Network- and systems-based re-engineering of dendritic cells with non-coding RNAs for cancer immunotherapy.

Dendritic cells (DCs) are professional antigen-presenting cells that induce and regulate adaptive immunity by presenting antigens to T cells. Due to their coordinative role in adaptive immune responses, DCs have been used as cell-based therapeutic vaccination against cancer. The capacity of DCs to induce a therapeutic immune response can be enhanced by re-wiring of cellular signalling pathways with microRNAs (miRNAs). Methods: Since the activation and maturation of DCs is controlled by an interconnected signalling network, we deploy an approach that combines RNA sequencing data and systems biology methods to delineate miRNA-based strategies that enhance DC-elicited immune responses. Results: Through RNA sequencing of IKKß-matured DCs that are currently being tested in a clinical trial on therapeutic anti-cancer vaccination, we identified 44 differentially expressed miRNAs. According to a network analysis, most of these miRNAs regulate targets that are linked to immune pathways, such as cytokine and interleukin signalling. We employed a network topology-oriented scoring model to rank the miRNAs, analysed their impact on immunogenic potency of DCs, and identified dozens of promising miRNA candidates, with miR-15a and miR-16 as the top ones. The results of our analysis are presented in a database that constitutes a tool to identify DC-relevant miRNA-gene interactions with therapeutic potential (https://www.synmirapy.net/dc-optimization). Conclusions: Our approach enables the systematic analysis and identification of functional miRNA-gene interactions that can be experimentally tested for improving DC immunogenic potency.

Curatopes Melanoma: A Database of Predicted T-cell Epitopes from Overly Expressed Proteins in Metastatic Cutaneous Melanoma.

Therapeutic anticancer vaccination has been adapted as an immunotherapy in several solid tumors. However, the selection of promising candidates from the total quantity of possible epitopes poses a challenge to clinicians and bioinformaticians alike, and very few epitopes have been tested in experimental or clinical settings to validate their efficacy. Here, we present a comprehensive database of predicted nonmutated peptide epitopes derived from genes that are overly expressed in a group of 32 melanoma biopsies compared with healthy tissues and that were filtered against expression in a curated list of survival-critical tissues. We hypothesize that these "self-tolerant" epitopes have two desirable properties: they do not depend on mutations, being immediately applicable to a large patient collective, and they potentially cause fewer autoimmune reactions. To support epitope selection, we provide an aggregated score of expected therapeutic efficiency as a shortlist mechanism. The database has applications in facilitating epitope selection and trial design and is freely accessible at https://www.curatopes.com. SIGNIFICANCE: A database is presented that predicts and scores antitumor T-cell epitopes, with a focus on tolerability and avoidance of severe autoimmunity, offering a supplementary epitope set for further investigation in immunotherapy.

A web platform for the network analysis of high-throughput data in melanoma and its use to investigate mechanisms of resistance to anti-PD1 immunotherapy.

Cellular phenotypes are established and controlled by complex and precisely orchestrated molecular networks. In cancer, mutations and dysregulations of multiple molecular factors perturb the regulation of these networks and lead to malignant transformation. High-throughput technologies are a valuable source of information to establish the complex molecular relationships behind the emergence of malignancy, but full exploitation of this massive amount of data requires bioinformatics tools that rely on network-based analyses. In this report we present the Virtual Melanoma Cell, an online tool developed to facilitate the mining and interpretation of high-throughput data on melanoma by biomedical researches. The platform is based on a comprehensive, manually generated and expert-validated regulatory map composed of signaling pathways important in malignant melanoma. The Virtual Melanoma Cell is a tool designed to accept, visualize and analyze user-generated datasets. It is available at: https://www.vcells.net/melanoma. To illustrate the utilization of the web platform and the regulatory map, we have analyzed a large publicly available dataset accounting for anti-PD1 immunotherapy treatment of malignant melanoma patients.

Personalized cancer immunotherapy using Systems Medicine approaches.

The immune system is by definition multi-scale because it involves biochemical networks that regulate cell fates across cell boundaries, but also because immune cells communicate with each other by direct contact or through the secretion of local or systemic signals. Furthermore, tumor and immune cells communicate, and this interaction is affected by the tumor microenvironment. Altogether, the tumor-immunity interaction is a complex multi-scale biological system whose analysis requires a systemic view to succeed in developing efficient immunotherapies for cancer and immune-related diseases. In this review we discuss the necessity and the structure of a systems medicine approach for the design of anticancer immunotherapies. We support the idea that the approach must be a combination of algorithms and methods from bioinformatics and patient-data-driven mathematical models conceived to investigate the role of clinical interventions in the tumor-immunity interaction. For each step of the integrative approach proposed, we review the advancement with respect to the computational tools and methods available, but also successful case studies. We particularized our idea for the case of identifying novel tumor-associated antigens and therapeutic targets by integration of patient's immune and tumor profiling in case of aggressive melanoma.

Electroporated Antigen-Encoding mRNA Is Not a Danger Signal to Human Mature Monocyte-Derived Dendritic Cells.

For therapeutic cancer vaccination, the adoptive transfer of mRNA-electroporated dendritic cells (DCs) is frequently performed, usually with monocyte-derived, cytokine-matured DCs (moDCs). However, DCs are rich in danger-sensing receptors which could recognize the exogenously delivered mRNA and induce DC activation, hence influencing the DCs' immunogenicity. Therefore, we examined whether electroporation of mRNA with a proper cap and a poly-A tail of at least 64 adenosines had any influence on cocktail-matured moDCs. We used 16 different RNAs, encoding tumor antigens (MelanA, NRAS, BRAF, GNAQ, GNA11, and WT1), and variants thereof. None of those RNAs induced changes in the expression of CD25, CD40, CD83, CD86, and CD70 or the secretion of the cytokines IL-8, IL-6, and TNFα of more than 1.5-fold compared to the control condition, while an mRNA encoding an NF-κB-activation protein as positive control induced massive secretion of the cytokines. To determine whether mRNA electroporation had any effect on the whole transcriptome of the DCs, we performed microarray analyses of DCs of 6 different donors. None of 60,000 probes was significantly different between mock-electroporated DCs and MelanA-transfected DCs. Hence, we conclude that no transcriptional programs were induced within cocktail-matured DCs by electroporation of single tumor-antigen-encoding mRNAs.