Osteosarcoma enters a post genomic era with in silico opportunities: Generation of the High Dimensional Database for facilitating sarcoma biology research: A report from the Children's Oncology Group and the QuadW Foundation.
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ABSTRACT:
SUBMITTER: Glover J
PROVIDER: S-EPMC5521774 | biostudies-other | 2017
REPOSITORIES: biostudies-other
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Project description:Survival rates of patients with osteosarcoma have remained stagnant over the last thirty years. Better understanding of biology, new therapeutics, and improved biomarkers are needed. The Children's Oncology Group (COG) addressed this need by developing one of the largest osteosarcoma biorepositories ever, containing over 15,000 tumor and tissue samples from over 1,500 patients.The biology study P9851 and the banking study AOST06B1 has enrolled 1,787 patients (as of September, 2013). Clinical information was lacking on 510 patients on P9851, who were not enrolled on a concurrent therapeutic trial. The value of these specimens was diminished. The lack of statistical support available for biology projects slowed the analysis of several critical studies. The QuadW Foundation, CureSearch, and the COG formed the Childhood Sarcoma Biostatistics and Annotation Office (CSBAO) to provide the infrastructure and address these needs by linking clinically annotated patient data to archived tissue samples and to develop biostatistical support for childhood sarcoma research.Originally 5.3% of samples from the 510 patients on P9851 not enrolled on a therapeutic study had full clinical annotation. The efforts of the CSBAO have linked clinical annotation to 90.8% of those specimens and provided statistical analyses to several studies that had used COG samples. As a result, 24 biology studies in osteosarcoma have been completed and published in peer-reviewed journals.These samples and in-silico data are available to the research community for basic and translational science projects to improve the biological understanding and treatment of patients affected by osteosarcoma.
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Project description:BACKGROUND:New prognostic markers are needed to identify patients with Ewing sarcoma (EWS) and osteosarcoma unlikely to benefit from standard therapy. We describe the incidence and association with outcome of circulating tumour DNA (ctDNA) using next-generation sequencing (NGS) assays. METHODS:A NGS hybrid capture assay and an ultra-low-pass whole-genome sequencing assay were used to detect ctDNA in banked plasma from patients with EWS and osteosarcoma, respectively. Patients were coded as positive or negative for ctDNA and tested for association with clinical features and outcome. RESULTS:The analytic cohort included 94 patients with EWS (82% from initial diagnosis) and 72 patients with primary localised osteosarcoma (100% from initial diagnosis). ctDNA was detectable in 53% and 57% of newly diagnosed patients with EWS and osteosarcoma, respectively. Among patients with newly diagnosed localised EWS, detectable ctDNA was associated with inferior 3-year event-free survival (48.6% vs. 82.1%; p?=?0.006) and overall survival (79.8% vs. 92.6%; p?=?0.01). In both EWS and osteosarcoma, risk of event and death increased with ctDNA levels. CONCLUSIONS:NGS assays agnostic of primary tumour sequencing results detect ctDNA in half of the plasma samples from patients with newly diagnosed EWS and osteosarcoma. Detectable ctDNA is associated with inferior outcomes.
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Project description:The tremendous amount of biological sequence data available, combined with the recent methodological breakthrough in deep learning in domains such as computer vision or natural language processing, is leading today to the transformation of bioinformatics through the emergence of deep genomics, the application of deep learning to genomic sequences. We review here the new applications that the use of deep learning enables in the field, focusing on three aspects: the functional annotation of genomes, the sequence determinants of the genome functions and the possibility to write synthetic genomic sequences.
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Project description:BACKGROUND:Despite drastic improvement in overall survival for pediatric patients with cancer, those with osteosarcoma have stable rates of survival since the 1980s. This project evaluates the effect of several variables on survival after first recurrence in patients with osteosarcoma. METHODS:Data from three prospective North American cooperative group trials for newly diagnosed osteosarcoma are included: INT-0133, POG-9754, and AOST0121. The analytic population for this study is all enrolled patients with first event-free survival (EFS) event of relapse. The primary outcome measure for this retrospective analysis was survival after recurrence (SAR). RESULTS:The analytic population consisted of N = 431 patients. SAR was statistically significantly associated with age at enrollment (<10 years, P = 0.027), presence of metastatic disease at diagnosis (localized, P < 0.0001), site of relapse (combination lung + bone, unfavorable, P = 0.005), and time to first relapse (2+ years, favorable, P < 0.0001) in multivariate analysis. Ethnicity, primary site of tumor, race, and sex were not significantly related to SAR. CONCLUSIONS:Prolonged SAR in patients with relapsed osteosarcoma is associated with age, extent of disease at diagnosis, site of and time to relapse. Adolescent and young adult patients with osteosarcoma have shorter SAR than younger patients, consistent with studies showing decreased overall survival in this group. Although patients with primary metastatic disease have shorter SAR, there is a subset of patients who relapse greater than 2 years from initial diagnosis that will become survivors. Histological response was significantly associated with time to relapse, but was not predictive of SAR.
