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YAP1 is an independent prognostic marker in pancreatic cancer and associated with extracellular matrix remodeling

YAP1 is an independent prognostic marker in pancreatic cancer and associated with extracellular... Background: Pancreatic cancer is a major cause of cancer‑related mortality. The identification of effective biomarkers is essential in order to improve management of the disease. Yes‑associated protein 1 (YAP1) is a downstream effector of the Hippo pathway, a signal transduction system implicated in tissue repair and regeneration, as well as tumorigen‑ esis. Here we evaluate the biomarker potential of YAP1 in pancreatic cancer tissue. Methods: YAP1 was selected as a possible biomarker for pancreatic cancer from global protein sequencing of fresh frozen pancreatic cancer tissue samples and normal pancreas controls. The prognostic utility of YAP1 was evaluated using mRNA expression data from 176 pancreatic cancer patients in The Cancer Genome Atlas ( TCGA), as well as protein expression data from immunohistochemistry analysis of a local tissue microarray ( TMA) cohort comprising 140 pancreatic cancer patients. Ingenuity Pathway Analysis was applied to outline the interaction network for YAP1 in connection to the pancreatic tumor microenvironment. The expression of YAP1 target gene products was evaluated after treatment of the pancreatic cancer cell line Panc‑1 with three substances interrupting YAP–TEAD interaction, including Super‑ TDU, Verteporfin and CA3. Results: Mass spectrometry based proteomics showed that YAP1 is the top upregulated protein in pancreatic cancer tissue when compared to normal controls (log2 fold change 6.4; p = 5E−06). Prognostic analysis of YAP1 demon‑ strated a significant correlation between mRNA expression level data and reduced overall survival (p = 0.001). In addi‑ tion, TMA and immunohistochemistry analysis suggested that YAP1 protein expression is an independent predictor of poor overall survival [hazard ratio (HR) 1.870, 95% confidence interval (CI) 1.224–2.855, p = 0.004], as well as reduced disease‑free survival (HR 1.950, 95% CI 1.299–2.927, p = 0.001). Bioinformatic analyses coupled with in vitro assays indi‑ cated that YAP1 is involved in the transcriptional control of target genes, associated with extracellular matrix remod‑ eling, which could be modified by selected substances disrupting the YAP1‑ TEAD interaction. Conclusions: Our findings indicate that YAP1 is an important prognostic biomarker for pancreatic cancer and may play a regulatory role in the remodeling of the extracellular matrix. Keywords: Pancreatic cancer, YAP1, Transcriptomics, Proteomics, Prognosis, Extracellular matrix remodeling, Cancer Background Pancreatic cancer is one of the most aggressive malig- nancies with a dismal 5-year survival rate of 9% [1]. It *Correspondence: daniel.ansari@med.lu.se has surpassed breast cancer to become the third leading Department of Surgery, Clinical Sciences Lund, Lund University and Skåne University Hospital, 221 85 Lund, Sweden cause of cancer-related death and is estimated to rise to Full list of author information is available at the end of the article © The Author(s) 2020. This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article’s Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creat iveco mmons .org/licen ses/by/4.0/. The Creative Commons Public Domain Dedication waiver (http://creat iveco mmons .org/publi cdoma in/ zero/1.0/) applies to the data made available in this article, unless otherwise stated in a credit line to the data. Zhou et al. J Transl Med (2020) 18:77 Page 2 of 10 the second leading cause by 2030 [2]. Multiple factors, Research in Sweden and Lund University Diabetes center such as late diagnosis and resistance to conventional (LUDC). therapies, contribute to the overall poor prognosis. The immunohistochemical (IHC) target verification The ability to identify subgroups of patients that may was performed using tissue microarrays (TMA) from benefit from specific clinical management is considered archival formalin-fixed paraffin-embedded (FFPE) resec - central to modern precision oncology. For that pur- tion specimens from 140 patients with pancreatic ductal pose, large-scale genomic studies have been performed adenocarcinoma who underwent curative intent pancre- to determine molecular subtypes of pancreatic cancer atic surgery from 1995 to 2017 at Skåne University Hos- requiring individualized treatments [3–6]. Such studies pital, Lund and Malmö, Sweden. have massively increased our understanding of pancre- All samples were histopathologically verified and atic cancer at the molecular level. selected by a specialized surgical pathologist prior to Proteomics is a valuable complement to genetic stud- analysis. Ethical permission for the study was granted by ies. Mass spectrometry (MS)-based proteomics profil - the Ethical Committee at Lund University (Ref 2010/684, ing of patient-derived samples has been suggested as an 2012/661, 2015/266, 2017/320). The REMARK guidelines effective approach for the discovery of biomarkers and were followed where applicable [16]. detection of suitable therapeutic targets in many cancers [7–10]. MS‑based proteomics Yes-associated protein 1 (YAP1) is a downstream effec - Sample processing and LC–MS/MS analysis were per- tor of the Hippo signaling pathway, which is involved in formed as reported previously [10]. Briefly, proteins tissue repair and regeneration, as well as tumorigenesis. extracted from fresh frozen pancreas specimens were Activation of the Hippo pathway leads to inactivation of reduced, alkylated and digested into peptides using Lys-C YAP1 by cytoplasmic retention or proteolytic degrada- and trypsin. The peptides were analyzed using a high- tion [11, 12]. YAP1 in its active form, on the other hand, performance liquid chromatography system, EASY-nLC functions as a transcriptional co-activator predominantly 1000 connected to Q Exactive quadrupole-Orbitrap mass mediated by an interaction with TEAD transcription spectrometer equipped with a nanospray ion source factors [13]. Active YAP1 is also recognized as a potent (Thermo-Fisher Scientific, Bremen, Germany). To iden - oncogene closely linked to the progression of several can- tify the detected proteins, the acquired MS/MS data were cer types [14, 15]. However, the role of the YAP1-TEAD managed using Proteome Discoverer software, version interaction in regulating the expression of target genes in 1.4 (Thermo Fisher). pancreatic cancer has not been completely explored. In a previous study [10], we identified YAP1 as a differ - mRNA expression data entially expressed protein between pancreatic cancer and Publicly available transcriptomics data were retrieved normal controls using MS-based proteomics profiling. from 176 pancreatic cancer patients from The Cancer In the present study, we investigate the prognostic util- Genome Atlas (TCGA) [17–19]. RNA-seq data were ana- ity and the biological significance of YAP1 in pancreatic lyzed as the number of Fragments Per Kilobase of exon cancer using large and clinically well-annotated cohorts, per Million reads (FPKM). complemented by bioinformatics and in vitro experimen- tal analyses. Tissue microarray The TMA was constructed from FFPE pancreatic tumors by a trained biomedical technician using an automated tissue array device (Minicore 3, Alphelys, Plaisir, Materials and methods France). A set of 4 cores with a diameter of 2  mm were Patient samples extracted from each specimen and fixed into a new paraf - For the MS-based proteomics, fresh frozen pancreatic fin block. The completed blocks were then sectioned into cancer tissues (n = 10) were collected from patients with 3 µm thick sections and mounted on glass slides. pancreatic ductal adenocarcinoma undergoing pancrea- ticoduodenectomy between July 2013 and April 2015 at Immunohistochemistry the Department of Surgery, Skåne University Hospital, IHC analysis was performed as described previously Lund, Sweden. Written informed consent was obtained [20]. Briefly, deparaffinization, rehydration and antigen- from the patients included in the study. Age and gen- retrieval were performed using the automated PT Link der-matched, fresh frozen, normal pancreatic biopsies system (Dako, Agilent Technologies, Glostrup, Den- (n = 10) were assessed from organ donors and obtained mark). TMA-slides were then incubated with monoclo- from the national consortium Excellence of Diabetes