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Pancreatic cancer prognosis is predicted by an ATAC-array technology for assessing chromatin accessibility

Author

Listed:
  • S. Dhara

    (Dartmouth Geisel School of Medicine and Norris Cotton Cancer Center)

  • S. Chhangawala

    (Weill Cornell Graduate School of Medical Sciences
    Computational Biology Program, Memorial Sloan Kettering Cancer Center)

  • H. Chintalapudi

    (Dartmouth Geisel School of Medicine and Norris Cotton Cancer Center)

  • G. Askan

    (David M. Rubenstein Center for Pancreatic Cancer Research, Memorial Sloan Kettering Cancer Center)

  • V. Aveson

    (David M. Rubenstein Center for Pancreatic Cancer Research, Memorial Sloan Kettering Cancer Center
    Weill Cornell Medicine)

  • A. L. Massa

    (Dartmouth Geisel School of Medicine and Norris Cotton Cancer Center)

  • L. Zhang

    (David M. Rubenstein Center for Pancreatic Cancer Research, Memorial Sloan Kettering Cancer Center)

  • D. Torres

    (Dartmouth Geisel School of Medicine and Norris Cotton Cancer Center)

  • A. P. Makohon-Moore

    (David M. Rubenstein Center for Pancreatic Cancer Research, Memorial Sloan Kettering Cancer Center)

  • N. Lecomte

    (David M. Rubenstein Center for Pancreatic Cancer Research, Memorial Sloan Kettering Cancer Center)

  • J. P. Melchor

    (David M. Rubenstein Center for Pancreatic Cancer Research, Memorial Sloan Kettering Cancer Center)

  • J. Bermeo

    (David M. Rubenstein Center for Pancreatic Cancer Research, Memorial Sloan Kettering Cancer Center)

  • A. Cardenas

    (David M. Rubenstein Center for Pancreatic Cancer Research, Memorial Sloan Kettering Cancer Center)

  • S. Sinha

    (David M. Rubenstein Center for Pancreatic Cancer Research, Memorial Sloan Kettering Cancer Center)

  • D. Glassman

    (David M. Rubenstein Center for Pancreatic Cancer Research, Memorial Sloan Kettering Cancer Center)

  • R. Nicolle

    (Programme Cartes d’Identité des Tumeurs, Ligue Nationale Contre Le Cancer)

  • R. Moffitt

    (Stony Brook University)

  • K. H. Yu

    (David M. Rubenstein Center for Pancreatic Cancer Research, Memorial Sloan Kettering Cancer Center)

  • S. Leppanen

    (Agilent Technologies Inc.)

  • S. Laderman

    (Agilent Technologies Inc.)

  • B. Curry

    (Agilent Technologies Inc.)

  • J. Gui

    (Dartmouth Geisel School of Medicine and Norris Cotton Cancer Center)

  • V. P. Balachandran

    (David M. Rubenstein Center for Pancreatic Cancer Research, Memorial Sloan Kettering Cancer Center)

  • C. Iacobuzio-Donahue

    (David M. Rubenstein Center for Pancreatic Cancer Research, Memorial Sloan Kettering Cancer Center)

  • R. Chandwani

    (Weill Cornell Medicine)

  • C. S. Leslie

    (Computational Biology Program, Memorial Sloan Kettering Cancer Center)

  • S. D. Leach

    (Dartmouth Geisel School of Medicine and Norris Cotton Cancer Center)

Abstract

Unlike other malignancies, therapeutic options in pancreatic ductal adenocarcinoma (PDAC) are largely limited to cytotoxic chemotherapy without the benefit of molecular markers predicting response. Here we report tumor-cell-intrinsic chromatin accessibility patterns of treatment-naïve surgically resected PDAC tumors that were subsequently treated with (Gem)/Abraxane adjuvant chemotherapy. By ATAC-seq analyses of EpCAM+ PDAC malignant epithelial cells sorted from 54 freshly resected human tumors, we show here the discovery of a signature of 1092 chromatin loci displaying differential accessibility between patients with disease free survival (DFS) 1 year. Analyzing transcription factor (TF) binding motifs within these loci, we identify two TFs (ZKSCAN1 and HNF1b) displaying differential nuclear localization between patients with short vs. long DFS. We further develop a chromatin accessibility microarray methodology termed “ATAC-array”, an easy-to-use platform obviating the time and cost of next generation sequencing. Applying this methodology to the original ATAC-seq libraries as well as independent libraries generated from patient-derived organoids, we validate ATAC-array technology in both the original ATAC-seq cohort as well as in an independent validation cohort. We conclude that PDAC prognosis can be predicted by ATAC-array, which represents a low-cost, clinically feasible technology for assessing chromatin accessibility profiles.

Suggested Citation

  • S. Dhara & S. Chhangawala & H. Chintalapudi & G. Askan & V. Aveson & A. L. Massa & L. Zhang & D. Torres & A. P. Makohon-Moore & N. Lecomte & J. P. Melchor & J. Bermeo & A. Cardenas & S. Sinha & D. Gla, 2021. "Pancreatic cancer prognosis is predicted by an ATAC-array technology for assessing chromatin accessibility," Nature Communications, Nature, vol. 12(1), pages 1-9, December.
  • Handle: RePEc:nat:natcom:v:12:y:2021:i:1:d:10.1038_s41467-021-23237-2
    DOI: 10.1038/s41467-021-23237-2
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