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Biological network figures are ubiquitous in the biology and medical literature. On the one hand, a good network figure can quickly provide information about the nature and degree of interactions between items and enable inferences about the reason for those interactions. On the other hand, good network figures are difficult to create. In this paper, we outline 10 simple rules for creating biological network figures for communication, from choosing layouts, to applying color or other channels to show attributes, to the use of layering and separation. These rules are accompanied by illustrative examples. We also provide a concise set of references and additional resources for each rule. [ABSTRACT FROM AUTHOR]

High dimensional biomedical data contain tens of thousands of features, accurate and effective identification of the core features in these data can be used to assist diagnose related diseases. However, there are often a large number of irrelevant or redundant features in biomedical data, which seriously affect subsequent classification accuracy and machine learning efficiency. To solve this problem, a novel filter feature selection algorithm based on redundant removal (FSBRR) is proposed to classify high dimensional biomedical data in this paper. First of all, two redundant criteria are determined by vertical relevance (the relationship between feature and class attribute) and horizontal relevance (the relationship between feature and feature). Secondly, to quantify redundant criteria, an approximate redundancy feature framework based on mutual information (MI) is defined to remove redundant and irrelevant features. To evaluate the effectiveness of our proposed algorithm, controlled trials based on typical feature selection algorithm are conducted using three different classifiers, and the experimental results indicate that the FSBRR algorithm can effectively reduce the feature dimension and improve the classification accuracy. In addition, an experiment of small sample dataset is designed and conducted in the section of discussion and analysis to clarify the specific implementation process of FSBRR algorithm more clearly. [ABSTRACT FROM AUTHOR]

Our aim was to determine the characteristics, treatments and outcomes of patients with primary spinal glioblastomas (GB) or gliosarcomas (GS) reported in literature until March 2015. PubMed and Web of Science were searched for peer-reviewed articles pertaining to cases of glioblastomas / gliosarcomas with primary spinal origin, using predefined search terms. Furthermore we performed hand searches tracking the references from the selected papers. Eighty-two articles published between 1938 and March 2015 were eligible. They reported on 157 patients. Median age at diagnosis was 22 years. The proportion of patients who received adjuvant chemo- or radiotherapy clearly increased from the time before 1980 until present. Median overall survival from diagnosis was 8.0 ± 0.9 months. On univariate analysis age influenced overall survival, whereas tumor location, gender and the extent of initial resection did not. Outcomes did not differ between children (< 18 years) and adults. However, the patients who were treated after 1980 achieved longer survival times than the patients treated before. On multivariable analysis only age (< 60 years) and the time period of treatment (≥ 1980) were confirmed as positive independent prognostic factors. In conclusion, primary spinal GB / GS mainly affect younger patients and are associated with a dismal prognosis. However, most likely due to the increasing use of adjuvant treatment, modest therapeutic progress has been achieved over recent decades. The characteristics and treatments of primary spinal glioblastomas should be entered into a central registry in order to gain more information about the ideal treatment approach in the future. [ABSTRACT FROM AUTHOR]

The article explores a research concerning the role of RAS gene as a major transforming entity and risks of developing cervical carcinoma, anogenital tract cancers and oropharyngeal tumors among women. The research explores the aspects of polymerase chain reaction (PCR), RNA interference, or CRISPR/CAS9-based genome editinh in biomedical research on cancer cells. The author also highlights the concept of advance studies on cancer cells and its development.

Background: To enhance risk stratification for Wilms tumour (WT) in a pre-operative chemotherapy setting, we explored the prognostic significance and optimal age cutoffs in patients treated according to International Society of Paediatric Oncology Renal Tumour Study Group (SIOP-RTSG) protocols. Methods: Patients(6 months-18 years) with unilateral WT were selected from prospective SIOP 93–01 and 2001 studies(1993–2016). Martingale residual analysis was used to explore optimal age cutoffs. Outcome according to age was analyzed by uni- and multivariable analysis, adjusted for sex, biopsy(yes/no), stage, histology and tumour volume at surgery. Results: 5631 patients were included; median age was 3.4 years(IQR: 2–5.1). Estimated 5-year event-free survival (EFS) and overall survival (OS) were 85%(95%CI 83.5–85.5) and 93%(95%CI 92.0–93.4). Martingale residual plots detected no optimal age cutoffs. Multivariable analysis showed lower EFS with increasing age(linear trend P<0.001). Using previously described age categories, EFS was lower for patients aged 2-4(HR 1.34, P = 0.02), 4-10(HR 1.83, P<0.0001) and 10–18 years(HR 1.74, P = 0.01) as compared to patients aged 6 months-2 years. OS was lower for patients 4–10 years(HR 1.67, P = 0.01) and 10–18 years(HR 1.87, P = 0.04), but not for 2–4 years(HR 1.29, P = 0.23). Higher stage, histological risk group and tumour volume were independent adverse prognostic factors. Conclusion: Although optimal age cutoffs could not be identified, we demonstrated the prognostic significance of age as well as previously described cutoffs for EFS (2 and 4 years) and OS (4 years) in children with WT treated with pre-operative chemotherapy. These findings encourage the consideration of age in the design of future SIOP-RTSG protocols. [ABSTRACT FROM AUTHOR]

Glioblastomas are the most common primary brain tumours. They are known for their highly aggressive growth and invasion, leading to short survival times. Treatments for glioblastomas commonly involve a combination of surgical intervention, chemotherapy, and external beam radiation therapy (XRT). Previous works have not only successfully modelled the natural growth of glioblastomas in vivo, but also show potential for the prediction of response to radiation prior to treatment. This suggests that the efficacy of XRT can be optimized before treatment in order to yield longer survival times. However, while current efforts focus on optimal scheduling of radiotherapy treatment, they do not include a similarly sophisticated spatial optimization. In an effort to improve XRT, we present a method for the spatial optimization of radiation profiles. We expand upon previous results in the general problem and examine the more physically reasonable cases of 1-step and 2-step radiation profiles during the first and second XRT fractions. The results show that by including spatial optimization in XRT, while retaining a constant prescribed total dose amount, we are able to increase the total cell kill from the clinically-applied uniform case. [ABSTRACT FROM AUTHOR]

Objectives: The extent of peritumoral tumor cell infiltrations in glioblastoma contributes to poor prognosis. We aimed to assess additive prognostic value of Minkowski functionals in analyzing heterogeneity of peritumoral hyperintensity on T2WI in glioblastoma patients. Methods: Clinical data (age, sex, extent of surgical resection), O6-methylguanine-DNA methyltransferase (MGMT) promoter methylation status and pre-operative T2WI of 113 pathologically confirmed glioblastoma patients (from our institution, n = 61; from the Cancer Imaging Archive, n = 52) were retrospectively reviewed. The patients were randomly grouped into a training set (n = 80) and a test set (n = 33). Peritumoral T2 hyperintensity was manually segmented and Minkowski functionals—a texture analysis method capturing heterogeneity of MR images—were computed as a function of 11 grayscale thresholds. The Cox proportional hazards models were fitted with clinical variables, Minkowski functionals features as well as both combined. The risk prediction performances of the Minkowski functionals and combined models were validated on a separate test dataset. The sex-specific survival difference of the entire cohort was analyzed according to MGMT methylation status via Kaplan-Meier survival curves. Results: Thirty-three Minkowski features (11 area, 11 perimeter and 11 genus) for each patient were acquired giving a total of 3729 features. Cox regression models fitted with clinical data, Minkowski features, and both combined had incremental concordance indices of 0.577 (P = 0.02), 0.706 (P = 0.02) and 0.714 (P = 0.01) respectively. The prediction error rate of the combined model—having clinical and Minkowski features—was lower than that of Minkowski functionals model (0.135 and 0.161, respectively) when validated on a test dataset. No sex-specific survival difference was found according to MGMT methylation status (male, P = 0.2; female, P = 0.22). Conclusions: Minkowski functionals features computed from peritumoral hyperintensity can capture heterogeneity of glioblastoma on T2WI and have additive prognostic value in predicting survival, demonstrating their potential in complementing currently available prognostic parameters. [ABSTRACT FROM AUTHOR]

Glioblastoma multiforme (GBM) is the most common type of malignant gliomas, characterized by genetic instability, intratumoral histopathological variability and unpredictable clinical behavior. Disappointing results in the treatment of gliomas with surgery, radiation and chemotherapy have fueled a search for new therapeutic targets and treatment modalities. Here we report new approach towards RNA interference therapy of glioblastoma multiforme based on the magnetic nanoparticles delivery of the double-stranded RNA (dsRNA) with homological sequences to mRNA of tenascin-C (TN-C), named ATN-RNA. The obtained nanocomposite consisted of polyethyleneimine (PEI) coated magnetic nanoparticles conjugated to the dsRNA show high efficiency in ATN-RNA delivery, resulting not only in significant TN-C expression level suppressesion, but also impairing the tumor cells migration. Moreover, synthesized nanomaterials show high contrast properties in magnetic resonance imaging (MRI) and low cytotoxicity combining with lack of induction of interferon response. We believe that the present work is a successful combination of effective, functional, non-immunostimulatory dsRNA delivery system based on magnetic nanoparticles with high potential for further application in GBM therapy. [ABSTRACT FROM AUTHOR]

