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  • 1
    Online Resource
    Online Resource
    American Association for Cancer Research (AACR) ; 2021
    In:  Cancer Research Vol. 81, No. 24 ( 2021-12-15), p. 6106-6116
    In: Cancer Research, American Association for Cancer Research (AACR), Vol. 81, No. 24 ( 2021-12-15), p. 6106-6116
    Abstract: Cancer somatic mutations are the product of multiple mutational and repair processes, both of which are tightly associated with DNA replication. Distinctive patterns of somatic mutation accumulation, termed mutational signatures, are indicative of processes sustained within tumors. However, the association of various mutational processes with replication timing (RT) remains an open question. In this study, we systematically analyzed the mutational landscape of 2,787 tumors from 32 tumor types separately for early and late replicating regions using sequence context normalization and chromatin data to account for sequence and chromatin accessibility differences. To account for sequence differences between various genomic regions, an artificial genome–based approach was developed to expand the signature analyses to doublet base substitutions and small insertions and deletions. The association of mutational processes and RT was signature specific: Some signatures were associated with early or late replication (such as SBS7b and SBS7a, respectively), and others had no association. Most associations existed even after normalizing for genome accessibility. A focused mutational signature identification approach was also developed that uses RT information to improve signature identification; this approach found that SBS16, which is biased toward early replication, is strongly associated with better survival rates in liver cancer. Overall, this novel and comprehensive approach provides a better understanding of the etiology of mutational signatures, which may lead to improved cancer prevention, diagnosis, and treatment. Significance: Many mutational processes associate with early or late replication timing regions independently of chromatin accessibility, enabling development of a focused identification approach to improve mutational signature detection.
    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: 2021
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  • 2
    In: Blood, American Society of Hematology, Vol. 120, No. 3 ( 2012-07-19), p. 603-612
    Abstract: Human cancers display substantial intratumoral genetic heterogeneity, which facilitates tumor survival under changing microenvironmental conditions. Tumor substructure and its effect on disease progression and relapse are incompletely understood. In the present study, a high-throughput method that uses neutral somatic mutations accumulated in individual cells to reconstruct cell lineage trees was applied to hundreds of cells of human acute leukemia harvested from multiple patients at diagnosis and at relapse. The reconstructed cell lineage trees of patients with acute myeloid leukemia showed that leukemia cells at relapse were shallow (divide rarely) compared with cells at diagnosis and were closely related to their stem cell subpopulation, implying that in these instances relapse might have originated from rarely dividing stem cells. In contrast, among patients with acute lymphoid leukemia, no differences in cell depth were observed between diagnosis and relapse. In one case of chronic myeloid leukemia, at blast crisis, most of the cells at relapse were mismatch-repair deficient. In almost all leukemia cases, 〉 1 lineage was observed at relapse, indicating that diverse mechanisms can promote relapse in the same patient. In conclusion, diverse relapse mechanisms can be observed by systematic reconstruction of cell lineage trees of patients with leukemia.
    Type of Medium: Online Resource
    ISSN: 0006-4971 , 1528-0020
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    Language: English
    Publisher: American Society of Hematology
    Publication Date: 2012
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  • 3
    In: Blood, American Society of Hematology, Vol. 116, No. 21 ( 2010-11-19), p. 178-178
    Abstract: Abstract 178 Introduction: Leukemic cells are heterogeneous in many ways, and specifically in replication rates. Dormancy and quiescence particularly among leukemia stem cells (LSCs) have been suggested to play a pivotal role in leukemia resistance to chemotherapy. This has been suggested in chronic leukemia, but never proven in acute leukemia, where most cancer cells divide frequently, and it is not known which subpopulation causes relapse. Cell lineage analysis of single leukemia cells can describe the variable kinetics of leukemia subpopulations by studying the evolutionary genetic changes between diagnosis and relapse in the same patient, and hence potentially pinpoint the relapse population already at diagnosis. In the current study a novel methodology was used in order to describe the evolutionary history of single leukemia cells. The reconstruction of phylogenetic trees from single cells can shed light of the relative number of replications of each cell (depth), and the diversity and heterogeneity of the tumor. Method: