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It has been proposed that CD4 T-cell responses to Staphylococcus aureus (SA) can inadvertently enhance neoplastic progression in models of skin cancer and cutaneous T-cell lymphoma (CTCL). In this prospective study, we explored the effect of transient antibiotic treatment on tumor cells and disease activity in 8 patients with advanced-stage CTCL. All patients experienced significant decrease in clinical symptoms in response to aggressive, transient antibiotic treatment. In some patients, clinical improvements lasted for more than 8 months. In 6 of 8 patients, a malignant T-cell clone could be identified in lesional skin, and a significant decrease in the fraction of malignant T cells was observed following antibiotics but an otherwise unchanged treatment regimen. Immunohistochemistry, global messenger RNA expression, and cell-signaling pathway analysis indicated that transient aggressive antibiotic therapy was associated with decreased expression of interleukin-2 high-affinity receptors (CD25), STAT3 signaling, and cell proliferation in lesional skin. In conclusion, this study provides novel evidence suggesting that aggressive antibiotic treatment inhibits malignant T cells in lesional skin. Thus, we provide a novel rationale for treatment of SA in advanced CTCL.

Mycosis fungoides (MF) is the most frequent form of cutaneous T-cell lymphoma. The disease often takes an indolent course, but in approximately one-third of the patients, the disease progresses to an aggressive malignancy with a poor prognosis. At the time of diagnosis, it is impossible to predict which patients develop severe disease and are in need of aggressive treatment. Accordingly, we investigated the prognostic potential of microRNAs (miRNAs) at the time of diagnosis in MF. Using a quantitative reverse transcription polymerase chain reaction platform, we analyzed miRNA expression in diagnostic skin biopsies from 154 Danish patients with early-stage MF. The patients were subdivided into a discovery cohort (n = 82) and an independent validation cohort (n = 72). The miRNA classifier was built using a LASSO (least absolute shrinkage and selection operator) Cox regression to predict progression-free survival (PFS). We developed a 3-miRNA classifier, based on miR-106b-5p, miR-148a-3p, and miR-338-3p, which successfully separated patients into high-risk and low-risk groups of disease progression. PFS was significantly different between these groups in both the discovery cohort and the validation cohort. The classifier was stronger than existing clinical prognostic factors and remained a strong independent prognostic tool after stratification and adjustment for these factors. Importantly, patients in the high-risk group had a significantly reduced overall survival. The 3-miRNA classifier is an effective tool to predict disease progression of early-stage MF at the time of diagnosis. The classifier adds significant prognostic value to existing clinical prognostic factors and may facilitate more individualized treatment of these patients.