The 2016 World Health Organization Classification of Tumors of the Central Nervous System is both a conceptual and practical advance over its 2007 predecessor. For the first time, the WHO classification of CNS tumors uses molecular parameters in addition to histology to define many tumor entities, thus formulating a concept for how CNS tumor diagnoses should be structured in the molecular era. As such, the 2016 CNS WHO presents major restructuring of the diffuse gliomas, medulloblastomas and other embryonal tumors, and incorporates new entities that are defined by both histology and molecular features, including glioblastoma, IDH-wildtype and glioblastoma, IDH-mutant; diffuse midline glioma, H3 K27M-mutant; RELA fusion-positive ependymoma; medulloblastoma, WNT-activated and medulloblastoma, SHH-activated; and embryonal tumour with multilayered rosettes, C19MC-altered. The 2016 edition has added newly recognized neoplasms, and has deleted some entities, variants and patterns that no longer have diagnostic and/or biological relevance. Other notable changes include the addition of brain invasion as a criterion for atypical meningioma and the introduction of a soft tissue-type grading system for the now combined entity of solitary fibrous tumor / hemangiopericytoma-a departure from the manner by which other CNS tumors are graded. Overall, it is hoped that the 2016 CNS WHO will facilitate clinical, experimental and epidemiological studies that will lead to improvements in the lives of patients with brain tumors.

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The 2016 World Health Organization Classification of Tumors of the Central Nervous System: a summary.

Probability Distributions.- Linear Models for Regression.- Linear Models for Classification.- Neural Networks.- Kernel Methods.- Sparse Kernel Machines.- Graphical Models.- Mixture Models and EM.- Approximate Inference.- Sampling Methods.- Continuous Latent Variables.- Sequential Data.- Combining Models.

Pattern Recognition and Machine Learning

Resolving the molecular details of proteome variation in the different tissues and organs of the human body will greatly increase our knowledge of human biology and disease. Here, we present a map of the human tissue proteome based on an integrated omics approach that involves quantitative transcriptomics at the tissue and organ level, combined with tissue microarray-based immunohistochemistry, to achieve spatial localization of proteins down to the single-cell level. Our tissue-based analysis detected more than 90% of the putative protein-coding genes. We used this approach to explore the human secretome, the membrane proteome, the druggable proteome, the cancer proteome, and the metabolic functions in 32 different tissues and organs. All the data are integrated in an interactive Web-based database that allows exploration of individual proteins, as well as navigation of global expression patterns, in all major tissues and organs in the human body.

Tissue-based map of the human proteome

Anomaly detection is an important problem that has been researched within diverse research areas and application domains. Many anomaly detection techniques have been specifically developed for certain application domains, while others are more generic. This survey tries to provide a structured and comprehensive overview of the research on anomaly detection. We have grouped existing techniques into different categories based on the underlying approach adopted by each technique. For each category we have identified key assumptions, which are used by the techniques to differentiate between normal and anomalous behavior. When applying a given technique to a particular domain, these assumptions can be used as guidelines to assess the effectiveness of the technique in that domain. For each category, we provide a basic anomaly detection technique, and then show how the different existing techniques in that category are variants of the basic technique. This template provides an easier and more succinct understanding of the techniques belonging to each category. Further, for each category, we identify the advantages and disadvantages of the techniques in that category. We also provide a discussion on the computational complexity of the techniques since it is an important issue in real application domains. We hope that this survey will provide a better understanding of the different directions in which research has been done on this topic, and how techniques developed in one area can be applied in domains for which they were not intended to begin with.

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Anomaly detection: A survey

All cancers are caused by somatic mutations; however, understanding of the biological processes generating these mutations is limited. The catalogue of somatic mutations from a cancer genome bears the signatures of the mutational processes that have been operative. Here we analysed 4,938,362 mutations from 7,042 cancers and extracted more than 20 distinct mutational signatures. Some are present in many cancer types, notably a signature attributed to the APOBEC family of cytidine deaminases, whereas others are confined to a single cancer class. Certain signatures are associated with age of the patient at cancer diagnosis, known mutagenic exposures or defects in DNA maintenance, but many are of cryptic origin. In addition to these genome-wide mutational signatures, hypermutation localized to small genomic regions, 'kataegis', is found in many cancer types. The results reveal the diversity of mutational processes underlying the development of cancer, with potential implications for understanding of cancer aetiology, prevention and therapy.

