*Wisteria floribunda* **Agglutinin-Positive Mac-2 Binding Protein but not** α**-Fetoprotein as a Long-Term Hepatocellular Carcinoma Predictor**

**Leona Osawa 1,2, Nobuharu Tamaki 1,2 , Masayuki Kurosaki <sup>1</sup> , Sakura Kirino <sup>1</sup> , Keiya Watakabe <sup>1</sup> , Wan Wang <sup>1</sup> , Mao Okada <sup>1</sup> , Takao Shimizu <sup>1</sup> , Mayu Higuchi 1,2 , Kenta Takaura <sup>1</sup> , Hitomi Takada 1,2, Shun Kaneko <sup>1</sup> , Yutaka Yasui <sup>1</sup> , Kaoru Tsuchiya <sup>1</sup> , Hiroyuki Nakanishi <sup>1</sup> , Jun Itakura <sup>1</sup> , Yuka Takahashi <sup>1</sup> , Nobuyuki Enomoto <sup>2</sup> and Namiki Izumi 1,\***


Received: 11 May 2020; Accepted: 19 May 2020; Published: 21 May 2020

**Abstract:** Identification of high-risk patients for hepatocellular carcinoma (HCC) after sustained virological responses (SVR) is necessary to define candidates for long-term surveillance. In this study, we examined whether serum markers after 1 year of SVR could predict subsequent HCC development. Total 734 chronic hepatitis C patients without a history of HCC who achieved SVR with direct-acting antivirals were included. The regular surveillance for HCC started from 24 weeks after the end of treatment (SVR24). Factors at SVR24 and 1 year after SVR24 were analyzed for predicting HCC development. During the mean observation period of 19.7 ± 10 months, 24 patients developed HCC. At SVR24, *Wisteria floribunda* agglutinin-positive mac-2 binding protein (WFA±M2BP) ≥ 1.85 and α-fetoprotein (AFP) ≥ 6.0 ng/mL were independent factors of HCC development. However, at 1 year after SVR24, WFA±M2BP ≥ 1.85 was associated with subsequent HCC development (hazard ratio: 23.5, 95% confidence interval: 2.68–205) but not AFP. Among patients with WFA±M2BP ≥ 1.85 at SVR24, 42% had WFA±M2BP < 1.85 at 1 year after SVR24 (WFA±M2BP declined group). Subsequent HCC development was significantly lower in the declined group than in the non-declined group (1 year HCC rate: 0% vs. 9.4%, *p* = 0.04). In conclusion, WFA±M2BP but not AFP could identify high and no-risk cases of HCC at 1 year after SVR. Therefore, it was useful as a real-time monitoring tool to identify the candidates for continuous surveillance for HCC.

**Keywords:** hepatocellular carcinoma; WFA±M2BP; AFP; chronic hepatitis C; direct-acting antivirals

#### **1. Introduction**

Direct-acting antivirals (DAAs) treatment for chronic hepatitis C has enabled sustained virological responses (SVR) in several patients in recent years [1–6]. However, the number of patients with SVR has increased among the elderly and those with cirrhosis, and the number of patients who develop hepatocellular carcinoma (HCC) after SVR will increase in the future [7]. Therefore, it is clinically important to identify patients at a high risk of developing HCC after SVR and to perform appropriate screening.

Non-invasive fibrosis markers and α-fetoprotein (AFP) levels at 12 or 24 weeks after the end of treatment (SVR12 or 24) are reportedly associated with subsequent HCC development [8–13]. *Wisteria floribunda* agglutinin-positive mac-2 binding protein (WFA±M2BP) is a novel serum fibrosis marker [14,15], and WFA±M2BP at SVR is reported to be associated with HCC development [16,17]. Although WFA±M2BP and AFP can identify patients at high risk of HCC development at the time of SVR, it is difficult to continue screening for all cases judged high risk at the time of SVR. Liver fibrosis changes after the achievement of SVR differ from case to case [18], and subsequent changes in fibrosis lead to a different risk of HCC development [19,20]. Therefore, it is necessary to reevaluate the risk of HCC development over time.

Serum markers can be simply and repeatedly measured; therefore, it is considered possible to reevaluate the risk of HCC over time and further narrow down the high-risk cases. However, to our knowledge, no report has examined whether WFA±M2BP and AFP at 1 year after SVR are associated with HCC development. Further, it is unclear whether changes in the fibrosis markers alter the risk of carcinogenesis. Therefore, we examined whether WFA±M2BP and AFP after 1 year of achieving SVR are associated with HCC development and whether these changes could be used to evaluate the risk of HCC.

#### **2. Results**

#### *2.1. Patient Characteristics*

The clinical characteristics and laboratory data of patients are described at the time point of SVR24 and one year after SVR24 in Table 1. Average aspartate aminotransferase (AST) and alanine aminotransferase (ALT) at SVR24 were within the normal ranges because all patients achieved SVR. Twenty-one patients had liver nodules with intermediate probability of HCC (LR3) or probably of HCC (LR4) as defined by the liver imaging reporting and data system (LI-RADS) at entry [21]. There were 501 cases at 1 year after SVR24, excluding 18 patients with HCC development within 1 year. At 1 year after SVR24, AST and ALT were also within the normal ranges. The observation period began at the time of SVR24, and during the mean observation period of 19.7 ± 10 months, 24 patients developed HCC.


AST, aspartate aminotransferase; ALT, alanine aminotransferase; WFA±M2BP, *Wisteria floribunda* agglutinin-positive mac-2 binding protein; COI, cut off index; AFP, alpha fetoprotein; LR, liver imaging reporting and data system; LR3, intermediate probability of HCC; LR4, probably of HCC.

A

#### Association between WFA±M2BP and Fibrosis Stage

Association between WFA±M2BP and fibrosis stage was examined. Median value of WFA±M2BP in F1, F2, F3, and F4 was 0.75, 1.16, 2.06, and 3.01, respectively, and WFA±M2BP increased as fibrosis stage increased (*p* < 0.001).

#### *2.2. Prediction of HCC Development Using WFA* ±*M2BP and AFP at SVR24*

Serum WFA±M2BP and AFP at SVR24 were analyzed for predicting HCC development. ROC analysis was used to select WFA±M2BP of 1.85 cut off index (COI) as the optimal cutoff value for predicting HCC development within 1 year. WFA±M2BP of <1.85/≥1.85 were defined as low/high risk and low/high-risk patients were 567 (77.2%), and 167 (22.8%), respectively. The AFP level of 6.0 ng/mL was selected as the cutoff value and AFP of <6.0/≥6.0 ng/mL was defined as low/high risk of AFP. The 1-, 2-, and 3-year rate of HCC development in patients with low/high risk of WFA±M2BP were 1.2%/1.5%/1.5%, and 8.1%/13.1%/14.6%, respectively. The cumulative rate of HCC development was higher in patients with high risk than those with low risk (*p* < 0.001, Figure 1A). Similarly, the 1-, 2-, and 3-years rates of HCC development in patients with low/high risk of AFP were 0.9%/2.2%/2.2%, and 12.6%/13.8%/15.6%, respectively (Figure 1B). The cumulative rate of HCC development was high in high-risk groups (*p* < 0.001). ≥1.85 ≥

**Figure 1.** Cumulative incidence of hepatocellular carcinoma (HCC) development sustained virological responses after 24 weeks (SVR24). (**A**) patients were categorized into two groups as per *Wisteria floribunda* agglutinin-positive mac-2 binding protein (WFA±M2BP) at SVR24. (**B**) patients were categorized into two groups as per AFP at SVR24.

