1905 results

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• XClone for analyzing somatic copy number alterations

  Somatic copy number alterations (CNAs) are major mutations that contribute to the development and progression of various cancers. Despite a few computational methods proposed to detect CNAs from single-cell transcriptomic data, the technical sparsity of such data makes it challenging to identify allele-specific CNAs, particularly in complex clonal structures. In this study, we present a statistical method, XClone, that strengthens the signals of read depth and allelic imbalance by effective smoothing on cell neighborhood and gene coordinate graphs to detect haplotype-aware CNAs from scRNA-seq data. By applying XClone to multiple datasets with challenging compositions, we demonstrated its ability to robustly detect different types of allele-specific CNAs and potentially indicate whole genome duplication, therefore enabling the discovery of corresponding subclones and the dissection of their phenotypic impacts.

  Study EGAS00001007854

• Whole genome and whole exome sequencing of epilaptic patients

  In this project, we aim to identify genetic changes that predispose to epilepsy and those that predict the response to various anti-epileptic drugs. We sequenced whole genomes and whole exomes of epileptic individuals with different range of response to anti-epileptic drugs, and their relatives.

  Study EGAS00001002825

• Luminal breast epithelial cells from wildtype and BRCA mutation carriers harbor copy number alterations commonly associated with breast cancer

  Cancer-associated mutations have been documented in normal tissues, but the prevalence and nature of somatic copy number alterations and their role in tumor initiation and evolution is not well understood. Here, using single cell DNA sequencing, we describe the landscape of CNA variants in >48,000 breast epithelial cells from women with normal or high risk of developing breast cancer. Individual cells with one or two of a specific subset of CNAs (e.g. 1q gain and 16q, 22q, 7q, and 10q loss) are detectable in almost all breast tissues and, in those from BRCA1 or BRCA2 mutations carriers, occurs prior to loss of heterozygosity (LOH) of the wildtype alleles. These CNAs, which are among the most common associated with ductal carcinoma in situ (DCIS) and malignant breast tumors, are enriched almost exclusively in luminal cells and are generally absent from basal myoepithelial cells. Allele-specific analysis of the enriched CNAs reveals that each allele was independently altered, demonstrating convergent evolution of these CNAs in an individual breast. Tissues from BRCA1 or BRCA2 mutation carriers contained a small percentage of cells with extreme aneuploidy, featuring loss of TP53, LOH of BRCA1 or BRCA2, and multiple breast cancer-associated CNAs in addition to one or more of the common CNAs in 1q, 10q or 16q. Notably, cells with intermediate levels of CNAs were not detected, arguing against a stepwise gradual accumulation of CNAs. Overall, our findings demonstrate that chromosomal alterations in normal breast epithelium including from high risk women, link early stage CNAs to clonally expanded tumor genomes .

  Study EGAS00001007716

• Mutational dynamics of triple negative breast cancer over neoadjuvant chemotherapy treatment reveal frequent whole genome duplication events

  Background Triple-negative breast cancer (TNBC) is associated with poor survival rate and high genomic instability, generating complex tumour genomes. However, the processes generating this complexity are poorly studied over time. Here, we study the temporal dynamics of TNBC somatic mutations, revealing major transitions in tumour genome evolution, from diagnostic biopsies, through treatment, to cancer remission or recurrence. Methods Deep whole exome sequencing and CUTseq, a reduced representation whole genome sequencing approach, were performed in parallel, to comprehensively identify short nucleotide variants (SNVs), copy number alterations (CNAs) and aneuploidies genome-wide. We profiled (N=74) tumour samples from 22 patients across the course of disease, including spatially diverse samples from many tumours, allowing us to observe the gain and loss of candidate driver variants over time. Results As expected, tumour infiltrating lymphocyte (TIL) levels and residual cancer burden (RCB) score were negatively correlated, with good responses to neoadjuvant chemotherapy (NACT) seen in pre-treatment samples with high infiltration. In general, SNV mutational burden remained stable across disease progression and RCB classes. Recurrent SNVs across the cohort implicated several known TNBC driver genes in disease progression and response to treatment, with TP53, MICA, CYP2D6, BRCA1 and BRCA2 frequently altered. However, the presence of candidate driver SNVs in these genes often varied throughout a patient’s treatment, including the loss of those seen in a given driver gene in pre-treatment samples, but gain of novel variants in the same gene at later time points. Dramatic structural dynamics were seen in all tumours, including abundant CNA including chromosome arm aneuploidies seen in pre-treatment samples, followed by frequent loss of these alterations post-treatment, and their re-emergence at recurrence. Whole genome duplication (WGD) events appear to drive these dynamics, with a higher frequency of pre-treatment WGD seen in patients with the best response to NACT. Conclusions Comprehensive longitudinal profiling demonstrates the complex interplay of SNVs and copy number alterations during TNBC progression, leading to diverse evolutionary trajectories and patient outcomes. Complex mutational patterns emerge as important features during progression, with WGD events emerging as potential candidate biomarkers of response at both tumour establishment and recurrence.

