Validation of a multicellular tumor microenvironment system for modeling patient tumor biology and drug response

Mobile sensing to advance tumor modeling in cancer patients: A conceptual framework

As mobile and wearable devices continue to grow in popularity, there is strong yet unrealized potential to harness people's mobile sensing data to improve our understanding of their cellular and biologically-based diseases. Breakthrough technical innovations in tumor modeling, such as the three dimensional tumor microenvironment system (TMES), allow researchers to study the behavior of tumor cells in a controlled environment that closely mimics the human body. Although patients' health behaviors are known to impact their tumor growth through circulating hormones (cortisol, melatonin), capturing this process is a challenge to rendering realistic tumor models in the TMES or similar tumor modeling systems. The goal of this paper is to propose a conceptual framework that unifies researchers from digital health, data science, oncology, and cellular signaling, in a common cause to improve cancer patients' treatment outcomes through mobile sensing. In support of our framework, existing studies indicate that it is feasible to use people's mobile sensing data to approximate their underlying hormone levels. Further, it was found that when cortisol is cycled through the TMES based on actual patients' cortisol levels, there is a significant increase in pancreatic tumor cell growth compared to when cortisol levels are at normal healthy levels. Taken together, findings from these studies indicate that continuous monitoring of people's hormone levels through mobile sensing may improve experimentation in the TMES, by informing how hormones should be introduced. We hope our framework inspires digital health researchers in the psychosocial sciences to consider how their expertise can be applied to advancing outcomes across levels of inquiry, from behavioral to cellular.

Human cardiovascular disease model predicts xanthine oxidase inhibitor cardiovascular risk

Some health concerns are often not identified until late into clinical development of drugs, which can place participants and patients at significant risk. For example, the United States Food and Drug Administration (FDA) labeled the xanthine oxidase inhibitor febuxostat with a"boxed" warning regarding an increased risk of cardiovascular death, and this safety risk was only identified during Phase 3b clinical trials after its approval. Thus, better preclinical assessment of drug efficacy and safety are needed to accurately evaluate candidate drug risk earlier in discovery and development. This study explored whether an in vitro vascular model incorporating human vascular cells and hemodynamics could be used to differentiate the potential cardiovascular risk associated with molecules that have similar on-target mechanisms of action. We compared the transcriptomic responses induced by febuxostat and other xanthine oxidase inhibitors to a database of 111 different compounds profiled in the human vascular model. Of the 111 compounds in the database, 107 are clinical-stage and 33 are FDA-labelled for increased cardiovascular risk. Febuxostat induces pathway-level regulation that has high similarity to the set of drugs FDA-labelled for increased cardiovascular risk. These results were replicated with a febuxostat analog, but not another structurally distinct xanthine oxidase inhibitor that does not confer cardiovascular risk. Together, these data suggest that the FDA warning for febuxostat stems from the chemical structure of the medication itself, rather than the target, xanthine oxidase. Importantly, these data indicate that cardiovascular risk can be evaluated in this in vitro human vascular model, which may facilitate understanding the drug candidate safety profile earlier in discovery and development.

The downregulated drug-metabolism related ALDH6A1 serves as predictor for prognosis and therapeutic immune response in gastric cancer

Drug metabolism-associated genes have been clarified to play a vital role in the process of cancer cell growth and migration. Nevertheless, the correlation between drug metabolism-associated genes and gastric cancer (GC) has not been fully explored and clarified. This paper has focused on the role of aldehyde dehydrogenase 6 family member A1 (ALDH6A1), a drug metabolism-associated gene, in the immune regulation and prognosis of GC patients. Using several bioinformatics platforms and immunohistochemistry (IHC) assay, we found that ALDH6A1 expression was significantly down-regulated in GC tissues. Moreover, higher expression of ALDH6A1 was related to the better prognosis of GC patients. ALDH6A1 was also found to be involved in the regulation of several immune-associated signatures, including immunoinhibitors. In conclusion, the above results have concluded that aberrant expression of ALDH6A1 might be served as the promising predictor for prognosis and clinical immunotherapy response in GC patients.