The Role of FAS Receptor Methylation in Osteosarcoma Metastasis.

Osteosarcoma is the most frequent primary malignant bone tumor with an annual incidence of about 400 cases in the United States. Osteosarcoma primarily metastasizes to the lungs, where FAS ligand (FASL) is constitutively expressed. The interaction of FASL and its cell surface receptor, FAS, triggers apoptosis in normal cells; however, this function is altered in cancer cells. DNA methylation has previously been explored as a mechanism for altering FAS expression, but no variability was identified in the CpG island (CGI) overlapping the promoter. Analysis of an expanded region, including CGI shores and shelves, revealed high variability in the methylation of certain CpG sites that correlated significantly with FAS mRNA expression in a negative manner. Bisulfite sequencing revealed additional CpG sites, which were highly methylated in the metastatic LM7 cell line but unmethylated in its parental non-metastatic SaOS-2 cell line. Treatment with the demethylating agent, 5-azacytidine, resulted in a loss of methylation in CpG sites located within the FAS promoter and restored FAS protein expression in LM7 cells, resulting in reduced migration. Orthotopic implantation of 5-azacytidine treated LM7 cells into severe combined immunodeficient mice led to decreased lung metastases. These results suggest that DNA methylation of CGI shore sites may regulate FAS expression and constitute a potential target for osteosarcoma therapy, utilizing demethylating agents currently approved for the treatment of other cancers.

Integrated DNA Copy Number and Expression Profiling Identifies IGF1R as a Prognostic Biomarker in Pediatric Osteosarcoma.

Osteosarcoma is a primary malignant bone tumor arising from bone-forming mesenchymal cells in children and adolescents. Despite efforts to understand the biology of the disease and identify novel therapeutics, the survival of osteosarcoma patients remains dismal. We have concurrently profiled the copy number and gene expression of 226 osteosarcoma samples as part of the Strategic Partnering to Evaluate Cancer Signatures (SPECS) initiative. Our results demonstrate the heterogeneous landscape of osteosarcoma in younger populations by showing the presence of genome-wide copy number abnormalities occurring both recurrently among samples and in a high frequency. Insulin growth factor receptor 1 (IGF1R) is a receptor tyrosine kinase which binds IGF1 and IGF2 to activate downstream pathways involved in cell apoptosis and proliferation. We identify prevalent amplification of IGF1R corresponding with increased gene expression in patients with poor survival outcomes. Our results substantiate previously tenuously associated copy number abnormalities identified in smaller datasets (13q34+, 20p13+, 4q35-, 20q13.33-), and indicate the significance of high fibroblast growth factor receptor 2 (FGFR2) expression in distinguishing patients with poor prognosis. FGFR2 is involved in cellular proliferation processes such as division, growth and angiogenesis. In summary, our findings demonstrate the prognostic significance of several genes associated with osteosarcoma pathogenesis.

Pulse dynamics in reaction-diffusion equations with strong spatially localized impurities.

In this article, a general geometric singular perturbation framework is developed to study the impact of strong, spatially localized, nonlinear impurities on the existence, stability and bifurcations of localized structures in systems of linear reaction-diffusion equations. By taking advantage of the multiple-scale nature of the problem, we derive algebraic conditions determining the existence and stability of pinned single- and multi-pulse solutions. Our methods enable us to explicitly control the spectrum associated with a (multi-)pulse solution. In the scalar case, we show how eigenvalues may move in and out of the essential spectrum and that Hopf bifurcations cannot occur. By contrast, even a pinned 1-pulse solution can undergo a Hopf bifurcation in a two-component system of linear reaction-diffusion equations with (only) one impurity.This article is part of the theme issue 'Stability of nonlinear waves and patterns and related topics'.

Therapeutic implications of CD1d expression and tumor-infiltrating macrophages in pediatric medulloblastomas.

