Cancer ecosystems
Resolve how genomic alterations and multicellular states shape tumor evolution, immunity, and treatment response across patients.
My primary clinical and scientific focus is urologic oncology—particularly bladder and urothelial cancer—while my research extends across broader solid tumors, tumor immunology, and immune-cell therapy. I integrate clinical medicine with cancer genomics, tumor immunology, artificial intelligence, functional genomics, and single-cell & spatial multi-omics to uncover mechanisms of progression, immune escape, therapeutic resistance, and clinically actionable vulnerabilities.
My goal is not to specialize in one technology. It is to choose and integrate the right clinical, computational, and experimental approaches to answer important biological questions.
I am a physician-scientist whose primary disease focus is urologic oncology, especially bladder and urothelial cancers, with a broader research program spanning solid tumors and immune-cell therapy. I work at the intersection of clinical oncology, cancer genomics, tumor immunology, artificial intelligence, functional genomics, and single-cell & spatial systems biology.
My research starts from clinically meaningful problems encountered in oncology—why tumors recur, progress, evade immunity, or resist therapy—and connects patient cohorts with high-dimensional molecular profiling, computational modeling, functional perturbation, and mechanistic validation. Urologic cancers provide a central clinical framework for this work, while the underlying biological questions extend across cancer types.
A major focus of my work has been loss of the Y chromosome (LOY). In a co-first-author Nature study in 2023, we established a causal link between Y-chromosome loss in cancer cells, adaptive immune evasion, and response to immune-checkpoint blockade. In a first-author Nature study in 2025, I led pan-cancer analyses integrating more than one million single-cell profiles and clinical cohorts across 29 cancer types to reveal coordinated LOY across tumor and immune compartments and its impact on patient outcome.
My work also spans T-cell exhaustion and differentiation, AI-enabled radiogenomics, immunotherapy biomarkers, and current efforts in CAR-T systems biology and perturbational genomics. Across these projects, I aim to move from descriptive molecular associations toward causal mechanisms and actionable therapeutic hypotheses.
Three connected research pillars organize my work across urologic oncology, pan-cancer biology, computational science, functional genomics, and therapeutic translation.
Resolve how genomic alterations and multicellular states shape tumor evolution, immunity, and treatment response across patients.
Use genetic perturbation, regulatory modeling, and AI-enabled in silico experiments to distinguish causal drivers from molecular correlation.
Connect mechanism to biomarkers, therapeutic targets, rational combinations, and clinically relevant strategies for precision oncology.
My strongest disease-specific body of work is in urologic malignancies—particularly bladder and urothelial cancer—where I have built a sustained research trajectory across tumor immunology, radiogenomics, treatment-response biomarkers, clinical translational studies, and precision oncology.
My early first/co-first-author work defined CD8⁺ T-effector, immune-checkpoint, pyroptosis, and tumor-microenvironment programs associated with prognosis and immunotherapy response in bladder cancer, establishing the clinical and biological foundation for my later work on tumor–immune co-evolution.
In a co-first-author Nature study, I helped connect a genomic alteration observed in bladder cancer to altered T-cell states, adaptive immune escape, clinical outcome, and differential sensitivity to immune-checkpoint blockade—illustrating a direct path from human tumor genomics to mechanism and therapeutic relevance.
I co-developed radiogenomic approaches integrating quantitative MRI and tumor transcriptomics for more accurate staging and risk assessment in muscle-invasive bladder cancer. This work contributed to a U.S. patent application and reflects my interest in translating computational models into clinically useful tools.
My clinical translational work includes qPCR-based survival stratification in NAC-treated muscle-invasive bladder cancer and upper-tract urothelial carcinoma projects focused on treatment response and outcome prediction—bridging molecular profiling with real-world therapeutic decision making.
Urologic oncology is the clinical anchor of my work; the same computational, immunologic, and functional frameworks extend across pan-cancer biology and cell therapy.
I developed and led a pan-cancer framework integrating bulk tumors, paired tumor–blood cohorts, more than one million single-cell profiles, and spatial analyses across 29 cancer types. The work expanded LOY from a tumor-cell alteration into a feature of the broader tumor–immune ecosystem.
Co-led human single-cell, clinical-cohort, and translational analyses linking Y-negative tumors to altered T-cell states, immune escape, adverse outcome, and enhanced sensitivity to immune-checkpoint blockade.
