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• MicroRNAs, Hypertension and End Organ Damage in Humans

  Study 1) Profiling of microRNAs in plasma of patients with hypertension complicated or not by metabolic syndrome or chronic kidney disease Hypertension (HTN) or high blood pressure is associated with subclinical target organ damage such as cardiac, vascular and kidney injury, which may lead to complications and death. In this study, we investigated circulating microRNAs as biomarkers of target organ damage in HTN patients. We profiled circulating microRNAs by RNA sequencing in platelet-poor plasma of normotensive subjects and patients with HTN complicated or not by metabolic syndrome (MetS) or chronic kidney disease (CKD) (n=15 each group). Differentially expressed microRNAs were identified with a threshold of false discovery rate <0.1. Differentially expressed microRNAs were identified uniquely to associate with HTN (8), MetS (1) or CKD (13), and 8 were similarly differentially expressed in different groups. This study identified the association of differentially expressed circulating microRNAs with target organ damage in HTN patients, which could have some pathophysiological and therapeutic implications. Study 2) Profiling of microRNAs in gluteal subcutaneous small arteries of patients with hypertension complicated or not by chronic kidney disease Hypertension (HTN) is associated with vascular damage characterized by endothelial dysfunction and vascular remodeling and stiffening, which contributes to kidney injury leading to chronic kidney disease (CKD). MicroRNAs are short non-coding RNAs which repress/degrade target mRNAs. The microRNA role in vascular injury in HTN remains unclear. In this study, we aimed to identify differentially expressed microRNAs in small arteries of patients with HTN associated or not with CKD, in order to shed light on the pathophysiological molecular mechanisms. Normotensive subjects and HTN patients associated or not with CKD grades 3-4 were studied (n=15-16). Small arteries were isolated from subcutaneous gluteal biopsies, RNAs were extracted, and small and total RNA sequencing was performed by Illumina HiSeq-2500. Differentially expressed genes were identified with a P<0.05 and fold change (FC) >1.3. Differentially expressed microRNAs and mRNAs were identified uniquely to associate with HTN (microRNAs: 10, mRNAs: 68), CKD (microRNAs: 68, mRNAs: 395), and both groups (microRNAs: 2, mRNAs: 32). This study identified differentially expressed microRNAs and mRNAs in small arteries with target organ damage in HTN, which could have some pathophysiological and therapeutic implications.

  Study phs002389

• DAC-2020-03-26-Lemola (DAC-039))

  This is only the location. For the raw data and any check if the dataset may be relevant please refer to the Harvard Dataverse (https://dataverse.harvard.edu/dataverse/lemola).

  Study EGAS50000000635

• Clinical utility of combined low-pass whole genome and targeted sequencing in liquid biopsies for diagnosis and monitoring of pediatric solid tumors

  Low-pass whole genome sequencing samples from pediatric solid tumor patients who are deceased

  Dataset EGAD00001009972

• 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

• Single cell RNA sequencing of colorectal cancer patients (KUL5)

  All libraries were sequenced on Illumina NextSeq or NovaSeq6000 until sufficient saturation was reached.

  Dataset EGAD00001008585

• Oncogenic Ectodomain deletion of FGFR1 caused by Breakage-Fusion-Bridges in Squamous Cell lung Cancer

  The identification of recurrent 8p11.23 amplifications including FGFR1 raised the hope of a treatable target in squamous cell lung cancer (SQLC). However, only a minority of patients with FGFR1-amplified tumors respond to single agent inhibitor therapy targeting FGFR. To understand the underlying mechanism of FGFR1 dependency, we performed whole genome and transcriptome sequencing of 25 FGFR1-amplified primary tumors with unknown response upon FGFR inhibition. In addition, we performed deep sequencing of 26 FGFR1-amplified samples whereof the response upon FGFR inhibition was known for 25 samples. In both cohorts we identified intra-chromosomal tail-to-tail breaks close to the FGFR1 transcription start site, being responsible for focal amplification of FGFR1. These specific breaks are caused by a Breakage-Fusion-Bridge-like (BFB-like) mechanism. Here, we associate these breaks with FGFR inhibitor sensitivity. Moreover, in some cases these breaks are located within the open reading frame of FGFR1, which leads to the expression of an ΔEC-FGFR1 transcript that lacks the ecto-domain. Overexpression of ΔEC-FGFR1 transforms Baf3 cells and lead to an FGFR1-dependent phenotype. Our results demonstrate that the truncation of the FGFR1 ectodomain is a frequent event in 8p11.23-amplified squamous cell lung cancer caused by tail-to-tail breaks. These breaks might be used as a predictive therapeutic marker to stratify patients for FGFR-inhibitor therapy.

