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  • 1
    In: Cancer Research, American Association for Cancer Research (AACR), Vol. 65, No. 18 ( 2005-09-15), p. 8142-8150
    Abstract: Osteosarcoma is the most common malignant bone tumor in children. After initial diagnosis is made with a biopsy, treatment consists of preoperative chemotherapy followed by definitive surgery and postoperative chemotherapy. The degree of tumor necrosis in response to preoperative chemotherapy is a reliable prognostic factor and is used to guide the choice of postoperative chemotherapy. Patients with tumors, which reveal ≥90% necrosis (good responders), have a much better prognosis than those with & lt;90% necrosis (poor responders). Despite previous attempts to improve the outcome of poor responders by modifying the postoperative chemotherapy, their prognosis remains poor. Therefore, there is a need to predict at the time of diagnosis patients' response to preoperative chemotherapy. This will provide the basis for developing potentially effective therapy that can be given at the outset for those who are likely to have a poor response. Here, we report the analysis of 34 pediatric osteosarcoma samples by expression profiling. Using parametric two-sample t test, we identified 45 genes that discriminate between good and poor responders (P & lt; 0.005) in 20 definitive surgery samples. A support vector machine classifier was built using these predictor genes and was tested for its ability to classify initial biopsy samples. Five of six initial biopsy samples that had corresponding definitive surgery samples in the training set were classified correctly (83%; confidence interval, 36%, 100%). When this classifier was used to predict eight independent initial biopsy samples, there was 100% accuracy (confidence interval, 63%, 100%). Many of the predictor genes are implicated in bone development, drug resistance, and tumorigenesis.
    Type of Medium: Online Resource
    ISSN: 0008-5472 , 1538-7445
    RVK:
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    Language: English
    Publisher: American Association for Cancer Research (AACR)
    Publication Date: 2005
    detail.hit.zdb_id: 2036785-5
    detail.hit.zdb_id: 1432-1
    detail.hit.zdb_id: 410466-3
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  • 2
    In: Journal of Vascular and Interventional Radiology, Elsevier BV, Vol. 12, No. 6 ( 2001-6), p. 761-763
    Type of Medium: Online Resource
    ISSN: 1051-0443
    Language: English
    Publisher: Elsevier BV
    Publication Date: 2001
    detail.hit.zdb_id: 2041331-2
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  • 3
    Online Resource
    Online Resource
    Bentham Science Publishers Ltd. ; 2009
    In:  The Open Biology Journal Vol. 2, No. 1 ( 2009-7-08), p. 54-65
    In: The Open Biology Journal, Bentham Science Publishers Ltd., Vol. 2, No. 1 ( 2009-7-08), p. 54-65
    Abstract: Gene copy number change is an essential characteristic of many types of cancer. However, it is important to distinguish copy number variation (CNV) in the human genome of normal individuals from bona fide abnormal copy number changes of genes specific to cancers. Based on Affymetrix 50K single nucleotide polymorphism (SNP) array data, we identified genome-wide copy number variations among 104 normal subjects from three ethnic groups that were used in the HapMap project. Our analysis revealed 155 CNV regions, of which 37% were gains and 63% were losses. About 21% (30) of the CNV regions are concordant with earlier reports. These 155 CNV regions are located on more than 100 cytobands across all 23 chromosomes. The CNVs range from 68bp to 18 Mb in length, with a median length of 86 Kb. Eight CNV regions were selected for validation by quantitative PCR. Analysis of genomic sequences within and adjacent to CNVs suggests that repetitive sequences such as long interspersed nuclear elements (LINEs) and long terminal repeats (LTRs) may play a role in the origin of CNVs by facilitating non-allelic homologous recombination. Thirty-two percent of the CNVs identified in this study are associated with segmental duplications. CNVs were not preferentially enriched in gene-encoding regions. Among the 364 genes that are completely encompassed by these 155 CNVs, genes related to olfactory sensory, chemical stimulus, and other physiological responses are significantly enriched. A statistical analysis of CNVs by ethnic group revealed distinct patterns regarding the CNV location and gain-to-loss ratio. The CNVs reported here will help build a more comprehensive map of genomic variations in the human genome and facilitate the differentiation between copy number variation and somatic changes in cancers. The potential roles of certain repeat elements in CNV formation, as corroborated by other studies, shed light on the origin of CNVs and will improve our understanding of the mechanisms of genomic rearrangements in the human genome.
