10960 results for "fc 26 coins u7buy Visit Buyfc26coins.com Megkaptam az FC 26 érméket a garantált idő előtt. Mindig bonuszként!.HNTf"

in 39.88 milliseconds.

• The immunological characterization of expanded tumor-infiltrating lymphocytes in renal cell carcinoma patients

  In this study, we comprehensively characterized the non-expanded and expanded tumor-infiltrating lymphocytes (TILs) from treatment-naïve RCC patients, as well as the corresponding “young” TILs (pre-REP TILs) and “rapidly expanded” TILs (REP TILs) following a clinical-grade TIL production protocol. From our scRNA+TCRαβ-seq and TCRβ-seq analyses, we show that the REP protocol preferentially favors the expansion CD4+ T-cells that originate from small T-cell clones in the tumor microenvironment (TME), indicating that the large, exhausted T-cell clones in the tumor do not expand during the protocol. We further identified RCC-associated TCR motifs that were validated in multiple TCRαβ-seq and scRNA+TCRαβ-seq datasets, as well as quantified the RCC-associated TCRs from the REP protocol. Overall, the T-cells carrying the RCC-associated TCRs remained high in the tumors and corresponding pre-REP TILs, but the frequency was reduced in the REP TILs. Furthermore, the overall anti-viral TCRs remained low throughout the REP protocol. Our results provide an in-depth understanding of the origin, phenotype, and specificity of the TCRs in RCC TILs.

  Study EGAS00001006952

• Covid19 Transcriptomic Data analysis in Irish Population

  The Samples were collected from Saint James's Hospital, Dublin and after informed consent. RNA-Sequencing library preparation was performed using the Illumina TruSeq Stranded Total RNA Library Prep Globin kit (20020612) with an input amount of 100 – 1000 ng. Library preparation was automated and processed using a Hamilton NGS Star. Library quality was assessed using the Roche KAPA Library Quantification Kit (7960298001) and GX Caliper HS Assay (CLS760672, 760517), run on Roche Lightcycler 480 II and Perkin Elmer LabChip GX Touch analyser respectively. Libraries were pooled and sequenced (75bp PE) on an Illumina NovaSeq 6000 instrument using NovaSeq 6000 S2 Reagent Kit v1.5 (20028314) targeting 50M paired reads. Raw data (BCL format) were demultiplexed and converted to FASTQ format using BCL2FastQ (Illumina). Adapters were trimmed using Skewer (PMID: 24925680) and QC assessed using FASTQC. STAR (PMID: 23104886) was used to align reads to the reference genome (GRCh38/hg38) as well as to the transcriptome (GENCODE v. 25). Quality of the RNA alignment was assessed using Picard QC. Gene and isoform quantification was performed using RSEM (PMID: 21816040). The study shares expression data (gene.results) and chimeric.junction.out.

  Study EGAS00001007116

• CM067 WES - Clinical Outcomes by Tumor Mutational Burden and Inflammatory Gene Expression With Combined Nivolumab and Ipilimumab or Monotherapy in Advanced Melanoma

  Purpose Exploratory analyses of CheckMate 066 and 067 trials were conducted to investigate associations of tumor mutational burden (TMB), a 4-gene inflammatory gene expression signature, and BRAF mutation status with tumor response, progression-free survival (PFS), and overall survival (OS) in patients with advanced melanoma. Patients and Methods Patients with known programmed death ligand 1 (PD-L1) expression and BRAF mutation status received nivolumab (NIVO) or dacarbazine in CheckMate 066 and either NIVO, ipilimumab (IPI), or NIVO+IPI in CheckMate 067. Whole exome sequencing and RNA sequencing were used to determine TMB and inflammatory gene expression signature scores, respectively. These biomarkers were evaluated in terms of their association with PFS and OS. Results In the NIVO, NIVO+IPI, and IPI arms of CheckMate 067, longer survival was associated with high (> median) versus low (≤ median) TMB with hazard ratios (HRs) (95% confidence interval [CI]) for PFS of 0.45 (0.30–0.65), 0.55 (0.38–0.81), and 0.60 (0.43–0.82), and for OS of 0.46 (0.30–0.71), 0.53 (0.34–0.82), and 0.52 (0.36–0.74), respectively. For NIVO-treated patients, these results were confirmed in CheckMate 066. A survival benefit was observed with high TMB and absence of BRAF mutation. Survival was associated with high versus low inflammatory signature scores with HRs (95% CI) for PFS of 0.56 (0.34–0.94), 0.40 (0.23–0.72), and 0.43 (0.27–0.70), and for OS of 0.37 (0.20–0.66), 0.38 (0.19–0.74), and 0.46 (0.27–0.79), in the NIVO, NIVO+IPI, and IPI arms, respectively. Weak correlations were observed between PD-L1, TMB, and the inflammatory signature. Conclusions Combined assessment of TMB, inflammatory gene expression signature, and BRAF mutation status may be predictive for response to immunotherapy in advanced melanoma.

  Dataset EGAD00001007573

• Somatic mutant selection is altered by prior NOTCH1 mutation in ageing esophageal epithelium

  Authors: Charlotte King1, Emilie Abbie1, Joanna C. Fowler1, Irina Abnizova1, Roshan K. Sood1, Swee Hoe Ong1, Michael W. J. Hall1,2, Faye Lynch-Williams3, Benjamin A. Hall4, Philip H. Jones1,2,5 Abstract: In cancer evolution, genome alterations often occur in a specific order, implying selection depends on the prior clonal genotype 1-3. It is unknown if similar constraints operate in normal epithelia. Here, we mapped mutations in normal mid-esophagus of aged UK subjects. Mutant NOTCH1 clones colonized most of the epithelium by age 60 and above 70 tissue was saturated with mutants under strong competitive selection. Mutant TP53 was more strongly selected in donors over 60 years of age. Samples predominantly mutant for NOTCH1 showed increased selection of NOTCH2 mutants and weaker selection of mutant TP53 compared with samples that were mostly NOTCH1 wild type. In mouse esophagus lacking Notch1 we observed strong selection of mutant Notch2 and other genes not selected in wild type esophagus. In normal ageing esophagus, the first driver mutation may change the trajectory of subsequent somatic evolution by altering mutant selection.

  Dataset EGAD00001015256

• Somatic mutant selection is altered by prior NOTCH1 mutation in ageing esophageal epithelium

  Authors: Charlotte King1, Emilie Abbie1, Joanna C. Fowler1, Irina Abnizova1, Roshan K. Sood1, Swee Hoe Ong1, Michael W. J. Hall1,2, Faye Lynch-Williams3, Benjamin A. Hall4, Philip H. Jones1,2,5 Abstract: In cancer evolution, genome alterations often occur in a specific order, implying selection depends on the prior clonal genotype 1-3. It is unknown if similar constraints operate in normal epithelia. Here, we mapped mutations in normal mid-esophagus of aged UK subjects. Mutant NOTCH1 clones colonized most of the epithelium by age 60 and above 70 tissue was saturated with mutants under strong competitive selection. Mutant TP53 was more strongly selected in donors over 60 years of age. Samples predominantly mutant for NOTCH1 showed increased selection of NOTCH2 mutants and weaker selection of mutant TP53 compared with samples that were mostly NOTCH1 wild type. In mouse esophagus lacking Notch1 we observed strong selection of mutant Notch2 and other genes not selected in wild type esophagus. In normal ageing esophagus, the first driver mutation may change the trajectory of subsequent somatic evolution by altering mutant selection.