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Signatures of mutational processes in human cancer

EDITORIAL Is Dietary Fat a Risk Factor for Prostate Cancer

New radiotracers for positron emission tomography imaging that target prostate-specific membrane antigen (PSMA) have emerged as important clinical tools for imaging prostate cancer (PCa). PSMA-targeted radiotracers have demonstrated high sensitivity and high specificity for detecting sites of PCa and are demonstrably superior to conventional imaging modalities such as computed tomography and bone scan. Vas deferens invasion is a rarely encountered poor prognostic feature of PCa. In this case report, we describe a novel pattern of radiotracer uptake in a patient with PCa imaged with PSMA-targeted18F-DCFPyL positron emission tomography/computed tomography that is consistent with diffuse vas deferens involvement.

Vas deferens infiltration by prostate cancer on prostate-specific membrane antigen-targeted 18F-DCFPyL positron emission tomography/computed tomography: A unique visual pattern.

Abstract Although metastasis is the leading cause of cancer deaths, it is quite rare at the cellular level. Only a rare subset of cancer cells (~ 1 in 1.5 billion) can complete the entire metastatic cascade: invasion, intravasation, survival in the circulation, extravasation, and colonization (i.e. are metastasis competent). We propose that cells engaging a Polyaneuploid Cancer Cell (PACC) phenotype are metastasis competent. Cells in the PACC state are enlarged, endocycling (i.e. non-dividing) cells with increased genomic content that form in response to stress. Single-cell tracking using time lapse microscopy reveals that PACC state cells have increased motility. Additionally, cells in the PACC state exhibit increased capacity for environment-sensing and directional migration in chemotactic environments, predicting successful invasion. Magnetic Twisting Cytometry and Atomic Force Microscopy reveal that cells in the PACC state display hyper-elastic properties like increased peripheral deformability and maintained peri-nuclear cortical integrity that predict successful intravasation and extravasation. Furthermore, four orthogonal methods reveal that cells in the PACC state have increased expression of vimentin, a hyper-elastic biomolecule known to modulate biomechanical properties and induce mesenchymal-like motility. Taken together, these data indicate that cells in the PACC state have increased metastatic potential and are worthy of further in vivo analysis. 

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Cells in the polyaneuploid cancer cell (PACC) state have increased metastatic potential

Renal cell carcinoma (RCC) accounts for over 400,000 new cases and 175,000 deaths annually. Diagnostic RCC biomarkers may prevent overtreatment in patients with early disease. Extracellular vesicles (EVs) are a promising source of RCC biomarkers because EVs carry proteins and messenger RNA (mRNA) among other biomolecules. We aimed to identify biomarkers and assess biological functions of EV cargo from clear cell RCC (ccRCC), papillary RCC (pRCC), and benign kidney cell lines. EVs were enriched from conditioned cell media by size exclusion chromatography. The EV proteome was assessed using Tandem Mass Tag mass spectrometry (TMT-MS) and NanoString nCounter technology was used to profile 770 cancer-related mRNA present in EVs. The heterogeneity of protein and mRNA abundance and identification highlighted the heterogeneity of EV cargo, even between cell lines of a similar pathological group (e.g., ccRCC or pRCC). Overall, 1726 proteins were quantified across all EV samples, including 181 proteins that were detected in all samples. In the targeted profiling of mRNA by NanoString, 461 mRNAs were detected in EVs from at least one cell line, including 159 that were present in EVs from all cell lines. In addition to a shared EV cargo signature, pRCC, ccRCC, and/or benign renal cell lines also showed unique signatures. Using this multi-omics approach, we identified 34 protein candidate pRCC EV biomarkers and 20 protein and 8 mRNA candidate ccRCC EV biomarkers for clinical validation.

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Defining candidate mRNA and protein EV biomarkers to discriminate ccRCC and pRCC from non-malignant renal cells in vitro

Gamma-tocopherol (natural vitamin e) demonstrates greater inhibition of growth on a human prostate cancer cell line than alpha-tocopherol (synthetic vitamin e)

Kenneth J. Pienta

Papers

EDITORIAL Is Dietary Fat a Risk Factor for Prostate Cancer

Vas deferens infiltration by prostate cancer on prostate-specific membrane antigen-targeted 18F-DCFPyL positron emission tomography/computed tomography: A unique visual pattern.

Cells in the polyaneuploid cancer cell (PACC) state have increased metastatic potential

Defining candidate mRNA and protein EV biomarkers to discriminate ccRCC and pRCC from non-malignant renal cells in vitro

Gamma-tocopherol (natural vitamin e) demonstrates greater inhibition of growth on a human prostate cancer cell line than alpha-tocopherol (synthetic vitamin e)