Publisher Correction: Tumor-necrosis factor impairs CD4+ T cell-mediated immunological control in chronic viral infection.

An amendment to this paper has been published and can be accessed via a link at the top of the paper.

Tumor-necrosis factor impairs CD4(+) T cell-mediated immunological control in chronic viral infection.

Persistent viral infections are characterized by the simultaneous presence of chronic inflammation and T cell dysfunction. In prototypic models of chronicity--infection with human immunodeficiency virus (HIV) or lymphocytic choriomeningitis virus (LCMV)--we used transcriptome-based modeling to reveal that CD4(+) T cells were co-exposed not only to multiple inhibitory signals but also to tumor-necrosis factor (TNF). Blockade of TNF during chronic infection with LCMV abrogated the inhibitory gene-expression signature in CD4(+) T cells, including reduced expression of the inhibitory receptor PD-1, and reconstituted virus-specific immunity, which led to control of infection. Preventing signaling via the TNF receptor selectively in T cells sufficed to induce these effects. Targeted immunological interventions to disrupt the TNF-mediated link between chronic inflammation and T cell dysfunction might therefore lead to therapies to overcome persistent viral infection.

An integer linear programming approach for finding deregulated subgraphs in regulatory networks.

Deregulation of cell signaling pathways plays a crucial role in the development of tumors. The identification of such pathways requires effective analysis tools that facilitate the interpretation of expression differences. Here, we present a novel and highly efficient method for identifying deregulated subnetworks in a regulatory network. Given a score for each node that measures the degree of deregulation of the corresponding gene or protein, the algorithm computes the heaviest connected subnetwork of a specified size reachable from a designated root node. This root node can be interpreted as a molecular key player responsible for the observed deregulation. To demonstrate the potential of our approach, we analyzed three gene expression data sets. In one scenario, we compared expression profiles of non-malignant primary mammary epithelial cells derived from BRCA1 mutation carriers and of epithelial cells without BRCA1 mutation. Our results suggest that oxidative stress plays an important role in epithelial cells of BRCA1 mutation carriers and that the activation of stress proteins may result in avoidance of apoptosis leading to an increased overall survival of cells with genetic alterations. In summary, our approach opens new avenues for the elucidation of pathogenic mechanisms and for the detection of molecular key players.

Human-protein-derived peptides for intracellular delivery of biomolecules.

Access of therapeutic biomolecules to cytoplasmic and nuclear targets is hampered by the inability of these molecules to cross biological membranes. Approaches to overcome this hurdle involve CPPs (cell-penetrating peptides) or protein transduction domains. Most of these require rather high concentrations to elicit cell-penetrating functionality, are non-human, pathogen-derived or synthetic entities, and may therefore not be tolerated or even immunogenic. We identified novel human-protein-derived CPPs by a combination of in silico and experimental analyses: polycationic CPP candidates were identified in an in silico library of all 30-mer peptides of the human proteome. Of these peptides, 60 derived from extracellular proteins were evaluated experimentally. Cell viability and siRNA (small interfering RNA) transfection assays revealed that 20 out of the 60 peptides were functional. Three of these showed CPP functionality without interfering with cell viability. A peptide derived from human NRTN (neurturin), which contains an α-helix, performed the best in our screen and was uniformly taken up by cultured cells. Examples for payloads that can be delivered to the cytosol by the NRTN peptide include complexed siRNAs and both N- and C-terminally fused pro-apoptotic peptides.

Regulatory T-cell Genes Drive Altered Immune Microenvironment in Adult Solid Cancers and Allow for Immune Contextual Patient Subtyping.

