Abstract 4095: Advancing cancer prognosis: FFPE-CUTAC for comprehensive and affordable transcription profiling in oncology

Abstract RNA-seq has been the method of choice for profiling patient samples. However, it predominantly detects genes expressed at moderate-to-high levels and is limited by the fragility of RNA, especially in Formalin-Fixed Paraffin-Embedded (FFPE) sections. We introduce Cleavage Under Targeted Accessible Chromatin (CUTAC) with an antibody to RNA Polymerase II (RNAPII) as a sensitive, cost-effective alternative for directly profiling transcription in FFPEs. Our findings reveal that FFPE-CUTAC libraries are significantly more comprehensive than RNA-seq libraries from both frozen and FFPE clinical sections, capturing low-level transcription of most active genes often missed by RNA-seq. Integrating RNAPII FFPE-CUTAC data from meningioma tumor samples with RNA-seq data from 1,298 patients, we demonstrate that RNAPII occupancy correlates strongly with transcriptional output. Embedding RNAPII FFPE-CUTAC datasets within a meningioma RNA-seq UMAP enhances the prediction of poor clinical outcomes, offering a powerful and economical replacement for RNA-seq in general cancer diagnosis. Moreover, we observed widespread hypertranscription in human cancers, which correlates with poor prognosis. Using FFPE-CUTAC, we demonstrated genome-wide hypertranscription in transgene-driven mouse gliomas and various human tumors at active regulatory elements. Notably, hypertranscription challenges most normalization strategies that assume equal fragment volumes across samples. Tumor burden varies greatly across patients and tumor types, with significantly more cells in tumors compared to their corresponding normal samples. Within tumor cells, hypertranscription results in substantially higher FFPE-CUTAC fragment count. Assuming equal reads between tumor and normal samples can obscure hypertranscription signals. To address this, we developed a background-driven normalization strategy for FFPE-CUTAC data, accounting for the variations of cell numbers and fragment volumes to ensure accurate comparison across tumor and normal samples. We validated this strategy using both single-cell simulated data and specially designed experiments with known cell proportions and signal fold changes. Our experimental and computational results affirm that FFPE-CUTAC provides a sensitive and affordable approach for detecting hypertranscription and classifying tumors using small tissue sections, advancing genome-wide strategies for personalized medicine. Citation Format: Ye Zheng, Kami Ahmad, Steven Henikoff. Advancing cancer prognosis: FFPE-CUTAC for comprehensive and affordable transcription profiling in oncology [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2025; Part 1 (Regular Abstracts); 2025 Apr 25-30; Chicago, IL. Philadelphia (PA): AACR; Cancer Res 2025;85(8_Suppl_1):Abstract nr 4095.