Unraveling the potential of Morinda officinalis oligosaccharides as an adjuvant of escitalopram in depression treatment and exploring the underlying mechanisms

ETHNOPHAMACOLOGICAL RELEVANCE

Morinda officinalis oligosaccharides (MOs) is a mixture of oligosaccharides extracted from the roots of Morinda officinalis (MO). It is approved by Chinese Food and Drug Administration (CFDA) for depression treatment. MOs could improve the antidepressant efficacy of escitalopram in clinic.

AIM OF THE STUDY

We aim to explore the antidepressant activity and potential mechanism of the combination usage of MOs and escitalopram on animal model of depression.

MATERIALS AND METHODS

Depressive animal model was induced by chronic mild stress (CMS). Behavioral tests were conducted to evaluate the antidepressant efficacy of MOs and escitalopram. Serum neurotransmitter levels were detected by High-performance liquid chromatography (HPLC). Quantitative real-time PCR and Western blotting were applied to assay the hippocampus neurotrophic factors' mRNA and protein levels. Peripheral cytokines levels were measured through Enzyme-Linked Immunosorbent Assay (ELISA). Micorglia polization phenotype was assayed by immunofluorescence and flow cytometry.

RESULTS

MOs and escitalopram obviously attenuated depression-like behaviors of CMS mice. Importantly, MOs plus escitalopram exhibited better antidepressant activity on CMS mice than monotherapy. At the same time, MOs combined escitalopram treatment significantly increased hippocampus neurotransmitters and neurotrophic factor levels, stimulated hippocampus neurogenesis and relieved central nervous system (CNS) microglia over-activation of CMS mice. The combination therapy had greater effect on neuroprotection and inflammation attenuation of CMS mice than monotherapy.

CONCLUSION

Our results indicates MOs combined escitalopram might produce antidepressant activity through protecting neuron activity, relieving inflammation and modulating microglia polarization process.

Xianglian Pill combined with 5-fluorouracil enhances antitumor activity and reduces gastrointestinal toxicity in gastric cancer by regulating the p38 MAPK/NF-κB signaling pathway

ETHNOPHARMACOLOGICAL RELEVANCE

Perioperative or postoperative adjuvant chemotherapy based on 5-fluorouracil (5-FU) is a common first-line adjuvant therapy for gastric cancer (GC). However, drug resistance and the side effects of 5-FU have reduced its efficacy. Among these side effects, gastrointestinal (GI) toxicity is one of the most common. Xianglian Pill (XLP) is a Chinese patent medicine that is commonly used for the treatment of diarrhoea. It can reduce inflammation and has a protective effect on the intestinal mucosa. Recent studies have shown that many components of XLP can inhibite tumor cell growth. However, the therapeutic effect of XLP in combination with 5-FU on GC is unclear.

AIM OF THE STUDY

To investigate whether the combination of XLP and 5-FU can enhance anti-GC activity while reducing GI toxicity.

MATERIALS AND METHODS

XLP was administered orally during intraperitoneal injection of 5-FU in GC mice model. Mice were continuously monitored for diarrhea and xenograft tumor growth. After 2 weeks, the mice were sacrificed and serum was collected to determine interleukin-6 levels. Pathological changes, the expression of pro-inflammatory factors and p38 mitogen-activated protein kinase (MAPK) in GI tissue were determined by Western blot analysis. Pathological changes, apoptosis levels and p38 MAPK expression levels in xenograft tissues were also determined.

RESULTS

The results showed that XLP could alleviate GI mucosal injury caused by 5-FU, alleviated diarrhea, and inhibited the expression of nuclear factor (NF)-κB and myeloid differentiation primary response-88. Besides, XLP could promote the 5-FU-induced apoptosis of GC cells and enhance the inhibitory effect of 5-FU on tumor xenografts. Further study showed that XLP administration could regulate the expression of p38 MAPK.

CONCLUSIONS

XLP in combination with 5-FU could alleviate its GI side effects and enhance its inhibitory effect on xenograft tumor. Moreover, these effects were found to be related to the regulation of the p38 MAPK/NF-κB pathway.

Combination therapy involving HSP90 inhibitors for combating cancer: an overview of clinical and preclinical progress

The molecular chaperone heat shock protein 90 (HSP90) regulates multiple crucial signalling pathways in cancer by driving the maturation of key signalling components, thereby playing a crucial role in tumorigenesis and drug resistance in cancer. Inhibition of HSP90 results in metastable conformational collapse of its client proteins and their proteasomal degradation. Considerable efforts have been devoted to the development of small-molecule inhibitors targeting HSP90, and more than 20 inhibitors have been evaluated in clinical trials for cancer therapy. However, owing to disadvantages such as organ toxicity and drug resistance, only one HSP90 inhibitor has been approved for use in clinical settings. In recent years, HSP90 inhibitors used in combination with other anti-cancer therapies have shown remarkable potential in the treatment of cancer. HSP90 inhibitors work synergistically with various anti-cancer therapies, including chemotherapy, targeted therapy, radiation therapy and immunotherapy. HSP90 inhibitors can improve the pharmacological effects of the above-mentioned therapies and reduce treatment resistance. This review provides an overview of the use of combination therapy with HSP90 inhibitors and other anti-cancer therapies in clinical and preclinical studies reported in the past decade and summarises design strategies and prospects for these combination therapies. Altogether, this review provides a theoretical basis for further research and application of these combination therapies in the treatment of cancer.

PermuteDDS: a permutable feature fusion network for drug-drug synergy prediction

MOTIVATION

Drug combination therapies have shown promise in clinical cancer treatments. However, it is hard to experimentally identify all drug combinations for synergistic interaction even with high-throughput screening due to the vast space of potential combinations. Although a number of computational methods for drug synergy prediction have proven successful in narrowing down this space, fusing drug pairs and cell line features effectively still lacks study, hindering current algorithms from understanding the complex interaction between drugs and cell lines.

RESULTS

In this paper, we proposed a Permutable feature fusion network for Drug-Drug Synergy prediction, named PermuteDDS. PermuteDDS takes multiple representations of drugs and cell lines as input and employs a permutable fusion mechanism to combine drug and cell line features. In experiments, PermuteDDS exhibits state-of-the-art performance on two benchmark data sets. Additionally, the results on independent test set grouped by different tissues reveal that PermuteDDS has good generalization performance. We believed that PermuteDDS is an effective and valuable tool for identifying synergistic drug combinations. It is publicly available at https://github.com/littlewei-lazy/PermuteDDS .

SCIENTIFIC CONTRIBUTION

First, this paper proposes a permutable feature fusion network for predicting drug synergy termed PermuteDDS, which extract diverse information from multiple drug representations and cell line representations. Second, the permutable fusion mechanism combine the drug and cell line features by integrating information of different channels, enabling the utilization of complex relationships between drugs and cell lines. Third, comparative and ablation experiments provide evidence of the efficacy of PermuteDDS in predicting drug-drug synergy.

DRSPRING: Graph convolutional network (GCN)-Based drug synergy prediction utilizing drug-induced gene expression profile

Great efforts have been made over the years to identify novel drug pairs with synergistic effects. Although numerous computational approaches have been proposed to analyze diverse types of biological big data, the pharmacogenomic profiles, presumably the most direct proxy of drug effects, have been rarely used due to the data sparsity problem. In this study, we developed a composite deep-learning-based model that predicts the drug synergy effect utilizing pharmacogenomic profiles as well as molecular properties. Graph convolutional network (GCN) was used to represent and integrate the chemical structure, genetic interactions, drug-target information, and gene expression profiles of cell lines. Insufficient amount of pharmacogenomic data, i.e., drug-induced expression profiles from the LINCS project, was resolved by augmenting the data with the predicted profiles. Our method learned and predicted the Loewe synergy score in the DrugComb database and achieved a better or comparable performance compared to other published methods in a benchmark test. We also investigated contribution of various input features, which highlighted the value of basal gene expression and pharmacogenomic profiles of each cell line. Importantly, DRSPRING (DRug Synergy PRediction by INtegrated GCN) can be applied to any drug pairs and any cell lines, greatly expanding its applicability compared to previous methods.

Effect of Cerebralcare Granule® combined with memantine on Alzheimer's disease

ETHNOPHARMACOLOGICAL RELEVANCE

In elderly people, Alzheimer's disease (AD) is the most common form of dementia. It has been shown that traditional Chinese medicine (TCM) based on phytomedicines enhances the therapeutic effects of modern medicine when taken in conjunction with them. Modern medicine N-methyl-D-aspartate receptor (NMDA) antagonist memantine (Mm) are mainly used in the clinical treatment of AD. TCM Cerebralcare Granule® (CG) has long been an effective treatment for headaches, dizziness, and other symptoms. In this study, we employ a blend of CG and Mm to address Alzheimer's disease-like symptoms and explore their impacts and underlying mechanisms.

AIM OF THE STUDY

The objective of our study was to observe the effects of CG combined with Memantine (Mm) on learning and memory impairment of AD mice induced by D-galactose and to explore the mechanism at work.

MATERIALS AND METHODS

CG and Mm were combined to target multiple pathological processes involved in AD. For a thorough analysis, we performed various experiments such as behavioral detection, pathological detection, proteomic detection, and other experimental methods of detection.

RESULTS

It was found that the combination of CG and Mm was significantly effective for improving learning and memory in AD mice as well as brain pathology. The serum and hippocampal tissue of AD mice were significantly enhanced with catalase (CAT), superoxide dismutase (SOD), and glutathione peroxidase (GSH-Px) activities and malondialdehyde (MDA) levels were decreased with this treatment. In AD mice, a combination of Mm and CG (CG + Mm) significantly increased the levels of the anti-inflammatory factors IL-4 and IL-10, decreased the levels of pro-inflammatory factors (IL-6, IL-1β) and tumor necrosis factor-alpha (TNF-α), improved synaptic plasticity by restoring synaptophysin (SYP) and postsynaptic density protein-95 (PSD-95) expression in the hippocampus, enhanced Aβ phagocytosis of microglia in AD mice, and increased mitochondrial respiratory chain enzyme complexes I, II, III, and IV, lead to an increase in the number of functionally active NMDA receptors in the hippocampus. Proteomic analysis GO analysis showed that the positive regulation gene H3BIV5 of G protein coupled receptor signal pathway and synaptic transmission was up-regulated, while the transsynaptic signal of postsynaptic membrane potential and regulation-related gene Q5NCT9 were down-regulated. Most proteins showed significant enriched signal transduction pathway profiles after CG + Mm treatment, based on the KEGG pathway database.

