Restriction of drug transport by the tumor environment

A novel diabetic foot ulcer diagnostic model: identification and analysis of genes related to glutamine metabolism and immune infiltration

BACKGROUND

Diabetic foot ulcer (DFU) is one of the most common and severe complications of diabetes, with vascular changes, neuropathy, and infections being the primary pathological mechanisms. Glutamine (Gln) metabolism has been found to play a crucial role in diabetes complications. This study aims to identify and validate potential Gln metabolism biomarkers associated with DFU through bioinformatics and machine learning analysis.

METHODS

We downloaded two microarray datasets related to DFU patients from the Gene Expression Omnibus (GEO) database, namely GSE134431, GSE68183, and GSE80178. From the GSE134431 dataset, we obtained differentially expressed Gln-metabolism related genes (deGlnMRGs) between DFU and normal controls. We analyzed the correlation between deGlnMRGs and immune cell infiltration status. We also explored the relationship between GlnMRGs molecular clusters and immune cell infiltration status. Notably, WGCNA to identify differentially expressed genes (DEGs) within specific clusters. Additionally, we conducted GSVA to annotate enriched genes. Subsequently, we constructed and screened the best machine learning model. Finally, we validated the predictions' accuracy using a nomogram, calibration curves, decision curve analysis (DCA), and the GSE134431, GSE68183, and GSE80178 dataset.

RESULTS

In both the DFU and normal control groups, we confirmed the presence of deGlnMRGs and an activated immune response. From the GSE134431 dataset, we obtained 20 deGlnMRGs, including CTPS1, NAGS, SLC7A11, GGT1, GCLM, RIMKLA, ARG2, ASL, ASNS, ASNSD1, PPAT, GLS2, GLUD1, MECP2, ASS1, PRODH, CTPS2, ALDH5A1, DGLUCY, and SLC25A12. Furthermore, two clusters were identified in DFU. Immune infiltration analysis indicated the presence of immune heterogeneity in these two clusters. Additionally, we established a Support Vector Machine (SVM) model based on 5 genes (R3HCC1, ZNF562, MFN1, DRAM1, and PTGDS), which exhibited excellent performance on the external validation datasetGSE134431, GSE68183, and GSE80178 (AUC = 0.929).

CONCLUSION

This study has identified five Gln metabolism genes associated with DFU, revealing potential novel biomarkers and therapeutic targets for DFU. Additionally, the infiltration of immune-inflammatory cells plays a crucial role in the progression of DFU.

Glutamine metabolism-related genes and immunotherapy in nonspecific orbital inflammation were validated using bioinformatics and machine learning

BACKGROUND

Nonspecific orbital inflammation (NSOI) is an idiopathic, persistent, and proliferative inflammatory condition affecting the orbit, characterized by polymorphous lymphoid infiltration. Its pathogenesis and progression have been linked to imbalances in tumor metabolic pathways, with glutamine (Gln) metabolism emerging as a critical aspect in cancer. Metabolic reprogramming is known to influence clinical outcomes in various malignancies. However, comprehensive research on glutamine metabolism's significance in NSOI is lacking.

METHODS

This study conducted a bioinformatics analysis to identify and validate potential glutamine-related molecules (GlnMgs) associated with NSOI. The discovery of GlnMgs involved the intersection of differential expression analysis with a set of 42 candidate GlnMgs. The biological functions and pathways of the identified GlnMgs were analyzed using GSEA and GSVA. Lasso regression and SVM-RFE methods identified hub genes and assessed the diagnostic efficacy of fourteen GlnMgs in NSOI. The correlation between hub GlnMgs and clinical characteristics was also examined. The expression levels of the fourteen GlnMgs were validated using datasets GSE58331 and GSE105149.

RESULTS

Fourteen GlnMgs related to NSOI were identified, including FTCD, CPS1, CTPS1, NAGS, DDAH2, PHGDH, GGT1, GCLM, GLUD1, ART4, AADAT, ASNSD1, SLC38A1, and GFPT2. Biological function analysis indicated their involvement in responses to extracellular stimulus, mitochondrial matrix, and lipid transport. The diagnostic performance of these GlnMgs in distinguishing NSOI showed promising results.

CONCLUSIONS

This study successfully identified fourteen GlnMgs associated with NSOI, providing insights into potential novel biomarkers for NSOI and avenues for monitoring disease progression.

Bioinformatics and machine learning were used to validate glutamine metabolism-related genes and immunotherapy in osteoporosis patients

BACKGROUND

Osteoporosis (OP), often referred to as the "silent disease of the twenty-first century," poses a significant public health concern due to its severity, chronic nature, and progressive course, predominantly affecting postmenopausal women and elderly individuals. The pathogenesis and progression of this disease have been associated with dysregulation in tumor metabolic pathways. Notably, the metabolic utilization of glutamine has emerged as a critical player in cancer biology. While metabolic reprogramming has been extensively studied in various malignancies and linked to clinical outcomes, its comprehensive investigation within the context of OP remains lacking.

