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  • American Association for Cancer Research (AACR)  (5)
  • Demeulemeester, Jonas  (5)
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  • American Association for Cancer Research (AACR)  (5)
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  • 1
    Online Resource
    Online Resource
    American Association for Cancer Research (AACR) ; 2022
    In:  Cancer Research Vol. 82, No. 12_Supplement ( 2022-06-15), p. 2286-2286
    In: Cancer Research, American Association for Cancer Research (AACR), Vol. 82, No. 12_Supplement ( 2022-06-15), p. 2286-2286
    Abstract: Genomic rearrangements are key mutational processes in a number of bone and soft tissue tumors (sarcomas). These events are used for both disease classification and as prognostic and predictive biomarkers. However, the rearrangement architecture and mutational processes giving rise to many of these events remain poorly characterized. Recent data indicate that sarcomas show particularly high frequencies of complex structural rearrangements, including patterns which do not fit those of known mutational mechanisms. As the largest whole genome sequencing (WGS) dataset of sarcomas to date, the Genomics England (GE) 100,000 Genomes Project represents a unique cohort in which to examine these events. Structural variants (SVs) were identified using five SV callers (Manta, Delly, LUMPY, SvABA and GRIDSS) in WGS data from 1330 GE samples. SVs were filtered to retain only those passing the quality filter, and to remove variants present in either matched germline samples or & gt;1% of a panel of normal variants. Caller performance was evaluated by comparison of distances between SV and copy number call breakpoints generated by Battenberg. SVs identified by at least two callers were taken forward as high-quality calls. Chromothriptic events, extrachromosomal DNA (ecDNA) and breakage-fusion-bridges were identified using established algorithms. In keeping with previous data, the prevalence of structural variants varies by tumor type, with particularly high numbers of SVs observed in liposarcoma and osteosarcoma. Many tumor types included notable outlier samples; these were more likely to show evidence of chromothripsis, as identified by a dedicated chromothripsis caller. Liposarcomas show the highest frequency of chromothripsis, as described previously. In addition, we have examined some tumor types at higher granularity than previously available, demonstrating directly that the prevalence of chromothripsis varies by histological subtype. For example, chromothriptic events are identified in 100% of well-differentiated liposarcomas, but less than 10% of myxoid liposarcomas. Similarly, the presence of ecDNA varies by tumor type, with the novel observation of particularly high rates in angiosarcoma. Despite recent advances in histological classification, the survival for patients with sarcoma has remained largely static for over 40 years. Determination of the mutational processes generating these rearrangements will shed light on the pathogenesis of these tumors. Citation Format: Sara Waise, Tom Lesluyes, Jonas Demeulemeester, Maxime Tarabichi, Sarcoma Genomics England Clinical Interpretation Partnership, Nischalan Pillay, Adrienne M. Flanagan, Peter Van Loo. Profiling the complex rearrangement landscape of sarcoma [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2022; 2022 Apr 8-13. Philadelphia (PA): AACR; Cancer Res 2022;82(12_Suppl):Abstract nr 2286.