CONCLUSION

The data supported the idea that CG and Mm could be more effective in treating AD mice induced by D-galactose than Mm alone. We provided a basis for the clinical use of CG with Mm.

MFSynDCP: multi-source feature collaborative interactive learning for drug combination synergy prediction

Drug combination therapy is generally more effective than monotherapy in the field of cancer treatment. However, screening for effective synergistic combinations from a wide range of drug combinations is particularly important given the increase in the number of available drug classes and potential drug-drug interactions. Existing methods for predicting the synergistic effects of drug combinations primarily focus on extracting structural features of drug molecules and cell lines, but neglect the interaction mechanisms between cell lines and drug combinations. Consequently, there is a deficiency in comprehensive understanding of the synergistic effects of drug combinations. To address this issue, we propose a drug combination synergy prediction model based on multi-source feature interaction learning, named MFSynDCP, aiming to predict the synergistic effects of anti-tumor drug combinations. This model includes a graph aggregation module with an adaptive attention mechanism for learning drug interactions and a multi-source feature interaction learning controller for managing information transfer between different data sources, accommodating both drug and cell line features. Comparative studies with benchmark datasets demonstrate MFSynDCP's superiority over existing methods. Additionally, its adaptive attention mechanism graph aggregation module identifies drug chemical substructures crucial to the synergy mechanism. Overall, MFSynDCP is a robust tool for predicting synergistic drug combinations. The source code is available from GitHub at https://github.com/kkioplkg/MFSynDCP .

High-content analysis identified synergistic drug interactions between INK128, an mTOR inhibitor, and HDAC inhibitors in a non-small cell lung cancer cell line

BACKGROUND

The development of drug resistance is a major cause of cancer therapy failures. To inhibit drug resistance, multiple drugs are often treated together as a combinatorial therapy. In particular, synergistic drug combinations, which kill cancer cells at a lower concentration, guarantee a better prognosis and fewer side effects in cancer patients. Many studies have sought out synergistic combinations by small-scale function-based targeted growth assays or large-scale nontargeted growth assays, but their discoveries are always challenging due to technical problems such as a large number of possible test combinations.

METHODS

To address this issue, we carried out a medium-scale optical drug synergy screening in a non-small cell lung cancer cell line and further investigated individual drug interactions in combination drug responses by high-content image analysis. Optical high-content analysis of cellular responses has recently attracted much interest in the field of drug discovery, functional genomics, and toxicology. Here, we adopted a similar approach to study combinatorial drug responses.

RESULTS

By examining all possible combinations of 12 drug compounds in 6 different drug classes, such as mTOR inhibitors, HDAC inhibitors, HSP90 inhibitors, MT inhibitors, DNA inhibitors, and proteasome inhibitors, we successfully identified synergism between INK128, an mTOR inhibitor, and HDAC inhibitors, which has also been reported elsewhere. Our high-content analysis further showed that HDAC inhibitors, HSP90 inhibitors, and proteasome inhibitors played a dominant role in combinatorial drug responses when they were mixed with MT inhibitors, DNA inhibitors, or mTOR inhibitors, suggesting that recessive drugs could be less prioritized as components of multidrug cocktails.

CONCLUSIONS

In conclusion, our optical drug screening platform efficiently identified synergistic drug combinations in a non-small cell lung cancer cell line, and our high-content analysis further revealed how individual drugs in the drug mix interact with each other to generate combinatorial drug response.

Combination of navitoclax (Bcl-2 and Bcl-xL inhibitor) and Debio-0932 (Hsp90 inhibitor) suppresses the viability of prostate cancer cells via induction of apoptotic signaling pathway

Prostate cancer is one of the most common cancers in men. Given the diverse nature of prostate cancer and its tendency to respond differently to various treatments, combination therapies are often employed to enhance outcomes. In this study, the synergetic efficiency of chemotherapeutic drug Navitoclax and heat shock protein 90 (Hsp90) inhibitor Debio-0932 was evaluated in human prostate cancer cell line (PC3). Our results indicated that Navitoclax-Debio-0932 combination exhibited synergistic activity in PC3 cells at concentrations lower than IC50 values. The combination of Navitoclax and Debio-0932 decreased PC3 cell viability in a dose dependent manner at 48 h. To investigate the apoptotic potential of the Navitoclax-Debio-0932 combination against prostate cancer cells, the mRNA and protein expression levels of apoptotic and antiapoptotic markers (Bax, Bcl-2, Bcl-xL, Cyt-c, Apaf-1, Casp-3, Casp-7, and Casp-9) were measured using RT-PCR and ELISA assay. Furthermore, the cleavage activity of Casp-3 was determined by colorimetric assay. The results revealed that Navitoclax-Debio-0932 combination potently induced intrinsic apoptotic pathway in PC3 cells rather than using drugs alone. The combined treatment of Navitoclax and Debio-0932 displayed synergistic cytotoxic and apoptotic effects on prostate cancer cells, presenting a promising approach for combination therapy in prostate cancer.

Unlocking the therapeutic potential of drug combinations through synergy prediction using graph transformer networks

Drug combinations are frequently used to treat cancer to reduce side effects and increase efficacy. The experimental discovery of drug combination synergy is time-consuming and expensive for large datasets. Therefore, an efficient and reliable computational approach is required to investigate these drug combinations. Advancements in deep learning can handle large datasets with various biological problems. In this study, we developed a SynergyGTN model based on the Graph Transformer Network to predict the synergistic drug combinations against an untreated cancer cell line expression profile. We represent the drug via a graph, with each node and edge of the graph containing nine types of atomic feature vectors and four bonds features, respectively. The cell lines represent based on their gene expression profiles. The drug graph was passed through the GTN layers to extract a generalized feature map for each drug pairs. The drug pair extracted features and cell-line gene expression profiles were concatenated and subsequently subjected to processing through multiple densely connected layers. SynergyGTN outperformed the state-of-the-art methods, with a receiver operating characteristic area under the curve improvement of 5% on the 5-fold cross-validation. The accuracy of SynergyGTN was further verified through three types of cross-validation tests strategies namely leave-drug-out, leave-combination-out, and leave-tissue-out, resulting in improvement in accuracy of 8%, 1%, and 2%, respectively. The Astrazeneca Dream dataset was utilized as an independent dataset to validate and assess the generalizability of the proposed method, resulting in an improvement in balanced accuracy of 13%. In conclusion, SynergyGTN is a reliable and efficient computational approach for predicting drug combination synergy in cancer treatment. Finally, we developed a web server tool to facilitate the pharmaceutical industry and researchers, as available at: http://nsclbio.jbnu.ac.kr/tools/SynergyGTN/.

Interpreting drug synergy in breast cancer with deep learning using target-protein inhibition profiles

BACKGROUND

Breast cancer is the most common malignancy among women worldwide. Despite advances in treating breast cancer over the past decades, drug resistance and adverse effects remain challenging. Recent therapeutic progress has shifted toward using drug combinations for better treatment efficiency. However, with a growing number of potential small-molecule cancer inhibitors, in silico strategies to predict pharmacological synergy before experimental trials are required to compensate for time and cost restrictions. Many deep learning models have been previously proposed to predict the synergistic effects of drug combinations with high performance. However, these models heavily relied on a large number of drug chemical structural fingerprints as their main features, which made model interpretation a challenge.

RESULTS

This study developed a deep neural network model that predicts synergy between small-molecule pairs based on their inhibitory activities against 13 selected key proteins. The synergy prediction model achieved a Pearson correlation coefficient between model predictions and experimental data of 0.63 across five breast cancer cell lines. BT-549 and MCF-7 achieved the highest correlation of 0.67 when considering individual cell lines. Despite achieving a moderate correlation compared to previous deep learning models, our model offers a distinctive advantage in terms of interpretability. Using the inhibitory activities against key protein targets as the main features allowed a straightforward interpretation of the model since the individual features had direct biological meaning. By tracing the synergistic interactions of compounds through their target proteins, we gained insights into the patterns our model recognized as indicative of synergistic effects.

CONCLUSIONS

The framework employed in the present study lays the groundwork for future advancements, especially in model interpretation. By combining deep learning techniques and target-specific models, this study shed light on potential patterns of target-protein inhibition profiles that could be exploited in breast cancer treatment.

Discovery of psoralen as a quorum sensing inhibitor suppresses Pseudomonas aeruginosa virulence

Pseudomonas aeruginosa is a common opportunistic pathogen with growing resistance and presents heightened treatment challenges. Quorum sensing (QS) is a cell-to-cell communication system that contributes to the production of a variety of virulence factors and is also related to biofilm formation of P. aeruginosa. Compared to traditional antibiotics which kill bacteria directly, the anti-virulence strategy by targeting QS is a promising strategy for combating pseudomonal infections. In this study, the QS inhibition potential of the compounds derived from the Traditional Chinese Medicines was evaluated by using in silico, in vitro, and in vivo analyses. The results showed that psoralen, a natural furocoumarin compound derived from Psoralea corylifolia L., was capable of simultaneously inhibiting the three main QS regulators, LasR, RhlR, and PqsR of P. aeruginosa. Psoralen had no bactericidal activity but could widely inhibit the production of extracellular proteases, pyocyanin, and biofilm, and the cell motilities of the model and clinical P. aeruginosa strains. RNA-sequencing and quantitative PCR analyses further demonstrated that a majority of QS-activated genes in P. aeruginosa were suppressed by psoralen. The supplementation of psoralen could protect Caenorhabditis elegans from P. aeruginosa challenge, especially for the hypervirulent strain PA14. Moreover, psoralen showed synergistic antibacterial effects with polymyxin B, levofloxacin, and kanamycin. In conclusions, this study identifies the anti-QS and antibiofilm effects of psoralen against P. aeruginosa strains and sheds light on the discovery of anti-pseudomonal drugs among Traditional Chinese Medicines. KEY POINTS: • Psoralen derived from Psoralea corylifolia L. inhibits the virulence-related phenotypes of P. aeruginosa. • Psoralen simultaneously targets the three core regulators of P. aeruginosa QS system and inhibits the expression of a large part of downstream genes. • Psoralen protects C. elegans from P. aeruginosa challenge and enhances the susceptibility of P. aeruginosa to antibiotics.

