54 research outputs found

    Immunological-based approaches for cancer therapy

    Get PDF
    The immunologic landscape of tumors has been continuously unveiled, providing a new look at the interactions between cancer cells and the immune system. Emerging tumor cells are constantly eliminated by the immune system, but some cells establish a long-term equilibrium phase leading to tumor immunoediting and, eventually, evasion. During this process, tumor cells tend to acquire more mutations. Bearing a high mutation burden leads to a greater number of neoantigens with the potential to initiate an immune response. Although many tumors evoke an immune response, tumor clearance by the immune system does not occur due to a suppressive tumor microenvironment. The mechanisms by which tumors achieve the ability to evade immunologic control vary. Understanding these differences is crucial for the improvement and application of new immune-based therapies. Much effort has been placed in developing in silico algorithms to predict tumor immunogenicity and to characterize the microenvironment via high-throughput sequencing and gene expression techniques. Each sequencing source, transcriptomics, and genomics yields a distinct level of data, helping to elucidate the tumor-based immune responses and guiding the fine-tuning of current and upcoming immune-based therapies. In this review, we explore some of the immunological concepts behind the new immunotherapies and the bioinformatic tools to study the immunological aspects of tumors, focusing on neoantigen determination and microenvironment deconvolution. We further discuss the immune-based therapies already in clinical use, those underway for future clinical application, the next steps in immunotherapy, and how the characterization of the tumor immune contexture can impact therapies aiming to promote or unleash immune-based tumor elimination

    CD40 activation of BCP-ALL cells generates IL-10-producing, IL-12-defective APCs that induce allogeneic T-cell anergy

    Get PDF
    The use of leukemia cells as antigenpresenting cells (APCs) in immunotherapy is critically dependent on their capacity to initiate and sustain an antitumor-specific immune response. Previous studies suggested that pediatric B-cell precursor acute lymphoblastic leukemia (BCP-ALL) cells could be manipulated in vitro through the CD40-CD40L pathway to increase their immunostimulatory capacity. We extended the APC characterization of CD40L-activated BCP-ALL for their potential use in immunotherapy in a series of 19 patients. Engaging CD40 induced the up-regulation of CCR7 in 7 of 11 patients and then the migration to CCL19 in 2 of 5 patients. As accessory cells, CD40Lactivated BCP-ALL induced a strong proliferation response of naive T lymphocytes. Leukemia cells, however, were unable to sustain proliferation over time, and T cells eventually became anergic. After CD40-activation, BCP-ALL cells released substantial amounts of interleukin-10 (IL-10) but were unable to produce bioactive IL-12 or to polarize TH1 effectors. Interestingly, adding exogenous IL-12 induced the generation of interferon- (IFN- )–secreting TH1 effectors and reverted the anergic profile in a secondary response. Therefore, engaging CD40 on BCP-ALL cells is insufficient for the acquisition of full functional properties of immunostimulatory APCs. These results suggest caution against the potential use of CD40L-activated BCP-ALL cells as agents for immunotherapy unless additional stimuli, such as IL-12, are provided.Fil: D'Amico, Giovanna. Università Milano Bicocca; ItaliaFil: Vulcano, Marisa. Universidad de Buenos Aires. Facultad de Medicina; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas. Oficina de Coordinación Administrativa Houssay; ArgentinaFil: Bugarin, Cristina. Università Milano Bicocca; ItaliaFil: Bianchi, Giancarlo. Università Milano Bicocca; ItaliaFil: Pirovano, Gisella. Università Milano Bicocca; ItaliaFil: Bonamino, Martin. Università Milano Bicocca; ItaliaFil: Marin, Virna. Università Milano Bicocca; ItaliaFil: Allavena, Paola. Università Milano Bicocca; ItaliaFil: Biagi, Ettore. Università Milano Bicocca; ItaliaFil: Biondi, Andrea. Università Milano Bicocca; Itali