nal rabbit anti-human primary antibody against YAP1 Zhou  et al. J Transl Med (2020) 18:77 Page 3 of 10 (dilution 1:200; Cell Signaling) followed by biotinylated Bioapplication software was thereafter used for image goat anti-rabbit secondary antibody (dilution 1:200; processing. Vector Laboratories, Burlingame, CA). Avidin–biotin– In each well, a cell population consisting of two thou- peroxidase complex (Vectastain Elite ABC-HRP Kit, Vec- sand cells was analysed using multiparameter fluores - tor Laboratories, Burlingame, CA) was used for signal cent microscopic imaging system designed for high amplification. The color was developed using chromo - content screening. The processed data obtained from gen diaminobenzidine (DAB) (Vector Laboratories). The automatically acquired images were quantified as fluores - nuclei were colored with hematoxylin. The immunostain - cence intensity for the selected channel (Alexa 488). The ing was evaluated by three independent pathologists, accessed images were visualized using automated fluo - blinded to clinical information. H-score was applied as rescence microscopy. a semiquantitative approach [21, 22]. The intensity of YAP1 staining was scored as [0] (negative), [1+] (weak), [2+] (moderate), or [3+] (strong) and the percentage of YAP1 target gene expression cells at each staining intensity level was recorded. The To evaluate the expression of selected YAP1 target genes, H-scores were calculated by following formula: the cells were seeded in 6-well plates with a concentra- tion of thirty thousand cells per well. After one cell cycle, H-score = 0 × (% cells 0 ) + 1 × (% cells 1 ) [ ] [ ] the cells were incubated with a maximal tolerable dose of + 2 × (% cells 2 ) + 3 × (% cells 3 ). [ ] [ ] three substances interrupting YAP–TEAD interaction; Super-TDU (500  nM), Verteporfin (100  nM) and CA3 (100 nM) or complete medium. After 48 h, the cell lysates Bioinformatics and conditioned medium from respective well and plate Ingenuity Pathway Analysis software (IPA, Qiagen, Inc. were collected. All experiments were executed in tripli- Redwood City, CA, USA) was used for bioinformatic cates. Expression levels of YAP1 targets genes, including analysis of networks involving the biological relation- amphiregulin (AREG), connective tissue growth factor ship between YAP1 and pancreatic cancer. A network (CTGF), cysteine-rich angiogenic inducer 61 (CYR61), involving all direct interactors of these proteins was built fibroblast growth factor 1 (FGF1) and mesothelin and analyzed for pathway enrichment and functional (MSLN), were selected from the Ingenuity Pathway Anal- annotations. ysis and measured in each sample using enzyme-linked immunosorbent  assay (ELISA). 100  µg protein from respective sample was analyzed in each assay according Cell culture to the manufacturer’s instructions. AREG, CTGF, CYR61, The patient derived pancreatic cancer cell line Panc-1 FGF1 were purchased from Nordic Biosite AB, Täby, SE (ATCC-LGC Standards, Manassas, VA, USA) was used and MSLN from Biolegend, San Diego, CA, USA. for the in  vitro experiments. The cells were maintained in DMEM supplemented with 10% fetal bovine serum, 100 U/ml penicillin and 100  μg/ml streptomycin and Statistical analysis kept in a humified atmosphere, in 5% CO at 37 °C. Prior The correlation between YAP1 expression levels and experiment, the cells were observed using phase contrast clinicopathological parameters was estimated using the microscope to ensure the condition of the cells including Mann–Whitney U test for continuous variables and morphological characteristics and vitality. 2 Fisher’s exact test or χ for categorical variables. The Kaplan–Meier method was used to model the cumulative probability of overall survival (OS) and disease-free sur- Immunofluorescence based Cellomics vival (DFS) and statistical differences were assessed using To assert the YAP1 expression profile, the cells were the log-rank test. Univariable and multivariable survival seeded in 6 well plates with the density of fifty thousand analysis were also performed using Cox proportional cells per well. After 48 h, the cells were fixed with 4% par - hazards regression modeling. aformaldehyde (Histolab, Västra Frölunda, Sweden) and One-way ANOVA parametric test was applied to com- stained with primary rabbit anti-human YAP1 (dilution pare the concentrations of secreted YAP target genes 1: 250, Cell Signaling) followed by Alexa Fluor 488 con- measured in condition medium obtained from Panc-1 jugated donkey-anti-rabbit secondary antibody (dilution cells subjected to three substances interrupting YAP1 1:200, Invitrogen, USA). The nucleus was marked using transcriptional activity or untreated cells. DAPI (NucBlue , Molecular probes, Life technologies, Statistical evaluation was conducted with SPSS version USA). Cellomics ArrayScan platform VTI HCS (Ther - 23.0 (SPSS Inc., Chicago, IL, USA) and GraphPad Prism moScientific, Rockford, IL, USA) reader connected to Zhou et al. J Transl Med (2020) 18:77 Page 4 of 10 Fig. 1 Selection of the YAP1 protein for validation. a Label‑free quantitative MS spectra of YAP1 (based on peptide SQLPTLEQDGGTQNPVSSPGMSQELR). b Box‑plot showing relative expression levels of YAP1 in pancreatic cancer (PC) and healthy controls (HC) Table 1 Characteristics of the TCGA cohort (n = 176) Variable N = 176 Median age (range), years 65 (35–88) Female gender 50 (45.5%) AJCC‑stage I 21 (11.9%) II 145 (82.4%) III 3 (1.7%) IV 4 (2.3%) Unknown 3 (1.7%) Median FPKM (range) 19.0 (0.5‑46.6) FPKM fragments per kilobase of exon per million reads Fig. 2 Kaplan–Meier survival curves stratified by YAP1 mRNA v.8.0.1 (La Jolla, CA, USA). A p-value < 0.05 was consid- expression levels in the TCGA cohort. Patients were categorized ered statistically significant. based on the median number of fragments per kilobase of exon per million reads (FPKM) into low expression (≤ 19) and high expression groups (> 19) Results YAP1 is the top upregulated protein in pancreatic cancer Fresh frozen biopsies from pancreatic tumors (n = 10) and healthy pancreatic tissue (n = 10), were analyzed TCGA (Table  1). The median FPKM value was 19.0, using label-free quantitative proteomics to discover dif- ranging from 0.5 to 46.6. The median FPKM value was ferentially expressed proteins. In total, 4138 proteins used to divide the cohort into a low (FPKM ≤ 19) and a were identified, and 2950 proteins were quantified based high expression group (FPKM > 19). The Kaplan–Meier on one or more unique peptides. 165 candidates were plots revealed that high YAP1 mRNA expression was subsequently determined as potential biomarkers for significantly correlated with poorer OS when compared pancreatic cancer, as previously reported [10]. Character- with low mRNA YAP1 expression, as illustrated in Fig. 2 ized by six unique peptides, YAP1 was annotated as the (median survival 17  months vs. 23  months, respectively, top upregulated protein in pancreatic tumor specimens p = 0.001). (log2 fold change 6.4; p = 5E−06) (Fig. 1a, b). mRNA expression levels of YAP1 as a prognostic marker YAP1 protein expression levels and prognosis To assess the prognostic significance of YAP1, we ana - The protein expression levels of YAP1 were analyzed lyzed mRNA expression level data and patient survival using immunohistochemistry staining on TMA sections based on 176 pancreatic cancer patients included in constructed from 140 pancreatic tumors. The antibody Zhou  et al. J Transl Med (2020) 18:77 Page 5 of 10 staining specific for YAP1 was detected in the nucleus or analysis, high YAP1 protein expression was identified in the nucleus and cytoplasm of tumor cells. The median as an independent risk factor for poor OS (hazard ratio H-score was 170 (range, 59–289). Based on the median (HR) 1.870, 95% confidence interval (CI) 1.224–2.855, H-score (170), a low (H-score ≤ 170) and a high expres- p = 0.004). Moreover, univariable Cox regression analysis sion group (H-score > 170) were created (Fig. 3a). No sig- of DFS determined histopathological grade (p = 0.028), nificant differences in clinicopathological features were resection margin ≥ R1 (p = 0.028), and high expression identified between high and low YAP1 expression groups of YAP1 (p = 0.006) as factors associated with decreased (Table 2). DFS. Multivariable Cox regression analysis confirmed the Kaplan–Meier analysis revealed that high YAP1 pro- results, indicating that high YAP1 protein expression is tein expression was significantly correlated with