Panomics for Precision Medicine

Abstract

Medicine is poised to undergo a digital transformation. High-throughput platforms are creating terabytes of genomic, transcriptomic, proteomic, and metabolomic data. The challenge is to interpret these data in a meaningful manner - to uncover relationships that are not readily apparent between molecular profiles and states of health or disease. This will require the development of novel data pipelines and computational tools. The combined analysis of multi-dimensional data is referred to as 'panomics'. The ultimate hope of integrative panomics is that it will lead to the discovery and application of novel markers and targeted therapeutics that drive forward a new era of 'precision medicine' where inter-individual variation is accounted for in the treatment of patients.

The Case for Proteomics and Phospho‐Proteomics in Personalized Cancer Medicine

“…This illustrates that the limitations of genomics and transcriptomics restrict our ability to fully comprehend the pathophysiology and complexity of cancer. Instead, panomics, the integration of multiple “omic” approaches may be better able to decipher causal relationships . Furthermore, it has become clear that the development and complexity of cancer cannot be explained simply by genetic alterations and transcriptional changes alone.…”

“…We believe that robust, highly sensitive, and specific personalized proteomic technology can be developed to profile tumor‐specific expression of proteins and PTMs. By combining proteomic data with genomic and clinical data, the ultimate aim is to generate a personalized panomics profile for each patient to better inform treatment decisions . Large initiatives such as the Obama Precision Medicine program highlight the importance of taking individual molecular variability into account.…”

Precision pharmacotherapy: Integrating pharmacogenomics into clinical pharmacy practice

“…In particular, randomized controlled trials (RCTs) remain the gold standard for clinical research and are often relied on to show the benefit of an intervention; however, conducting RCTs to evaluate the benefit of clinical pharmacogenomics is expensive and logistically complex. RCTs require large diverse patient cohorts to capture rare variants/phenotypes and have ethical considerations . Therefore, innovative trial designs are critical for future clinical pharmacogenomic research efforts and will likely include the use of pragmatic studies, quality improvement projects, well‐designed retrospective studies, and meta‐analyses.…”

“…RCTs require large diverse patient cohorts to capture rare variants/phenotypes and have ethical considerations. 85 Therefore, innovative trial designs are critical for future clinical pharmacogenomic research efforts and will likely include the use of pragmatic studies, quality improvement projects, well-designed retrospective studies, and meta-analyses. A multitude of evidence, rather than a single RCT, will likely be needed to demonstrate the value of clinical pharmacogenomics.…”

Analysis of Pan-Omics Data in Human Interactome Network (APODHIN)

“…Different types of omics data include RNA transcriptomics, miRNA transcriptomics, proteomics, phosphoproteomics, genomics, epigenomics, metabolomics, lipidomics, and pharmacogenomics which are also considered as 'big' data in the context of biological data analysis. Collective analysis of these multi-dimensional data is referred to as 'pan-omics' [1].…”