Prediction and identification of synergistic compound combinations against pancreatic cancer cells.

Resistance to current therapies is common for pancreatic cancer and hence novel treatment options are urgently needed. In this work, we developed and validated a computational method to select synergistic compound combinations based on transcriptomic profiles from both the disease and compound side, combined with a pathway scoring system, which was then validated prospectively by testing 30 compounds (and their combinations) on PANC-1 cells. Some compounds selected as single agents showed lower GI50 values than the standard of care, gemcitabine. Compounds suggested as combination agents with standard therapy gemcitabine based on the best performing scoring system showed on average 2.82-5.18 times higher synergies compared to compounds that were predicted to be active as single agents. Examples of highly synergistic in vitro validated compound pairs include gemcitabine combined with Entinostat, thioridazine, loperamide, scriptaid and Saracatinib. Hence, the computational approach presented here was able to identify synergistic compound combinations against pancreatic cancer cells

CHK1 Inhibition Synergizes with Gemcitabine Initially by Destabilizing the DNA Replication Apparatus.

Combining cell-cycle checkpoint kinase inhibitors with the DNA-damaging chemotherapeutic agent gemcitabine offers clinical appeal, with a mechanistic rationale based chiefly on abrogation of gemcitabine-induced G2-M checkpoint activation. However, evidence supporting this mechanistic rationale from chemosensitization studies has not been consistent. Here we report a systematic definition of how pancreatic cancer cells harboring mutant p53 respond to this combination therapy, by combining mathematical models with large-scale quantitative biologic analyses of single cells and cell populations. Notably, we uncovered a dynamic range of mechanistic effects at different ratios of gemcitabine and CHK1 inhibitors. Remarkably, effective synergy was attained even where cells exhibited an apparently functional G2-M surveillance mechanism, as exemplified by a lack of both overt premature CDK1 activation and S-phase mitotic entry. Consistent with these findings, S-G2 duration was extended in treated cells, leading to a definable set of lineage-dependent catastrophic fates. At synergistic drug concentrations, global replication stress was a distinct indicator of chemosensitization as characterized molecularly by an accumulation of S-phase cells with high levels of hyperphosphorylated RPA-loaded single-stranded DNA. In a fraction of these cells, persistent genomic damage was observed, including chromosomal fragmentation with a loss of centromeric regions that prevented proper kinetochore-microtubule attachment. Together, our results suggested a "foot-in-the-door" mechanism for drug synergy where cells were destroyed not by frank G2-M phase abrogation but rather by initiating a cumulative genotoxicity that deregulated DNA synthesis.This study was funded by Cancer Research UK via Institute Senior Group Leader funding (C14303/A17197) to DI Jodrell, and by Sentinel Oncology through an award from Innovate UK.This is the author accepted manuscript. The final version is available from American Association for Cancer Research via http://dx.doi.org/10.1158/0008-5472.CAN-14-334

An automated fitting procedure and software for dose-response curves with multiphasic features.

In cancer pharmacology (and many other areas), most dose-response curves are satisfactorily described by a classical Hill equation (i.e. 4 parameters logistical). Nevertheless, there are instances where the marked presence of more than one point of inflection, or the presence of combined agonist and antagonist effects, prevents straight-forward modelling of the data via a standard Hill equation. Here we propose a modified model and automated fitting procedure to describe dose-response curves with multiphasic features. The resulting general model enables interpreting each phase of the dose-response as an independent dose-dependent process. We developed an algorithm which automatically generates and ranks dose-response models with varying degrees of multiphasic features. The algorithm was implemented in new freely available Dr Fit software (sourceforge.net/projects/drfit/). We show how our approach is successful in describing dose-response curves with multiphasic features. Additionally, we analysed a large cancer cell viability screen involving 11650 dose-response curves. Based on our algorithm, we found that 28% of cases were better described by a multiphasic model than by the Hill model. We thus provide a robust approach to fit dose-response curves with various degrees of complexity, which, together with the provided software implementation, should enable a wide audience to easily process their own data.This work was funded by Cancer Research UK grant C14303/A17197.This is the final version of the article. It first appeared from NPG via http://dx.doi.org/10.1038/srep1470

The ATR Inhibitor AZD6738 Synergizes with Gemcitabine In Vitro and In Vivo to Induce Pancreatic Ductal Adenocarcinoma Regression.

Pancreatic ductal adenocarcinoma (PDAC) is among the deadliest cancers, and overall survival rates have barely improved over the past five decades. The antimetabolite gemcitabine remains part of the standard of care but shows very limited antitumor efficacy. Ataxia telangiectasia and Rad3-related protein (ATR), the apical kinase of the intra-S-phase DNA damage response, plays a central role in safeguarding cells from replication stress and can therefore limit the efficacy of antimetabolite drug therapies. We investigated the ability of the ATR inhibitor, AZD6738, to prevent the gemcitabine-induced intra-S-phase checkpoint activation and evaluated the antitumor potential of this combination in vitro and in vivo In PDAC cell lines, AZD6738 inhibited gemcitabine-induced Chk1 activation, prevented cell-cycle arrest, and restrained RRM2 accumulation, leading to the strong induction of replication stress markers only with the combination. Moreover, synergistic growth inhibition was identified in a panel of 5 mouse and 7 human PDAC cell lines using both Bliss Independence and Loewe models. In clonogenic assays, the combination abrogated survival at concentrations for which single agents had minor effects. In vivo, AZD6738 in combination with gemcitabine was well tolerated and induced tumor regression in a subcutaneous allograft model of a KrasG12D; Trp53R172H; Pdx-Cre (KPC) mouse cancer cell line, significantly extending survival. Remarkably, the combination also induced regression of a subgroup of KPC autochthonous tumors, which generally do not respond well to conventional chemotherapy. Altogether, our data suggest that AZD6738 in combination with gemcitabine merits evaluation in a clinical trial in patients with PDAC. Mol Cancer Ther; 17(8); 1670-82. ©2018 AACR

Mechanistic Distinctions between CHK1 and WEE1 Inhibition Guide the Scheduling of Triple Therapy with Gemcitabine.

Combination of cytotoxic therapy with emerging DNA damage response inhibitors (DDRi) has been limited by tolerability issues. However, the goal of most combination trials has been to administer DDRi with standard-of-care doses of chemotherapy. We hypothesized that mechanism-guided treatment scheduling could reduce the incidence of dose-limiting toxicities and enable tolerable multitherapeutic regimens. Integrative analyses of mathematical modeling and single-cell assays distinguished the synergy kinetics of WEE1 inhibitor (WEE1i) from CHEK1 inhibitor (CHK1i) by potency, spatiotemporal perturbation, and mitotic effects when combined with gemcitabine. These divergent properties collectively supported a triple-agent strategy, whereby a pulse of gemcitabine and CHK1i followed by WEE1i durably suppressed tumor cell growth. In xenografts, CHK1i exaggerated replication stress without mitotic CDK hyperactivation, enriching a geminin-positive subpopulation and intratumoral gemcitabine metabolite. Without overt toxicity, addition of WEE1i to low-dose gemcitabine and CHK1i was most effective in tumor control compared with single and double agents. Overall, our work provides quantitative insights into the mechanisms of DDRi chemosensitization, leading to the rational development of a tolerable multitherapeutic regimen.Significance: Multiple lines of mechanistic insight regarding DNA damage response inhibitors rationally guide the preclinical development of a tolerable multitherapeutic regimen.Graphical Abstract: http://cancerres.aacrjournals.org/content/canres/78/11/3054/F1.large.jpg Cancer Res; 78(11); 3054-66. ©2018 AACR