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1.
J Neurooncol ; 155(2): 143-152, 2021 Nov.
Artigo em Inglês | MEDLINE | ID: mdl-34599481

RESUMO

INTRODUCTION: Many patients with glioma experience surgery-related language impairment. This study developed a classification system to predict postoperative language prognosis. METHODS: Sixty-eight patients were retrospectively reviewed. Based on their location, tumors were subtyped as follows: (I) inferior frontal lobe or precentral gyrus; (II) posterior central gyrus or supramarginal gyrus (above the lateral fissure level); (III) posterior region of the superior or middle temporal gyri or supramarginal gyrus (below the lateral fissure level); and (IV) insular lobe. The distance from the tumor to the superior longitudinal fasciculus/arcuate fasciculus was calculated. The recovery of language function was assessed using the Western Aphasia Battery before surgery, and a comprehensive language test was conducted on the day of surgery; 3, 7, and 14 days after surgery. Our follow-up information of was the comprehensive language test from telephone interviews in 3 months after surgery. RESULTS: Thirty-three patients experienced transient language impairment within 1 week of surgery. Fourteen patients had permanent language impairment. Type II tumors, shorter distance from the tumor to the posterior superior longitudinal fasciculus/arcuate fasciculus, and isocitrate dehydrogenase mutations were risk factors for surgery-related language impairment. Regarding the presence or absence of permanent surgery-related language impairments, the cut-off distance between the tumor and posterior superior longitudinal fasciculus/arcuate fasciculus was 2.75 mm. CONCLUSIONS: According to our classification, patients with type II tumors had the worst language prognosis and longest recovery time. Our classification, based on tumor location, can reliably predict postoperative language status and may be used to guide tumor resection.

3.
Nanoscale ; 13(17): 8012-8016, 2021 May 06.
Artigo em Inglês | MEDLINE | ID: mdl-33884397

RESUMO

While photodynamic therapy (PDT) of cancer has attracted much recent attention, its general applications are limited by the shallow tissue penetration depth of short-wavelength photons and the low oxygen contents in typical solid tumors. Herein, we develop small molecule (BthB)-based nanoparticles (NPs) which not only generate heat for effective photothermal therapy (PTT), but also generate superoxide radicals (O2˙-) for hypoxia-overcoming photodynamic therapy (PDT) upon irradiation with an 808 nm laser. To the best of our knowledge, there are few reports of organic PDT agents which can work in hypoxia upon irradiation with photons having wavelengths longer than 800 nm. With the merits of NIR-excitability for better penetration depth, the BthB NPs are demonstrated both in vitro and in vivo to be highly effective for cancer ablation.


Assuntos
Nanopartículas , Neoplasias , Fotoquimioterapia , Humanos , Hipóxia , Nanomedicina , Neoplasias/tratamento farmacológico , Fármacos Fotossensibilizantes/uso terapêutico , Oxigênio Singlete , Superóxidos
4.
Comput Math Methods Med ; 2021: 5518209, 2021.
Artigo em Inglês | MEDLINE | ID: mdl-33927782

RESUMO

Antioxidant proteins perform significant functions in disease control and delaying aging which can prevent free radicals from damaging organisms. Accurate identification of antioxidant proteins has important implications for the development of new drugs and the treatment of related diseases, as they play a critical role in the control or prevention of cancer and aging-related conditions. Since experimental identification techniques are time-consuming and expensive, many computational methods have been proposed to identify antioxidant proteins. Although the accuracy of these methods is acceptable, there are still some challenges. In this study, we developed a computational model called ANPrAod to identify antioxidant proteins based on a support vector machine. In order to eliminate potential redundant features and improve prediction accuracy, 673 amino acid reduction alphabets were calculated by us to find the optimal feature representation scheme. The final model could produce an overall accuracy of 87.53% with the ROC of 0.7266 in five-fold cross-validation, which was better than the existing methods. The results of the independent dataset also demonstrated the excellent robustness and reliability of ANPrAod, which could be a promising tool for antioxidant protein identification and contribute to hypothesis-driven experimental design.


