Panomics for Precision Medicine.

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.

Evaluation of data-dependent versus targeted shotgun proteomic approaches for monitoring transcription factor expression in breast cancer.

In breast cancer, there is a significant degree of molecular diversity among tumors. Multiple perturbations in signal transduction pathways impinge on transcriptional networks that in turn dictate malignant transformation and metastatic progression. Detailed knowledge of the sequence-specific transcription factors that become activated or repressed within a tumor and comparison of their relative levels of expression in cancer versus normal tissue should therefore provide insight into disease mechanisms, improving patient stratification and facilitating personalized treatment. While high-throughput tandem mass spectrometry methods for global proteome profiling have been developed, existing approaches have limited sensitivity and are often unable to detect low-abundance transcription factors in a complex biological specimen like a biopsy or tumor cell extract. To this end, we have undertaken a systematic comparative evaluation of three MS/MS methods for the ability to detect reference transcription factors spiked in known amounts into a cell-free breast cancer nuclear extract: Data-Dependent Acquisition (DDA), wherein precursor ion intensity dictates selection for fragmentation; Targeted Peptide Monitoring (TPM), a directed approach using successive isolation and fragmentation of predefined m/ z ratios; and Multiple Reaction Monitoring (MRM), in which specific precursor ion to product ion transitions are selectively monitored. Through a series of controlled, parallel benchmarking experiments, we have determined the relative figures-of-merit of each approach, and have established that prior knowledge of signature proteotypic peptides markedly improves overall detection sensitivity, reliability, and quantification.

Global protein shotgun expression profiling of proliferating mcf-7 breast cancer cells.

Protein expression becomes altered in breast epithelium during malignant transformation. Knowledge of these perturbations should provide insight into the molecular basis of breast cancer, as well as reveal possible new therapeutic targets. To this end, we have performed an extensive comparative proteomic survey of global protein expression patterns in proliferating MCF-7 breast cancer cells and normal human mammary epithelial cells using gel-free shotgun tandem mass spectrometry. Pathophysiological alterations associated with the malignant breast cancer phenotype were detected, including differences in the apparent levels of key regulators of the cell cycle, signal transduction, apoptosis, transcriptional regulation, and cell metabolism.

Altered p27(Kip1) phosphorylation, localization, and function in human epithelial cells resistant to transforming growth factor beta-mediated G(1) arrest.

p27(Kip1) is an important effector of G(1) arrest by transforming growth factor beta (TGF-beta). Investigations in a human mammary epithelial cell (HMEC) model, including cells that are sensitive (184(S)) and resistant (184A1L5(R)) to G(1) arrest by TGF-beta, revealed aberrant p27 regulation in the resistant cells. Cyclin E1-cyclin-dependent kinase 2 (cdk2) and cyclin A-cdk2 activities were increased, and p27-associated kinase activity was detected in 184A1L5(R) cells. p27 from 184A1L5(R) cells was localized to both nucleus and cytoplasm, showed an altered profile of phosphoisoforms, and had a reduced ability to bind and inhibit cyclin E1-cdk2 in vitro when compared to p27 from the sensitive 184(S) cells. In proliferating 184A1L5(R) cells, more p27 was associated with cyclin D1-cdk4 complexes than in 184(S). While TGF-beta inhibited the formation of cyclin D1-cdk4-p27 complexes in 184(S) cells, it did not inhibit the assembly of cyclin D1-cdk4-p27 complexes in the resistant 184A1L5(R) cells. p27 phosphorylation changed during cell cycle progression, with cyclin E1-bound p27 in G(0) showing a different phosphorylation pattern from that of cyclin D1-bound p27 in mid-G(1). These data suggest a model in which TGF-beta modulates p27 phosphorylation from its cyclin D1-bound assembly phosphoform to an alternate form that binds tightly to inhibit cyclin E1-cdk2. Altered phosphorylation of p27 in the resistant 184A1L5(R) cells may favor the binding of p27 to cyclin D1-cdk4 and prevent its accumulation in cyclin E1-cdk2 in response to TGF-beta.