Background: The consistent focus of ‘Advances in Neuroblastoma Research’ congresses on the topic neuroblastoma sets it as a model for a circumscribed scientific community. Methods: The contributions of authors, institutions and countries to congress abstracts and their collaborations were compared to the Hirsch index (h-index) calculated from the Web of Science publication output on the topic ‘neuroblastoma’. Results: From 1975 to 2016, 18 congresses were held. 8459 authors affiliated to 553 institutions of 53 countries presented 3,993 abstracts. The number of coauthors increased over the years from 2 to 7. A considerable proportion of authors, institutions and countries presented only once (53.7%/25.7%/13.2%). Authors with a high number of abstracts and with a large local network were often among those with a higher publication rate and success (R2 = 0.508 for Pearson’s correlation between weight and h-index, R2 = 0.474 for degree centrality, R2 = 0.364 for lobby-index). Closeness and betweenness centralities were less correlated (R2 = 0.127/R2 = 0.33, resp.). The institutions showed a similar impact of local interactions on publication success (degree centrality R2 = 0.417, weight R2 = 0.308), while countries demonstrated a higher correlation of betweenness centrality and h-Index (R2 = 0.704) emphasizing their brokerage role. Of 553 institutions, 520 collaborated within 13 communities and belonged to the large scientific network. 33 satellite institutions had no connections to the central network. They attended 1–4 congresses over a period of 1–16 years. Conclusion: A large scientific network has been developed during the recent 42 years. Growth and interaction at congresses were correlated to publication success. Weight is suggested as a useful and simple estimate. [ABSTRACT FROM AUTHOR]

Introduction: Risk of developing a malignancy when born premature is unknown. We hypothesised that risk of certain cancers might be increased in youth born preterm versus term. We therefore performed a systematic review and meta-analysis to evaluate the incidence of malignancy in the context of preterm birth, according to various cancer types. Methods: The study was designed per MOOSE and PRISMA guidelines. Articles were identified through November 2015. Observational studies exploring the association between childhood malignancy and birth characteristics were included. Of the 1658 records identified, 109 full text articles were evaluated for eligibility. Random effects meta-analyses were conducted on 10/26 studies retained; 95% confidence intervals were computed and adjusted following sensitivity analysis. Publication bias was evaluated using funnel plots, Begg’s and Egger’s tests. Results: No differences in risk of primary central nervous system tumor [OR 1.05; 95% CI 0.93–1.17, 5 studies, 580 cases] and neuroblastoma [OR 1.09; 95% CI 0.90–1.32, 5 studies, 211 cases] were observed in individuals born <37 versus ≥37 weeks’ gestation. Preterm birth was consistently associated with hepatoblastoma [ORs 3.12 (95% CI 2.32–4.20), 1.52 (95% CI 1.1–2.1), 1.82 (95% CI 1.01–3.26), and 2.65 (95% CI 1.98–3.55)], but not leukemia, astrocytoma, ependymoma, medulloblastoma, lymphoma, nephroblastoma, rhabdomyosarcoma, retinoblastoma or thyroid cancer. Conclusions: Children born premature may be at increased risk for hepatoblastoma but there is no strong evidence of an increased risk of primary central nervous system tumours or neuroblastoma. There is insufficient evidence to conclude whether prematurity modulates the risk of other childhood cancers. [ABSTRACT FROM AUTHOR]

We introduce the CDRP (Concatenated Diagnostic-Relapse Prognostic) architecture for multi-task deep learning that incorporates a clinical algorithm, e.g., a risk stratification schema to improve prognostic profiling. We present the first application to survival prediction in High-Risk (HR) Neuroblastoma from transcriptomics data, a task that studies from the MAQC consortium have shown to remain the hardest among multiple diagnostic and prognostic endpoints predictable from the same dataset. To obtain a more accurate risk stratification needed for appropriate treatment strategies, CDRP combines a first component (CDRP-A) synthesizing a diagnostic task and a second component (CDRP-N) dedicated to one or more prognostic tasks. The approach leverages the advent of semi-supervised deep learning structures that can flexibly integrate multimodal data or internally create multiple processing paths. CDRP-A is an autoencoder trained on gene expression on the HR/non-HR risk stratification by the Children’s Oncology Group, obtaining a 64-node representation in the bottleneck layer. CDRP-N is a multi-task classifier for two prognostic endpoints, i.e., Event-Free Survival (EFS) and Overall Survival (OS). CDRP-A provides the HR embedding input to the CDRP-N shared layer, from which two branches depart to model EFS and OS, respectively. To control for selection bias, CDRP is trained and evaluated using a Data Analysis Protocol (DAP) developed within the MAQC initiative. CDRP was applied on Illumina RNA-Seq of 498 Neuroblastoma patients (HR: 176) from the SEQC study (12,464 Entrez genes) and on Affymetrix Human Exon Array expression profiles (17,450 genes) of 247 primary diagnostic Neuroblastoma of the TARGET NBL cohort. On the SEQC HR patients, CDRP achieves Matthews Correlation Coefficient (MCC) 0.38 for EFS and MCC = 0.19 for OS in external validation, improving over published SEQC models. We show that a CDRP-N embedding is indeed parametrically associated to increasing severity and the embedding can be used to better stratify patients’ survival. [ABSTRACT FROM AUTHOR]

Sequencing of the T cell receptor repertoire is a powerful tool for deeper study of immune response, but the unique structure of this type of data makes its meaningful quantification challenging. We introduce a new method, the Gamma-GPD spliced threshold model, to address this difficulty. This biologically interpretable model captures the distribution of the TCR repertoire, demonstrates stability across varying sequencing depths, and permits comparative analysis across any number of sampled individuals. We apply our method to several datasets and obtain insights regarding the differentiating features in the T cell receptor repertoire among sampled individuals across conditions. We have implemented our method in the open-source R package powerTCR. [ABSTRACT FROM AUTHOR]

Significant advances in biotechnology have allowed for simultaneous measurement of molecular data across multiple genomic, epigenomic and transcriptomic levels from a single tumor/patient sample. This has motivated systematic data-driven approaches to integrate multi-dimensional structured datasets, since cancer development and progression is driven by numerous co-ordinated molecular alterations and the interactions between them. We propose a novel multi-scale Bayesian approach that combines integrative graphical structure learning from multiple sources of data with a variable selection framework—to determine the key genomic drivers of cancer progression. The integrative structure learning is first accomplished through novel joint graphical models for heterogeneous (mixed scale) data, allowing for flexible and interpretable incorporation of prior existing knowledge. This subsequently informs a variable selection step to identify groups of co-ordinated molecular features within and across platforms associated with clinical outcomes of cancer progression, while according appropriate adjustments for multicollinearity and multiplicities. We evaluate our methods through rigorous simulations to establish superiority over existing methods that do not take the network and/or prior information into account. Our methods are motivated by and applied to a glioblastoma multiforme (GBM) dataset from The Cancer Genome Atlas to predict patient survival times integrating gene expression, copy number and methylation data. We find a high concordance between our selected prognostic gene network modules with known associations with GBM. In addition, our model discovers several novel cross-platform network interactions (both cis and trans acting) between gene expression, copy number variation associated gene dosing and epigenetic regulation through promoter methylation, some with known implications in the etiology of GBM. Our framework provides a useful tool for biomedical researchers, since clinical prediction using multi-platform genomic information is an important step towards personalized treatment of many cancers. [ABSTRACT FROM AUTHOR]

Introduction: Aim was to develop a full automatic clustering approach of the time-activity curves (TAC) from dynamic 18F-FET PET and evaluate its association with IDH1 mutation status and survival in patients with gliomas. Methods: Thirty-seven patients (mean age: 45±13 y) with newly diagnosed gliomas and dynamic 18F-FET PET before any histopathologic investigation or treatment were retrospectively included. Each dynamic 18F-FET PET was realigned to the first image and spatially normalized in the Montreal Neurological Institute template. A tumor mask was semi-automatically generated from Z-score maps. Each brain tumor voxel was clustered in one of the 3 following centroids using dynamic time warping and k-means clustering (centroid #1: slowly increasing slope; centroid #2: rapidly increasing followed by slowly decreasing slope; and centroid #3: rapidly increasing followed by rapidly decreasing slope). The percentage of each dynamic 18F-FET TAC within tumors and other conventional 18F-FET PET parameters (maximum and mean tumor-to-brain ratios [TBRmax and TBRmean], time-to-peak [TTP] and slope) was compared between wild-type and IDH1 mutant tumors. Their prognostic value was assessed in terms of progression free-survival (PFS) and overall survival (OS) by Kaplan-Meier estimates. Results: Twenty patients were IDH1 wild-type and 17 IDH1 mutant. Higher percentage of centroid #1 and centroid #3 within tumors were positively (P = 0.016) and negatively (P = 0.01) correlated with IDH1 mutated status. Also, TBRmax, TBRmean, TTP, and slope discriminated significantly between tumors with and without IDH1 mutation (P range 0.01 to 0.04). Progression occurred in 22 patients (59%) at a median of 13.1 months (7.6–37.6 months) and 13 patients (35%) died from tumor progression. Patients with a percentage of centroid #1 > 90% had a longer survival compared with those with a percentage of centroid #1 < 90% (P = 0.003 for PFS and P = 0.028 for OS). This remained significant after stratification on IDH1 mutation status (P = 0.029 for PFS and P = 0.034 for OS). Compared to other conventional 18F-FET PET parameters, TTP and slope were associated with PFS and OS (P range 0.009 to 0.04). Conclusions: Based on dynamic 18F-FET PET acquisition, we developed a full automatic clustering approach of TAC which appears to be a valuable noninvasive diagnostic and prognostic marker in patients with gliomas. [ABSTRACT FROM AUTHOR]