  Dataset EGAD00001015257

• Somatic mutant selection is altered by prior NOTCH1 mutation in ageing esophageal epithelium

  Authors: Charlotte King1, Emilie Abbie1, Joanna C. Fowler1, Irina Abnizova1, Roshan K. Sood1, Swee Hoe Ong1, Michael W. J. Hall1,2, Faye Lynch-Williams3, Benjamin A. Hall4, Philip H. Jones1,2,5 Abstract: In cancer evolution, genome alterations often occur in a specific order, implying selection depends on the prior clonal genotype 1-3. It is unknown if similar constraints operate in normal epithelia. Here, we mapped mutations in normal mid-esophagus of aged UK subjects. Mutant NOTCH1 clones colonized most of the epithelium by age 60 and above 70 tissue was saturated with mutants under strong competitive selection. Mutant TP53 was more strongly selected in donors over 60 years of age. Samples predominantly mutant for NOTCH1 showed increased selection of NOTCH2 mutants and weaker selection of mutant TP53 compared with samples that were mostly NOTCH1 wild type. In mouse esophagus lacking Notch1 we observed strong selection of mutant Notch2 and other genes not selected in wild type esophagus. In normal ageing esophagus, the first driver mutation may change the trajectory of subsequent somatic evolution by altering mutant selection.

  Dataset EGAD00001015258

• Somatic mutant selection is altered by prior NOTCH1 mutation in ageing esophageal epithelium

  Authors: Charlotte King1, Emilie Abbie1, Joanna C. Fowler1, Irina Abnizova1, Roshan K. Sood1, Swee Hoe Ong1, Michael W. J. Hall1,2, Faye Lynch-Williams3, Benjamin A. Hall4, Philip H. Jones1,2,5 Abstract: In cancer evolution, genome alterations often occur in a specific order, implying selection depends on the prior clonal genotype 1-3. It is unknown if similar constraints operate in normal epithelia. Here, we mapped mutations in normal mid-esophagus of aged UK subjects. Mutant NOTCH1 clones colonized most of the epithelium by age 60 and above 70 tissue was saturated with mutants under strong competitive selection. Mutant TP53 was more strongly selected in donors over 60 years of age. Samples predominantly mutant for NOTCH1 showed increased selection of NOTCH2 mutants and weaker selection of mutant TP53 compared with samples that were mostly NOTCH1 wild type. In mouse esophagus lacking Notch1 we observed strong selection of mutant Notch2 and other genes not selected in wild type esophagus. In normal ageing esophagus, the first driver mutation may change the trajectory of subsequent somatic evolution by altering mutant selection.

  Dataset EGAD00001015259

• Somatic mutant selection is altered by prior NOTCH1 mutation in ageing esophageal epithelium

  Authors: Charlotte King1, Emilie Abbie1, Joanna C. Fowler1, Irina Abnizova1, Roshan K. Sood1, Swee Hoe Ong1, Michael W. J. Hall1,2, Faye Lynch-Williams3, Benjamin A. Hall4, Philip H. Jones1,2,5 Abstract: In cancer evolution, genome alterations often occur in a specific order, implying selection depends on the prior clonal genotype 1-3. It is unknown if similar constraints operate in normal epithelia. Here, we mapped mutations in normal mid-esophagus of aged UK subjects. Mutant NOTCH1 clones colonized most of the epithelium by age 60 and above 70 tissue was saturated with mutants under strong competitive selection. Mutant TP53 was more strongly selected in donors over 60 years of age. Samples predominantly mutant for NOTCH1 showed increased selection of NOTCH2 mutants and weaker selection of mutant TP53 compared with samples that were mostly NOTCH1 wild type. In mouse esophagus lacking Notch1 we observed strong selection of mutant Notch2 and other genes not selected in wild type esophagus. In normal ageing esophagus, the first driver mutation may change the trajectory of subsequent somatic evolution by altering mutant selection.

  Dataset EGAD00001015260

• Somatic mutant selection is altered by prior NOTCH1 mutation in ageing esophageal epithelium

  Authors: Charlotte King1, Emilie Abbie1, Joanna C. Fowler1, Irina Abnizova1, Roshan K. Sood1, Swee Hoe Ong1, Michael W. J. Hall1,2, Faye Lynch-Williams3, Benjamin A. Hall4, Philip H. Jones1,2,5 Abstract: In cancer evolution, genome alterations often occur in a specific order, implying selection depends on the prior clonal genotype 1-3. It is unknown if similar constraints operate in normal epithelia. Here, we mapped mutations in normal mid-esophagus of aged UK subjects. Mutant NOTCH1 clones colonized most of the epithelium by age 60 and above 70 tissue was saturated with mutants under strong competitive selection. Mutant TP53 was more strongly selected in donors over 60 years of age. Samples predominantly mutant for NOTCH1 showed increased selection of NOTCH2 mutants and weaker selection of mutant TP53 compared with samples that were mostly NOTCH1 wild type. In mouse esophagus lacking Notch1 we observed strong selection of mutant Notch2 and other genes not selected in wild type esophagus. In normal ageing esophagus, the first driver mutation may change the trajectory of subsequent somatic evolution by altering mutant selection.

  Dataset EGAD00001015261

• Pan-neuroblastoma analysis reveals age- and signature-associated driver alterations

  Neuroblastoma is a pediatric malignancy with heterogeneous clinical outcomes depending on age and other factors. To better understand neuroblastoma pathogenesis, here we analyze whole-genome, whole-exome and/or transcriptome sequencing data from 702 neuroblastoma samples, half of which are new data. Over 95% of samples harbor at least one recurrent driver alteration and most aberrations, including MYCN, ATRX, and TERT alterations, differ in frequency by age. MYCN alterations occur at median 2.3 years of age, TERT at 3.8 years, and ATRX at 5.6 years, suggesting age-specific susceptibility to genetic alterations. Mutational signature analysis shows that reactive oxygen-species (ROS)-induced mutations are the most common cause of single nucleotide variant (SNV) drivers in neuroblastoma, including most ALK and Ras pathway SNVs. ROS-induced mutagenesis is both an early event, as it causes truncal variants, and continuous as it also induces relapse-specific mutations. ROS-induced mutations are more abundant in neuroblastomas with MYCN amplification, 17q gains, and increased expression of mitochondrial ribosome genes. We observe recurrent FGFR1 N546K or internal tandem duplication variants in 6 patients and ALK N-terminal structural alterations in 5 samples, identifying additional patients amenable to precision therapy.

