Predicting Lymph Node Metastasis in Intrahepatic Cholangiocarcinoma

A snapshot on current approaches to lymphadenectomy in liver resection for intrahepatic cholangiocarcinoma: results from an international survey

The use of lymphadenectomy (LND) during resection of intrahepatic cholangiocarcinoma (ICC) is still debated, leading to differing practices in different centers and countries. The aim of this study was to assess such differences. A survey on LND for ICC was distributed to the members of the International Hepato-PancreatoBiliary Association (IHPBA) and the Italian Chapter of IHPBA (AICEP). Two-hundred thirty-four surgeons completed the survey (88% males; median age 46 years). Preoperative nodal staging was deemed mandatory/very important by 65%. Adequate LND was defined as hepatoduodenal ligament LND by 33%, LND at specific nodal stations by 28% and retrieval of > 5 nodes by 28%. The decision to perform LND was influenced by comorbidities (48%), chronic liver disease (38%) and satellitosis (32%). Most participants modify perioperative management in case of clinically positive nodes, 50% stating they would give neoadjuvant therapy. The role of LND in clinically node negative disease was adequate staging for 88%, survival benefit for 50.5% and clinical trials eligibility for 18.5%. Our survey confirms heterogeneity in the evaluation of role and extent of LND for ICC, how this relates to subjective perception of importance of LND, and need of a systematic approach in this area.

Predictive score for identifying intrahepatic cholangiocarcinoma patients without lymph node metastasis: a basis for omitting lymph node dissection

BACKGROUND

This study aimed to develop a predictive score for intrahepatic cholangiocarcinoma (ICC) in patients without lymph node metastasis (LNM) using preoperative factors.

METHODS

A retrospective analysis of 113 ICC patients who underwent liver resection with systemic lymph node dissection between 2002 and 2021 was conducted. A multivariate logistic regression analysis was used as a predictive scoring system for node-negative patients based on the β coefficients of preoperatively available factors.

RESULTS

LNM was observed in 36 patients (31.9%). Four factors were associated with LNM: suspicion of LNM on MDCT (odds ratio [OR] 13.40, p < 0.001), low-vascularity tumor (OR 6.28, p = 0.005), CA19-9 ≥500 U/mL (OR 5.90, p = 0.010), and tumor location in the left lobe (OR 3.67, p = 0.057). The predictive scoring system was created using these factors (assigning 3 points for suspected LNM on MDCT, 2 points for CA19-9 ≥500 U/mL, 2 points for low vascularity tumor, and 1 point for tumor location in the left lobe). A score cutoff value of 4 resulted in 0.861 sensitivity and a negative predictive value of 0.922 for detecting LNM. Notably, no patients with peripheral tumors and a score of ≤3 had LNM.

CONCLUSION

The developed scoring system may effectively help identify ICC patients without LNM.

Accuracy and Prognostic Impact of Nodal Status on Preoperative Imaging for Management of Pancreatic Neuroendocrine Tumors: A Multi-Institutional Study

BACKGROUND

We sought to define the accuracy of preoperative imaging to detect lymph node metastasis (LNM) among patients with pancreatic neuroendocrine tumors (pNETs), as well as characterize the impact of preoperative imaging nodal status on survival.

METHODS

Patients who underwent curative-intent resection for pNETs between 2000 and 2020 were identified from eight centers. Sensitivity and specificity of computed tomography (CT), magnetic resonance imaging (MRI), positron emission tomography (PET)-CT, and OctreoScan for LNM were evaluated. The impact of preoperative lymph node status on lymphadenectomy (LND), as well as overall and recurrence-free survival was defined.

RESULTS

Among 852 patients, 235 (27.6%) individuals had LNM on final histologic examination (hN1). The sensitivity, specificity, positive predictive value (PPV), and negative predictive value (NPV) were 12.4%, 98.1%, 71.8%, and 74.4% for CT, 6.3%, 100%, 100%, and 80.1% for MRI, 9.5%, 100%, 100%, and 58.7% for PET, 11.3%, 97.5%, 66.7%, and 70.8% for OctreoScan, respectively. Among patients with any combination of these imaging modalities, overall sensitivity, specificity, PPV, and NPV was 14.9%, 97.9%, 72.9%, and 75.1%, respectively. Preoperative N1 on imaging (iN1) was associated with a higher number of LND (iN1 13 vs. iN0 9, p = 0.003) and a higher frequency of final hN1 versus preoperative iN0 (iN1 72.9% vs. iN0 24.9%, p < 0.001). Preoperative iN1 was associated with a higher risk of recurrence versus preoperative iN0 (median recurrence-free survival, iN1→hN1 47.5 vs. iN0→hN1 92.7 months, p = 0.05).