Immunobiology of medulloblastoma (MB), the most common malignant brain tumor in children, is poorly understood. Although tumor cells in some MBs were recently shown to express CD1d and be susceptible to Vα24-invariant natural killer T (NKT)-cell cytotoxicity, the clinical relevance of CD1d expression in MB patients remains unknown. We investigated the expression of CD1d in pediatric MBs and correlated with molecular and clinical characteristics. Specifically, we explored if NKT cell therapy can be targeted at a subset of pediatric MBs with poorer prognosis. Particularly, infantile MBs have a worse outcome because radiotherapy is delayed to avoid neurocognitive sequelae. Immunohistochemistry for CD1d was performed on a screening set of 38 primary pediatric MBs. Gene expression of the membrane form of M2 macrophage marker, CD163, was studied in an expanded cohort of 60 tumors. Outcome data was collected prospectively. Thirteen of 38 MBs (34.2 %) expressed CD1d on immunohistochemistry. CD1d was expressed mainly on MB tumor cells, and on some tumor-associated macrophages. Majority (18/22, 82 %) of non sonic-hedgehog/Wingless-activated MBs (group 3 and 4) were CD1d-negative (p = 0.05). A subset of infantile MBs (4/9, 44.4 %) expressed CD1d. Macrophages infiltrating MB expressed CD163 apart from CD1d. Molecular subtypes demonstrated statistical differences in CD163 expression, SHH-tumors were the most enriched (p = 0.006). Molecular and clinical subtypes of pediatric MB exhibit distinct differences in CD1d expression, which have important therapeutic implications. High CD1d expression in infantile MBs offers potential new immunotherapeutic treatment with NKT cell therapy in infants, where treatment is suboptimal due delayed radiotherapy.

Implications of tumor location on subtypes of medulloblastoma.

BACKGROUND: Medulloblastoma (MB) comprises of four molecular subtypes, Sonic hedgehog (SHH), Wingless (WNT), Groups 3 and 4. WNT-subtype MBs were found to arise from midline of the brainstem occupying the fourth ventricle while SHH-subtype occupied the cerebellar hemisphere in a small subset of patients. PROCEDURE: We tested this hypothesis in a large cohort of pediatric MBs comprising of all four molecular subtypes. RESULTS: We validated in the first comprehensive analysis of tumor location of 60 human MBs representative of the four molecular subtypes, that hemispheric tumors are significantly associated with SHH-subtype MBs while midline tumors with WNT-subtype, Group 3 and 4 MBs (P < 0.001). Nearly half of SHH-subtype MBs were midline. CONCLUSIONS: Tumor location should not be generalized to MB subtypes. SHH-subtype MBs are not exclusively hemispheric and hemispheric MBs are not always SHH-activated. It is imperative to identify subtypes in conjunction with tumor location when exploring currently available targeted therapy.

Assessing the mechanism of citywide test-trace-isolate Zero-COVID policy and exit strategy of COVID-19 pandemic.

BACKGROUND: Countries that aimed for eliminating the cases of COVID-19 with test-trace-isolate policy are found to have lower infections, deaths, and better economic performance, compared with those that opted for other mitigation strategies. However, the continuous evolution of new strains has raised the question of whether COVID-19 eradication is still possible given the limited public health response capacity and fatigue of the epidemic. We aim to investigate the mechanism of the Zero-COVID policy on outbreak containment, and to explore the possibility of eradication of Omicron transmission using the citywide test-trace-isolate (CTTI) strategy. METHODS: We develop a compartmental model incorporating the CTTI Zero-COVID policy to understand how it contributes to the SARS-CoV-2 elimination. We employ our model to mimic the Delta outbreak in Fujian Province, China, from September 10 to October 9, 2021, and the Omicron outbreak in Jilin Province, China for the period from March 1 to April 1, 2022. Projections and sensitivity analyses were conducted using dynamical system and Latin Hypercube Sampling/ Partial Rank Correlation Coefficient (PRCC). RESULTS: Calibration results of the model estimate the Fujian Delta outbreak can end in 30 (95% confidence interval CI: 28-33) days, after 10 (95% CI: 9-11) rounds of citywide testing. The emerging Jilin Omicron outbreak may achieve zero COVID cases in 50 (95% CI: 41-57) days if supported with sufficient public health resources and population compliance, which shows the effectiveness of the CTTI Zero-COVID policy. CONCLUSIONS: The CTTI policy shows the capacity for the eradication of the Delta outbreaks and also the Omicron outbreaks. Nonetheless, the implementation of radical CTTI is challenging, which requires routine monitoring for early detection, adequate testing capacity, efficient contact tracing, and high isolation compliance, which constrain its benefits in regions with limited resources. Moreover, these challenges become even more acute in the face of more contagious variants with a high proportion of asymptomatic cases. Hence, in regions where CTTI is not possible, personal protection, public health control measures, and vaccination are indispensable for mitigating and exiting the COVID-19 pandemic.

