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. 2019 Aug 3;34(5-6):403–411. doi: 10.1093/mutage/gez021

KRAS pathway expression changes in pancreatic cancer models by conventional and experimental taxanes

M Oliverius 1,2,#, D Flasarova 3,#, B Mohelnikova-Duchonova 3,4, M Ehrlichova 5, V Hlavac 5, M Kocik 2, O Strouhal 3, P Dvorak 5, I Ojima 6, P Soucek 4,5,✉
PMCID: PMC6923165  PMID: 31375828

Abstract

The KRAS signalling pathway is pivotal for pancreatic ductal adenocarcinoma (PDAC) development. After the failure of most conventional cytotoxic and targeted therapeutics tested so far, the combination of taxane nab-paclitaxel (Abraxane) with gemcitabine recently demonstrated promising improvements in the survival of PDAC patients. This study aimed to explore interactions of conventional paclitaxel and experimental taxane SB-T-1216 with the KRAS signalling pathway expression in in vivo and in vitro PDAC models in order to decipher potential predictive biomarkers or targets for future individualised therapy. Mouse PDAC PaCa-44 xenograft model was used for evaluation of changes in transcript and protein levels of the KRAS signalling pathway caused by administration of experimental taxane SB-T-1216 in vivo. Subsequently, KRAS wild-type (BxPc-3) and mutated (MiaPaCa-2 and PaCa-44) cell line models were treated with paclitaxel to verify dysregulation of the KRAS signalling pathway gene expression profile in vitro and investigate the role of KRAS mutation status. By comparing the gene expression profiles, this study observed for the first time that in vitro cell models differ in the basal transcriptional profile of the KRAS signalling pathway, but there were no differences between KRAS mutated and wild-type cells in sensitivity to taxanes. Generally, the taxane administration caused a downregulation of the KRAS signalling pathway both in vitro and in vivo, but this effect was not dependent on the KRAS mutation status. In conclusion, putative biomarkers for prediction of taxane activity or targets for stimulation of taxane anticancer effects were not discovered by the KRAS signalling pathway profiling in various PDAC models.

Introduction

Pancreatic ductal adenocarcinoma (PDAC, OMIM: 260350) ranks among the less frequent cancer diagnoses (ranking 12th in incidence worldwide). However, its mortality is the fourth leading cause of cancer death today and predicted to become the second leading cause of cancer death in the USA by 2030 (1,2). Systemic chemotherapy is administered to >80% of PDAC patients, but the mortality, paralleling the incidence, indicates the failure of either conventional chemotherapy or any so far tested targeted therapeutics.

As stated above, the need for better therapies resulted in numerous clinical trials and experiments aiming to individualise the therapy (3). The combination of taxane nab-paclitaxel (Abraxane) with gemcitabine, along with some other drug combination regimens, e.g. leucovorin, 5-fluorouracil, irinotecan and oxaliplatin (FOLFIRINOX), brought promising improvements in survival of PDAC patients (4,5). Taxanes are mitotic poisons inhibiting microtubule depolymerisation during cell division (6) and blocking the G2/M phase of the cell cycle. Our previous work has shown that the new generation taxoid SB-T-1216 (7) suppresses the Hedgehog pathway expression in PDAC PaCa-44 xenograft in vivo model indicating a new mechanism of taxane action with potential use for PDAC treatment (8). In line with the previous observation that another new generation taxane SB-T-1214 exerts high cytotoxic potency against human PDAC cell line (BxPc-3 and PANC-1) in vitro and CFPAC-1 xenograft in vivo models these compounds seem very promising for future PDAC therapy development (7).

