116 research outputs found

    Defining the clinical genomic landscape for real-world precision oncology

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    Through the delivery of large international projects including ICGC and TCGA, knowledge of cancer genomics is reaching saturation point. Enabling this to improve patient outcomes now requires embedding comprehensive genomic profiling into routine oncology practice. Towards this goal, this study defined the biologically and clinically relevant genomic features of adult cancer through detailed curation and analysis of large genomic datasets, accumulated literature and biomarker-driven therapeutics in clinic and development. The characteristics and prevalence of these features were then interrogated in 2348 whole genome sequences, covering 21 solid tumour types, generated by the PCAWG project. This analysis highlights the predominant contribution of copy number alterations and identifies a critical role for disruptive structural variants in the inactivation of clinically important tumour suppressor genes, including PTEN and RB1, which are not currently captured by diagnostic assays. This study defines a set of essential genomic features for the characterisation of common adult cancers

    High-resolution array CGH clarifies events occurring on 8p in carcinogenesis.

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    BACKGROUND: Rearrangement of the short arm of chromosome 8 (8p) is very common in epithelial cancers such as breast cancer. Usually there is an unbalanced translocation breakpoint in 8p12 (29.7 Mb - 38.5 Mb) with loss of distal 8p, sometimes with proximal amplification of 8p11-12. Rearrangements in 8p11-12 have been investigated using high-resolution array CGH, but the first 30 Mb of 8p are less well characterised, although this region contains several proposed tumour suppressor genes. METHODS: We analysed the whole of 8p by array CGH at tiling-path BAC resolution in 32 breast and six pancreatic cancer cell lines. Regions of recurrent rearrangement distal to 8p12 were further characterised, using regional fosmid arrays. FISH, and quantitative RT-PCR on over 60 breast tumours validated the existence of similar events in primary material. RESULTS: We confirmed that 8p is usually lost up to at least 30 Mb, but a few lines showed focal loss or copy number steps within this region. Three regions showed rearrangements common to at least two cases: two regions of recurrent loss and one region of amplification. Loss within 8p23.3 (0 Mb - 2.2 Mb) was found in six cell lines. Of the genes always affected, ARHGEF10 showed a point mutation of the remaining normal copies in the DU4475 cell line. Deletions within 12.7 Mb - 19.1 Mb in 8p22, in two cases, affected TUSC3. A novel amplicon was found within 8p21.3 (19.1 Mb - 23.4 Mb) in two lines and one of 98 tumours. CONCLUSION: The pattern of rearrangements seen on 8p may be a consequence of the high density of potential targets on this chromosome arm, and ARHGEF10 may be a new candidate tumour suppressor gene

    The Specificity of the FOXL2 c.402C>G Somatic Mutation: A Survey of Solid Tumors

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    A somatic mutation in the FOXL2 gene is reported to be present in almost all (97%; 86/89) morphologically defined, adult-type, granulosa-cell tumors (A-GCTs). This FOXL2 c.402C>G mutation changes a highly conserved cysteine residue to a tryptophan (p.C134W). It was also found in a minority of other ovarian malignant stromal tumors, but not in benign ovarian stromal tumors or unrelated ovarian tumors or breast cancers.Herein we studied other cancers and cell lines for the presence of this mutation. We screened DNA from 752 tumors of epithelial and mesenchymal origin and 28 ovarian cancer cell lines and 52 other cancer cell lines of varied origin. We found the FOXL2 c.402C>G mutation in an unreported A-GCT case and the A-GCT-derived cell line KGN. All other tumors and cell lines analyzed were mutation negative.In addition to proving that the KGN cell line is a useful model to study A-GCTs, these data show that the c.402C>G mutation in FOXL2 is not commonly found in a wide variety of other cancers and therefore it is likely pathognomonic for A-GCTs and closely related tumors

    Recurrent mutation of IGF signalling genes and distinct patterns of genomic rearrangement in osteosarcoma

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    Osteosarcoma is a primary malignancy of bone that affects children and adults. Here, we present the largest sequencing study of osteosarcoma to date, comprising 112 childhood and adult tumours encompassing all major histological subtypes. A key finding of our study is the identification of mutations in insulin-like growth factor (IGF) signalling genes in 8/112 (7%) of cases. We validate this observation using fluorescence in situ hybridization (FISH) in an additional 87 osteosarcomas, with IGF1 receptor (IGF1R) amplification observed in 14% of tumours. These findings may inform patient selection in future trials of IGF1R inhibitors in osteosarcoma. Analysing patterns of mutation, we identify distinct rearrangement profiles including a process characterized by chromothripsis and amplification. This process operates recurrently at discrete genomic regions and generates driver mutations. It may represent an age-independent mutational mechanism that contributes to the development of osteosarcoma in children and adults alike