Phylogenetic analysis was applied to single cells from peripheral blood of two acute myeloid leukemia (AML) patients (n≂F40 cells from each patient), sampled at diagnosis and relapse. Leukemia and T cells were separated by FACS. T cells, which were not part of the malignant AML clone served for the validation of sorting. Single cells underwent whole genome amplification followed by PCR reactions amplifying 120 microsatellite (MS) loci, using a high throughput robotic and computer aided systems. As MSs accumulate genetic variation during replication, the phylogenetic tree of the malignancies can be reconstructed from the genetic changes in MSs between the cells and the application of a neighbor joining algorithm. The relative depth of cells was calculated from the genetic distance of each cell from the root of the tree, which was designated as the median value of all cells for a specific MS. Result: In the reconstructed cell lineage trees of both AML patients (L1 n=41 leukemia cells; L2 n=43 leukemia cells), cells at relapse were shallow compared to cells at diagnosis, implying that they originate from cells that divided rarely prior to relapse (p 〈 10e-5, p 〈 0.0001, L1 and L2 respectively) (Figure 1). Furthermore for patient L2 single LSCs, LIN- CD34+ CD38- CD90+ from diagnosis, were analyzed (n=21 LSCs), and were found to be shallower than the general population of leukemia cells at diagnosis (p=0.01), but deeper than leukemia cells at relapse (p=0.036) (Figure 1). T cells in both AML patients were clustered on a different branch of the lineage tree (L1 n=32, p 〈 10-6; L2 n=29, p=7.4*10-6). Conclusion: A novel single cell phylogenetic approach applied to AML cells uncovered the role of dormancy and LSCs in AML relapse. As chemotherapy preferentially targets rapidly-dividing cells, dormant cells are positively selected to resist chemotherapy at least in some AML patients. In such cases, in order to prevent relapse, leukemia therapy must also target such rarely-dividing leukemia cells. We have further demonstrated that LSCs are genetically correlated to the rarely dividing cells at relapse. The ability of cell lineage analysis to identify rarely dividing cells and correlate them to LSCs and possibly to normal stem cells already at diagnosis may enable their characterization and hence the design of improved targeted and personalized therapy for leukemia and other types of cancer with similar relapse mechanisms. Furthermore, this evolutionary-based approach can also shed more light on the diversity of leukemia in a time scale and uncover other chemotherapy resistance mechanisms. Phylogenetic trees of leukemia single cells at diagnosis and relapse from 2 AML patients. a, L1: Left – reconstructed lineage tree of CD33+ CD4+ CD15- peripheral blood (PB) individual leukemia cells at diagnosis (full, n=14); and relapse (blank, n=27) for patient L1; The root was determined by calculation of the median signal of all cells. Right - comparison of median depth between cells at diagnosis (full) and relapse (blank), (p 〈 10^-5). b, L2: Left – reconstructed lineage tree of CD117+ PB individual leukemia blast cells at diagnosis (full, n=33), LSCs LIN-CD34+ CD38- CD90+ (gray, n=21) and relapse(blank, n=10) for patient L2. Right - Comparison of median depth between cells at diagnosis (full) and relapse (blank), (p=0.0001). Y axis represents depth in arbitrary units (logarithmic scale). Disclosures: No relevant conflicts of interest to declare.
    Type of Medium: Online Resource
    ISSN: 0006-4971 , 1528-0020
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    Language: English
    Publisher: American Society of Hematology
    Publication Date: 2010
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  • 4
    In: SSRN Electronic Journal, Elsevier BV
    Type of Medium: Online Resource
    ISSN: 1556-5068
    Language: English
    Publisher: Elsevier BV
    Publication Date: 2021
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  • 5
    Online Resource
    Online Resource
    Springer Science and Business Media LLC ; 2023
    In:  Scientific Reports Vol. 13, No. 1 ( 2023-05-15)
    In: Scientific Reports, Springer Science and Business Media LLC, Vol. 13, No. 1 ( 2023-05-15)
    Abstract: Mutational signatures’ association with replication timing (RT) has been studied in cancer samples, but the RT distribution of somatic mutations in non-cancerous cells was only minimally explored. Here, we performed comprehensive analyses of mutational signatures in 2.9 million somatic mutations across multiple non-cancerous tissues, stratified by early and late RT regions. We found that many mutational processes are active mainly or solely in early RT, such as SBS16 in hepatocytes and SBS88 in the colon, or in late RT, such as SBS4 in lung and hepatocytes, and SBS18 across many tissues. The two ubiquitous signatures, SBS1 and SBS5, showed late and early bias, respectively, across multiple tissues and in mutations representing germ cells. We also performed a direct comparison with cancer samples in 4 matched tissue-cancer types. Unexpectedly, while for most signatures the RT bias was consistent in normal tissue and in cancer, we found that SBS1’s late RT bias is lost in cancer.