The RAS pathway, together with Hedgehog, TGFB, NOTCH, WNT/CTNNB1, RB, SWI/SNF and DNA repair, is among the most frequently implicated pathways in PDAC (9). Somatic KRAS gene (OMIM: 190070) mutations were observed in 71% PDAC patients (n = 7431) and 99% of these are missense substitutions, mainly in codon 12 (10). The most prevalent mutations are p.G12D (47% from all KRAS mutations), p.G12V (31%) and p.G12R (12%), while the rest accounts for <10% of the total (10). These mutations cause persistent KRAS activation and subsequent dysregulation of a number of cellular functions leading to metabolic reprogramming, loss of differentiation, accelerated proliferation and prolonged survival. Despite numerous studies about the prognostic and predictive role of KRAS mutations in PDAC having been conducted, the published results remain controversial and so far preclude the clinical use of KRAS in PDAC diagnosis, prognosis and therapy individualisation (11). Association of the KRAS signalling pathway dysregulation and the KRAS mutation status with survival of PDAC patients has not recently been confirmed (12). Moreover, there are no clinically successful inhibitors of this pathway either (13) and therefore it is imperative to search for biomarkers of personalisation of conventional therapeutics most successful in PDAC treatment to date.

Taken together, the detailed mechanisms and consequences of the KRAS signalling pathway dysregulation in PDAC chemoresistance and progression remain incompletely understood and the same applies to the potential contribution of the KRAS signalling pathway status to taxane mechanism of action. Recently, functional genetic screens demonstrated that KRAS expression in cancer cell lines leads to sensitivity and interference with mitosis and the co-existence of KRAS mutations and high MYC expression predicts anti-mitotic drug sensitivity (14).

The aim of the present study was to evaluate whether the administration of experimental taxane SB-T-1216 to PDAC mouse xenograft model in vivo and conventional paclitaxel to PDAC cell lines in vitro interacts with the KRAS signalling pathway expression on both a transcript and protein level. This is the first study to date addressing interactions between the major PDAC driver signalling pathway (RAS) and the clinically successful anticancer compounds used for treatment of this cancer.

Materials and methods

Xenografts

The human-mouse xenograft study was conducted in the Institute of Clinical and Experimental Medicine (Prague, Czech Republic) and approved by the Institutional Review Board of the Institute.

SB-T-1216 was synthesised and characterised as previously described (7). Female athymic nude mice (nu/nu) between 4 and 6 weeks of age were obtained from Charles River Laboratories (Duesseldorf, Germany). Human pancreatic carcinoma cell line Paca-44 with the already described characteristics (8) was obtained from the Leibniz Institute DSMZ-German Collection of Microorganisms and Cell Cultures (Braunschweig, Germany) and cultivated according to the manufacturer’s protocol. The Paca-44 cell line was used because it harbours the G12V mutation in KRAS (15) frequently occurring in PDAC patients and also for its fast and homogeneous growth in subcutaneous tumours compared to other PDAC cell lines (16). On Day 0, the animals were injected subcutaneously with 200 µl of a cell suspension containing 5 × 106 cells in phosphate-buffered saline. The treatment was initiated after the tumours reached a size of ~100 mm3. In total, 12 Paca-44 xenografts were prepared and divided into two groups: (A) SB-T-1216-treated group (n = 5) and (B) control group (n = 7). Group A received intravenously two doses of 10 mg of SB-T-1216 per kg weight weekly, i.e. the first dose on Day 1 and the second dose on Day 7. Group B received no treatment. The animals were sacrificed on the day after the second dose, i.e. on the eighth day after the first dose. Tumour volume was estimated by calliper in weekly intervals and expressed in mm3 using the standard formula, (W2 × L)/2, where L and W are the major and minor diameters of the tumour in millimetres.

Isolation of nucleic acids and cDNA synthesis

Tissue samples and cell pellets were homogenised and total RNA and DNA was isolated and characterised as previously described (17). cDNA was synthesised using 0.5 μg of total RNA, characterised as described previously (18) and then preamplified by TaqMan PreAmp Master Mix to enrich the specific targets for gene expression analysis using TaqMan Gene Expression Assays (Supplementary Table 1, available at Mutagenesis Online, Life Technologies Corp., Carlsbad, CA, USA). The cDNA preamplification was performed with 5 μl of cDNA using 14 preamplification cycles, and the preamplification uniformity of cDNA was checked by the procedure recommended by the manufacturer (Life Technologies Corp.).

