IRX-2, a Novel Immunotherapeutic, Enhances Functions of Human Dendritic Cells

Background: In a recent phase II clinical trial for HNSCC patients, IRX-2, a cell-derived biologic, promoted T-cell infiltration into the tumor and prolonged overall survival. Mechanisms responsible for these IRX-2-mediated effects are unknown. We hypothesized that IRX-2 enhanced tumor antigen-(TA)-specific immunity by up-regulating functions of dendritic cells (DC). Methodology/Principal Findings: Monocyte-derived DC obtained from 18 HNSCC patients and 12 healthy donors were matured using IRX-2 or a mix of TNF-α, IL-1β and IL-6 ("conv. mix"). Multicolor flow cytometry was used to study the DC phenotype and antigen processing machinery (APM) component expression. ELISPOT and cytotoxicity assays were used to evaluate tumor-reactive cytotoxic T lymphocytes (CTL). IL-12p70 and IL-10 production by DC was measured by Luminex® and DC migration toward CCL21 was tested in transwell migration assays. IRX-2-matured DC functions were compared with those of conv. mix-matured DC. IRX-2-matured DC expressed higher levels (p<0.05) of CD11c, CD40, CCR7 as well as LMP2, TAP1, TAP2 and tapasin than conv. mix-matured DC. IRX-2-matured DC migrated significantly better towards CCL21, produced more IL-12p70 and had a higher IL12p70/IL-10 ratio than conv. mix-matured DC (p<0.05 for all). IRX-2-matured DC carried a higher density of tumor antigen-derived peptides, and CTL primed with these DC mediated higher cytotoxicity against tumor targets (p<0.05) compared to the conv. mix-matured DC. Conclusion: Excellent ability of IRX-2 to induce ex vivo DC maturation in HNSCC patients explains, in part, its clinical benefits and emphasizes its utility in ex vivo maturation of DC generated for therapy. © 2013 Schilling et al

What do we have to know about PD-L1 expression in prostate cancer? A systematic literature review. part 4: Experimental treatments in pre-clinical studies (cell lines and mouse models)

In prostate cancer (PC), the PD-1/PD-L1 axis regulates various signaling pathways and it is influenced by extracellular factors. Pre-clinical experimental studies investigating the effects of various treatments (alone or combined) may discover how to overcome the immunotherapyresistance in PC-patients. We performed a systematic literature review (PRISMA guidelines) to delineate the landscape of pre-clinical studies (including cell lines and mouse models) that tested treatments with effects on PD-L1 signaling in PC. NF-kB, MEK, JAK, or STAT inhibitors on human/mouse, primary/metastatic PC-cell lines variably down-modulated PD-L1-expression, reducing chemoresistance and tumor cell migration. If PC-cells were co-cultured with NK, CD8+ Tcells or CAR-T cells, the immune cell cytotoxicity increased when PD-L1 was downregulated (opposite effects for PD-L1 upregulation). In mouse models, radiotherapy, CDK4/6-inhibitors, and RB deletion induced PD-L1-upregulation, causing PC-immune-evasion. Epigenetic drugs may reduce PD-L1 expression. In some PC experimental models, blocking only the PD-1/PD-L1 pathway had limited efficacy in reducing the tumor growth. Anti-tumor effects could be increased by combining the PD-1/PD-L1 blockade with other approaches (inhibitors of tyrosine kinase, PI3K/mTOR or JAK/STAT3 pathways, p300/CBP; anti-RANKL and/or anti-CTLA-4 antibodies; cytokines; nitroxoline; DNA/cell vaccines; radiotherapy/Radium-223)

PhyloSim - Monte Carlo simulation of sequence evolution in the R statistical computing environment

<p>Abstract</p> <p>Background</p> <p>The Monte Carlo simulation of sequence evolution is routinely used to assess the performance of phylogenetic inference methods and sequence alignment algorithms. Progress in the field of molecular evolution fuels the need for more realistic and hence more complex simulations, adapted to particular situations, yet current software makes unreasonable assumptions such as homogeneous substitution dynamics or a uniform distribution of indels across the simulated sequences. This calls for an extensible simulation framework written in a high-level functional language, offering new functionality and making it easy to incorporate further complexity.</p> <p>Results</p> <p><monospace>PhyloSim</monospace> is an extensible framework for the Monte Carlo simulation of sequence evolution, written in R, using the Gillespie algorithm to integrate the actions of many concurrent processes such as substitutions, insertions and deletions. Uniquely among sequence simulation tools, <monospace>PhyloSim</monospace> can simulate arbitrarily complex patterns of rate variation and multiple indel processes, and allows for the incorporation of selective constraints on indel events. User-defined complex patterns of mutation and selection can be easily integrated into simulations, allowing <monospace>PhyloSim</monospace> to be adapted to specific needs.</p> <p>Conclusions</p> <p>Close integration with <monospace>R</monospace> and the wide range of features implemented offer unmatched flexibility, making it possible to simulate sequence evolution under a wide range of realistic settings. We believe that <monospace>PhyloSim</monospace> will be useful to future studies involving simulated alignments.</p

