Search Results - EGA European Genome-Phenome Archive

Surgical Treatment for Ischemic Heart Failure (STICH-BioLINCC)

Data Access NOTE: Please refer to the “Authorized Access” section below for information about how access to the data from this accession differs from many other dbGaP accessions. ObjectiveTo compare medical therapy with coronary bypass surgery and/or surgical ventricular reconstruction for patients with congestive heart failure and coronary artery disease.BackgroundCoronary artery disease (CAD) is the most common cause of heart failure, which in turn is a major cause of death and disability globally. Evidence from previous clinical trials supports the use of coronary-artery bypass grafting (CABG) to relieve disabling symptoms of angina, particularly among high-risk subgroups with extensive CAD. However, the studies did not include patients with severe left ventricular dysfunction, and developments in medical therapy have since led to updated guidelines. In addition, the benefits of CABG in patients with ischemic cardiomyopathy had still not been clearly established at the time of this study. STICH sought to evaluate the role of CABG in the treatment of patients with CAD and left ventricular systolic dysfunction.Reduced left ventricular function may occur after myocardial infarction, often in conjunction with left ventricular remodeling, including left ventricular enlargement and changes in chamber geometry. Left ventricular remodeling is correlated with progression of heart failure and a poor prognosis. Therefore, a surgical approach to remodeling through left ventricular volume reduction could improve outcomes for patients with CAD and heart failure. Surgical ventricular reconstruction (SVR) has been shown to reduce the left ventricular volume, increase the ejection fraction, and improve ventricular function. There is also evidence that SVR performed with CABG may reduce the rate of hospitalization and improve ventricular function, as compared to CABG alone. As part of a second hypothesis, STICH additionally investigated whether SVR when added to CABG would improve outcomes in patients with heart failure and CAD.ParticipantsA total of 2,136 participants were enrolled in STICH. 1,212 were enrolled in the hypothesis 1 component of the trial, with 602 participants assigned to receive medical therapy alone, and 610 participants assigned to receive medical therapy plus CABG. 1,000 were enrolled in the hypothesis 2 component, with 499 participants assigned to receive medical therapy plus CABG, and 501 participants assigned to receive medical therapy plus CABG and SVR. 76 participants that were assigned to the CABG with medical therapy treatment were enrolled in both hypothesis components.DesignAfter initial determination of overall eligibility, participants were evaluated to determine which component of the STICH program was appropriate for them on the basis of suitable therapeutic options. All participants underwent cardiac imaging for assessment of left ventricular function and wall motion. Participants in the hypothesis 1 component were randomly assigned to receive either medical therapy alone or medical therapy plus CABG. Participants in the hypothesis 2 component were randomly assigned to receive either medical therapy plus CABG or medical therapy plus CABG and SVR.At baseline, demographic factors and clinical characteristics were assessed, including current medications and prior diagnostic and other cardiovascular procedures, and a physical examination was performed. Guideline-based recommendations for drug and device use were emphasized for all participants. All participants underwent follow-up evaluations at the time of discharge or at 30 days for participants still hospitalized, every 4 months for the first year, and every 6 months thereafter. The median length of follow-up was 56 months for hypothesis 1 and 48 months for hypothesis 2.For participants receiving CABG, arterial grafting for stenosis of the left anterior descending coronary artery was required for all participants without specific contraindications. The use of additional arterial conduits supplemented by vein grafts was recommended for revascularization of all major vessels with clinically significant stenoses. Concurrent mitral-valve surgery for regurgitation was performed at the discretion of the surgeon. For participants receiving SVR, the operation was most commonly performed during a single period of cardioplegic arrest after construction of bypass grafts. However, the procedure could also be performed with the heart beating in order to facilitate identification of the noncontractile zone of scarring. After an anterior left ventriculotomy was centered in the zone of anterior asynergy, a suture was placed in the interior of the ventricle to encircle the scar at the boundary between the akinetic and viable tissue. Visual inspection and palpation facilitated the judgment of whether a patch was needed to optimize the chamber size without deforming the left ventricle during closure of the ventriculotomy.The primary outcome for hypothesis 1 was the rate of death from any cause. The primary outcome for hypothesis two was a composite of death from any cause and hospitalization for cardiac causes.ConclusionsThere was no significant difference between medical therapy alone and medical therapy plus CABG for death from any cause, though participants that underwent CABG had lower rates of death from cardiovascular causes, death from any cause, or hospitalization for cardiovascular causes. Adding SVR to CABG reduced the left ventricular volume, as compared with CABG alone. However, this anatomical change was not associated with a greater improvement in symptoms or exercise tolerance, or with a reduction in the rate of death or hospitalization for cardiac causes.