Selection of genes representing the KRAS signalling pathway

Genes for the study of the KRAS signalling pathway were selected using publicly available databases KEGG (19) and BioCarta (20). In total, 42 genes were selected for gene expression analysis (Supplementary Table 1, available at Mutagenesis Online).

Quantitative real-time PCR

Quantitative real-time PCR (qPCR) was performed by the Roche LightCycler 480 Real-Time PCR System using TaqMan® Gene Expression Assays with optimised primer and probe sets and TaqMan™ Universal Master Mix II with UNG (Life Technologies Corp.). The PCR reaction was run in a 96-well plate and the total volume of the reaction mixture per well was 10 µl. POP4, ELF1, MRPL19 and EIF2B1 were used as reference genes specific for studies of human PDAC based on our previously published data (21). The non-template control (NTC) contained water instead of cDNA. Negative cDNA synthesis controls (RNA transcribed without reverse transcriptase) were also employed to reveal possible carry-over contamination. Each sample was assayed in duplicate and the mean value was used for calculations. The PCR reaction was started at 50°C for 2 min, followed by initial denaturation for 10 min at 95°C, followed by 40 cycles of denaturing for 15 s at 95°C and elongation for 1 min at 60°C. Samples with a variation larger than 0.5 Ct (cycle threshold) were reanalysed. Transcript levels were analysed by Roche LightCycler 480 System Software. The ratio of Ct of a particular target gene to an arithmetic mean of Ct of all the reference genes was calculated for each sample and used for statistical evaluation using RT2 Profiler PCR Array Data Analysis v3.5 (Qiagen). The qPCR study adhered to the MIQE Guidelines (Minimum Information for Publication of Quantitative Real-Time PCR Experiments) (22).

Cells and culture conditions

Human PDAC MiaPaCa-2 cell line [harbouring the KRAS G12C mutation and resistant to gemcitabine (23)] and BxPc-3 [KRAS wild-type and sensitive to gemcitabine (23)] were purchased from American Type Culture Collection (Manassas, VA, USA). The origin of the cell line Paca-44 [KRAS G12V mutant (15)] is described above in the chapter about xenografts. Cells between 4th and 40th passages were used for all the experiments. The cell line was authenticated and genomic stability monitored in the 4th and 40th passages by Short Tandem Repeat profiling using PowerPlex ESI 17 Pro System (Promega Corp., Madison, WI, USA). Cells were cultured in a basic medium with added heat-inactivated (Paca-44, MIAPaCa-2) or native (BxPC-3) 10% foetal bovine serum in a humidified atmosphere of 5% CO2 at 37°C. RPMI 1640 containing extra L-glutamine (300 μg/ml), sodium pyruvate (110 μg/ml), 15 mM HEPES buffer, penicillin (100 U/ml) and streptomycin (100 μg/ml) was used as a basic medium. The cells were trypsinised by 0.25% Trypsin and 0.02% EDTA in phosphate-buffered saline (all chemicals from PANBiotech GmbH, Aidenbach, Germany).

Cell line treatment with paclitaxel

Cells grown in the culture medium were harvested by low-speed centrifugation, washed with medium, seeded at 1 × 106 cells/5 ml (biological duplicates) of medium into plastic culture dishes and preincubated for 18 h allowing the cells to attach. The medium was changed to a culture medium without paclitaxel (control) or with selected concentrations of paclitaxel (30, 100 and 300 nM). After the required incubation period (24 and 72 h), the cells were harvested by low-speed centrifugation, washed with phosphate-buffered saline and the pellets of the cells were suspended in 1 ml of Trizol Reagent. The total RNA was isolated and cDNA was synthesised as described before (17,18).

Cytotoxicity assessment

Cells maintained in the culture medium were harvested by low-speed centrifugation, washed with the medium and then seeded at 5 × 103 cells/200 µl of the medium into the wells of a E-Plate View 16PET (ACEA Biosciences Inc., San Diego, CA, USA). After 18 h of preincubation period allowing the cells to attach, the medium without a taxane (control) or with a taxane at desired concentrations (0, 3, 10, 30, 100, 300 and 1000 nM) was added in a 2 μl volume. Cell growth and survival were evaluated after 72 h of incubation by xCELLigence Real-Time cell Analyzer (RTCA). The number of living cells (IC50) was determined by RTCA Software (ACEA Biosciences Inc.).

