7196 results for "canc*"

in 19.97 milliseconds.

• Multimodal plasma and urinary cell-free DNA profiling improves risk stratification in newly diagnosed prostate cancer

  Prostate cancer (PCa) is a heterogeneous disease, impeding early detection and risk stratification. Liquid biopsies (LBx) enable minimally invasive tumor profiling, but circulating tumor-derived DNA (ctDNA) detection remains difficult, particularly in early-stage PCa. We developed a multimodal LBx approach combining genomic and epigenomic cell-free DNA (cfDNA) features in plasma and urine from newly diagnosed PCa patients to improve early characterization of PCa and risk stratification of aggressive disease. Plasma and urine samples from 55 localized PCa (lPCa) patients, 18 advanced PCa (aPCa) patients, and 36 cancer-free controls were subjected to low-coverage whole-genome sequencing and methylated DNA immunoprecipitation sequencing to assess fragmentation, chromosomal instability, and methylation in cfDNA. This complementary approach yielded a 45% ctDNA detection rate in newly diagnosed PCa. Major differences were observed between aPCa and controls, reflecting increasing signals with tumor progression. Epigenomic cfDNA features differentiated lPCa from aPCa, and ctDNA was detected in 46% of PCa patients with prostate-specific antigen <10 ng/ml, suggesting potential for risk stratification. This study highlights the value of multimodal LBx approaches for early characterization of primary PCa and identification of aggressive disease at initial diagnosis. Integration into clinical workflows could complement diagnostics and support personalized decision-making tailored to patients’ PCa risk profiles. 

  Study EGAS00001008195

• Primary breast tumor heterogeneity through therapy

  We performed whole-exome sequencing on multiple regions (n=2-3) from four primary untreated breast tumors (n=1 HER2+, n=2 ER+/HER2-, n=1 triple-negative), as well as matched normal. We also performed whole-exome sequencing on one region from the pre-treatment diagnostic core biopsy and multiple regions (n=2-6) from the post-treatment surgical specimen for five HER2+ primary breast tumors, as well as matched normal; all were treated with combination chemotherapy and trastuzumab. Analysis of these specimens allows characterization of breast tumor heterogeneity and clonal evolution.

  Study EGAS00001003168

• CAGEKID: Cancer Genomics of the Kidney

  The aim of CAGEKID is to carry out comprehensive detection of DNA markers for conventional (clear cell) renal carcinoma. The project includes complete analysis of somatic and constitutional DNA variation, methylation patterns and expression in a large number of constitutional/tumor pairs. CAGEKID is a part of the International Cancer Genome Consortium, ICGC.

  Study EGAS00001000083

• Recurrent somatic DICER1 mutations in non-epithelial ovarian tumors

  Background: Germline truncating mutations in DICER1, an RNase III-type endoribonuclease essential for processing of microRNAs, are seen in families with the pleuropulmonary blastoma-family tumor and dysplasia syndrome; these individuals have a propensity to develop non-epithelial ovarian tumors (i.e. sex-cord stromal and germ cell tumors). Methods: We sequenced the whole transcriptomes or exomes of 14 non-epithelial ovarian tumors and noted closely clustered mutations in the RNase IIIb domain of DICER1 in four cases. Using Sanger sequencing, we then analyzed additional ovarian tumors for mutations in this region. The impact of the mutations on the enzymatic activity of Dicer1 was determined using in vitro RNA cleavage assays. Results: RNase IIIb domain DICER1 mutations were found in 30/102 non-epithelial ovarian tumors (29%), predominantly Sertoli-Leydig cell tumors (26/43, 60%), including 4/4 from individuals with germline DICER1 mutations. The mutations were restricted to metal binding sites within the RNase IIIb catalytic centres critical for miRNA interaction and cleavage, and were somatic in all 14 cases where germline DNA was available for testing. Of 266 epithelial ovarian and endometrial cancers tested, one case, an ovarian carcinosarcoma, had a hotspot mutation. In vitro, the mutant DICER proteins showed reduced RNase IIIb activity but retained RNase IIIa activity. Conclusions: Somatic missense mutations of the RNase IIIb domain of DICER1 are common in non-epithelial ovarian tumors. Genetic, pathologic, and functional evidence suggest that these mutations do not obliterate DICER1 function, rather, they alter it in specific cell types, a novel mechanism through which perturbed microRNA expression is oncogenic.

  Study EGAS00001000135

• Full genome sequencing of a monozygotic twin discordant for schizophrenia

  We sequenced the genomes from a monozygotic twin discordant for schizophrenia and a tumor-normal pair of an ovarian cancer patient. Using whole-genome twin data to discriminate between correctly identified single nucleotide variants (SNVs) and errors a strategy for the accurate detection of SNVs was developed. By applying stringent sequencing quality measures, excluding error-prone regions and selecting SNVs identified by different mapping and variation calling algorithms, error rates were ~37-fold reduced. This enabled us to identify the first discordant SNVs in monozygotic twins using whole-genome sequencing. In addition, by showing that novel SNVs are highly enriched in errors, accurate estimates of the number of novel and rare SNVs occurring in unrelated Caucasian individuals were obtained. Finally, somatic mutations in coding and regulatory sequences were reliably identified in the highly rearranged ovarian tumor. Overall, our data demonstrate that strategies to reduce error rates in whole-genomes are required for disease gene discovery.

  Study EGAS00001000152

• Whole genome sequencing of matched primary and metastatic acral melanomas

  Next generation sequencing has enabled systematic discovery of mutational spectra in cancer samples. Here we used whole genome sequencing to characterise somatic mutations and structural variation in a primary acral melanoma and its lymph node metastasis. Our data show that the somatic mutational rates in this acral melanoma sample pair was more comparable to the rate reported in cancer genomes not associated with mutagenic exposure than in the genome of a melanoma cell line or the transcriptome of melanoma short-term cultures. Despite the perception that acral skin is sun-protected, the dominant mutational signature in these samples is compatible with damage due to ultraviolet light exposure. A nonsense mutation in ERCC5 discovered in both the primary and metastatic tumours, could also have contributed to the mutational signature through accumulation of unrepaired dipyrimidine lesions. However, evidence of transcription-coupled repair was suggested by the lower mutational rate in the transcribed regions and expressed genes. The primary and the metastasis are highly similar at the level of global gene copy number alterations, loss of heterozygosity and single nucleotide variation (SNV). Furthermore, the majority of the SNVs in the primary tumour were propagated in the metastasis and one non-synonymous coding SNV and one splice site mutation appeared to arise de novo in the metastatic lesion.

