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• Count Me In (CMI): The Angiosarcoma (ASC) Project (CMI-ASCproject)

  Count Me In - The Angiosarcoma Project: A Patient-Partnered Research Initiative to Accelerate Research in a Rare Sarcoma The Angiosarcoma Project (ASCproject) is a research study that directly engages angiosarcoma patients online and empowers them to accelerate cancer research by sharing medical information and clinical samples. Angiosarcoma is an exceedingly rare soft tissue sarcoma with an incidence of ~300 newly diagnosed cases per year in the United States. This low incidence has impeded large-scale research efforts in this disease that are strongly needed to catalyze research and improve clinical outcomes. The Angiosarcoma Project, launched in March 2017, has demonstrated the feasibility of directly engaging geographically dispersed patients to democratize research and establish a large patient cohort to characterize the genomic and clinical landscape of a rare disease. Angiosarcoma patients living in the US or Canada can access the study and consent online through an online portal (ASCproject.org). Enrolled patients are mailed saliva and blood draw kits, which can be used to extract germline DNA and cell-free DNA (cfDNA), respectively. The study team contacts participants' healthcare institutions to obtain medical records and a portion of archived tumor samples. All received tumor samples are subjected to centralized histological re-review by an expert pathologist to confirm a diagnosis of angiosarcoma. Whole exome sequencing is performed on tumor DNA, germline DNA, and cfDNA; transcriptome sequencing is performed on tumor RNA. De-identified data, including linked genomic, clinical, and patient-reported data, are shared via public databases on a recurring pre-publication basis. Participants are regularly provided updates on the study.

  Study phs001931

• Identification of New Therapeutic Targets for Renal Medullary Carcinoma via Integrated Genomic and Transcriptomic Profiling

  Renal medullary carcinoma (RMC) is a rare, aggressive kidney cancer associated with sickle cell trait, characterized by SMARCB1 loss and resistance to conventional therapies used for other renal cell carcinomas (RCC). We conducted whole exome sequencing (WES) on RMC samples. This study provides a large molecular characterization of RMC, highlighting TROP2 and other cell surface markers as promising therapeutic targets.

  Study EGAS50000001280

• Early detection of ovarian cancer using cell-free DNA fragmentomes and protein biomarkers

  Ovarian cancer is the leading cause of death from gynecological cancers worldwide. No effective screening methods exist, and tumors are commonly detected at advanced stages where treatment is much less effective. In this study, we used whole-genome cell-free DNA (cfDNA) fragmentome and protein biomarker (CA-125 and HE4) analyses to evaluate 591 women from the European Union or the United States with ovarian cancer, benign adnexal masses, or without ovarian lesions. Using a machine learning model that incorporated multi-analyte fragmentome data and protein measurements, we detected ovarian cancer with high specificity >99% and sensitivity of 72%, 69%, 87%, and 100% for stages I–IV, respectively (AUC=0.96, 95% CI: 0.94-0.99), including 90% of high grade serous ovarian cancers. At the same specificity, CA-125 alone detected 34%, 62%, 63%, and 100% of ovarian cancers for stages I–IV (p=0.001, two-sided test of equal proportions). Additionally, our approach distinguished benign masses from ovarian cancers with high accuracy (AUC of 0.88, 95% CI=0.83-0.92). These results were validated in an independent population. These findings show that integrated cfDNA fragmentome and protein analyses detect ovarian cancers with high performance, enabling a new accessible approach for noninvasive ovarian cancer screening and diagnostic evaluation.

  Study EGAS50000000484

• Control iPSC lines with clinically annotated genetic variants for versatile multi-lineage differentiation Part 2

  This is 2nd part of data for original Control iPSC lines with clinically annotated genetic variants for versatile multi-lineage differentiation,

  Dataset EGAD00001005359

• Short and long-read genome sequencing methodologies for somatic variant detection; genomic analysis of a patient with diffuse large B-cell lymphoma

  Recent advances in throughput and accuracy mean that the Oxford Nanopore Technologies (ONT) PromethION platform is a now a viable solution for WGS. New bioinformatic methods have been developed to take advantage of this long read data, however much of the validation of these tools has focussed on calling germline variants (both SNVs and structural variants). Somatic variants are outnumbered many-fold by germline variants and their detection is further complicated due to their frequency varying depending on tumour purity/subclonality. Here, we evaluate the extent to which Nanopore WGS enables genome-wide detection and analysis of somatic variation. We do this through sequencing tumour and germline genomes for a patient with diffuse B-cell lymphoma. We examine the capability of currently available tools for calling somatic variants in ONT data by comparing the data with results from 150bp short-read sequencing of the same samples. We then conduct a detailed analysis of the performance of multiple long-read mappers and structural variant callers for calling large, somatic structural variants (SVs) in ONT data. Our protocol achieved yields of up to 96 mapped Gb per PromethION flow cell with average read lengths of ~5kb. Calling germline SNVs from these data achieved good specificity and sensitivity. However, results of somatic SNV calling highlight the need for the development of specialized joint calling algorithms. Our analysis of structural variants shows that the comparative performance of different tools varies significantly between SV types, and suggest long reads are especially advantageous for calling large somatic deletions and duplications. Finally, we highlight the utility of long reads for phasing clinically relevant variants by using the ONT data to confirm that a somatic 1.6Mb deletion and a p.(Arg249Met) mutation involving TP53 are oriented in trans.

