a driving force in the multistep process of head and neck cancer (HNC) and result from the interaction of exogenous environmental exposures and endogenous cellular processes. Each of these processes leaves a characteristic pattern of mutations on the tumor genome providing the unique opportunity to decipher specific signatures of mutational processes operative during HNC pathogenesis and to address their prognostic value. Computational analysis of whole exome sequencing data of the HIPO-HNC (n=83) and TCGA-HNSC (n=506) cohorts revealed five common mutational signatures (COSMIC signature 1, 2, 3, 13 and 16), and demonstrated their significant association with etiological risk factors (tobacco, alcohol and HPV16).

  Study EGAS00001004588

• The dataset for Detection and characterization of lung cancer using cell-free DNA fragmentomes

  The dataset for Detection and characterization of lung cancer using cell-free DNA fragmentomes includes 872 bam files from whole genome next-generation sequencing on the Illumina HiSeq2500. The samples analyzed include plasma samples from healthy individuals and patients with cancer.

  Dataset EGAD00001007796

• Mutational evolution in a lobular breast tumour profiled at single nucleotide resolution

  We have used next generation sequencing to sequence genomes (>43-fold coverage) and transcriptomes of an oestrogen-receptor-alpha-positive metastatic lobular breast cancer at depth. We found 32 somatic non-synonymous coding mutations present in the metastasis, and measured the frequency of these somatic mutations in DNA from the primary tumour of the same patient.

  Study EGAS00000000054

• High-throughput single-cell DNA sequencing of acute myeloid leukemia tumors with droplet microfluidics

  We developed a novel microfluidic platform to automatically barcode genomic DNA from individual cancer cells. Using this approach, we sequenced acute myeloid leukemia (AML) tumors targeting up to 62 loci relevant for the disease from thousands of cells. We predict that our platform will enable analysis of heterogeneity in AML and improve stratification and therapy selection.

  Study phs001627

• Molecular Analysis of Alliance A031201 Study

  This is the first study examining the relationship between clonal hematopoiesis and clinical outcomes in prostate cancer patients. We used a targeted gene sequencing panel to identify patients in the A031201 clinical trial with and without clonal hematopoiesis. We found that clonal hematopoiesis did not affect overall or progression free survival in A031201 but was associated more adverse cardiac events.

  Study phs003717

• Analysis of genes related to the oncogenesis, progression or effectiveness of drug therapies of urological tumors .

  To clarify the oncogenesis and the progression mechanism of urological tumors, we continuously collect tumor samples of our patients with high quality. Then we used them to comprehensive analyses such as genome sequencing or epi-genome sequencing. Through these analyses, we aim for elucidating the oncogenesis or for developing newly treatment strategies of each cancer.

  Study JGAS000737

• SCANDARE HNSCC DNA targeted panel sequencing

  SCANDARE (NCT03017573) is a multicentric biobanking study, enrolling adult patients with newly diagnosed head and neck squamous cell carcinoma (HNSCC), triple negative breast cancer (TNBC), ovarian and cervical cancer. Tumor tissue and blood samples are collected at several time points during patient's journey, including at diagnosis, post-neoadjuvant chemotherapy in case of neoadjuvant treatment, at surgery, at recurrence and at disease progression following treatment initiated at recurrence. Since its launch in 2017 at Institut Curie, SCANDARE has enabled the longitudinal collection and preservation of samples for in-depth analyses. Here, we describe molecular alterations in 232 FFPE samples at baseline from 83 HNSCC patients using DNA targeted panel sequencing, with FASTQ files deposited in the dataset.

  Dataset EGAD50000001654

• Analysis of genes related to the oncogenesis, progression or effectiveness of drug therapies of urological tumors .

  To clarify the oncogenesis and the progression mechanism of urological tumors, we continuously collect tumor samples of our patients with high quality. Then we used them to comprehensive analyses such as genome sequencing or epi-genome sequencing. Through these analyses, we aim for elucidating the oncogenesis or for developing newly treatment strategies of each cancer.

  Study JGAS000564

• WES Analysis of precancerous lesions in Lynch Syndrome

  The project focuses on identifying the genetic alterations involved in the early stages of tumor development in individuals with Lynch Syndrome. Using Whole Exome Sequencing (WES), the study aims to characterize somatic mutations and molecular pathways that drive the transformation from normal tissue to precancerous lesions. This research contributes to a better understanding of tumorigenesis in hereditary colorectal cancer syndromes.