CONCLUSIONS

Only 4% of patients with LNM on final pathologic examine had preoperative imaging that was suspicious for LNM. Traditional imaging modalities had low sensitivity to determine nodal status among patients with pNETs.

Interpretable machine learning-based clinical prediction model for predicting lymph node metastasis in patients with intrahepatic cholangiocarcinoma

OBJECTIVE

Prediction of lymph node metastasis (LNM) for intrahepatic cholangiocarcinoma (ICC) is critical for the treatment regimen and prognosis. We aim to develop and validate machine learning (ML)-based predictive models for LNM in patients with ICC.

METHODS

A total of 345 patients with clinicopathological characteristics confirmed ICC from Jan 2007 to Jan 2019 were enrolled. The predictors of LNM were identified by the least absolute shrinkage and selection operator (LASSO) and logistic analysis. The selected variables were used for developing prediction models for LNM by six ML algorithms, including Logistic regression (LR), Gradient boosting machine (GBM), Extreme gradient boosting (XGB), Random Forest (RF), Decision tree (DT), Multilayer perceptron (MLP). We applied 10-fold cross validation as internal validation and calculated the average of the areas under the receiver operating characteristic (ROC) curve to measure the performance of all models. A feature selection approach was applied to identify importance of predictors in each model. The heat map was used to investigate the correlation of features. Finally, we established a web calculator using the best-performing model.

RESULTS

In multivariate logistic regression analysis, factors including alcoholic liver disease (ALD), smoking, boundary, diameter, and white blood cell (WBC) were identified as independent predictors for LNM in patients with ICC. In internal validation, the average values of AUC of six models ranged from 0.820 to 0.908. The XGB model was identified as the best model, the average AUC was 0.908. Finally, we established a web calculator by XGB model, which was useful for clinicians to calculate the likelihood of LNM.

CONCLUSION

The proposed ML-based predicted models had a good performance to predict LNM of patients with ICC. XGB performed best. A web calculator based on the ML algorithm showed promise in assisting clinicians to predict LNM and developed individualized medical plans.

Prediction of regional lymph node metastasis in intrahepatic cholangiocarcinoma: it's not all about size

OBJECTIVES

Lymph node metastases (LNM) are frequent in patients with intrahepatic cholangiocarcinoma (iCC) and worsen their prognosis even after surgery. Our aim was to investigate the predictive value of lymph node (LN) short axis, the most common discriminator for identifying LNM in tumor-imaging and to develop a predictive model for regional LNM in iCC taking computed tomography (CT) features of extranodal disease into account.

MATERIALS AND METHODS

We enrolled 102 patients with pathologically proven iCC who underwent CT prior to hepatic resection and hilar lymph node dissection (LND) from 2005 to 2021. Two blinded radiologists assessed various imaging characteristics and LN diameters, which were analyzed by bivariate and multivariate logistic regression to develop a prediction model for LNM.

RESULTS

Prevalence of LNM was high (42.4 %) and estimated survival was shorter in LN-positive patients (p = 0.07). An LN short axis diameter of ≥ 9 mm demonstrated the highest predictive power for LNM. Three additional, statistically significant imaging features, presence of intrahepatic metastasis (p = 0.003), hilar tumor infiltration (p = 0.003), and tumor growth along the liver capsule (p = 0.004), were integrated into a prediction model, which substantially outperformed use of LN axis alone in ROC analysis (AUC 0.856 vs 0.701).

CONCLUSIONS

LN diameter alone proved to be a relevant but unreliable imaging-marker for LNM prediction in iCC. Our proposed prognostic model, which additionally considers intrahepatic metastases and hilar and capsular infiltration, significantly improves discriminatory power. Hilar and capsular involvement might indicate direct tumor extension to lymphatic liver structures.

