Integrating Genomic & Epigenomic Features for Noninvasive Characterization of T-Cell Lymphomas - Project Summary/Abstract Peripheral T-cell lymphoma (PTCL) represents a heterogeneous group of aggressive malignancies poor clinical outcomes, diagnostic uncertainty, and limited options for disease monitoring. Current diagnostic approaches rely heavily on histopathologic evaluation, which is variable due to overlapping morphological and immunophenotypic features. Moreover, single-site biopsies fail to capture the spatial and temporal heterogeneity inherent to PTCL, limiting their utility in guiding clinical decisions. Circulating cell-free DNA (cfDNA) and cell-free RNA (cfRNA) have emerged as promising noninvasive biomarkers capturing systemic tumor burden, molecular phenotype, and immune microenvironment. We previously showed the utility of cfDNA-based approaches for monitoring other cancers. However, the complementary roles and clinical utility of cfDNA and cfRNA in PTCL remain largely unexplored. The central goal of this proposal is to establish an integrated, high-resolution liquid biopsy framework leveraging cfDNA and cfRNA to detect minimal residual disease (MRD), monitor disease dynamics, improve classification, and comprehensively profile tumor heterogeneity and immune status in PTCL. In Aim 1, we will define an optimal strategy combining cfDNA genetic profiling with cfRNA expression analysis, benchmarking their sensitivity and clinical correlation against PET scan and clinical indices at diagnosis, and performance against use of either strategy alone. We will also evaluate tumor- informed and tumor-naïve monitoring strategies for their ability to detect relapse and progression. In Aim 2, we will develop a noninvasive disease classification strategy for PTCL by integrating cfDNA fragmentation-based inferred gene expression (EPIC-Seq) and cfRNA expression profiles (RARE- Seq). We hypothesize that these integrated signatures will recapitulate known PTCL subtypes and better stratify clinical outcomes, enabling superior prediction of treatment outcomes from pre- treatment samples in a manner that could inform future PTCL personalized treatment strategies. In Aim 3, we will characterize tumor heterogeneity and clonal evolution by comparing mutation and copy number alteration profiles between cfDNA and matched tumor DNA. We will investigate intra- tumoral heterogeneity with spatial transcriptomics and targeted subclone analysis to resolve clonal evolution and tumor–immune architecture within lesions. Finally, we will compare bulk tumor RNA-seq with immune-related gene expression profiles from EPIC-Seq and RARE-Seq to evaluate systemic immune heterogeneity and elucidate clinical relevance of immune status by liquid biopsy. Collectively, these studies will establish a robust, noninvasive approach for detection, classification, and monitoring of PTCL, providing insights into tumor biology, immune interactions, and treatment resistance, ultimately informing precision medicine and enhancing outcomes for patients with PTCL.