Background: The tumor microenvironment is an important factor in cancer immunotherapy response. To further understand how a tumor affects the local immune system, we analyzed immune gene expression differences between matching normal and tumor tissue.Methods: We analyzed public and new gene expression data from solid cancers and isolated immune cell populations. We also determined the correlation between CD8, FoxP3 IHC, and our gene signatures.Results: We observed that regulatory T cells (Tregs) were one of the main drivers of immune gene expression differences between normal and tumor tissue. A tumor-specific CD8 signature was slightly lower in tumor tissue compared with normal of most (12 of 16) cancers, whereas a Treg signature was higher in tumor tissue of all cancers except liver. Clustering by Treg signature found two groups in colorectal cancer datasets. The high Treg cluster had more samples that were consensus molecular subtype 1/4, right-sided, and microsatellite-instable, compared with the low Treg cluster. Finally, we found that the correlation between signature and IHC was low in our small dataset, but samples in the high Treg cluster had significantly more CD8+ and FoxP3+ cells compared with the low Treg cluster.Conclusions: Treg gene expression is highly indicative of the overall tumor immune environment.Impact: In comparison with the consensus molecular subtype and microsatellite status, the Treg signature identifies more colorectal tumors with high immune activation that may benefit from cancer immunotherapy. Cancer Epidemiol Biomarkers Prev; 27(1); 103-12. ©2017 AACR.

Targeting Tumor Cells with Anti-CD44 Antibody Triggers Macrophage-Mediated Immune Modulatory Effects in a Cancer Xenograft Model.

CD44, a transmembrane receptor reported to be involved in various cellular functions, is overexpressed in several cancer types and supposed to be involved in the initiation, progression and prognosis of these cancers. Since the sequence of events following the blockage of the CD44-HA interaction has not yet been studied in detail, we profiled xenograft tumors by RNA Sequencing to elucidate the mode of action of the anti-CD44 antibody RG7356. Analysis of tumor and host gene-expression profiles led us to the hypothesis that treatment with RG7356 antibody leads to an activation of the immune system. Using cytokine measurements we further show that this activation involves the secretion of chemo-attractants necessary for the recruitment of immune cells (i.e. macrophages) to the tumor site. We finally provide evidence for antibody-dependent cellular phagocytosis (ADCP) of the malignant cells by macrophages.

The translational potential for target validation and therapy using intracellular antibodies in oncology.

Antibody-based molecules can be delivered into cells either by intracellular expression or through cellular uptake. We describe technologies for identification and expression of intracellular antibodies for target validation, intracellular immunization and tumor therapy, such as intracellular antibody capture technology, suicide or silencing technology, antigen-antibody interaction dependent apoptosis and their application for inhibition of oncogenic intracellular proteins and induction of apoptosis. These strategies have to be viewed in the context that inhibition of protein-protein interactions by small molecules is often limited due to their large interaction surface. We summarize antibodies with the ability to penetrate cells and strategies to induce uptake of antibodies after modification with protein transduction domains. Interference in oncogenic pathways is described for moieties based on antibody 3E10, which translocates into the nucleus after extracellular administration. Finally, we discuss examples of tumor immunotherapy and vaccination against intracellular antigens, and possible interactions mediating their mode of action.

Global quantitative phosphoproteome analysis of human tumor xenografts treated with a CD44 antagonist.

The cell surface glycoprotein CD44 plays an important role in the development and progression of various tumor types. RG7356 is a humanized antibody targeting the constant region of CD44 that shows antitumor efficacy in mice implanted with CD44-expressing tumors such as MDA-MB-231 breast cancer cells. CD44 receptor seems to function as the main receptor for hyaluronic acid and osteopontin, serving as coreceptor for growth factor pathways like cMet, EGFR, HER-2, and VEGFR and by cytoskeletal modulation via ERM and Rho kinase signaling. To assess the direct impact of RG7356 binding to the CD44 receptor, a global mass spectrometry-based phosphoproteomics approach was applied to freshly isolated MDA-MB-231 tumor xenografts. Results from a global phosphoproteomics screen were further corroborated by Western blot and ELISA analyses of tumor lysates from CD44-expressing tumors. Short-term treatment of tumor-bearing mice with RG7356 resulted in modifications of the MAPK pathway in the responsive model, although no effects on downstream phosphorylation were observed in a nonresponsive xenograft model. Taken together, our approach augments the value of other high throughput techniques to identify biomarkers for clinical development of targeted agents.

Synthetic lethality-based targets for discovery of new cancer therapeutics.

Synthetic lethality is based on the incompatibility of cell survival with the loss of function of two or more genes, not with loss of function of a single gene. If targets of synthetic lethality are deregulated or mutated in cancer cells, the strategy of synthetic lethality can result in significant increase of therapeutic efficacy and a favourable therapeutic window. In this review, we discuss synthetic lethality based on deficient DNA repair mechanisms, activating mutations of RAS, loss of function mutations of the tumor suppressor genes p53, Rb and von Hippel-Lindau, and disruption of interactive protein kinase networks in the context of development of new anticancer agents.