  Study EGAS50000001546

• MutWP5: CRUK Mutographs of Cancer: Lung: PD43291_Novaseq (Exome) (2021-02-02)

  Sequencing of LCM-derived microbiopsies from explanted lung from COPD patient. Goal to assess the mutational burden, spectrum, and clonal dynamics within the tissue. Deep sampling throughout multiple regions of the lung will determine whether there are differences in smoking-related mutaiton burden in different portions of the lung. Whole-genome sequencing will be conducted on samples identified as promising from the initial targeted data. Results from this poriton of the study will be compared to other individuals with smoking-related diseases (COPD, pulmonary fibrosis, lung cancer), and normal, non-smoking lungs. . This dataset contains all the data available for this study on 2021-02-02.

  Dataset EGAD00001006932

• ENU-CCK-81 cetuximab pilot project

  Cetuximab is a targeted monoclonal antibody against the epidermal growth factor receptor (EGFR) which is used therapeutically for the treatment of KRAS wild-type colorectal cancer (CRC). The Cetuximab sensitive KRAS wild-type CRC cell line NCI-H508 has been treated with a fixed concentration of ENU for 24 hours and then selected with Cetuximab until drug resistant clones were ready to be picked and grown up as sub-clones of the parental cell line. These will have genes causally implicated in cancer sequenced to identify common point mutations in multiple independently derived drug resistant clones as a forward genetic screen for mechanisms of resistance to Cetuximab in CRC.

  Dataset EGAD00001001947

• MutWP5: CRUK Mutographs of Cancer: Lung: PD38234 (WG) (2020-02-20)

  Sequencing of LCM-derived microbiopsies from explanted lung from pulmonary fibrosis patient. Goal to assess the mutational burden, spectrum, and clonal dynamics within the tissue. Deep sampling throughout multiple regions of the lung will determine whether there are differences in smoking-related mutation burden in different portions of the lung. Whole-genome sequencing will be conducted on samples identified as promising from the initial targeted data. Results from this portion of the study will be compared to other individuals with smoking-related diseases (COPD, pulmonary fibrosis, lung cancer), and normal, non-smoking lungs. . This dataset contains all the data available for this study on 2020-02-20.

  Dataset EGAD00001005991

• MutWP5: CRUK Mutographs of Cancer: Lung: PD37920 (WG) (2020-02-20)

  Sequencing of LCM-derived microbiopsies from explanted lung from COPD patient. Goal to assess the mutational burden, spectrum, and clonal dynamics within the tissue. Deep sampling throughout multiple regions of the lung will determine whether there are differences in smoking-related mutation burden in different portions of the lung. Whole-genome sequencing will be conducted on samples identified as promising from the initial targeted data. Results from this portion of the study will be compared to other individuals with smoking-related diseases (COPD, pulmonary fibrosis, lung cancer), and normal, non-smoking lungs. . This dataset contains all the data available for this study on 2020-02-20.

  Dataset EGAD00001005990

• Inter and intra - tumor heterogeneity in Colorectal Cancer

  The dataset consists of two main sample groups. 1) The inter-tumour sample group contains a total of 97 samples from 27 patients. Each patient has a single normal and primary sample as well as one or more metastases. All samples were sequenced using IonTorrent PGM and a custom colorectal cancer (CRC) panel. 2) The intra-tumour sample group contains a total of 68 samples from a single tumour as well as a normal tissue sample. All 68 samples were sequenced using IonTorrent PGM and a custom CRC panel. Shallow whole genome sequencing was additionally applied to 10 of the samples using Illumina HiSeq 4000.

  Dataset EGAD00001003131

• March 2018 cumulative data release for reference epigenomes generated at Centre for Epigenome Mapping Technologies, Genome Sciences Center, B.C. Cancer Agency as part of the International Human Epigenome Consortium.