A multi-center imaging trial by the American College of Radiology Imaging Network (ACRIN) “A Multicenter, phase II assessment of tumor hypoxia in glioblastoma using 18F Fluoromisonidazole (FMISO) with PET and MRI (ACRIN 6684)”, was conducted to assess hypoxia in patients with glioblastoma (GBM). The aims of this study were to support the role of proton magnetic resonance spectroscopic imaging (1H MRSI) as a prognostic marker for brain tumor patients in multi-center clinical trials. Seventeen participants from four sites had analyzable 3D MRSI datasets acquired on Philips, GE or Siemens scanners at either 1.5T or 3T. MRSI data were analyzed using LCModel to quantify metabolites N-acetylaspartate (NAA), creatine (Cr), choline (Cho), and lactate (Lac). Receiver operating characteristic curves for NAA/Cho, Cho/Cr, lactate/Cr, and lactate/NAA were constructed for overall survival at 1-year (OS-1) and 6-month progression free survival (PFS-6). The OS-1 for the 17 evaluable patients was 59% (10/17). Receiver operating characteristic analyses found the NAA/Cho in tumor (AUC = 0.83, 95% CI: 0.61 to 1.00) and in peritumoral regions (AUC = 0.95, 95% CI 0.85 to 1.00) were predictive for survival at 1 year. PFS-6 was 65% (11/17). Neither NAA/Cho nor Cho/Cr was effective in predicting 6-month progression free survival. Lac/Cr in tumor was a significant negative predictor of PFS-6, indicating that higher lactate/Cr levels are associated with poorer outcome. (AUC = 0.79, 95% CI: 0.54 to 1.00). In conclusion, despite the small sample size in the setting of a multi-center trial comprising different vendors, field strengths, and varying levels of expertise at data acquisition, MRS markers NAA/Cho, Lac/Cr and Lac/NAA predicted overall survival at 1 year and 6-month progression free survival. This study validates that MRSI may be useful in evaluating the prognosis in glioblastoma and should be considered for incorporating into multi-center clinical trials. [ABSTRACT FROM AUTHOR]

Purpose: To report associations between disease- and treatment-related variables and rates of recurrence-free survival and ocular survival in eyes treated with ophthalmic artery chemosurgery (OAC) for retinoblastoma. Design: Pre-post study. Subjects: All eyes treated with OAC for retinoblastoma at Memorial Sloan Kettering Cancer Center between May 2006 and February 2017. Methods: This retrospective review included 452 retinoblastoma eyes treated with OAC. The Kaplan-Meier method was used to estimate recurrence-free survival (RFS), progression-free survival (PFS) and ocular survival (OcS), and Cox regression was used to estimate hazard ratios. Eyes treated in the pre-intravitreous chemotherapy era were analyzed separately from eyes treated in the intravitreal era. Main outcome measures: Recurrence-free survival, ocular survival, associations with risk of recurrence Results: Disease and treatment characteristics were recorded over a median 23.6 month follow-up. One-year OcS, PFS and RFS were 96% (95% CI 93–99%), 88% (95% CI 88–94%) and 74% (95% CI 67–81%) in the pre-intravitreal era and 96% (95% CI 94–99%), 93% (95% CI 89–96%) and 78% (95% CI 72–83%) in the intravitreal era, respectively. Presence of vitreous seeds was associated with increased risk of recurrence in the pre-intravitreal era but not in the intravitreal era. Longer time interval between OAC sessions was associated with increased risk of recurrence and majority OAC access via the ophthalmic artery was associated with decreased risk of recurrence in both eras. Conclusions: Approximately a quarter of eyes initially treated with ophthalmic artery chemosurgery develop recurrent disease, with the majority of recurrences within the first year following completion of OAC. Despite this, these eyes have a very good chance of salvage. In eyes with vitreous seeds at presentation, intravitreal injections are useful in minimizing future vitreous recurrence. Eyes that receive the majority of drug infusions via non-ophthalmic artery routes or greater interval between OAC are more likely to recur and might warrant closer monitoring. [ABSTRACT FROM AUTHOR]

Purpose: Peritumoral edema impedes the full delineation of fiber tracts due to partial volume effects in image voxels that contain a mixture of cerebral parenchyma and extracellular water. The purpose of this study is to investigate the effect of incorporating a free water (FW) model of edema for white matter tractography in the presence of edema. Materials and methods: We retrospectively evaluated 26 consecutive brain tumor patients with diffusion MRI and T2-weighted images acquired presurgically. Tractography of the arcuate fasciculus (AF) was performed using the two-tensor unscented Kalman filter tractography (UKFt) method, the UKFt method with a reduced fiber tracking stopping fractional anisotropy (FA) threshold (UKFt+rFA), and the UKFt method with the addition of a FW compartment (UKFt+FW). An automated white matter fiber tract identification approach was applied to delineate the AF. Quantitative measurements included tract volume, edema volume, and mean FW fraction. Visual comparisons were performed by three experts to evaluate the quality of the detected AF tracts. Results: The AF volume in edematous brain hemispheres was significantly larger using the UKFt+FW method (p<0.0001) compared to UKFt, but not significantly larger (p = 0.0996) in hemispheres without edema. The AF size increase depended on the volume of edema: a significant correlation was found between AF volume affected by (intersecting) edema and AF volume change with the FW model (Pearson r = 0.806, p<0.0001). The mean FW fraction was significantly larger in tracts intersecting edema (p = 0.0271). Compared to the UKFt+rFA method, there was a significant increase of the volume of the AF tract that intersected the edema using the UKFt+FW method, while the whole AF volumes were similar. Expert judgment results, based on the five patients with the smallest AF volumes, indicated that the expert readers generally preferred the AF tract obtained by using the FW model, according to their anatomical knowledge and considering the potential influence of the final results on the surgical route. Conclusion: Our results indicate that incorporating biophysical models of edema can increase the sensitivity of tractography in regions of peritumoral edema, allowing better tract visualization in patients with high grade gliomas and metastases. [ABSTRACT FROM AUTHOR]

Although studies from pediatric cancers (largely acute lymphoblastic leukemia) have shown that patients undergoing systemic chemotherapy may experience decreased growth velocity during the treatment phase, no such data exist for retinoblastoma patients treated with systemic chemotherapy or ophthalmic artery chemosurgery (OAC). The purpose of this study is to report growth patterns of our retinoblastoma (Rb) population who were treated with OAC in a retrospective, single center (Memorial Sloan Kettering Cancer Center) review of 341 patients treated between 2006 and 2016. Children who only received OAC were classified as naive; those who were treated initially with systemic chemotherapy and subsequently presented to our center for OAC were termed secondary; and a small group of patients who received single-agent systemic chemotherapy prior to OAC were labeled bridge. For all patients, height and weight were recorded at monthly intervals during OAC (short-term) and then annually during a follow-up period (long-term) up to 3 years after treatment. Excluded from this study were children who received external radiation therapy and those with genetic syndromes, which are independently associated with growth derangements. During OAC, there was no significant difference in growth velocity between the naïve and secondary groups. In either group, number of treatments also did not affect growth rate. Three years after the end of OAC, naïve patients were in the 68th percentile by height (95% CI 61.30, 74.63) compared to secondary patients in the 61st percentile (95% CI 51.1, 71.47). Both groups were in the same weight percentiles during the first two years of follow-up but at the three-year follow-up period, naïve patients were in the 63rd percentile (95% CI 57.4, 69.4) and secondary patients were in the 60th percentile (95% CI 50.4, 69.7). OAC for retinoblastoma does not appear to impact short-term growth velocity, weight gain during the treatment period or after three years. [ABSTRACT FROM AUTHOR]

