Muscular toxicity of colchicine combined with statins: a real-world study based on the FDA adverse event reporting system database from 2004-2023.

Background: Through an analysis of the Food and Drug Administration Adverse Event Reporting System (FAERS), we explored the signal strength of adverse reactions (ADRs) related to myopathy caused by the combination of colchicine and statins and gained insight into the characteristics of these myopathy related ADRs. Methods: We extracted data from the FAERS database about ADRs in individuals with myopathy resulting from the combination of colchicine and statins. The analysis was conducted for the period spanning from January 2004 to December 2023 using the reported odds ratio (ROR) and information component (IC) methods to assess muscle-related ADR signals. Results: A total of 18,386 reports of statin myopathy-associated adverse reactions, 348 colchicine myopathy-associated adverse reactions, and 461 muscle-associated adverse reactions due to the combination of the two were collected; the strongest signals of statin myotoxicity events were for necrotizing myositis (ROR 50.47, 95% CL 41.74-61.01; IC 3.70 95% CL 3.25-4.08); the strongest signal for colchicine myotoxicity events was toxic myopathy (ROR 32.50, 95% CL 19.74-53.51; IC 4.97 95% CL 1.89-5.10), and the strongest signal for statins combined with colchicine was toxic myopathy (ROR 159.85, 95% CL 111.60-228.98; IC 7.22 95% CL 3.59-5.9); muscle-related adverse reactions signals were meaningful when the two drugs were combined in the order of colchicine combined with fluvastatin (ROR 187.38, 95% CL 96.68-363.17; IC 6.99 95% CL 1.65-5.68); colchicine combined with simvastatin in 135 cases (ROR 30.08. 95% CL 25.25-35.85; IC 4.80 95% CL 3.96-5.12); and colchicine combined with rosuvastatin (ROR 25.73, 95% CL 20.16-32.83; IC 4.59 95% CL 3.38-4.98) versus colchicine combined with atorvastatin (ROR 25.73, 95% CL 22.33-29.66; IC 4.59 95% CL 3.97-4.91) with almost identical signal intensity, followed by colchicine combined with pravastatin (ROR 13.67, 95% CL 9.17-20.37; IC 3.73 95% CL 1.87-4.47), whereas no signals were generated for lovastatin or pitavastatin. Conclusion: Similar ADRs can occur when colchicine and statins are used individually or in combination; however, the strength of these reactions may differ. To minimize the risk of drug interactions, statins with less potential interactions, such as lovastatin, pitavastatin, and pravastatin, should be chosen, and myopathy-related indices and symptoms should be closely monitored during use.

[Adverse effects of the tezacaftor/ivacaftor/elexacaftor combination that may lead to discontinuation: About a series of 10 cases]. / Effets indésirables de l'association tezacaftor/ivacaftor/elexacaftor pouvant mener à un arrêt de traitement : à propos d'une série de 10 cas.

INTRODUCTION: Cystic fibrosis transmembrane regulator (CFTR) channel modulators (ivacaftor, lumacaftor, tezacaftor and elexacaftor) represent a major advance in the management of cystic fibrosis. However, few data are available on the real-life safety profile of these medications, in particular on adverse events that may lead to their discontinuation. The aim of this study is to describe the characteristics and evolution of adverse reactions to the tezacaftor/ivacaftor/elexacaftor combination that led to discontinuation and were reported to the Centre régional de pharmacovigilance (CRPV) in Rennes (France). MATERIALS AND METHODS: A retrospective study was conducted from December 2021 to May 2023, focusing on cases of discontinuation of the tezacaftor/ivacaftor/elexacaftor combination due to the occurrence of one or more adverse effects, and reported to the CRPV of Rennes, France. RESULTS: Ten cases of drug discontinuation were reported to the Rennes CRPV (6 women/4 men). Adverse effects mainly involved neuropsychiatric disorders (n=6), followed by liver disorders (n=2), ear, nose and throat disorders (n=1), and digestive disorders (n=1). The average duration of treatment at discontinuation was 339.8 [39-668] days. The drug was reintroduced in 7 patients on average 48.7 [7-123] days after discontinuation, with a dosage adjustments (n=4) consisting of changes in dosing times or a reduction in daily doses, with varying success in alleviating adverse symptoms depending on the case. CONCLUSION: This small case series suggests that neuropsychiatric adverse effects may occur more frequently than initially described after initiation of tezacaftor/ivacaftor/elexacaftor, and should be carefully screened and monitored. Dosage or administration schedule modifications may be considered for patients experiencing these adverse effects. Further pharmacovigilance studies are needed to better understand the adverse effect profiles of "caftors", their possible risk factors, and the impact of adjusting dosing modalities.