shorter an independent risk factor for reduced DFS (HR 1.950, OS when compared with low YAP1 protein expression 95% CI 1.299–2.927, p = 0.001) (Table 3). (median survival, 17.9 vs. 34.3  months, respectively, We thus interpret that YAP1 may function as a marker p = 0.001, log-rank test; Fig.  3b). Furthermore, patients for poor prognosis and disease relapse in pancreatic can- exhibiting high YAP1 protein expression had significantly cer patients. reduced DFS when compared to the low YAP1 protein expression group (median DFS, 10.7 vs. 17.5  months, YAP1 is connected to mediators promoting remodeling respectively, p = 0.005, log-rank test; Fig. 3c). of the extracellular matrix The univariable Cox regression analysis of OS identi - Subsequently, we explored the biological background of fied smoking history (p = 0.04), symptoms at diagno- the obtained results with the aim to identify the most sis (p = 0.05), histopathological grade (p = 0.03), and significant networks and relationships associated with high expression of YAP1 (p = 0.001) as factors associ- YAP1 expression in pancreatic cancer. Bioinformatic ated with shorter OS. In multivariable Cox regression analysis using the IPA software revealed that YAP1 is Fig. 3 Immunohistochemical analysis of YAP1 protein expression in the tissue microarray cohort. a Representative images of YAP1 immunostaining in low and high expression groups using the median H‑score (170) as cut ‑ off. b Kaplan–Meier survival curves for overall survival stratified by YAP1 protein expression. c Kaplan–Meier survival curves for disease‑free survival stratified by YAP1 protein expression Zhou et al. J Transl Med (2020) 18:77 Page 6 of 10 Table 2 Characteristics of the TMA cohort (n = 140) Variable N All patients Low YAP1 protein High YAP1 protein p (n = 140) expression expression (n = 70) (n = 70) Age > 65 years 140 93 (66.4) 48 (68.6) 45 (64.3) 0.721 Female gender 140 66 (47.1) 35 (50) 31 (44.3) 0.612 BMI > 25 kg/m 132 57 (43.2) 32 (47.1) 25 (39.1) 0.383 Smoking history 139 67 (48.2) 28 (40.6) 39 (55.7) 0.09 Diabetes mellitus 139 33 (23.7) 19 (27.1) 14 (20.3) 0.426 Symptoms at diagnosis 136 131 (96.3) 68 (100) 63 (92.6) 0.058 Tumor location (head) 140 117 (83.6) 62 (88.6) 55 (78.6) 0.17 Tumor size > 2 cm 139 117 (84.2) 60 (87) 57 (81.4) 0.487 T‑stage ≥ T2 139 121 (87.1) 60 (87) 61 (87.1) 1 N‑stage ≥ N1 138 104 (75.4) 53 (76.8) 51 (73.9) 0.844 AJCC‑stage ≥ II 138 112 (81.2) 56 (81.2) 56 (81.2) 1 Histological grade ≥ 3 138 83 (60.1) 38 (55.9) 45 (64.3) 0.385 Positive resection margin 139 55 (39.6) 28 (40.6) 27 (38.6) 0.863 Adjuvant chemotherapy 135 113 (83.7) 60 (87) 53 (80.3) 0.355 Recurrence of disease 127 103 (81.1) 51 (79.7) 52 (82.5) 0.821 N, number of non-missing values. Qualitative data are expressed as n (%) AJCC American Joint Committee on Cancer, BMI body mass index, N-stage nodal stage, T-stage tumor stage Table 3 Univariable and multivariable Cox regression analysis in the TMA cohort (n = 140) Variable OS DFS Univariable HR p Multivariate HR p Univariable HR p Multivariable HR p (95% CI) (95% CI) (95% CI) (95% CI) Age (> 65) 0.994 (0.658–1.501) 0.977 0.760 (0.506–1.144) 0.189 Female gender 0.825 (0.557–1.221) 0.336 0.675 (0.453–1.005) 0.053 BMI (> 25 kg/m ) 1.250 (0.832–1.876) 0.283 1.372 (0.913–2.061) 0.128 Smoking history 1.510 (1.019–2.239) 0.04* 1.319 (0.868–2.003) 0.195 1.268 (0.852–1.887) 0.242 Diabetes 0.782 (0.479–1.277) 0.326 0.927 (0.567–1.515) 0.762 Symptoms at diag‑ 0.363 (0.132–1.000) 0.05* 0.548 (0.193–1.559) 0.260 0.620 (0.227–1.693) 0.351 nosis Tumor location (head) 0.658 (0.390–1.112) 0.118 1.143 (0.625–2.092) 0.664 Tumor size (> 2 cm) 1.090 (0.653–1.819) 0.741 1.215 (0.710–2.079) 0.478 T‑stage (≥ T2) 1.152 (0.672–1.973) 0.607 1.429 (0.795–2.571) 0.233 N‑stage (≥ N1) 1.474 (0.924–2.352) 0.104 1.316 (0.829–2.088) 0.244 AJCC‑stage (≥ II) 1.426 (0.855–2.379) 0.174 1.345 (0.814–2.222) 0.248 Histological grade 1.580 (1.045–2.390) 0.03* 1.728 (1.123–2.657) 0.013* 1.592 (1.050–2.413) 0.028* 1.628 (1.072–2.472) 0.022* (≥ 3) Resection margin 1.388 (0.926–2.080) 0.112 1.585 (1.050–2.394) 0.028* 1.716 (1.127–2.613) 0.012* (≥ R1) Adjuvant chemo‑ 0.712 (0.435–1.166) 0.177 1.632 (0.887–3.002) 0.115 therapy YAP1 protein expres‑ 1.917 (1.288–2.854) 0.001* 1.870 (1.224–2.855) 0.004* 1.752 (1.178–2.608) 0.006* 1.950 (1.299–2.927) 0.001* sion (High) Variables with p ≤ 0.05 were marked with asterisk (*), variables with p ≤ 0.05 in univariable analysis were included in multivariable analysis AJCC American Joint Committee on Cancer, BMI body mass index, CI confidence interval, DFS disease free survival, HR hazard ratio, N-stage nodal stage, OS overall survival, T-stage tumor stage Zhou  et al. J Transl Med (2020) 18:77 Page 7 of 10 positively stained cells showed a strong fluoresce inten - sity located in the nucleus (Fig. 5a). YAP1 participates in the transcription of target genes involved in profibrotic tumor microenvironment Next, we investigated co-transcriptional activity of YAP1 in synthesis of secreted proteins associated with remod- eling of the tumor microenvironment in pancreatic cancer. First, Panc-1 cells were cultured under standard conditions to assess the expression levels of proteins ascertained by the IPA analysis. All investigated proteins, AREG, CTGF, CYR61, FGF1, and MSLN were considered as low abundant and detected in low concentrations (pg/ ml) in lysates of Panc-1 cells cultured under standard conditions. As presented in Fig. 5b, the expression levels corresponded to at a maximum 0.2‰ of the total cellular protein amount. Next, the collected conditioned medium from the Fig. 4 Ingenuity Pathway Analysis showing the plasma membrane Panc-1 cells was analyzed for the presence of selected and extracellular proteins directly related to YAP1. The relation proteins. AREG, CTGF, CYR61, and MSLN were identi- to proteins involved in mechanotransduction include the cell fied and the secretion pattern was further investigated. membrane protein PATJ (crumbs cell polarity complex component), which is directly related to YAP1 and is also interacting with PIEZO1, Panc-1 cells were subjected to substances inhibiting the Piezo type mechanosensitive ion channel component 1. YAP1 YAP1 transcriptional activity and the concentrations of is also an indirect regulator of both PIEZO1 and PIEZO2. Further, the the determined secreted proteins were measured. Levels cytokine endothelin 1 (EDN1) is directly related to YAP1 and is also a of secreted AREG, CTGF, CYR61, and MSLN were sig- regulator of the degenerin/epithelial sodium channels (DEG/ENaC, nificantly lower (p = 0.0001) or undetectable in condi- here marked as SCNN1A, SCNN1B, SCNN1G, SCNN1D). Tight junction signaling proteins related to YAP1 include CTNNA1, MPDZMPP5, tioned medium after the treatment (Fig. 5c). Based on the OCLN, PATJ, TJP2. Epithelial adherens junction signaling proteins obtained results, we suggest that YAP1 is involved in the related to YAP1 include CDH1, CTNNA1, CTNNA2, EGFR, FGF1, PARD3, transcription of genes associated with remodeling of the ZYX. Examples of secreted proteins involved in creating a pro‑fibrotic pancreatic tumor microenvironment. microenvironment include AREG, CTGF, CYR61, FGF1, and MSLN and these YAP1 target genes are highlighted and were chosen for further in vitro confirmation Discussion In this transcriptome- and proteome-based study, we identified YAP1 as an indicator of poor OS and DFS in directly related to proteins involved in mechanotrans- patients with pancreatic cancer. duction, such as PATJ and PIEZO1, and the cytokine The American Joint Committee on Cancer (AJCC) EDN1 (Fig. 4). Tight junction signalling proteins related tumor-node-metastasis (TNM) classification system is to YAP1 include CTNNA1, MPDZMPP5, OCLN, PATJ, currently the gold standard for pancreatic cancer prog- and TJP2, while epithelial adherens junction signaling nostication [23]. However, the AJCC TNM system is proteins related to YAP1 include CDH1, CTNNA1, only concerned with the anatomical extent of the disease CTNNA2, EGFR, FGF1, PARD3, and ZYX. Examples though patients within the same stage may exhibit dif- of secreted proteins involved in creating a pro-fibrotic ferent outcomes [24]. Such evaluation may lead to either microenvironment include AREG, CTGF, CYR61, over- or undertreatment. Improved staging systems, FGF1, and MSLN and these YAP1 target genes were considering molecular factors  are necessary in order to chosen for further in vitro confirmation. enhance individual prognostication