    Type of Medium: Online Resource
    ISSN: 1874-1967
    Language: English
    Publisher: Bentham Science Publishers Ltd.
    Publication Date: 2009
    detail.hit.zdb_id: 2451952-2
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  • 4
    Online Resource
    Online Resource
    American Society for Microbiology ; 1998
    In:  Journal of Bacteriology Vol. 180, No. 16 ( 1998-08-15), p. 4294-4299
    In: Journal of Bacteriology, American Society for Microbiology, Vol. 180, No. 16 ( 1998-08-15), p. 4294-4299
    Abstract: We show that epd ( gapB ) mutants lacking an erythrose 4-phosphate (E4P) dehydrogenase are impaired for growth on some media and contain less pyridoxal 5′-phosphate (PLP) and pyridoxamine 5′-phosphate (PMP) than their epd + parent. In contrast to a previous report, we found that gapA epd double mutants lacking the glyceraldehyde 3-phosphate and E4P dehydrogenases are auxotrophic for pyridoxine. These results implicate the GapA and Epd dehydrogenases in de novo PLP and PMP coenzyme biosynthesis.
    Type of Medium: Online Resource
    ISSN: 0021-9193 , 1098-5530
    Language: English
    Publisher: American Society for Microbiology
    Publication Date: 1998
    detail.hit.zdb_id: 1481988-0
    SSG: 12
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  • 5
    In: Pediatric Blood & Cancer, Wiley, Vol. 51, No. 2 ( 2008-08), p. 171-177
    Type of Medium: Online Resource
    ISSN: 1545-5009 , 1545-5017
    URL: Issue
    Language: English
    Publisher: Wiley
    Publication Date: 2008
    detail.hit.zdb_id: 2130978-4
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  • 6
    Online Resource
    Online Resource
    PiscoMed Publishing Pte. Ltd. ; 2017
    In:  Advances in Modern Oncology Research Vol. 3, No. 4 ( 2017-08-15)
    In: Advances in Modern Oncology Research, PiscoMed Publishing Pte. Ltd., Vol. 3, No. 4 ( 2017-08-15)
    Abstract: 〈 p 〉 In the age of big data, genomics and clinical research have reached a crossroads. A wealth of data is being generated, but it is becoming increasingly complicated to analyze these data to extract meaningful results. The ability to understand biological systems holistically has unprecedented potential to transform how cancers are treated. Recent major advances leading biomedical research towards “systems medicine” have been fueled by high-throughput platforms, such as microarrays and next-generation sequencing, which can capture vast amounts of data in different genomic spaces. Unfortunately, because of high dimensionality and complex relationships among these data, inferring comprehensive and useful biological models has proven computationally and statistically challenging. However, novel bioinformatic methods for data integration of cancer genomic datasets have been developed. In this review, we will describe the applications of various genomic approaches in sarcoma research and introduce bioinformatic methods for data integration. With the continuing evolution of technological and bioinformatic methodologies, the application of big data within clinics and hospitals will ultimately result in significant improvements on how cancers are detected and treated. 〈 /p 〉
    Type of Medium: Online Resource
    ISSN: 2424-7855 , 2424-7847
    Language: Unknown
    Publisher: PiscoMed Publishing Pte. Ltd.