#### *2.3. Prediction of HCC Development as Per WFA* ±*M2BP and AFP at 1 Year after SVR24*

Serum WFA±M2BP and AFP at 1 year after SVR24 (78 weeks post-treatment) were analyzed for predicting HCC development thereafter. Using the same cutoff values (WFA±M2BP of 1.85 COI and AFP level of 6.0 ng/mL), the cumulative incidence of HCC development was examined. Seven patients developed HCC after 1 year of SVR. The 1- and 2-year rate of HCC development, starting from the time point of 78 weeks post-treatment, in patients with low/high risk of WFA±M2BP at 1 year after SVR24 were 0.3%/0.3%, and 8.6%/11.3%, respectively (*p* < 0.001, Figure 2A). In contrast, the 1-, and 2-year rate of HCC development in patients with low/high risk of AFP at 1 year after SVR24 were 1.6%/1.6%, and 0.0%/2.9%, respectively and there was no significant difference between high and low-risk groups (*p* = 0.8, Figure 2B).

**Figure 2.** Cumulative incidence of HCC development from 1 year after SVR24 (**A**) patients were categorized into two groups as per the WFA±M2BP at 1 year after SVR24. (**B**) patients were categorized into two groups as per the AFP at 1 year after SVR24.

#### *2.4. Time-Course Changes in WFA* ±*M2BP and AFP and HCC Risk*

Time-course changes in WFA±M2BP and AFP were examined. WFA±M2BP at SVR24 was 1.52 ± 1.4 COI that decreased significantly to 1.28 ± 1.1 COI at 1 year after SVR24 (*p* < 0.001). Similarly, the AFP level at SVR24 was 3.99 ± 3.4 ng/mL and decreased significantly to 3.51 ± 2.2 ng/mL 1 year after SVR24 (*p* < 0.001).

Among patients with a high risk of WFA±M2BP (≥1.85 COI) at SVR24, WFA±M2BP decreased to < 1.85 COI (low risk) at 1 year after SVR24 in 42 patients (42/102, 42%) (WFA±M2BP declined group) and remained ≥ 1.85 COI in 60 patients (60%) (WFA±M2BP non-declined group). Among patients with a high risk of AFP (≥6.0 ng/mL) at SVR24, AFP decreased to < 6.0 ng/mL at 1 year after SVR24 in 30% (20/67) patients (AFP declined group) and remained ≥ 6.0 ng/mL in 70% of the patients (AFP non-declined group). The 1- and 2-year rates of HCC development, starting from the time point of 78 weeks post-treatment, were 0% and 0%, respectively, in the WFA±M2BP declined group, while these rates were 9.4% and 12.4%, respectively, in the WFA±M2BP non-declined group. The cumulative incidence of HCC development was significantly higher in patients in the WFA±M2BP non-declined group (*p* = 0.04, Figure 3A). In contrast, there was no significant difference in the cumulative rate of HCC development between the AFP declined and non-declined group (Figure 3B). M2BP (≥ and remained ≥ 1.85 COI in 60 patients (60%) (WFA of AFP (≥ declined group) and remained ≥

M2BP ≥ 1.85 atients were categorized into two groups as per the change in AFP. The patients with AFP ≥ 6.0 **Figure 3.** Cumulative incidence of HCC development as per change in the serum marker (**A**) patients were categorized into two groups as per the change in WFA±M2BP. Patients with WFA±M2BP ≥ 1.85 COI at SVR24 and WFA±M2BP < 1.85 at 1 year after SVR24 were defined as the declined group. (**B**) patients were categorized into two groups as per the change in AFP. The patients with AFP ≥ 6.0 ng/mL at SVR24 and AFP < 6.0 at 1 year after SVR24 were defined as the declined group.

#### *2.5. Association between AFP and LR3*/*4 nodule*

The association between serum AFP levels and the presence of LR3/4 nodule was analyzed at the time point of SVR24 and 1 year after SVR24. At SVR24, 2.1% (13/623) of patients with AFP at SVR24 < 6.0 ng/m had LR3/4 nodules and 7.2% (8/111) of patients with AFP ≥ 6.0 ng/m had LR3/4 nodules, and presence of LR3/4 nodules was significantly higher in patients with AFP ≥ 6.0 ng/mg (*p* = 0.008). However, at 1 year after SVR24, 0% of the patients with AFP ≥ 6.0 ng/m and 2.1% of those with AFP < 6.0 ng/m had LR3/4 nodules, with no significant difference.

#### *2.6. Multivariable Analysis of Factors at SVR24 Associated with HCC Development*

Factors at SVR24, including those other than WFA±M2BP and AFP, were analyzed for their association with HCC development. Age (every 10 years), albumin, AST (every 30 IU/L), ALT (every 30 IU/L), platelet counts, WFA±M2BP ≥ 1.85 COI (hazard ratio [HR]: 9.43, 95% confidence interval (CI): 3.91–22.7, *p* < 0.001, Table 2), AFP ≥ 6.0 ng/mL (HR: 8.17, 95%CI: 2.63–18.4, *p* < 0.001), and presence of LR3/4 nodules (HR: 15.4, 95%CI: 6.06–39.2, *p* < 0.001) were associated with HCC development in the univariate analysis. By using these factors, multivariate analysis revealed that WFA±M2BP ≥ 1.85 COI (HR: 5.29, 95% CI: 2.07–13.0, *p* < 0.001), AFP ≥ 6.0 ng/mL (HR: 4.27, 95% CI: 1.84–9.94, *p* < 0.001), and the presence of LR3/4 nodules (HR: 8.49, 95%CI: 3.29–21.9, *p* < 0.001) were independently associated with HCC development.




HCC, hepatocellular carcinoma; SVR, sustained virological response; HR, hazard ratio; CI, confidence interval, AST, aspartate aminotransferase; ALT, alanine aminotransferase; WFA±M2BP, *Wisteria floribunda* agglutinin-positive mac-2 binding protein; COI, cut off index; AFP, alpha-fetoprotein; LR, liver imaging reporting and data system; LR3, intermediate probability of HCC; LR4, probably of HCC.

#### *2.7. Multivariable Analysis of Factors at 1 Year after SVR24 Associated with HCC Development*

Similarly, factors at 1 year after SVR24, including those other than WFA±M2BP and AFP, were analyzed for their association with HCC development. Similar to SVR24, WFA±M2BP ≥ 1.85 COI (HR: 35.3, 95% CI: 4.25–293, *p* < 0.001), albumin, platelet counts, and presence of LR3/4 nodules (HR: 60.1, 95%CI: 13.2–273, *p* < 0.001) at 1 year after SVR24 were associated with HCC development in the univariate analysis. However, AFP ≥ 6.0 ng/mL at 1 year after SVR24 was not associated with subsequent HCC development (HR: 1.23, 95% CI: 0.15–10.2, *p* = 0.9). Multivariate analysis revealed that WFA±M2BP ≥ 1.85 COI (HR: 23.5, HR: 2.68–205, *p* = 0.004) and presence of LR3/4 nodules (HR:24.1, 95%CI: 5.02–116, *p* < 0.001) were independent factors at 1 year after SVR24 for the prediction of HCC development thereafter.

#### **3. Discussion**

The present study revealed that WFA±M2BP was useful for predicting HCC development at 1 year of SVR; however, AFP was not useful. In addition, even if WFA±M2BP was high (≥ 1.85 COI) at SVR, the risk of HCC decreases in patients in whom WFA±M2BP subsequently declines (<1.85 COI). However, AFP was useful for predicting HCC at the time of SVR, but not after one year. WFA±M2BP could be easily measured and helped identify high cases of HCC development at any time after SVR; therefore, it was useful as a real-time monitor of HCC development risk in the long-term follow-up after SVR.

