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Multi-omics approach to infer cancer therapeutic targets on chromosome 20q across tumor types.

ABSTRACT: The identification of good targets is a critical step for the development of targeted therapies for cancer treatment. Here, we used a multi-omics approach to delineate potential targets on chromosome 20q, which frequently shows a complex pattern of DNA copy number amplification in many human cancers suggesting the presence of multiple driver genes. By comparing the amounts of individual mRNAs in cancer from 11 different human tissues with those in their corresponding normal tissues, we identified 18 genes that were robustly elevated across human cancers. Moreover, we found that higher expression levels of a majority of these genes were associated with poor prognosis in many human cancer types. Using DNA copy number and expression data for all 18 genes obtained from The Cancer Genome Atlas project, we discovered that amplification is a major mechanism driving overexpression of these 18 genes in the majority of human cancers. Our integrated analysis suggests that 18 genes on chromosome 20q might serve as novel potential molecular targets for targeted cancer therapy.

SUBMITTER: Snijders AM

PROVIDER: S-EPMC5025263 | biostudies-literature | 2016

REPOSITORIES: biostudies-literature

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Multi-omics approach to infer cancer therapeutic targets on chromosome 20q across tumor types.

Snijders Antoine M AM Mao Jian-Hua JH

Advances in modern oncology research 20160713 4

The identification of good targets is a critical step for the development of targeted therapies for cancer treatment. Here, we used a multi-omics approach to delineate potential targets on chromosome 20q, which frequently shows a complex pattern of DNA copy number amplification in many human cancers suggesting the presence of multiple driver genes. By comparing the amounts of individual mRNAs in cancer from 11 different human tissues with those in their corresponding normal tissues, we identifie ...[more]

PMID: 27642640

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Project description:Staphylococcus aureus infection is a leading cause of mortality and morbidity in community, hospital and live-stock sectors, especially with the widespread emergence of methicillin-resistant S. aureus (MRSA) strains. To identify new drug molecules to treat MRSA patients, we have undertaken to search essential proteins that are indispensable for their survival but non-homologous to human host proteins. The current study utilizes a subtractive genome and proteome approach to screen the possible therapeutic targets against S. aureus USA300. Bacterial essential genes are obtained from the DEG database and are compared to avoid cross-reactivity with human host genes. In silico analysis shows 198 proteins that may be considered as therapeutic candidates. Depending on their sub-cellular localization, proteins are grouped as either vaccine or drug targets or both. Extracellular proteins such as cell division proteins (Q2FZ91, Q2FZ95), penicillin-binding proteins (Q2FZ94, Q2FYI0) of the bacterial cell wall, phosphoglucomutase (Q2FE11) and lipoteichoic acid synthase (Q2FIS2) are considered as vaccine targets, and their epitopes have been mapped. Altogether, 53 drug targets are identified, which have shown similarity with the drug targets available in the DrugBank database. Predicted drug targets belong to the common metabolic pathways of MRSA, such as fatty acid biosynthesis, folate biosynthesis, peptidoglycan biosynthesis, ribosome, etc. Protein-protein interaction analysis emphasizing peptidoglycan biosynthesis reveals the connection between penicillin-binding proteins, mur-family proteins and FemXAB proteins. In this study, staphylococcal FemA protein (P0A0A5) is subjected to structure-based virtual screening for the drug repurposing approach. There are 20 residues missing in the crystal structure of FemA, and 12 of these residues are located at the catalytic site. The missing residues are modelled, and stereochemistry is checked. FDA approved drugs available in the DrugBank database have been used in virtual screening with FemA in search of potential repurposed molecules. This approach provides us with 10 drugs that may be used in the treatment of methicillin-resistant staphylococcal mediated diseases. AutoDock 4.2 is used for in silico screening and shows a comparable inhibition constant (Ki) for all 10 FDA-approved drugs towards FemA. Most of these drugs are used in the treatment of various cancers, migraines and leukaemia. Protein-drug interaction analysis shows that the drugs mostly interact with hydrophobic residues of FemA. Moreover, Tyr328 and Lys383 contribute largely to hydrogen bondings during interactions. All interacting amino acids that bind to the drugs are part of the active site cavity of FemA.Supplementary informationThe online version contains supplementary material available at 10.1007/s10989-021-10287-9.

Dataset Information

Multi-omics approach to infer cancer therapeutic targets on chromosome 20q across tumor types.

Publications

Multi-omics approach to infer cancer therapeutic targets on chromosome 20q across tumor types.

Similar Datasets

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