RDF Sketch Maps - Knowledge Complexity Reduction for Precision Medicine Analytics

Abstract

Realization of precision medicine ideas requires significant research effort to be able to spot subtle differences in complex diseases at the molecular level to develop personalized therapies. It is especially important in many cases of highly heterogeneous cancers. Precision diagnostics and therapeutics of such diseases demands interrogation of vast amounts of biological knowledge coupled with novel analytic methodologies. For instance, pathway-based approaches can shed light on the way tumorigenesis takes place in individual patient cases and pinpoint to novel drug targets. However, comprehensive analysis of hundreds of pathways and thousands of genes creates a combinatorial explosion, that is challenging for medical practitioners to handle at the point of care. Here we extend our previous work on mapping clinical omics data to curated Resource Description Framework (RDF) knowledge bases to derive influence diagrams of interrelationships of biomarker proteins, diseases and signal transduction pathways for personalized theranostics. We present RDF Sketch Maps-a computational method to reduce knowledge complexity for precision medicine analytics. The method of RDF Sketch Maps is inspired by the way a sketch artist conveys only important visual information and discards other unnecessary details. In our case, we compute and retain only so-called RDF Edges-places with highly important diagnostic and therapeutic information. To do this we utilize 35 maps of human signal transduction pathways by transforming 300 KEGG maps into highly processable RDF knowledge base. We have demonstrated potential clinical utility of RDF Sketch Maps in hematopoietic cancers, including analysis of pathways associated with Hairy Cell Leukemia (HCL) and Chronic Myeloid Leukemia (CML) where we achieved up to 20-fold reduction in the number of biological entities to be analyzed, while retaining most likely important entities. In experiments with pathways associated with HCL a generated RDF Sketch Map of the top 30% paths retained important information about signaling cascades leading to activation of proto-oncogene BRAF, which is usually associated with a different cancer, melanoma. Recent reports of successful treatments of HCL patients by the BRAF-targeted drug vemurafenib support the validity of the RDF Sketch Maps findings. We therefore believe that RDF Sketch Maps will be invaluable for hypothesis generation for precision diagnostics and therapeutics as well as drug repurposing studies.

Knowledge Representation and Management, It’s Time to Integrate!

“…The section editors achieved a first selection of 100 papers based on titles and abstracts. After a second review of this set of papers, a selection of 15 candidate best papers was established [6][7][8][9][10][11][12][13][14][15][16][17][18][19][20]. Five reviewers reviewed these pre-selected papers to select the best four final papers [6][7][8][9].…”

“…Thanintorn et al [19] proposed the method of "sketch map" in order to reduce knowledge complexity for precision medicine analytics. The authors tend to demonstrate that the description of pathways with a new KEGG (Kyoto Encyclopedia Genes and Genomes) ontology and their method would be invaluable for hypothesis generation in different domains as precision diagnostics.…”

Computational Approaches in Theranostics: Mining and Predicting Cancer Data

“…Some authors [148] have also investigated advanced inference methods for mapping data from clinical biomarkers of key biological pathways to reproduce interactions and cooperative effects of signaling proteomic networks in each patient case [149,150]. A new framework [150] for providing case-specific rationales for theranostics has also been proposed.…”

“…Other methods to reduce the system complexity and produce relevant visual information for theranostics analysis, including the establishment of hypothesis for precision diagnostics and therapeutics and drug repurposing, have been supported by Resource Description Framework Sketch Maps [148]. The cancer model has been initially defined, reflecting the propagation of the biological signal transduction from the intercellular space via surface proteomic receptors located into the nuclear region in which specific activated protein complexes control gene expression.…”

“…Thanintorn et al [148] have explored RDF Sketch Maps in hematopoietic cancers (hairy cell leukemia, chronic myeloid leukemia) for which a significant reduction of ca. 20-fold of number of biological entities to be evaluated was obtained, and the most significant entities were retained.…”