Immunoblotting analysis of protein expression

All tissue samples were stored at −80°C prior to protein isolation. The samples were ground using a mortar and pestle and then the protein was isolated using Allprep DNA/RNA/Protein Mini kit (Qiagen, Hildesheim, Germany) in accordance with the manufacturer’s protocol. Protein concentration was determined by a bicinchoninic acid assay (Pierce BCA Protein Assay Kit, Thermo Scientific Pierce Protein Research Products, Rockford, IL, USA). Immunoblotting was performed as previously described (24). Briefly, 20 μg of protein was used for separation by sodium dodecyl sulfate-polyacrylamide gel electrophoresis (10% gel, Precision Plus Protein™ Kaleidoscope™ Standards Bio-Rad #161-0375 as a ladder) and transferred onto 0.2 µm Protran® nitrocellulose membrane (Whatman, Kent, UK). The membranes were first blocked in 5% w/v bovine serum albumin for 30 min at room temperature. Membranes were then incubated overnight at 4°C with primary antibodies. Rabbit monoclonal antibodies against total MEK1/2 (no. D1A5, dilution in incubation 1:1000 in 1% blocking reagent), phospho-MEK1/2-Ser221 (no. 166F8, 1:2000), total ERK1/2 (no. 137F5, 1:1000), phospho-ERK1/2-Tyr202/Tyr204 (no. D13.14.4E, 1:2000), total AKT (no. C67E7, 1:1000), phospho-AKT-Ser473 (no. D9E, 1:2000), β-actin (no. 13E5, 1:1000 for tumour samples and 1:2000 for cell line samples) and GAPDH (no. 14C10, 1:2000) were purchased from Cell Signaling Technology (Danvers, MA, USA) and antibodies against KRAS (no. GTX100636, dilution 1:1000) and RAF1 (no. GTX61196, dilution 1:1000) from GeneTex (Irvine, CA, USA). After the washing steps, the membranes were incubated for 2 h at room temperature with corresponding horseradish peroxidase-conjugated secondary antibodies (no. A0545, dilution 1:10000; Sigma-Aldrich, Prague, Czech Republic). Protein bands were visualised with an enhanced chemiluminescence detection system (Thermo Scientific Pierce Protein Research Products) by Odyssey Fc Imaging System (LI-COR Biosciences, Lincoln, NE, USA). Densitometry was performed using ImageJ program (https://imagej.nih.gov/ij/).

Statistical analyses

Data preprocessing and a quality check was performed with the use of Microsoft Excel software. The fold change due to treatment was calculated from raw Ct values in accordance with the comparative Ct method described by Livak and Schmittgen (25). Hierarchical clustering and heat map visualisation were performed with the help of publicly available bioinformatic tools, Heatmapper (26) and Shinyheatmap (27). Hierarchical clustering with Euclidean distances and the Ward method was chosen as the best for visualisation of our data from in vivo experiment in accordance with previous experiences (8,28) and the Spearman correlation with complete linkage was used for evaluation of in vitro experiments.

Differences in single gene and protein expression levels between the treated and control xenografts were assessed by the ANOVA test using SPSS v16.0 Software (SPSS Inc., Chicago, IL, USA). The transcript levels of target genes normalised to reference genes and protein levels normalised to the level of GAPDH or β-actin control proteins were used.

A P-value of <0.05 was considered statistically significant. All P-values are departures from two-sided tests. Type I error in single gene expression analyses was controlled by the false discovery rate (FDR) test according to Benjamini and Hochberg (29) and adjusted P-values are provided for each comparison except for xenograft protein level analyses.

