Depression, anxiety, and other manifestations of distress are major causes of morbidity for cancer patients and contribute to a decreased quality of life. A combination of pharmacological, behavioral, and psychiatric interventions have been shown to lessen the symptoms of depression and improve patients’ quality of life. The Integrated Psychosocial Oncology Program (IPOP) at the Seattle Cancer Care Alliance (SCCA) uses the collaborative care model to provide cancer patients with care and support to manage symptoms of distress while receiving treatment at the SCCA. This evaluation of the SCCA IPOP program aims to 1) illuminate barriers and risk-factors in the pathway to psychosocial services, including screening, referrals, and follow-ups; and 2) develop process interventions to improve outcomes in treatment. Preliminary analysis shows that of the patients referred to the IPOP between June 2015 and May 2016 (N=919), 83.2% were screened for depression and anxiety, but only 28.3% (N=440) of those found to demonstrate moderate symptoms of depression or anxiety received a follow-up screening. Without follow-up screenings, the SCCA is unable to evaluate the efficacy of its interventions provided by the social work team. In order to improve the frequency of these follow-ups, the SCCA Social Work team is introducing a patient roadmap to improve patient engagement and changing data-collection processes to improve the availability of population health metrics. These changes are expected to improve two-month follow-ups, and improve the outcomes of SCCA social work patients, which will be monitored over the next 6 months.

Influenza is a prolific and hazardous virus, affecting even those in the population who have been previously infected or vaccinated. The innate immune system serves as a key first line of defense against this pathogen, with the signaling components, called interferons, driving the production of a potent cellular antiviral response. Studies have indicated that viral populations replete in defective virus particles, virions with a deletion in a portion of their genome, are less efficient at blocking the antiviral response, as shown by increased interferon in the host. Our project seeks to explore this phenomenon of RNA deletions leading to increased interferon expression in host cells by testing the hypothesis that deletions in the three polymerase genes of influenza alone are sufficient to cause an increase in the interferon response. To begin answering this question, an interferon reporter system was used to analyze the viral genome of interferon positive cells, and deletions within various lengths of the PB1, PB2, and PA polymerase genes were found to be enriched. I then created pure populations of influenza with these empirically derived gene deletions in PB1 while my mentor, Dr. Alistair Russell, created pure PB2 deletion populations, which were grown on cell lines expressing functional PB1 and PB2 proteins respectively. When used to infect unmodified cell lines, it was found that pure populations of both PB1 and PB2 defective influenza were sufficient to induce the host interferon response. In the future, I will create PA expressing cell lines and influenza with deletions in PA to analyze the effect of PA deletions within the influenza genome on the host interferon response, and it is hoped that these results can be used to explore a mechanism for how influenza occasionally fails to escape the innate immune response.

Bacteria are widely used in metabolic engineering because they can synthesize chemical products from cheap, renewable carbon sources. A major current problem, however, is that toxic intermediates can build up when bacteria express heterologous biosynthetic pathways. In principle, we can control metabolic gene expression levels so that downstream enzymes quickly consume toxic intermediates. To achieve this goal, we use a programmable gene regulatory tool called the CRISPR-Cas system. To optimize gene activation activity of CRISPR-Cas in bacteria, we sought to identify modular transcriptional activation domains that could be recruited to specific genes to activate transcription. This strategy has been previously used successfully in eukaryotic cells, but with only limited success in bacteria. We used CRISPR-Cas to recruit a number of potential synthetic transcriptional activators to specific loci in E. coli, and identified candidates that can activate a fluorescent reporter gene. We also used protein-engineering approaches to optimize the gene activation activity of our CRISPR-Cas system. The transcription factor screening and protein engineering we did gave an 80-100-fold increase in activation compared to basal transcription levels. To make this new tool useful for practical metabolic engineering, we plan to use this system to dynamically respond to metabolic stresses. This tool could potentially be used to optimize biosynthesis of useful polymer precursors such as lactate and p-aminostyrene. Production of these types of cheap, biosynthetic precursors will help us move towards a greener industrial future.