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On page 1 showing 1 ~ 20 papers out of 35 papers

Therapeutic Impact of Cytoreductive Surgery and Irradiation of Posterior Fossa Ependymoma in the Molecular Era: A Retrospective Multicohort Analysis.

  • Vijay Ramaswamy‎ et al.
  • Journal of clinical oncology : official journal of the American Society of Clinical Oncology‎
  • 2016‎

Posterior fossa ependymoma comprises two distinct molecular variants termed EPN_PFA and EPN_PFB that have a distinct biology and natural history. The therapeutic value of cytoreductive surgery and radiation therapy for posterior fossa ependymoma after accounting for molecular subgroup is not known.


YAP Inhibition Restores Hepatocyte Differentiation in Advanced HCC, Leading to Tumor Regression.

  • Julien Fitamant‎ et al.
  • Cell reports‎
  • 2015‎

Defective Hippo/YAP signaling in the liver results in tissue overgrowth and development of hepatocellular carcinoma (HCC). Here, we uncover mechanisms of YAP-mediated hepatocyte reprogramming and HCC pathogenesis. YAP functions as a rheostat in maintaining metabolic specialization, differentiation, and quiescence within the hepatocyte compartment. Increased or decreased YAP activity reprograms subsets of hepatocytes to different fates associated with deregulation of the HNF4A, CTNNB1, and E2F transcriptional programs that control hepatocyte quiescence and differentiation. Importantly, treatment with small interfering RNA-lipid nanoparticles (siRNA-LNPs) targeting YAP restores hepatocyte differentiation and causes pronounced tumor regression in a genetically engineered mouse HCC model. Furthermore, YAP targets are enriched in an aggressive human HCC subtype characterized by a proliferative signature and absence of CTNNB1 mutations. Thus, our work reveals Hippo signaling as a key regulator of the positional identity of hepatocytes, supports targeting of YAP using siRNA-LNPs as a paradigm of differentiation-based therapy, and identifies an HCC subtype that is potentially responsive to this approach.


An intronic LINE-1 insertion in MERTK is strongly associated with retinopathy in Swedish Vallhund dogs.

  • Richard Everson‎ et al.
  • PloS one‎
  • 2017‎

The domestic dog segregates a significant number of inherited progressive retinal diseases, several of which mirror human retinal diseases and which are collectively termed progressive retinal atrophy (PRA). In 2014, a novel form of PRA was reported in the Swedish Vallhund breed, and the disease was mapped to canine chromosome 17. The causal mutation was not identified, but expression analyses of the retinas of affected Vallhunds demonstrated a 6-fold increased expression of the MERTK gene compared to unaffected dogs. Using 24 retinopathy cases and 97 controls with no clinical signs of retinopathy, we replicated the chromosome 17 association in Swedish Vallhunds from the UK and aimed to elucidate the causal variant underlying this association using whole genome sequencing (WGS) of an affected dog. This revealed a 6-8 kb insertion in intron 1 of MERTK that was not present in WGS of 49 dogs of other breeds. Sequencing and BLASTN analysis of the inserted segment was consistent with the insertion comprising a full-length intact LINE-1 retroelement. Testing of the LINE-1 insertion for association with retinopathy in the UK set of 24 cases and 97 controls revealed a strong statistical association (P-value 6.0 x 10-11) that was subsequently replicated in the original Finnish study set (49 cases and 89 controls (P-value 4.3 x 10-19). In a pooled analysis of both studies (73 cases and 186 controls), the LINE-1 insertion was associated with a ~20-fold increased risk of retinopathy (odds ratio 23.41, 95% confidence intervals 10.99-49.86, P-value 1.3 x 10-27). Our study adds further support for regulatory disruption of MERTK in Swedish Vallhund retinopathy; however, further work is required to establish a functional overexpression model. Future work to characterise the mechanism by which this intronic mutation disrupts gene regulation will further improve the understanding of MERTK biology and its role in retinal function.


Gene expression analysis of glioblastomas identifies the major molecular basis for the prognostic benefit of younger age.

  • Yohan Lee‎ et al.
  • BMC medical genomics‎
  • 2008‎

Glioblastomas are the most common primary brain tumour in adults. While the prognosis for patients is poor, gene expression profiling has detected signatures that can sub-classify GBMs relative to histopathology and clinical variables. One category of GBM defined by a gene expression signature is termed ProNeural (PN), and has substantially longer patient survival relative to other gene expression-based subtypes of GBMs. Age of onset is a major predictor of the length of patient survival where younger patients survive longer than older patients. The reason for this survival advantage has not been clear.


