ABSTRACT
Prostate cancer is the most commonly diagnosed cancer in men worldwide. Early diagnosis of the disease provides better treatment options for these patients. Magnetic resonance imaging (MRI) provides an overall assessment of prostate disease. Quantitative metrics (radiomics) from the MRI provide a better evaluation of the tumor and have been shown to improve disease detection. Recent studies have demonstrated that plasma extracellular vesicle microRNAs (miRNAs) are functionally linked to cancer progression, metastasis, and aggressiveness. In our study, we analyzed a matched cohort with baseline blood plasma and MRI to access tumor morphology using imaging-based radiomics and cellular characteristics using miRNAs-based transcriptomics. Our findings indicate that the univariate feature-based model with the highest Youden's index achieved average areas under the receiver operating characteristic curve (AUC) of 0.76, 0.82, and 0.84 for miRNA, MR-T2W, and MR-ADC features, respectively, in identifying clinically aggressive (Gleason grade) disease. The multivariable feature-based model demonstrated an average AUC of 0.88 and 0.95 using combinations of miRNA markers with imaging features in MR-ADC and MR-T2W, respectively. Our study demonstrates combining miRNA markers with MRI-based radiomics improves predictability of clinically aggressive prostate cancer.
ABSTRACT
The congenital myopathies are a heterogeneous group of inherited neuromuscular disorders characterized by early-onset muscular weakness, hypotonia, and developmental delay. The congenital myopathies are further classified into centranuclear myopathies, nemaline myopathies, core myopathies, and congenital fiber-type disproportion based on major pathological features found in muscle biopsies. There is no evidence at present to show that cleft palate is associated with severe nemaline myopathies and fetal akinesia. The results of our study suggest that KLHL40 mutation associated with Cleft palate, nemaline myopathy and fetal akinesia.