Rationale and feasibility of mucin expression profiling by qRT-PCR as diagnostic biomarkers in cytology specimens of pancreatic cancer

Rationale and feasibility of mucin expression profiling by qRT-PCR as diagnostic biomarkers in cytology specimens of pancreatic cancer

Pancreatology xxx (2018) 1e6 Contents lists available at ScienceDirect Pancreatology journal homepage: www.elsevier.com/locate/pan Rationale and fe...

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Pancreatology xxx (2018) 1e6

Contents lists available at ScienceDirect

Pancreatology journal homepage: www.elsevier.com/locate/pan

Rationale and feasibility of mucin expression profiling by qRT-PCR as diagnostic biomarkers in cytology specimens of pancreatic cancer Milosz Wiktorowicz a, Damian Mlynarski b, Radoslaw Pach a, Romana Tomaszewska b, Jan Kulig a, Piotr Richter a, Marek Sierzega a, * a b

First Department of Surgery, Jagiellonian University Medical College, Krakow, Poland Department of Pathology, Jagiellonian University Medical College, Krakow, Poland

a r t i c l e i n f o

a b s t r a c t

Article history: Received 2 March 2018 Received in revised form 18 September 2018 Accepted 24 September 2018 Available online xxx

Background: Aberrantly expressed mucin glycoproteins (MUC) play important roles in pancreatic ductal adenocarcinoma (PDAC), yet their use as a diagnostic aid in fine-needle aspiration biopsy (FNAB) is poorly documented. The aim of this study was to investigate the rationale and feasibility of mucin (MUC1, MUC2, MUC3, MUC4, MUC5AC, and MUC6) expression profiling by RT-PCR for diagnostic applications in cytology. Methods: Mucin expression was examined by RT-PCR and immunohistochemistry in specimens resected from patients with pancreatic (n ¼ 101), ampullary (n ¼ 23), and common bile duct (n ¼ 10) cancers and 33 with chronic pancreatitis. Furthermore, mucin profiling by RT-PCR was prospectively compared in surgical and biopsy specimens of 40 patients with pancreatic solid tumours qualified for FNAB prior to surgery. Results: A logistic regression model to distinguish PDAC from chronic pancreatitis using RT-PCR profiling included MUC3, MUC5AC, and MUC6. The same set of mucins differentiated ampullary and bile duct cancers from chronic pancreatitis. AUCs for the ROC curves derived from the two models were 0.95 (95% CI 0.87e0.99) and 0.92 (95%CI 0.81e0.98), respectively. The corresponding positive likelihood ratios were 6.02 and 5.97, while the negative likelihood ratios were 0.10 and 0.12. AUCs of ROC curves obtained by RT-PCR and immunohistochemistry demonstrated that both analytical methods were comparable. Surgical and cytological samples showed significantly correlated values of DCt for individual mucins with the overall Pearson's correlation coefficient r ¼ 0.841 (P ¼ 0.001). Conclusions: Mucin expression profiling of pancreatic cancer with RT-PCR is feasible and may be a valuable help in discriminating malignant lesions from chronic pancreatitis in FNAB cytology. © 2018 Published by Elsevier B.V. on behalf of IAP and EPC.

Keywords: Pancreatic cancer Chronic pancreatitis Mucins Diagnosis Fine needle aspiration biopsy

Introduction The differential diagnosis of pancreatic ductal cell adenocarcinoma (PDAC) from other malignancies and chronic pancreatitis is sometimes troublesome as all of these conditions may demonstrate similar symptoms and imaging features [1,2]. Although the requirement for tissue diagnosis of a potentially resectable pancreatic mass remains controversial, tumour sampling for cytology is considered when the information obtained may potentially affect clinical decision making [3]. The latter situation is

* Corresponding author. First Department of Surgery, 40 Kopernika Street, 31501, Krakow, Poland. E-mail address: [email protected] (M. Sierzega).