Re-expression of epigenetically silenced PTPRR by histone acetylation sensitizes RAS-mutant lung adenocarcinoma to SHP2 inhibition

Silenced protein tyrosine phosphatase receptor type R (PTPRR) participates in mitogen-activated protein kinase (MAPK) signaling cascades during the genesis and development of tumors. Rat sarcoma virus (Ras) genes are frequently mutated in lung adenocarcinoma, thereby resulting in hyperactivation of downstream MAPK signaling. However, the molecular mechanism manipulating the regulation and function of PTPRR in RAS-mutant lung adenocarcinoma is not known. Patient records collected from the Cancer Genome Atlas and Gene Expression Omnibus showed that silenced PTPRR was positively correlated with the prognosis. Exogenous expression of PTPRR suppressed the proliferation and migration of lung cancer cells. PTPRR expression and Src homology 2 containing protein tyrosine phosphatase 2 (SHP2) inhibition acted synergistically to control ERK1/2 phosphorylation in RAS-driven lung cancer cells. Chromatin immunoprecipitation assay revealed that HDAC inhibition induced enriched histone acetylation in the promoter region of PTPRR and recovered PTPRR transcription. The combination of the HDAC inhibitor SAHA and SHP2 inhibitor SHP099 suppressed the progression of lung cancer markedly in vitro and in vivo. Therefore, we revealed the epigenetic silencing mechanism of PTPRR and demonstrated that combination therapy targeting HDAC and SHP2 might represent a novel strategy to treat RAS-mutant lung cancer.

Programmed Co-delivery of tamoxifen and docetaxel using lipid-coated mesoporous silica nanoparticles for overcoming CYP3A4-mediated resistance in triple-negative breast cancer treatment

PURPOSE

This study aims to revolutionize the treatment of aggressive triple-negative breast cancer (TNBC), notorious for its resistance to standard therapies. By ingeniously combining Tamoxifen (TMX) and Docetaxel (DTX) within a lipid-coated mesoporous silica nanoparticle (LP-MSN) delivery system, we intend to enhance therapeutic efficacy while circumventing DTX resistance mediated by CYP3A4 expression.

METHODS

We rigorously tested TNBC cell lines to confirm the responsiveness to Docetaxel (DTX) and Tamoxifen (TMX). We adeptly engineered LP-MSN nanoparticles and conducted a thorough examination of the optimal drug release strategy, evaluating the LP-MSN system's ability to mitigate the impact of CYP3A4 on DTX. Additionally, we comprehensively analyzed its pharmacological performance.

RESULTS

Our innovative approach utilizing TMX and DTX within LP-MSN showcased remarkable efficacy. Sequential drug release from the lipid layer and mesoporous core curbed CYP3A4-mediated metabolism, substantially enhancing cytotoxic effects on TNBC cells without harming normal cells.

CONCLUSION

This pioneering research introduces a breakthrough strategy for tackling TNBC. By capitalizing on synergistic TMX and DTX effects via LP-MSN, we surmount drug resistance mediated by CYP3A4. This advancement holds immense potential for transforming TNBC treatment, warranting further clinical validation.

Systems pharmacodynamic model of combined gemcitabine and trabectedin in pancreatic cancer cells. Part I.Çô Effects on signal transduction pathways related to tumor growth

Pancreatic ductal adenocarcinoma (PDAC) is often chemotherapy-resistant, and novel drug combinations would fill an unmet clinical need. Previously we reported synergistic cytotoxic effects of gemcitabine and trabectedin on pancreatic cancer cells, but underlying protein-level interaction mechanisms remained unclear. We employed a reliable, sensitive, comprehensive, quantitative, high-throughput IonStar proteomic workflow to investigate the time course of gemcitabine and trabectedin effects, alone and combined, upon pancreatic cancer cells. MiaPaCa-2 cells were incubated with vehicle (controls), gemcitabine, trabectedin, and their combinations over 72 hours. Samples were collected at intervals and analyzed using the label-free IonStar liquid chromatography-mass spectrometry (LC-MS/MS) workflow to provide temporal quantification of protein expression for 4,829 proteins in four experimental groups. To characterize diverse signal transduction pathways, a comprehensive systems pharmacodynamic (SPD) model was developed. The analysis is presented in two parts. Here, Part I describes drug responses in cancer cell growth and migration pathways included in the full model: receptor tyrosine kinase- (RTK), integrin-, G-protein coupled receptor- (GPCR), and calcium-signaling pathways. The developed model revealed multiple underlying mechanisms of drug actions, provides insight into the basis of drug interaction synergism, and offers a scientific rationale for potential drug combination strategies.

New developments and standard of care in the management of advanced gastric cancer

Advanced gastric adenocarcinoma is a common disease with a poor prognosis whose treatment has for decades been based on cytotoxic chemotherapy, including platinum salts in first-line, and taxane or irinotecan in second or later line. Recent years have seen the emergence of new drugs that have improved patient survival, such as trastuzumab in first-line for HER2-positive tumors, ramucirumab alone or in combination with paclitaxel in second-line, and trifluridine-tipiracil beyond the second-line treatment. More recently, two monoclonal antibodies have demonstrated their efficacy in combination with oxaliplatin-based first-line chemotherapy, nivolumab (anti-PD1) for PD-L1 CPS ≥5 tumors, and zolbetuximab for tumors overexpressing Claudin 18.2. In addition, regorafenib has been also showed effective in phase 3 trial for heavily pretreated patients. Based on phase 2 studies, trastuzumab-deruxtecan was approved in 2022 by the EMA for HER2-positive pretreated patients. This agent is currently evaluated in phase 3 study (DESTINY-Gastric04 trial), as are several other anti-HER2 (zanidatamab, margetuximab, tucatinib), immune checkpoint inhibitors, or targeted therapies (anti-FGFR2b).

Small-molecule drugs of colorectal cancer: Current status and future directions

Colorectal cancer (CRC) is the third most commonly diagnosed cancer and the world's fourth most deadly cancer. CRC, as a genetic susceptible disease, faces significant challenges in optimizing prognosis through optimal drug treatment modalities. In recent decades, the development of innovative small-molecule drugs is expected to provide targeted interventions that accurately address the different molecular characteristics of CRC. Although the clinical application of single-target drugs is limited by the heterogeneity and high metastasis of CRC, novel small-molecule drug treatment strategies such as dual/multiple-target drugs, drug repurposing, and combination therapies can help overcome these challenges and provide new insights for improving CRC treatment. In this review, we focus on the current status of a range of small molecule drugs that are being considered for CRC therapy, including single-target drugs, dual/multiple-target drugs, drug repurposing and combination strategies, which will pave the way for targeting CRC vulnerabilities with small-molecule drugs in future personalized treatment.

A proteomic landscape of pharmacologic perturbations for functional relevance

Pharmacological perturbation studies based on protein-level signatures are fundamental for drug discovery. In the present study, we used a mass spectrometry (MS)-based proteomic platform to profile the whole proteome of the breast cancer MCF7 cell line under stress induced by 78 bioactive compounds. The integrated analysis of perturbed signal abundance revealed the connectivity between phenotypic behaviors and molecular features in cancer cells. Our data showed functional relevance in exploring the novel pharmacological activity of phenolic xanthohumol, as well as the noncanonical targets of clinically approved tamoxifen, lovastatin, and their derivatives. Furthermore, the rational design of synergistic inhibition using a combination of histone methyltransferase and topoisomerase was identified based on their complementary drug fingerprints. This study provides rich resources for the proteomic landscape of drug responses for precision therapeutic medicine.

Systems Pharmacodynamic Model of Combined Gemcitabine and Trabectedin in Pancreatic Cancer Cells. Part II: Cell Cycle, DNA Damage Response, and Apoptosis Pathways

Despite decades of research efforts, pancreatic adenocarcinoma (PDAC) continues to present a formidable clinical challenge, demanding innovative therapeutic approaches. In a prior study, we reported the synergistic cytotoxic effects of gemcitabine and trabectedin on pancreatic cancer cells. To investigate potential mechanisms underlying this synergistic pharmacodynamic interaction, liquid chromatography-mass spectrometry-based proteomic analysis was performed, and a systems pharmacodynamics model (SPD) was developed to capture pancreatic cancer cell responses to gemcitabine and trabectedin, alone and combined, at the proteome level. Companion report Part I describes the proteomic workflow and drug effects on the upstream portion of the SPD model related to cell growth and migration, specifically the RTK-, integrin-, GPCR-, and calcium-signaling pathways. This report presents Part II of the SPD model. Here we describe drug effects on pathways associated with cell cycle, DNA damage response (DDR), and apoptosis, and provide insights into underlying mechanisms. Drug combination effects on protein changes in the cell cycle- and apoptosis pathways contribute to the synergistic effects observed between gemcitabine and trabectedin. The SPD model was subsequently incorporated into our previously-established cell cycle model, forming a comprehensive, multi-scale quantification platform for evaluating drug effects across multiple scales, spanning the proteomic-, cellular-, and subcellular levels. This approach provides a quantitative mechanistic framework for evaluating drug-drug interactions in combination chemotherapy, and could potentially serve as a tool to predict combinatorial efficacy and assist in target selection.

