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• The Library of Integrated Network-Based Cellular Signatures (LINCS) - NeuroLINCS

  The NeuroLINCS Center is part of the NIH Common Fund's Library of Integrated Network-based Cellular Signatures (LINCS) program, which aims to characterize how a variety of human cells, tissues and the entire organism respond to perturbations by drugs and other molecular factors. As Part of the LINCS program, the NeuroLINCS study concentrates on human brain cells, which are far less understood than other cells in the body. Our initial focus is to produce diseased motor neurons from patients by utilizing high-quality induced pluripotent stem cell (iPSC) lines from Amyotrophic Lateral Sclerosis (ALS) and Spinal Muscular Atrophy (SMA) patients in addition to unaffected normal healthy controls. Using state-of-the-art OMICS methods (genomics, epigenomics, transcriptomics, and proteomics), we intend to create a wealth of cellular data that is patient-specific in the context of their baseline genetic perturbations and in the presence of other genetic and environmental perturbagens (e.g. endoplasmic reticulum stress). The primary data will be used to build cell signatures that convey the key features that distinguish the state of a cell and determine its behavior. Ultimately, the analysis of these datasets will lead to the identification of a network of unique signatures relevant to each of these motor neuron diseases. The datasets represented in this study are generated from assays interrogating RNA expression (RNA-seq), chromatin accessibility (ATAC-seq) and whole genome sequencing.

  Study phs001231

• Raw sequencing of single-cell RNA-seq data of a phase II clinical trial (NCT03419481)

  This is a single-arm Phase II trial of pembrolizumab in patients with hepatitis B virus-related hepatocellular carcinoma with parallel study on baseline and serial change in the immune environment.

  Study EGAS50000001315

• Targeted sequencing data of cfDNA, archival tissue, and WBC from 208 patients with mUC

  Targeted tissue (n=81), cfDNA (n=319), and WBC (n=208) Illumina sequencing of metastatic urothelial carcinoma patients. All cfDNA is collected in the metastatic setting, while archival tissue is from across the disease course. White blood cell (WBC) samples are used as patient matched germline samples. All files are in paired-end fastq format.

  Dataset EGAD50000002089

• Targeted sequencing data of cfDNA, archival tissue, and WBC from 226 patients with mUC

  Targeted tissue (n=210), cfDNA (n=402), and WBC (n=245) Illumina sequencing of metastatic urothelial carcinoma patients. All cfDNA is collected in the metastatic setting, while archival tissue is from across the disease course. White blood cell (WBC) samples are used as patient matched germline samples. All files are in paired-end fastq format.

  Dataset EGAD50000001571

• RNA-seq data of breast cancer HCI011 model from Ros et al (2020)

  RNA-seq data of the HCI011 and HCI011R models, GDC032 treated and control (total of 21 samples), from the paper: FOXM1 is a biomarker of resistance to PI3Kα inhibition in ER+ breast cancer that is detectable using metabolic imaging (Ros et al, 2020)

  Dataset EGAD00001006245

• Linked Read Sequencing of Gastric Cancer Metastases for Complex SV Resolution

  In this study, linked read sequencing was performed on two ovarian metastases and matched normal tissue, from a patient with primary diffuse gastric cancer. Linked read sequencing is a DNA preparation technology whereby high molecular weight molecules of DNA are uniquely barcoded prior to fragmentation and sequencing, thus retaining information about genomic contiguity. This study performed an extended analysis of linked read sequencing data to resolve the complex structures of structural variants in the cancer genomes. Complex structural rearrangements were identified in the genomic region surrounding the known oncogene FGFR2, and the association between FGFR2 and gastric cancer metastasis was demonstrated in an organoid model.

  Study phs001362

• Evolution and clinical impact of genetic epistasis within EGFR-mutant lung cancers: multi-timepoint exome sequencing of a single patient's disease

  This dataset is a time-series of EGFR-mutant NSCLC clinical specimens from an individual patient profiled using tumor-based whole exome sequencing and the data is in BAM format. DNA was extracted from FFPE for primary tumor and frozen tumor tissue samples and matched non-tumor tissue using the Qiagen Allprep DNA/RNA Mini Kit.  The library preparation protocol was based on the Agilent SureSelect Library Prep and Capture System. DNA was resuspended in a low TE buffer and sheared (Duty Cycle 5%; Intensity 175; Cycles/Burst: 200; Time: 300s, Corvaris S2 Utrasonicator).  Bar-coded exome libraries were prepared using the Agilent Sure Select V5 library kit per manfucaturer’s specifications. The libraries were run on the HiSeq2500. Raw paired end reads (100bp) in FastQ format generated by the Illumina pipeline were aligned to the full hg19 genomic assembly obtained from USCS, gencode 14, using bwa version 0.7.12. Picard tools version 1.117 was used to sort, remove duplicate reads and generate QC statistics. Tumor DNA was sequenced to median depth of 303X (range 114.39-383.41) and the matched germline DNA to average depth of 231.65.