  Study EGAS00001004266

• Investigation of MMBIR DNA Repair in Normal and Cancer Human Cells

  Microhomology-mediated break-induced replication (MMBIR) is a DNA repair pathway in which template switching at microhomology was proposed to promote complex genomic rearrangements (CGRs) that contribute to cancer. Yet, the extent of MMBIR activity in genomes is poorly understood due to difficulty in directly identifying MMBIR events by whole genome sequencing (WGS). This study aims to detect MMBIR events in human cancer genomes and to determine their frequency and complexity in tumors as compared to their non-tumor counterparts. This study contains WGS data from matched tumor and normal samples, and cultured cell line control WGS datasets that are not currently represented in other cancer genome databases.

  Study phs002237

• Genomic and transcriptomic analysis of thymic epithelial tumors

  Thymic epithelial tumors (TETs), comprising various histologic types of thymomas and thymic carcinomas, originate from thymic epithelial cells. Each histologic type is typically associated with a distinct immune cell composition and clinical manifestation. A better understanding of the cellular origins and molecular pathways underlying this heterogeneity is needed to improve patient stratification and treatment. Here, we conducted an integrated genomic and transcriptomic analysis of 124 thymomas and 13 thymic carcinomas, including 20 newly sequenced cases combined with 117 cases from publicly available datasets. This approach stratified TETs into three subgroups with different possible origins: GTF2I-mutant (GTF2I-type) thymomas, copy number-altered (CN-type) thymomas, and thymic carcinomas.

  Study EGAS00001004227

• National Heart Lung and Blood Institute (NHLBI) GO-ESP: Heart Cohorts Component of the Exome Sequencing Project (ARIC)

  The NHLBI "Grand Opportunity" Exome Sequencing Project (GO-ESP), a signature project of the NHLBI Recovery Act investment, was designed to identify genetic variants in coding regions (exons) of the human genome (the "exome") that are associated with heart, lung and blood diseases. These and related diseases that are of high impact to public health and individuals from diverse racial and ethnic groups will be studied. These data may help researchers understand the causes of disease, contributing to better ways to prevent, diagnose, and treat diseases, as well as determine whether to tailor prevention and treatments to specific populations. This could lead to more effective treatments and reduce the likelihood of side effects. GO-ESP is comprised of five collaborative components: 3 cohort consortia - HeartGO, LungGO, and WHISP - and 2 sequencing centers - BroadGO and SeattleGO. HeartGO is a consortium of six well-phenotyped NHLBI cohorts: Atherosclerosis Risk in Communities (ARIC) study, the Coronary Artery Risk Development in Young Adults (CARDIA) study, the Cardiovascular Health Study, the Framingham Heart Study, the Jackson Heart Study, and the Multi-Ethnic Study of Atherosclerosis. Together, these cohorts have provided DNA and phenotype datasets from a diverse cohort of individuals of African-American, Caucasian, Asian, and Hispanic ancestry to be made available for use by qualified investigators in dbGaP. HeartGO investigators will conduct genotype-phenotype analyses for phenotypes related not only to heart disease but with other variables that will be contributed to dbGaP. The HeartGO dataset provides investigators with genotype-phenotype analytic opportunities for traits not only related to heart disease but also associated with ancillary variables that will be contributed to dbGaP, including disease endpoints, risk factors, biomarkers, and subclinical disease measures. The phenotypes planned for investigation as part of the GO-ESP HeartGO project include early-onset myocardial infarction (EOMI), low density lipoprotein (LDL) cholesterol, body mass index/type 2 diabetes (BMI/T2D), blood pressure and ischemic stroke. Results of the proposed analyses as well as relevant replication/follow-up analyses will be reported in peer-reviewed journals. This study phs000398 contains the Atherosclerosis Risk in Communities (ARIC) subset of GO-ESP/Heart-GO. Additional GO-ESP data is also available via dbGaP.

