Personalized or precision medicine (PM) is developing and adopting of the safest and most cost-effective therapeutic approach for each patient. PM approach aims to identify phenotypic and genotypic individual characteristics, observe how these parameters are correlated with the disease status, severity, and intervention responsiveness to predict the best personalized clinical protocol. On the other hand, the risk of severe toxicity and adverse effects might be related to the patient-specific characteristics.
Thus, this promising clinical strategy needs to take into account a complex scenario where patient genetic background as well as pathophysiological status and environmental factors are important. Given that each disorder exhibits large inter- and intra-individual variability in space and time there is a critical need to understand each patient molecular characteristics and identify personalized biomarkers correlated with the disease onset and progress. To this aim, PM relies on systems-levels computational data analyzing coming from genome sequencing, physiological, hemodynamic, and neuroimaging investigations. Patients have been stratified using these big databases that correlate, for example, phenotypic classification with genetic profile as well as neurophysiological and neuroimaging analysis.
Some initial studies have shown PM would bring promising clinical outcomes for the diagnosis and treatment of different neurological disorders including Alzheimer's disease, Parkinson's disease, Brain cancers, depressive disorders, multiple sclerosis through early and differential diagnosis, improved prognosis, prediction of treatment response.
Predictive, prognostic, and early response biomarkers are of particular importance in Neuro-oncology and Neuroscience. Recent advances in multiplex genotyping technologies and high-throughput genomic profiling by next-generation sequencing make possible the rapid and comprehensive analysis of a disorder genome of individual patients. In addition to classic single molecular markers, high-throughput approaches including whole genome sequencing, single-nucleotide polymorphism analysis, microarray analysis, and mass spectrometry are under development. Predictive biomarkers based on molecular diagnostics are currently used in clinical practice of PM to define molecularly targeted biomarker therapies in Oncology such as Tyrosine kinase inhibitors, anaplastic lymphoma kinase (ALK) inhibitors with EML4-ALk fusion, HER2/neu blockage in HER2/neu-positive, and epidermal growth factor receptors inhibition.
This Research Topic will welcome Original Research and Review articles focusing on the recent advances, applications, and clinical challenges of PM in Neuro-oncology and Neuroscience:
• Biomarkers established for PM approaches in neurological disorders and cancer treatment.
• Applications of PM in screening, early and differential diagnosis, prognosis, treatment response prediction, stratification of patients into different subgroups.
Personalized or precision medicine (PM) is developing and adopting of the safest and most cost-effective therapeutic approach for each patient. PM approach aims to identify phenotypic and genotypic individual characteristics, observe how these parameters are correlated with the disease status, severity, and intervention responsiveness to predict the best personalized clinical protocol. On the other hand, the risk of severe toxicity and adverse effects might be related to the patient-specific characteristics.
Thus, this promising clinical strategy needs to take into account a complex scenario where patient genetic background as well as pathophysiological status and environmental factors are important. Given that each disorder exhibits large inter- and intra-individual variability in space and time there is a critical need to understand each patient molecular characteristics and identify personalized biomarkers correlated with the disease onset and progress. To this aim, PM relies on systems-levels computational data analyzing coming from genome sequencing, physiological, hemodynamic, and neuroimaging investigations. Patients have been stratified using these big databases that correlate, for example, phenotypic classification with genetic profile as well as neurophysiological and neuroimaging analysis.
Some initial studies have shown PM would bring promising clinical outcomes for the diagnosis and treatment of different neurological disorders including Alzheimer's disease, Parkinson's disease, Brain cancers, depressive disorders, multiple sclerosis through early and differential diagnosis, improved prognosis, prediction of treatment response.
Predictive, prognostic, and early response biomarkers are of particular importance in Neuro-oncology and Neuroscience. Recent advances in multiplex genotyping technologies and high-throughput genomic profiling by next-generation sequencing make possible the rapid and comprehensive analysis of a disorder genome of individual patients. In addition to classic single molecular markers, high-throughput approaches including whole genome sequencing, single-nucleotide polymorphism analysis, microarray analysis, and mass spectrometry are under development. Predictive biomarkers based on molecular diagnostics are currently used in clinical practice of PM to define molecularly targeted biomarker therapies in Oncology such as Tyrosine kinase inhibitors, anaplastic lymphoma kinase (ALK) inhibitors with EML4-ALk fusion, HER2/neu blockage in HER2/neu-positive, and epidermal growth factor receptors inhibition.
This Research Topic will welcome Original Research and Review articles focusing on the recent advances, applications, and clinical challenges of PM in Neuro-oncology and Neuroscience:
• Biomarkers established for PM approaches in neurological disorders and cancer treatment.
• Applications of PM in screening, early and differential diagnosis, prognosis, treatment response prediction, stratification of patients into different subgroups.
