Integration of omics sciences to advance biology and medicine

Emily S Boja,Christopher R Kinsinger,Pothur Srinivas,Henry Rodriguez

doi:10.1186/1559-0275-11-45

Abstract

In the past two decades, our ability to study cellular and molecular systems has been transformed through the development of omics sciences. While unlimited potential lies within massive omics datasets, the success of omics sciences to further our understanding of human disease and/or translating these findings to clinical utility remains elusive due to a number of factors. A significant limiting factor is the integration of different omics datasets (i.e., integromics) for extraction of biological and clinical insights. To this end, the National Cancer Institute (NCI) and the National Heart, Lung and Blood Institute (NHLBI) organized a joint workshop in June 2012 with the focus on integration issues related to multi-omics technologies that needed to be resolved in order to realize the full utility of integrating omics datasets by providing a glimpse into the disease as an integrated “system”. The overarching goals were to (1) identify challenges and roadblocks in omics integration, and (2) facilitate the full maturation of ‘integromics’ in biology and medicine. Participants reached a consensus on the most significant barriers for integrating omics sciences and provided recommendations on viable approaches to overcome each of these barriers within the areas of technology, bioinformatics and clinical medicine.

Highlights

The past two decades have been witness to an explosion of data stemming from the development and gradual maturation of ‘omics’ technologies and bioinformatics
Whole-genome sequencing has become a routine research tool, and state-of-the-art proteomic technologies have caught up to genomics in the past few years in terms of coverage as evidenced by their ability to identify a large percentage of all observed human gene products, including functionally significant alternative splice variants [1,2,3,4]
The National Cancer Institute (NCI)’s The Cancer Genome Atlas (TCGA) integrated multiple data types to identify three mutually exclusive pathways that affect the development of glioblastoma multiforme (e.g., RTK, TP53, RB) [6], suggesting that the presence of one aberration removes the selective pressure for a second aberration

Summary

Introduction

The past two decades have been witness to an explosion of data stemming from the development and gradual maturation of ‘omics’ technologies and bioinformatics. Technological challenges Two major technological challenges that were recognized to limit omics integration into medicine were (1) a lack of reproducibility of data acquired through nonuniformly standardized sample preparation, including a lack of understanding of the impact of pre-analytical variables on samples [32], and inconsistent instrument performance [19], and (2) a lack of high-throughput and multiplexing methods that make parallel measurements of multiple types of analytes for handling large clinical studies Addressing such obstacles, the scientific community has come a long way to demonstrate the analytical robustness of genomic, proteomic, and metabolomic workflows, including data analysis pipelines as witnessed by a flurry of standardization/harmonization activities during the last two decades in several omics areas including Genomic Standards Consortium, CPTAC, HUPO and ABRF [33,34,35,36,37,38,39,40]. Translating scores to a scale that physicians can understand and converting to a single scale that can be modified over time is very important in this process [19,45]

Conclusion

Findings

35. Martínez-Bartolomé S