Mesenchymal stem cells and their use as cell replacement therapy and disease modelling tool.

Mesenchymal stem cells (MSCs) from adult somatic tissues may differentiate in vitro and in vivo into multiple mesodermal tissues including bone, cartilage, adipose tissue, tendon, ligament or even muscle. MSCs preferentially home to damaged tissues where they exert their therapeutic potential. A striking feature of the MSCs is their low inherent immunogenicity as they induce little, if any, proliferation of allogeneic lymphocytes and antigen-presenting cells. Instead, MSCs appear to be immunosuppressive in vitro. Their multilineage differentiation potential coupled to their immuno-privileged properties is being exploited worldwide for both autologous and allogeneic cell replacement strategies. Here, we introduce the readers to the biology of MSCs and the mechanisms underlying immune tolerance. We then outline potential cell replacement strategies and clinical applications based on the MSCs immunological properties. Ongoing clinical trials for graft-versus-host-disease, haematopoietic recovery after co-transplantation of MSCs along with haematopoietic stem cells and tissue repair are discussed. Finally, we review the emerging area based on the use of MSCs as a target cell subset for either spontaneous or induced neoplastic transformation and, for modelling non-haematological mesenchymal cancers such as sarcomas

Topics in cancer genomics

Large-scale projects such as the The Cancer Genome Atlas (TCGA) have generated extensive exome libraries across several disease types and populations. Detection of somatic changes in HLA genes by whole-exome sequencing (WES) has been complicated by the highly polymorphic nature of these loci. We developed a method POLYSOLVER (POLYmorphic loci reSOLVER) for accurate inference of class I HLA-A, -B and -C alleles from WES data, and achieved 97% accuracy at protein level resolution when this was applied to 133 HapMap samples of known HLA type. By applying POLYSOLVER in conjunction with somatic change detection tools to 2688 tumor/normal pairs TCGA that were previously analyzed by conventional approaches, we re-discovered 37 of 56 (66%) HLA mutations, while further identifying 23 new events. An analysis of WES data from a larger set of 3768 tumor/normal pairs by POLYSOLVER revealed 131 class I mutations with an enrichment for potentially loss-of-function events. 3% of samples had at least one HLA event with 95 of 131 mutations in the T cell interacting and peptide binding domains. Recurrent hotspot sites of missense, nonsense and splice site mutations were discovered that suggest positive selection, and support immune evasion as an important pathway in cancer. Exome sequencing has also revealed a large number of shared and personal somatic mutations across human cancers. In principle, any genetic alteration affecting a protein-coding region has the potential to generate mutated peptides that are presented by surface HLA class I proteins that might be recognized by cytotoxic T cells. Utilizing POLYSOLVER in conjunction with knowledge of mutations in other genetic loci inferred from exome data, we developed a pipeline for the prediction and validation of such neoantigens derived from individual tumors and presented by patient-specific alleles of the HLA proteins. We applied our computational pipeline to 91 chronic lymphocytic leukemias (CLL) that had undergone whole-exome sequencing. We predicted ~22 mutated HLA-binding peptides per leukemia (derived from ~16 missense mutations), and experimentally confirmed HLA binding for ~55% of such peptides. Finally, we computationally predicted HLA-binding peptides with missense or frameshift mutations for several cancer types and predicted dozens to thousands of neoantigens per individual tumor, suggesting that neoantigens are frequent in most tumors. The neoantigen prediction pipeline can also elucidate the neoantigens unique to a particular cancer patient and help in the design of personalized immune vaccines. MicroRNAs (miRs) are a class of non-coding small RNAs that regulate gene expression by promoting mRNA degradation or by inhibiting mRNA translation. Context Likelihood of Relatedness (CLR) is genetic network reconstruction method that considers the local network context in assessing the significance of connections while also allowing for detection of non-linear associations. Leveraging TCGA multidimensional data in glioblastoma, we inferred the putative regulatory network between microRNA and mRNA using the CLR algorithm. Interrogation of the network in context of defined molecular subtypes identified 8 microRNAs with a strong discriminatory potential between proneural and mesenchymal subtypes. Integrative in silico analyses, a functional genetic screen, and experimental validation identified miR-34a as a tumor suppressor in proneural subtype glioblastoma. Mechanistically, in addition to its direct regulation of platelet-derived growth factor receptor-alpha (PDGFRA), promoter enrichment analysis of CLR-inferred mRNA nodes established miR-34a as a novel regulator of a SMAD4 transcriptional network. Clinically, miR-34a expression level is shown to be prognostic, where miR-34a low-expressing glioblastomas exhibited better overall survival. This work illustrates the potential of comprehensive multidimensional cancer genomic data combined with computational and experimental models to enable mechanistic exploration of relationships among different genetic elements across the genome space in cancer

In vitro expanded human CD4+CD25+ regulatory T cells suppress effector T cell proliferation.

