FRAX597, a PAK1 inhibitor, synergistically reduces pancreatic cancer growth when combined with gemcitabine

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Abstract

Background

Pancreatic ductal adenocarcinoma remains one of the most lethal of all solid tumours. Treatment options are limited and gemcitabine-based chemotherapy remains the standard of care. Although growing evidence shows that p21-activated kinase 1 (PAK1) plays a crucial role in pancreatic cancer, its role has not been fully elucidated. This study aimed to characterise the expression and functional relevance of PAK1 in pancreatic cancer.

Methods

PAK1 expression was measured in pancreatic cancer specimens by immunohistochemistry and in pancreatic cancer cell lines by western blotting. The effect of inhibition of PAK1 by either shRNA knock-down (KD), or by a selective inhibitor, FRAX597, alone or in combination with gemcitabine, on cell proliferation and migration/invasion was measured by thymidine uptake and Boyden chamber assays, respectively. The effect on tumour growth and survival was assessed in orthotopic murine models.

Results

PAK1 was expressed in all human pancreatic cancer samples tested, an7d was upregulated in all pancreatic cancer cell lines tested. PAK1 KD inhibited pancreatic cancer cell growth and survival, and increased sensitivity to gemcitabine treatment. AKT activity and HIF1α expression were also inhibited. FRAX597 inhibited pancreatic cancer cell proliferation, survival, and migration/invasion. When combined with gemcitabine, FRAX597 synergistically inhibited pancreatic cancer proliferation in vitro and inhibited tumour growth in vivo.

Conclusions

These results implicate PAK1 as a regulator of pancreatic cancer cell growth and survival. Combination of a PAK1 inhibitor such as FRAX597 with cytotoxic chemotherapy deserves further study as a novel therapeutic approach to pancreatic cancer treatment.

Electronic supplementary material

The online version of this article (doi:10.1186/s12885-016-2057-z) contains supplementary material, which is available to authorized users.

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Most cited references 17

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Quantitative analysis of dose-effect relationships: the combined effects of multiple drugs or enzyme inhibitors.

P Talalay, T C Chou (1984)

A generalized method for analyzing the effects of multiple drugs and for determining summation, synergism and antagonism has been proposed. The derived, generalized equations are based on kinetic principles. The method is relatively simple and is not limited by whether the dose-effect relationships are hyperbolic or sigmoidal, whether the effects of the drugs are mutually exclusive or nonexclusive, whether the ligand interactions are competitive, noncompetitive or uncompetitive, whether the drugs are agonists or antagonists, or the number of drugs involved. The equations for the two most widely used methods for analyzing synergism, antagonism and summation of effects of multiple drugs, the isobologram and fractional product concepts, have been derived and been shown to have limitations in their applications. These two methods cannot be used indiscriminately. The equations underlying these two methods can be derived from a more generalized equation previously developed by us (59). It can be shown that the isobologram is valid only for drugs whose effects are mutually exclusive, whereas the fractional product method is valid only for mutually nonexclusive drugs which have hyperbolic dose-effect curves. Furthermore, in the isobol method, it is laborious to find proper combinations of drugs that would produce an iso-effective curve, and the fractional product method tends to give indication of synergism, since it underestimates the summation of the effect of mutually nonexclusive drugs that have sigmoidal dose-effect curves. The method described herein is devoid of these deficiencies and limitations. The simplified experimental design proposed for multiple drug-effect analysis has the following advantages: It provides a simple diagnostic plot (i.e., the median-effect plot) for evaluating the applicability of the data, and provides parameters that can be directly used to obtain a general equation for the dose-effect relation; the analysis which involves logarithmic conversion and linear regression can be readily carried out with a simple programmable electronic calculator and does not require special graph paper or tables; and the simplicity of the equation allows flexibility of application and the use of a minimum number of data points. This method has been used to analyze experimental data obtained from enzymatic, cellular and animal systems.

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PAK signaling in cancer

Diana Zi Ye, Jeffrey Field (2012)

Transformation of a normal cell to a cancer cell is caused by mutations in genes that regulate proliferation, apoptosis, and invasion. Small GTPases such as Ras, Rho, Rac and Cdc42 orchestrate many of the signals that are required for malignant transformation. The p21-activated kinases (PAKs) are effectors of Rac and Cdc42. PAKs are a family of serine/threonine protein kinases comprised of six isoforms (PAK1–6), and they play important roles in cytoskeletal dynamics, cell survival and proliferation. They act as key signal transducers in several cancer signaling pathways, including Ras, Raf, NFκB, Akt, Bad and p53. Although PAKs are not mutated in cancers, they are overexpressed, hyperactivated or amplified in several human tumors and their role in cell transformation make them attractive therapeutic targets. This review discusses the evidence that PAK is important for cell transformation and some key signaling pathways it regulates. This review primarily discusses Group I PAKs (PAK1, PAK2 and PAK3) as Group II PAKs (PAK4, PAK5 and PAK6) are discussed elsewhere in this issue (by Minden).