and utilization of precision therapies. The prognostic significance of YAP1 protein expression YAP1 protein expression in a patient derived cell line has only been evaluated in one previous small study by We performed immunofluorescence based Cellomics Allende et al. [25]. However, YAP1 protein expression did to evaluate the protein expression profile of YAP1 in not reach statistical significance in their Kaplan–Meier Panc-1 cells. In accordance with the TMA/IHC patient analysis, likely due to the small cohort size (64 patients). data, a positive YAP1 staining was detected in both Only when conducting subgroup analyses, stratifying nucleus and cytoplasm of Panc-1 cells. The majority of Zhou et al. J Transl Med (2020) 18:77 Page 8 of 10 ac Fig. 5 In vitro analysis of YAP1 and selected target genes in Panc‑1 cells. a YAP1 protein expression in Panc‑1 cells. The image represents an immunofluorescence staining of endogenous YAP1 in Panc‑1 cells, plated in 6 well plates and cultivated for 48 h under standard conditions. The arrows indicate an exemplification of YAP1 nuclear accumulation. b Concentrations of YAP1 target genes in lysates obtained from Panc‑1 cells cultivated under standard conditions. C) Concentrations of YAP1 target genes in conditioned medium obtained from Panc‑1 cells that were subjected to maximal tolerable doses (MTD) of substances blocking the YAP1/TEAD interaction survival into groups of patients surviving more than or signaling pathways involved in the tumor-stroma interac- less than 30 months, it was shown that patients with high tions [27–31]. YAP1 expression had worse survival. Therefore, to clarify Pancreatic cancer progression is generally associated the prognostic role of YAP1 protein expression in pan- with a dense fibrotic stroma characterized by an exten - creatic cancer, additional studies based on larger cohorts sive deposition of extracellular matrix components sur- are needed. The TMA/immunohistochemistry analysis rounding the cancer cells [32, 33]. The desmoplastic based on 140 patients in our study revealed that overex- extracellular matrix, mainly produced by activated cancer pression of YAP1 is an independent factor for unfavora- associated fibroblasts, accounts for up to 80% of entire ble outcome and disease recurrence. These findings are tumor mass [33]. The fibrotic environment is known to in agreement with the public mRNA dataset from the undergo an extensive remodeling connected to the stiff - TCGA, which illustrate that high expression of YAP1 ening of tumor tissue. Such stromal reshaping presum- significantly correlates with poor survival in pancreatic ably modifies the crosstalk between residual cells within cancer patients. The agreement between the transcrip - the tumor and directs the tumor progression towards an tome- and proteome-based survival analyses in the pre- aggressive phenotype [33–35]. The increased stiffness sent study strengthens the clinical significance of YAP1 of matricellular tumor microenvironment also activates as a prognostic variable. However, it is important to note YAP1 to further modulate the behavior of cancer cells on that knowledge about mRNA abundances can only par- the transcriptional level [36, 37]. tially predict protein abundances, with a large fraction of YAP1 itself, however, lacks DNA-binding activity and the variance also being explained by other factors such as requires an interaction with DNA-binding transcrip- post-transcriptional and translational regulation, as well tion factors such as TEAD to activate target genes [38]. as protein degradation [26]. AREG, CTGF and CYR61 account for the most acknowl- To understand the biological role of YAP1 in pancre- edged target genes for YAP1/TEAD [39–41]. The YAP1/ atic cancer, we performed bioinformatic analyses of pro- TEAD interactions are also reported to regulate the tein networks. The results revealed that YAP1 is directly expression of FGF1 and MSLN [42–44]. connected to secreted AREG, CTGF, CYR61, FGF1 We hypothesized that the secreted YAP1/TEAD tar- and MSLN that are involved in fibrosis and other key get gene products contribute to the enhanced fibrotic Zhou  et al. J Transl Med (2020) 18:77 Page 9 of 10 Hain Foundation for Medical Research, the Clas Groschinsky Foundation, the reaction and intra-tumoral stiffening which consecutively Gunnar Nilsson Foundation, the Gyllenstiernska Krapperup Foundation, the promote YAP1 transcriptional activity. Such paracrine Bengt Ihre Foundation, the Emil and Wera Cornell Foundation, the Crafoord loop would further affect the tumor microenvironment Foundation, Governmental Funding of Clinical Research within the National Health Service (ALF) and Sweden´s Innovation Agency ( Vinnova). and maintain the aggressive course of the disease. Using the patient derived pancreatic cancer cell line Availability of data and materials Panc-1, we evaluated the effect of substances designed The datasets generated and/or analyzed during the current study are available from the corresponding author on reasonable request. to inhibit the YAP1/TEAD mediated gene transcription. We showed that the disruption of YAP1/TEAD complex Ethics approval and consent to participate significantly reduced the presence of the selected YAP1/ This study was performed in compliance with the Helsinki Declaration on ethi‑ cal principles for handling human tissue specimens, with all EU and national TEAD target gene products in the conditioned medium. regulations and requirements. Written informed consent was obtained from Suppression of YAP1 oncogenic activity with a subse- participants. Ethical permission for the study was granted by the Ethics Com‑ quent modification of the tumor microenvironment mittee at Lund University (Ref 2010/684, 2012/661, 2015/266, 2017/320). may thus be an advantageous approach to control tumor Consent for publication growth and improve prognosis. Although the clinical uti- Consent for publication was obtained from included participants. lization for such treatment remains to be determined, Competing interests YAP1 as a biomarker may aid in the individual prognos- The authors declare that they have no competing interests. tication of patients diagnosed with pancreatic cancer and the selection of precision therapy. Author details The Eye Hospital, School of Ophthalmology and Optometry, Wenzhou Medical University, Wenzhou, Zhejiang, China. Department of Surgery, Clinical Sciences Lund, Lund University and Skåne University Hospital, 221 Conclusions 85 Lund, Sweden. Clinical Protein Science and Imaging, Biomedical Centre, We demonstrate that YAP1 is an independent prognostic Department of Biomedical Engineering, Lund University, Lund, Sweden. marker associated with recurrence and unfavorable sur- Department of Surgery, The Second Affiliated Hospital and Yuying Children’s Hospital of Wenzhou Medical University, Wenzhou, Zhejiang, China. Depart‑ vival in pancreatic cancer. We also show that inhibition of ment of Pathology, Skåne University Hospital, Lund, Sweden. Department YAP1/TEAD interaction interferes with the expression of of Pathology, The First Affiliated Hospital of Nanchang University, Nanchang, AREG, CTGF, CYR61, and MSLN suggesting that YAP1 China. Department of Experimental Design and Bioinformatics, Warsaw University of Life Sciences, Warsaw, Poland. Department of Translational transcriptional activity may affect the development and Medicine, Lund University, Malmö, Sweden. persistence of a fibrotic tumor microenvironment. YAP1 is thus considered as a clinically and biologically relevant Received: 10 September 2019 Accepted: 1 February 2020 biomarker derived from pancreatic cancer tissue. Abbreviations References AJCC: American Joint Committee on Cancer; AREG: Amphiregulin; BMI: Body 1. Siegel RL, Miller KD, Jemal A. Cancer statistics, 2019. CA Cancer J Clin. mass index; CI: Confidence interval; CTGF: Connective tissue growth factor; 2019;69:7–34. CYR61: Cysteine‑rich angiogenic inducer 61; DFS: Disease ‑free survival; 2. Rahib L, Smith BD, Aizenberg R, Rosenzweig AB, Fleshman JM, Matrisian ELISA: Enzyme‑linked immunosorbent assay; FFPE: Formalin‑fixed paraffin‑ LM. Projecting cancer incidence and deaths to 2030: the unexpected embedded; FGF1: Fibroblast growth factor 1; FPKM: Fragments per kilobase burden of thyroid, liver, and pancreas cancers in the United States. Cancer of exon per million reads; HR: Hazard ratio; IHC: Immunohistochemistry; IPA: Res. 2014;74:2913–21. Ingenuity Pathway Analysis; MS: Mass spectrometry; MSLN: Mesothelin; OS: 3. Jones S, Zhang X, Parsons DW, Lin JC, Leary RJ, Angenendt P, Mankoo Overall survival; TCGA : The Cancer Genome Atlas; TMA: Tissue microarray; TNM: P, Carter H, Kamiyama H, Jimeno A, et al. Core signaling pathways in Tumor‑node ‑metastasis; YAP1: Yes‑associated protein 1. human pancreatic cancers revealed by global genomic analyses. Science. 2008;321:1801–6. Acknowledgements 4. Collisson EA, Sadanandam A, Olson P, Gibb WJ, Truitt M, Gu S, Cooc The mRNA results published here are based upon data generated by the TCGA J, Weinkle J, Kim GE, Jakkula L, et al. Subtypes of pancreatic ductal Research Network (https ://www.cance r.gov/tcga) and the Human Protein adenocarcinoma and their differing responses to therapy. Nat Med. Atlas program (http://www.prote inatl as.org/patho logy). We thank Indira Pla, 2011;17:500–3. Aniel Sanchez Puente, Jeovanis Gil valdes and Lazaro Hiram Betancourt for 5. 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YAP1 is an independent prognostic marker in pancreatic cancer and associated with extracellular matrix remodeling

