Chemoresistance and metastasis are the major challenges for the current ovarian cancer treatment. Understanding the mechanisms of ovarian cancer progression and metastasis is critically important for developing novel therapies. The advances in extracellular vesicles (EVs) research in recent years have attracted extensive attention. EVs contain a variety of proteins, RNAs, DNAs, and metabolites. Accumulating evidence indicates that ovarian cancer cells secrete a large amount of EVs, playing an important role in tumor progression and recurrence. In the microenvironment of ovarian tumor, EVs participate in the information transmission between stromal cells and immune cells, promoting the immune escape of ovarian cancer cells and facilitating cancer metastasis. Here, we review the recent advances of EVs in chemoresistance, mechanisms of metastasis, and immune evasion of ovarian cancer. Furthermore, we also discuss the challenges of EV research and future application of EVs as promising biomarker sources in response to therapy and in therapy-delivery approaches for ovarian cancer patients.

Extracellular vesicles (EVs) contain specific proteins, lipids, and nucleic acids that can be passed to other cells as signal molecules to alter their function. However, there are many problems and challenges in the conversion and clinical application of EVs. Storage and protection of EVs is one of the issues that need further research. To adapt to potential clinical applications, this type of problem must be solved. This review summarizes the storage practices of EVs in recent years, and explains the impact of temperature on the quality and stability of EVs during storage based on current research, and explains the potential mechanisms involved in this effect as much as possible.

No abstract

Background and Aims We need more pragmatic trials of interventions to improve care and outcomes for people living with Alzheimer’s disease and related dementias. However, these trials present unique methodological challenges in their design, analysis, and reporting—often, due to the presence of one or more sources of clustering. Failure to account for clustering in the design and analysis can lead to increased risks of Type I and Type II errors. We conducted a review to describe key methodological characteristics and obtain a “baseline assessment” of methodological quality of pragmatic trials in dementia research, with a view to developing new methods and practical guidance to support investigators and methodologists conducting pragmatic trials in this field. Methods We used a published search filter in MEDLINE to identify trials more likely to be pragmatic and identified a subset that focused on people living with Alzheimer’s disease or other dementias or included them as a defined subgroup. Pairs of reviewers extracted descriptive information and key methodological quality indicators from each trial. Results We identified N = 62 eligible primary trial reports published across 36 different journals. There were 15 (24%) individually randomized, 38 (61%) cluster randomized, and 9 (15%) individually randomized group treatment designs; 54 (87%) trials used repeated measures on the same individual and/or cluster over time and 17 (27%) had a multivariate primary outcome (e.g. due to measuring an outcome on both the patient and their caregiver). Of the 38 cluster randomized trials, 16 (42%) did not report sample size calculations accounting for the intracluster correlation and 13 (34%) did not account for intracluster correlation in the analysis. Of the 9 individually randomized group treatment trials, 6 (67%) did not report sample size calculations accounting for intracluster correlation and 8 (89%) did not account for it in the analysis. Of the 54 trials with repeated measurements, 45 (83%) did not report sample size calculations accounting for repeated measurements and 19 (35%) did not utilize at least some of the repeated measures in the analysis. No trials accounted for the multivariate nature of their primary outcomes in sample size calculation; only one did so in the analysis. Conclusion There is a need and opportunity to improve the design, analysis, and reporting of pragmatic trials in dementia research. Investigators should pay attention to the potential presence of one or more sources of clustering. While methods for longitudinal and cluster randomized trials are well developed, accessible resources and new methods for dealing with multiple sources of clustering are required. Involvement of a statistician with expertise in longitudinal and clustered designs is recommended.

No abstract