Preoperative prediction model for microvascular invasion in HBV-related intrahepatic cholangiocarcinoma

BACKGROUND AND AIMS

Preoperative prediction of microvascular invasion (MVI) using a noninvasive method remain unresolved, especially in HBV-related in intrahepatic cholangiocarcinoma (ICC). This study aimed to build and validate a preoperative prediction model for MVI in HBV-related ICC.

METHODS

Patients with HBV-associated ICC undergoing curative surgical resection were identified. Univariate and multivariate logistic regression analyses were performed to determine the independent risk factors of MVI in the training cohort. Then, a prediction model was built by enrolling the independent risk factors. The predictive performance was validated by receiver operator characteristic curve (ROC) and calibration in the validation cohort.

RESULTS

Consecutive 626 patients were identified and randomly divided into the training (418, 67%) and validation (208, 33%) cohorts. Multivariate analysis showed that TBIL, CA19-9, tumor size, tumor number, and preoperative image lymph node metastasis were independently associated with MVI. Then, a model was built by enrolling former fiver risk factors. In the validation cohort, the performance of this model showed good calibration. The area under the curve was 0.874 (95% CI: 0.765-0.894) and 0.729 (95%CI: 0.706-0.751) in the training and validation cohort, respectively. Decision curve analysis showed an obvious net benefit from the model.

CONCLUSION

Based on clinical data, an easy model was built for the preoperative prediction of MVI, which can assist clinicians in surgical decision-making and adjuvant therapy.

A preoperative scoring system to predict lymph node metastasis in intrahepatic cholangiocarcinoma

BACKGROUND

The abnormality of imaging finding of lymph node (LN) has demonstrated unsatisfactory diagnostic accuracy for pathologic lymph node metastasis (LNM). We aimed to develop and validate a simple scoring system predicting LNM in patients with intrahepatic cholangiocarcinoma (iCCA) prior to surgery based on MRI and clinical findings.

METHODS

We retrospectively enrolled consecutive patients who underwent surgical resection for treatment-naïve iCCA from six institutions between January 2009 and December 2015. Patients who underwent lymph node dissection (LND) were randomly assigned to the training and validation cohorts at a 2:1 ratio, an¹ìd pathologic LN status was evaluated. Patients who did not undergo LND were assigned to the test cohort, and clinical LN status was evaluated. Using MRI and clinical findings, a preoperative LNM score was developed in the training cohort and validated in the validation and test cohorts.

RESULTS

The training, validation, and test cohorts included 102, 53, and 118 patients, respectively. The preoperative LNM score consisted of serum carcinoembryonic antigen and two MRI findings (suspicious LN and bile duct invasion). The preoperative LNM score was associated with pathologic LNM in training (p < 0.001) and validation (p = 0.010) cohorts and clinical LNM in test cohort (p < 0.001). The preoperative LNM score outperformed MRI-suspicious LN alone in predicting pathologic LNM (area under the curve, 0.703 vs. 0.604, p = 0.004). The preoperative LNM score was also associated with overall survival in all cohorts (p < 0.001).

CONCLUSIONS

Our preoperative LNM score was significantly associated with pathologic or clinical LNM and outperformed MRI-suspicious LN alone.

Prognostic Role of the Intrahepatic Lymphatic System in Liver Cancer

Although several prognosticators, such as lymph node metastasis (LNM), were reported for hepatocellular carcinoma (HCC) and intrahepatic cholangiocarcinoma (ICC), the prognostic impact of intrahepatic lymphatic vessel invasion (LVI) in liver cancer has rarely been reported. We sought to clarify the prognostic impact of intrahepatic lymphatic system involvement in liver cancer. We systematically reviewed retrospective studies that described LVI and clinical outcomes of liver cancer and also included studies that investigated tumor-associated lymphangiogenesis. We conducted a meta-analysis using RevMan software (version 5.4.1; Cochrane Collaboration, Oxford, UK). The prognostic impact of intrahepatic LVI in HCC was not reported previously. However, tumor-associated lymphangiogenesis reportedly correlates with prognosis after HCC resection. The prognostic impact of intrahepatic LVI was reported severally for ICC and a meta-analysis showed that overall survival was poorer in patients with positive LVI than with negative LVI after resection of ICC. Lymphangiogenesis was also reported to predict unfavorable prognosis in ICC. Regarding colorectal liver metastases, LVI was identified as a poor prognosticator in a meta-analysis. A few reports showed correlations between LVI/lymphangiogenesis and LNM in liver cancer. LVI and lymphangiogenesis showed worse prognostic impacts for liver cancer than their absence, but further study is needed.