Antiviral activity of vitamin D derivatives against severe fever with thrombocytopenia syndrome virus in vitro and in vivo.

Severe fever with thrombocytopenia syndrome virus (SFTSV) is a tick-borne virus that causes the severe fever thrombocytopenia syndrome, which manifests as fever and haemorrhage, accompanied by severe neurological complications. To date, no specific antiviral drugs have been approved for this indication. Herein, we investigated whether vitamin D derivatives inhibit SFTSV both in vitro and in vivo. An in vitro study demonstrated that vitamin D derivatives significantly suppressed viral RNA replication, plaque formation, and protein expression in a dose-dependent manner. Subsequently, in vivo studies revealed that doxercalciferol and alfacalcidol were associated with increased survival and reduced viral RNA load in the blood. Time-of-addition assay suggested that vitamin D derivatives primarily acted during the post-entry phase of SFTSV infection. However, cytopathic effect protective activity was not observed in RIG-I immunodeficient cell line Huh7.5, and the administration of vitamin D derivatives did not improve the survival rates or reduce the blood viral load in adult A129 mice. Further transcriptome exploration into the antiviral mechanism revealed that alfacalcidol stimulate host innate immunity to exert antiviral effects. To expand the application of vitamin D derivatives, in vitro and in vivo drug combination assays were performed, which highlighted the synergistic effects of vitamin D derivatives and T-705 on SFTSV. The combination of alfacalcidol and T-705 significantly enhanced the therapeutic effects in mice. This study highlights the potential of vitamin D derivatives against SFTSV and suggests that they may have synergistic effects with other compounds used in the treatment of SFTSV infection.

Synergistic action of antimicrobial peptides and antibiotics: current understanding and future directions.

Antibiotic resistance is a growing global problem that requires innovative therapeutic approaches and strategies for administering antibiotics. One promising approach is combination therapy, in which two or more drugs are combined to combat an infection. Along this line, the combination of antimicrobial peptides (AMPs) with conventional antibiotics has gained attention mainly due to the complementary mechanisms of action of AMPs and conventional antibiotics. In this article, we review both in vitro and in vivo studies that explore the synergy between AMPs and antibiotics. We highlight several mechanisms through which synergy is observed in in vitro experiments, including increasing membrane permeability, disrupting biofilms, directly potentiating antibiotic efficacy, and inhibiting resistance development. Moreover, in vivo studies reveal additional mechanisms such as enhanced/modulated immune responses, reduced inflammation, and improved tissue regeneration. Together, the current literature demonstrates that AMP-antibiotic combinations can substantially enhance efficacy of antibiotic therapies, including therapies against resistant bacteria, which represents a valuable enhancement to current antimicrobial strategies.

The Efficiency and Safety of Triple-Drug Combination of Albumin-Bound Paclitaxel, Anlotinib and PD-1/L1 Inhibitors in the 2nd or Above Line of Advanced NSCLC: A Retrospective Cohort Study.

