Integrative Omics Analysis Reveals Soluble Cadherin-3 As a Survival

Published OnlineFirst March 10, 2020; DOI: 10.1158/1078-0432.CCR-19-3972

CLINICAL CANCER RESEARCH | PRECISION MEDICINE AND IMAGING

Integrative Omics Analysis Reveals Soluble Cadherin-3 as a Survival Predictor and an Early Monitoring Marker of EGFR Tyrosine Kinase Inhibitor Therapy in Lung Cancer Ting-Feng Hsiao1, Chih-Liang Wang2,3, Yi-Cheng Wu4, Hsiang-Pu Feng1, Yen-Chuan Chiu1, Hao-Yu Lin1, Ko-Jiunn Liu5,6, Gee-Chen Chang7,8, Kun-Yi Chien1,9,10, Jau-Song Yu9,10,11,12, and Chia-Jung Yu1,3,9,10

ABSTRACT ◥ Purpose: EGFR tyrosine kinase inhibitors (EGFR-TKI) (OS) were assessed to evaluate the prognostic values of the benefit patients with advanced lung adenocarcinoma (ADC) potential biomarkers. harboring activating EGFR mutations. We aimed to iden- Results: Fifteen proteins were identified as potential biomarkers tify biomarkers to monitor and predict the progression of of EGFR-TKI resistance. Cadherin-3 (CDH3) was overexpressed in patients receiving EGFR-TKIs via a comprehensive omic ADC tissues compared with normal tissues. CDH3 knockdown analysis. enhanced EGFR-TKI sensitivity in ADC cells. The PE level of Experimental Design: We applied quantitative proteomics soluble CDH3 (sCDH3) was increased in patients with resistance. to generate the TKI resistance–associated pleural effusion (PE) The altered sCDH3 serum level reflected the efficacy of EGFR-TKI proteome from patients with ADC with or without EGFR-TKI after 1 month of treatment (n ¼ 43). Baseline sCDH3 was signif- resistance. Candidates were selected from integrated genomic icantly associated with PFS and OS in patients with ADC after and proteomic datasets. The PE (n ¼ 33) and serum (n ¼ 329) EGFR-TKI therapy (n ¼ 76). Moreover, sCDH3 was positively levels of potential biomarkers were validated with ELISAs. associated with tumor stage in non–small cell lung cancer (n ¼ 272). Western blotting was applied to detect protein expression in Conclusions: We provide useful marker candidates for drug tissues, PEs, and a cell line. Gene knockdown, TKI treatment, resistance studies. sCDH3 is a survival predictor and real-time and proliferation assays were used to determine EGFR-TKI indicator of treatment efficacy in patients with ADC treated with sensitivity. Progression-free survival (PFS) and overall survival EGFR-TKIs.

Introduction lung cancers, and adenocarcinoma (ADC) is the most common subtype of NSCLC (2). EGFR mutations specifically target patients Lung cancer is the leading cause of cancer-related death world- with lung ADC (60%) in East Asian countries, including Tai- wide (1). Non–small cell lung cancer (NSCLC) represents 80% of all wan (3, 4). EGFR-tyrosine kinase inhibitors (EGFR-TKI), such as the first-generation TKIs erlotinib and gefitinib and the second-generation TKI afatinib, have been determined to benefit patients with ADC with 1Graduate Institute of Biomedical Sciences, College of Medicine, Chang Gung EGFR-activating mutations (5). These response evaluations of targeted University, Taoyuan, Taiwan. 2School of Medicine, College of Medicine, Chang therapy are based on the RECIST guidelines (6), and an EGFR Gung University, Taoyuan, Taiwan. 3Division of Pulmonary Oncology and Inter- mutation is recognized as a good predictor for the initial efficacy of ventional Bronchoscopy, Department of Thoracic Medicine, Chang Gung Memo- EGFR-TKI treatments, in which the response rates and disease control 4 rial Hospital, Linkou, Taoyuan, Taiwan. Department of Thoracic Surgery, Chang rates are 60%–70% and 85%–95%, respectively. These TKIs are Gung Memorial Hospital, Linkou, Taoyuan, Taiwan. 5National Institute of Cancer Research, National Health Research Institutes, Tainan, Taiwan. 6School of associated with a median progression-free survival (PFS) time of – – Medical Laboratory Science and Biotechnology, Taipei Medical University, 9 14 months compared with 5 7 months for platinum-based Taipei, Taiwan. 7Division of Chest Medicine, Department of Internal Medicine, chemotherapy (7). Unfortunately, patients treated with first/second- Taichung Veterans General Hospital, Taichung, Taiwan. 8Faculty of Medicine, generation EGFR-TKIs eventually develop acquired resistance to these 9 School of Medicine, National Yang-Ming University, Taipei, Taiwan. Department agents after a median of 10–16 months that most commonly (50%– of Cell and Molecular Biology, College of Medicine, Chang Gung University, 60% of cases) results from a secondary mutation at position 790 in Taoyuan, Taiwan. 10Molecular Medicine Research Center, Chang Gung Univer- sity, Taoyuan, Taiwan. 11Liver Research Center, Chang Gung Memorial Hospital, EGFR (T790M; refs. 8, 9). Osimertinib, a third-generation irreversible – Linkou, Taoyuan, Taiwan. 12Research Center for Food and Cosmetic Safety, EGFR-TKI that selectively inhibits both EGFR-TKI sensitizing and College of Human Ecology, Chang Gung University of Science and Technology, EGFR T790M–resistance mutations (10), obtained FDA-accelerated Taoyuan, Taiwan. approval in November 2015. Recent studies have also shown that Note: Supplementary data for this article are available at Clinical Cancer osimertinib improves both the median PFS (18.9 vs. 10.2 months) and Research Online (http://clincancerres.aacrjournals.org/). overall survival (OS; 38.6 vs. 31.8 months) compared with first- € T.-F. Hsiao and C.-L. Wang contributed equally to this article. generation EGFR-TKIs in patients with treatment-na ve, EGFR mutation–positive (exon 19 deletion or L858R) advanced NSCLC (11, 12), Corresponding Author: Chia-Jung Yu, Chang Gung University, No. 259 Wenhua fi 1st Rd., Guishan Dist., Taoyuan 33302, Taiwan. Phone: 886-3211-8800, ext. 3424; suggesting that osimertinib will be a new standard of care in rst-line Fax: 886-3211-8042; E-mail: [email protected] EGFR-mutated NSCLC. T790M can be evaluated via either a tissue rebiopsy or circulating cell-free tumor DNA in the plasma, and its Clin Cancer Res 2020;XX:XX–XX evaluation is currently mandatory after progression to first/second- doi: 10.1158/1078-0432.CCR-19-3972 generation EGFR-TKIs (13). However, neither cancer progression nor 2020 American Association for Cancer Research. an improvement in the patient's OS is correlated with EGFR