  Study phs000398

• National Heart Lung and Blood Institute (NHLBI) GO-ESP: Heart Cohorts Component of the Exome Sequencing Project (FHS)

  The NHLBI "Grand Opportunity" Exome Sequencing Project (GO-ESP), a signature project of the NHLBI Recovery Act investment, was designed to identify genetic variants in coding regions (exons) of the human genome (the "exome") that are associated with heart, lung and blood diseases. These and related diseases that are of high impact to public health and individuals from diverse racial and ethnic groups will be studied. These data may help researchers understand the causes of disease, contributing to better ways to prevent, diagnose, and treat diseases, as well as determine whether to tailor prevention and treatments to specific populations. This could lead to more effective treatments and reduce the likelihood of side effects. GO-ESP is comprised of five collaborative components: 3 cohort consortia - HeartGO, LungGO, and WHISP - and 2 sequencing centers - BroadGO and SeattleGO. HeartGO is a consortium of six well-phenotyped NHLBI cohorts: Atherosclerosis Risk in Communities (ARIC) study, the Coronary Artery Risk Development in Young Adults (CARDIA) study, the Cardiovascular Health Study, the Framingham Heart Study, the Jackson Heart Study, and the Multi-Ethnic Study of Atherosclerosis. Together, these cohorts have provided DNA and phenotype datasets from a diverse cohort of individuals of African-American, Caucasian, Asian, and Hispanic ancestry to be made available for use by qualified investigators in dbGaP. HeartGO investigators will conduct genotype-phenotype analyses for phenotypes related not only to heart disease but with other variables that will be contributed to dbGaP. The HeartGO dataset provides investigators with genotype-phenotype analytic opportunities for traits not only related to heart disease but also associated with ancillary variables that will be contributed to dbGaP, including disease endpoints, risk factors, biomarkers, and subclinical disease measures. The phenotypes planned for investigation as part of the GO-ESP HeartGO project include early-onset myocardial infarction (EOMI), low density lipoprotein (LDL) cholesterol, body mass index/type 2 diabetes (BMI/T2D), blood pressure and ischemic stroke. Results of the proposed analyses as well as relevant replication/follow-up analyses will be reported in peer-reviewed journals. This study phs000401 contains the Framingham Heart Study (FHS) subset of GO-ESP/Heart-GO. Additional GO-ESP data is also available via dbGaP.

  Study phs000401

• National Heart Lung and Blood Institute (NHLBI) GO-ESP: Heart Cohorts Component of the Exome Sequencing Project (JHS)

  The NHLBI "Grand Opportunity" Exome Sequencing Project (GO-ESP), a signature project of the NHLBI Recovery Act investment, was designed to identify genetic variants in coding regions (exons) of the human genome (the "exome") that are associated with heart, lung and blood diseases. These and related diseases that are of high impact to public health and individuals from diverse racial and ethnic groups will be studied. These data may help researchers understand the causes of disease, contributing to better ways to prevent, diagnose, and treat diseases, as well as determine whether to tailor prevention and treatments to specific populations. This could lead to more effective treatments and reduce the likelihood of side effects. GO-ESP is comprised of five collaborative components: 3 cohort consortia - HeartGO, LungGO, and WHISP - and 2 sequencing centers - BroadGO and SeattleGO. HeartGO is a consortium of six well-phenotyped NHLBI cohorts: Atherosclerosis Risk in Communities (ARIC) study, the Coronary Artery Risk Development in Young Adults (CARDIA) study, the Cardiovascular Health Study, the Framingham Heart Study, the Jackson Heart Study, and the Multi-Ethnic Study of Atherosclerosis. Together, these cohorts have provided DNA and phenotype datasets from a diverse cohort of individuals of African-American, Caucasian, Asian, and Hispanic ancestry to be made available for use by qualified investigators in dbGaP. HeartGO investigators will conduct genotype-phenotype analyses for phenotypes related not only to heart disease but with other variables that will be contributed to dbGaP. The HeartGO dataset provides investigators with genotype-phenotype analytic opportunities for traits not only related to heart disease but also associated with ancillary variables that will be contributed to dbGaP, including disease endpoints, risk factors, biomarkers, and subclinical disease measures. The phenotypes planned for investigation as part of the GO-ESP HeartGO project include early-onset myocardial infarction (EOMI), low density lipoprotein (LDL) cholesterol, body mass index/type 2 diabetes (BMI/T2D), blood pressure and ischemic stroke. Results of the proposed analyses as well as relevant replication/follow-up analyses will be reported in peer-reviewed journals. This study phs000402 contains the Jackson Heart Study (JHS) subset of GO-ESP/Heart-GO. Additional GO-ESP data is also available via dbGaP.