  March 2018 cumulative data release (bams,fastqs) for reference epigenomes generated at Centre for Epigenome Mapping Technologies, Genome Sciences Center, B.C. Cancer Agency as part of the International Human Epigenome Consortium

  Dataset EGAD00001003963

• ENU-NCI-H508-Cetuximab-SecondRound

  Cetuximab is a targeted monoclonal antibody against the epidermal growth factor receptor (EGFR) which is used therapeutically for the treatment of KRAS wild-type colorectal cancer (CRC). The Cetuximab sensitive KRAS wild-type CRC cell line NCI-H508 has been treated with a fixed concentration of ENU for 24 hours and then selected with Cetuximab until drug resistant clones were ready to be picked and grown up as sub-clones of the parental cell line. These will have genes causally implicated in cancer sequenced to identify common point mutations in multiple independently derived drug resistant clones as a forward genetic screen for mechanisms of resistance to Cetuximab in CRC

  Dataset EGAD00001002065

• ENU-NCI-H508 cetuximab fixed concentration project

  Cetuximab is a targeted monoclonal antibody against the epidermal growth factor receptor (EGFR) which is used therapeutically for the treatment of KRAS wild-type colorectal cancer (CRC). The Cetuximab sensitive KRAS wild-type CRC cell line NCI-H508 has been treated with a fixed concentration of ENU for 24 hours and then selected with Cetuximab until drug resistant clones were ready to be picked and grown up as sub-clones of the parental cell line. These will have genes causally implicated in cancer sequenced to identify common point mutations in multiple independently derived drug resistant clones as a forward genetic screen for mechanisms of resistance to Cetuximab in CRC

  Dataset EGAD00001001948

• mutational landscape of normal human breast

  The accumulation of somatic mutations in the healthy breast throughout life and pregnancy is poorly understood. Here we describe whole genome sequencing analysis of epithelial and stromal compartments from the normal breast. We aimed to study how pregnancy and age affect both the mutational burden and the clonality of the healthy breast, and the subsequent implications on breast cancer risk.

  Study EGAS00001004672

• Whole genome analysis of pediatric patients with medulloblastoma

  Cancer genomes often contain structural variations (SVs) in non-coding regions, while its impact on tumorigenesis is still unclear. Our goal is to discover genome folding changes resulted from SVs using InfoGenomeR and InfoHiC frameworks, which may reveal novel therapeutic targets. We applied our frameworks to five pediatric patients with medulloblastoma, revealing 3D genome changes of medulloblastoma driver genes.

  Study EGAS00001006653

• Targeted DNA sequencing

  Targeted DNA sequencing of high-grade serous ovarian cancer (HGSC) tumour and normal samples from 15 patients with homologous recombination deficiencies. The dataset includes fastq files from 243 HGSC tumours (15 primary, 3 relapse, 225 end-stage) and 15 normals from 15 HGSC patients. Following target hybrid capture of 63 genes involved in DNA repair and response to treatment with an Agilent SureSelect XT panel, sequencing libraries were generated using the SureSelect XT Low Input Target Enrichment System (Agilent) as per the manufacturer's protocol. Libraries were sequenced on an Illumina NextSeq 500 at the Peter MacCallum Cancer Centre (Melbourne, Australia).

  Dataset EGAD00001009747

• MutWP5: CRUK Mutographs of Cancer: Lung: PD43291_Novaseq (WG)

  Sequencing of LCM-derived microbiopsies from explanted lung from COPD patient. Goal to assess the mutational burden, spectrum, and clonal dynamics within the tissue. Deep sampling throughout multiple regions of the lung will determine whether there are differences in smoking-related mutaiton burden in different portions of the lung. Whole-genome sequencing will be conducted on samples identified as promising from the initial targeted data. Results from this poriton of the study will be compared to other individuals with smoking-related diseases (COPD, pulmonary fibrosis, lung cancer), and normal, non-smoking lungs. . This dataset contains all the data available for this study on 2023-03-08.

  Dataset EGAD00001010111

• Early onset sporadic rectal cancer exome from Indian population

  Paired tumor-normal exome data from 47 Microsatellite stable Early-onset sporadic rectal cancer exome from the Indian population

  Dataset EGAD00001008504

• March 2019 data update for reference epigenomes generated at Centre for Epigenome Mapping Technologies, Genome Sciences Center, B.C. Cancer Agency as part of the International Human Epigenome Consortium.

