A combined approach to data mining of textual and structured data to identify cancer-related targets

BACKGROUND: We present an effective, rapid, systematic data mining approach for identifying genes or proteins related to a particular interest. A selected combination of programs exploring PubMed abstracts, universal gene/protein databases (UniProt, InterPro, NCBI Entrez), and state-of-the-art pathway knowledge bases (LSGraph and Ingenuity Pathway Analysis) was assembled to distinguish enzymes with hydrolytic activities that are expressed in the extracellular space of cancer cells. Proteins were identified with respect to six types of cancer occurring in the prostate, breast, lung, colon, ovary, and pancreas. RESULTS: The data mining method identified previously undetected targets. Our combined strategy applied to each cancer type identified a minimum of 375 proteins expressed within the extracellular space and/or attached to the plasma membrane. The method led to the recognition of human cancer-related hydrolases (on average, ~35 per cancer type), among which were prostatic acid phosphatase, prostate-specific antigen, and sulfatase 1. CONCLUSION: The combined data mining of several databases overcame many of the limitations of querying a single database and enabled the facile identification of gene products. In the case of cancer-related targets, it produced a list of putative extracellular, hydrolytic enzymes that merit additional study as candidates for cancer radioimaging and radiotherapy. The proposed data mining strategy is of a general nature and can be applied to other biological databases for understanding biological functions and diseases

Ernst Freund as Precursor of the Rational Study of Corporate Law

Gindis, David, Ernst Freund as Precursor of the Rational Study of Corporate Law (October 27, 2017). Journal of Institutional Economics, Forthcoming. Available at SSRN: https://ssrn.com/abstract=2905547, doi: https://dx.doi.org/10.2139/ssrn.2905547The rise of large business corporations in the late 19th century compelled many American observers to admit that the nature of the corporation had yet to be understood. Published in this context, Ernst Freund's little-known The Legal Nature of Corporations (1897) was an original attempt to come to terms with a new legal and economic reality. But it can also be described, to paraphrase Oliver Wendell Holmes, as the earliest example of the rational study of corporate law. The paper shows that Freund had the intuitions of an institutional economist, and engaged in what today would be called comparative institutional analysis. Remarkably, his argument that the corporate form secures property against insider defection and against outsiders anticipated recent work on entity shielding and capital lock-in, and can be read as an early contribution to what today would be called the theory of the firm.Peer reviewe

Integrative Genomic Data Mining for Discovery of Potential Blood-Borne Biomarkers for Early Diagnosis of Cancer

Background: With the arrival of the postgenomic era, there is increasing interest in the discovery of biomarkers for the accurate diagnosis, prognosis, and early detection of cancer. Blood-borne cancer markers are favored by clinicians, because blood samples can be obtained and analyzed with relative ease. We have used a combined mining strategy based on an integrated cancer microarray platform, Oncomine, and the biomarker module of the Ingenuity Pathways Analysis (IPA) program to identify potential blood-based markers for six common human cancer types. Methodology/Principal Findings: In the Oncomine platform, the genes overexpressed in cancer tissues relative to their corresponding normal tissues were filtered by Gene Ontology keywords, with the extracellular environment stipulated and a corrected Q value (false discovery rate) cut-off implemented. The identified genes were imported to the IPA biomarker module to separate out those genes encoding putative secreted or cell-surface proteins as blood-borne (blood/serum/plasma) cancer markers. The filtered potential indicators were ranked and prioritized according to normalized absolute Student t values. The retrieval of numerous marker genes that are already clinically useful or under active investigation confirmed the effectiveness of our mining strategy. To identify the biomarkers that are unique for each cancer type, the upregulated marker genes that are in common between each two tumor types across the six human tumors were also analyzed by the IPA biomarker comparison function. Conclusion/Significance: The upregulated marker genes shared among the six cancer types may serve as a molecular tool to complement histopathologic examination, and the combination of the commonly upregulated and unique biomarkers may serve as differentiating markers for a specific cancer. This approach will be increasingly useful to discover diagnostic signatures as the mass of microarray data continues to grow in the ‘omics’ era

Regulation of human CD4+ T cell differentiation

Naive CD4+ T cells differentiate into specific effector subsets—Th1, Th2, Th17, and T follicular helper (Tfh)—that provide immunity against pathogen infection. The signaling pathways involved in generating these effector cells are partially known. However, the effects of mutations underlying human primary immunodeficiencies on these processes, and how they compromise specific immune responses, remain unresolved. By studying individuals with mutations in key signaling pathways, we identified nonredundant pathways regulating human CD4+ T cell differentiation in vitro. IL12Rβ1/TYK2 and IFN-γR/STAT1 function in a feed-forward loop to induce Th1 cells, whereas IL-21/IL-21R/STAT3 signaling is required for Th17, Tfh, and IL-10–secreting cells. IL12Rβ1/TYK2 and NEMO are also required for Th17 induction. Strikingly, gain-of-function STAT1 mutations recapitulated the impact of dominant-negative STAT3 mutations on Tfh and Th17 cells, revealing a putative inhibitory effect of hypermorphic STAT1 over STAT3. These findings provide mechanistic insight into the requirements for human T cell effector function, and explain clinical manifestations of these immunodeficient conditions. Furthermore, they identify molecules that could be targeted to modulate CD4+ T cell effector function in the settings of infection, vaccination, or immune dysregulation

General Approach to Identifying Potential Targets for Cancer Imaging by Integrated Bioinformatics Analysis of Publicly Available Genomic Profiles

Molecular imaging has moved to the forefront of drug development and biomedical research. The identification of appropriate imaging targets has become the touchstone for the accurate diagnosis and prognosis of human cancer. Particularly, cell surface- or membrane-bound proteins are attractive imaging targets for their aberrant expression, easily accessible location, and unique biochemical functions in tumor cells. Previously, we published a literature mining of potential targets for our in-house enzyme-mediated cancer imaging and therapy technology. Here we present a simple and integrated bioinformatics analysis approach that assembles a public cancer microarray database with a pathway knowledge base for ascertaining and prioritizing upregulated genes encoding cell surface- or membrane-bound proteins, which could serve imaging targets. As examples, we obtained lists of potential hits for six common and lethal human tumors in the prostate, breast, lung, colon, ovary, and pancreas. As control tests, a number of well-known cancer imaging targets were detected and confirmed by our study. Further, by consulting gene-disease and protein-disease databases, we suggest a number of significantly upregulated genes as promising imaging targets, including cell surface-associated mucin-1, prostate-specific membrane antigen, hepsin, urokinase plasminogen activator receptor, and folate receptors. By integrating pathway analysis, we are able to organize and map “focused” interaction networks derived from significantly dysregulated entity pairs to reflect important cellular functions in disease processes. We provide herein an example of identifying a tumor cell growth and proliferation subnetwork for prostate cancer. This systematic mining approach can be broadly applied to identify imaging or therapeutic targets for other human diseases