Higher Tumor Burden Status Dictates the Impact of Surgical Margin Status on Overall Survival in Patients Undergoing Resection of Intrahepatic Cholangiocarcinoma

BACKGROUND

The present study aimed to examine the prognostic significance of margin status following hepatectomy of intrahepatic cholangiocarcinoma (ICC) relative to overall tumor burden and nodal status.

METHOD

Patients who underwent curative-intent surgery for ICC between 1990 and 2017 were included from a multi-institutional database. The impact of margin status and width on overall survival (OS) was examined relative to TBS and preoperative nodal status.

RESULTS

Among 1105 patients with ICC who underwent resection, median tumor burden score (TBS) was 6.1 (IQR 4.2-8.8) and 218 (19.7%) patients had N1 disease. More than one in eight patients had an R1 surgical margin (n = 154, 13.9%). Among patients with low or medium TBS, an increasing margin width was associated with an incrementally improved 5-year OS (R1 31.9% vs. 1-3 mm 38.5% vs. 3-10 mm 48.0% vs. ≥ 10 mm 52.3%). In contrast, among patients with a high TBS, margin width was not associated with better survival (R1 28.9% vs. 1-3 mm 22.8% vs. 3-10 mm 29.6% vs. ≥ 10 mm 13.7%). In addition, surgical margin status did not impact survival with cutoffs of TBS 7 or greater. Furthermore, patients with low or medium TBS and preoperative negative lymph nodes derived a survival benefit from an R0 resection (R1 resection, HR 2.15, 95% CI 1.35-3.44, p = 0.001). In contrast, margin status was not associated with prognosis among patients with a high TBS and preoperative positive/suspicious lymph nodes (R1 resection, HR 1.34, 95% CI 0.58-3.11, p = 0.50).

CONCLUSION

R0 resection and wider margin resection resulted in improved outcomes in patients with low tumor burden; however, the survival benefit of negative margin status disappeared in patients with underlying poor tumor biology.

Application of Hazard Function to Investigate Recurrence of Intrahepatic Cholangiocarcinoma After Curative-Intent Liver Resection: A Novel Approach to Characterize Recurrence

PURPOSE

To investigate recurrence patterns after surgery for intrahepatic cholangiocarcinoma (ICC) relative to lymph node status, tumor extension, tumor burden score (TBS), and adjuvant chemotherapy.

METHODS

Patients who underwent curative-intent resection for ICC from 1990 to 2020 were enrolled from a multi-institutional database. The hazard function was applied to plot the hazard rates over time, with further stratification by T and N AJCC 8th edition categories, TBS, and adjuvant chemotherapy.

RESULTS

A total of 1192 patients underwent curative-intent resection for ICC and 59.9% experienced recurrence. Overall, the peak of recurrence occurred at 6.6 months. Among patients with negative lymph nodes, the T4-category had a higher peak rate of recurrence (0.1199 at 10.2 months) compared with other T-categories, while high TBS had an earlier peak of recurrence (4.2 months) compared with lower TBS. Among patients with N1 disease, T2-T4 categories had multipeak patterns of recurrence with higher hazard rates during the first 3 years after surgery in comparison with T1-category, while patients with high TBS had an earlier (4.0 months) and higher hazard peak rate compared with lower TBS groups. The administration of adjuvant chemotherapy was associated with delayed hazard rates of recurrence for N1 (4 months) and NX (6 months) categories.

DISCUSSION

The novel application of the hazard function to assess hazard rates and timing patterns of recurrence following resection for ICC demonstrated that recurrence varied based on T- and N-categories, as well as TBS. Hazard function-based recurrence data may be helpful to tailor counseling, surveillance, and adjuvant therapy recommendations.

The impact of tumor location on the value of lymphadenectomy for intrahepatic cholangiocarcinoma

BACKGROUND

The therapeutic role of lymphadenectomy (LND) for intrahepatic cholangiocarcinoma (ICC) patients remains ill-defined. We sought to analyze the therapeutic value of LND relative to tumor location and preoperative lymph node metastasis (LNM) risk.

