Introduction
Over the past three decades, incidence rates of esophageal adenocarcinoma (EAC) have been progressively increasing [
1]. This increase is up to six fold in Western countries and still rising, characterized by a striking rise in incidence of males. For patients with locoregional EAC disease the preferred treatment strategy is neoadjuvant chemoradiation therapy (nCRT) or perioperative chemotherapy followed by an esophagectomy [
2], but prognosis remains poor [
3]. Thus far, no targeted treatment options are available in the curative setting. Treatment strategies directed against signaling pathways that drive treatment resistance, could improve therapy outcomes.
EAC is characterized by a complex network of aberrant signal transduction pathways, making therapeutic targeting challenging [
4,
5]. In order to develop novel targeting strategies, these aberrant pathways must be identified. Up until now, methods to examine such pathways have relied on assessments of protein (over-)expression or activation, copy number variations, gene mutations, and full transcriptome through RNA-sequencing approaches [
6]. However, these modalities have limited value for implementation in clinical practice. The fresh frozen tissue required for many of these analyses is usually not available, and often the expression of a single protein is assessed, not fully capturing relevant tumor biology. Here, we address these issues by a novel previously described computational Bayesian approach to interpret mRNA expression levels of gene sets [
6‐
8]. Target gene mRNA expression levels are used to infer transcription complex activity of the corresponding signal transduction pathway and thereby the activity of the signal transduction pathway. The advantage of such analysis is that a more complete and therefore reliable read-out of the signal transduction pathway is obtained, compared to an mRNA measurement as a proxy for merely its corresponding protein activity [
6,
7]. Importantly, mRNA extracted from a small amount of formaldehyde fixed-paraffin embedded (FFPE) tissue, which is readily available in clinical practice, suffices for the analysis.
The aim of this study was to identify aberrant signaling pathways that drive therapy resistance in EAC. To reveal candidate signaling pathways as targets for targeted therapy, we investigated key signal transduction pathways in material available from daily clinical routine. Tissue specimens before and after nCRT, and for primary tumor and recurrent disease were assessed and compared to clinicopathological outcome data. Using patient-derived cell lines, candidate signaling pathways were targeted to study their potential therapeutic relevance.
Material and methods
Patient selection
Medical records of a national referral center for esophagogastric cancer, the Amsterdam UMC, location Academic Medical Center, were systematically searched for patients with histologically proven EAC, including gastric esophageal junction (GEJ), treated between June 2004 and May 2013. (i) Resectable disease: patients treated with curative intent by an esophagectomy as single treatment or by the CROSS regimen: nCRT with paclitaxel (50 mg/m
2 body-surface area), carboplatin (AUC 2 ml/min), 41.4 Gy radiotherapy in 23 fractions of 1.8 Gy, followed by resection. As part of a randomized phase II study [
9], panitumumab, an anti-EGFR monoclonal antibody, was added to the nCRT regimen. Sensitivity analysis showed no significant differences between nCRT only or nCRT + panitumumab, thus in following analysis groups were merged. Cases with available pre-treatment biopsy of the primary tumor site and the corresponding resection specimen were selected. (ii) Recurrent disease: patients with available resection specimen of the primary tumor site and a corresponding metachronous recurrence. Medical records were extracted by a trained physician using standardized data extraction concerning the location of primary tumor, TNM stage of pathological resections reports (pTNM), Mandard response score, received treatment and survival. Confirmation of adenocarcinoma histological subtype, response to therapy and non-cancerous healthy tissue were assessed by a trained pathologist.