Background: Existing research data indicates that albumin-bound paclitaxel (nab-ptx), anlotinib, and PD-1/L1 inhibitors have individually shown efficacy in second-line and subsequent treatments for advanced non-small cell lung cancer (NSCLC). This study seeks to investigate the potential of an optimized treatment regimen in this context by combining these three drugs and evaluating both efficacy and safety outcomes. Patients and Methods: Between January 2020 and January 2022, we collected data from pre-treated advanced NSCLC patients who received a combination therapy of nab-ptx, anlotinib, and PD-1/L1 inhibitors as a second-line or later treatment. The primary endpoints for the study included the objective response rate (ORR), progression-free survival (PFS), disease control rate (DCR) and overall survival (OS), while adverse events (AEs) were also recorded. Results: Our findings revealed that the ORR of this regimen in pretreated NSCLC patients was 35.71%, with mean PFS of 5.0 months and mean OS of 10.0 months. Further analysis suggested correlations between the efficacy of the regimen and factors such as PD-L1 expression levels, the occurrence of certain types of adverse events, and the status of NK cell activity. Additionally, the tolerable toxicity profile of this regimen indicates its potential applicability in the treatment of pretreated advanced NSCLC. Conclusion: Our study displayed that triple-drug combination of nab-ptx, anlotinib and PD-1/L1 inhibitors showed promising efficiency and tolerated cytotoxicity in the 2nd or above line treatment of advanced NSCLC, indicating the potential of such regimen as an important option for second-line treatment of advanced NSCLC. However, due to limitations in patient numbers, its actual clinical value awaits further research confirmation.

Synergistic antitumor effect of liposomal-based formulations of olaparib and topotecan in primary epithelial ovarian cancer cells.

BACKGROUND: Olaparib is a PARP inhibitor inducing synthetic lethality in tumors with deficient homologous recombination (HRD) caused by BRCA1/2 mutations. The FDA has approved monotherapy for first-line platinum-sensitive, recurrent high-grade epithelial ovarian cancer. Combination therapy alongside DNA-damaging therapeutics is a promising solution to overcome the limited efficacy in patients with HRD. The present study was designed to develop topotecan- and olaparib-loaded liposomes (TLL and OLL) and assess the effectiveness of their combination in patient-derived ovarian cancer samples. METHODS: We used HEOC, four clear-cell tumors (EOC 1-4), malignant ascites, and an OCI-E1p endometrioid primary ovarian cancer cell line and performed NGS analysis of BRCA1/2 mutation status. Antiproliferative activity was determined with the MTT assay. The Chou-Talalay algorithm was used to investigate the in vitro pharmacodynamic interactions of TLLs and OLLs. RESULTS: The OLL showed significantly higher efficacy in all ovarian cancer types with wild-type BRCA1/2 than a conventional formulation, suggesting potential for increased in vivo efficacy. The TLL revealed substantially higher toxicity to EOC 1, EOC 3, ascites and lower toxicity to HEOC than the standard formulation, suggesting better therapeutic efficacy and safety profile. The combination of studied compounds showed a higher reduction in cell viability than drugs used individually, demonstrating a synergistic antitumor effect at most of the selected concentrations. CONCLUSIONS: The concentration-dependent response of different ovarian cancer cell types to combination therapy confirms the need for in vitro optimization to maximize drug cytotoxicity. The OLL and TLL combination is a promising formulation for further animal studies, especially for eliminating epithelial ovarian cancer with wild-type BRCA1/2.

Computational modeling of drug response identifies mutant-specific constraints for dosing panRAF and MEK inhibitors in melanoma.

Purpose: This study explores the potential of preclinical in vitro cell line response data and computational modeling in identifying optimal dosage requirements of pan-RAF (Belvarafenib) and MEK (Cobimetinib) inhibitors in melanoma treatment. Our research is motivated by the critical role of drug combinations in enhancing anti-cancer responses and the need to close the knowledge gap around selecting effective dosing strategies to maximize their potential. Results: In a drug combination screen of 43 melanoma cell lines, we identified unique dosage landscapes of panRAF and MEK inhibitors for NRAS vs BRAF mutant melanomas. Both experienced benefits, but with a notably more synergistic and narrow dosage range for NRAS mutant melanoma. Computational modeling and molecular experiments attributed the difference to a mechanism of adaptive resistance by negative feedback. We validated in vivo translatability of in vitro dose-response maps by accurately predicting tumor growth in xenografts. Then, we analyzed pharmacokinetic and tumor growth data from Phase 1 clinical trials of Belvarafenib with Cobimetinib to show that the synergy requirement imposes stricter precision dose constraints in NRAS mutant melanoma patients. Conclusion: Leveraging pre-clinical data and computational modeling, our approach proposes dosage strategies that can optimize synergy in drug combinations, while also bringing forth the real-world challenges of staying within a precise dose range.