    Type of Medium: Online Resource
    ISSN: 1538-7445
    Language: English
    Publisher: American Association for Cancer Research (AACR)
    Publication Date: 2022
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    Location Call Number Limitation Availability
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  • 2
    In: Cancer Research, American Association for Cancer Research (AACR), Vol. 78, No. 13_Supplement ( 2018-07-01), p. 3000-3000
    Abstract: We have characterised intra-tumour heterogeneity (ITH) across 2,778 whole genome sequences of tumours in the International Cancer Genome Consortium Pan-Cancer Analysis of Whole Genomes project, representing 36 distinct cancer types. We applied 6 copy number (CNA) callers and 11 subclonal reconstruction algorithms and developed approaches to integrate the results in robust, high-confidence CNA calls and subclonal architectures. The analysis reveals widespread ITH. We find at least one subclone in nearly all (96.7%) tumours with sufficient sequencing depth. Analysis using dN/dS ratios yields clear signs of positive selection in clonal and subclonal mutations and we find subclonal driver mutations in known driver genes. However, only 24% of subclones contain a driver mutation in a known driver gene, suggesting that a multitude of undiscovered late drivers exist and that tumours continue to undergo selection after tumourigenesis, at least until diagnosis. Consistent with other studies, we find that in 9% of tumours all clinically actionable mutations are subclonal, while 20% of tumours contain at least one subclonal actionable driver. These findings emphasise the relevance of ITH in treatment decision making. Distinct patterns of ITH emerge; for example, prostate, uterus and esophageal adenocarcinomas show high proportions of both subclonal single nucleotide variants (SNVs) and CNAs. Kidney chromophobe and pancreatic endocrine tumours also contain high proportions of subclonal SNVs, but few subclonal CNAs. On the other hand, hepatocellular carcinomas and head-and-neck and lung SCCs contain low proportions of subclonal SNVs and high proportions of subclonal CNAs. Mutational signature analysis reveals changes in signature activity. Exposures to UV light in melanomas and acid reflux in stomach and oesophageal cancers contribute more clonal mutations. While APOBEC and DNA damage repair response related signatures show increased activity in subclones. These findings highlight distinct evolutionary narratives between and within histologically distinct tumour types. Citation Format: Stefan Dentro, Ignaty Leshchiner, Kerstin Haase, Jeff Wintersinger, Amit Deshwar, Maxime Tarabichi, Yulia Rubanova, Kaixian Yu, Ignacio Vázquez García, Geoff Macintyre, Kortine Kleinheinz, Dimitri Livitz, Salem Malikic, Nilgun Donmez, Subhajit Sengupta, Yuan Ji, Jonas Demeulemeester, Pavana Anur, Clemency Jolly, Marek Cmero, Daniel Rosebrock, Steve Schumacher, Yu Fan, Matthew Fittall, Xiaotong Yao, Juhee Lee, Matthias Schlesner, Hongtu Zhu, David Adams, Gad Getz, Paul Boutros, Marcin Imielinski, Rameen Beroukhim, Cenk Sahinalp, Martin Peifer, Inigo Martincorena, Florian Markowetz, Ville Mustonen, Ke Yuan, Moritz Gerstung, Wenyi Wang, Paul Spellman, Quaid Morris, David Wedge, Peter Van Loo. Pervasive intra-tumour heterogeneity and subclonal selection across cancer types [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2018; 2018 Apr 14-18; Chicago, IL. Philadelphia (PA): AACR; Cancer Res 2018;78(13 Suppl):Abstract nr 3000.
    Type of Medium: Online Resource
    ISSN: 0008-5472 , 1538-7445
    RVK:
    RVK:
    Language: English
    Publisher: American Association for Cancer Research (AACR)
    Publication Date: 2018
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  • 3
    Online Resource
    Online Resource
    American Association for Cancer Research (AACR) ; 2020
    In:  Cancer Research Vol. 80, No. 16_Supplement ( 2020-08-15), p. 1320-1320
    In: Cancer Research, American Association for Cancer Research (AACR), Vol. 80, No. 16_Supplement ( 2020-08-15), p. 1320-1320
    Abstract: Somatic mutation calling from bulk DNA sequencing is a complex problem susceptible to elevated false positive rates. High mapping quality is considered an important feature of reliable variant calls. At the resolution of short reads, ~10% of the genome displays high sequence similarity with at least one other genomic region and is assigned low mapping quality by alignment algorithms. These low-mapping-quality regions represent recurrent blind spots for mutation callers, which discard many of the variants they harbor, overlooking true biological variation. Here, we developed a pipeline to call substitutions in the low-mapping-quality genome. We used a published thesaurus approach to annotate the variant positions with their high-similarity links. We trained a classifier to emulate high-quality consensus calls made in unique regions using 20 features unrelated to mapping quality, reaching ~95% accuracy in those regions. In an independent sample more than 90% of the thesaurus calls were validated through linked-read sequencing. We then applied the classifier to all candidate substitutions of 2,658 cancer whole genomes from the PCAWG/ICGC consortium including variants falling in low-mapability regions. We retrieve hidden thesaurus variants genome-wide in ~6% of the genome, including genic, coding, and promoter regions. Thesaurus calls are directly proportional in numbers to somatic calls falling in the low-mapping-quality genome and share a similar trinucleotide context spectrum. Rescuing these mutations reveal hidden signal in known cancer genes, including PIK3CA, and excess of mutations genome-wide in promoter, untranslated, and coding regions of many other genes. We also find potential excess of non-synonymous mutations, including in genes from the TRIM and POTE families, having been previously implicated in multiple cancer types. Altogether, we developed a pipeline to call somatic substitutions in the low-mapping-quality genome and uncovered hidden somatic changes along the genomes of human cancers. In the future, this pipeline could be extended to indels and structural variants, and applied to the study of de novo germline variants. Citation Format: Maxime Tarabichi, Jonas Demeulemeester, Annelien Verfaillie, Peter Van Loo, Tomasz Konopka. The landscape of somatic substitutions in the repetitive genome across cancer types [abstract]. In: Proceedings of the Annual Meeting of the American Association for Cancer Research 2020; 2020 Apr 27-28 and Jun 22-24. Philadelphia (PA): AACR; Cancer Res 2020;80(16 Suppl):Abstract nr 1320.