especially relevant for high-risk surgical patients with a pancreatic tumour of undeterminable type or those requiring diagnosis of malignancy before neoadjuvant or palliative therapy [4,5]. Fineneedle aspiration biopsy (FNAB) has an established role in differentiating PDAC from other neoplasms (e.g. neuroendocrine tumours or lymphoma) as well as non-malignant conditions. However, relatively low negative predictive values of 27e80% markedly limit its ability to definitely rule out malignancy in some cases [6,7]. Human mucin glycoproteins (MUC), characterized by the presence of O-glycosylated tandem repeat regions, are encoded by a family of 21 genes for either secreted mucins (e.g. (MUC2, MUC5AC, MUC6) or membrane bounded mucins (e.g. MUC1, MUC3, MUC4) [8]. Both types of glycoproteins are not only the main components of mucus secreted by epithelial cells, but also participate in various

https://doi.org/10.1016/j.pan.2018.09.008 1424-3903/© 2018 Published by Elsevier B.V. on behalf of IAP and EPC.

Please cite this article in press as: Wiktorowicz M, et al., Rationale and feasibility of mucin expression profiling by qRT-PCR as diagnostic biomarkers in cytology specimens of pancreatic cancer, Pancreatology (2018), https://doi.org/10.1016/j.pan.2018.09.008

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biological processes, like regulation of cell growth and proliferation, differentiation, and apoptosis. Therefore, aberrantly expressed mucins play an important role in the development and progression of various malignancies, including PDAC [9]. Several previous studies demonstrated that pancreatic cancer is associated with a high expression of MUC1, MUC4 and MUC5AC along with diminished levels of MUC2 [10e13]. Recently, we have demonstrated that semiquantitative immunohistochemical evaluation of three mucins (MUC3, MUC5AC, MUC6) offered promising ability to discriminate pancreatic cancer from non-malignant pancreatic tissue [14]. Therefore, mucin profiling may be of assistance in distinguishing malignant lesions from chronic pancreatitis and decrease the odds of false-negative cytology obtained with FNAB [1,15]. However, most previous studies used only immunohistochemistry (IHC) in surgical specimens from resected lesions. This may be of limited importance for FNAB where the amount of tissue sampled could be insufficient for several IHC staining reactions required for comprehensive mucin profiling. Quantitative real-time PCR (RTPCR) may be an alternative in these situations, but there are very few studies evaluating the feasibility of such a diagnostic approach. Moreover, it is not known if mucin profiling in FNAB specimens by RT-PCR corresponds to their expression at the protein level. The aim of this study was to investigate the rationale of mucin expression profiling by RT-PCR in patients with pancreatic, ampullary, and common bile duct cancers and the feasibility of mucin detection in tissue samples obtained by FNAB from patients with pancreatic tumours. Patients and methods Patients and procedures An electronic database of all patients undergoing pancreatic resections between 2007 and 2010 at our academic tertiary surgical centre was reviewed to select cases for experiments evaluating mucin expression in pancreatic, ampullary and common bile duct cancers. Relevant data, including demographics, clinical findings, details of surgical procedures, and histopathological parameters, were collected prospectively by a pancreatic research fellow (M.S.) using standardized forms and stored in a dedicated electronic database. Tumour typing and staging were adapted to the recent guidelines (D.M., R.T.) [16,17]. For experiments comparing mucin profiling by RT-PCR in surgical and biopsy specimens, a group of 40 consecutive patients with pancreatic solid tumours qualified for FNAB prior to surgery was prospectively recruited between 2012 and 2014. All biopsies were carried out using Chiba type needles (19.5G) by three surgeons acquainted with US-guided abdominal biopsies and a caseload of about 100 per year. Corresponding tissue samples were collected intraoperatively after tumour resection. The study was approved by the Bioethics Committee of Jagiellonian University and all participants gave their informed consent (KBET/4/B/2009). Immunohistochemistry Expression of six mucins (MUC1, MUC2, MUC3, MUC4, MUC5AC, and MUC6) was determined in formalin-fixed, paraffinembedded (FFPE) samples by immunohistochemistry, as previously described [14]. Briefly, 5 mm tumour sections were deparaffinised, rehydrated, and subjected to epitope retrieval by microwaving, followed by endogenous peroxidase blocking. IHC staining was carried out using the following primary mouse monoclonal antibodies (Santa Cruz Biotechnology Inc., Dallas, Texas): mucin 1 (clone B413, dilution 1:50), mucin 2 (clone H-300, dilution 1:100), mucin 3 (clone SPM200, dilution 1:100), mucin 4

