Cell Differentiation Trajectory-Associated Molecular Classification of Osteosarcoma.

This study aims to investigate the differentiation trajectory of osteosarcoma cells and to construct molecular subtypes with their respective characteristics and generate a multi-gene signature for predicting prognosis. Integrated single-cell RNA-sequencing (scRNA-seq) data, bulk RNA-seq data and microarray data from osteosarcoma samples were used for analysis. Via scRNA-seq data, time-related as well as differentiation-related genes were recognized as osteosarcoma tumor stem cell-related genes (OSCGs). In Gene Expression Omnibus (GEO) cohort, osteosarcoma patients were classified into two subtypes based on prognostic OSCGs and it was found that molecular typing successfully predicted overall survival, tumor microenvironment and immune infiltration status. Further, available drugs for influencing osteosarcoma via prognostic OSCGs were revealed. A 3-OSCG-based prognostic risk score signature was generated and by combining other clinic-pathological independent prognostic factor, stage at diagnosis, a nomogram was established to predict individual survival probability. In external independent TARGET cohort, the molecular types, the 3-gene signature as well as nomogram were validated. In conclusion, osteosarcoma cell differentiation occupies a crucial position in many facets, such as tumor prognosis and microenvironment, suggesting promising therapeutic targets for this disease.

Identification of a 3-gene signature based on differentially expressed invasion genes related to cancer molecular subtypes to predict the prognosis of osteosarcoma patients.

Invasion is a critical pathway leading to tumor metastasis. This study constructed an invasion-related polygenic signature to predict osteosarcoma prognosis. We initially determined two molecular subtypes of osteosarcoma, Cluster1 (C1) and Cluster2 (C2).. A 3 invasive-gene signature was established by univariate Cox analysis and least absolute shrinkage and selection operator (LASSO) Cox regression analysis of the differentially expressed genes (DEGs) between the two subtypes, and was validated in internal and two external data sets (GSE21257 and GSE39058). Patients were divided into high- and low-risk groups by their signature, and the prognosis of osteosarcoma patients in the high-risk group was poor. Based on the time-independent receiver operating characteristic (ROC) curve, the area under the curve (AUC) for 1-year and 2-year OS were higher than 0.75 in internal and external cohorts. This signature also showed a high accuracy and independence in predicting osteosarcoma prognosis and a higher AUC in predicting 1-year osteosarcoma survival than other four existing models. In a word, a 3 invasive gene-based signature was developed, showing a high performance in predicting osteosarcoma prognosis. This signature could facilitate clinical prognostic analysis of osteosarcoma.

Advances in targeted therapy for osteosarcoma based on molecular classification.

Osteosarcoma, a highly malignant tumor, is characterized by widespread and recurrent chromosomal and genetic abnormalities. In recent years, a number of elaborated sequencing analyses have made it possible to cluster the osteosarcoma based on the identification of candidate driver genes and develop targeted therapy. Here, we reviewed recent next-generation genome sequencing studies and advances in targeted therapies for osteosarcoma based on molecular classification. First, we stratified osteosarcomas into ten molecular subtypes based on genetic changes. And we analyzed potential targeted therapies for osteosarcoma based on the identified molecular subtypes. Finally, the development of targeted therapies for osteosarcoma investigated in clinical trials were further summarized and discussed. Therefore, we indicated the importance of molecular classification on the targeted therapy for osteosarcoma. And the stratification of patients based on the genetic characteristics of osteosarcoma will help to obtain a better therapeutic response to targeted therapies, bringing us closer to the era of personalized medicine.

Derivation and validation of risk groups in patients with osteosarcoma utilizing regression tree analysis.