Maximizing the potential of aggressive mouse tumor models in preclinical drug testing.

Atypical teratoid rhabdoid tumor (ATRT) is an aggressive embryonal brain tumor among infants and young children. Two challenges exist for preclinical testing in ATRT. First, genetically quiet, ATRT is a difficult tumor to target molecularly. Tumor cells need to divide to propagate tumor growth-intercepting the common crossroads in cell cycle progression is a feasible strategy. KIF11 is needed for bipolar spindle formation in metaphase. We identified KIF11 as a universal target of all ATRT-molecular-subtypes. Ispinesib, a KIF11-inhibitor, effectively inhibited tumor proliferation in all seven cell lines. A second challenge-a major challenge in preclinical drug testing in-vivo among aggressive tumor models, is the narrow therapeutic window to administer drugs within the limited murine lifespan. Our most aggressive ATRT tumor model was lethal in all mice within ~ 1 month of tumor implantation. Such short-surviving mouse models are difficult to employ for preclinical drug testing due to the narrow time window to administer drugs. To overcome this time restriction, we developed a clinical staging system which allowed physically-fit mice to continue treatment, in contrast to the conventional method of fixed drug-dose-duration regimen in preclinical testing which will not be feasible in such short-surviving mouse models. We validated this approach in a second embryonal brain tumor, medulloblastoma. This is a clinically relevant, cost-efficient approach in preclinical testing for cancer and non-cancer disease phenotypes. Widely used preclinical mouse models are not the most accurate and lack the aggressive tumor spectrum found within a single tumor type. Mice bearing the most aggressive tumor spectrum progress rapidly in the limited murine life-span, resulting in a narrow therapeutic window to administer drugs, and are thus difficult to employ in preclinical testing. Our approach overcomes this challenge. We discovered ispinesib is efficacious against two embryonal brain tumor types.

Relevance of a TCGA-derived Glioblastoma Subtype Gene-Classifier among Patient Populations.

Glioblastoma multiforme (GBM), a deadly cancer, is the most lethal and common malignant brain tumor, and the leading cause of death in adult brain tumors. While genomic data continues to rocket, clinical application and translation to patient care are lagging behind. Big data now deposited in the TCGA network offers a window to generate novel clinical hypotheses. We hypothesized that a TCGA-derived gene-classifier can be applied across different gene profiling platforms and population groups. This gene-classifier validated three robust GBM-subtypes across six different platforms, among Caucasian, Korean and Chinese populations: Three Caucasian-predominant TCGA-cohorts (Affymetrix U133A = 548, Agilent Custom-Array = 588, RNA-seq = 168), and three Asian-cohorts (Affymetrix Human Gene 1.0ST-Array = 61, Illumina = 52, Agilent 4 × 44 K = 60). To understand subtype-relevance in patient therapy, we investigated retrospective TCGA patient clinical sets. Subtype-specific patient survival outcome was similarly poor and reflected the net result of a mixture of treatment regimens with/without surgical resection. As a proof-of-concept, in subtype-specific patient-derived orthotopic xenograft (PDOX) mice, Classical-subtype demonstrated no survival difference comparing radiation-therapy versus temozolomide monotherapies. Though preliminary, a PDOX model of Proneural/Neural-subtype demonstrated significantly improved survival with temozolomide compared to radiation-therapy. A larger scale study using this gene-classifier may be useful in clinical outcome prediction and patient selection for trials based on subtyping.

