Identification of anthelmintic parbendazole as a therapeutic molecule for HNSCC through connectivity map-based drug repositioning

Icariside II inhibits Epithelial-Mesenchymal transition in metastatic osteosarcoma by antagonizing the miR-194/215 cluster via PGK1

Osteosarcoma, the most prevalent malignant bone tumor in adolescents, is characterized by its aggressiveness and tendency to metastasize. Despite the advancements in treatment that have improved survival rates for localized cases, metastatic osteosarcoma remains challenging to treat due to the limited efficacy of current therapies and the severe side effects of chemotherapy. Epithelial-mesenchymal transition (EMT) is a key factor in osteosarcoma metastasis, and the miR-194/215 cluster, which is upregulated in osteosarcoma, promotes this process. This study sought to investigate natural compounds that could counteract the miR-194/215 cluster's effects and inhibit osteosarcoma metastasis. By analyzing miRNA databases and clinical data, a signature gene set for the miR-194/215 cluster was established, and the LINCS database was screened to find natural compounds with antagonistic effects. Icariside II, an active component of Epimedium, was identified as a potential inhibitor and was shown to reduce the migration and invasion of osteosarcoma cells in vitro and lung metastasis in vivo. The study utilized various techniques, including Gene Set Enrichment Analysis (GSEA), Drug Affinity Responsive Target Stability (DARTS), Cellular Thermal Shift Assay (CETSA), molecular docking, and enzyme activity assays, to identify phosphoglycerate kinase 1 (PGK1) as the target protein of Icariside II. It was found that Icariside II competitively inhibits PGK1 by binding to its ADP binding pocket, reducing its activity and thus antagonizing the miR-194/215 cluster's promotion of EMT in metastatic osteosarcoma. The results suggest that Icariside II could be a promising therapeutic agent for metastatic osteosarcoma, providing new targets and strategies for clinical treatment.

SCG2 Mediates HNSCC Progression With CCL2/TGFβ1high M2 Macrophage Infiltration

OBJECTIVES

This study aims to unravel the mechanisms underlying M2 macrophage polarization in head and neck squamous cell carcinoma (HNSCC), and identify potential therapeutic targets.

MATERIALS AND METHODS

We conducted an integrated bioinformatic analysis using HNSCC bulk transcriptomes from TCGA and GEO databases to pinpoint critical factors influencing M2 macrophage polarization and tumor prognosis. The significance of these genes was validated in function analysis, single-cell transcriptome datasets, and in vitro experiments. Their mechanisms in modulating M2 macrophage polarization were further explored by gene knockdown, cell coculture, and other assays for quantification.

RESULTS

We identified a novel prognostic signature of five genes associated with M2 macrophage infiltration, in which SCG2 emerged as a pivotal factor in M2 macrophage polarization in HNSCC. High expression of SCG2 in tumor patients correlated with poorer prognoses, and knocking down SCG2 reduced the proliferation and migration of HNSCC cells, disrupting M2 macrophage polarization. Furthermore, interference of SCG2 resulted in a significant decrease in the secretion of pro-tumor cytokines such as CCL2 and TGFβ1.

CONCLUSIONS

Our findings provide deeper insights into the pathogenesis of HNSCC and offer promising therapeutic targets for HNSCC, especially SCG2, to inhibit M2 macrophage polarization and modulate cytokine secretion.

A deep learning framework for in silico screening of anticancer drugs at the single-cell level

Tumor heterogeneity plays a pivotal role in tumor progression and resistance to clinical treatment. Single-cell RNA sequencing (scRNA-seq) enables us to explore heterogeneity within a cell population and identify rare cell types, thereby improving our design of targeted therapeutic strategies. Here, we use a pan-cancer and pan-tissue single-cell transcriptional landscape to reveal heterogeneous expression patterns within malignant cells, precancerous cells, as well as cancer-associated stromal and endothelial cells. We introduce a deep learning framework named Shennong for in silico screening of anticancer drugs for targeting each of the landscape cell clusters. Utilizing Shennong, we could predict individual cell responses to pharmacologic compounds, evaluate drug candidates' tissue damaging effects, and investigate their corresponding action mechanisms. Prioritized compounds in Shennong's prediction results include FDA-approved drugs currently undergoing clinical trials for new indications, as well as drug candidates reporting anti-tumor activity. Furthermore, the tissue damaging effect prediction aligns with documented injuries and terminated discovery events. This robust and explainable framework has the potential to accelerate the drug discovery process and enhance the accuracy and efficiency of drug screening.