Study phs003493

All you need to know about our new DAC Portal

With the DAC Portal, it is possible to streamline the process of managing access to sensitive data, ensuring that researchers have the necessary resources to advance scientific discovery while maintaining the highest standards of data protection and privacy. We know that, as a new tool, its first use can be complex. For this reason, in this article we will try to show all the elements of interest. Enjoy! Credentials: who needs to create a new user to access the DAC Portal and who doesn't? Only new users (since September the 12th) need to create an EGA account to access the DAC Portal. The EGA team went one step ahead by creating EGA accounts for former DAC members to login to the DAC Portal. These accounts are linked to the personal email used in the DAC structure: To check the linked email, DAC members can paste the DAC ID right after this link: https://metadata.ega-archive.org/dacs/ (e.g. https://metadata.ega-archive.org/dacs/EGAC00001002543) In case of password oblivion, it is possible to set a new one. All the process is channelled through the personal email. Some DAC members may be interested in updating the DAC email. This action can be done contacting our Helpdesk team. For the correct functioning of the DAC Portal, users must add the missing information of the DAC Profile. For a deeper dive, check out our documentation. The first step: knowing your workspace on the Portal Once logged in to the platform using the EGA User credentials, note the sections available: DACs and Policies. In the first one it is possible to check all user's registered DACs by default. It provides a comprehensive overview of each DAC, including its EGA accessions (EGAC), title, status, and the number of data access requests associated with each DAC. Whereas the Policies section is where users can manage and view all their registered policies, along with their associated EGA accessions, links, and titles. A drop-down menu is available with shortcuts to the most useful pages in the top right corner. It is possible to check DACs and policies, as well as creating new ones. In this menu, users can also contact the Helpdesk team using the “Need Help?” section to make inquiries about DACs and policies. Comprehending the DACs list & making the most of all the features Colours are crucial in the DAC's section as they will indicate the user role and the status in every committee, namely: Yellow: you are the administrator of the DAC and have full control to add other contacts, modify the content, and manage data access requests. Orange: you are a member of the DAC and have the authority to manage data access requests but cannot make any changes to the content. Blue: you have been invited to join the DAC and need to either accept or decline the invitation. Grey: the DAC is currently pending validation by the EGA Helpdesk team. Red: the DAC has been declined by the EGA Helpdesk team. Discover more information on how to view the message from Helpdesk containing the declination reason or how to validate or reject a DAC invitation by taking the tour of the DAC Portal. How to create, register and edit a DAC Creating a DAC is an easy process that only requires users to complete the necessary information. After that, the EGA Helpdesk team will review the proposal and validate the proposal. Once the DAC is validated it is possible for authorised users with admin role to edit it at any time, ensuring that all information and contacts associated with the committee is accurate and up to date. Membership management is controlled by searching for the EGA user looking for their username, email, or organisation. Please, note that for a person's details to appear in this search engine, they must have registered as a EGA user. Data Access Committee administrators manage two types of permissions that apply to contacts: Main contact and Role. Both can be modified at any time: Main contact refers to the primary person we firstly contact for any inquiry about the DAC (please, note that we can contact all DAC members, and this refers to the person we will contact first). Role defines the actions that can be taken by each contact. There are two possible status, admin and member, details of which can be found in the Take the Tour. Keep in mind that, to save the modifications, it is always necessary to click on “Update”. Moreover, it is also possible to delete any contact in a DAC whenever it is needed. The data request process: how to manage access requests The data request process is now channelled through the EGA website. Once a user sends a request access, the petition will go directly to the DAC Portal profile of the DAC members liked to the requested dataset. Whenever a request is received, a sand clock symbol will be displayed next to the DAC responsible for the dataset involved. By clicking on the DAC, it is possible to discover more information about requester(s). In this section, DAC Portal users will also be able to modify the display of the data access requests. It is possible to group requests by dataset accession or username, depending on the user preferences. Additionally, it is possible to isolate specific requests by user or dataset. To accept a request, users must slide the button to the right. Once the button turns green, it signifies that the request is accepted; the requester will be granted access to the requested dataset. To make lives easier, we have implemented a “Select all” button to easily accept or revoke multiple requests at once. To decline requests, it is necessary to slide the button to the left. A red button means the requester will not be granted access to the dataset. The DAC Portal will always ask to submit the reason why the data access was denied. Please, note that any decision, grant or denial, must be confirmed clicking the "Apply" button. This will update the status of the request and notify the requester accordingly. Taking control of the activity in the DAC Portal: checking the requests history The History button is a useful feature that allows users to access a list of all the requests that have been granted. This is especially useful for auditing purposes, as it enables to keep track of who has been granted access to the data and when. To facilitate control for those users with several requests we have included a filtering option. It allows to filter requests by user, mail, dataset, EGA ID, and date (these are combinable to boost the search). Don't forget about policies: creation, management, and update Similarly to the DACs section, in the Policies one users can manage and view all their registered policies. By clicking on any policy, it is possible to view its details as well as making any necessary updates or modifications. The sheets symbol and its adjacent number indicate the quantity of objects using a policy. By clicking in the location symbol users will go directly to the DAC page on the DAC Portal to see more information about that DAC. DAC Portal users can create new policies. The first step requires to link the policy to a registered DAC. After defining the title, users can either add a link to an external URL containing terms & conditions or write the policy content directly on the DAC Portal. Keep in mind that both options can be included. Data Use Ontology (DUO) codes can be added to new policies. These codes are used to specify the permitted and prohibited uses of the data. Please, note that some of them require a modifier to provide additional specificity. Find out more by checking out this specific content on the DAC Portal Tour. Policies can be modified at any given time by clicking on one registered policy, which will display the current information.

