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• Genomic consequences of aberrant DNA repair mechanisms stratify ovarian cancer histotypes

  Aberrant DNA repair processes are a hallmark of human tumours. How these deficiencies variously impact the genomes of ovarian cancer between and within histotypes remains unknown. We studied the whole genome pointmutation and structural variation patterns of 133 tumours (59 high grade serous (HGSC), 35 clear cell (CCOC), 29 endometrioid (ENOC), and 10 adult granulosa cell tumours (GCT)) as a substrate for class discovery in ovarian cancer. Ab-initio clustering of integrated point mutation and structural variation signatures revealed seven novel subgroups, comprising between and within histotype stratification. Prevalence of fold-back inversions (FBI) co-localised with high level amplification events divided HGSC into two prognostically significant subgroups. This finding was recapitulated in two additional independent cohorts (total n=576 cases), and transcended gene based mutation status and gene expression as prognostically relevant features of HGSC. CCOC were divided into one group harbouring a signature reflective of active genome editing via APOBEC enzymes (26%) and a complementary group with an age-relatedmutational signature. ENOC were divided intomicrosatellite instable (MSI) cases (28%) with a distinctmismatch repairmutation signature and an outlying mutation rate, with the remainder of cases distributed amongst the remaining six groups. We suggest the FBI, MSI, and APOBEC groups represent biologic strata that could direct treatment strategies. Taken together, our work establishes the efficacy of the somatic genome as a biomarker to stratify ovarian cancers, simultaneously identifying patients that may benefit from emerging therapeutics and distinct subgroups within classic ovarian cancer histotypes.

  Study EGAS00001002390

• Circumventing intratumoral heterogeneity to identify potential therapeutic targets in hepatocellular carcinoma. Details please contact lifuqiang@genomics and zhaoxin@genomics.cn.

  Background and aims: Intratumoral heterogeneity (ITH) challenges identifying mutations with target therapy potential whereas circulating cell-free DNAs (cfDNAs) could reflect nearly the entire mutation spectrum in given tumors. We investigated how to minimize the limit of ITH for profiling hepatocellular carcinoma (HCC).Methods: Thirty-two multi-regional HCC samples from five patients were subjected to whole exome sequencing (WES) and targeted deep sequencing (TDS). ITH extent was measured by the average percentage of non-ubiquitous mutations (present in parts of tumor regions). Matched cfDNAs were also analyzed by WES and TDS. Profiling efficiencies of single tumor specimen and cfDNA were compared and the one better depicted mutational landscape was selected to screen therapeutic targets.Results: We found variable extents of ITH in HCCs and observed branched and parallel evolution patterns. ITH level decreased at higher sequencing depth of TDS than that measured by WES (28.1% vs 34.9%, P < 0.01) but it remained unchanged upon additional samples analyzed. TDS of single tumor specimen detected an average of 70% the total mutations in HCC. Although more mutations were detected in cfDNA under TDS than WES, an average of 47.2% total HCC mutations uncovered by cfDNA suggested tissue outperform cfDNA and the latter may serve as alternative in profiling HCC genome. Consequently, TDS of single tumor tissue in 66 patients and cfDNAs in four unresectable HCCs identified 38.6% (26/66 and 1/4) patients bearing therapeutic targets.Conclusions: TDS of single tumor specimen could largely circumvent ITH to uncover mutations indicative of target therapy in HCC.

  Study EGAS00001002207

• Smoking-dependent expression alterations in nasal epithelium reveal immune impairment linked to germline variation and lung cancer risk.

  Lung cancer is the leading cause of cancer-related death in the world. In contrast to many other cancers, a direct connection to lifestyle risk in the form of cigarette smoke has long been established. More than 50% of all smoking-related lung cancers occur in former smokers, often many years after smoking cessation. Despite extensive research, the molecular processes for persistent lung cancer risk are unclear. CT screening of current and former smokers has been shown to reduce lung cancer mortality by up to 26%. To examine whether clinical risk stratification can be improved upon by the addition of genetic data, and to explore the mechanisms of the persisting risk in former smokers, we have analyzed transcriptomic data from accessible airway tissues of 487 subjects. We developed a model to assess smoking associated gene expression changes and their reversibility after smoking is stopped, in both healthy subjects and clinic patients. We find persistent smoking associated immune alterations to be a hallmark of the clinic patients. Integrating previous GWAS data using a transcriptional network approach, we demonstrate that the same immune and interferon related pathways are strongly enriched for genes linked to known genetic risk factors, demonstrating a causal relationship between immune alteration and lung cancer risk. Finally, we used accessible airway transcriptomic data to derive a non-invasive lung cancer risk classifier. Our results provide initial evidence for germline-mediated personalised smoke injury response and risk in the general population, with potential implications for managing long-term lung cancer incidence and mortality.

