Survivin-Sodium Iodide Symporter Reporter as a Non-Invasive Diagnostic Marker to Differentiate Uterine Leiomyosarcoma from Leiomyoma.
Natalia GarciaMara UlinQiwei YangMohamed AliMaarten C BoslandWeiqiao ZengLiaohai ChenAyman Al-HendyPublished in: Cells (2023)
Leiomyosarcoma (LMS) has been challenging to diagnose because of limitations in clinical and radiographic predictors, as well as the lack of reliable serum or urinary biomarkers. Most uterine masses consist of benign leiomyoma (LM). However, it is currently a significant challenge in gynecology practice to differentiate LMS from LM. This inability poses grave consequences for patients, leading to a high number of unnecessary hysterectomies, infertility, and other major morbidities and possible mortalities. This study aimed to evaluate the use of Survivin-Sodium iodide symporter (Ad-Sur-NIS) as a reporter gene biomarker to differentiate malignant LMS from benign LM by using an F18-NaBF 4 PET/CT scan. The PET/CT scan images showed a significantly increased radiotracer uptake and a decreased radiotracer decay attributable to the higher abundance of Ad-Sur-NIS in the LMS tumors compared to LM ( p < 0.05). An excellent safety profile was observed, with no pathological or metabolic differences detected in Ad-Sur-NIS-treated animal versus the vehicle control. Ad-Sur-NIS as a PET scan reporter is a promising imaging biomarker that can differentiate uterine LMS from LM using F18-NaBF 4 as a radiotracer. As a new diagnostic method, the F18 NaBF 4 PET/CT scan can provide a much-needed tool in clinical practices to effectively triage women with suspicious uterine masses and avoid unnecessary invasive interventions.
Keyphrases
- pet ct
- computed tomography
- crispr cas
- positron emission tomography
- pet imaging
- end stage renal disease
- primary care
- newly diagnosed
- healthcare
- ejection fraction
- emergency department
- chronic kidney disease
- high resolution
- deep learning
- type diabetes
- peritoneal dialysis
- physical activity
- magnetic resonance imaging
- copy number
- dual energy
- genome wide
- convolutional neural network
- gene expression
- machine learning
- dna methylation
- patient reported
- contrast enhanced ultrasound
- insulin resistance
- transcription factor
- quality improvement
- photodynamic therapy
- antibiotic resistance genes