RNA analysis
Using hematoxylin and eosin (H&E) stained slides of included biopsies and resection specimens, FFPE tumor blocks containing the highest tumor percentage were selected by a trained pathologist. Selected H&E slides were scanned using Philips Ultra-Fast Scanner (UFS; Philips, Eindhoven, the Netherlands). Tumor areas were marked by a trained pathologist using the Digital Pathology Images portal (Philips, Eindhoven, The Netherlands). A minimal area of 2 mm
2 was annotated. In case of diffuse tumor distribution, areas with a high tumor density were selected. Using a custom-built device, digital annotations of whole slide H&E scans were transferred to an adjacent H-stained slide and deparaffinized. Marked tumor areas were scraped off for RNA extraction with the RNeasy kit (Qiagen). qPCR data from extracted RNA were subjected to stringent quality checks (QC) prior to determining signaling pathway activity scores of the androgen receptor (AR), estrogen receptor (ER), Phosphatidylinositol 3 Kinase (PI3K)-Forkhead Box O (FOXO), Hedgehog (HH), Transforming growth factor receptor Beta (TGF-β) and Wingless-Integrated (WNT) pathways by applying the computational model described below [
6,
7,
10‐
12].
Measuring activity of signal transduction pathway activity
Measuring signal transduction pathway activity on Affymetrix U133 Plus2.0 data has been described extensively before. Pathway activity was inferred from target gene mRNA levels of six key oncogenic signaling pathways that play a role in tumor growth and metastasis [
6] using a Bayesian network, inferring the odds for pathway activity, as published earlier [
6,
7,
10,
11]. Affymetrix assays were converted to qPCR-based assays, developed and performed by Philips (Philips Molecular Pathway Dx, Eindhoven) [
13]. Samples that failed quality control (QC) were removed from analysis. PI3K pathway activity is inversely related to the measured FOXO transcription factor activity, on the premise that no cellular oxidative stress is present. Therefore, FOXO activity score was interpreted together with SOD2 target gene expression level to distinguish between oxidative stress- and growth control-induced FOXO activity, as described before [
7,
11].
Cell culture and treatment
Primary EAC cell lines EAC007B, EAC031M, EAC058M, EAC081R and EAC289B were established from patient EAC material as previously described [
14]. Primary cell lines EAC007B and EAC031M were cultured in Advanced DMEM/F12 (Gibco) supplemented with N2 (5 ml; Invitrogen), HEPES (5 mM; Life Technologies), D-glucose (0.15%; Sigma-Aldrich), β-mercaptoethanol (100 μM; Sigma-Aldrich), Insulin (10 μg/ml; Sigma-Aldrich), Heparin (2 μg/ml; Sigma-Aldrich) and 1:1000 Trace elements B and C (Fisher Scientific) [
15], EAC058M, EAC081R and EAC289B were cultured in DMEM (Gibco). Publicly available EAC cell lines Flo1 (RRID:CVCL_2045), OE19 (RRID:CVCL_1622) and OE33 (RRID:CVCL_1622; ATCC, Manassas, VA) were maintained in RPMI (Lonza). All cell lines have been authenticated using STR profiling within a year. All experiments were performed with mycoplasma-free cells. All medium during experiments contained 2% fetal bovine serum, L-glutamine (2 mM; Sigma-Aldrich), penicillin and streptomycin (500 µg/mL; Lonza). Carboplatin and paclitaxel were purchased from the Amsterdam UMC clinical pharmacy, as used for EAC patients in nCRT setting. The nCRT regimen was mimicked in vitro by challenging all cell lines 7 days with CRT, comprising carboplatin (20 μM) and paclitaxel (0.05 nM) combined with 1 Gy radiation daily as described earlier [
16]. On day 1 cells were plated, on day 2–5, cells received 1 Gy radiation per day and from day 2–7 cells were exposed to chemotherapy and PI3K inhibitors LY3023414, Alpelisib, Pictilisib or Idelalisib (Additional file
5: Table S2). Assays were performed on day 8. An Axiovert 200 M microscope (Zeiss) was used to obtain phase contrast images.
