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• RNA-seq in LCLs derived from constitutional MLH1 epimutation carriers and non-carrier relatives

  Transcriptome profiling in human lymphoblastoid cell lines derived from constitutional MLH1 epimutation carriers and non-carrier relatives

  Study EGAS50000000498

• Single-cell Transcriptome Profiling of Treatment-naïve and Post-treatment Colorectal Cancer: Insights into Putative Mechanisms of Chemoresistance

  These terms and conditions govern access to the managed access datasets to which the User Institution has requested access. The User Institution agrees to be bound by these terms and conditions.

  Dac EGAC50000000482

• Paired Exome sequencing of Sarcoma tumor and control

  Paired Exome sequencing of Sarcoma tumor and control of 10 samples (5 tumor/control pairs). The sequencing was done on Illumina Hiseq 4000 and Agilent Sureselect V5+UTRs kit.

  Dataset EGAD00001010278

• Whole genome sequencing and whole exome sequencing of pediatric osteosarcoma

  Whole genome sequencing and whole exome sequencing of 13 pediatric osteosarcoma patients including 13 primary, 10 metastatic, and 3 relapsed tumors.

  Dataset EGAD00001004482

• Dataset for WES PCNSL

  WES sequencing of 23 samples from PCNSL tumor and blood control samples. Sequencing was performed on a NovaSeq 6000 and NextSeq 500 using Agilent SureSelectXT HS Human All Exon V7 and V8. Sequencing was always paired.

  Dataset EGAD00001010847

• Whole transcriptome and 850k methylome profiling of human MBM

  Whole transcriptome and 850k mehylome profiling of human intraoperative or snap frozen and FFPE MBM.

  Dataset EGAD00001008508

• RNA-seq data from the tumor samples of head and neck cancer patients

  This dataset contains paired-end RNA sequencing data (2x50 bp) from the primary tumors and the recurrences/metastases of 6 head and neck cancer patients.

  Dataset EGAD00001011279

• Center for Common Disease Genomics [CCDG] - Neuropsychiatric: Autism - Simons Simplex Collection (SSC)

  In this study, we address the enormous challenges common complex diseases pose for genomic analysis and the enormous opportunities surmounting them offers for advancing healthcare. The common genetic disorders proposed for study here are believed to have extreme locus heterogeneity, requiring the analysis of large numbers of samples to comprehensively identify the genomic variants underlying them. We propose that a combination of deep population studies and joint analysis of SNPs, indels, and structural variants both in coding and noncoding regions will provide the next level of understanding of common genetic disorders. Whole genome sequencing (WGS) will be critical to this next-generation approach to the genomics of complex disease. WGS will need to be accompanied by the technical ability to generate and handle very large data sets, a particular focus and strength of New York Genome Center (NYGC). WGS will also need to be accompanied by new statistical tools and algorithms, which will be developed by the strong core group committed to this proposal. An overarching goal of this proposal, one that capitalizes on the power of WGS, is to identify disease-associated variants at the individual nucleotide level. In many cases pathogenic mutations fall in noncoding regions of the genome, which can only be fruitfully explored with WGS. A major effort was put into building new computational strategies to functionally annotate noncoding transcribed sequences, and to build new datasets to enable such strategies, opening new frontiers of understanding of disease-related regulatory variants.

  Study phs001676

• Center for Common Disease Genomics [CCDG] - Neuropsychiatric: SPARK Simons Foundation Powering Autism Research for Knowledge

  In this study, we address the enormous challenges common complex diseases pose for genomic analysis and the enormous opportunities surmounting them offers for advancing healthcare. The common genetic disorders proposed for study here are believed to have extreme locus heterogeneity, requiring the analysis of large numbers of samples to comprehensively identify the genomic variants underlying them. We propose that a combination of deep population studies and joint analysis of SNPs, indels, and structural variants, both in coding and noncoding regions, will provide the next level of understanding of common genetic disorders. Whole genome sequencing (WGS) will be critical to this next-generation approach to the genomics of complex disease. WGS will need to be accompanied by the technical ability to generate and handle very large data sets, a particular focus and strength of New York Genome Center (NYGC). WGS will also need to be accompanied by new statistical tools and algorithms, which will be developed by the strong core group committed to this proposal.An overarching goal of this proposal, one that capitalizes on the power of WGS, is to identify disease-associated variants at the individual nucleotide level. In many cases, pathogenic mutations fall in noncoding regions of the genome, which can only be fruitfully explored with WGS. A major effort was put into building new computational strategies to functionally annotate noncoding transcribed sequences, and to build new datasets to enable such strategies, opening new frontiers of understanding of disease-related regulatory variants.

  Study phs002511

• Tumor Evolution Analysis Uncovered Immune-Escape Related Mutations in Relapsed Diffuse Large B-Cell Lymphoma

  More than 60% of patients with primary diffuse large B-cell lymphoma (DLBCL) achieve durable remissions upon the chemoimmunotherapy with R-CHOP. However, the outcome of the relapse patients is extremely poor. To characterize the molecular features that underlie treatment resistance, we performed whole-exome sequencing (n=44) and deep targeted sequencing (n=27) of 44 diagnosis-relapse DLBCL pairs. We found that the overall landscape of genetic alterations was concordant between diagnosis and relapse DLBCL. By a deep comparison of the longitudinal sequencings, we identified relapse-enriched mutations that involved in evasion of immune surveillance (CD58, TNFRSF14, PKD1, FAS), resistance to DNA damaging agents (ATM, TP53), and critical tumor suppressor gene (ZFHX3). Knockdown of ATM and ZFHX3 resulted in increased drug resistance in both germinal center B cell like (GCB) and activated B cell like (ABC) DLBCL cell lines in vitro, while the knockdown of TNFRSF14 and FAS conferred resistance specifically in GCB cell lines. Furthermore, we summarized two evolutionary patterns of DLBCL relapse as the “durable retention” model with stable clone structure, and the “selective sweep” model which exhibited significant clonal switch. Of note, genetic alterations leading to attenuated immune responses usually presented as trunk mutations in the “durable retention” model (7/12) while were newly acquired or expanded upon relapse in the “selective sweep” model (9/16). Overall, our study demonstrated that relapse DLBCL derives from distinct clonal evolutionary patterns, and highlighted immune escape as an important contributor of tumor relapse.

  Study EGAS50000000032