Zhen Zeng, PhD

In her spare time, Dr. Zheng and her husband enjoy playing tennis and badminton as well as indoor climbing, both bouldering and top rope. She considers these athletic endeavors to be both calming and empowering. Describing her research as intense but rewarding, she also likes to get lost in creating acrylic paintings. Dr. Zheng hopes that her drive and determination as an independent researcher will help pave the way for future lung cancer patients and physicians.

“As an aspiring researcher focused on advancing the prevention, treatment, and control of lung cancer, I am committed to a career at the intersection of computational biology and immunotherapy. My long-term goal is to develop bioinformatics tools that enhance the identification and characterization of tumor-reactive T cells, leading to novel predictive biomarkers and personalized immunotherapy strategies for cancer patients. This grant will provide the critical resources and training to achieve these goals by focusing on the spatial dynamics of immune-tumor interactions.”

A Deeper Dive into Zhen Zeng’s Research

The proposed project will refine the MANAscore, a tool for identifying tumor-reactive T cells in spatial transcriptomics data, using both single-cell and high-dimensional spatial transcriptomics data from lung cancer patients. By investigating the spatial relationship between these T cells and other components in tumor microenvironment, I aim to uncover distinct immune niches within TME that influence therapeutic responses. This work will address the critical challenge in immunotherapy of understanding how the spatial organization and local interactions of tumor-reactive T cells contribute to variability in clinical outcomes.

Through integrating spatial data with clinical outcomes from neoadjuvant anti-PD-1 trials, this research will offer valuable insights into behavior of tumor-reactive T cells within the TME, filling an unmet need in lung cancer immunotherapy.

Lung cancer is a leading cause of cancer-related deaths, while immune checkpoint blockade (ICB) therapies offer new hope by helping the immune system attack tumors. Unfortunately, only a subset of patients can benefit from these treatments, and reliable ways to predict who will respond to ICB remain unavailable. A critical component of ICB success is the activity of special immune cells called tumor-infiltrating lymphocytes (TIL), which can recognize and kill cancer cells. Among these, TIL that target mutation-associated neoantigens (MANA) are particularly effective, but they are rare and difficult to identify with current methods that are costly and labor-intensive.

To address this, we developed MANAscore, a bioinformatics tool that uses the activity of three specific genes to identify tumor-reactive TIL without the need for expensive assays. While effective, we know that the ability of these TIL to fight cancer depends on how they interact with other cells in the tumor microenvironment, including regulatory T cells (Tregs) that can either enhance or suppress immune activity.

This study will refine MANAscore for use with advanced spatial technologies that allow us to map the locations of tumor-reactive TIL within the tumor and study how their proximity to different cell types influences patient outcomes, such as relapse-free survival. By uncovering these spatial relationships, we aim to develop better tools for predicting patient responses to ICB and guide personalized cancer treatments, ultimately improving outcomes for people with lung cancer.

Statement of Significance: This proposed research is highly significant for advancing the control of lung cancer by addressing a critical need for predictive biomarkers and mechanistic insights into immune responses to immune checkpoint blockade (ICB). Lung cancer is the leading cause of cancer-related deaths worldwide, and while ICB therapies have revolutionized treatment, only a subset of patients can benefit. Currently, there are no reliable tools to predict which patients will respond, leading to suboptimal outcomes and unnecessary exposure to costly therapies.

This project focuses on tumor-infiltrating lymphocytes (TIL), immune cells essential for effective ICB responses. Specifically, tumor-reactive TIL that target mutation-associated neoantigens (MANA) play a pivotal role in anti-tumor immunity but are rare and difficult to identify. By developing and validating a refined spatial MANAscore, this research aims to accurately identify these tumor-reactive TIL within the tumor microenvironment and study their spatial interactions with other cell types, such as regulatory T cells (Tregs).

The ability to integrate spatial transcriptomics data with clinical outcomes, such as relapse-free survival, will provide a deeper understanding of the mechanisms driving ICB success. This knowledge has the potential to transform patient care by enabling personalized immunotherapy approaches, optimizing treatment selection, and identifying new therapeutic targets. Beyond lung cancer, the principles and tools developed in this project can be applied to malignancies, broadening its impact and advancing precision oncology for a wide range of cancers.

“This grant will equip me with expertise in spatial transcriptomics and bioinformatics, enhancing my ability to conduct translational research. By fostering collaborations with leading experts in thoracic oncology, this opportunity will position me to drive innovations that improve lung cancer treatments and directly benefit patients.”