  Dac EGAC50000000169

• scRNA-seq of total bone marrow and T cells from multiple myeloma long-term survivors

  scRNA This dataset contains 50 scRNA-seq samples from bone marrow aspirates of 11 multiple myeloma patients experiencing long-term survival and 3 healthy donors. For each donor, total bone marrow and CD3+ T cells were sequenced. For multiple myeloma patients, paired samples were collected at initial diagnosis and between 7-17 years after first-line therapy. Bone marrow mononuclear cells were isolated by Ficoll density gradient centrifugation. For sorting of total bone marrow cells singlet, live cells were gated and sorted, for sorting of T cells CD45+, CD3+ cells were gated and sorted on either FACSAria Fusion or FACSAria II. Single-cell RNA sequencing were generated using 10x Genomics single-cell RNAseq technology (Chromium Single Cell 3’ Solution v2) according to the manufacturer’s protocol and sequenced on an Illumina HiSeq4000 (paired end, 26 and 74 bp). Bulk RNA Singlet, live CD3+CD4- CXCR3+CD8+ and CD3+CD4- CXCR3-CD8+ cells were sorted from 7 bone marrow and 3 peripheral blood samples of 7 multiple myeloma patients using a FACSAria Fusion machine. Bulk-RNA sequencing libraries were generated using the SMART Seq Stranded Total RNA-Seq kit (Takara) and sequenced using the Illumina NovaSeq 6000 platform (2 x 100 bp).

  Dataset EGAD00001010025

• Single cell sequencing of a post-PD-1 inhibitor metastatic melanoma mass

  Three technical replicates of FACS-sorted T cells (CD45+CD3+) and one replicate of FACS-sorted tumor cells (MCSP+) were loaded to a targeted 10,000 cells per lane on the 10X Genomics Chromium Controler with the single cell 5’ Immune Repertoire and Gene Expression profiling kit. In total, we loaded ~30,000 individual tumor infiltrating lymphocytes (TILs) and ~10,000 melanoma cells on the 10X platform (10X Genomics, CA, USA). Reverse transcription, TCR enrichment, and library preparations were performed according to the 10X Genomics 5’ V(D)J protocol revision C. Transcriptome libraries were pooled and sequenced on the Illumina NovaSeq 6000 S2 flow cell with 26 R1, 8 i7, and 91 R2 cycles respectively. The TCR libraries were pooled and sequenced on the Illumina MiSeq V2 150 cycles paired-end. Single cell transcriptomic and TCR data was processed with the 10X Genomics Cell Ranger Pipeline version 2.2.0 with the software-provided GRCh38 reference transcriptomes. After quality control, there was RNAseq profile data available from 6267 immune and 4303 melanoma cells. Downstream processing and visualization was encompassed through Seurat and tSNE plots.

  Dataset EGAD00001006013

• Paired-WGS Sequencing of Primary lymphomas of the central nervous system (PCNSL)

  26 Tumor/Control pairs of WGS data of PCNSL tumors, sequenced on either Illumina HiSeq2000/2500 instruments or HiSeq X Ten. The controls are blood or buffy coat samples in most cases.

  Dataset EGAD00001007806

• RNA-seq data for study 'Smoking-dependent expression alterations in nasal epithelium reveal immune impairment linked to germline variation and lung cancer risk.'