Results

Transcript levels of the KRAS signalling pathway genes in mouse xenografts—effect of SB-T-1216 treatment in vivo

Expression of 42 KRAS pathway genes was determined in tumour tissues by qPCR. First, the KRAS signalling pathway gene expression profile was evaluated by hierarchical clustering and then by single gene analysis. Cluster analysis indicated that SB-T-1216 treatment of Paca-44 xenografts resulted in division of the expressed genes into two major clusters, one composed of 25 and the other composed of 17 genes (heat map in Figure 1A, genes divided into both clusters in Supplementary Figure 1, available at Mutagenesis Online). Single gene analysis basically confirmed the general view of the cluster analysis, i.e. downregulation of the majority of the KRAS signalling pathway genes by SB-T-1216 treatment in vivo (Figure 1B). Significant downregulation of 18 genes and upregulation of SHC1 were observed after correction to multiple testing (Supplementary Table 2, available at Mutagenesis Online).

Figure 1.

Figure 1.

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Dysregulation of the KRAS signalling pathway by treatment of PDAC mouse PaCa-44 xenograft model with SB-T-1216 in vivo. (A) Heat map of the KRAS pathway gene expression profile in control animals (n = 7, marked with rectangle) compared with SB-T-1216-treated ones (n = 5). Upregulated genes are in red (in black and white resolution represented in dark colour) and downregulated genes are in green (in black and white resolution represented in light colour). The two most apparent clusters of dysregulated genes between both groups are highlighted with a light and dark grey box (for a list of genes and their positions in the KRAS signalling pathway, see Supplementary Figure 1, available at Mutagenesis Online). (B) The KRAS signalling pathway map noting the differentially expressed genes in control animals compared with SB-T-1216-treated ones. Downregulated genes are in green (in black and white resolution represented in light colour) and upregulated genes are in red (in black and white resolution represented in dark colour). Genes without differential expression are without colour. A list of genes with significances and directions of dysregulation is in Supplementary Table 2, available at Mutagenesis Online. MAPK pathway scaffold is in rounded rectangle. Figure available in colour online.

The downregulated genes represented the upstream branch of the PI3K/AKT pathway including AKT1/2, RAC1 and PAK1 and the downstream genes of RALGDS and RIN1 branches of the KRAS signalling pathway, including JNK kinases MAPK9 and MAPK10. The stem, including MAPK scaffold, of the KRAS signalling pathway was also mostly downregulated (KRAS, ARAF, MAP2K2, MAPK1, MKNK2 and RPS6AK2) indicating pathway suppression on a transcript level.

Protein expression of major parts of the KRAS signalling pathway in SB-T-1216-treated mouse xenografts in vivo

In order to elaborate results from gene expression study, the levels of proteins representing the stem of the KRAS and the scaffold of the MAPK pathways (KRAS, RAF1, MAP2K1/2—MEK, MAPK1/3—ERK) and (pan)AKT were determined in tumour samples from control and SB-T-1216-treated animals by immunoblotting. MAPK scaffold (MEK and ERK) and AKT were followed in both total and phosphorylated protein forms (Figure 2A). Densitometry demonstrated that the KRAS protein level was downregulated (P = 0.039) while RAF1, pERK and tAKT were significantly upregulated (P = 0.027, P = 0.009 and P = 0.007, respectively) by the SB-T-1216 treatment in vivo (Figure 2B).

Figure 2.

Figure 2.

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Changes in the major KRAS signalling pathway protein levels by treatment of PDAC mouse PaCa-44 xenograft model with SB-T-1216 in vivo. (A) Immunoblots of the KRAS signalling pathway proteins in control animals (n = 4) compared with SB-T-1216-treated ones (n = 4). KRAS, RAF1, t- and p-MEK, t- and p-ERK and t- and p-AKT levels were determined by immunoblotting and quantified by densitometry as described in the Materials and methods. Actin and GAPGH protein levels were used for normalisation of the results (the average of the three independent blots). (B) Normalised levels of the KRAS signalling pathway proteins in the control and SB-T-1216-treated animals assessed by densitometry. Statistical significance is depicted by stars (* means 0.05 > P > 0.01 and **P < 0.01). Figure available in colour online.

Immunoblotting analysis therefore confirmed downregulation of KRAS effector previously observed on the transcript level, but revealed upregulation of RAF1 and AKT in contrast with downregulation of the corresponding transcripts levels (of the borderline significance for RAF1 transcript, P = 0.055). In terms of ERK, the significant increase in the phosphorylated protein level as the post-transcriptional event cannot be paralleled with the transcript data and represents a unique observation of this study.

