Acute management of ruptured cavernous malformation of the optic nerve: illustrative case.

BACKGROUND: A cavernous malformation of the optic nerve (CMON) is a rare condition that often presents with an abrupt decline in vision. Acute management of ruptured optic nerve cavernous malformations is generally surgical, although the timing of surgery is controversial. OBSERVATIONS: A 47-year-old female experienced the sudden loss of vision in her left eye. Examination showed that this eye was nearly blind, and her right eye had a temporal field defect. Neuroimaging showed hemorrhage in her left optic nerve and optic chiasm. She was taken to the operating room on an emergent basis where the optic canal was decompressed, the hemorrhage was evacuated, and a vascular malformation with features of a cavernoma was removed from the optic nerve. Over the next 2 days, the vision in her right eye significantly recovered. LESSONS: CMONs remain rare, and it is unlikely that enough cases can be gathered to form a larger trial to compare the role and timing of surgery. On the basis of our experience with this case, the authors recommend that acute CMON-related hematomas should be treated as a surgical emergency and managed with acute optic nerve decompression, hematoma evacuation, and cavernoma resection to improve chances of vision recovery and prevent further vision loss.

Rhabdomyosarcoma: Current Therapy, Challenges, and Future Approaches to Treatment Strategies.

Rhabdomyosarcoma is a rare cancer arising in skeletal muscle that typically impacts children and young adults. It is a worldwide challenge in child health as treatment outcomes for metastatic and recurrent disease still pose a major concern for both basic and clinical scientists. The treatment strategies for rhabdomyosarcoma include multi-agent chemotherapies after surgical resection with or without ionization radiotherapy. In this comprehensive review, we first provide a detailed clinical understanding of rhabdomyosarcoma including its classification and subtypes, diagnosis, and treatment strategies. Later, we focus on chemotherapy strategies for this childhood sarcoma and discuss the impact of three mechanisms that are involved in the chemotherapy response including apoptosis, macro-autophagy, and the unfolded protein response. Finally, we discuss in vivo mouse and zebrafish models and in vitro three-dimensional bioengineering models of rhabdomyosarcoma to screen future therapeutic approaches and promote muscle regeneration.

Differential impact of doxorubicin dose on cell death and autophagy pathways during acute cardiotoxicity.

Doxorubicin (DOX) is an effective anthracycline used in chemotherapeutic regimens for a variety of haematological and solid tumors. However, its utility remains limited by its well-described, but poorly understood cardiotoxicity. Despite numerous studies describing various forms of regulated cell death and their involvement in DOX-mediated cardiotoxicity, the predominate form of cell death remains unclear. Part of this inconsistency lies in a lack of standardization of in vivo and in vitro model design. To this end, the objective of this study was to characterize acute low- and high-dose DOX exposure on cardiac structure and function in C57BL/6 N mice, and evaluate regulated cell death pathways and autophagy both in vivo and in cardiomyocyte culture models. Acute low-dose DOX had no significant impact on cardiac structure or function; however, acute high-dose DOX elicited substantial cardiac necrosis resulting in diminished cardiac mass and volume, with a corresponding reduced cardiac output, and without impacting ejection fraction or fibrosis. Low-dose DOX consistently activated caspase-signaling with evidence of mitochondrial permeability transition. However, acute high-dose DOX had only modest impact on common necrotic signaling pathways, but instead led to an inhibition in autophagic flux. Intriguingly, when autophagy was inhibited in cultured cardiomyoblasts, DOX-induced necrosis was enhanced. Collectively, these observations implicate inhibition of autophagy flux as an important component of the acute necrotic response to DOX, but also suggest that acute high-dose DOX exposure does not recapitulate the disease phenotype observed in human cardiotoxicity.

Misoprostol treatment prevents hypoxia-induced cardiac dysfunction through a 14-3-3 and PKA regulatory motif on Bnip3.

Systemic hypoxia is a common element in most perinatal emergencies and is a known driver of Bnip3 expression in the neonatal heart. Bnip3 plays a prominent role in the evolution of necrotic cell death, disrupting ER calcium homeostasis and initiating mitochondrial permeability transition (MPT). Emerging evidence suggests a cardioprotective role for the prostaglandin E1 analog misoprostol during periods of hypoxia, but the mechanisms for this protection are not completely understood. Using a combination of mouse and cell models, we tested if misoprostol is cardioprotective during neonatal hypoxic injury by altering Bnip3 function. Here we report that hypoxia elicits mitochondrial-fragmentation, MPT, reduced ejection fraction, and evidence of necroinflammation, which were abrogated with misoprostol treatment or Bnip3 knockout. Through molecular studies we show that misoprostol leads to PKA-dependent Bnip3 phosphorylation at threonine-181, and subsequent redistribution of Bnip3 from mitochondrial Opa1 and the ER through an interaction with 14-3-3 proteins. Taken together, our results demonstrate a role for Bnip3 phosphorylation in the regulation of cardiomyocyte contractile/metabolic dysfunction, and necroinflammation. Furthermore, we identify a potential pharmacological mechanism to prevent neonatal hypoxic injury.

