Design of a Splicing Promiscuity Model Capable of Predicting Treatment Response of Immune Checkpoint Blockade Treatments; Explore the Societal Impact of Rapid Advancements in Immunotherapy-related Technology

Introduction
With 1.95 million new cases diagnosed and 0.6 million people died in the United States alone in year 2023 according to the National Center for Health statistics, cancer remains the main cause of death in the world. Immunotherapy, the treatment that utilizes a patient’s own immune system to combat cancer, stands as a promising method in the landscape of cancer treatment. Common cancer treatments include surgery, chemotherapy, radiation therapy, but are all subject to different limitations. For example, surgery is only suitable for patients with early-stage tumors that have not metastasized. Meanwhile, chemotherapy and radiation therapy can cause severe side effects, exacerbating the health condition of the patients. In contrast, Immunotherapy has the potential of becoming more personalized, precise, and more effective treatment, while exhibiting fewer side effects. These potentials made immunotherapy a beacon of hope to many patients and their families, waiting for some challenging cancers to be conquered.
The advent of checkpoint blockade (ICB) treatment and chimeric antigen receptor-T (CAR-T) therapies, both modern sub-classes of immunotherapy, marks significant milestones in cancer care. In 2014, the FDA approved two drugs for checkpoint blockade (ICB) treatment, and in 2017, the FDA approved two chimeric antigen receptor-T (CAR-T) therapies, which adds on to this paradigm shift. Only one year later, notably, the 2018 Nobel Prize in Physiology or Medicine was awarded to James P. Allison and Tasuku Honjo for their contributions in the field of immunotherapy. These achievements have hold profound implications for both society and the scientific field. Therefore, my thesis technical research and STS paper will focus on this broad topic.
Project summary
Tumor mutation Burden (TMB) is used as a clinical biomarker for predicting the response of ICB therapy in patients. Concerns have been raised regarding the applicability of TMB as a universal biomarker for all types of solid tumors. There are patients who do not have promising outcome predicted by TMB still have partial response (at least a 30% decrease in the sum of the target lesions) or complete response (the disappearance of all target lesions) to ICB treatment. Conversely, patients with certain types of cancers tend to result in promising outcome predicted by TMB but remain unresponsive to ICB therapy. These limitations show that TMB alone does not provide a comprehensive prediction of the response to ICB. Therefore, in my technical project, I am collaborating with my team to develop a model that is capable of model to offset the limitation of TMB in the process of making clinical decisions to select treatment plans.
The field of immunotherapy experienced a surge in both attention and funding right after the granting of Nobel Prize in 2018. The increased enthusiasm has occasionally led to inflated expectations and misconceptions about the current capabilities of immunotherapy. Patients and the public have understandably begun to envision a near-miraculous transformation in the landscape of cancer treatment. Coupled with the exaggerated reports from media, some people even generate the belief that a universal treatment of cancer is readily within grasp. After I have explained for a dozenth time to relatives and friends who had little knowledge in the biomedical field that immunotherapy was not a panacea and that cancer was not completely conquered by any one treatment, I realized that I need to do something to clarify this. Therefore, the topic of this STS report focuses on evaluating the true societal impact resulting from the rapid progress in immunotherapy-related technology.
Conclusion
As I worked on both my technical research project and my STS paper, I realized that it is important for an engineer to not only knowledge-based information but also need to pay attention to the distribution of information. Even though the source of information may be disinteresting, it is highly likely that the information will be exaggerated by the media, which could cause misunderstanding in general public. In my future work and research as an engineer or a scientist, I commit to rigorously addressing my point of view.
Finally, I would like to use this paragraph to express my sincere gratitude to my STS professor, Dr. Richard Jacques, my technical research advisor, Dr. Li, and my graduate student mentor Samuel Haddox. Thank you for your guidance in these two projects.

School of Engineering and Applied Science
Bachelor of Science in Biomedical Engineering
Technical Advisor: Dr. Hui Li, Samuel Haddox
STS Advisor: Dr. Richard Jacques
Technical Team Members: Ningxi Huang, Samuel McKey