Blog new-dac-portal

GEDI: A Developmental Model of Gene-Environment Interplay in SUDs: Combined Genotype Dataset from the "Great Smoky Mountains Study" and the "Caring for Children in the Community Study".

1. Great Smoky Mountains Study (GSMS; Costello et al. 1996, 1997) Three cohorts of boys and girls, aged 9, 11, and 13 years at intake in 1993, were selected from a rural population of some 20,000 children using a household equal probability design. A two-phase procedure was used for White and African-American youth to increase power by oversampling children at risk for psychiatric and SUDs. Parents (usually mothers) of the first stage random population sample completed a questionnaire about their child's behavioral problems. Of 4,195 subjects selected, 95% (N=3,896) of parents completed the screen. All children scoring above a predetermined threshold (the top 25% of the total scores), plus a 10% random sample of the remaining 75%, were recruited for detailed interviews. Results can be back-weighted to population levels for analyses. Half of the sample consists of females, and 6% are African Americans, reflecting the population of the study area. The interviewed sample of white and African-American subjects was 1,070 (80% of those recruited). American Indian youth were oversampled (100%) because they are an understudied group known to be at high risk for stressful events, substance disorders, and mood disorders. Of 431 age-eligible children, 350 (81% boys, 49% girls) participated. Thus, the size of total GSMS sample is 1,070 + 350 = 1,420. Data collection is complete for ages 9-26, and age 30 interviews are in progress. By age 26 a total of 9,858 interviews had been completed; the average number of interviews per subject was seven, and by age 26, 97.3% completed two or more interviews. 2. The Caring for Children in the Community Study (CCC; Angold et al., 2002) This representative study of psychiatric illness and service use in African-American and White youth took place in four rural counties in the southeastern USA. The two-stage sampling design and methods are similar to those used in the GSMS. Of 4,500 youth randomly selected from the 17,117 9- to 17-year-olds in the public school's database, 3,613 (80.0%) were successfully contacted and agreed to complete the behavioral screen. Of the 1,302 selected to participate in the study, 920 (70.7%) interviews were completed. Because CCC was also the only study in GEDI to contain more than a very few African-American participants, these were omitted from the multi-site analyses. Reprinted with permission from Cambridge University Press from Costello et al., 2013: PMID: 23461817 References: Costello et al., 1996: PMID: 8956679 Costello et al., 1997: PMID: 9184514 Angold et al., 2002: PMID: 12365876