Discovery of highly potent and selective KRASG12C degraders by VHL-recruiting PROTACs for the treatment of tumors with KRASG12C-Mutation

Although several covalent KRASG12C inhibitors have made great progress in the treatment of KRASG12C-mutant cancer, their clinical applications are limited by adaptive resistance, motivating novel therapeutic strategies. Through drug design and structure optimization, a series of highly potent and selective KRASG12C Proteolysis Targeting Chimeras (PROTACs) were developed by incorporating AMG510 and VHL ligand VH032. Among them, degrader YN14 significantly inhibited KRASG12C-dependent cancer cells growth with nanomolar IC50 and DC50 values, and ＞ 95 % maximum degradation (Dmax). Molecular dynamics (MD) simulation showed that YN14 induced a stable KRASG12C: YN14: VHL ternary complex with low binding free energy (ΔG). Notably, YN14 led to tumor regression with tumor growth inhibition (TGI%) rates more than 100 % in the MIA PaCa-2 xenograft model with well-tolerated dose-schedules. We also found that KRASG12C degradation exhibited advantages in overcoming adaptive KRASG12C feedback resistance over KRASG12C inhibition. Furthermore, combination of RTKs, SHP2, or CDK9 inhibitors with YN14 exhibited synergetic efficacy in KRASG12C-mutant cancer cells. Overall, these results demonstrated that YN14 holds exciting prospects for the treatment of tumors with KRASG12C-mutation and boosted efficacy could be achieved for greater clinical applications via drug combination.

Human gnathostomiasis: A review on the biology of the parasite with special reference on the current therapeutic management

Gnathostoma is a parasitic nematode that can infect a wide range of animal species, but human populations have become accidental hosts because of their habit of eating raw or undercooked meat from a wide variety of intermediate hosts. While gnathostomiasis is considered an endemic disease, cases of human gnathostomiasis have been increasing over time, most notably in nonendemic areas. There are several complexities to this parasitic disease, and this review provides an update on human gnathostomiasis, including the life cycle, diagnosis, treatment, and treatment strategies used to combat drug resistance. Even now, a definitive diagnosis of gnathostomiasis is still challenging because it is difficult to isolate larvae for parasitological confirmation. Another reason is the varying clinical symptoms recorded in reported cases. Clinical cases can be confirmed by immunodiagnosis. For Gnathosotoma spinigerum, the detection of IgG against a specific antigenic band with a molecular weight of 24 kDa from G. spinigerum advanced third-stage larvae (aL3), while for other species of Gnathostoma including G. binucleatum, the 33-kDa antigen protein is being used. This review also discusses cases of recurrence of gnathostomiasis and resistance mechanisms to two effective chemotherapeutics (albendazole and ivermectin) used against gnathostomiasis. This is significant, especially when planning strategies to combat anthelmintic resistance. Lastly, while no new chemotherapeutics against gnathostomiasis have been made available, we describe the management of recurrent gnathostomiasis using albendazole and ivermectin combinations or extensions of drug treatment plans.

What if amoxicillin/clavulanic acid reduces the cisplatin anticancer impact on oral cancer treatment?

Antibiotics-chemotherapeutics combination have become on the table for many cancer treatments. For this reason, we thought that further progress and development of studies to support chemotherapeutic approaches with the use of antibiotics may be beneficial in the clinical field. Cell lines (SCC-15, HTB-41, and MRC-5) were treated with 5-100 μM/ml concentrations of cisplatin (cisp) and amoxicillin/clavulanic acid (amx/cla) with combination (amx/cla-cisp) and alone in three different incubation periods. The all-cells viability was examined with WST-1 and apoptotic activity of the drugs were investigated via cell death ELISA assay kit. The cytotoxic impact of the 100 μM amx/cla-cisp combination was found to be reduced by up to 21.8%, which was significant given that the cytotoxic effect of only cisplatin therapy was 86.1%. Because our findings demonstrated that solo amx/cla therapy have almost no impact on proliferation or death, we focused on the amx/cla-cisp combination effect. It was found that the amx/cla-cisp combination has reduced the apoptotic fragment when comparing with the solely cisp-treated cells. Due to amx/cla-cisp combination on both cells but significantly on SCC-15 recovered the sole cisplatin effect, we believe that there might be a second thought when prescribing antibiotics while treating cancer patients. Not only the antibiotic's type but also the cancer type might interact to lessen the chemotherapeutic agent's impact which is clinically a dilemma to focus on.

The Efficacy of Single-pill Combination of Olmesartan Medoxomil and Amlodipine Besylate on Office Blood Pressure in Hypertensive Patients who did not Respond to Amlodipine Besylate Monotherapy

Background

As combination therapy, switching to single-pill combination (SPC) medication after a short period of monotherapy is helpful because reducing pill numbers can improve patients' adherence to medications. This study was aimed to assess the effect of the single-pill combination (SPC) of olmesartan medoxomil 20 mg and amlodipine besylate 5mg (OLM 20 mg/AML 5 mg) on blood pressure (BP) reduction in hypertensive patients who did not respond to amlodipine besylate 5 mg (AML 5 mg) monotherapy for 4 weeks.

Methods

This study was a prospective, open-label, multi-center, non-comparative study. Patients whose BP was not got the target BP (≥140 mmHg and if diabetic patients ≥130 mmHg) after 4 weeks treatment with AML 5 mg, were enrolled. AML 5 mg was switched to the SPC (OLM 20 mg/AML 5 mg) treatment for 8 weeks. The primary effectiveness endpoint was the reduction of seated systolic blood pressure (SeSBP) after SPC (OLM 20 mg/AML 5 mg) treatment for 8 weeks. The changes of brachial-ankle pulse wave velocity (baPWV), central BP (CBP), and augmentation index (AIx@75) were evaluated also.

Results

Forty-seven patients were enrolled (mean age = 52±9 years, 36 men). After the SPC treatment for 8 weeks, SeSBP was reduced from 153±9 mmHg to 131±18 mmHg and seated diastolic BP (SeDBP) from 95±8 mmHg to 81±11 mmHg (p<0.001 and p<0.001, respectively). The reduction of SeSBP/SeDBP were 22 mmHg and 14 mmHg, respectively. The target goal BP achievement rate was 74.5%, and baPWV, CBP, and AIx@75 were improved.

Conclusion

SPC (OLM 20 mg/AML 5 mg) treatment for 8 weeks was effective in reducing BP, achieving target BP goal, and also improving arterial stiffness in uncontrolled hypertensive patients with AML 5 mg monotherapy.

Extensive preclinical evaluation of combined mangiferin and glycyrrhizic acid for restricting synovial neovascularization in rheumatoid arthritis

BACKGROUND

Synovial neovascularization promotes rheumatoid arthritis (RA) progression. Baihu guizhi decoction (BHGZD) has a potential in restricting this pathological change of RA.

PURPOSE

To identify bioactive compounds (BACs) of BHGZD and to elucidate the underlying mechanisms in restricting synovial neovascularization of RA.

METHOD

Through transcriptomic profiling, the chemical profiling of BHGZD and its effective transcriptomic profiling against RA were identified. Then, candidate targets and the corresponding BACs against synovial neovascularization were screened by "disease gene-drug target" interaction network analysis and in silico molecular docking. The binding affinities of candidate BAC-target pairs were verified using surface plasmon resonance, and the pharmacokinetic characteristics of BACs in vivo after BHGZD administration at different time points were detected by Ultra Performance Liquid Chromatography-Mass spectrum/Mass spectrum. After that, in vivo experiments based on adjuvant-induced arthritis (AIA-M) rats, and in vitro experiments based on human umbilical vein endothelial cells (HUVEC) and arthritic synovial fibroblasts (MH7A) were carried out to evaluate the pharmacological effects of BHGZD and the two-BACs-combination, and to verify the associated mechanisms.

RESULT

VEGFA/VEGFR2/SRC/PI3K/AKT signal axis was screened as one of the key network targets of BHGZD against synovial neovascularization in RA. Mangiferin (MG) and glycyrrhizic acid (GA) were identified as the representative BACs of BHGZD for their strong binding affinities with components of the VEGFA/VEGFR2/SRC/PI3K/AKT signal axis, and their high exposed quantity in vivo. Both BHGZD and the two-BAC combination of MG and GA were demonstrated to be effective in restricting disease severity, reducing synovial inflammation and decreasing the formation of vascular opacities in AIA-M rats, and also reducing the migrative and invasive activities of HUVEC and MH7A cells and attenuating the lumen formation ability of HUVEC cells significantly. Mechanically, both BHGZD and the two-BAC combination markedly reduced the expression of VEGFA in synovial tissues, the serum levels of VEGF and NO, and the enzymatic activity of eNOS, increased the content of endostatin, and also reversed the abnormal alterations in the VEGFA/VEGFR2/SRC/PI3K/AKT signal axis in vivo and in vitro.

CONCLUSION

MG and GA may be the representative BACs of BHGZD for restricting excessive synovial vascularization in RA via regulating VEGFA/VEGFR2/SRC/PI3K/AKT signal axis.