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Hospital (Linkou, Taoyuan, Taiwan; approval number: 99-3738B and Translational Relevance 99-3671B). This study was conducted in accordance with the Decla- Mutated EGFR is a predictor of the initial treatment efficacy of ration of Helsinki and Good Clinical Practice. Written informed EGFR–tyrosine kinase inhibitors (TKI) in advanced lung adeno- consent was received from all patients before collection. For the carcinoma (ADC). Unfortunately, neither EGFR mutations nor discovery phase, malignant pleural effusion (MPE) from 23 patients molecular markers can accurately monitor cancer progression or with advanced lung ADC with EGFR mutations who received EGFR- predict patient survival. EGFR-TKI susceptibility associated bio- TKI–targeted therapy with or without following chemotherapy regi- markers to benefit patients with lung ADC are in high demand. mens were included. PE from 10 patients with tuberculosis (TB) Pleural effusion (PE) has been recognized as a promising source for represents benign pulmonary disease. These 33 patients' PEs were biomarker discovery. By integrating PE proteomic and tissue divided into four groups (Fig. 1A; Supplementary Table S2): MPE genomic analyses, we herein identified soluble cadherin-3 (sCDH3) obtained prior to treatment (before treatment, BT group) from 11 as a marker for monitoring first/second-generation EGFR-TKI patients who achieved partial response (PR) for at least 6 months, MPE resistance in real time. Cadherin-3 (CDH3) knockdown enhances obtained on the day of failure from 8 patients who received EGFR-TKI EGFR-TKI sensitivity in ADC cells. Importantly, the baseline treatment followed by chemotherapy [progressive disease; PD (TþC)], serum sCDH3 level is associated with progression-free survival in MPE obtained on the day of failure from 4 patients who received patients with ADC who received EGFR-TKI therapy and with EGFR-TKI treatment [PD (T)], and PE from 10 patients with TB. For overall survival in patients with non–small cell lung cancer the verification phase, these 33 PEs used in the discovery phase were (NSCLC). Our results establish a biomarker dataset for EGFR- included in ELISA. To determine the sCDH3 level via ELISA, serum TKI resistance and prognosis. This study significantly advances the samples were obtained from 272 treatment-na€ve NSCLC patients development of a liquid biopsy to benefit patients with NSCLC and (baseline) and 57 healthy controls (Table 1). Specifically, 23 MPE and provides new insights into EGFR-TKI resistance in lung ADC. 76 serum samples from patients with ADC with mutated EGFR and who received first/second-generation EGFR-TKIs were collected between 2009 and 2016. Among these 272 patients with NSCLC, serum samples collected 1 month (29 8 days) after EGFR-TKI mutations. This suggests that even in patients with the same EGFR treatment from 43 patients with ADC (28 PR and 15 non-PR) with mutation status, the event of acquiring resistance and the timing of EGFR mutations were included to examine alterations in sCDH3 levels resistance are heterogeneous and unpredictable. To improve the upon EGFR-TKI treatment. To detect CDH3 expression in tissues via prediction of the response to EGFR-TKI–targeted therapy in patients Western blotting, cancerous and adjacent normal tissues from 11 ADC with ADC as well as their prognosis, certain serum molecules, such as patients was included (Supplementary Table S3). The PE and serum carcinoembryonic antigen (CEA), CA125, CA19-9, CA27-29, and samples were centrifuged at 2,000 g for 15 minutes at 4C. The CYFRA 21-1, and cell-free circulating tumor DNA have been reported supernatants were transferred to a new tube and stored at 80C for as potential biomarkers (14–16). Because of their limited sensitivity/ further analysis or verification. The tissue samples were collected specificity and sample size, the clinical significance of these potential during surgical resection and stored at 80C until analysis. markers is underevaluated. Pleural effusion (PE), a tumor-proximal body fluid, is associated Removal of high-abundance proteins from PE with lung malignancy and serves as a promising source for biomarker The PE from each group of patients was pooled and subjected to the discovery (17, 18). Previously, we generated the differential PE pro- depletion of 14 high-abundance proteins using a Multiple Affinity teomes from six types of exudative PEs via a label-free quantitative Removal System (MARS) Affinity Column (Agilent Technologies) via proteomics approach to facilitate the discovery of lung ADC biomar- AKTA€ purifier 10 fast performance liquid chromatography according kers (19). This study aimed to search for serum biomarkers that could to the manufacturer's instructions (GE Healthcare). Unbound frac- be used to monitor the treatment efficacy and prognosis of patients tions were collected, concentrated, desalted, and concentrated by with advanced ADC with first/second-generation EGFR-TKI therapy centrifugation in Amicon Ultra-4 Tubes (Millipore). The resulting in real time. We then established a drug resistance–associated PE protein concentration was quantified with a Bradford Protein Assay database via isobaric tags for relative and absolute quantitation (Bio-Rad Laboratories, Inc.). (iTRAQ)-based quantitative technology combined with high- throughput tandem mass spectrometry. We selected potential bio- In-solution digestion of proteins and iTRAQ labeling markers by integrating our quantitative proteomic database with Gene The PE proteins were reduced with 5 mmol/L tris-(2-carboxyethyl) Expression Profiling Interactive Analysis (GEPIA, http://gepia.cancer- phosphine at 60C and then alkylated with 10 mmol/L iodoacetamide pku.cn/) and the Human Protein Atlas (https://www.proteinatlas.org/) for 30 minutes at 37C. Proteins were digested overnight at 37C with database. Cadherin-3 (CDH3), a promising marker candidate, was trypsin (Promega), and the peptides were extracted for further anal- selected for further verification and validation using lung tissues, PEs, a ysis. For iTRAQ labeling, the tryptic peptides were reconstituted in cell line, and a large cohort of serum samples. Our results support that iTRAQ reagent buffer, and the four groups of PE samples were the baseline soluble CDH3 (sCDH3) level is a noninvasive biomarker separately labeled with four different iTRAQ labeling reagents, as for the diagnosis of late-stage NSCLC and a prognostic marker for shown in Fig. 1A [114, BT; 115, PD(TþC); 116, PD(T); and 117, TB] patients with ADC receiving first/second-generation EGFR-TKI therapy. according to the manufacturer's instructions (AB Sciex, Inc.).

