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  • American Association for Cancer Research (AACR)  (2)
  • Baer, Constance  (2)
  • 1
    In: Cancer Research, American Association for Cancer Research (AACR), Vol. 79, No. 13_Supplement ( 2019-07-01), p. 4259-4259
    Abstract: The confluence of deep sequencing and powerful machine learning is providing an unprecedented peek at the darkest of the dark genomic matter. While deep sequencing uncovers rare tumor variants, the heterogeneity of the disease confounds the best of machine learning (ML) algorithms. Here we set out to answer if the dark-matter of the genome encompass signals that can classify the fine subtypes of disease that are otherwise gnomically indistinguishable. We introduce a novel stochastic regularization, ReVeal, that empowers ML to classify subtle cancer subtypes even from the same ‘cell of origin’. Analogous to heritability, implicitly defined on whole genome, we use predictability (F1 score) definable on portions of the genome. In an effort to classify cancer subtypes using dark-matter DNA, we applied ReVeal to a new WGS dataset from 727 patient samples with seven forms of hematological cancers and assessed the predictivity over several genomic regions including genic, non-dark, non-coding, non-genic, dark. ReVeal allowed the classification of all segments of the genome better than standard ML algorithms. The non-genic, non-coding and the dark-matter had the highest F1 scores with dark-matter having the highest level of predictability (F1 = 0.78). Based on ReVeal’s predictability of different sectors of the genome, dark matter contains signal significant enough to classify fine subtypes of disease. The agglomeration of rare variants, even in the hitherto unannotated and ill-understood regions of the genome, may play a substantial role in the disease etiology and deserve much more attention. Citation Format: Laxmi Parida, Claudia Haferlach, Kahn Rhrissorrakrai, Filippo Utro, Chaya Levovitz, Kern Wolfgang, Niroshan Nadarajah, Stephan Hutter, Manja Meggendorfer, Wencke Walter, Constance Baer, Torsten Haferlach. Defining subtle cancer subtypes using the darkest DNA [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2019; 2019 Mar 29-Apr 3; Atlanta, GA. Philadelphia (PA): AACR; Cancer Res 2019;79(13 Suppl):Abstract nr 4259.
    Type of Medium: Online Resource
    ISSN: 0008-5472 , 1538-7445
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    Language: English
    Publisher: American Association for Cancer Research (AACR)
    Publication Date: 2019
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  • 2
    In: Cancer Research, American Association for Cancer Research (AACR), Vol. 82, No. 12_Supplement ( 2022-06-15), p. 5788-5788
    Abstract: The DNA damage response (DDR) pathway is frequently deregulated in cancer and it represent an attractive therapeutic opportunity. In acute myeloid leukemia (AML), different mechanisms of DDR deregulation have been identified, but a systematic investigation on DDR alterations is missing. To understand how the DDR pathways contribute to leukemogenesis, we studied the gene expression and mutational profiles of 274 DDR genes by analysing 539 AML cases profiled by whole genome (WGS) and RNA sequencing. WGS data were used to identify mutations in genes of the DDR and in a panel of genes known to be mutated in AML (n=73). Transcriptomic data were analysed through unsupervised clustering, differential expression and enrichment analysis. We detected 150 single nucleotide variants (SNVs) in 130 patients (24%, average 0.3 SNVs/case). Genes mutated in more than 1% of cases were ATM, BLM, BRCA2, POLG and POLQ. The most frequently altered pathway was the homologous recombination/Fanconi Anemia (HR) pathway (29%), followed by the genes that coordinates the DDR pathway (20%). We detected a trend toward mutual exclusivity between mutations in TP53 and mutations in genes of HR pathway or the genes that coordinates the DDR pathway (adj-p & lt;0.02). To further investigate the interplay between TP53 mutations and the HR pathway, we analysed the expression profiles of HR genes in 539 patients. We identified two groups of patients having higher (HR-high) or lower (HR-low) expression levels of HR genes. A panel of 5 genes was able to discriminate patients between the two groups (BRCA1, RAD54B, RMI2, UBE2T and XRCC2; AUC=0.9). Enrichment analysis on differentially expressed genes and gene set enrichment analysis showed that the cell cycle pathway, together with the G2/M transition/mitotic phase, E2F targets and the fatty acid metabolism pathways were upregulated in HR-high patients, while the pRB, EZH2, RPS14 and HOXA9 pathways were downregulated. Moreover, we observed that AML expressing CBFB-MYH1, RUNX1-RUNXT1 or carrying RAD21 mutations had higher chances to express lower levels of HR genes (HR-low), while patients with STAG2, SRSF2, U2AF1, FLT3-ITD alterations had higher chances of having higher expression of HR genes (p & lt;0.05). NPM1-mutated cases without FLT3-ITD clustered within the HR-low profile (adj-p & lt;0.05), while TP53 mutated cases tended to cluster in the HR-high group, although statistical significance was not reached. In conclusion, our data showed the presence of alterations in the DDR pathway that might be the reflection of driver events in AML. Functional studies will elucidate the functional impact of these alterations. The results suggested the presence of a therapeutic window that might be exploited with DDR inhibitors in molecularly-defined subgroups of patients. Supported by the Torsten Haferlach-Leukämiediagnostik-Stiftung and AIRC IG 2019 (project 23810). Citation Format: Antonella Padella, Stephan Hutter, Wencke Walter, Constance Baer, Irene Azzali, Andrea Ghelli Luserna Di Rorà, Martina Ghetti, Lorenzo Ledda, Matteo Paganelli, Claudia Haferlach, Wolfgang Kern, Giorgia Simonetti, Giovanni Martinelli, Torsten Haferlach. Genomic and transcriptomic profiles of DNA damage response genes in acute myeloid leukemia [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 5788.
    Type of Medium: Online Resource
    ISSN: 1538-7445
    Language: English
    Publisher: American Association for Cancer Research (AACR)
    Publication Date: 2022
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    detail.hit.zdb_id: 1432-1
    detail.hit.zdb_id: 410466-3
    Location Call Number Limitation Availability
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