Regulatory T cells (Tregs) have been shown to be critical in the balance between autoimmunity and tolerance and have been implicated in several human autoimmune diseases. However, the small number of Tregs in peripheral blood limits their therapeutic potential. Therefore, we developed a protocol that would allow for the expansion of Tregs while retaining their suppressive activity. We isolated CD4+CD25 hi cells from human peripheral blood and expanded them in vitro in the presence of anti-CD3 and anti-CD28 magnetic Xcyte Dynabeads and high concentrations of exogenous Interleukin (IL)-2. Tregs were effectively expanded up to 200-fold while maintaining surface expression of CD25 and other markers of Tregs: CD62L, HLA-DR, CCR6, and FOXP3. The expanded Tregs suppressed proliferation and cytokine secretion of responder PBMCs in co-cultures stimulated with anti-CD3 or alloantigen. Treg expansion is a critical first step before consideration of Tregs as a therapeutic intervention in patients with autoimmune or graft-versus-host disease

Clinical applications of personalized medicine: a new paradigm and challenge

The personalized medicine is an emergent and rapidly developing method of clinical practice that uses new technologies to provide decisions in regard to the prediction, prevention, diagnosis and treatment of disease. The continue evolution of technology and the developments in molecular diagnostics and genomic analysis increased the possibility of an even more understanding and interpretation of the human genome and exome, allowing a "personalized" approach to clinical care, so that the concepts of "Systems Medicine" and "System Biology" are increasingly actual. The purpose of this study is to evaluate the personalized medicine about its indications and benefits, actual clinical applications and future perspectives as well as its issues and health care implications. It was made a careful review of the scientific literature on this field that highlighted the applicability and usefulness of this new medical approach as well as the fact that personalized medicine strategy is even more increasing in numerous fields of applications

Cancer Immunotherapy and Biological Cancer Treatments

In recent years, biological cancer therapies, including immunotherapy, have moved from the bench to mainstream medical treatments of several types of cancer. The success of these treatments relies on innovative approaches to specifically interfere with molecular targets that are involved in the growth, progression, and spread of malignant cells, or to bypass the tumor evasion of the immune system utilizing the latest advances in cancer vaccine development, formulation, and delivery. This book presents an up-to-date overview of novel cancer biological and immunotherapeutic approaches, including cancer vaccines, mimetic vaccines, monoclonal antibodies, adoptive T-cell transfer, chimeric antigen receptor T- cells, tumor infiltrating lymphocytes, dendritic cells, natural killer cells, immune checkpoint inhibitors, laser ablation, and immune stimulating interstitial laser thermotherapy

Cell-type-specific resolution epigenetics without the need for cell sorting or single-cell biology.

High costs and technical limitations of cell sorting and single-cell techniques currently restrict the collection of large-scale, cell-type-specific DNA methylation data. This, in turn, impedes our ability to tackle key biological questions that pertain to variation within a population, such as identification of disease-associated genes at a cell-type-specific resolution. Here, we show mathematically and empirically that cell-type-specific methylation levels of an individual can be learned from its tissue-level bulk data, conceptually emulating the case where the individual has been profiled with a single-cell resolution and then signals were aggregated in each cell population separately. Provided with this unprecedented way to perform powerful large-scale epigenetic studies with cell-type-specific resolution, we revisit previous studies with tissue-level bulk methylation and reveal novel associations with leukocyte composition in blood and with rheumatoid arthritis. For the latter, we further show consistency with validation data collected from sorted leukocyte sub-types

Immunorecognition of leukemic stem cells by NK cells : the role of HDAC inhibitors in NKG2D ligand-mediated anti-tumor responses in acute myeloid leukemia

