Man vs Machine: How will Artificial Intelligence and Machine Learning Systems Impact Cancer Diagnosis and the Patient-Physician Relationship?

Oncologic diagnosticians are physicians who specialize in interpreting diagnostic exams to diagnose cancer in patients. Software companies have been developing artificial intelligence (AI) systems to interpret these exams to diagnose cancer. These AI systems may affect the traditional role of oncologic diagnosticians if they were to be implemented in the clinical setting. Therefore, I set out to answer my research question: How will AI and machine learning systems impact the roles of oncologic diagnosticians in diagnosing cancer and the patient-physician relationship? By analyzing surveys and studies, I examined the attitudes of oncologic diagnosticians versus cancer patients toward implementing AI systems in healthcare. Furthermore, I compared the diagnosing accuracies of AI systems and oncologic diagnosticians to uncover which screening entity is superior. I also evaluated specific diagnostic workflows to explore the practical implementations of AI systems in oncology. I investigated AI systems’ potential effects on the oncologic patient-physician relationship. Moreover, I reviewed the ethics of utilizing AI systems in cancer diagnostics to determine if AI implementation is practical. I observed positive attitudes amongst oncologic diagnosticians and patients towards the usage of AI systems, especially if these systems are to be used as assistance programs for physicians. In terms of screening accuracy and the impact on patient-physician relationships, studies showed a lack of consensus. There are also several ethical implications present, but policies and guidelines can be implemented to regulate and manage the usage of AI systems as diagnostic tools. In summary, AI and machine learning systems seem unlikely to replace oncologic diagnosticians. Instead, studies suggest that these devices will assist physicians to reduce diagnostic errors and improve accuracy and reliability. The extent to which the patient-physician relationship is influenced by AI systems seems likely to depend on the physician and their style of practice.https://scholarscompass.vcu.edu/uresposters/1411/thumbnail.jp

Isoprenylation Inhibition Suppresses FcεRI-mediated Mast Cell Function and Allergic Inflammation

Allergic disease is driven by cell signaling cascades that activate immune cells. One key player is mast cells, which is activated by IgE antibodies signaling through the high affinity IgE receptor, FceRI. Therefore, targeting FceRI-mediated cascades can offer for novel treatments for allergic disease. Statins have been demonstrated to reduce the severity of asthma, a common allergic airway disease. Statins are an FDA approved class of drugs with the intended purpose of lowering blood cholesterol. We previously found that while statins inhibit mast cell function in allergic disease, these anti-inflammatory effects vary widely amongst differing mouse strains and human donors, suggesting genetic variability. This project sought to overcome statin resistance by acting “downstream” in the cholesterol synthesis pathway on protein isoprenylation pathways. The logic is that isoprenylated proteins are critical for FceRI signaling, thus blocking this step of protein modification should reduce FceRI-mediated mast cell function. The novel FGTI-2734 drug was used to suppress the isoprenylation enzymes farnesyl transferase and geranylgeranyl transferase. FGTI-2734 reduced IgE-mediated mast cell degranulation and cytokine and chemokine secretion. Additional work found that both transferases must be targeted to produce these anti-inflammatory effects. Furthermore, we revealed that the K-Ras protein is an isoprenylation target that is essential for IgE-mediated mast cell function. Collectively, these studies demonstrate the translational potential of the novel drug FGTI-2734 and suggest it acts by suppressing isoprenylation of proteins critical for mast cell function, including K-Ras.https://scholarscompass.vcu.edu/uresposters/1455/thumbnail.jp

Targeting Mast Cells in Allergic Disease: Current Therapies and Drug Repurposing

The incidence of allergic disease has grown tremendously in the past three generations. While current treatments are effective for some, there is considerable unmet need. Mast cells are critical effectors of allergic inflammation. Their secreted mediators and the receptors for these mediators have long been the target of allergy therapy. Recent drugs have moved a step earlier in mast cell activation, blocking IgE, IL-4, and IL-13 interactions with their receptors. In this review, we summarize the latest therapies targeting mast cells as well as new drugs in clinical trials. In addition, we offer support for repurposing FDA-approved drugs to target mast cells in new ways. With a multitude of highly selective drugs available for cancer, autoimmunity, and metabolic disorders, drug repurposing offers optimism for the future of allergy therapy