The Role of BiP and the IRE1α-XBP1 Axis in Rhabdomyosarcoma Pathology.

BACKGROUND: Rhabdomyosarcoma (RMS) is the most common soft-tissue sarcoma in children, and is associated with a poor prognosis in patients presenting with recurrent or metastatic disease. The unfolded protein response (UPR) plays pivotal roles in tumor development and resistance to therapy, including RMS. METHODS: In this study, we used immunohistochemistry and a tissue microarray (TMA) on human RMS and normal skeletal muscle to evaluate the expression of key UPR proteins (GRP78/BiP, IRE1α and cytosolic/nuclear XBP1 (spliced XBP1-sXBP1)) in the four main RMS subtypes: alveolar (ARMS), embryonal (ERMS), pleomorphic (PRMS) and sclerosing/spindle cell (SRMS) RMS. We also investigated the correlation of these proteins with the risk of RMS and several clinicopathological indices, such as lymph node involvement, distant metastasis, tumor stage and tumor scores. RESULTS: Our results revealed that the expression of BiP, sXBP1, and IRE1α, but not cytosolic XBP1, are significantly associated with RMS (BiP and sXBP1 p-value = 0.0001, IRE1 p-value = 0.001) in all of the studied types of RMS tumors (n = 192) compared to normal skeletal muscle tissues (n = 16). In addition, significant correlations of BiP with the lymph node score (p = 0.05), and of IRE1α (p value = 0.004), cytosolic XBP1 (p = 0.001) and sXBP1 (p value = 0.001) with the stage score were observed. At the subtype level, BiP and sXBP1 expression were significantly associated with all subtypes of RMS, whereas IRE1α was associated with ARMS, PRMS and ERMS, and cytosolic XBP1 expression was associated with ARMS and SRMS. Importantly, the expression levels of IRE1α and sXBP1 were more pronounced in ARMS than in any of the other subtypes. The results also showed correlations of BiP with the lymph node score in ARMS (p value = 0.05), and of sXBP1 with the tumor score in PRMS (p value = 0.002). CONCLUSIONS: In summary, this study demonstrates that the overall UPR is upregulated and, more specifically, that the IRE1/sXBP1 axis is active in RMS. The subtype and stage-specific dependency on the UPR machinery in RMS may open new avenues for the development of novel targeted therapeutic strategies and the identification of specific tumor markers in this rare but deadly childhood and young-adult disease.

Mechanisms of simvastatin myotoxicity: The role of autophagy flux inhibition.

Statins are some of the most widely used drugs worldwide, but one of their major side effects is myotoxicity. Using mouse myoblast (C2C12) and human alveolar rhabdomyosarcoma cell lines (RH30) in both 2-dimensional (2D) and 3-dimensional (3D) cell culture, we investigated the mechanisms of simvastatin's myotoxicity. We found that simvastatin significantly reduced cell viability in C2C12 cells compared to RH30 cells. However, simvastatin induced greater apoptosis in RH30 compared to C2C12 cells. Simvastatin-induced cell death is dependent on geranylgeranyl pyrophosphate (GGPP) in C2C12 cells, while in RH30 cells it is dependent on both farnesyl pyrophosphate (FPP) and GGPP. Simvastatin inhibited autophagy flux in both C2C12 and RH30 cells and inhibited lysosomal acidification in C2C12 cells, while autophagy inhibition with Bafilomycin-A1 increased simvastatin myotoxicity in both cell lines. Simvastatin induced greater cell death in RH30 cells compared to C2C12 in a 3D culture model with similar effects on autophagy flux as in 2D culture. Overall, our results suggest that simvastatin-induced myotoxicity involves both apoptosis and autophagy, where autophagy serves a pro-survival role in both cell lines. The sensitivity to simvastatin-induced myotoxicity differs between 2D and 3D culture, demonstrating that the cellular microenvironment is a critical factor in regulating simvastatin-induced cell death in myoblasts.

Autophagy modulates temozolomide-induced cell death in alveolar Rhabdomyosarcoma cells.