BACKGROUND: For patients with osteosarcoma, apart from stage and primary site, we lack reliable prognostic factors for risk stratification at diagnosis. There is a need for further defined, discrete prognostic groups using presenting clinical features. METHODS: We analyzed a cohort of 3069 patients less than 50 years of age, diagnosed with primary osteosarcoma of the bone between 1986 and 2013 from the Surveillance, Epidemiology, and End Results (SEER) database. Patients were randomly split into test and validation cohorts. Optimal cut points for age, tumor size, and grade were identified using classification and regression tree analysis. Manual recursive partitioning was used to identify discrete prognostic groups within the test cohort. These groups were applied to the validation cohort, and overall survival was analyzed using Cox models, Kaplan Meier methods, and log-rank tests. RESULTS: After applying recursive partitioning to the test cohort, our initial model included six groups. Application of these groups to the validation cohort resulted in four final groups. Key risk factors included presence of metastases, tumor site, tumor grade, age, and tumor size. Patients with localized axial tumors were identified as having similar outcomes to patients with metastases. Age and tumor size were only prognostically important in patients with extremity tumors when assessed in the validation cohort. CONCLUSIONS: This analysis supports prior reports that patients with axial tumors are a high-risk group, and demonstrates the importance of age and tumor size in patients with appendicular tumors. Biologic and genetic markers are needed to further define subgroups in osteosarcoma.

Osteosarcoma Patients Classification Using Plain X-Rays and Metabolomic Data.

Osteosarcoma is the most common type of bone cancer. The primary means of osteosarcoma diagnosis is through evaluating plain x-rays. Using image analysis techniques, features that clinicians use to diagnose osteosarcoma can be quantified and studied using computer algorithms. In this paper, we classify benign tumor patients and osteosarcoma patients using both image features and metabolomic data. These two types of feature sets are processed with feature selection algorithms - recursive feature elimination and information gain. The selected features are then assessed by two classification models - random forest and support vector machine (SVM). The performances of the two models are evaluated and compared using receiver operating characteristic curves. The random forest classifier outperformed the SVM, with a sensitivity of .92 and a specificity of .78.

Generating lung-metastatic osteosarcoma targeting aptamers for in vivo and clinical tissue imaging.

Osteosarcoma (OS) is one of most malignant bone tumors in early adolescence, which is a highly metastatic cancer and pulmonary metastasis is the most common cause of death. Thus, the development of efficient approaches to discover potential compounds that target metastasis of OS remains a topic of considerable interest. In this study, subtractive Cell-SELEX was performed to screen OS metastasis specific DNA aptamers by using cell lines with similar tumorigenic potentials but opposite metastatic aggressiveness (highly metastatic 143B cells and non-metastatic U-2 OS cells as the target and negative cells, respectively). This in vitro selection generated an ssDNA aptamer LP-16 that exhibited high binding affinity to 143B cells with an equilibrium dissociation constant (Kd) of 56.73 ±â€¯7.750 nM. However, the aptamer LP-16 did not bind to the non-metastatic U-2 OS and normal hFOB 1.19 cells. We further preliminarily presumed the target molecules of aptamer LP-16 was a membrane protein on the cell surface by proteinase treatment. Furthermore, both in vivo fluorescence imaging and clinical tissue imaging also clearly demonstrated that LP-16 could achieve prominently targeting efficiency. Therefore, the ssDNA aptamer LP-16 generated here could be a promising molecular probe for OS metastasis diagnosis. We have developed subtractive Cell-SELEX to screen osteosarcoma metastasis specific DNA aptamers by using cell lines with similar tumorigenic potentials but opposite metastatic aggressiveness (highly metastatic 143B cells and non-metastatic U-2 OS cells as the target and negative cells, respectively).

Convolutional Neural Network for Histopathological Analysis of Osteosarcoma.

Pathologists often deal with high complexity and sometimes disagreement over osteosarcoma tumor classification due to cellular heterogeneity in the dataset. Segmentation and classification of histology tissue in H&E stained tumor image datasets is a challenging task because of intra-class variations, inter-class similarity, crowded context, and noisy data. In recent years, deep learning approaches have led to encouraging results in breast cancer and prostate cancer analysis. In this article, we propose convolutional neural network (CNN) as a tool to improve efficiency and accuracy of osteosarcoma tumor classification into tumor classes (viable tumor, necrosis) versus nontumor. The proposed CNN architecture contains eight learned layers: three sets of stacked two convolutional layers interspersed with max pooling layers for feature extraction and two fully connected layers with data augmentation strategies to boost performance. The use of a neural network results in higher accuracy of average 92% for the classification. We compare the proposed architecture with three existing and proven CNN architectures for image classification: AlexNet, LeNet, and VGGNet. We also provide a pipeline to calculate percentage necrosis in a given whole slide image. We conclude that the use of neural networks can assure both high accuracy and efficiency in osteosarcoma classification.