| S-EPMC6249072 | biostudies-literature
Project description:PAPER 1:"Identification of novel subgroups of high-risk pediatric precursor B acute lymphoblastic leukemia (B-ALL) by unsupervised microarray analysis: clinical correlates and therapeutic implications. A Children's Oncology Group (COG) study." ABSTRACT We examined gene expression profiles of pre-treatment specimens from 207 patients from the COG P9906 study to identify signatures of children with high risk B-precursor acute lymphoblastic leukemia (ALL) and to determine whether the resulting clusters are associated with either specific clinical features or treatment response characteristics. Four unsupervised clustering methods were utilized to classify patients into similar groups. The different clustering algorithms showed significant overlap in cluster membership. Two clusters contained all cases with either t(1;19)(q23;p13) translocations or MLL rearrangements. The other six clusters were novel and had no recurring chromosomal abnormalities or distinctive clinical features. Members of two of these novel clusters had significant survival differences when compared to the overall 4-year relapse-free survival (RFS) of 61%. These included clusters of patients with either significantly better (94.7%) or worse (21.0%) RFS at 4 years. Children of Hispanic/Latino ethnicity were disproportionately present in the poor outcome cluster. The poor outcome cluster represents a novel biologically distinctive subset of B-precursor ALL that may occur at least as frequently as BCR/ABL. Further molecular characterization of this cluster may lead to the discovery of genomic abnormalities that can be targeted to improve the currently dismal outcome for children with this gene signature. The Sample data have also been used in another study: PAPER 2: "Gene expression classifiers for minimal residual disease and relapse free survival improve outcome prediction and risk classification in children with high risk acute lymphoblastic leukemia. A Children's Oncology Group study". ABSTRACT Background. Nearly 25% of children with B-precursor ALL present with "high-risk" disease (HR-ALL) that is resistant to current therapies. Gene expression profiling may yield molecular classifiers for outcome prediction that can be used to improve risk classification and therapeutic targeting. Methods. Expression profiles were obtained in pre-treatment leukemic samples from 207 uniformly treated children with HR-ALL. Relapse free survival (RFS) was 61% at 4 years and flow cytometric measures of minimal residual disease (MRD) at the end of induction (day 29) were predictive of outcome (P<0.001). Molecular classifiers predictive of RFS and MRD were developed using extensive cross-validation procedures. Results. A 38 gene molecular risk classifier predictive of RFS (MRC-RFS) distinguished two groups in HR-ALL with different relapse risks: low (4 yr RFS: 81%, n=109) vs. high (4 yr RFS: 50%, n=98) (P<0.0001). In multivariate analysis, the best predictor combined MRC-RFS and day 29 flow MRD data, classifying children into low (87% RFS), intermediate (62% RFS), or high risk (29% RFS) groups (P<0.0001). A 21 gene molecular classifier predictive of MRD could effectively substitute for day 29 flow MRD, yielding a combined classifier that similarly distinguished three risk groups at pre-treatment (low: 82% RFS; intermediate: 63% RFS; and high risk: 45% RFS) (P<0.0001). This combined molecular classifier was further validated on an independent cohort of 84 children with HR-ALL (P = 0.006). Conclusions. Molecular classifiers predictive of RFS and MRD can be used to distinguish distinct prognostic groups within HR-ALL, significantly improving risk classification schemes and the ability to prospectively identify children at diagnosis who will respond to or fail current treatment regimens. NOTE: Due to Children's Oncology Group (COG) restrictions, outcome and MRD data cannot be provided as part of the covariate data for this dataset at the present time. If you would like to arrange individual access to this data, please contact COG or the PI of this study, Dr. Cheryl Willman, at the University of New Mexico Cancer Center (cwillman@unm.edu) to arrange a collaboration.
