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

ThereceptortyrosinekinaseAxlisoverexpressedinavarietyofcancersandisknowntoplayaroleinproliferation andinvasion.PreviousdatafromourlaboratoryindicatethatAxlanditsligandgrowtharrest–specific6(GAS6)may play a role in establishing metastatic dormancy in the bone marrow microenvironment. In the current study, we foundthatAxlishighlyexpressedinmetastaticprostatecancercelllinesPC3andDU145andhasnegligiblelevelsof expression in a nonmetastatic cancer cell line LNCaP. Knockdown of Axl in PC3 and DU145 cells resulted in decreased expression of several mesenchymal markers including Snail, Slug, and N-cadherin, and enhanced expression of the epithelial marker E-cadherin, suggesting that Axl is involved in the epithelial–mesenchymal transition in prostate cancer cells. The Axl-knockdown PC3 and DU145 cells also displayed decreased in vitro migrationand invasion.Interestingly,whenPC3andDU145cellsweretreatedwithGAS6,Axlproteinlevelswere downregulated.Moreover,CoCl2,ahypoxiamimickingagent,preventedGAS6-mediateddownregulationofAxlin thesecelllines.ImmunochemicalstainingofhumanprostatecancertissuemicroarraysshowedthatAxl,GAS6,and hypoxia-inducible factor-1a (Hif-1a; indicator of hypoxia) were all coexpressed in prostate cancer and in bone metastases compared with normal tissues. Together, our studies indicate that Axl plays a crucial role in prostate cancer metastasis and that GAS6 regulates the expression of Axl. Importantly, in a hypoxic tumor microenvironment Axl expression is maintained leading to enhanced signaling. Mol Cancer Res; 10(6); 703–12. � 2012 AACR.

HypoxiaStabilizes GAS6/Axl Signaling in Metastatic Prostate Cancer

Prostate Cancer Chemotherapy: Closing Out a Century and Opening a New One


 Recent advances in precision medicine and immunotherapy have made great strides in cancer treatment and care, but chemoresistance remains a major challenge. One method of chemoresistance employed by cancer cells is accession of the protective polyaneuploid cancer cell (PACC) state, in which cells enter a functionally dormant state upon environmental stress. Entry into the PACC state begins with a whole-genome duplication event followed by endocycling, where the cells are metabolically active and cycling through repeated G1, S and G2 phases of the cell cycle without dividing. While in this state, cells avoid the mitotic stress exerted by common chemotherapeutics and survive therapy, eventually undergoing a depolyploidization process to repopulate the tumor, driving cancer lethality. The mechanisms by which a cancer cell can switch between a mitotic cell cycle and an endocycle are unknown. Cancer is characterized by deregulated cell proliferation, often driven by mutation or amplification of genes that govern the cell cycle. C-myc, an oncogenic transcription factor, is dysregulated in roughly 70% of cancers and is clinically used as a negative prognostic factor for disease-free survival and metastasis. C-myc is responsible for the transcriptional activation of many cell cycle-related genes, and repression of cell cycle inhibitors. Our data indicate that endocycling cells in the PACC state downregulate c-myc expression. Transcriptomic analyses show repression of myc targets, along with supporting protein data that total c-myc protein levels are decreased. While myc downregulation is expected in non-proliferative cells, the compensatory mechanisms mediating the G1/S transition in the cancer endocycle remain unknown. These observations suggest the presence of underlying mechanisms to reprogram the mitotic cell cycle to access the PACC state. We hypothesize that myc downregulation is essential for cells to activate the cancer endocyle and enter the protective PACC state. Understanding the mechanisms that govern this transition is crucial to generate next-generation cancer therapeutics to block accession or disrupt this state.
 Citation Format: Michael Loycano, Kenneth J. Pienta, Sarah R. Amend. Myc suppression permits entry into the cancer endocycle to evade toxic effects of chemotherapy [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2023; Part 1 (Regular and Invited Abstracts); 2023 Apr 14-19; Orlando, FL. Philadelphia (PA): AACR; Cancer Res 2023;83(7_Suppl):Abstract nr 1690.

Abstract 1690: Myc suppression permits entry into the cancer endocycle to evade toxic effects of chemotherapy

Author Contributions: Kim, C-J: conceptualization, methodology, investigation, writing (original draft), writing (review and editing), visualization. Gonye, ALK: conceptualization, methodology, investigation, writing (original draft), writing (review and editing), visualization. Truskowski, K: methodology, investigation. Lee, C-F: investigation. Cho, Y-K: conceptualization, writing (review and editing), funding acquisition. Austin, RH: conceptualization, writing (review). Pienta, KJ: conceptualization, writing (review and editing), funding acquisition. Amend, SR: conceptualization, writing (review and editing), funding acquisition.

Kenneth J. Pienta

Papers

HypoxiaStabilizes GAS6/Axl Signaling in Metastatic Prostate Cancer

Prostate Cancer Chemotherapy: Closing Out a Century and Opening a New One

Abstract 1690: Myc suppression permits entry into the cancer endocycle to evade toxic effects of chemotherapy

Impact of the cancer endocycle on cell survival after therapy

Cancer Genetics, Cancer Biology, and Tumor Growth and Metastasis