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Integrative Genomic, Histologic, and Spatial Profiling of ClonalHematopoiesis in Lung Cancer

Principal Investigator

Name
Janghee Woo

Degrees
MD, PhD

Institution
Emory University

Position Title
Assistant Professor

Email
janghee.woo@emory.edu

About this CDAS Project

Study
PLCO (Learn more about this study)

Project ID
PLCOI-2024

Initial CDAS Request Approval
Mar 30, 2026

Title
Integrative Genomic, Histologic, and Spatial Profiling of ClonalHematopoiesis in Lung Cancer

Summary
Clonal hematopoiesis (CH), defined by age-associated expansion of hematopoietic stem cell clones carrying somatic mutations in genes such as DNMT3A, TET2, and ASXL1, is increasingly recognized as a systemic driver of chronic inflammation and immune dysregulation. Beyond its links to cardiovascular disease and hematologic malignancies, CH is strongly associated with solid tumors, particularly lung cancer. Human association studies demonstrate enrichment of CH mutations among lung cancer patients, yet whether CH promotes lung carcinogenesis and how clonal evolution interacts with tumor development remain poorly defined.

Our preliminary data provide mechanistic support for a causalframework. Using single-cell RNA sequencing of peripheral bloodmononuclear cells (PBMCs) from lung cancer patients with and withoutCH mutations, we demonstrate that CH is associated with systemicimmune remodeling. CH-positive patients exhibit more differentiated T-cell phenotypes, including increased effector and exhausted states, reduced naïve T-cells, and enhanced transcriptional programs consistentwith chronic stimulation. Importantly, the magnitude and nature of theseimmune alterations vary by specific CH mutations, indicating distinctmutation-dependent immune phenotypes. These findings support amodel in which CH-driven immune remodeling promotes animmunosuppressive systemic environment that facilitates lung cancerdevelopment.

We will leverage longitudinal biospecimens from the Prostate, Lung, Colorectal and Ovarian (PLCO) Cancer Screening Trial to define the temporal and spatial consequences of CH in lung cancer. PLCO uniquely provides pre-diagnostic PBMC samples, diagnostic blood samples, matched tumor DNA, archived formalin-fixed paraffin-embedded lung tumor tissue, digitized histopathology, and detailed clinical annotation within a population-based cohort.

In Aim 1, we will determine whether pre-diagnostic CH promotes lung cancer development through longitudinal clonal dynamics. We will identify CH mutations in pre-diagnostic PBMC DNA and longitudinally quantify clonal burden and expansion at cancer diagnosis in both PBMCs and matched tumor tissues. We will assess mutation-specific clonal expansion over time, evaluate concordance between circulating clones and tumor-infiltrating CH mutations, and quantify the association between pre-diagnostic CH burden and subsequent lung cancer risk within the PLCO cohort.

In Aim 2, we will classify patients as CH-positive or CH-negative, with gene-specific stratification where feasible. Using digitized H&E slides, we will apply artificial intelligence–based computational pathology to extract quantitative morphologic features, including tumor-infiltrating lymphocyte density, stromal fraction, necrosis, vascular architecture, and spatial immune organization. Supervised models will determine whether distinct histomorphologic signatures are associated with CH status and tumor-infiltrating CH burden.

In Aim 3, we will characterize CH-associated remodeling of the lung cancer immune microenvironment using tissue microarray–based multiplex spatial transcriptomics. Matched CH-positive and CH-negative tumors will be profiled for immune subsets, macrophage polarization, immune checkpoint expression, stromal activation and cell-to-cell communication. Spatial analyses will define cell-type–specific inflammatory programs and immune–stromal interaction networks associated with CH status.

We hypothesize that CH-positive individuals exhibit coordinated systemic and tumor-local immune alterations characterized by enhanced antigen presentation in myeloid and B cells, T-cell differentiation, and immune exhaustion. By integrating mutation status in blood and tumor with computational histopathology and spatial profiling within PLCO, this project will provide the first comprehensive characterization of CH-mediated immune remodeling in human lung cancer and inform prevention and immunotherapy strategies in aging populations.

Aims

Aim 1: Determine whether pre-diagnostic clonal hematopoiesis promotes lung cancer through longitudinal clonal dynamics.
• Identify CH mutations in pre-diagnostic PBMC DNA.
• Longitudinally quantify clonal burden and expansion at cancer diagnosis in both PBMCs and matched tumor tissues.
• Detect tumor-infiltrating CH mutations in matched tumor DNA and evaluate concordance with circulating clones.
• Determine whether CH and clonal expansion over time is associated with lung cancer development and tumor-infiltrating CH burden.

Aim 2: Define CH-associated genomic and histomorphologic features in lung cancer using integrated mutation profiling and AI-based computational pathology.
• Classify patients by systemic and tumor-infiltrating CH status with gene-level stratification.
• Apply artificial intelligence and machine learning to digitized H&E slides to extract quantitative morphologic features, including tumor-infiltrating lymphocyte density, stromal fraction, necrosis, vascular architecture, and spatial immune organization.
• Develop supervised models to identify morphologic signatures associated with CH status and tumor-infiltrating CH burden.
• Define reproducible histologic biomarkers of CH-associated immune remodeling.

Aim 3: Characterize CH-associated remodeling of the lung tumor immune microenvironment using spatial molecular profiling.
• Construct and classify tissue microarrays from mutation-defined CH-positive and CH-negative tumors.
• Perform multiplex spatial transcriptomics and immunophenotyping to profile immune subsets, macrophage polarization, antigen presentation programs, immune checkpoint expression, stromal activation, and complement signaling.
• Conduct spatial neighborhood and cell–cell communication analyses to define mutation-specific inflammatory pathways and immune–stromal interaction networks.

Impact
• Provide the first longitudinal, population-based characterization of pre-diagnostic CH and clonal evolution in lung cancer.
• Define how systemic clonal dynamics reshape the tumor immune microenvironment.
• Identify morphologic and spatial biomarkers of CH-mediated immune remodeling that may inform lung cancer risk stratification and immunotherapy strategies.

Collaborators

Janghee Woo Winship Cancer Institute of Emory University