  March 2019 data update for cord blood CD34+CD38-, CMP, GMP, MEP, monocyte, erythroid precursor, B cell and primary AML total blasts reference epigenomes generated at Centre for Epigenome Mapping Technologies, Genome Sciences Center, B.C. Cancer Agency as part of the International Human Epigenome Consortium. This dataset contains data for samples: CEMT0158 CEMT0159 CEMT0160 CEMT0161 CEMT0162 CEMT0163 CEMT0164 CEMT0165 CEMT0166 CEMT0167 CEMT0168 CEMT0169 CEMT0170 CEMT0171 CEMT0172 CEMT0189

  Dataset EGAD00001004950

• Targeted and exome sequencing data from 24 prostate cancer patients with somatic hypermutation

  This dataset contains all available targeted and exome sequencing paired fastq files from our study, "Identification of hypermutation and defective mismatch repair in ctDNA from metastatic prostate cancer". Patient identifiers are denoted by the first three characters of the sample aliases (e.g. "P01"), and additional information is appended to reflect the panel used (targeted 73 gene panel: "PC", or whole-exome panel: "WXS"), and whether the sample represents cell-free DNA ("cfdna") or paired white-blood cell control ("wbc"). Several patients have multiple serial collections available, and these are denoted by the characters "C1, C2, C3," etc. All samples were sequenced using Illumina technology.

  Dataset EGAD00001005474

• 76 cancer and normal whole genomes from eleven SI-NET patients

  This dataset comprises of 76 cancer and normal whole genomes obtained from 11 SI-NET patients, in the form of two fastq files (forward and reverse reads) for each genome containing sequences generated by Illumina NovaSeq 6000 system.

  Dataset EGAD00001006161

• MutWP5: CRUK Mutographs of Cancer: Lung: PD38233 (WG) (2021-02-02)

  Sequencing of LCM-derived microbiopsies from explanted lung from COPD patient. Goal to assess the mutational burden, spectrum, and clonal dynamics within the tissue. Deep sampling throughout multiple regions of the lung will determine whether there are differences in smoking-related mutation burden in different portions of the lung. Whole-genome sequencing will be conducted on samples identified as promising from the initial targeted data. Results from this portion of the study will be compared to other individuals with smoking-related diseases (COPD, pulmonary fibrosis, lung cancer), and normal, non-smoking lungs. . This dataset contains all the data available for this study on 2021-02-02.

  Dataset EGAD00001006930

• Evolution and clinical impact of genetic epistasis within EGFR-mutant lung cancers

  The current understanding of tumorigenesis is largely centered on a monogenic driver oncogene model. This paradigm is incompatible with the prevailing clinical experience in most solid malignancies: monotherapy with a drug directed against an individual oncogenic driver typically results in incomplete clinical responses and eventual tumor progression1-7. By profiling the somatic genetic alterations present in over 2,000 cases of lung cancer, the leading cause of cancer mortality worldwide, we show that combinations of functional genetic alterations, i.e. genetic collectives dominate the landscape of advanced-stage disease. We highlight this polygenic landscape and evolution of advanced-stage non-small cell lung cancer (NSCLC) through the spatial-temporal genomic profiling of 7 distinct tumor biopsy specimens and 6 plasma specimens obtained from an EGFR-mutant NSCLC patient at (1) initial diagnosis of early-stage disease, (2) metastatic progression, (3) sequential treatment and resistance to 2 EGFR inhibitors, (4) death. The comprehensive genomic analysis of this case, coupled with circulating free (cf) tumor DNA profiling of additional advanced-stage EGFR-mutant NSCLC clinical cohorts with associated treatment responses uncovered features of evolutionary selection for multiple concurrent gene alterations: including the presence of EGFR inhibitor-sensitive (EGFRL858R;EGFRexon19del) or inhibitor-resistant (EGFRT790M;EGFRC797S) forms of oncogenic EGFR along with cell cycle gene alterations (e.g. in CDK4/6, CCNE1, RB1) and activating alterations in WNT/β-catenin and PI3K pathway genes, which our data suggest can cooperatively impart non-redundant functions to limit EGFR targeted therapy response and/or promote tumor progression. Moreover, evidence of an unanticipated parallel evolution of both EGFR T790M and two distinct forms of oncogenic PIK3CA was observed. Our study provides a large-scale clinical and genetic dataset of advanced-stage EGFR-mutant NSCLC, a rationale for specific polytherapy strategies such as EGFR and CDK4/6 inhibitor co-treatment to potentially enhance clinical outcomes, and prompts a re-evaluation of the prevailing paradigm of monogenic-based molecular stratification for targeted therapy. Instead, our findings highlight an alternative model of genetic collectives that operate through epistasis to drive lung cancer progression and therapy resistance.

