Detection of statistically significant network changes in complex biological networks

Table S1. Description of data: GHD and MRA Results for all the 457 considered transcription factors on the TCGA and Rembrandt datasets. (XLSX 62.7 kb

VEGAWES: variational segmentation on whole exome sequencing for copy number detection

Background Copy number variations are important in the detection and progression of significant tumors and diseases. Recently, Whole Exome Sequencing is gaining popularity with copy number variations detection due to low cost and better efficiency. In this work, we developed VEGAWES for accurate and robust detection of copy number variations on WES data. VEGAWES is an extension to a variational based segmentation algorithm, VEGA: Variational estimator for genomic aberrations, which has previously outperformed several algorithms on segmenting array comparative genomic hybridization data. Results We tested this algorithm on synthetic data and 100 Glioblastoma Multiforme primary tumor samples. The results on the real data were analyzed with segmentation obtained from Single-nucleotide polymorphism data as ground truth. We compared our results with two other segmentation algorithms and assessed the performance based on accuracy and time. Conclusions In terms of both accuracy and time, VEGAWES provided better results on the synthetic data and tumor samples demonstrating its potential in robust detection of aberrant regions in the genome

Degradation of Id2 by the anaphase-promoting complex couples cell cycle exit and axonal growth

In the developing nervous system, Id2 (inhibitor of DNA binding 2, also known as inhibitor of differentiation 2) enhances cell proliferation, promotes tumour progression and inhibits the activity of neurogenic basic helix\u2013loop\u2013helix (bHLH) transcrip- tion factors1,2. The anaphase promoting complex/cyclosome and its activator Cdh1 (APC/CCdh1) restrains axonal growth but the targets of APC/CCdh1 in neurons are unknown3\u20135. Id2 and other members of the Id family are very unstable proteins that are eliminated as cells enter the quiescent state, but how they are targeted for degradation has remained elusive6,7. Here we show that Id2 interacts with the core subunits of APC/C and Cdh1 in primary neurons. APC/CCdh1 targets Id2 for degradation through a destruction box motif (D box) that is conserved in Id1 and Id4. Depletion of Cdh1 stabilizes Id proteins in neurons, whereas Id2 D-box mutants are impaired for Cdh1 binding and remain stable in cells that exit from the cell cycle and contain active APC/CCdh1. Mutants of the Id2 D box enhance axonal growth in cerebellar granule neurons in vitro and in the context of the cerebellar cortex, and overcome the myelin inhibitory signals for growth. Conversely, activation of bHLH transcription factors induces a cluster of genes with potent axonal inhibitory functions including the gene coding for the Nogo receptor, a key transducer of myelin inhibition. Degradation of Id2 in neurons permits the accumu- lation of the Nogo receptor, thereby linking APC/CCdh1 activity with bHLH target genes for the inhibition of axonal growth. These findings indicate that deregulated Id activity might be useful to reprogramme quiescent neurons into the axonal growth mode

RT-PCR assay to detect FGFR3::TACC3 fusions in formalin-fixed, paraffin-embedded glioblastoma samples.

