Digital health constitutes a merger of both software and hardware technology with health care delivery and management, and encompasses a number of domains, from wearable devices to artificial intelligence, each associated with widely disparate interaction and data collection models. In this review, we focus on the landscape of the current integration of digital health technology in cancer care by subdividing digital health technologies into the following sections: connected devices, digital patient information collection, telehealth, and digital assistants. In these sections, we give an overview of the potential clinical impact of such technologies as they pertain to key domains, including patient education, patient outcomes, quality of life, and health care value. We performed a search of PubMed ( www.ncbi.nlm.nih.gov/pubmed ) and www.ClinicalTrials.gov for numerous terms related to digital health technologies, including digital health, connected devices, smart devices, wearables, activity trackers, connected sensors, remote monitoring, electronic surveys, electronic patient-reported outcomes, telehealth, telemedicine, artificial intelligence, chatbot, and digital assistants. The terms health care and cancer were appended to the previously mentioned terms to filter results for cancer-specific applications. From these results, studies were included that exemplified use of the various domains of digital health technologies in oncologic care. Digital health encompasses the integration of a vast array of technologies with health care, each associated with varied methods of data collection and information flow. Integration of these technologies into clinical practice has seen applications throughout the spectrum of care, including cancer screening, on-treatment patient management, acute post-treatment follow-up, and survivorship. Implementation of these systems may serve to reduce costs and workflow inefficiencies, as well as to improve overall health care value, patient outcomes, and quality of life.

Interleukin 13 receptor α 2 (IL-13Rα2) is a glioblastoma multiforme (GBM)-associated plasma membrane receptor, a brain tumor of dismal prognosis. Here, we isolated peptide ligands for IL-13Rα2 with use of a cyclic disulphide-constrained heptapeptide phages display library and 2 in vitro biopanning schemes with GBM cells that do (G26-H2 and SnB19-pcDNA cells) or do not (G26-V2 and SnB19-asIL-13Rα2 cells) over-express IL-13Rα2. We identified 3 peptide phages that bind to IL-13Rα2 in cellular and protein assays. One of the 3 peptide phages, termed Pep-1, bound to IL-13Rα2 with the highest specificity, surprisingly, also in a reducing environment. Pep-1 was thus synthesized and further analyzed in both linear and disulphide-constrained forms. The linear peptide bound to IL-13Rα2 more avidly than did the disulphide-constrained form and was efficiently internalized by IL-13Rα2-expressing GBM cells. The native ligand, IL-13, did not compete for the Pep-1 binding to the receptor and vice versa in any of the assays, indicating that the peptide might be binding to a site on the receptor different from the native ligand. Furthermore, we demonstrated by noninvasive near infrared fluorescence imaging in nude mice that Pep-1 binds and homes to both subcutaneous and orthotopic human GBM xenografts expressing IL-13Rα2 when injected by an intravenous route. Thus, we identified a linear heptapeptide specific for the IL-13Rα2 that is capable of crossing the blood-brain tumor barrier and homing to tumors. Pep-1 can be further developed for various applications in cancer and/or inflammatory diseases.

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