Badgeley, Marcus A.

AbstractBackgroundIn recent years, the fibroblast growth factor receptor (FGFR) pathway has been proven to be an important therapeutic target in bladder cancer. FGFR‐targeted therapies are effective for patients with FGFR mutation, which can be discovered through genetic sequencing. However, genetic sequencing is not commonly performed at diagnosis, whereas a histologic assessment of the tumor is. We aim to computationally extract imaging biomarkers from existing tumor diagnostic slides in order to predict FGFR alterations in bladder cancer.MethodsThis study analyzed genomic profiles and H&E‐stained tumor diagnostic slides of bladder cancer cases from The Cancer Genome Atlas (n = 418 cases). A convolutional neural network (CNN) identified tumor‐infiltrating lymphocytes (TIL). The percentage of the tissue containing TIL (“TIL percentage”) was then used to predict FGFR activation status with a logistic regression model.ResultsThis predictive model could proficiently identify patients with any type of FGFR gene aberration using the CNN‐based TIL percentage (sensitivity = 0.89, specificity = 0.42, AUROC = 0.76). A similar model which focused on predicting patients with only FGFR2/FGFR3 mutation was also found to be highly sensitive, but also specific (sensitivity = 0.82, specificity = 0.85, AUROC = 0.86).ConclusionTIL percentage is a computationally derived image biomarker from routine tumor histology that can predict whether a tumor has FGFR mutations. CNNs and other digital pathology methods may complement genome sequencing and provide earlier screening options for candidates of targeted therapies.

Abstract Here, we report a nanoparticle-based probe that affords facile cell labeling with cholesterol in cholesterol efflux (CE) assays. This probe, called ezFlux, was optimized through a screening of multiple nanoformulations engineered with a Förster resonance energy transfer (FRET) reporter. The physicochemical- and bio-similarity of ezFlux to standard semi-synthetic acetylated low-density lipoprotein (acLDL) was confirmed by testing uptake in macrophages, the intracellular route of degradation, and performance in CE assays. A single-step fast self-assembly fabrication makes ezFlux an attractive alternative to acLDL. We also show that CE testing using ezFlux is significantly cheaper than that performed using commercial kits or acLDL. Additionally, we analyze clinical trials that measure CE and show that ezFlux has a place in many research and clinical laboratories worldwide that use CE to assess cellular and lipoprotein function.