Assuntos
Antioxidantes/química , Proteínas/química , Algoritmos , Sequência de Aminoácidos , Análise por Conglomerados , Biologia Computacional , Bases de Dados de Proteínas , Humanos , Peptídeos/química , Curva ROC , Análise de Sequência de Proteína , Máquina de Vetores de Suporte
5.
Sci Rep ; 11(1): 4449, 2021 02 24.
Artigo em Inglês | MEDLINE | ID: mdl-33627737

RESUMO

Glioblastoma is the most common primary brain cancer and it is nearly impossible to remove the entire tumor with surgery or a single drug. EGFRvIII is the most frequent genetic change associated with glioblastoma, so EGFRvIII-based targeting therapies provide promise for treating glioblastoma. Herein, poly[2-methoxy-5-(2'-ethylhexyloxy)-p-phenylenevinylene] (PPV) was used as the core to prepare a conjugated polymer nanoparticle (PPVN) modified with anti-EGFRvIII (PPVN-A) that exhibited high ROS generation ability under white light irradiation. PPVN-A could target EGFRvIII-overexpressed tumor cells and damaged more than 90% of tumor cells with the light illumination while PPVN without modification exhibited no obvious cytotoxicity toward these cells under the same condition. Thus, the photodynamic treatment of glioblastoma cells using PPVN-A could be achieved, indicating the potential of anti-EGFRvIII-modified nanoparticles as a therapeutic material for treating glioblastoma in clinic.

6.
Talanta ; 217: 121021, 2020 Sep 01.
Artigo em Inglês | MEDLINE | ID: mdl-32498896

RESUMO

Circular RNAs (circRNAs), as a class of newly emerging biomarkers, have shown to be associated with many fundamental life processes and diseases, especially cancer. However, various limitations in currently available detection methods have seriously restricted the development of the studies associated with circRNA's biological functions and the diagnosis of diseases by using circRNA as the biomarker. By specifically designing a pair of stem-loop primers (SLPs) exactly recognize the junction sequence of circRNA, we firstly establish a SLP induced double exponential amplification method for sensitive and specific detection of circRNA with the ability to directly discriminate circRNA from linear RNA. Through the extension of SLPs during thermo cycles, one circRNA can generate a large amount of double stem-loop structure DNA which can initiate the subsequent isothermal amplification, leading to the sensitive detection of as low as 10 aM circRNA which is the most sensitive method for circRNA detection up to now. The proposed method has successfully applied to the detection of circRNA in many kinds of cancer cells in homogeneous solution without any separation step.


Assuntos
Técnicas de Amplificação de Ácido Nucleico , RNA Circular/genética , Biomarcadores/análise , Linhagem Celular Tumoral , Células HT29 , Humanos , Células K562 , Reação em Cadeia da Polimerase em Tempo Real
7.
Front Oncol ; 10: 235, 2020.
Artigo em Inglês | MEDLINE | ID: mdl-32231995

RESUMO

Purpose: The majority of patients with low-grade gliomas (LGGs) experience tumor-related epilepsy during the disease course. Our study aimed to build a radiomic prediction model for LGG-related epilepsy type based on magnetic resonance imaging (MRI) data. Methods: A total of 205 cases with LGG-related epilepsy were enrolled in the retrospective study and divided into training and validation cohorts (1:1) according to their surgery time. Seven hundred thirty-four radiomic features were extracted from T2-weighted imaging, including six location features. Pearson correlation coefficient, univariate area under curve (AUC) analysis, and least absolute shrinkage and selection operator regression were adopted to select the most relevant features for the epilepsy type to build a radiomic signature. Furthermore, a novel radiomic nomogram was developed for clinical application using the radiomic signature and clinical variables from all patients. Results: Four MRI-based features were selected from the 734 radiomic features, including one location feature. Good discriminative performances were achieved in both training (AUC = 0.859, 95% CI = 0.787-0.932) and validation cohorts (AUC = 0.839, 95% CI = 0.761-0.917) for the type of epilepsy. The accuracies were 80.4 and 80.6%, respectively. The radiomic nomogram also allowed for a high degree of discrimination. All models presented favorable calibration curves and decision curve analyses. Conclusion: Our results suggested that the MRI-based radiomic analysis may predict the type of LGG-related epilepsy to enable individualized therapy for patients with LGG-related epilepsy.

