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

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. Glassman, R. Nicolle, R. Moffitt, K. H. Yu, S. Leppanen, S. Laderman, B. Curry, J. Gui, V. P. Balachandran, C. Iacobuzio-Donahue, R. Chandwani, C. S. Leslie () and S. D. Leach ()
Additional contact information
S. Dhara: Dartmouth Geisel School of Medicine and Norris Cotton Cancer Center
S. Chhangawala: Weill Cornell Graduate School of Medical Sciences
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
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

Nature Communications, 2021, vol. 12, issue 1, 1-9

Abstract: 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.

Date: 2021
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DOI: 10.1038/s41467-021-23237-2

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