Abstract
My technical and STS research projects share a focus on glioblastoma (GB), the most common and aggressive malignant brain tumor in adults. Given GB’s poor therapeutic outcomes, there is an urgent need for innovative treatments and deeper insight into biological and systemic factors influencing its diagnosis and management. In my technical project, my team and I are engineering and testing the effects of SARS-CoV-2 Wuhan spike protein (SP) and ACE2 receptor proteins on two human GB cell lines, U251 and U87, to explore how viral proteins may interact with the tumor microenvironment and enhance the immune response. To better understand how novel therapies such as this fusogenic therapy might eventually transition into clinical practice, my STS research analyzes the sociotechnical network surrounding the failed CheckMate 143 phase 3 clinical trial. By examining how this multi-faceted network of human and non-human actors failed to stabilize, I aim to inform the future clinical translation of my team’s technical work by identifying structural and organizational factors that can support or hinder innovation in GB treatment.
My technical project explores the use of fusogenic therapy to treat GB by enhancing the immune response. The proposed design is a therapeutic system that leverages the SARS-CoV-2 Wuhan strain SP and ACE2 receptor to induce syncytia formation, or cell fusion, and kill GB cells. The system allows continuous SP expression, enabling analysis of how expression patterns affect tumor cell death, immune activation, and treatment efficacy. In addition, the project includes the development of a predictive computational model to simulate immune responses, particularly antibody production, based on SP expression dynamics. This research aims to develop a tunable fusogenic therapy for GB, with potential applications in other cancers.
My STS research analyzes the sociotechnical factors that contributed to the failure of the CheckMate 143 clinical trial, the first randomized trial testing a PD-1 immune checkpoint inhibitor for GB. Using Actor Network Theory (ANT) as my framework, I examine how the trial's network of human and non-human actors was inadequately identified, misaligned, and ultimately destabilized. My claim is that the trial failed not only because of biological limitations, but also due to a breakdown in forming and maintaining an effective clinical trial network. My paper explores this idea by identifying key overlooked actors, such as MGMT promoter methylation and corticosteroid use, and analyzing how their improper integration and stabilization disrupted the trial’s ability to generate meaningful clinical conclusions. The goal of my research is to offer a more comprehensive understanding of why GB treatments may fail in translation and to inform future clinical trial design for more effective therapy strategies.
Working on these two projects in tandem greatly enriched both projects. My technical work gave me a deeper understanding of GB’s biological complexity and the challenges of developing effective therapies, particularly when targeting the immune system. This context helped me identify critical actors and biological factors in the CheckMate 143 trial, allowing me to analyze the trial through a more informed and clinically relevant lens in my STS research. Using ANT also showed me that therapeutic success depends not just on the science, but on the broader network of patients, clinicians, regulations, and biological variables. In summary, working on both my STS research paper and my technical project together this past year allowed me to explore GB from both an engineering and sociotechnical perspective.