Chondroblastic and fibroblastic osteosarcoma of the jaws: Report of two cases and review of literature.

This study aims to report of two variants of gnathic osteosarcoma with highlights on the varied histopathological presentation of osteosarcomas (OS). OS present with diverse histological appearances. Despite significant advances in molecular pathogenesis and biomarkers, clinicopathologic correlation is still considered as the important criteria in diagnosis. Chondroblastic osteosarcoma in a 52-year-old female and fibroblastic osteosarcoma in a 35-year-old female. Osteosarcoma is a relatively rare disease of the oral and maxillofacial region. Regular screening and follow-up is highly recommended, as recurrence rates are higher. Thorough understanding of the histologic spectrum of osteosarcoma reduces the diagnostic difficulties in categorizing the OS and separating these neoplasms from benign bone diseases.

A Novel System for the Surgical Staging of Primary High-grade Osteosarcoma: The Birmingham Classification.

BACKGROUND: Chemotherapy response and surgical margins have been shown to be associated with the risk of local recurrence in patients with osteosarcoma. However, existing surgical staging systems fail to reflect the response to chemotherapy or define an appropriate safe metric distance from the tumor that will allow complete excision and closely predict the chance of disease recurrence. We therefore sought to review a group of patients with primary high-grade osteosarcoma treated with neoadjuvant chemotherapy and surgical resection and analyzed margins and chemotherapy response in terms of local recurrence. QUESTIONS/PURPOSES: (1) What predictor or combination of predictors available to the clinician can be assessed that more reliably predict the likelihood of local recurrence? (2) Can we determine a better predictor of local recurrence-free survival than the currently applied system of surgical margins? (3) Can we determine a better predictor of overall survival than the currently applied system of surgical margins? METHODS: This retrospective study included all patients with high-grade conventional osteosarcomas without metastasis at diagnosis treated at one center between 1997 and 2012 with preoperative chemotherapy followed by resection or amputation of the primary tumor who were younger than age 50 years with minimum 24-month followup for those still alive. A total of 389 participants matched the inclusion criteria. Univariate log-rank test and multivariate Cox analyses were undertaken to identify predictors of local recurrence-free survival (LRFS). The Birmingham classification was devised on the basis of two stems: the response to chemotherapy (good response = ≥ 90% necrosis; poor response = < 90% necrosis) and margins (< 2 mm or ≥ 2 mm). The 5-year overall survival rate was 67% (95% confidence interval [CI], 61%-71%) and 47 patients developed local recurrence (12%). RESULTS: Intralesional margins (hazard ratio [HR], 9.9; 95% CI, 1.2-82; p = 0.03 versus radical margin HR, 1) and a poor response to neoadjuvant chemotherapy (HR, 3.8; 95% CI, 1.7-8.4; p = 0.001 versus good response HR, 1) were independent risk factors for local recurrence (LR). The best predictor of LR, however, was a combination of margins ≤ 2 mm and a less than 90% necrosis response to chemotherapy (Birmingham 2b HR, 19.6; 95% CI, 2.6-144; p = 0.003 versus Birmingham 1a; margin >2 mm and more than 90% necrosis HR, 1). Two-stage Cox regression model and higher Harrell's C statistic demonstrate that the Birmingham classification was superior to the Musculoskeletal Tumor Society (MSTS) margin classification for predicting LR (Harrell's C statistic Birmingham classification 0.68, MSTS criteria 0.59). A difference in overall survival was seen between groups of the Birmingham classification (log-rank test p < 0.0001), whereas the MSTS margin system was not discriminatory (log-rank test p = 0.14). CONCLUSIONS: Based on these observations, we believe that a combination of the recording of surgical margins in millimeters and the response to neoadjuvant chemotherapy can more accurately predict the risk of local recurrence than the current MSTS system. A multicenter collaboration study initiated by the International Society of Limb Salvage is recommended to test the validity of the proposed classification and if these findings are confirmed, this classification system might be considered the standard practice in oncology centers treating patients with osteosarcomas and allow more effective communication of margin status for research. LEVEL OF EVIDENCE: Level IV, prognostic study.

