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• Lung Multi-site Targeted Sequence Capture

  DNA extracted from multiple biopsies taken from different areas of primary lung tumours will be subjected to targeted re-sequencing and analysed in order to assess intra-tumour heterogeneity with respect to mutations in a selection of cancer related genes.

  Dataset EGAD00001001017

• Array data for oesophageal and related samples – Ganguli et al (methylation array)

  Array data for oesophageal and related samples – Ganguli et al (methylation array)

  Dataset EGAD00010002682

• Sequencing data for oesophageal and related samples - Ganguli et al (sWGS)

  Data supporting: "TBC" Ganguli et al (sWGS for 75 samples)

  Dataset EGAD00001011189

• Splicing signature analysis of RNU4-2, RNU5A-1 and RNU5B-1

  Pathogenic variants in the snRNA RNU4-2 were recently described as a frequent cause of neurodevelopmental disorders. In our study we further delineate the phenotype associated with RNU4-2 and we also identify pathogenic variants in RNU5A-A and RNU5B-1. Capture-based RNA-Seq were performed to compare splicing pattern between affected and control individuals. A strong signature based on alternative 5' splice site usage was found for RNU4-2 patients, and we suggest an either 5' or 3' signature depending on the variant's localiztion in U5 genes.

  Study EGAS50000000889

• Functionally Active Copy Number Variants Associated with Prostate Cancer Risk

  Prostate cancer is a leading cause of cancer death in males throughout the world and has the largest estimated effect of heritability among the most common tumor types. Copy Number Variants (CNVs) are a recently recognized class of human germline polymorphisms (Iafrate AJ, et al. (2004) Nat Genet 36, 949-951; Sebat J, et al. (2004) Science 305, 525-528.) and are associated with a variety of human diseases, including cancer. This study characterized 1,903 individuals from the Tyrol Early Prostate Cancer Detection Program (Bartsch G, et al. (2008) BJU Int 101, 809-816) using a computational framework (Banerjee S, et al. (2011) PLoS One 29;6(3)). The study results establish non-coding and coding germline CNVs as significant risk factors for prostate cancer susceptibility and implicate their role in disease development and progression. The study "Identification of functionally active, low frequency copy number variants at 15q21.3 and 12q21.31 associated with prostate cancer risk," Demichelis F, Setlur SR, Proc Natl Acad Sci U S A. 2012 Apr 24;109(17):6686-91.

  Study phs000487

• RNA sequencing from High-grade B-cell lymphoma, not otherwise specified: an LLMPP study

  RNA-seq for 26 newly added samples in High-grade B-cell lymphoma, not otherwise specified: an LLMPP study, and 32 samples from a previously uploaded dataset.

  Dataset EGAD50000001365

• Neuroblastoma_MP-PCR_MultiplexPCR_TargetedSequencing_BAMs

  This dataset contains raw sequencing data (BAM/BAI files) generated from human neuroblastoma patient samples. The data were produced using targeted high-throughput next-generation sequencing and are intended to support genomic analyses of tumor-associated alterations. All files are provided under controlled access in accordance with EGA data protection requirements.

  Dataset EGAD50000002260

• Mutation analysis of 17 genes in plasma DNA of CRC patients using the AVENIO ctDNA Targeted Kit

  Mutation analysis of 17 genes (ALK, APC, BRAF, BRCA1, BRCA2, DPYD, EGFR, ERBB2, KIT, KRAS, MET, NRAS, PDGFRA, RET, ROS1, TP53, UGT1A1) in plasma DNA of CRC patients using the AVENIO ctDNA Targeted Kit.

  Dataset EGAD00001006103

• Whole genome sequencing data of high-grade serous ovarian cancer samples (set 8a)

  Whole genome sequencing data of 26 high-grade serous carcinoma (HGSC) patients (87 samples) sequenced with MGISEQ-2000 and HiSeq X Ten.

