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• Center for Technology Licensing at Cornell University for data associated with Nature Medicine 2024 paper

  For data access to plasma/tumor/normal samples from the manuscript "Ultrasensitive plasma-based monitoring of tumor burden using machine learning-guided signal enrichment" from Widman et al. Nature Medicine 2024

  Dac EGAC50000000207

• Identification of biomarkers for prediction of efficacy of microtubule inhibitors and antifolates in non-small cell lung cancer

  Identification of predictive markers based on transcriptome modules for microtubule inhibitors of lung adenocarcinoma patients

  Study JGAS000267

• Hi-C and promoter capture Hi-C data

  Hi-C and promoter capture Hi-C data for HT29 and LoVo. 2 replicates per cell line for the Hi-C. 3 replicates per cell line for the CHi-C.

  Dataset EGAD00001003257

• WGS data for MMML for Study EGAS00001002199

  Whole genome sequencing data for MMML (24 tumor/control pairs), fastq-files

  Dataset EGAD00001003276

• Validation for human early embryonic substitutions (2017-05-11)

  PCR and MiSeq validation for early embryonic substitution candidates from 400 Breast cancer patients This dataset contains all the data available for this study on 2017-05-11.

  Dataset EGAD00001003332

• DAC for access to anonymised study data for UK and Norwegian AAD families

  Dac EGAC00001000333

• monozygotic twin discordant for schizophrenia

  monozygotic twin discordant for schizophrenia

  Dataset EGAD00001000048

• Spatially resolved niche and tumor microenvironmental alterations in gastric cancer peritoneal metastases

  Peritoneal metastases (PM) in gastric cancer (GC) portend a poor prognosis, yet our understanding of tumor microenvironmental (TME) characteristics associated with GCPM remain limited. Here, we analyzed intrinsic genomic alterations and transcriptomic programs predictive of GCPM in a prospective cohort of 248 patients, identifying CDH1, PIGR, and ELF3 mutations as predictors. By inspecting the spatial dynamics of the TME, we find that tumor compartment infiltration of pro-tumorigenic cell types such as inflammatory cancer-associated fibroblasts (CAFs) predict peritoneal recurrence. Next, in a cross-sectional study of 205 samples from 55 patients, distinct pathways and immune compositions in GCPM relative to liver metastases highlight the TME's significance in transcoelomic metastases. Notably, several putative therapeutic targets exhibited distinct expression patterns between PTs and PMs. Our findings highlight transcriptomic variations and niche reprogramming in the GCPM peritoneal environment, revealing roles of myeloid dendritic cells, effector memory CD8+ T cells, and CAFs in metastatic progression.

  Study EGAS50000000501

• Recurrent COPA mutation drives R-spondin-independent Wnt activation in intestinal tumors

  The majority of intestinal tumors harbor mutations in canonical Wnt pathway genes such as APC, whereas the lack of such alterations in a subset of tumors implies alternative tumorigenic routes. Here, we identify recurrent in-frame deletion in COPA, frequently co-occurring with USP9X truncating mutation, in small intestinal adenoma and adenocarcinoma. Patient-derived and CRISPR-engineered small intestinal organoids carrying COPA in-frame deletions exhibit R-spondin-independent yet Wnt ligand-dependent growth, maintaining LGR5 expression without canonical Wnt drivers. Mechanistically, COPA mutation stabilizes frizzled co-receptor LRP6 irrespective of R-spondin, sustaining Wnt pathway activation under growth factor-restricted conditions. USP9X loss further potentiates this phenotype. Unlike canonical Wnt pathway members, COPA encodes the alpha-subunit of coatomer complex I, which engages in vesicle trafficking with little prior linkage to intestinal tumorigenesis. Our findings establish COPA mutation as a novel and atypical intestinal tumor driver and implicate USP9X loss as a cooperating lesion.