    Type of Medium: Online Resource
    ISSN: 0008-5472 , 1538-7445
    RVK:
    RVK:
    Language: English
    Publisher: American Association for Cancer Research (AACR)
    Publication Date: 2020
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  • 4
    In: Cancer Research, American Association for Cancer Research (AACR), Vol. 82, No. 12_Supplement ( 2022-06-15), p. 1606-1606
    Abstract: Background Malignant peripheral nerve sheath tumors (MPNSTs) are rare, highly aggressive soft tissue sarcomas derived from Schwann cells with poor prognosis. Previous studies, although limited in scale and depth, have shown that these tumors are typically genomically complex, with a moderate burden of single nucleotide variants but extensive copy number aberrations (CNAs). Methods We applied a multi-omics approach to scrutinize the evolution and heterogeneity of a primary MPNST and five recurrence regions from one patient with an NF1 phenotype. Techniques utilized included bulk whole genome sequencing (WGS), single-cell DNA sequencing (scDNA-seq), single-cell RNA sequencing (scRNA-seq), simultaneous genome and transcriptome sequencing (G & T-seq), spatial transcriptomics, and laser capture microdissection (LCM)-based spatial genomics. Results We find significant heterogeneity in copy number profiles, suggestive of ongoing chromosomal instability and evolution. We perform in-depth tumor phylogenetic reconstruction from bulk WGS data. scDNA-seq revealed further CNA heterogeneity across and within regions, allowing us to refine the tree down to single-cell resolution. De novo somatic variant calling in scDNA-seq data confirms the reconstructed tree and identifies additional subclonal mutations. We also profile different populations of tumor and non-tumor cells and confirmed this with a genotyping approach. CNA profiles inferred from scRNA-seq reflect the within-region heterogeneity seen in scDNA-seq. We find tumor cells with similar CNA profiles typically cluster together by their gene expression profiles as well, implying that the majority of gene expression heterogeneity in this tumor is underpinned by copy number changes. By using CNA profiles as a native barcoding system, we link genetic subclones to clusters of cells and their transcriptomes to characterize the effects of gene dosage. Finally, we explore the spatial relationships between tumor subclones using LCM. We detect heterogeneity within tissue sections evidencing local clonal expansions and CNA events that follow spatial distributions. Using spatial transcriptomics, we show tumor cells are homogeneously admixed with tumor microenvironment populations. Conclusions Our work demonstrates the power of combining spatial multi-omics at the single-cell and bulk levels to study cancer evolution. This enables a spatio-temporal representation of a tumor’s development with annotation of genetic and transcriptomic events. Citation Format: Haixi Yan, Jonas Demeulemeester, Annelien Verfaillie, Cristina Cotobal Martin, Tom Kaufmann, Roland Schwarz, Thierry Voet, Simone Zaccaria, Adrienne Flanagan, Maxime Tarabichi, Peter Van Loo. Chromosomal instability drives spatial and temporal phenotypic diversity in Schwann cancer cells [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2022; 2022 Apr 8-13. Philadelphia (PA): AACR; Cancer Res 2022;82(12_Suppl):Abstract nr 1606.