METHODS

This study aimed to identify and validate potential glutamine metabolism genes (GlnMgs) associated with OP through comprehensive bioinformatics analysis. The identification of GlnMgs was achieved by integrating the weighted gene co-expression network analysis and a set of 28 candidate GlnMgs. Subsequently, the putative biological functions and pathways associated with GlnMgs were elucidated using gene set variation analysis. The LASSO method was employed to identify key hub genes, and the diagnostic efficacy of five selected GlnMgs in OP detection was assessed. Additionally, the relationship between hub GlnMgs and clinical characteristics was investigated. Finally, the expression levels of the five GlnMgs were validated using independent datasets (GSE2208, GSE7158, GSE56815, and GSE35956).

RESULTS

Five GlnMgs, namely IGKC, TMEM187, RPS11, IGLL3P, and GOLGA8N, were identified in this study. To gain insights into their biological functions, particular emphasis was placed on synaptic transmission GABAergic, inward rectifier potassium channel activity, and the cytoplasmic side of the lysosomal membrane. Furthermore, the diagnostic potential of these five GlnMgs in distinguishing individuals with OP yielded promising results, indicating their efficacy as discriminative markers for OP.

CONCLUSIONS

This study discovered five GlnMgs that are linked to OP. They shed light on potential new biomarkers for OP and tracking its progression.

Glutamine metabolism genes prognostic signature for stomach adenocarcinoma and immune infiltration: potential biomarkers for predicting overall survival

Background

Stomach adenocarcinoma (STAD), caused by mutations in stomach cells, is characterized by poor overall survival. Chemotherapy is commonly administered for stomach cancer patients following surgical resection. An imbalance in tumor metabolic pathways is connected to tumor genesis and growth. It has been discovered that glutamine (Gln) metabolism plays a crucial role in cancer. Metabolic reprogramming is associated with clinical prognosis in various cancers. However, the role of glutamine metabolism genes (GlnMgs) in the fight against STAD remains poorly understood.

Methods

GlnMgs were determined in STAD samples from the TCGA and GEO datasets. The TCGA and GEO databases provide information on stemness indices (mRNAsi), gene mutations, copy number variations (CNV), tumor mutation burden (TMB), and clinical characteristics. Lasso regression was performed to build the prediction model. The relationship between gene expression and Gln metabolism was investigated using co-expression analysis.

Results

GlnMgs, found to be overexpressed in the high-risk group even in the absence of any symptomatology, demonstrated strong predictive potential for STAD outcomes. GSEA highlighted immunological and tumor-related pathways in the high-risk group. Immune function and m6a gene expression differed significantly between the low- and high-risk groups. AFP, CST6, CGB5, and ELANE may be linked to the oncology process in STAD patients. The prognostic model, CNVs, single nucleotide polymorphism (SNP), and medication sensitivity all revealed a strong link to the gene.

Conclusion

GlnMgs are connected to the genesis and development of STAD. These corresponding prognostic models aid in predicting the prognosis of STAD GlnMgs and immune cell infiltration in the tumor microenvironment (TME) may be possible therapeutic targets in STAD. Furthermore, the glutamine metabolism gene signature presents a credible alternative for predicting STAD outcomes, suggesting that these GlnMgs could open a new field of study for STAD-focused therapy Additional trials are needed to validate the results of the current study.

Breaking through the barrier: Modelling and exploiting the physical microenvironment to enhance drug transport and efficacy

Pharmaceutical compounds are the main pillar in the treatment of various illnesses. To administer these drugs in the therapeutic setting, multiple routes of administration have been defined, including ingestion, inhalation, and injection. After administration, drugs need to find their way to the intended target for high effectiveness, and this penetration is greatly dependent on obstacles the drugs encounter along their path. Key hurdles include the physical barriers that are present within the body and knowledge of those is indispensable for progress in the development of drugs with increased therapeutic efficacy. In this review, we examine several important physical barriers, such as the blood-brain barrier, the gut-mucosal barrier, and the extracellular matrix barrier, and evaluate their influence on drug transport and efficacy. We explore various in vitro model systems that aid in understanding how parameters within the barrier model affect drug transfer and therapeutic effect. We conclude that physical barriers in the body restrict the quantity of drugs that can pass through, mainly as a consequence of the barrier architecture. In addition, the specific physical properties of the tissue can trigger intracellular changes, altering cell behavior in response to drugs. Though the barriers negatively influence drug distribution, physical stimulation of the surrounding environment may also be exploited as a mechanism to control drug release. This drug delivery approach is explored in this review as a potential alternative to the conventional ways of delivering therapeutics.