Patched haploinsufficient mouse rhabdomyosarcoma overexpress secreted phosphoprotein 1 and matrix metalloproteinases.

Rhabdomyosarcoma is the most common soft tissue sarcoma of childhood. Improving the management of rhabdomyosarcoma requires a better understanding of growth regulation. Patched haploinsufficient (Ptch+/-) mice spontaneously develop soft tissue sarcomas that resemble human rhabdomyosarcomas. Using microarray profiling and quantitative real-time reverse transcriptase polymerase chain reaction, we identified candidate genes differentially expressed in Ptch+/- mouse rhabdomyosarcoma relative to mature muscle. Overexpressed genes include Secreted Phosphoprotein 1 (Spp1, Osteopontin), and Matrix Metalloproteinases-2 and -14 (Mmp2 and Mmp14). Spp1 is an integrin-binding phosphoglycoprotein upregulated in carcinomas, and Mmps regulate tumour invasion. Immunochemical analyses of murine and human rhabdomyosarcoma specimens confirmed increased expression of Spp1, Mmp2, Mmp14, nuclear factor-kappa B (NF-kappaB) p65 and its phosphorylated active isoform. Neutralising Spp1 antibody decreased Mmp14 RNA in murine rhabdomyosarcoma cultures, indicating a positive regulatory role for extracellular Spp1. Plasma from rhabdomyosarcoma patients display elevated levels of SPP1. These results implicate Spp1, NF-kappaB, and Mmp activation as a putative signalling pathway involved in rhabdomyosarcoma growth.

Expression profiles of osteosarcoma that can predict response to chemotherapy.

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 > or = 90% necrosis (good responders), have a much better prognosis than those with < 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 < 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.

Biomarker significance of plasma and tumor miR-21, miR-221, and miR-106a in osteosarcoma.

Osteosarcoma is the most common malignant bone tumor in children and young adults. Despite the use of surgery and multi-agent chemotherapy, osteosarcoma patients who have a poor response to chemotherapy or develop relapses have a dismal outcome. Identification of biomarkers for active disease may help to monitor tumor burden, detect early relapses, and predict prognosis in these patients. In this study, we examined whether circulating miRNAs can be used as biomarkers in osteosarcoma patients. We performed genome-wide miRNA profiling on a discovery cohort of osteosarcoma and control plasma samples. A total of 56 miRNAs were upregulated and 164 miRNAs were downregulated in osteosarcoma samples when compared to control plasma samples. miR-21, miR-221 and miR-106a were selected for further validation based on their known biological importance. We showed that all three circulating miRNAs were expressed significantly higher in osteosarcoma samples than normal samples in an independent cohort obtained from the Children's Oncology Group. Furthermore, we demonstrated that miR-21 was expressed significantly higher in osteosarcoma tumors compared with normal bone controls. More importantly, lower expressions of miR-21 and miR-221, but not miR-106a, significantly correlated with a poor outcome. In conclusion, our results indicate that miR-21, miR-221 and miR-106a were elevated in the circulation of osteosarcoma patients, whereas tumor expressions of miR-21 and miR-221 are prognostically significant. Further investigation of these miRNAs may lead to a better prognostic method and potential miRNA therapeutics for osteosarcoma.

Optimising the use of TRIzol-extracted proteins in surface enhanced laser desorption/ ionization (SELDI) analysis.