(clone 1G8, dilution 1:200), mucin 5AC (clone CLH2, dilution 1:50), mucin 6 (clone CLH5, dilution 1:100). After incubation for 90 min, slides were exposed to biotinylated secondary antibodies (EnVision™þ System, Dako Denmark A/S) and immunostaining was visualized with AEC Substrate-Chromogen (Dako Denmark A/ S), containing 3-amino-9-ethylcarbazole. Samples of colorectal cancer (mucin 1, 3, 4), ileal cancer (mucin 2) and gastric cancer (mucin 5AC, 6) with known expression of the evaluated proteins were used as positive controls. The same procedure including all the aforementioned stages except primary antibodies was used as a negative control. Two pathologists, experienced with IHC and mucin family proteins staining patterns, blinded to the clinical characteristics and outcomes data assessed all slides. Final decisions regarding the percentage of positive cells and intensity of staining were made by consensus. A quickscore (QS, range 0e300) was calculated by multiplying staining intensity (0 e no staining, 1 e weak staining, 2 e moderate staining, 3 e intense staining) and the percentage of positive cells (0e100) over 10 representative high-power fields (40  magnificantion) [18,19]. Sample preparation and mRNA extraction Four 10 mm-thick unstained FFPE sections corresponding to tumour samples subject to IHC were cut and mounted on coated slides. The tissue sections were submerged in 70% ethanol and the surrounding non-tumorous tissue was discarded after microscopic evaluation. Fresh tissue samples obtained from surgical specimens and FNAB were immediately transferred to RNAlater stabilization solution (Thermo Fisher Scientific). Total RNA was extracted from FFPE and fresh samples using dedicated RNeasy RNA Isolation Kits (Qiagen) according to the manufacturer's instructions. Isolated RNA was eluted in RNase-free water, and stored at 80  C. RNA concentrations were measured with NanoDrop (Thermo Fisher Scientific) and quality was determined by RNA integrity number (RIN) using Agilent Bioanalyser (Agilent Technologies). Mucin profiling by RT-PCR Mucin mRNA was examined using SYBR® green-based quantitative real-time PCR assays (SABiosciences). A fixed volume (1 mL corresponding to 500 ng) of total RNA was reverse transcribed using RT2 First Strand Kit (SABiosciences) in a total volume of 20 mL with the following conditions: 42  C for 15 min and 95  C for 5 min. Real-time PCR was conducted using the following primers (SABiosciences): MUC1 (Unigene Hs.89603), MUC2 (Hs.315), MUC3 (Hs.489354), MUC4 (Hs.369646), MUC5AC (Hs.534332), and MUC6 (Hs.528432). All reactions were performed in triplicate on the MiniOpticon system (Bio-Rad) with the following cycling conditions: 95  C for 10 min, followed by 45 cycles of 95  C for 15 s, 55  C for 40 s, and 72  C for 30 s. Expression levels of mucin mRNAs were determined by the DCt method. The candidate reference genes were evaluated in a pilot study where 16 FFPE samples were profiled with the Human Housekeeping Genes RT2 Profiler™ PCR Array (SABiosciences) containing twelve commonly used housekeeping genes. Subsequently, the geNorm algorithm identified GAPDH (Hs.592355) as the most stable reference gene used in further experiments. Researchers performing PCR experiments were blinded to the clinical characteristics and outcomes data. Statistical analysis Receiver operating characteristics (ROC) curves were constructed to determine the optimum cut-off value of mucin QS and