The combination of paeoniflorin and metformin synergistically inhibits the progression of liver fibrosis in mice.

Liver fibrosis is a pathological process that endangers human health, for which effective treatments remain elusive to date. Paeoniflorin (PAE), a pineane-type monoter penoid compound from the traditional Chinese medicine PaeoniaeRubra Radix, and metformin (MET), an oral biguanide hypoglycemic agent, both demonstrate anti-inflammatory and hepatoprotective effects. In current work, we first discovered that the combined treatment of PAE and MET synergistically inhibited the progression of liver fibrosis in two different animal models: therapeutic and preventive. This therapeutic effect is evidenced by a reduction in the expression levels of liver fibrosis markers and an improvement in histopathological characteristics. Mechanistic exploration further revealed that this combination therapy downregulated the expression of TGF-ß1 and p-Smad2, while upregulating Smad7 expression in both models. Importantly, we also found that this combinatorial approach significantly reduced hepatotoxicity and nephrotoxicity in both models. Our findings suggest an effective combination therapy for liver fibrosis and provide the possibility of therapeutic improvement for patients with liver fibrosis.

MMFSyn: A Multimodal Deep Learning Model for Predicting Anticancer Synergistic Drug Combination Effect.

Combination therapy aims to synergistically enhance efficacy or reduce toxic side effects and has widely been used in clinical practice. However, with the rapid increase in the types of drug combinations, identifying the synergistic relationships between drugs remains a highly challenging task. This paper proposes a novel deep learning model MMFSyn based on multimodal drug data combined with cell line features. Firstly, to ensure the full expression of drug molecular features, multiple modalities of drugs, including Morgan fingerprints, atom sequences, molecular diagrams, and atomic point cloud data, are extracted using SMILES. Secondly, for different modal data, a Bi-LSTM, gMLP, multi-head attention mechanism, and multi-scale GCNs are comprehensively applied to extract the drug feature. Then, it selects appropriate omics features from gene expression and mutation omics data of cancer cell lines to construct cancer cell line features. Finally, these features are combined to predict the synergistic anti-cancer drug combination effect. The experimental results verify that MMFSyn has significant advantages in performance compared to other popular methods, with a root mean square error of 13.33 and a Pearson correlation coefficient of 0.81, which indicates that MMFSyn can better capture the complex relationship between multimodal drug combinations and omics data, thereby improving the synergistic drug combination prediction.

Drug Combination Nanoparticles Containing Gemcitabine and Paclitaxel Enable Orthotopic 4T1 Breast Tumor Regression.

Early diagnosis, intervention, and therapeutic advancements have extended the lives of breast cancer patients; however, even with molecularly targeted therapies, many patients eventually progress to metastatic cancer. Recent data suggest that residual breast cancer cells often reside in the lymphatic system before rapidly spreading through the bloodstream. To address this challenge, an effective drug combination composed of gemcitabine (G) and paclitaxel (T) is administered intravenously in sequence at the metastatic stage, but intravenous GT infusion may limit lymphatic GT drug accessibility and asynchronous drug exposure in cancer cells within the lymph. To determine whether co-localization of intracellular gemcitabine and paclitaxel (referred to as GT) could overcome these limitations and enhance the efficacy of GT, we have evaluated a previously reported GT drug-combination formulated in nanoparticle (referred to as GT-in-DcNP) evaluated in an orthotopic breast tumor model. Previously, with indocyanine green-labeled nanoparticles, we reported that GT-in-DcNP particles after subcutaneous dosing were taken up rapidly and preferentially into the lymph instead of blood vessels. The pharmacokinetic study showed enhanced co-localization of GT within the tumors and likely through lymphatic access, before drug apparency in the plasma leading to apparent long-acting plasma time-course. The mechanisms may be related to significantly greater inhibitions of tumor growth-by 100 to 140 times-in both sub-iliac and axillary regions compared to the equivalent dosing with free-and-soluble GT formulation. Furthermore, GT-in-DcNP exhibited dose-dependent effects with significant tumor regression. In contrast, even at the highest dose of free GT combination, only a modest tumor growth reduction was notable. Preliminary studies with MDA-231-HM human breast cancer in an orthotopic xenograft model indicated that GT-in-DcNP may be effective in suppressing human breast tumor growth. Taken together, the synchronized delivery of GT-in-DcNP to mammary tumors through the lymphatic system offers enhanced cellular retention and greater efficacy.