Peptide dendrimers as potentiators of conventional chemotherapy in the treatment of pancreatic cancer in a mouse model

Chemotherapy is the recommended treatment for patients with advanced pancreatic ductal adenocarcinoma (PDAC). However, efficacy of traditional chemotherapy is not satisfactory due to the presence of a dense dysplastic tumor stroma which prevents drug accumulation in and deep penetration into tumors. To overcome these obstacles, we designed and synthesized peptide dendrimers as potentiators of conventional chemotherapy. The dendrimers markedly promoted free doxorubicin accumulation and penetration deeply into 3D multicellular PDAC tumor cultures upon co-incubation. Co-administration of the dendrimer and doxorubicin into PDAC tumor xenograft-bearing mice greatly increased the doxorubicin concentration in the tumor. In addition, the dendrimer also promoted free doxorubicin internalization into PDAC cells upon co-incubation in media mimicking tumor microenvironment. Finally, a significant enhancement in the anticancer efficacy of doxorubicin and gemcitabine when either of the drugs was individually co-administered with the dendrimer into PDAC tumor xenograft-bearing mice was observed. This was especially pronounced for the combination treatment with the dendrimer and gemcitabine, resulting in a tumor weight decrease to 12.9% compared to the treatment with gemcitabine alone. This can be attributed to the combination of the multi-functionalities of the dendrimer, i.e., promoting free drug accumulation and penetration deeply into tumors and internalization into cancer cells.

YAP/TAZ Suppress Drug Penetration Into Hepatocellular Carcinoma Through Stromal Activation

BACKGROUND AND AIMS

HCC is the most predominant type of liver cancer affecting 800,000 people globally each year. Various small-molecule compounds targeting diverse oncogenic signaling pathways have been tested for patients with HCC, and clinical outcomes were not satisfactory. In this study, we investigated molecular signaling that determines the efficiency of drug delivery into HCC.

APPROACH AND RESULTS

Hydrodynamics-based transfection (HT) was performed to develop mouse models for HCC induced by various oncogenes. Mice bearing liver cancer were treated with verteporfin at 5 weeks after HT. Multicellular HCC organoid (MCHO) models were established that contained various types of stromal cells, such as hepatic stellate cells, fibroblasts, and endothelial cells together with HCC cells. Tumor organoids were treated with verteporfin, and distributions of the drug in the organoids were assessed using fluorescence microscopy. Murine HCC models developed by HT methods showed that a high Yes-associated protein/Transcriptional co-activator with PDZ-binding motif (YAP/TAZ) activity in HCC cells impaired verteporfin penetration into the cancer. Activation of tumor stroma was observed in HCC with a high YAP/TAZ activity. Consistent with the findings in the in vivo models of HCC, MCHOs with activated YAP/TAZ signaling showed stromal activation and impaired penetration of verteporfin into the tumor organoids. Inhibition of YAP/TAZ transcriptional activity in HCC cells significantly increased drug penetration into the MCHO.

CONCLUSIONS

Drug delivery into liver cancer is impaired by YAP/TAZ signaling in tumor cells and subsequent activation of stroma by the signaling. Disrupting or targeting activated tumor stroma might improve drug delivery into HCC with an elevated YAP/TAZ activity.

Co-administration of a branched arginine-rich polymer enhances the anti-cancer efficacy of doxorubicin

The severe side-effects and drug resistance development of conventional chemotherapy are mainly caused by poor tumor penetration as well as nonspecific biodistribution and insufficient cellular uptake of drugs. Herein a branched arginine-rich polymer was synthesized and co-administration of this polymer with doxorubicin, a model drug of chemotherapeutic agents, overcame simultaneously the three obstacles shown above. Co-incubation of the polymer promoted doxorubicin penetration deeply into multicellular tumor spheroids and internalization into cancer cells. Upon co-injection of the polymer with doxorubicin into tumor-bearing mice, the enhanced drug accumulation in and deep penetration into tumor tissue were observed compared to injection of doxorubicin alone. A combined therapy of doxorubicin and the polymer in the treatment of tumor-bearing mice showed a marked enhancement in anticancer efficacy compared to doxorubicin alone. Notably, the treatment with the combination regime reduced the doxorubicin dose to one fifth without reducing the antitumor efficacy compared to the treatment with doxorubicin alone. The possible mechanism of action of the polymer was postulated, in which the guanidinium groups of arginine residues in the polymer may play a pivotal role in the action.