Two-dimensional LC/MS-MS and protein database search Materials and Methods The two-dimensional (2D) LC/MS-MS analysis was performed as Patient populations and clinical specimens described previously (20, 21). The resulting MS-MS spectra were The acquired clinical samples were approved by the Institutional searched against the Swiss-Prot human sequence database using the Review Board for Research Ethics at the Chang Gung Memorial Mascot search engine (Matrix Science, version 2.2.04). To quantify the

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Figure 1. Experimental design and workflow used for the discovery of EGFR-TKI resistance–associated biomarkers in lung ADC harboring EGFR mutations. A, Allotment and grouping of patients used in the discovery phase. MPE from ADC and PE from TB were divided into four groups: 11 MPEs with PR collected before treatment, eight MPEs with ongoing PD (TþC), four MPEs with ongoing PD (T), and 10 PEs with TB. The MPE and PE of each group were pooled and prepared for iTRAQ labeling. B, MPE and PE samples allotted as shown in (A) were used for proteomic analysis, which comprises prefractionation by the removal of high-abundance proteins, chemical labeling by iTRAQ, and 2D LC/MS-MS analysis. Differentially expressed proteins were selected by integrating the proteomic and genomic datasets. The cancer tissue, PE, and serum samples were included in the verification and validation phase via immunodetection methods. A survival analysis was applied to evaluate the clinical significance of the potential biomarkers. ADC, adenocarcinoma; (T), EGFR-TKI; (TþC), EGFR-TKI and chemotherapy; Tx, treatment.

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Table 1. Demographics of 329 patients used to detect sCDH3 Statistical analysis levels in serum via ELISA. All data were processed using SPSS 12.0 (SPSS, Inc.). All continuous variables are presented as mean SD. The nonparametric Mann– Healthy control ADC Non-ADC NSCLC Whitney U test or Student t test was used to compare the protein levels n ¼ n ¼ n ¼ Variable 57 206 66 in the serum between two groups. To compare more than two Sex continuous variables, one-way ANOVA was applied. Survival rates Female 26 (45.6%) 91 (44.2%) 10 (15.2%) were obtained using the Kaplan–Meier method and were compared Male 31 (54.4%) 115 (56.8%) 56 (84.8%) using the log-rank test via Prism software (GraphPad). A P value less Age 58.80 15.82 61.60 11.79 64.57 10.56 than 0.05 was considered statistically significant. Smoke No 42 (73.7%) 152 (73.8%) 16 (24%) Supplementary data Yes 15 (26.3%) 54 (26.2%) 50 (76%) Supplementary data for this article are available at Clinical Cancer Stage Research Online (http://clincancerres.aacrjournals.org/). Early 77 (37.4%) 21 (31.8%) Late 129 (62.6%) 45 (68.2%) EGFR status in late-stage ADC Results WT 53 (41.1%) Mutant 76 (58.9%) Generation of drug resistance–associated proteomic datasets from lung ADC MPE On the basis of the experimental design shown in Fig. 1, we depleted the abundant proteins from the four groups of PE samples with a identified proteins, the raw spectrometry data, including the reporter MARS affinity column. The depletion efficacy and differential protein ions quantifier node for iTRAQ, were analyzed using Proteome pattern of the fractionated PE samples were examined by SDS-PAGE Discoverer Software (version 1.4, Thermo Fisher Scientific). with silver staining (Supplementary Fig. S1). The PE proteins were digested and labeled with iTRAQ reagent followed by 2D LC/MS-MS. ELISA The reporter ion intensities of 114 (BT), 115 [PD(TþC)], 116 [PD(T)], The sCDH3 protein levels in PE or serum samples were determined and 117 (TB) represent the expression levels of the identified proteins with a Sandwich ELISA Kit according to the manufacturer's instruc- in each group of PE samples. Accordingly, 694 and 658 quantified tions (R&D Systems). The dilution factors used for PE and serum proteins with high-confidence identification were obtained from two samples in the ELISA were 1:50 and 1:25, respectively. The serum CEA independent analyses (Supplementary Fig. S2A). In total, 561 quan- level was detected with an ELISA Kit purchased from GenWay (GWB- tified proteins were repeatedly identified from the two independent BQK050) at a 1:3 dilution. All ELISAs were performed in duplicate for proteomics analyses. The reproducibility of protein quantification each sample. obtained from these two experiments was confirmed by Pearson correlation (Supplementary Fig. S2B). Detailed information for pro- Western blot analysis teins identified in duplicate experiments of four PE samples is shown in Proteins extracted from tissue samples were separated by SDS- Supplementary Table S1. To verify the differential protein levels in PAGE and transferred to polyvinylidene difluoride (PVDF) mem- these four PE groups, HGFAC and CDH3 were selected for quanti- branes. The CDH3 protein was detected using a monoclonal mouse fication by ELISA (Supplementary Table S2). We observed that the antibody (R&D Systems, MAB861) followed by incubation with a relative protein levels detected by ELISA were consistent with those horseradish peroxidase–conjugated secondary antibody and devel- obtained from our mass spectrometry analysis, supporting the reli- oped using a chemiluminescent substrate (Merck Millipore). ability of our proteomic datasets.

