Drug repositioning is a cost-efficient and time-saving process to drug development compared to traditional techniques. A systematic method to drug repositioning is to identify candidate drug's gene expression profiles on target disease models and determine how similar these profiles are to approved drugs. Databases such as the CMAP have been developed recently to help with systematic drug repositioning.

Leukemic stem cells (LSCs) can acquire non-mutational resistance following drug treatment leading to therapeutic failure and relapse. However, oncogene-independent mechanisms of drug persistence in LSCs are incompletely understood, which is the primary focus of this study. We integrated proteomics, transcriptomics, and metabolomics to determine the contribution of STAT3 in promoting metabolic changes in tyrosine kinase inhibitor (TKI) persistent chronic myeloid leukemia (CML) cells. Proteomic and transcriptional differences in TKI persistent CML cells revealed BCR-ABL-independent STAT3 activation in these cells. While knockout of STAT3 inhibited the CML cells from developing drug-persistence, inhibition of STAT3 using a small molecule inhibitor sensitized the persistent CML cells to TKI treatment. Interestingly, given the role of phosphorylated STAT3 as a transcription factor, it localized uniquely to genes regulating metabolic pathways in the TKI-persistent CML stem and progenitor cells. Subsequently, we observed that STAT3 dysregulated mitochondrial metabolism forcing the TKI-persistent CML cells to depend on glycolysis, unlike TKI-sensitive CML cells, which are more reliant on oxidative phosphorylation. Finally, targeting pyruvate kinase M2, a rate-limiting glycolytic enzyme, specifically eradicated the TKI-persistent CML cells. By exploring the role of STAT3 in altering metabolism, we provide critical insight into identifying potential therapeutic targets for eliminating TKI-persistent LSCs.

Improved diagnostic methods are needed for bronchiolitis obliterans syndrome (BOS), a serious complication after allogeneic hematopoietic cell transplantation (HCT) and lung transplantation. For protein candidate discovery, we compared plasma pools from HCT transplantation recipients with BOS at onset (n = 12), pulmonary infection (n = 16), chronic graft‐versus‐host disease without pulmonary involvement (n = 15) and no chronic complications after HCT (n = 15). Pools were labeled with different tags (isobaric tags for relative and absolute quantification), and two software tools identified differentially expressed proteins (≥1.5‐fold change). Candidate proteins were further selected using a six‐step computational biology approach. The diagnostic value of the lead candidate, matrix metalloproteinase 3 (MMP3), was evaluated by enzyme‐linked immunosorbent assay in plasma of a verification cohort (n = 112) with and without BOS following HCT (n = 76) or lung transplantation (n = 36). MMP3 plasma concentrations differed significantly between patients with and without BOS (area under the receiver operating characteristic curve 0.77). Consequently, MMP3 represents a potential noninvasive blood test for diagnosis of BOS.

Much effort has been devoted to the discovery of specific mechanisms between drugs and single targets to date. However, as biological systems maintain homeostasis at the level of functional networks robustly controlling the internal environment, such networks commonly contain multiple redundant mechanisms designed to counteract loss or perturbation of a single member of the network. As such, investigation of therapeutics that target dysregulated pathways or processes, rather than single targets, may identify agents that function at a level of the biological organization more relevant to the pathology of complex diseases such as Parkinson’s Disease (PD). Genome-wide association studies (GWAS) in PD have identified common variants underlying disease susceptibility, while gene expression microarray data provide genome-wide transcriptional profiles. These genomic studies can illustrate upstream perturbations causing the dysfunction in signaling pathways and downstream biochemical mechanisms leading to the PD phenotype. We hypothesize that drugs acting at the level of a gene expression module specific to PD can overcome the lack of efficacy associated with targeting a single gene in polygenic diseases. Thus, this approach represents a promising new direction for module-based drug discovery in human diseases such as PD. We built a framework that integrates GWAS data with gene co-expression modules from tissues representing three brain regions—the frontal gyrus, the lateral substantia, and the medial substantia in PD patients. Using weighted gene correlation network analysis (WGCNA) software package in R, we conducted enrichment analysis of data from a GWAS of PD. This led to the identification of two over-represented PD-specific gene co-expression network modules: the Brown Module (Br) containing 449 genes and the Turquoise module (T) containing 905 genes. Further enrichment analysis identified four functional pathways within the Br module (cellular respiration, intracellular transport, energy coupled proton transport against the electrochemical gradient, and microtubule-based movement), and one functional pathway within the T module (M-phase). Next, we utilized drug-protein regulatory relationship databases (DMAP) and developed a Drug Effect Sum Score (DESS) to evaluate all candidate drugs that might restore gene expression to normal level across the Br and T modules. Among the drugs with the 12 highest DESS scores, 5 had been reported as potential treatments for PD and 6 hold potential repositioning applications. In this study, we present a systems pharmacology framework which draws on genetic data from GWAS and gene expression microarray data to reposition drugs for PD. Our innovative approach integrates gene co-expression modules with biomolecular interaction network analysis to identify network modules critical to the PD pathway and disease mechanism. We quantify the positive effects of drugs in a DESS score that is based on known drug-target activity profiles. Our results illustrate that this modular approach is promising for repositioning drugs for use in polygenic diseases such as PD, and is capable of addressing challenges of the hindered gene target in drug repositioning approaches to date.

The tumor microenvironment (TME) is pivotal in tumor growth and metastasis, aligning with the “Seed and Soil” theory. Within the TME, tumor-associated macrophages (TAMs) play a central role, profoundly influencing tumor progression. Strategies targeting TAMs have surfaced as potential therapeutic avenues, encompassing interventions to block TAM recruitment, eliminate TAMs, reprogram M2 TAMs, or bolster their phagocytic capabilities via specific pathways. Nanomaterials including inorganic materials, organic materials for small molecules and large molecules stand at the forefront, presenting significant opportunities for precise targeting and modulation of TAMs to enhance therapeutic efficacy in cancer treatment. This review provides an overview of the progress in designing nanoparticles for interacting with and influencing the TAMs as a significant strategy in cancer therapy. This comprehensive review presents the role of TAMs in the TME and various targeting strategies as a promising frontier in the ever-evolving field of cancer therapy. The current trends and challenges associated with TAM-based therapy in cancer are presented.