  Study phs000402

• National Heart Lung and Blood Institute (NHLBI) GO-ESP: Heart Cohorts Component of the Exome Sequencing Project (CHS)

  The NHLBI "Grand Opportunity" Exome Sequencing Project (GO-ESP), a signature project of the NHLBI Recovery Act investment, was designed to identify genetic variants in coding regions (exons) of the human genome (the "exome") that are associated with heart, lung and blood diseases. These and related diseases that are of high impact to public health and individuals from diverse racial and ethnic groups will be studied. These data may help researchers understand the causes of disease, contributing to better ways to prevent, diagnose, and treat diseases, as well as determine whether to tailor prevention and treatments to specific populations. This could lead to more effective treatments and reduce the likelihood of side effects. GO-ESP is comprised of five collaborative components: 3 cohort consortia - HeartGO, LungGO, and WHISP - and 2 sequencing centers - BroadGO and SeattleGO. HeartGO is a consortium of six well-phenotyped NHLBI cohorts: Atherosclerosis Risk in Communities (ARIC) study, the Coronary Artery Risk Development in Young Adults (CARDIA) study, the Cardiovascular Health Study, the Framingham Heart Study, the Jackson Heart Study, and the Multi-Ethnic Study of Atherosclerosis. Together, these cohorts have provided DNA and phenotype datasets from a diverse cohort of individuals of African-American, Caucasian, Asian, and Hispanic ancestry to be made available for use by qualified investigators in dbGaP. HeartGO investigators will conduct genotype-phenotype analyses for phenotypes related not only to heart disease but with other variables that will be contributed to dbGaP. The HeartGO dataset provides investigators with genotype-phenotype analytic opportunities for traits not only related to heart disease but also associated with ancillary variables that will be contributed to dbGaP, including disease endpoints, risk factors, biomarkers, and subclinical disease measures. The phenotypes planned for investigation as part of the GO-ESP HeartGO project include early-onset myocardial infarction (EOMI), low density lipoprotein (LDL) cholesterol, body mass index/type 2 diabetes (BMI/T2D), blood pressure and ischemic stroke. Results of the proposed analyses as well as relevant replication/follow-up analyses will be reported in peer-reviewed journals. This study phs000400 contains the Cardiovascular Health Study (CHS) subset of GO-ESP/Heart-GO. Additional GO-ESP data is also available via dbGaP.

  Study phs000400

• Virtual Growing Child 5-Dimensional Functional Models for Treating Respiratory Anomalies (dMRI-VGC)

  Objectives We are sharing a database of dynamic magnetic resonance imaging (dMRI) scans of normal children, which can serve as a reference standard to quantify regional respiratory abnormalities in young patients with various respiratory conditions and facilitate treatment planning and response assessment. The database can also be useful to advance future AI-based research on image-based object segmentation and analysis. Background In pediatric patients with respiratory abnormalities, it is important to understand the alterations in regional dynamics of the lungs and other thoracoabdominal components, which in turn requires a quantitative understanding of what is considered as normal in healthy children. Currently, such a normative database of regional respiratory structure and function in healthy children does not exist. Participants 200 normal children (ages 6-18 years) participated in our research study related to this dataset. DesignThe shared open-source normative database is from our ongoing virtual growing child (VGC) project, which includes 4D dMRI images representing one breathing cycle for each normal child and also segmentations of 10 objects at end expiration (EE) and end inspiration (EI) phases of the respiratory cycle in the 4D image. The lung volumes at EE and EI as well as the excursion volumes of chest wall and diaphragm from EE to EI, left and right sides separately, are also reported. The database has thus 4,000 3D segmentations from 200 normal children in total. The database is unique and provides dMRI images, object segmentations, and quantitative regional respiratory measurement parameters of volumes for normal children. All dMRI scans are acquired from normal children during free-breathing. The dMRI acquisition protocol was as follows: 3T MRI scanner (Verio, Siemens, Erlangen, Germany), true-FISP bright-blood sequence, TR=3.82 ms, TE=1.91 ms, voxel size ~1×1×6 mm3, 320×320 matrix, bandwidth 258 Hz, and flip angle 76o. With recent advances, for each sagittal location across the thorax and abdomen, we acquired 40 2D slices over several tidal breathing cycles at ~480 ms/slice. On average, 35 sagittal locations are imaged, yielding a total of ~1400 2D MRI slices, with a resulting total scan time of 11-13 minutes for any particular study participant.The collected dMRI scan data then went through the procedure of 4D image construction, image processing, object segmentation, and volumetric measurements from segmentations. 4D image construction: For the acquired dMRI scans, we utilized an automated 4D image construction approach to form one 4D image over one breathing cycle (consisting of typically 5-8 respiratory phases) from each acquired dMRI scan to represent the whole dynamic thoraco-abdominal body region. The algorithm selects 175-280 slices (35 sagittal locations × 5-8 respiratory phases) from the 1400 acquired slices in an optimal manner using an optical flux method. Image processing: Intensity standardization is performed on every time point/3D volume of the 4D image so that image values have the same tissue-specific meaning across all subjects. Object segmentation: For each subject, there are 10 objects segmented at both EE and EI time points in this database. They include the thoracoabdominal skin outer boundary, left and right lungs, liver, spleen, left and right kidneys, diaphragm, and left and right hemi-diaphragms. All dMRI scans utilize large field of view images, which include the full thorax and abdomen to the inferior aspect of the kidneys in the sagittal plane. We used a pretrained U-Net based deep learning network to first segment all objects, and then all auto-segmentation results were visually checked and manually refined as needed, under the supervision of a radiologist with over 25 years of expertise in MRI and thoracoabdominal radiology. Manual segmentations have been performed for all objects in all datasets. Volumetric measurements based on object segmentations for lung volumes (left and right separately) at EE and EI, as well as for chest wall and diaphragm excursion volumes (left and right separately) are reported. ConclusionsThe provided database is unique and provides dMRI images, object segmentations, and quantitative regional respiratory measurement parameters of volumes for normal children. The database has 4,000 3D segmentations from 200 normal children, which to our knowledge is the largest and only such dMRI dataset to date. All images and object segmentations are saved in DICOM. All DICOM files (176,574 in total) have been anonymized, and PHI has been removed. The database can be used as a reference standard to quantify regional respiratory abnormalities in young patients with various respiratory conditions and facilitate treatment planning and response assessment. The large amount of object segmentations can potentially benefit AI-based research on image-based object segmentation and analysis.