Cell culture and cell viability assay Selection of potential EGFR-TKI resistance–associated The PE089 cell line was derived from a female patient with advanced biomarkers ADC and an EGFR exon 19 deletion. This cell line was established To select potential EGFR-TKI resistance–associated biomarkers, 98 and kindly provided by Professor Ko-Jiunn Liu (National Institute of differentially expressed proteins with a 116/114 iTRAQ ratio greater Cancer Research, National Health Research Institutes, Tainan, Taiwan; than 1.5 were selected. By integrating these 98 candidates with 113 ref. 22). Cells were cultured in Minimum Essential Media (Invitrogen) malignancy-associated proteins (117/114 >1.5), we chose 15 proteins supplemented with 10% FBS under a humidified atmosphere of 95% for further analysis (Supplementary Fig. S3A). We next searched for fi air/5% CO2 at 37 C. Mycoplasma free in cell cultures was determined the gene expression pro les of these 15 candidate proteins based on the by DNA fluorochrome staining with Hoechst 33258 bisbenzimide. For public GEPIA dataset, and we gained seven candidates with a 1.5-fold CDH3 gene knockdown, 19-nucleotide RNA duplexes targeting increase at the mRNA level in tumor (T) tissue compared with normal human CDH3 were synthesized and annealed by Dharmacon (Thermo (N) lung tissues (Table 2; Supplementary Fig. S3B). Notably, CDH3 Fisher Scientific). Cells were transfected with a control siRNA and a was the most upregulated gene, with the highest T/N ratio of 11.34. We pooled siRNA targeting CDH3 (UGAAUCAGCUCAAGUCUAA; also found that six of these 15 candidate proteins, namely, CDH3, GUGACAACGUCUUCUACUA; GAAAUCGGCAACUUUAUAA; MET, CDH1, FAM3C, HSP90B1, and NPEPPS, exhibited high to and GAGGGUGUCUUCGCUGUAG) using Lipofectamine RNAi- moderate expression patterns in lung cancer tissues via IHC (Table 2). MAX Reagent (Invitrogen) according to the manufacturer's protocol. We then applied Western blot analysis to confirm that CDH3 was After 24 hours, the cells were reseeded into a 24-well plate with or indeed overexpressed in lung ADC tissues compared with their without gefitinib (Tocris), and a cell viability assay was performed using adjacent normal tissues (Fig. 2A). Consistent with our proteomic 3-(4,5-dimethylthiazol-2-yl)-2,5-diphenytetrazolium bromide colori- discovery, Western blot analysis revealed a differential level of sCDH3, metric growth assay as described previously (21). a protein band with an appropriate molecular weight of 80 kDa in

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Table 2. List of EGFR-TKI resistance–associated proteins identiﬁed in this study.

