Replenish the source within: Rescuing tumor-infiltrating lymphocytes by double checkpoint blockade.

We have recently reported that the PD-1 and CTLA4 signaling pathways are active in both effector and regulatory T cells, causing profound immune dysfunctions in the tumor microenvironment. In line with this notion, the dual blockade of PD-1- and CTLA4-conveyed signals may exert robust therapeutic effects. Here, we discuss the mechanisms possibly underlying such a synergic interaction

T-cell and NK-cell infiltration into solid tumors: a key limiting factor for efficacious cancer immunotherapy.

Cancer immunotherapy has great promise, but is limited by diverse mechanisms used by tumors to prevent sustained antitumor immune responses. Tumors disrupt antigen presentation, T/NK-cell activation, and T/NK-cell homing through soluble and cell-surface mediators, the vasculature, and immunosuppressive cells such as myeloid-derived suppressor cells and regulatory T cells. However, many molecular mechanisms preventing the efficacy of antitumor immunity have been identified and can be disrupted by combination immunotherapy. Here, we examine immunosuppressive mechanisms exploited by tumors and provide insights into the therapies under development to overcome them, focusing on lymphocyte traffic

Combining immunotherapy and anticancer agents: the right path to achieve cancer cure?

This article summarizes the immune mediated effect of chemotherapies, the biological and clinical features of new immunotherapies like checkpoint blockers and the rational to use these treatment in combinatio

'Hotspots' of Antigen Presentation Revealed by Human Leukocyte Antigen Ligandomics for Neoantigen Prioritization.

The remarkable clinical efficacy of the immune checkpoint blockade therapies has motivated researchers to discover immunogenic epitopes and exploit them for personalized vaccines. Human leukocyte antigen (HLA)-binding peptides derived from processing and presentation of mutated proteins are one of the leading targets for T-cell recognition of cancer cells. Currently, most studies attempt to identify neoantigens based on predicted affinity to HLA molecules, but the performance of such prediction algorithms is rather poor for rare HLA class I alleles and for HLA class II. Direct identification of neoantigens by mass spectrometry (MS) is becoming feasible; however, it is not yet applicable to most patients and lacks sensitivity. In an attempt to capitalize on existing immunopeptidomics data and extract information that could complement HLA-binding prediction, we first compiled a large HLA class I and class II immunopeptidomics database across dozens of cell types and HLA allotypes and detected hotspots that are subsequences of proteins frequently presented. About 3% of the peptidome was detected in both class I and class II. Based on the gene ontology of their source proteins and the peptide's length, we propose that their processing may partake by the cellular class II presentation machinery. Our database captures the global nature of the in vivo peptidome averaged over many HLA alleles, and therefore, reflects the propensity of peptides to be presented on HLA complexes, which is complementary to the existing neoantigen prediction features such as binding affinity and stability or RNA abundance. We further introduce two immunopeptidomics MS-based features to guide prioritization of neoantigens: the number of peptides matching a protein in our database and the overlap of the predicted wild-type peptide with other peptides in our database. We show as a proof of concept that our immunopeptidomics MS-based features improved neoantigen prioritization by up to 50%. Overall, our work shows that, in addition to providing huge training data to improve the HLA binding prediction, immunopeptidomics also captures other aspects of the natural in vivo presentation that significantly improve prediction of clinically relevant neoantigens

Targeting the undruggable: immunotherapy meets personalized oncology in the genomic era

Genomic technologies have enabled personalized cancer treatments based on the unique molecular aberrations in each person's tumor. T-cell-based immunotherapies may expand the range of therapeutic options for personalized oncology. Here, we discuss the advantages of targeting T cells towards mutations, and the identification and potential therapeutic utilization of mutation-reactive T cell

Cell therapies in ovarian cancer.

Epithelial ovarian cancer (EOC) is the most important cause of gynecological cancer-related mortality. Despite improvements in medical therapies, particularly with the incorporation of drugs targeting homologous recombination deficiency, EOC survival rates remain low. Adoptive cell therapy (ACT) is a personalized form of immunotherapy in which autologous lymphocytes are expanded, manipulated ex vivo, and re-infused into patients to mediate cancer rejection. This highly promising novel approach with curative potential encompasses multiple strategies, including the adoptive transfer of tumor-infiltrating lymphocytes, natural killer cells, or engineered immune components such as chimeric antigen receptor (CAR) constructs and engineered T-cell receptors. Technical advances in genomics and immuno-engineering have made possible neoantigen-based ACT strategies, as well as CAR-T cells with increased cell persistence and intratumoral trafficking, which have the potential to broaden the opportunity for patients with EOC. Furthermore, dendritic cell-based immunotherapies have been tested in patients with EOC with modest but encouraging results, while the combination of DC-based vaccination as a priming modality for other cancer therapies has shown encouraging results. In this manuscript, we provide a clinically oriented historical overview of various forms of cell therapies for the treatment of EOC, with an emphasis on T-cell therapy

Cancer and HIV-1 Infection: Patterns of Chronic Antigen Exposure.