Transcript level analysis of the KRAS signalling pathway genes in cell line models with different KRAS mutation status—effect of treatment with paclitaxel in vitro

The time and concentration course of taxane effects on the gene expression of the KRAS signalling pathway and the potential modulatory effect of the KRAS mutation status were studied using several in vitro models differing in terms of the KRAS mutation status. Genes upstream KRAS effector (GRB2, RASA1/2, SOS1/2 and SHC1) and RAP1A were not addressed in these experiments due to the lack of major effects in vivo. Paclitaxel was used in these experiments because it had comparable cytotoxicity (measured as IC50 by RTCA—see Supplementary Figure 2, available at Mutagenesis Online) in all the examined PDAC models. Moreover, paclitaxel is relevant to anticancer therapy of patients.

The gene expression profile of all the cell lines without treatment was initially compared together to estimate major differences connected with KRAS mutation status. Cells cultivated for 24 h without any treatment were compared by hierarchical clustering (Supplementary Figure 3A, available at Mutagenesis Online). The KRAS signalling pathway gene expression profile of BxPc-3 KRAS wild-type cell line notably differed from both KRAS mutated cell lines MiaPaCa-2 and PaCa-44. The KRAS pathway stem, including the KRAS effector molecule and MAPK scaffold, was mostly downregulated while several upstream genes belonging to branches (RALGDS, RIN1, RAC1 and PIK3CG) were upregulated in KRAS wild-type BxPc-3 line compared to both KRAS mutated lines in vitro (Supplementary Figure 3B and Supplementary Table 3, available at Mutagenesis Online).

The time and concentration course of paclitaxel effects was consequently studied in all three cell line models differing by the KRAS mutation status in vitro. The time course analysis monitored changes in the KRAS signalling pathway gene expression as early changes—24 h after paclitaxel treatment and late changes—72 h after treatment. The concentration course involved control cells without treatment and cells treated with increasing concentration of paclitaxel (30, 100 and 300 nM).

The KRAS signalling pathway dysregulation in PaCa-44 cells, caused by paclitaxel after treatment for 24 h in vitro, was compared to changes in PaCa-44 mouse xenografts treated with SB-T-1216 in vivo. Several common trends were observed, namely downregulation of the main stem genes KRAS, ARAF, MAP2K2, MKNK2 and RPS6AK2 and downregulation of other genes representing pathway branches (PIK3CA, PDPK1, AKT2, PAK1, RALBP1 and RAC1) (Supplementary Figure 4, available at Mutagenesis Online). This overall concordance suggested that both taxane derivatives produce similar main effects in both in vitro and in vivo models. In contrast, MAPK9 was downregulated by SB-T-1216 in vivo, but upregulated by paclitaxel in vitro suggesting subtle differences worth further study.

The effect of paclitaxel on dysregulation of the KRAS signalling pathway genes in various cell line models, differing in the KRAS mutation status, was finally evaluated by hierarchical clustering. Concentration-dependent changes were monitored in both times (24 and 72 h) and within all three cell lines (cluster analysis in Supplementary Figure 5, available at Mutagenesis Online). Consistent changes in all three cell lines (trends of up or downregulation with increasing paclitaxel concentration) for both times were observed in general. A comparison makes it apparent that the response of cell line models to paclitaxel on a transcript level does not significantly differ according to the KRAS mutation status (BxPc-3 compared to the rest).

Early effects of paclitaxel (24-h treatment, Figure 3A) may be generalised as downregulation of the major KRAS pathway stem including MAPK scaffold (KRAS, ARAF, BRAF, MAP2K1/2 and MKNK2 genes) and branches, namely upstream RAC1 (RALA and RALBP1) and downstream PIK3CA (PDPK1 and RAC1) and AKT (MTOR and GSK3B). The majority of early changes rather faded away at 72 h with several exceptions. PTK2, MAPK3 and MAP3K1 became downregulated and RALGDS upregulated after 72 h and may be considered major late effects of paclitaxel treatment (Figure 3B; Table 1).

