Poly (lactic-co-glycolic acid)-encapsulated Endostar-loaded calcium phosphate cement as anti-tumor bone cement for the treatment of bone metastasis in lung cancer.

Lung cancer is one of the most common malignant tumors in the world. In approximately 30%-40% of lung cancer patients, bone metastases ensues with osteolytic destruction. Worse still, intractable pain, pathological fracture, and nerve compression caused by bone metastases are currently the bottleneck of research, diagnosis, and treatment of lung cancer. Therefore, the present study aims at investigating the effectiveness of a new composite material made of calcium phosphate cement (CPC) and Endostar on repairing bone defects in vitro and in vivo. As indicated in results, the mechanical properties of CPC+Endostar and CPC+PLGA+Endostar do not differ from those of pure CPC. The PLGA-embedded Endostar slow-release microspheres were designed and prepared, and were combined with CPC. Poly (lactic-co-glycolic acid (PLGA) is a biodegradable polymer material in vivo, so the effect on its mechanical properties is negligible. CPC+Endostar and CPC+PLGA+Endostar have been proved to inhibit cell proliferation, promote apoptosis and block cell cycle in G2 phase; the expression levels of osteoclast-related genes CXCL2, TGF-ß1, IGF-1, IL-6, and RANKL were significantly decreased while osteogenic ability and alkaline phosphatase activity observably enhanced. In vivo studies have revealed that the expression levels of TRAP, RANKL, and Caspase3 in CPC+PLGA+ENDO-treated tumor tissues after 3 weeks were higher than those in other groups with the prolongation of animal treatment time, while the expression levels of OPN and BCL2 were lower than those in other groups. In hematoxylin and eosin and TUNEL staining, 3 weeks of CPC+PLGA+ENDO-treatment yielded higher tissue necrosis and apoptosis than other groups; computed tomography and magnetic resonance imaging results showed the posterior edge bone damage reduced as a result of the CPC+PLGA+ENDO grafting in vertebral pedicle. Overall, the feasibility and reliability of CPC-loaded Endostar in the treatment of bone metastasis in lung cancer were investigated in this study, so as to promote the basic research and treatment of bone metastasis in lung cancer and other malignant tumors.

Application of cementoplasty in patients with symptomatic benign osteopathy disease.

BACKGROUND: The optimal treatment for some symptomatic, benign osteopathy lesions is yet to be identified. PURPOSE: To investigate the clinical efficiency of cementoplasty in managing symptomatic, benign osteopathy. MATERIAL AND METHODS: Between June 2006 and January 2020, we retrospectively enrolled 31 patients (10 men, 21 women; mean age = 46.5 ± 16.6 years; age range = 20-85 years), accounting for 34 treatment sites, who underwent percutaneous osteoplasty (14 treatment sites) and percutaneous vertebroplasty (20 treatment sites) with digital subtraction angiography (DSA) or DSA combined with computed tomography (CT). All the participants experienced different degrees of clinical symptoms with benign osteopathy lesions. The technical success of the procedure and occurrence of complications were recorded. Follow-up examinations were conducted to assess the treatment outcome using the MacNab criteria. RESULTS: All the participants had a diagnosis of benign osteopathy lesions before or after the cementoplasty. Surgery was successfully completed in all patients. Cement distributions were diffuse and homogeneous, with the complication of cement leakage occurring in 17.6% (6 of 34) of the lesions. The leakage occurred in the intervertebral disc (n = 1), the intra-articular space (n = 1), and the surrounding soft tissue (n = 4). Analysis of the treatment outcome using the MacNab criteria revealed that all patients showed improvement in their clinical symptoms to some extent and in the quality of life. CONCLUSION: Cementoplasty is an effective treatment for symptomatic, benign osteopathy, with the advantage of favorable clinical outcomes, and low complication rate.

Diagnostic performance of MR imaging in evaluating prognostic factors in patients with cervical cancer: a meta-analysis.

