Identification of aneuploidy-related gene signature to predict survival in head and neck squamous cell carcinomas

BACKGROUND

To parse the characteristics of aneuploidy related riskscore (ARS) model in head and neck squamous cell carcinomas (HNSC) and their predictive ability on patient prognosis.

METHODS

Molecular subtyping of HNSC specimens was clustered by Copy Number Variation (CNV) data from The Cancer Genome Atlas (TCGA) dataset applying consistent clustering, followed by immune condition evaluation, differentially expressed genes (DEGs) analysis and DEGs function annotation. Weighted gene co-expression network analysis (WGCNA), protein-protein interaction, Univariate Cox regression analysis, least absolute shrinkage and selection operator (LASSO) and stepwise multivariate Cox regression analysis were implemented to construct an ARS model. A nomogram for clinic practice was designed by rms package. Immunotherapy evaluation and drug sensitivity prediction were also carried out.

RESULTS

We stratified HNSC patients into three different molecular subgroups, with the best prognosis in C1 cluster among 3 clusters. C1 cluster displayed greatest immune infiltration status. The most DEGs between C1 and C2 groups, mainly enriched in cell cycle and immune function. We constructed a nine-gene ARS model (ICOS, IL21R, CCR7, SELL, CYTIP, ZAP70, CCR4, S1PR4 and CD79A) that effectively differentiates between high- and low-risk patients. Patients in low ARS group showed a higher sensitivity to immunotherapy. A nomogram built by integrating ARS and clinic-pathological characteristics helped predict clinic survival benefit. Drug sensitivity evaluation found that 4/9 inhibitor drugs (MK-8776, AZD5438, PD-0332991, PHA-665752) acted on the cell cycle.

CONCLUSIONS

We classified 3 molecular subtypes for HNSC patients and established an ARS prognostic model, which offered a prospective direction for prognosis in HNSC.

Measuring Equine-Assisted Therapy: Validation and Confirmatory Factor Analysis of an ICF-Based Standardized Assessment-Tool

The International Classification of Functioning, Disability, and Health (ICF) of the World Health Organization (WHO) was established as an international framework for monitoring rehabilitation outcomes and the impacts of health interventions since, as the term “functioning” implies, it emphasizes a person’s “lived health” in addition to their biological health status. Equine-assisted therapy (EAT) represents a holistic intervention approach that aims to improve both biomedical functioning and the patient’s lived health in relation to performing activities and participating in social situations. In this study, the psychometric properties of an ICF-based digital assessment tool for the measurement of the rehabilitation impacts of EAT were analyzed via simultaneous confirmatory factor analyses (CFA) and reliability and sensitivity tests. In total, 265 patients from equine-assisted therapy centers in Germany were included for CFA. Change sensitivity was assessed via multi-level analyses based on 876 repeated assessments by 30 therapists. Results show satisfactory model-fit statistics; McDonald’s omega (ML) showed excellent scores for the total scale (ω = 0.96) and three subscales (ω = 0.95; ω = 0.95, ω = 0.93). The tool proved itself to be change sensitive and reliable (change sensitivity p ≤ 0.001), retest r = 0.745 **, p ≤ 0.001). Overall, the developed assessment tool satisfactorily fulfills psychometric requirements and can be applied in therapeutic practice.

State of the Art of Natural Killer Cell Imaging: A Systematic Review

Natural killer (NK) cell therapy is a promising alternative to conventional T cell-based treatments, although there is a lack of diagnostic tools to predict and evaluate therapeutic outcomes. Molecular imaging can offer several approaches to non-invasively address this issue. In this study, we systematically reviewed the literature to evaluate the state of the art of NK cell imaging and its translational potential. PubMed and Scopus databases were searched for published articles on the imaging of NK cells in humans and preclinical models. Study quality was evaluated following Quality Assessment of Diagnostic Accuracy Studies (QUADAS-2) criteria. We pooled studies as follows: Optical, magnetic resonance imaging (MRI) and nuclear medicine imaging with a total of 21 studies (n = 5, n = 8 and n = 8, respectively). Considering the limitation of comparing different imaging modalities, it appears that optical imaging (OI) of NK cells is very useful in a preclinical setting, but has the least translational potential. MRI provides high quality images without ionizing radiations with lower sensitivity. Nuclear medicine is the only imaging technique that has been applied in humans (four papers), but results were not outstanding due to a limited number of enrolled patients. At present, no technique emerged as superior over the others and more standardization is required in conducting human and animal studies.

PET/MR in oncology: an introduction with focus on MR and future perspectives for hybrid imaging

After more than 20 years of research, a fully integrated PET/MR scanner was launched in 2010 enabling simultaneous acquisition of PET and MR imaging. Currently, no clinical indication for combined PET/MR has been established, however the expectations are high. In this paper we will discuss some of the challenges inherent in this new technology, but focus on potential applications for simultaneous PET/MR in the field of oncology. Methods and tracers for use with the PET technology will be familiar to most readers of this journal; thus this paper aims to provide a short and basic introduction to a number of different MRI techniques, such as DWI-MR (diffusion weighted imaging MR), DCE-MR (dynamic contrast enhanced MR), MRS (MR spectroscopy) and MR for attenuation correction of PET. All MR techniques presented in this paper have shown promising results in the treatment of patients with solid tumors and could be applied together with PET increasing the amount of information about the tissues of interest. The potential clinical benefit of applying PET/MR in staging, radiotherapy planning and treatment evaluation in oncology, as well as the research perspectives for the use of PET/MR in the development of new tracers and drugs will be discussed.