Bioinformatics strategies for identification of cancer biomarkers and targets in pathogens associated with cancer

Abstract

Cancer and bacterial infectious diseases are major cause of deaths globally and molecular biomarkers are essential tools for screening, diagnosis, prognosis, and therapy of these diseases. Various strategies have been employed to identify biomarkers over years. In this research, five novel bioinformatics strategies have been used to identify biomarkers in human diseases (especially cancer) and genomic targets in human pathogenic bacteria. (I) A novel in silico reverse-transcriptomics strategy based a panel of sub-type specific lung cancer biomarkers have been identified and validated in patients blood samples using qPCR. An upregulation of TFPD1, E2F6, IRF1, and HMGA1 + NO expression of SUV39H1, RBL1, and HNRPD in blood sample are characteristics of Adeno and Squamous cell lung carcinomas. E2F6 is found a novel marker in lung cancer. The strategy can be useful in any other complex diseases and can explore novel insight of the disease pathogenesis, identification of early markers, and will be helpful in developing personalized medicine. (II) The second method describes miRegulome-a manually curated novel miRNA knowledgebase that gives entire regulatory modules of miRNAs and thus provide comprehensive understanding of miRNA regulatory networks and miRNA functions. Exploration of new and novel biological events and discovery of biomarkers and therapeutics can be achieved with high precision using Chemical-disease, miRNA-disease, Genedisease, and Disease-chemical/miRNA analysis tools that are integrated with miRegulome. (III) In third bioinformatics strategy is on a novel computational methodology/pipeline (consensus of six network inference algorithms along with graph theory) for identification of miRNA-miRNA interactions based disease-specific and common miRNA Signatures (miRsig) in cancers or other diseases. The miRsig is powerful enough to identify early deregulated pan-cancer miRNA networks and therefore such miRNAs may be useful as screening or early diagnostic tools in cancer. miRsig can equally be applied in other diseases too. (IV) To identify common conserved targets in M. tuberculosis, C. pseudotuberculosis (Cp), C. diphtheriae, C. ulcerans, Y. pestis, and pathogenic E. coli, a novel integrated bioinformatics approach combining protein-protein interactions (PPI), host-pathogen interactions, and subtractive genomics is presented in the forth strategy. Using this method, first time we have developed intra-species PPIs Cp strains and acetate kinase (Ack) as a common conserved target for all these pathogens. Piperdardine and Dehydropipernonaline from Piper betel target Ack more effectively than Penicillin and Ceftiofur in silico and in in vitro, Piperdardine inhibits E. coli O157:H7 growth similar to penicillin. (V) In the fifth strategy, comparative and subtractive exoproteomics and secretomics in combination with modified reverse vaccinology approach, ompU, uppP and yajC were identified as novel and common conserved targets in 21 V. cholerae serotypes. Seven Piper betel compounds showinhibitory effects against these targets in in silico and anti- Vibrio effects in vitro. Although these bacteria are predominantly associated with various infectious diseases, they are also reported to be associated with tumor/ cancer. The M. tuberculosis infection increases the risk of lung cancer, and several human miRNAs are deregulated in both lung cancer and pulmonary tuberculosis; The future scope of this research is to develop bioinformatics strategies to identify the common signature associated with both pulmonary tuberculosis and lung cancer so that common cause and common management strategies can be developed against pulmonary tuberculosis and lung cancer.