One of the novel findings of this study was that it confirmed that a high level of WFA±M2BP after 1 year of SVR is associated with HCC development risk. The association between WFA±M2BP at SVR and HCC risk has been reported by several studies, including our report [16,17]. Since WFA±M2BP at SVR was associated with histological fibrosis stage before DAA treatment, WFA±M2BP at SVR was a risk factor of HCC development after SVR. One advantage of WFA±M2BP is that it can assess the fibrosis stage instead of a liver biopsy and is easy to measure repeatedly. However, to our knowledge, no study has examined the association between WFA±M2BP and HCC development risk after long-term follow-up. Early detection of HCC development after DAA treatment requires long-term follow-up. Therefore, not only the prediction of HCC development at SVR time point but also the prediction of HCC development at each follow-up time point is important. We found that WFA±M2BP ≥ 1.85 COI at 1 year of SVR, as well as SVR24, were factors for HCC development.

Considering the changes in WFA±M2BP after SVR, WFA±M2BP generally declines over time. Patients with WFA±M2BP ≥ 1.85 COI at SVR were at high-risk for subsequent HCC development; however, those with decreased WFA±M2BP after 1 year had a reduced risk of HCC development. However, in some cases, WFA±M2BP was still high, and in such cases, the risk of HCC development remained high. The advantage of WFA±M2BP is that the change in the HCC risk can be identified by observing the time-dependent changes in WFA±M2BP.

Although long-term follow-up is necessary to identify patients with HCC development after SVR, it is difficult to screen all patients frequently. However, the lack of screening after SVR is a known risk factor for the development of advanced HCC [22]. Therefore, there is an urgent need to construct a surveillance strategy after SVR. In surveillance, it is necessary to reevaluate the risk of HCC development not only at SVR but also at follow-up and to narrow down high-risk cases of HCC. WFA±M2BP is useful as a real-time monitor for the prediction of HCC development in that WFA±M2BP can assess the risk of HCC at any time point and assess changes in HCC risk by observing changes over time; further, clinically important information can be obtained noninvasively and conveniently.

Another novel finding of this study was that AFP after 1 year of SVR was not useful for predicting HCC development. It has been widely reported that AFP levels at SVR are associated with HCC risk [9–12,17]. This point was also confirmed in this study. However, it became clear that the AFP level 1 year after SVR was not associated with HCC development. It has been reported that high levels of AFP at the time of SVR are associated with the presence of LR3/4 nodules, and such patients are at a high risk of HCC development [23,24]. In this study, high levels of AFP at SVR were associated with the presence of LR3/4 nodules, and the cumulative incidence of HCC development was high in these patients; in particular, many HCC developments were observed within 1 year. Further, the AFP at 1 year after SVR decreased significantly, and no correlation was found when examining the association between AFP and LR3/4 nodules at 1 year after SVR. Although high AFP levels at SVR24 were associated with already existing HCC, high-risk nodules, and early development of HCC, no association between AFP and HCC development after 1 year of SVR, excluding that in these high-risk cases, is believed to exist. AFP was associated with the early development of HCC after SVR; however, one year thereafter, AFP was not useful for predicting HCC development; this was a novel finding of this study. AFP was not useful for predicting HCC development in the long-term follow-up; thus, WFA±M2BP, rather than AFP, was useful for HCC monitoring during long-term follow-up after SVR.

There are certain limitations to this study. At present, few cases have been followed up for 2 years. To verify the usefulness of WFA±M2BP over time, it is necessary to verify whether WFA±M2BP of 2 years after SVR24 and later is useful for prediction of HCC development, which is a future study subject. Moreover, there were few HCC cases; therefore, future long-term studies on a larger cohort are needed to examine the usefulness of WFA±M2BP over time. Several fibrosis markers have been confirmed as a predictive marker of HCC development after SVR [13,25]. The diagnostic accuracy of HCC development after SVR should be compared between WFA±M2BP and other markers in future studies.

In conclusion, WFA±M2BP but not AFP was useful as a real-time monitor of HCC prediction in long-term follow-up after SVR.

#### **4. Materials and Methods**

#### *4.1. Patients*

Between October 2014 and March 2018, 871 patients received DAAs at the Musashino Red Cross Hospital for the treatment of chronic hepatitis C and achieved SVR. Of these, 734 who met the following criteria were enrolled in this study: (1) those who were followed up for 6 months or more after SVR24, (2) had no history of HCC development, and (3) had no co-infection with hepatitis B virus or human immunodeficiency virus. The observation period began at the time of SVR24, and HCC development after SVR was followed up. Written informed consent was obtained from each patient. The study protocol conformed to the ethical guidelines of the Declaration of Helsinki and was approved by the institutional ethics review committee (approval number:28089, 4 April 2017).

#### *4.2. Clinical and Laboratory Data*

Age and sex of the patients were recorded at SVR24. Fasting blood counts and biochemical tests were also conducted on SVR24 and 1 year after SVR24 using standard methods.

#### *4.3. HCC Surveillance and Diagnosis*

Ultrasonography and blood tests, including tests for tumor markers, were performed every 3–6 months for HCC surveillance. When tumor marker levels rose abnormally and/or abdominal ultrasonography suggested a lesion suspicious of HCC, contrast-enhanced computed tomography, magnetic resonance imaging, or angiography was performed. HCC was diagnosed for tumors displaying vascular enhancement at the early phase and washout at the later phase as per the guidelines of the American Association for the Study of Liver Diseases, and the Japan Society of Hepatology [26,27]. Tumor biopsy was used to diagnose tumors with non-typical imaging findings.

#### Histological Evaluation

Of all patients enrolled in the study, liver biopsy was performed in 257 patients 1 month prior to the initiation of DAA treatment until the treatment. Liver biopsy specimens were obtained laparoscopically using 13G needles or by percutaneous ultrasound-guided liver biopsy using 15G needles. Specimens

were fixed, paraffin-embedded, and stained using hematoxylin–eosin and Masson's trichrome. A minimum of a 15-mm biopsy sample was required for diagnosis. All liver biopsy samples were independently evaluated by two senior pathologists who were blinded to the clinical data. Fibrosis staging was assessed according to the METAVIR score: F0, no fibrosis; F1, portal fibrosis without septa; F2, portal fibrosis with few septa; F3, numerous septa without cirrhosis; and F4, cirrhosis.

#### *4.4. Statistical Analyses*

Receiver operating characteristic (ROC) curves and the Youden index were used to determine the optimal cutoff value of WFA±M2BP and AFP for predicting HCC development. Statistical significance was defined as a *p*-value < 0.05. Cumulative incidences of HCC development were calculated using the Kaplan–Meier method. The factors associated with HCC development were analyzed using the Cox-proportional hazard model. Correlated factors with a *p*-value < 0.05 in the univariate analysis were used for further multivariate analysis. Backward stepwise selection method was used for multivariate analyses. Association between WFA±M2BP and fibrosis stage was analyzed using Spearman's rank correlation test. Statistical analyses were performed using EZR (Saitama Medical Center, Jichi Medical University, Saitama, Japan) [28] and a graphical user interface for R (The R Foundation for Statistical Computing, Vienna, Austria).

