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• The neo-open reading frame peptides that comprise the tumor framome are a rich source of neoantigens for cancer immunotherapy

  Identification of immunogenic cancer neoantigens as targets for therapy is challenging. Here, we integrate whole genome and long-read transcript sequencing of cancers to identify the collection of neo-open reading frame peptides (NOPs) expressed in tumors. We termed this collection of NOPs the tumor framome. NOPs represent tumor-specific peptides that are different from wild-type proteins and may be strongly immunogenic. We describe a class of hidden NOPs that derive from structural genomic variants involving an upstream protein coding gene driving expression and translation of non-coding regions of the genome downstream of a rearrangement breakpoint, i.e. where no gene annotation or evidence for transcription exists. The entire collection of NOPs represents a vast number of possible neoantigens particularly in tumors with many structural genomic variants and a low number of missense mutations. We show that NOPs are immunogenic and epitopes derived from NOPs can bind to MHC class I molecules. Finally, we provide evidence for the presence of memory T cells specific for hidden NOPs in peripheral blood from a patient with lung cancer. This work highlights NOPs as a major source of possible neoantigens for personalized cancer immunotherapy and provides a rationale for analyzing the complete cancer genome and transcriptome as a basis for detection of NOPs.

  Study EGAS00001006021

• WTCCC case-control study for Breast cancer - Combined Controls

  WTCCC genome-wide case-control association study for Breast cancer (BC) - Combined Controls.

  Study EGAS00000000025

• Exome sequencing for LySeqST

  Exome sequencing of 120 lymphoma samples and 13 normal samples for LySeqST: A targeted sequencing assay for robust genomic classification of diffuse large B-cell lymphoma.

  Dataset EGAD50000002289

• cfDNA dataset with expanded panel for cfDNA cohort

  Cell free DNA sequencing data for 9 samples with expanded panel across multiple cancer types for cfDNA cohort

  Dataset EGAD50000000667

• PPGL RNA-Seq dataset 2

  Dataset includes fastq files for RNA-Seq experiments for tumor samples of PPGL patients. Single end reads fastq files are available for 81 different samples

  Dataset EGAD50000000019

• Genome-wide DNA-methylation assessment by MethylCap-seq and Infinium HumanMethylation450 BeadChips: an independent large-scale comparison

  DNA-methylation is an important epigenetic feature in health and disease. Two cost-efficient genome-scale methodologies to assess DNA-methylation are MethylCap-seq and Illumina's Infinium HumanMethylation450 BeadChips (HM450). However, objective information regarding the best-suited methodology for a specific research question is scant. Therefore, we performed a large-scale evaluation on a set of 70 brain tissue samples obtained from 65 glioblastoma and 5 non-tumoral brain tissues, using a gold standard free Bayesian modeling procedure. While conditional specificity was adequate for both approaches, conditional sensitivity was systematically higher for HM450. Also the genome-wide characteristics were compared, revealing that the HM450 probes assess less than 10% of the regions identified as methylated by MethylCap-seq. Hence the latter method may detect more potentially relevant DNA-methylation, defined by either functional location or previously reported differentially methylated candidate regions. Our results therefore indicate that – at least for the tissue under study - both methodologies are complementary, with a higher sensitivity for HM450, but a far larger genome-wide coverage for MethylCap-seq. Note that here only the relevant MethylCap-seq data is deposited, for the HM450 data we refer to GEO (GSE60274).

  Study EGAS00001001191

• Effective screening strategy for deafness using a new-genetation sequencing platform: a consecutive analysis

  The diagnosis of the genetic etiology of deafness contributes to the clinical management of patients. We performed the following four genetic tests in three stages for 52 consecutive deafness subjects in one facility. We used the Invade assay and Sanger sequencing for the GJB2 gene or SLC26A4 gene in the first stage test, TaqMan genotyping assay in second stage test, and targeted exon sequencing using the massively parallel DNA sequencing in third stage test. Overall, we identified the genetic cause in 40% (21/52) of patients. The diagnostic rates of the first-, second- and third-stage genetic testing were 17%(9/52), 9%(4/43) and 21% (8/39), respectively. The combination approach using these genetic tests appears to be useful as a diagnostic tool for deafness patients. We recommended that genetic testing for the screening of common mutations in deafness genes using the Invader assay or TaqMan genotyping assay be performed as the initial evaluation. For the remaining undiagnosed cases, targeted exon sequencing using MPS is clinically and economically beneficial. This data set was MPS reads data (fastq) for 39 sensorineural hearing loss patients.

  Study JGAS000032

• Pipeline Olympics: Continuous benchmarking of computational workflows for DNA methylation sequencing data

  DNA methylation is a widely studied epigenetic mark and a powerful biomarker of cell type, age, environmental exposure, and disease. Genome-wide DNA methylation profiling is usually performed using whole-genome sequencing following selective conversion of unmethylated cytosines into thymines via bisulfite treatment or enzymatic methods. Numerous software tools facilitate processing of raw sequencing data for DNA methylation profiling, but a comprehensive benchmarking has been lacking. In this study, we systematically compared methods and tools for processing DNA methylation sequencing data. We established a dedicated benchmarking dataset comprising genome-wide DNA methylation profiling data for four reference samples using five experimental protocols each. The results of data processing were compared to highly quantitative locus-specific DNA methylation measurements available for 46 genomic loci. Based on this gold-standard reference dataset, we identified workflows that consistently demonstrated high performance. We present our results in an interactive application that provides a “living benchmark” ready for continuous updating as new workflows are proposed and require benchmarking against existing methods. In summary, our study provides guidance for any laboratory studying DNA methylation on a genome-wide scale.

  Study EGAS50000000541

• MGP Panel: a comprehensive targeted genomics panel for molecular profiling of multiple myeloma patients

  We designed a comprehensive multiple myeloma (MM) targeted sequencing panel to identify common genomic abnormalities in a single assay and validated it against known standards. The panel comprised 228 genes/exons for mutations, 6 regions for translocations, and 56 regions for copy number abnormalities (CNAs). Toward panel validation, targeted sequencing was conducted on 233 patient samples and further validated using clinical fluorescence in situ hybridization (FISH) (translocations), multiplex ligation probe analysis (MLPA) (CNAs), whole genome sequencing (WGS) (CNAs, mutations, translocations) or droplet digital PCR (ddPCR) of known standards (mutations). Canonical IgH translocations were detected in 43.2% of patients by sequencing, and aligned with FISH except for one patient. CNAs determined by sequencing and MLPA for 22 regions were comparable in 103 samples and concordance between platforms was R2=0.969. VAFs for 74 mutations were compared between sequencing and ddPCR with concordance of R2=0.9849. In summary, we have developed a targeted sequencing panel that is as robust or superior to FISH and WGS. This molecular panel is cost effective, comprehensive, clinically actionable and can be routinely deployed to assist risk stratification at diagnosis or post-treatment to guide sequencing of therapies.

  Study EGAS00001006222

• Demographic History and Local Adaptation in Asian Population

  Due to harboring high genetic and cultural diversity of populations, Central Asia is one key area for understanding the recent evolutionary history of humans. In this project, our aims include: (1) to resequence genome sequences with high sequencing depth for Central Asian populations Balti; (2) to discern the genomic diversity, populations structure and demographic history of Balti; (3) to investigate the genetic mechanisms for local adaptations in Balti.

  Study JGAS000238