METHODS

Patients who underwent curative-intent hepatic resection of ICC between 1990 and 2020 were included from a multi-institutional database. Therapeutic LND (tLND) was defined as LND that harvested ≥3 lymph nodes.

RESULTS

Among 662 patients, 178 (26.9%) individuals received tLND. Patients were categorized into central type ICC (n = 156, 23.6%) and peripheral type ICC (n = 506, 76.4%). Central type harbored multiple adverse clinicopathologic factors and worse overall survival (OS) compared with peripheral type (5-year OS, central: 27.0% vs. peripheral: 47.2%, p < 0.001). After consideration of preoperative LNM risk, patients with central type and high-risk LNM who underwent tLND survived longer than individuals who did not (5-year OS, tLND: 27.9% vs. non-tLND: 9.0%, p = 0.001), whereas tLND was not associated with better survival among patients with peripheral type ICC or low-risk LNM. The therapeutic index of hepatoduodenal ligament (HDL) and other regions was higher in central type than in peripheral type, which was more pronounced among high-risk LNM patients.

CONCLUSIONS

Central type ICC with high-risk LNM should undergo LND involving regions beyond the HDL.

A Novel Online Calculator to Predict Risk of Microvascular Invasion in the Preoperative Setting for Hepatocellular Carcinoma Patients Undergoing Curative-Intent Surgery

BACKGROUND

The presence of microvascular invasion (MVI) has been highlighted as an important determinant of hepatocellular carcinoma (HCC) prognosis. We sought to build and validate a novel model to predict MVI in the preoperative setting.

METHODS

Patients who underwent curative-intent surgery for HCC between 2000 and 2020 were identified using a multi-institutional database. Preoperative predictive models for MVI were built, validated, and used to develop a web-based calculator.

RESULTS

Among 689 patients, MVI was observed in 323 patients (46.9%). On multivariate analysis in the test cohort, preoperative parameters associated with MVI included α-fetoprotein (AFP; odds ratio [OR] 1.50, 95% confidence interval [CI] 1.23-1.83), imaging tumor burden score (TBS; hazard ratio [HR] 1.11, 95% CI 1.04-1.18), and neutrophil-to-lymphocyte ratio (NLR; OR 1.18, 95% CI 1.03-1.35). An online calculator to predict MVI was developed based on the weighted β-coefficients of these three variables ( https://yutaka-endo.shinyapps.io/MVIrisk/ ). The c-index of the test and validation cohorts was 0.71 and 0.72, respectively. Patients with a high risk of MVI had worse disease-free survival (DFS) and overall survival (OS) compared with low-risk MVI patients (3-year DFS: 33.0% vs. 51.9%, p < 0.001; 5-year OS: 44.2% vs. 64.8%, p < 0.001). DFS was worse among patients who underwent an R1 versus R0 resection among those patients at high risk of MVI (R0 vs. R1 resection: 3-year DFS, 36.3% vs. 16.1%, p = 0.002). In contrast, DFS was comparable among patients at low risk of MVI regardless of margin status (R0 vs. R1 resection: 3-year DFS, 52.9% vs. 47.3%, p = 0.16).

CONCLUSION

Preoperative assessment of MVI using the online tool demonstrated very good accuracy to predict MVI.

Preoperative prediction of intrahepatic cholangiocarcinoma lymph node metastasis by means of machine learning: a multicenter study in China

Background

Hepatectomy is currently the most effective modality for the treatment of intrahepatic cholangiocarcinoma (ICC). The status of the lymph nodes directly affects the choice of surgical method and the formulation of postoperative treatment plans. Therefore, a preoperative judgment of lymph node status is of great significance for patients diagnosed with this condition. Previous prediction models mostly adopted logistic regression modeling, and few relevant studies applied random forests in the prediction of ICC lymph node metastasis (LNM).

Methods

A total of 149 ICC patients who met clinical conditions were enrolled in the training group. Taking into account preoperative clinical data and imaging features, 21 indicators were included for analysis and modeling. Logistic regression was used to filter variables through multivariate analysis, and random forest regression was used to rank the importance of these variables through the use of algorithms. The model’s prediction accuracy was assessed by the concordance index (C-index) and calibration curve and validated with external data.