Dextromethorphan-bupropion (Auvelity) for the Treatment of Major Depressive Disorder

Depression is a significant cause of morbidity and mortality globally. Although various pharmacologic options exist for depression, treatments are limited by delayed or incomplete therapeutic response, low rates of remission, and adverse effects necessitating effective, fast-acting, and better tolerated alternatives. The purpose of this review is to describe the safety and efficacy of dextromethorphan-bupropion (Auvelity), a Food and Drug Administration approved treatment for major depressive disorder in adults. Dextromethorphan modulates glutamate signaling through uncompetitive antagonism of N-methyl-D-aspartate receptors and sigma-1 agonism, while bupropion increases the bioavailability of dextromethorphan by CYP2D6 inhibition. In a phase 3 trial with dextromethorphan-bupropion 45-105 mg for patients with major depressive disorder saw significant reductions in their Montgomery-Åsberg Depression Rating Scale total scores compared to placebo. A phase 2 trial comparing dextromethorphan-bupropion 45-105 mg to bupropion monotherapy led to significant reduction in Montgomery-Åsberg Depression Rating Scale score. Changes in Montgomery-Åsberg Depression Rating Scale with dextromethorphan-bupropion were seen within two weeks in both clinical trials. Remission and response rates were significantly higher with dextromethorphan-bupropion in both studies. The medication was well-tolerated in both trials, with the most common adverse events being rated as mild-to-moderate. Two long-term, open-label studies with dextromethorphan-bupropion saw large reductions in Montgomery-Åsberg Depression Rating Scale scores that were maintained through 12 and 15 months of treatment. In both long-term studies, remission rates approached 70%, while response rates were greater than 80%. These data suggest that dextromethorphan-bupropion is an effective, fast-acting, and well tolerated option for depression treatment and produced remission in a large percentage of patients.

JAK2 inhibitors for the treatment of Philadelphia-negative myeloproliferative neoplasms: current status and future directions

The overactivation of Janus kinases 2 (JAK2) by gain-of-function mutations in the JAK2, Myeloproliferative leukemia virus oncogene, or Calreticulin genes are the most important factor in the development of Philadelphia-negative myeloproliferative neoplasms (MPNs). The discovery of the JAK2V617F mutation is a significant breakthrough in understanding the pathogenesis of MPNs, and inhibition of JAK2 abnormal activation has become one of the most effective strategies against MPNs. Currently, three JAK2 inhibitors for treating MPNs have been approved, and several are being evaluated in clinical trials. However, persistent challenges in terms of drug resistance and off-target effects remain unresolved. In this review, we introduce and classify the available JAK2 inhibitors in terms of their mechanisms and clinical considerations. Additionally, through an analysis of target points, binding modes, and structure-activity inhibitor relationships, we propose strategies such as combination therapy and allosteric inhibitors to overcome specific challenges. This review offers valuable insights into current trends and future directions for optimal management of MPNs using JAK2 inhibitors.

Tunable polymeric micelles for taxane and corticosteroid co-delivery

Nanomedicine holds promise for potentiating drug combination therapies. Increasing (pre)clinical evidence is available exemplifying the value of co-formulating and co-delivering different drugs in modular nanocarriers. Taxanes like paclitaxel (PTX) are widely used anticancer agents, and commonly combined with corticosteroids like dexamethasone (DEX), which besides for suppressing inflammation and infusion reactions, are increasingly explored for modulating the tumor microenvironment towards enhanced nano-chemotherapy delivery and efficacy. We here set out to develop a size- and release rate-tunable polymeric micelle platform for co-delivery of taxanes and corticosteroids. We synthesized amphiphilic mPEG-b-p(HPMAm-Bz) block copolymers of various molecular weights and used them to prepare PTX and DEX single- and double-loaded micelles of different sizes. Both drugs could be efficiently co-encapsulated, and systematic comparison between single- and co-loaded formulations demonstrated comparable physicochemical properties, encapsulation efficiencies, and release profiles. Larger micelles showed slower drug release, and DEX release was always faster than PTX. The versatility of the platform was exemplified by co-encapsulating two additional taxane-corticosteroid combinations, demonstrating that drug hydrophobicity and molecular weight are key properties that strongly contribute to drug retention in micelles. Altogether, our work shows that mPEG-b-p(HPMAm-Bz) polymeric micelles serve as a tunable and versatile nanoparticle platform for controlled co-delivery of taxanes and corticosteroids, thereby paving the way for using these micelles as a modular carrier for multidrug nanomedicine.

Design, synthesis and characterization of a novel multicomponent salt of bexarotene with metformin and application in ameliorating psoriasis with T2DM

Psoriasis is a common systemic inflammatory skin disorder affecting over 60 million people globally. Some patients with psoriasis are associated with a higher risk of type 2 diabetes mellitus (T2DM). Psoriasis and T2DM occur concurrently in some patients; however, there is no effective drug for the treatment of psoriasis with T2DM. Bexarotene (BEX) is a specific RXR agonist and an antineoplastic agent indicated by the FDA for cutaneous T-cell lymphoma (CTLA). Metformin (MET) is the first-line treatment for T2DM. To develop novel effective drugs for the treatment of psoriasis with T2DM, multicomponent salts containing MET and BEX were designed and synthesized based on the drug-drug combination strategy. MET-BEX (1:1) and MET-BEX-H2O (1:1:1) were obtained and structurally characterized. The in vitro evaluation results showed that the hygroscopicity of MET was significantly optimized by the salt formation strategy, while the solubility of BEX was improved, which laid the foundation for improving the bioavailability of BEX in vivo. In a mouse model of imiquimod-induced psoriasis with T2DM, MET-BEX ameliorated imiquimod-induced psoriasis morphological features and systematic inflammation and improved glucolipid metabolism. These results showed that the multicomponent drug combination strategy in this study optimized the physicochemical properties of MET and BEX simultaneously, providing a promising candidate therapy for psoriasis with T2DM.

Cordycepin improves sensitivity to temozolomide in glioblastoma cells by down-regulating MYC

PURPOSE

Glioblastoma is one of the malignant tumors with poor prognosis and no effective treatment is available at present.

METHODS

To study the effect of cordycepin combined with temozolomide on glioblastoma, we explored the effect of the combination based on network pharmacology and biological verification.

RESULTS

It was found that the drug combination significantly inhibited the cell growth, proliferation, migration and invasion of LN-229 cells. Drug combination inhibited epithelial-mesenchymal transition (EMT) by up-regulating the expression of E-cadherin and suppressing the expression of N-cadherin, Zeb1 and Twist1. Through network pharmacology, we further explored the molecular mechanism of drug combination against glioblastoma, and 36 drug-disease common targets were screened. The GO biological process analysis included 44 items (P < 0.01), which mainly involved the regulation of apoptosis, cell proliferation, cell migration, etc. The enrichment analysis of KEGG pathways included 28 pathways (P < 0.05), and the first four pathways were "MicroRNA in cancer, Proteoglycans in cancer, Pathways in cancer and PI3K-AKT signaling pathway". We detected the expression of important genes in the pathways and PPI network, and the results showed that the drug combination down-regulated NFKB1, MYC, MMP-9, MCL1, CTNNB1, and up-regulated PDCD4.

CONCLUSION

Cordycepin combined with temozolomide may down-regulate MYC through "MicroRNA in cancer, Proteoglycans in cancer, Pathways in cancer and PI3K-AKT signaling pathway", which in turn regulate the expression of MCL1, CTNNB1, MMP9, PDCD4, thus regulating cell proliferation, migration and apoptosis in glioblastoma.

The effect of PLK1 inhibitor in osimertinib resistant non-small cell lung carcinoma cells

OBJECTIVES

To investigate the effects of PLK1 inhibitors on osimertinib-resistant non-small cell lung carcinoma (NSCLC) cells and the anti-tumor effect combined with osimertinib.

METHODS

An osimertinib resistant NCI-H1975 cell line was induced by exposure to gradually increasing drug concentrations. Osimertinib-resistant cells were co-treated with compounds from classical tumor pathway inhibitor library and osimertinib to screen for compounds with synergistic effects with osimertinib. The Gene Set Enrichment Analysis (GSEA) was used to investigate the activated signaling pathways in osimertinib-resistant cells; sulforhodamine B (SRB) staining was used to investigate the effect of PLK1 inhibitors on osimertinib-resistant cells and the synergistic effect of PLK1 inhibitors combined with osimertinib.

RESULTS

Osimertinib-resistance in NCI-H1975 cell (resistance index=43.45) was successfully established. The PLK1 inhibitors GSK 461364 and BI 2536 had synergistic effect with osimertinib. Compared with osimertinib-sensitive cells, PLK1 regulatory pathway and cell cycle pathway were significantly activated in osimertinib-resistant cells. In NSCLC patients with epidermal growth factor receptor mutations treated with osimertinib, PLK1 mRNA levels were negatively correlated with progression free survival of patients (R=－0.62, P<0.05), indicating that excessive activation of PLK1 in NSCLC cells may cause cell resistant to osimertinib. Further in vitro experiments showed that IC50 of PLK1 inhibitors BI 6727 and GSK 461364 in osimertinib-resistant cells were lower than those in sensitive ones. Compared with the mono treatment of osimertinib, PLK1 inhibitors combined with osimertinib behaved significantly stronger effect on the proliferation of osimertinib-resistant cells.

CONCLUSIONS

PLK1 inhibitors have a synergistic effect with osimertinib on osimertinib-resistant NSCLC cells which indicates that they may have potential clinical value in the treatment of NSCLC patients with osimertinib resistance.

Open a new epoch of arsenic trioxide investigation: ATOdb

Arsenic trioxide (ATO) is a great discovery in the treatment of acute promyelocytic leukemia (APL), which has been used in an increasing number of malignant diseases. Systematic integrative analysis will help to precisely understand the mechanism of ATO and find new combined drugs. Therefore, we developed a one-stop comprehensive database of ATO named ATOdb by manually compiling a wealth of experimentally supported ATO-related data from 3479 articles, and integrated analysis tools. The current version of ATOdb contains 8373 associations among 2300 ATO targets, 80 conditions and 262 combined drugs. Each entry in ATOdb contains detailed information on ATO targets, therapeutic/side effects, systems, cell names, cell types, regulations, detection methods, brief descriptions, references, etc. Furthermore, ATOdb also provides data visualization and analysis results such as the drug similarities, protein-protein interactions, and miRNA-mRNA relationships. An easy-to-use web interface was deployed in ATOdb for users to easily browse, search and download the data. In conclusion, ATOdb will serve as a valuable resource for in-depth study of the mechanism of ATO, discovery of new drug combination strategies, promotion of rational drug use and individualized treatments. ATOdb is freely available at http://bio-bigdata.hrbmu.edu.cn/ATOdb/index.jsp.