  Study phs004002

• Repli-seq data for 'Replication timing alterations are associated with mutation acquisition during tumour evolution in breast and lung cancer'

  The essential process of DNA replication timing during each cell cycle is highly regulated ensuring the correct duplication of the genome. The extent and importance of alterations in this process during malignant transformation has not been extensively explored. Here, we evaluate the impact of altered replication timing (ART) on cancer evolution by analysing replication-timing sequencing of cancer and normal cell lines and 952 whole-genome sequenced lung and breast tumours. We find 6%-18% of the cancer genome displays ART. Genomic regions with a change from early to late replication exhibit an increased mutation rate and distinct mutational signatures, while regions changing from late to early contain genes with increased expression and present a preponderance of APOBEC3-mediated mutation clusters and associated driver mutations. We demonstrate that ART is a relatively early event during cancer evolution and that ART may have a stronger correlation with mutation acquisition than alterations in chromatin structure.

  Study EGAS00001007773

• Ulcerative Colitis Human Microbiome Project (UCHMP)

  The aims of the multi-center Ulcerative Colitis Human Microbiome Project (UCHMP) are to examine the role of the enteric microbiome in causing human ulcerative colitis, specifically the development of pouchitis. Pouchitis is an inflammatory condition of the surgically-created ileoanal pouch that serves as a pseudo-rectum in patients with ulcerative colitis who have undergone a total colectomy. It is a condition unique to ulcerative colitis (UC), as it rarely occurs in non-UC patients who have the same procedure. Within one year, about 50% of patients will develop pouchitis. The condition is almost certainly due to aspects of the pouch microbiota on a background of genetic susceptibility, as most patients respond to treatment with antibiotics. While there have been reports on the microbiota in pouchitis patients, all have been performed after the inflammatory process is initiated, rendering interpretation of the results difficult, as the inflammatory process itself will change the microbiota. Our project is therefore unique and possibly the only opportunity in the role of the enteric microbiome in IBD in a prospective manner, thereby establishing potentially important causal relationships between microbiota structure or function and development of UC.The studies also offer two additional advantages. First, the development of the pouch microbiota can be observed prospectively. Second, the cause of antibiotic treatment failure in some patients with pouchitis may be revealed. The two aims are (1) to identify causal factors in the structure and/or function of the enteric microbiota in the development of pouchitis, and (2) to determine the basis of treatment failure in UC pouchitis patients. Our analyses will include serial measurements of enteric microbial structure (16S rRNA gene-based), function (metagenomics and functional candidate genes), and cultivation, the latter to enhance interpretation of gene sequences derived from metagenomes and targeted gene surveys (either functional or 16S genes). The insights gained from these studies will help us understand the fundamental and causative roles of the enteric microbiome in human inflammatory bowel diseases (IBD). This information will be the basis for developing strategies to restore host-microbial relationships to prevent and treat IBD.

