JAK blockade and HTLV

JAK2 V617F Mutation in Adult T Cell Leukemia-Lymphoma

Adult T cell Leukemia/lymphoma (ATL) is a mature T-cell neoplasm that has strong association with the human T-lymphotropic virus type 1 (HTLV-I) infection. This infection is endemic in our region (north eastern Iran). It has been highlighted that Janus Kinase family proteins and specially JAK2 mutations have a pivotal role in the development of many types of hematological malignancies and in particular myeloproliferative neoplasms. So far, the underlying molecular mechanisms leading to the ATL are not well understood. Therefore, in this study it was hypothesized that JAK2 (V617F) mutation may be present in samples from patients with ATL. This case control study was performed in north-eastern Iran. Using polymerase chain reaction, JAK2 (V617F) mutation was performed in 20 DNA samples from ATL patients and 20 HTLV-1 asymptomatic carriers (control group). The results of ATL subjects and the control group were compared by using SPSS software. In the case group 13 (65 %) and 7 patients (35 %) were male and female respectively, with the age range between 40 and 80 years. Only one patients has JAK2 mutation and this mutation was absent in 95 % of ATL patients as well as the HTLV-1 asymptomatic carriers. The results of our study demonstrated that JAK2 V617F mutation is not a common phenomenon in ATL. However, further studies are required to investigate the possible dysregulation of JAK signaling in ATL.

Inducible nitric oxide synthase mediates DNA double strand breaks in Human T-Cell Leukemia Virus Type 1-induced leukemia/lymphoma

Background

Adult T-cell leukemia/lymphoma (ATLL) is an aggressive and fatal malignancy of CD4⁺ T-lymphocytes infected by the Human T-Cell Virus Type 1 (HTLV-1). The molecular mechanisms of transformation in ATLL have not been fully elucidated. However, genomic instability and cumulative DNA damage during the long period of latency is believed to be essential for HTLV-1 induced leukemogenesis. In addition, constitutive activation of the NF-κB pathway was found to be a critical determinant for transformation. Whether a connection exists between NF-κB activation and accumulation of DNA damage is not clear. We recently found that the HTLV-1 viral oncoprotein, Tax, the activator of the NF-κB pathway, induces DNA double strand breaks (DSBs).

Results

Here, we investigated whether any of the NF-κB target genes are critical in inducing DSBs. Of note, we found that inducible nitric oxide synthase (iNOS) that catalyzes the production of nitric oxide (NO) in macrophages, neutrophils and T-cells is over expressed in HTLV-1 infected and Tax-expressing cells. Interestingly, we show that in HTLV-1 infected cells, iNOS expression is Tax-dependent and specifically requires the activation of the classical NF-κB and JAK/STAT pathways. A dramatic reduction of DSBs was observed when NO production was inhibited, indicating that Tax induces DSBs through the activation of NO synthesis.

Conclusions

Determination of the impact of NO on HTLV-1-induced leukemogenesis opens a new area for treatment or prevention of ATLL and perhaps other cancers in which NO is produced.

A novel one-class SVM based negative data sampling method for reconstructing proteome-wide HTLV-human protein interaction networks

Protein-protein interaction (PPI) prediction is generally treated as a problem of binary classification wherein negative data sampling is still an open problem to be addressed. The commonly used random sampling is prone to yield less representative negative data with considerable false negatives. Meanwhile rational constraints are seldom exerted on model selection to reduce the risk of false positive predictions for most of the existing computational methods. In this work, we propose a novel negative data sampling method based on one-class SVM (support vector machine, SVM) to predict proteome-wide protein interactions between HTLV retrovirus and Homo sapiens, wherein one-class SVM is used to choose reliable and representative negative data, and two-class SVM is used to yield proteome-wide outcomes as predictive feedback for rational model selection. Computational results suggest that one-class SVM is more suited to be used as negative data sampling method than two-class PPI predictor, and the predictive feedback constrained model selection helps to yield a rational predictive model that reduces the risk of false positive predictions. Some predictions have been validated by the recent literature. Lastly, gene ontology based clustering of the predicted PPI networks is conducted to provide valuable cues for the pathogenesis of HTLV retrovirus.

Dysregulation of JAK-STAT pathway in hematological malignancies and JAK inhibitors for clinical application

JAK-STAT (Janus associated kinase-signal transducer and activator of transcription) pathway plays a critical role in transduction of extracellular signals from cytokines and growth factors involved in hematopoiesis, immune regulation, fertility, lactation, growth and embryogenesis. JAK family contains four cytoplasmic tyrosine kinases, JAK1-3 and Tyk2. Seven STAT proteins have been identified in human cells, STAT1-6, including STAT5a and STAT5b. Negative regulators of JAK-STAT pathways include tyrosine phosphatases (SHP1 and 2, CD45), protein inhibitors of activated STATs (PIAS), suppressors of cytokine signaling (SOCS) proteins, and cytokine-inducible SH2-containing protein (CIS). Dysregulation of JAK-STAT pathway have been found to be key events in a variety of hematological malignancies. JAK inhibitors are among the first successful agents reaching clinical application. Ruxolitinib (Jakafi), a non-selective inhibitor of JAK1 & 2, has been approved by FDA for patients with intermediate to high risk primary or secondary myelofibrosis. This review will also summarize early data on selective JAK inhibitors, including SAR302503 (TG101348), lestaurtinib (CEP701), CYT387, SB1518 (pacritinib), LY2784544, XL019, BMS-911543, NS-018, and AZD1480.