The feasibility of using citizens to segment anatomy from medical images: Accuracy and motivation.

  • Judith R Meakin‎ et al.
  • PloS one‎
  • 2019‎

The development of automatic methods for segmenting anatomy from medical images is an important goal for many medical and healthcare research areas. Datasets that can be used to train and test computer algorithms, however, are often small due to the difficulties in obtaining experts to segment enough examples. Citizen science provides a potential solution to this problem but the feasibility of using the public to identify and segment anatomy in a medical image has not been investigated. Our study therefore aimed to explore the feasibility, in terms of performance and motivation, of using citizens for such purposes. Public involvement was woven into the study design and evaluation. Twenty-nine citizens were recruited and, after brief training, asked to segment the spine from a dataset of 150 magnetic resonance images. Participants segmented as many images as they could within three one-hour sessions. Their accuracy was evaluated by comparing them, as individuals and as a combined consensus, to the segmentations of three experts. Questionnaires and a focus group were used to determine the citizens' motivation for taking part and their experience of the study. Citizen segmentation accuracy, in terms of agreement with the expert consensus segmentation, varied considerably between individual citizens. The citizen consensus, however, was close to the expert consensus, indicating that when pooled, citizens may be able to replace or supplement experts for generating large image datasets. Personal interest and a desire to help were the two most common reasons for taking part in the study.


Characterization of Cognitive Function in Survivors of Diffuse Gliomas Using Morphometric Correlation Networks.

  • Chencai Wang‎ et al.
  • Tomography (Ann Arbor, Mich.)‎
  • 2022‎

This pilot study investigates structural alterations and their relationships with cognitive function in survivors of diffuse gliomas. Twenty-four survivors of diffuse gliomas (mean age 44.5 ± 11.5), from whom high-resolution T1-weighted images, neuropsychological tests, and self-report questionnaires were obtained, were analyzed. Patients were grouped by degree of cognitive impairment, and interregional correlations of cortical thickness were computed to generate morphometric correlation networks (MCNs). The results show that the cortical thickness of the right insula (R2 = 0.3025, p = 0.0054) was negatively associated with time since the last treatment, and the cortical thickness of the left superior temporal gyrus (R2 = 0.2839, p = 0.0107) was positively associated with cognitive performance. Multiple cortical regions in the default mode, salience, and language networks were identified as predominant nodes in the MCNs of survivors of diffuse gliomas. Compared to cognitively impaired patients, cognitively non-impaired patients tended to have higher network stability in network nodes removal analysis, especially when the fraction of removed nodes (among 66 nodes in total) exceeded 55%. These findings suggest that structural networks are altered in survivors of diffuse gliomas and that their cortical structures may also be adapting to support cognitive function during survivorship.


MRI Radiomic Features to Predict IDH1 Mutation Status in Gliomas: A Machine Learning Approach using Gradient Tree Boosting.

  • Yu Sakai‎ et al.
  • International journal of molecular sciences‎
  • 2020‎

Patients with gliomas, isocitrate dehydrogenase 1 (IDH1) mutation status have been studied as a prognostic indicator. Recent advances in machine learning (ML) have demonstrated promise in utilizing radiomic features to study disease processes in the brain. We investigate whether ML analysis of multiparametric radiomic features from preoperative Magnetic Resonance Imaging (MRI) can predict IDH1 mutation status in patients with glioma. This retrospective study included patients with glioma with known IDH1 status and preoperative MRI. Radiomic features were extracted from Fluid-Attenuated Inversion Recovery (FLAIR) and Diffused Weighted Imaging (DWI). The dataset was split into training, validation, and testing sets by stratified sampling. Synthetic Minority Oversampling Technique (SMOTE) was applied to the training sets. eXtreme Gradient Boosting (XGBoost) classifiers were trained, and the hyperparameters were tuned. Receiver operating characteristic curve (ROC), accuracy, and f1-scores were collected. A total of 100 patients (age: 55 ± 15, M/F 60/40); with IDH1 mutant (n = 22) and IDH1 wildtype (n = 78) were included. The best performance was seen with a DWI-trained XGBoost model, which achieved ROC with Area Under the Curve (AUC) of 0.97, accuracy of 0.90, and f1-score of 0.75 on the test set. The FLAIR-trained XGBoost model achieved ROC with AUC of 0.95, accuracy of 0.90, f1-score of 0.75 on the test set. A model that was trained on combined FLAIR-DWI radiomic features did not provide incremental accuracy. The results show that a XGBoost classifier using multiparametric radiomic features derived from preoperative MRI can predict IDH1 mutation status with > 90% accuracy.