    Publication Date: 2017
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  • 7
    In: Blood, American Society of Hematology, Vol. 140, No. Supplement 1 ( 2022-11-15), p. 9597-9597
    Type of Medium: Online Resource
    ISSN: 0006-4971 , 1528-0020
    RVK:
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    Language: English
    Publisher: American Society of Hematology
    Publication Date: 2022
    detail.hit.zdb_id: 1468538-3
    detail.hit.zdb_id: 80069-7
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  • 8
    In: Blood, American Society of Hematology, Vol. 122, No. 21 ( 2013-11-15), p. 2854-2854
    Abstract: Despite indistinguishable histology and the common feature of Birbeck granules in lesion biopsies, clinical presentation of patients with Langerhans Cell Histiocytosis (LCH) is highly variable, from single lesion cured by curretage, to multi-system disease requiring aggressive chemotherapy or stem cell transplant. Risk stratification for Langerhans Cell Histiocytosis has historically assigned clinical risk groups based on anatomic location and extent of LCH lesions, which is the basis for dose and duration of chemotherpy on recent Histiocyte Society trials. In this study, we test the hypothesis that distinct subgroups of patients with LCH may be identified by relative levels of circulating biomarkers. Methods Pre-therapy plasma was collected on 97 patients with LCH (82 Pediatric: 17 High-Risk, 23 Multisystem/Multifocal “Non-risk”, 42 Single Lesion “Non-risk”; 15 Adult: 5 High-Risk, 5 Multisystem/Multifocal “Non-risk”, 5 Single Lesion “Non-risk”) and 49 control subjects (32 Pediatric, 17 Adult). Quantitative levels of plasma proteins (158 analytes) was determined by multiplex analysis with Millipore MagPix kits and the Luminex plate reader. Data were analyzed with both unsupervised and supervised methodologies. Results Consensus clustering with non-negative matrix factorization (NMF) clusters identified three groups which were analyzed along with clinical categories. Significant clinical variables included age (adult samples clustered in NMF group 1) and LCH risk category (High-Risk LCH samples clustered in NMF group 3). Samples from patients with the BRAF-V600Emutation or relapse within 1 year did not cluster into any NMF group with signifiance. Additionally, supervised analysis identified specific molecules that were significantly differentially expressed between different clinical categories after multiple testing correction (FDR 〈 0.10): Pediatric LCH vs Adult LCH (72 molecules significant, largest differences in MMP-3, MMP-2 and osteopontin); Pediatric Control vs Pediatric LCH (66 molecules significant, largest differences in SDF-1a, IL-20, MIP-1d, FGF-2 and sIL-4R); Pediatric Low-Risk vs Pediatric High-Risk (47 molecules significant, largest differences in sTNF-R11, sTNF-RI, I-309, sIL2Ra and osteopontin). While previous studies have analyzed expression differences of cytokines in LCH lesions and plasma, in this study the most striking differences are between control vs LCH samples are chemokine molecules. The largest differences between Low-Risk and High-Risk LCH patients include inflammatory cytokines and receptors. Conclusions Despite mounting evidence supporting pathogenesis of LCH as a myeloid neoplasia arising from immature dendritic cell precursors, these results are consistent with exuberant chemokine and cytokine expression in patients with active LCH, supporting a potential role for inflammation in pathogenesis. This study demonstrates the feasibility of identifying novel LCH sub-groups according to plasma protein profiles with unsupervised analysis, and significant differences can be detected in protein levels between clinical risk groups. Future studies will validate the clinical utility of plasma biomarkers in diagnosis, risk-stratification and determining response to therapy. Finally, feasibility of collecting plasma compared to viable lesions makes plasma studies ideal for prospective collection and analysis in cooperative group studies. 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: 2013
    detail.hit.zdb_id: 1468538-3
    detail.hit.zdb_id: 80069-7
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  • 9
    Online Resource
    Online Resource
    American Society of Hematology ; 2021
    In:  Blood Vol. 138, No. Supplement 1 ( 2021-11-05), p. 3458-3458
    In: Blood, American Society of Hematology, Vol. 138, No. Supplement 1 ( 2021-11-05), p. 3458-3458