  Study EGAS00001002604

• Chromatin profiles classify castration-resistant prostate cancers suggesting therapeutic targets

  Untreated prostate cancers rely on androgen receptor (AR) signaling for growth and survival, forming the basis for the initial efficacy of androgen deprivation therapy (ADT). Yet, the disease can relapse and progress to a lethal stage termed castration-resistant prostate cancer (CRPC). Reactivation of AR signaling represents the most common driver of CRPC growth and next generation AR signaling inhibitors (ARSIs) are now used in combination with ADT as a first line therapy. However, ARSIs can result in selective pressure generating AR-independent tumors. The transition from AR-dependence frequently accompanies a change in phenotype resembling developmental trans-differentiation or ‘lineage plasticity’. Neuroendocrine prostate cancer, which lacks a defined pathologic classification, is the most studied type of lineage plasticity. However, most AR-null tumors do not exhibit neuroendocrine features and are classified as ‘double-negative prostate cancer’, the drivers of which are poorly defined. Lineage plasticity studies in CRPC are limited by the lack of genetically defined patient-derived models that recapitulate the disease spectrum. To address this, we developed a biobank of organoids generated from patient biopsies to study the landscape of metastatic CRPC and allow for functional validation assays. Proteins called transcription factors (TFs) are drivers of tumor lineage plasticity. To identify the key TFs that drive the growth of AR-independent tumors, we integrated epigenetic and transcriptomic data generated from CRPC models. By presenting a map of the chromatin accessibility and transcriptomic landscape of CRPC using a diverse biobank of organoids, PDXs and cell lines that recapitulate the heterogeneity of metastatic prostate cancer, we validate CRPC-AR and CRPC-NE subtypes and reveal two subtypes of AR-negative/low samples as well as their respective masterTFs. Additional analysis revealed a model in which YAP, TAZ, TEAD and AP-1 function together and drive oncogenic growth in CRPC-SCL samples. Overall, we show here how an approach to stratify CRPC patients into four subtypes using their transcriptomic signatures can potentially inform upon appropriate clinical decisions.

  Study EGAS00001006059

• Influence of Genomic Landscape on Cancer Immunotherapy for Newly Diagnosed Ovarian Cancer: Biomarker Analyses from the IMagyn050 Randomized Clinical Trial

  The IMagyn050 trial (NCT03038100), which evaluated the efficacy of Atezo vs placebo (Pla) with carboplatin, paclitaxel and bevacizumab (CPB) in front line ovarian cancer patient (pts), did not meet its co-primary endpoints of PFS in ITT or PD-L1+ (Moore et al. JCO 2021). The aim of this exploratory study was to evaluate whether patients with BRCA1/2-mutated or homologous recombination-deficient (HRD) ovarian cancers benefitted from atezolizumab in the phase III IMagyn050 (NCT03038100) trial. Methods: Patients with newly diagnosed ovarian cancer were randomized to either atezolizumab or placebo with standard chemotherapy and bevacizumab. PD-L1 status of tumor-infiltrating immune cells was determined centrally (VENTANA SP142 assay). Genomic alterations, including deleterious BRCA1/2 alterations, genomic loss of heterozygosity (gLOH), tumor mutation burden (TMB), and microsatellite instability (MSI), were evaluated using the FoundationOne assay. HRD was defined as gLOH ≥16%, regardless of BRCA1/2 mutation status. Potential associations between progression-free survival (PFS) and genomic biomarkers were evaluated using standard correlation analyses and log-rank of Kaplan-Meier estimates. Results Among biomarker-evaluable samples, 22% (234/1050) harbored BRCA1/2 mutations and 46% (446/980) were HRD. Median TMB was low irrespective of BRCA1/2 or HRD. Only 3% (29/1024) had TMB ≥10 mut/Mb and 0.3% (3/1022) were MSI-high. PFS was better in BRCA2-mutated versus BRCA2-non-mutated tumors and in HRD versus proficient tumors. PD-L1 positivity (≥1% expression on immune cells) was associated with HRD but not BRCA1/2 mutations. PFS was not improved by adding atezolizumab in BRCA2-mutated or HRD tumors; there was a trend toward enhanced PFS with atezolizumab in BRCA1-mutated tumors. Conclusion Most ovarian tumors have low TMB despite BRCA1/2 mutations or HRD. Neither BRCA1/2 mutation nor HRD predicted enhanced benefit from atezolizumab. This is the first randomized double-blind trial in ovarian cancer demonstrating that genomic instability triggered by BRCA1/2 mutation or HRD is not associated with improved sensitivity to immune checkpoint inhibitors.

