ALBERT

Description: Stat6 transcription factor is a critical mediator of IL-4-specific gene responses. Tyrosine phosphorylation is required for nuclear localization and DNA binding of Stat6. The authors investigated whether Stat6-dependent transcriptional responses are regulated through IL-4-induced serine/threonine phosphorylation. In Ramos B cells, the serine/threonine kinase inhibitor H7 inhibited IL-4-induced expression of CD23. Treatment with H7 did not affect IL-4R-mediated immediate signaling events such as tyrosine phosphorylation of Jak1, Jak3, insulin receptor substrate (IRS)-1 and IRS-2, or tyrosine phosphorylation and DNA binding of Stat6. To analyze whether the H7-sensitive pathway was regulating Stat6-activated transcription, we used reporter constructs containing different IL-4 responsive elements. H7 abrogated Stat6-, as well as Stat5-, mediated reporter gene activation and partially reduced C/EBP-dependent reporter activity. By contrast, IL-4-induced transcription was not affected by wortmannin, an inhibitor of the phosphatidyl-inositol 3′-kinase pathway. Phospho-amino acid analysis and tryptic phosphopeptide maps revealed that IL-4 induced phosphorylation of Stat6 on serine and tyrosine residues in Ramos cells and in 32D cells lacking endogenous IRS proteins. However, H7 treatment did not inhibit the phosphorylation of Stat6. Instead, H7 inhibited the IL-4-induced phosphorylation of RNA polymerase II. These results indicate that Stat6-induced transcription is dependent on phosphorylation events mediated by H7-sensitive kinase(s) but that it also involves serine phosphorylation of Stat6 by an H7-insensitive kinase independent of the IRS pathway.

Description: Key Points Germline activating STAT3 mutations were detected in 3 patients with autoimmunity, hypogammaglobulinemia, and mycobacterial disease. T-cell lymphoproliferation, deficiency of regulatory and helper 17 T cells, natural killer cells, dendritic cells, and eosinophils were common.

Description: There is a Blood Commentary on this article in this issue.

Description: Background In most solid tumors, CD8+ cytotoxic T-cells and type 1 T-helper cells are associated with a positive prognosis, but a strong immunosuppressive microenvironment may hamper their effectiveness. This notion has contributed to the development of new immune-activating therapies, such as immune checkpoint inhibitors. Although having demonstrated long-term remissions in many different solid tumor types, immune checkpoint inhibitors have not been evaluated comprehensively in hematological malignancies. In this study, we aimed to characterize the cellular and molecular immunological profiles of chronic myeloid leukemia (CML) patients' bone marrow (BM) samples. Methods BM biopsies were taken at the time of diagnosis from chronic phase CML patients (n=57) treated in the Helsinki University Hospital during years 2005-2015. We used non-leukemic (NL) BM biopsies (n=10) as controls. Using hematopathologic expertise, we constructed tissue microarray (TMA) blocks from duplicate BM spots characterized with high leukemic cell infiltration. We stained TMA slides using multiplexed immunohistochemistry (IHC) combining fluorescent and chromogenic staining allowing detection of up to six markers and nuclei simultaneously. Marker panels included T and B-lymphoid (CD3, CD4, CD8, CD20), myeloid dendritic (CD11c, BDCA-1, BDCA-3), macrophage (CD68, pSTAT1, c-MAF), natural killer cell (CD3 and CD56) and leukemia cell (CD34) markers. In addition, we examined immune checkpoint molecules (PD1, CTLA4, OX40, LAG3, TIM3) and their ligands in leukemic cells (HLA-G, PD-L1, PD-L2, HLA-ABC), as well as activation markers (CD25, CD27, CD57, Granzyme B and CD45RO). We analyzed leukemia patients' immune checkpoint expression profiles quantitatively using the image analysis software Cell Profiler and cell analysis software FlowJo and compared results with NL BMs' immune cell profiles. Results The proportion of CD3+ T cells of all cells was significantly higher in CML BM vs. NL BM (median 6.0% [interquartile range (IQR) 3.6-10.7] vs. 2.1% [IQR 1.5-4.5], p=0.001). There was no significant difference in CD8+ cytotoxic T cell levels, but CD4+ helper T cells were 8-fold more abundant in CML as compared to non-leukemic BM (p