  Dataset EGAD00001003769

• Improved Detection and Identification of Microsatellite Instability Features in Colorectal Cancer

  In this study, we analyzed a series of colorectal cancers using a new sequencing technology that sequences more than 200 microsatellite regions in parallel. With this technology, we evaluated mono-, di- , tri- and tetranucleotide repeats to provide a broad spectrum of microsatellite instability (MSI) events. This deep sequencing technology provides greater than 2000X coverage and eliminates the need for PCR amplification. Because every read corresponds to a single DNA molecule, we eliminated artifacts introduced by PCR that obscured true MSI events. Also included in our analysis is a new method for detection of somatic copy number changes in 83 cancer genes, with which we can infer chromosomal instability (CIN) status.

  Study phs001914

• Identification of improved IL28B SNPs and haplotypes for prediction of drug response in treatment of hepatitis C using massively parallel sequencing in a cross-sectional European cohort

  The hepatitis C virus infects nearly 3% of the World’s population, causing severe liver disease in many. Standard of care therapy is currently pegylated interferon alpha and ribavirin (PegIFN/R), which is effective in less than half of those infected with the most common viral genotype. Two IL28B SNPs, rs8099917 and rs12979860, predict response to (PegIFN/R) therapy in treatment of hepatitis C virus infection. These SNPs were identified in genome wide analyses using Illumina genotyping chips. In people of European ancestry, there are 6 common (>1%) haplotypes for IL28B, one tagged by rs8099917 minor allele, four tagged by rs12979860. We used massive parallel sequencing of the IL28B and IL28A gene regions generated by PCR from pooled DNA samples from 100 responders and 99 non-responders to therapy, to identify common variants. Variants that had high odds ratios and were validated were then genotyped in a cohort of 905 responders and non-responders. Their predictive power was assessed, alone and in combination with HLA-C. Only SNPs in the IL28B linkage disequilibrium block predicted drug response. Eighteen SNPs were identified with evidence for association with drug response, and with a high degree of confidence in the sequence call. We found that two SNPs, rs4803221 (homozygote minor allele positive predictive value (PPV) of 77%) and rs7248668 (PPV 78%), predicted failure to respond better than the current best, rs8099917 (PPV 73%) and rs12979860 (PPV 68%) in this cross-sectional cohort. The best SNPs tagged a single common haplotype, haplotype 2. Genotypes predicted lack of response better than alleles. However, combination of IL28B haplotype 2 carrier status with the HLA-C C2C2 genotype, which has previousl y been reported to improve prediction in combination with IL28B, provides the highest PPV (80%). The haplotypes present alternative putative transcription factor binding and methylation sites. Massive parallel sequencing allowed identification and comparison of the best common SNPs for identifying treatment failure in therapy for HCV SNPs tagging a single haplotype have the highest PPV, especially in combination with HLA-C. The functional basis for the association may be due to altered regulation of the gene. These approaches have utility in improving diagnostic testing and identifying causal haplotypes or SNPs.

  Study EGAS00001000096

• Genetics of gene expression in primary human immune cells

  The purpose of this study was to identify cell specific expression quantitative trait loci in freshly isolated highly purified primary B-cells and monocytes from healthy subjects of European ancestry. Cells were purified from Ficoll gradient prepared peripheral blood mononuclear cell fractions using positive selection via magnetic bead labelling of the B-cell marker CD19 and monocyte marker CD14. RNA was extracted from 287 B-cell samples and 288 monocyte samples. RNA was then hybridised to HumanHT-12 v4 BeadChips whole genome expression arrays (Illumina). Individuals were genotyped on HumanOmniExpress-12v1.0 BeadChips (Illumina) at 733202 genetic markers. Data presented include the raw expression values and Robust Spline Normalised values (RSN) for expression for each cell type per individual. Additional genotype data per individual is available on request.

  Study EGAS00000000109