Study phs000852

Efficacy of a Therapeutic Treatment Trial in Angelman Syndrome

This study has been designed to evaluate the possible therapeutic benefits of L-5-methyltetrahydrofolate (Metafolin), vitamin B12, creatine and betaine in children with Angelman Syndrome (AS). This study is based on the hypotheses 1) that dietary manipulation may increase global DNA methylation; 2) that increased methylation of the paternal chromosome in AS participants may increase expression of the Angelman gene causing clinical benefit; and 3) that dietary interventions with Metafolin in conjunction with creatine, betaine, and vitamin B12 would represent little risk, but some chance for benefit. The dietary regimen is felt to be quite benign and safe. The clinical response will be measured by recording: changes in seizure activity, changes in communication skills, changes in developmental skills and changes in behavioral patterns as indicated by formal developmental assessments and clinical evaluations. We will assess the progress of the participants by monitoring their changes from baseline throughout their participation in the study and measure their improvement in particular in the developmental parameters. As a secondary aim, we plan to measure the biochemical response to these compounds by obtaining levels of homocysteine, methionine, S-adenosyl-methionine (SAM), and S-adenosyl-homocysteine (SAH). The molecular response will be measured by global DNA methylation analysis. As an exploratory aim, we hope to use control data we have previously obtained from a double blind placebo-controlled trial done in the past using betaine and folic acid to compare the development of those children who have and those who have not received medications. More specifically, we wish to compare differences in the rate of development for those children who have never received study medications (from the first trial) with those who have received medications from the present trial. Developmental parameters used in the previous trial will be consistent with those used in the present trial in order to permit these comparisons. The previous trial was conducted at Baylor College of Medicine, Rady San Diego Children's Hospital and Boston Children's Hospital whereas a group of AS participants received folic acid and betaine or placebo in a randomized double-blind basis. All the participants for the study will include patients who have a documented molecular diagnosis of AS. The participants will be seen at Baylor College of Medicine, Rady Children's Hospital of San Diego, Boston Children's Hospital and the Greenwood Genetics Center at 0 months and at 12 months for follow-up. Clinical and relevant historical data will be collected during the clinical visit and examination and also by reviewing medical and laboratory records. This information will then be entered into a HIPAA compliant clinical research database.

Study phs000701

Genetics of Lipid Lowering Drugs and Diet Network (GOLDN) Lipidomics Study

The GOLDN study was initiated to assess how genetic factors interact with environmental (diet and drug) interventions to influence blood levels of triglycerides and other atherogenic lipid species and inflammation markers (registered at clinicaltrails.gov, number NCT00083369). The study recruited Caucasian participants primarily from three-generational pedigrees from two NHLBI Family Heart Study (FHS) field centers (Minneapolis, MN and Salt Lake City, UT). Only families with at least two siblings were recruited and only participants who did not take lipid-lowering agents (pharmaceuticals or nutraceuticals) for at least 4 weeks prior to the initial visit were included. A total of 1048 GOLDN participants were included in the diet intervention. The diet intervention followed the protocol of Patsch et al. (1992). The whipping cream (83% fat) meal had 700 Calories/m2 body surface area (2.93 MJ/m2 body surface area): 3% of calories were derived from protein (instant nonfat dry milk) and 14% from carbohydrate (sugar). The ratio of polyunsaturated to saturated fat was 0.06 and the cholesterol content of the average meal was 240 mg. The mixture was blended with ice and flavorings. Blood samples were drawn immediately before (fasting) and at 3.5 and 6 hours after consuming the high-fat meal. For the GOLDN lipidomics study, sterols and fatty acids were measured from stored plasma (-80 degrees Celsius) collected at fasting and 3.5 hours after the diet intervention using TrueMass Panels from Lipomics (West Sacramento, CA). A total of 11 sterols were quantified in nmols/gram of sample including total cholesterol, 7-dehydrocholesterol, desmosterol, lanosterol, lathasterol, cholestanol, coprostanol, beta-sitosterol, campesterol, stigmasterol, and 7alpha-hydroxycholesterol. A total of 35 fatty acids were quantified in nmols/gram of sample inlcuding myristic acid (14:0); pentadecanoic acid (15:0); palmitic acid (16:0); stearic acid (18:0); arachidic acid (20:0); behenic acid (22:0); lignoceric acid (24:0); myristoleic acid (14:1n5); palmitoleic acid (16:1n7); palmitelaidic acid (t16:1n7); oleic acid (18:1n9); elaidic acid (t18:1n9); vaccenic acid (18:1n7); linoleic acid (18:2n6); gamma-linolenic acid (18:3n6); alpha-linolenic acid (18:3n3); stearidonic acid (18:4n3); eicosenoic acid (20:1n9); eicosadienoic acid (20:2n6); mead acid (20:3n9); di-homo-gamma-linolenic acid (20:3n6); arachidonic acid (20:4n6); eicsoatetraenoic acid (20:4n3); eicosapentaenoic acid (20:5n3); erucic acid (22:1n9); docosadienoic acid (22:2n6); adrenic acid (22:4n6); docosapentaenoic acid (22:5n6); docosapentaenoic acid (22:5n3); docosahexaenoic acid (22:6n3); nervonic acid (24:1n9); and plasmalogen derivatives of 16:0, 18:0, 18:1n9, and 18:1n7.