BACKGROUND: Research with clinical specimens is always hampered by the limited availability of relevant samples, necessitating the use of a single sample for multiple assays. TRIzol is a common reagent for RNA extraction, but DNA and protein fractions can also be used for other studies. However, little is known about using TRIzol-extracted proteins in proteomic research, partly because proteins extracted from TRIzol are very resistant to solubilization. RESULTS: To facilitate the use of TRIzol-extracted proteins, we first compared the ability of four different common solubilizing reagents to solubilize the TRIzol-extracted proteins from an osteosarcoma cell line, U2-OS. Then we analyzed the solubilized proteins by Surface Enhanced Laser Desorption/Ionization technique (SELDI). The results showed that solubilization of TRIzol-extracted proteins with 9.5 M Urea and 2% CHAPS ([3-[(3-cholamidopropyl)-dimethylammonio]propanesulfonate]) (UREA-CHAPS) was significantly better than the standard 1% SDS in terms of solubilization efficiency and the number of detectable ion peaks. Using three different types of SELDI arrays (CM10, H50, and IMAC-Cu), we demonstrated that peak detection with proteins solubilized by UREA-CHAPS was reproducible (r > 0.9). Further SELDI analysis indicated that the number of ion peaks detected in TRIzol-extracted proteins was comparable to a direct extraction method, suggesting many proteins still remain in the TRIzol protein fraction. CONCLUSION: Our results suggest that UREA-CHAPS performed very well in solubilizing TRIzol-extracted proteins for SELDI applications. Protein fractions left over after TRIzol RNA extraction could be a valuable but neglected source for proteomic or biochemical analysis when additional samples are not available.

Allelic imbalance analysis by high-density single-nucleotide polymorphic allele (SNP) array with whole genome amplified DNA.

Besides their use in mRNA expression profiling, oligonucleotide microarrays have also been applied to single-nucleotide polymorphism (SNP) and loss of heterozygosity (LOH) or allelic imbalance studies. In this report, we evaluate the reliability of using whole genome amplified DNA for analysis with an oligonucleotide microarray containing 11 560 SNPs to detect allelic imbalance and chromosomal copy number abnormalities. Whole genome SNP analyses were performed with DNA extracted from osteosarcoma tissues and patient-matched blood. SNP calls were then generated by Affymetrix GeneChip DNA Analysis Software. In two osteosarcoma cases, using unamplified DNA, we identified 793 and 1070 SNP loci with allelic imbalance, respectively. In a parallel experiment with amplified DNA, 78% and 83% of these SNP loci with allelic imbalance was detected. The average false-positive rate is 13.8%. Furthermore, using the Affymetrix GeneChip Chromosome Copy Number Tool to analyze the SNP array data, we were able to detect identical chromosomal regions with gain or loss in both amplified and unamplified DNA at cytoband resolution.

A systems biology approach reveals common metastatic pathways in osteosarcoma.

BACKGROUND: Osteosarcoma (OS) is the most common malignant bone tumor in children and adolescents. The survival rate of patients with metastatic disease remains very dismal. Nevertheless, metastasis is a complex process and a single-level analysis is not likely to identify its key biological determinants. In this study, we used a systems biology approach to identify common metastatic pathways that are jointly supported by both mRNA and protein expression data in two distinct human metastatic OS models. RESULTS: mRNA expression microarray and N-linked glycoproteomic analyses were performed on two commonly used isogenic pairs of human metastatic OS cell lines, namely HOS/143B and SaOS-2/LM7. Pathway analysis of the differentially regulated genes and glycoproteins separately revealed pathways associated to metastasis including cell cycle regulation, immune response, and epithelial-to-mesenchymal-transition. However, no common significant pathway was found at both genomic and proteomic levels between the two metastatic models, suggesting a very different biological nature of the cell lines. To address this issue, we used a topological significance analysis based on a "shortest-path" algorithm to identify topological nodes, which uncovered additional biological information with respect to the genomic and glycoproteomic profiles but remained hidden from the direct analyses. Pathway analysis of the significant topological nodes revealed a striking concordance between the models and identified significant common pathways, including "Cytoskeleton remodeling/TGF/WNT", "Cytoskeleton remodeling/Cytoskeleton remodeling", and "Cell adhesion/Chemokines and adhesion". Of these, the "Cytoskeleton remodeling/TGF/WNT" was the top ranked common pathway from the topological analysis of the genomic and proteomic profiles in the two metastatic models. The up-regulation of proteins in the "Cytoskeleton remodeling/TGF/WNT" pathway in the SaOS-2/LM7 and HOS/143B models was further validated using an orthogonal Reverse Phase Protein Array platform. CONCLUSIONS: In this study, we used a systems biology approach by integrating genomic and proteomic data to identify key and common metastatic mechanisms in OS. The use of the topological analysis revealed hidden biological pathways that are known to play critical roles in metastasis. Wnt signaling has been previously implicated in OS and other tumors, and inhibitors of Wnt signaling pathways are available for clinical testing. Further characterization of this common pathway and other topological pathways identified from this study may lead to a novel therapeutic strategy for the treatment of metastatic OS.