Introduction: Leptomeningeal disease is a feared sequelae of malignant paediatric brain tumours. Current methods for its detection is the combined use of cranio-spinal MRI, and CSF cytology from a post-operative lumbar puncture. In this study, the authors hypothesize that CSF taken at the start of surgery, either from an external ventricular drain or neuroendoscope will have equal sensitivity for positive tumour cells, in comparison to lumbar puncture. Secondary hypotheses include positive correlation between CSF cytology and MRI findings of LMD. From a clinical perspective, the key aim of the study was for affected paediatric patients to avoid an additional procedure of a lumbar puncture, often performed under anaesthesia after neurosurgical intervention. Methods: This is single-institution, retrospective study of paediatric patients diagnosed with malignant brain tumours. Its main aim was to compare cytological data from CSF collected at the time of surgery versus data from an interval lumbar puncture. In addition, MRI imaging of the same cohort of patients was examined for leptomeningeal disease and corroborated against CSF tumour cytology findings. Results: Thirty patients are recruited for this study. Data analysis demonstrates a statistically significant association between our intra-operative CSF and LP sampling. Furthermore, our results also show for significant correlation between evidence of leptomeningeal disease on MRI findings versus intra-operative CSF positivity for tumour cells. Conclusion: Although this is a retrospective study with a limited population, our data concurs with potential to avoid an additional procedure for the paediatric patient diagnosed with a malignant brain tumour. [ABSTRACT FROM AUTHOR]

One of the goals of cancer research is to identify a set of genes that cause or control disease progression. However, although multiple such gene sets were published, these are usually in very poor agreement with each other, and very few of the genes proved to be functional therapeutic targets. Furthermore, recent findings from a breast cancer gene-expression cohort showed that sets of genes selected randomly can be used to predict survival with a much higher probability than expected. These results imply that many of the genes identified in breast cancer gene expression analysis may not be causal of cancer progression, even though they can still be highly predictive of prognosis. We performed a similar analysis on all the cancer types available in the cancer genome atlas (TCGA), namely, estimating the predictive power of random gene sets for survival. Our work shows that most cancer types exhibit the property that random selections of genes are more predictive of survival than expected. In contrast to previous work, this property is not removed by using a proliferation signature, which implies that proliferation may not always be the confounder that drives this property. We suggest one possible solution in the form of data-driven sub-classification to reduce this property significantly. Our results suggest that the predictive power of random gene sets may be used to identify the existence of sub-classes in the data, and thus may allow better understanding of patient stratification. Furthermore, by reducing the observed bias this may allow more direct identification of biologically relevant, and potentially causal, genes. [ABSTRACT FROM AUTHOR]

Glioma is the most common malignant intracranial tumour. Recently, several publications have suggested that miRNAs can be used as potential diagnostic biomarkers of glioma. Here we performed a meta-analysis to identify the diagnostic accuracy of differentially expressed circulating miRNAs in gliomas. Using PubMed, Medline and Cochrane databases, we searched for studies which evaluated a single or panel of miRNAs from circulating blood as potential biomarkers of glioma. Sixteen publications involving 23 studies of miRNAs from serum or plasma met our criteria and were included in this meta-analysis. The pooled diagnostic parameters were calculated by random effect models and overall diagnostic performance of altered miRNAs was illustrated by the summary receiver operator characteristic (SROC) curves. The pooled sensitivity, specificity, positive likelihood ratio (PLR) and negative likelihood ratio (NLR) from each study were calculated. The pooled PLR, NLR and Diagnostic Odds Ratio were 6.39 (95% CI, 4.61–8.87), 0.15 (95% CI, 0.11–0.21) and 41.91 (95% CI, 23.15–75.88), respectively. The pooled sensitivity, specificity and area under the curve (AUC) were 0.87 (95% CI, 0.82–0.91), 0.86 (95% CI, 0.82–0.90) and 0.93 (95% CI, 0.91–0.95), respectively. This meta-analysis demonstrated that circulating miRNAs are capable of distinguishing glioma from healthy controls. Circulating miRNAs are promising diagnostic biomarkers for glioma and can potentially be used as a non-invasive early detection. [ABSTRACT FROM AUTHOR]

Current treatments for glioblastoma multiforme (GBM)—an aggressive form of brain cancer—are minimally effective and yield a median survival of 14.6 months and a two-year survival rate of 30%. Given the severity of GBM and the limitations of its treatment, there is a need for the discovery of novel drug targets for GBM and more personalized treatment approaches based on the characteristics of an individual’s tumor. Most receptor tyrosine kinases—such as EGFR—act as oncogenes, but publicly available data from the Cancer Cell Line Encyclopedia (CCLE) indicates copy number loss in the ERBB4 RTK gene across dozens of GBM cell lines, suggesting a potential tumor suppressor role. This loss is mutually exclusive with loss of its cognate ligand NRG1 in CCLE as well, more strongly suggesting a functional role. The availability of higher resolution copy number data from clinical GBM patients in The Cancer Genome Atlas (TCGA) revealed that a region in Intron 1 of the ERBB4 gene was deleted in 69.1% of tumor samples harboring ERBB4 copy number loss; however, it was also found to be deleted in the matched normal tissue samples from these GBM patients (n = 81). Using the DECIPHER Genome Browser, we also discovered that this mutation occurs at approximately the same frequency in the general population as it does in the disease population. We conclude from these results that this loss in Intron 1 of the ERBB4 gene is neither a de novo driver mutation nor a predisposing factor to GBM, despite the indications from CCLE. A biological role of this significantly occurring genetic alteration is still unknown. While this is a negative result, the broader conclusion is that while copy number data from large cell line-based data repositories may yield compelling hypotheses, careful follow up with higher resolution copy number assays, patient data, and general population analyses are essential to codify initial hypotheses prior to investing experimental resources. [ABSTRACT FROM AUTHOR]

Resection of the bulk of a tumour often cannot eliminate all cancer cells, due to their infiltration into the surrounding healthy tissue. This may lead to recurrence of the tumour at a later time. We use a reaction-diffusion equation based model of tumour growth to investigate how the invasion front is delayed by resection, and how this depends on the density and behaviour of the remaining cancer cells. We show that the delay time is highly sensitive to qualitative details of the proliferation dynamics of the cancer cell population. The typically assumed logistic type proliferation leads to unrealistic results, predicting immediate recurrence. We find that in glioblastoma cell cultures the cell proliferation rate is an increasing function of the density at small cell densities. Our analysis suggests that cooperative behaviour of cancer cells, analogous to the Allee effect in ecology, can play a critical role in determining the time until tumour recurrence. [ABSTRACT FROM AUTHOR]

LDL receptor-related proteins (LRPs) are transmembrane receptors involved in endocytosis, cell-signaling, and trafficking of other cellular proteins. Considerable work has focused on LRPs in the fields of vascular biology and neurobiology. How these receptors affect cancer progression in humans remains largely unknown. Herein, we mined provisional databases in The Cancer Genome Atlas (TCGA) to compare expression of thirteen LRPs in ten common solid malignancies in patients. Our first goal was to determine the abundance of LRP mRNAs in each type of cancer. Our second goal was to determine whether expression of LRPs is associated with improved or worsened patient survival. In total, data from 4,629 patients were mined. In nine of ten cancers studied, the most abundantly expressed LRP was LRP1; however, a correlation between LRP1 mRNA expression and patient survival was observed only in bladder urothelial carcinoma. In this malignancy, high levels of LRP1 mRNA were associated with worsened patient survival. High levels of LDL receptor (LDLR) mRNA were associated with decreased patient survival in pancreatic adenocarcinoma. High levels of LRP10 mRNA were associated with decreased patient survival in hepatocellular carcinoma, lung adenocarcinoma, and pancreatic adenocarcinoma. LRP2 was the only LRP for which high levels of mRNA expression correlated with improved patient survival. This correlation was observed in renal clear cell carcinoma. Insights into LRP gene expression in human cancers and their effects on patient survival should guide future research. [ABSTRACT FROM AUTHOR]

Reverse transcription quantitative polymerase chain reaction (RT-qPCR) is considered as the gold standard for accurate, sensitive, and fast measurement of gene expression. Prior to downstream statistical analysis, RT-qPCR fluorescence amplification curves are summarized into one single value, the quantification cycle (Cq). When RT-qPCR does not reach the limit of detection, the Cq is labeled as “undetermined”. Current state of the art qPCR data analysis pipelines acknowledge the importance of normalization for removing non-biological sample to sample variation in the Cq values. However, their strategies for handling undetermined Cq values are very ad hoc. We show that popular methods for handling undetermined values can have a severe impact on the downstream differential expression analysis. They introduce a considerable bias and suffer from a lower precision. We propose a novel method that unites preprocessing and differential expression analysis in a single statistical model that provides a rigorous way for handling undetermined Cq values. We compare our method with existing approaches in a simulation study and on published microRNA and mRNA gene expression datasets. We show that our method outperforms traditional RT-qPCR differential expression analysis pipelines in the presence of undetermined values, both in terms of accuracy and precision. [ABSTRACT FROM AUTHOR]

To investigate in patients with retinoblastoma (RB). We collected 0.1 ml AH of 35 children with RB and 20 patients with congenital cataracts as controls. Multiplex enzyme-linked immunosorbent assays (ELISAs) and Luminex xMAP technology were used to assess 45 cytokines/chemokines, matrix metalloproteinases (MMPs), and acute-phase proteins in the identification cohort. The concentrations of IL-6, IL-7, IL-8, IFN-γ, PIGF-1, VEGF-A, β-NGF, HGF, EGF and FGF-2 were significantly higher in the AH of patients with RB than those in the control group (P<0.05). The study showed that the higher levels of IP-10, IL-6, IL-7, IL-8, IFN-γ, PIGF-1, VEGF-A, β-NGF, HGF, EGF and FGF-2 in AH may be associated with RB. Our findings may facilitate a better understanding of the molecular pathways of tumors and solid molecular targets for new strategies for therapy and the earlier diagnosis of RB. [ABSTRACT FROM AUTHOR]

