Mycosis fungoides progression could be regulated by microRNAs.
Rebeca MansoNerea Martínez-MagunacelayaItziar Eraña-TomásVerónica MonsalvezJosé L Rodríguez-PeraltoPablo-L Ortiz-RomeroCarlos SantonjaIon CristóbalMiguel A PirisSocorro M Rodríguez-PinillaPublished in: PloS one (2018)
Differentiating early mycosis fungoides (MF) from inflammatory dermatitis is a challenge. We compare the differential expression profile of early-stage MF samples and benign inflammatory dermatoses using microRNA (miRNA) arrays. 114 miRNAs were found to be dysregulated between these entities. The seven most differentially expressed miRNAs between these two conditions were further analyzed using RT-PCR in two series comprising 38 samples of early MFs and 18 samples of inflammatory dermatitis. A series of 51 paraffin-embedded samples belonging to paired stages of 16 MF patients was also analyzed. MiRNAs 26a, 222, 181a and 146a were differentially expressed between tumoral and inflammatory conditions. Two of these miRNAs (miRNA-181a and miRNA-146a) were significantly deregulated between early and advanced MF stages. Bioinformatic analysis showed FOXP3 expression to be regulated by these miRNAs. Immunohistochemistry revealed the level of FOXP3 expression to be lower in tumoral MFs than in plaque lesions in paraffin-embedded tissue. A functional study confirmed that both miRNAs diminished FOXP3 expression when overexpressed in CTCL cells. The data presented here suggest that the analysis of a restricted number of miRNAs (26a, 222, 181a and 146a) could be sufficient to differentiate tumoral from reactive conditions. Moreover, these miRNAs seem to be involved in MF progression.
Keyphrases
- poor prognosis
- early stage
- regulatory t cells
- oxidative stress
- end stage renal disease
- newly diagnosed
- induced apoptosis
- ejection fraction
- chronic kidney disease
- coronary artery disease
- computed tomography
- prognostic factors
- machine learning
- cell death
- radiation therapy
- immune response
- endoplasmic reticulum stress
- peritoneal dialysis
- magnetic resonance
- deep learning
- atopic dermatitis
- pi k akt