  Study phs000262

• Reading about genomic analysis of pan-neuroblastoma

  There are virtually no research fields that do not benefit from the large-scale genomic analysis that are so popular nowadays. For research into diseases with highly diverse clinical behavior like pediatric neuroblastoma, nevertheless, this type of approach has been a game-changer. Samuel W. Brady and colleagues, from St. Jude Children’s Research Hospital in Memphis, have gathered data from 702 neuroblastomas which were profiled by whole genome sequencing (WGS, n = 205), whole exome sequencing (WES, n = 539), and/or RNA-Seq. Less than half of the samples were generated during this study, while the others were obtained from previous work. Part of the WES data was indeed deposited in EGA in 2012 (EGA study EGAS00001000213). A scratchy summary about the huge work from Samuel W. Brady and colleagues, published in Nature Communications this October 2020 “These findings suggest that the sympathetic nervous system, the tissue from which neuroblastoma arises, is susceptible to different oncogenic insults at different times during development, which could be explored in future investigations using animal models.” Conclude the authors, highlighting the importance of their findings. Pediatric neuroblastomas are classified according to clinical and molecular features into low, intermediate, and high risk. Age plays a critical role in the classification, with younger children having an overall better prognosis. The samples included in this study belonged to all ages and risk-groups: the aim of such set up is the identification of age-associated molecular aberrations. The authors defined a mutational landscape of pediatric neuroblastoma including rare driver events, impossible to pick with a smaller data set. Interestingly, most driver mutations' frequency was found to be age-related. Those include alterations on MYCN, TERT, PTPRD, and Ras pathway, in addition to the previously reported ATRX. In addition, the large data set allowed the authors to define co-existence relations between the mutations (mutual exclusion or co-occurrence) which is a crucial puzzle piece to unravel the mechanisms driving the pathogenesis. Enjoy this really interesting article, open source on Pubmed.

  Blog genomic-analysis-of-pan-neuroblastoma

• BMP4 and temozolomide synergize in the majority of patient derived glioblastoma cultures

  The poor prognosis of patients with glioblastoma is partly due to resistance to standard treatment, which combines chemoradiation using temozolomide (TMZ). The concept of cancer stem cells provided new insight into tumor resistance and management, and isolated Glioblastoma stem-like cells (GSCs) which contribute to this therapy resistance. Bone morphogenetic protein 4 (BMP4) is a differentiation factor that stimulates astroglial differentiation of such GSCs, thereby reducing their self-renewal. Exposing GSCs to BMP4 could therefore sensitize them to chemotherapy with TMZ, but previous studies with various treatment paradigms have produced contradictory results in this matter. Therefore, we re-defined the optimal treatment paradigm for the combination of TMZ and BMP4 and subsequently re-assessed the inter-tumoral variability in response to co-treatment with TMZ+BMP4 in vitro. First, the simultaneous treatment was found more effective than sequential therapy. Second, after application of our optimized treatment protocol, 70% of a total of 20 patient-derived glioblastoma cultures showed synergy when the treatments were combined. The synergistic effect was a result of increased cellular apoptosis and not of decreased proliferation. Comparative RNA-sequencing suggested that combination treatment results in decreased MAPK signaling. We conclude that addition of BMP4 to standard therapy with TMZ could enlarge the group of patients with good therapeutic response.

  Study EGAS00001007095

• RAG mediated recombination is the predominant driver of oncogenic rearrangement in ETV6-RUNX1 Acute Lymphoblastic Leukemia (Rearrangement_sequencing_data)

  The ETV6-RUNX1 fusion gene, found in 25% of childhood acute lymphoblastic leukemia (ALL), is acquired in utero but requires additional somatic mutations for overt leukemia. We used exome and low-coverage whole-genome sequencing to characterize the critical secondary events associated with leukemic transformation. RAG-mediated deletions emerge as the dominant mutational process, accounting for at least 43% of genomic rearrangements and characterized by the presence of recombination signal sequence motifs near the breakpoints; incorporation of non-templated sequence at the junction and a ten-fold enrichment at promoters and enhancers of genes actively transcribed in early B-lineage development. Single-cell tracking shows that this mechanism is not restricted to one founder cell but is rather active throughout leukemic evolution. Integration of point mutation and rearrangement data identifies recurrent inactivation of ATF7IP and MGA as two new tumor suppressor genes.Thus, a remarkably parsimonious mutational process transforms ETV6-RUNX1 lymphoblasts, striking promoters and enhancers of the genes that normally control B-cell differentiation.

