Cell Differentiation Trajectory-Associated Molecular Classification of Osteosarcoma

Abstract

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.

Immune Microenvironment in Osteosarcoma: Components, Therapeutic Strategies and Clinical Applications

“…Xu et al. ( 117 ) divided osteosarcoma patients into two clusters based on osteosarcoma tumor stem cell-related genes. Cluster 1 had a higher immune infiltration score and a better prognosis than Cluster 2.…”

Knowledge atlas and emerging trends on ncRNAs of osteosarcoma: A bibliometric analysis

“…Cluster 4 majorly focused on osteosarcoma cell gene and differentiation. Osteosarcoma tumor stem cell–related genes and their signaling pathways had acted a vital role in the development of osteosarcoma and cell differentiations ( 47 , 48 ), which had been considered to be promising therapeutic targets for osteosarcoma and had been extensively studied in the past years. Cluster 5 was mainly about osteosarcoma biological behavior studies, including the invasion, migration, and proliferation of osteosarcoma, which were the basic and crucial research objectives.…”

Development and validation of a prognostic model based on a single-cell RNA-seq in Wilms tumor in children

“…To evaluate the predictive power of the prognostic model, this study first performed Kaplan-Meier survival analysis on the high-risk and low-risk groups; second, the receiver operator characteristic (ROC) curves of the 3-and 5-year disease-free survival (DFS) of WT patients were drawn, and the area under the curve (AUC) values of the 3-and 5-year DFS were calculated by the ''survival'' and ''timeROC'' packages. 16 When the AUC value is less than 0.5, the accuracy of the model is not significant; when the AUC value is greater than 0.7, the accuracy of the model is moderate; when the AUC value is greater than 0.9, the accuracy of the model is quite high.…”

“…Combining prognostic genes and clinical features, a nomogram was generated to predict prognosis of WT patients. The nomogram was constructed according to the regression coefficients obtained from the multivariate COX regression analysis using the ''rms'' package of R. 16 The nomogram prediction probabilities against the observed rates was visualized by drawing a calibration curve, and the predictive power of the nomogram was evaluated by the ROC curve. The proportional hazard assumption was tested by Kaplan-Meier curves.…”