Result

Multivariate analysis shows that Carcinoembryonic antigen (CEA), Carbohydrate antigen19-9 (CA19-9), and lymphadenopathy on imaging are independent risk factors for lymph node metastasis. The random forest algorithm identifies the top four risk factors as CEA, CA19-9, and lymphadenopathy on imaging and Aspartate Transaminase (AST). The predictive power of random forest is significantly better than the nomogram established by logistic regression in both the validation group and the training group (Area Under Curve reached 0.758 in the validation group).

Conclusions

We constructed a random forest model for predicting lymph node metastasis that, compared with the traditional nomogram, has higher prediction accuracy and simultaneously plays an auxiliary role in imaging examinations.

Radiomics-Based Preoperative Prediction of Lymph Node Metastasis in Intrahepatic Cholangiocarcinoma Using Contrast-Enhanced Computed Tomography

BACKGROUND

Lymph node (LN) metastasis is significantly associated with worse prognosis for patients with intrahepatic cholangiocarcinoma (ICC). Improvement in preoperative assessment on LN metastasis helps in treatment decision-making. We aimed to investigate the role of radiomics-based method in predicting LN metastasis for patients with ICC.

METHODS

A total of 296 patients with ICC who underwent curative-intent hepatectomy and lymphadenectomy at two centers in China were analyzed. Radiomic features, including histogram- and wavelet-based features, shape and size features, and texture features were extracted from four-phase computerized tomography (CT) images. The clinical and conventional radiological variables which were independently associated with LN metastasis were also identified. A combined nomogram predicting LN metastasis was developed, and its performance was determined by discrimination, calibration, and stratification of long-term prognosis. The results were validated by the internal and external validation cohorts.

RESULTS

Twenty-four radiomic features were selected into the nomogram. The established nomogram demonstrated good discrimination and calibration, with areas under the curve (AUCs) of 0.98 [95% confidence interval (CI) 0.96-0.99], 0.93 (0.88-0.98), and 0.89 (0.81-0.96) in the training and two validation cohorts, respectively. The 5-year overall survival (OS) and recurrence-free survival (RFS) rates of patients with high risk of LN metastasis as grouped by nomogram were poorer than those of patients with low risk in the training cohort (OS 28.8% versus 53.9%, p < 0.001; RFS 26.3% versus 44.2%, p = 0.001). Similar results were observed in the two validation cohorts.

CONCLUSIONS

Radiomics-based method provided accurate prediction of LN metastasis and prognostic assessment for ICC patients, and might aid the preoperative surgical decision.

Predicting Disease-Specific Survival for Patients With Primary Cholangiocarcinoma Undergoing Curative Resection by Using a Decision Tree Model

Background

The aim of this study was to derive and validate a decision tree model to predict disease-specific survival after curative resection for primary cholangiocarcinoma (CCA).

Method

Twenty-one clinical characteristics were collected from 482 patients after curative resection for primary CCA. A total of 289 patients were randomly allocated into a training cohort and 193 were randomly allocated into a validation cohort. We built three decision tree models based on 5, 12, and 21 variables, respectively. Area under curve (AUC), sensitivity, and specificity were used for comparison of the 0.5-, 1-, and 3-year decision tree models and regression models. AUC and decision curve analysis (DCA) were used to determine the predictive performances of the 0.5-, 1-, and 3-year decision tree models and AJCC TNM stage models.

Results

According to the fitting degree and the computational cost, the decision tree model derived from 12 variables displayed superior predictive efficacy to the other two models, with an accuracy of 0.938 in the training cohort and 0.751 in the validation cohort. Maximum tumor size, resection margin, lymph node status, histological differentiation, TB level, ALBI, AKP, AAPR, ALT, γ-GT, CA19-9, and Child-Pugh grade were involved in the model. The performances of 0.5-, 1-, and 3-year decision tree models were better than those of conventional models and AJCC TNM stage models.

Conclusion

We developed a decision tree model to predict outcomes for CCA undergoing curative resection. The present decision tree model outperformed other clinical models, facilitating individual decision-making of adjuvant therapy after curative resection.