Protein name Gene symbol 116/114a 114/117a T/N mRNA ratiob Protein levelc

Cadherin-3 CDH3 5.84 1.62 11.34 þ Hepatocyte growth factor receptor MET 1.84 3.23 4.23 þ Cadherin-1 CDH1 1.67 1.88 4.11 þ Protein FAM3C FAM3C 2.03 1.69 1.53 þ Endoplasmin HSP90B1 1.64 1.5 1.42 þ Puromycin-sensitive aminopeptidase NPEPPS 2.45 2.02 0.78 þ Alpha-amylase 1 AMY1A 1.54 3.92 4.00 Fibrinogen beta chain FGB 3.21 1.87 3.67 Fibrinogen gamma chain FGG 3.73 2.09 2.21 Multiple EGF-like domains protein 8 MEGF8 1.95 2.01 0.84 Deleted in malignant brain tumors 1 protein DMBT1 11.24 2.28 0.54 Coagulation factor XIII A chain F13A1 2.21 1.77 0.47 Complement component C8 beta chain C8B 1.91 2.13 0.18 Apolipoprotein A-I APOA1 1.51 1.58 0.1 Apolipoprotein B-100 APOB 2.95 2.79 N.D.d a114, 115, 116, and 117 represent the reporter ions quantifier node for iTRAQ. bmRNA levels in tumor (T) and normal (N) tissues derived from the GEPIA database. cPlus symbol (þ) and minus symbol () represent proteins with and without high to moderate expression patterns (high þ medium > 50%) in lung cancerous tissues based on IHC results, respectively. This information was obtained from the Human Protein Atlas database. dThe fold change of mRNA levels in tumor and normal parts were unable to be estimated on the basis of GEPIA database. different groups of PE samples (Fig. 2B). Therefore, the combined showed that baseline sCDH3 was not correlated with sex, age, smoking database analysis allowed us to narrow down the biomarker candidates status, TKI response, or EGFR-TKIs. Consistent with these results, a efficiently, and sCDH3 was selected as our top priority for further high CDH3 level was significantly associated with fewer treatment validation. days (Table 3; P ¼ 0.036). These results suggest that the baseline sCDH3 level could be used as a marker for the early detection of Validation of serum sCDH3 as an early indicator of treatment treatment efficacy and for monitoring cancer progression in patients efficacy and a potential prognostic marker in patients with ADC with ADC with EGFR mutations. The baseline sCDH3 level can also be receiving EGFR-TKI–targeted therapy used to predict OS in all patients with ADC regardless of their EGFR To develop a noninvasive method for detecting the treatment gene mutation status. efficacy of EGFR-TKI as early as possible, we determined the serum levels of sCDH3 at baseline and 1 month after EGFR-TKI treatment Serum sCDH3 is positively associated with tumor stage and from 43 patients with ADC with EGFR mutations. Figure 2C shows poor OS in NSCLC that the serum levels of CDH3 in 28 PR patients were significantly To further explore the clinical application of baseline sCDH3 in reduced after EGFR-TKI treatment for 1 month (9.49 4.55 vs. 5.54 NSCLC diagnosis and prognosis, we detected baseline sCDH3 in the 2.67; P < 0.0001), but no significant change was observed in 15 non-PR sera from 200 additional individuals, including 57 healthy controls, 77 patients (15.43 16.74 vs. 15.6 20.24). Simultaneously, we observed patients with early-stage ADC, and 66 patients with non-ADC NSCLC a similar CEA level in these 28 PR patients' paired samples (Fig. 2D; (Table 1). The relationships between sCDH3 levels and clinical Supplementary Table S4). This result indicated that serum sCDH3 characteristics are summarized in Table 4. The sCDH3 levels were could be a potential marker for the early monitoring of EGFR-TKI higher in 272 patients with NSCLC than in 57 healthy controls (10.65 treatment efficacy. To test the potential role of CDH3 in EGFR-TKI 10.95 ng/mL vs. 6.63 2.84 ng/mL; P ¼ 0.0007). The sCDH3 levels resistance, we examined cell viability and EGFR-TKI sensitivity in in 174 patients with late-stage NSCLC were significantly higher than CDH3-knockdown PE089 cells, an ADC cell line with mutated EGFR those in 98 patients with early-stage NSCLC (12.91 12.10 ng/mL vs. (exon 19 deletion). CDH3 knockdown promoted EGFR-TKI sensi- 6.63 6.94 ng/mL; P < 0.001). The survival analysis showed that tivity (Fig. 2E; P ¼ 0.009), but it did not affect cell viability or the higher sCDH3 levels were significantly correlated with poorer OS phosphorylated AKT level in PE089 cells. Next, we performed a (Fig. 2H; P < 0.0001). The multivariable analysis further confirmed survival analysis to evaluate the prognostic significance of baseline that the sCDH3 level is an independent predictive factor of OS in sCDH3 in 76 patients with late-stage ADC harboring EGFR mutations. NSCLC (Supplementary Table S7). Consistent with these findings, the These 76 patients were stratified into two groups (high vs. low sCDH3 sCDH3 level was not associated with the PFS of patients with NSCLC level) using a protein concentration of 12 mg/mL as the cut-off value. who received chemotherapy (Supplementary Table S8). These results The survival analysis revealed that patients with a high serum sCDH3 collectively support the potential clinical applications of sCDH3 in level exhibited a shorter PFS than those with a low sCDH3 level (P ¼ NSCLC diagnosis and prognosis. 0.0220). Moreover, a high level of sCDH3 was significantly associated with poor OS (P ¼ 0.0408; Fig. 2F; Supplementary Table S5). Notably, we also observed that the baseline serum sCDH3 level in 53 patients Discussion with late-stage ADC with wild-type (WT) EGFR and undergoing Previously, we used a high-abundance protein removal system chemotherapy was associated with OS (P ¼ 0.0093) but not PFS (P combined with a gel-based and label-free proteomic analysis to ¼ 0.1566; Fig. 2G; Supplementary Table S6). The statistical analysis identify 363 common PE proteins in all six types of exudative PEs

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Figure 2. Validation of serum sCDH3 as an early indicator of treatment efficacy and a potential prognostic marker in patients with ADC receiving EGFR-TKI–targeted therapy. A, CDH3 was overexpressed in lung ADC tissues. Proteins from lung ADC tissues (pooled samples from 2 or 3 patients) and their adjacent normal tissues were prepared and subjected to Western blot analysis using an anti-CDH3 antibody. Actin was used as a loading control. E, early-stage; L, late-stage; N, adjacent normal; T, tumor. B, Detection of sCDH3 in PE samples via Western blot analysis. The crude and pooled MPE or PE samples used in the discovery phase were subjected to SDS-PAGE, transferred to PVDF membranes, and stained with Fast Green FCF dye as a loading control (left). The proteins were then detected with an anti-CDH3 antibody. , albumin in crude PEs. C and D, Validation of sCDH3, but not CEA, as an early indicator of EGFR-TKI efficacy by ELISA. Serum samples were collected prior to EGFR-TKI treatment (before treatment, BT) and approximately 1 month (298 days) after treatment (AT). Compared with baseline, sCDH3 was significantly decreased in PR patients (n ¼ 28) but not non-PR (n ¼ 15) patients. The CEA level was not correlated with treatment efficacy. (Continued on the following page.)