A new subtype of high-grade mandibular osteosarcoma with RASAL1/MDM2 amplification.

In contrast to long bone osteosarcoma, mandibular osteosarcoma is highly heterogeneous and morphologically overlaps with benign tumors, obscuring diagnosis and treatment selection. Molecular characterization is difficult due to the paucity of available specimens of this rare disease. We aimed to characterize the spectrum of mandibular osteosarcoma using immunohistochemistry and molecular techniques (quantitative polymerase chain reaction and sequencing) and compare them with benign fibro-osseous lesions. Forty-nine paraffin-embedded mandible osteosarcoma tissue samples were collected retrospectively and compared with 10 fibrous dysplasia and 15 ossifying fibroma cases. These were analyzed for molecular markers thought to differ between the different diseases and subtypes: MDM2 (murine double-minute type 2) overexpression, GNAS (guanine nucleotide-binding protein/α subunit) mutations, and amplification of MDM2 and/or RASAL1 (RAS protein activator like 1). Five fibroblastic high-grade osteosarcoma subtypes showed MDM2 amplification, including 2 with a microscopic appearance of high-grade osteosarcoma with part low-grade osteosarcoma (differentiated/dedifferentiated osteosarcoma) and MDM2 overexpression. The other 3 contained a coamplification of MDM2 and RASAL1, a signature also described for juvenile ossifying fibroma, with no overexpression of MDM2. These were of the giant cell-rich high-grade osteosarcoma, with areas mimicking juvenile ossifying fibroma (ossifying fibroma-like osteosarcoma). Our results show that some diagnosed high-grade osteosarcomas are differentiated/dedifferentiated osteosarcomas and harbor an overexpression and amplification of MDM2. In addition, juvenile ossifying fibromas can potentially evolve into giant cell-rich high-grade osteosarcomas and are characterized by a RASAL1 amplification (osteosarcoma with juvenile ossifying fibroma-like genotype). Thus, the presence of a RASAL1 amplification in ossifying fibroma may indicate a requirement for closer follow-up and more aggressive management.

NELL-1 expression in benign and malignant bone tumors.

NELL-1 (NEL-like Protein 1) is an osteoinductive protein with increasing usage as a bone graft substitute in preclinical animal models. NELL-1 was first identified to have bone-forming properties by its overexpression in fusing cranial sutures. Since this time, addition of recombinant NELL-1 has been used to successfully induce bone formation in the calvarial, axial and appendicular skeleton. With increasing interest in the use of NELL-1 as a bone-graft substitute, we sought to examine the expression of NELL-1 in a wide spectrum of benign and malignant bone-forming skeletal tumors. Immunohistochemical expression was examined in human pathologic specimens. Quantitative RT-PCR evaluated NELL-1 expression among OS cell lines in vitro. Results showed NELL-1 expression in all bone tumors. Likewise, all OS cell lines demonstrated increased NELL-1 expression in comparison to non-lesional human bone marrow stromal cells. Among, benign bone tumors (osteoid osteoma and osteoblastoma), strong and diffuse staining was observed, which spatially correlated with markers of osteogenic differentiation. In contrast, a relative reduction in NELL-1 staining was observed in osteosarcoma, accompanied by increased variation between tumors. Among osteosarcoma specimens, NELL-1 expression did not correlate well with markers of osteogenic differentiation. Surprisingly, among osteosarcoma subtypes, fibroblastic osteosarcoma demonstrated the highest expression of NELL-1. In summary, NELL-1 demonstrates diffuse and reliable expression in benign but not malignant bone-forming skeletal tumors. Future studies will further define the basic biologic, diagnostic and prognostic importance of NELL-1 in bone neoplasms.