  RNA-seq data from nasal and bronchial tissues in 649 subjects, many with lung cancer. Lung cancer is the leading cause of cancer-related death in the world. In contrast to many other cancers, a direct connection to lifestyle risk in the form of cigarette smoke has long been established. More than 50% of all smoking-related lung cancers occur in former smokers, often many years after smoking cessation. Despite extensive research, the molecular processes for persistent lung cancer risk are unclear. CT screening of current and former smokers has been shown to reduce lung cancer mortality by up to 26%. To examine whether clinical risk stratification can be improved upon by the addition of genetic data, and to explore the mechanisms of the persisting risk in former smokers, we have analyzed transcriptomic data from accessible airway tissues of 487 subjects. We developed a model to assess smoking associated gene expression changes and their reversibility after smoking is stopped, in both healthy subjects and clinic patients. We find persistent smoking associated immune alterations to be a hallmark of the clinic patients. Integrating previous GWAS data using a transcriptional network approach, we demonstrate that the same immune and interferon related pathways are strongly enriched for genes linked to known genetic risk factors, demonstrating a causal relationship between immune alteration and lung cancer risk. Finally, we used accessible airway transcriptomic data to derive a non-invasive lung cancer risk classifier. Our results provide initial evidence for germline-mediated personalised smoke injury response and risk in the general population, with potential implications for managing long-term lung cancer incidence and mortality.

  Dataset EGAD50000000333

• GCAT| ICD Disease Diagnoses

  Disease diagnoses of GCAT Cohort participants obtained from electronic health records (EHR), mainly including the time period from 2012 to 2017. Disease diagnoses are codified in ICD-9, and the position of diagnosis refers to primary/secondary diagnoses (up to 14 secondary diagnoses per visit). The date and origin of the visit are also specified (AP: primary care, UGR: emergency, AH: hospital care, SMA: outpatient medical service, SMH: hospital medical service).

  Dataset EGAD00001007731

• PCGP Ph-like ALL

  Background: BCR-ABL1-like, or Ph-like acute lymphoblastic leukemia is characterized by a gene expression profile similar to BCR-ABL1 positive ALL, genetic alterations of lymphoid transcription factor genes, and poor outcome. Sequencing of small numbers of Ph-like ALL cases has identified genetic alterations activating kinase signaling suggesting Ph-like ALL may be amenable to treatment with tyrosine kinase inhibitors. However, the spectrum of genetic alterations in childhood and adult Ph-like ALL is incompletely understood. Methods: We performed genomic profiling of 1736 B-ALL cases and next-generation sequencing for 160 Ph-like cases. We examined the functional effects of chimeric fusion proteins in mouse cell lines. Results: The frequency of Ph-like ALL rose from 11% in children to 26% in young adults, and was associated with very poor outcome. Kinase-activating alterations were identified in 90% of Ph-like cases, most commonly fusions involving 10 kinase or cytokine receptor genes (ABL1, ABL2, CRLF2, CSF1R, EPOR, JAK2, NTRK3, PDGFRB, PTK2B and TYK2), and mutations involving FLT3, IL7R and SH2B3. Expression of ABL1, ABL2, CSF1R and JAK2 fusions resulted in cytokine-independent proliferation of cell lines and activation of pSTAT5. Cells expressing ABL1, ABL2, CSF1R and PDGFRB fusions were sensitive to dasatinib, and JAK2 fusions to ruxolitinib. Conclusions: Ph-like ALL is characterized by a diverse range of genomic alterations that converge on a limited number of kinase signaling pathways amenable to inhibition with currently available tyrosine kinase inhibitors. Trials identifying Ph-like ALL and testing the efficacy of tyrosine kinase inhibitor therapy are warranted

  Study EGAS00001000654

• CSER: North Carolina Clinical Genomic Evaluation by Next-Gen Exome Sequencing 2

  The North Carolina Clinical Genomic Evaluation by Next-gen Exome Sequencing, 2 (NCGENES 2) study is part of a larger consortium project investigating the clinical utility, or net benefit of an intervention on patient and family well-being as well as diagnostic efficacy, management planning, and medical outcomes. A clinical trial will be implemented to compare (1) first-line exome sequencing to usual care and (2) participant pre-visit preparation to no pre-visit preparation. The study will use a randomized controlled design, with 2x2 factorial design, coupled with patient-reported outcomes and comprehensive clinical data collection addressing key outcomes, to determine the net impact of diagnostic results and secondary findings.

  Study phs002110