Triterpene-Based Prodrug for Self-Boosted Drug Release and Targeted Oral Squamous Cell Carcinoma Chemotherapy

Chemotherapy is one of the main treatments for oral squamous cell carcinoma (OSCC), especially as a combined modality approach with and after surgery or radiotherapy. Limited therapeutic efficiency and serious side effects greatly restrict the clinical performance of chemotherapeutic drugs. The development of smart nanomedicines has provided new research directions, to some extent. However, the involvement of complex carrier compositions inevitably brings biosafety concerns and greatly limits the "bench-to-bed" translation of most nanomedicines reported. In this study, a carrier-free self-assembled prodrug was fabricated by two triterpenes (glycyrrhetinic acid, GA and ginsenoside Rh2, Rh2) isolated from medicinal plants, licorice, and ginseng, for the targeted and highly effective treatment of OSCC. Reactive oxygen species (ROS) self-supplied molecule TK-GA2 was synthesized with ROS-responsive thioketal linker and prodrug was prepared by a rapid-solvent-exchange method with TK-GA2 and Rh2. After administration, oral tumor cells transported large amounts of prodrugs with glucose ligands competitively. Endogenous ROS in oral tumor cells then promoted the release of GA and Rh2. GA further evoked the generation of a large number of ROS to help self-boosted drug release and increase oxidative stress, synergistically causing tumor cell apoptosis with Rh2. Overall, this carrier-free triterpene-based prodrug might provide a preeminent opinion on the design of effective chemotherapeutics with low systemic toxicity against OSCC.

Based on scRNA-seq and bulk RNA-seq to establish tumor immune microenvironment-associated signature of skin melanoma and predict immunotherapy response

Skin cutaneous melanoma (SKCM), a form of skin cancer, ranks among the most formidable and lethal malignancies. Exploring tumor microenvironment (TME)-based prognostic indicators would help improve the efficacy of immunotherapy for SKCM patients. This study analyzed SKCM scRNA-seq data to cluster non-malignant cells that could be used to explore the TME into nine immune/stromal cell types, including B cells, CD4 T cells, CD8 T cells, dendritic cells, endothelial cells, Fibroblasts, macrophages, neurons, and natural killer (NK) cells. Using data from The Cancer Genome Atlas (TCGA), we employed SKCM expression profiling to identify differentially expressed immune-associated genes (DEIAGs), which were then incorporated into weighted gene co-expression network analysis (WGCNA) to investigate TME-associated hub genes. Discover candidate small molecule drugs based on pivotal genes. Tumor immune microenvironment-associated genes (TIMAGs) for constructing TIMAS were identified and validated. Finally, the characteristics of TIAMS subgroups and the ability of TIMAS to predict immunotherapy outcomes were analyzed. We identified five TIMAGs (CD86, CD80, SEMA4D, C1QA, and IRF1) and used them to construct TIMAS. In addition, five potential SKCM drugs were identified. The results showed that TIMAS-low patients were associated with immune-related signaling pathways, high MUC16 mutation frequency, high T cell infiltration, and M1 macrophages, and were more favorable for immunotherapy. Collectively, TIMAS constructed by comprehensive analysis of scRNA-seq and bulk RNA-seq data is a promising marker for predicting ICI treatment outcomes and improving individualized therapy for SKCM patients.

Parbendazole as a promising drug for inducing differentiation of acute myeloid leukemia cells with various subtypes

Acute myeloid leukemia (AML) is a malignancy characterized by differentiation arrest of hematopoietic precursor cells. Differentiation therapy is effective for patients with acute promyelocytic leukemia; however, only a few effective differentiation therapies have been established for patients with other AML subtypes. In this study, seven benzimidazole anthelmintics were examined to determine the effects of differentiation on AML cells. The expression of monocyte markers (CD11b and CD14) was elevated after treatment with most benzimidazole anthelmintics. Among these drugs, parbendazole (PBZ) induced AML cell differentiation at low concentration. PBZ induced the monocyte marker expression, KLF4/DPYSL2A gene expression, and apoptosis for 21 AML cell lines with various subtypes and a primary AML sample. Finally, an in vivo analysis using an AML patient-derived xenograft mouse model showed a significant decrease in the chimerism level and prolonged survival in PBZ-treated mice. These findings could lead to a more effective differentiation therapy for AML.

Abnormal expression and related regulatory mechanism of long noncoding RNA in head and neck squamous cell carcinoma

OBJECTIVE

The objective of this study was to investigate the effect and mechanism of long noncoding RNA (lncRNA) on head and neck squamous cell carcinoma (HNSCC).

STUDY DESIGN

RNA was extracted from HNSCC tissue and adjacent tissues and sequenced. Differentially expressed lncRNA and microRNA (miRNA) were screened. Quantitative real-time polymerase chain reaction was used to compare the expression of target lncRNA between human oral keratinocyte (HOK) and cancer cell lines. LAMB1-210 in SCC-4 and CAL-27 cells was downregulated by transfecting short hairpin RNA (shRNA). Methyl thiazolyl tetrazolium, wound healing, and Transwell assay were used to evaluate viability, migration, and invasion ability in SCC-4 and CAL-27 cells.

RESULTS

Eighty-one lncRNAs were differentially expressed, of which 40 were upregulated, 41 were downregulated, and 280 miRNAs were differentially expressed. Compared with HOK cells, the expression of LAMB1-210 was significantly upregulated in FADU, SCC-4, and CAL-27 cells (P < .001). LAMB1-210 was successfully downregulated by shRNA-LAMB1-210 (P < .001), and downregulated LAMB1-210 inhibited the cell viability, migration, and invasion ability of SCC-4 and CAL-27 cells (P < .001).