Please cite this article in press as: Wiktorowicz M, et al., Rationale and feasibility of mucin expression profiling by qRT-PCR as diagnostic biomarkers in cytology specimens of pancreatic cancer, Pancreatology (2018), https://doi.org/10.1016/j.pan.2018.09.008

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Table 1 Baseline characteristics of the patients. Variable

Retrospective phase (n ¼ 167)

Prospective phase (n ¼ 40)

Gender (female: male) Age, median (IQR) yrs Final diagnosis, n (%) pancreatic cancer cancer of the ampulla of Vater pancreatobiliary phenotype other phenotype common bile duct cancer chronic pancreatitis Differentiation*, n (%) good or moderate poor Primary tumour (T, AJCC 2010)*, n (%) T1 T2 T3 T4 Lymph nodes (N, AJCC 2010)*, n (%) N0 N1 Tumour staging (N, AJCC 2010)*, n (%) I II III IV

71:96 59 (46e67)

29:11 62 (51e69)

101 (60) 23 (14) 16 7 10 (6) 33 (20)

30 (75) 0 (0) 0 0 0 (0) 10 (25)

94 (70) 40 (30)

16 (53) 14 (47)

4 (3) 13 (10) 99 (74) 18 (13)

0 (0) 2 (7) 28 (93) 0 (0)

58 (43) 76 (57)

9 (30) 21 (70)

13 89 22 10

2 (7) 28 (93) 0 (0) 0 (0)

(10) (67) (16) (7)

AJCC e American Joint Committee on Cancer 7th edition; IQR, interquartile range *only malignant tumours.

DCt mRNA for the differential diagnosis of PDAC and other malignancies from chronic pancreatitis. The statistical significances of the differences in QS and AUC of ROC curves were analysed by the ManneWhitney U test. A logistic regression model with backward stepwise selection was developed to evaluate the preferred mucin profile for discrimination of malignant lesions and chronic pancreatitis. The probability for entering the model was 0.05 and for removal from the model 0.100. The diagnostic performance of the final model was evaluated by ROC analysis. Statistical analysis was performed using the PASW Statistics 21 software package (IBM, Chicago, IL, USA). A two-tailed, exact P value < 0.05 was considered statistically significant.

there was a significant heterogeneity in the mucin staining pattern related to the primary pathology. Median values for QS are summarized in Table 2 and Supplementary Table 1. Compared to chronic pancreatitis, PDAC demonstrated significantly higher values for MUC1 and MUC5AC, while those for MUC3 and MUC6 were significantly lower. Ampullary cancers were characterized by higher QS values for MUC4 and MUC5AC than in chronic pancreatitis along with lower values for MUC3 and MUC6. Similar differences were observed for common bile duct cancers.

Results

Values of DCt for individual mucins (Table 3) were used to estimate ROC curves differentiating malignant lesions from chronic pancreatitis (Fig. 1) and Table 4 summarizes sensitivity and specificity for these assays. As there were no significant differences in mucin expression patterns between ampullary and common bile duct cancers, both tumour types were pooled together for further comparisons with chronic pancreatitis (Supplementary Table 2). To determine correlations between mucin expression at the mRNA and protein levels, AUCs of ROC curves obtained by IHC and RT-PCR were compared as summarized in Table 5. For all analysed mucins the values obtained by both analytical methods were comparable. The optimum set of mucins required to distinguish PDAC and other neoplasms from inflammatory lesions was determined with a stepwise logistic regression model. A statistically relevant model

Study population For the retrospective study a group of 167 patients were retrieved, including PDAC (n ¼ 101), ampullary cancer (n ¼ 23), distal bile duct cancer (n ¼ 10), and chronic pancreatitis (n ¼ 33). The prospective phase recruited 40 patients with the final diagnosis of PDAC (n ¼ 30) and chronic pancreatitis (n ¼ 10). Clinical and demographic data of the selected population are summarized in Table 1. Immunohistochemistry Except MUC2, where most patients showed weak staining,

Mucin profiling by RT-PCR

Table 2 Pattern of mucin expression by immunohistochemical Quickscore.