  Study EGAS00001000169

• Driver mutations in histone H3.3 and chromatin remodelling genes in paediatric glioblastoma

  Glioblastoma multiforme (GBM) is a lethal brain tumour in adults and children. However, DNA copy number and gene expression signatures indicate differences between adult and paediatric cases. To explore the genetic events underlying this distinction, we sequenced the exomes of 48 paediatric GBM samples. Somatic mutations in the H3.3-ATRX-DAXX chromatin remodelling pathway were identified in 44% of tumours (21/48). Recurrent mutations in H3F3A, which encodes the replication-independent histone 3 variant H3.3, were observed in 31% of tumours, and led to amino acid substitutions at two critical positions within the histone tail (K27M, G34R/G34V) involved in key regulatory post-translational modifications. Mutations in ATRX (alpha-thalassaemia/mental retardation syndrome X-linked) and DAXX (death-domain associated protein), encoding two subunits of a chromatin remodelling complex required for H3.3 incorporation at pericentric heterochromatin and telomeres, were identified in 31% of samples overall, and in 100% of tumours harbouring a G34R or G34V H3.3 mutation. Somatic TP53 mutations were identified in 54% of all cases, and in 86% of samples with H3F3A and/or ATRX mutations. Screening of a large cohort of gliomas of various grades and histologies (n=784) showed H3F3A mutations to be specific to GBM and highly prevalent in children and young adults. Furthermore, the presence of H3F3A/ATRX-DAXX/TP53 mutations was strongly associated with alternative lengthening of telomeres and specific gene expression profiles. This is, to our knowledge, the first report to highlight recurrent mutations in a regulatory histone in humans, and our data suggest that defects of the chromatin architecture underlie paediatric and young adult GBM pathogenesis.

  Study EGAS00001000226

• A Comprehensive Catalogue of Somatic Mutations from a Human Cancer Genome

  We previously reported the whole-genome sequencing of the well-studied human malignant melanoma cell line, COLO-829, and a lymphoblastoid cell line from the same individual, providing the first comprehensive catalogue of somatic mutations from an individual cancer (Pleasance et al. (2010) Nature 463, 191). This initial study was carried out using the Illumina Genome Analyzer II, largely using paired-end reads of 75 bases from standard Illumina paired-end libraries. Here we report the results of sequencing the genomes of COLO-829 and its matched lymphoblastoid sample using HiSeq2000 with v3 cluster-generation and sequencing chemistries. This has significantly improved the evenness and completeness of genomic coverage, particularly in areas of extreme sequence composition that were underrepresented in the initial study.

  Study EGAS00001000245

• Accurate mutation detection in leukemia by re-sequencing a cancer gene set

  With the advent of whole-genome and whole-exome sequencing, high-quality catalogs of recurrently mutated cancer genes are becoming available for many cancer types. Increasing access to sequencing technology, including bench-top sequencers, provide the opportunity to re-sequence a limited set of cancer genes across a patient cohort with limited processing time. Here, we re-sequenced a set of cancer genes in T-cell acute lymphoblastic leukemia (T-ALL) using the Roche/454 technology coupled with Nimblegen sequence capture. First, we investigated how a maximal sensitivity and specificity of mutation detection can be achieved through a benchmark study. We tested nine combinations of different mapping and variant-calling methods, varied the variant calling parameters, and compared the predicted mutations with a large independent validation set obtained by capillary re-sequencing. We found that the combination of two mapping algorithms, namely BWA-SW and SSAHA2, coupled with the variant calling algorithm Atlas-SNP2 yields the highest sensitivity (95%) and the highest specificity (93%). Next, we applied this analysis pipeline to identify mutations in a set of 58 cancer genes, in a panel of 18 T-ALL cell lines and 15 T-ALL patient samples. We confirmed mutations in known T-ALL drivers, including PHF6, NF1, FBXW7, NOTCH1, KRAS, NRAS, PIK3CA, and PTEN. Interestingly, we also found mutations in several cancer genes that had not been linked to T-ALL before, including JAK3. Finally, we re-sequenced a small set of 39 candidate genes and identified recurrent mutations in TET1, SPRY3 and SPRY4. In conclusion, we established an optimized analysis pipeline for Roche/454 data that can be applied to accurately detect gene mutations in cancer, which led to the identification of several new candidate T-ALL driver mutations.

  Study EGAS00001000268

• Genentech Colon Cancer Screen

  Identifying and understanding changes in cancer genomes is essential for the development of targeted therapeutics. Here we analyse systematically more than 70 pairs of primary human colon tumours by applying next-generation sequencing to characterize their exomes, transcriptomes and copy-number alterations. We have identified 36,303 protein-altering somatic changes that include several new recurrent mutations in the Wnt pathway gene TCF7L2, chromatin-remodelling genes such as TET2 and TET3 and receptor tyrosine kinases including ERBB3. Our analysis for significantly mutated cancer genes identified 23 candidates, including the cell cycle checkpoint kinase ATM. Copy-number and RNA-seq data analysis identified amplifications and corresponding overexpression of IGF2 in a subset of colon tumours. Furthermore, using RNA-seq data we identified multiple fusion transcripts including recurrent gene fusions involving R-spondin family members RSPO2 and RSPO3 that together occur in 10% of colon tumours. The RSPO fusions were mutually exclusive with APC mutations, indicating that they probably have a role in the activation of Wnt signalling and tumorigenesis. Consistent with this we show that the RSPO fusion proteins were capable of potentiating Wnt signalling. The R-spondin gene fusions and several other gene mutations identified in this study provide new potential opportunities for therapeutic intervention in colon cancer.

  Study EGAS00001000288

• Exome sequencing identifies mutation of the ribosome in T-cell acute lymphoblastic leukemia

  Acute lymphoblastic leukemia (ALL) is the most common pediatric malignancy and responds well to therapy in children, but not in adults. We used exome sequencing of 67 T-cell ALL (T- ALL) samples to gain insight in the mutational spectrum and age related differences of these leukemias. We detected protein-altering mutations in 508 genes, with an average of 8.2 mutations in pediatric and 21.0 in adult T-ALL. Based on stringent filtering, we predict 15 of these genes to be drivers, including 7 genes that were not previously implicated in T-ALL. We identify CNOT3 as a new tumor suppressor, as it is mutated in 12.2 % of adult T-ALLs and its knock-down causes de novo tumors in a sensitized drosophila eye tumor model. In addition, we identify mutations in RPL5 and RPL10, proteins of the 60S ribosomal complex2, in 18.2 % of pediatric T-ALLs. Mutation of arginine 98 in the X-linked RPL10 gene was most frequent. Yeast cells expressing the Rpl10 R98S mutant showed a clear ribosome biogenesis defect, excluding that this mutation is a passenger mutation. Our data provide insights in the mutational landscape of pediatric and adult T-ALL and identify the ribosome as a potential oncogenic factor in cancer.