  Study EGAS00001003931

• CIDR: The Role of Rare Coding Variation in Prostate Cancer in Men of African Ancestry - RESPOND Project 2

  In RESPOND Project 2, we seek to identify rare genetic factors that are associated with prostate cancer (PCa) risk and aggressiveness in men of African ancestry (AA). We will conduct exome sequencing of 15,000 prostate cancer cases and 5,000 controls from the RESPOND cohort and the African Ancestry Prostate Cancer Consortium (AAPC) with cases selected based on risk categories: high-risk (stage T3/T4 or Gleason 8+ or PSA>20 ng/ml), intermediate-risk (stage T2b/T2c or Gleason 7 or PSA 10-20 ng/ml) and low-risk disease (stage T1/T2a and Gleason ≤ 6 and PSA<10 ng/ml). We expect the findings from this Project to significantly advance knowledge of susceptibility to aggressive PCa and racial/ethnic disparities in PCa risk, and to guide the development of future preventive, early detection and prognostic measures for AA men. The first phase of the study will include exome sequence data for approximately 7,500 cases and 5,000 controls from AAPC. The second phase of the study will include exome data for 5,000 cases from RESPOND and AAPC.ACKNOWLEDGMENTS and CONTRIBUTING SITES Multiethnic Cohort (MEC): The MEC and the genotyping in this study were supported by National Institutes of Health (NIH) grants CA63464, CA54281, CA1326792, CA148085, and HG004726. Cancer incidence data for the MEC and Los Angeles Study of Aggressive Prostate Cancer (LAAPC) studies have been collected by the Los Angeles Cancer Surveillance Program of the University of Southern California with federal funds from the National Cancer Institute (NCI)/NIH/Department of Health and Human Services (DHHS) under Contract No. N01-PC-35139, and the California Department of Health Services as part of the state-wide cancer reporting program mandated by California Health and Safety Code Section 103885, and grant 1U58DP000807-3 from the Centers for Disease Control and Prevention (CDC). Ghana Prostate Study (GPS): The Ghana Prostate Study was funded by the Intramural Program of the NCI/NIH/DHHS under Contract No. HHSN261200800001E. Men of African Descent and Carcinoma of the Prostate (MADCaP): We thank all MADCaP study participants. This work is a product of the MADCaP network. This work was supported by NCI/NIH grant U01CA184374 to Timothy Rebbeck and National Institute of General Medical Sciences (NIGMS) MIRA grant R35GM133727 to Joseph Lachance. Additional funding includes a seed grant from the Integrated Cancer Research Center at Georgia Institute of Technology. UGANDA: The UGANDA study was supported by NIH grant R01CA165862. Southern Community Cohort (SCCS) is funded by NIH grant CA092447. SCCS sample preparation was conducted at the Epidemiology Biospecimen Core Lab that is supported in part by the Vanderbilt Ingram Cancer Center (CA68485). Data on SCCS cancer cases were provided by Alabama Statewide Cancer Registry, Kentucky Cancer Registry, Office of Cancer Surveillance at Tennessee Department of Health, Florida Cancer Data System, Central Cancer Registry at North Carolina Division of Public Health, Georgia Comprehensive Cancer Registry, Louisiana Tumor Registry, Mississippi Cancer Registry, South Carolina Central Cancer Registry, Virginia Cancer Registry at Virginia Department of Health, and Cancer Registry at Arkansas Department of Health. The Arkansas Central Cancer Registry is fully funded by a grant from National Program of Cancer Registries (NPCR)/Centers for Disease Control and Prevention (CDC). Data on SCCS cancer cases from Mississippi were collected by the Mississippi Cancer Registry which participates in the NPCR/CDC. The contents of this publication are solely the responsibility of the authors and do not necessarily represent the official views of the CDC or the Mississippi Cancer Registry. Karuprostate: The Karuprostate study was supported by the French National Health Directorate and by the Association pour la Recherche sur les Tumeurs de la Prostate. Séverine Ferdinand, Marc Romana. The North Carolina - Louisiana Prostate Cancer Project (PCaP) is carried out as a collaborative study supported by the Department of Defense contract DAMD 17-03-2-0052. The authors thank the staff, advisory committees and research subjects participating in the PCaP study for their important contributions. We would also like to acknowledge the UNC BioSpecimen Facility and the LSUHSC Pathology Lab for our DNA extractions, blood processing, storage and sample disbursement (https://genome.unc.edu/bsp). Gene-Environment Interaction in Prostate Study (GECAP) was supported by NIH grant ES011126. King County Prostate Cancer Study (KCPCS) was supported by NIH grants CA056678, CA082664, and CA092579, with additional support from the Fred Hutchinson Cancer Research Center. We thank the participants in these studies, and Ms. Suzanne Kolb for help with study management. The Los Angeles Study of Aggressive Prostate Cancer (LAAPC) was funded by grant 99-00524V-10258 from the Cancer Research Fund, under Interagency Agreement #97-12013 (University of California contract #98-00924V) with the Department of Health Services Cancer Research Program. Cancer incidence data for the MEC and LAAPC studies have been collected by the Los Angeles Cancer Surveillance Program of the University of Southern California with Federal funds from the NCI/NIH/DHHS under Contract No. N01-PC-35139, and the California Department of Health Services as part of the state-wide cancer reporting program mandated by California Health and Safety Code Section 103885, and grant 1U58DP000807-3 from the CDC. Prostate Cancer Studies at MD Anderson (MDA) was supported by grants CA68578, ES007784, DAMD W81XWH-07-1-0645, and CA140388.

  Study phs002637

• Durvalumab Plus Tremelimumab Alone or in Combination with Low-Dose or Hypofractionated Radiotherapy in Metastatic Non-Small-Cell Lung Cancer Refractory to Previous PD(L)-1 Therapy: an Open-Label, Multicentre, Randomised, Phase 2 Trial