  Dataset EGAD00001000635

• RAG mediated recombination is the predominant driver of oncogenic rearrangement in ETV6-RUNX1 Acute Lymphoblastic Leukemia (Whole_exome_sequencing_data)

  The ETV6-RUNX1 fusion gene, found in 25% of childhood acute lymphoblastic leukemia (ALL), is acquired in utero but requires additional somatic mutations for overt leukemia. We used exome and low-coverage whole-genome sequencing to characterize the critical secondary events associated with leukemic transformation. RAG-mediated deletions emerge as the dominant mutational process, accounting for at least 43% of genomic rearrangements and characterized by the presence of recombination signal sequence motifs near the breakpoints; incorporation of non-templated sequence at the junction and a ten-fold enrichment at promoters and enhancers of genes actively transcribed in early B-lineage development. Single-cell tracking shows that this mechanism is not restricted to one founder cell but is rather active throughout leukemic evolution. Integration of point mutation and rearrangement data identifies recurrent inactivation of ATF7IP and MGA as two new tumor suppressor genes.Thus, a remarkably parsimonious mutational process transforms ETV6-RUNX1 lymphoblasts, striking promoters and enhancers of the genes that normally control B-cell differentiation.

  Dataset EGAD00001000636

• RAG mediated recombination is the predominant driver of oncogenic rearrangement in ETV6-RUNX1 Acute Lymphoblastic Leukemia (Whole_Genome_sequencing_data)

  The ETV6-RUNX1 fusion gene, found in 25% of childhood acute lymphoblastic leukemia (ALL), is acquired in utero but requires additional somatic mutations for overt leukemia. We used exome and low-coverage whole-genome sequencing to characterize the critical secondary events associated with leukemic transformation. RAG-mediated deletions emerge as the dominant mutational process, accounting for at least 43% of genomic rearrangements and characterized by the presence of recombination signal sequence motifs near the breakpoints; incorporation of non-templated sequence at the junction and a ten-fold enrichment at promoters and enhancers of genes actively transcribed in early B-lineage development. Single-cell tracking shows that this mechanism is not restricted to one founder cell but is rather active throughout leukemic evolution. Integration of point mutation and rearrangement data identifies recurrent inactivation of ATF7IP and MGA as two new tumor suppressor genes.Thus, a remarkably parsimonious mutational process transforms ETV6-RUNX1 lymphoblasts, striking promoters and enhancers of the genes that normally control B-cell differentiation.

  Dataset EGAD00001000634

• German early-onset prostate cancer cohort of the Pan-Prostate Cancer Genome (PPCG) project

  Prostate cancer is the most frequent malignant tumor in males and the second most frequent cause of cancer-related death. Currently, in Germany, more than 60,000 prostate cancers are diagnosed every year. Although most of these patients are treated in a curative attempt, more than 10,000 German men die from prostate cancer annually. Owing to the demographic changes of our society, a further doubling of prostate cancer incidences during the next 20 years is expected. Prostate cancer is generally considered a tumor of elderly men. However, a fraction of prostate cancers are diagnosed at the age of 55 years or less. For several reasons, these “early onset prostate cancers” may represent a key entity for the understanding of prostate cancer biology. First, it is likely that early onset prostate cancers represent a distinct molecular subgroup of prostate cancer (PCa), potentially characterized by relatively small numbers of genetic changes, some of which may be particularly strong driver mutations for PCa development. Second, a fraction of prostate cancers in young individuals could represent classical prostate cancers that are detected at a very early stage and might therefore have accumulated molecular changes/mutations occurring that are most instrumental for prostate cancer early detection. Third, PCa with hereditary backgrounds are likely to accumulate in the age group below 55 years. A comparison with other sample sets (e.g. from other ICGC consortia), a systematic genomic analysis of young men with PCa could therefore lead to the detection of mechanisms for hereditary PCa. Fourth, a better understanding of these tumors is particularly relevant as finding optimal treatment regimens is most critical in young cancer patients. We are analyzing the entire genomic DNA sequences of at least 200 PCas (and matched non-tumorous DNA) of young men (≤ 55y), to at least 30 fold coverage, and integrate single-nucleotide variants and genomic structural variations with differential methylation, mRNA and miRNA expression data.Tissues were collected at the University Medical Center Hamburg-Eppendorf. Sequencing was performed at DKFZ and NCT (Heidelberg), EMBL (Heidelberg), and MPIMG (Berlin). Data management and bioinformatic data analyses is being conducted at DKFZ.

  Study EGAS00001003373

• Aberrant Oligoclonal Hematopoiesis in Remission AML and Relapse from Rare Cells Genomically Resembling Leukemic Blasts

  Acute myelogenous leukemia (AML) is a hematological malignancy that often responds well to initial treatment in which patients achieve a complete remission (CR). Nevertheless, most patients will relapse after achieving a CR, which is often fatal. This minimal residual disease (MRD) that remains after CR is likely the source of relapse and so improved measurement and characterization of these residual cells is critical. Employing droplet digital PCR (ddPCR), we were able to measure mutated alleles of many recurrently mutated genes in bone marrow samples acquired during CR from AML patients at levels as low as 0.002% variant allele frequency. Most of these gene mutations persisted in CR but at very variable and gene-dependent levels. Most AML cases involved residual aberrant oligoclonal hematopoiesis, and rare cell populations (as few as 1 in 15,000) were detected that were genomically similar to the AML blast populations at that dominated at diagnosis and were fully clonally represented at relapse. From a clinical perspective, the mutant allele frequency correlated closely with relapse-free and overall survival.

