Transplantation of stem cells, in particular mesenchymal stem cells (MSCs), stands as a promising therapy for trauma, stroke or neurodegenerative conditions such as spinal cord or traumatic brain injuries (SCI or TBI), ischemic stroke (IS), or Parkinson’s disease (PD). Over the last few years, cell transplantation-based approaches have started to focus on the use of cell byproducts, with a strong emphasis on cell secretome. Having this in mind, the present review discusses the current state of the art of secretome-based therapy applications in different central nervous system (CNS) pathologies. For this purpose, the following topics are discussed: (1) What are the main cell secretome sources, composition, and associated collection techniques; (2) Possible differences of the therapeutic potential of the protein and vesicular fraction of the secretome; and (3) Impact of the cell secretome on CNS-related problems such as SCI, TBI, IS, and PD. With this, we aim to clarify some of the main questions that currently exist in the field of secretome-based therapies and consequently gain new knowledge that may help in the clinical application of secretome in CNS disorders.

Spinal cord injury (SCI) leads to severe functional deficits. Currently, there are no available pharmacological treatments to promote neurological recovery in SCI patients. Recent work from our group has shown that a baclofen treatment can promote functional recovery after a compression SCI in mice [1]. Here, we provide transcriptomic (RNA-seq) data from adult mouse spinal cords collected 7 days after a compression SCI and baclofen (vs vehicle) administration. The Illumina NovaSeq 6000 platform was used to generate the raw transcriptomic data. In addition, we also present bioinformatic analyses including differential gene expression analysis, enrichment analyses for various functional annotations (gene ontology, KEGG and BioCarta pathways or InterPro domains) and transcription factor targets. The raw RNA-seq data has been uploaded to the NCBI Sequence Read Archive (SRA) database (Bioproject ID PRJNA886048). The data generated from the bioinformatic analyses is contained within the article.