Pharmacodynamic mechanisms of anti-inflammatory drugs on the chemosensitization of multidrug-resistant cancers and the pharmacogenetics effectiveness

Advances in skin gene therapy: utilizing innovative dressing scaffolds for wound healing, a comprehensive review

The skin, serving as the body's outermost layer, boasts a vast area and intricate structure, functioning as the primary barrier against external threats. Disruptions in the composition and functionality of the skin can lead to a diverse array of skin conditions, such as wounds, burns, and diabetic ulcers, along with inflammatory disorders, infections, and various types of skin cancer. These disorders not only exacerbate concerns regarding skin health and beauty but also have a significant impact on mental well-being. Due to the complexity of these disorders, conventional treatments often prove insufficient, necessitating the exploration of new therapeutic approaches. Researchers develop new therapies by deciphering these intricacies and gaining a thorough understanding of the protein networks and molecular processes in skin. A new window of opportunity has opened up for improving wound healing processes because of recent advancements in skin gene therapy. To enhance skin regeneration and healing, this extensive review investigates the use of novel dressing scaffolds in conjunction with gene therapy approaches. Scaffolds that do double duty as wound protectors and vectors for therapeutic gene delivery are being developed using innovative biomaterials. To improve cellular responses and speed healing, these state-of-the-art scaffolds allow for the targeted delivery and sustained release of genetic material. The most recent developments in gene therapy techniques include RNA interference, CRISPR-based gene editing, and the utilization of viral and non-viral vectors in conjunction with scaffolds, which were reviewed here to overcome skin disorders and wound complications. In the future, there will be rare chances to develop custom methods for skin health care thanks to the combination of modern technology and collaboration among disciplines.

Intelligent berberine-loaded erythrocytes attenuated inflammatory cytokine productions in macrophages

Erythrocytes are impressive tools for drug delivery, especially to macrophages. Therefore, berberine was loaded into erythrocytes using both hypotonic pre-swelling and endocytosis methods to target macrophages. Physicochemical and kinetic parameters of the resulting carrier cells, such as drug loading/release kinetics, osmotic fragility, and hematological indices, were determined. Drug loading was optimized for the study using Taguchi experimental design and lab experiments. Loaded erythrocytes were targeted to macrophages using ZnCl2 and bis-sulfosuccinimidyl-suberate, and targeting was evaluated using flow cytometry and Wright-Giemsa staining. Differentiated macrophages were stimulated with lipopolysaccharide, and the inflammatory profiles of macrophages were evaluated using ELISA, western blotting, and real-time PCR. Findings indicated that the endocytosis method is preferred due to its low impact on the erythrocyte's structural integrity. Maximum loading achieved (1386.68 ± 22.43 μg/ml) at 1500 μg/ml berberine treatment at 37 °C for 2 h. Berberine successfully inhibited NF-κB translation in macrophages, and inflammatory response markers such as IL-1β, IL-8, IL-23, and TNF-α were decreased by approximately ninefold, sixfold, twofold, eightfold, and twofold, respectively, compared to the LPS-treated macrophages. It was concluded that berberine-loaded erythrocytes can effectively target macrophages and modulate the inflammatory response.

Epigenetic disruption of histone deacetylase-2 accelerated apoptotic signaling and retarded malignancy in gastric cells

Background: The objective of this research was to determine whether HDAC2 function is associated with gastric cancer progression. Methods: HDAC2 was knocked out in EPG85.257 cells using CRISPR/Cas9 and tumorigenesis pathways were evaluated. Results: Cell proliferation, colony formation, wound healing and transwell invasion were inhibited in ΔHDAC2:EPG85.257 cells. Quantitative analyses revealed a significant downregulation of MMP1, p53, Bax, MAPK1, MAPK3, pro-Caspase3, ERK1/2, p-ERK1/2, AKT1/2/3, p-AKT1/2/3, p-NF-κB (p65), Twist, Snail and p-FAK transcripts/proteins, while SIRT1, PTEN, p21 and Caspase3 were upregulated in ΔHDAC2:EPG85.257 cells. Conclusion: These results indicated that HDAC2 enhanced migration, colony formation and transmigration ability. HDAC2 inhibition may improve gastric cancer chemotherapy pathways.

Enhanced Sensitivity of A549 Cells to Doxorubicin with WS2 and WSe2 Nanosheets via the Induction of Autophagy

The excellent physicochemical properties of two-dimensional transition-metal dichalcogenides (2D TMDCs) such as WS2 and WSe2 provide potential benefits for biomedical applications, such as drug delivery, photothermal therapy, and bioimaging. WS2 and WSe2 have recently been used as chemosensitizers; however, the detailed molecular basis underlying WS2- and WSe2-induced sensitization remains elusive. Our recent findings showed that 2D TMDCs with different thicknesses and different element compositions induced autophagy in normal human bronchial epithelial cells and mouse alveolar macrophages at sublethal concentrations. Here, we explored the mechanism by which WS2 and WSe2 act as sensitizers to increase lung cancer cell susceptibility to chemotherapeutic agents. The results showed that WS2 and WSe2 enhanced autophagy flux in A549 lung cancer cells at sublethal concentrations without causing significant cell death. Through the autophagy-specific RT2 Profiler PCR Array, we identified the genes significantly affected by WS2 and WSe2 treatment. Furthermore, the key genes that play central roles in regulating autophagy were identified by constructing a molecular interaction network. A mechanism investigation uncovered that WS2 and WSe2 activated autophagy-related signaling pathways by interacting with different cell surface proteins or cytoplasmic proteins. By utilizing this mechanism, the efficacy of the chemotherapeutic agent doxorubicin was enhanced by WS2 and WSe2 pre-treatment in A549 lung cancer cells. This study revealed a feature of WS2 and WSe2 in cancer therapy, in which they eliminate the resistance of A549 lung cancer cells against doxorubicin, at least partially, by inducing autophagy.

