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• Phenotype information

  This study explores the cell-free transcriptome in a humanized DLBCL patient-derived tumor xenograft (PDTX) model. Blood plasma samples (n=171) derived from a DLBCL PDTX model in-cluding 27 humanized (HIS) PDTX, 8 HIS non-PDTX and 21 non-HIS PDTX non-obese diabetic (NOD)-scid IL2Rgnull (NSG) mice were collected during humanization, xenografting, treatment, and sacrifice. The mice were treated with either rituximab, cyclophosphamide, doxorubicin, vincris-tine, and prednisone (R-CHOP), CD20-targeted human IFNα2-based AcTaferon combined with CHOP (huCD20-Fc-AFN-CHOP), or phosphate-buffered saline (PBS). RNA was extracted using the miRNeasy serum/plasma kit and sequenced on the NovaSeq 6000 platform using the using the SMARTer Stranded Total RNA-Seq Kit v3.

  Dataset EGAD50000000806

• Drug Perturbation of Primary Lymphoma Patient Samples and RNA Sequencing

  This submission contains 3'-end-based shallow-depth RNA sequencing data from 108 patients with chronic lymphocytic leukemia and 8 patients with lymphoma. Each primary patient sample was treated in vitro with DMSO as a control and with up to ten small-molecule drugs (ibrutinib, duvelisib, everolimus, trametinib, nutlin-3a, I-BET762, MK2206, selinexor, compound 26, and a combination of ibrutinib and compound 26). The samples were sequenced after 48 hours. The total data set consists of 1476 RNA sequencing samples from 6 batches (pilot, batch 1, batch 1 replicate, batch 2, batch 3, batch 4).

  Study EGAS50000001500

• Lymphoma_primary_patient_drug_perturbed_RNASeq_samples

  3'-end low-depth RNA sequencing data from 108 patients with chronic lymphocytic leukemia and 8 patients with lymphoma. Each primary patient sample was treated in vitro with DMSO as a control and with up to ten small-molecule inhibitors (ibrutinib, duvelisib, everolimus, trametinib, nutlin-3a, I-BET-762, MK2206, selinexor, compound 26, and a combination of ibrutinib and compound 26). Sequencing was performed on the Illumina HiSeq4000. The dataset contains FASTQ files.

  Dac EGAC50000000578

• scMultiome (snRNA + snATAC) data of 26 regionally sampled GBM tissue from 6 patients

  This dataset contains snRNA-seq data of 26 regionally sampled GBM tissue (peritumoral region, tumor edge, and tumor core). Regionally sampled GBM patient tissue was dissociated and nuclei were processed unsorted or by sorting with 7AAD to remove debris and dead cells. Single-nuclei suspension was prepared following the nuclei isolation protocol Single Cell Multiome ATAC + Gene Expression Sequencing protocol using Chromium Nuclei Isolation Kit. Single-nuclei suspension was prepared following the nuclei isolation protocol Single Cell Multiome ATAC + Gene Expression Sequencing protocol using Chromium Nuclei Isolation Kit, nuclei were barcoded and RNA and ATAC libraries were constructed, allowing for simultaneous capture of transcriptome and epigenome from the same cells.

  Dataset EGAD50000001838

• Exome-sequencing of human B cell lymphoma cell lines

  26 cell lines derived from human Diffuse Large B Cell lymphomas (DLBCL) or Burkit Lymphomas (BL) were subjected to whole exome sequencing. Exome capture was carried out using the SeqCap EZ Exome Library 2.0 kit (Roche/Nimblegen) and 100 bp single-read sequencing was performed on a HiSeq2500 (Illumina). 82% of the coding region was covered at least 30x.

  Dataset EGAD00001002262

• WES in muscle-invasive bladder cancer (MIBC) treated with durvalumab plus olaparib in the neoadjuvant setting: NEODURVARIB trial

  This submission contains the metadata derived from the whole exome sequencing of 70 samples from 26 patients who developed advanced urothelial carcinomas. The patients were enrolled in the Neodurvarib clinical trial, which compares the molecular profiles at diagnosis and after neoadjuvant treatment with Durvalumab and Olaparib. In this regard, the analyzed samples include: normal tissue and tumoral tissue obtained from the transurethral resection of the bladder (TURBT, a procedure performed prior to neoadjuvant therapy) from the 26 patients (52 samples), as well as tissue obtained from the radical cystectomy (a procedure performed after treatment with the aforementioned drugs; 18 samples).