  Study EGAS00001000296

• Inferring tumor genomes from peripheral blood i.e. CTCs and plasma-DNA using deep sequencing and targeted enrichment

  In this study we tested whether complex tumor genomes can be inferred from the peripheral blood (plasma DNA /CTCs) of 32 patients with stage IV colorectal carcinoma (CRC). To establish the percentage of mutated plasma DNA fragments we used 8 patient samples with different plasma DNA size distributions and KRAS mutations in their corresponding primary tumors and employed ultra-deep pyrosequencing with 3 different sequencing reaction sizes (i.e., 119 bp, 168 bp, and 323 bp). Furthermore, we used massive parallel sequencing of a panel of 68 CRC-associated genes to establish the mutation spectrum of cancer driver genes in the primary tumors, metastases, and CTCs of two colorectal cancer patients. To investigate, whether mutations found in only one CTC (“private CTC mutations”) are true mutations occurring with allele frequencies below the resolution limits of current detection methods, or whether they are amplification or sequencing artifacts, we performed ultra-deep sequencing of the primary tumors, metastases, plasma DNAs and normal tissues.

  Study EGAS00001000337

• Genetic landscape of pediatric Retinoblastoma

  Retinoblastoma is a pediatric cancer of the developing retina. All retinoblastomas are believed to initiate with biallelic inactivation of the RB1 gene. To identify subsequent genetic lesions in retinoblastoma, we performed whole genome sequencing of tumor and normal DNA of 4 children with retinoblastoma and one matched orthotopic xenograft. Both alleles of RB1 were inactivated in the tumor samples. 3 of the patients had sporadic retinoblastoma and one patient had inherited retinoblastoma. Overall, there were few single nucleotide changes in coding regions of the genome and some of the tumors had few chromosomal lesions. There were very few new genetic lesions in the xenograft compared to the primary tumor. These data suggest that the genome in retinoblastoma is more stable than previously believed and there are relatively few recurrent genetic lesions in known cancer pathways other than the RB1 pathway.

  Study EGAS00001000346

• Cancer genome scanning in plasma: detection of tumor-associated copy number aberrations, single nucleotide variants and tumoral heterogeneity by massively parallel sequencing

  Tumor-derived DNA can be found in the plasma of cancer patients. We explored the use of shotgun massively parallel sequencing of plasma DNA obtained from cancer patients to scan a cancer genome noninvasively. We achieved the profiling of copy number aberrations and point mutations, in a genomewide manner using this approach. By measuring the genomewide aggregated allelic loss and point mutations, we determined the fractional tumor-derived DNA concentrations in plasma and correlated these values with tumor size and surgical treatment. We have also demonstrated the application of this approach to monitoring a complex oncologic scenario, in a patient with two synchronous cancers. In particular, through the use of multi-regional sequencing of tumoral tissues and shotgun sequencing of plasma DNA, we have shown that plasma DNA sequencing is a valuable approach for studying tumoral heterogeneity. Shotgun plasma DNA sequencing is thus a powerful tool for cancer monitoring and research.

  Study EGAS00001000370

• The genomic landscape of large and small tumors in early-onset prostate cancer patients

  This study characterizes the genomic landscape of prostate cancer (PCA) cells in patients below or at the age of 50 years. Tumors of such early onset patients already show a broad spectrum of sizes. To test if the size differences are indicative of special cancer subgroups, we sequenced the genome of the tumor cells and matched control samples from blood.

  Study EGAS00001000383

• The landscape of somatic mutations in epigenetic regulators across 1000 pediatric cancer genomes

  To define the frequency and pattern of somatic mutations in epigenetic regulators in pediatric cancer, we sequenced 633 genes, encoding the majority of proteins involved in patterning the epigenome, in 1000 pediatric tumors spanning 21 different cancer subtypes. This analysis establishes an epigenetic landscape of pediatric cancer, which expands the knowledge for potential therapeutic targets and for developing personalized therapy.

  Study EGAS00001000449

• Identification of mutations and structural rearrangements in plasma DNA form metastatic prostate cancer patients

  In this study we analysed patients with metastatic prostate cancer to scan their tumor genomes noninvasively in plasma DNA. We enriched 1.3 Mbp of seven plasma DNAs (4 CRPC cases: CRPC1-3 and CRPC5; 3 CSPC cases: CSPC1-2 and CSPC4) including exonic sequences of 55 cancer genes and 38 introns of 18 genes, where fusion breakpoints have been described using Sure Select Custom DNA Kit.

  Study EGAS00001000453

• an integrated molecular study of clear cell renal cell carcinoma (ccRCC) including whole-genome/exome and RNA sequencing as well as array-based gene expression/copy-number/methylation analyses

  an integrated molecular study of clear cell renal cell carcinoma (ccRCC) including whole-genome/exome and RNA sequencing as well as array-based gene expression/copy-number/methylation analyses

  Study EGAS00001000509

• A Cancer Cell-Line Titration Series for Evaluating Somatic Classification

  Accurate detection of somatic single nucleotide variants and small insertions and deletions from DNA sequencing experiments of tumour-normal pairs is a challenging task. Tumour samples are often contaminated with normal cells confounding the available evidence for the somatic variants. Furthermore, tumours are heterogeneous so sub-clonal variants are observed at reduced allele frequencies. We present here a cell-line titration series dataset that can be used to evaluate somatic variant calling pipelines with the goal of reliably calling true somatic mutations at low allele frequencies. Cell-line DNA was mixed with matched normal DNA at 8 different ratios to generate samples with known tumour cellularities, and exome sequenced on Illumina HiSeq to depths of >300x. The data was processed with several different variant calling pipelines and verification experiments were performed to assay >1,500 somatic variant candidates using Ion Torrent PGM as an orthogonal technology. By examining the variants called at varying cellularities and depths of coverage, we show that the best performing pipelines are able to maintain a high level of precision at any cellularity. In addition, we estimate the number of true somatic variants undetected as cellularity and coverage decrease. Our cell-line titration series dataset, along with the associated verification results, is effective for this evaluation and will serve as a valuable dataset for future somatic calling algorithm development.

