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4 result(s) for "Yano, Max"
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Rare t(X;14)(q28;q32) translocation reveals link between MTCP1 and chronic lymphocytic leukemia
Rare, recurrent balanced translocations occur in a variety of cancers but are often not functionally interrogated. Balanced translocations with the immunoglobulin heavy chain locus ( IGH ; 14q32) in chronic lymphocytic leukemia (CLL) are infrequent but have led to the discovery of pathogenic genes including CCND1 , BCL2 , and BCL3 . Following identification of a t(X;14)(q28;q32) translocation that placed the mature T cell proliferation 1 gene ( MTCP1 ) adjacent to the immunoglobulin locus in a CLL patient, we hypothesized that this gene may have previously unrecognized importance. Indeed, here we report overexpression of human MTCP1 restricted to the B cell compartment in mice produces a clonal CD5 + /CD19 + leukemia recapitulating the major characteristics of human CLL and demonstrates favorable response to therapeutic intervention with ibrutinib. We reinforce the importance of genetic interrogation of rare, recurrent balanced translocations to identify cancer driving genes via the story of MTCP1 as a contributor to CLL pathogenesis. Some genes that are part of balanced translocations are reported as drivers for tumourigenesis. Here, the authors report a translocation involving MTCP1 in chronic lymphocytic leukemia and show that MTCP1 overexpression leads to the disease in a murine model.
Natural Killer Cells in Chronic Lymphocytic Leukemia: Functional Impairment and Therapeutic Potential
Immunotherapy approaches have advanced rapidly in recent years. While the greatest therapeutic advances so far have been achieved with T cell therapies such as immune checkpoint blockade and CAR-T, recent advances in NK cell therapy have highlighted the therapeutic potential of these cells. Chronic lymphocytic leukemia (CLL), the most prevalent form of leukemia in Western countries, is a very immunosuppressive disease but still shows significant potential as a target of immunotherapy, including NK-based therapies. In addition to their antileukemia potential, NK cells are important immune effectors in the response to infections, which represent a major clinical concern for CLL patients. Here, we review the interactions between NK cells and CLL, describing functional changes and mechanisms of CLL-induced NK suppression, interactions with current therapeutic options, and the potential for therapeutic benefit using NK cell therapies.
Activating Lymphocyte Reactions Against Chronic Lymphocytic Leukemia
Strategies to harness the immune system to treat cancer have been pursued for decades, but only in the past ten years has this dream begun to be realized in earnest with the approval of the first immune checkpoint inhibitor in 2011 and the first cellular immunotherapy in 2017. Since then, immunotherapy has revolutionized the care of multiple diseases by producing durable remissions in many patients who do not respond well to conventional treatments. Here, we describe two efforts to develop novel immunotherapeutic options for chronic lymphocytic leukemia, the most prevalent form of leukemia in the United States. Chronic lymphocytic leukemia (CLL) is a malignancy of mature B cells that mainly affects older adults and causes symptoms including fever, weight loss, lymphadenopathy, and infections. In most patients, this disease progresses slowly or can be managed effectively with current therapeutic options such as targeted inhibitors of BTK, PI3K, or Bcl-2. However, a subset of patients with CLL will experience a more aggressive disease that progresses more rapidly and resists multiple rounds of treatment. For these patients, novel treatment options such as immunotherapy are an area of great need. The first strategy that we employ is using natural killer (NK) cells as a cell therapy. NK cells are lymphoid cells with innate immune functions that include eliminating cancer cells. Stimulated natural killer cells have shown promise as a cellular therapy but their application has been constrained by limited expansion capacity and low cytotoxic activity against CLL cells. We hypothesized that natural killer cells stimulated with feeder cells expressing membrane-bound IL-21 (mbIL-21) would expand and be cytotoxic toward CLL cells. Indeed, both healthy donor-derived and CLL patient-derived NK cells stimulated in this manner expand rapidly and have potent cytotoxic function against allogeneic or autologous CLL cells. Combination with anti-CD20 antibodies significantly enhances NK recognition and killing of CLL targets. Notably, mbIL-21 NK cells have enhanced CLL cytotoxicity when combined with engineered therapeutic antibodies. The mechanism of direct NK cytotoxicity toward CLL cells occurs in part through TRAIL whereas antibody directed cytotoxicity of CLL cells occurs primarily through perforin- and granzyme- mediated killing. We furthermore investigated the effects of current targeted CLL therapies on mbIL-21-expanded NK cells. As any CLL immune therapy would likely be given in combination, we assessed commonly-used treatments and demonstrate that ibrutinib has mixed suppressive and protective effects on expanded NK cells whereas expanded NKs are highly resistant to venetoclax. To assure rigor of our in vitro findings, we demonstrate significant efficacy in vivo in two xenograft mouse models of human CLL that support building upon a regimen of venetoclax and obinutuzumab with mbIL-21- expanded NK cells. Our second strategy of anti-CLL immunotherapy involves targeting the upstream regulation of CTLA4. CTLA4 is a major immune checkpoint limiting T cell reactions and target for cancer immunotherapy. While originally discovered and primarily studied on T cells, its role on other cell types has also been recognized in recent years. Here we describe an unexpected interaction between ibrutinib (a targeted inhibitor of Bruton’s tyrosine kinase, BTK) and CTLA4 expression on malignant chronic lymphocytic leukemia (CLL) cells. While BTK itself does play a role in CTLA4 expression in CLL, we demonstrate that the main suppressive effect on CTLA4 protein expression and trafficking occurs through non-BTK targets of ibrutinib. This suppression is not seen in T cells, indicating a different mechanism of CTLA4 regulation in CLL versus T cells. Collectively, our data point to two novel approaches to CLL immunotherapy. Our work on mbIL-21 expanded NK cells supports development mbIL-21-expanded NKs combined with the CD20 antibody obinutuzumab and venetoclax in the treatment of CLL. A clinical trial to test the safety of this approach for CLL patients is currently being developed. While our work on CTLA4 has a longer road to clinical translation, appreciating this beneficial other-target effect of ibrutinib may contribute to understanding the immune benefits of ibrutinib treatment and lead to therapeutic approaches to improve immune function in CLL patients by suppressing immune checkpoint expression.
Identifying time dependence in network growth
Identifying power-law scaling in real networks - indicative of preferential attachment - has proved controversial. Critics argue that measuring the temporal evolution of a network directly is better than measuring the degree distribution when looking for preferential attachment. However, many of the established methods do not account for any potential time-dependence in the attachment kernels of growing networks, or methods assume that node degree is the key observable determining network evolution. In this paper, we argue that these assumptions may lead to misleading conclusions about the evolution of growing networks. We illustrate this by introducing a simple adaptation of the Barab{á}si-Albert model, the \"k2 model\", where new nodes attach to nodes in the existing network in proportion to the number of nodes one or two steps from the target node. The k2 model results in time dependent degree distributions and attachment kernels, despite initially appearing to grow as linear preferential attachment, and without the need to include explicit time dependence in key network parameters (such as the average out-degree). We show that similar effects are seen in several real world networks where constant network growth rules do not describe their evolution. This implies that measurements of specific degree distributions in real networks are also likely to change over time.