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Table 3. Relationships between baseline sCDH3 serum levels and recognized as key mechanisms underlying acquired resistance to clinical characteristics in 129 patients with late-stage ADC. EGFR-TKIs (25). Notably, soluble MET and soluble cadherin-1 (CDH1) in the serum have been reported as lung cancer biomarkers a Variable Number sCDH3 (ng/mL) P by us and others (19, 26). MUC1 was recently identified as an effective Sex sensor for monitoring the effects of erlotinib treatment (27). Consis- Female 64 13.34 14.89 0.341 tent with this observation, we also detected an increase in the MUC1 Male 65 14.22 12.09 level (1.44-fold; Supplementary Table S1) in patients resistant to first/ Age second-generation EGFR-TKIs. This study verified and validated <60 62 12.71 15.54 0.241 sCDH3 as a novel biomarker of EGFR-TKI resistance in MPE, and ≥60 67 11.93 11.90 serum samples further supported the utility of our proteome datasets Smoke for the prediction, monitoring, and prognosis of patients with lung No 90 14.01 11.33 0.390 ADC with targeted therapy. Yes 39 13.26 17.69 CDH3, encoded by the CDH3 gene, is a classical cadherin expressed Treatment fi EGFR-TKI 76 12.84 7.71 0.663 in epithelial cells and was rst found in the mouse placenta in Chemotherapy 53 15.14 18.97 1986 (28). It has been reported that CDH3 is involved in the main- EGFR-TKI response tenance of tissue architecture, organ morphogenesis, cell differentia- PR 54 13.01 7.49 0.481 tion, cellular movement, and stem cell biology (29–31). Several studies Non-PR 22 12.43 8.41 have proposed that CDH3 acts as an oncogene and a tumor suppressor EGFR-TKI drug gene, in which its role in oncogenesis is cell content and cancer type b Gefitinib 44 12.44 6.65 >0.05 dependent (30). CDH3 overexpression is detected in breast, ovarian, > b Erlotinib 23 11.81 7.30 0.05 prostate, endometrial, skin, gastric, and pancreatic cancers. However, Afatinib 9 17.43 12.08 >0.05b CDH3 is downregulated in oral squamous cell carcinoma, melanoma, TKI treatment days <1 year 40 14.53 8.65 0.036c and hepatocellular carcinoma. Both the oncogenic and suppressive ≥1 year 36 10.91 6.03 roles of CDH3 in one particular cancer type have also been fi Chemotherapy observed (30, 32). Speci cally, a tumor suppressive role of CDH3 in PR 18 10.70 5.33 0.241 lung cancer was proposed according to an IHC analysis of 28 NSCLC Non-PR 35 17.42 22.81 cancer tissues in 1999 (33). Recently, Imai and colleagues reported that Chemotherapy treatment days CDH3 was overexpressed in NSCLC tissues and correlated with a poor <180 days 35 17.59 22.88 0.280 prognosis in NSCLC (32). The discrepancy regarding the role of CDH3 ≥180 days 18 10.42 4.24 in these two NSCLC-related studies might have resulted from the different histologic types, subcellular localizations, and even antibodies aMann–Whitney U test. fi b used in the IHC analysis. Importantly, we herein identi ed sCDH3 as One-way ANOVA. – cA P value less than 0.05 indicates significance based on Mann-Whitney U test. an EGFR-TKI resistance associated biomarker via MS-MS, a highly accurate protein identification method based on unique peptide sequences. The specificity of the antibodies used in this study was (TB, pneumonia, lung ADC paramalignant PE, lung ADC MPE, breast also confirmed via Western blot analysis using lung cancer tissues and cancer MPE, and gastric cancer MPE; ref. 19). Taking advantage of the PE089 cell line with CDH3 gene knockdown (Fig. 2). We further isobaric labeling–based quantification methodology used for unbiased provide evidence that CDH3 is overexpressed in ADC cancer tissues untargeted biomarker discovery, this study established, for the first and that baseline sCDH3 is positively associated with late-stage cancer time, a PE proteome with 561 reproducibly quantified proteins related and OS in patients with NSCLC regardless of their EGFR gene status. to first/second-generation EGFR-TKI resistance from four groups of Therefore, we herein propose an oncogenic role for CDH3 in ADC PEs via high-abundance protein depletion technology combined with progression. þ an iTRAQ-based quantitative proteomics approach. To the best of our CDH3 is a Ca2 -dependent cell–cell adhesion glycoprotein com- knowledge, this is the most comprehensive quantitative PE dataset. prised of five extracellular cadherin repeats, a transmembrane region, Mundt and colleagues identified 386 overlapping proteins in two and a highly conserved cytoplasmic tail. It is well documented that pooled PE samples from three types of PEs (lung ADC, malignant both matrix metalloproteases (MMP) and metalloendopeptidases mesothelioma, and benign mesothelioma; ref. 23). Recently, Shi and (ADAM) are involved in the shedding of the ectodomains of mem- colleagues identified 432 proteins from lung MPE and TB (24). We brane-anchored growth factors, cytokines, and receptors (34). The herein integrated genomic and proteomic approaches to identify 15 extracellular cleavage and shedding of CDH3 is regulated by MMPs potential EGFR-TKI resistance–associated protein markers. MET such as MMP-1 and MMP-2 in breast cancer cells (35). The sCDH3 amplification, MET protein hyperactivation, and MET mutation are level was significantly increased in patients with late-stage NSCLC with

