Evaluating class III antiarrhythmic agents as novel MYC targeting drugs in ovarian cancer

Tabersonine Enhances Olaparib Sensitivity through FHL1-Mediated Epithelial-Mesenchymal Transition in an Ovarian Tumor

Ovarian cancer (OVC) is one of the most aggressive gynecological malignancies worldwide. Although olaparib treatment has shown favorable outcomes against the treatment of OVC, its effectiveness remains limited in some OVC patients. Investigating new strategies to improve the therapeutic efficacy of olaparib against OVC is imperative. Our study identified tabersonine, a natural indole alkaloid, for its potential to increase the chemosensitivity of olaparib in OVC. The combined treatment of olaparib and tabersonine synergistically inhibited cell proliferation in OVC cells and suppressed tumor growth in A2780 xenografts. The combined treatment effectively suppressed epithelial-mesenchymal transition (EMT) by altering the expression of E-cadherin, N-cadherin, and vimentin and induced DNA damage responses. Integrating quantitative proteomics, FHL1 was identified as a potential regulator to modulate EMT after tabersonine treatment. Increased expression of FHL1 was induced by tabersonine treatment, while downregulation of FHL1 reversed the inhibitory effects of tabersonine on OVC cells by mediating EMT. In vivo findings further reflected that the combined treatment of tabersonine and olaparib significantly inhibited tumor growth and OVC metastasis through upregulation of FHL1. Our findings reveal the role of tabersonine in improving the sensitivity of olaparib in OVC through FHL1-mediated EMT, suggesting that tabersonine holds promise for future application in OVC treatment.

Drug repositioning and ovarian cancer, a study based on Mendelian randomisation analysis

Background

The role of drug repositioning in the treatment of ovarian cancer has received increasing attention. Although promising results have been achieved, there are also major controversies.

Methods

In this study, we conducted a drug-target Mendelian randomisation (MR) analysis to systematically investigate the reported effects and relevance of traditional drugs in the treatment of ovarian cancer. The inverse-variance weighted (IVW) method was used in the main analysis to estimate the causal effect. Several MR methods were used simultaneously to test the robustness of the results.

Results

By screening 31 drugs with 110 targets, FNTA, HSPA5, NEU1, CCND1, CASP1, CASP3 were negatively correlated with ovarian cancer, and HMGCR, PLA2G4A, ITGAL, PTGS1, FNTB were positively correlated with ovarian cancer.

Conclusion

Statins (HMGCR blockers), lonafarnib (farnesyltransferase inhibitors), the anti-inflammatory drug aspirin, and the anti-malarial drug adiponectin all have potential therapeutic roles in ovarian cancer treatment.

Microfluidic production of amiodarone loaded nanoparticles and application in drug repositioning in ovarian cancer

Amiodarone repositioning in cancer treatment is promising, however toxicity limits seem to arise, constraining its exploitability. Notably, amiodarone has been investigated for the treatment of ovarian cancer, a tumour known for metastasizing within the peritoneal cavity. This is associated with an increase of fatty acid oxidation, which strongly depends on CPT1A, a transport protein which has been found overexpressed in ovarian cancer. Amiodarone is an inhibitor of CPT1A but its role still has to be explored. Therefore, in the present study, amiodarone was tested on ovarian cancer cell lines with a focus on lipid alteration, confirming its activity. Moreover, considering that drug delivery systems could lower drug side effects, microfluidics was employed for the development of drug delivery systems of amiodarone obtaining simultaneously liposomes with a high payload and amiodarone particles. Prior to amiodarone loading, microfluidics production was optimized in term of temperature and flow rate ratio. Moreover, stability over time of particles was evaluated. In vitro tests confirmed the efficacy of the drug delivery systems.

Gut-microbiota-microglia-brain interactions in Alzheimer's disease: knowledge-based, multi-dimensional characterization

BACKGROUND

Interactions between the gut microbiota, microglia, and aging may modulate Alzheimer's disease (AD) pathogenesis but the precise nature of such interactions is not known.

METHODS

We developed an integrated multi-dimensional, knowledge-driven, systems approach to identify interactions among microbial metabolites, microglia, and AD. Publicly available datasets were repurposed to create a multi-dimensional knowledge-driven pipeline consisting of an integrated network of microbial metabolite-gene-pathway-phenotype (MGPPN) consisting of 34,509 nodes (216 microbial metabolites, 22,982 genes, 1329 pathways, 9982 mouse phenotypes) and 1,032,942 edges.

