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With the advent of high-throughput technologies leading to big data generation, increasing number of gene signatures are being published to predict various features of diseases such as prognosis and patient survival. However, to use these signatures for identifying therapeutic targets, use of additional bioinformatic tools is indispensible part of research. Here, we have generated a pipeline comprised of nearly 15 bioinformatic tools and enrichment statistical methods to propose and validate a drug combination strategy from already approved drugs and present our approach using published pan-cancer epithelial–mesenchymal transition (EMT) signatures as a case study. We observed that histone deacetylases were critical targets to tune expression of multiple epithelial versus mesenchymal genes. Moreover, SRC and IKBK were the principal intracellular kinases regulating multiple signaling pathways. To confirm the anti-EMT efficacy of the proposed target combination in silico , we validated expression of targets in mesenchymal versus epithelial subtypes of ovarian cancer. Additionally, we inhibited the pinpointed proteins in vitro using an invasive lung cancer cell line. We found that whereas low-dose mono-therapy failed to limit cell dispersion from collagen spheroids in a microfluidic device as a metric of EMT, the combination fully inhibited dissociation and invasion of cancer cells toward cocultured endothelial cells. Given the approval status and safety profiles of the suggested drugs, the proposed combination set can be considered in clinical trials. [ABSTRACT FROM AUTHOR]

Network pharmacology elucidates the relationship between drugs and targets. As the identified targets for each drug increases, the corresponding drug-target network (DTN) evolves from solely reflection of the pharmaceutical industry trend to a portrait of polypharmacology. The aim of this study was to evaluate the potentials of DrugBank database in advancing systems pharmacology. We constructed and analyzed DTN from drugs and targets associations in the DrugBank 4.0 database. Our results showed that in bipartite DTN, increased ratio of identified targets for drugs augmented density and connectivity of drugs and targets and decreased modular structure. To clear up the details in the network structure, the DTNs were projected into two networks namely, drug similarity network (DSN) and target similarity network (TSN). In DSN, various classes of Food and Drug Administration-approved drugs with distinct therapeutic categories were linked together based on shared targets. Projected TSN also showed complexity because of promiscuity of the drugs. By including investigational drugs that are currently being tested in clinical trials, the networks manifested more connectivity and pictured the upcoming pharmacological space in the future years. Diverse biological processes and protein-protein interactions were manipulated by new drugs, which can extend possible target combinations. We conclude that network-based organization of DrugBank 4.0 data not only reveals the potential for repurposing of existing drugs, also allows generating novel predictions about drugs off-targets, drug-drug interactions and their side effects. Our results also encourage further effort for high-throughput identification of targets to build networks that can be integrated into disease networks. [ABSTRACT FROM AUTHOR]

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Because of the low mutational burden and consequently, fewer potential neoantigens, children with acute myeloid leukemia (AML) are thought to have a T cell-depleted or 'cold' tumor microenvironment and may have a low likelihood of response to T cell-directed immunotherapies. Understanding the composition, phenotype, and spatial organization of T cells and other microenvironmental populations in the pediatric AML bone marrow (BM) is essential for informing future immunotherapeutic trials about targetable immune-evasion mechanisms specific to pediatric AML. Here, we conducted a multidimensional analysis of the tumor immune microenvironment in pediatric AML and non-leukemic controls. We demonstrated that nearly one-third of pediatric AML cases has an immune-infiltrated BM, which is characterized by a decreased ratio of M2-to M1-like macrophages. Furthermore, we detected the presence of large T cell networks, both with and without colocalizing B cells, in the BM and dissected the cellular composition of T- and B cell-rich aggregates using spatial transcriptomics. These analyses revealed that these aggregates are hotspots of CD8 + T cells, memory B cells, plasma cells and/or plasmablasts, and M1-like macrophages. Collectively, our study provides a multidimensional characterization of the BM immune microenvironment in pediatric AML and indicates starting points for further investigations into immunomodulatory mechanisms in this devastating disease.

Human leukocyte antigen (HLA) restriction of conventional T-cell targeting introduces complexity in generating T-cell therapy strategies for patients with cancer with diverse HLA-backgrounds. A subpopulation of atypical, major histocompatibility complex-I related protein 1 (MR1)-restricted T-cells, distinctive from mucosal-associated invariant T-cells (MAITs), was recently identified recognizing currently unidentified MR1-presented cancer-specific metabolites. It is hypothesized that the MC.7.G5 MR1T-clone has potential as a pan-cancer, pan-population T-cell immunotherapy approach. These cells are irresponsive to healthy tissue while conferring T-cell receptor(TCR) dependent, HLA-independent cytotoxicity to a wide range of adult cancers. Studies so far are limited to adult malignancies. Here, we investigated the potential of MR1-targeting cellular therapy strategies in pediatric cancer. Bulk RNA sequencing data of primary pediatric tumors were analyzed to assess MR1 expression. In vitro pediatric tumor models were subsequently screened to evaluate their susceptibility to engineered MC.7.G5 TCR-expressing T-cells. Targeting capacity was correlated with qPCR-based MR1 mRNA and protein overexpression. RNA expression of MR1 in primary pediatric tumors varied widely within and between tumor entities. Notably, embryonal tumors exhibited significantly lower MR1 expression than other pediatric tumors. In line with this, most screened embryonal tumors displayed resistance to MR1T-targeting in vitro MR1T susceptibility was observed particularly in pediatric leukemia and diffuse midline glioma models. This study demonstrates potential of MC.7.G5 MR1T-cell immunotherapy in pediatric leukemias and diffuse midline glioma, while activity against embryonal tumors was limited. The dismal prognosis associated with relapsed/refractory leukemias and high-grade brain tumors highlights the promise to improve survival rates of children with these cancers., Competing Interests: Competing interests: ZS and JK are inventors on different patents for γδ TCR sequences, recognition mechanisms and isolation strategies. JK is scientific cofounder and shareholder of Gadeta (www.gadeta.nl). The remaining authors declare no competing interests., (© Author(s) (or their employer(s)) 2024. Re-use permitted under CC BY-NC. No commercial re-use. See rights and permissions. Published by BMJ.)