Mechanisms of the antiangiogenic effects of aspirin in cancer

Aspirin is an old drug extracted from willow bark and is widely used for the prevention and treatment of cardiovascular diseases. Accumulating evidence has shown that aspirin use may significantly reduce the angiogenesis of cancer; however, the mechanism of the association between angiogenesis and aspirin is complex. Although COX-1 is widely known as a target of aspirin, several studies reveal other antiangiogenic targets of aspirin, such as angiotensin II, glucose transporter 1, heparanase, and matrix metalloproteinase. In addition, some data indicates that aspirin may produce antiangiogenic effects after acting in different cell types, such as endothelial cells, platelets, pericytes, and macrophages. In this review, we concentrate on research regarding the antiangiogenic effects of aspirin in cancer, and we discuss the molecular mechanisms of aspirin and its metabolites. Moreover, we discuss some mechanisms through which aspirin treatment may normalize existing blood vessels, including preventing the disintegration of endothelial adheres junctions and the recruitment of pericytes. We also address the antiangiogenic effects and the underlying mechanisms of aspirin derivatives, which are aimed at improving safety and efficacy.

Combined cancer therapeutics-Tackling the complexity of the tumor microenvironment

Cancer treatment has yet to find a "silver bullet" capable of selectively and effectively kill tumor cells without damaging healthy cells. Nanomedicine is a promising field that can combine several moieties in one system to produce a multifaceted nanoplatform. The tumor microenvironment (TME) is considered responsible for the ineffectiveness of cancer therapeutics and the difficulty in the translation from the bench to bed side of novel nanomedicines. A promising approach is the use of combinatorial therapies targeting the TME with the use of stimuli-responsive nanomaterials which would increase tumor targeting. Contemporary combined strategies for TME-targeting nanoformulations are based on the application of external stimuli therapies, such as photothermy, hyperthermia or ultrasounds, in combination with stimuli-responsive nanoparticles containing a core, usually composed by metal oxides or graphene, and a biocompatible stimuli-responsive coating layer that could also contain tumor targeting moieties and a chemotherapeutic agent to enhance the therapeutic efficacy. The obstacles that nanotherapeutics must overcome in the TME to accomplish an effective therapeutic cargo delivery and the proposed strategies for improved nanotherapeutics will be reviewed. This article is categorized under: Therapeutic Approaches and Drug Discovery > Nanomedicine for Oncologic Disease Nanotechnology Approaches to Biology > Nanoscale Systems in Biology Therapeutic Approaches and Drug Discovery > Emerging Technologies.

3D cultures for modeling nanomaterial-based photothermal therapy

Photothermal therapy (PTT) is one of the most promising techniques for cancer tumor ablation. Nanoparticles are increasingly being investigated for use with PTT and can serve as theranostic agents. Based on the ability of near-infrared nano-photo-absorbers to generate heat under laser irradiation, PTT could prove advantageous in certain situations over more classical cancer therapies. To analyze the efficacy of nanoparticle-based PTT, preclinical in vitro studies typically use 2D cultures, but this method cannot completely mimic the complex tumor organization, bioactivity, and physiology that all control the complex penetration depth, biodistribution, and tissue diffusion parameters of nanomaterials in vivo. To fill this knowledge gap, 3D culture systems have been explored for PTT analysis. These models provide more realistic microenvironments that allow spatiotemporal oxygen gradients and cancer cell adaptations to be considered. This review highlights the work that has been done to advance 3D models for cancer microenvironment modeling, specifically in the context of advanced, functionalized nanoparticle-directed PTT.

Cell-in-Cell Phenomenon and Its Relationship With Tumor Microenvironment and Tumor Progression: A Review

The term cell-in-cell, morphologically, refers to the presence of one cell within another. This phenomenon can occur in tumors but also among non-tumor cells. The cell-in-cell phenomenon was first observed 100 years ago, and it has since been found in a variety of tumor types. Recently, increasing attention has been paid to this phenomenon and the underlying mechanism has gradually been elucidated. There are three main related process: cannibalism, emperipolesis, and entosis. These processes are affected by many factors, including the tumor microenvironment, mitosis, and genetic factors. There is considerable evidence to suggest that the cell-in-cell phenomenon is associated with the prognosis of cancers, and it promotes tumor progression in most situations. Notably, in pancreatic cancer, the cell-in-cell phenomenon is associated with reduced metastasis, which is the opposite of what happens in other tumor types. Thus, it can also inhibit tumor progression. Studies show that cell-in-cell structure formation is affected by the tumor microenvironment, and that it may lead to changes in cellular characteristics. In this review, we summarize the different cell-in-cell processes and discuss their role in tumor progression and how they are regulated by different mechanisms.