Enhanced efficacy with reduced toxicity of tripterygium glycoside tablet by compatibility with total glucosides of paeony for rheumatoid arthritis therapy

BACKGROUND AND AIMS

Drug-induced liver injury remains a critical issue to hinder clinical application of Tripterygium Glycosides Tablets (TGTs) for rheumatoid arthritis (RA) therapy. Combination of TGTs with Total Glucosides of Peony (TGP) may be the most common therapeutic strategy for enhancing TGTs' efficacy and reducing its toxicity. Herein, we aimed to investigate the efficacy-enhancing and toxicity-reducing properties and mechanisms of TGT-TGP combination.

METHODS

Both TGT-induced acute and chronic liver injury animal models were established. ELISA, transmission electron microscopy, immunohistochemistry, western blot and quantitative PCR were performed to determine the efficacy, toxicity and regulatory mechanisms of TGT-TGP combination.

RESULTS

The compatibility of TGP significantly reduced the abnormal serum ALT and AST levels, and improved liver histopathological changes in both acute and chronic DILI animal models induced by TGTs, with the most effective dosage of TGP-M (medium-dose TGP, 450 mg/kg). Additionally, TGP and TGT synergistically alleviated joint swelling and improved the elevation of serum inflammatory factors, in line with the positive changes in joint histopathological features of collagen induced arthritis mice, with the same effective dosage of TGP-M following 5 weeks' drug combination treatment. Mechanically, TGT significantly increased the number of autophagosomes and the expression of LC3II protein while reducing p62 protein expression in the liver tissues, which were significantly reversed by the compatibility with TGP, similar to the findings based on the inflamed joint tissues.

CONCLUSIONS

These findings suggest an enhanced efficacy with reduced toxicity of TGT by the compatibility with TGP for RA therapy, possibly through regulating various autophagy-related proteins.

Arrest of mouse preterm labor until term delivery by combination therapy with atosiban and mundulone, a natural product with tocolytic efficacy

There is a lack of FDA-approved tocolytics for the management of preterm labor (PL). In prior drug discovery efforts, we identified mundulone and mundulone acetate (MA) as inhibitors of in vitro intracellular Ca2+-regulated myometrial contractility. In this study, we probed the tocolytic potential of these compounds using human myometrial samples and a mouse model of preterm birth. In a phenotypic assay, mundulone displayed greater efficacy, while MA showed greater potency and uterine-selectivity in the inhibition of intracellular-Ca2+ mobilization. Cell viability assays revealed that MA was significantly less cytotoxic. Organ bath and vessel myography studies showed that only mundulone exerted inhibition of myometrial contractions and that neither compounds affected vasoreactivity of ductus arteriosus. A high-throughput combination screen identified that mundulone exhibits synergism with two clinical-tocolytics (atosiban and nifedipine), and MA displayed synergistic efficacy with nifedipine. Of these combinations, mundulone+atosiban demonstrated a significant improvement in the in vitro therapeutic index compared to mundulone alone. The ex vivo and in vivo synergism of mundulone+atosiban was substantiated, yielding greater tocolytic efficacy and potency on myometrial tissue and reduced preterm birth rates in a mouse model of PL compared to each single agent. Treatment with mundulone after mifepristone administration dose-dependently delayed the timing of delivery. Importantly, mundulone+atosiban permitted long-term management of PL, allowing 71% dams to deliver viable pups at term (>day 19, 4-5 days post-mifepristone exposure) without visible maternal and fetal consequences. Collectively, these studies provide a strong foundation for the development of mundulone as a single or combination tocolytic for management of PL.

Ponatinib: An update on its drug targets, therapeutic potential and safety

Leukemia is a malignancy of the hematopoietic system, and as its pathogenesis has become better understood, three generations of tyrosine kinase inhibitors (TKIs) have been developed. Ponatinib is the third-generation breakpoint cluster region (BCR) and Abelson (ABL) TKI, which has been influential in the leukemia therapy for a decade. Moreover, ponatinib is a potent multi-target kinase inhibitor that acts on various kinases, such as KIT, RET, and Src, making it a promising treatment option for triple-negative breast cancer (TNBC), lung cancer, myeloproliferative syndrome, and other diseases. The drug's significant cardiovascular toxicity poses a significant challenge to its clinical use, requiring the development of strategies to minimize its toxicity and side effects. In this article, the pharmacokinetics, targets, therapeutic potential, toxicity and production mechanism of ponatinib will be reviewed. Furthermore, we will discuss methods to reduce the drug's toxicity, providing new avenues for research to improve its safety in clinical use.

Anticancer activity of thymoquinone against breast cancer cells: Mechanisms of action and delivery approaches

The rising incidence of breast cancer has been a significant source of concern in the medical community. Regarding the adverse effects and consequences of current treatments, cancers' health, and socio-economical aspects have become more complicated, leaving research aimed at improved or new treatments on top priority. Medicinal herbs contain multitarget compounds that can control cancer development and advancement. Owing to Nigella Sativa's elements, it can treat many disorders. Thymoquinone (TQ) is a natural chemical derived from the black seeds of Nigella sativa Linn proved to have anti-cancer and anti-inflammatory properties. TQ interferes in a broad spectrum of tumorigenic procedures and inhibits carcinogenesis, malignant development, invasion, migration, and angiogenesis owing to its multitargeting ability. It effectively facilitates miR-34a up-regulation, regulates the p53-dependent pathway, and suppresses Rac1 expression. TQ promotes apoptosis and controls the expression of pro- and anti-apoptotic genes. It has also been shown to diminish the phosphorylation of NF-B and IKK and decrease the metastasis and ERK1/2 and PI3K activity. We discuss TQ's cytotoxic effects for breast cancer treatment with a deep look at the relevant stimulatory or inhibitory signaling pathways. This review discusses the various forms of polymeric and non-polymeric nanocarriers (NC) and the encapsulation of TQ for increasing oral bioavailability and enhanced in vitro and in vivo efficacy of TQ-combined treatment with different chemotherapeutic agents against various breast cancer cell lines. This study can be useful to a broad scientific community, comprising pharmaceutical and biological scientists, as well as clinical investigators.

EDST: a decision stump based ensemble algorithm for synergistic drug combination prediction

INTRODUCTION

There are countless possibilities for drug combinations, which makes it expensive and time-consuming to rely solely on clinical trials to determine the effects of each possible drug combination. In order to screen out the most effective drug combinations more quickly, scholars began to apply machine learning to drug combination prediction. However, most of them are of low interpretability. Consequently, even though they can sometimes produce high prediction accuracy, experts in the medical and biological fields can still not fully rely on their judgments because of the lack of knowledge about the decision-making process.

RELATED WORK

Decision trees and their ensemble algorithms are considered to be suitable methods for pharmaceutical applications due to their excellent performance and good interpretability. We review existing decision trees or decision tree ensemble algorithms in the medical field and point out their shortcomings.

METHOD

This study proposes a decision stump (DS)-based solution to extract interpretable knowledge from data sets. In this method, a set of DSs is first generated to selectively form a decision tree (DST). Different from the traditional decision tree, our algorithm not only enables a partial exchange of information between base classifiers by introducing a stump exchange method but also uses a modified Gini index to evaluate stump performance so that the generation of each node is evaluated by a global view to maintain high generalization ability. Furthermore, these trees are combined to construct an ensemble of DST (EDST).

EXPERIMENT

The two-drug combination data sets are collected from two cell lines with three classes (additive, antagonistic and synergistic effects) to test our method. Experimental results show that both our DST and EDST perform better than other methods. Besides, the rules generated by our methods are more compact and more accurate than other rule-based algorithms. Finally, we also analyze the extracted knowledge by the model in the field of bioinformatics.

CONCLUSION

The novel decision tree ensemble model can effectively predict the effect of drug combination datasets and easily obtain the decision-making process.

A co-formulation of interferons alpha2b and gamma distinctively targets cell cycle in the glioblastoma-derived cell line U-87MG

BACKGROUND

HeberFERON is a co-formulation of α2b and γ interferons, based on their synergism, which has shown its clinical superiority over individual interferons in basal cell carcinomas. In glioblastoma (GBM), HeberFERON has displayed promising preclinical and clinical results. This led us to design a microarray experiment aimed at identifying the molecular mechanisms involved in the distinctive effect of HeberFERON compared to the individual interferons in U-87MG model.

METHODS

Transcriptional expression profiling including a control (untreated) and three groups receiving α2b-interferon, γ-interferon and HeberFERON was performed using an Illumina HT-12 microarray platform. Unsupervised methods for gene and sample grouping, identification of differentially expressed genes, functional enrichment and network analysis computational biology methods were applied to identify distinctive transcription patterns of HeberFERON. Validation of most representative genes was performed by qPCR. For the cell cycle analysis of cells treated with HeberFERON for 24 h, 48 and 72 h we used flow cytometry.

RESULTS

The three treatments show different behavior based on the gene expression profiles. The enrichment analysis identified several mitotic cell cycle related events, in particular from prometaphase to anaphase, which are exclusively targeted by HeberFERON. The FOXM1 transcription factor network that is involved in several cell cycle phases and is highly expressed in GBMs, is significantly down regulated. Flow cytometry experiments corroborated the action of HeberFERON on the cell cycle in a dose and time dependent manner with a clear cellular arrest as of 24 h post-treatment. Despite the fact that p53 was not down-regulated, several genes involved in its regulatory activity were functionally enriched. Network analysis also revealed a strong relationship of p53 with genes targeted by HeberFERON. We propose a mechanistic model to explain this distinctive action, based on the simultaneous activation of PKR and ATF3, p53 phosphorylation changes, as well as its reduced MDM2 mediated ubiquitination and export from the nucleus to the cytoplasm. PLK1, AURKB, BIRC5 and CCNB1 genes, all regulated by FOXM1, also play central roles in this model. These and other interactions could explain a G2/M arrest and the effect of HeberFERON on the proliferation of U-87MG.