  Study EGAS00001001016

• Single cell sequencing of breast cancer T cells reveals a tissue-resident memory subset associated with improved prognosis

  The quantity of tumor infiltrating lymphocytes (TILs) in breast cancer (BC) is a robust prognostic factor for improved patient survival particularly in triple negative and HER2-overexpressing BC subtypes. Whilst T cells are the predominant TIL population, the relationship between quantitative and qualitative differences in T cell subpopulations and patient prognosis remains unknown. We performed single-cell RNA sequencing (scRNA-seq) of 6311 T cells isolated from human BCs, and show for the first time that significant heterogeneity exists in the infiltrating T cell population. We demonstrated that high TIL BCs contained significant numbers of CD8+ T cells with features of tissue-resident memory T (TRM) cell differentiation and that these CD8+ TRM cells expressed high levels of immune checkpoint molecules and effector proteins. A CD8+ TRM gene signature developed from the scRNA-seq data was significantly associated with improved patient survival in early-stage triple negative breast cancer (TNBC) and provided better prognostication compared with CD8 expression alone. Our data suggests that CD8+ TRM contribute to BC immunosurveillance and are the key targets of modulation through immune checkpoint inhibition. Further understanding of the development, maintenance and regulation of TRM cells will be crucial for successful immunotherapeutic development in BC.

  Study EGAS00001002845

• De novo metastatic prostate cancer cohort

  Fastq files from RNA sequencing of normal and tumor samples from 16 patients from the de novo metastatic prostate cancer cohort.

  Dataset EGAD50000002381

• Multifocal cohort analysis unveils cell types associated with regional lymph node seeding in prostate cancer

  The aim of this project was to assess the effect of intratumor heterogeneity on pathological and molecular markers in locally advanced prostate cancer. We demonstrate how primary lesions with a higher metastatic potential more closely resemble the state in the metastatic lymph nodes, for some biological signatures. Finally, we developed a statistical procedure to identify the most likely seeding lesion and introduced a statistical testing procedure to leverage the intratumor heterogeneity to identify signatures that characterize the seeding lesion.

  Study EGAS00001006715

• Locally advanced prostate cancer cohort

  Fastq files from RNA sequencing and BAM files from tNGS of normal and tumor samples from 17 patients from the locally advanced prostate cancer cohort.

  Dataset EGAD50000002380

• Data Access Committee for the DNA sequencing data included in the study "Multifocal cohort analysis unveils cell types associated with regional lymph node seeding in prostate cancer".

  A data transfer agreement (DTA), based on the example DTA provided by UZ Gent, is to be filled out by the requester and Multifocal RNA-seq and tNGS data from primary and metastatic tissues of locally advanced and de novo metastatic cohorts - Data Access Committee. https://www.uzgent.be/nl/over-uz-gent/organisatie/data-access-comite/wat-zijn-de-opdrachten-van-het-data-access-comite Coordinator: Muriel Fouquet E-mail: dataaccesscommittee@uzgent.be

  Dac EGAC50000000930

• Multiomic cell-free DNA profiling to inform molecular classification and immunotherapy outcomes in endometrial cancer

  This study involved a cell-free DNA (cfDNA) framework integrating genomic, transcriptomic and epigenomic profiling to investigate patient response to immune checkpoint inhibitors in advanced endometrial cancer (EC) with mismatch repair deficiency (dMMR).

  Study EGAS50000001582

• Biomodal duet +modC sequencing of endometrial cancer plasma cfDNA samples

  This dataset contains biomodal sequencing data generated using the duet + modC assay from plasma-derived cell-free DNA of endometrial cancer patients and healthy donors. Sequencing was performed on an Illumina NovaSeq 6000. Dataset includes raw sequencing FASTQ files. Duet +modC output enables whole-genome profiling of both genetic variation and DNA methylation.

  Dataset EGAD50000002261

• TruSight Oncology 500 ctDNA targeted sequencing data from endometrial cancer patients

  This dataset contains targeted sequencing data generated using the TruSight Oncology 500 ctDNA v2 assay from plasma-derived cell-free DNA of dMMR endometrial cancer patients, at baseline and C3D1 of immunotherapy. Sequencing was performed on Illumina NovaSeq600. Dataset includes aligned sequencing files in BAM format generated using the DRAGEN TruSight Oncology 500 ctDNA v2.6.0 analysis pipeline.

  Dataset EGAD50000002262

• Whole-genome sequencing of endometrial cancer plasma circulating DNA

  This dataset contains whole-genome sequencing data generated from plasma cell-free DNA of dMMR endometrial cancer patients. Sequencing was performed on Illumina platforms to an average depth of approximately 10× and the dataset includes raw sequencing reads in FASTQ format.

  Dataset EGAD50000002263

• Variant calling for LUNG-NSCLC2 cohort

  The goal of IMMUcan is to understand how the immune system interacts with tumors and how therapeutic interventions influence this interaction. This cohort includes patients with non-small cell lung cancer who had surgical resection. This is a subcohort of the EORTC SPECTAlung study. This dataset contains whole exome sequencing data from tumor samples processed with the Vegan pipeline. In the absence of matching germline samples, variant calling is performed using two panel of normals (one for female and one for male). It includes SNP and CNV calling.

  Dataset EGAD50000002235

• Whole genome sequencing data of high-grade serous ovarian cancer samples (set 17)

  The dataset contains whole genome sequencing data of 26 high-grade serous carcinoma (HGSC) patients sequenced with Novoseq 6000. The 86 samples are either fresh frozen tumour samples or blood samples. The files provided are paired fastq files.

  Dataset EGAD50000002409

• High-depth whole genome sequencing of 51 premalignant breast lesions

  Ductal carcinoma in situ (DCIS) is a non-obligate precursor lesion of breast cancer, representing 20-25% of newly diagnosed breast cancer lesions. It is currently not possible to predict which DCIS patients will progress to invasive breast cancer. The samples deposited here are part of a larger study using high-depth whole-genome sequencing (WGS) to investigate the somatic mutation genomic landscape of DCIS. Comprehensive evaluation of DCIS genomes aims to uncover biological insights into breast cancer progression and potential opportunities to stratify DCIS patients for personalised treatment options or active surveillance.

  Study EGAS50000001436

• High-depth whole genome sequencing of 26 premalignant breast lesions

  Ductal carcinoma in situ (DCIS) is a non-obligate precursor lesion of breast cancer, representing 20-25% of newly diagnosed breast cancer lesions. It is currently not possible to predict which DCIS patients will progress to invasive breast cancer. The samples deposited here are part of a larger study using high-depth whole-genome sequencing (WGS) to investigate the somatic mutation genomic landscape of DCIS. Comprehensive evaluation of DCIS genomes aims to uncover biological insights into breast cancer progression and potential opportunities to stratify DCIS patients for personalised treatment options or active surveillance. Due to specific restrictions imposed by the ethical approval at sample collection, the use of the germline data is restricted to filtering of somatic mutation calls only and cannot be used outside this purpose.