  Study JGAS000868

• H014: HES5 mediates NOTCH signaling by interaction with AKT to drive liver carcinogenesis

  Notch signaling plays a pivotal role in liver development and aberrant Notch signaling may lead to hepatocellular (HCC) or cholangiocellular carcinoma (CCA) development. Using whole exome sequencing of 54 human HCC samples, we discovered 19 somatic missense mutations in 15 different Notch pathway genes affecting 24.6% (14 of 57) of patients. Prediction of functional impact of these Notch pathway mutations revealed HES5-R31G to have high relevance. We found HES5 to be strongly activated by Notch signaling. In vitro, HES5 reduced cell migration and clonogenicity and in vivo, HES5 inhibited MYC-dependent liver tumor formation. But together with AKT, HES5 increased liver tumor formation in a mouse model. HES5 directly binds to AKT and AKT expression leads to increase HES5 protein levels. Furthermore, HES5 exhibits a negative feed-back loop by inhibiting NOTCH1 and HES1 gene expression. In contrast, HES5-R31G appears to be non-functional possibly by loss of nuclear translocation

  Study EGAS00001003329

• Genome-wide quantification of rare somatic mutations in normal human tissues using massively parallel sequencing

  We present Bottleneck Sequencing System (BotSeqS), a nextgeneration sequencing method that simultaneously quantifies rare somatic point mutations across the mitochondrial and nuclear genomes. BotSeqS combines molecular barcoding with a simple dilution step immediately prior to library amplification. We use BotSeqS to show age and tissue-dependent accumulations of rare mutations and demonstrate that somatic mutational burden in normal tissues can vary by several orders of magnitude, depending on biologic and environmental factors. We further show major differences between the mutational patterns of the mitochondrial and nuclear genomes in normal tissues. Lastly, the mutation spectra of normal tissues were different from each other, but similar to those of the cancers that arose in them. This technology can provide insights into the number and nature of genetic alterations in normal tissues and can be used to address a variety of fundamental questions about the genomes of diseased tissues.

  Study EGAS00001001838

• The genomic landscape of early stage ovarian high grade serous carcinoma

  To determine whether early-stage ovarian high grade serous carcinoma (HGSC) represents a distinct genomic entity, we collected samples from 43 patients with stage IA-IIA HGSC to identify potential differences in short genomic variants and copy number aberrations, and compared them to a cohort of 52 late-stage (stage IIIC-IV) cases. We found no significant differences in somatic mutations or focal copy number alterations between early-stage and late-stage cohorts. There was, however, a significant difference in both ploidy and copy number signature exposure between early and late-stage samples, with higher ploidy and signature 4 exposure in late-stage cases. Unsupervised hierarchical clustering revealed three clusters, which were prognostic. Together, our data suggest that early and late-stage HGSC share fundamental genomic features, but that late- stage disease appears distinct from early-stage, with evidence of whole genome duplication that may provide evolutionary benefit.

  Study EGAS00001005567

• DNAmet

  DNAmet analysis of olfactory mucosa (OM) cells derived from cognitively healthy and individuals with AD exposed to traffic-related ultrafine particles (UFPs) for 72h in submerged cultures. The UFPs used for exposures were: A0 and A20. Exposures were compared to the corresponding blank samples.

  Study EGAS50000001051

• miRNA seq

  miRNA Sequencing of olfactory mucosa (OM) cells derived from cognitively healthy and individuals with AD exposed to traffic-related ultrafine particles (UFPs) for 72h in submerged cultures. The UFPs used for exposures were: A0 and A20. Exposures were compared to the corresponding blank samples.

  Study EGAS50000001050

• Insights from genome-wide data from Thailand and Laos

  We provide the first detailed insights into the genetic profiles of Thai/Lao ethnolinguistic groups, which should be helpful for reconstructing human genetic history in MSEA and selecting populations for participation in ongoing whole genome sequence and biomedical studies

  Study EGAS00001006053

• Sequencing data for study Dissociation of solid tumour tissues with cold active protease for single-cell RNA-seq minimizes conserved collagenase-associated stress responses for library TENX021_SA854_001

  Single-cell RNA-sequencing data generated using the 10X genomics chromium platform, comprising patient derived xenograft, cell line, and primary tumour data. This includes different digestion conditions (37C collagenase vs 6C cold protease) and FACS sorting for live, dying, and dead cells. 3 samples; filetype=fastq

  Dataset EGAD00001005141

• Sequencing data for study Dissociation of solid tumour tissues with cold active protease for single-cell RNA-seq minimizes conserved collagenase-associated stress responses for library TENX021_SA854_004

  Single-cell RNA-sequencing data generated using the 10X genomics chromium platform, comprising patient derived xenograft, cell line, and primary tumour data. This includes different digestion conditions (37C collagenase vs 6C cold protease) and FACS sorting for live, dying, and dead cells. 3 samples; filetype=fastq