CONCLUSIONS

We proposed molecular mechanisms underlying the distinctive behavior of HeberFERON compared to the treatments with the individual interferons in U-87MG model, where cell cycle related events were highly relevant.

Targeting sphingolipid metabolism with the sphingosine kinase inhibitor SKI-II overcomes hypoxia-induced chemotherapy resistance in glioblastoma cells: effects on cell death, self-renewal, and invasion

BACKGROUND

Glioblastoma patients commonly develop resistance to temozolomide chemotherapy. Hypoxia, which supports chemotherapy resistance, favors the expansion of glioblastoma stem cells (GSC), contributing to tumor relapse. Because of a deregulated sphingolipid metabolism, glioblastoma tissues contain high levels of the pro-survival sphingosine-1-phosphate and low levels of the pro-apoptotic ceramide. The latter can be metabolized to sphingosine-1-phosphate by sphingosine kinase (SK) 1 that is overexpressed in glioblastoma. The small molecule SKI-II inhibits SK and dihydroceramide desaturase 1, which converts dihydroceramide to ceramide. We previously reported that SKI-II combined with temozolomide induces caspase-dependent cell death, preceded by dihydrosphingolipids accumulation and autophagy in normoxia. In the present study, we investigated the effects of a low-dose combination of temozolomide and SKI-II under normoxia and hypoxia in glioblastoma cells and patient-derived GCSs.

METHODS

Drug synergism was analyzed with the Chou-Talalay Combination Index method. Dose-effect curves of each drug were determined with the Sulforhodamine B colorimetric assay. Cell death mechanisms and autophagy were analyzed by immunofluorescence, flow cytometry and western blot; sphingolipid metabolism alterations by mass spectrometry and gene expression analysis. GSCs self-renewal capacity was determined using extreme limiting dilution assays and invasion of glioblastoma cells using a 3D spheroid model.

RESULTS

Temozolomide resistance of glioblastoma cells was increased under hypoxia. However, combination of temozolomide (48 µM) with SKI-II (2.66 µM) synergistically inhibited glioblastoma cell growth and potentiated glioblastoma cell death relative to single treatments under hypoxia. This low-dose combination did not induce dihydrosphingolipids accumulation, but a decrease in ceramide and its metabolites. It induced oxidative and endoplasmic reticulum stress and triggered caspase-independent cell death. It impaired the self-renewal capacity of temozolomide-resistant GSCs, especially under hypoxia. Furthermore, it decreased invasion of glioblastoma cell spheroids.

CONCLUSIONS

This in vitro study provides novel insights on the links between sphingolipid metabolism and invasion, a hallmark of cancer, and cancer stem cells, key drivers of cancer. It demonstrates the therapeutic potential of approaches that combine modulation of sphingolipid metabolism with first-line agent temozolomide in overcoming tumor growth and relapse by reducing hypoxia-induced resistance to chemotherapy and by targeting both differentiated and stem glioblastoma cells.

Isoniazid-N-acylhydrazones as promising compounds for the anti-tuberculosis treatment

Tuberculosis (TB), a disease caused by Mycobacterium tuberculosis complex, still presents significant numbers of incidence and mortality, in addition to several cases of drug resistance. Resistance, especially to isoniazid, which is one of the main drugs used in the treatment, has increased. In this context, N-acylhydrazones derived from isoniazid have shown important anti-Mycobacterium tuberculosis activity. Hence, this work aimed to determine the anti-TB potential of 11 isoniazid-N-acylhydrazones (INH-acylhydrazones). For this purpose, the determination of minimum inhibitory concentration (MIC) against M. tuberculosis H37Rv and clinical isolates was carried out. Drug combination, minimum bactericidal concentration, cytotoxicity, and in silico parameters were also performed. INH-acylhydrazones (2), (8), and (9) had MIC for M. tuberculosis H37Rv similar to or lower than isoniazid, and bactericidal activity was observed. In addition, these compounds showed low cytotoxicity, with a selectivity index greater than 3,000. Interesting results were also obtained in the drug combination assay, with synergistic combinations with isoniazid, ethambutol, and rifampicin. In the in silico study, INH-acylhydrazones behaved similarly to INH, but with improvements in some aspects. Based on these findings, it is concluded that compounds (2), (8), and (9) are considered promising scaffolds and warrant further investigation for designing future antimicrobial drugs.

Fucoxanthin Potentiates the Bactericidal Activity of Cefotaxime Against Staphylococcus aureus

The increasing prevalence of antimicrobial resistance (AMR) in Staphylococcus aureus against commonly used antibiotics is a major global health issue. To prevent the emergence of AMR and maintain the desired therapeutic effect, the use of drug combinations in the therapeutic management of infections can be contemplated. This approach allows for the administration of lower antibiotic dosages without compromising the desired therapeutic outcome. Despite the documented antimicrobial activity of fucoxanthin, a widely recognized marine carotenoid, there are a lack of previous reports exploring its potential to enhance the therapeutic effect of antibiotics. The current study aimed to investigate whether fucoxanthin can inhibit S. aureus including the strains resistant to methicillin and to investigate whether fucoxanthin can enhance the therapeutic effect of cefotaxime, a widely prescribed 3rd-generation cephalosporin β-lactam antibiotic known to exhibit resistance in certain cases. Synergism or additive interactions were determined using checkerboard dilution and isobologram analysis, while bactericidal activity was carried out using the time-kill kinetic assay. It is important to highlight that a synergistic bactericidal effect was observed in all strains of S. aureus when fucoxanthin was combined with cefotaxime at a specific concentration ratio. These findings suggest that fucoxanthin holds promise in enhancing the therapeutic efficacy of cefotaxime.

Albendazole - Ivermectin combination decreases inflammation in experimental neurocysticercosis

Neurocysticercosis (NCC) is a public health issue in endemic regions and is considered the main preventable cause of neurologic disease. It is caused by the presence of Taenia solium cysticercus in the central nervous system. The current treatment is performed with anthelminthic drugs - albendazole (ABZ) or praziquantel - associated with anti-inflammatory and corticosteroids in order to prevent the negative effects of the inflammatory reaction to the parasite's death. Ivermectin (IVM) is an anthelminthic drug that has been shown to present an anti-inflammatory effect. The aim of this study was to was to evaluate the histopathologic aspects of experimental NCC after in vivo treatment with a combination of ABZ-IVM. Balb/c mice were intracranially inoculated with T. crassiceps cysticerci and after 30 days of infection were treated with a single dose of NaCl 0.9% (control group), ABZ monotherapy (40 mg/kg), IVM monotherapy (0.2 mg/kg) or a combination of ABZ-IVM. 24h after the treatment the animals were euthanized and the brain was removed for histopathologic analysis. The IVM monotherapy and ABZ-IVM combination showed more degenerated cysticerci, less inflammatory infiltration, meningitis and hyperemia than the other groups. Therefore, it is possible to recommend the combination of albendazole and ivermectin as alternative chemotherapy for NCC due to its antiparasitic and anti-inflammatory effects, with potential to decrease the negative effects of the inflammatory burst when the parasite is killed within the CNS.

A novel AKR1C3 specific prodrug AST-3424 and its combination therapy in hepatocellular carcinoma

OBJECTIVE

AST-3424 is a novel specific aldo-keto reductase 1C3 (AKR1C3) prodrug that releases a DNA alkylating reagent upon reduction by AKR1C3. This study aimed to evaluate the efficacy and safety of AST-3424 in patient-derived tumor xenograft (PDTX) model and orthotopic model against hepatocellular carcinoma (HCC).

MATERIALS AND METHOD

PDTX models derived from three HCC patients and orthotopic mice models using HepG2 cells were developed. The mice were treated with AST-3424 alone or combined with other drugs (oxaliplatin, apatinib, sorafenib and elemene in PDTX models, oxaliplatin and 5- fluorouracil in orthotopic models). The tumor volume and weight, as well as the mice weight were assessed. The liver tumor and transplanted tumor were removed for histological, immunohistochemical and Western blot detection in orthotopic model experiments.

RESULTS

AST-3424 could inhibit tumor growth in HCC PDTX models and orthotopic models, with no difference in safety compared with other marketed drugs, and the drug combination did not increase toxicity. The inhibitory effect of combination treatment was more obvious than which used alone. The reduction of AKR1C3 expression was negatively correlated with AST-3424 dose.

CONCLUSION

AST-3424 had a promising effect against HCC in PDTX model and orthotopic model with good safety. It could promote the sensitivity of other drugs without increasing toxicity. Clinical trials are warranted to further certify its antitumor effect and safety.

Cocktail hepatocarcinoma therapy by a super-assembled nano-pill targeting XPO1 and ATR synergistically

Intensive cancer treatment with drug combination is widely exploited in the clinic but suffers from inconsistent pharmacokinetics among different therapeutic agents. To overcome it, the emerging nanomedicine offers an unparalleled opportunity for encapsulating multiple drugs in a nano-carrier. Herein, a two-step super-assembled strategy was performed to unify the pharmacokinetics of a peptide and a small molecular compound. In this proof-of-concept study, the bioinformatics analysis firstly revealed the potential synergies towards hepatoma therapy for the associative inhibition of exportin 1 (XPO1) and ataxia telangiectasia mutated-Rad3-related (ATR), and then a super-assembled nano-pill (gold nano drug carrier loaded AZD6738 and 97-110 amino acids of apoptin (AP) (AA@G)) was constructed through camouflaging AZD6738 (ATR small-molecule inhibitor)-binding human serum albumin onto the AP-Au supramolecular nanoparticle. As expected, both in vitro and in vivo experiment results verified that the AA@G possessed extraordinary biocompatibility and enhanced therapeutic effect through inducing cell cycle arrest, promoting DNA damage and inhibiting DNA repair of hepatoma cell. This work not only provides a co-delivery strategy for intensive liver cancer treatment with the clinical translational potential, but develops a common approach to unify the pharmacokinetics of peptide and small-molecular compounds, thereby extending the scope of drugs for developing the advanced combination therapy.