The diagnosis of acute myeloid leukemia (AML) is associated to a poor long-term outcome due to frequent relapse despite intensive chemotherapy, radiation and hematopoietic stem cell transplantation (HSCT) as well as continuous advances in treatment modalities. Relapses might be caused by leukemic stem cells (LSC). According to a recently emerging concept, LSC display many features of normal hematopoietic stem cells (HSC) like quiescence and self renewal capacity and therefore are poorly accessible for conventional therapies which primarily reach the rapidly proliferating cells. Additionally, LSC are apparently able to escape from immunorecognition and thereby sustain the disease. NK cells, as the main innate immune effectors against tumor cells, are able to recognize and kill malignant cells when triggered by cell surface expression of a multitude of activating ligands. The best-described receptor-ligand pair in humans is NKG2D and its ligands, ULBP and MICA/B. Furthermore, NCR is an important family of activating receptors on NK cells, whose ligands are not yet known. The regulation of NK cells is completed by several inhibitory receptors (KIR) specific for different HLA class I molecules on potential target cells. While preceding work in our lab was describing the interaction between NK cells and leukemic blasts of AML, there is no information available on the recognition of LSC by NK cells. In this study we aimed to elucidate the interaction of NK cells with LSC of AML. The cell surface expression of ligands for activating and inhibitory NK cell receptors on LSC was in focus of these studies. Moreover, we applied a pharmacological approach to treat the patient-derived primary AML leukemic cells and examined the consequences for cell surface expression of NK cell-specific ligands. By employing hematopoietic colony forming assays, cytotoxicity assays as well as in vivo NOD/SCID xenotransplantation we aimed to functionally assess the implications of the upregulation of activating ligands for NK cell immunorecognition of LSC. In initial experiments, we demonstrated that activating ligands for the NKG2D receptor and NCR receptors on NK cells are absent or only weakly expressed on the surface of patient derived AML blasts. This expression could be increased by pharmacological means applying bryostatin-1, a modulator of PKC activity. Upregulation of cell surface expression of NKG2D ligands on AML blasts led to increased immunorecognition by NK cells in cytotoxicity assays. Subsequently, we demonstrated that similarly to total blasts, LSC of AML as judged by the phenotype CD45dimCD34+CD38-, did not express ULBP and MICA/B on their surface. To pharmacologically increase their expression, we employed the HDAC inhibitor valproic acid (VA), a drug acting through epigenetic modification of gene expression and having long-term records in different clinical applications. This treatment with VA proved to be of importance for the immunorecognition by NK cells. In the functional assays we employed NK cells selected for the KIR-HLA class I mismatch in order to circumvent inhibitory signals inactivating the NK cells. Serial replating colony forming unit (CFU) assays with LSC after treatment with VA and after coincubation with KIR-HLA mismatched NK cells demonstrated an efficient reduction in colony formation capacity upon this synergistic treatment. The cytotoxicity assays with VA-treated LSC as targets and KIR-HLA mismatched NK cells as effectors revealed interindividual differences among patient samples, reflecting a complex regulation of NK cell activation and immunorecognition. Altogether, a direct interaction of NK cells and LSC could be demonstrated in vitro. In the in vivo setting, by transplantation of AML cells intrafemurally into NOD/SCID mice with consecutive treatment of VA and HLA-mismatched NK cells, we were able to achieve a stable engraftment of human AML in the mouse bone marrow. However, the combined treatment with VA and NK cells was not influencing the content of malignant cells as compared to untreated mice. The ongoing studies aim at optimization of AML treatment with NK cell-based immunotherapy in the preclinical NOD/SCID transplantation model. Taken together, these results showed the potential of VA as an applicable anti-neoplastic drug to enhance immunorecognition of LSC of AML by NK cells, mediated by increased cell surface expression of activating ligands. The functional consequences of an enhanced immunorecognition by NK cells in abolishing the colony forming capacity of patient derived LSC are promising beneficial effects for innovative AML treatments in future

Artificial Neural Network Inference (ANNI): A Study on Gene-Gene Interaction for Biomarkers in Childhood Sarcomas

Objective: To model the potential interaction between previously identified biomarkers in children sarcomas using artificial neural network inference (ANNI). Method: To concisely demonstrate the biological interactions between correlated genes in an interaction network map, only 2 types of sarcomas in the children small round blue cell tumors (SRBCTs) dataset are discussed in this paper. A backpropagation neural network was used to model the potential interaction between genes. The prediction weights and signal directions were used to model the strengths of the interaction signals and the direction of the interaction link between genes. The ANN model was validated using Monte Carlo cross-validation to minimize the risk of over-fitting and to optimize generalization ability of the model. Results: Strong connection links on certain genes (TNNT1 and FNDC5 in rhabdomyosarcoma (RMS); FCGRT and OLFM1 in Ewing’s sarcoma (EWS)) suggested their potency as central hubs in the interconnection of genes with different functionalities. The results showed that the RMS patients in this dataset are likely to be congenital and at low risk of cardiomyopathy development. The EWS patients are likely to be complicated by EWS-FLI fusion and deficiency in various signaling pathways, including Wnt, Fas/Rho and intracellular oxygen. Conclusions: The ANN network inference approach and the examination of identified genes in the published literature within the context of the disease highlights the substantial influence of certain genes in sarcomas