  Dataset EGAD00001011304

• Verification of BCR reconstruction from single-cell RNA-seq using BraCeR

  This dataset was made to verify the computational reconstruction of B cell reseptors from single-cell RNA-seq using BraCeR. The dataset contains BCR-derived reads from single-cell RNA-seq from 13 cells using the Smart-seq2 protocol, as well as targeted BCR-sequencing data from the same cells.

  Dataset EGAD00001004199

• Dedifferentiated Melanoma (2021-02-02)

  De- and transdifferentiation of melanoma is a rare histopathological phenomenon that has not be characterised genetically. In this project we plan to sequence the genomes of de and transdifferentiated cases so as to define their genetic make-up. . This dataset contains all the data available for this study on 2021-02-02.

  Dataset EGAD00001006931

• Detection of cancers three years prior to diagnosis using plasma cell-free DNA

  A major goal of early cancer detection is to identify subclinical disease when the tumor burden is low, so that treatments are more effective. But how early can cancers be detected prior to clinical signs or symptoms? This question can be answered only through the evaluation of participants whose clinical course has not been altered by the study itself. We here describe such an evaluation, performed on prospectively collected plasma samples from the Atherosclerosis Risk in Communities (ARIC) study, including 26 participants diagnosed with cancer and 26 matched controls. At the index time point, eight of these 52 participants scored positively with a multicancer early detection (MCED) blood test. All eight of these participants were diagnosed with cancer within 4 months after blood collection. In six of these 8 participants, we were able to assess an earlier plasma sample collected 3.1 to 3.5 years prior to clinical diagnosis. In four of these six participants, the same mutations detected by the MCED test could be identified, but at 8.6 to 79-fold lower levels. These results demonstrate that it is possible to detect circulating tumor DNA (ctDNA) more than three years prior to clinical diagnosis, and provide benchmark sensitivities required for the success of ctDNA-based tests for this purpose.

  Study EGAS00001008068

• 20210729_EGA_BrainMet Saunus et al J Path (2015)

  Exome sequencing on HiSeq platform of 36 brain metastases with matched normal samples, 32 having matched RNA seq. Published Saunus et al J Path, (2015); https://doi.org/10.1002/path.4583