    Abstract: Introduction - Acute myeloid leukemia (AML) is an aggressive disease with a relapse rate of approximately 40% in children. Progress in improving cure rates has been slow, in part because AML is very heterogeneous. Molecular studies consistently show that most cases are comprised of distinct subclones that diminish or expand over the course of therapy. Single-cell profiling methods now allow parsing of the leukemic population into subsets based on gene and/or protein expression patterns. We hypothesized that comparing the features of the subsets that are dominant at relapse with those that are dominant at diagnosis would reveal mechanisms of treatment failure. Methods - We profiled diagnosis-relapse pairs from 6 pediatric AML patients by Cellular Indexing of Transcriptomes and Epitopes by Sequencing (CITE-Seq). All patients were treated at Texas Children's Cancer Center and consented to banking of tissue for research. CITE-Seq was performed by Immunai (New York, NY) using a customized panel of 65 oligonucleotide-tagged antibodies, the 10x Genomics Chromium system for single-cell RNA library generation, and the Novaseq 6000 for sequencing. After data cleanup and normalization, clustering by scRNA-seq was done using the Seurat package. Cell-type identification of clusters was facilitated by published healthy bone marrow scRNA-seq datasets (van Galen et al, Cell 2019). Differentially expressed genes (DEGs) and proteins (DEPs) between diagnosis and relapse were determined using Wilcoxin ranked sum tests. Results - We generated single-cell transcriptomes for a total of 28,486 cells from 12 samples, with a mean of 2373 cells and 1416 genes per sample. Samples were integrated with batch effect correction, producing 30 distinct clusters (cell types) in total (Figure 1A). Cell types with expression profiles consistent with lymphocytes and erythroid precursors were identified in multiple patients, whereas AML cell types tended to be specific to individual patients (Figure 1B). For patients TCH1, TCH2 and TCH3, the most abundant cell types at diagnosis were rare at relapse, and cell types that were rare at diagnosis became dominant at relapse. For these 3 cases, we identified DEGs between the dominant diagnosis cell types and dominant relapse cell types. We found 18 genes that were upregulated at relapse in at least 2 of the cases. Several genes related to actin polymerization were enriched (ARPC1B, ACTB, PFN1), possibly reflecting an enhanced capacity for adhesion and migration. Also of note, macrophage migration inhibitory factor (MIF) and its receptor CD74 were upregulated at relapse, suggesting a role in chemoresistance. For patients TCH4, TCH5 and TCH6, the same cell types that were abundant at diagnosis were also abundant at relapse, and few genes were significantly altered between diagnosis and relapse in multiple cases. Only SRGN, which encodes the proteoglycan serglycin, and GAPDH were altered in 2 of these 3 cases, and both were downregulated at relapse. We performed similar comparisons to identify proteins that were differentially expressed between diagnosis and relapse pairs. The number of DEPs between the dominant diagnosis and relapse cell types ranged from 0 (TCH1 and TCH6) to 5 (TCH2). The only protein altered in more than one case was CD7, which was enriched at relapse in TCH2, TCH3 and TCH4. Conclusions - From CITE-Seq profiling of 6 pediatric AML cases we identified two distinct patterns of relapse. For 3 cases, relapse occurred by expansion of a subset that was small but present at diagnosis. Enrichment of genes associated with adhesion and survival signaling suggests that these cells survived because they were well-equipped to take advantage of interactions with the microenvironment. For 3 other cases, the population that was dominant at diagnosis persisted and expanded at relapse with few substantial changes in gene or protein expression profiles. This pattern suggests that these AML cells were a priori equipped to survive chemotherapy, even though bulk disease levels were transiently reduced below the limit of detection. Most profiled proteins did not change substantially between diagnosis and relapse. An exception is CD7, which was enriched at relapse in 50% of our cases and represents a potential therapeutic target. Analysis of more cases will refine these relapse patterns, reveal potential mechanisms of chemoresistance and inform the development of novel therapies. Figure 1 Figure 1. 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: 2021
    detail.hit.zdb_id: 1468538-3
    detail.hit.zdb_id: 80069-7
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  • 10
    In: Blood, American Society of Hematology, Vol. 132, No. Supplement 1 ( 2018-11-29), p. 1510-1510