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10.1186/s12967-020-02254-7
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Abstract

Background: Pancreatic cancer is a major cause of cancer‑related mortality. The identification of effective biomarkers is essential in order to improve management of the disease. Yes‑associated protein 1 (YAP1) is a downstream effector of the Hippo pathway, a signal transduction system implicated in tissue repair and regeneration, as well as tumorigen‑ esis. Here we evaluate the biomarker potential of YAP1 in pancreatic cancer tissue. Methods: YAP1 was selected as a possible biomarker for pancreatic cancer from global protein sequencing of fresh frozen pancreatic cancer tissue samples and normal pancreas controls. The prognostic utility of YAP1 was evaluated using mRNA expression data from 176 pancreatic cancer patients in The Cancer Genome Atlas ( TCGA), as well as protein expression data from immunohistochemistry analysis of a local tissue microarray ( TMA) cohort comprising 140 pancreatic cancer patients. Ingenuity Pathway Analysis was applied to outline the interaction network for YAP1 in connection to the pancreatic tumor microenvironment. The expression of YAP1 target gene products was evaluated after treatment of the pancreatic cancer cell line Panc‑1 with three substances interrupting YAP–TEAD interaction, including Super‑ TDU, Verteporfin and CA3. Results: Mass spectrometry based proteomics showed that YAP1 is the top upregulated protein in pancreatic cancer tissue when compared to normal controls (log2 fold change 6.4; p = 5E−06). Prognostic analysis of YAP1 demon‑ strated a significant correlation between mRNA expression level data and reduced overall survival (p = 0.001). In addi‑ tion, TMA and immunohistochemistry analysis suggested that YAP1 protein expression is an independent predictor of poor overall survival [hazard ratio (HR) 1.870, 95% confidence interval (CI) 1.224–2.855, p = 0.004], as well as reduced disease‑free survival (HR 1.950, 95% CI 1.299–2.927, p = 0.001). Bioinformatic analyses coupled with in vitro assays indi‑ cated that YAP1 is involved in the transcriptional control of target genes, associated with extracellular matrix remod‑ eling, which could be modified by selected substances disrupting the YAP1‑ TEAD interaction. Conclusions: Our findings indicate that YAP1 is an important prognostic biomarker for pancreatic cancer and may play a regulatory role in the remodeling of the extracellular matrix. Keywords: Pancreatic cancer, YAP1, Transcriptomics, Proteomics, Prognosis, Extracellular matrix remodeling, Cancer Background Pancreatic cancer is one of the most aggressive malig- nancies with a dismal 5-year survival rate of 9% [1]. It *Correspondence: daniel.ansari@med.lu.se has surpassed breast cancer to become the third leading Department of Surgery, Clinical Sciences Lund, Lund University and Skåne University Hospital, 221 85 Lund, Sweden cause of cancer-related death and is estimated to rise to Full list of author information is available at the end of the article © The Author(s) 2020. This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article’s Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creat iveco mmons .org/licen ses/by/4.0/. The Creative Commons Public Domain Dedication waiver (http://creat iveco mmons .org/publi cdoma in/ zero/1.0/) applies to the data made available in this article, unless otherwise stated in a credit line to the data. Zhou et al. J Transl Med (2020) 18:77 Page 2 of 10 the second leading cause by 2030 [2]. Multiple factors, Research in Sweden and Lund University Diabetes center such as late diagnosis and resistance to conventional (LUDC). therapies, contribute to the overall poor prognosis. The immunohistochemical (IHC) target verification The ability to identify subgroups of patients that may was performed using tissue microarrays (TMA) from benefit from specific clinical management is considered archival formalin-fixed paraffin-embedded (FFPE) resec - central to modern precision oncology. For that pur- tion specimens from 140 patients with pancreatic ductal pose, large-scale genomic studies have been performed adenocarcinoma who underwent curative intent pancre- to determine molecular subtypes of pancreatic cancer atic surgery from 1995 to 2017 at Skåne University Hos- requiring individualized treatments [3–6]. Such studies pital, Lund and Malmö, Sweden. have massively increased our understanding of pancre- All samples were histopathologically verified and atic cancer at the molecular level. selected by a specialized surgical pathologist prior to Proteomics is a valuable complement to genetic stud- analysis. Ethical permission for the study was granted by ies. Mass spectrometry (MS)-based proteomics profil - the Ethical Committee at Lund University (Ref 2010/684, ing of patient-derived samples has been suggested as an 2012/661, 2015/266, 2017/320). The REMARK guidelines effective approach for the discovery of biomarkers and were followed where applicable [16]. detection of suitable therapeutic targets in many cancers [7–10]. MS‑based proteomics Yes-associated protein 1 (YAP1) is a downstream effec - Sample processing and LC–MS/MS analysis were per- tor of the Hippo signaling pathway, which is involved in formed as reported previously [10]. Briefly, proteins tissue repair and regeneration, as well as tumorigenesis. extracted from fresh frozen pancreas specimens were Activation of the Hippo pathway leads to inactivation of reduced, alkylated and digested into peptides using Lys-C YAP1 by cytoplasmic retention or proteolytic degrada- and trypsin. The peptides were analyzed using a high- tion [11, 12]. YAP1 in its active form, on the other hand, performance liquid chromatography system, EASY-nLC functions as a transcriptional co-activator predominantly 1000 connected to Q Exactive quadrupole-Orbitrap mass mediated by an interaction with TEAD transcription spectrometer equipped with a nanospray ion source factors [13]. Active YAP1 is also recognized as a potent (Thermo-Fisher Scientific, Bremen, Germany). To iden - oncogene closely linked to the progression of several can- tify the detected proteins, the acquired MS/MS data were cer types [14, 15]. However, the role of the YAP1-TEAD managed using Proteome Discoverer software, version interaction in regulating the expression of target genes in 1.4 (Thermo Fisher). pancreatic cancer has not been completely explored. In a previous study [10], we identified YAP1 as a differ - mRNA expression data entially expressed protein between pancreatic cancer and Publicly available transcriptomics data were retrieved normal controls using MS-based proteomics profiling. from 176 pancreatic cancer patients from The Cancer In the present study, we investigate the prognostic util- Genome Atlas (TCGA) [17–19]. RNA-seq data were ana- ity and the biological significance of YAP1 in pancreatic lyzed as the number of Fragments Per Kilobase of exon cancer using large and clinically well-annotated cohorts, per Million reads (FPKM). complemented by bioinformatics and in vitro experimen- tal analyses. Tissue microarray The TMA was constructed from FFPE pancreatic tumors by a trained biomedical technician using an automated tissue array device (Minicore 3, Alphelys, Plaisir, Materials and methods France). A set of 4 cores with a diameter of 2  mm were Patient samples extracted from each