Human α-synuclein overexpression upregulates SKOR1 in a rat model of simulated nigrostriatal ageing

Parkinson's disease (PD) is characterised by progressive loss of dopaminergic (DA) neurons from the substantia nigra (SN) and α-synuclein (αSyn) accumulation. Age is the biggest risk factor for PD and may create a vulnerable pre-parkinsonian state, but the drivers of this association are unclear. It is known that ageing increases αSyn expression in DA neurons and that this may alter molecular processes that are central to maintaining nigrostriatal integrity. To model this, adult female Sprague-Dawley rats received a unilateral intranigral injection of adeno-associated viral (AAV) vector carrying wild-type human αSyn (AAV-αSyn) or control vector (AAV-Null). AAV-αSyn induced no detrimental effects on motor behaviour, but there was expression of human wild-type αSyn throughout the midbrain and ipsilateral striatum at 20 weeks post-surgery. Microarray analysis revealed that the gene most-upregulated in the ipsilateral SN of the AAV-αSyn group was the SKI Family Transcriptional Corepressor 1 (SKOR1). Bioenergetic state analysis of mitochondrial function found that SKOR1 overexpression reduced the maximum rate of cellular respiration in SH-SY5Y cells. Furthermore, experiments in SH-SY5Y cells revealed that SKOR1 overexpression impaired neurite growth to the same extent as αSyn, and inhibited BMP-SMAD-dependent transcription, a pathway that promotes DA neuronal survival and growth. Given the normal influence of ageing on DA neuron loss in human SN, the extent of αSyn-induced SKOR1 expression may influence whether an individual undergoes normal nigrostriatal ageing or reaches a threshold for prodromal PD. This provides new insight into mechanisms through which ageing-related increases in αSyn may influence molecular mechanisms important for the maintenance of neuronal integrity.

Copy number alteration signatures as biomarkers in cancer: a review

Within certain cancers, extensive copy number alterations (CNAs) contribute to a complex and heterogenic genomic profile. This makes it difficult to understand and unravel the distinct molecular dynamics shaping the disease while preventing clinically effective patient stratification. CNA signature analysis represents a novel genomic stratification tool for probing this complexity, offering an intricate framework for deriving CNA patterns at the molecular level. This allows the underlying genomic mechanisms of specific cancers to be revealed, leading to the potential identification of therapeutic targets and prognostic associations. This review outlines the molecular and methodological basis of CNA signatures and focuses on recent advances highlighting their clinical utility, limitations and prospective future as novel diagnostic and prognostic cancer biomarkers.