Genome-wide profiling of transcription factor activity in primary liver cancer using single-cell ATAC sequencing

Amanda J. Craig, Maruhen A.Datsch Silveira, Lichun Ma, Mahler Revsine, Limin Wang, Sophia Heinrich, Zachary Rae, Allison Ruchinskas, Kimia Dadkhah, Whitney Do, Shay Behrens, Farid R. Mehrabadi, Dana A. Dominguez, Marshonna Forgues, Anuradha Budhu, Jittiporn Chaisaingmongkol, Jonathan M. Hernandez, Jeremy L. Davis, Bao Tran, Jens U. MarquardtMathuros Ruchirawat, Michael Kelly, Tim F. Greten, Xin W. Wang*

*Corresponding author for this work

Abstract

Primary liver cancer (PLC) consists of two main histological subtypes; hepatocellular carcinoma (HCC) and intrahepatic cholangiocarcinoma (iCCA). The role of transcription factors (TFs) in malignant hepatobiliary lineage commitment between HCC and iCCA remains underexplored. Here, we present genome-wide profiling of transcription regulatory elements of 16 PLC patients using single-cell assay for transposase accessible chromatin sequencing. Single-cell open chromatin profiles reflect the compositional diversity of liver cancer, identifying both malignant and microenvironment component cells. TF motif enrichment levels of 31 TFs strongly discriminate HCC from iCCA tumors. These TFs are members of the nuclear/retinoid receptor, POU, or ETS motif families. POU factors are associated with prognostic features in iCCA. Overall, nuclear receptors, ETS and POU TF motif families delineate transcription regulation between HCC and iCCA tumors, which may be relevant to development and selection of PLC subtype-specific therapeutics.

Original languageEnglish
Article number113446
JournalCell Reports
Volume42
Issue number11
Pages (from-to)113446
ISSN2211-1247
DOIs
Publication statusPublished - 28.11.2023

Funding

Support from CCR Single Cell Analysis Facility for single-cell RNA-Seq captures, library preparation, sequencing and primary data processing was funded by FNLCR Contract 75N91019D00024. This work utilized the computational resources of the NIH HPC Biowulf cluster (http://hpc.nih.gov). This work was supported by grants (Z01 BC 010877, Z01 BC 010876, Z01 BC 010313, and ZIA BC 011870) from the intramural research program of the Center for Cancer Research, National Cancer Institute of the United States. J.U.M. was supported by a grant from the Wilhelm Sander Foundation (2021.089.1). BioRender software was used to generate the graphical abstract. Conceptualization, A.J.C. and X.W.W.; software, A.J.C. L.M. M.R. K.D. and F.R.M.; validation, A.J.C.; formal analysis, A.J.C. L.M. M.R. L.W. Z.R. A.R. K.D. W.D. S.B. F.R.M. M.A.D.S. M.F. B.T. and M.K.; resources, J.C. J.M.H. J.L.D. J.U.M. M.R. and T.F.G.; data curation, A.J.C. L.M. M.R. W.D. S.B. and D.A.D.; writing – original draft, A.J.C.; writing – review & editing, A.J.C. M.A.D.S. and X.W.W.; visualization, A.J.C. L.M. M.A.D.S. and W.D.; supervision, X.W.W.; project administration, A.J.C.; funding acquisition, X.W.W. The authors declare no competing interests. Support from CCR Single Cell Analysis Facility for single-cell RNA-Seq captures, library preparation, sequencing and primary data processing was funded by FNLCR Contract 75N91019D00024 . This work utilized the computational resources of the NIH HPC Biowulf cluster ( http://hpc.nih.gov ). This work was supported by grants ( Z01 BC 010877 , Z01 BC 010876 , Z01 BC 010313 , and ZIA BC 011870 ) from the intramural research program of the Center for Cancer Research , National Cancer Institute of the United States. J.U.M. was supported by a grant from the Wilhelm Sander Foundation ( 2021.089.1 ). BioRender software was used to generate the graphical abstract.

Research Areas and Centers

  • Research Area: Luebeck Integrated Oncology Network (LION)
  • Centers: University Cancer Center Schleswig-Holstein (UCCSH)

DFG Research Classification Scheme

  • 2.22-14 Hematology, Oncology

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