Serum Angiopoietin-Like Protein 4: A Potential Prognostic Biomarker for Prediction of Vascular Invasion and Lymph Node Metastasis in Cholangiocarcinoma Patients

Cholangiocarcinoma (CCA) is a tumor arising from cholangiocytes lining the bile ducts. Vascular invasion and lymph node metastasis are important prognostic factors for disease staging as well as clinical therapeutic decisions for CCA patients. In the present study, we applied CCA sera proteomic analysis to identify a potential biomarker for prognosis of CCA patients. Then, using bioinformatics tools, we identified angiopoietin-like protein 4 (ANGPTL4) which expressed highest signal intensity among candidate proteins in proteomic analysis of CCA sera. Expression of ANGPTL4 in CCA tissues was determined using immunohistochemistry. The results showed that ANGPTL4 was stained at higher level in CCA cells when compared with normal cholangiocytes. The high expression of ANGPTL4 was associated with lymph node metastasis and advanced tumor stage (p = 0.013 and p = 0.031, respectively). Furthermore, serum ANGPTL4 levels in CCA and healthy control (HC) were analyzed using a dot blot assay. And it was found that ANGPTL4 level was significantly higher in CCA than HC group (p < 0.0001). ROC curve analysis revealed that serum ANGPTL4 level was effectively distinguished CCA from healthy patients (cutoff = 0.2697 arbitrary unit (AU), 80.0% sensitivity, 72.7% specificity, AUC = 0.825, p < 0.0001). Serum ANGPTL4 level was associated with vascular invasion and lymph node metastasis (p = 0.0004 and p = 0.006), so that it differentiated CCA with vascular invasion from CCA without vascular invasion (cutoff = 0.5526 AU, 64.9% sensitivity, 92.9% specificity, AUC = 0.751, p = 0.006) and it corresponded to CCA with/without lymph node metastasis (cutoff = 0.5399 AU, 71.4% sensitivity, 70.8% specificity, AUC = 0.691, p = 0.01) by ROC analysis. Serum ANGPTL4 levels showed superior predictive efficiency compared with CA 19-9 and CEA for vascular invasion and lymph node metastasis. In addition, serum ANGPTL4 level was an independent predictive indicator by multivariate regression analysis. In conclusion, serum ANGPTL4 could be a novel prognostic biomarker for prediction of vascular invasion and lymph node metastasis of CCA patients.

Results of Intrahepatic Cholangiocarcinoma Resections: a Single-Center Analysis

INTRODUCTION

Intrahepatic cholangiocarcinoma (ICC) is the second most common primary neoplasm of the liver after hepatocellular carcinoma (HCC). Although an underlying cause is not usually found, liver flukes, cirrhosis, primary sclerosing cholangitis, and viral hepatitis have been found to increase the risk in recent years. In this study, we aimed to present our experience on ICC and compare the outcomes of patients with a concomitant liver pathology and with incidentally detected ICC.

PATIENTS AND METHODS

Thirty-three patients who underwent surgical resection for ICC were included in the study. Patients were divided into two groups, group one (with concomitant liver disease, n = 13) and group two (incidentally detected ICC, n = 18). Demographics, perioperative findings, pathological properties, recurrence rates, and survival rates were retrospectively analyzed and compared between the groups.

RESULTS

The mean age of patients was 59.77 ± 9.81 years, of whom sixteen (51.6%) were males. Thirteen patients (41.9%) had concomitant liver disease, the most common being chronic hepatitis B infection. Eighteen patients (58.1%) had incidentally detected ICC. There were no significant differences between the groups except for follow-up time and recurrence rate. The recurrence rate was significantly higher in the incidentally detected ICC group (61.1% versus 7.7%, p = 0.003). Follow-up time was significantly higher in patients with concomitant liver disease (42 versus 17.5 months, p = 0.007). The mortality rate was higher in the incidentally detected ICC group (55.6 to 23.1%, p = 0.071) but the difference did not reach statistical significance.

CONCLUSION

Surgical resection in ICC patients with underlying liver disease is associated with better prognosis than in incidentally detected ICC patients. Incidental ICC may be a different tumor with different biology, hence the high recurrence rates.