Western blot
Pre-treatment cells were lysed in RIPA buffer (Cell Signaling) containing phosphatase and protease inhibitor cocktail (Cell Signaling). Protein levels were determined by BCA (Pierce). Samples were heated for 5 min at 95 ºC loaded on 4–20% polyacrylamide precast gels (Bio-Rad) and transferred to PVDF membranes. Samples were blocked with 5% BSA (Lonza) in Tris buffered saline with 0.1% Tween-20 (TBS-T), and incubated overnight at 4 °C with primary antibodies (Additional file
3: Table S3). All were used at 1:1000. (HRP)-conjugated secondary were used at 1:5000 and incubated for 2 h at room temperature. Proteins were imaged using a FuijFilm LAS 4000 imager (Fuji), using ECL Western blotting substrate (Pierce). Western blot bands were quantified using Image J by dividing protein of interest per lane by the housekeeping protein.
Cell viability assay
Cell viability was determined using a Cell Titer-Blue Cell Viability Assay kit (G8081; Promega, Madison, WI). Cells were seeded into 96-well plates in triplicates. After cell adhesion overnight, cells were treated. After one week, cell viability was measured by adding 20 μL of Cell Titer-Blue reagent to each well followed by three hours incubation. Plates were read at 560/590 nm in a cytofluormeter (BioTek Instruments). Viability was calculated from values from CRT cells with or without PI3K inhibitors, minus baseline cell viability.
Imaging based proliferation assay
Proliferation was determined using IncuCyte™ live cell imaging system (Essen BioScience), quantitatively detecting live cells. Cells were imaged after one week of treatment.
Apoptosis assay
Apoptosis was similarly assessed using the IncuCyte system, by incubating cells in 0.33 mg/mL annexin V-FITC, administered simultaneously with drugs. Cells were imaged after one week of treatment. Apoptotic fraction was calculated by the ratio of FITC-positive cell area, divided by confluence (total cell area).
Gene expression database analysis
Gene expression of Broad Hallmark
PI3K_AKT_mTor_signaling gene set was correlated with the Broad Hallmark
Epithelial_Mesenchymal_transition gene set in two publicly available datasets: Esophageal Adenocarcinoma Fitzgerald (GSE96669)[
17] and Esophageal Carcinoma Tumor Cancer Genome Atlas (TCGA-ESCA;
https://gdc-portal.nci.nih.gov/projects/TCGA-ESCA) [
4]. Analysis was performed using the web‐based genomics platform R2 (R2: Genomics Analysis and Visualization Platform,
http://r2.amc.nl).
Statistical analyses
Pathway activity between normal and EAC tissue were calculated using the Mann–Whitney test to compare ranks. In case of paired samples—between matched pre-treatment biopsies and resection specimen or resection specimen and recurrence, the Wilcoxon matched-pairs signed ranked test was used. Correlation of pathway activities was assessed using Pearson’s correlations. Sensitivity analyses were performed for patients receiving panitumumab [
9]. Survival analyses were performed using Kaplan–Meier and multivariable Cox proportional hazard regression analysis, including clinically relevant clinicopathological variables. Statistical analyses were performed in R. A p-value of p < 0.05 was regarded statistically significant. In all in vitro experiments Spearman correlation tests were performed using GraphPad Prism 8. Error bars in bar graphs indicate the mean ± SD. A
p-value of p < 0.05 was considered statistically significant.
Discussion
Using clinically available FFPE material we were able to determine activity of key cancer driving pathways before and after nCRT using small amounts of EAC tissue. Persistent low FOXO transcriptional activity was associated with poor response to nCRT in EAC patient samples. This poor nCRT responder profile was also seen in recurrences of nCRT-pretreated patients. In addition, heterogeneity in high PI3K activity, inversely linked with FOXO, was seen in patient-derived cell lines, providing a valuable tool to experimentally target candidate signaling pathways, such as PI3K-FOXO. Our exploratory data demonstrate that PI3K inhibition can indeed sensitize nCRT-resistant cell lines.