  Study phs001408

• Identification and Molecular Characterization of Somatic Mutations in Malformations of Cortical Development

  Genetic mutations causing disease may be inherited, newly acquired in parental gametes and present in the zygote or acquired as somatic events at some point in development after fertilization. The burden and localization of an acquired mutation depend on when the mutation arises. As is the case for inherited genetic variation, there is accumulating evidence that somatic mutations can lead to severe tissue-specific disease. Malformations of cortical development (MCD) represent a group of disorders characterized by a range of morphological and structural abnormalities of the cerebral cortex reflecting errors in embryonic cortical development. MCD are associated with intellectual disability, as well as refractory epilepsy, and may require the surgical removal of the affected tissue. Inherited gene mutations involved in neuronal development explain only a fraction of MCD cases. In this project we sought to evaluate the hypothesis that somatic mutations disrupt embryonic cortical development and are responsible for a substantial fraction of MCD. Using high coverage next generation sequencing of protein-coding regions in DNA extracted from abnormal brain tissue and unaffected tissue (leukocytes) from patients with three forms of MCD, we sought to identify somatic mutations within each patient with MCD. Exome sequence data from study participants are provided to facilitate research into the genetic underpinnings of MCD.

  Study phs002128

• RNA sequencing data from patient derived colorectal cancer organoids

  This study aimed to develop NovumRNA, a bioinformatics pipeline designed to predict non-canonical tumor-specific antigens (ncTSAs) from human tumor RNA-sequencing data, potentially broadening the target pool for cancer neo-epitope-based immunotherapies. The pipeline was utilized to analyze RNA-seq data from ten patient-derived colorectal cancer (CRC) organoids, representing seven microsatellite stable (MSS) and three microsatellite instable (MSI) tumors. The goal was to explore the ncTSA landscape in CRC, particularly in MSS cases, which typically exhibit low tumor mutational burden and limited response to current immunotherapies. The study identified comparable ncTSA burdens across MSI and MSS tumors, suggesting new avenues for immunotherapy targeting non-canonical antigens in CRC. NovumRNA is available at: https://github.com/ComputationalBiomedicineGroup/NovumRNA.

  Study EGAS50000000685

• Genetics and Pathophysiology of Autoinflammatory Disorders

  In this study, patients with suspected disorders of inflammation and innate immune system dysregulation will undergo whole exome sequencing. This will involve both family studies (often trios or multiplex families including affected and unaffected individuals) and sporadic cases. The overall objective is to discover rare/novel high-penetrance mutations in genes that have not yet been implicated as the cause of monogenic autoinflammatory diseases. The aim also includes discovery of variants associated with inflammatory disease susceptibility.

  Study phs001860

• Somatic mutation burden and copy-number variation analysis in neurofibromatosis type 1-associated plexiform neurofibromas

  Neurofibromatosis type 1 (NF1) is a common tumor-predisposition disorder due to germline mutations in the tumor suppressor gene NF1. A virtually pathognomonic finding of NF1 is the plexiform neurofibroma (PN), a benign, likely congenital tumor that arises from biallelic inactivation of NF1. PN can undergo transformation to a malignant peripheral nerve sheath tumor, an aggressive soft-tissue sarcoma. To better understand the non-NF1 genetic contributions to PN pathogenesis, we performed whole-exome sequencing and genome-wide copy-number determination for 23 low-passage Schwann cell cultures established from surgical PN material with matching germline DNA. All resected tumors were derived from routine debulking surgeries. None of the tumors were considered at risk for malignant transformation at the time, e.g., there was no pain or rapid growth. Deep (~500X) NF1 exon sequencing was also conducted on tumor DNA. Non-NF1 somatic mutation verification was performed using the Ampliseq/IonTorrent platform. We identified 100% of the germline NF1 mutations and found somatic NF1 inactivation in 74% of the PN. One individual with three PNs had different NF1 somatic mutations in each tumor. The median number of somatic mutations per sample, including NF1, was one (range 0 - 8). NF1 was the only gene that was recurrently somatically inactivated in multiple tumors. We found no recurrent non-NF1 locus copy-number variation in PN. This is the first multi-sample whole-exome sequencing study of NF1-associated PN. Taken together with concurrent copy-number data, our comprehensive genetic analysis reveals the primacy of NF1 loss as the driver of PN tumorigenesis.

  Study phs001403