American Association for Cancer Research
15357163mct150598-sup-152810_1_supp_3208127_nx1fxx.png (601.18 kB)

Supplementary Figure 7 from 3-Dimensional Patient-Derived Lung Cancer Assays Reveal Resistance to Standards-of-Care Promoted by Stromal Cells but Sensitivity to Histone Deacetylase Inhibitors

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posted on 2023-04-03, 15:45 authored by David Onion, Richard H. Argent, Alexander M. Reece-Smith, Madeleine L. Craze, Robert G. Pineda, Philip A. Clarke, Hari L. Ratan, Simon L. Parsons, Dileep N. Lobo, John P. Duffy, John C. Atherton, Andrew J. McKenzie, Rajendra Kumari, Peter King, Brett M. Hall, Anna M. Grabowska

Drug sensitivity of NSCLC specimens to HDAC inhibitors and combination with standards of care.


Janssen Research & Development, LLC and NC3Rs



There is a growing recognition that current preclinical models do not reflect the tumor microenvironment in cellular, biological, and biophysical content and this may have a profound effect on drug efficacy testing, especially in the era of molecular-targeted agents. Here, we describe a method to directly embed low-passage patient tumor–derived tissue into basement membrane extract, ensuring a low proportion of cell death to anoikis and growth complementation by coculture with patient-derived cancer-associated fibroblasts (CAF). A range of solid tumors proved amenable to growth and pharmacologic testing in this 3D assay. A study of 30 early-stage non–small cell lung cancer (NSCLC) specimens revealed high levels of de novo resistance to a large range of standard-of-care agents, while histone deacetylase (HDAC) inhibitors and their combination with antineoplastic drugs displayed high levels of efficacy. Increased resistance was seen in the presence of patient-derived CAFs for many agents, highlighting the utility of the assay for tumor microenvironment-educated drug testing. Standard-of-care agents showed similar responses in the 3D ex vivo and patient-matched in vivo models validating the 3D-Tumor Growth Assay (3D-TGA) as a high-throughput screen for close-to-patient tumors using significantly reduced animal numbers. Mol Cancer Ther; 15(4); 753–63. ©2016 AACR.