Low Complexity Regularization of Linear Inverse Problems

Inverse problems and regularization theory is a central theme in contemporary signal processing, where the goal is to reconstruct an unknown signal from partial indirect, and possibly noisy, measurements of it. A now standard method for recovering the unknown signal is to solve a convex optimization problem that enforces some prior knowledge about its structure. This has proved efficient in many problems routinely encountered in imaging sciences, statistics and machine learning. This chapter delivers a review of recent advances in the field where the regularization prior promotes solutions conforming to some notion of simplicity/low-complexity. These priors encompass as popular examples sparsity and group sparsity (to capture the compressibility of natural signals and images), total variation and analysis sparsity (to promote piecewise regularity), and low-rank (as natural extension of sparsity to matrix-valued data). Our aim is to provide a unified treatment of all these regularizations under a single umbrella, namely the theory of partial smoothness. This framework is very general and accommodates all low-complexity regularizers just mentioned, as well as many others. Partial smoothness turns out to be the canonical way to encode low-dimensional models that can be linear spaces or more general smooth manifolds. This review is intended to serve as a one stop shop toward the understanding of the theoretical properties of the so-regularized solutions. It covers a large spectrum including: (i) recovery guarantees and stability to noise, both in terms of $\ell^2$-stability and model (manifold) identification; (ii) sensitivity analysis to perturbations of the parameters involved (in particular the observations), with applications to unbiased risk estimation ; (iii) convergence properties of the forward-backward proximal splitting scheme, that is particularly well suited to solve the corresponding large-scale regularized optimization problem

What do we have to know about PD-L1 expression in prostate cancer? A systematic literature review. Part 3: PD-L1, intracellular signaling pathways and tumor microenvironment

The tumor microenvironment (TME) includes immune (T, B, NK, dendritic), stromal, mesenchymal, endothelial, adipocytic cells, extracellular matrix, and cytokines/chemokines/soluble factors regulating various intracellular signaling pathways (ISP) in tumor cells. TME influences the survival/progression of prostate cancer (PC), enabling tumor cell immune-evasion also through the activation of the PD-1/PD-L1 axis. We have performed a systematic literature review according to the PRISMA guidelines, to investigate how the PD-1/PD-L1 pathway is influenced by TME and ISPs. Tumor immune-escape mechanisms include suppression/exhaustion of tumor infiltrating cytotoxic T lymphocytes, inhibition of tumor suppressive NK cells, increase in immune-suppressive immune cells (regulatory T, M2 macrophagic, myeloid-derived suppressor, dendritic, stromal, and adipocytic cells). IFN-γ (the most investigated factor), TGF-β, TNF-α, IL-6, IL-17, IL-15, IL-27, complement factor C5a, and other soluble molecules secreted by TME components (and sometimes increased in patients’ serum), as well as and hypoxia, influenced the regulation of PD-L1. Experimental studies using human and mouse PC cell lines (derived from either androgen-sensitive or androgen-resistant tumors) revealed that the intracellular ERK/MEK, Akt-mTOR, NF-kB, WNT and JAK/STAT pathways were involved in PD-L1 upregulation in PC. Blocking the PD-1/PD-L1 signaling by using immunotherapy drugs can prevent tumor immune-escape, increasing the anti-tumor activity of immune cells

What do we have to know about pd-l1 expression in prostate cancer? A systematic literature review. part 1: Focus on immunohistochemical results with discussion of pre-analytical and interpretation variables

Immunotherapy targeting the PD-1–PD-L1 axis yielded good results in treating different immunologically ‘‘hot’’ tumors. A phase II study revealed good therapeutic activity of pembroli-zumab in selected prostatic carcinoma (PC)-patients. We performed a systematic literature review (PRISMA guidelines), which analyzes the immunohistochemical expression of PD-L1 in human PC samples and highlights the pre-analytical and interpretation variables. Interestingly, 29% acinar PCs, 7% ductal PCs, and 46% neuroendocrine carcinomas/tumors were PD-L1+ on immunohisto-chemistry. Different scoring methods or cut-off criteria were applied on variable specimen-types, evaluating tumors showing different clinic-pathologic features. The positivity rate of different PD-L1 antibody clones in tumor cells ranged from 3% (SP142) to 50% (ABM4E54), excluding the single case tested for RM-320. The most tested clone was E1L3N, followed by 22C3 (most used for pem-brolizumab eligibility), SP263, SP142, and 28-8, which gave the positivity rates of 35%, 11–41% (de-pending on different scoring systems), 6%, 3%, and 15%, respectively. Other clones were tested in &lt;200 cases. The PD-L1 positivity rate was usually higher in tumors than benign tissues. It was higher in non-tissue microarray specimens (41–50% vs. 15%), as PC cells frequently showed heterogenous or focal PD-L1-staining. PD-L1 was expressed by immune or stromal cells in 12% and 69% cases, respectively. Tumor heterogeneity, inter-institutional preanalytics, and inter-observer interpretation variability may account for result biases

Characterization of highly frequent epitope-specific CD45RA(+)/CCR7(+/- )T lymphocyte responses against p53-binding domains of the human polyomavirus BK large tumor antigen in HLA-A*0201+ BKV-seropositive donors

Human polyomavirus BK (BKV) has been implicated in oncogenic transformation. Its ability to replicate is determined by the binding of its large tumor antigen (LTag) to products of tumor-suppressor genes regulating cell cycle, as specifically p53. We investigated CD8+ T immune responses to BKV LTag portions involved in p53 binding in HLA-A*0201+ BKV LTag experienced individuals. Peptides selected from either p53-binding region (LTag(351–450 )and LTag(533–626)) by current algorithms and capacity to bind HLA-A*0201 molecule were used to stimulate CD8+ T responses, as assessed by IFN-γ gene expression ex vivo and detected by cytotoxicity assays following in vitro culture. We observed epitope-specific immune responses in all HLA-A*0201+ BKV LTag experienced individuals tested. At least one epitope, LTag(579–587); LLLIWFRPV, was naturally processed in non professional antigen presenting cells and induced cytotoxic responses with CTL precursor frequencies in the order of 1/20'000. Antigen specific CD8+ T cells were only detectable in the CD45RA+ subset, in both CCR7+ and CCR7- subpopulations. These data indicate that widespread cellular immune responses against epitopes within BKV LTag-p53 binding regions exist and question their roles in immunosurveillance against tumors possibly associated with BKV infection