Dataset Information

Analysis of microRNA-target interactions across diverse cancer types.

ABSTRACT: Little is known about the extent to which individual microRNAs (miRNAs) regulate common processes of tumor biology across diverse cancer types. Using molecular profiles of >3,000 tumors from 11 human cancer types in The Cancer Genome Atlas, we systematically analyzed expression of miRNAs and mRNAs across cancer types to infer recurrent cancer-associated miRNA-target relationships. As we expected, the inferred relationships were consistent with sequence-based predictions and published data from miRNA perturbation experiments. Notably, miRNAs with recurrent target relationships were frequently regulated by genetic and epigenetic alterations across the studied cancer types. We also identify new examples of miRNAs that coordinately regulate cancer pathways, including the miR-29 family, which recurrently regulates active DNA demethylation pathway members TET1 and TDG. The online resource http://cancerminer.org allows exploration and prioritization of miRNA-target interactions that potentially regulate tumorigenesis.

SUBMITTER: Jacobsen A

PROVIDER: S-EPMC3982325 | biostudies-literature | 2013 Nov

REPOSITORIES: biostudies-literature

ACCESS DATA

Publications

Analysis of microRNA-target interactions across diverse cancer types.

Jacobsen Anders A Silber Joachim J Harinath Girish G Huse Jason T JT Schultz Nikolaus N Sander Chris C

Nature structural & molecular biology 20131006 11

Little is known about the extent to which individual microRNAs (miRNAs) regulate common processes of tumor biology across diverse cancer types. Using molecular profiles of >3,000 tumors from 11 human cancer types in The Cancer Genome Atlas, we systematically analyzed expression of miRNAs and mRNAs across cancer types to infer recurrent cancer-associated miRNA-target relationships. As we expected, the inferred relationships were consistent with sequence-based predictions and published data from m ...[more]

PMID: 24096364

Similar Datasets

Project description:(p)ppGpp, highly phosphorylated guanosine, are global regulatory nucleotides that modulate several biochemical events in bacterial physiology ranging from core central dogma to various metabolic pathways. Conventionally, (p)ppGpp collectively refers to two nucleotides, ppGpp, and pppGpp in the literature. Initially, (p)ppGpp has been discovered as a transcription regulatory molecule as it binds to RNA polymerase and regulates transcriptional gene regulation. During the past decade, several other target proteins of (p)ppGpp have been discovered and as of now, more than 30 proteins have been reported to be regulated by the binding of these two signaling nucleotides. The regulation of diverse biochemical activities by (p)ppGpp requires fine-tuned molecular interactions with various classes of proteins so that it can moderate varied functions. Here we report a structural dynamics of (p)ppGpp in the unbound state using well-defined computational tools and its interactions with target proteins to understand the differential regulation by (p)ppGpp at the molecular level. We carried out replica exchange molecular dynamics simulation studies to enhance sampling of conformations during (p)ppGpp simulation. The detailed comparative analysis of torsion angle conformation of ribose sugar of unbound (p)ppGpp and bound states of (p)ppGpp was carried out. The structural dynamics shows that two linear phosphate chains provide plasticity to (p)ppGpp nucleotides for the binding to diverse proteins. Moreover, the intermolecular interactions between (p)ppGpp and target proteins were characterized through various physicochemical parameters including, hydrogen bonds, van der Waal's interactions, aromatic stacking, and side chains of interacting residues of proteins. Surprisingly, we observed that interactions of (p)ppGpp to target protein have a consensus binding pattern for a particular functional class of enzymes. For example, the binding of (p)ppGpp to RNA polymerase is significantly different from the binding of (p)ppGpp to the proteins involved in the ribosome biogenesis pathway. Whereas, (p)ppGpp binding to enzymes involved in nucleotide metabolism facilitates the functional regulation through oligomerization. Analysis of these datasets revealed that guanine base-specific contacts are key determinants to discriminate functional class of protein. Altogether, our studies provide significant information to understand the differential interaction pattern of (p)ppGpp to its target and this information may be useful to design antibacterial compounds based on (p)ppGpp analogs.

Dataset Information

Analysis of microRNA-target interactions across diverse cancer types.

Publications

Analysis of microRNA-target interactions across diverse cancer types.

Similar Datasets

OmicsDI is part of the ELIXIR infrastructure

Tweets