NY-ESO-1-specific immunological pressure and escape in a patient with metastatic melanoma.

During cancer progression, malignant cells may evade immunosurveillance. However, evidence for immunological escape in humans is scarce. We report here the clinical course of a melanoma patient whose initial tumor was positive for the antigens NY-ESO-1, MAGE-C1, and Melan-A. Upon immunization with a recombinant vaccinia/fowlpox NY-ESO-1 construct, the patient experienced a mixed clinical response and spreading of the NY-ESO-1 epitopes in the CD4+ T cell compartment. After NY-ESO-1 protein + CpG immunization, the patient's anti-NY-ESO-1 IgG response increased. Over the following years, progressing lesions were resected and found to be NY-ESO-1-negative while being positive for MAGE-C1, Melan-A, and MHC-I. The fatal, inoperable brain metastasis was analyzed after his death and also proved to be NY-ESO-1-negative, while being positive for MAGE-C1 and Melan-A, as well as MHC-I. We propose that cancer control and cancer escape in this patient were governed by NY-ESO-1-specific immunological pressure. Our findings provide evidence for the existence of immunoediting and immunoescape in this cancer patient.

Rapid eye movement sleep behavior disorder: a narrative review from a technological perspective.

STUDY OBJECTIVES: Isolated rapid eye movement sleep behavior disorder (iRBD) is a parasomnia characterized by dream enactment. It represents a prodromal state of α-synucleinopathies, like Parkinson's disease. In recent years, biomarkers of increased risk of phenoconversion from iRBD to overt α-synucleinopathies have been identified. Currently, diagnosis and monitoring rely on self-reported reports and polysomnography (PSG) performed in the sleep lab, which is limited in availability and cost-intensive. Wearable technologies and computerized algorithms may provide comfortable and cost-efficient means to not only improve the identification of patients with iRBD but also to monitor risk factors of phenoconversion. In this work, we review studies using these technologies to identify iRBD or monitor phenoconversion biomarkers. METHODS: A review of articles published until May 31, 2022 using the Medline database was performed. We included only papers in which participants with RBD were part of the study population. The selected papers were divided into four sessions: actigraphy, gait analysis systems, computerized algorithms, and novel technologies. RESULTS: In total, 25 articles were included in the review. Actigraphy, wearable accelerometers, pressure mats, smartphones, tablets, and algorithms based on PSG signals were used to identify RBD and monitor the phenoconversion. Rest-activity patterns, core body temperature, gait, and sleep parameters were able to identify the different stages of the disease. CONCLUSIONS: These tools may complement current diagnostic systems in the future, providing objective ambulatory data obtained comfortably and inexpensively. Consequently, screening for iRBD and follow-up will be more accessible for the concerned patient cohort.