Description: Background Natural killer (NK) cell malignancies are rare lymphoid neoplasms characterized by aggressive clinical behavior and poor treatment outcomes. Clinically they are classified as extranodal NK/T-cell lymphoma, nasal type (NKTCL) and aggressive NK cell leukemia (ANKL). Both subtypes are almost invariably associated with Epstein-Barr virus (EBV). Recently, genomic studies in NKTCL have identified recurrent somatic mutations in JAK-STAT pathway molecules STAT3 and STAT5b as well as in the RNA helicase gene DDX3X in addition to previously detected chromosomal aberrations. Here, we identified somatic mutations in 4 cases of ANKL in order to understand whether these entities share common alterations at the molecular level. To further establish common patterns of deregulated oncogenic signaling pathways operating in malignant NK cells, we performed drug sensitivity profiling using NK cell lines representing ANKL, NKTCL and other malignant NK cell proliferations. We aimed to identify sensitivities to agents that selectively target components of pathways required for survival of malignant NK cells in an unbiased manner. Methods Exome sequencing was performed on peripheral blood or bone marrow of ANKL patients using the NK cell negative fraction or other healthy tissue as control. Profiling of drug responses was performed with a high-throughput drug sensitivity and resistance testing (DSRT) platform comprising 461 approved and investigational oncology drugs. The NK cell lines KAI3, KHYG-1, NKL, NK-YS, NK-92, SNK-6 and YT and IL-2-stimulated and resting NK cells from healthy donors were used as sample material. All drugs were tested on a 384-well format in 5 different concentrations over a 10,000-fold concentration range for 72 h and cell viability was measured. A Drug Sensitivity Score (DSS) was calculated for each drug using normalized dose response curve values. Results The ANKL patients displayed mutations in genes reported as recurrently mutated in NKTCL, such as FAS, TP53, NRAS, STAT3 and DDX3X. Additionally, novel alterations in genes previously implicated in the pathogenesis of NKTCL were detected. These included an inactivating mutation in INPP5D (SHIP), a negative regulator of the PI3K/mTOR pathway and a missense mutation in PTPRK, a negative regulator of STAT3 activation. Interestingly, the total number of nonsilent somatic mutations in 3 out of 4 ANKL patients (97, 82 and 45) was remarkably high compared to other hematological malignancies analyzed in our variant calling pipeline. Analysis of drug sensitivities in NK cell lines showed a close correlation between all cell lines and a markedly higher correlation with those of IL-2 stimulated than resting healthy NK cells, suggesting that malignant NK cells may share a common drug response pattern. Furthermore, in an unsupervised hierarchical clustering the NK cell lines formed a distinct group from other leukemia cell lines tested (Fig. A). Among pathway-selective compounds (namely, kinase inhibitors and rapalogs), the drugs most selective for malignant NK cells fell into two major categories: PI3K/mTOR inhibitors (e.g. temsirolimus, buparlisib) and inhibitors of aurora and polo-like kinases such as rigosertib and GSK-461364 (Fig. B). JAK inhibitors (e.g. ruxolitinib, gandotinib) and CDK inhibitors (e.g. dinaciclib) showed strong efficacy in both malignant NK cells and IL-2 activated healthy NK cells. Conclusions Our exome sequencing results suggest that candidate driver alterations affecting similar signaling pathways underlie the pathogenesis of ANKL as has been reported in NKTCL. Drug sensitivity profiling highlights the PI3K/mTOR pathway as a potential major driver of malignant NK cell proliferation, whereas JAK-STAT signaling appears to be essential in both healthy and malignant NK cells. Components of these pathways harbored mutations in our small cohort of ANKL patients and have been shown to be deregulated by mutations or other mechanisms in previous studies, underlining their importance as putative drivers. The systematic large-scale characterization of drug responses also identified these pathways as potential targets for novel therapy strategies in NK cell malignancies. Figure 1. (A) Unsupervised hierarchical clustering based on drug sensitivity scores (DSS) of NK, AML, CML and T-ALL cell lines. (B) Scatter plot comparing DSS of malignant NK cell lines (average) and healthy IL-2 stimulated NK cells. Figure 1. (A) Unsupervised hierarchical clustering based on drug sensitivity scores (DSS) of NK, AML, CML and T-ALL cell lines. (B) Scatter plot comparing DSS of malignant NK cell lines (average) and healthy IL-2 stimulated NK cells. Disclosures Mustjoki: Novartis: Honoraria, Research Funding; Bristol-Myers Squibb: Honoraria, Research Funding; Pfizer: Honoraria, Research Funding.