The main role of the human immune system is to eliminate cells presenting foreign antigens and abnormal patterns, while maintaining self-tolerance. However, when facing highly variable pathogens or antigens very similar to self-antigens, this system can fail in completely eliminating the anomalies, leading to the establishment of chronic pathologies. Prototypical examples of immune system defeat are cancer and Human Immunodeficiency Virus-1 (HIV-1) infection. In both conditions, the immune system is persistently exposed to antigens leading to systemic inflammation, lack of generation of long-term memory and exhaustion of effector cells. This triggers a negative feedback loop where effector cells are unable to resolve the pathology and cannot be replaced due to the lack of a pool of undifferentiated, self-renewing memory T cells. In addition, in an attempt to reduce tissue damage due to chronic inflammation, antigen presenting cells and myeloid components of the immune system activate systemic regulatory and tolerogenic programs. Beside these homologies shared between cancer and HIV-1 infection, the immune system can be shaped differently depending on the type and distribution of the eliciting antigens with ultimate consequences at the phenotypic and functional level of immune exhaustion. T cell differentiation, functionality, cytotoxic potential and proliferation reserve, immune-cell polarization, upregulation of negative regulators (immune checkpoint molecules) are indeed directly linked to the quantitative and qualitative differences in priming and recalling conditions. Better understanding of distinct mechanisms and functional consequences underlying disease-specific immune cell dysfunction will contribute to further improve and personalize immunotherapy. In the present review, we describe relevant players of immune cell exhaustion in cancer and HIV-1 infection, and enumerate the best-defined hallmarks of T cell dysfunction. Moreover, we highlight shared and divergent aspects of T cell exhaustion and T cell activation to the best of current knowledge

TIE-2 expressing monocytes in human cancers.

Tumor-associated macrophages (TAM) are well known as a key player in the tumor microenvironment, which support cancer progression. More recently, a lineage of monocytes characterized by the expression of the TIE-2/Tek angiopoietin receptor identified a subset of circulating and tumor-associated monocytes endowed with proangiogenic activity. TIE-2 expressing monocytes (TEM) were found both in humans and mice. Here, we review the phenotypes and functions of TEM reported so far in human cancer and their potential use as markers of cancer progression and metastasis. Finally, we discuss the therapeutic approaches currently used or proposed to target TEM

Identifying biological mechanisms for favorable cancer prognosis using non-hypothesis-driven iterative survival analysis.

Survival analyses based on the Kaplan-Meier estimate have been pervasively used to support or validate the relevance of biological mechanisms in cancer research. Recently, with the appearance of gene expression high-throughput technologies, this kind of analysis has been applied to tumor transcriptomics data. In a 'bottom-up' approach, gene-expression profiles that are associated with a deregulated pathway hypothetically involved in cancer progression are first identified and then subsequently correlated with a survival effect, which statistically supports or requires the rejection of such a hypothesis. In this work, we propose a 'top-down' approach, in which the clinical outcome (survival) is the starting point that guides the identification of deregulated biological mechanisms in cancer by a non-hypothesis-driven iterative survival analysis. We show that the application of our novel method to a population of ~2,000 breast cancer patients of the METABRIC consortium allows the identification of several well-known cancer mechanisms, such as ERBB4, HNF3A and TGFB pathways, and the investigation of their paradoxical dual effect. In addition, several novel biological mechanisms are proposed as potentially involved in cancer progression. The proposed exploratory methodology can be considered both alternative and complementary to classical 'bottom-up' approaches for validation of biological hypotheses. We propose that our method may be used to better characterize cancer, and may therefore impact the future design of therapies that are truly molecularly tailored to individual patients. The method, named SURCOMED, was implemented as a web-based tool, which is publicly available at http://surcomed.vital-it.ch. R scripts are also available at http://surcomed.sourceforge.net)