Figure 3.

Figure 3.

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Time-dependent changes of gene expression of the KRAS signaling pathway after treatment of PDAC model cell lines differing by the KRAS mutation status with paclitaxel in vitro. Map of consensus in the KRAS signaling pathway expression profiles of paclitaxel (30, 100 and 300 nM) treated BxPc-3, PaCa-44 and MiaPaCa-2 cell lines treated with the same paclitaxel concentrations for 24 h (A) and 72 h (B) compared to corresponding untreated controls. Genes upregulated in a concentration dependent manner are in red (in black and white resolution represented in dark colour) and downregulated genes in green (in black and white resolution represented in light colour). Genes without differential expression are without color. Time-dependent differences are highlighted by rectangles. Changes present only after 24 h treatment are in light grey rectangles in the B part and changes present only after 72 h treatment are in dark grey rectangles in the A part. MAPK pathway scaffold is in rounded rectangle.

Table 1.

Table 1.

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Time-dependent changes of expression of the KRAS signalling pathway genes after treatment of PDAC model cell lines differing by the KRAS mutation status with paclitaxel in vitro

Discussion

PDAC is a disease with infaust prognosis, especially for late diagnosis in the advanced stage of the disease, high resistance to chemotherapy and the absence of effective targeted therapy. Mutations in KRAS occur in PDAC with frequencies higher than 90%. Mutations in codons 12 and 13 of the KRAS gene result in protein blockage in an active state in with it is unable to hydrolyse GTP, triggering continuous KRAS signalling activity. Dysregulation of this pathway ultimately results in the development of pancreatic cancer. Genes of four branches of KRAS signalling pathway are differentially expressed in PDAC tumour tissue compared to non-tumour paired tissue. Three out of four branch pathways (PI3K/PDK1/AKT, RAL guanine nucleotide exchange factor and RIN1/ABL) are significantly overexpressed, which are in direct context with tumour cell migration and disease spread. In contrast, the expression of RAF/MAPK branch pathway in PDAC is reduced (12). Studying the KRAS signalling pathway is therefore extremely important and a detailed understanding of its functioning can contribute to the effectiveness of PDAC treatment.

The present study addressed the effect of taxanes on the expression of KRAS signalling pathway in various experimental PDAC models in search of biomarkers and/or targets enabling personalised therapy of this cancer.

In vivo, the treatment with experimental taxane SB-T-1216 significantly suppressed the KRAS signalling pathway stem and major branches on the transcript level paralleled by the observed downregulation of KRAS effector protein expression. A highly similar observation has previously been described in a case of other major PDAC carcinogenesis-associated signalling pathway (8). All the Hedgehog signalling pathway genes downstream of the Sonic Hedgehog ligand were transcriptionally downregulated by SB-T-1216 treatment of PaCa-44 mouse xenografts in vivo (8). We further explored this phenomenon using in vitro PDAC models with a different KRAS mutation status.

A recently published patient study concluded that KRAS mutation status is not associated with either the intratumoural gene expression profile of KRAS signalling pathway or with the clinical outcome of PDAC patients (12). Although a recent meta-analysis reported the potential prognostic role of KRAS mutation status in PDAC (30), another study has found no significant difference in overall survival for KRAS wild-type patients compared to mutation carriers (31). Congruently, no putative biomarker or therapeutic target in the KRAS signalling pathway has been found by the present study.