Computational Modeling of Drug Response Identifies Mutant-Specific Constraints for Dosing panRAF and MEK Inhibitors in Melanoma.

PURPOSE: This study explores the potential of pre-clinical in vitro cell line response data and computational modeling in identifying the optimal dosage requirements of pan-RAF (Belvarafenib) and MEK (Cobimetinib) inhibitors in melanoma treatment. Our research is motivated by the critical role of drug combinations in enhancing anti-cancer responses and the need to close the knowledge gap around selecting effective dosing strategies to maximize their potential. RESULTS: In a drug combination screen of 43 melanoma cell lines, we identified specific dosage landscapes of panRAF and MEK inhibitors for NRAS vs. BRAF mutant melanomas. Both experienced benefits, but with a notably more synergistic and narrow dosage range for NRAS mutant melanoma (mean Bliss score of 0.27 in NRAS vs. 0.1 in BRAF mutants). Computational modeling and follow-up molecular experiments attributed the difference to a mechanism of adaptive resistance by negative feedback. We validated the in vivo translatability of in vitro dose-response maps by predicting tumor growth in xenografts with high accuracy in capturing cytostatic and cytotoxic responses. We analyzed the pharmacokinetic and tumor growth data from Phase 1 clinical trials of Belvarafenib with Cobimetinib to show that the synergy requirement imposes stricter precision dose constraints in NRAS mutant melanoma patients. CONCLUSION: Leveraging pre-clinical data and computational modeling, our approach proposes dosage strategies that can optimize synergy in drug combinations, while also bringing forth the real-world challenges of staying within a precise dose range. Overall, this work presents a framework to aid dose selection in drug combinations.

Analysis of the PARAGON-HF Study Results Using Win Ratio.

BACKGROUND: The PARAGON-HF study (Prospective Comparison of ARNI With ARB Global Outcomes in Heart Failure With Preserved Ejection Fraction) investigated the effect of sacubitril-valsartan in heart failure (HF) with preserved ejection fraction. The results, which were analyzed using conventional statistical methods, did not find a significant reduction in the primary composite end point of cardiovascular death and total hospitalization for HF. Recent clinical trials used win ratio statistics that enable the incorporation of multiple outcome aspects into the primary end point and can detect positive outcomes with fewer patients. In this study, we assessed the effect of sacubitril-valsartan on outcomes using the win ratio to analyze results from patients included in the PARAGON-HF study. METHODS: In the PARAGON-HF study, 4822 patients with HF with preserved ejection fraction were randomized either to sacubitril-valsartan or valsartan groups. In the present study, the primary outcome was a hierarchical composite of time to cardiovascular death, total number of hospitalization for HF, time to first hospitalization for HF, time to renal composite outcome, and change in the Kansas City Cardiomyopathy Questionnaire total symptom score at 8 months analyzed using a win ratio statistical model. RESULTS: Using this approach, we found that a greater number of patients who received sacubitril-valsartan experienced clinical benefits compared with those who received valsartan (win ratio, 1.13 [95% CI, 1.04-1.23]; P=0.005). This clinical advantage was evident in patients regardless of whether the left ventricular ejection fraction was above or below the median, that is, the left ventricular ejection fraction of 57%, and regardless of sex (Pinteraction=0.76 for the left ventricular ejection fraction and 0.73 for sex). CONCLUSIONS: Employing the innovative win ratio approach, sacubitril-valsartan demonstrated significant clinical benefits among patients with HF with preserved ejection fraction. Notably, this benefit was observed irrespective of left ventricular ejection fraction and sex. REGISTRATION: URL: https://www.clinicaltrials.gov; Unique identifier: NCT01920711.