MUC1 MUC2 MUC3 MUC4 MUC5AC MUC6 a

Pancreatic cancer (n ¼ 101)

Ampullary cancer (n ¼ 23)

Common bile duct cancer (n ¼ 10)

Chronic pancreatitis (n ¼ 33)

300 (270e300)a 0 (0e15) 15 (0e60)a 150 (80e210) 180 (90e270)a 30 (3e120)a

300 (240e300) 10 (0e60) 50 (40e120)a 180 (80e240)a 150 (30e270)a 60 (10e120)a

300 (300-300)a 10 (0e15) 35 (10e60)a 210 (160e300)a 210 (100e300)a 135 (40e240)a

270 (270e270) 2 (0e30) 100 (70e160) 120 (60e180) 50 (30e90) 180 (150e240)

ManneWhitney U test P < 0.01 compared to chronic pancreatitis; Quickscore is reported as median (interquartile range).

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Table 3 Pattern of RT-PCR mucin expression by DCt.

MUC1 MUC2 MUC3 MUC4 MUC5AC MUC6 a

Pancreatic cancer (n ¼ 101)

Ampullary cancer (n ¼ 23)

1.80 (1.80e1.85)a 10.00 (4.43e10.00) 4.43 (2.92e10.00)a 2.21 (2.00e2.67) 2.09 (1.85e2.58)a 3.59 (2.37e7.18)a

1.80 5.00 3.08 2.09 2.21 2.92

(1.80e1.92)a (2.92e10.00) (2.37e3.29)a (1.92e2.67) (1.85e3.59)a (2.37e5.00)a

Common bile duct cancer (n ¼ 10) 1.80 5.00 3.44 2.01 2.03 2.89

(1.80e1.80)a (4.43e10.00) (2.92e5.00)a (1.80e2.17)a (1.80e2.50)a (2.32e3.29)a

Chronic pancreatitis (n ¼ 33) 1.85 8.12 2.50 2.37 3.08 2.09

(1.85e1.95) (3.59e10.00) (2.17e2.78) (2.09e2.92) (2.58e3.59) (1.92e2.21)

ManneWhitney U test P < 0.01 compared to chronic pancreatitis; DCt is reported as median (interquartile range) and calculated as Ctmucin e CtGAPDH.

helpful to distinguish PDAC from chronic pancreatitis included MUC3 (OR 0.43, 95% CI 0.28e0.65, P ¼ 0.001), MUC5AC (OR 1.69, 95% CI 1.20e2.37, P ¼ 0.003), and MUC6 (OR 0.54, 0.38e0.78, P ¼ 0.001). The model required to identify other neoplasms included the same set of mucins, i.e. MUC3 (OR 0.42, 95% CI 0.23e0.76, P ¼ 0.004), MUC5AC (OR 1.85, 95% CI 1.17e2.92, P ¼ 0.008), and MUC6 (OR 0.54, 0.38e0.78, P ¼ 0.004). AUCs for the ROC curves derived from the two models were 0.95 (95% CI 0.87e0.99) and 0.92 (95% CI 0.81e0.98), respectively (Fig. 2). The corresponding positive likelihood ratios of both models were 6.02 and 5.97, while the negative likelihood ratios were 0.10 and 0.12, respectively. Mucin profiling in FNAB and surgical specimens The amount of RNA isolated from surgical specimens (18.2 ± 9.3 mg) was significantly higher than for FNAB (5.7 ± 2.4 mg, P ¼ 0.001). However, the quality of RNA was similar in terms of OD 260/280 (2.1 ± 0.02 vs 2.0 ± 0.08), OD 260/230 (1.94 ± 0.31 vs 1.96 ± 0.29), and RNA integrity number (6.9 ± 0.4 vs 6.7 ± 0.5). Moreover, values of DCt for individual mucins were significantly correlated between surgical samples and FNAB obtained from the same patient with an overall Pearson's correlation coefficient r ¼ 0.841 (P ¼ 0.001). The value of AUC for the ROC curve estimated based on MUC3, MUC5AC, and MUC6 used to differentiate PDAC from chronic pancreatitis in this population was 0.90 (95% CI 0.82e0.96). Discussion Application of molecular assays for the analysis of aspirates obtained by fine-needle biopsies offers new opportunities compared to standard cytology. The current study demonstrated that mucin profiling by RT-PCR is equivalent to immunohistochemistry in terms of accurate differentiation between chronic pancreatitis and pancreatic cancer. Moreover, results in resected surgical specimens corresponded to biopsy samples, and this warrants further testing for potential clinical applications as a diagnostic aid to cytology. Many previous reports suggested that mucin profiling by IHC