    Abstract: Pediatric AML has a relapse rate approaching 40%, indicating that resistance to chemotherapy remains a critical problem. We are focused on identifying and overcoming environment-mediated mechanisms of resistance. We previously reported that the sensitivity of G-CSF- and IL-6-induced STAT3 signaling was significantly associated with outcome in pediatric AML patients. In this follow-up study, we used conditioned medium (CM) from HS5 stromal cells as a more physiological stimulus to evaluate the capacity of primary AML cells to activate signaling pathways. We studied 111 diagnostic bone marrow samples from patients who enrolled on Children's Oncology Group (COG) AML treatment studies, AAML03P1 or AAML0531, and provided informed consent to bank bone marrow. The same chemotherapy backbone was used in both trials. All samples had at least 70% viability after thawing. Thawed cells were divided into aliquots for stimulation with 50% CM, 10 ng/ml G-CSF, or 5 ng/ml IL-6. Unstimulated cells were used for isotype controls and for determination of basal signaling levels. Following 15 min stimulation, cells were fixed and processed for FACS analysis of CD45, pY-STAT3, pY-STAT5, pERK1/2, and pAKT. Responses were expressed as the fold change in mean fluorescence intensity for stimulated cells over unstimulated cells (ΔMFI). The ΔMFIs for pY-STAT3 and pY-STAT5 varied between 0.1 and 31.8. The ΔMFIs for pERK1/2 and pAKT rarely exceeded 2. Samples with a robust response to one stimulus generally responded robustly to the others. The Pearson correlation coefficient (r) for CM-induced pY-STAT3 v. G-CSF-induced pY-STAT3 was 0.8511 (p 〈 0.00001). The CM-induced pY-STAT5 and G-CSF-induced pY-STAT5 responses were significantly but less strongly correlated (r=0.2765; p=0.0043). Cut point analyses identified response thresholds that distinguished patients with higher EFS from those with lower EFS. We found that higher CM-induced pY-STAT5 was significantly associated with an inferior EFS (Figure 1), with HR 2.06 for those with ΔMFI 〉 1.96 (p=0.034). Previously we found that higher inducible pY-STAT3 was associated with significantly better EFS (Redell, et al, Blood, 2013; Long, et al, Oncotarget, 2017). In this study, no cut point for CM-induced pY-STAT3 ΔMFI distinguished patients with good or poor EFS. Cytogenetics and FLT3/ITD were not significantly different for groups above and below the ΔMFI cut points. The finding that robust STAT5 signaling is associated with inferior EFS suggests that a factor that signals primarily through STAT5 and not STAT3 (e.g. GM-CSF, IL-3, FL) could contribute to treatment resistance and relapse. Interestingly, most of the samples that failed to activate STAT3/5 pathways in response to G-CSF also failed to respond to the cocktail of factors in CM, suggesting a generalized signaling dysfunction. To investigate intrinsic gene expression differences, we leveraged existing RNA-seq data for the samples for which we generated signaling responses. We obtained RNA-seq data for 27 samples from the NCI Therapeutically Applicable Research to Generate Effective Treatments (TARGET) database. RNA-seq data for an additional 45 samples were provided through collaboration with the University of Washington. Of these 72 samples, 29 samples were resistant to CM-induced pY-STAT3 (ΔMFI 〈 2, CM-R) and 43 samples were sensitive (ΔMFI 〉 2, CM-S). Raw counts were normalized and analyzed by EdgeR with GLM algorithm and blocking to control for batch effects from the two datasets. We found that 219 features were significantly differentially expressed (DE; FDR 〈 0.05), with 192 being expressed more highly in the CM-R group. Gene set enrichment analysis identified the "matrisome" gene set, including genes encoding growth factors and matrix proteins, as being significantly enriched in the CM-R group. For example, genes encoding G-CSF, GM-CSF, WNT7B, and integrin B3 were upregulated in CM-R samples. Additionally, a number of non-HOX homeobox genes, including DLX2, DLX3 and MSX2, were increased in CM-R samples. There was no difference in the mean %blasts for the samples in the CM-R and CM-S groups, arguing against the increased expression of matrix-related genes being due to a higher proportion of non-blast cells in the CM-R samples. Our integration of gene expression with inducible STAT3/5 responses will yield novel insights into extrinsic survival signaling and mechanisms of dysfunction. Disclosures No relevant conflicts of interest to declare.
    Type of Medium: Online Resource
    ISSN: 0006-4971 , 1528-0020
    RVK:
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    Language: English
    Publisher: American Society of Hematology
    Publication Date: 2018
    detail.hit.zdb_id: 1468538-3
    detail.hit.zdb_id: 80069-7
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