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Pancreatic cancer: overview of descriptive epidemiology.

Maurice Zeegers, Carlo La Vecchia, Eva Negri … (2011)

Pancreatic cancer mortality rates have been increasing in high-income countries between the 1950s and the 1980s, and have leveled off or declined thereafter, particularly in men. To provide a global overview of recent pancreatic cancer mortality, we analyzed official death of the world certification data derived from the World Health Organization for 35 European countries and 19 other countries over the period 1980-2007. In 2007, the highest mortality rates from pancreatic cancer were in the Baltic countries, and some central/eastern and northern European countries (over 9.5/100 000 men and 6/100 000 women), whereas the lowest ones were in Latin America and Hong Kong (below 5/100 000 men and 3/100 000 women). Japan, the USA, Russia and the European Union (EU), as well as the largest countries in the EU, had rates around 7-9/100 000 men and 5-6/100 000 women. In the early 2000s, rates have been approximately stable in many European countries, as in the USA, Japan, and Australia. In Nordic countries and the UK, where declines in rates have been observed between the 1980s and the 1990s, mortality from pancreatic cancer has tended to rise over most recent calendar years. Some persisting rises were still found in men from a few countries of southern and central/eastern Europe (with low rates in the past), as well as in the EU overall, and in women from European and Asian countries. Recent trends were generally more favorable in young adults (30-49 yr), suggesting that overall trends are likely to improve in the near future. Copyright © 2011 Wiley Periodicals, Inc.

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Author and article information

Contributors

Dannel Yeo: yeod@student.unimelb.edu.au

Hong He: hong.he@unimelb.edu.au

Oneel Patel: patelo@unimelb.edu.au

Andrew M. Lowy: alowy@ucsd.edu.au

Graham S. Baldwin: grahamsb@unimelb.edu.au

Mehrdad Nikfarjam: mehrdad.nikfarjam@gmail.com

Journal

Journal ID (nlm-ta): BMC Cancer

Journal ID (iso-abbrev): BMC Cancer

Title: BMC Cancer

Publisher: BioMed Central (London )

ISSN (Electronic): 1471-2407

Publication date (Electronic): 16 January 2016

Publication date PMC-release: 16 January 2016

Publication date Collection: 2016

Volume: 16

Electronic Location Identifier: 24

Affiliations

[ ]Department of Surgery, Austin Health, University of Melbourne, Heidelberg, VIC Australia

[ ]Department of Surgery, Division of Surgical Oncology, University of California at San Diego, Moores Cancer, La Jolla, CA USA

Article

Publisher ID: 2057

DOI: 10.1186/s12885-016-2057-z

PMC ID: 4715347

PubMed ID: 26774265

SO-VID: 4aa8498d-6606-4b46-a663-1883fdcddc86

License:

Open AccessThis article is distributed under the terms of the Creative Commons Attribution 4.0 International License ( http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The Creative Commons Public Domain Dedication waiver ( http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated.

History

Date received : 12 August 2015

Date accepted : 8 January 2016

Funding

Funded by: FundRef http://dx.doi.org/10.13039/501100000925, National Health and Medical Research Council (AU);

Award ID: 508908

Award ID: 1020983

Award Recipient : Hong He Graham S. Baldwin

Funded by: FundRef http://dx.doi.org/10.13039/100000002, National Institutes of Health (US);

Award ID: CA155620-01

Award Recipient : Andrew M. Lowy

Funded by: FundRef http://dx.doi.org/http://dx.doi.org/10.13039/501100001193, Sir Edward Dunlop Medical Research Foundation (AU);

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ScienceOpen disciplines: Oncology & Radiotherapy

Keywords: pancreatic adenocarcinoma,pak1,gemcitabine,proliferation,orthotopic murine model

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ScienceOpen disciplines: Oncology & Radiotherapy

Keywords: pancreatic adenocarcinoma, pak1, gemcitabine, proliferation, orthotopic murine model

FRAX597, a PAK1 inhibitor, synergistically reduces pancreatic cancer growth when combined with gemcitabine

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Conclusions

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Karger: Oncology

Most cited references 17

Quantitative analysis of dose-effect relationships: the combined effects of multiple drugs or enzyme inhibitors.

PAK signaling in cancer

Pancreatic cancer: overview of descriptive epidemiology.

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