2009-06-25 | GSE11877 | GEO
Project description:Patients who are diagnosed with osteosarcoma (OS) today receive the same therapy that patients have received over the last 4 decades. Extensive efforts to identify more effective or less toxic regimens have proved disappointing. As we enter a postgenomic era in which we now recognize OS not as a cancer of mutations but as one defined by p53 loss, chromosomal complexity, copy number alteration, and profound heterogeneity, emerging threads of discovery leave many hopeful that an improving understanding of biology will drive discoveries that improve clinical care. Under the organization of the Bone Tumor Biology Committee of the Children's Oncology Group, a team of clinicians and scientists sought to define the state of the science and to identify questions that, if answered, have the greatest potential to drive fundamental clinical advances. Having discussed these questions in a series of meetings, each led by invited experts, we distilled these conversations into a series of seven Provocative Questions. These include questions about the molecular events that trigger oncogenesis, the genomic and epigenomic drivers of disease, the biology of lung metastasis, research models that best predict clinical outcomes, and processes for translating findings into clinical trials. Here, we briefly present each Provocative Question, review the current scientific evidence, note the immediate opportunities, and speculate on the impact that answered questions might have on the field. We do so with an intent to provide a framework around which investigators can build programs and collaborations to tackle the hardest problems and to establish research priorities for those developing policies and providing funding.
| S-EPMC6948723 | biostudies-literature
Project description:PAPER 1:"Identification of novel subgroups of high-risk pediatric precursor B acute lymphoblastic leukemia (B-ALL) by unsupervised microarray analysis: clinical correlates and therapeutic implications. A Children's Oncology Group (COG) study." ABSTRACT We examined gene expression profiles of pre-treatment specimens from 207 patients from the COG P9906 study to identify signatures of children with high risk B-precursor acute lymphoblastic leukemia (ALL) and to determine whether the resulting clusters are associated with either specific clinical features or treatment response characteristics. Four unsupervised clustering methods were utilized to classify patients into similar groups. The different clustering algorithms showed significant overlap in cluster membership. Two clusters contained all cases with either t(1;19)(q23;p13) translocations or MLL rearrangements. The other six clusters were novel and had no recurring chromosomal abnormalities or distinctive clinical features. Members of two of these novel clusters had significant survival differences when compared to the overall 4-year relapse-free survival (RFS) of 61%. These included clusters of patients with either significantly better (94.7%) or worse (21.0%) RFS at 4 years. Children of Hispanic/Latino ethnicity were disproportionately present in the poor outcome cluster. The poor outcome cluster represents a novel biologically distinctive subset of B-precursor ALL that may occur at least as frequently as BCR/ABL. Further molecular characterization of this cluster may lead to the discovery of genomic abnormalities that can be targeted to improve the currently dismal outcome for children with this gene signature. The Sample data have also been used in another study: PAPER 2: "Gene expression classifiers for minimal residual disease and relapse free survival improve outcome prediction and risk classification in children with high risk acute lymphoblastic leukemia. A Children's Oncology Group study". ABSTRACT Background. Nearly 25% of children with B-precursor ALL present with "high-risk" disease (HR-ALL) that is resistant to current therapies. Gene expression profiling may yield molecular classifiers for outcome prediction that can be used to improve risk classification and therapeutic targeting. Methods. Expression profiles were obtained in pre-treatment leukemic samples from 207 uniformly treated children with HR-ALL. Relapse free survival (RFS) was 61% at 4 years and flow cytometric measures of minimal residual disease (MRD) at the end of induction (day 29) were predictive of outcome (P<0.001). Molecular classifiers predictive of RFS and MRD were developed using extensive cross-validation procedures. Results. A 38 gene molecular risk classifier predictive of RFS (MRC-RFS) distinguished two groups in HR-ALL with different relapse risks: low (4 yr RFS: 81%, n=109) vs. high (4 yr RFS: 50%, n=98) (P<0.0001). In multivariate analysis, the best predictor combined MRC-RFS and day 29 flow MRD data, classifying children into low (87% RFS), intermediate (62% RFS), or high risk (29% RFS) groups (P<0.0001). A 21 gene molecular classifier predictive of MRD could effectively substitute for day 29 flow MRD, yielding a combined classifier that similarly distinguished three risk groups at pre-treatment (low: 82% RFS; intermediate: 63% RFS; and high risk: 45% RFS) (P<0.0001). This combined molecular classifier was further validated on an independent cohort of 84 children with HR-ALL (P = 0.006). Conclusions. Molecular classifiers predictive of RFS and MRD can be used to distinguish distinct prognostic groups within HR-ALL, significantly improving risk classification schemes and the ability to prospectively identify children at diagnosis who will respond to or fail current treatment regimens. NOTE: Due to Children's Oncology Group (COG) restrictions, outcome and MRD data cannot be provided as part of the covariate data for this dataset at the present time. If you would like to arrange individual access to this data, please contact COG or the PI of this study, Dr. Cheryl Willman, at the University of New Mexico Cancer Center (cwillman@unm.edu) to arrange a collaboration. Unsupervised clustering and supervised risk classification analyses of 207 diagnostic samples and associated clinical covariate data. See the Summary for greater details. The data were analyzed using Microarray Suite version 5.0 (MAS 5.0) in the Affymetrix Gene Chip Operating Software Version 1.4. Probe masking was used (see 9906_TT207_Affymetrix_probe_mask.msk, linked below as a supplementary file). Otherwise all Affymetrix default parameter settings were used. Global scaling as the normalization method, with the default target intensity of 500, was used.
