Transcriptomic analysis reveals the anti-cancer effect of gestational mesenchymal stem cell secretome.
Salvatore VaiasiccaGianmarco MeloneDavid W JamesMarcos QuintelaJing XiaoSeydou YaoRichard H FinnellRobert S ConlanLewis W FrancisBruna CorradettiPublished in: Stem cells translational medicine (2024)
The environment created during embryogenesis contributes to reducing aberrations that drive structural malformations and tumorigenesis. In this study, we investigate the anti-cancer effect of mesenchymal stem cells (MSCs) derived from 2 different gestational tissues, the amniotic fluid (AF) and the chorionic villi (CV), with emphasis on their secretome. Transcriptomic analysis was performed on patient-derived AF- and CV-MSCs collected during prenatal diagnosis and identified both mRNAs and lncRNAs, involved in tissue homeostasis and inhibiting biological processes associated with the etiology of aggressive cancers while regulating immune pathways shown to be important in chronic disorders. Secretome enrichment analysis also identified soluble moieties involved in target cell regulation, tissue homeostasis, and cancer cell inhibition through the highlighted Wnt, TNF, and TGF-β signaling pathways. Transcriptomic data were experimentally confirmed through in vitro assays, by evaluating the anti-cancer effect of the media conditioned by AF- and CV-MSCs and the exosomes derived from them on ovarian cancer cells, revealing inhibitory effects in 2D (by reducing cell viability and inducing apoptosis) and in 3D conditions (by negatively interfering with spheroid formation). These data provide molecular insights into the potential role of gestational tissues-derived MSCs as source of anti-cancer factors, paving the way for the development of therapeutics to create a pro-regenerative environment for tissue restoration following injury, disease, or against degenerative disorders.
Keyphrases
- mesenchymal stem cells
- umbilical cord
- weight gain
- cell therapy
- pregnant women
- atrial fibrillation
- bone marrow
- signaling pathway
- single cell
- electronic health record
- gene expression
- body mass index
- stem cells
- birth weight
- cell proliferation
- rheumatoid arthritis
- oxidative stress
- big data
- machine learning
- risk assessment
- endoplasmic reticulum stress
- rna seq
- anti inflammatory
- high throughput
- cell cycle arrest
- physical activity
- genome wide
- pi k akt
- network analysis
- genome wide analysis