8.
Macromol Biosci ; 20(2): e1900301, 2020 02.
Artigo em Inglês | MEDLINE | ID: mdl-31762196

RESUMO

In this work, dual-mode antibacterial conjugated polymer nanoparticles (DMCPNs) combined with photothermal therapy (PTT) and photodynamic therapy (PDT) are designed and explored for efficient killing of ampicillin-resistant Escherichia coli (Ampr E. coli). The DMCPNs are self-assembled into nanoparticles with a size of 50.4 ± 0.6 nm by co-precipitation method using the photothermal agent poly(diketopyrrolopyrrole-thienothiophene) (PDPPTT) and the photosensitizer poly[2-methoxy-5-((2-ethylhexyl)oxy)-p-phenylenevinylene] (MEH-PPV) in the presence of poly(styrene-co-maleic anhydride) which makes nanoparticles disperse well in water via hydrophobic interactions. Thus, DMCPNs simultaneously possess photothermal effect and the ability of sensitizing oxygen in the surrounding to generate reactive oxygen species upon the illumination of light, which could easily damage resistant bacteria. Under combined irradiation of near-infrared light (550 mW cm-2 , 5 min) and white light (65 mW cm-2 , 5 min), DMCPNs with a concentration of 9.6 × 10-4 µm could reach a 93% inhibition rate against Ampr E. coli, which is higher than the efficiency treated by PTT or PDT alone. The dual-mode nanoparticles provide potential for treating pathogenic infections induced by resistant microorganisms in clinic.


Assuntos
Antibacterianos , Escherichia coli/crescimento & desenvolvimento , Hipertermia Induzida , Nanopartículas/química , Fotoquimioterapia , Fármacos Fotossensibilizantes , Antibacterianos/química , Antibacterianos/farmacologia , Humanos , Fármacos Fotossensibilizantes/química , Fármacos Fotossensibilizantes/farmacocinética
9.
Front Oncol ; 10: 606741, 2020.
Artigo em Inglês | MEDLINE | ID: mdl-33643908

RESUMO

The detection of mutations in telomerase reverse transcriptase promoter (pTERT) is important since preoperative diagnosis of pTERT status helps with evaluating prognosis and determining the surgical strategy. Here, we aimed to establish a radiomics-based machine-learning algorithm and evaluated its performance with regard to the prediction of mutations in pTERT in patients with World Health Organization (WHO) grade II gliomas. In total, 164 patients with WHO grade II gliomas were enrolled in this retrospective study. We extracted a total of 1,293 radiomics features from multi-parametric magnetic resonance imaging scans. Elastic net (used for feature selection) and support vector machine with linear kernel were applied in nested 10-fold cross-validation loops. The predictive model was evaluated by receiver operating characteristic and precision-recall analyses. We performed an unpaired t-test to compare the posterior predictive probabilities among patients with differing pTERT statuses. We selected 12 valuable radiomics features using nested 10-fold cross-validation loops. The area under the curve (AUC) was 0.8446 (95% confidence interval [CI], 0.7735-0.9065) with an optimal summed value of sensitivity of 0.9355 (95% CI, 0.8802-0.9788) and specificity of 0.6197 (95% CI, 0.5071-0.7371). The overall accuracy was 0.7988 (95% CI, 0.7378-0.8598). The F1-score was 0.8406 (95% CI, 0.7684-0.902) with an optimal precision of 0.7632 (95% CI, 0.6818-0.8364) and recall of 0.9355 (95% CI, 0.8802-0.9788). Posterior probabilities of pTERT mutations were significantly different between patients with wild-type and mutant TERT promoters. Our findings suggest that a radiomics analysis with a machine-learning algorithm can be useful for predicting pTERT status in patients with WHO grade II glioma and may aid in glioma management.

