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• L1 Retrotransposon sequencing in Cocaine Use Disorder - Study 1

  Cocaine Use Disorder (CUD) is a global public health problem, with no effective pharmacotherapies. While CUD is marked by high heritability, discovery of variants associated with risk for CUD has proven difficult. We used Restriction Enzyme Based Enriched L1 sequencing (REBELseq) to amplify L1 retrotransposons in gDNA isolated from medial prefrontal cortex NeuN+ neuronal nuclei from 25 CUD cases and 26 controls. Amplified libraries were sequenced on the Illumina HiSeq 4000 platform, and sequencing data was analyzed with the REBELseq bioinformatics pipeline.

  Study phs001966

• Small‑scale mutations are infrequent as mechanisms of resistance in post‑PARP inhibitor tumour samples in high grade serous ovarian cancer

  Targeted DNA sequencing of high-grade serous ovarian cancer (HGSC) tumour and normal samples from 26 patients. Following target hybrid capture of 63 genes involved in DNA repair and response to treatment with an Agilent SureSelect XT panel, sequencing libraries were generated using the SureSelect XT Low Input Target Enrichment System (Agilent) as per the manufacturer's protocol. Libraries were sequenced on an Illumina NextSeq 500 at the Peter MacCallum Cancer Centre (Melbourne, Australia).

  Study EGAS50000000146

• Microbiome

  16S-sequencing: All stool samples were processed according to the standards of the Flemish Gut Flora Project (Falony et al., 2016). All samples were processed together and sequenced in as a single batch (dual index run DI23R22) which included positive controls (PC, identical stool sample), negative controls (PCR-mix) and ‘blanks’ or negative controls of the extraction (no sample). In addition, a Runella strain (RS) was included to check for potential cross-contamination, as this strain is not present in human samples. The V4 region of the 16S rRNA gene was amplified with the primer pair 515F and 806R (GTGYCAGCMGCCGCGGTAA and GGACTACNVGGGTWTCTAAT, resp.), modified to contain a barcode sequence between each primer and the Illumina adaptor sequences to produce dual- barcoded libraries (Tito et al., 2019). Sequencing was performed on the Illumina MiSeq. Sequences were processed using the LotuS (Hildebrand et al., 2014) and DADA2 pipeline (Callahan et al., 2016) using RDP 16 as the reference taxonomy.

  Dataset EGAD50000002027

• PROstate Cancer Medically Optimized Genome Enhanced ThErapy (PROMOTE) of Castration Resistant Prostate Cancer (CRPC) Patients Treated with Abiraterone Acetate

  The Prostate Cancer Medically Optimized Genome-Enhanced Therapy (PROMOTE) study uses genetic clues in castration-resistant prostate cancer that may identify an individualized treatment approach for men with the disease. Understanding the molecular biology behind castration-resistant prostate cancer has led to more treatment options, but there are still no definite conclusions about which specific drug best treats patients - maximum suppression of cancer growth while minimizing side effects. The PROMOTE study explores the genetic characteristics of each tumor to predict these treatment paradigms for the future, resulting in more effective and less toxic options for patients. Our long-term goal is to improve treatments for men with advanced prostate cancer by using genomic sequencing to increase life span and quality of life. We also will uncover novel vulnerable targets in the cancer genome that may provide new drug therapies. PARTICIPATION Eligible participants are men: With castration-resistant prostate cancer or prostate cancer not responding to hormone treatments About to begin abiraterone acetate therapy Agreeable to undergoing two tumor biopsies During the study, participants travel to Mayo Clinic for an initial biopsy (before beginning abiraterone acetate) and a second biopsy approximately three months later. The cell tissue collected is analyzed to identify gene alterations in the tumor that could eventually be targeted with treatments. Tissue is preserved for future research. Participants can continue to be treated by their local cancer care team during this period and beyond. In addition, the Mayo team carefully monitors participants' cancer via follow-up studies and the genetic signature of tumors that were biopsied so that patients may benefit from future treatments.

  Study phs001141

• 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

• Chromatin accessibility in human monocyte differentiation

  This dataset consists of ATAC-seq data from human monocytes, monocyte-derived dendritic cells or monocyte-derived macrophages as well as monocyte-derived cells that were subjected to siRNA treatment targeting TET2, IRF4 and EGR2. In total, it includes 26 samples.

  Dataset EGAD00001006601

• Aligned FOS RNA sequencing data

  Total RNA-sequencing Paired-End was performed by GenomeScan (Leiden, the Netherlands) on the NovaSeq6000 platform for full-length FOS (FOS FL), truncated FOS (FOSΔ), a FOS isoform with an L376N mutation (FOS mut), untransduced fMSC (unt) and fMSC with empty pLV (pLV) at week 0, 1, 2, and 3 in triplicate (total of 60 samples). Raw RNA-seq data were processed by the RNA-seq BioWDL pipeline pipeline version 5.0.0 developed by the SASC team at LUMC, LUMC, Leiden, the Netherlands).

  Dataset EGAD50000001839

• ATAC-seq of metastatic prostate tumors

  This dataset includes Assay for Transposase-Accessible Chromatin using sequencing (ATAC-seq) data, in FASTQ format, from 70 metastatic castration-resistant prostate cancer tumor samples from the SU2C/PCF West Coast Dream Team (WCDT) project. The sequencing data is paired-end, 150 bp sequencing data from an Illumina NovaSeq 6000 machine. ATAC-seq libraries were prepared following the protocol described in Buenrostro et al. Nature Methods. 2013 (PMID: 24097267) and Corces et al. Nature Methods. 2017 (PMID: 28846090).

  Dataset EGAD00001009654

• 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

• 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