Background:
Malignant gliomas constitute a complex disease phenotype that demands optimum decisionmaking. Despite being the most common type of primary brain tumors, gliomas are highly heterogeneous when their
pathophysiology and response to treatment are considered. Such inter-individual variability also renders differential and
early diagnosis extremely difficult. Recent evidence highlight that the gene-environment interplay becomes of
fundamental importance in oncogenesis and progression of gliomas.
Objective:
To unmask key features of the gliomas disease phenotype and map the inter-individual variability of patients,
we explore genotype-to-phenotype associations. Emphasis is put on microRNAs as they regulate gene expression, have
been implicated in the pathogenesis of gliomas and may serve as theranostics, empowering non-invasive strategies
(circulating free or in exosomes).
Method:
We mined text and omic datasets (as of 2019) and conducted a mixed-method content analysis. A novel
framework was developed to meet the aims of our analysis, interrogating data in terms of content and context. We relied
on literature data from PubMed/Medline and Scopus, as they are considered the largest abstract and citation databases of
peer-reviewed literature. To avoid selection biases, both publicly available and private texts have been assessed. Both
percent agreement and Cohen's kappa statistic have been calculated to avoid biases by SAS macro MAGREE with
multicategorical ratings.
Results:
Gliomas serve as a paradigm for multifaceted datasets, despite data sparsity and scarcity. miRNAs and miRNAbased therapeutics are ready for prime time. Exosomal miRNAs empower non-invasive strategies, surpassing circulating
free miRNAs, when accuracy and precision are considered.
Conclusion:
miRNAs holds promise as theranostics.
Acoustic stimulation increases implicit adaptation in sensorimotor adaptation