RESULTS

We evaluated the network-based ranking algorithm by showing that abnormal microglia function and physiology are significantly associated with AD pathology at both genetic and phenotypic levels: AD risk genes were ranked at the top 6.4% among 22,982 genes, P < 0.001. AD phenotypes were ranked at the top 11.5% among 9982 phenotypes, P < 0.001. A total of 8094 microglia-microbial metabolite-gene-pathway-phenotype-AD interactions were identified for top-ranked AD-associated microbial metabolites. Short-chain fatty acids (SCFAs) were ranked at the top among prioritized AD-associated microbial metabolites. Through data-driven analyses, we provided evidence that SCFAs are involved in microglia-mediated gut-microbiota-brain interactions in AD at both genetic, functional, and phenotypic levels.

CONCLUSION

Our analysis produces a novel framework to offer insights into the mechanistic links between gut microbial metabolites, microglia, and AD, with the overall goal to facilitate disease mechanism understanding, therapeutic target identification, and designing confirmatory experimental studies.

Drugs Repurposing in High-Grade Serous Ovarian Cancer

BACKGROUND

Ovary Carcinoma (OC) is the most lethal gynecological neoplasm due to the late diagnoses and to the common development of resistance to platinum-based chemotherapy. Thus, novel therapeutic approaches are urgently required. In this regard, the strategy of drug repurposing is becoming attractive. By this approach, the effectiveness of a drug originally developed for another indication is tested in a different pathology. The advantage is that data about pharmacokinetic properties and toxicity are already available. Thus, in principle, it is possible to reduce research costs and to speed up drug usage/marketing.

RESULTS

Here, some noticeable examples of repurposed drugs for OC, such as amiodarone, ruxolitinib, statins, disulfiram, ormeloxifenem, and Quinacrine, are reported. Amiodarone, an antiarrhythmic agent, has shown promising anti-OC activity, although the systemic toxicity should not be neglected. The JAK inhibitor, Ruxolitinib, may be employed particularly in coadministration with standard OC therapy as it synergistically interacts with platinum-based drugs. Particularly interesting is the use of statin which represent one of the most commonly administered drugs in aged population to treat hypercholesterolemia. Disulfiram, employed in the treatment of chronic alcoholism, has shown anti-OC properties. Ormeloxifene, commonly used for contraception, seems to be promising, especially due to the negligible side effects. Finally, Quinacrine used as an antimicrobial and anti-inflammatory drug, is able to downregulate OC cell growth and promote cell death.

CONCLUSION

Whereas further testing in patients are necessary to better clarify the therapeutic potential of repurposed drugs for OC, it is believed that their use, better if combined with OC targeted delivery systems, can significantly contribute to the development of novel and effective anti-OC treatments.

Data-driven multiple-level analysis of gut-microbiome-immune-joint interactions in rheumatoid arthritis

Background

Rheumatoid arthritis (RA) is the most common autoimmune disease and affects about 1% of the population. The cause of RA remains largely unknown and could result from a complex interaction between genes and environment factors. Recent studies suggested that gut microbiota and their collective metabolic outputs exert profound effects on the host immune system and are implicated in RA. However, which and how gut microbial metabolites interact with host genetics in contributing to RA pathogenesis remains unknown. In this study, we present a data-driven study to understand how gut microbial metabolites contribute to RA at the genetic, functional and phenotypic levels.

Results

We used publicly available disease genetics, chemical genetics, human metabolome, genetic signaling pathways, mouse genome-wide mutation phenotypes, and mouse phenotype ontology data. We identified RA-associated microbial metabolites and prioritized them based on their genetic, functional and phenotypic relevance to RA. We evaluated the prioritization methods using short-chain fatty acids (SCFAs), which were previously shown to be involved in RA etiology. We validate the algorithms by showing that SCFAs are highly associated with RA at genetic, functional and phenotypic levels: SCFAs ranked at top 3.52% based on shared genes with RA, top 5.69% based on shared genetic pathways, and top 16.94% based on shared phenotypes. Based on the genetic-level analysis, human gut microbial metabolites directly interact with many RA-associated genes (as many as 18.1% of all 166 RA genes). Based on the functional-level analysis, human gut microbial metabolites participate in many RA-associated genetic pathways (as many as 71.4% of 311 genetic pathways significantly enriched for RA), including immune system pathways. Based on the phenotypic-level analysis, gut microbial metabolites affect many RA-related phenotypes (as many as 51.3% of 978 phenotypes significantly enriched for RA), including many immune system phenotypes.

Conclusions

Our study demonstrates strong gut-microbiome-immune-joint interactions in RA, which converged on both genetic, functional and phenotypic levels.