Performance of Machine Learning Algorithms for Predicting Progression to Dementia in Memory Clinic Patients.

  • Charlotte James‎ et al.
  • JAMA network open‎
  • 2021‎

Machine learning algorithms could be used as the basis for clinical decision-making aids to enhance clinical practice.


Characterization of cognitive function in survivors of diffuse gliomas using resting-state functional MRI (rs-fMRI).

  • Chencai Wang‎ et al.
  • Brain imaging and behavior‎
  • 2022‎

As treatments for diffuse gliomas have advanced, survival for patients with gliomas has also increased. However, there remains limited knowledge on the relationships between brain connectivity and the lasting changes to cognitive function that glioma survivors often experience long after completing treatment. This resting-state functional magnetic resonance imaging (rs-fMRI) study explored functional connectivity (FC) alterations associated with cognitive function in survivors of gliomas. In this pilot study, 22 patients (mean age 43.8 ± 11.9) with diffuse gliomas who completed treatment within the past 10 years were evaluated using rs-fMRI and neuropsychological measures. Novel rs-fMRI analysis methods were used to account for missing brain in the resection cavity. FC relationships were assessed between cognitively impaired and non-impaired glioma patients, along with self-reported cognitive impairment, non-work daily functioning, and time with surgery. In the cognitively non-impaired patients, FC was stronger in the medial prefrontal cortex, rostral prefrontal cortex, and intraparietal sulcus compared to the impaired survivors. When examining non-work daily functioning, a positive correlation with FC was observed between the accumbens and the intracalcarine cortices, while a negative correlation with FC was observed between the parietal operculum cortex and the cerebellum. Additionally, worse self-reported cognitive impairment and worse non-work daily functioning were associated with increased FC between regions involved in cognition and sensorimotor processing. These preliminary findings suggest that neural correlates for cognitive and daily functioning in glioma patients can be revealed using rs-fMRI. Resting-state network alterations may serve as a biomarker for patients' cognition and functioning.


Bone morphogenetic protein 7 sensitizes O6-methylguanine methyltransferase expressing-glioblastoma stem cells to clinically relevant dose of temozolomide.

  • Jonathan L Tso‎ et al.
  • Molecular cancer‎
  • 2015‎

Temozolomide (TMZ) is an oral DNA-alkylating agent used for treating patients with glioblastoma. However, therapeutic benefits of TMZ can be compromised by the expression of O6-methylguanine methyltransferase (MGMT) in tumor tissue. Here we used MGMT-expressing glioblastoma stem cells (GSC) lines as a model for investigating the molecular mechanism underlying TMZ resistance, while aiming to explore a new treatment strategy designed to possibly overcome resistance to the clinically relevant dose of TMZ (35 μM).


Federated learning enables big data for rare cancer boundary detection.

  • Sarthak Pati‎ et al.
  • Nature communications‎
  • 2022‎

Although machine learning (ML) has shown promise across disciplines, out-of-sample generalizability is concerning. This is currently addressed by sharing multi-site data, but such centralization is challenging/infeasible to scale due to various limitations. Federated ML (FL) provides an alternative paradigm for accurate and generalizable ML, by only sharing numerical model updates. Here we present the largest FL study to-date, involving data from 71 sites across 6 continents, to generate an automatic tumor boundary detector for the rare disease of glioblastoma, reporting the largest such dataset in the literature (n = 6, 314). We demonstrate a 33% delineation improvement for the surgically targetable tumor, and 23% for the complete tumor extent, over a publicly trained model. We anticipate our study to: 1) enable more healthcare studies informed by large diverse data, ensuring meaningful results for rare diseases and underrepresented populations, 2) facilitate further analyses for glioblastoma by releasing our consensus model, and 3) demonstrate the FL effectiveness at such scale and task-complexity as a paradigm shift for multi-site collaborations, alleviating the need for data-sharing.


Quantification of tumor microenvironment acidity in glioblastoma using principal component analysis of dynamic susceptibility contrast enhanced MR imaging.