  Brief SummaryThis randomized phase II trial studies the side effects of durvalumab and tremelimumab and to see how well they work with or without high or low-dose radiation therapy in treating patients with colorectal or non-small cell lung cancer that has spread to other parts of the body (metastatic). Immunotherapy with durvalumab and tremelimumab, may induce changes in body's immune system and may interfere with the ability of tumor cells to grow and spread. Radiation therapy uses high energy x-rays to kill tumor cells and shrink tumors. Giving durvalumab and tremelimumab with radiation therapy may work better in treating patients with colorectal or non-small cell lung cancer.Detailed DescriptionPRIMARY OBJECTIVES:I. To assess safety and tolerability of combined checkpoint blockade with MEDI4736 (durvalumab) and tremelimumab alone or with high or low-dose radiation in non-small cell lung cancer (NSCLC). (NSCLC Cohort) II. To compare the overall response (excluding the irradiated lesion[s]) between combined checkpoint blockade with MEDI4736 and tremelimumab alone or combined checkpoint blockade with low or high dose radiation. (NSCLC Cohort) III. To assess safety and tolerability of combined checkpoint blockade with MEDI4736 and tremelimumab with high or low-dose radiation. (Colorectal Cohort) IV. To determine the overall response rate (excluding the irradiated lesion[s]) with combined checkpoint blockade with MEDI4736 and tremelimumab with either low or high dose radiation. (Colorectal Cohort)SECONDARY OBJECTIVES:I. To estimate median progression-free survival and overall survival. (NSCLC Cohort) II. To determine local control within the irradiated field(s) and abscopal response rates. (NSCLC Cohort) III. To evaluate associations between PD-L1 expression as well as levels of infiltrating CD3+, CD8+ T-cells and overall response. (NSCLC Cohort) IV. To explore changes in PD-L1 expression, circulating T-cell populations, T-cell infiltration, ribonucleic acid (RNA) expression, spatial relationship of immune markers, and mutational burden as a result of low or high dose radiation. (NSCLC Cohort) V. To estimate median progression-free survival and overall survival. (Colorectal Cohort) VI. To determine local control within the irradiated field and abscopal response rates. (Colorectal Cohort) VII. To evaluate associations between PD-L1 expression as well as levels of infiltrating CD3+ CD8+ T-cells and overall response. (Colorectal Cohort) VIII. To evaluate changes between PD-L1 expression as well as levels of infiltrating CD3+, CD8+ T-cells induced by targeted low or high dose radiation. (Colorectal Cohort) IX. To explore changes in circulating T-cell populations, T-cell infiltration, RNA expression, spatial relationship of immune markers, and mutational burden as a result of low or high dose radiation. (Colorectal Cohort)OUTLINE: Patients are assigned to 1 of 2 cohorts. NOTE: This Study is only for Cohort 1. Please see phs003294 for Cohort 2COHORT 1: Patients with NSCLC are randomized to 1 of 3 arms.ARM A: Patients receive tremelimumab and durvalumab and as in Arm C. Beginning at week 2, patients receive high dose radiation therapy once per day (QD) over 10 days for up to 3 fractions.ARM B: Patients receive tremelimumab and durvalumab and as in Arm C. Beginning at week 2, patients receive low dose radiation therapy every 6 hours twice per day (BID) on weeks 2, 6, 10 and 14.ARM C: Patients receive tremelimumab intravenously (IV) and durvalumab IV over 60 minutes every 4 weeks for up to 16 weeks in the absence of disease progression or unacceptable toxicity. Patients then receive durvalumab IV over 60 minutes 4 weeks after last combination dose for up to 9 additional doses.COHORT 2: Patients with CRC are randomized to 1 of 2 arms.ARM A: Patients receive tremelimumab intravenously (IV) and durvalumab IV over 60 minutes every 4 weeks for up to 16 weeks in the absence of disease progression or unacceptable toxicity. Patients then receive durvalumab IV over 60 minutes 4 weeks after last combination dose for up to 9 additional doses. Beginning at week 2, patients receive high dose radiation therapy once per day (QD) over 10 days for up to 3 fractions.ARM B: Patients receive tremelimumab intravenously (IV) and durvalumab IV over 60 minutes every 4 weeks for up to 16 weeks in the absence of disease progression or unacceptable toxicity. Patients then receive durvalumab IV over 60 minutes 4 weeks after last combination dose for up to 9 additional doses. Beginning at week 2, patients receive low dose radiation therapy every 6 hours twice per day (BID) on weeks 2, 6, 10 and 14.After completion of study treatment, patients are followed for up to 12 weeks.Official TitleA Phase 2 Study of MEDI4736 (Durvalumab) and Tremelimumab Alone or in Combination With High or Low-Dose Radiation in Metastatic Colorectal and NSCLC Conditions Metastatic Colorectal CarcinomaMetastatic Lung Non-Small Cell CarcinomaStage IV Colorectal Cancer AJCC v7Stage IV Lung Non-Small Cell Cancer AJCC v7Stage IVA Colorectal Cancer AJCC v7Stage IVB Colorectal Cancer AJCC v7 Intervention/Treatment Biological: DurvalumabRadiation: Radiation TherapyBiological: Tremelimumab Other Study ID Numbers NCI-2016-01325NCI-2016-01325 ( Registry Identifier ) (REGISTRY: CTRP (Clinical Trial Reporting Program))17-71910021 ( Other Identifier ) (OTHER: Dana-Farber - Harvard Cancer Center LAO)10021 ( Other Identifier ) (OTHER: CTEP) Molecular Technologies / AssaysCyTOFIHCmIFOlinkRNAseqWES

  Study phs003295

• RNAseq dataset for MALT1 in MCL

  Manuscript Title: Co-targeting of BTK and MALT1 overcomes resistance to BTK inhibitors in mantle cell lymphoma Journal: Journal of Clinical Investigation Authors Vivian Changying Jiang1, Yang Liu1, Junwei Lian1, Shengjian Huang1, Alexa Jordan1, Qingsong Cai1, Fangfang Yan3, Joseph Mitchell McIntosh1, Yijing Li1, Yuxuan Che1, Zhihong Chen1, Jovanny Vargas1, Maria Badillo1, JohnNelson Bigcal1, Heng-Huan Lee1, Wei Wang1, Yixin Yao1, Lei Nie1, Christopher Flowers1, and Michael Wang1, 2* Abstract Bruton’s tyrosine kinase (BTK) is a proven target in mantle cell lymphoma (MCL), an aggressive subtype of non-Hodgkin lymphoma. However, resistance to BTK inhibitors is a major clinical challenge. We here report that MALT1 is one of the top overexpressed genes in ibrutinib-resistant MCL cells, while expression of CARD11, which is upstream of MALT1, is decreased. MALT1 genetic knockout or inhibition produced dramatic defects in MCL cell growth regardless of ibrutinib sensitivity. Conversely, CARD11 knockout cells showed anti-tumor effects only in ibrutinib-sensitive cells, suggesting that MALT1 overexpression could drive ibrutinib resistance via bypassing BTK-CARD11 signaling. Additionally, BTK knockdown and MALT1 knockout markedly impaired MCL tumor migration and dissemination, and MALT1 pharmacological inhibition decreased MCL cell viability, adhesion, and migration by suppressing NF-κB, PI3K-ATK-mTOR, and integrin signaling. Importantly, co-targeting MALT1 with safimaltib and BTK with pirtobrutinib induced potent anti-MCL activity in ibrutinib-resistant MCL cell lines and patient-derived xenografts. Therefore, we conclude that MALT1 overexpression associates with resistance to BTK inhibitors in MCL, targeting abnormal MALT1 activity could be a promising therapeutic strategy to overcome BTK inhibitor resistance, and co-targeting of MALT1 and BTK should improve MCL treatment efficacy and durability as well as patient outcomes. Dataset description: The bulk RNA-seq dataset was generated for the cell lines below and used for two major purposes: 1. DEG analysis and GSEA analysis comparing IBN-R and IBN-S cells 2. DEG analysis and GSEA analysis comparing MCL cells with/without MI-2 treatment. sample Cell MI-2 Ibrutinib (IBN) Venetoclax (VEN) Used for IBN-R vs IBN-S comparison Used for MI-2 vs untreated (DMSO) H9 Granta519 - R S yes H21 Granta519 - R S yes H33 Granta519 - R S yes H10 Granta519-VEN-R - R R yes H22 Granta519-VEN-R - R R yes H34 Granta519-VEN-R - R R yes H3 JeKo BTK KD_1 - R R yes yes H15 JeKo BTK KD_1 - R R yes yes H27 JeKo BTK KD_1 - R R yes yes H5 JeKo BTK KD_2 - R R yes yes H17 JeKo BTK KD_2 - R R yes yes H29 JeKo BTK KD_2 - R R yes yes H1 JeKo-1 - S R yes yes H13 JeKo-1 - S R yes yes H25 JeKo-1 - S R yes yes H7 Mino - S S yes H19 Mino - S S yes H31 Mino - S S yes H8 Mino-VEN-R - S R yes H20 Mino-VEN-R - S R yes H32 Mino-VEN-R - S R yes H11 Rec-1 - S S yes H23 Rec-1 - S S yes H12 Rec-VEN-R - S S yes H24 Rec-VEN-R - S R yes H36 Rec-VEN-R - S R yes H35 Rec-1 -- S R yes H4 JeKo BTK KD_1 + MI-2 + yes H16 JeKo BTK KD_1 + MI-2 + yes H28 JeKo BTK KD_1 + MI-2 + yes H6 JeKo BTK KD_2 + MI-2 + yes H18 JeKo BTK KD_2 + MI-2 + yes H30 JeKo BTK KD_2 + MI-2 + yes H2 JeKo-1 + MI-2 + yes H14 JeKo-1 + MI-2 + yes H26 JeKo-1 + MI-2 + yes