  Study EGAS50000000791

• Poly(A) RNA sequencing of hepatocellular carcinoma tumors and their matched noncancerous liver tissues

  Background & Aims: The differentiation of distinct multifocal hepatocellular carcinoma (HCC): multicentric disease vs. intrahepatic metastases, in which the management and prognosis varies substantively, remains problematic. We aim to stratify multifocal HCC and identify novel diagnostic and prognostic biomarkers by performing whole genome and transcriptome sequencing, as part of a multi-omics strategy Methods: A complete collection of tumour and somatic specimens (intrahepatic HCC lesions, matched non-cancerous liver tissue and blood) were obtained from representative patientswith multifocal HCC exhibiting two distinct postsurgical courses. Whole-genome and transcriptome sequencing with genotyping were performed for each tissue specimen to con-trast genomic alterations, including hepatitis B virus integrations, somatic mutations, copy number variations, and structural variations. We then constructed a phylogenetic tree to visualise individual tumour evolution and performed functional enrichment analyses on select differentially expressed genes to elucidate biological processes involved in multifocal HCC development. Multi-omics data were integrated with detailed clinicopathological information to identify HCC biomarkers, which were further validated using a large cohort of HCC patients (n = 174).Results: The multi-omics profiling and tumour biomarkers could successfully distinguish the two multifocal HCC types, while accurately predicting clonality and aggressiveness. The dual specificity protein kinase TTK, which is a key mitotic checkpoint regulator with links to p53 signaling, was further shown to be a promising overall prognostic marker for HCC in the large patient cohort.Conclusions: Comprehensive multi-omics characterisation of multifocal tumour evolution may improve clinical decision-making, facilitate personalised medicine, and expedite identification of novel biomarkers and therapeutic targets in HCC.

  Study EGAS00001002337

• whole genome sequence data of multifocal hepatocellular carcinoma

  Background & Aims: The differentiation of distinct multifocal hepatocellular carcinoma (HCC): multicentric disease vs. intrahepatic metastases, in which the management and prognosis varies substantively, remains problematic. We aim to stratify multifocal HCC and identify novel diagnostic and prognostic biomarkers by performing whole genome and transcriptome sequencing, as part of a multi-omics strategy Methods: A complete collection of tumour and somatic specimens (intrahepatic HCC lesions, matched non-cancerous liver tissue and blood) were obtained from representative patientswith multifocal HCC exhibiting two distinct postsurgical courses. Whole-genome and transcriptome sequencing with genotyping were performed for each tissue specimen to con-trast genomic alterations, including hepatitis B virus integrations, somatic mutations, copy number variations, and structural variations. We then constructed a phylogenetic tree to visualise individual tumour evolution and performed functional enrichment analyses on select differentially expressed genes to elucidate biological processes involved in multifocal HCC development. Multi-omics data were integrated with detailed clinicopathological information to identify HCC biomarkers, which were further validated using a large cohort of HCC patients (n = 174).Results: The multi-omics pro?ling and tumour biomarkers could successfully distinguish the two multifocal HCC types, while accurately predicting clonality and aggressiveness. The dual speci?city protein kinase TTK, which is a key mitotic checkpoint regulator with links to p53 signaling, was further shown to be a promising overall prognostic marker for HCC in the large patient cohort.Conclusions: Comprehensive multi-omics characterisation of multifocal tumour evolution may improve clinical decision-making, facilitate personalised medicine, and expedite identi?cation of novel biomarkers and therapeutic targets in HCC.

  Study EGAS00001002338

• InsPIRE islets

  We explored the relationship between genetic variants influencing predisposition to type 2 diabetes (T2D) and related glycemic traits, and human pancreatic islet transcription using RNA-Seq and genotyping data from 420 islet donors and 26 FAC sorted beta-cells.

  Study EGAS00001003997

• Genetic analysis of HLA and immune escape genes in Diffuse Large B-cell Lymphoma

  We performed genetic analysis of HLA and immune escape genes in samples from 44 patients sequenced by whole exome sequencing (34 tumor samples, 32 normal samples) and whole genome sequencing (10 tumor samples, 12 normal samples). We also performed HLA targeted sequencing in 26/44 patients (26 tumor samples, 26 normal samples).

  Dataset EGAD00001007565