  Dataset EGAD00001005144

• Sequencing data for study Dissociation of solid tumour tissues with cold active protease for single-cell RNA-seq minimizes conserved collagenase-associated stress responses for library TENX023_SA604X9XB02413_002

  Single-cell RNA-sequencing data generated using the 10X genomics chromium platform, comprising patient derived xenograft, cell line, and primary tumour data. This includes different digestion conditions (37C collagenase vs 6C cold protease) and FACS sorting for live, dying, and dead cells. 24 samples; filetype=fastq

  Dataset EGAD00001005146

• Sequencing data for study Dissociation of solid tumour tissues with cold active protease for single-cell RNA-seq minimizes conserved collagenase-associated stress responses for library TENX004_SA605X3XB01966_004

  Single-cell RNA-sequencing data generated using the 10X genomics chromium platform, comprising patient derived xenograft, cell line, and primary tumour data. This includes different digestion conditions (37C collagenase vs 6C cold protease) and FACS sorting for live, dying, and dead cells. 12 samples; filetype=fastq

  Dataset EGAD00001005162

• Sequencing data for study Dissociation of solid tumour tissues with cold active protease for single-cell RNA-seq minimizes conserved collagenase-associated stress responses for library TENX056_VOA11924F_37C

  Single-cell RNA-sequencing data generated using the 10X genomics chromium platform, comprising patient derived xenograft, cell line, and primary tumour data. This includes different digestion conditions (37C collagenase vs 6C cold protease) and FACS sorting for live, dying, and dead cells. 12 samples; filetype=fastq

  Dataset EGAD00001005171

• Sequencing data for study Dissociation of solid tumour tissues with cold active protease for single-cell RNA-seq minimizes conserved collagenase-associated stress responses for library TENX019_SA604X7XB02089_003

  Single-cell RNA-sequencing data generated using the 10X genomics chromium platform, comprising patient derived xenograft, cell line, and primary tumour data. This includes different digestion conditions (37C collagenase vs 6C cold protease) and FACS sorting for live, dying, and dead cells. 24 samples; filetype=fastq

  Dataset EGAD00001005152

• Sequencing data for study Dissociation of solid tumour tissues with cold active protease for single-cell RNA-seq minimizes conserved collagenase-associated stress responses for library TENX006_PBC04106_001

  Single-cell RNA-sequencing data generated using the 10X genomics chromium platform, comprising patient derived xenograft, cell line, and primary tumour data. This includes different digestion conditions (37C collagenase vs 6C cold protease) and FACS sorting for live, dying, and dead cells. 3 samples; filetype=fastq

  Dataset EGAD00001005163

• Sequencing data for study Dissociation of solid tumour tissues with cold active protease for single-cell RNA-seq minimizes conserved collagenase-associated stress responses for library TENX051_PBC04633_001

  Single-cell RNA-sequencing data generated using the 10X genomics chromium platform, comprising patient derived xenograft, cell line, and primary tumour data. This includes different digestion conditions (37C collagenase vs 6C cold protease) and FACS sorting for live, dying, and dead cells. 12 samples; filetype=fastq

  Dataset EGAD00001005168

• Sequencing data for study Dissociation of solid tumour tissues with cold active protease for single-cell RNA-seq minimizes conserved collagenase-associated stress responses for library TENX055_VOA11924A_37C

  Single-cell RNA-sequencing data generated using the 10X genomics chromium platform, comprising patient derived xenograft, cell line, and primary tumour data. This includes different digestion conditions (37C collagenase vs 6C cold protease) and FACS sorting for live, dying, and dead cells. 12 samples; filetype=fastq

  Dataset EGAD00001005170

• Sequencing data for study Dissociation of solid tumour tissues with cold active protease for single-cell RNA-seq minimizes conserved collagenase-associated stress responses for library TENX049_SA928_003

  Single-cell RNA-sequencing data generated using the 10X genomics chromium platform, comprising patient derived xenograft, cell line, and primary tumour data. This includes different digestion conditions (37C collagenase vs 6C cold protease) and FACS sorting for live, dying, and dead cells. 12 samples; filetype=fastq

  Dataset EGAD00001005178