  Dataset EGAD00001007973

• Genome-Wide Association Study of HCC in Non-Asian USA Population

  This GWAS of HCC relied on existing biological and data resources from 7 USA sites and one Canadian site which allows for the integration of genetic and environmental data. Total of 2199 case patients and 1103 non cancer controls were genotyped. Case patients are defined as patients with pathological or radiological diagnosis of HCC with and without chronic hepatitis C virus infection. Study was restricted to Caucasian population without prior infection with chronic HBV infection. All DNA samples were extracted from peripheral blood. Study population of the participated sites are: Site-1: University of Texas MD Anderson Cancer Center A hospital based-case-control study was initiated at UT MD Anderson Cancer Center in 2000 and approved by the Institutional Review Board of The University of Texas M. D. Anderson Cancer Center. Study design was previously described in detailed (1-3). Written informed consent for an interview and for a biological sample was obtained from each participant. At time of diagnosis prior to treatment exposure. Case patients were recruited from the population of patients with newly diagnosed HCC who were evaluated and treated at the institution's gastrointestinal medical and surgical oncology outpatient clinics. Inclusion criteria were as follows: a pathologically confirmed diagnosis of HCC, U.S. residency, and the ability to communicate in English. Patients with concurrent or past history of other types of cancers were excluded. Control subjects were healthy spouses of patients with cancers other than liver, gastrointestinal, lung, or head and neck (smoking-related cancers) undergoing treatment at our institution. Eligibility criteria for control subjects were the same as those for patients, except that control subjects could not have ever had cancer. A short, structured questionnaire was used to screen potential control subjects on the basis of eligibility criteria. Control subjects and patients were recruited simultaneously. Case patients and control subjects were interviewed by well-trained interviewers who followed a written protocol to guide ascertainment and reduce surveillance, interviewer, and recall bias. No proxy interviews were conducted. The interviewers used a structured and validated questionnaire to collect information about demographic characteristics and potential risk factors for HCC such as personal smoking history, alcohol use, medical history, occupational history, and family history of cancer. Blood samples from cases and controls were tested for HBV and HCV. HCV antibodies, hepatitis B surface antigen, and antibodies to hepatitis B core antigen were detected by use of a third-generation enzyme-linked immunosorbent assay (ELISA) (Abbott Laboratories, North Chicago, IL). Important clinical information were retrieved from patients' medical records. Total of 1188 case patients and 278 controls from MD Anderson study were genotyped. Site-2: Mayo Clinic Case patients and controls included in the study from Mayo clinic were recruited as part of Mayo International Hepatobiliary Neoplasia Register and Biorepository. Only USA patients and controls were participated. All cases and controls signed informed consent indicating their willingness to participate in genetic studies. Epidemiological and clinical data were collected from participants and retrieved from medical records. Total of 522 HCC case patients and 182 controls were genotyped in this study. Site-3: Toronto University Molecular Epidemiology of Hepatobiliary Tumors (HBT study, CAPCR 09-0289) is a hospital-based study that includes 1710 patients diagnosed with liver, bile duct or gallbladder adenocarcinoma (Hepatocellular carcinoma - HCC; cholangiocarcinoma - CCA; and gall bladder adenocarcinoma -GBCa) recruited at University Health Network (UHN) between 2009 and 2018. HBT study is a prospective study of cancer patients that collects self-reported demographic and epidemiological data, medical records/clinical information and blood samples for research purposes. Eligible patients recruited between 2009 and March 15 2016 were selected to participate in the Genome-Wide Association Study in Patients with Hepatocellular Carcinoma (GWAS in HCC, CAPCR 15-9943-CE), a sub-study of the HBT study. Eligible prospective patients recruited after March 15 2016 signed the Addendum to the HBT consent form and became eligible to participate in the GWAS in HCC study. Total of 271 cases and 21 controls were genotyped from Toronto University Site-4: University of Pittsburgh The design of the study has been described previously (4-6). Briefly, this population-based study enrolled 120 HCC patients and 230 matched controls from black, Hispanic, and non-Hispanic white residents of Los Angeles County who were between 18 and 74 years of age at diagnosis from January 1995 through December 2001. HCC Cases were identified through the Los Angeles County Cancer Surveillance Program. We sought to recruit up to two control subjects per case from the neighborhoods where HCC patients resided at the time of diagnosis, who were matched to the index case by sex, age (within 5 years), and race (Hispanic white, non-Hispanic white, black). Blood samples (plasma and buffy coat), medical and lifestyle factors were collected from all consenting participants. Total of 65 cases and 60 controls were genotyped in this study Site-5: South Western Dallas Under IRB approval, HCC Cases and controls were prospectively collected since 2015 from the outpatient Liver clinics from Parkland Health and Hospital System and UT Southwestern Medical Center, two large health systems in Dallas TX. A Total of 31 cases and 29 controls were genotyped from site 5. Site-6: Columbia University HCC patients from Columbia are those recruited as part of the Herbert Irving Comprehensive Cancer Center Database Shared Resource which seeks to recruit all cancer patients for potential future studies. The PI is Dr. Katherine Crew AAAL5871. This resource collects sociodemographic, lifestyle and clinical data on patients as well as a blood sample. Those who indicated on their consent form that they would participate in genetic studies were included. Total of 79 case patients with HCC were genotyped from Columbia University. Site-7: University of Michigan The study population included from University of Michigan were included from a prospective study of with chronic HCV infection recruited in Ann Arbor Patients who had under- gone liver transplantation, known coinfection with HIV, life expectancy <12 months due to extra-hepatic illnesses, or were receiving HCV treatment at enrolment, were excluded. Protocol, surveys, and data forms were developed where each enrolled patient completed the same questionnaire All patients provided written informed consent before enrolment in the study. The study was approved by the institutional review board or ethics committee at the University of Michigan. Detailed study description was previously published (7). Total of 44 cases and 347 controls were genotyped Site-8: Veteran Administration Medical Center in Houston This research including written informed consent form was jointly approved by Institutional Review Boards for the Baylor College of Medicine and the Michael E. DeBakey VA Medical Center in Houston, Texas. Study details have been previously published (8). Briefly, we prospectively recruited consecutive HCV-infected veterans prior to their previously scheduled HCV clinic visit at a large tertiary care VA medical center between May 1, 2009 and December 31, 2012. Patients completed a research assistant (RA) administered survey interrogating medical and risk factor history including lifetime alcohol use, had anthropometric measurements taken, and completed a fasting venipuncture for performance of the FibroSure-ActiTest as a measure of hepatic pathology. We restricted our current analysis to individuals who were: (1) White male veterans between 18 and 70 years; (2) had no history of HCC, liver transplant, decompensated liver disease including ascites, dementia, or psychosis; (3) were serologically-confirmed to have chronic HCV and to be negative for both HIV and active HBV infection; (4) were not currently receiving anti-HCV pharmacotherapy; and (5) had FibroSURE testing shown F3/F4 fibrosis consistent with cirrhosis.