Integrative analyses of high-throughput ‘omic data, such as DNA methylation, DNA copy number alteration, mRNA and protein expression levels, have created unprecedented opportunities to understand the molecular basis of human disease. In particular, integrative analyses have been the cornerstone in the study of cancer to determine molecular subtypes within a given cancer. As malignant tumors with similar morphological characteristics have been shown to exhibit entirely different molecular profiles, there has been significant interest in using multiple ‘omic data for the identification of novel molecular subtypes of disease, which could impact treatment decisions. Therefore, we have developed intNMF, an integrative approach for disease subtype classification based on non-negative matrix factorization. The proposed approach carries out integrative clustering of multiple high dimensional molecular data in a single comprehensive analysis utilizing the information across multiple biological levels assessed on the same individual. As intNMF does not assume any distributional form for the data, it has obvious advantages over other model based clustering methods which require specific distributional assumptions. Application of intNMF is illustrated using both simulated and real data from The Cancer Genome Atlas (TCGA). [ABSTRACT FROM AUTHOR]

A small molecule which specifically blocks the interaction of Rictor and mTOR was identified utilizing a high-throughput yeast two-hybrid screen and evaluated as a potential inhibitor of mTORC2 activity in glioblastoma multiforme (GBM). In vitro, CID613034 inhibited mTORC2 kinase activity at submicromolar concentrations and in cellular assays specifically inhibited phosphorylation of mTORC2 substrates, including AKT (Ser-473), NDRG1 (Thr-346) and PKCα (Ser-657), while having no appreciable effects on the phosphorylation status of the mTORC1 substrate S6K (Thr-389) or mTORC1-dependent negative feedback loops. CID613034 demonstrated significant inhibitory effects on cell growth, motility and invasiveness in GBM cell lines and sensitivity correlated with relative Rictor or SIN1 expression. Structure-activity relationship analyses afforded an inhibitor, JR-AB2-011, with improved anti-GBM properties and blocked mTORC2 signaling and Rictor association with mTOR at lower effective concentrations. In GBM xenograft studies, JR-AB2-011 demonstrated significant anti-tumor properties. These data support mTORC2 as a viable therapeutic target in GBM and suggest that targeting protein-protein interactions critical for mTORC2 function is an effective strategy to achieve therapeutic responses. [ABSTRACT FROM AUTHOR]

Medulloblastoma is a fatal brain tumor in children, primarily due to the presence of treatment-resistant medulloblastoma stem cells. The energy metabolic pathway is a potential target of cancer therapy because it is often different between cancer cells and normal cells. However, the metabolic properties of medulloblastoma stem cells, and whether specific metabolic pathways are essential for sustaining their stem cell-like phenotype and radioresistance, remain unclear. We have established radioresistant medulloblastoma stem-like clones (rMSLCs) by irradiation of the human medulloblastoma cell line ONS-76. Here, we assessed reactive oxygen species (ROS) production, mitochondria function, oxygen consumption rate (OCR), energy state, and metabolites of glycolysis and tricarboxylic acid cycle in rMSLCs and parental cells. rMSLCs showed higher lactate production and lower oxygen consumption rate than parental cells. Additionally, rMSLCs had low mitochondria mass, low endogenous ROS production, and existed in a low-energy state. Treatment with the metabolic modifier dichloroacetate (DCA) resulted in mitochondria dysfunction, glycolysis inhibition, elongated mitochondria morphology, and increased ROS production. DCA also increased radiosensitivity by suppression of the DNA repair capacity through nuclear oxidization and accelerated the generation of acetyl CoA to compensate for the lack of ATP. Moreover, treatment with DCA decreased cancer stem cell-like characters (e.g., CD133 positivity and sphere-forming ability) in rMSLCs. Together, our findings provide insights into the specific metabolism of rMSLCs and illuminate potential metabolic targets that might be exploited for therapeutic benefit in medulloblastoma. [ABSTRACT FROM AUTHOR]

Retinoblastoma and uveal melanoma are fast spreading eye tumors usually diagnosed by using 2D Fundus Image Photography (Fundus) and 2D Ultrasound (US). Diagnosis and treatment planning of such diseases often require additional complementary imaging to confirm the tumor extend via 3D Magnetic Resonance Imaging (MRI). In this context, having automatic segmentations to estimate the size and the distribution of the pathological tissue would be advantageous towards tumor characterization. Until now, the alternative has been the manual delineation of eye structures, a rather time consuming and error-prone task, to be conducted in multiple MRI sequences simultaneously. This situation, and the lack of tools for accurate eye MRI analysis, reduces the interest in MRI beyond the qualitative evaluation of the optic nerve invasion and the confirmation of recurrent malignancies below calcified tumors. In this manuscript, we propose a new framework for the automatic segmentation of eye structures and ocular tumors in multi-sequence MRI. Our key contribution is the introduction of a pathological eye model from which Eye Patient-Specific Features (EPSF) can be computed. These features combine intensity and shape information of pathological tissue while embedded in healthy structures of the eye. We assess our work on a dataset of pathological patient eyes by computing the Dice Similarity Coefficient (DSC) of the sclera, the cornea, the vitreous humor, the lens and the tumor. In addition, we quantitatively show the superior performance of our pathological eye model as compared to the segmentation obtained by using a healthy model (over 4% DSC) and demonstrate the relevance of our EPSF, which improve the final segmentation regardless of the classifier employed. [ABSTRACT FROM AUTHOR]

In the recent few years, an increasing number of studies have shown that microRNAs (miRNAs) play critical roles in many fundamental and important biological processes. As one of pathogenetic factors, the molecular mechanisms underlying human complex diseases still have not been completely understood from the perspective of miRNA. Predicting potential miRNA-disease associations makes important contributions to understanding the pathogenesis of diseases, developing new drugs, and formulating individualized diagnosis and treatment for diverse human complex diseases. Instead of only depending on expensive and time-consuming biological experiments, computational prediction models are effective by predicting potential miRNA-disease associations, prioritizing candidate miRNAs for the investigated diseases, and selecting those miRNAs with higher association probabilities for further experimental validation. In this study, ath-ased iRNA-isease ssociation (PBMDA) prediction model was proposed by integrating known human miRNA-disease associations, miRNA functional similarity, disease semantic similarity, and Gaussian interaction profile kernel similarity for miRNAs and diseases. This model constructed a heterogeneous graph consisting of three interlinked sub-graphs and further adopted depth-first search algorithm to infer potential miRNA-disease associations. As a result, PBMDA achieved reliable performance in the frameworks of both local and global LOOCV (AUCs of 0.8341 and 0.9169, respectively) and 5-fold cross validation (average AUC of 0.9172). In the cases studies of three important human diseases, 88% (Esophageal Neoplasms), 88% (Kidney Neoplasms) and 90% (Colon Neoplasms) of top-50 predicted miRNAs have been manually confirmed by previous experimental reports from literatures. Through the comparison performance between PBMDA and other previous models in case studies, the reliable performance also demonstrates that PBMDA could serve as a powerful computational tool to accelerate the identification of disease-miRNA associations. [ABSTRACT FROM AUTHOR]

Glioblastoma (GBM) is a malignant brain tumor that continues to be associated with neurological morbidity and poor survival times. Brain invasion is a fundamental property of malignant glioma cells. The Go-or-Grow (GoG) phenotype proposes that cancer cell motility and proliferation are mutually exclusive. Here, we construct and apply a single glioma cell mathematical model that includes motility and angiogenesis and lacks the GoG phenotype. Simulations replicate key features of GBM including its multilayer structure (i.e.edema, enhancement, and necrosis), its progression patterns associated with bevacizumab treatment, and replicate the survival times of GBM treated or untreated with bevacizumab. These results suggest that the GoG phenotype is not a necessary property for the formation of the multilayer structure, recurrence patterns, and the poor survival times of patients diagnosed with GBM. [ABSTRACT FROM AUTHOR]