**Author Contributions:** Study conception: L.O., N.T., M.K.; data collection: all authors; data analysis: L.O., N.T.; manuscript drafting: L.O., N.T.; clinical revision: M.K., N.E., N.I.; obtained funding: N.I.; study supervision: N.E., N.I., L.O. and N.T. have equally contributed to this study. All authors read and approved the published version of the manuscript.

**Funding:** This study was supported by a grant-in-aid from the Japan Agency for Medical Research and Development (grant number: JP19fk0210025h0003, URL: http://www.amed.go.jp/en/).

**Conflicts of Interest:** All authors have no conflict of interest to disclose.

#### **Abbreviations**


#### **References**


© 2020 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (http://creativecommons.org/licenses/by/4.0/).

## *Article* **Form-Vessel Classification of Cholangioscopy Findings to Diagnose Biliary Tract Carcinoma's Superficial Spread**

**Yoshimitsu Fukasawa , Shinichi Takano \* , Mitsuharu Fukasawa, Shinya Maekawa , Makoto Kadokura, Hiroko Shindo, Ei Takahashi, Sumio Hirose, Satoshi Kawakami, Hiroshi Hayakawa , Tatsuya Yamaguchi, Yasuhiro Nakayama, Taisuke Inoue, Tadashi Sato and Nobuyuki Enomoto**

First Department of Internal Medicine, Faculty of Medicine, University of Yamanashi, Chuo, Yamanashi 409-3898, Japan; ii258pp2@yahoo.co.jp (Y.F.); fmitsu@yamanashi.ac.jp (M.F.); maekawa@yamanashi.ac.jp (S.M.); makotok@yamanashi.ac.jp (M.K.); shindoh@yamanashi.ac.jp (H.S.); etakahashi@yamanashi.ac.jp (E.T.); sh99073@yahoo.co.jp (S.H.); k234\_0516@yahoo.co.jp (S.K.); hhayakawa@yamanashi.ac.jp (H.H.); ytatsuya@yamanashi.ac.jp (T.Y.); ynakayama@yamanashi.ac.jp (Y.N.); tinoue@yamanashi.ac.jp (T.I.); tadashis@yamanashi.ac.jp (T.S.); enomoto@yamanashi.ac.jp (N.E.)

**\*** Correspondence: stakano@yamanashi.ac.jp; Tel.: +81-55-273-9584

Received: 8 April 2020; Accepted: 5 May 2020; Published: 7 May 2020

**Abstract:** We aimed to evaluate a newly developed peroral cholangioscopy (POCS) classification system by comparing classified lesions with histological and genetic findings. We analyzed 30 biopsied specimens from 11 patients with biliary tract cancer (BTC) who underwent POCS. An original classification of POCS findings was made based on the biliary surface's form (F factor, 4 grades) and vessel structure (V-factor, 3 grades). Findings were then compared with those of corresponding biopsy specimens analyzed histologically and by next-generation sequencing to identify somatic mutations. In addition, the histology of postoperative surgical stumps and preoperative POCS findings were compared. Histological malignancy rate in biopsied specimens increased with increasing F- and V-factor scores (F1, 0%; F1, 25%; F3, 50%; F4, 62.5%; *p* = 0.0015; V1, 0%; V2, 20%; V3, 70%; *p* < 0.001). Furthermore, we observed a statistically significant increase of the mutant allele frequency of mutated genes with increasing F- and V-factor scores (F factor, *p* = 0.0050; V-factor, *p* < 0.001). All surgical stumps were accurately diagnosed using POCS findings. The F–V classification of POCS findings is both histologically and genetically valid and will contribute to the methods of diagnosing the superficial spread of BTC tumors.

**Keywords:** bile duct cancer; cholangioscope; genetic mutation; tumor spread; biopsy

#### **1. Introduction**

Biliary tract cancer (BTC), which arises from the biliary epithelium of the intrahepatic, extrahepatic, and gallbladder bile ducts, accounts for about 3% of all gastrointestinal cancers [1] and is the sixth leading cause of cancer death [2]. In Japan, perihilar bile duct, distal bile duct, and gallbladder cancers have overall 5-year survival rates of 24.2%, 39.1%, and 39.8%, respectively [3]. To date, surgery has been the exclusive curative therapy for BTC. In addition, survival post-surgery is short in cases involving positive resection margins, perineural invasion, lymph node metastasis, and undifferentiated adenocarcinoma in resected tissues [4].

To avoid unnecessary invasive procedures and determine the appropriate therapy, a precise diagnosis of tumor spread is important. Currently, more extensive surgery made possible by accumulated experience and recent technical advances has allowed for complete resection of BTC

lesions (e.g., hepatopancreatoduodenectomy) [5]. By conducting a thorough examination pre-surgery, a positive resected margin is avoidable, improving risk factors related to postoperative survival. Earlier studies have reported the primary tumor's superficial spread or extension in 31.6–39.3% of BTC cases, with more than 20-mm length of superficial spread in 14.6–17.9% cases [6,7]. These lesions can be identified using ultrasonography [8], multi detector-row computed tomography (MDCT) [9], and magnetic resonance imaging [10]. Intraductal ultrasonography (IDUS) during endoscopic retrograde cholangiopancreatography (ERCP) has been shown to be beneficial for both qualitative diagnosis and the diagnosis of the main tumor's superficial spread [11,12]. However, these methods have a limited diagnostic accuracy in terms of the superficial tumor spread. In contrast, superficial spread of tumor can be diagnosed using peroral cholangioscopy (POCS), which has the advantage of allowing direct visualization of the bile duct lumen [13]. The diagnostic accuracy has been reported to increase when POCS is used with bile duct biopsy [14–16]. Furthermore, recent improvements in image resolution and the development of narrow-band imaging have enabled the detailed observation of surface structures and the fine vasculature of bile ducts [17]. Several POCS studies, focusing on surface and vessel structures, have reported on benign and malignant bile ducts findings [16,18–20]. However, to date, there are no reports systematically classifying POCS findings.

Recent advances in next-generation sequencing (NGS) have enabled rapid and comprehensive gene sequencing, which have allowed the identification of gene alterations in numerous tumors, including BTC [21,22]. Of note, targeted deep sequencing has a high sensitivity in detecting multiple gene mutations. The variant allele frequency (VAF) of genes reflect the fraction of tumor cells per sample and can be used to determine the tumor grade [23].

In this study, we developed a classification system based on POCS findings in surface and vessel structures to diagnose BTC tumor spread. The validity of this classification system was evaluated using histological diagnosis and gene mutation analysis in biopsy specimens. Furthermore, we examined the effectiveness of this classification in determining the extent of resection.

#### **2. Results**

#### *2.1. Patient Characteristics and Assessment of Biopsied Samples*

A total of 11 patients (8 men and 3 women) were enrolled in this study, with their median age being 70 (range, 59–79) years. Lesions were in the following regions: intrahepatic bile duct (*n* = 1), perihilar bile duct (*n* = 2), and distal bile duct (*n* = 8). Macroscopic classification revealed 5, 4, and 2 cases of papillary type, nodular type, and flat type, respectively. Histological tumor invasion around the bile duct (pT) and histological lymph node metastasis (pN) were evaluated according to the TNM Classification of Malignant Tumors (7th edition) [24]. Staging revealed 4 early-stage (<pT3) cases and 7 more advanced cases (≥pT3), with 7 pN0 cases and 4 pN1 cases (Table 1). Endoscopic procedures resulted in no complications. Surgical resection after POCS examination was performed in all patients.