Study phs000741

National Epidemiologic Survey on Alcohol and Related Conditions-III (NESARC-III)

The National Epidemiologic Survey on Alcohol and Related Conditions-III (NESARC-III) is a nationally representative cross-sectional survey of the U.S. general population, which was sponsored by the National Institute on Alcohol Abuse and Alcoholism (NIAAA) and conducted in 2012-2013. The NESARC-III's target population was the U.S. noninstitutionalized civilian population, 18 years and older, including residents of selected group quarters (e.g., group homes, workers' dormitories). Multistage probability sampling was used to randomly select respondents. Primary sampling units (PSUs) were individual counties or groups of contiguous counties, secondary sampling units (SSU) comprised groups of Census-defined blocks, and tertiary sampling units were households within SSUs. Finally, eligible adults within sampled households were randomly selected. Hispanics, Blacks, and Asians were oversampled and resulted in a total of 36,309 respondents. All respondents provided informed consent for survey participation. Data were adjusted for oversampling and screener - and person-level nonresponse, then weighted through post-stratification to represent the US civilian population based on the 2012 American Community Survey. These weighting adjustments were found to compensate adequately for nonresponse. Interviewer field methods involved initial structured home study, in-person training, ongoing supervision, and random respondent callbacks to verify data. The NESARC-III collected information on alcohol and drug consumption, alcohol use disorder, other substance use disorders (e.g., nicotine, cannabis and opioid), and associated physical and psychiatric adverse consequences. In addition to a full array of sociodemographic characteristics such as race/ethnicity, gender, age, risk and environmental factors including adverse childhood experiences (e.g., sexual, physical abuse and neglect) and family history for alcohol, drug use disorders and other psychiatric disorders (e.g., mood, anxiety, personality disorders and PTSD) were included (phenotypic variables=4,320). As part of the NESARC-III, 22,848 informative samples were genotyped on Affymetrix Axiom Exome Array consisting of 319,283 SNPs and 103,404 custom-selected SNPs Array (refer to the SNP annotation file). The latter array was selected based on the addiction associated genes, the results of 5 GWAS of alcohol and other psychiatric disorders, and animal models with addiction phenotypes. After filtering out poor quality SNPs using the standard Affymetrix pipeline there are 295,218 SNPs in the NESARC-III genetic data. The 22,848 subjects in this study were all deeply and consistently phenotyped via structured diagnostic interview. Controls group can be selected for specific disorders from a pool of all samples. Here are numbers of cases for major DSM-5 mental disorders in NESARC-III genetic data: Alcohol use disorder (7,075); Nicotine use disorder (6,641); Drug use disorder (2,570); Major depressive disorder (5,214); Persistent depression(1,429); Bipolar I (543); Anxiety disorders (4,226); PTSD (1,674); Personality disorders (4,014); Eating Disorders (457).