Background and Purpose: Although bevacizumab (BV) has been approved as second-line therapy for recurrent glioblastoma (GB), the efficacy and safety of BV for patients with newly diagnosed GB remain unclear. Methodology/Principal Findings: We systematically searched electronic databases (PubMed, EMBASE, OVID, etc.) to identify related studies published from January 1966 and August 2016. Eight randomized controlled trials including a total of 2,185 patients with GB were included. We found that the median progression-free survival (PFS) was higher in the BV group than in the standard therapy (ST) group (pooled hazard ratio, 0.73; 95%CI, 0.62–0.86; P = 0.0001). Compared with ST, BV improved the PFS rate at 6 months (OR 3.33, 95% CI 2.73–4.06, p<0.00001) and 12 months (OR 2.10, 95% CI 1.74–2.54, p<0.00001). There were no significant differences in median overall survival between the BV and ST groups (OR, 1.01; 95%CI, 0.83–1.23; P = 0.95). The BV group had higher survival rates at 6 months (OR, 1.41; 95% CI, 1.09–1.84; P = 0.01) and 12 months (OR, 1.23; 95% CI, 1.02–1.48; P = 0.03), but a low survival rate at the 36-month follow-up (OR, 0.57; 95% CI, 0.32–0.98; P = 0.04). For the incidence of adverse events, three adverse outcomes were found to be significantly different between BV and ST groups, including hypertension (8.37% vs. 1.62%, p<0.000001), proteinuria (7.65% vs. 0%, p<0.001), and fatigue (14.54% vs. 9.01%, p = 0.05). Conclusions/Significance: Our study indicates that combination of BV with ST for newly diagnosed GB did not improve the median overall survival but result in longer median PFS, maintaining the quality of life and functional status. However, the long-term use of BV is associated with a higher incidence of adverse events and mortality. Study Registration: This research was registered at PROSPERO. (Registration Number: CRD42016038247). [ABSTRACT FROM AUTHOR]

Neuroblastoma is characterized by a relative paucity of recurrent somatic mutations at diagnosis. However, recent studies have shown that the mutational burden increases at relapse, likely as a result of clonal evolution of mutation-carrying cells during primary treatment. To inform the development of personalized therapies, we sought to further define the frequency of potentially actionable mutations in neuroblastoma, both at diagnosis and after chemotherapy. We performed a retrospective study to determine mutation frequency, the only inclusion criterion being availability of cancer gene panel sequencing data from Foundation Medicine. We analyzed 151 neuroblastoma tumor samples: 44 obtained at diagnosis, 42 at second look surgery or biopsy for stable disease after chemotherapy, and 59 at relapse (6 were obtained at unknown time points). Nine patients had multiple tumor biopsies. ALK was the most commonly mutated gene in this cohort, and we observed a higher frequency of suspected oncogenic ALK mutations in relapsed disease than at diagnosis. Patients with relapsed disease had, on average, a greater number of mutations reported to be recurrent in cancer, and a greater number of mutations in genes that are potentially targetable with available therapeutics. We also observed an enrichment of reported recurrent RAS/MAPK pathway mutations in tumors obtained after chemotherapy. Our data support recent evidence suggesting that neuroblastomas undergo substantial mutational evolution during therapy, and that relapsed disease is more likely to be driven by a targetable oncogenic pathway, highlighting that it is critical to base treatment decisions on the molecular profile of the tumor at the time of treatment. However, it will be necessary to conduct prospective clinical trials that match sequencing results to targeted therapeutic intervention to determine if cancer genomic profiling improves patient outcomes. [ABSTRACT FROM AUTHOR]

We present here a novel genetic algorithm-based random forest (GARF) modeling technique that enables a reduction in the complexity of large gene disease signatures to highly accurate, greatly simplified gene panels. When applied to 803 glioblastoma multiforme samples, this method allowed the 840-gene Verhaak et al. gene panel (the standard in the field) to be reduced to a 48-gene classifier, while retaining 90.91% classification accuracy, and outperforming the best available alternative methods. Additionally, using this approach we produced a 32-gene panel which allows for better consistency between RNA-seq and microarray-based classifications, improving cross-platform classification retention from 69.67% to 86.07%. A webpage producing these classifications is available at . [ABSTRACT FROM AUTHOR]

Background: The advance of omics technologies has made possible to measure several data modalities on a system of interest. In this work, we illustrate how the Non-Parametric Combination methodology, namely NPC, can be used for simultaneously assessing the association of different molecular quantities with an outcome of interest. We argue that NPC methods have several potential applications in integrating heterogeneous omics technologies, as for example identifying genes whose methylation and transcriptional levels are jointly deregulated, or finding proteins whose abundance shows the same trends of the expression of their encoding genes. Results: We implemented the NPC methodology within “omicsNPC”, an R function specifically tailored for the characteristics of omics data. We compare omicsNPC against a range of alternative methods on simulated as well as on real data. Comparisons on simulated data point out that omicsNPC produces unbiased / calibrated p-values and performs equally or significantly better than the other methods included in the study; furthermore, the analysis of real data show that omicsNPC (a) exhibits higher statistical power than other methods, (b) it is easily applicable in a number of different scenarios, and (c) its results have improved biological interpretability. Conclusions: The omicsNPC function competitively behaves in all comparisons conducted in this study. Taking into account that the method (i) requires minimal assumptions, (ii) it can be used on different studies designs and (iii) it captures the dependences among heterogeneous data modalities, omicsNPC provides a flexible and statistically powerful solution for the integrative analysis of different omics data. [ABSTRACT FROM AUTHOR]

To facilitate a more widespread use of volumetric tumor segmentation in clinical studies, there is an urgent need for reliable, user-friendly segmentation software. The aim of this study was therefore to compare three different software packages for semi-automatic brain tumor segmentation of glioblastoma; namely BrainVoyagerTM QX, ITK-Snap and 3D Slicer, and to make data available for future reference. Pre-operative, contrast enhanced T1-weighted 1.5 or 3 Tesla Magnetic Resonance Imaging (MRI) scans were obtained in 20 consecutive patients who underwent surgery for glioblastoma. MRI scans were segmented twice in each software package by two investigators. Intra-rater, inter-rater and between-software agreement was compared by using differences of means with 95% limits of agreement (LoA), Dice’s similarity coefficients (DSC) and Hausdorff distance (HD). Time expenditure of segmentations was measured using a stopwatch. Eighteen tumors were included in the analyses. Inter-rater agreement was highest for BrainVoyager with difference of means of 0.19 mL and 95% LoA from -2.42 mL to 2.81 mL. Between-software agreement and 95% LoA were very similar for the different software packages. Intra-rater, inter-rater and between-software DSC were ≥ 0.93 in all analyses. Time expenditure was approximately 41 min per segmentation in BrainVoyager, and 18 min per segmentation in both 3D Slicer and ITK-Snap. Our main findings were that there is a high agreement within and between the software packages in terms of small intra-rater, inter-rater and between-software differences of means and high Dice’s similarity coefficients. Time expenditure was highest for BrainVoyager, but all software packages were relatively time-consuming, which may limit usability in an everyday clinical setting. [ABSTRACT FROM AUTHOR]

Background: Several maternal and birth characteristics have been reported to be associated with an increased risk of many childhood cancers. Our goal was to evaluate the risk of childhood embryonal solid tumors in relation to pre- and perinatal characteristics. Methods: A case-cohort study was performed using two population-based datasets, which were linked through R software. Tumors were classified as central nervous system (CNS) or non-CNS-embryonal (retinoblastoma, neuroblastoma, renal tumors, germ cell tumors, hepatoblastoma and soft tissue sarcoma). Children aged <6 years were selected. Adjustments were made for potential confounders. Odds ratios (OR) with 95% confidence intervals (CI) were computed by unconditional logistic regression analysis using SPSS. Results: Males, high maternal education level, and birth anomalies were independent risk factors. Among children diagnosed older than 24 months of age, cesarean section (CS) was a significant risk factor. Five-minute Apgar ≤8 was an independent risk factor for renal tumors. A decreasing risk with increasing birth order was observed for all tumor types except for retinoblastoma. Among children with neuroblastoma, the risk decreased with increasing birth order (OR = 0.82 (95% CI 0.67–1.01)). Children delivered by CS had a marginally significantly increased OR for all tumors except retinoblastoma. High maternal education level showed a significant increase in the odds for all tumors together, CNS tumors, and neuroblastoma. Conclusion: This evidence suggests that male gender, high maternal education level, and birth anomalies are risk factors for childhood tumors irrespective of the age at diagnosis. Cesarean section, birth order, and 5-minute Apgar score were risk factors for some tumor subtypes. [ABSTRACT FROM AUTHOR]

Nonnegative Matrix Factorization (NMF) has proved to be an effective method for unsupervised clustering analysis of gene expression data. By the nonnegativity constraint, NMF provides a decomposition of the data matrix into two matrices that have been used for clustering analysis. However, the decomposition is not unique. This allows different clustering results to be obtained, resulting in different interpretations of the decomposition. To alleviate this problem, some existing methods directly enforce uniqueness to some extent by adding regularization terms in the NMF objective function. Alternatively, various normalization methods have been applied to the factor matrices; however, the effects of the choice of normalization have not been carefully investigated. Here we investigate the performance of NMF for the task of cancer class discovery, under a wide range of normalization choices. After extensive evaluations, we observe that the maximum norm showed the best performance, although the maximum norm has not previously been used for NMF. Matlab codes are freely available from: . [ABSTRACT FROM AUTHOR]