  Study EGAS00001008261

• Mutation of FOXL2 in granulosa cell tumors of the ovary

  We generated paired-end RNA-Seq data using the Illumina Genome Analyzer II platform for four adult granulosa cell tumours (GCTs) of the ovary (1 primary, 3 recurrent). We screened this data for the presence of GCT specific sequence variants and detected a non-synonymous mutation in the FOXL2 gene that was found to be recurrent in 97% of 89 additional GCTs. To measure genomic stability of the four index cases, we generated Affmetrix SNP 6.0 data and analysed these data for copy number changes. Raw sequence reads as well as Affymetrix CEL files are available to applicants.

  Study EGAS00000000040

• Genetic_background_for_cardio_vascular_disorders_in_the_general_Finnish_population

  Low coverage (4-6x) sequencing on samples from population cohorts (Finrisk, Health2000) will be done at Wellcome Trust Sanger Institute (WTSI) using Illumina HiSeq sequencing technology. We will produce 100bp paired end reads. Variants will be called using the 1000 Genomes Project pipeline. The samples have been selected from a national representative set of approximately 30,300 samples and comprises 500 individuals of each gender in the extreme tail of high density lipoprotein (HDL) concentrations. Included individuals were between 25 and 65 years of age. Individuals with a diagnosis of diabetes or BMI>30 were excluded from the study.

  Study EGAS00001000229

• Measuring the level of relatedness between NGS datasets

  Sequencing technologies are providing increasingly detailed insight in genetic makeup are paving their way into molecular diagnostics. The field will benefit from rigorous and bias-free measures for the quality of sequence data and for the proper representation of the complexity of the original samples. While current methodologies rely on the availability of a well-characterized reference genome, we propose kMer profiling for alignment-free assessment of the quality, comparability, and complexity of sequencing datasets. We show that kMer detects technical artefacts such as high duplication rates, library chimaeras, and differences in library preparation protocols in whole-genome, whole-exome, and RNA sequencing data. Additionally, it successfully captures the complexity and diversity of microbiomes. Thus, kMer allows for a robust evaluation of the quality and complexity of sequencing data without relying on any prior information and opens the way to a more reliable biological reasoning.

  Study EGAS00001000600

• CD49f single-cell methylomes

  Single-cell DNA methylation has emerged as a powerful tool to study molecular heterogeneity within cellular populations. We report the development of a bisulfite based whole genome protocol suitable for use on single index sorted primary mammalian cells. Application of this protocol to human hematopoietic stem cells provided quantitative DNA methylation measurements of up to 5.7 million CpGs in a single cell. Analysis of cis CpG methylation states in single cells revealed a loss of concordance beyond 2kb, which supported the development of a new analytical framework (PDclust) for single-cell DNA methylation datasets that considers heterogeneity of methylation states at single CpG resolution. PDclust identified epigenetically distinct subpopulations within highly purified and functionally defined human stem cell populations. In silico merging of the methylation states from the single cells allowed us to ascribe function to these epigenetically distinct subpopulations on the basis of their epigenetic states.

  Study EGAS00001002789

• multi-OMICs study of a pair of infant monozygotic twins with concordant B-cell ALL

  B-cell acute lymphoblastic leukemia (B-cell ALL) is the most common cancer in childhood. Studying identical twins with B-cell ALL provides a unique and tractable model for deciphering the developmental timing of pre- and post-natal mutations contributing to clonal evolution. To date, this has mainly focused on major cytogenetic subgroups of childhood B-cell ALL, including MLL fusions, ETV6-RUNX1, hyperdiploidy, and BCR-ABL1. However, formal demonstration of the prenatal origin and “backtracking” the natural history of the leukemia remains understudied in “B-other”/Normal Karyotype (NK) B-cell ALL. To characterize the genetic and the epigenetic landscape of this particular leukemia subtype, we performed whole genome DNA-, B-cell receptor (BCR)-, and DNA bisulfite-sequencing on a pair of 8-month-old monozygotic twins diagnosed with concordant “B-other”/NK B-cell ALL.

  Study EGAS00001003651

• The genomic and radiomic complexity of multifocal prostate cancer

  Multiparametric magnetic resonance imaging (mpMRI) and molecular prognostic tests are emerging to guide screening and prostate cancer (PCa) diagnosis, however their efficacy and cross validation requires further assessment in the context of intraprostatic heterogeneity and patient prognosis. To evaluate the molecular features that make prostate tumors visible to mpMRI, we established an mpMRI-blind multicore collection and performed low pass whole genome, exome, transcriptome and methylation profiling of 14 lesions and 23 representative cores from 6 PCa patients. Our results show that diagnosis based on mpMRI does not capture the genomic complexity of tumors, and reveal that commercial prognostic signature results based on single-biopsy assessments are insufficient to define risk of progression. Altogether, our study supports the use of a multi-biopsy assessment in both mpMRI visible and non-visible areas in order to provide a truly personalised diagnosis

  Study EGAS00001002767