  • Hamed Akbari‎ et al.
  • Scientific reports‎
  • 2021‎

Glioblastoma (GBM) has high metabolic demands, which can lead to acidification of the tumor microenvironment. We hypothesize that a machine learning model built on temporal principal component analysis (PCA) of dynamic susceptibility contrast-enhanced (DSC) perfusion MRI can be used to estimate tumor acidity in GBM, as estimated by pH-sensitive amine chemical exchange saturation transfer echo-planar imaging (CEST-EPI). We analyzed 78 MRI scans in 32 treatment naïve and post-treatment GBM patients. All patients were imaged with DSC-MRI, and pH-weighting that was quantified from CEST-EPI estimation of the magnetization transfer ratio asymmetry (MTRasym) at 3 ppm. Enhancing tumor (ET), non-enhancing core (NC), and peritumoral T2 hyperintensity (namely, edema, ED) were used to extract principal components (PCs) and to build support vector machines regression (SVR) models to predict MTRasym values using PCs. Our predicted map correlated with MTRasym values with Spearman's r equal to 0.66, 0.47, 0.67, 0.71, in NC, ET, ED, and overall, respectively (p < 0.006). The results of this study demonstrates that PCA analysis of DSC imaging data can provide information about tumor pH in GBM patients, with the strongest association within the peritumoral regions.


Metabolic characterization of isocitrate dehydrogenase (IDH) mutant and IDH wildtype gliomaspheres uncovers cell type-specific vulnerabilities.

  • Matthew Garrett‎ et al.
  • Cancer & metabolism‎
  • 2018‎

There is considerable interest in defining the metabolic abnormalities of IDH mutant tumors to exploit for therapy. While most studies have attempted to discern function by using cell lines transduced with exogenous IDH mutant enzyme, in this study, we perform unbiased metabolomics to discover metabolic differences between a cohort of patient-derived IDH1 mutant and IDH wildtype gliomaspheres.


Use of Clinical Pathway Simulation and Machine Learning to Identify Key Levers for Maximizing the Benefit of Intravenous Thrombolysis in Acute Stroke.

  • Michael Allen‎ et al.
  • Stroke‎
  • 2022‎

Expert opinion is that about 20% of emergency stroke patients should receive thrombolysis. Currently, 11% to 12% of patients in England and Wales receive thrombolysis, ranging from 2% to 24% between hospitals. The aim of this study was to assess how much variation is due to differences in local patient populations, and how much is due to differences in clinical decision-making and stroke pathway performance, while estimating a realistic target thrombolysis use.


dCas9/CRISPR-based methylation of O-6-methylguanine-DNA methyltransferase enhances chemosensitivity to temozolomide in malignant glioma.

  • Serendipity Zapanta Rinonos‎ et al.
  • Journal of neuro-oncology‎
  • 2024‎

Malignant glioma carries a poor prognosis despite current therapeutic modalities. Standard of care therapy consists of surgical resection, fractionated radiotherapy concurrently administered with temozolomide (TMZ), a DNA-alkylating chemotherapeutic agent, followed by adjuvant TMZ. O-6-methylguanine-DNA methyltransferase (MGMT), a DNA repair enzyme, removes alkylated lesions from tumor DNA, thereby promoting chemoresistance. MGMT promoter methylation status predicts responsiveness to TMZ; patients harboring unmethylated MGMT (~60% of glioblastoma) have a poorer prognosis with limited treatment benefits from TMZ.


K-RAS mutant pancreatic tumors show higher sensitivity to MEK than to PI3K inhibition in vivo.

  • Irmgard Hofmann‎ et al.
  • PloS one‎
  • 2012‎

Activating K-RAS mutations occur at a frequency of 90% in pancreatic cancer, and to date no therapies exist targeting this oncogene. K-RAS signals via downstream effector pathways such as the MAPK and the PI3K signaling pathways, and much effort has been focused on developing drugs targeting components of these pathways. To better understand the requirements for K-RAS and its downstream signaling pathways MAPK and PI3K in pancreatic tumor maintenance, we established an inducible K-RAS knock down system that allowed us to ablate K-RAS in established tumors. Knock down of K-RAS resulted in impaired tumor growth in all pancreatic xenograft models tested, demonstrating that K-RAS expression is indeed required for tumor maintenance of K-RAS mutant pancreatic tumors. We further examined signaling downstream of K-RAS, and detected a robust reduction of pERK levels upon K-RAS knock down. In contrast, no effect on pAKT levels could be observed due to almost undetectable basal expression levels. To investigate the requirement of the MAPK and the PI3K pathways on tumor maintenance, three selected pancreatic xenograft models were tested for their response to MEK or PI3K inhibition. Tumors of all three models regressed upon MEK inhibition, but showed less pronounced response to PI3K inhibition. The effect of MEK inhibition on pancreatic xenografts could be enhanced further by combined application of a PI3K inhibitor. These data provide further rationale for testing combinations of MEK and PI3K inhibitors in clinical trials comprising a patient population with pancreatic cancer harboring mutations in K-RAS.