The differentiation between glioblastoma multiforme (GBM) and primary cerebral lymphoma (PCL) is important because the treatments are substantially different. The purpose of this article is to describe the MR imaging characteristics of GBM and PCL with emphasis on the quantitative ADC analysis in the tumor necrosis, the most strongly-enhanced tumor area, and the peritumoral edema. This retrospective cohort study collected 104 GBM (WHO grade IV) patients and 22 immune-competent PCL (diffuse large B cell lymphoma) patients. All these patients had pretreatment brain MR DWI and ADC imaging. Analysis of conventional MR imaging and quantitative ADC measurement including the tumor necrosis (ADCn), the most strongly-enhanced tumor area (ADCt), and the peritumoral edema (ADCe) were done. ROC analysis with optimal cut-off values and area-under-the ROC curve (AUC) was performed. For conventional MR imaging, there are statistical differences in tumor size, tumor location, tumor margin, and the presence of tumor necrosis between GBM and PCL. Quantitative ADC analysis shows that GBM tended to have significantly (P<0.05) higher ADC in the most strongly-enhanced area (ADCt) and lower ADC in the peritumoral edema (ADCe) as compared with PCL. Excellent AUC (0.94) with optimal sensitivity of 90% and specificity of 86% for differentiating between GBM and PCL was obtained by combination of ADC in the tumor necrosis (ADCn), the most strongly-enhanced tumor area (ADCt), and the peritumoral edema (ADCe). Besides, there are positive ADC gradients in the peritumoral edema in a subset of GBMs but not in the PCLs. Quantitative ADC analysis in these three areas can thus be implemented to improve diagnostic accuracy for these two brain tumor types. The histological correlation of the ADC difference deserves further investigation. [ABSTRACT FROM AUTHOR]

Trefoil factor family (TFF) peptides have been shown to effect cell proliferation, apoptosis, migration and invasion of normal cells and various cancer cell lines. In the literature TFF peptides are controversially discussed as tumor suppressors and potential tumor progression factors. In the study presented, we investigated the effect of TFF3 overexpression on growth, viability, migration and tumorigenicity of the human retinoblastoma cell lines Y-79, WERI-Rb1, RBL-13 and RBL-15. As revealed by WST-1 and TUNEL assays as well as DAPI and BrdU cell counts, recombinant human TFF3 significantly lowers retinoblastoma cell viability and increases apoptosis levels. Transient TFF3 overexpression likewise significantly increases RB cell apoptosis. Stable, lentiviral TFF3 overexpression lowers retinoblastoma cell viability, proliferation and growth and significantly increases cell death in retinoblastoma cells. Blockage experiments using a broad-spectrum caspase inhibitor and capase-3 immunocytochemistry revealed the involvement of caspases in general and of caspase-3 in particular in TFF3 induced apoptosis in retinoblastoma cell lines. Soft agarose and in ovo chicken chorioallantoic membrane (CAM) assays revealed that TFF3 overexpression influences anchorage independent growth and significantly decreases the size of tumors forming from retinoblastoma cells. Our study demonstrates that forced TFF3 expression exerts a significant pro-apoptotic, anti-proliferative, and tumor suppressive effect in retinoblastoma cells, setting a starting point for new additive chemotherapeutic approaches in the treatment of retinoblastoma. [ABSTRACT FROM AUTHOR]

Despite all efforts made to develop predictive biomarkers for antiangiogenic therapies, no unambiguous markers have been identified so far. This is due to among others the lack of standardized tests. This study presents an improved microvessel density quantification method in tumor tissue based on stereological principles and using whole-slide images. Vessels in tissue sections of different cancer types were stained for CD31 by an automated and validated immunohistochemical staining method. The stained slides were digitized with a digital slide scanner. Systematic, uniform, random sampling of the regions of interest on the whole-slide images was performed semi-automatically with the previously published applications AutoTag and AutoSnap. Subsequently, an unbiased counting grid was combined with the images generated with these scripts. Up to six independent observers counted microvessels in up to four cancer types: colorectal carcinoma, glioblastoma multiforme, ovarian carcinoma and renal cell carcinoma. At first, inter-observer variability was found to be unacceptable. However, after a series of consensus training sessions and interim statistical analysis, counting rules were modified and inter-observer concordance improved considerably. Every CD31-positive object was counted, with exclusion of suspected CD31-positive monocytes, macrophages and tumor cells. Furthermore, if interconnected, stained objects were considered a single vessel. Ten regions of interest were sufficient for accurate microvessel density measurements. Intra-observer and inter-observer variability were low (intraclass correlation coefficient > 0.7) if the observers were adequately trained. [ABSTRACT FROM AUTHOR]

Background: Antiangiogenic therapies for glioblastoma (GBM) such as bevacizumab (BVZ), have been unable to extend survival in large patient cohorts. However, a subset of patients having angiogenesis-dependent tumors might benefit from these therapies. Currently, there are no biomarkers allowing to discriminate responders from non-responders before the start of the therapy. Methods: 40 patients from the randomized GENOM009 study complied the inclusion criteria (quality of images, clinical data available). Of those, 23 patients received first line temozolomide (TMZ) for eight weeks and then concomitant radiotherapy and TMZ. 17 patients received BVZ+TMZ for seven weeks and then added radiotherapy to the treatment. Clinical variables were collected, tumors segmented and several geometrical measures computed including: Contrast enhancing (CE), necrotic, and total volumes; equivalent spherical CE width; several geometric measures of the CE ‘rim’ geometry and a set of image texture measures. The significance of the results was studied using Kaplan-Meier and Cox proportional hazards analysis. Correlations were assessed using Spearman correlation coefficients. Results: Kaplan-Meier and Cox proportional hazards analysis showed that total, CE and inner volume (p = 0.019, HR = 4.258) and geometric heterogeneity of the CE areas (p = 0.011, HR = 3.931) were significant parameters identifying response to BVZ. The group of patients with either regular CE areas (small geometric heterogeneity, median difference survival 15.88 months, p = 0.011) or those with small necrotic volume (median survival difference 14.50 months, p = 0.047) benefited substantially from BVZ. Conclusion: Imaging biomarkers related to the irregularity of contrast enhancing areas and the necrotic volume were able to discriminate GBM patients with a substantial survival benefit from BVZ. A prospective study is needed to validate our results. [ABSTRACT FROM AUTHOR]

Background: Medulloblastoma (MB) is the most common pediatric primary malignant brain tumor. Approximately one-third of MB patients succumb to treatment failure and some survivors suffer detrimental side effects. Hence, the purpose of this study is to explore new therapeutic regimens to overcome chemotherapeutic agent resistance or reduce chemotherapy-induced toxicity. Methods: We detected the expression of inhibitors of apoptosis proteins (IAPs) in MB and CD133+ MB cell lines and MB tissues using immunoblotting and immunohistochemical staining. The antitumor effects of inhibitors against IAPs on MB or CD133+ MB cells were evaluated by MTT assay, Annexin V/PI analysis, and caspase-3/7 activity. Autophagy was assessed by the conversion of light chain (LC) 3-I to LC3-II and Cyto-ID autophagy detection kit. Results: MB cells showed higher expression of IAPs compared to normal astrocytes and normal brain tissues. Conventional chemotherapeutic agents combined with small-molecule IAP inhibitors (LCL161 or LBW242) showed a synergistic effect in MB cells. Combined treatments triggered apoptosis in MB cells through activation of caspase-3/7 and autophagic flux simultaneously. In addition, we found that CD133+ MB cells with features of cancer stem cells displayed higher levels of X-linked inhibitor of apoptosis (XIAP) and cellular inhibitor of apoptosis 1/2 (cIAP1/2), and were hypersensitive to treatment with IAP inhibitors. Conclusions: These results shed light on the biological effects of combination therapy on MB cells and illustrate that IAP inhibitors are more effective for CD133+ stem-like MB cells. [ABSTRACT FROM AUTHOR]

We previously developed a method for determining MYCN gene amplification status using cell-free DNA fragments released from cancer cells into the blood of patients with neuroblastoma (NB). Here, we analyzed the relationship between MYCN amplification (MNA) status and neuroblastoma prognosis. We screened serum samples from 151 patients with NB for MNA, using real-time quantitative PCR, and compared the results with MYCN status determined using paired tumor samples. We additionally investigated whether MNA status correlates with patient survival. When a cut-off value of 5 was used, serum-based MNA analysis was found to show good sensitivity (86%) and very high specificity (95%). The sensitivities for stage 1 and 2 might be acceptable, even though it is not as good as for stage 3 and 4 (67% for stage 1 and 2, 92% for stage 3, and 87% for stage 4). MNA status correlated with overall survival in our cohort of 82 patients, with survival data available (p < 0.01). The hazard ratio of MNA status was 4.98 in patients diagnosed at less than 18 months of age (95% confidence interval, 1.00–24.78), and 1.41 (95% confidence interval, 0.63–3.14) for those diagnosed at 18 months of age or older. Serum-based MNA analysis is rapid and non-invasive compared with tumor-based MNA analysis, and has potential to predict tumor MNA status. There is still a room to improve the sensitivity of the test for tumors of stages 1 and 2, nonetheless this assay might help to determine therapeutic strategies prior to tumor biopsy, especially for patients with a life-threatening condition, as well as for patients of less than 18 months of age whose risk-grouping and treatment allocation depends on their MNA status. [ABSTRACT FROM AUTHOR]

