The tumor-associated antigen RHAMM (HMMR/CD168) is expressed by monocyte-derived dendritic cells and presented to T cells

We formerly demonstrated that vaccination with Wilms' tumor 1 (WT1)-loaded autologous monocyte-derived dendritic cells (mo-DCs) can be a well-tolerated effective treatment in acute myeloid leukemia (AML) patients. Here, we investigated whether we could introduce the receptor for hyaluronic acid-mediated motility (RHAMM/HMMR/CD168), another clinically relevant tumor-associated antigen, into these mo-DCs through mRNA electroporation and elicit RHAMM-specific immune responses. While RHAMM mRNA electroporation significantly increased RHAMM protein expression by mo-DCs, our data indicate that classical mo-DCs already express and present RHAMM at sufficient levels to activate RHAMM-specific T cells, regardless of electroporation. Moreover, we found that RHAMM-specific T cells are present at vaccination sites in AML patients. Our findings implicate that we and others who are using classical mo-DCs for cancer immunotherapy are already vaccinating against RHAMM

Evaluation of automated hypnogram analysis on multi-scored polysomnographies

A new method for automated sleep stage scoring of polysomnographies is proposed that uses a random forest approach to model feature interactions and temporal effects. The model mostly relies on features based on the rules from the American Academy of Sleep Medicine, which allows medical experts to gain insights into the model. A common way to evaluate automated approaches to constructing hypnograms is to compare the one produced by the algorithm to an expert's hypnogram. However, given the same data, two expert annotators will construct (slightly) different hypnograms due to differing interpretations of the data or individual mistakes. A thorough evaluation of our method is performed on a multi-labeled dataset in which both the inter-rater variability as well as the prediction uncertainties are taken into account, leading to a new standard for the evaluation of automated sleep stage scoring algorithms. On all epochs, our model achieves an accuracy of 82.7%, which is only slightly lower than the inter-rater disagreement. When only considering the 63.3% of the epochs where both the experts and algorithm are certain, the model achieves an accuracy of 97.8%. Transition periods between sleep stages are identified and studied for the first time. Scoring guidelines for medical experts are provided to complement the certain predictions by scoring only a few epochs manually. This makes the proposed method highly time-efficient while guaranteeing a highly accurate final hypnogram

Ribonucleic Acid Engineering of Dendritic Cells for Therapeutic Vaccination: Ready ‘N Able to Improve Clinical Outcome?

Targeting and exploiting the immune system has become a valid alternative to conventional options for treating cancer and infectious disease. Dendritic cells (DCs) take a central place given their role as key orchestrators of immunity. Therapeutic vaccination with autologous DCs aims to stimulate the patient’s own immune system to specifically target his/her disease and has proven to be an effective form of immunotherapy with very little toxicity. A great amount of research in this field has concentrated on engineering these DCs through ribonucleic acid (RNA) to improve vaccine efficacy and thereby the historically low response rates. We reviewed in depth the 52 clinical trials that have been published on RNA-engineered DC vaccination, spanning from 2001 to date and reporting on 696 different vaccinated patients. While ambiguity prevents reliable quantification of effects, these trials do provide evidence that RNA-modified DC vaccination can induce objective clinical responses and survival benefit in cancer patients through stimulation of anti-cancer immunity, without significant toxicity. Succinct background knowledge of RNA engineering strategies and concise conclusions from available clinical and recent preclinical evidence will help guide future research in the larger domain of DC immunotherapy