specimen and fixed into a new paraf - For the MS-based proteomics, fresh frozen pancreatic fin block. The completed blocks were then sectioned into cancer tissues (n = 10) were collected from patients with 3 µm thick sections and mounted on glass slides. pancreatic ductal adenocarcinoma undergoing pancrea- ticoduodenectomy between July 2013 and April 2015 at Immunohistochemistry the Department of Surgery, Skåne University Hospital, IHC analysis was performed as described previously Lund, Sweden. Written informed consent was obtained [20]. Briefly, deparaffinization, rehydration and antigen- from the patients included in the study. Age and gen- retrieval were performed using the automated PT Link der-matched, fresh frozen, normal pancreatic biopsies system (Dako, Agilent Technologies, Glostrup, Den- (n = 10) were assessed from organ donors and obtained mark). TMA-slides were then incubated with monoclo- from the national consortium Excellence of Diabetes nal rabbit anti-human primary antibody against YAP1 Zhou  et al. J Transl Med (2020) 18:77 Page 3 of 10 (dilution 1:200; Cell Signaling) followed by biotinylated Bioapplication software was thereafter used for image goat anti-rabbit secondary antibody (dilution 1:200; processing. Vector Laboratories, Burlingame, CA). Avidin–biotin– In each well, a cell population consisting of two thou- peroxidase complex (Vectastain Elite ABC-HRP Kit, Vec- sand cells was analysed using multiparameter fluores - tor Laboratories, Burlingame, CA) was used for signal cent microscopic imaging system designed for high amplification. The color was developed using chromo - content screening. The processed data obtained from gen diaminobenzidine (DAB) (Vector Laboratories). The automatically acquired images were quantified as fluores - nuclei were colored with hematoxylin. The immunostain - cence intensity for the selected channel (Alexa 488). The ing was evaluated by three independent pathologists, accessed images were visualized using automated fluo - blinded to clinical information. H-score was applied as rescence microscopy. a semiquantitative approach [21, 22]. The intensity of YAP1 staining was scored as [0] (negative), [1+] (weak), [2+] (moderate), or [3+] (strong) and the percentage of YAP1 target gene expression cells at each staining intensity level was recorded. The To evaluate the expression of selected YAP1 target genes, H-scores were calculated by following formula: the cells were seeded in 6-well plates with a concentra- tion of thirty thousand cells per well. After one cell cycle, H-score = 0 × (% cells 0 ) + 1 × (% cells 1 ) [ ] [ ] the cells were incubated with a maximal tolerable dose of + 2 × (% cells 2 ) + 3 × (% cells 3 ). [ ] [ ] three substances interrupting YAP–TEAD interaction; Super-TDU (500  nM), Verteporfin (100  nM) and CA3 (100 nM) or complete medium. After 48 h, the cell lysates Bioinformatics and conditioned medium from respective well and plate Ingenuity Pathway Analysis software (IPA, Qiagen, Inc. were collected. All experiments were executed in tripli- Redwood City, CA, USA) was used for bioinformatic cates. Expression levels of YAP1 targets genes, including analysis of networks involving the biological relation- amphiregulin (AREG), connective tissue growth factor ship between YAP1 and pancreatic cancer. A network (CTGF), cysteine-rich angiogenic inducer 61 (CYR61), involving all direct interactors of these proteins was built fibroblast growth factor 1 (FGF1) and mesothelin and analyzed for pathway enrichment and functional (MSLN), were selected from the Ingenuity Pathway Anal- annotations. ysis and measured in each sample using enzyme-linked immunosorbent  assay (ELISA). 100  µg protein from respective sample was analyzed in each assay according Cell culture to the manufacturer’s instructions. AREG, CTGF, CYR61, The patient derived pancreatic cancer cell line Panc-1 FGF1 were purchased from Nordic Biosite AB, Täby, SE (ATCC-LGC Standards, Manassas, VA, USA) was used and MSLN from Biolegend, San Diego, CA, USA. for the in  vitro experiments. The cells were maintained in DMEM supplemented with 10% fetal bovine serum, 100 U/ml penicillin and 100  μg/ml streptomycin and Statistical analysis kept in a humified atmosphere, in 5% CO at 37 °C. Prior The correlation between YAP1 expression levels and experiment, the cells were observed using phase contrast clinicopathological parameters was estimated using the microscope to ensure the condition of the cells including Mann–Whitney U test for continuous variables and morphological characteristics and vitality. 2 Fisher’s exact test or χ for categorical variables. The Kaplan–Meier method was used to model the cumulative probability of overall survival (OS) and disease-free sur- Immunofluorescence based Cellomics vival (DFS) and statistical differences were assessed using To assert the YAP1 expression profile, the cells were the log-rank test. Univariable and multivariable survival seeded in 6 well plates with the density of fifty thousand analysis were also performed using Cox proportional cells per well. After 48 h, the cells were fixed with 4% par - hazards regression modeling. aformaldehyde (Histolab, Västra Frölunda, Sweden) and One-way ANOVA parametric test was applied to com- stained with primary rabbit anti-human YAP1 (dilution pare the concentrations of secreted YAP target genes 1: 250, Cell Signaling) followed by Alexa Fluor 488 con- measured in condition medium obtained from Panc-1 jugated donkey-anti-rabbit secondary antibody (dilution cells subjected to three substances interrupting YAP1 1:200, Invitrogen, USA). The nucleus was marked using transcriptional activity or untreated cells. DAPI (NucBlue , Molecular probes, Life technologies, Statistical evaluation was conducted with SPSS version USA). Cellomics ArrayScan platform VTI HCS (Ther - 23.0 (SPSS Inc., Chicago, IL, USA) and GraphPad Prism moScientific, Rockford, IL, USA) reader connected to Zhou et al. J Transl Med (2020) 18:77 Page 4 of 10 Fig. 1 Selection of the YAP1 protein for validation. a Label‑free quantitative MS spectra of YAP1 (based on peptide SQLPTLEQDGGTQNPVSSPGMSQELR). b Box‑plot showing relative expression levels of YAP1 in pancreatic cancer (PC) and healthy controls (HC) Table 1 Characteristics of the TCGA cohort (n = 176) Variable N = 176 Median age (range), years 65 (35–88) Female gender 50 (45.5%) AJCC‑stage I 21 (11.9%) II 145 (82.4%) III 3 (1.7%) IV 4 (2.3%) Unknown 3 (1.7%) Median FPKM (range) 19.0 (0.5‑46.6) FPKM fragments per kilobase of exon per million reads Fig. 2 Kaplan–Meier survival curves stratified by YAP1 mRNA v.8.0.1 (La Jolla, CA, USA). A p-value < 0.05 was consid- expression levels in the TCGA cohort. Patients were categorized ered statistically significant. based on the median number of fragments per kilobase of exon per million reads (FPKM) into low expression (≤ 19) and high expression groups (> 19) Results YAP1 is the top upregulated protein in pancreatic cancer Fresh frozen biopsies from pancreatic tumors (n = 10) and healthy pancreatic tissue (n = 10), were analyzed TCGA (Table  1). The median FPKM value was 19.0, using label-free quantitative proteomics to discover dif- ranging from 0.5 to 46.6. The median FPKM value was ferentially expressed proteins. In total, 4138 proteins used to divide the cohort into a low (FPKM ≤ 19) and a were identified, and 2950 proteins were quantified based high expression group (FPKM > 19). The Kaplan–Meier on one or more unique peptides. 