  Study EGAS50000001559

• High-depth whole genome sequencing of paired ductal carcinoma in-situ (DCIS) and germline control samples from 51 individuals.

  Deposited here are whole-genome sequencing data for 51 paired breast cancer DCIS and matched-normal samples taken from the same individual. Average sequence depth is 110x for DCIS samples and 39x for matched-normals. Matched-normals are from blood (n=14) or adjacent normal breast (n=37). Sequencing was performed on Illumina HIseqX (n=70) or Illumina Novoseq (n=32). They are a part of a broader project that uses high-depth WGS to investigate the somatic mutation genomic landscape of DCIS in order to uncover biological insights into breast cancer progression as well as possible methods to stratify DCIS patients for individualised therapy or disease monitoring.

  Dataset EGAD50000002071

• High-depth whole genome sequencing of paired ductal carcinoma in-situ (DCIS) and germline control samples from 26 individuals.

  Deposited here are whole-genome sequencing data for 26 paired breast cancer DCIS and matched-normal samples taken from the same individual. Average sequence coverage is 118x for DCIS samples and 41x for matched-normals. Matched-normal samples are from blood. Sequencing was performed on an Illumina HiseqX. Due to specific restrictions imposed by the ethical approval at sample collection, the use of the germline data is restricted to filtering of somatic mutation calls only and cannot be used outside this purpose.They are a part of a broader project that uses high-depth WGS to investigate the somatic mutation genomic landscape of DCIS in order to uncover biological insights into breast cancer progression as well as possible methods to stratify DCIS patients for individualised therapy or disease monitoring.

  Dataset EGAD50000002237

• DCIS fresh frozen fragmentomics dataset

  Ductal carcinoma in situ (DCIS) is a non-obligate precursor lesion of breast cancer (BC). Often detected by mammography, most cases are managed through surgical and/or radiotherapy approaches. Today, it is not possible to predict which patients will progress to invasive disease. Here, we evaluated high-depth whole-genome sequenced (WGS) DCIS, enriched for highgrade clinical lesions, to understand whether deep WGS could reveal biological insights and/or personalized therapeutic vulnerabilities that may be targetable. We find genomic locations that are likely susceptible to producing the initiating lesion for structural variations (SVs) prone to subsequent evolution, termed SHOREs (Susceptibility HOtspots for Rearrangements and ongoing Evolution). We additionally highlight individualized therapeutic potential that would otherwise not be appreciable without WGS. We posit that holistic WGS profiling could offer a more precise stratification approach, discerning higher-risk cases for prospective clinical studies on personalized therapies, from truly low-risk cases suitable for active monitoring. To substantiate our WGS findings, we also performed RNAseq on the same samples, this EGA study contains the RNAseq data.

  Study EGAS50000001475

• 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

• Sequencing data from triple-negative breast cancer tumors

  Autoimmunity and anti-cancer immunity lie on the same biological continuum1,2, but their link remains obscure. The paraneoplastic neurological syndrome anti-NMDA receptor (NMDAR) encephalitis (ANRE) is a paradigm for their connectivity3 given that intratumoral NMDAR expression correlates with the generation of anti-NMDAR antibodies4,5. Here, we verify ectopic expression of GluN1 and GluN2B NMDAR sub-units in triple-negative breast cancer (TNBC)6 and model this using orthotopic TNBC tumors with inducible expression of GluN1-GluN2B NMDARs. We show that NMDAR expression is sufficient to induce B cell recruitment and their affinity maturation, consistent with an integrated adaptive immune response. Reconstruction of extended intratumoral B cell phylogenies and cryo-EM structural analyses demonstrated that affinity-matured hypermutated and class-switched antibodies emerged from pre-existing germline-configuration lower-affinity anti-NMDAR antibodies. Distinct matured antibodies targeted specific epitopes and induced conformational rearrangements within the NMDAR amino-terminal domain, predictive of their functional effects, ranging from inhibition to potentiation. Passive transfer of an NMDAR-potentiating antibody caused autonomic dysregulation and lowered the seizure threshold in healthy female mice, recapitulating key diagnostic criteria of ANRE4,5. We further identify a correlation between intratumoral NMDAR expression and anti-NMDAR antibody titers in TNBC patients. Taken together, our data establish a direct connection between intratumoral NMDAR expression, antibody maturation, and the onset of autoimmunity. These findings suggest that germline-encoded anti-NMDAR antibodies contribute to immune surveillance but can also trigger autoimmune disease upon maturation, revealing a mechanistic tradeoff between cancer immunity and neurotoxicity.

  Study EGAS50000001585

• Sequencing data from triple-negative breast cancer tumors

  Autoimmunity and anti-cancer immunity lie on the same biological continuum1,2, but their link remains obscure. The paraneoplastic neurological syndrome anti-NMDA receptor (NMDAR) encephalitis (ANRE) is a paradigm for their connectivity3 given that intratumoral NMDAR expression correlates with the generation of anti-NMDAR antibodies4,5. Here, we verify ectopic expression of GluN1 and GluN2B NMDAR sub-units in triple-negative breast cancer (TNBC)6 and model this using orthotopic TNBC tumors with inducible expression of GluN1-GluN2B NMDARs. We show that NMDAR expression is sufficient to induce B cell recruitment and their affinity maturation, consistent with an integrated adaptive immune response. Reconstruction of extended intratumoral B cell phylogenies and cryo-EM structural analyses demonstrated that affinity-matured hypermutated and class-switched antibodies emerged from pre-existing germline-configuration lower-affinity anti-NMDAR antibodies. Distinct matured antibodies targeted specific epitopes and induced conformational rearrangements within the NMDAR amino-terminal domain, predictive of their functional effects, ranging from inhibition to potentiation. Passive transfer of an NMDAR-potentiating antibody caused autonomic dysregulation and lowered the seizure threshold in healthy female mice, recapitulating key diagnostic criteria of ANRE4,5. We further identify a correlation between intratumoral NMDAR expression and anti-NMDAR antibody titers in TNBC patients. Taken together, our data establish a direct connection between intratumoral NMDAR expression, antibody maturation, and the onset of autoimmunity. These findings suggest that germline-encoded anti-NMDAR antibodies contribute to immune surveillance but can also trigger autoimmune disease upon maturation, revealing a mechanistic tradeoff between cancer immunity and neurotoxicity.

