Introduction

Mycosis fungoides (MF) and Sézary syndrome (SS) are the most common subtypes of cutaneous T-cell lymphomas. The diagnosis of these patients is very challenging and requires an integrated approach, incorporating clinical, morphological, immunophenotypic and molecular features. The molecular substrate of early and advanced stages of MF / SS is still poorly understood and, consequently, treatment selection is mainly based on clinical data. The study aimed to transfer what is known about the molecular pathogenesis of MF / SS to early diagnosis, prognosis, and selection of therapy by identifying molecular markers associated with the course of the disease.

Methods

Using the NanoString platform for gene-expression analysis, we design a custom panel of 77 genes relevant in the pathogenesis of MF/SS, together with genes known to be therapeutic targets. A series of 104 formalin-fixed, paraffin-embedded (FFPE) samples belonging to 31 MF/SS patients in different phases of the disease and inflammatory samples are included in the study.

Results

The technique was informative in all analyzed cases, independently of the clinical or histological stage or density of the tumor infiltration. For each case or sample the analysis provided an objective measure of the T-cell phenotype (T-cell differentiation gene sets), cellular composition of the infiltrate (dendritic cells, macrophages, B-cells, …) expression of markers used for therapy selection (CD30, CXCR4 and KIR3DL2) and expression level of surrogate markers for the main cell-survival oncogenic pathways.
Unexpectedly, non-supervised clustering showed that most of the clustering was dependent of the patient identity, suggesting that MF/SS has a high degree of inter-tumoral heterogeneity and that molecular signature for each patient tends to remain relatively stable along the disease.
Samples corresponding to pre-MF lesions tend to cluster with early MF/SS samples, suggesting that pre-MF lesions indeed correspond to early phases of the disease.
On the other hand, patients who progress to advanced stages have a tendency to cluster with each other. Several differentially expressed genes were comparing early and advanced stages. FGFR3, NUAK1, FJX1, CXCL12 and RORC were up regulated in early lesions, while CARD11, CD2, CD38, CD3D, CD3E, CD3G, CXCR4, GZMA, IL10 and SELL were up - regulated in tumors (p< 0,005).

Conclusions

Gene-expression profiling using a customized NanoString platform can be applied to routine paraffin embedded MF/SS samples and provides data that allow to a better understanding of MF genesis and progression. MF/SS samples show an unexpected high degree of inter-tumoral heterogeneity, suggesting that every patient has some individual molecular signature features that are found in consecutive biopsies.
The analysis brings also particular gene signatures associated with early MF and progression, allowing recognizing stage-specific signatures.