In:
Cancer Research, American Association for Cancer Research (AACR), Vol. 78, No. 13_Supplement ( 2018-07-01), p. 1308-1308
Abstract:
Epithelial-mesenchymal transition (EMT) mediates intrinsic and acquired resistance to epidermal growth factor receptor (EGFR) inhibitors. This becomes a major hurdle in lung cancer treatment due to the lack of effective therapeutic strategies. We hypothesized that decoding the EMT signaling network could provide insights into the specific combinatorial logic associated with EMT signaling and identify new therapeutic strategies to combat EGFRi resistance. To test this hypothesis, we applied sequential enrichment of post-translational modifications (SEPTM) proteomics to analyze proteomes of expressed proteins and multiple post-translational modifications (PTM) including phosphorylation, ubiquitination, and acetylation in erlotinib sensitive cells (HCC4006) and matched erlotinib resistant cells after EMT (HCC4006ER). We conducted integrative informatics to characterize EMT associated proteins, PTMs, pathways, cross-talk among PTMs and signaling networks from our data. We used siRNA and small molecules to functionally interrogate our results by assaying cell viability and migration. We identified 6,641 proteins, 2,418 unique pSTY sites, 784 unique UbK-sites and 713 unique AcK-sites respectively. We found 377 proteins increased and 1377 proteins decreased (p & lt;0.05, fold & gt;2) in HCC4006ER cells compared to parent HCC4006 cells. We constructed an EMT signaling network, composed of 206 proteins with PTM changes including pSTY-sites (141 increase, 191 decrease), UbK-sites (29 increase, 32 decrease) and AcK-sites (14 increase, 46 decrease). Of 206 differentially modified proteins, 88 proteins are reported to be associated with EMT. Pathway analysis enriched 284 pathways from this EMT signaling network. We identified small molecule inhibitors associated with various pathways and tested for their effects on resistant cells. Inhibitors targeting 17 pathways and 3 major transcription factors were found to have effects on H4006ER viability, with inhibitors targeting DDR1, WNT and CDK signaling pathways demonstrating the most impact. Using RNAi, we found that that loss-of-function of 8 of 88 EMT-associated proteins (TAGLN2, STMN1, FYN, HNRNPA2B1, DDR1, INPPL1, OSMR and PRKAR2A) decreased HCC4006ER cell viability. Finally, integrative informatics revealed cross-talk among PTMs within EMT signaling network. From this analysis, we found that inhibiting GLI induced transcription sensitizes H4006ER cells to both EGFR inhibitor and Casein Kinase inhibitor. Collectively, SEPTM proteomics allows decoding the complex interplay in PTM modulation associated with EMT-mediated resistance. Our results suggest DDR1 as a potential actionable target for EMT driven resistance, which can serve as an example for combinatorial targeting of EMT proteins and signaling pathways as a strategy for overcoming EMT-mediated drug resistance. Citation Format: Guolin Zhang, Karen Ross, Bin Fang, Jun-Min Zhou, Paul A. Stewart, Emma Adhikari, Eric A. Welsh, Xuefeng Wang, John M. Koomen, Cathy H. Wu, Eric B. Haura. Post translational crosstalk networks identify strategies to overcome EMT-mediated resistance to EGFR inhibitors [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2018; 2018 Apr 14-18; Chicago, IL. Philadelphia (PA): AACR; Cancer Res 2018;78(13 Suppl):Abstract nr 1308.
Type of Medium:
Online Resource
ISSN:
0008-5472
,
1538-7445
DOI:
10.1158/1538-7445.AM2018-1308
Language:
English
Publisher:
American Association for Cancer Research (AACR)
Publication Date:
2018
detail.hit.zdb_id:
2036785-5
detail.hit.zdb_id:
1432-1
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