  Study EGAS00001005059

• Neoadjuvant immune checkpoint blockade in mismatch-repair proficient colon cancers

  Immune checkpoint blockade has led to paradigm shifts in the treatment of various tumour types, yet limited efficacy has been observed in patients with metastatic mismatch-repair proficient (pMMR) colorectal cancer. Here we report an in-depth analysis of patients with early-stage pMMR colon cancer from the phase II NICHE study (ClinicalTrials.gov: NCT03026140). A total of 31 patients received neoadjuvant treatment of nivolumab plus ipilimumab followed by surgery. The response rate was 26% and included six patients with a major pathological response (≤10% residual viable tumour). One patient with an ongoing clinical complete response did not undergo surgery. Responses were observed despite a low tumour mutational burden in all tumours, while chromosomal genomic instability scores were significantly higher in responders compared to non-responders. Responding tumours were more likely to be TP53 mutant, KRASG12 wildtype and had significantly higher baseline expression of proliferation signatures and TCF1. Imaging mass cytometry also revealed a higher percentage of Ki-67+ cancer and Ki-67+ CD8+ T cells in responders compared to non-responders. Meanwhile, in non-responders, we observed an enrichment for an inflamed-fibrotic microenvironment associated with TGF-β expression, hinting towards possible resistance mechanisms. These results provide a comprehensive analysis of response to neoadjuvant ICB in early-stage pMMR colon cancers and identify potential biomarkers for patient selection.

  Study EGAS50000000856

• Single_Cell_Sequencing_of_Sperm__scSperm_

  The aim of this project is to genotype and sequence single spermatozoa from two men, one in his twenties and the other in his seventies. The resulting data is used to quantify the mutations that have arisen in the gametes of both individuals in order to better understand the effect of aging on mutation rates and modes.Project Outline. In order to quantify mutations, semen from two individuals are sequenced. 48 single sperm cells are isolated from each individual, and their DNA is extracted. The resulting genomes are amplified using PicoPlex, GenomiPhi MDA, Repli-G MDA, and MALBAC. QC step is applied to check the quality of WGA DNA using standard Sequenom plex (26 SNPs). A subset of 32 amplification products which pass the intiall QC, are genotyped using Affymetrix SNP6 chips. 12 of the genotyped amplification products are also sequenced. In addition, one multi-cell sample per individual is sequenced as a reference and for validation purposes.Altogether, 12 single cell sperm genomes and two multi-cell genomes are sequenced, coming to a total of 14 genomes. Of the single cell sperm genomes, 2 are sequenced to 50x coverage, and the other 10 to 25x coverage. Both multi-cell genomes are sequenced to 25x coverage.

  Study EGAS00001000935

• RNA-seq data from 224 advanced prostate tumors generated by the West Coast Dream Team

  224 pairs of FASTQ files from metastatic Castration-Resistant Prostate Cancer (mCRPC) sequenced on HiSeq 4000 instruments. Patients were enrolled in the West Coast Dream Team study. Biopsies include various tissue sites including bone, soft tissue, and lymph node.

  Dataset EGAD00001008487

• EGA account management

  How to manage your EGA account Welcome to the documentation page for creating an EGA user. The European Genome-Phenome Archive (EGA) is a platform for archiving, managing, and sharing human genomic and phenotypic data. To submit, access, and manage requests for the data hosted on the EGA platform, users are required to register for an account. This documentation page provides step-by-step instructions for creating an EGA user account, as well as information on the different types of EGA user accounts and their associated privileges. You can check the EGA data flow for a better understanding. Manage EGA account step-by-step guide Contact Information Public Keys Password Authenticator Federated Identity Sessions Request an EGA account step-by-step guide Fill in this form.You cannot use a generic email account (e.g., Gmail). Make sure you use your institutional email account.Your email is by default your username.The criteria for a strong password is: It should contain between 8 and 32 charactersIt should contain at least one uppercase letterIt should contain at least one numberIt should contain at least one special characterYou will need to wait for the Helpdesk team to check your identity. Please allow two business days for this step.After the Helpdesk validation step, you will receive an email with a link to validate your institutional email.Click the link to verify your email. It will redirect you to the EGA website.As soon as your account has been validated, you will be able to start adding more information to your EGA profile. For that, you first need to log in using your credentials from step 1. Manage EGA account step-by-step guide As a logged-in user, go to your profile by clicking on Welcome > My Profile. To modify it, click the Edit button.You will see the following options: Contact Information In this section, you can modify the personal information of your EGA account. Public Keys Adding a public key is necessary for downloading data via Live Outbox distribution. If you don’t know how to generate your key, you can follow the instructions available on How do I create a key? Password In the Password tab, you can change your password anytime to ensure the security of your account. However, if you receive an email notifying you that your password was modified and you did not initiate the change, it could be a sign that your account has been compromised. In this case, you should immediately contact our Helpdesk team to report the issue and receive assistance in restoring your account security. Authenticator You can set your two-factor authentication (2FA) system for your EGA account as an identity and access management security method that requires two forms of identification to access resources and data. To obtain your code, please follow the instructions below, also available in the Authenticator tab in your profile. Sessions The Sessions tab displays a list of all devices where you are currently logged in as an EGA user. This includes any open sessions you have on your computer, phone, or other devices. By reviewing the list of active sessions, you can monitor the devices that have access to your account and ensure that there are no unauthorised logins. If you notice any suspicious activity, you can close the sessions from this page to immediately terminate access to your account from the unauthorised device.

  Documentation how-to-manage-your-account