Mahan Fellowship

Project: ctDNA-based modeling of genotypic & phenotypic dynamics during mCRPC therapy

Prostate cancer is the second most common cause of cancer mortality among men in the United States. Progression to metastatic castration resistant prostate cancer is lethal with essentially no curative treatment. Novel prostate-specific membrane antigen radioligand therapies (PSMA-RLT) hold promise, but treatment responses are not durable. There is a major unmet clinical need to better understand the molecular changes associated with resistance and to identify biomarkers for predicting which patients will likely derive benefit from these therapies. This project proposes to develop new computational methods and statistical frameworks for the analysis of circulating tumor DNA (ctDNA) obtained from cancer patients as non-invasive “liquid biopsy” to identify genotypic and phenotypic features that can better monitor treatment response and predict therapeutic outcomes. The development of these ctDNA-based prediction and serial monitoring tools will provide insights to improve treatment strategies and management of patients receiving PSMA-RLT therapies.

Project: High-throughput DNA synthesis in picoliter droplets

Current DNA synthesis is expensive and limited by sequence fidelity and length. We are developing a platform for multiplex assembly of high-fidelity DNA sequences at kilobase length scales using new barcoded assembly reactions in semi-permeable capsules. This platform can accelerate the screening of biomolecular designs for many applications, from basic biology to therapeutic discovery.

To adequately protect the body from invaders, the adaptive immune system is trained to distinguish the immune self from non-self. T cell lymphocytes govern the adaptive immune system and are taught to make this distinction in the thymus during a process called positive and negative selection. A person’s T cell repertoire - is an almost unique fingerprint based on various environmental factors such as previous infections, but also genetic factors such as sex and HLA haplotype, which influence the positive and negative selection process. In my research, I hope to get more insights into how the characterization between the self and non-self is done. My project will aim to model the relationship between an individual's genetic factors and their repertoire and gain a little more understanding of the basis of immune recognition

Project: Structural and functional mechanisms of ribosome stalling

Accurate protein expression is essential for maintaining all cellular processes and is dependent on the stability of mRNA during translation. As such, the synthesis of proteins via the ribosome must be tightly regulated to prevent the accumulation of aberrant proteins. While significant progress has been made to uncover the ribosome’s role in gene regulation, protein synthesis, and antibiotic drug development, there is a lack of understanding on how the ribosome itself is regulated by the encoded peptide sequence. Furthermore, the mechanisms of ribosome-associated quality control pathways that initiate reduce factors to alleviate stalled and collided ribosomes remain elusive. My research aims to combine biophysical, computational, and genomic approaches to illuminate the structural dynamics of ribosome stalling and its implications on translation regulation. 

Project: Comprehensive characterization of T cells from patients undergoing checkpoint blockade immunotherapy

Checkpoint blockade immunotherapy is a revolutionary cancer treatment that activates a patient’s own immune system to destroy tumor cells. While highly effective in some cases, it is not entirely clear why this treatment sometimes fails to mobilize a patient’s T cells. To identify differences between these responders and non-responders, I will apply single-cell multi-omic sequencing to comprehensively characterize T cells from cancer patients undergoing checkpoint blockade immunotherapy. This study will reveal the key features of effective immunity before and after treatment, guiding development of new immunotherapies and enabling identification of predictive biomarkers to help doctors choose the right approach for each patient

I study the n-body problem of our immune system. How does human serum, with its millions of different antibodies, protects us against pathogens? A lot of groups are examining how single antibodies fight flu or HIV, but few are investigating collective antibody action. As the field moves in this direction, it will shed light on the full repertoire our immune system unleashes against viral invaders.

It is paradoxical how the misexpression of the same gene (DUX4) can cause disparate cellular phenotypes in two different diseases: muscle wasting in Facioscapulohumeral Muscular Dystrophy (FSHD), but uncontrolled cell proliferation in a subtype of B-cell precursor Acute Lymphoblastic Leukemia (BCP-ALL). By analyzing the RNA expression in patient samples from both these diseases, Guo-Liang aims to understand the molecular basis of DUX4-induced pathology in both diseases, as well as to use the insights gained from one disease to develop therapies for the other.

My research focuses on investigating the plasticity and heterogeneity of therapeutic T cells during adoptive cell therapy within solid tumors. I am working on using systems-level big data at bulk and single-cell resolution to map the signaling dynamics, epigenetic landscape of the therapeutic T cells within the context of the tumor microenvironment. Overall, my project will help us understand how to better engineering our T cells as a powerful weapon to treat cancer.

Sequence data from emerging infectious disease epidemics are becoming a universal tool for gaining insight into how pathogens spread and how to control them efficiently. The project focused on rapidly evolving RNA viruses and how their evolution can be used to understand their patterns of transmission. The West African Ebola virus epidemic of 2013-2016 was a primary focus of the project, where the factors affecting the virus' ability to spread and proliferate within the region were determined. Simultaneously, in collaboration with Nathan Grubaugh and Kristian Andersen at Scripps, as well as researchers from University of Oxford, the project also investigated the nature of a Zika virus outbreak in Florida in 2016. The final part of the project focusing on reconstructing the epidemiology of Middle East respiratory syndrome-associated coronavirus (MERS-CoV) at the interface between its two known major hosts, humans and camels, is currently in review.

My research focuses on how viruses such as influenza evolve to infect diverse host species. Zoonotic transmission of influenza from avian and swine hosts to humans have the potential to result in pandemics with severe public health consequences. I am working to map the evolutionary pathways by which influenza can adapt to new species, and using this map to assess adaptation and thus pandemic risk of novel influenza strains. Overall, these studies will help us understand the specifics of influenza adaptation, and more broadly, how viral evolution is shaped by host genetics.