In vivo cisplatin-resistant neuroblastoma metastatic model reveals tumour necrosis factor receptor superfamily member 4 (TNFRSF4) as an independent prognostic factor of survival in neuroblastoma.

Neuroblastoma is the most common solid extracranial tumour in children. Despite major advances in available therapies, children with drug-resistant and/or recurrent neuroblastoma have a dismal outlook with 5-year survival rates of less than 20%. Therefore, tackling relapsed tumour biology by developing and characterising clinically relevant models is a priority in finding targetable vulnerability in neuroblastoma. Using matched cisplatin-sensitive KellyLuc and resistant KellyCis83Luc cell lines, we developed a cisplatin-resistant metastatic MYCN-amplified neuroblastoma model. The average number of metastases per mouse was significantly higher in the KellyCis83Luc group than in the KellyLuc group. The vast majority of sites were confirmed as having lymph node metastasis. Their stiffness characteristics of lymph node metastasis values were within the range reported for the patient samples. Targeted transcriptomic profiling of immuno-oncology genes identified tumour necrosis factor receptor superfamily member 4 (TNFRSF4) as a significantly dysregulated MYCN-independent gene. Importantly, differential TNFRSF4 expression was identified in tumour cells rather than lymphocytes. Low TNFRSF4 expression correlated with poor prognostic indicators in neuroblastoma, such as age at diagnosis, stage, and risk stratification and significantly associated with reduced probability of both event-free and overall survival in neuroblastoma. Therefore, TNFRSF4 Low expression is an independent prognostic factor of survival in neuroblastoma.

Application of Photogrammetry in Biomedical Science.

Photogrammetry is an upcoming technology in biomedical science as it provides a non-invasive and cost-effective alternative to established 3D imaging techniques such as computed tomography. This review introduces the photogrammetry approaches currently used for digital 3D reconstruction in biomedical science and discusses their suitability for different applications. It aims to offer the reader a better understanding of photogrammetry as a 3D reconstruction technique and to provide some guidance on how to choose the appropriate photogrammetry approach for their research area (including single- versus multi-camera setups, structure-from-motion versus conventional photogrammetry and macro- versus microphotogrammetry) as well as guidance on how to obtain high-quality data. This review highlights some key advantages of photogrammetry for a variety of applications in biomedical science, but it also discusses the limitations of this technique and the importance of taking steps to obtain high-quality images for accurate 3D reconstruction.