Dataset: Transcription profiling by array of human normal bronchial epithelia cells to study the impact of TNFa on NFkB translocation and gene expression pattern

Modern omics technologies, where changes in the expression of thousands of molecular species can be investigated in even a simple experiment, provide contemporary biomedical researchers with an unprecedented level of molecular granularity. An outstanding challenge is transformation of this experimental detail and complexity into meaningful biological insight. This is especially true for drug development and toxicological risk assessment, where molecular profiling data is increasingly being used to investigate the biological effects of a variety of exposures, from drugs to environmental factors, on human systems. Recently, we proposed a systems-based strategy for objectively predicting the mechanistic impact of biologically active substances from transcriptomic data, and report here on an initial implementation of this strategy. We applied a set of biological network models and novel scoring algorithms to investigate transcriptomic data from a range of experimental systems. Importantly, this approach enabled continuity between investigation at the molecular, pathway, and systems levels. For both in vitro systems with simple exposures and in vivo systems with complex exposures, the method was able to identify and provide relative quantitation for the precise mechanisms that were impacted. Importantly, many of the effects indicated by the methodology were supported by experimental endpoint data, providing further objective validation of the general approach. We propose that various fields of human disease research, from drug development to consumer product testing, could benefit from using this or similar approaches to evaluate the biological impact of exposures.

Species:

human

Samples:

48

Source:

E-MTAB-1312

Updated:

Dec.12, 2014

Registered:

Jul.12, 2014