  Study EGAS50000001598

• Triple-negative breast cancer sequencing data

  Single-cell RNA sequencing and spatial transcriptomic sequencing data associated with manuscript 'Ectopic NMDAR expression in cancer unmasks germline-encoded autoimmunity'

  Dataset EGAD50000002266

• Triple-negative breast cancer - Visium HD data

  Visium HD aligned reads from patient 1D525, BAM file from 10X spaceranger output directory

  Dataset EGAD50000002284

• Efficacy of dual KRAS G12D–EGFR blockade versus triple combinations in patient-derived models of KRAS G12D-mutant colorectal cancer

  RNA sequencing was performed on patient-derived xenograft (PDX)-derived organoid models of metastatic colorectal cancer (mCRC). The aim of this study was to characterize the transcriptional landscape of KRAS-mutant mCRC cells in response to therapeutic strategies targeting the EGFR and KRAS signaling pathways. Transcriptomic profiling was conducted following drug treatments to investigate molecular changes associated with single and combination therapies. A total of 24 samples were analyzed.

  Study EGAS50000001700

• RNA sequencing of untreated and treated KRAS-mutated metastatic colorectal cancer PDX-derived organoids.

  RNA sequencing was performed on patient-derived xenograft (PDX)-derived organoid models of metastatic colorectal cancer (mCRC). The aim of this study was to characterize the transcriptional landscape of KRAS-mutant mCRC cells in response to therapeutic strategies targeting the EGFR and KRAS signaling pathways. Transcriptomic profiling was conducted following drug treatments to investigate molecular changes associated with single and combination therapies. A total of 24 samples were analyzed.

  Dataset EGAD50000002443

• After the completion of CINECA, EUCANCan, and euCanSHare. What's next?

  CINECA, EUCANCan, and euCanSHare were part of the EUCAN Cluster, made up of six projects that received funding under the same Horizon 2020 call. All EUCAN projects (CINECA, EUCANCan, EUCAN-Connect, euCanSHare, Receptor Plus, and ReCoDID) were aimed at facilitating data reuse and knowledge discovery by enhancing data exchange and long-term collaboration in the health field. Here are some highlights about EGA’s contribution to these projects. CINECA: advances in Federated discovery and infrastructure for cohorts CINECA (Common Infrastructure for National Cohorts in Europe, Canada, and Africa) developed a federated cloud-based infrastructure for making genomic and biomolecular data accessible. The project has assembled a virtual cohort of 1.4 million individuals from sources such as the EGA, CanDIG and H3Africa. The EGA–CRG co-leaded a work package Work Package 1 on Federated Data Discovery and Querying. Beacon v2, championed by Jordi Rambla and Lauren Fromont, has been one of the central elements for the discovery of human genetic and phenotypic data. The EGA-CRG contributed to the development of a model for cohort discovery inside the Beacon v2 model. The team also delivered a Discovery Portal was implemented to explore cohorts and individuals of synthetic data. It is a UI that gathers a network of Beacons, a service for query expansion, and a visualisation tool. Have a look at the Discovery Portal UI, gathering a network of Beacons. You will find entities such as the Barcelona Supercomputing Center (BSC), BioData.pt and the European Genomic Data Infrastructure (GDI), among others. euCanSHare: facilitation of data access management This joint EU-Canada project aimed to build a European and Canadian FAIR platform for cardiovascular data sharing and analysis. The EGA’s tasks contributed to the development of the data management plan and data flows, main web-portal and interoperability protocols. An important part of the EuCanShare platform is the data access manager, a tool for the data owners to control the access to their sensitive datasets. We built a user-friendly interface for data access committees (data owners) to easily manage their data requests and access credentials. The data access portal facilitates the creation and internal organization of the data access committees as well as the linkage of data usage conditions to specific datasets. The interface includes filters for browsing requests and page to visualize the request history helping with the handling of data access requests. EUCANCan: toward a federation of clinical institutions in oncology The EUropean-CAnadian CANcer Network worked towards building a federated network to advance personalized medicine in oncology, by promoting the standard analysis, management and sharing of harmonized genomic and phenotypic data. The EGA led tasks on defining data flows and preparing an adapted infrastructure for long-term data storage and sharing. One of the key contributions was the conception of the EGA communities, offering standard and interoperable solutions for data discovery, processing, and sharing to projects and institutions that would like to manage and share data in the context of the EGA ecosystem. What's Next? The participation in projects such as CINECA, EUCANCan, and euCanSHare provide us with experience for future projects. We are happy to enhance data sharing and reuse, vital for advancing clinical and genomic research. The Discovery Portal is a wonderful proof of concept for the Beacon network. Next, we will finalise both the network and the user interface, and make sure it can be applied to more clinically-centred settings like hospitals. Most data hosted at the EGA are about cancer research. Currently, we contribute to building tools and infrastructure to empower oncology research in several European projects such as EUCAIM, EUCANIMAGE and EOSC4Cancer. We also do not lose sight of initiatives in the field such as the International Cancer Genome Consortium (ICGC) with the project ARGO, whose data model was adopted in EUCanCan.

  Blog cineca-eucancan-and-eucanshare-were-concluded-in-june

• Beacon v2 and Federated EGA, part of the GDI project Starter Kit to enable access to genomic and phenotypic data across borders

  The European Genomic Data Infrastructure project has released a ‘Starter Kit’ based on the rare disease and cancer proof-of-concepts from the Beyond 1 Million Genomes (B1MG) project. The Starter Kit, freely available to any interested parties, contains a set of software applications and components co-developed by the 20 GDI nodes and based on open community standards from the Global Alliance for Genomics and Health (GA4GH). Products in the Starter Kit give all countries the technical capability to access synthetic genomic and phenotypic data across borders. The image above shows the full workflow of the GDI Starter Kit user journey. The dotted circles are not included in the Starter Kit yet The EGA’s work is represented in the Starter Kit with Beacon v2 and Federated EGA among the software applications and components. About Beacon v2 Beacon is a protocol for data discovery. This API allows the search of genomic variants and associated information without breaching the datasets privacy. The European Genome-phenome Archive (EGA) is a key contributor to the Beacon v2 Protocol, the Beacon v2 Reference Implementation (B2RI) and the EGA Beacon(s). About Federated EGA The Federated EGA network offers a tool for data storage and sharing. Officially launched in 2022, this network of connected resources enables transnational discovery of and access to human omics data for research, while also respecting jurisdictional data protection regulations. The Federated EGA Onboarding Website contains all the information related to the establishment of a Federated Node.

