Dataset Information

Combining antiangiogenic therapy and radiation in nasopharyngeal carcinoma.

ABSTRACT: Radiation therapy is the primary treatment in nasopharyngeal carcinoma (NPC), and the effect of radiation therapy is strongly related to the oxygen content of cancer cells. That means, it is imperative to balance the interactions between radiotherapy and anti-angiogenesis therapy when giving combination therapy to improve clinical outcomes. The complicated mechanisms between antiangiogenic agents and radiation involve many interactions between the cancer cells, vasculature, and cancer stroma. The proliferation and metastasis of cancer depends on angiogenesis, while rapid growth of cancers will cause hypoxia, which contributes to radioresistance. Antiangiogenic agents can modulate the cancer blood flow and oxygenation through target cancer vasculature, leading to increased radiosensitivity. This study discusses the mechanisms of the synergistic effect of the antiangiogenic therapy with radiation therapy in metastatic NPC, and reviews the data supporting this strategy as a promising treatment for metastatic NPC.

SUBMITTER: Chen Z

PROVIDER: S-EPMC4454898 | biostudies-other | 2015 Jun

REPOSITORIES: biostudies-other

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Combining antiangiogenic therapy and radiation in nasopharyngeal carcinoma.

Chen Zhuo Z Xu Xin-Hua XH

Saudi medical journal 20150601 6

Radiation therapy is the primary treatment in nasopharyngeal carcinoma (NPC), and the effect of radiation therapy is strongly related to the oxygen content of cancer cells. That means, it is imperative to balance the interactions between radiotherapy and anti-angiogenesis therapy when giving combination therapy to improve clinical outcomes. The complicated mechanisms between antiangiogenic agents and radiation involve many interactions between the cancer cells, vasculature, and cancer stroma. Th ...[more]

PMID: 25987106

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Project description:Nasopharyngeal carcinoma (NPC) has a particularly high prevalence in southern China, southeastern Asia and northern Africa. Radiation resistance remains a serious obstacle to successful treatment in NPC. This study aimed to explore the metabolic feature of radiation-resistant NPC cells and identify new molecular-targeted agents to improve the therapeutic effects of radiotherapy in NPC. Methods: Radiation-responsive and radiation-resistant NPC cells were used as the model system in vitro and in vivo. Metabolomics approach was used to illustrate the global metabolic changes. 13C isotopomer tracing experiment and Seahorse XF analysis were undertaken to determine the activity of fatty acid oxidation (FAO). qRT-PCR was performed to evaluate the expression of essential FAO genes including CPT1A. NPC tumor tissue microarray was used to investigate the prognostic role of CPT1A. Either RNA interference or pharmacological blockade by Etomoxir were used to inhibit CPT1A. Radiation resistance was evaluated by colony formation assay. Mitochondrial membrane potential, apoptosis and neutral lipid content were measured by flow cytometry analysis using JC-1, Annexin V and LipidTOX Red probe respectively. Molecular markers of mitochondrial apoptosis were detected by western blot. Xenografts were treated with Etomoxir, radiation, or a combination of Etomoxir and radiation. Mitochondrial apoptosis and lipid droplets content of tumor tissues were detected by cleaved caspase 9 and Oil Red O staining respectively. Liquid chromatography coupled with tandem mass spectrometry approach was used to identify CPT1A-binding proteins. The interaction of CPT1A and Rab14 were detected by immunoprecipitation, immunofluorescence and in situ proximity ligation analysis. Fragment docking and direct coupling combined computational protein-protein interaction prediction method were used to predict the binding interface. Fatty acid trafficking was measured by pulse-chase assay using BODIPY C16 and MitoTracker Red probe. Results: FAO was active in radiation-resistant NPC cells, and the rate-limiting enzyme of FAO, carnitine palmitoyl transferase 1 A (CPT1A), was consistently up-regulated in these cells. The protein level of CPT1A was significantly associated with poor overall survival of NPC patients following radiotherapy. Inhibition of CPT1A re-sensitized NPC cells to radiation therapy by activating mitochondrial apoptosis both in vitro and in vivo. In addition, we identified Rab14 as a novel CPT1A binding protein. The CPT1A-Rab14 interaction facilitated fatty acid trafficking from lipid droplets to mitochondria, which decreased radiation-induced lipid accumulation and maximized ATP production. Knockdown of Rab14 attenuated CPT1A-mediated fatty acid trafficking and radiation resistance. Conclusion: An active FAO is a vital signature of NPC radiation resistance. Targeting CPT1A could be a beneficial regimen to improve the therapeutic effects of radiotherapy in NPC patients. Importantly, the CPT1A-Rab14 interaction plays roles in CPT1A-mediated radiation resistance by facilitating fatty acid trafficking. This interaction could be an attractive interface for the discovery of novel CPT1A inhibitors.