  Dataset EGAD00001009771

• OV04 chemo prediction

  Predicting resistance to chemotherapy using chromosomal instability signatures Joe Sneath Thompson1,2,*, Laura Madrid2,*, Barbara Hernando1,*, Carolin M. Sauer3, Maria Vias3, Maria Escobar-Rey1,2, Wing-Kit Leung2,3, Diego Garcia-Lopez2, Jamie Huckstep3, Magdalena Sekowska3, Karen Hosking4,5, Mercedes Jimenez-Linan5,6, Marika A. V. Reinius3,5,6, Abhipsa Roy2, Omar Abdulle2, Justina Pangonyte3, Harry Dobson2, Amy Cullen2,3, Dilrini De Silva2, David Gómez-Sánchez1,7, Marina Torres1, Ángel Fernández-Sanromán1, Deborah Sanders3, Filipe Correia Martins3,5,6, Ionut-Gabriel Funingana3,4,5, Giovanni Codacci-Pisanelli3,4,8, Miguel Quintela-Fandino1, Florian Markowetz2,3,4, Jason Yip2, James D. Brenton2,3,4,5,6, Anna M. Piskorz#,2,3, Geoff Macintyre#,1,2 1 Spanish National Cancer Research Centre (CNIO), Madrid, Spain 2 Tailor Bio Ltd, Cambridge, UK 3 Cancer Research UK Cambridge Institute, University of Cambridge, Cambridge, UK 4 Department of Oncology, University of Cambridge, Cambridge, UK 5 Cambridge University Hospitals NHS Foundation Trust, Cambridge, UK 6 Cancer Research UK Major Centre - Cambridge, University of Cambridge, Cambridge, UK 7 H12O-CNIO Lung Cancer Clinical Research Unit, Health Research Institute Hospital 12 de Octubre (imas12), Madrid, Spain 8 University of Rome "la Sapienza", Rome, Italy

  Dac EGAC50000000612

• Single-cell RNA sequencing of airway epithelial cells derived from patient-specific and gene-corrected human iPSCs carrying a CCNO variant

  This study aims to elucidate the molecular mechanisms underlying the pathology of Primary Ciliary Dyskinesia (PCD) caused by disease-associated gene variants. To this end, we will establish patient-specific iPSCs and gene-corrected iPSC lines, differentiate them into airway epithelial cells, and perform single-cell RNA sequencing for comparative transcriptomic analysis. Insights gained from this study are expected to contribute to the development of novel diagnostic and therapeutic strategies for PCD.

  Study JGAS000846

• Personalized analysis of ctDNA for detection of molecular residual disease and recurrence in a cohort of surgically treated patients with head and neck squamous cell carcinoma

  Despite advances in multimodal treatment, survival for patients with advanced head and neck squamous cell carcinoma (HNSCC) has improved only modestly. The recent advent of tumor-informed assays capable of detecting circulating cell-free tumor DNA (ctDNA) has enabled early detection of molecular residual disease (MRD) and recurrence following curative therapy. We assessed ctDNA in plasma from 76 and saliva from 54 HNSCC patients, respectively, who received primary curative-intent surgery.

  Study EGAS50000001018

• A 3D genome atlas of breast cancer progression (BRCA3D)

  In this study, we aimed to understand how the 3D genome changes during breast cancer development and progression, in situ. Towards this goal, we collected cells from patient biopsies and performed Hi-C on four types of biopsies representing different stages of disease progression: healthy mammary tissue, primary breast tumours, liver metastasis and malignant pleural effusions. We survey the changes in the 3D genomes at the level of structural variation, compartments and TADs, as well as ERα associated distal interactions.

  Study EGAS50000000444

• A GWAS for cutaneous leishmaniasis in Brazil

  Our goal was to identify genetic risk factors for cutaneous leishmaniasis (CL) caused by Leishmania braziliensis. Genotyping 2066 CL cases and 2046 controls using Illumina HumanCoreExomeBeadChips provided data for 4,498,586 imputed single nucleotide variants (SNVs). Genome-wide association testing using linear mixed models took account of genetic diversity/ethnicity/admixture. Post-GWAS positional, expression quantitative trait locus (eQTL), and chromatin interaction mapping was performed in FUMA. Transcriptional data were compared between lesions and normal skin, and cytokines measured using flow cytometry and Bioplex assay.

  Study EGAS00001004596

• Catalogue Statistics

  EGA Statistics Bibliography Growth Community Archive Distribution Catalogue What is in the EGA? The European Genome-phenome Archive (EGA) overview The EGA archives and distributes the results of several types of studies. Such studies include genome-wide association studies (GWAS), different purpose sequencing and molecular diagnosis assays among others. Moreover, these studies target many different kind of diseases from cancer to neurodegenerative alterations. We summarised all this data in the charts below. The statistics are computed daily based on an updated list of studies. Each pie chart depicts a different aspect of the studies: which disease type was studied, which type of sampling method was used and what was the scope of the genomic analysis. Number of studies per disease type Studies in the EGA by disease barHorizontalChart('disease-graph', 'https://stats.ega-archive.org/catalog/by_disease') Number of studies per technology type Studies in the EGA by technology barHorizontalChart('technology-graph', '/stats/studies/technology', 'Include dbGaP') Number of studies per sample type Studies in the EGA by samples barChart('samples-graph', '/stats/studies/sample-types', 'Include dbGaP')

  Documentation about/statistics/catalogue

• scRNA-Seq & scATAC-Seq Feature-counting Results Derived from 10X Cellrange-arc-count pipeline

  The feature-counting outputs from Cellrange-arc-count pipeline contain information at the single cell level, jointly for both scRNA-Seq and scATAT-Seq on 103 DLBCL samples and 3 normal controls (Please note that sc-40 only has scRNA-Seq data without scATAC-Seq). These files can be used as the input files for further downstream analysis software (e.g. Seurat Package). Moreover, a matrix of single-cell barcodes and associated cell biological types (used in the study) is also provided for users’ reference. This dataset is large and split into two parts to facilitate downloads. This dataset is large and split into two parts to facilitate downloads. The Linux command line of "tar -xvf xxxx_PART1.gz" should be used to extract the individual files. For additional information regarding the genomic data associated with the study, please also see the paper companion website at https://llmpp.ccr.cancer.gov/local/DLBCL_singlecell/

  Dataset EGAD50000002490

• Progressive supranuclear palsy - bulk RNA seq of prefrontal cortex

  Dataset corresponding to the bulk RNA-seq dataset from prefrontal cortex for a total of N=42 samples. Tissue samples correspond to donors with pathologically confirmed progressive supranuclear palsy. RNA-seq was carried out using ribosomal depletion. Dataset contains paired fastq files, sample metadata and downstream quantification files. Quantification was performed with salmon v1.3.0 with Gencode 35 (GRCh38.p13).