The median amount of DNA extracted from 18 biopsied samples was 13.0 (range, 2.5–34.0) ng. However, the amount of DNA extracted from the other 12 samples was below the detection sensitivity. The median sequence read depth was 7570 (range, 261–16,055) (Table S1). Specimens of 12, 8, 2, and 8 parts in the bile ducts were biopsied from areas with F1, F2, F3, and F4, respectively. Specimens of 15, 5, and 10 were from areas with V1, V2, and V3, respectively.


**Table 1.** Baseline characteristics of patients.

CBD, common bile duct; Bh, intrahepatic bile duct; Bp, perihilar bile duct; Bd, distal bile duct.

#### *2.2. Association between the F–V Classification and the Histological Assessment of Biopsied Samples*

We observed a positive correlation between F factor and V-factor scores (correlation coefficient: 0.91; Figure S1). The pathological malignancy rates with respect to the F factor were as follows: F1, 0%; F2, 25%; F3, 50%; and F4, 62.5% (Figure 1A). Similarly, those with respect to the V-factor were as follows: V1, 0%; V2, 20%; and V3, 70% (Figure 1B). We found that higher F–V scores significantly corresponded with higher histological malignancies of the biopsied specimens (F factor, *p* = 0.0015; V-factor, *p* < 0.001). However, no malignancy of the biopsied specimens was observed in POCS findings in terms of F1V1 and F2V1. Surgical margins were negative in 9 of 11 cases, and all stumps of these 9 cases were F1V1 in POCS findings. In 2 cases, surgical margins were positive with carcinoma in situ, and these cases had a positive surgical margin with F2V3 in POCS findings. *Int. J. Mol. Sci.* **2020**, *21*, x FOR PEER REVIEW 4 of 14

**Figure 1.** Association between pathological malignancy rate and F–V factors. Pathological malignancy rates increased with increasing F- and V-factor scores (**A**, F factor; **B**, V-factor). Statistical significance was determined using the Cochran–Armitage trend test. **Figure 1.** Association between pathological malignancy rate and F–V factors. Pathological malignancy rates increased with increasing F- and V-factor scores (**A**, F factor; **B**, V-factor). Statistical significance was determined using the Cochran–Armitage trend test.

one gene mutation (Figure S2). The fraction of samples with a gene mutation according to the F factor was as follows: F1, 16.7%; and F2–F4, 61.1% (Figure 2A), whereas those with a mutation according to the V-factor were as follows: V1, 13.3%; V2–V3, 73.3% (Figure 2B). We observed that the differences between V-factor categories were statistically significant (F factor, *p* = 0.0423; V-factor, *p* = 0.0032). Furthermore, we found an increase in VAF of the mutated genes with increasing F- and V-factor

*2.3. Association between the F–V Classification and Genetic Mutations* 

scores (Figure 2C,D, *p* = 0.005 and <0.001, respectively).

mutation VAF.

#### *2.3. Association between the F–V Classification and Genetic Mutations*

In the present study, of the 50 cancer-related genes that were examined, *TP53* (36%), *RB1* (27%), and *KIT* (18%) were the most frequently mutated ones. Of the tested samples, 13 (43.3%) had at least one gene mutation (Figure S2). The fraction of samples with a gene mutation according to the F factor was as follows: F1, 16.7%; and F2–F4, 61.1% (Figure 2A), whereas those with a mutation according to the V-factor were as follows: V1, 13.3%; V2–V3, 73.3% (Figure 2B). We observed that the differences between V-factor categories were statistically significant (F factor, *p* = 0.0423; V-factor, *p* = 0.0032). Furthermore, we found an increase in VAF of the mutated genes with increasing F- and V-factor scores (Figure 2C,D, *<sup>p</sup>* <sup>=</sup> 0.005 and <sup>&</sup>lt;0.001, respectively). *Int. J. Mol. Sci.* **2020**, *21*, x FOR PEER REVIEW 5 of 14

**Figure 2.** Association between the percentage of cases with a gene mutation and F–V-factor scores. Bar graphs represent the percentage of cases with a gene mutation by F factor score (**A**) and V-factor score (**B**). The rate of genetic mutations of F2**–**F4 was higher than F1 (A). The rate of genetic mutations of V2**–**V3 was higher than V1 (**B**). Statistical significance was assessed using χ<sup>2</sup> test. The variant allele frequencies (VAFs) increased with increasing F- and V-factor scores (**C**, F factor; **D**, V-factor). Horizontal bars indicate the mean. Increasing trends were analyzed using the Jonckheere–Terpstra **Figure 2.** Association between the percentage of cases with a gene mutation and F–V-factor scores. Bar graphs represent the percentage of cases with a gene mutation by F factor score (**A**) and V-factor score (**B**). The rate of genetic mutations of F2–F4 was higher than F1 (A). The rate of genetic mutations of V2–V3 was higher than V1 (**B**). Statistical significance was assessed using χ 2 test. The variant allele frequencies (VAFs) increased with increasing F- and V-factor scores (**C**, F factor; **D**, V-factor). Horizontal bars indicate the mean. Increasing trends were analyzed using the Jonckheere–Terpstra trend test. VAFs were plotted only for specimens with a confirmed gene mutation.

#### *2.4. Association between the Histological Assessment and Genetic Mutations in F–V Classification*

trend test. VAFs were plotted only for specimens with a confirmed gene mutation.

*2.4. Association between the Histological Assessment and Genetic Mutations in F–V Classification*  We assessed the association between F–V classification and histological diagnosis (Figure 3A) or VAFs (Figure 3B) of biopsied specimens. The group evaluated as F1V1 or F2V1 in POCS were all We assessed the association between F–V classification and histological diagnosis (Figure 3A) or VAFs (Figure 3B) of biopsied specimens. The group evaluated as F1V1 or F2V1 in POCS were all histologically benign, had a low rate of genetic mutation, and a low gene mutation VAF. On the

histologically benign, had a low rate of genetic mutation, and a low gene mutation VAF. On the

contrary, the groups evaluated as F4V3 or F3V3 or F2V3 in POCS were histologically malignant, had a high rate of genetic mutation, and had a high gene mutation VAF. The group evaluated as F3V2 or F2V2 in POCS were histologically benign, had a high rate of genetic mutation, and had a low gene mutation VAF. *Int. J. Mol. Sci.* **2020**, *21*, x FOR PEER REVIEW 6 of 14

**Figure 3.** Association between the histological assessment and genetic mutations in F–V classification. The upper Figure (**A**) shows the association between F**–**V classification and histological assessment. Black circle (●) indicates malignancy and white circle (〇) indicates non-malignant lesions. The lower Figure (**B**) shows the association between F–V classification and genetic mutation. Dotted circles represent specimens without genetic mutation, and solid circles represent specimens with genetic **Figure 3.** Association between the histological assessment and genetic mutations in F–V classification. The upper Figure (**A**) shows the association between F–V classification and histological assessment. Black circle (•) indicates malignancy and white circle (O) indicates non-malignant lesions. The lower Figure (**B**) shows the association between F–V classification and genetic mutation. Dotted circles represent specimens without genetic mutation, and solid circles represent specimens with genetic mutation. The color density in the circle indicates the VAF.

mutation. The color density in the circle indicates the VAF. Figure 4 shows a representative case. Specifically, this case highlights the relationship among F– V classification of POCS findings, histology, and genetic mutations. In this case, the main tumor lies in the middle bile duct. It is classified as F3V3 according to POCS findings, malignant pathology, and gene mutations (Figure 4C). In addition, the perihilar and inferior bile duct has a benign lesion. The benign lesion in the inferior bile duct is classified as F1V1 according to POCS findings, with no gene mutation (Figure 4A,D). The tumor extends into the superior bile duct, categorized as F3V2 with a gene mutation, with a benign pathology (Figure 4B). These findings were consistent with those of the Figure 4 shows a representative case. Specifically, this case highlights the relationship among F–V classification of POCS findings, histology, and genetic mutations. In this case, the main tumor lies in the middle bile duct. It is classified as F3V3 according to POCS findings, malignant pathology, and gene mutations (Figure 4C). In addition, the perihilar and inferior bile duct has a benign lesion. The benign lesion in the inferior bile duct is classified as F1V1 according to POCS findings, with no gene mutation (Figure 4A,D). The tumor extends into the superior bile duct, categorized as F3V2 with a gene mutation, with a benign pathology (Figure 4B). These findings were consistent with those of the resected tissues that were pathologically diagnosed.

resected tissues that were pathologically diagnosed.