Study phs001590

Molecularly matched targeted therapies plus radiotherapy in patients with newly diagnosed glioblastoma without MGMT promoter hypermethylation (N2M2/NOA-20 phase I/IIa umbrella trial)

Background: Patients with glioblastoma without MGMT promoter hypermethylation are unlikely to benefit from temozolomide (TMZ). Trials aiming at replacing TMZ with targeted agents in not molecularly selected patient populations have failed. Methods: This phase I/IIa umbrella trial aimed at showing safety, feasibility, and preliminary efficacy of targeted compounds in addition to standard radiotherapy initiated within 42 days postoperatively. Molecular diagnostics and bioinformatic evaluation are performed within 28 days after surgery. Stratification for treatment takes place in five subtrials, including alectinib, idasanutlin, palbociclib, vismogedib and temsirolimus, according to the best matching molecular alteration. Patients without matching alterations are randomized between subtrials without strong biomarkers using atezolizumab and asunercept and TMZ as standard of care. Primary objective of the phase I parts of the trial was dose finding or dose validation. In the phase IIa trials, centrally determined progression-free survival at six months (PFS-6) is used as endpoint for efficacy with interim analyses for futility (H0: p=0.231). Results: From May 2018 through July 2022, 301 patients were enrolled and 228 treated in 13 German NOA sites. The alectinib and vismodegib subtrials were closed since no molecularly matching patients were accrued; the idasanutlin subtrial was closed prior to the optimal dose at nine patients at discretion of the company providing the drug. The TMZ subtrial showed a PFS-6 of 18.52% (10/54 patients) (p=0.831) and a median overall survival (OS) of 12.1 months. Asunercept: PFS-6 of 15.4% (4/26) (p=0.8825) and OS of 12.8 months. Atezolizumab: PFS-6 of 21.4% (9/42) (p=0.660) and OS of 11.7 months. Palbociclib with patients demonstrating CDK4 amplification or CDKN2A/B codeletion: PFS-6 of 24.4% (10/41) (p=0.4823) and OS of 12.6 months. Temsirolimus with patients demonstrating mTOR activation: PFS-6 of 39.1% (18/46) (p=0.0109) and OS of 15.4 months. The regimen-limiting toxicity (RLT)-rate is 34.8%, which is insignificantly above the predefined unacceptable rate for RLTs of 30%. Most RLTs had severity grade 3, one RLT had severity grade 4. No RLTs resulted in death. Conclusions: N2M2 allows for elaborate molecular testing being integrated into the treatment decision and efficient determination of treatment activity for patients with newly diagnosed glioblastoma. There is clinical activity of temsirolimus in patients with tumors harboring an activated mTOR pathway although this is not positively prognostic without mTOR inhibition; there is no clinical activity for asunercept and atezolizumab in not molecularly selected patients and also palbociclib in molecularly selected patients.

Study EGAS00001008033

Swarm Learning to identify COVID-19, tuberculosis and leukemia patients based on blood transcriptomes

Identification of patients with life-threatening diseases including leukemias or infections such as tuberculosis or COVID-19 is an important goal of modern precision medicine. However, there is an increasing divide between what is technically possible and what is allowed because of privacy legislation. We have recently illustrated that classical machine learning can identify leukemia patients based on their blood transcriptomes. To facilitate integration of any omics data from any data owner world-wide without violating privacy laws, we here introduce Swarm Learning (SL), a decentralized machine learning approach uniting edge computing, artificial intelligence (AI), blockchain and privacy protection without the need for a central coordinator thereby going beyond federated learning. To illustrate its feasibility, using more than 12,000 transcriptomes from peripheral blood mononuclear cells and more than 2,000 peripheral blood transcriptomes we demonstrate that SL of omics data distributed across different individual sites leads to disease classifiers that outperform those developed at individual sites. Yet, SL completely protects local privacy regulations by design. We propose this approach to noticeably accelerate the introduction of precision medicine.

Dataset EGAD00001006231

The Dutch Microbiome Project Batch 2

The Dutch Microbiome Project (DMP) data includes shotgun metagenomic sequencing of faecal samples 8,208 Dutch individuals. Paired-end sequencing was performed using Illumina HiSeq 2000 platform. Data is archived in two batches to facilitate easier data access and upload to EGA. Batch 2 of DMP includes ~400 samples.

Dataset EGAD00001007501

Targeted sequencing of diffuse large B-cell lymphoma tumour samples from the UK's Haematological Malignancy Research Network

Targeted sequencing was applied to an unselected population-based diffuse large B-cell lymphoma cohort (n=928) diagnosed in the UK's Haematological Malignancy Research Network catchment population of ~4 million (14 centres). DNA extracted from tumour samples was sequenced with a 293-gene panel using the Illumina HiSeq 2500. All data are provided in the CRAM format.

Dataset EGAD00001008616

14970 results for "cancer studies using rna-seq"

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