  Dataset EGAD50000002623

• Multiple system atrophy - bulk RNA seq of prefrontal cortex

  Dataset corresponding to the bulk RNA-seq dataset from prefrontal cortex for a total of N=35 samples. Tissue samples correspond to donors with pathologically confirmed multiple system atrophy. RNA-seq was carried out using ribosomal depletion. Dataset contains paired fastq files, sample metadata and downstream quantification files. Quantification was performed with salmon v1.3.0 with Gencode 35 (GRCh38.p13). N=6 samples are overlapping with EGAS50000000301.

  Dataset EGAD50000002624

• Alzheimer's disease - bulk RNA seq of prefrontal cortex

  Dataset corresponding to the bulk RNA-seq dataset from prefrontal cortex for a total of N=72 samples. Tissue samples correspond to donors with pathologically confirmed Alzheimer's disease. RNA-seq was carried out using ribosomal depletion. Dataset contains paired fastq files, sample metadata and downstream quantification files. Quantification was performed with salmon v1.3.0 with Gencode 35 (GRCh38.p13).

  Dataset EGAD50000002625

• Dementia with Lewy bodies - bulk RNA seq of prefrontal cortex

  Dataset corresponding to the bulk RNA-seq dataset from prefrontal cortex for a total of N=80 samples. Tissue samples correspond to donors with pathologically confirmed dementia with Lewy bodies. RNA-seq was carried out using ribosomal depletion. Dataset contains paired fastq files, sample metadata and downstream quantification files. Quantification was performed with salmon v1.3.0 with Gencode 35 (GRCh38.p13).

  Dataset EGAD50000002626

• Parkinson's disease - bulk RNA seq of prefrontal cortex

  Dataset corresponding to the bulk RNA-seq dataset from prefrontal cortex for a total of N=448 samples. Tissue samples correspond to donors with pathologically confirmed Parkinson's disease. RNA-seq was carried out using ribosomal depletion. Dataset contains paired fastq files, sample metadata and downstream quantification files. Quantification was performed with salmon v1.3.0 with Gencode 35 (GRCh38.p13). N=81 samples are overlapping with EGAS50000000301.

  Dataset EGAD50000002627

• Controls - bulk RNA seq of prefrontal cortex

  Dataset corresponding to the bulk RNA-seq dataset from prefrontal cortex for a total of N=283 samples. Tissue samples correspond to health control donors. RNA-seq was carried out using ribosomal depletion. Dataset contains paired fastq files, sample metadata and downstream quantification files. Quantification was performed with salmon v1.3.0 with Gencode 35 (GRCh38.p13). N=21 samples are overlapping with EGAS50000000301.

  Dataset EGAD50000002628

• Corticobasal degeneration - bulk RNA seq of prefrontal cortex

  Dataset corresponding to the bulk RNA-seq dataset from prefrontal cortex for a total of N=17 samples. Tissue samples correspond to donors with pathologically confirmed corticobasal degeneration. RNA-seq was carried out using ribosomal depletion. Dataset contains paired fastq files, sample metadata and downstream quantification files. Quantification was performed with salmon v1.3.0 with Gencode 35 (GRCh38.p13).

  Dataset EGAD50000002629

• DEPArray-based sorting of pure carcinoma and stromal populations from formalin-fixed paraffin-embedded (FFPE) tissues followed by shallow whole genome sequencing

  To overcome the challenges of low DNA yields, degraded DNA by formalin fixation and diluted signal of genomic aberrations by non-carcinoma components in the heterogeneous FFPE samples, we isolated pure carcinoma and stromal cells using the DEPArray™ NxT system, a microchip-based digital sorter that allows isolation of pure, homogeneous subpopulations of cells from FFPE samples. We isolated pure carcinoma and stromal cell populations from 12 FFPE tissues, including tissues from 9 primary and metastatic breast cancer and 3 primary ovarian high-grade serous carcinomas. This was followed by downstream shallow whole genome sequencing (WGS) for copy number landscape profiling for 10 samples. Seven out of 10 samples (even some with low tumour content or of old age) produced good quality genomic data, detecting sCNA in all carcinoma population samples but not in the stromal populations.

  Dataset EGAD50000001895

• DEPArray-based sorting of pure carcinoma and stromal populations from formalin-fixed paraffin-embedded (FFPE) tissues followed by shallow whole genome sequencing

  To overcome the challenges of low DNA yields, degraded DNA by formalin fixation and diluted signal of genomic aberrations by non-carcinoma components in the heterogeneous FFPE samples, we isolated pure carcinoma and stromal cells using the DEPArray™ NxT system, a microchip-based digital sorter that allows isolation of pure, homogeneous subpopulations of cells from FFPE samples. We isolated pure carcinoma and stromal cell populations from 12 FFPE tissues, including tissues from 9 primary and metastatic breast cancer and 3 primary ovarian high-grade serous carcinomas. This was followed by downstream shallow whole genome sequencing (WGS) for copy number landscape profiling for 10 samples. Seven out of 10 samples (even some with low tumour content or of old age) produced good quality genomic data, detecting sCNA in all carcinoma population samples but not in the stromal populations.

  Dataset EGAD50000001894

• DEPArray-based sorting of pure carcinoma and stromal populations from formalin-fixed paraffin-embedded (FFPE) tissues followed by shallow whole genome sequencing

  To overcome the challenges of low DNA yields, degraded DNA by formalin fixation and diluted signal of genomic aberrations by non-carcinoma components in the heterogeneous FFPE samples, we isolated pure carcinoma and stromal cells using the DEPArray™ NxT system, a microchip-based digital sorter that allows isolation of pure, homogeneous subpopulations of cells from FFPE samples. We isolated pure carcinoma and stromal cell populations from 12 FFPE tissues, including tissues from 9 primary and metastatic breast cancer and 3 primary ovarian high-grade serous carcinomas. This was followed by downstream shallow whole genome sequencing (WGS) for copy number landscape profiling for 10 samples. Seven out of 10 samples (even some with low tumour content or of old age) produced good quality genomic data, detecting sCNA in all carcinoma population samples but not in the stromal populations.

  Dataset EGAD50000001893

• DEPArray-based sorting of pure carcinoma and stromal populations from formalin-fixed paraffin-embedded (FFPE) tissues followed by shallow whole genome sequencing

  To overcome the challenges of low DNA yields, degraded DNA by formalin fixation and diluted signal of genomic aberrations by non-carcinoma components in the heterogeneous FFPE samples, we isolated pure carcinoma and stromal cells using the DEPArray™ NxT system, a microchip-based digital sorter that allows isolation of pure, homogeneous subpopulations of cells from FFPE samples. We isolated pure carcinoma and stromal cell populations from 12 FFPE tissues, including tissues from 9 primary and metastatic breast cancer and 3 primary ovarian high-grade serous carcinomas. This was followed by downstream shallow whole genome sequencing (WGS) for copy number landscape profiling for 10 samples. Seven out of 10 samples (even some with low tumour content or of old age) produced good quality genomic data, detecting sCNA in all carcinoma population samples but not in the stromal populations.