Description: INTRODUCTION Natural killer (NK) cell malignancies are rare aggressive neoplasms that are classified by the WHO as extranodal NK/T-cell lymphoma, nasal type (NKTCL) and aggressive NK-cell leukemia (ANKL). Recently, genome and exome level studies in NKTCL have shed light on the mutational spectrum of the disease. However, somatic mutations in ANKL have not been characterized. Here, we identified somatic mutations in 14 cases of ANKL to further clarify the genetic landscape underlying malignant NK cell proliferation. We compared the discovered variants to those detected in NKTCL to understand whether the two diseases harbor common molecular alterations. Moreover, we used high-throughput drug screening and RNA sequencing on NK cell lines derived from ANKL, NKTCL and other malignant NK cell proliferations to identify therapeutically actionable drivers of malignant NK cell growth. METHODS We performed whole-exome sequencing on genomic DNA extracted from peripheral blood or bone marrow samples of 14 ANKL patients. To compare the mutational profiles in ANKL and NTKCL, we re-analyzed the published whole-exome NKTCL data from Jiang et al. (Nat Genet 2015) using our somatic variant calling pipeline. For profiling of drug responses, we used a high-throughput drug sensitivity and resistance testing (DSRT) platform comprising 461 approved and investigational oncology drugs to screen the ANKL cell lines IMC-1, KHYG-1 and NK-92, NKTCL cell lines NK-YS and SNK-6 as well as DERL-7, KAI3, NKL, YT and IL-2-stimulated NK cells from healthy donors. All drugs were tested in 384-well format in 5 concentrations over a 10,000-fold concentration range for 72 h, cell viability was measured and normalized dose response curve values were used to calculate a drug sensitivity score (DSS) for each drug. Finally, we performed amplicon sequencing of known cancer driver genes and RNA sequencing on the cell lines and healthy NK cells to identify driver mutations and integrate gene expression profiles with drug sensitivity patterns. RESULTS We identified recurrent somatic activating mutations in STAT3 in 21% (3 of 14) of ANKL patients. Other mutated genes included RAS-MAPK pathway molecules (BRAF, NRAS, KRAS), protein phosphatases regulating JAK-STAT and PI3K-AKT-mTOR pathways (PTPRT, PTPRK, INPP5D) as well as several epigenetic modifiers (TET2, ARID2, KDM2B, SETD7, SETD2) and the tumor suppressor TP53. Interestingly, we detected mutations in genes recurrently mutated in NKTCL, such as the RNA helicase DDX3X and the cell surface receptor FAS. Re-analysis of the published NKTCL data revealed a high frequency of missense mutations in receptor type and non-receptor type protein phosphatases (e.g. PTPRC, PTPRR, PTPRT, PTPN1, PTPN2, PTPN3), many of which have established roles as negative regulators of JAK-STAT signaling. These findings potentially expand the subset of NK cell tumors where the JAK-STAT pathway is somatically activated and implicate deregulated JAK-STAT signaling as a major driver in these diseases. The malignant NK cell lines used in drug sensitivity profiling frequently harbored mutations in same genes and pathways, including STAT3 (N=3), STAT5B (N=1), DDX3X (N=2), KRAS (N=1), FAS (N=2) and several epigenetic modifiers, thus validating these cell lines as relevant disease models. The drug sensitivities in NK cell lines showed a high correlation and the cell lines formed a distinct group from other lymphoid and myeloid leukemia cell lines in unsupervised hierarchical clustering, suggesting an NK-cell specific drug response pattern. The most effective targeted drugs across all NK cell lines included HDAC inhibitors, inhibitors of Aurora and Polo-like kinases, JAK inhibitors, HSP inhibitors and CDK inhibitors as well as the Bcl-2 inhibitor navitoclax. Compared to other leukemia and lymphoma cell lines, JAK inhibitors, navitoclax and methotrexate emerged as the most NK-cell specific compounds. CONCLUSIONS Our genetic data demonstrate extensive heterogeneity in the mutational spectrum of ANKL and implicate JAK-STAT and RAS-MAPK signaling as well as disruption of epigenetic modifiers in the disease pathogenesis. Integrated drug sensitivity and gene expression profiling corroborates the JAK-STAT pathway as a major therapeutically actionable driver of malignant NK cell proliferation and identifies other potential novel targeted therapy options such as Bcl-2 inhibition in NK cell malignancies. Disclosures Suzumiya: Chugai: Honoraria, Research Funding; Toyama Chemical: Research Funding; Kyowa Hakko kirin: Research Funding; Astellas: Research Funding; Eisai: Honoraria, Research Funding; Takeda: Honoraria. Ohshima:Chugai: Research Funding, Speakers Bureau; Kyowa Kirin: Research Funding, Speakers Bureau. Mustjoki:Pfizer: Honoraria, Research Funding; Ariad: Research Funding; Novartis: Honoraria, Research Funding; Bristol-Myers Squibb: Honoraria, Research Funding.