The many dimensions of combination therapy: How to combine antibiotics to limit resistance evolution.

In combination therapy, bacteria are challenged with two or more antibiotics simultaneously. Ideally, separate mutations are required to adapt to each of them, which is a priori expected to hinder the evolution of full resistance. Yet, the success of this strategy ultimately depends on how well the combination controls the growth of bacteria with and without resistance mutations. To design a combination treatment, we need to choose drugs and their doses and decide how many drugs get mixed. Which combinations are good? To answer this question, we set up a stochastic pharmacodynamic model and determine the probability to successfully eradicate a bacterial population. We consider bacteriostatic and two types of bactericidal drugs-those that kill independent of replication and those that kill during replication. To establish results for a null model, we consider non-interacting drugs and implement the two most common models for drug independence-Loewe additivity and Bliss independence. Our results show that combination therapy is almost always better in limiting the evolution of resistance than administering just one drug, even though we keep the total drug dose constant for a 'fair' comparison. Yet, exceptions exist for drugs with steep dose-response curves. Combining a bacteriostatic and a bactericidal drug which can kill non-replicating cells is particularly beneficial. Our results suggest that a 50:50 drug ratio-even if not always optimal-is usually a good and safe choice. Applying three or four drugs is beneficial for treatment of strains with large mutation rates but adding more drugs otherwise only provides a marginal benefit or even a disadvantage. By systematically addressing key elements of treatment design, our study provides a basis for future models which take further factors into account. It also highlights conceptual challenges with translating the traditional concepts of drug independence to the single-cell level.

Anticancer Potential of Valencia Peanut (Arachis hypogaea L.) Skin Extract against Cervical Cancer Cells In Vitro and in Nude Mouse Xenograft Models.

This study investigated the impact of Valencia KK4-type peanut skin ethanolic extract (KK4-PSE) combined with cisplatin or 5-fluorouracil (5-FU) on HeLa cells in vitro and in xenograft models. At exposure times of 24, 48 and 72 h, KK4-PSE inhibited the growth of HeLa cells with a half maximal inhibitory concentration (IC50) of 79.43 ± 0.54, 55.55 ± 1.57 and 41.32 ± 0.74 µg/mL, respectively. Drug interactions evaluated by the Chou-Talalay method demonstrated that KK4-PSE enhanced antiproliferative activity of 5-FU against HeLa cells with combination index (CI) values of 0.49 (48 h) and 0.60 (72 h), indicating a synergistic effect, while KK4-PSE combined with cisplatin exhibited an additive effect (CI = 1.02) at 72 h, and an antagonistic effect at 24 and 48 h exposures (CI = 1.12 and 1.18, respectively). In nude mouse xenograft models, the combination of 5-FU and KK4-PSE markedly reduced HeLa tumor weights compared with the control and single agent treatments groups. The combination of KK4-PSE and 5-FU achieved greater tumor growth inhibition than that of the KK4-PSE-cisplatin combination. KK4-PSE mitigated hepatotoxicity induced by both cisplatin and 5-FU in nude mice. The spleen hyaloserositis was significantly reduced in the combination treatment of 5-FU and KK4-PSE. These results suggest that KK4-PSE has the potential to limit cervical cancer cell proliferation while reducing the toxicity of cisplatin and 5-FU.

SAFER: sub-hypergraph attention-based neural network for predicting effective responses to dose combinations.