  Dataset EGAD50000001892

• DEPArray-based sorting of pure carcinoma and stromal populations from formalin-fixed paraffin-embedded (FFPE) tissues followed by shallow whole genome sequencing

  To overcome the challenges of low DNA yields, degraded DNA by formalin fixation and diluted signal of genomic aberrations by non-carcinoma components in the heterogeneous FFPE samples, we isolated pure carcinoma and stromal cells using the DEPArray™ NxT system, a microchip-based digital sorter that allows isolation of pure, homogeneous subpopulations of cells from FFPE samples. We isolated pure carcinoma and stromal cell populations from 12 FFPE tissues, including tissues from 9 primary and metastatic breast cancer and 3 primary ovarian high-grade serous carcinomas. This was followed by downstream shallow whole genome sequencing (WGS) for copy number landscape profiling for 10 samples. Seven out of 10 samples (even some with low tumour content or of old age) produced good quality genomic data, detecting sCNA in all carcinoma population samples but not in the stromal populations.

  Dataset EGAD50000001891

• DEPArray-based sorting of pure carcinoma and stromal populations from formalin-fixed paraffin-embedded (FFPE) tissues followed by shallow whole genome sequencing

  To overcome the challenges of low DNA yields, degraded DNA by formalin fixation and diluted signal of genomic aberrations by non-carcinoma components in the heterogeneous FFPE samples, we isolated pure carcinoma and stromal cells using the DEPArray™ NxT system, a microchip-based digital sorter that allows isolation of pure, homogeneous subpopulations of cells from FFPE samples. We isolated pure carcinoma and stromal cell populations from 12 FFPE tissues, including tissues from 9 primary and metastatic breast cancer and 3 primary ovarian high-grade serous carcinomas. This was followed by downstream shallow whole genome sequencing (WGS) for copy number landscape profiling for 10 samples. Seven out of 10 samples (even some with low tumour content or of old age) produced good quality genomic data, detecting sCNA in all carcinoma population samples but not in the stromal populations.

  Dataset EGAD50000001889

• Differential expression in clear cell renal cell carcinoma

  To investigate the levels of gene expression in clear cell renal cell carcinoma (ccRCC), we performed an RNA-seq analysis in 786-O, A-498, UM-RC-2 clear cell renal carcinoma cell lines, as well as HK-2 normal renal epithelium cell line, cultured under normoxic (20% O2) and hypoxic (0.05% O2) conditions. Data are provided in raw fastq files and csv files with the differential expression results. Differential expression was calculated by the RNAflow pipeline (DEseq2), and log fold changes are calculated with respect to the normal cell line (HK-2), with separate results between normoxic and hypoxic datasets.

  Dataset EGAD50000001883

• Whole Exome Sequencing analysis of three tumor biopsies from a LUAD patient

  Whole Exome Sequencing (WES) analysis was performed on three distinct tumor biopsies collected at different time points, along with their matched germline non-tumor sample, from the same LUAD patient. DNA was extracted using the DNeasy Blood and Tissue Kit (Qiagen, Germantown, MD) according to the manufacturer’s instructions and quantified using the Qubit Fluorometer assay (Life Technologies, Carlsbad, CA). To minimize FFPE-related sequencing artifacts (e.g., C:G > T:A transitions), the extracted DNA was treated with the DNA repair enzyme Uracil-DNA-Glycosylase (UDG) following the manufacturer’s protocol (New England Biolabs, Ipswich, MA). Whole-exome capture was performed with the Twist Human Core Exome + RefSeq + Mito-Panel kit (Twist Bioscience), in accordance with the manufacturer’s guidelines. Sequencing generated paired-end 100-bp reads on the Illumina NovaSeq 6000 platform. The resulting reads were aligned to the reference human genome (GRCh38) using the Burrows-Wheeler Aligner (BWA, v0.7.12).

  Dataset EGAD50000001198

• Variant calling dataset from the whole-exome study of familial pulmonary fibrosis in the Canary Islands-VCF files

  Sequence reads were obtained from a set of 13 families with familial pulmonary fibrosis in the Canary Islands, Spain, using Illumina paired-end reads, respectively, at the Institute of Technology and Renewable Energy (ITER). Briefly, we used bcl2fastq v2.18 to perform sample demultiplexing and BWA-MEM v0.7.15 (https://github.com/lh3/bwa) to align reads to GRCh37/hg19 reference. Resulting BAM files were assessed with SAMtools v1.3 (http://www.htslib.org) and Picard v2.10.10 (https://broadinstitute.github.io/picard/) for quality control steps. Small insertions/deletions (< 50 bp) and single nucleotide variants (SNVs) were identified using an in-house bioinformatics pipeline based on GATK HaplotypeCaller v3.8 (https://gatk.broadinstitute.org/hc/en-us/articles/360037225632-HaplotypeCaller). This pipeline follows the Best Practices recommendations for germline variant calling and its description is publicly available (https://github.com/genomicsITER/benchmarking/tree/master/WES).

  Dataset EGAD50000001152

• Calprotectin in vitro effects on human early hematopoiesis

  Dataset content : Raw data from sequencing (fastq) 184 samples from 4 experiments : - Bulk mRNA seq - 24h and 48h, CTRL, CAL, IL6 and combination treatment - single-cell RNAseq - 7days CTRL, CAL, IL6 and combination treatment - ATACseq - 7days CTRL, CAL, IL6 and combination treatment To explore the effects of calprotectin (CAL) on early hematopoiesis, we incubated CD34+ cells from four healthy donors for 7 days in the presence of stem cell factor (SCF), FLT3-ligand and thrombopoietin (TPO) without and with CAL, interleukin-6 (IL6) and the IL6_CAL combination before collecting cells. We performed the same experiment with CD34+ cells collected from three patients with JAK2-V617F-mediated myelofibrosis (MF). A total of 135,545 cells from healthy donors and 111,725 cells from myelofibrosis patients were analyzed by single-cell RNA sequencing (scRNA-seq) using the 10X Chromium droplet-based platform.

  Dataset EGAD50000000659

• Single-nuclei RNA sequencing of pheochromocytoma and paraganglioma arising from germline SDHB mutations

  10x genomics single-nuclei RNA sequencing of 9 SDHB-deficient non-metastatic and metastatic pheochromocytoma and paraganglioma. snRNA-seq was performed using the ‘Frankenstein’ protocol (dx.doi.org/10.17504/protocols.io.bqxymxpw). Briefly, nuclei were extracted from frozen tissues and subjected to fluorescence-activated nuclei sorting (FANS) using 4′,6-diamidino-2-phenylindole (DAPI). Sorting was performed using a BD FACSaria 2 instrument, sorting between 3000 and 10,000 nuclei per sample, capturing both diploid and tetraploid populations. FAN-sorted nuclei were immediately processed using either the 10x Chromium Single Cell 5’ (PN-1000006, 4 samples) or 3’ (PN-1000075, 4 samples) Library & Gel Bead Kit (10x Genomics, USA). Once processed, snRNA-seq libraries were sequenced on the Illumina Nova-Seq 6000 (Illumina, USA) using 150bp paired-end sequencing. This dataset contains raw sequencing reads in FASTQ format.