  Blog beacon-v2-and-federated-ega-part-of-the-gdi-project-starter-kit

• The EGA joins EUCAIM, the European project powering AI and imaging in cancer research

  EUCAIM (EUropean Federation for CAncer IMages) is the cornerstone of the European Cancer Imaging Initiative, one of the flagships of the Europe’s Beating Cancer Plan (EBCP). The European Genome-Phenome Archive (EGA), as member of the EUCAIM consortium, attended the kick-off meeting organized this week in Brussels for the launch of the Initiative. The EGA will contribute to the project with the experience gained in the deployment of our federated network, the Federated EGA (FEGA), and the experience gained as partners of EuCanImage (AI4HI initiative) contributing to the definition of common data models, ontologies and data standards. The ultimate goal of the project is to unlock the power of imaging and Artificial Intelligence for the benefit of cancer patients, clinicians and researchers. The consortium will deploy a pan-European digital federated infrastructure hosting cancer-related images, and associated pathology, molecular and laboratory data from Real-World. This endeavour will provide a comprehensive dashboard for imaging data discovery, federated search, metadata harvesting, annotation and distributed data processing. EUCAIM joins 76 partners, gathering the experience and previous effort made by the different repositories of the AI4HI initiative, European Research Infrastructures and national/regional repositories. Find out more information about the EUCAIM launch here

  Blog the-ega-joins-eucaim

• 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

  Blog upcycling-and-merging-data-to-challenge-glioblastoma

• Providing safe access to sensitive human data across borders: Federated EGA becomes a reality

  Enabling discovery and access to sensitive data across national boundaries is vital for improving human health. It enables more powerful and efficient research by increasing the volume and diversity of data available for analysis. It allows us to better understand the causes of diseases – cancer, rare diseases, infectious diseases like COVID-19 – and develop new medicines and treatments. Sensitive human omics data are typically generated by research initiatives and shared using specialist repositories which provide services for data submission, discovery, and access. The EGA is one such repository. Established in 2008 at EMBL’s European Bioinformatics Institute (EMBL-EBI) in the UK, since 2012 the EGA (“Central EGA”) has been jointly managed by EMBL-EBI and the Centre for Genomic Regulation (CRG) in Spain. Many countries have emerging personalised medicine programmes which generate data from national initiatives. These programmes are driving a transition in human genomics from being research-driven to receiving funding through healthcare. Data generated in a clinical context are subject to stricter governance than research data and must follow national data protection legislation. To solve these challenges, the Federated EGA provides a network of connected resources to enable transnational discovery of and access to human omics data for research, while also respecting jurisdictional data protection regulations. In this way, the Federated EGA infrastructure supports the goals of European initiatives such as the 1+ Million Genomes initiative (1+MG), the European Health Data Space, and a number of EU-funded 1+MG implementation projects including Beyond 1 Million Genomes. The Federated EGA is made up of “Nodes” – typically nationally funded and operated – which store and manage data locally while allowing global discovery within the Federated EGA network. Since 2016, multiple parallel efforts, supported by ELIXIR and other transnational and national initiatives, have created technical and legal frameworks for establishing the Federated EGA. In 2022, the first five Nodes – Finland, Germany, Norway, Spain, and Sweden – officially joined the Federated EGA by signing Federated EGA Collaboration Agreements with Central EGA. The Finnish FEGA Node is operated by CSC - IT Center for Science and provides data management services according to national laws and the requirements of the EU General Data Protection Regulation (GDPR). These services provide tools and support for the whole life-cycle of sensitive research data from collating to analysis, publication, and authorised re-use. The development of the services has been a joint effort with the other Nordic nodes within NeIC's Tryggve and Heilsa projects, and funded by Finnish Ministry of Education and Culture and projects coordinated by ELIXIR Finland. Read more about Finnish FEGA signing. The German Human Genome-Phenome Archive (GHGA) strives to provide a national infrastructure as well as an ethical and legal framework that balances FAIR omics data usage and data protection needs for Germany. As a Germany-wide consortium funded by the German Research Foundation under the umbrella of the NFDI association, GHGA combines the expertise of 21 universities and research institutions to form a federated national infrastructure. Read more about GHGA signing. The German Human Genome-Phenome Archive (GHGA) strives to provide a national infrastructure as well as an ethical and legal framework that balances FAIR omics data usage and data protection needs for Germany. As a Germany-wide consortium funded by the German Research Foundation under the umbrella of the NFDI association, GHGA combines the expertise of 21 universities and research institutions to form a federated national infrastructure. Read more about GHGA signing. In Norway, a key component of the infrastructure is the services of The Sensitive Data Service (TSD) offered by USIT at University of Oslo. The Federated EGA Norway Node is developed by ELIXIR Norway and operated by the University of Oslo as the responsible legal entity. Core software modules are developed jointly with the other Nordic nodes in the NeIC Tryggve and Heilsa projects. Read more about FEGA Norway signing. The Spanish FEGA (es-FEGA) is a national service for storing sensitive biomedical data in Spain. Supported by the Spanish Institute of Bioinformatics (INB) in collaboration with Central EGA, sensitive research datasets are primarily hosted at the Barcelona Supercomputing Centre facilities. The Swedish Sensitive Data Archive is a secure data archive and sharing platform for sensitive datasets. It was developed by the National Bioinformatics Infrastructure Sweden (NBIS) in collaboration with other Nordic ELIXIR Nodes through the Tryggve and Heilsa projects funded by NeIC and coordinated with Central EGA through ELIXIR. Read more about the Swedish Node signing. The Swedish Sensitive Data Archive is a secure data archive and sharing platform for sensitive datasets. It was developed by the National Bioinformatics Infrastructure Sweden (NBIS) in collaboration with other Nordic ELIXIR Nodes through the Tryggve and Heilsa projects funded by NeIC and coordinated with Central EGA through ELIXIR. Read more about the Swedish Node signing. By providing a solution for secure and efficient management of human omics data, the Federated EGA aims to foster data reuse, enable reproducibility, accelerate biomedical research, and improve human health. Find out more Interested in setting up your own Federated EGA Node? Check out the FEGA Onboarding Knowledge Base for more information. The ELIXIR Federated Human Data Community is a great entry point for anyone interested in learning more about the Federated EGA. You can: Join the ELIXIR Federated Human Data Community mailing list (select “Human Data”) Attend the ELIXIR Federated Human Data Community calls

  Blog safe-access-to-sensitive-human-data-federated-ega

• How upcycled prostate cancer sequences enabled key findings on telomeres length