Project description:Background and purpose: Adaptive radiotherapy (ART) can compensate for the dosimetric impacts induced by anatomic and geometric variations in patients with nasopharyngeal carcinoma (NPC); Yet, the need for ART can only be assessed during the radiation treatment and the implementation of ART is resource intensive. Therefore, we aimed to determine tumoral biomarkers using pre-treatment MR images for predicting ART eligibility in NPC patients prior to the start of treatment. Methods: Seventy patients with biopsy-proven NPC (Stage II-IVB) in 2015 were enrolled into this retrospective study. Pre-treatment contrast-enhanced T1-w (CET1-w), T2-w MR images were processed and filtered using Laplacian of Gaussian (LoG) filter before radiomic features extraction. A total of 479 radiomics features, including the first-order (n = 90), shape (n = 14), and texture features (n = 375), were initially extracted from Gross-Tumor-Volume of primary tumor (GTVnp) using CET1-w, T2-w MR images. Patients were randomly divided into a training set (n = 51) and testing set (n = 19). The least absolute shrinkage and selection operator (LASSO) logistic regression model was applied for radiomic model construction in training set to select the most predictive features to predict patients who were replanned and assessed in the testing set. A double cross-validation approach of 100 resampled iterations with 3-fold nested cross-validation was employed in LASSO during model construction. The predictive performance of each model was evaluated using the area under the receiver operator characteristic (ROC) curve (AUC). Results: In the present cohort, 13 of 70 patients (18.6%) underwent ART. Average AUCs in training and testing sets were 0.962 (95%CI: 0.961-0.963) and 0.852 (95%CI: 0.847-0.857) with 8 selected features for CET1-w model; 0.895 (95%CI: 0.893-0.896) and 0.750 (95%CI: 0.745-0.755) with 6 selected features for T2-w model; and 0.984 (95%CI: 0.983-0.984) and 0.930 (95%CI: 0.928-0.933) with 6 selected features for joint T1-T2 model, respectively. In general, the joint T1-T2 model outperformed either CET1-w or T2-w model alone. Conclusions: Our study successfully showed promising capability of MRI-based radiomics features for pre-treatment identification of ART eligibility in NPC patients.

Project description:BackgroundTo investigate the feasibility of a knowledge-based automated intensity-modulated radiation therapy (IMRT) planning technique for locally advanced nasopharyngeal carcinoma (NPC) radiotherapy.MethodsOne hundred forty NPC patients treated with definitive radiation therapy with the step-and-shoot IMRT techniques were retrospectively selected and separated into a knowledge library (n = 115) and a test library (n = 25). For each patient in the knowledge library, the overlap volume histogram (OVH), target volume histogram (TVH) and dose objectives were extracted from the manually generated plan. 5-fold cross validation was performed to divide the patients in the knowledge library into 5 groups before validating one group by using the other 4 groups to train each neural network (NN) machine learning models. For patients in the test library, their OVH and TVH were then used by the trained models to predict a corresponding set of mean dose objectives, which were subsequently used to generate automated plans (APs) in Pinnacle planning system via an in-house developed automated scripting system. All APs were obtained after a single step of optimization. Manual plans (MPs) for the test patients were generated by an experienced medical physicist strictly following the established clinical protocols. The qualities of the APs and MPs were evaluated by an attending radiation oncologist. The dosimetric parameters for planning target volume (PTV) coverage and the organs-at-risk (OAR) sparing were also quantitatively measured and compared using Mann-Whitney U test and Bonferroni correction.ResultsAPs and MPs had the same rating for more than 80% of the patients (19 out of 25) in the test group. Both AP and MP achieved PTV coverage criteria for no less than 80% of the patients. For each OAR, the number of APs achieving its criterion was similar to that in the MPs. The AP approach improved planning efficiency by greatly reducing the planning duration to about 17% of the MP (9.85 ± 1.13 min vs. 57.10 ± 6.35 min).ConclusionA robust and effective knowledge-based IMRT treatment planning technique for locally advanced NPC is developed. Patient specific dose objectives can be predicted by trained NN models based on the individual's OVH and clinical TVH goals. The automated planning scripts can use these dose objectives to efficiently generate APs with largely shortened planning time. These APs had comparable dosimetric qualities when compared to our clinic's manual plans.

Dataset Information

Combining antiangiogenic therapy and radiation in nasopharyngeal carcinoma.

Publications

Combining antiangiogenic therapy and radiation in nasopharyngeal carcinoma.

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