  Dataset EGAD50000000505

• A single-cell multi-omic atlas of nodal B-cell non-Hodgkin lymphomas

  CITE-Seq (cellular indexing of transcriptomes and epitopes) of 51 lymph node (LN) samples from including mantle cell lymphoma (MCL, n = 8), follicular lymphoma (FL, n = 12), germinal center (GCB, n = 5) or activated B-cell (non-GCB/ABC, n = 7) diffuse large B-cell lymphoma (DLBCL), and marginal zone lymphomas (MZL, n = 11), in addition to non-malignant reactive lymph nodes (rLN, n = 8). Of the malignant LN samples, 20 were collected at the time of initial diagnosis and 23 were from patients who had previously undergone one or more lines of systemic treatment. Relapse samples were collected at least 3 months after cessation of systemic treatment. This dataset also includes 5 prime RNA sequencing and immune receptor sequencing (10X Genomics) for 11 of these samples (2 rLN, 2 MCL, 3 FL, 2 DLBCL (GCB) and 2 MZL).

  Dataset EGAD50000000497

• RNA sequencing from patient-derived intestinal organoids

  uman duodenal tissues for establishing organoid cultures used in this study were sourced from de-identified surgical specimens (n = 3) of the duodenum obtained from patients who had undergone biopsy procedures unrelated to CeD at Tampere University Hospital. The protocol was approved by the Ethics Committee of Tampere University Hospital, Tampere, Finland (ETL code R18082). RNA from the duodenal organoids was isolated using an RNeasy Kit (Qiagen, Hilden, Germany) following the manufacturer’s instructions. RNA purity and concentration were measured using a NanoDrop One spectrophotometer (NanoDrop Technologies, Wilmington, Delaware, USA). Preparation of the RNA library and transcriptome sequencing was conducted by Novogene Co., LTD (Cambridge, UK). Messenger RNA was purified from total RNA using polyA selection and subjected to library construction. Sequencing was performed on an Illumina platform, and 150 bp paired-end reads were generated.

  Dataset EGAD50000000492

• EpiMatch_DNA_Methylation_Resource

  Genome-wide DNA Methylation Data from Illumina HumanMethylationEPIC arrays for whole blood samples from 403 healthy individuals. Additional raw data (IDAT files) and associated phenotype information are available for all individuals included in this study (n=570) directly from CIBMTR. Data are available under controlled access release upon reasonable request and execution of a data use agreement. Requests should be submitted to CIBMTR at info-request@mcw.edu and include the study reference IB17-04

  Dataset EGAD00010002283

• Exome sequencing of patients with Ewings sarcoma

  Cancer is driven by mutations in the genome. We will uncover the mutations that give rise to Ewing's sarcoma, a bone tumour that largely affects children. We will use second generation Illumina massively parallel sequencing, and bespoke software, to characterise the genomes and transcriptomes of Ewing,s sarcoma tumours.

  Dataset EGAD00001000333

• RNA sequencing of Korean ER positive breast cancer females aged under 35 years old.

  Corresponding data set is composed of RNA sequencing of Korean ER positive breast cancer under 35 years old. This set provides 50 alignment files of 50 tumor samples. This is a part of total project data set.

  Dataset EGAD00001003243

• Lung cancer organoids

  Organoids are self-organizing 3D structures grown from stem cells that recapitulate essential aspects of organ structure and function. Here we describe a method to establish long-term culture conditions of human airway epithelial organoids that contain all major cell populations and allow personalized human disease modelling. We collected macroscopically inconspicuous lung tissue from non-small-cell lung cancer (NSCLC) patients undergoing medically indicated surgery and isolated epithelial cells to engineer 3D organoids. We exploit the potential to derive sub-clones from AOs to demonstrate the feasibility of CRISPR gene editing. Finally, we show that AOs readily allow modelling of viral infections such as RSV and for the first time demonstrate the possibility to study neutrophil-epithelium interaction in an organoid model. Taken together, we anticipate that human AOs will find broad applications in the study of adult human airway epithelium in health and disease.

  Dataset EGAD00001004013

• Exome sequencing of 142 gastric cancer and matched normal from Japanese cohorts (UT)

  As a contribution to the International Cancer Genome Consortium, exome sequencing of 142 Japanese gastric cancer with various histological subtypes have been conducted. This study aims to identify unique and common driver genes and molecular subtypes in Japanese gastric cancer. Please refer ICGC website for detail: http://icgc.org/icgc/cgp/69/420/1012357

  Dataset EGAD00001004041

• Exome sequencing of 102 gastric cancer and matched normal from Japanese cohorts (YCU)

  As a contribution to the International Cancer Genome Consortium, exome sequencing of 102 Japanese gastric cancer with various histological subtypes have been conducted. This study aims to identify unique and common driver genes and molecular subtypes in Japanese gastric cancer. Please refer ICGC website for detail: http://icgc.org/icgc/cgp/69/420/1012357

  Dataset EGAD00001004042

• Whole Genome Sequencing of a secondary myelodysplastic syndrome (MDS)

  Illumina HiSeq sequence data (with &gt;30x coverage) were aligned to the hg19 human reference genome assembly using BWA (Li and Durbin, 2009); duplicate reads were removed from the final BAM file. No realignment or recalibration was performed. Sample derived from secondary myelodysplastic syndrome (MDS), arising after treatment for medulloblastoma in an 11-year old female Li-Fraumeni syndrome case (LFS-MB1; Rausch et al., 2012; matching WGS data available under EGAS00001000085).

  Dataset EGAD00001000665

• SPECTA: NGS Screening Program for Efficient Clinical Trial Access

  SPECTA comprises a network of participating European clinical sites and NGS screening platforms that can screen individual patients for multiple molecular targets and potentially allow the design of trials that will match the specific biology of the diseases affecting specific patients with cancer.

  Dataset EGAD00001000894

• Comparison of transcriptional response of induced pluripotent stem (iPS) cell-derived and monocyte-derived macrophages to bacterial lipopolysaccharide stimulation

  In the first part of this project, we will differentiate IPS cells from 5 human donors into macrophages, and extract RNA from unstimulated and LPS stimulated macrophages to perform RNA sequencing. We will also extract RNA before and after stimulation in blood- derived macrophages from 5 additional, unrelated healthy samples. In the second part of the project, RNA-seq data will be analysed to compare LPS response of these two macrophage populations. In summary, we will perform 75bp PE RNA-seq on 20 samples (10 pre and post stimulus), on the HiSeq 2500 platform. Samples will be multiplexed at 5 samples / lane, so we will require 4 flow cells in total.This data is part of a pre-publication release. For information on the proper use of pre-publication data shared by the Wellcome Trust Sanger Institute (including details of any publication moratoria), please see http://www.sanger.ac.uk/datasharing/

  Dataset EGAD00001001106

• Atypical teratoid/rhabdoid tumors (ATRT) are comprised of three epigenetic subgroups with distinct enhancer landscapes

  Atypical teratoid/rhabdoid tumor (ATRT) is one of the most common brain tumors in infants and young children. Although the prognosis of ATRT patients is poor, some patients respond very well to current treatments, suggesting inter-tumor molecular heterogeneity. To investigate this further, we genetically and epigenetically analyzed a large cohort of ATRTs (n = 170). Three distinct molecular subgroups of ATRTs, associated with differences in demographics, tumor location and type of SMARCB1 alterations, were identified using DNA-methylation or gene expression analyses. Whole genome DNA- and RNA-sequencing found no other recurrent mutations explaining the differences between subgroups. However, whole genome bisulfite-sequencing and H3K27Ac ChIP-sequencing of primary tumors revealed clear differences in methylation patterns and enhancer landscapes, leading to the identification of subgroup-specific regulatory networks.

  Dataset EGAD00001001444