    Type of Medium: Online Resource
    ISSN: 1538-7445
    Language: English
    Publisher: American Association for Cancer Research (AACR)
    Publication Date: 2022
    detail.hit.zdb_id: 2036785-5
    detail.hit.zdb_id: 1432-1
    detail.hit.zdb_id: 410466-3
    Location Call Number Limitation Availability
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  • 5
    In: Cancer Research, American Association for Cancer Research (AACR), Vol. 78, No. 13_Supplement ( 2018-07-01), p. 218-218
    Abstract: Cancer develops through a continuous process of somatic evolution. Whole genome sequencing provides a snapshot of the tumor genome at the point of sampling, however, the data can contain information that permits the reconstruction of a tumor's evolutionary past. Here, we apply such life history analyses on an unprecedented scale, to a set of 2,658 tumors spanning 39 cancer types. We estimated the timing of large chromosomal gains during tumor evolution, by comparing the rates of doubled to non-doubled point mutations within gained regions. Although we find that such events typically occur in the second half of clonal evolution, we also observe distinctive and early chromosomal gains in some cancer types, such as gains of chromosomes 7, 19 and 20 in glioblastoma, and isochromosome 17q in medulloblastoma. By integrating these results with the qualitative timing of individual driver mutations, we obtained an overall ranking, from early to late, of frequent somatic events per cancer type, which both identified novel patterns of tumor evolution, and incorporated additional detail into known models, such as the progression of APC-KRAS-TP53 in colorectal cancer proposed by Vogelstein and Fearon. To estimate how mutational processes acting on the tumor genome change over time, we classified mutations in each sample according to three broad time periods (early clonal, late clonal, and subclonal), and quantified the activity of mutational signatures in each period. Most mutational processes appear to remain remarkably constant, however, certain signatures show clear and consistent changes during clonal evolution. Particularly, mutational signatures associated with exposure to carcinogens, such as smoking and UV light, tend to decrease over time. In contrast, signatures associated with defective endogenous processes, such as APOBEC mutagenesis and defective double strand break repair, show an increase between early and late phases of tumor evolution. Making use of clock-like mutational signatures, we converted mutational time estimates for large events, such as whole genome duplication (WGD), and the emergence of the most recent common ancestor (MRCA), into real time estimates, which allowed us to combine our analyses into overall timelines of cancer evolution, per tumor type. For example, the typical timeline of ovarian adenocarcinoma development shows that early tumor evolution is characterized by mutations in TP53, and widespread genome instability, with WGD events taking place on average 8 years prior to diagnosis. In later stages of evolution, signatures of defective repair processes increase, and the MRCA emerges on average 1 year before diagnosis. Taken together, these data reveal the common and divergent evolutionary trajectories available to a cancer, which might be crucial in understanding specific tumor biology, and in providing new opportunities for early detection and cancer prevention. Citation Format: Clemency Jolly, Moritz Gerstung, Ignaty Leshchiner, Stefan C. Dentro, Santiago Gonzalez, Thomas J. Mitchell, Yulia Rubanova, Pavana Anur, Daniel Rosebrock, Kaixian Yu, Maxime Tarabichi, Amit Deshwar, Jeff Wintersinger, Kortine Kleinheinz, Ignacio Vásquez-García, Kerstin Haase, Subhajit Sengupta, Geoff Macintyre, Salem Malikic, Nilgun Donmez, Dimitri G. Livitz, Mark Cmero, Jonas Demeulemeester, Steve Schumacher, Yu Fan, Xiaotong Yao, Juhee Lee, Matthias Schlesner, Paul C. Boutros, David D. Bowtell, Hongtu Zhu, Gad Getz, Marcin Imielinski, Rameen Beroukhim, S Cenk Sahinalp, Yuan Ji, Martin Peifer, Florian Markowetz, Ville Mustonen, Ke Juan, Wenyi Wang, Quaid D. Morris, Paul T. Spellman, David C. Wedge, Peter Van Loo, PCAWG Evolution and Heterogeneity Working Group. The evolutionary history of 2,658 cancers [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2018; 2018 Apr 14-18; Chicago, IL. Philadelphia (PA): AACR; Cancer Res 2018;78(13 Suppl):Abstract nr 218.
    Type of Medium: Online Resource
    ISSN: 0008-5472 , 1538-7445
    RVK:
    RVK:
    Language: English
    Publisher: American Association for Cancer Research (AACR)
    Publication Date: 2018
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    detail.hit.zdb_id: 410466-3
    Location Call Number Limitation Availability
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