Some particular results may need more attention. Despite transcriptional downregulation of the upstream branch of the PI3K/AKT signalling pathway (AKT1/2, RAC1 and PAK1) having been observed, AKT and RAF1 proteins were increased by taxane treatment in vivo. The PI3K/AKT/MTOR pathway represents a significant target for various clinically tested inhibitors (32). However, despite the fact that tAKT was increased, its active form pAKT remained unchanged by taxane treatment in the present study and thus the observed discrepancy may not be biologically relevant. In contrast, the RAF1 induction by taxane treatment in vivo may have future implications for drug design. First, very recently a detailed mapping of membrane components necessary for the KRAS signal transduction discovered the key role of RAF1 domains synergising the KRAS partitioning to the membrane (33). Second, RAF proteins activate MEK1/2 and subsequently drive the MAPK pathway stem modulating terminal regulators of cell proliferation, survival, differentiation and apoptosis (34). Additionally, the present study ascertained the discrepancy in MAPK9 dysregulation; it was downregulated by SB-T-1216 in vivo, but upregulated by paclitaxel in vitro. MAPK9 has been found as the top immunogenic candidate antigen in PDAC compared to healthy donor sera (35) and together with several other tested factors related to host immune response to cancer has potential as a putative diagnostic screening tool or prognostic biomarker (36). Moreover, docetaxel induces activation of MAPK9 (formerly termed JNK2) and accelerates cancer cell death under hypoxic conditions (37). Taken together, both observations suggest that subtle differences may exist which are worth further study, especially in individual patients who greatly differ from the quite homogeneous cancer models used here.

In contrast to the lack of considerable differences in dysregulation of most KRAS signalling pathway parts between taxane-treated cell models with different KRAS mutation status, the baseline gene expression profile of KRAS wild-type cell line notably differed from both KRAS mutated cell lines. The KRAS signalling pathway stem, including the KRAS effector molecule and MAPK scaffold, was mostly downregulated while several upstream genes belonging to branches (RALGDS, RIN1, RAC1 and PIK3CG) were upregulated in the KRAS wild-type compared to both KRAS mutated lines in vitro. The ratio, however, between the total and phosphorylated protein forms of KRAS stem part in the KRAS wild-type model was not estimated, and this observation does not seem to represent a clinically meaningful result as previously no statistically significant differences in transcript levels of the KRAS signalling pathway have been found in PDAC tumours of patients after surgical treatment for an early stage of PDAC (12). Thus, the present study detected dysregulation of the gene expression among uniform cell culture in vitro models, which widely differ from the clinical reality of PDAC tumours consisting of a heterogeneous population of malignant cells.

The study has some limitations. First, in vitro experiments were performed with conventional taxane paclitaxel and data for SB-T-1216 are not available. Since minor differences in the exact effect of the taxanes on cell death have been described (Ehrlichova et al. 2009), we decided to test in particular the clinically relevant paclitaxel (on biologically distinct types of PDAC cell lines) and to validate in vivo the results of only a selected line using an experimental taxane with a higher cytotoxic effect. The cytotoxicity testing revealed, however, a similar efficacy of both compounds in all cell line models in vitro and a comparison of gene expression data from in vivo model treated with SB-T-1216 and in vitro model treated with paclitaxel also demonstrated a good agreement. Second, the results of in vitro experiments were not confirmed on the protein level due to the fact that the gene expression analysis has not indicated major changes between KRAS mutated and wild-type models and also the time and concentration effects of paclitaxel failed to indicate dramatic trends. Despite these facts, protein changes may not necessarily correlate with gene expression levels and thus, further studies should confirm or disprove data presented on the transcript level here.

In conclusion, this study demonstrated for the first time that the cell models often used for study of PDAC differ in basal transcriptional levels in accordance with the KRAS mutation status in vitro, but these changes do not seem to contribute to the mechanism of action of taxanes, namely paclitaxel. Thus, there are no differences in KRAS mutated and wild-type cells in the sensitivity to taxanes in vitro. Using in vitro and in vivo models, treatment with taxanes caused the downregulation of the KRAS signalling pathway, but no apparent targets for further pre-clinical testing were identified in the KRAS signalling pathway on the transcriptional level.

Funding

This work was supported by the Ministry of Health of the Czech Republic (16-28375A to B.M.-D.); the Czech Ministry of Education (LO1304 to B.M.-D. and LO1503 to P.S.); Palacky University (IGA_LF_2018_010 to D.F.); National Institutes of Health, USA (CA 103314 to I.O.) and Charles University (UNCE/MED/006 to P.S.).

Conflict of interest statement: None declared.

Supplementary Material

gez021_Suppl_Supplementary_Material
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