(Continued.) N.S., not significant; , P value less than 0.0001 indicates significance based on the paired t test. E, CDH3 knockdown promoted gefitinib sensitivity in PE089 cells. PE089 cells were transfected with control siRNA or CDH3 siRNA. After 24 hours, cells were reseeded onto a 12-well plate and subjected to Western blot analysis at different time points to examine gene knockdown efficacy. Simultaneously, cells were subjected to a viability assay via the colorimetric growth method. EGFR-TKI sensitivity was determined after incubation with gefitinib for 5 days. F and G, A high baseline level of sCDH3 was positively associated with poor PFS in patients with lung ADC receiving EGFR-TKI–targeted therapy. The serum sCDH3 levels obtained from the ELISA were used to perform the survival analysis of 76 patients with ADC with EGFR mutations who received EGFR-TKI therapy (F) and 53 patients with ADC with EGFR WT who received chemotherapy (G). H, A high baseline sCDH3 level was significantly associated with poor OS in patients with NSCLC. The serum sCDH3 levels obtained from the ELISA were used to perform the survival analysis of 272 patients with NSCLC. The patients were stratified into two groups (high vs. low CDH3 level) using a protein concentration of 12 mg/mL as the cut-off value (F–H). P < 0.05 obtained from the log-rank test indicated statistical significance.

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Table 4. Relations between baseline sCDH3 serum levels and expression from CDH1 to CDH2 and/or CDH3, is a hallmark of EMT clinical characteristics in 57 healthy controls and 272 patients with in certain types of cancer (e.g., prostate, ovarian, and bladder cancers; NSCLC. ref. 41). The relationship between CDH3- and EMT-related genes is complicated and even controversial in different types of cancer. a Variable Number CDH3 (ng/mL) P Overexpression of the mesenchymal markers SNAI2 (also known as Sex Slug) and ZEB1 represses CDH1 expression, promoting the migration Female 156 9.31 10.96 0.292 of melanoma cells, but decreases adhesion to human keratinocytes. Male 173 10.53 9.32 SNAI2 overexpression also suppresses CDH3 expression (42). Inter- Age estingly, SNAI2 is a direct transcriptional activator at the ZEB1 <60 143 9.50 8.58 0.939 promoter (43), indicating that SNAI2 and ZEB1 cooperatively regulate ≥60 186 10.30 11.20 the EMT process by suppressing the expression of CDH1 and/or Smoke CDH3 in melanoma cells. However, CDH3 overexpression promotes No 210 9.69 9.18 0.065 the expression of three members of the Snail family (SNAI1, SNAI2, Yes 119 10.42 11.67 and SNAI3) and ZEB1 but does not regulate the level of TWIST1 or Healthy vs. NSCLC Healthy control 57 6.63 2.84 0.0007 vimentin in oral squamous carcinoma SCC22A cells (37). In this study, NSCLC 272 10.65 10.95 CDH3 knockdown induced the expression of the epithelial marker Lung cancer histology CDH1, but also the expressions of mesenchymal marker ZEB1 and Healthy 57 6.63 2.84 SNAI2 in lung ADC cells (Supplementary Fig. S4). These findings NSCLC–non ADC 66 9.85 7.24 <0.05b suggest that the role of CDH3 in the modulation of EMT remains an ADC 206 10.90 11.90 <0.01c object of debate. On the other hand, EMT is strongly associated with Cancer stage acquired resistance to EGFR-TKIs (44). Recent studies provide Healthy 57 6.63 2.84 evidence that EMT is a mechanism for escape from EGFR- Early stage (stage I/II) 98 6.63 6.94 <0.001d targeted therapy in lung cancer (45). Furthermore, both EMT and Late stage (stage III/IV) 174 12.91 12.10 <0.001e resistance to the EGFR-TKI erlotinib are associated with over- aThe data are presented as the mean SD. expression of the mesenchymal marker AXL (46), supporting bThe P value represents the difference between healthy controls and patients a positive correlation between a high level of sCDH3 and a poor out- with NSCLC–non ADC. come in EGFR-mutated patients treated with first/second-generation cThe P value represents the difference between healthy controls and patients EGFR-TKIs. with ADC. The clinical significance of and novel oncogenic molecular path- d The P value represents the difference between patients with early-stage and ways mediated by CDH3 are partially uncovered, providing the basis late-stage cancer. eThe P value represents the difference between healthy controls and patients for the development of personalized medicine targeting CDH3 in with late-stage cancer. invasive and/or metastatic diseases, including certain types of human cancer (30, 47). For example, the fully humanized anti-CDH3 (P-cadherin) IgG1 mAb PF-03732010 (48), the extended half-life or without EGFR mutations (Table 3). However, the sCDH3 level was dual-affinity retargeting bispecific molecule against CDH3 and CD3 associated with the PFS of patients with ADC receiving EGFR-TKI (PF-06671008; ref. 49), and the yttrium Y 90 anti-CDH3 mAb FF- therapy but not chemotherapy, supporting a specific role for CDH3 in 21101 (50) were developed to overcome CDH3-mediated pathogen- EGFR-TKI resistance (Fig. 2). Although a proinvasive role of sCDH3 esis, and these antibody-based inhibitors of CDH3 are currently in in breast cancer has been reported (35, 36), this study, for the first time, clinical trials. CDH3 knockdown enhanced gefitinib sensitivity, but reports the clinical significance of CDH3 in EGFR-TKI resistance CDH3 knockdown did not reduce cell viability or AKT activity in and NSCLC. CDH3 cross-talks with EGFR through the ligand- PE089 lung ADC cells (Fig. 2), supporting the theory that CDH3 may dependent signaling of EGFR and overexpressed CDH3 may prolong act as a novel regulator in EGFR-TKI resistance. Our future work will activation of the MAP and AKT signaling pathways in certain types of focus on the underlying mechanism of CDH3 in EGFR-TKI resistance cancer cells (30, 37). Notably, a disintegrin and metalloproteinase-17 and the potential application of targeting CDH3 to overcome the (ADAM17) is involved in the cleavage of the ectodomain of EGFR EGFR-TKI resistance in the clinic. ligandssuchasamphiregulin,TGFa, and EGF. ADAM17 plays an The limitation to this study is the lack of complete information on undisputable role in ADC oncogenesis and has been recognized as the T790M mutational status of patients with ADC recruited between the center of EGFR signaling (38). Although CDH3 and EGFR 2009 and 2016. Nine of 76 patients (7 PR and 2 non-PR) were ligands are processed by MMPs and ADAM17, respectively, these diagnosed with T790M-positive advanced ADC, and the serum levels two types of metalloproteinases are significantly dysregulated and of sCDH3 in 7 PR patients with the T790M mutation were significantly contribute to lung cancer invasion. Interestingly, high levels of reduced after EGFR-TKI treatment for 1 month (9.68 4.42 vs. 5.40 amphiregulin and TGFa in the serum predict a poor response to the 2.12, P ¼ 0.0043), but no significant change was observed in 2 non-PR EGFR-TKI gefitinib in patients with advanced NSCLC (39), sug- patients (7.78 2.13 vs. 6.22 3.42). Future work will be interesting gesting potential interplay between MMPs and ADAM17 in the and necessary to investigate the potential application of sCDH3 in modulation of EGFR-mediated lung cancer progression and EGFR- monitoring the efficacy of osimertinib and even the T790M mutation TKI resistance. in advanced ADC. Epithelial–mesenchymal transition (EMT), a temporary and revers- In conclusion, our study established a comprehensive quantitative ible phenomenon in which adherent epithelial cells undergo morpho- PE proteome useful in EGFR-TKI resistance studies, and we validated logic changes accompanied by a gain in migratory capacity and serum sCDH3 as a potentially novel biomarker for monitoring EGFR- invasion and vice versa, is a critical process in cancer metastasis (40). TKI resistance. We also show the diagnostic and prognostic value of Cadherin switching, a process in which cells shift cadherin isoform baseline sCDH3 in NSCLC. Together, our studies provide a new

