We report the development of novel reagents and approaches for generating recyclable biosensors. The use of aqueous media for the formation of protein binding alkylthiolate monolayers on Au surfaces results in accelerated alkylthiolate monolayer formation and improvement in monolayer integrity as visualized by fluorescence microscopy and CV techniques. We have also developed an electrocleaning protocol that is compatible with microfluidics devices, and this technique serves as an on-chip method for cleaning Au substrates both before and after monolayer formation. The techniques for the formation and dissociation of biotinylated SAMs from aqueous solvents reported here may be applied towards the development of Au-based sensor devices and microfluidics chips in the future. A potential use of these devices includes the specific capture and triggered release of target cells, proteins, or small molecules from liquid samples.

Bladder cancer is a genetically heterogeneous disease, and novel therapeutic strategies are needed to expand treatment options and improve clinical outcomes. Here, we identified a unique subset of urothelial tumors with focal amplification of the RAF1 (CRAF) kinase gene. RAF1-amplified tumors had activation of the RAF/MEK/ERK signaling pathway and exhibited a luminal gene expression pattern. Genetic studies demonstrated that RAF1-amplified tumors were dependent upon RAF1 activity for survival, and RAF1-activated cell lines and patient-derived models were sensitive to available and emerging RAF inhibitors as well as combined RAF plus MEK inhibition. Furthermore, we found that bladder tumors with HRAS- or NRAS-activating mutations were dependent on RAF1-mediated signaling and were sensitive to RAF1-targeted therapy. Together, these data identified RAF1 activation as a dependency in a subset making up nearly 20% of urothelial tumors and suggested that targeting RAF1-mediated signaling represents a rational therapeutic strategy.

Collateral lethality occurs when loss of a gene/protein renders cancer cells dependent on its remaining paralog. Combining genome-scale CRISPR/Cas9 loss-of-function screens with RNA sequencing in over 900 cancer cell lines, we found that cancers of nervous system lineage, including adult and pediatric gliomas and neuroblastomas, required the nuclear kinase vaccinia-related kinase 1 (VRK1) for their survival in vivo. VRK1 dependency was inversely correlated with expression of its paralog VRK2 . VRK2 knockout sensitized cells to VRK1 loss, and conversely, VRK2 overexpression increased cell fitness in the setting of VRK1 loss. DNA methylation of the VRK2 promoter was associated with low VRK2 expression in human neuroblastomas and adult and pediatric gliomas. Mechanistically, depletion of VRK1 reduced barrier-to-autointegration factor phosphorylation during mitosis, resulting in DNA damage and apoptosis. Together, these studies identify VRK1 as a synthetic lethal target in VRK2 promoter–methylated adult and pediatric gliomas and neuroblastomas.

Analysis of kinase signaling involved in TRAIL-induced cell death highlights potential targets for combination cancer therapy.

Sarcomere and cytoskeleton genes, or actomyosin genes, regulate cell biology including mechanical stress, cell motility, and cell division. While actomyosin genes are recurrently dysregulated in cancers, their oncogenic roles have not been examined in a lineage-specific fashion. In this report, we investigated dysregulation of nine sarcomeric and cytoskeletal genes across 20 cancer lineages. We found that uterine cancers harbored the highest frequencies of amplification and overexpression of the gamma actin gene, ACTG1. Each of the four subtypes of uterine cancers, mixed endometrial carcinomas, serous carcinomas, endometroid carcinomas, and carcinosarcomas harbored between 5~20% of ACTG1 gene amplification or overexpression. Clinically, patients with ACTG1 gains had a poor prognosis. ACTG1 gains showed transcriptional patterns that reflect activation of oncogenic signals, repressed response to innate immunity, or immunotherapy. Functionally, the CRISPR-CAS9 gene deletion of ACTG1 had the most robust and consistent effects in uterine cancer cells relative to 20 other lineages. Overall, we propose that ACTG1 regulates the fitness of uterine cancer cells by modulating cell-intrinsic properties and the tumor microenvironment. In summary, the ACTG1 functions relative to other actomyosin genes support the notion that it is a potential biomarker and a target gene in uterine cancer precision therapies.

Objectives: Accelerating demand for patient messaging has impacted the practice of many providers. Messages are not recommended for urgent medical issues, but some do require rapid attention. This presents an opportunity for artificial intelligence (AI) methods to prioritize review of messages. Our study aimed to highlight some patient portal messages for prioritized review using a custom AI system integrated into the electronic health record (EHR). Materials and Methods: We developed a Bidirectional Encoder Representations from Transformers (BERT)-based large language model using 40 132 patient-sent messages to identify patterns involving high acuity topics that warrant an immediate callback. The model was then implemented into 2 shared pools of patient messages managed by dozens of registered nurses. A primary outcome, such as the time before messages were read, was evaluated with a difference-in-difference methodology. Results: Model validation on an expert-reviewed dataset (n = 7260) yielded very promising performance (C-statistic = 97%, average-precision = 72%). A binarized output (precision = 67%, sensitivity = 63%) was integrated into the EHR for 2 years. In a pre-post analysis (n = 396 466), an improvement exceeding the trend was observed in the time high-scoring messages sit unread (21 minutes, 63 vs 42 for messages sent outside business hours). Discussion: Our work shows great promise in improving care when AI is aligned with human workflow. Future work involves audience expansion, aiding users with suggested actions, and drafting responses. Conclusion: Many patients utilize patient portal messages, and while most messages are routine, a small fraction describe alarming symptoms. Our AI-based workflow shortens the turnaround time to get a trained clinician to review these messages to provide safer, higher-quality care.