BACKGROUND: One targeted treatment option for isocitrate dehydrogenase ( IDH)-wild-type glioblastoma focuses on tumors with fibroblast growth factor receptor 3::transforming acidic coiled-coil-containing protein 3 ( FGFR3::TACC3) fusions. FGFR3::TACC3 fusion detection can be challenging, as targeted RNA next-generation sequencing (NGS) is not routinely performed, and immunohistochemistry is an imperfect surrogate marker. Fusion status can be determined using reverse transcription polymerase chain reaction (RT-PCR) on fresh frozen (FF) material, but sometimes only formalin-fixed, paraffin-embedded (FFPE) tissue is available. AIM: To develop an RT-PCR assay to determine FGFR3::TACC3 status in FFPE glioblastoma samples. METHODS: Twelve tissue microarrays with 353 historical glioblastoma samples were immunohistochemically stained for FGFR3. Samples with overexpression of FGFR3 ( n  = 13) were subjected to FGFR3::TACC3 RT-PCR on FFPE, using 5 primer sets for the detection of 5 common fusion variants. Fusion-negative samples were additionally analyzed with NGS ( n  = 6), FGFR3 Fluorescence In Situ Hybridization ( n  = 6), and RNA sequencing ( n  = 5). RESULTS: Using RT-PCR on FFPE material of the 13 samples with FGFR3 overexpression, we detected an FGFR3::TACC3 fusion in 7 samples, covering 3 different fusion variants. For 5 of these FF was available, and the presence of the fusion was confirmed through RT-PCR on FF. With RNA sequencing, 1 additional sample was found to harbor an FGFR3::TACC3 fusion (variant not covered by current RT-PCR for FFPE). The frequency of FGFR3::TACC3 fusion in this cohort was 9/353 (2.5%). CONCLUSIONS: RT-PCR for FGFR3::TACC3 fusions can successfully be performed on FFPE material, with a specificity of 100% and (due to limited primer sets) a sensitivity of 83.3%. This assay allows for the identification of potential targeted treatment options when only formalin-fixed tissue is available

A Distinct DNA Methylation Shift in a Subset of Glioma CpG Island Methylator Phenotypes during Tumor Recurrence

Glioma diagnosis is based on histomorphology and grading; however, such classification does not have predictive clinical outcome after glioblastomas have developed. To date, no bona fide biomarkers that significantly translate into a survival benefit to glioblastoma patients have been identified. We previously reported that the IDH mutant G-CIMP-high subtype would be a predecessor to the G-CIMP-low subtype. Here, we performed a comprehensive DNA methylation longitudinal analysis of diffuse gliomas from 77 patients (200 tumors) to enlighten the epigenome-based malignant transformation of initially lower-grade gliomas. Intra-subtype heterogeneity among G-CIMP-high primary tumors allowed us to identify predictive biomarkers for assessing the risk of malignant recurrence at early stages of disease. G-CIMP-low recurrence appeared in 9.5% of all gliomas, and these resembled IDH-wild-type primary glioblastoma. G-CIMP-low recurrence can be characterized by distinct epigenetic changes at candidate functional tissue enhancers with AP-1/SOX binding elements, mesenchymal stem cell-like epigenomic phenotype, and genomic instability. Molecular abnormalities of longitudinal G-CIMP offer possibilities to defy glioblastoma progression

Quantifying intra-tumoral genetic heterogeneity of glioblastoma toward precision medicine using MRI and a data-inclusive machine learning algorithm

Glioblastoma (GBM) is one of the most aggressive and lethal human cancers. Intra-tumoral genetic heterogeneity poses a significant challenge for treatment. Biopsy is invasive, which motivates the development of non-invasive, MRI-based machine learning (ML) models to quantify intra-tumoral genetic heterogeneity for each patient. This capability holds great promise for enabling better therapeutic selection to improve patient outcomes. We proposed a novel Weakly Supervised Ordinal Support Vector Machine (WSO-SVM) to predict regional genetic alteration status within each GBM tumor using MRI. WSO-SVM was applied to a unique dataset of 318 image-localized biopsies with spatially matched multiparametric MRI from 74 GBM patients. The model was trained to predict the regional genetic alteration of three GBM driver genes (EGFR, PDGFRA, and PTEN) based on features extracted from the corresponding region of five MRI contrast images. For comparison, a variety of existing ML algorithms were also applied. The classification accuracy of each gene was compared between the different algorithms. The SHapley Additive exPlanations (SHAP) method was further applied to compute contribution scores of different contrast images. Finally, the trained WSO-SVM was used to generate prediction maps within the tumoral area of each patient to help visualize the intra-tumoral genetic heterogeneity. This study demonstrated the feasibility of using MRI and WSO-SVM to enable non-invasive prediction of intra-tumoral regional genetic alteration for each GBM patient, which can inform future adaptive therapies for individualized oncology.Comment: 36 pages, 8 figures, 3 table