Differential splicing generates new transmembrane receptor and extracellular matrix-related targets for antibody-based therapy of cancer.

Alternative splicing has been shown to be deregulated in cancer and a link to growth stimulation has been established. Here we describe transmembrane and extracellular matrix-related targets generated by alternative splicing with a restricted pattern of expression in normal tissues and a deregulated pattern of expression in cancer as possible targets for therapeutic intervention with antibody-related agents. We focus on isoforms of transmembrane and extracellular matrix proteins, such as CD44, Claudin 18, L1 cell adhesion molecule and epithelial cellular adhesion molecule, fibronectin, tenascin, osteopontin and versican as well as transmembrane tyrosine kinases, such as fibroblast growth factor receptors, epidermal growth factor receptor and receptor d'origin nantais.

Intracellular proteins displayed on the surface of tumor cells as targets for therapeutic intervention with antibody-related agents.

The identification of targets which are located intracellularly in normal cells and are exposed on the surface of malignant cells is an issue in the target selection process for the development of anticancer agents. Targets with these characteristics should increase the specificity of intervention and the corresponding therapeutic window. We discuss targets such as heat-shock protein 70 (HSP70) and heat-shock protein 90 (HSP90), glucose-regulated protein 78 (GRP78), actin, cytokeratins, vimentin, nucleolin, nucleosomes, estrogen receptor-alpha variant 36 (ER-α36) and feto-acinar pancreatic protein (FAPP). Involvement of these targets in cellular processes, tumor specificity and tractability with antibody-related agents, are discussed.

The Roche Cancer Genome Database 2.0.

BACKGROUND: Cancer is a disease of genome alterations that arise through the acquisition of multiple somatic DNA sequence mutations. Some of these mutations can be critical for the development of a tumor and can be useful to characterize tumor types or predict outcome. DESCRIPTION: We have constructed an integrated biological information system termed the Roche Cancer Genome Database (RCGDB) combining different human mutation databases already publicly available. This data is further extended by hand-curated information from publications.The current version of the RCGDB provides a user-friendly graphical interface that gives access to the data in different ways: (1) Single interactive search by genes, samples, cell lines, diseases, as well as pathways, (2) batch searches for genes and cell lines, (3) customized searches for regularly occurring requests, and (4) an advanced query interface enabling the user to query for samples and mutations by various filter criteria. CONCLUSION: The interfaces of the presented database enable the user to search and view mutations in an intuitive and straight-forward manner. The database is freely accessible at http://rcgdb.bioinf.uni-sb.de/MutomeWeb/.

Blood-based gene expression signatures in non-small cell lung cancer.

PURPOSE: Blood-based surrogate markers would be attractive biomarkers for early detection, diagnosis, prognosis, and prediction of therapeutic outcome in cancer. Disease-associated gene expression signatures in peripheral blood mononuclear cells (PBMC) have been described for several cancer types. However, RNA-stabilized whole blood-based technologies would be clinically more applicable and robust. We evaluated the applicability of whole blood-based gene expression profiling for the detection of non-small cell lung cancer (NSCLC). EXPERIMENTAL DESIGN: Expression profiles were generated from PAXgene-stabilized blood samples from three independent groups consisting of NSCLC cases and controls (n = 77, 54, and 102), using the Illumina WG6-VS2 system. RESULTS: Several genes are consistently differentially expressed in whole blood of NSCLC patients and controls. These expression profiles were used to build a diagnostic classifier for NSCLC, which was validated in an independent validation set of NSCLC patients (stages I-IV) and hospital-based controls. The area under the receiver operator curve was calculated to be 0.824 (P < 0.001). In a further independent dataset of stage I NSCLC patients and healthy controls the AUC was 0.977 (P < 0.001). Specificity of the classifier was validated by permutation analysis in both validation cohorts. Genes within the classifier are enriched in immune-associated genes and show specificity for NSCLC. CONCLUSIONS: Our results show that gene expression profiles of whole blood allow for detection of manifest NSCLC. These results prompt further development of gene expression-based biomarker tests in peripheral blood for the diagnosis and early detection of NSCLC.