165 candidates were plots revealed that high YAP1 mRNA expression was subsequently determined as potential biomarkers for significantly correlated with poorer OS when compared pancreatic cancer, as previously reported [10]. Character- with low mRNA YAP1 expression, as illustrated in Fig. 2 ized by six unique peptides, YAP1 was annotated as the (median survival 17  months vs. 23  months, respectively, top upregulated protein in pancreatic tumor specimens p = 0.001). (log2 fold change 6.4; p = 5E−06) (Fig. 1a, b). mRNA expression levels of YAP1 as a prognostic marker YAP1 protein expression levels and prognosis To assess the prognostic significance of YAP1, we ana - The protein expression levels of YAP1 were analyzed lyzed mRNA expression level data and patient survival using immunohistochemistry staining on TMA sections based on 176 pancreatic cancer patients included in constructed from 140 pancreatic tumors. The antibody Zhou  et al. J Transl Med (2020) 18:77 Page 5 of 10 staining specific for YAP1 was detected in the nucleus or analysis, high YAP1 protein expression was identified in the nucleus and cytoplasm of tumor cells. The median as an independent risk factor for poor OS (hazard ratio H-score was 170 (range, 59–289). Based on the median (HR) 1.870, 95% confidence interval (CI) 1.224–2.855, H-score (170), a low (H-score ≤ 170) and a high expres- p = 0.004). Moreover, univariable Cox regression analysis sion group (H-score > 170) were created (Fig. 3a). No sig- of DFS determined histopathological grade (p = 0.028), nificant differences in clinicopathological features were resection margin ≥ R1 (p = 0.028), and high expression identified between high and low YAP1 expression groups of YAP1 (p = 0.006) as factors associated with decreased (Table 2). DFS. Multivariable Cox regression analysis confirmed the Kaplan–Meier analysis revealed that high YAP1 pro- results, indicating that high YAP1 protein expression is tein expression was significantly correlated with shorter an independent risk factor for reduced DFS (HR 1.950, OS when compared with low YAP1 protein expression 95% CI 1.299–2.927, p = 0.001) (Table 3). (median survival, 17.9 vs. 34.3  months, respectively, We thus interpret that YAP1 may function as a marker p = 0.001, log-rank test; Fig.  3b). Furthermore, patients for poor prognosis and disease relapse in pancreatic can- exhibiting high YAP1 protein expression had significantly cer patients. reduced DFS when compared to the low YAP1 protein expression group (median DFS, 10.7 vs. 17.5  months, YAP1 is connected to mediators promoting remodeling respectively, p = 0.005, log-rank test; Fig. 3c). of the extracellular matrix The univariable Cox regression analysis of OS identi - Subsequently, we explored the biological background of fied smoking history (p = 0.04), symptoms at diagno- the obtained results with the aim to identify the most sis (p = 0.05), histopathological grade (p = 0.03), and significant networks and relationships associated with high expression of YAP1 (p = 0.001) as factors associ- YAP1 expression in pancreatic cancer. Bioinformatic ated with shorter OS. In multivariable Cox regression analysis using the IPA software revealed that YAP1 is Fig. 3 Immunohistochemical analysis of YAP1 protein expression in the tissue microarray cohort. a Representative images of YAP1 immunostaining in low and high expression groups using the median H‑score (170) as cut ‑ off. b Kaplan–Meier survival curves for overall survival stratified by YAP1 protein expression. c Kaplan–Meier survival curves for disease‑free survival stratified by YAP1 protein expression Zhou et al. J Transl Med (2020) 18:77 Page 6 of 10 Table 2 Characteristics of the TMA cohort (n = 140) Variable N All patients Low YAP1 protein High YAP1 protein p (n = 140) expression expression (n = 70) (n = 70) Age > 65 years 140 93 (66.4) 48 (68.6) 45 (64.3) 0.721 Female gender 140 66 (47.1) 35 (50) 31 (44.3) 0.612 BMI > 25 kg/m 132 57 (43.2) 32 (47.1) 25 (39.1) 0.383 Smoking history 139 67 (48.2) 28 (40.6) 39 (55.7) 0.09 Diabetes mellitus 139 33 (23.7) 19 (27.1) 14 (20.3) 0.426 Symptoms at diagnosis 136 131 (96.3) 68 (100) 63 (92.6) 0.058 Tumor location (head) 140 117 (83.6) 62 (88.6) 55 (78.6) 0.17 Tumor size > 2 cm 139 117 (84.2) 60 (87) 57 (81.4) 0.487 T‑stage ≥ T2 139 121 (87.1) 60 (87) 61 (87.1) 1 N‑stage ≥ N1 138 104 (75.4) 53 (76.8) 51 (73.9) 0.844 AJCC‑stage ≥ II 138 112 (81.2) 56 (81.2) 56 (81.2) 1 Histological grade ≥ 3 138 83 (60.1) 38 (55.9) 45 (64.3) 0.385 Positive resection margin 139 55 (39.6) 28 (40.6) 27 (38.6) 0.863 Adjuvant chemotherapy 135 113 (83.7) 60 (87) 53 (80.3) 0.355 Recurrence of disease 127 103 (81.1) 51 (79.7) 52 (82.5) 0.821 N, number of non-missing values. Qualitative data are expressed as n (%) AJCC American Joint Committee on Cancer, BMI body mass index, N-stage nodal stage, T-stage tumor stage Table 3 Univariable and multivariable Cox regression analysis in the TMA cohort (n = 140) Variable OS DFS Univariable HR p Multivariate HR p Univariable HR p Multivariable HR p (95% CI) (95% CI) (95% CI) (95% CI) Age (> 65) 0.994 (0.658–1.501) 0.977 0.760 (0.506–1.144) 0.189 Female gender 0.825 (0.557–1.221) 0.336 0.675 (0.453–1.005) 0.053 BMI (> 25 kg/m ) 1.250 (0.832–1.876) 0.283 1.372 (0.913–2.061) 0.128 Smoking history 1.510 (1.019–2.239) 0.04* 1.319 (0.868–2.003) 0.195 1.268 (0.852–1.887) 0.242 Diabetes 0.782 (0.479–1.277) 0.326 0.927 (0.567–1.515) 0.762 Symptoms at diag‑ 0.363 (0.132–1.000) 0.05* 0.548 (0.193–1.559) 0.260 0.620 (0.227–1.693) 0.351 nosis Tumor location (head) 0.658 (0.390–1.112) 0.118 1.143 (0.625–2.092) 0.664 Tumor size (> 2 cm) 1.090 (0.653–1.819) 0.741 1.215 (0.710–2.079) 0.478 T‑stage (≥ T2) 1.152 (0.672–1.973) 0.607 1.429 (0.795–2.571) 0.233 N‑stage (≥ N1) 1.474 (0.924–2.352) 0.104 1.316 (0.829–2.088) 0.244 AJCC‑stage (≥ II) 1.426 (0.855–2.379) 0.174 1.345 (0.814–2.222) 0.248 Histological grade 1.580 (1.045–2.390) 0.03* 1.728 (1.123–2.657) 0.013* 1.592 (1.050–2.413) 0.028* 1.628 (1.072–2.472) 0.022* (≥ 3) Resection margin 1.388 (0.926–2.080) 0.112 1.585 (1.050–2.394) 0.028* 1.716 (1.127–2.613) 0.012* (≥ R1) Adjuvant chemo‑ 0.712 (0.435–1.166) 0.177 1.632 (0.887–3.002) 0.115 therapy YAP1 protein expres‑ 1.917 (1.288–2.854) 0.001* 1.870 (1.224–2.855) 0.004* 1.752 (1.178–2.608) 0.006* 1.950 (1.299–2.927) 0.001* sion (High) Variables with p ≤ 0.05 were marked with asterisk (*), variables with p ≤ 0.05 in univariable analysis were included in multivariable analysis AJCC American Joint Committee on Cancer, BMI body mass index, CI confidence interval, DFS disease free survival, HR hazard ratio, N-stage nodal stage, OS overall survival, T-stage tumor stage Zhou  et al. J Transl Med (2020) 18:77 Page 7 of 10 positively stained cells showed a strong fluoresce inten - sity located in the nucleus (Fig. 5a). YAP1 participates in the transcription of target genes involved in profibrotic tumor microenvironment Next, we investigated co-transcriptional activity of YAP1 in synthesis of secreted proteins associated with remod- eling of the tumor microenvironment in pancreatic cancer. First, Panc-1 cells were cultured under standard conditions to assess the expression levels of proteins ascertained by the IPA analysis. All investigated proteins, AREG, CTGF, CYR61, FGF1, and MSLN were considered as low abundant and detected in low concentrations (pg/ ml) in lysates of Panc-1 cells cultured under standard conditions. As presented in Fig. 5b, the expression levels corresponded to at a maximum 0.2‰ of the total cellular protein amount. Next, the collected conditioned medium from the Fig. 4 Ingenuity Pathway Analysis showing the plasma membrane Panc-1 cells was analyzed for the presence of selected and extracellular proteins directly related to YAP1. The relation proteins. AREG, CTGF, CYR61, and MSLN were identi- to proteins involved in mechanotransduction include the cell fied and the secretion pattern was further investigated. membrane protein PATJ (crumbs cell polarity complex component), which is directly related to YAP1 and is also interacting with PIEZO1, Panc-1 cells were subjected to substances inhibiting the Piezo type mechanosensitive ion channel component 1. YAP1 YAP1 transcriptional activity and the concentrations of is also an indirect regulator of both PIEZO1 and PIEZO2. Further, the the determined secreted proteins were measured. Levels cytokine endothelin 1 (EDN1) is directly related to YAP1 and is also a of secreted AREG, CTGF, CYR61, and MSLN were sig- regulator of the degenerin/epithelial sodium channels (DEG/ENaC, nificantly lower (p = 0.0001) or undetectable in condi- here marked as SCNN1A, SCNN1B, SCNN1G, SCNN1D). Tight junction signaling proteins related to YAP1 include CTNNA1, MPDZMPP5, tioned medium after the treatment (Fig. 5c). Based on the OCLN, PATJ, TJP2. Epithelial adherens junction signaling proteins obtained results, we suggest that YAP1 is involved in the related to YAP1 include CDH1, CTNNA1, CTNNA2, EGFR, FGF1, PARD3, transcription of genes associated with remodeling of the ZYX. Examples of secreted proteins involved in creating a pro‑fibrotic pancreatic tumor microenvironment. microenvironment include AREG, CTGF, CYR61, FGF1, and MSLN and these YAP1 target genes are highlighted and were chosen for further in vitro confirmation Discussion In this transcriptome- and proteome-based study, we identified YAP1 as an indicator of poor OS and DFS in directly related to proteins involved in mechanotrans- patients with pancreatic cancer. duction, such as PATJ and PIEZO1, and the