2009-06-25 | E-GEOD-11877 | biostudies-arrayexpress
Project description:To investigate the role of insulin-like growth factor-1 (IGF-1), in localized osteosarcoma, serum levels of IGF-1, IGFBP-2, and IGFBP-3 were measured in 224 similarly treated, newly diagnosed patients. We demonstrated that younger patients had lower concentrations of IGF-1 and IGFBP-3 compared to older (P?<?0.001) along with lower IGFBP-3:IGF-1 and IGFBP-2:IGF-1 ratios (P?<?0.001). IGFBP-2 did not correlate with age (P?=?0.16), yet IGFBP-2:IGF-1 ratios were higher in the younger population (P?<?0.001). These findings show that older patients have higher concentrations of free IGF-1. None of IGF-1, IGFBP-2, nor IGFBP-3 concentrations were associated with event-free nor overall survival.
| S-EPMC3946315 | biostudies-literature
Project description:PurposeThe use of radiographic response as the primary end point in phase II osteosarcoma trials may limit optimal detection of treatment response because of the calcified tumor matrix. We performed this study to determine if time to progression could be used as an end point for subsequent studies.Patients and methodsWe performed a retrospective analysis of outcome for patients with recurrent/refractory osteosarcoma enrolled in one of seven phase II trials conducted by the Children's Oncology Group and predecessor groups from 1997 to 2007. All trials used RECIST or WHO radiographic response criteria and the primary end point of response rate. The following potential prognostic factors-age, trial, number of prior chemotherapy regimens, sex, and race/ethnicity-were evaluated for their impact on event-free survival (EFS). We used data from a phase II study (AOST0221) of patients with osteosarcoma who were given inhaled granulocyte-macrophage colony-stimulating factor with first pulmonary recurrence who had an EFS as well as biologic end point to determine the historical disease control rate for patients with fully resected disease.ResultsIn each included trial, the drugs tested were determined to be inactive on the basis of radiographic response rates. The EFS for 96 patients with osteosarcoma and measurable disease was 12% at 4 months (95% CI, 6% to 19%). There was no significant difference in EFS across trials according to number of prior treatment regimens or patient age, sex, and ethnicity. The 12-month EFS for the 42 evaluable patients enrolled in AOST0221 was 20% (95% CI, 10% to 34%).ConclusionThe EFS was uniformly poor for children with recurrent/refractory osteosarcoma in these single-arm phase II trials. We have now constructed baseline EFS outcomes that can be used as a comparison for future phase II trials for recurrent osteosarcoma.
| S-EPMC5012712 | biostudies-literature
Project description:Although chemotherapy has improved outcome of osteosarcoma, 30-40% of patients succumb to this disease. Survivors experience substantial morbidity and mortality from anthracycline-induced cardiotoxicity. We hypothesized that the cardioprotectant dexrazoxane would (i) support escalation of the cumulative doxorubicin dose (600?mg/m(2)) and (ii) not interfere with the cytotoxicity of chemotherapy measured by necrosis grading in comparison to historical control data.Children and adolescents with nonmetastatic osteosarcoma were treated with MAP (methotrexate, doxorubicin, cisplatin) or MAPI (MAP/ifosfamide). Dexrazoxane was administered with all doxorubicin doses. Cardioprotection was assessed by measuring left ventricular fractional shortening. Interference with chemotherapy-induced cytotoxicity was determined by measuring tumor necrosis after induction chemotherapy. Feasibility of intensifying therapy with either high cumulative-dose doxorubicin or high-dose ifosfamide/etoposide was evaluated for "standard responders" (SR, <98% tumor necrosis at definitive surgery).Dexrazoxane did not compromise response to induction chemotherapy. With doxorubicin (450-600?mg/m(2)) and dexrazoxane, grade 1 or 2 left ventricular dysfunction occurred in five patients; 4/5 had transient effects. Left ventricular fractional shortening z-scores (FSZ) showed minimal reductions (0.0170 ?±? 0.009/week) over 78 weeks. Two patients (<1%) had secondary leukemia, one as a first event, a similar rate to what has been observed in prior trials. Intensification with high-dose ifosfamide/etoposide was also feasible.Dexrazoxane cardioprotection was safely administered. It did not impair tumor response or increase the risk of secondary malignancy. Dexrazoxane allowed for therapeutic intensification increasing the cumulative doxorubicin dose in SR to induction chemotherapy. These findings support the use of dexrazoxane in children and adolescents with osteosarcoma.
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