*Int. J. Mol. Sci.* **2020**, *21*, x FOR PEER REVIEW 7 of 14

**Figure 4.** Schema of a representative bile duct carcinoma case. (**A**) In the perihilar bile duct, POCS showed the presence of a flat bile duct epithelium with a network of thin vessels (F1V1). In this region's biopsied specimens, neither a tumor nor a genetic mutation was identified. (**B**) In the superior bile duct, POCS revealed a papillary bile duct epithelium with irregular, non-dilated vessels (F3V2). In this region's biopsied specimens, no tumor was observed. However, a genetic mutation in *ATM*  was found (VAF; 15.4%). (**C**) In the main lesion of the middle bile duct, POCS demonstrated the presence of a papillary bile duct epithelium with an irregular, dilated, and tortuous vessel (F3V3). The biopsied specimens showed adenocarcinoma. Genetic mutations in *TP53* (VAF, 24.3%) and *ATM* (VAF, 23.3%) were identified. (**D**) In the inferior bile duct, POCS revealed a flat bile duct epithelium, with a network of thin vessels (F1V1). In this region's biopsied specimens, neither a tumor nor genetic mutation was observed. VAF, variant allele frequency; WT, wild type. The double line shows the **Figure 4.** Schema of a representative bile duct carcinoma case. (**A**) In the perihilar bile duct, POCS showed the presence of a flat bile duct epithelium with a network of thin vessels (F1V1). In this region's biopsied specimens, neither a tumor nor a genetic mutation was identified. (**B**) In the superior bile duct, POCS revealed a papillary bile duct epithelium with irregular, non-dilated vessels (F3V2). In this region's biopsied specimens, no tumor was observed. However, a genetic mutation in *ATM* was found (VAF; 15.4%). (**C**) In the main lesion of the middle bile duct, POCS demonstrated the presence of a papillary bile duct epithelium with an irregular, dilated, and tortuous vessel (F3V3). The biopsied specimens showed adenocarcinoma. Genetic mutations in *TP53* (VAF, 24.3%) and *ATM* (VAF, 23.3%) were identified. (**D**) In the inferior bile duct, POCS revealed a flat bile duct epithelium, with a network of thin vessels (F1V1). In this region's biopsied specimens, neither a tumor nor genetic mutation was observed. VAF, variant allele frequency; WT, wild type. The double line shows the resection line.

#### resection line. *2.5. Association between F–V Classification and Pathology Diagnosis of Resected Stump*

had no carcinoma and the F2V3 stumps had carcinoma in situ.

*2.5. Association between F–V Classification and Pathology Diagnosis of Resected Stump*  In total, 11 patients underwent the following procedures: pancreatoduodenectomy (*n* = 7), hepatectomy (*n* = 3), and extrahepatic bile tract resection (*n* = 1, Table 2). Of the 15 resected stumps, 13 were F1V1 and 2 were F2V3 according to the F–V classification. Histologically, the F1V1 stumps In total, 11 patients underwent the following procedures: pancreatoduodenectomy (*n* = 7), hepatectomy (*n* = 3), and extrahepatic bile tract resection (*n* = 1, Table 2). Of the 15 resected stumps, 13 were F1V1 and 2 were F2V3 according to the F–V classification. Histologically, the F1V1 stumps had no carcinoma and the F2V3 stumps had carcinoma in situ.


**Table 2.** Relationship between F–V classification and pathology diagnosis of resected stump.

\*, Extrahepatic bile tract resection; PD, Pancreatoduodenectomy; CIS, Carcinoma in situ.

#### **3. Discussion**

In the present study, we classified the POCS findings of BTC cases based on the form of the bile duct surface (F factor) and vascular structures (V-factor). This new system is called "the F–V classification of POCS findings." The system was validated by comparing it to the histological diagnosis and genetic mutation analysis in simultaneously biopsied specimens. Comparison with the histological diagnosis revealed a statistically significant increase of the malignancy rate with increasing F- and V-factor scores. Comparison with the mutation status showed an increased frequency of mutant variants in samples with an increase in the F- and V-factor scores. In addition, the F–V classifications of resected margins according to POCS findings were all accurate.

F–V classification is the first reported system to quantify and classify BTC based on POCS findings. Several reports have quantified POCS findings according to bile duct malignancies [16,19,20,25]. However, none of these have reported methods for stratification according to malignancy. We found that this approach is confusing when applied to diagnosis. On the contrary, we noticed that the reported observations of POCS findings could be categorized into 2 groups. The first group comprised surface structures of the bile duct such as "irregular fine granular pattern" [16], "irregular papillogranular surface" [19], "nodular elevated surface-like submucosal tumor" [19], "irregular surface or papillary projections" [20], and "luminal narrowing that was continuous with the main cancerous lesion" [20]. The second group comprised vascular structures such as "fish-egg-like appearance" [16,19], "irregularly dilated and tortuous vessels" [20], and "irregular or spider vascularity" [25]. Therefore, we decided to develop a classification system by further scoring these POCS findings according to the degree of malignancy. Specifically, our F–V classification of POCS findings is based on these systematic studies. Its validity was verified by comparing it with histological diagnosis and genetic mutation analysis in biopsied specimens.

Recent advances in NGS have enabled the identification of comprehensive gene profiles of numerous cancers, including BTC, which has been reported to have frequent alterations in *TP53*, *KRAS*, *SMAD4*, and *BAP1* genes [22]. Characteristic gene alterations vary depending on the main tumor site. For example, alterations in *TP53*, *KRAS*, *BAP1*, *ARID1A*, *IDH,* and *SMAD4* are generally observed in intrahepatic cholangiocarcinoma, whereas *TP53*, *KRAS*, *SMAD4*, and *ERBB2* mutations are associated with extrahepatic cholangiocarcinoma [22,26]. *TP53* alterations are characteristic of extrahepatic cholangiocarcinoma. In our study, *TP53* mutations were the most frequently observed one in extrahepatic cholangiocarcinoma. For other mutations, we did not observe the same tendency as reported. We believe that this discrepancy may be because of the small sample size in our study, not accurately reflecting distribution of gene alterations. The VAF, also known as the mutant allele frequency, indicates tumor cellularity from extracted DNA. The VAF has been used to predict the degree of malignancy [23] and the reactivity to drugs [27] in certain tumors. Thus, we used the VAFs of biopsied bile duct specimens to classify the degree of malignancy. We found a correlation between the fraction of cases with a mutation and the F–V classification of POCS findings. The same was true for the histological diagnosis.

