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Lymphocyte antigen 6K (LY6K) is a small GPI-linked protein that is normally expressed in testes. Increased expression of LY6K is significantly associated with poor survival outcomes in many solid cancers, including cancers of the breast, ovary, gastrointestinal tract, head and neck, brain, bladder, and lung. LY6K is required for ERK-AKT and TGF-β pathways in cancer cells and is required for in vivo tumor growth. In this report, we describe a novel role for LY6K in mitosis and cytokinesis through aurora B kinase and its substrate histone H3 signaling axis. Further, we describe the structural basis of the molecular interaction of small molecule NSC243928 with LY6K protein and the disruption of LY6K-aurora B signaling in cell cycle progression due to LY6K-NSC243928 interaction. Overall, disruption of LY6K function via NSC243928 led to failed cytokinesis, multinucleated cells, DNA damage, senescence, and apoptosis of cancer cells. LY6K is not required for vital organ function, thus inhibition of LY6K signaling is an ideal therapeutic approach for hard-to-treat cancers that lack targeted therapy such as triple-negative breast cancer., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Published by Elsevier B.V.)

Biologically accurate mouse models of human cancer have become important tools for the study of human disease. The anatomical location of various target organs, such as brain, pancreas, and prostate, makes determination of disease status difficult. Imaging modalities, such as magnetic resonance imaging, can greatly enhance diagnosis, and longitudinal imaging of tumor progression is an important source of experimental data. Even in models where the tumors arise in areas that permit visual determination of tumorigenesis, longitudinal anatomical and functional imaging can enhance the scope of studies by facilitating the assessment of biological alterations, (such as changes in angiogenesis, metabolism, cellular invasion) as well as tissue perfusion and diffusion. One of the challenges in preclinical imaging is the development of infrastructural platforms required for integrating in vivo imaging and therapeutic response data with ex vivo pathological and molecular data using a more systems-based multiscale modeling approach. Further challenges exist in integrating these data for computational modeling to better understand the pathobiology of cancer and to better affect its cure. We review the current applications of preclinical imaging and discuss the implications of applying functional imaging to visualize cancer progression and treatment. Finally, we provide new data from an ongoing preclinical drug study demonstrating how multiscale modeling can lead to a more comprehensive understanding of cancer biology and therapy., (Copyright © 2013 American Society for Investigative Pathology. Published by Elsevier Inc. All rights reserved.)

Background: Multiple recent studies have found aberrant expression profiles of microRNAome in human cancers. While several target genes have been experimentally identified for some microRNAs in various tumors, the global pattern of cellular functions and pathways affected by co-expressed microRNAs in cancer remains elusive. The goal of this study was to develop a computational approach to global analysis of the major biological processes and signaling pathways that are most likely to be affected collectively by co-expressed microRNAs in cancer cells., Results: We report results of computational analysis of five datasets of aberrantly expressed microRNAs in five human cancers published by the authors (pancreatic cancer) and others (breast cancer, colon cancer, lung cancer and lymphoma). Using the combinatorial target prediction algorithm miRgate and a two-step data reduction procedure we have determined Gene Ontology categories as well as biological functions, disease categories, toxicological categories and signaling pathways that are: targeted by multiple microRNAs; statistically significantly enriched with target genes; and known to be affected in specific cancers., Conclusion: Our global analysis of predicted miRNA targets suggests that co-expressed miRNAs collectively provide systemic compensatory response to the abnormal phenotypic changes in cancer cells by targeting a broad range of functional categories and signaling pathways known to be affected in a particular cancer. Such systems biology based approach provides new avenues for biological interpretation of miRNA profiling data and generation of experimentally testable hypotheses regarding collective regulatory functions of miRNA in cancer.

A new type of noncoding short single-stranded RNA molecules, microRNA (miRNA), has recently emerged as one of the most important new classes of cellular regulators. Recent advances in miRNA research have provided evidence that aberrant expression of specific miRNAs is associated with a broad spectrum of human diseases, such as cancer, diabetes, cardiovascular diseases, psychological disorders and others. Global microRNAome profiling has demonstrated drastic changes in expression of multiple miRNAs in many common human cancers. miRNA expression signatures have been shown to provide a more accurate method of classifying cancer subtypes than transcriptome profiling of an entire set of known protein-coding genes. miRNA profiling also allows classification of different stages in tumor progression and can predict disease outcome in some cases. Further characterization of these abnormal miRNA expression signatures and identification of the most significant and informative aberrantly expressed miRNAs could lead to the development of tissue- and biofluid-specific diagnostic markers, as well as a new type of oligonucleotide-based therapeutics. As researchers continue to study miRNA expression in cancer and focus on most relevant miRNAs, the further advancement of miRNA-detection technologies and bioinformatics algorithms is critical for successful identification of the most informative diagnostics markers among the tissue-specific miRNAs.