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sCDH3 is an EGFR-TKI Resistance-Associated Serum Biomarker

prospect for classic cadherin CDH3 and for its clinical application. Study supervision: C.-L. Wang, C.-J. Yu Further investigations of sCDH3 and CDH3 should focus on its drug- Other (mass spectrometric data acquisition): K.-Y. Chien resistant molecular mechanisms in detail. Acknowledgments Disclosure of Potential Conflicts of Interest This work was financially supported by grants from Chang Gung Memorial Hospital (Taoyuan, Taiwan; CORPD1J0091, CMRPD1H0641-2, CMRPD1H0081-3, No potential conflicts of interest were disclosed. and BMRP894 to C.-J. Yu; CMRPG3A0661 to C.-L. Wang; and CLRPD190019); the ’ Ministry of Science and Technology, Taiwan (105-2320-B-182-035-MY3 and 108- Authors Contributions 2320-B-182-007-MY3 to C.-J. Yu); the Molecular Medicine Research Center, Chang Conception and design: T.-F. Hsiao, C.-L. Wang, H.-Y. Lin, C.-J. Yu Gung University (Taoyuan, Taiwan); and The Featured Areas Research Center Development of methodology: T.-F. Hsiao, H.-Y. Lin Program within the framework of the Higher Education Sprout Project by the Acquisition of data (provided animals, acquired and managed patients, provided Ministry of Education, Taiwan. facilities, etc.): T.-F. Hsiao, C.-L. Wang, Y.-C. Wu, Y.-C. Chiu, K.-J. Liu, G.-C. Chang, K.-Y. Chien, J.-S. Yu Analysis and interpretation of data (e.g., statistical analysis, biostatistics, The costs of publication of this article were defrayed in part by the payment of page computational analysis): T.-F. Hsiao, C.-L. Wang, H.-P. Feng, Y.-C. Chiu, charges. This article must therefore be hereby marked advertisement in accordance H.-Y. Lin, C.-J. Yu with 18 U.S.C. Section 1734 solely to indicate this fact. Writing, review, and/or revision of the manuscript: T.-F. Hsiao, C.-L. Wang, C.-J. Yu Administrative, technical, or material support (i.e., reporting or organizing data, Received December 4, 2019; revised February 4, 2020; accepted March 5, 2020; constructing databases): C.-L. Wang, Y.-C. Wu, J.-S. Yu, C.-J. Yu published first March 10, 2020.

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OF10 Clin Cancer Res; 2020 CLINICAL CANCER RESEARCH

Integrative Omics Analysis Reveals Soluble Cadherin-3 as a Survival Predictor and an Early Monitoring Marker of EGFR Tyrosine Kinase Inhibitor Therapy in Lung Cancer

Ting-Feng Hsiao, Chih-Liang Wang, Yi-Cheng Wu, et al.

Clin Cancer Res Published OnlineFirst March 10, 2020.

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