To select the appropriate surgical procedure, the superficial spread of a tumor should be precisely diagnosed by POCS. This is because BTC is often accompanied by superficial spread in the bile duct [6,7]. Postoperative 5-year survival rate is unaffected by positive surgical margins with carcinoma in situ [6,28]. However, because positive margins are reported to affect longer post-surgical survival, we should aim for negative surgical margins [29]. On the contrary, more extensive biliary resection may greatly increase surgical stress. Specifically, resection of the upstream bile duct requires hepatectomy, whereas the resection of the downstream bile duct requires pancreatectomy. These expanded surgical procedures are associated with the risk of surgery-related death [30]. Thus, an adequate surgery, neither excessive nor insufficient, should be chosen based on the disease extent, patient's general condition, and the imposed surgical risks. Currently, the final resection margin in BTC surgery is determined by intraoperative frozen-section diagnosis, which is not always correct [31,32]. Reports show that the epithelial layer's correct diagnosis rate is considerably lower than subepithelial layer [31]. POCS can

directly visualize the bile duct lumen with biopsy, thereby aiding the diagnosis of BTC's spread [18,20]. Here, assuming that F2V3 in F–V classification is malignant, the correct diagnosis rate of the F–V classification in stump evaluation was 100%. Therefore, we believe that the F–V classification may be more effective in the diagnosis of BTC superficial spread versus intraoperative frozen sections. Furthermore, in the future, it may become possible to determine the range of resection by POCS findings and genetic variation of the biopsy specimen. In summary, the F–V classification of POCS findings, together with intraoperative frozen-section diagnosis, may enable the precise diagnosis of a surgical stump.

Multiple clinical implications were fostered by the findings of this study. First, the F–V classification of POCS findings may guide in the assessment of the potential risks in diagnosed bile duct tumors. In a prospective multicenter study, the diagnostic accuracy of BTC superficial spread has been reported to be 83.7% (41/49) for POCS findings and 92.9% (39/42) for POCS with biopsy [19]. However, even with the addition of biopsy to the POCS diagnosis, the accuracy remains to be imperfect, probably because biopsy specimens were too small for histological diagnosis and the gray zones of the histologic characteristics that exist precluded differentiation between benignity and malignancy. As shown in Figure 4, some samples with mutations but without histological confirmation of malignancy had V2 findings by the F–V classification. In other words, a V2 finding in the F–V classification may be equivalent to a histologic diagnosis of malignancy or to a potential risk of malignancy because only this finding can allow the identification of mutated bile duct epithelium without histological confirmation of malignancy. Furthermore, in another study, we recently reported similar concepts about the relation between the endoscopic findings of colorectal tumors and genetic abnormalities [33]. Accumulated gene alterations in the adenoma components of colorectal carcinoma could be diagnosed based on irregular surface pattern findings on magnifying endoscopy. this means that a gray zone with accumulated genetic changes exists that cannot be diagnosed as malignant tumor via histology. Second, in accordance with the preceding discussion, we believe that the F–V classification may be useful in determining whether the surgical margins for the papillary and nodular expanding types of BTC are distal or perihilar. The papillary and nodular expanding types of BTC tend to show extensive spread on histology [6,28,34] and often require hepatectomy, in addition to pancreatoduodenectomy [6]. The F–V classification of POCS findings may be beneficial, especially for the gray zone that cannot be diagnosed even by biopsy.

There are several limitations in our study. First, this was a single-centered retrospective study with a small sample size. Although 36 patients underwent resection, 22 of them underwent POCS during the study period and only 11 patients who had available POCS findings and mutational analysis of the biopsied samples were included in our study. Second, no correlation was found between F-factors and mutation frequency in tissue samples, which might be because of insufficient sampling, especially of the main lesions. This could have likely reduced the chances of detecting target gene mutations. Thus, the rate of malignancy in histological diagnosis and that of genetic mutation are not high in BTC main lesions. Alternatively, different gene mutations other than those analyzed in this study might have existed in our biopsied samples. Third, there are inflammatory biliary diseases such as IgG4-related sclerosing cholangitis, which should be differentiated from BTC. We did not assess whether our POCS classification would be useful for the diagnosis of such inflammatory biliary diseases. Therefore, future prospective studies with a large sample size and the selection of more appropriate target genes may improve the correlation between the POCS findings and analysis of the biopsied specimens.

In conclusion, we classified POCS findings of BTC as "the classification of POCS findings." In addition, we evaluated its validity by performing histological diagnosis and genetic mutation analysis on biopsied specimens. Although the findings of this pilot study need further verification, we hope that this classification would help stratify the grade of malignancy around the tumor lesion and enable the selection of an appropriate surgical procedure by precisely diagnosing the superficial spread of BTC tumors.

#### **4. Materials and Methods**

#### *4.1. Patients and Samples*

We retrospectively reviewed the medical records of 11 patients who underwent POCS examination to diagnose BTC and its superficial spread before surgery at Yamanashi University Hospital between January 2013 and December 2017. We assessed 2 to 5 regions up- and downstream of the main lesion (Figure 4) and took 2–3 biopsies from each region of the bile duct using POCS, which yielded a total of 70 specimens from 11 patients. Of these specimens, 30 good quality specimens were included in the study (Table S2). The remaining 40 samples were excluded because of inability to extract DNA (*n* = 3), poor quality of the extracted DNA (*n* = 10), or duplication of collection sites (*n* = 27). When several samples were obtained from the same region, we chose those with the best size, quantity, and quality of the extracted DNA. The Human Ethics Review Committee of Yamanashi University Hospital approved this study (Receipt number: 1523, From January 2017 to March 2019).

#### *4.2. Bile Duct Biopsies Using POCS*

A video cholangioscope (CHF-B260, Olympus Medical Systems, Tokyo, Japan) with outer diameters of 3.4 and 1.2 mm was used as the baby scope. It was passed through the side-viewing mother scope (TJF-240, Olympus Medical Systems) with a 4.2-mm working channel into the bile duct using a 0.025-inch guide wire. Before inserting the baby scope into the bile duct, endoscopic sphincterotomy, or endoscopic papillary balloon dilation was performed. The bile duct was irrigated with sterile saline solution during the POCS procedure through a working channel. Furthermore, the bile duct surface was observed. Tissues were sampled according to bile duct assessment using thin biopsy forceps (Spybite Biopsy Forceps, Boston Scientific, Marlborough, MA, USA) (Figure S3). A pathologist performed histological diagnosis on hematoxylin-eosin-stained slides. Malignancy was noted as suspicious or definite. Patients were under conscious sedation using intravenous flunitrazepam (5–10 mg) during all endoscopic procedures, and all 11 cases in this study underwent ERCP with the introduction of a plastic stent or an endoscopic nasobiliary drainage tube, days before POCS. No cases of cholangitis were observed when performing POCS.

#### *4.3. Form-Vessel Classification of Bile Duct Carcinoma POCS Findings and Its Diagnostic Accuracy of Surgical Margins*

POCS findings of bile duct surface were evaluated according to the form of the bile duct surface (F factor) and vessel structure (V-factor) in the following regions: left and right hepatic duct, the confluence of the hepatic ducts, and the superior, middle, and inferior parts of the bile duct lumen in order to determine whether pancreatoduodenectomy or hepatectomy was required. We used 4 grades to classify the bile duct surface form: F1, flat pattern; F2, granular pattern; F3, papillary pattern; and F4, nodular pattern. Vessel structures were classified into 3 grades: V1, network of thin vessels; V2, irregular non-dilated vessel; and V3, irregular dilated and tortuous vessels (Figure 5). Atypicality was worse and more severe with a higher score. This classification system was named "the F–V classification of POCS findings." At least 3 gastroenterologists specialized in the bile ducts evaluated the classified findings.

