A Novel Predictive Model Associated with Osteosarcoma Metastasis
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Abstract:
Long non-coding RNAs (lncRNAs) have diverse roles in modulating gene expression on both transcriptional and translational levels, but their involvement in osteosarcoma (OS) metastasis remains unknown.Transcriptional and clinical data were downloaded from TARGET datasets. A total of seven lncRNAs screened by univariate cox regression, lasso regression, and multivariate cox regression analysis were used to establish the OS metastasis model. The area under the receiver operating characteristic curve (AUC) was used to evaluate the model.The established model showed exceptional predictive performance (1 year: AUC = 0.92, 95% Cl = 0.83-0.99; 3 years: AUC = 0.87, 95% Cl = 0.79-0.96; 5 years: AUC = 0.86, 95% Cl = 0.76-0.96). Patients in the high group had a poor survival outcome than those in the low group (p < 0.0001). GSEA analysis revealed that "NOTCH_SIGNALING" and "WNT_BETA_CATENIN_SIGNALING" were significantly enriched and that resting dendritic cells were associated with AL512422.1, AL357507.1, and AC006033.2 (p < 0.05).Based on seven prognosis-related lncRNAs, we constructed a novel model with high reliability and accuracy for predicting metastasis in OS patients.Keywords:
Univariate
Lasso
Univariate analysis
Objective:To investigate the expression of c-kit in conventional osteosarcoma and their relationships with clinicopathological parameters and prognostic value.Methods: The expression of c-kit was determined in 40 patients with conventional osteosarcoma by immunohistochemistry.Their relationship with prognosis was statistically analyzed.Results:(1)The expression rate of c-kit in conventional osteosarcoma was 62.5%.(2)The conventional osteosarcoma with a high expression of c-kit was prone to recur locally.(3)The post-operative survival of patients with highly expressed c-kit was significantly lower than that of patients with lowly expressed c-kit.Conclusion: The expression of c-kit is related to the biological behavior of osteosarcoma in conventional osteosarcoma,and it is valuable in judging the prognosis and therapy for osteosarcoma.
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Objective to find resistant and sensitive osteosarcoma tumor tissue samples,so that to prepare for further looking for differences in protein.Methods Obtain the tissue of patients with osteosarcoma,osteosarcoma cells isolated and cultured in vitro drug sensitivity test cells,so as to identify drug-resistant and sensitive osteosarcoma tissue samples.Results Detection curve of osteosarcoma cells to various chemotherapy drugs and Found resistant and sensitive osteosarcoma tissue samples.Conclusion Osteosarcoma has different sensitivity to various chemotherapeutic drugs,Cisplatin is further appropriate drugs to look for differences in protein research.
Chemosensitivity assay
Chemotherapeutic drugs
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Introduction: Osteosarcoma usually originates in the metaphyseal region of long bone, but may also arise in the diaphyseal of long bone. Diaphyseal osteosarcoma is a rare cases account for <10% of all osteosarcoma. In some cases two or more osteosarcoma lesions are seen in the same patient, at the same time (Synchronous osteosarcoma). It’s unusual condition of osteosarcoma, they are found at a frequency of about 1–3% osteosarcoma cases.
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Osteosarcoma (OS) is a rare malignant bone tumor. It affects mostly young persons and has poor outcome with the present treatment. No improvement was observed since the introduction of chemotherapy. The better understanding of osteosarcoma development could indicate better management strategy. Repetitive DNA elements were found to play a role in cancer mechanism especially in epithelial tumors but not yet analyzed in osteosarcoma. We conducted the study to analyse the expression profile of repetitive elements (RE) in osteosarcoma. Methods: Fresh bone paired (tumor and normal bone) samples were obtained from excised parts of tumors of 18 patients with osteosarcoma. We performed sequencing of RNA extracted from 36 samples (18 tumor tissues and 18 normal bone for controls), mapped raw reads to the human genome and identified the REs. EdgeR package was used to analyse the difference in expression of REs between osteosarcoma and normal bone. Results: 82 REs were found differentially expressed (FDR < 0.05) between osteosarcoma and normal bone. Out of all significantly changed REs, 35 were upregulated and 47 were downregulated. HERVs (THE1C-int, LTR5, MER57F and MER87B) and satellite elements (HSATII, ALR-alpha) were the most significantly differential expressed elements between osteosarcoma and normal tissues. These results suggest significant impact of REs in the osteosarcoma. The role of REs should be further studied to understand the mechanism they have in the genesis of osteosarcoma.
Bone cancer
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Cases of unusual osteosarcoma comprising parosteal osteosarcoma, intraosseous well differentiated osteosarcoma, postradiation osteosarcoma, epithelioid osteosarcoma, and MFH-like osteosarcoma were reported. They were apparently differed from conventional osteosarcoma in the point of biologic activity and prognosis. Osteosarcoma is, therefore, considered as a heterogeneic tumor. It is important to make an exact diagnosis and to make an appropriate treatment depending on the diagnosis.
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Circular RNA
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Metachronous osteosarcomas (MOS) are currently defined as tumors that arise in a way and site unusual for typical metastasis. In this article, we reviewed the recent literature on the occurrence of metachronous osteosarcoma and presented a case from our center. Our patient, a 10-year-old girl, presented with metachronous osteoblastic osteosarcoma of the left distal femur ∼5 years after the successful treatment for osteosarcoma of the right distal femur. Even after several relapses, complete remission (CR) was achieved after the first osteosarcoma and after the metachronous osteosarcoma. The literature research revealed that metachronous osteosarcoma occurs in 3.4 to 5.4% of osteosarcoma patients. The time interval between the diagnosis of the initial osteosarcoma and the metachronous tumor ranged from 0.2 to 14.3 years (median 2.5 y). MOS appears to have differences in localization and metastatic spread, as well as a different survival pattern compared with primary osteosarcoma and osteosarcoma recurrence. Survival (median 4.3 y, range 0 to 24.6 y) appears to be associated with the time interval to diagnosis of MOS. In particular, early MOS (<24 mo after primary diagnosis) seem to have a poorer prognosis. Therefore, the occurrence of MOS at oncological unusual sites should be considered as a differential diagnosis in osteosarcoma survivors.
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Pathogenesis
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Conducting an extensive empirical study on short-term electricity price forecasting (EPF), involving state-of-the-art parsimonious expert models as benchmarks, datasets from 12 power markets and 32 multi-parameter regression models estimated via the lasso, we show that using the latter shrinkage approach can bring statistically significant accuracy gains compared to commonly-used EPF models. We also address the long-standing question on the optimal model structure for EPF. We provide evidence that despite a minor edge in predictive performance overall, the multivariate modeling approach does not uniformly outperform univariate models across all datasets, seasons of the year or hours of the day, and at times is outperformed by the latter. This may be an indication that combining advanced structures or the corresponding forecasts from both modeling classes may bring a further improvement in forecasting accuracy. Finally, we also analyze variable selection for the best performing multivariate and univariate high-dimensional lasso-type models, thus provide guidelines to structuring better performing forecasting model designs.
Univariate
Lasso
Electricity Price Forecasting
Predictive modelling
Predictive power
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