Epigenomic Profiling on FFPE Samples and Cancer Studies

Overview: Genome-wide hypertranscription is common in human cancer and predicts poor prognosis. To understand how hypertranscription might drive cancer, we applied our FFPE-CUTAC method for mapping RNA Polymerase II (RNAPII) genome-wide in formalin-fixed paraffin-embedded (FFPE) sections. We demonstrate global RNAPII elevations in mouse gliomas and assorted human tumors in small clinical samples and discover regional elevations corresponding to de novo HER2 amplifications punctuated by likely selective sweeps.

Motivation: Traditional methods for studying gene regulation in cancer have been limited by the availability of fresh tissue samples, making it difficult to analyze archived clinical specimens. FFPE tissue preservation, while excellent for maintaining morphological features, has historically posed challenges for molecular studies. Our FFPE-CUTAC method addresses these limitations by:

1. Enabling epigenomic profiling on archived FFPE samples
2. Providing genome-wide transcriptional state information
3. Allowing direct comparison between tumor and normal tissues
4. Supporting retrospective studies with clinical outcome data

Representative Results: Our comprehensive analysis spans multiple cancer types, demonstrating the broad applicability of FFPE-CUTAC:

• Breast carcinoma (36F)
• Colon adenocarcinoma (70M)
• Kidney clear-cell carcinoma (56F)
• Hepatocellular carcinoma (51M)
• Lung adenocarcinoma with papillary features (51M)
• Rectal well-differentiated adenocarcinoma (68F)
• Gastric adenocarcinoma (51M)

Each paired analysis reveals distinct RNAPII occupancy patterns between tumor and normal tissues, providing insights into cancer-specific transcriptional changes.

RNAPII occupancy at replication-coupled histone genes correlated with WHO grade in meningiomas, accurately predicted rapid recurrence, and corresponded to whole-arm chromosome losses. Elevated RNAPII at histone genes in meningiomas and diverse breast cancers is consistent with histone production being rate-limiting for S-phase progression and histone gene hypertranscription driving overproliferation and aneuploidy in cancer, with general implications for precision oncology.

Publications

⁺: co-corresponding author *: co-first author

1. Henikoff S*, Zheng Y*, Paranal R, Xu Y, Greene J, Henikoff J, Russell Z, Szulzewsky F, Thirimanne H, Kugel S, Holland E, Ahmad K. RNA Polymerase II at histone genes predicts outcome in human cancer. Science. ads2169 (2024).
2. Henikoff S, Zheng Y, Ahmad K. Mitotic errors do not explain aneuploidy in cancer. Under the second round of review of Trends in Genetics. (2024).
3. Vitanza N, Biery M, Myers C, Ferguson E,\textbf{Zheng Y}, Girard E, Przystal J, Park G, Noll A, Pakiam F, Winter C, Morris S, Sarthy J, Cole B, Leary S, Crane C, Lieberman N, Mueller S, Nazarian J, Gottardo R, Brusniak M, Mhyre A, Olson J. Optimal therapeutic targeting by HDAC inhibition in biopsy-derived treatment-naïve diffuse midline glioma models. Neuro-Oncology. (2021).
4. Wu S, Furlan S, Mihalas A, Kaya-Okur H, Feroze H, Emerson S, \textbf{Zheng Y}, Carson K, Cimino P, Keene C, Holland E, Sarthy J, Gottardo R, Ahmad K, Henikoff S, Patel A. Single-cell CUT&Tag analysis of chromatin modifications in differentiation and tumor progression. Nature Biotechnology. (2021).
5. Zeng X, Li B, Welch R, Rojo C, \textbf{Zheng Y}, Dewey CN, Kele\c{s} S. Perm-seq: Mapping Protein-DNA Interactions in Segmental Duplication and Highly Repetitive Regions of Genomes with Prior-enhanced Read Mapping. PLoS Computational Biology. (2015).

Protocols & Resources

1. Zheng Y, Ahmad K, Henikoff S. CUT&Tag Data Processing and Analysis Tutorial. Protocols.io. (2020)
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Book Chapter Book Chapter Savonen et al. Choosing Genomics Tools. (2023) Chapter 19 CUT&RUN and CUT&Tag.

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