Table 4 Diagnostic performance of mucin expression by RT-PCR for PDAC and other neoplasms compared to chronic pancreatitis.

Fig. 1. Receiver operating characteristic (ROC) curves for diagnosis of malignant and inflammatory lesions with RT-PCR assays of individual mucins. A. Pancreatic cancer vs chronic pancreatitis, B. Ampullary and common bile duct cancers vs chronic pancreatitis.

Mucin

PDAC vs CP

Other neoplasms vs CP

Sensitivity

Specificity

Sensitivity

Specificity

MUC1 MUC2 MUC3 MUC4 MUC5AC MUC6

56% 58% 85% 15% 77% 77%

76% 55% 76% 97% 73% 76%

59% 58% 55% 55% 61% 70%

78% 55% 95% 76% 85% 76%

CP e chronic pancreatitis, PDAC e pancreatic ductal cell carcinoma.

Please cite this article in press as: Wiktorowicz M, et al., Rationale and feasibility of mucin expression profiling by qRT-PCR as diagnostic biomarkers in cytology specimens of pancreatic cancer, Pancreatology (2018), https://doi.org/10.1016/j.pan.2018.09.008

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Table 5 AUCs (95% CI) for ROC curves of mucins detected by immunohistochemistry and RT-PCR (P > 0.05 for all comparisons between ICH and RT-PCR). Mucin

MUC1 MUC2 MUC3 MUC4 MUC5AC MUC6

Immunohistochemistry

RT-PCR

PDAC vs CP

Other neoplasms vs CP

PDAC vs CP

Other neoplasms vs CP

0.75 0.57 0.87 0.57 0.77 0.82

0.77 0.53 0.75 0.68 0.74 0.77

0.77 0.53 0.88 0.55 0.81 0.79

0.70 0.51 0.87 0.57 0.79 0.78

(0.68e0.83) (0.46e0.69) (0.82e0.94) (0.46e0.68) (0.69e0.85) (0.75e0.89)

(0.63e0.91) (0.39e0.67) (0.63e0.88) (0.55e0.80) (0.62e0.87) (0.66e0.89)

(0.69e0.85) (0.42e0.64) (0.83e0.94) (0.43e0.66) (0.73e0.89) (0.72e0.87)

(0.59e0.84) (0.40e0.61) (0.81e0.92) (0.46e0.68) (0.72e0.87) (0.71e0.86)

PDAC e pancreatic ductal cell carcinoma; CP e chronic pancreatitis.

Fig. 2. Receiver operating characteristic (ROC) curves for diagnostic performance of regression models based on RT-PCR assays for selected mucins (MUC3, MUC5AC, MUC6). A. Pancreatic cancer vs chronic pancreatitis, B. Ampullary and common bile duct cancers vs chronic pancreatitis.