Application of X-Band Wave Radar for Coastal Dynamic Analysis: Case Test of Bagnara Calabra (South Tyrrhenian Sea, Italy)

Sea state knowledge has a key role in evaluation of coastal erosion, the assessment of vulnerability and potential in coastal zone utilization, and development of numerical models to predict its evolution. X-band radar measurements were conducted to observe the spatial and temporal variation of the sea-state parameters along a 3 km long sandy-gravelly pocket beaches forming a littoral cell on Bagnara Calabra. We produced a sequence of 1000 images of the sea state extending offshore up to 1 mile. The survey has allowed monitoring the coastline, the directional wave spectra, the sea surface current fields, and the significant wave heights and detecting strong rip currents which cause scours around the open inlets and affect the stability of the submerged reef-type breakwaters. The possibility to validate the data acquired with other datasets (e.g., LaMMA Consortium) demonstrates the potential of the X-band radar technology as a monitoring tool to advance the understanding of the linkages between sea conditions, nearshore sediment dynamics, and coastal change. This work proves the possibility to obtain relevant information (e.g., wave number, period, and direction) for evaluation of local erosion phenomena and of morphological changes in the nearshore and surf zone

Direct-acting antivirals and hepatocellular carcinoma in chronic hepatitis C: A few lights and many shadows

With the introduction of direct-acting antiviral agents (DAA), the rate of sustained virological response (SVR) in the treatment of hepatitis C virus (HCV) has radically improved to over 95%. Robust scientific evidence supports a beneficial role of SVR after interferon therapy in the progression of cirrhosis, resulting in a decreased incidence of hepatocellular carcinoma (HCC). However, a debate on the impact of DAAs on the development of HCC is ongoing. This review aimed to analyse the scientific literature regarding the risk of HCC in terms of its recurrence and occurrence after the use of DAAs to eradicate HCV infection. Among 11 studies examining HCC occurrence, the de novo incidence rate ranged from 0 to 7.4% (maximum follow-up: 18 mo). Among 18 studies regarding HCC recurrence, the rate ranged from 0 to 54.4% (maximum "not well-defined" followup: 32 mo). This review highlights the major difficulties in interpreting data and reconciling the results of the included studies. These difficulties include heterogeneous cohorts, potential misclassifications of HCC prior to DAA therapy, the absence of an adequate control group, short follow-up times and different kinds of follow-up. Moreover, no clinical feature-based scoring system accounts for the molecular characteristics and pathobiology of the tumours. Nonetheless, this review does not suggest that there is a higher rate of de novo HCC occurrence or recurrence after DAA therapy in patients with previous HCV infection. \ua9 2018 The Author(s). Published by Baishideng Publishing Group Inc. All rights reserved

Transcriptional regulatory networks of tumor-associated macrophages that drive malignancy in mesenchymal glioblastoma.

BACKGROUND: Glioblastoma (GBM) is a complex disease with extensive molecular and transcriptional heterogeneity. GBM can be subcategorized into four distinct subtypes; tumors that shift towards the mesenchymal phenotype upon recurrence are generally associated with treatment resistance, unfavorable prognosis, and the infiltration of pro-tumorigenic macrophages. RESULTS: We explore the transcriptional regulatory networks of mesenchymal-associated tumor-associated macrophages (MA-TAMs), which drive the malignant phenotypic state of GBM, and identify macrophage receptor with collagenous structure (MARCO) as the most highly differentially expressed gene. MARCO CONCLUSIONS: Collectively, our study characterizes the global transcriptional profile of TAMs driving mesenchymal GBM pathogenesis, providing potential therapeutic targets for improving the effectiveness of GBM immunotherapy