Identification and gene expression profiling of tumor-initiating cells isolated from human osteosarcoma cell lines in an orthotopic mouse model.

In the cancer stem cell model a cell hierarchy has been suggested as an explanation for intratumoral heterogeneity and tumor formation is thought to be driven by this tumor cell subpopulation. The identification of cancer stem cells in osteosarcoma (OS) and the biological processes dysregulated in this cell subpopulation, also known as tumor-initiating cells (TICs), may provide new therapeutic targets. The goal of this study, therefore, was to identify and characterize the gene expression profiles of TICs isolated from human OS cell lines. We analyzed the self-renewal capacity of OS cell lines and primary OS tumors based upon their ability to form sphere-like structures (sarcospheres) under serum-starving conditions. TICs were identify from OS cell lines using the long-term label retention dye PKH26. OS TICs and the bulk of tumor cells were isolated and used to assess their ability to initiate tumors in NOD/SCID mice. Gene expression profiles of OS TICs were obtained from fresh orthotopic tumor samples. We observed that increased sarcosphere efficiency correlated with an enhanced tumorigenic potential in OS. PKH26Hi cells were shown to constitute OS TICs based upon their capacity to form more sarcospheres, as well as to generate both primary bone tumors and lung metastases efficiently in NOD/SCID mice. Genomic profiling of OS TICs revealed that both bone development and cell migration processes were dysregulated in this tumor cell subpopulation. PKH26 labeling represents a valuable tool to identify OS TICs and gene expression analysis of this tumor cell compartment may identify potential therapeutic targets.

Plasma proteome predicts chemotherapy response in osteosarcoma patients.

Osteosarcoma is the most common malignant bone tumor that affects hundreds of children and young adults every year. The major prognostic factor in patients with localized osteosarcoma is the development of resistance towards pre-operative chemotherapy. However, modifications of post-operative chemotherapy based on the histological response have not significantly improved the outcome of patients. Thus, it would be of tremendous clinical value if the poor responders could be identified at the time of diagnosis, so that ineffective therapy can be prevented and intensified or alternative therapy could be provided to improve their outcome. We hypothesized that plasma proteomic profiles could be used to distinguish good from poor responders prior to the start of treatment. In order to test this hypothesis, we analyzed the proteomic profiles in two sets of plasma samples (n=54) from osteosarcoma patients collected before (n=27) and after (n=27) pre-operative chemotherapy. Using a linear support vector machine algorithm and external leave-one-out cross validation, we developed two classifiers that classified good and poor responders with an equal accuracy of 85% (p<0.01 after 5000 permutations) in both sets of plasma samples. In order to understand the biological basis of the classifiers, we further identified and validated two plasma proteins, serum amyloid protein A and transthyretin, in the classifiers. Our results suggest that plasma proteomic profiles can predict chemotherapy response before treatment as accurately as after treatment. Our study could lead to the development of a simple blood test that can predict chemotherapy response in osteosarcoma patients. Since the two identified proteins are involved in innate immunity, our findings are corroborated by the notion that boosting the innate immunity in conjunction with chemotherapy, achieves a better anti-tumor activity, thus improving the overall survival of osteosarcoma patients.

MMP13, Birc2 (cIAP1), and Birc3 (cIAP2), amplified on chromosome 9, collaborate with p53 deficiency in mouse osteosarcoma progression.