  Study phs001744

• Transcriptome Sequencing PPGL (2)

  RNA-Seq data (n=81) library preparation was performed as previously reported by Calsina et al 2023 using QuantSeq 3' mRNA-Seq Library Prep Kit FWD for Illumina (Lexogen, 015). The prepared libraries were subsequently sequenced on NovaSeq™ system (Illumina). To combine the new CNIO samples (n=81) with the CNIO+TCGA dataset generated in Calsina et al., 2023, RNA data were processed using ComBat-seq as described in that same article.

  Study EGAS50000000013

• 120 individuals from the TEENAGE study (Ntalla et al., 2013) have been genotyped on the Illumina HumanCoreExome-12v1-1_A array. This is a population-based study of adolescents from the Attica region in Greece

  120 individuals from the TEENAGE study (Ntalla et al., 2013) have been genotyped on the Illumina HumanCoreExome-12v1-1_A array. This is a population-based study of adolescents from the Attica region in Greece

  Study EGAS00001001733

• Characterization of the molecular signature of human monocytes in aging and myelodysplastic syndrome

  Deep immunophenotypic profiling of peripheral blood immune cells from young and older control subjects as well as patients with MDS was initially performed, using mass cytometry to identify monocyte subpopulations. Abundance of monocyte subpopulations separated the samples from patients with MDS from elderly control subjects was identified. Therefore, targeted immunophenotyping of monocytes was also performed with flow cytometry and RNA sequencing from isolated CD14+ peripheral blood longitudinally in 26 subjects, six young healthy individuals, nine older healthy individuals and eleven patients with MDS.

  Study EGAS00001007676

• Datasets of RNA-seq of tumor samples from clear cell renal cell carcinoma patients included in the Translational Program of the NIVOREN GETUG-AFU-26 trial

  RNA-seq analyses were performed on tumor tissue samples of 115 advanced clear cell renal cell carcinoma patients who participated in the NIVOREN GETUG-AFU-26 trial. The samples were obtained prior to treatment initiation. RNA-seq was performed to evaluate previously published gene expression signatures. These included: the IMmotion T effector (CD8A, EOMES, PRF1, IFNG and CD274) and the IMmotion Myeloid (IL-6, CXCL1, CXCL2, CXCL3, CXCL8, and PTGS2) gene signatures represent gene expression patterns associated with T effector cells and myeloid cells, respectively, while JAVELIN Renal 101 Immuno (T-cell receptor signaling: CD3G, CD3E, CD8B, THEMIS, TRAT1, GRAP2, CD247; T-cell activation, proliferation, and differentiation: CD2, CD96, PRF1, CD6, IL7R, ITK, GPR18, EOMES, SIT1, NLRC3; Natural killer cell mediated cytotoxicity: D2, CD96, PRF1, CD244, KLRD1, SH2D1A; Chemokine: CCL5, XCL2; and Other immune response genes: CST7, GFI1, KCNA3, PSTPIP1) represents gene expression patterns associated with both innate and adaptive immune response.