CONCLUSIONS

The expression of lncRNA and miRNA in HNSCC tissues differs from that in normal tissues. LAMB1-210 is significantly overexpressed in tumor cells and is related to their survival, migration, and invasion.

A novel prognostic signature and potential therapeutic drugs based on tumor immune microenvironment characterization in breast cancer

Tumor microenvironment (TME) is closely correlated to the occurrence and progression of breast cancer, however its potentiality in assisting diagnosis and therapeutic decision remains unclear. Therefore, the major aim of this study is to explore the prognostic value of TME related gene in breast cancer. Expression matrices and clinical data of breast cancer obtained from public databases were divided into TME relevant clusters according to immune characterization. A 12-gene molecular classifier was generated through the utilization of differentially expressed genes identified between distinct Tumor Microenvironment (TME) clusters, coupled with correlative regression analysis. The performance of this TME-driven prognostic signature (TPS) were examined across both the training and validation cohorts. Furthermore, our study revealed that breast cancer cases classified as high-risk based on the TPS exhibited the phenotype with elevated immune cell infiltration, higher tumor mutational burden, and a notably worse overall prognostic outcome. To conclude, the novel TME-based TPS was able to serve as a superior prognosis indicator for breast cancer, alone or jointly with other clinical factors. Also, breast cancer patients belong to different risk subgroups of TPS were found potentially suitable for distinguished therapeutic agents, which might improve personalized treatment for breast cancer in the future.

Bioinformatic identification of hub genes Myd88 and Ccl3 and TWS-119 as a potential agent for the treatment of massive cerebral infarction

Background

Massive cerebral infarction (MCI) causes severe neurological deficits, coma and can even result in death. Here, we identified hub genes and pathways after MCI by analyzing microarray data from a murine model of ischemic stroke and identified potential therapeutic agents for the treatment of MCI.

Methods

Microarray expression profiling was performed using the GSE28731 and GSE32529 datasets from the Gene Expression Omnibus (GEO) database. Data from a sham group (n = 6 mice) and a middle cerebral artery occlusion (MCAO) group (n = 7 mice) were extracted to identify common differentially expressed genes (DEGs). After identifying gene interactions, we generated a protein-protein interaction (PPI) network with Cytoscape software. Then, the MCODE plug-in in Cytoscape was used to determine key sub-modules according to MCODE scores. Enrichment analyses were then conducted on DEGs in the key sub-modules to evaluate their biological functions. Furthermore, hub genes were identified by generating the intersections of several algorithms in the cytohubba plug-in; these genes were then verified in other datasets. Finally, we used Connectivity MAP (CMap) to identify potential agents for MCI therapy.

Results

A total of 215 common DEGs were identified and a PPI network was generated with 154 nodes and 947 edges. The most significant key sub-module had 24 nodes and 221 edges. Gene ontology (GO) analysis showed that the DEGs in this sub-module showed enrichment in inflammatory response, extracellular space and cytokine activity in terms of biological process, cellular component and molecular function, respectively. Kyoto Encyclopedia of Genes and Genomes (KEGG) analysis revealed that TNF signaling was the most enriched pathway. Myd88 and Ccl3 were identified as hub genes and TWS-119 was identified as the most potential therapeutic agent by CMap.

Conclusions

Bioinformatic analysis identified two hub genes (Myd88 and Ccl3) for ischemic injury. Further analysis identified TWS-119 as the best potential candidate for MCI therapy and that this target may be associated with TLR/MyD88 signaling.

Benzimidazole-carbamate anthelmintics: Perspective candidates for the anticancer drug development

Cellular oncogenesis involves a complex interplay between the several synchronized, interdependent pathways that collectively determine the pathogenesis and pathophysiology of cancer. Limited therapeutic success with the existing anticancer drugs drew huge interest in the design and development of new pharmacophores with improved clinical efficacy, however despite huge investments in anticancer RD; the average number of Food and Drug Administration-approved anticancer drugs declined since the 1990s. The contemporary anticancer medications possess high attrition rates, bear substantial costs, and experience low efficacy owing to the drug resistance expressed by the aggressive tumors. Mainly, the translation of novel candidate anticancer drugs into clinical practice, their commercialization, and transformation from the bench to bedside require a long timeframe of 10-15 years and capital worth millions of dollars. The repurposing strategy substantially accelerated the anticancer drug development regime as the approved drugs with tested safety and efficacy ensure a minimal risk of failure, and nominal R&D expenses as anticipated for the newly identified candidate drugs yet to enter the clinical trials. In addition, the repurposed drugs ensure a rapid clinical translation due to a validated clinical profile and their ability to target the identified hallmarks and hitherto unknown vulnerabilities of cancer. The flagship project "Repurposing Drugs in Oncology" (ReDO) identified 268 "hard repurposing" noncancer medications as candidate drugs with a promising anticancer profile (https://www.anticancerfund.org/en/redo-db). However, the generic profile of 84% of repurposed drugs in ReDO data set discourages the commercial sponsors from funding the repurposing trials, especially the Phase III efficacy trials that require significant capital.