Description: Differentiation of macrophages from myeloid progenitor cells depends on a discrete balance between cell growth, survival, and differentiation signals. Interleukin-3 (IL-3) supports the growth and survival of myeloid progenitor cells through the activation of Jak2 tyrosine kinase, and macrophage differentiation has been shown to be regulated by protein kinase C (PKC). During terminal differentiation of macrophages, the cells lose their mitogenic response to IL-3 and undergo growth arrest, but the underlying signaling mechanisms have remained elusive. Here we show that in IL-3–dependent 32D myeloid progenitor cells, the differentiation-inducing PKC isoforms PKC- and PKC-δ specifically caused rapid inhibition of IL-3–induced tyrosine phosphorylation. The target for this inhibition was Jak2, and the activation of PKC by 12-O-tetradecanoyl-phorbol-13-acetate treatment also abrogated IL-3–induced tyrosine phosphorylation of Jak2 in Ba/F3 cells. The mechanism of this regulation was investigated in 32D and COS7 cells, and the inhibition of Jak2 required catalytic activity of PKC-δ and involved the phosphorylation of Jak2 on serine and threonine residues by the associated PKC-δ. Furthermore, PKC-δ inhibited the in vitro catalytic activity of Jak2, indicating that Jak2 was a direct target for PKC-δ. In 32D cells, the inhibition of Jak2 either by PKC-δ, tyrosine kinase inhibitor AG490, or IL-3 deprivation caused a similar growth arrest. Reversal of PKC-δ–mediated inhibition by the overexpression of Jak2 promoted apoptosis in differentiating 32D cells. These results demonstrate a PKC-mediated negative regulatory mechanism of cytokine signaling and Jak2, and they suggest that it serves to integrate growth-promoting and differentiation signals during macrophage differentiation.

Description: JAB/suppressor of cytokine signaling 1 (SOCS1) STAT-induced STAT inhibitor–1 (SSI-1) (JAB/SOCS1/SSI-1) is an SH2-domain–containing protein that is induced by and negatively regulates signaling by a number of cytokines including interleukin-4 (IL-4), IL-6, interferon (IFN)-γ, prolactin, growth hormone, and erythropoietin. The role of JAB/SOCS1/SSI-1 in IL-2 signaling has been analyzed. JAB/SOCS1/SSI-1 is strongly induced by IL-2 in peripheral blood T cells, and JAB/SOCS1/SSI-1 overexpression strongly inhibits IL-2–induced signal transducer and activator of transcription–5 (Stat5) phosphorylation and transcriptional activity. In cotransfection experiments, JAB/SOCS1/SSI-1 associates with both Jak1 and Jak3; however, JAB/SOCS1/SSI-1 had a greater effect on Jak1 tyrosine phosphorylation and kinase activity. JAB/SOCS1/SSI-1 also interacts with IL-2Rβ, and this interaction requires the A region (residues 313-382) of IL-2Rβ. However, this interaction was not essential for the inhibitory action of JAB. Thus, JAB/SOCS1/SSI-1 is an IL-2–induced inhibitor of IL-2 signaling that functions by inhibiting Jak kinase activity. This suggests an important role for JAB/SOCS1/SSI-1 in regulating T-cell responses.