Targeting cancer-related inflammation with non-steroidal anti-inflammatory drugs: Perspectives in pharmacogenomics

Inflammatory processes are essential for innate immunity and contribute to carcinogenesis in various malignancies, such as colorectal cancer, esophageal cancer and lung cancer. Pharmacotherapies targeting inflammation have the potential to reduce the risk of carcinogenesis and improve therapeutic efficacy of existing anti-cancer treatment. Non-steroidal anti-inflammatory drugs (NSAIDs), comprising a variety of structurally different chemicals that can inhibit cyclooxygenase (COX) enzymes and other COX-independent pathways, are originally used to treat inflammatory diseases, but their preventive and therapeutic potential for cancers have also attracted researchers' attention. Pharmacogenomic variability, including distinct genetic characteristics among different patients, can significantly affect pharmacokinetics and effectiveness of NSAIDs, which might determine the preventive or therapeutic success for cancer patients. Hence, a more comprehensive understanding in pharmacogenomic characteristics of NSAIDs and cancer-related inflammation would provide new insights into this appealing strategy. In this review, the up-to-date advances in clinical and experimental researches targeting cancer-related inflammation with NSAIDs are presented, and the potential of pharmacogenomics are discussed as well.

Comparison of effects of aminosalicylic acid, glucocorticoids and immunosuppressive agents on the expression of multidrug-resistant genes in ulcerative colitis

To compare the effects of aminosalicylic acid, glucocorticoids and immunosuppressants on the expression levels of multidrug resistance genes in patients with ulcerative colitis (UC), with the aim of providing a theoretical and therapeutic basis for the diagnosis, treatment, and prevention of UC. Fresh colonic mucosal tissues or postoperative pathological biopsies from 148 UC patients were collected, and the distribution sites and morphology of P-glycoprotein (P-gp) were detected using immunohistochemical staining. RT-PCR was used to quantify the expression levels of multidrug resistance gene (MDR1) mRNA before and after the corresponding treatment, and the effects of aminosalicylic acid, glucocorticoids and immunosuppressive drugs on P-gp were compared. In addition, the effects of the three drugs on MDR1 mRNA were analyzed. Administration of 5-aminosalicylic acid (5-ASA) drugs did not correlate with MDR1 expression in UC, whereas administration of glucocorticoids and immunosuppressive drugs was positively correlated with MDR1 expression profile. The expression levels of MDR1 mRNA and its product P-gp were significantly upregulated in patients who did not respond to glucocorticoids and immunosuppressive drugs. 5-ASA had no effect on the expression levels of MDR1 and its product P-gp in patients with a confirmed diagnosis of UC. However, the use of glucocorticoids and immunosuppressants can increase the expression level of MDR1.

Interactions of Analgesics with Cisplatin: Modulation of Anticancer Efficacy and Potential Organ Toxicity

Cisplatin (CDDP), one of the most eminent cancer chemotherapeutic agents, has been successfully used to treat more than half of all known cancers worldwide. Despite its effectiveness, CDDP might cause severe toxic adverse effects on multiple body organs during cancer chemotherapy, including the kidneys, heart, liver, gastrointestinal tract, and auditory system, as well as peripheral nerves causing severely painful neuropathy. The latter, among other pains patients feel during chemotherapy, is an indication for the use of analgesics during treatment with CDDP. Different types of analgesics, such as acetaminophen, non-steroidal anti-inflammatory drugs (NSAIDS), and narcotic analgesics, could be used according to the severity of pain. Administered analgesics might modulate CDDP’s efficacy as an anticancer drug. NSAIDS, on one hand, might have cytotoxic effects on their own and few of them can potentiate CDDP’s anticancer effects via inhibiting the CDDP-induced cyclooxygenase (COX) enzyme, or through COX-independent mechanisms. On the other hand, some narcotic analgesics might ameliorate CDDP’s anti-neoplastic effects, causing chemotherapy to fail. Concerning safety, some analgesics share the same adverse effects on normal tissues as CDDP, augmenting its potentially hazardous effects on organ impairment. This article offers an overview of the reported literature on the interactions between analgesics and CDDP, paying special attention to possible mechanisms that modulate CDDP’s cytotoxic efficacy and potential adverse reactions.

PPDTS: Predicting potential drug-target interactions based on network similarity

Identification of drug–target interactions (DTIs) has great practical importance in the drug discovery process for known diseases. However, only a small proportion of DTIs in these databases has been verified experimentally, and the computational methods for predicting the interactions remain challenging. As a result, some effective computational models have become increasingly popular for predicting DTIs. In this work, the authors predict potential DTIs from the local structure of drug–target associations' network, which is different from the traditional global network similarity methods based on structure and ligand. A novel method called PPDTS is proposed to predict DTIs. First, according to the DTIs’ network local structure, the known DTIs are converted into a binary network. Second, the Resource Allocation algorithm is used to obtain a drug–drug similarity network and a target–target similarity network. Third, a Collaborative Filtering algorithm is used with the known drug–target topology information to obtain similarity scores. Fourth, the linear combination of drug–target similarity model and the target–drug similarity model are innovatively proposed to obtain the final prediction results. Finally, the experimental performance of PPDTS has proved to be higher than that of the previously mentioned four popular network‐based similarity methods, which is validated in different experimental datasets. Some of the predicted results can be supported in UniProt and DrugBank databases.