骨肿瘤是一种罕见的癌症,其位置主要在骨组织和软骨组织中。骨肿瘤主要分为良性和恶性两种类型。早期发现可以大大提高骨肿瘤患者的生存率,骨肿瘤引起的截肢危险可以大大降低。在这项研究中,我们首先在恶性和良性骨肿瘤患者和健康个体中筛选出差异最大的前25%血清miRNAs。然后使用无监督聚类和PCA检查骨肿瘤患者血清miRNAs的表达,结果表明,血清miRNAs的整体表达对良/恶性骨肿瘤患者的区分无效。随后,我们通过LASSOlogistic回归筛选了19种miRNA生物标志物,这些生物标志物可用于确定患者的良性/恶性骨肿瘤。使用ROC曲线验证这些基因。结果表明,有11个miRNAs可以准确区分单独的良/恶性骨肿瘤。这11个miRNA是,即,hsa-miR-192-5p,hsa-miR-137,hsa-miR-142-3p,hsa-miR-155-3p,hsa-miR-1205,hsa-miR-1273a,hsa-miR-3187-3p,hsa-miR-1255b-2-3p,hsa-miR-1288-5p,hsa-miR-6836-5p,和hsa-miR-6862-5p。接下来,我们使用logistic回归建立了诊断模型,并使用ROC曲线对诊断模型进行了验证。结果表明,该模型具有良好的诊断效能。然后,我们还验证了由这11种miRNA建立的诊断模型可以使用无监督聚类和PCA来区分良性/恶性骨肿瘤患者。最后,通过使用qPCR,我们验证了11种miRNAs在恶性和良性骨肿瘤患者血清中的表达,健康的志愿者。结果与公共数据库中miRNA的表达趋势一致。总之,我们检测了良性和恶性骨肿瘤患者血清miRNAs的差异表达,发现了11种miRNA生物标志物,可用于区分两者.
Bone tumor is a kind of rare cancer, the location of which is mainly in bone tissue as well as cartilage tissue. Bone tumor is mainly classified into benign and malignant types. The survival rate of patients with bone tumors can be considerably improved by early detection, and the danger of amputation caused by bone tumors can be greatly reduced. In this study, we first screened the top 25% serum miRNAs with the greatest variance in patients with malignant and benign bone tumor and healthy individuals. The expression of serum miRNAs in patients with bone tumor was then examined using unsupervised clustering and PCA, and the results revealed that the overall expression of serum miRNAs was ineffective in distinguishing patients with benign/malignant bone tumors. Subsequently, we screened 19 miRNA biomarkers that could be used to determine the benign/malignant bone tumor of patients by LASSO logistic regression. These genes were validated using ROC curves. Results showed that there were 11 miRNAs that could accurately distinguish benign/malignant bone tumor alone. These 11 miRNAs were, namely, hsa-miR-192-5p, hsa-miR-137, hsa-miR-142-3p, hsa-miR-155-3p, hsa-miR-1205, hsa-miR-1273a, hsa-miR-3187-3p, hsa-miR-1255b-2-3p, hsa-miR-1288-5p, hsa-miR-6836-5p, and hsa-miR-6862-5p. Next, we established a diagnostic model using logistic regression and validated the diagnostic model using ROC curves; the result of which showed that the model had good diagnostic efficacy. Then, we also verified that the diagnostic model established by these 11 miRNAs could distinguish patients with benign/malignant bone tumor using unsupervised clustering as well as PCA. Finally, by using qPCR, we validated the expression of 11 miRNAs in the serum of patients with malignant and benign bone tumors, as well as healthy volunteers. The results were consistent with the trend of miRNAs expression in public databases. In summary, we examined the differential expression of serum miRNAs in individuals with benign and malignant bone tumors and discovered 11 miRNA biomarkers that could be utilized to discriminate between the two.