BACKGROUND: The potential benefits of drug combination synergy in cancer medicine are significant, yet the risks must be carefully managed due to the possibility of increased toxicity. Although artificial intelligence applications have demonstrated notable success in predicting drug combination synergy, several key challenges persist: (1) Existing models often predict average synergy values across a restricted range of testing dosages, neglecting crucial dose amounts and the mechanisms of action of the drugs involved. (2) Many graph-based models rely on static protein-protein interactions, failing to adapt to dynamic and higher-order relationships. These limitations constrain the applicability of current methods. RESULTS: We introduce SAFER, a Sub-hypergraph Attention-based graph model, addressing these issues by incorporating complex relationships among biological knowledge networks and considering dosing effects on subject-specific networks. SAFER outperformed previous models on the benchmark and the independent test set. The analysis of subgraph attention weight for the lung cancer cell line highlighted JAK-STAT signaling pathway, PRDM12, ZNF781, and CDC5L that have been implicated in lung fibrosis. CONCLUSIONS: SAFER presents an interpretable framework designed to identify drug-responsive signals. Tailored for comprehending dose effects on subject-specific molecular contexts, our model uniquely captures dose-level drug combination responses. This capability unlocks previously inaccessible avenues of investigation compared to earlier models. Furthermore, the SAFER framework can be leveraged by future inquiries to investigate molecular networks that uniquely characterize individual patients and can be applied to prioritize personalized effective treatment based on safe dose combinations.

Advances in nano-preparations for improving tetrandrine solubility and bioavailability.

Tetrandrine (TET) is a natural bis-benzylisoquinoline alkaloid isolated from Stephania species with a wide range of biological and pharmacologic activities; it mainly serves as an anti-inflammatory agent or antitumor adjuvant in clinical applications. However, limitations such as prominent hydrophobicity, severe off-target toxicity, and low absorption result in suboptimal therapeutic outcomes preventing its widespread adoption. Nanoparticles have proven to be efficient devices for targeted drug delivery since drug-carrying nanoparticles can be passively transported to the tumor site by the enhanced permeability and retention (EPR) effects, thus securing a niche in cancer therapies. Great progress has been made in nanocarrier construction for TET delivery due to their outstanding advantages such as increased water-solubility, improved biodistribution and blood circulation, reduced off-target irritation, and combinational therapy. Herein, we systematically reviewed the latest advancements in TET-loaded nanoparticles and their respective features with the expectation of providing perspective and guidelines for future research and potential applications of TET.

Use of Drug Sensitisers to Improve Therapeutic Index in Cancer.

The clinical management of malignant tumours is challenging, often leading to severe adverse effects and death. Drug resistance (DR) antagonises the effectiveness of treatments, and increasing drug dosage can worsen the therapeutic index (TI). Current efforts to overcome DR predominantly involve the use of drug combinations, including applying multiple anti-cancerous drugs, employing drug sensitisers, which are chemical agents that enhance pharmacokinetics (PK), including the targeting of cellular pathways and regulating pertinent membrane transporters. While combining multiple compounds may lead to drug-drug interactions (DDI) or polypharmacy effect, the use of drug sensitisers permits rapid attainment of effective treatment dosages at the disease site to prevent early DR and minimise side effects and will reduce the chance of DDI as lower drug doses are required. This review highlights the essential use of TI in evaluating drug dosage for cancer treatment and discusses the lack of a unified standard for TI within the field. Commonly used benefit-risk assessment criteria are summarised, and the critical exploration of the current use of TI in the pharmaceutical industrial sector is included. Specifically, this review leads to the discussion of drug sensitisers to facilitate improved ratios of effective dose to toxic dose directly in humans. The combination of drug and sensitiser molecules might see additional benefits to rekindle those drugs that failed late-stage clinical trials by the removal of detrimental off-target activities through the use of lower drug doses. Drug combinations and employing drug sensitisers are potential means to combat DR. The evolution of drug combinations and polypharmacy on TI are reviewed. Notably, the novel binary weapon approach is introduced as a new opportunity to improve TI. This review emphasises the urgent need for a criterion to systematically evaluate drug safety and efficiency for practical implementation in the field.

Why Is Wnt/ß-Catenin Not Yet Targeted in Routine Cancer Care?