As EAC is known to be a heterogeneous tumor, the full characteristics of the tumor might not be represented by the analysis of single tumor sites. This could be problematic, as large intratumoral heterogeneity might hamper patient selection for targeted therapy. In addition, not merely tumor cells but also stromal and immune cells influence EAC tumor biology [
15]. These environmental stimuli are only partially captured in our analyses. Moreover, a potential lack in our study is the absence of post-treatment healthy esophageal tissue, to compare with pre-treatment healthy tissue as a control for treatment effects of nCRT on FOXO or other transcriptional activities. Additionally, as merely one FFPE tissue slide was used, sometimes insufficient mRNA was extracted in good nCRT responders (post-nCRT Mandard 1 score). By using two or more FFPE slides, this issue could be circumvented. Nevertheless, we demonstrate that in a single tissue sample from a possibly heterogeneous and effectively treated tumor, clinically relevant sample characteristics can be determined.
Here we described that low FOXO transcriptional activity is associated with worse clinical outcome, sometimes combined with low TGF-β pathway activity. TGF-β signaling has a complex dual role in human cancer [
18,
33]. Via the canonical Smad pathway TGF-β signaling has tumor suppressive effects in early carcinomas. As tumors develop, these protective effects of TGF-β are often lost and TGF-β signaling switches to promote cancer progression, as we have shown before using flow cytometry analysis [
16]. Nevertheless, based on our mRNA based pathway activity analysis TGF-β signalling activity in EAC samples seems to be predominantly tumor suppressive. Given that the dual role of TGF-β has not been fully elucidated in EAC, to design a new treatment strategy, we focused on targeting the PI3K-FOXO pathway.
The phosphatidylinositol 3-kinase (PI3K) pathway is one of the main cellular growth factor signaling pathways frequently hyperactivated in cancer [
34]. Because PI3K pathway activity negatively regulates forkhead box-O (FOXO) transcription factor activity, FOXO target gene expression is inversely correlated with PI3K activity. Additionally, numerous studies have revealed that high PI3K and low FOXO activity is associated with a poor prognosis [
25,
35,
36], although little research has been done in EAC [
35,
36]. As our results show an association with poor response and metastatic behavior, in line with other cancer types, PI3K inhibition appears a promising candidate for therapeutic targeting in EAC patients [
10,
37].
To experimentally test novel therapeutic strategies as PI3K pathway inhibition, preclinical cancer models representative of patients’ tumor biology are essential. We found that patient-derived cell lines show heterogeneity in PI3K pathway activity, allowing their use as a tool to test predictive signals for response to PI3K pathway inhibition. In line with our patient data, both good and poor nCRT responder cell lines were identified with corresponding PI3K pathway activity on phosphorylated protein level. In the relatively small number of cell lines we could not find and association of nCRT on FOXO transcriptional activity level. However, as phosphorylation plays an essential role in activation of the comprehensive PI3K pathway, we were able to detect a relation on protein phosphorylation level. Although these experimental data are encouraging, caution must be taken drawing conclusions as additional experiments should be performed in 3D models.
Nonetheless, we identified a PI3K inhibitor that could give a beneficial additional effect to nCRT; LY3023414, a novel PI3K/mTOR inhibitor, with potent activity in EAC in rat models [
38]. Interestingly, LY3023414 demonstrated a manageable safety profile in a phase 2 clinical trial [
39], as improved clinical responses of all four used inhibitors [
26‐
29,
39,
40]. Hence, we believe it is of value to investigate the use of PI3K pathway inhibition in patients with EAC, either combined with nCRT, or as adjuvant therapy.
To conclude, we were able to determine the activity of key cancer driving pathways before and after nCRT in clinically attainable amounts of EAC tissue. The poor nCRT responder profile was detected in tissue of the primary site, recurrences of nCRT-pretreated patients and patient derived cell lines. Hence, the pathway activity model described here may be used to identify patients irresponsive to nCRT and select for appropriate targeted therapies.
Novelty and impact
By using a novel Bayesian inference method to measure signaling pathway activity on clinically available material, we identified an association of low FOXO transcriptional activity with poor response to nCRT. Targeting this pathway sensitized cells for nCRT, underlining its feasibility to select appropriate targeted therapies.
Publisher's Note
Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.