Rationally Designed PI3Kα Mutants to Mimic ATR and Their Use to Understand Binding Specificity of ATR Inhibitors.

  • Yipin Lu‎ et al.
  • Journal of molecular biology‎
  • 2017‎

ATR, a protein kinase in the PIKK family, plays a critical role in the cell DNA-damage response and is an attractive anticancer drug target. Several potent and selective inhibitors of ATR have been reported showing significant antitumor efficacy, with most advanced ones entering clinical trials. However, due to the absence of an experimental ATR structure, the determinants contributing to ATR inhibitors' potency and specificity are not well understood. Here we present the mutations in the ATP-binding site of PI3Kα to progressively transform the pocket to mimic that of ATR. The generated PI3Kα mutants exhibit significantly improved affinity for selective ATR inhibitors in multiple chemical classes. Furthermore, we obtained the X-ray structures of the PI3Kα mutants in complex with the ATR inhibitors. The crystal structures together with the analysis on the inhibitor affinity profile elucidate the roles of individual amino acid residues in the binding of ATR inhibitors, offering key insights for the binding mechanism and revealing the structure features important for the specificity of ATR inhibitors. The ability to obtain structural and binding data for these PI3Kα mutants, together with their ATR-like inhibitor binding profiles, makes these chimeric PI3Kα proteins valuable model systems for structure-based inhibitor design.


A gene expression signature predicts recurrence-free survival in meningioma.

  • Adriana Olar‎ et al.
  • Oncotarget‎
  • 2018‎

Meningioma is the most common primary brain tumor and has a variable risk of local recurrence. While World Health Organization (WHO) grade generally correlates with recurrence, there is substantial within-grade variation of recurrence risk. Current risk stratification does not accurately predict which patients are likely to benefit from adjuvant radiation therapy (RT). We hypothesized that tumors at risk for recurrence have unique gene expression profiles (GEP) that could better select patients for adjuvant RT.


Stem cell associated gene expression in glioblastoma multiforme: relationship to survival and the subventricular zone.

  • Melanie Kappadakunnel‎ et al.
  • Journal of neuro-oncology‎
  • 2010‎

Current therapies for glioblastoma (GBM) target bulk tumor through measures such as resection and radiotherapy. However, recent evidence suggests that targeting a subset of tumor cells, so-called cancer stem cells, may be critical for inhibiting tumor growth and relapse. The subventricular zone (SVZ), which lines the ventricles of the brain, is thought to be the origin for the majority of neural stem cells and potentially cancer stem cells. Therefore, we assessed the relationship between tumor contact with the SVZ as determined by MRI, cancer stem cell gene expression and survival in 47 patients with GBM. Using DNA microarrays, we found that genes associated with cancer stem cells were not over-expressed in tumors contacting the SVZ. Contact with the SVZ trended with shorter survival (median 358 versus 644, P = 0.066). Over-expression of CD133 (prominin-1) and maternal embryonic leucine zipper kinase (MELK) was associated with shorter survival, whereas mitogen activated protein kinase 8 (MAPK8) was associated with longer survival (P values 0.008, 0.005 and 0.002 respectively). Thus we found no evidence of a stem-cell derived genetic signature specific for GBM in contact with the SVZ, but there was a relationship between stem cell gene expression and survival. More research is required to clarify the relationship between the SVZ, cancer stem cells and survival.


Probabilistic independent component analysis of dynamic susceptibility contrast perfusion MRI in metastatic brain tumors.

  • Ararat Chakhoyan‎ et al.
  • Cancer imaging : the official publication of the International Cancer Imaging Society‎
  • 2019‎

To identify clinically relevant magnetic resonance imaging (MRI) features of different types of metastatic brain lesions, including standard anatomical, diffusion weighted imaging (DWI) and dynamic susceptibility contrast (DSC) perfusion MRI.


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