Led pan-cancer human single-cell dataset assembly, integrative analysis, and immunotherapy-cohort validation connecting stress programs with T-cell exhaustion and therapy resistance.
This work extends my research from observational immune states toward functional regulation of cytotoxic T-cell differentiation and supports my growing focus on perturbational genomics.
My urologic-oncology research integrates bladder and urothelial cancer cohorts with MRI, RNA-seq, machine learning, tumor-immune signatures, treatment-response modeling, and mechanistic tumor-immunity studies. This body of work spans immunotherapy biomarkers, neoadjuvant-treatment stratification, AI radiogenomics, and a U.S. patent application—forming the disease-specific foundation of my broader translational cancer research.
A clinically focused gene-signature study connecting molecular profiling with outcome stratification in patients receiving neoadjuvant chemotherapy.
Connecting patient-derived single-cell states with response, epigenetic regulation, functional perturbation, and AI-enabled causal prioritization.
I am building a harmonized single-cell CAR-T resource spanning hematologic malignancies and solid tumors, multiple treatment stages, disease contexts, and—across most cohorts—clinical response annotations. The resource is designed not simply for descriptive atlas building, but as a foundation for functional interrogation of the cellular programs that determine CAR-T expansion, persistence, cytotoxicity, signaling, differentiation, and dysfunction.
I integrate the patient-derived atlas with CRISPR screening, Perturb-seq, regulatory-network inference, virtual knockout, in silico perturbation, and genomic foundation models to investigate how epigenetic and transcriptional regulators shape immune-cell function and therapeutic response.
Technology is selected to answer the biological and clinical question—not the other way around.
Unmet need, response, resistance, progression
Cohorts, longitudinal samples, clinical endpoints
Genomics, single-cell, spatial & 3D biology
ML, LLMs, foundation models, networks
CRISPR, Perturb-seq, virtual KO
Cell states, interactions, causal regulators
Targets, biomarkers, combinations, clinical hypothesis
My strength is the ability to connect these domains into one coherent research program.
Urologic oncology, clinical question formulation, patient cohorts, longitudinal outcomes, biomarker development, treatment response and resistance, translational study design.
R, Python, Linux, machine learning, deep learning, LLM-assisted research workflows, genomic foundation models, reproducible large-scale analysis.
sc/snRNA-seq, scATAC-seq, spatial transcriptomics and proteomics, CosMx, CODEX, GeoMx, Visium, Xenium, emerging 3D spatial approaches.
CRISPR screening, Perturb-seq, regulatory networks, virtual knockout, in silico perturbation, functional target prioritization.
IHC/IF, western blot, co-culture and functional assays, animal models, clinical-sample processing, mechanistic validation and interdisciplinary project design.
Therapeutic vulnerabilities, rational combinations, immunotherapy, response biomarkers, patient stratification, and clinically actionable hypotheses.
My work combines disease-specific depth in urologic oncology with methodological breadth across cancer genomics, immunology, AI, functional genomics, and spatial systems biology. The goal is a research program that can move naturally between patient-derived observations, mechanistic biology, and therapeutic translation.
Selected from 26 peer-reviewed publications. Google Scholar metrics updated August 2026.
Lead computational and translational analyses in urologic oncology and broader cancer biology, integrating cancer genomics, tumor immunology, single-cell and spatial multi-omics, with active development of CAR-T systems biology and functional-genomics programs.
Led large-scale pan-cancer, single-cell, spatial and clinical-cohort analyses contributing to Nature-family publications, reproducible multi-omics pipelines, and radiogenomic precision-oncology projects.
Integrated genomic, single-cell and translational datasets in bladder cancer and tumor immunology, contributing to mechanistic and radiogenomic studies.
Research training in cancer genomics, tumor microenvironment biology, and translational urologic oncology.
Completed first-year doctoral coursework and laboratory rotations; training concluded in August 2025.
Clinical oncology and translational research training; recipient of the Hunan Province Outstanding Master's Thesis Award.
Five-year clinical medicine program; the degree was evaluated by WES as a U.S. first professional degree in medicine.
I welcome conversations around urologic oncology, urothelial cancer, tumor immunology, CAR-T biology, functional genomics, single-cell & spatial multi-omics, AI-enabled biomedical research, and precision oncology.