  Study EGAS00001006838

• EGAD00010000558

  SNP 6.0 arrays of small cell lung cancer

  Dataset EGAD00010000558

• The CCA Genome Core is responsible for archiving the sequencing data generated by the Cancer Centre Amsterdam (CCA).

  Dac EGAC00001000181

• WES dataset for cfDNA cohort

  Whole exome sequencing data for 457 samples, including diagnosis and germline sample, across multiple cancer types for cfDNA cohort

  Dataset EGAD50000000103

• WGS data for cfDNA cohort

  Whole genome sequencing data for 423 samples, including diagnosis and germline, across multiple cancer types for cfDNA cohort

  Dataset EGAD50000000102

• Tumor Profiler AML Study

  Multi-omics data generated from 22 samples from the Tumor Profiler AML cohort

  Study EGAS50000000577

• SMPaeds PanelSeq of cfDNA at relapse with UMIs

  Deep sequencing of a targeted panel of 67 paediatric cancer related genes for cfDNA with UMIs at approximately 1500xUMI coverage.

  Dataset EGAD50000000781

• Whole genome sequencing of colon cancer data

  We performed longitudinal genomic analysis of samples from patients with colorectal-derived neoplasias from different stages through metastasis and treatment.

  Dataset EGAD50000002141

• MDS_Sequential_Treatment_Validation

  Validations of variants identified by exome sequencing in sequential samples derived after treatment cycle with AZA.

  Study EGAS00001000703

• V2_Colorectal_panel_test

  Targeted gene screen of cell line tumour samples for testing the new V2 Colorectal gene panel.

  Study EGAS00001001806

• Mutational_Analysis_of_Colorectal_PDX_models

  Targeted exome sequencing of patient derived xenografts from primary colorectal tumours and liver metastases.

  Study EGAS00001001171

• NanoString gene expression of PBMC from bladder cancer and RCC patients

  This dataset contains NanoString gene expression of PBMC from patients from IMvigor210, IMvigor211 and IMmotion150 cohorts

  Dataset EGAD00001005976

• WES of HCC

  WES of HCC by HiSeq 2000,total 71 samples including Hepatocellular carcinoma cell lines and nornal sample(Peripheral Blood or the adjacent tissues of cancer)

  Dataset EGAD00001001249

• Illumina_WXS_MET

  Whole-exome sequencing on Illumina HiSeq2000/2500 of colorectal cancer metastasis sample

  Dataset EGAD00001002095

• Illumina_WGS_MET-CELL

  Whole-genome sequencing on Illumina HiSeq2000/2500 of PDO culture derived from colorectal cancer metastasis sample

  Dataset EGAD00001002085

• Illumina_WXS_T-CELL

  Whole-exome sequencing on Illumina HiSeq2000/2500 of PDO culture derived from colorectal cancer primary tumor sample

  Dataset EGAD00001002100

• Targeted_sequencing_of_in_vitro_colonies___bulks

  In this study we will perform targeted sequencing on the bulk samples of in vitro colonies

  Study EGAS00001003175

• Exploring_the_landscape_of_somatic_mutations_in_normal_tissue___POL___WGS

  Somatic mutations (burdens and signatures) and clonal dynamics in individuals with germline DNA polymerase mutations.

  Study EGAS00001003682

• Whole genome sequencing of 63 single cells isolated from bone marrow aspirates of six non-metastatic breast cancer patients after staining for disseminated tumor cells.

  Dataset EGAD00001002745

• SAFIR02_Cytoscan

  Genomics to select patients with metastatic breast cancer for targeted therapy (microarray_cytoscan)

  Dataset EGAD00010002239

• cfDNA dataset with expanded panel for cfDNA cohort

  Cell free DNA sequencing data for 9 samples with expanded panel across multiple cancer types for cfDNA cohort

  Dataset EGAD50000000667