Osteosarcoma is the primary malignant cancer of bone and particularly affects adolescents and young adults, causing debilitation and sometimes death. As a model for human osteosarcoma, we have been studying p53(+/-) mice, which develop osteosarcoma at high frequency. To discover genes that cooperate with p53 deficiency in osteosarcoma formation, we have integrated array comparative genomic hybridization, microarray expression analyses in mouse and human osteosarcomas, and functional assays. In this study, we found seven frequent regions of copy number gain and loss in the mouse p53(+/-) osteosarcomas but have focused on a recurrent amplification event on mouse chromosome 9A1. This amplicon is syntenic with a similar chromosome 11q22 amplicon identified in several human tumor types. Three genes on this amplicon, the matrix metalloproteinase gene MMP13 and the antiapoptotic genes Birc2 (cIAP1) and Birc3 (cIAP2), show elevated expression in mouse and human osteosarcomas. We developed a functional assay using clonal osteosarcoma cell lines transduced with lentiviral short hairpin RNA vectors to show that down-regulation of MMP13, Birc2, or Birc3 resulted in reduced tumor growth when transplanted into immunodeficient recipient mice. These experiments revealed that high MMP13 expression enhances osteosarcoma cell survival and that Birc2 and Birc3 also enhance cell survival but only in osteosarcoma cells with the chromosome 9A1 amplicon. We conclude that the antiapoptotic genes Birc2 and Birc3 are potential oncogenic drivers in the chromosome 9A1 amplicon.

Identification of a plasma proteomic signature to distinguish pediatric osteosarcoma from benign osteochondroma.

Osteosarcoma (OS) is the most common malignant bone tumor in children. To identify a plasma proteomic signature that can detect OS, we used SELDI MS to perform proteomic profiling on plasma specimens from 29 OS and 20 age-matched osteochondroma (OC) patients. Nineteen statistically significant ion peaks that were differentially expressed in OS when compared with OC patients were identified (p < 0.001 and false discovery rate < 10%). Using the proteomic profiles, we constructed a multivariate 3-nearest neighbors classifier to distinguish OS from OC patients with a sensitivity of 97% and a specificity of 80% based on external leave-one-out crossvalidation. Permutation test showed that the classification result was statistically significant (p < 0.00005). One of the proteins (m/z 11 704) in the proteomic signature was identified as serum amyloid protein A (SAA) by PMF. The higher plasma level of SAA in OS patients was further validated by Western blotting when compared to that of osteochrondroma patients and normal subjects as reference. The classifier based on this plasma proteomic signature may be useful to differentiate malignant bone cancer from benign bone tumors and for early detection of OS in high-risk individuals.

Characterization of an osteoblast-specific enhancer element in the CBFA1 gene.

Cbfa1 is a critical regulator of cell differentiation expressed only in the osteochondrogenic lineage. To define the molecular basis of this cell-specific expression we analyzed the murine Cbfa1 promoter. Here we show that the first 976 bp of this promoter are specifically active in osteoblastic cells. Within this region DNase I footprinting delineated a 40-bp area (CE1) protected differently by nuclear extracts from osteoblastic cells and from non-osteoblastic cells. When multimerized, CE1 conferred an osteoblast-specific activity to a heterologous promoter in DNA transfection experiments; this enhancing ability was conserved between mouse, rat, and human CE1 present in the respective Cbfa1 promoters. CE1 site-specific mutagenesis determined that it binds NF1- and AP1-like activities. Further analyses revealed that the NF1 site acts as a repressor in non-osteoblastic cells due to the binding of NF1-A, a NF1 isoform not expressed in osteoblastic cells. In contrast, the AP1 site mediates an osteoblast-specific activation caused by the preferential binding of FosB to CE1 in osteoblastic cells. In summary, this study identified an osteoblast-specific enhancer in the Cbfa1 promoter whose activity is achieved by the combination of an inhibitory and an activatory mechanism.