Identification of a STAT3-miRNA Axis in T-LGL Leukemia

Introduction

T large granular lymphocytes leukemia (T-LGLL) is a rare disease characterized by the abnormal expansion of T-large granular lymphocytes (T-LGLs) in the peripheral blood. The etiology of this disease is still largely unknown. LGL proliferation is maintained through an impairment of the apoptotic machinery due to the activation of many survival signals. Among these, JAK/STAT signaling represents one of the most important deregulated pathways in T-LGLL. In particular, leukemic LGLs are equipped with STAT3 constitutively over-expressed and over-activated. Moreover, in 30-40% of patients, STAT3 has been demonstrated carrying hot-spot mutations, likely resulting in STAT3 activation. Although STAT3 is an inducer of transcription of a large number of oncogenes, its relationship with microRNAs (miRNAs) has not yet been extensively evaluated in T-LGLL patients. As a matter of fact, several miRNAs contribute to normal hematopoietic processes and many miRNAs act both as tumor suppressors and oncogenes in the pathology of hematological malignancies, including acute and chronic leukemias and lymphomas, where they contribute to lymphomagenesis acting in various cellular functions, such as the regulation of cell survival and proliferation.

Aims

We investigated whether STAT3 could carry out its pathogenetic role in T-LGLL through an altered expression of miRNAs. A high throughput quantitative and qualitative analysis of the miRNA expression profile in leukemic LGLs compared to healthy controls was performed with the aim to investigate whether STAT3 activation and/or mutation were correlated to some miRNAs in leukemic LGLs.

Methods

Six patients (3 characterized by STAT3 mutations and 3 with wild type STAT3) and three healthy controls were enrolled in a pilot study. STAT3 mRNA expression and protein activation levels were analyzed by Real Time-PCR and Western Blot, respectively. The expression level of 756 mature miRNAs was assessed by using a TaqMan-based Low Density Array on purified LGLs. Experimental data were analyzed by ViiA7 RUO software and the relative miRNA expression values were calculated using U6 as endogenous control. miRNA array data underwent hierarchical cluster analysis (HCL) by using MEV. miRNAs with a 2 or 0.5 fold change and p value < 0.05 in samples as compared to controls were considered as differentially expressed. Results of this pilot study were validated on additional 12 T-LGLL and 3 healthy controls subjects.

Results

Two clusters were identified by HCL analysis: cluster A included healthy controls and LGL patients characterized by comparably low levels of STAT3 activation (S3_low) and absence of STAT3 mutations. Cluster B included four patients characterized by high levels of STAT3 activation (S3_high). Remarkably, three out of four LGL patients in cluster B shared STAT3 mutation. Comparative analysis of the miRNAs expressed identified 33 miRNAs upregulated and 9 miRNAs downregulated in S3_high as compared to S3_low. Interestingly, the level of expression of these selected miRNAs correlated with the level of STAT3 expression/activation in LGL. Among these, three miRNAs, miR-484, miR-501 and miR-1249, have been validated and confirmed in the validation cohort.

Conclusions

These data firstly describe the miRNA pattern in T-LGLL, providing evidence that a series of miRNAs are correlated with relevant key factors in T-LGLL pathogenesis, including STAT3 activation/expression and mutations. Our results suggest the hypothesis that STAT3 could mediate its role through some defined miRNAs.