OBJECTIVES: This study aims to determine the diagnostic performance of conventional magnetic resonance imaging (MRI) in assessing the distance between the tumor and the internal os, stromal infiltration, lymph node metastasis, and parametrial invasion in patients with cervical cancer. METHODS: A systematic English-language literature search of conventional MRI in the evaluation of human cervical cancer was performed in the PubMed, Cochrane Library, Embase, and Web of Science databases from 1995 to 2018. The pooled sensitivity, specificity, diagnostic odds ratio (DOR), and positive and negative likelihood ratios (PLR and NLR) of all studies were calculated. The results were then plotted in a hierarchical summary receiver operating characteristic (HSROC) plot, and meta-regression and subgroup analyses of the parametrial invasion were also performed. RESULTS: The pooled sensitivity, specificity, DOR, PLR, and NLR were 86%, 97%, 167.91, 24.74, and 0.15, respectively, in evaluating the internal os involvement (6 studies, 454 patients); 87%, 91%, 73.41, 10.22, and 0.14, respectively, in evaluating the stromal infiltration (11 studies, 672 patients); 51%, 89%, 8.63, 4.72, and 0.55, respectively, in evaluating the lymph node metastasis (15 studies, 997 patients); and 75%, 92%, 34.01, 9.38, and 0.28, respectively, in evaluating the parametrial invasion (19 studies, 1748 patients). The meta-regression of the parametrial invasion showed that the application of contrast enhancement was a significant factor affected the heterogeneity (p = 0.039). CONCLUSIONS: Conventional MRI can accurately evaluate the distance between the tumor and the internal os, as well as stromal infiltration, and performs well in diagnosing the parametrial invasion. However, this method exhibited a limited ability in diagnosing the lymph node metastasis. KEY POINTS: • MRI can help clinicians to accurately assess the distance between the tumor and the internal os, stromal infiltration, and parametrial invasion in patients with uterine cervical neoplasms. • MRI exhibits a limited ability in diagnosing the lymph node metastasis. • Management of patients with uterine cervical neoplasms becomes more appropriate.

Integrative Bioinformatics Analysis Reveals That miR-524-5p/MEF2C Regulates Bone Metastasis in Prostate Cancer and Breast Cancer.

Bone metastases are highly prevalent in patients with advanced prostate cancer and breast cancer and have a serious impact on the survival time and quality of life of these patients. It has been reported that microRNAs (miRNAs) are expressed abnormally in different types of cancer and metastases. However, it remains unknown whether the underlying miRNAs are associated with prostate and breast cancer bone metastasis. Differentially expressed miRNAs (DE-miRNAs) and their potential targets in the metastatic process were identified by bioinformatics analysis. Additionally, qPCR confirmed that the miR-524-5p expression was downregulated in prostate and breast cancer cells. The overexpression of miR-524-5p restrained cell proliferation, invasion, and metastasis in prostate and breast cancer cells. Meanwhile, miR-524-5p could target and inhibit the expression of MEF2C, which was verified by a luciferase assay. In conclusion, our data strongly suggest that downregulation of miR-524-5p appears to be a precocious event in prostate and breast cancer, and the miR-524-5p/MEF2C axis plays a novel role in bone metastases from prostate and breast cancers.

Radiomics Nomogram in Assisting Lymphadenectomy Decisions by Predicting Lymph Node Metastasis in Early-Stage Endometrial Cancer.

Background: Lymph node metastasis (LNM) is an important risk factor affecting treatment strategy and prognosis for endometrial cancer (EC) patients. A radiomics nomogram was established in assisting lymphadenectomy decisions preoperatively by predicting LNM status in early-stage EC patients. Methods: A total of 707 retrospective clinical early-stage EC patients were enrolled and randomly divided into a training cohort and a test cohort. Radiomics features were extracted from MR imaging. Three models were built, including a guideline-recommended clinical model (grade 1-2 endometrioid tumors by dilatation and curettage and less than 50% myometrial invasion on MRI without cervical infiltration), a radiomics model (selected radiomics features), and a radiomics nomogram model (combing the selected radiomics features, myometrial invasion on MRI, and cancer antigen 125). The predictive performance of the three models was assessed by the area under the receiver operating characteristic (ROC) curves (AUC). The clinical decision curves, net reclassification index (NRI), and total integrated discrimination index (IDI) based on the total included patients to assess the clinical benefit of the clinical model and the radiomics nomogram were calculated. Results: The predictive ability of the clinical model, the radiomics model, and the radiomics nomogram between LNM and non-LNM were 0.66 [95% CI: 0.55-0.77], 0.82 [95% CI: 0.74-0.90], and 0.85 [95% CI: 0.77-0.93] in the training cohort, and 0.67 [95% CI: 0.56-0.78], 0.81 [95% CI: 0.72-0.90], and 0.83 [95% CI: 0.74-0.92] in the test cohort, respectively. The decision curve analysis, NRI (1.06 [95% CI: 0.81-1.32]), and IDI (0.05 [95% CI: 0.03-0.07]) demonstrated the clinical usefulness of the radiomics nomogram. Conclusions: The predictive radiomics nomogram could be conveniently used for individualized prediction of LNM and assisting lymphadenectomy decisions in early-stage EC patients.