Purpose: Retinoblastoma is the most common primary malignant intra-ocular tumor in children. Although intra-arterial chemotherapy (IAC) by selectively infusing chemotherapy through the ophthalmic artery has become an essential technique in the treatment of advanced intra-ocular retinoblastoma in children, the outcome of IAC as primary therapy for infants less than 3 months of age remains unknown. In this retrospective study, we reviewed the outcome of IAC as primary therapy for retinoblastoma in infants less than 3 months of age. Methods: We retrospectively reviewed ten retinoblastoma patients attending our center from January 2009 to September 2015 and beginning primary IAC before the age of 3 months. The patient characteristics, overall outcomes and therapy-related complications were assessed. Results: The mean patient age at the first IAC treatment was 10.4 weeks (range 4.9–12.9 weeks). These eyes were classified according to the International Classification of Retinoblastoma (ICRB) as group A (n = 0), B (n = 2), C (n = 0), D (n = 9), or E (n = 2). A total of 28 catheterizations were performed, and the procedure was stopped in one patient because of internal carotid artery spasm. Each eye received a mean of 2.6 cycles of IAC (range 2–4 cycles). After IAC with a mean follow-up of 28.3 months (range 9–65 months), tumor regression was observed in 12 of 13 eyes. One eye was enucleated due to tumor progression. All patients are alive and no patient has developed metastatic disease or other malignancies. Conclusions: Our experience suggests IAC as primary therapy is a feasible and promising treatment for retinoblastoma in infants less than 3 months of age. [ABSTRACT FROM AUTHOR]

Objective: Several studies have analyzed a correlation between the apparent diffusion coefficient (ADC) derived from diffusion-weighted MRI and the tumor cellularity of corresponding histopathological specimens in brain tumors with inconclusive findings. Here, we compared a large dataset of ADC and cellularity values of stereotactic biopsies of glioblastoma patients using a new postprocessing approach including trajectory analysis and automatic nuclei counting. Materials and Methods: Thirty-seven patients with newly diagnosed glioblastomas were enrolled in this study. ADC maps were acquired preoperatively at 3T and coregistered to the intraoperative MRI that contained the coordinates of the biopsy trajectory. 561 biopsy specimens were obtained; corresponding cellularity was calculated by semi-automatic nuclei counting and correlated to the respective preoperative ADC values along the stereotactic biopsy trajectory which included areas of T1-contrast-enhancement and necrosis. Results: There was a weak to moderate inverse correlation between ADC and cellularity in glioblastomas that varied depending on the approach towards statistical analysis: for mean values per patient, Spearman’s ρ = -0.48 (p = 0.002), for all trajectory values in one joint analysis Spearman’s ρ = -0.32 (p < 0.001). The inverse correlation was additionally verified by a linear mixed model. Conclusions: Our data confirms a previously reported inverse correlation between ADC and tumor cellularity. However, the correlation in the current article is weaker than the pooled correlation of comparable previous studies. Hence, besides cell density, other factors, such as necrosis and edema might influence ADC values in glioblastomas. [ABSTRACT FROM AUTHOR]

Glioma amplified sequence 41(GAS41) is a potent transcription factor that play a crucial role in cell proliferation and survival. In glioblastoma, the expression of GAS41 at both transcriptional and post transcriptional level needs to be tightly maintained in response to cellular signals. Micro RNAs (miRNA) are small non coding RNA that act as important regulators for modulating the expression of various target genes. Studies have shown that several miRNAs play role in the post-transcriptional regulation of GAS41. Here we identified GAS41 as a novel target for endogenous miR-203 and demonstrate an inverse correlation of miR-203 expression with GAS41 in glioma cell lines (HNGC2 and U87). Over expression of miR-203 negatively regulates GAS41 expression in U87 and HNGC2 cell lines. Moreover, miR-203 restrained miR-10b action by suppressing GAS41. GAS41 is essential for repressing p53 in tumor suppressor pathway during cell proliferation. Enforced expression of GAS41 produced contradictory effect on miR-203 but was able to enhance p53 tumor suppressor pathway associated protein. It was also found that miR-203 maintains the stability of p53 as knock down of p53 expression using siRNA resulted in down regulation of pri-miR and mature miR-203 expression. Conversely reconstitution of miR-203 expression induced apoptosis and inhibited migratory property of glioma cells. Taken together, we show that miR-203 is a key negative regulator of GAS41 and acts as tumor suppressor microRNA in glioma. [ABSTRACT FROM AUTHOR]

Current treatment of retinoblastoma involves using the maximum dose of chemotherapy that induces tumor control and is tolerated by patients. The impact of dose and schedule on the cytotoxicity of chemotherapy has not been studied. Our aim was to gain insight into the cytotoxic and antiangiogenic effect of the treatment scheme of chemotherapy used in retinoblastoma by means of different in vitro models and to evaluate potential effects on multi-drug resistance proteins. Two commercial and two patient-derived retinoblastoma cell types and two human vascular endothelial cell types were exposed to increasing concentrations of melphalan or topotecan in a conventional (single exposure) or metronomic (7-day continuous exposure) treatment scheme. The concentration of chemotherapy causing a 50% decrease in cell proliferation (IC50) was determined by MTT and induction of apoptosis was evaluated by flow cytometry. Expression of ABCB1, ABCG2 and ABCC1 after conventional or metronomic treatments was assessed by RT-qPCR. We also evaluated the in vivo response to conventional (0.6 mg/kg once a week for 2 weeks) and metronomic (5 days a week for 2 weeks) topotecan in a retinoblastoma xenograft model. Melphalan and topotecan were cytotoxic to both retinoblastoma and endothelial cells after conventional and metronomic treatments. A significant decrease in the IC50 (median, 13-fold; range: 3–23) was observed following metronomic chemotherapy treatment in retinoblastoma and endothelial cell types compared to conventional treatment (p<0.05). Metronomic topotecan or melphalan significantly inhibited in vitro tube formation in HUVEC and EPC compared to vehicle-treated cells (p<0.05). Both treatment schemes induced apoptosis and/or necrosis in all cell models. No significant difference was observed in the expression of ABCB1, ABCC1 or ABCG2 when comparing cells treated with melphalan or topotecan between treatment schedules at the IC50 or with control cells (p>0.05). In mice, continuous topotecan lead to significantly lower tumor volumes compared to conventional treatment after 14 days of treatment (p<0.05). Continuous exposure to melphalan or topotecan increased the chemosensitivity of retinoblastoma and endothelial cells to both chemotherapy agents with lower IC50 values compared to short-term treatment. These findings were validated in an in vivo model. None of the dosing modalities induced multidrug resistance mechanisms while apoptosis was the mechanism of cell death after both treatment schedules. Metronomic chemotherapy may be a valid option for retinoblastoma treatment allowing reductions of the daily dose. [ABSTRACT FROM AUTHOR]

Background: A critical challenge in the management of Glioblastoma Multiforme (GBM) tumors is the accurate diagnosis and assessment of tumor progression in a noninvasive manner. We have identified Membrane-type 1 matrix metalloproteinase (MT1-MMP) as an attractive biomarker for GBM imaging since this protein is actively involved in tumor growth and progression, correlates with tumor grade and is closely associated with poor prognosis in GBM patients. Here, we report the development of an immunoPET tracer for effective detection of MT1-MMP in GBM models. Methods: An anti-human MT1-MMP monoclonal antibody (mAb), LEM2/15, was conjugated to p-isothiocyanatobenzyl-desferrioxamine (DFO-NCS) for 89Zr labeling. Biodistribution and PET imaging studies were performed in xenograft mice bearing human GBM cells (U251) expressing MT1-MMP and non-expressing breast carcinoma cells (MCF-7) as negative control. Two orthotopic brain GBM models, patient-derived neurospheres (TS543) and U251 cells, with different degrees of blood-brain barrier (BBB) disruption were also used for PET imaging experiments. Results: 89Zr labeling of DFO-LEM2/15 was achieved with high yield (>90%) and specific activity (78.5 MBq/mg). Biodistribution experiments indicated that 89Zr-DFO-LEM2/15 showed excellent potential as a radiotracer for detection of MT1-MMP positive GBM tumors. PET imaging also indicated a specific and prominent 89Zr-DFO-LEM2/15 uptake in MT1-MMP+ U251 GBM tumors compared to MT1-MMP- MCF-7 breast tumors. Results obtained in orthotopic brain GBM models revealed a high dependence of a disrupted BBB for tracer penetrance into tumors. 89Zr-DFO-LEM2/15 showed much higher accumulation in TS543 tumors with a highly disrupted BBB than in U251 orthotopic model in which the BBB permeability was only partially increased. Histological analysis confirmed the specificity of the immunoconjugate in all GBM models. Conclusion: A new anti MT1-MMP-mAb tracer, 89Zr-DFO-LEM2/15, was synthesized efficiently. In vivo validation showed high-specific-contrast imaging of MT1-MMP positive GBM tumors and provided strong evidence for utility of MT1-MMP-targeted immunoPET as an alternate to nonspecific imaging of GBM. [ABSTRACT FROM AUTHOR]