cytokine The American Joint Committee on Cancer (AJCC) EDN1 (Fig. 4). Tight junction signalling proteins related tumor-node-metastasis (TNM) classification system is to YAP1 include CTNNA1, MPDZMPP5, OCLN, PATJ, currently the gold standard for pancreatic cancer prog- and TJP2, while epithelial adherens junction signaling nostication [23]. However, the AJCC TNM system is proteins related to YAP1 include CDH1, CTNNA1, only concerned with the anatomical extent of the disease CTNNA2, EGFR, FGF1, PARD3, and ZYX. Examples though patients within the same stage may exhibit dif- of secreted proteins involved in creating a pro-fibrotic ferent outcomes [24]. Such evaluation may lead to either microenvironment include AREG, CTGF, CYR61, over- or undertreatment. Improved staging systems, FGF1, and MSLN and these YAP1 target genes were considering molecular factors  are necessary in order to chosen for further in vitro confirmation. enhance individual prognostication and utilization of precision therapies. The prognostic significance of YAP1 protein expression YAP1 protein expression in a patient derived cell line has only been evaluated in one previous small study by We performed immunofluorescence based Cellomics Allende et al. [25]. However, YAP1 protein expression did to evaluate the protein expression profile of YAP1 in not reach statistical significance in their Kaplan–Meier Panc-1 cells. In accordance with the TMA/IHC patient analysis, likely due to the small cohort size (64 patients). data, a positive YAP1 staining was detected in both Only when conducting subgroup analyses, stratifying nucleus and cytoplasm of Panc-1 cells. The majority of Zhou et al. J Transl Med (2020) 18:77 Page 8 of 10 ac Fig. 5 In vitro analysis of YAP1 and selected target genes in Panc‑1 cells. a YAP1 protein expression in Panc‑1 cells. The image represents an immunofluorescence staining of endogenous YAP1 in Panc‑1 cells, plated in 6 well plates and cultivated for 48 h under standard conditions. The arrows indicate an exemplification of YAP1 nuclear accumulation. b Concentrations of YAP1 target genes in lysates obtained from Panc‑1 cells cultivated under standard conditions. C) Concentrations of YAP1 target genes in conditioned medium obtained from Panc‑1 cells that were subjected to maximal tolerable doses (MTD) of substances blocking the YAP1/TEAD interaction survival into groups of patients surviving more than or signaling pathways involved in the tumor-stroma interac- less than 30 months, it was shown that patients with high tions [27–31]. YAP1 expression had worse survival. Therefore, to clarify Pancreatic cancer progression is generally associated the prognostic role of YAP1 protein expression in pan- with a dense fibrotic stroma characterized by an exten - creatic cancer, additional studies based on larger cohorts sive deposition of extracellular matrix components sur- are needed. The TMA/immunohistochemistry analysis rounding the cancer cells [32, 33]. The desmoplastic based on 140 patients in our study revealed that overex- extracellular matrix, mainly produced by activated cancer pression of YAP1 is an independent factor for unfavora- associated fibroblasts, accounts for up to 80% of entire ble outcome and disease recurrence. These findings are tumor mass [33]. The fibrotic environment is known to in agreement with the public mRNA dataset from the undergo an extensive remodeling connected to the stiff - TCGA, which illustrate that high expression of YAP1 ening of tumor tissue. Such stromal reshaping presum- significantly correlates with poor survival in pancreatic ably modifies the crosstalk between residual cells within cancer patients. The agreement between the transcrip - the tumor and directs the tumor progression towards an tome- and proteome-based survival analyses in the pre- aggressive phenotype [33–35]. The increased stiffness sent study strengthens the clinical significance of YAP1 of matricellular tumor microenvironment also activates as a prognostic variable. However, it is important to note YAP1 to further modulate the behavior of cancer cells on that knowledge about mRNA abundances can only par- the transcriptional level [36, 37]. tially predict protein abundances, with a large fraction of YAP1 itself, however, lacks DNA-binding activity and the variance also being explained by other factors such as requires an interaction with DNA-binding transcrip- post-transcriptional and translational regulation, as well tion factors such as TEAD to activate target genes [38]. as protein degradation [26]. AREG, CTGF and CYR61 account for the most acknowl- To understand the biological role of YAP1 in pancre- edged target genes for YAP1/TEAD [39–41]. The YAP1/ atic cancer, we performed bioinformatic analyses of pro- TEAD interactions are also reported to regulate the tein networks. The results revealed that YAP1 is directly expression of FGF1 and MSLN [42–44]. connected to secreted AREG, CTGF, CYR61, FGF1 We hypothesized that the secreted YAP1/TEAD tar- and MSLN that are involved in fibrosis and other key get gene products contribute to the enhanced fibrotic Zhou  et al. J Transl Med (2020) 18:77 Page 9 of 10 Hain Foundation for Medical Research, the Clas Groschinsky Foundation, the reaction and intra-tumoral stiffening which consecutively Gunnar Nilsson Foundation, the Gyllenstiernska Krapperup Foundation, the promote YAP1 transcriptional activity. Such paracrine Bengt Ihre Foundation, the Emil and Wera Cornell Foundation, the Crafoord loop would further affect the tumor microenvironment Foundation, Governmental Funding of Clinical Research within the National Health Service (ALF) and Sweden´s Innovation Agency ( Vinnova). and maintain the aggressive course of the disease. Using the patient derived pancreatic cancer cell line Availability of data and materials Panc-1, we evaluated the effect of substances designed The datasets generated and/or analyzed during the current study are available from the corresponding author on reasonable request. to inhibit the YAP1/TEAD mediated gene transcription. We showed that the disruption of YAP1/TEAD complex Ethics approval and consent to participate significantly reduced the presence of the selected YAP1/ This study was performed in compliance with the Helsinki Declaration on ethi‑ cal principles for handling human tissue specimens, with all EU and national TEAD target gene products in the conditioned medium. regulations and requirements. Written informed consent was obtained from Suppression of YAP1 oncogenic activity with a subse- participants. Ethical permission for the study was granted by the Ethics Com‑ quent modification of the tumor microenvironment mittee at Lund University (Ref 2010/684, 2012/661, 2015/266, 2017/320). may thus be an advantageous approach to control tumor Consent for publication growth and improve prognosis. Although the clinical uti- Consent for publication was obtained from included participants. lization for such treatment remains to be determined, Competing interests YAP1 as a biomarker may aid in the individual prognos- The authors declare that they have no competing interests. tication of patients diagnosed with pancreatic cancer and the selection of precision therapy. Author details The Eye Hospital, School of Ophthalmology and Optometry, Wenzhou Medical University, Wenzhou, Zhejiang, China. Department of Surgery, Clinical Sciences Lund, Lund University and Skåne University Hospital, 221 Conclusions 85 Lund, Sweden. Clinical Protein Science and Imaging, Biomedical Centre, We demonstrate that YAP1 is an independent prognostic Department of Biomedical Engineering, Lund University, Lund, Sweden. marker associated with recurrence and unfavorable sur- Department of Surgery, The Second Affiliated Hospital and Yuying Children’s Hospital of Wenzhou Medical University, Wenzhou, Zhejiang, China. Depart‑ vival in pancreatic cancer. We also show that inhibition of ment of Pathology, Skåne University Hospital, Lund, Sweden. Department YAP1/TEAD interaction interferes with the expression of of Pathology, The First Affiliated Hospital of Nanchang University, Nanchang, AREG, CTGF, CYR61, and MSLN suggesting that YAP1 China. Department of Experimental Design and Bioinformatics, Warsaw University of Life Sciences, Warsaw, Poland. Department of Translational transcriptional activity may affect the development and Medicine, Lund University, Malmö, Sweden. persistence of a fibrotic tumor microenvironment. 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