Related prophylaxis strategies should be implemented in patients involved with above-mentioned risk factors to prevent dislocation after revision THA.

Immune checkpoint blockade (ICB) has rapidly transformed the treatment paradigm for various cancer types. Multiple single or combinations of ICB treatments have been approved by the US Food and Drug Administration, providing more options for patients with advanced cancer. However, most patients could not benefit from these immunotherapies due to primary and acquired drug resistance. Thus, a better understanding of the mechanisms of ICB resistance is urgently needed to improve clinical outcomes. Here, we focused on the changes in the biological functions of CD8+ T cells to elucidate the underlying resistance mechanisms of ICB therapies and summarized the advanced coping strategies to increase ICB efficacy. Combinational ICB approaches and individualized immunotherapies require further in-depth investigation to facilitate longer-lasting efficacy and a more excellent safety of ICB in a broader range of patients.

No abstract

Background Prediction of drug response based on multi-omics data is a crucial task in the research of personalized cancer therapy. Results We proposed an iterative sure independent ranking and screening (ISIRS) scheme to select drug response-associated features and applied it to the Cancer Cell Line Encyclopedia (CCLE) dataset. For each drug in CCLE, we incorporated multi-omics data including copy number alterations, mutation and gene expression and selected up to 50 features using ISIRS. Then a linear regression model based on the selected features was exploited to predict the drug response. Cross validation test shows that our prediction accuracies are higher than existing methods for most drugs. Conclusions Our study indicates that the features selected by the marginal utility measure, which measures the conditional probability of drug responses given the feature, are helpful for drug response prediction.

No abstract