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

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

  Dac EGAC50000000627

• The Genetic Landscape of Ocular Adnexa MALT Lymphoma Reveals Frequent Aberrations in NFAT and MEF2B Signaling Pathways

  A comprehensive constellation of somatic non-silent mutations and copy number (CN) variations in ocular adnexa marginal zone lymphoma (OAMZL) is unknown. By utilizing whole-exome sequencing in 69 tumors we define the genetic landscape of OAMZL. Mutations and CN changes in CABIN1 (30%), RHOA (26%), TBL1XR1 (22%), and CREBBP (17%) and inactivation of TNFAIP3 (26%) were among the most common aberrations. Candidate cancer driver genes cluster in the B-cell receptor (BCR), NFkB, NOTCH and NFAT signaling pathways. One of the most commonly altered genes is CABIN1, a calcineurin inhibitor acting as a negative regulator of the NFAT and MEF2B transcriptional activity. CABIN1 deletions enhance BCR-stimulated NFAT and MEF2B transcriptional activity, while CABIN1 mutations enhance only MEF2B transcriptional activity by impairing binding of mSin3a to CABIN1. Our data provide an unbiased identification of genetically altered genes that may play a role in the molecular pathogenesis of OAMZL and serve as therapeutic targets.

  Study EGAS00001006631

• All counts

  This dataset is the expression profiling by high throughput sequencing, including all counts of genes for all samples in two groups. It includes 26 samples totally (Lean healthy group includes 12 samples: s001/SR01_Bright, s002/SR01_Dim, s004/SR02_Bright, s005/SR04_Dim, s006/SR04_Bright, s007/SR05_Dim, s008/SR05_Bright, s009/SR06_Bright, s011/SR07_Dim, s012/SR07_Bright, s013/SR08_Bright, s014/SR08_Dim; DM2 group includes 14 samples: s015/SR201_Bright, s017/SR202_Bright, s018/SR202_Dim, s019/SR203_Bright, s020/SR203_Dim, s021/SR204_Bright, s022/SR204_Dim, s023/SR205_Dim, s025/SR206_Dim, s026/SR206_Bright, s027/SR207_Dim, s028/SR207_Bright, s029/SR208_Bright, s030/SR208_Dim). It is a TAB file.

  Dataset EGAD50000001715

• Somatic Mutations and Their Etiological Determinants for Breast Cancer in African American Women (B-CAUSE Study)

  The breast cancer health disparity between women of African ancestry (AA) and European ancestry (EA) remains a major public health challenge in the United States. AA women are afflicted by higher rate of triple-negative breast cancer (TNBC) and bear the highest mortality rate of all populations from the disease. Even within TNBC, some data suggest that AA women have poorer outcomes than EA women. Mounting evidence points to population differences in cancer biology, a fundamental question that remains unsettled. The disparity also manifests in representativeness in tumor sequencing projects, due to the low inclusion of AAs in genomic studies. A recent analysis of The Cancer Genome Atlas (TCGA) data revealed that the number of AA cases sequenced was sufficient only for studying frequently mutated genes (≥10%), and the power was worse for TNBC as a separate disease entity. As a result, the breast tumor mutational landscape elucidated to date is derived mostly from EA cases, and may not necessarily represent AA cancer genomes. Moreover, as discovery potential for new driver genes has come close to a plateau, cancer in AAs derived from distinct genetic and environmental contexts may provide a powerful venue for discovering mutations that are rare in EA cases. This is showcased in recent studies in colon and prostate cancer. Thus, we carried out a collaborative project, B-CAUSE, to characterize the mutational landscape of AA breast cancer genomes by pooling resources from five established studies, including the Women's Circle of Health Study (WCHS), the Black Women's Health Study (BWHS), the Southern Community Cohort Study (SCCS), the Nashville Breast Health Study (NBHS), and the Southern Tri-State Breast Health Study (STSBHS). This effort has created the largest AA-specific breast tumor mutation dataset to date in an efficient manner. The data deposited here are from the whole-exome sequencing (WES) of matched tumor-normal pairs of 462 TNBC in AA women from the B-CAUSE Study.

  Study phs003962

• Immunoprotective mechanisms and microbiota interplay in Salmonella Typhi infection

  Vaccine development against Salmonella enterica serovar Typhi (S. Typhi) requires a better understanding of interaction between human host and the resident microbial consortia in gastrointestinal tract. Healthy adult volunteers received either Ty21a, M01ZH09 or placebo, and underwent challenges with wt S. Typhi. Stool samples were collected at the screening interview (Baseline 1), prior to the first vaccination visit (Baseline 2), during vaccination (Day -28 and -26 for placebo and M01ZH09 groups; Day -32, -30, -28, -26 for Ty21a group), prior to challenge with S. Typhi (Day 0), and after challenge (day 0 12h, day 1, day 3, day 7, and day 10). 16S rRNA and messenger RNA were extracted from stool and sequenced on the Illumina Miseq and HiSeq 2000 platforms, respectively.

  Study phs001521

• Sequencing of pancreatic cancer primary tumors and metastases

  The extent of heterogeneity of driver gene mutations present in naturally occurring metastases is largely unknown, i.e. treatment-naïve metastatic disease. To address this issue, 60x whole genome sequencing of 26 metastases from 4 patients was carried out. We found that the identical driver gene mutations were present in every metastatic lesion of each patient studied. Passenger gene mutations not known or predicted to have functional consequences accounted for all intratumoral heterogeneity. Even with respect to these passenger gene mutations, the genetic similarity among the founding cells of metastases was markedly higher than that expected for any two cells randomly taken from a normal tissue. The uniformity of driver gene mutations among metastases in the same patient has critical, encouraging implications for the success of future targeted therapies in advanced stage disease.

  Study EGAS00001002186

• 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

• DAC Ghent University - Department of Movement and Sports Sciences

  DAC of Ghent University for RNA-seq data of human skeletal muscle biopsies collected at the Department of Movement and Sports Sciences

  Dac EGAC50000000263

• Refractory Classic Hodgkins Lymphoma (cHL) sWGS

  Associated with the study: Blood-based Monitoring of Relapsed/Refractory Hodgkin Lymphoma Patients Predict Responses to Anti-PD-1 Treatment. 26 ctDNA Samples from 4 patients followed longitudinally. sWGS performed for copy number aberration (CNA) analysis.

  Dataset EGAD50000001163

• ATAC-seq

  ATAC-seq data for 26 CLL samples (7 controls, 19 tumor) of the CancerEpiSys-PRECiSe project.

  Dataset EGAD00001005967