  Dataset EGAD50000001541

• Whole Exome Sequencing of Human Gastro-esophageal Cancer PDXs

  The current study investigates biomarkers of response to anti-EGFR therapies in gastro-esophageal cancer. Whole exome sequencing was performed on 26 tumors to explore potential factors influencing treatment outcomes. As part of the analysis, somatic mutations in EGFR, ERBB2, and key downstream signaling genes (KRAS and PIK3CA) were examined to exclude the presence of known mutations conferring sensitivity/resistance. The study aims to contribute to the identification of patients who may benefit from lower-toxicity regimens, improving treatment personalization and minimizing adverse effects.

  Study EGAS50000000966

• Wilm's tumor sequencing data

  No. of samples: 80 (28 ULP-WGS, 26 WES, 26 RNA-SEQ) File types: FASTQ (28 ULP-WGS, 19 WES, 18 RNA) and BAM (7 WES, 8 RNA) Technology used: Sequencing - Illumina Novoseq 6000; Map/Align - Illumina DRAGEN v3.7.5; Genome assembly - GrCh38p13 Filename nomenclature: - SampleName_Passage_SampleType_TissueType_SequencingType - Passage of: PX = unknown; PZ = from patient; P0 = first passage from patient on plastic; P1 = first passage from plastic/PDX/organoid - SampleType: STN = normal; STT = tumor - SampleType STN: 00 = tissue unknown; 01 = adjacent normal; 02 = fibroblast; 03 = germline blood; 21 = cell line from patient tissue; 22 = cell line from PDX; 23 = cell line from patient fibroblast - SampleType STT: 00 = tissue unknown; 01 = primary tumor; 21 = cell line from patient; 22 = cell line from PDX - TissueType: WT = Wilm's tumor; 00 = kidney unknown; 01 = kidney left; 02 = kidney right - SequencingType: 00 = unknown; 02 = ultra-low pass whole-genome sequencing; 20 = whole-exome; 61 = bulk RNA-sequencing

  Dataset EGAD00001011111

• Differential Transcription Start Site Usage in Brain-related Samples

  RNA-Seq is an effective method to study the transcriptome, but specialized methods are required to identify 5' ends of transcripts. Several published strategies exist for this specific purpose, but their relative merits have not been systematically analyzed. Here, we directly compare the performance of six such methods - testing five with cellular RNA as well as a novel spike-in RNA assay that helps address interpretation challenges that arise from uncertainties in annotation or RNA processing. Using a single human RNA sample, we constructed and sequenced 18 libraries with these methods and one standard, control RNA-Seq library. We find that the CAGE method performed best for mRNA and that most of its unannotated peaks are supported by evidence from other genomic methods. We then applied CAGE to eight brain-related samples and revealed sample-specific transcription start site (TSS) usage as well as a transcriptome-wide shift in TSS usage between fetal and adult brain.

  Study phs001463

• Sci Trans Med - Mouliere et al, 2018. Non-ovarian cancer samples - STM4

  fastq files for shallow whole genome sequencing data as described in Mouliere et al, 2018. Files are those not included in STM2 i.e. these are largely non-ovarian cancer samples

  Dataset EGAD00001006132

• Breast cancer PDTX sequencing data from Bruna et al, Cell 2016

  Breast cancer PDTX sequencing data from Bruna et al, Cell 2016 - Exome Sequencing - Shallow Whole Genome Sequencing - RRBS Methylation Sequencing

  Dataset EGAD00001002685

• Sequencing data for oesophageal and related samples - Ganguli et al (RNA)