  The length of telomeres, the chromosomes’ end tails, as depicted in the figure below, physiologically shorten with aging. This means that younger cells have longer telomeres compared to their aged counterparts; one could say that the length of cells’ telomeres is a measure of their replicative power. Cancer cells are known to be able to turn this into their favour, and expand their replicative immortality through telomere lengthening and maintenance. Despite being a well-studied pan-cancer hallmark, the relation of the telomeres length to specific cancer genomic features is poorly understood. Julia Livingstone and her colleagues from P.C. Boutros' team in Los Angeles focused their work on prostate cancer. To investigate the relations between telomere length and the clinico-genomics of prostate tumours, they used whole genome sequencing (WGS) of 392 published tumour–reference pairs previously deposited at the EGA under accession numbers EGAS00001000400 and EGAS00001000900. Their work was published on Nature Communications in November 2021. They determined the telomere length of the sequencing sample, from both tumour and non-tumour adjacent tissues, and subsequently ran statistical analysis to investigate possible correlation between the telomeres length with several cancer features. The team discovered that telomeres length does not correlate with any specific driver gene mutation, but it does with the overall frequency of single nucleotides variants in a sample. This finding suggests that tumours with shorter telomeres accumulate more mutations without strong selective pressures for specific ones. While proliferation rate did not correlate directly with telomere length, methylation of almost half of all genes strongly did. The team’s results are massive and reveal a complicated and fascinating relation of different clinical and genomic features of prostate cancer with telomere length. In the paper discussion, they smartly consider different possibilities. As noted above, all these amazing results have been obtained analysing previously sequenced samples. Remarkably, the researchers who generated the samples did not focus at all on telomeres length. They indeed studied specific genes mutations and the features of early and late-onset prostate cancer. This proves, once again, the power of sequencing data re-use. This data is tremendously rich in information, and can hardly be exhausted with any number of analyses. Generating sequencing data, especially Whole Genome Sequencing, even better if tumor-reference paired, is like shopping every last article at the grocery store. You can then cook several recipes, or prepare a seven-course dinner, and still have ingredients left for someone else to borrow and cook something you have not thought about, a recipe that is just not in your cookbook. Noteworthy, the data retrieved from the EGA for this paper is associated with rich and complete metadata, meaning pheno-clinical information regarding the sample donors. As Julia Livingstone and her team wrote, using rich clinical annotations enabled them to assess the relationship between telomere length and patients outcome. This highlights once again the importance of reporting and annotating metadata correctly; It might feel like extra work for the researchers depositing their data, but it really has a huge value. Our team at the EGA is currently working to improve the metadata annotation process, with the aim to maximize the benefits for the scientific community.

  Blog prostate-cancer-sequences-enabled-key-findings-on-telomeres-length

• EuCANCan: EUropean-CANadian Cancer network

  The EUropean-CANadian Cancer network (EuCANCan) is a project aiming to develop a federated network of aligned and interoperable infrastructures for the homogeneous analysis, management and sharing of genomic oncology data for Personalized Medicine. This initiative, funded by the European Commission and the Canadian Institutes of Health and coordinated by the Barcelona Supercomputing Center (BSC), is expected to process and provide the scientific community with around 30-35 thousand patient samples from different types of cancer, coming from different nodes involved in this project, during the four years of the project. Data generated as part of primary studies, often in small hospitals or research centers, is hardly reused by other projects or groups. EuCANCan is proposed to foster the homogenisation and discoverability of cancer samples from very different sources for the whole community. These efforts will help paving the way to future standardised and global genomics projects, specially for those participant countries that eventually integrate the methodology and infrastructure generated during the project. “The more data we have access to the more and better discoveries. We attempt to overcome the legal and technical limitations in order to generate, gather and exploit bigger datasets as well as answer more ambitious questions”. These were some of the words Dr. David Torrents, main coordinator of the project, shared with a regional radio during the kick-off meeting of the project, on February 11th, 2019. The EUCANCan network will be composed of reference nodes in Amsterdam, Barcelona, Berlin, Heidelberg, Paris and Toronto which have established strong research and clinical programs in the field of genomic oncology. The Centre for Genomic Regulation (CRG), specifically the European Genome-phenome Archive (EGA), is among the leading institutions. Its exhaustive experience in biomedical data archival and secure distribution is considered key for crucial developments within the project. It is also notable the recent inclusion of EUCANCan in the list of GA4GH driver projects. Further information and details can be found in the following links: InsideHPC BSC official description Techweek (Spanish)

  Blog eucancan

• The last addition to the list of clonal evolution studies in the EGA

  Tumours of different types may arise from a single cell with at least one malignant mutation. Accumulation of subsequent hits generates lineages of cells with different cancer transformation power; thus, every clone follows an autonomous evolution, and several clones may co-exist into the same solid or liquid tumour. Clonal evolution studies are not new: the conceptual power of this approach has been recognized since the early ’80, especially in leukaemia patients. Nonetheless, these studies greatly benefit from recent technological improvements -machineries and protocols-, which enable ever-increasing sequencing depth, allowing the detection of low frequency variants and consequently more tumour clones. Note: the figure belongs to the original paper and is owned by the authors. Researchers at the University of Kyoto in Japan, have indeed used state of the art knowledge to investigate the clonal evolution of chronic myeloid leukemia (CML) in a large panel of patients. CML progresses from a majoritarian benign chronic phase into an often fatal blast crisis phase. It is nowadays known that blast crisis are triggered by genetic instability and disrupted DNA repair, which lead to accumulation of DNA mutations. The use of thyrosine kinase inhibitors targeting the Philadelphia chromosome have enormously improved the treatment of blast crisis, nonetheless resistant patients are still a medical challenge. Yotaro Ochi and collegues used Whole Exome Sequencing of paired chronic phase and blast crisis samples to depict the genetic landscape of progression from the first to the second stage of the disease (as illustrated in their figure). Their results were published in Nature Communication on this May 2021. They used a dataset previously deposited at the EGA (EGAS00001003071) and their new generated data have been made available under accession number EGAS00001005075. Their analysis of the occurring mutations contribute to understanding the mechanisms of CML evolution and therefore develop a protocol for early management of patients with a TKI resistance signature. Up to date, the EGA hosts 99 clonal evolution studies, developed in several cancer types, including myeloma, renal carcinomas and ovarian cancer, in addition to various leukaemia subtypes, where this approach has been more widely applied and produced important results and seminal papers. From a pan-cancer point of view, the definition of tumour architecture through clonal evolution studies is instrumental to unravel the mechanisms of disease progression and treatment-resistance insource. At the EGA, we are honoured to contribute to exciting and important science advances with our service!

  Blog the-last-addition-to-the-list-of-clonal-evolution-studies-in-the-ega