may be useful to distinguish pancreatic cancer from normal pancreas and chronic pancreatitis [15,20e24]. However, application of IHC to simultaneously detect several mucins in cells obtained by FNAB is limited by the small amount of tissue. This obstacle can be overcome by the application of molecular methods that require less cellular material for precise evaluation, such as quantitative RT-PCR. Surprisingly, previous studies using resected surgical specimens recruited small populations of less than 40 patients and were limited to either semiquantitative RT-PCR or in situ hybridization [25e31]. Consequently, little is known about the potential clinical application of mucin profiling using modern molecular methods. Using a well-defined population of patients with PDAC, ampullary and common bile duct cancers, this study demonstrated that evaluation of expression levels for MUC mRNAs allows us to accurately discriminate between chronic pancreatitis and these three types of malignancies. The final diagnostic model including MUC3, MUC5AC, and MUC6 for PDAC showed sensitivity and specificity markedly exceeding those obtained for most earlier cytological markers, thereby making it a promising diagnostic aid reducing the risk of false-negative cytology. Moreover, the expression pattern was found comparable at the mRNA and protein levels, as evidenced by the comparison of AUCs achieved for individual mucins. This was not unexpected, as in general, the previous results suggested good comparability between in situ hybridization and immunostaining for mucins [26e31]. The high diagnostic performance of the proposed mucin-based models and good correlations between mucin expression patterns in tissue samples obtained from surgical specimens and FNAB suggest that such a test could be a valuable diagnostic aid to classic cytology for differentiation between malignant and inflammatory lesions. However, this hypothesis was evaluated only by a single clinical study recruiting a heterogeneous population of 90 patients with a pancreatic mass, including pancreatic cancer (n ¼ 43) [32]. Mucins (MUC1, MUC2, MUC3, MUC4, MUC5A, MUC5B, MUC6, and MUC7) were evaluated by RT-PCR with Gsa as a housekeeping gene. However, due to technical reasons, only MUC2, MUC4, MUC5B, and MUC7 could be examined in all patients. The only statistically significant difference among the examined patients was a higher prevalence of MUC7 in pancreatic cancer compared to IPMN (73% vs 42%, P ¼ 0.020) and GEP-NET (73% vs 14%, P ¼ 0.003). Nevertheless, no details were provided of the criteria used to classify cases as positive for MUC7. The aim of the present study was to evaluate the feasibility of mucin profiling by RT-PCR as a diagnostic aid to cytological evaluation of pancreatic masses subject to FNAB. Therefore, despite promising results, the important limitation of the present study is related to the lack of appropriate validation. This, however, could only be made possible within a prospective clinical trial recruiting sufficiently large populations of patients. Another important aspect is related to the heterogeneity of FNAB material that normally contains various amounts of contaminant cells with different

Please cite this article in press as: Wiktorowicz M, et al., Rationale and feasibility of mucin expression profiling by qRT-PCR as diagnostic biomarkers in cytology specimens of pancreatic cancer, Pancreatology (2018), https://doi.org/10.1016/j.pan.2018.09.008

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mucin expression. This could be potentially overcome by microdissection of biopsy samples; however, such efforts are more laborious and require more specialized equipment. In conclusion, this study demonstrated that expression profiling of carefully selected mucins with RT-PCR offered a promising ability to discriminate pancreatic ductal cell adenocarcinoma from chronic pancreatitis. Therefore, such mucin panels are warranted for further studies involving tissue samples obtained from pancreatic biopsies to improve their diagnostic performance. Disclosure of potential conflicts of interest The authors declare that they have no conflict of interest.

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Not applicable. Authors' contributions Conception and design: M. Sierzega, J. Kulig, P. Richter. Data acquisition, analysis and interpretation: M. Wiktorowicz, D. Mlynarski, R. Pach,R. Tomaszewska. Drafting of the manuscript or revising it critically for important intellectual content: M. Wiktorowicz, D. Mlynarski, R. Pach, R. Tomaszewska, J. Kulig, P. Richter, M. Sierzega. Administrative, technical, or material support: J. Kulig, P. Richter. Grant support This study was financially supported by the Polish National Science Centre (NCN), grant no. N N403 591738. The provider of financial support was not involved in the study design, in the collection, analysis or interpretation of data; in the writing of the manuscript; or in the decision to submit the manuscript for publication.

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Please cite this article in press as: Wiktorowicz M, et al., Rationale and feasibility of mucin expression profiling by qRT-PCR as diagnostic biomarkers in cytology specimens of pancreatic cancer, Pancreatology (2018), https://doi.org/10.1016/j.pan.2018.09.008