[Classical osteosarcoma in children and adolescent].

Classical osteosarcoma is one of the most common primary malignant bone tumors in children and adolescents. It more frequently occurs in the areas of the highest growth plate proliferation: limb long bones particularly in the distal femur (30%), proximal tibia (15%), and proximal humerus (15%). In the long bones, the tumor is located usually in the metaphysis (90%), less frequently in the diaphysis (9%), and very rarely in the epiphysis. This paper considers the clinical, radiological, and histological diagnosis, and prognosis in this pathology.

Polyostotic Chondroblastic Osteosarcoma in a Kestrel ( Falco tinnunculus ).

We report a case of polyostotic chondroblastic osteosarcoma in a kestrel ( Falco tinnunculus ) admitted to the Wildlife Rehabilitation and Rescue Center (Naples, Italy). A consolidated fracture of the left tibiotarsus bone and a deviation of the limb were evident. After radiographic, cytologic, and histopathologic examinations, a diagnosis of polyostotic chondroblastic osteosarcoma was made. To our knowledge, this is the first report on polyostotic chondroblastic osteosarcoma in a kestrel.

Extraskeletal chondroblastic osteosarcoma in the left atrium.

Primary cardiac extrasceletal osteosarcomas are uncommon tumours. They have aggressive behaviour and thus poor prognosis. This report describes a 40-year old female patient who was referred to our hospital with dyspnoea, weakness and syncopal attacks. Echocardiography and chest computed tomography showed a left atrial mass, and tumour excision revealed a cardiac chondroblastic osteosarcoma. After pathological diagnosis, she was scheduled for chemotherapy and radiotherapy by the related departments.

Modeling distinct osteosarcoma subtypes in vivo using Cre:lox and lineage-restricted transgenic shRNA.

Osteosarcoma is the most common primary cancer of bone and one that predominantly affects children and adolescents. Osteoblastic osteosarcoma represents the major subtype of this tumor, with approximately equal representation of fibroblastic and chondroblastic subtypes. We and others have previously described murine models of osteosarcoma based on osteoblast-restricted Cre:lox deletion of Trp53 (p53) and Rb1 (Rb), resulting in a phenotype most similar to fibroblastic osteosarcoma in humans. We now report a model of the most prevalent form of human osteosarcoma, the osteoblastic subtype. In contrast to other osteosarcoma models that have used Cre:lox mediated gene deletion, this model was generated through shRNA-based knockdown of p53. As is the case with the human disease the shRNA tumors most frequently present in the long bones and preferentially disseminate to the lungs; feature less consistently modeled using Cre:lox approaches. Our approach allowed direct comparison of the in vivo consequences of targeting the same genetic drivers using two different technologies, Cre:lox and shRNA. This demonstrated that the effects of Cre:lox and shRNA mediated knock-down are qualitatively different, at least in the context of osteosarcoma, and yielded distinct subtypes of osteosarcoma. Through the use of complementary genetic modification strategies we have established a model of the most common clinical subtype of osteosarcoma that was not previously represented and more fully recapitulated the clinical spectrum of this cancer.

Osteoblastic osteosarcoma in a Grey Mouse Lemur (Microcebus murinus) - short communication.

The Grey Mouse Lemur (Microcebus murinus) is a nocturnal lemur species that lives only in Madagascar. It is one of the most abundant lemur species and its native populations are not endangered, but animals belonging to this species are rarely exhibited in zoos. While tumours are quite frequently described in other primates, there are very few publications about neoplasia in lemurs. In this case report we describe a mandibular osteoblastic osteosarcoma in a Grey Mouse Lemur (Microcebus murinus). To the best of the authors' knowledge, this is the first scientific article describing osteosarcoma in a prosimian and also reporting a tumour in the mandible in this taxon.