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

Transcriptional repressors and corepressors play a critical role in cellular homeostasis and are frequently altered in cancer. C-terminal binding protein 1 (CtBP1), a transcriptional corepressor that regulates the expression of tumor suppressors and genes involved in cell death, is known to play a role in multiple cancers. In this study, we observed the overexpression and mislocalization of CtBP1 in metastatic prostate cancer and demonstrated the functional significance of CtBP1 in prostate cancer progression. Transient and stable knockdown of CtBP1 in prostate cancer cells inhibited their proliferationand invasion. Expressionprofilingstudies ofprostatecancercelllinesrevealed thatmultiple

Role of Transcriptional Corepressor CtBP1 in Prostate

Prostate cancer is a leading cause of cancer-related deaths of men in the U.S., and in the past year, over 30,000 men died from this disease. While localized prostate cancer is highly treatable by surgical resection and radiation, cancer that has metastasized remains incurable. Alternatively activated macrophages, also known as M2-macrophages, primarily scavenge debris and in the process, promote angiogenesis and wound repair. M2-macrophages are phenotypically similar to M2 tumor-associated macrophages (M2-TAMs) have been reported to associate with solid tumors such as prostate cancer to facilitate epithelial to mesenchymal transition (EMT), tumor invasiveness, metastasis, and resistance to therapy. As an invasive species within the tumor microenvironment, this makes M2-TAMs an ideal therapeutic target in prostate cancer. The purpose of this project is to develop novel therapeutics that will directly target M2-TAMs for destruction and subsequently attenuate prostate tumor growth, progression and metastasis. The central hypothesis of this study is to determine if targeting of M2-TAMs using specific surface antigens will be an effective therapy for lethal prostate cancer and potentially, other cancers. Our study elucidated M2-Macrophage biology including creating homogenous populations of both M1 and M2 macrophages using a new strategy as to allow for identification of novel surface antigen markers. While using our new method for polarization of human monocyte polarization into macrophages, we found that M2 macrophages polarization was stymied in vitro after glutamine deprivation. We then assessed novel markers of macrophage populations, cytokine and chemokine production, T-Cell inactivation and we also assessed whether these surface antigens that are expressed on M2-macrophages are were found in metastatic human prostate cancers indicative of myeloid infiltration. Validation studies using metastatic prostate cancer tissues from rapid autopsies and surgical specimens supplied by the Department of Urology at Johns Hopkins University School of Medicine were also be performed. Complementary studies will be executed to target these markers for anti-tumor cell efficacy using these relevant model systems. By identifying and targeting specific markers on M2-TAMs, we predict that this targeting will provide a better prognosis for patients who have been diagnosed with lethal prostate cancer. Citation Format: Jelani C. Zarif, James R. Henandez, Kenneth J. Pienta. Assessment and targeting of M2-tumor associated macrophages (M2-TAMs) in prostate cancer. [abstract]. In: Proceedings of the 107th Annual Meeting of the American Association for Cancer Research; 2016 Apr 16-20; New Orleans, LA. Philadelphia (PA): AACR; Cancer Res 2016;76(14 Suppl):Abstract nr 3237.

Abstract 3237: Assessment and targeting of M2-tumor associated macrophages (M2-TAMs) in prostate cancer

Erratum to Mechanistic rationale for inhibition of poly(ADP-Ribose) polymerase in ETS gene fusion-positive prostate cancer [Cancer Cell, 19 (2011) 664-678]

Kenneth J. Pienta

Papers

Role of Transcriptional Corepressor CtBP1 in Prostate

Abstract 3237: Assessment and targeting of M2-tumor associated macrophages (M2-TAMs) in prostate cancer

Erratum to Mechanistic rationale for inhibition of poly(ADP-Ribose) polymerase in ETS gene fusion-positive prostate cancer [Cancer Cell, 19 (2011) 664-678]

Medical oncology committee

Cancer as a Disease: Types of Tumors, Their Frequencies, and Their Progression