10.
Neuroradiology ; 61(11): 1229-1237, 2019 Nov.
Artigo em Inglês | MEDLINE | ID: mdl-31218383

RESUMO

PURPOSE: PTEN mutation status is a pivotal biomarker for glioblastoma. This study aimed to establish a radiomic signature to predict PTEN mutation status in patients with glioblastoma, and to investigate the genetic background behind this radiomic signature. METHODS: In this study, a total of 862 radiomic features were extracted from each patient. The training (n = 69) and validation (n = 40) sets were retrospectively collected from the Cancer Genome Atlas and the Chinese Glioma Genome Atlas, respectively. The minimum redundancy maximum relevance (mRMR) algorithm was used to select the best predictive features of PTEN status. A machine learning model was then built with the selected features using a support vector machine classifier. The predictive performance of each selected feature and the complete model were evaluated via the area under the curve from receiver operating characteristic analysis in both the training and validation sets. The genetic background underlying the radiomic signature was determined using radiogenomic analysis. RESULTS: Six features were selected using the mRMR algorithm, including two features derived from contrast-enhanced images and four features derived from T2-weighted images. The predictive performance of the machine learning model for the training and validation sets were 0.925 and 0.787, respectively, which were better than the individual features. Radiogenomics analysis revealed that the PTEN-associated biological processes could be described using the radiomic signature. CONCLUSION: These results show that radiomic features derived from preoperative MRI can predict PTEN mutation status in glioblastoma patients, thus providing a novel noninvasive imaging biomarker.


Assuntos
Neoplasias Encefálicas/diagnóstico por imagem , Neoplasias Encefálicas/genética , Glioblastoma/diagnóstico por imagem , Glioblastoma/genética , Imageamento por Ressonância Magnética/métodos , PTEN Fosfo-Hidrolase/genética , Algoritmos , China , Meios de Contraste , Feminino , Humanos , Masculino , Pessoa de Meia-Idade , Mutação , Estudos Retrospectivos , Sensibilidade e Especificidade
11.
J Neurooncol ; 138(3): 659-666, 2018 Jul.
Artigo em Inglês | MEDLINE | ID: mdl-29556911

RESUMO

BACKGROUND: The newly proposed putamen classification system shows good prognostic value in patients with insular LGGs, yet no study towards the molecular profiles of putamen involved LGGs has been proposed. METHODS: Clinical information and imaging data of patients diagnosed with insular low-grade gliomas were collected retrospectively. Genetic information of the 34 tumors was assessed using RNA-sequencing. Gene set enrichment analysis was further performed to identify the genes showing differential expression between putamen-involved tumors and putamen non-involved tumors. The level of Ki-67 expression was also evaluated. RESULTS: There were 843 genes identified to be differentially expressed between putamen-involved and non-involved gliomas. Specifically, Gene set enrichment analysis discovered 13 Kyoto Encyclopedia of Genes and Genomes pathways and 37 Gene Ontology Biological Process term were upregulated in putamen-involved low-grade glioma cells. The enriched GO sets with the highest gene counts included cell cycle (42 genes), mitotic cell cycle (24 genes), and cell division (19 genes). Furthermore, high expression of Ki-67 was associated with putamen involvement in insular gliomas. CONCLUSIONS: There is clear genetic variation between putamen-involved and non-involved insular low-grade gliomas. The differential expression of genes related to the processes of cell proliferation, cell migration, or DNA repair may lead to putamen involvement. The findings suggest that among the two subtypes, putamen-involved insular low-grade gliomas have higher malignancy, and the clinical treatment towards the putamen-involved insular low-grade gliomas should be more active.


Assuntos
Neoplasias Encefálicas/metabolismo , Córtex Cerebral , Glioma/metabolismo , Putamen , Adulto , Biomarcadores Tumorais/genética , Biomarcadores Tumorais/metabolismo , Neoplasias Encefálicas/diagnóstico por imagem , Neoplasias Encefálicas/genética , Neoplasias Encefálicas/patologia , Córtex Cerebral/diagnóstico por imagem , Córtex Cerebral/metabolismo , Córtex Cerebral/patologia , Feminino , Regulação Neoplásica da Expressão Gênica , Glioma/diagnóstico por imagem , Glioma/genética , Glioma/patologia , Humanos , Antígeno Ki-67/metabolismo , Masculino , Pessoa de Meia-Idade , Gradação de Tumores , Prognóstico , Putamen/diagnóstico por imagem , Putamen/metabolismo , Putamen/patologia , Estudos Retrospectivos , Análise de Sobrevida , Adulto Jovem
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