    Genetic instability in the tumor microenvironment: a new look at an old neighbor

    Get PDF

    Immunological-based approaches for cancer therapy

    Get PDF
    The immunologic landscape of tumors has been continuously unveiled, providing a new look at the interactions between cancer cells and the immune system. Emerging tumor cells are constantly eliminated by the immune system, but some cells establish a long-term equilibrium phase leading to tumor immunoediting and, eventually, evasion. During this process, tumor cells tend to acquire more mutations. Bearing a high mutation burden leads to a greater number of neoantigens with the potential to initiate an immune response. Although many tumors evoke an immune response, tumor clearance by the immune system does not occur due to a suppressive tumor microenvironment. The mechanisms by which tumors achieve the ability to evade immunologic control vary. Understanding these differences is crucial for the improvement and application of new immune-based therapies. Much effort has been placed in developing in silico algorithms to predict tumor immunogenicity and to characterize the microenvironment via high-throughput sequencing and gene expression techniques. Each sequencing source, transcriptomics, and genomics yields a distinct level of data, helping to elucidate the tumor-based immune responses and guiding the fine-tuning of current and upcoming immune-based therapies. In this review, we explore some of the immunological concepts behind the new immunotherapies and the bioinformatic tools to study the immunological aspects of tumors, focusing on neoantigen determination and microenvironment deconvolution. We further discuss the immune-based therapies already in clinical use, those underway for future clinical application, the next steps in immunotherapy, and how the characterization of the tumor immune contexture can impact therapies aiming to promote or unleash immune-based tumor elimination

    An Efficient Low Cost Method for Gene Transfer to T Lymphocytes

    Get PDF
    <div><p></p><p>Gene transfer to T lymphocytes has historically relied on retro and lentivirus, but recently transposon-based gene transfer is rising as a simpler and straight forward approach to achieve stable transgene expression. Transfer of expression cassettes to T lymphocytes remains challenging, being based mainly on commercial kits.</p> <p>Aims</p><p>We herein report a convenient and affordable method based on <i>in house</i> made buffers, generic cuvettes and utilization of the widely available Lonza nucleofector II device to promote efficient gene transfer to T lymphocytes.</p> <p>Results</p><p>This approach renders high transgene expression levels in primary human T lymphocytes (mean 45%, 41–59%), the hard to transfect murine T cells (mean 38%, 36–42% for C57/BL6 strain) and human Jurkat T cell line. Cell viability levels after electroporation allowed further manipulations such as <i>in vitro</i> expansion and Chimeric Antigen Receptor (CAR) mediated gain of function for target cell lysis.</p> <p>Conclusions</p><p>We describe here an efficient general protocol for electroporation based modification of T lymphocytes. By opening access to this protocol, we expect that efficient gene transfer to T lymphocytes, for transient or stable expression, may be achieved by an increased number of laboratories at lower and affordable costs.</p> </div

    Genetic Alterations in Essential Thrombocythemia Progression to Acute Myeloid Leukemia: A Case Series and Review of the Literature

    No full text
    The genetic events associated with transformation of myeloproliferative neoplasms (MPNs) to secondary acute myeloid leukemia (sAML), particularly in the subgroup of essential thrombocythemia (ET) patients, remain incompletely understood. Deep studies using high-throughput methods might lead to a better understanding of genetic landscape of ET patients who transformed to sAML. We performed array-based comparative genomic hybridization (aCGH) and whole exome sequencing (WES) to analyze paired samples from ET and sAML phases. We investigated five patients with previous history of MPN, which four had initial diagnosis of ET (one case harboring JAK2 p.Val617Phe and the remaining three CALR type II p.Lys385fs*47), and one was diagnosed with MPN/myelodysplastic syndrome with thrombocytosis (SF3B1 p.Lys700Glu). All were homogeneously treated with hydroxyurea, but subsequently transformed to sAML (mean time of 6 years/median of 4 years to transformation). Two of them have chromosomal abnormalities, and both acquire 2p gain and 5q deletion at sAML stage. The molecular mechanisms associated with leukemic progression in MPN patients are not clear. Our WES data showed TP53 alterations recurrently observed as mutations (missense and frameshift) and monoallelic loss. On the other hand, aCGH showed novel chromosome abnormalities (+2p and del5q) potentially associated with disease progression. The results reported here add valuable information to the still fragmented molecular basis of ET to sAML evolution. Further studies are necessary to identify minimal deleted/amplified region and genes relevant to sAML transformation

    Electroporation of the Jurkat T cell line.

    No full text
    <p>(<b>A</b>) Jurkat cells were electroporated with pT2-GFP in the presence of each of the 7 different buffers. Viability and GFP expression were evaluated by flow cytometry after 24 h. Cell viability is expressed as % of the control mock electroporated condition (100%). Electroporation scores were determined as described in <a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0060298#s2" target="_blank">materials and methods</a>. Statistical analysis was performed using One Way ANOVA and Tukey post test (* = P<0.05). (<b>B</b>) Jurkat cells were electroporated with buffer 3P. Cell viability and GFP expression were observed until day 20. Values in this figure are the average of two separate experiments in triplicate and are expressed as mean±SEM. Data were analyzed by unpaired Student t test; p<0.05 (*);p<0.01 (**).</p
    corecore