Pregledni rad
https://doi.org/10.3325/cmj.2013.54.319
Stem cell systems informatics for advanced clinical biodiagnostics: tracing molecular signatures from bench to bedside
Randolph S. Faustino
; Division of Cardiovascular Diseases, Departments of Medicine Molecular Pharmacology and Experimental Therapeutics, Mayo Clinic, Rochester, MN, USA
D. Kent Arrell
; Division of Cardiovascular Diseases, Departments of Medicine Molecular Pharmacology and Experimental Therapeutics, Mayo Clinic, Rochester, MN, USA
Clifford D.L. Folmes
; Division of Cardiovascular Diseases, Departments of Medicine Molecular Pharmacology and Experimental Therapeutics, Mayo Clinic, Rochester, MN, USA
Andre Terzic
; Division of Cardiovascular Diseases, Departments of Medicine Molecular Pharmacology and Experimental Therapeutics, Mayo Clinic, Rochester, MN, USA
Carmen Perez-Terzic
; Physical Medicine and Rehabilitation, Mayo Clinic College of Medicine, Rochester, MN, USA
Sažetak
Development of innovative high throughput technologies
has enabled a variety of molecular landscapes to be interrogated
with an unprecedented degree of detail. Emergence
of next generation nucleotide sequencing methods,
advanced proteomic techniques, and metabolic profiling
approaches continue to produce a wealth of biological
data that captures molecular frameworks underlying phenotype.
The advent of these novel technologies has significant
translational applications, as investigators can now
explore molecular underpinnings of developmental states
with a high degree of resolution. Application of these leading-
edge techniques to patient samples has been successfully
used to unmask nuanced molecular details of disease
vs healthy tissue, which may provide novel targets for palliative
intervention. To enhance such approaches, concomitant
development of algorithms to reprogram differentiated
cells in order to recapitulate pluripotent capacity offers
a distinct advantage to advancing diagnostic methodology.
Bioinformatic deconvolution of several “-omic” layers
extracted from reprogrammed patient cells, could, in
principle, provide a means by which the evolution of individual
pathology can be developmentally monitored. Significant
logistic challenges face current implementation of
this novel paradigm of patient treatment and care, however,
several of these limitations have been successfully addressed
through continuous development of cutting edge
in silico archiving and processing methods. Comprehensive
elucidation of genomic, transcriptomic, proteomic,
and metabolomic networks that define normal and pathological
states, in combination with reprogrammed patient
cells are thus poised to become high value resources in
modern diagnosis and prognosis of patient disease.
Ključne riječi
Hrčak ID:
108670
URI
Datum izdavanja:
15.8.2013.
Posjeta: 1.077 *