Despite significant progress in cancer prevention, screening, and treatment, the still limited number of therapeutic options is an obstacle towards increasing the cancer cure rate. In recent years, many efforts were put forth to develop therapeutics that selectively target different components of the oncogenic Wnt/ß-catenin signaling pathway. These include small molecule inhibitors, antibodies, and more recently, gene-based approaches. Although some of them showed promising outcomes in clinical trials, the Wnt/ß-catenin pathway is still not targeted in routine clinical practice for cancer management. As for most anticancer treatments, a critical limitation to the use of Wnt/ß-catenin inhibitors is their therapeutic index, i.e., the difficulty of combining effective anticancer activity with acceptable toxicity. Protecting healthy tissues from the effects of Wnt/ß-catenin inhibitors is a major issue due to the vital role of the Wnt/ß-catenin signaling pathway in adult tissue homeostasis and regeneration. In this review, we provide an up-to-date summary of clinical trials on Wnt/ß-catenin pathway inhibitors, examine their anti-tumor activity and associated adverse events, and explore strategies under development to improve the benefit/risk profile of this therapeutic approach.

Design and modeling of order of addition experiment with component effects.

An order of addition experiment is an experiment to study how the order of addition of components affect the results, with the objective of predicting and determining the optimal order of addition of components. Order of addition experiment are also commonly used in the drug combination therapy, where experimenting with all drugs combinations is unaffordable. To solve this problem, we constructed a new design table, two-level component factorial design table (TLCF), which combine the component orthogonal array design table and the two-level partial factorial design table by matrix product. TLCF can explore the order and dosage effect of components on the results and can greatly reduce the number of experiments. We also prove that the relative D-efficiency of the TLCF can reach 100% and solve an explicit expression for the D-efficiency of the full design. In the simulation experiment, we compare the D-efficiency of the TLCF with the random design table to prove the superiority of TLCF. Finally, we give a treatment plan for the combination of three drugs for glioblastoma based on the TLCF, which provides a new perspective for the precision treatment of patients.

Ex vivo platform en route to functional precision medicine: clinical relevance in gynecological cancers.

A scientific interrogation-driven approach to the clinical management of cancer patients is based on molecular profiling of the tumor. Empowered by the knowledge of oncogenic drivers and biomarkers, oncologists chart an optimal treatment path toward increasing the mathematical probability of a positive outcome. In this entire chain of events, an experimental proof of logical interrogation has never been incorporated before. Here, we provide the first evidence that the result of ex vivo testing of a drug matched to the genomic profiling of an N-of-1 tumor can deliver meaningful insight connecting scientific interrogation and a clinical event. Using resected tissues from endometrial (EC) and ovarian (OC) cancer patients, we designed a personalized ex vivo platform to test combinations of drugs in the default histological architecture of the individual tumors. Following the CART-T cells' principle, we co-cultured with autologous T-cells to test targeted drugs and immune checkpoint inhibitors. The study was designed with a limited clinical information window from patient registration/consent to obtaining the tumor tissues, and adjuvant treatment/post-surgery event (PSE) data were accessed retrospectively. Using a checkerboard analysis, we found that PSE-free survival time was longer in patients whose therapy "matched" the effective drug combination in ex vivo culture/co-cultures compared to those with no effect. Specifically, out of 32 EC patients in the "test & treatment-matched" category whose tumor cells failed to respond to ex vivo drug testing, none achieved > 4 and > 3 years of PSE-free survival. In contrast, out of 38 EC patients in the "test & treatment-matched" category, 4 and 6 patients, whose tumor cells responded to drugs in ex vivo culture, achieved > 4 and > 3 years of PSE-free survival, respectively. Cases with genomically-guided ex vivo testing showed that a "match" between an effective ex vivo drug combination and therapy resulted in late PSE, whereas a "match" between prescribed treatment and an ineffective drug combination in ex vivo testing led to early PSE. Our study demonstrates that integrating genomic data with personalized drug testing on an ex vivo culture/co-culture platform is an effective tool for modeling functional precision medicine in gynecological cancers. This approach bridges the gap between next-generation drug testing in translational research and patient care, providing insight for improved treatment outcomes.