In additionally, we evaluated whether the POCS findings could accurately diagnose the pathology of resected margins. We correlated the POCS findings with the site of resection by measuring the distance from the boundary line of bile duct carcinoma to the point of confirmation, such as the junction of the cystic duct and the confluence of the hepatic ducts, on both POCS examination and surgery. Moreover, the pathology of surgical stumps was evaluated on the frozen section during surgery and after resection using formalin-fixed paraffin-embedded tissues. There were 15 resected stumps in 11 cases. All of them had liver side stump. Moreover, 4 patients who had undergone hepatectomy or extrahepatic bile tract resection had duodenal side stump. The histology of resected stumps was compared with preoperative assessment by the POCS findings.

the classified findings.



**Figure 5.** F–V classification of bile duct POCS findings. Bile duct epithelium POCS findings were classified into 4 surface structure groups (F1–F4) (**A**) and 3 vessel pattern groups (V1–V3) (**B**). **Figure 5.** F–V classification of bile duct POCS findings. Bile duct epithelium POCS findings were classified into 4 surface structure groups (F1–F4) (**A**) and 3 vessel pattern groups (V1–V3) (**B**).

*Int. J. Mol. Sci.* **2020**, *21*, x FOR PEER REVIEW 11 of 14

V2, irregular non-dilated vessel; and V3, irregular dilated and tortuous vessels (Figure 5). Atypicality was worse and more severe with a higher score. This classification system was named "the F–V classification of POCS findings." At least 3 gastroenterologists specialized in the bile ducts evaluated

In additionally, we evaluated whether the POCS findings could accurately diagnose the pathology of resected margins. We correlated the POCS findings with the site of resection by measuring the distance from the boundary line of bile duct carcinoma to the point of confirmation, such as the junction of the cystic duct and the confluence of the hepatic ducts, on both POCS examination and surgery. Moreover, the pathology of surgical stumps was evaluated on the frozen section during surgery and after resection using formalin-fixed paraffin-embedded tissues. There

of resected stumps was compared with preoperative assessment by the POCS findings.

#### *4.4. Genetic Mutational Analysis of Biopsied Specimens 4.4. Genetic Mutational Analysis of Biopsied Specimens*

DNA extraction and mutational analysis of biopsied specimens were performed as previously reported [35]. Briefly, biopsied specimens were laser-capture microdissected using the ArcturusXT Laser-Capture Microdissection System (Life Technologies, Carlsbad, CA, USA). Tissue was obtained from 8-μm thick sections of formalin-fixed paraffin-embedded (FFPE) samples. DNA was extracted using the GeneRead DNA FFPE Kit (QIAGEN, Hilden, Germany), following the manufacturer's instructions. Extracted DNA quantity and quality were assessed using NanoDrop (Thermo Fisher, Waltham, MA, USA) and Qubit (Thermo Fisher) platforms. Extracted DNA (10 ng) was amplified using barcode adaptors (Ion Xpress Barcode Adapters 1-96 Kit, Life Technologies) by the Ion AmpliSeq Cancer Horspot panel v.2 (Thermo Fisher), which contains 207 primer pairs and targets DNA extraction and mutational analysis of biopsied specimens were performed as previously reported [35]. Briefly, biopsied specimens were laser-capture microdissected using the ArcturusXT Laser-Capture Microdissection System (Life Technologies, Carlsbad, CA, USA). Tissue was obtained from 8-µm thick sections of formalin-fixed paraffin-embedded (FFPE) samples. DNA was extracted using the GeneRead DNA FFPE Kit (QIAGEN, Hilden, Germany), following the manufacturer's instructions. Extracted DNA quantity and quality were assessed using NanoDrop (Thermo Fisher, Waltham, MA, USA) and Qubit (Thermo Fisher) platforms. Extracted DNA (10 ng) was amplified using barcode adaptors (Ion Xpress Barcode Adapters 1-96 Kit, Life Technologies) by the Ion AmpliSeq Cancer Horspot panel v.2 (Thermo Fisher), which contains 207 primer pairs and targets approximately 2800 hotspot mutations located in the following 50 cancer-related genes: *ABL1*, *AKT1*, *ALK*, *APC*, *ATM*, *BRAF*, *CDH1*, *CDKN2A*, *CSF1R*, *CTNNB1*, *EGFR*, *ERBB2*, *ERBB4*, *EZH2*, *FBXW7*, *FGFR1*, *FGFR2*, *FGFR3*, *FLT3*, *GNA11*, *GNAS*, *GNAQ*, *HNF1A*, *HRAS*, *IDH1*, *JAK2*, *JAK3*, *IDH2*, *KDR*/*VEGFR2*, *KIT*, *KRAS*, *MET*, *MLH1*, *MPL*, *NOTCH1*, *NPM1*, *NRAS*, *PDGFRA*, *PIK3CA*, *PTEN*, *PTPN11*, *RB1*, *RET*, *SMAD4*, *SMARCB1*, *SMO*, *SRC*, *STK11*, *TP53*, and *VHL*. Such genes are available in the COSMIC database [36]. The barcoded libraries were amplified by emulsion PCR on Ion Sphere particles. Sequencing was then performed on an Ion Chef System and an Ion Proton Sequencer (Life Technologies) using the Ion PI Hi-Q Chef Kit (Life Technologies), based on the manufacturer's instructions. Variants were identified using Ion reporter software version 5.10 (Thermo Fisher), and those with a VAF > 2% (with a sequence read depth >100) were considered true variants. The highest VAF among several mutated genes in the same sample was used as the respective sample's VAF.

## *4.5. Statistical Analysis*

Statistical analysis was performed to validate our classification system. Specifically, we used the Cochran–Armitage trend test to determine the rates of histological malignancy and gene mutation. The Jonckheere–Terpstra trend test was used to compare the VAFs between F and V factors. A *P* value of <0.05 was considered statistically significant. All statistical analyses of recorded data were performed using the Excel statistical software package (Ekuseru–Toukei 2012; Social Survey Research Information Co., Ltd., Tokyo, Japan).

**Supplementary Materials:** Supplementary materials can be found at http://www.mdpi.com/1422-0067/21/9/3311/ s1.

**Author Contributions:** Conceptualization, S.T. and M.F.; Methodology, S.T.; Software, S.M.; Validation, E.T., H.S. and M.K.; Formal Analysis, Y.F.; Investigation, Y.F.; Resources, S.H., S.K., H.H.; Data Curation, H.S., E.T.; Writing—Original Draft Preparation, S.T.; Writing—Review & Editing, S.M.; Visualization, Y.F.; Supervision, T.Y., Y.N., T.I., T.S.; Project Administration, N.E.; Funding Acquisition, S.T., N.E. All authors have read and agreed to the published version of the manuscript.

**Funding:** This study was supported by grants from Japan Society for the Promotion of Science (JSPS KAKENHI Grant Numbers: 26670380 and 18K07999; http://www.jsps.go.jp/j-grantsinaid/).

**Acknowledgments:** We thank Tomoko Nakajima and Takako Ohmori for their valuable technical assistance and Hiroko Amemiya for her secretarial assistance. Statistical analyses were performed under the advice from Hiroshi Yokomichi (BMath, MD, MPH, PhD: Department of Health Sciences, Interdisciplinary Graduate School of Medicine and Engineering, University of Yamanashi). The authors would like to thank Enago (www.enago.jp) for the English language review.

**Conflicts of Interest:** The authors declare no conflict of interest.

#### **References**


© 2020 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (http://creativecommons.org/licenses/by/4.0/).

*Article*
