| Literature DB >> 30984002 |
Harald Hampel1,2,3,4, Edward J Goetzl5, Dimitrios Kapogiannis6, Simone Lista1,2,3,4, Andrea Vergallo1,2,3,4.
Abstract
Systems biology studies have demonstrated that different (epi)genetic and pathophysiological alterations may be mapped onto a single tumor's clinical phenotype thereby revealing commonalities shared by cancers with divergent phenotypes. The success of this approach in cancer based on analyses of traditional and emerging body fluid-based biomarkers has given rise to the concept of liquid biopsy enabling a non-invasive and widely accessible precision medicine approach and a significant paradigm shift in the management of cancer. Serial liquid biopsies offer clues about the evolution of cancer in individual patients across disease stages enabling the application of individualized genetically and biologically guided therapies. Moreover, liquid biopsy is contributing to the transformation of drug research and development strategies as well as supporting clinical practice allowing identification of subsets of patients who may enter pathway-based targeted therapies not dictated by clinical phenotypes alone. A similar liquid biopsy concept is emerging for Alzheimer's disease, in which blood-based biomarkers adaptable to each patient and stage of disease, may be used for positive and negative patient selection to facilitate establishment of high-value drug targets and counter-measures for drug resistance. Going beyond the "one marker, one drug" model, integrated applications of genomics, transcriptomics, proteomics, receptor expression and receptor cell biology and conformational status assessments during biomarker-drug co-development may lead to a new successful era for Alzheimer's disease therapeutics. We argue that the time is now for implementing a liquid biopsy-guided strategy for the development of drugs that precisely target Alzheimer's disease pathophysiology in individual patients.Entities:
Keywords: Alzheimer’s disease; exosomes; liquid biopsy; precision medicine; systems pharmacology
Year: 2019 PMID: 30984002 PMCID: PMC6450260 DOI: 10.3389/fphar.2019.00310
Source DB: PubMed Journal: Front Pharmacol ISSN: 1663-9812 Impact factor: 5.810
Experimental therapeutic targets suggested by neural exosome protein abnormalities.
| Disease | Protein(s) | Neural cell source | Desired effect | Estimated feasibility as an approachable target |
|---|---|---|---|---|
| AD | P-tau species | Neurons | Suppress kinase(s) (CDK5, GSK3b, ERK2) | 1 |
| Enhance phosphatase(s) | ||||
| P-S-IRS-1 | Neurons | Suppress kinase(s) | 2 | |
| Excitatory pathway synaptic proteins | Neurons | Restore protein levels | 2 | |
| Aβ-generating BACE-1 and γ-secretase | Astrocytes | Selective protease inhibitors | 2 | |
| Complement (C) system [C3b, Bb, C5b-C9] | Astrocytes | Suppress complement activation; block C receptors | 3 | |
| Growth and regenerative factors (HGF, FGF-13, IGF-1) | CSPG4 cells | Restore CSPG4 proteins | 3 | |
| CeVD | Regulators of vascular tone and repair/regeneration (NOSTRIN, YAP-1/P-YAP-1) | Endothelial cells | Decrease NOSTRIN, increase active YAP-1 | 2 |
| Complement (C) system [C3b, Bb, C5b-C9] | Endothelial cells | Suppress complement activation; block C receptors | 3 | |
FIGURE 1Liquid biopsy-guided management of Alzheimer’s disease according to a hypothetical model of spatial-temporal system-wide shifts: from adaptation to irreversible failure. Homeostasis is ensured by adaptive responses and compensatory mechanisms scaled in time and space across multi-level system networks: from molecular pathways, to cellular stress responses, to brain cell-to-cell and synaptic dynamics, to large-scale brain network activity, to brain-periphery cross-talks. If a decompensatory cascade occurs, homeostasis progressively breaks down until final systems failure. Functional stage – adaptation stage – stress responses: Metabolic and energetic reconfiguration associated with functional switch in molecular/cellular/tissue/brain systems/body system network activity. Functional–structural stage – compensation stage – resiliency mechanisms: Structural and functional counterbalancing of one or more initial pathomechanistic alterations. Early decompensation stage – breakdown of resiliency mechanisms: Initial and progressive loss of compensatory effect (resilience) or over sustained compensation which may be neither protective nor homeostatic. Late decompensation stage (failure stage) – failure of resiliency mechanisms: Hypothetical point of no-return. The colored curve line from green to red indicates a decreasing magnitude of drugs efficacy. The colored curve from green to red indicates a decreasing magnitude of drugs efficacy. The blue rectangles indicate the different context-of-use of biomarkers according to the pathophysiological evolution.
FIGURE 2Ideally, biomarkers should be carried through all phases of drug development and validated and qualified in agreement with regulators. The picture shows one possible model for biomarker-drug co-development program: a regulatory scenario for a single test that would be used in conjunction with a single drug in the clinical management of a patient. The figure highlights key events for both the diagnostic test and drug regulation with overall coordination of the regulatory processes governing them so that the products launch together.