Abstract A039: FFPE-CUT&Tag transcriptional activation mapping in FFPE patient biopsies reveals novel druggable pathways in lymphoma

Abstract

Peripheral T-cell lymphomas (PTCL) are aggressive malignancies where clinical assessment relies on formalin-fixed paraffin-embedded (FFPE) biopsies, yet molecular characterization of these samples remains limited by RNA degradation and poor performance of existing genomic assays. This constraint has hindered the ability to define active regulatory programs directly in patient tissue. To address this challenge, we developed FFPE-CUT&Tag that maps RNA Polymerase II (RNAPII) occupancy to directly measure transcriptional activation in FFPE samples. The assay incorporates optimized antibody selection and FFPE-optimized workflows to enable robust, genome-wide profiling from precious clinical material. As a DNA-based method, FFPE-CUT&Tag overcomes limitations of RNA degradation while providing a direct readout of engaged regulatory elements. Across multiple tissue types, FFPE-CUT&Tag generated high-quality profiles with strong enrichment at promoters and distal regulatory elements, capturing tissue-specific transcriptional programs. Comparative analysis demonstrated improved signal-to-noise and resolution relative to FFPE-ATAC and conventional ATAC approaches, with enhanced ability to stratify genes by transcriptional activity in agreement with RNA-seq. These results establish FFPE-CUT&Tag as a sensitive and reproducible method for functional regulatory profiling in FFPE specimens. Application to archived lymphoma biopsies revealed transcriptional activation at AP-1 family loci, including BATF3. AP-1 activity was associated with multiple oncogenic pathways, including IL-2/STAT5, PI3K–AKT, and TP53, consistent with a coordinated regulatory program in PTCL. These findings demonstrate that FFPE-CUT&Tag enables direct detection of transcriptional dependencies in clinical samples and supports the use of FFPE-based transcriptional activation profiling to uncover clinically relevant regulatory pathways, including emerging targets such as the AP-1 axis. NOTE: Generative AI was used to assist in drafting the abstract text; all authors reviewed and approved the final content.