Radiomics feature as a preoperative predictive of lymphovascular invasion in early-stage endometrial cancer: A multicenter study.

Background: The presence of lymphovascular space invasion (LVSI) has been demonstrated to be significantly associated with poor outcome in endometrial cancer (EC). No effective clinical tools could be used for the prediction of LVSI preoperatively in early-stage EC. A radiomics nomogram based on MRI was established to predict LVSI in patients with early-stage EC. Methods: This retrospective study included 339 consecutive patients with early-stage EC with or without LVSI from five centers. According to the ratio of 2:1, 226 and 113 patients were randomly assigned to a training group and a test group, respectively. Radiomics features were extracted from T1-weighted imaging (T1WI), T2-weighted imaging (T2WI), contrast-enhanced (CE), diffusion-weighted imaging (DWI), and apparent diffusion coefficient (ADC) maps. The radiomics signatures were constructed by using the Least Absolute Shrinkage and Selection Operator (LASSO) algorithm in the training group. The radiomics nomogram was developed using multivariable logistic regression analysis by incorporating radiomics signatures and clinical risk factors. The sensitivity, specificity, and AUC of the radiomics signatures, clinical risk factors, and radiomics nomogram were also calculated. Results: The individualized prediction nomogram was constructed by incorporating the radiomics signatures with the clinical risk factors (age and cancer antigen 125). The radiomics nomogram exhibited a good performance in discriminating between negative and positive LVSI patients with AUC of 0.89 (95% CI: 0.83-0.95) in the training group and of 0.85 (95% CI: 0.75-0.94) in the test group. The decision curve analysis indicated that clinicians could be benefit from the using of radiomics nomogram to predict the presence of LVSI preoperatively. Conclusion: The radiomics nomogram could individually predict LVSI in early-stage EC patients. The nomogram could be conveniently used to facilitate the treatment decision for clinicians.

An MRI radiomics nomogram improves the accuracy in identifying eligible candidates for fertility-preserving treatment in endometrioid adenocarcinoma.

It is difficult to identify eligible candidates for fertility-preserving treatment (FPT) among endometrioid adenocarcinoma (EAC) and atypical hyperplasia (AH) patients. Therefore, new approaches for improving the accuracy of candidate selection are warranted. From December 2014 to January 2020, 236 EAC/AH patients (age <50 and premenopausal) were retrospectively reviewed and randomly divided into the primary group (n=158) and validation group 1 (n=78). From February 2020 to December 2021, 51 EAC/AH patients were prospectively enrolled and formed the validation group 2. From the primary group, 385 features were extracted using pyradiomics from multiparameter magnetic resonance imaging (MRI) (including T2-weighted imaging, diffusion-weighted imaging, apparent diffusion coefficient, and contrast enhancement sequences) and 13 radiomics features were selected using a least absolute shrinkage and selection operator. A clinical model based on clinical information (myometrial invasion on MRI and tumor grade in curettage) and a radiomics nomogram by integrating clinical information with the radiomics features was developed to identify eligible candidates of FPT. For identifying eligible candidates of FPT, the areas under the receiver operating characteristic curve (AUCs) were 0.63 (95% confidence interval [CI]: 0.53-0.73) in the primary group, and 0.62 (95% CI: 0.45-0.78) and 0.69 (95% CI: 0.53-0.86) in validation groups 1 and 2, respectively, for the clinical model; were 0.86 (95% CI: 0.80-0.93) in the primary group, and 0.82 (95% CI: 0.71-0.93) and 0.94 (95% CI: 0.87-1.0) in validation groups 1 and 2, respectively, for the radiomics nomogram. With the help of radiomics nomogram, the treatment decision determined from the clinical model was revised in 45 EAC/AH patients. The net reclassification index (NRI) was 0.80 and integrated discrimination improvement (IDI) was 0.17, indicating that the nomogram could improve the accuracy in identifying eligible EAC/AH candidates for FPT.