Rhabdomyosarcoma (RMS) is a muscle-derived tumor. In both pre-clinical and clinical studies Temozolomide (TMZ) has been recently tested against RMS; however, the precise mechanism of action of TMZ in RMS remains unclear. Here we demonstrate that TMZ decreases the cell viability of the RH30 RMS and C2C12 cell line, where cells display evidence of mitochondrial outer membrane permeability. Interestingly, the C2C12 mouse myoblast line was relatively more resistant to TMZ-induced apoptosis. Moreover, we observed that TMZ activated biochemical and morphological markers of autophagy in both cell lines. Autophagy inhibition in both RH30 and C2C12 cells significantly increased TMZ-induced cell death. In RH30 cells, TMZ increased Mcl-1 and Bax protein expression compared to corresponding time match controls while in C2C12 Mcl-1, Bcl-2, Bcl-XL, and Bax protein expression were not changed. Baf-A1 co-treatment with TMZ significantly decrease Mcl-1 expression compared to TMZ while increase Bax expression in C2C12 cells (Bcl2 and Bcl-XL do not significantly change in Baf-A1/TMZ co-treatment). Using a three-dimensional (3D) C2C12 and RH30 culture model we demonstrated that TMZ is significantly more toxic in RH30 cells (live/dead assay). Additionally, we have observed in our 3D culture model that TMZ induced both apoptosis (cleavage of PARP) and autophagy (LC3-puncta and localization of LC3/p62). Therefore, our data demonstrate that TMZ induces simultaneous autophagy and apoptosis in both RH30 and C2C12 cells in 2D and 3D culture model, where RH30 cells are more sensitive to TMZ-induced death. Furthermore, autophagy serves to protect RH30 cells from TMZ-induced death.

Feasibility of predicting tumor motion using online data acquired during treatment and a generalized neural network optimized with offline patient tumor trajectories.

PURPOSE: The accurate prediction of intrafraction lung tumor motion is required to compensate for system latency in image-guided adaptive radiotherapy systems. The goal of this study was to identify an optimal prediction model that has a short learning period so that prediction and adaptation can commence soon after treatment begins, and requires minimal reoptimization for individual patients. Specifically, the feasibility of predicting tumor position using a combination of a generalized (i.e., averaged) neural network, optimized using historical patient data (i.e., tumor trajectories) obtained offline, coupled with the use of real-time online tumor positions (obtained during treatment delivery) was examined. METHODS: A 3-layer perceptron neural network was implemented to predict tumor motion for a prediction horizon of 650 ms. A backpropagation algorithm and batch gradient descent approach were used to train the model. Twenty-seven 1-min lung tumor motion samples (selected from a CyberKnife patient dataset) were sampled at a rate of 7.5 Hz (0.133 s) to emulate the frame rate of an electronic portal imaging device (EPID). A sliding temporal window was used to sample the data for learning. The sliding window length was set to be equivalent to the first breathing cycle detected from each trajectory. Performing a parametric sweep, an averaged error surface of mean square errors (MSE) was obtained from the prediction responses of seven trajectories used for the training of the model (Group 1). An optimal input data size and number of hidden neurons were selected to represent the generalized model. To evaluate the prediction performance of the generalized model on unseen data, twenty tumor traces (Group 2) that were not involved in the training of the model were used for the leave-one-out cross-validation purposes. RESULTS: An input data size of 35 samples (4.6 s) and 20 hidden neurons were selected for the generalized neural network. An average sliding window length of 28 data samples was used. The average initial learning period prior to the availability of the first predicted tumor position was 8.53 ± 1.03 s. Average mean absolute error (MAE) of 0.59 ± 0.13 mm and 0.56 ± 0.18 mm were obtained from Groups 1 and 2, respectively, giving an overall MAE of 0.57 ± 0.17 mm. Average root-mean-square-error (RMSE) of 0.67 ± 0.36 for all the traces (0.76 ± 0.34 mm, Group 1 and 0.63 ± 0.36 mm, Group 2), is comparable to previously published results. Prediction errors are mainly due to the irregular periodicities between cycles. Since the errors from Groups 1 and 2 are within the same range, it demonstrates that this model can generalize and predict on unseen data. CONCLUSIONS: This is a first attempt to use an averaged MSE error surface (obtained from the prediction of different patients' tumor trajectories) to determine the parameters of a generalized neural network. This network could be deployed as a plug-and-play predictor for tumor trajectory during treatment delivery, eliminating the need for optimizing individual networks with pretreatment patient data.