  Data supporting: "TBC" Ganguli et al (RNA for 394 samples)

  Dataset EGAD00001011190

• Upcycling and merging data to challenge the dogma and identify new therapeutic targets for Glioblastoma

  Glioblastoma is the most common brain tumour. Characterised by a poor prognosis and its recurrence after multimodal treatments, the search for preventable risk factors has been mainly inconclusive up to date. Recently, the data merge from datasetsdeposited at the EGA allowed Aaron Diaz’s team to discover that the glioblastoma cells shift toward a mesenchymal phenotype when the tumour is recurring. Challenges in glioblastoma research As for virtually all cancer types, many efforts have been made to unveil the molecular features responsible of the disease, and several cellular pathways have indeed been identified as being frequently mutated in glioblastoma. Nonetheless, targeted therapies based on identified genes have so far failed to improve outcome, thus survival mostly relies on a standard treatment unchanged since 2005. This is a frustrating situation for both the scientific and medical communities, and above all for the patients, still facing a dreadful path. Some researchers hypothesised that this may be due to the inability to efficiently target cancer stem cells, the originators of the other cell types, thus inducing cancer relapse. In 2019 Charles P. Couturier and colleagues sequenced RNA from single cells of freshly excised glioblastomas of 16 patients, and demonstrated that glioblastoma cells replicate normal brain cell development with a conserved neural cancer cell hierarchy centered around glial progenitor-like cells. In this way, they helped identify the possible target cells to improve efficacy and durability of treatment. Data upcycling at the EGA: the glioblastoma case study Single cell RNA sequencing is generated with a laborious and expensive protocol. The quality of the starting material is crucial (cells sample freshly extracted from the patients) and often several attempts are needed before producing reliable quality sequencing results. Collecting big numbers of patients is also challenging. The sequencing data produced by Kevin Petrecca’s group in Montreal, Canada and deposited at the EGA (EGAS00001004422) was recently upcycled by Lin Wang in San Francisco, California and pooled with their freshly produced ones, and then deposited at the EGA as Dataset EGAS00001004909 The data merge allowed Aaron Diaz’s team to discover that the glioblastoma cells shift toward a mesenchymal phenotype when the tumour is recurring. They profiled 86 primary-recurrent patient-matched paired glioblastoma samples with single-nucleus RNA, among other techniques. These very comprehensive results lead the team to challenge the findings from several other cancer fields where chemotherapy standard chemo-radiation therapy selection pressure at the level of genomic alterations; this is indeed not the case for glioblastoma, where the pressure results in phenotypic transition between cellular states. Several technical controls were made to ensure that the merge of the data was not introducing a bias in the results, and an Inter-table analysis demonstrated nearly equal contribution to overall variance from each of the studies included, indicating that the findings were not due to inter-laboratory technical effect. A novel principal-component analysis showed that the largest contribution to variation in primary glioblastoma neoplastic cells was an axis between MES (mesenchymal) and proneural expression programs. In summary, treating glioblastoma often makes a MES, as commented by Lucy Stead about this remarkable work. Check Aaron Diaz’s team Nature Cancer paper, with strong technical tools, state of the art analysis and data from different sources converging to the same outcomes that made possible a significant step toward a better handling of a frightful cancer. References Couturier, C.P., Ayyadhury, S., Le, P.U. et al. Single-cell RNA-seq reveals that glioblastoma recapitulates a normal neurodevelopmental hierarchy. Nat Commun 11, 3406 (2020). Stead, L.F. Treating glioblastoma often makes a MES. Nat Cancer 3, 1446–1448 (2022). Wang, L., Jung, J., Babikir, H. et al. A single-cell atlas of glioblastoma evolution under therapy reveals cell-intrinsic and cell-extrinsic therapeutic targets. Nat Cancer 3, 1534–1552 (2022). Related links: Kevin Petrecca’s group dataset deposited at the EGA: EGAS00001004422 Lin Wang dataset deposited at the EGA: EGAS00001004909

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