    Single-cell paired-end genome sequencing reveals structural variation per cell cycle

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    The nature and pace of genome mutation is largely unknown. Because standard methods sequence DNA from populations of cells, the genetic composition of individual cells is lost, de novo mutations in cells are concealed within the bulk signal and per cell cycle mutation rates and mechanisms remain elusive. Although single-cell genome analyses could resolve these problems, such analyses are error-prone because of whole-genome amplification (WGA) artefacts and are limited in the types of DNA mutation that can be discerned. We developed methods for paired-end sequence analysis of single-cell WGA products that enable (i) detecting multiple classes of DNA mutation, (ii) distinguishing DNA copy number changes from allelic WGA-amplification artefacts by the discovery of matching aberrantly mapping read pairs among the surfeit of paired-end WGA and mapping artefacts and (iii) delineating the break points and architecture of structural variants. By applying the methods, we capture DNA copy number changes acquired over one cell cycle in breast cancer cells and in blastomeres derived from a human zygote after in vitro fertilization. Furthermore, we were able to discover and fine-map a heritable inter-chromosomal rearrangement t(1;16)(p36;p12) by sequencing a single blastomere. The methods will expedite applications in basic genome research and provide a stepping stone to novel approaches for clinical genetic diagnosis

    Molecular subclusters of follicular lymphoma: a report from the UK's Haematological Malignancy Research Network

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    Follicular lymphoma (FL) is morphologically and clinically diverse, with mutations in epigenetic regulators alongside t(14;18) identified as disease-initiating events. Identification of additional mutational entities confirms this cancer’s heterogeneity, but whether mutational data can be resolved into mechanistically distinct subsets remains an open question. Targeted sequencing was applied to an unselected population-based FL cohort (n = 548) with full clinical follow-up (n = 538), which included 96 diffuse large B-cell lymphoma (DLBCL) transformations. We investigated whether molecular subclusters of FL can be identified and whether mutational data provide predictive information relating to transformation. DNA extracted from FL samples was sequenced with a 293-gene panel representing genes frequently mutated in DLBCL and FL. Three clusters were resolved using mutational data alone, independent of translocation status: FL_aSHM, with high burden of aberrant somatic hypermutation (aSHM) targets; FL_STAT6, with high STAT6 & CREBBP mutation and low aSHM; and FL_Com, with the absence of features of other subtypes and enriched KMT2D mutation. Analysis of mutation signatures demonstrated differential enrichment of predicted mutation signatures between subgroups and a dominant preference in the FL_aSHM subgroup for G(C>T)T and G(C>T)C transitions consistent with previously defined aSHM-like patterns. Of transformed cases with paired samples, 17 of 26 had evidence of branching evolution. Poorer overall survival (OS) in the aSHM group (P = .04) was associated with older age; however, overall tumor genetics provided limited information to predict individual patient risk. Our approach identifies 3 molecular subclusters of FL linked to differences in underlying mechanistic pathways. These clusters, which may be further resolved by the inclusion of translocation status and wider mutation profiles, have implications for understanding pathogenesis as well as improving treatment strategies in the future

    Direct Transcriptional Consequences of Somatic Mutation in Breast Cancer.

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    Disordered transcriptomes of cancer encompass direct effects of somatic mutation on transcription, coordinated secondary pathway alterations, and increased transcriptional noise. To catalog the rules governing how somatic mutation exerts direct transcriptional effects, we developed an exhaustive pipeline for analyzing RNA sequencing data, which we integrated with whole genomes from 23 breast cancers. Using X-inactivation analyses, we found that cancer cells are more transcriptionally active than intermixed stromal cells. This is especially true in estrogen receptor (ER)-negative tumors. Overall, 59% of substitutions were expressed. Nonsense mutations showed lower expression levels than expected, with patterns characteristic of nonsense-mediated decay. 14% of 4,234 rearrangements caused transcriptional abnormalities, including exon skips, exon reusage, fusions, and premature polyadenylation. We found productive, stable transcription from sense-to-antisense gene fusions and gene-to-intergenic rearrangements, suggesting that these mutation classes drive more transcriptional disruption than previously suspected. Systematic integration of transcriptome with genome data reveals the rules by which transcriptional machinery interprets somatic mutation
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