The recent progress of deep-learning-based in silico prediction of drug combination

Drug combination therapy has become a common strategy for the treatment of complex diseases. There is an urgent need for computational methods to efficiently identify appropriate drug combinations owing to the high cost of experimental screening. In recent years, deep learning has been widely used in the field of drug discovery. Here, we provide a comprehensive review on deep-learning-based drug combination prediction algorithms from multiple aspects. Current studies highlight the flexibility of this technology in integrating multimodal data and the ability to achieve state-of-art performance; it is expected that deep-learning-based prediction of drug combinations should play an important part in future drug discovery.

Antinociceptive and anti-inflammatory activity of DW-1021, the ionic complex of pelubiprofen and tramadol, in rodents

Although drugs such as acetaminophen, opioids, and nonsteroidal anti-inflammatory drugs (NSAIDs), are commonly used for pain management, the side effects of these drugs such as hepatotoxicity, nephrotoxicity, nausea, and vomiting, can not be neglected. Therefore, combinations of analgesics with different mechanisms raise the possibility of developing novel analgesics. Therefore, the aim of the present study was to evaluate whether DW-1021, the ionic complex of pelubiprofen (NSAID) and tramadol (opioid), has synergic antinociceptive and anti-inflammatory effects in nociceptive as well as inflammation-induced nociceptive models compared to pelubiprofen- or tramadol-only administration. Strong synergistic antinociceptive efficacy of DW-1021 was observed in the mouse writhing test and von Frey paw withdrawal threshold test in the carrageenan-induced rats. The hot plate test in mice and the Randall-Selitto mechanical paw pressure test in carrageenan-induced rats revealed that DW-1021 had a preferable effect on relieving pain to pelubiprofen, but not as much as tramadol. In the carrageenan-induced rats, DW-1021 had a more potent effect on reducing paw inflammation (paw volume, width, and thickness) via the suppression of PGE₂ production than tramadol, but less than that of pelubiprofen. Taken together, our results suggest that the administration of DW-1021, a combination of pelubiprofen and tramadol, exerted a potent effect and can be used as a potential therapeutic agent for relieving pain and inflammation.

Design, synthesis and biological evaluation of novel spiro-quinazolinone derivatives as chitin synthase inhibitors and antifungal agents

A series of spiro-quinazolinone scaffolds were constructed based on the bioactivity of quinazolinone and the inherent feature of spirocycle to design novel chitin synthase inhibitors that possess mode of action different from that of the currently used antifungal agents. Among them, the spiro[thiophen-quinazolin]-one derivatives containing α, β-unsaturated carbonyl fragments had shown inhibitory activities against chitin synthase and antifungal activities. The enzymatic experiments showed that among the sixteen compounds, compounds 12d, 12g, 12j, 12l and 12m exhibited inhibitions against chitin synthase with IC₅₀ values of 116.7 ± 19.6 μM, 106.7 ± 14.2 μM, 102.3 ± 9.6 μM, 122.7 ± 22.2 μM and 136.8 ± 12.4 μM, respectively, which were comparable to that of polyoxin B (IC₅₀ = 93.5 ± 11.1 μM). The assays of enzymatic Kinetic parameters showed that compound 12g was a non-competitive inhibitor of chitin synthase. The antifungal assays showed that compounds 12d, 12g, 12j, 12l and 12m exhibited a broad-spectrum of antifungal activity against the four strains tested in vitro. In which, compounds 12g and 12j had stronger antifungal activity against four tested strains than that of polyoxin B and similar to that of fluconazole, while compounds 12d, 12l and 12m showed antifungal activity comparable to that of polyoxin B against four tested strains. Meanwhile, compounds 12d, 12g, 12j, 12l and 12m exhibited good antifungal activity against fluconazole-resistant and micafungin-resistant fungi variants with MIC values ranging from 4 to 32 μg/mL while the MIC values of reference drugs were above 256 μg/mL. Furthermore, the results of drug-combination experiments showed that compounds 12d, 12g, 12j, 12l and 12m had synergistic or additive effects with fluconazole or polyoxin B. The results of sorbitol protection experiment and the experiment of antifungal activity against micafungin-resistant fungi further demonstrated that these compounds target chitin synthase. The result of cytotoxicity assay showed that compound 12g had low toxicity toward human lung cancer A549 cells and the ADME analysis in silico displayed that compound 12g possessed promising pharmacokinetic properties. The molecular docking indicated that compound 12g formed multiple hydrogen bond interactions binding to chitin synthase, which might be conductive to increasing the binding affinity and inhibiting the activity of chitin synthase. The above results indicated that the designed compounds were chitin synthase inhibitors with selectivity and broad-spectrum antifungal activity and could be act as the lead compounds against drug-resistant fungi.

Dasatinib in combination with BMS-754807 induce synergistic cytotoxicity in lung cancer cells through inhibiting lung cancer cell growth, and inducing autophagy as well as cell cycle arrest at the G1 phase

Lung cancer is the leading cause of cancer-related deaths worldwide. Combination of drugs targeting independent signaling pathways would effectively block the proliferation of cancer cells with lower concentrations and stronger synergy effects. Dasatinib, a multi-targeted protein tyrosine kinase inhibitor targeting BCR-ABL and kinases of SRC family, has been successfully applied in the treatment of chronic myeloid leukemia (CML). BMS-754807, an inhibitor targeting the insulin-like growth factor 1 receptor (IGF-IR) and insulin receptor (IR) family kinases, has been in phase I development for the treatment of a variety of human cancers. Herein, we demonstrated that dasatinib in combination with BMS-754807 inhibited lung cancer cell growth, while induced autophagy as well as cell cycle arrest at the G1 phase. Dasatinib in combination with BMS-754807 suppressed the expression of cell cycle marker proteins, Rb, p-Rb, CDK4, CDK6 and Cyclin D1, and the PI3K/Akt/mTOR signaling pathway. Dasatinib in combination with BMS-754807 induced autophagy in lung cancer cells, evidenced by the upregulation of LC3B II and beclin-1, the downregulation of LC3B I and SQSTM1/p62, and the autophagic flux observed with a confocal fluorescence microscopy. Furthermore, dasatinib (18 mg/kg) in combination with BMS-754807 (18 mg/kg) inhibited the growth of tumors in NCI-H3255 xenografts without changing the bodyweight. Overall, our results suggest that dasatinib in combination with BMS-754807 inhibits the lung cancer cell proliferation in vitro and tumor growth in vitro, which indicates promising evidence for the application of the drug combination in lung cancer therapy.

Nanoparticle-mediated synergistic drug combination for treating bone metastasis

Bone metastasis at an advanced disease stage is common in most solid tumors and is untreatable. Overexpression of receptor activator of nuclear factor κB ligand (RANKL) in tumor-bone marrow microenvironment drives a vicious cycle of tumor progression and bone resorption. Biodegradable nanoparticles (NPs), designed to localize in the tumor tissue in bone marrow, were evaluated in a prostate cancer model of bone metastasis. The combination treatment, encapsulating docetaxel, an anticancer drug (TXT-NPs), and Denosumab, a monoclonal antibody that binds to RANKL (DNmb-NPs), administered intravenously regressed the tumor completely, preventing bone resorption, without causing any mortality. With TXT-NPs alone treatment, after an initial regression, the tumor relapsed and acquired resistance, whereas DNmb-NPs alone treatment was ineffective. Only in the combination treatment RANKL was not detected in the tumor tibia, thus negating its role in tumor progression and bone resorption. The combination treatment was determined to be safe as the vital organ tissue showed no increase in inflammatory cytokine or liver ALT/AST levels, and the animals gained weight. Overall, dual drug treatment acted synergistically to modulate the tumor-bone microenvironment with encapsulation enhancing their therapeutic potency to achieve tumor regression.

HDACIs and TKIs combinations and their liposomal delivery for cancer treatment

Fixed-drug combinations have been used for the treatment of cancer. Current anticancer therapies, however, tend to induce resistance and provoke important toxicity. Therefore, there is still a need for further optimized treatments that would also take into account drug-drug interactions. Tyrosine kinase inhibitors (TKIs) and Histone deacetylase inhibitors (HDACIs) are two anticancer drug classes currently used separately in clinical practice. Those drug classes are currently being investigated in clinical trials. Several findings confirm the safety and tolerability of these treatments accompanied by clinical improvement. The activity and specificity of drug combinations can be further improved by employing appropriate drug delivery systems, such as nanocarrier systems. The different pharmacokinetic profiles of each drug may lead to a loss in synergistic effects, affecting treatment efficiency. Several combinations of either TKI or HDACI with an anticancer drug of another class co-loaded inside liposomal carriers are being investigated in vivo and show promising results in terms of efficacy and safety. In this review we discuss strategies for the delivery of synergistic drug combinations for cancer treatment.

Combination of furosemide, gold, and dopamine as a potential therapy for breast cancer

Breast cancer is one of the leading causes of death in women worldwide. Initially, it develops in the epithelium of the ducts or lobules of the breast glandular tissues with limited growth and the potential to metastasize. It is a highly heterogeneous malignancy; however, the common molecular mechanisms could help identify new targeted drugs for treating its subtypes. This study uses computational drug repositioning approaches to explore fresh drug candidates for breast cancer treatment. We also implemented reversal gene expression and gene expression-based signatures to explore novel drug candidates computationally. The drug activity profiles and related gene expression changes were acquired from the DrugBank, PubChem, and LINCS databases, and then in silico drug screening, molecular dynamics (MD) simulation, replica exchange MD simulations, and simulated annealing molecular dynamics (SAMD) simulations were conducted to discover and verify the valid drug candidates. We have found that compounds like furosemide, gold, and dopamine showed significant outcomes. Furthermore, the expression of genes related to breast cancer was observed to be reversed by these shortlisted drugs. Therefore, we postulate that combining furosemide, gold, and dopamine would be a potential combination therapy measurement for breast cancer patients.