    Type of Medium: Online Resource
    ISSN: 2045-2322
    Language: English
    Publisher: Springer Science and Business Media LLC
    Publication Date: 2023
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  • 6
    Online Resource
    Online Resource
    American Chemical Society (ACS) ; 2005
    In:  Environmental Science & Technology Vol. 39, No. 3 ( 2005-02-01), p. 748-755
    In: Environmental Science & Technology, American Chemical Society (ACS), Vol. 39, No. 3 ( 2005-02-01), p. 748-755
    Type of Medium: Online Resource
    ISSN: 0013-936X , 1520-5851
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    Language: English
    Publisher: American Chemical Society (ACS)
    Publication Date: 2005
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  • 7
    Online Resource
    Online Resource
    Public Library of Science (PLoS) ; 2008
    In:  PLoS Computational Biology Vol. 4, No. 5 ( 2008-5-9), p. e1000058-
    In: PLoS Computational Biology, Public Library of Science (PLoS), Vol. 4, No. 5 ( 2008-5-9), p. e1000058-
    Type of Medium: Online Resource
    ISSN: 1553-7358
    Language: English
    Publisher: Public Library of Science (PLoS)
    Publication Date: 2008
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  • 8
    Online Resource
    Online Resource
    Oxford University Press (OUP) ; 2020
    In:  Neuro-Oncology Vol. 22, No. Supplement_2 ( 2020-11-09), p. ii75-ii75
    In: Neuro-Oncology, Oxford University Press (OUP), Vol. 22, No. Supplement_2 ( 2020-11-09), p. ii75-ii75
    Abstract: Glioblastoma (GBM) is the most common and the most devastating primary brain cancer in adults. Precision genetic medicine approach does not provide benefit to majority of GBM patients. A major reason for this is tumor heterogeneity harboring potential resistance mechanisms. Here, we describe an approach to grow spheroids of GBM, containing tumor, stroma and vascular tissues. We show that this approach can identify undetected subclonal driver mutations that can potentially cause drug resistance later in the disease course. METHODS We grew spheroids of a GBM patient in a multi-well array and monitored them visually. Exome sequencing of the parental tumor (coverage of 557X) and of spheroids after 10 days (n=3) and 20 days (n=5) of growth was performed. In addition, we sequenced six spheroids that were grown for 10 days and treated by Temozolomide for the next 10 days. RESULTS 70 somatic mutations were detected in the parental tumor. 42/70 of the tumor’s somatic mutations were also detected in the spheroids. 192 somatic mutations were detected in the spheroids only and not in the parental tumor despite high coverage sequencing of the parental tumor. In cancer genes: six somatic mutations were identified in the parental tumor, 5/6 were also detected in the spheroids and 13 mutations were detected only in the spheroids. EGFR V774M mutation was detected in both tumor and spheroids. However – EGFR T790M was independently detected in 7/11 of the spheroids sequenced after 20 days or growth but not in the parental tumor. CONCLUSION Analysis of GBM spheroids enables detection of rare subclonal mutations not detected in parental tumor. We hypothesize that this is due to positive selection of the ex vivo growth conditions. This analysis enabled detection of EGFR T790M – an important targetable resistance mutation in lung cancer not previously described in primary GBM.
    Type of Medium: Online Resource
    ISSN: 1522-8517 , 1523-5866
    Language: English
    Publisher: Oxford University Press (OUP)
    Publication Date: 2020
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  • 9
    Online Resource
    Online Resource
    American Chemical Society (ACS) ; 2005
    In:  Environmental Science & Technology Vol. 39, No. 2 ( 2005-01-01), p. 505-512
    In: Environmental Science & Technology, American Chemical Society (ACS), Vol. 39, No. 2 ( 2005-01-01), p. 505-512
    Type of Medium: Online Resource
    ISSN: 0013-936X , 1520-5851
    RVK:
    Language: English
    Publisher: American Chemical Society (ACS)
    Publication Date: 2005
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    detail.hit.zdb_id: 1465132-4
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  • 10
    Online Resource
    Online Resource
    Elsevier BV ; 2006
    In:  Chemosphere Vol. 62, No. 1 ( 2006-1), p. 17-25
    In: Chemosphere, Elsevier BV, Vol. 62, No. 1 ( 2006-1), p. 17-25
    Type of Medium: Online Resource
    ISSN: 0045-6535
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    Language: English
    Publisher: Elsevier BV
    Publication Date: 2006
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