Predicting prognosis and evaluating the benefits of adjuvant chemotherapy depending on the tumor location in intrahepatic cholangiocarcinoma: focusing on the involvement of below 2nd bile duct confluence

Purpose

Intrahepatic cholangiocarcinoma (ICC) has various characteristics according to anatomical, histologic classifications, and its prognoses are different. This study aimed to compare oncologic outcomes according to tumor location (second bile duct confluence) and evaluate the effect of adjuvant chemotherapy.

Methods

Clinical data of 318 patients who underwent curative resection for ICC was reviewed. Central type ICC (C-ICC) and peripheral type ICC (P-ICC) were defined when the tumor invades the intrahepatic secondary biliary confluence and when located more peripherally, respectively.

Results

A larger tumor size, higher rate of elevated CA 19-9 level, vascular invasion, R1 resection, advanced T stage, and lymph node metastasis were found in C-ICC. C-ICC had poorer overall survival (median, 33 months vs. 58 months; P = 0.001), and the difference was more prominent in the early stage. C-ICC had a higher recurrence rate (68.7% vs. 55.1%, P = 0.014); otherwise, there was no difference in the recurrence patterns. There were no survival benefits of adjuvant chemotherapy in the entire cohort, but there were benefits in advanced stages (T3–4, N1 stage), especially in C-ICC.

Conclusion

C-ICC has more aggressive tumor characteristics and poor survival compared to P-ICC. Adjuvant chemotherapy seems to have survival benefits in the advanced stages, especially in the central type.

The State of Immunotherapy in Hepatobiliary Cancers

Hepatobiliary cancers, including hepatocellular carcinoma (HCC), cholangiocarcinoma (CCA), and gallbladder carcinoma (GBC), are lethal cancers with limited therapeutic options. Curative-intent treatment typically involves surgery, yet recurrence is common and many patients present with advanced disease not amenable to an operation. Immunotherapy represents a promising approach to improve outcomes, but the immunosuppressive tumor microenvironment of the liver characteristic of hepatobiliary cancers has hampered the development and implementation of this therapeutic approach. Current immunotherapies under investigation include immune checkpoint inhibitors (ICI), the adoptive transfer of immune cells, bispecific antibodies, vaccines, and oncolytic viruses. Programmed cell death protein 1 (PD-1) and cytotoxic T-lymphocyte-associated protein 4 (CTLA-4) are two ICIs that have demonstrated utility in HCC, and newer immune checkpoint targets are being tested in clinical trials. In advanced CCA and GBC, PD-1 ICIs have resulted in antitumor responses, but only in a minority of select patients. Other ICIs are being investigated for patients with CCA and GBC. Adoptive transfer may hold promise, with reports of complete durable regression in metastatic CCA, yet this therapeutic approach may not be generalizable. Alternative approaches have been developed and promising results have been observed, but clinical trials are needed to validate their utility. While the treatment of hepatobiliary cancers involves unique challenges that these cancers present, the progress seen with ICIs and adoptive transfer has solidified immunotherapy as an important approach in these challenging patients with few other effective treatment options.

Intrahepatic Cholangiocarcinoma with Lymph Node Metastasis: Treatment-Related Outcomes and the Role of Tumor Genomics in Patient Selection

PURPOSE

Lymph node metastasis (LNM) drastically reduces survival after resection of intrahepatic cholangiocarcinoma (IHC). Optimal treatment is ill defined, and it is unclear whether tumor mutational profiling can support treatment decisions.

EXPERIMENTAL DESIGN

Patients with liver-limited IHC with or without LNM treated with resection (N = 237), hepatic arterial infusion chemotherapy (HAIC; N = 196), or systemic chemotherapy alone (SYS; N = 140) at our institution between 2000 and 2018 were included. Genomic sequencing was analyzed to determine whether genetic alterations could stratify outcomes for patients with LNM.

RESULTS

For node-negative patients, resection was associated with the longest median overall survival [OS, 59.9 months; 95% confidence interval (CI), 47.2-74.31], followed by HAIC (24.9 months; 95% CI, 20.3-29.6), and SYS (13.7 months; 95% CI, 8.9-15.9; P < 0.001). There was no difference in survival for node-positive patients treated with resection (median OS, 19.7 months; 95% CI, 12.1-27.2) or HAIC (18.1 months; 95% CI, 14.1-26.6; P = 0.560); however, survival in both groups was greater than SYS (11.2 months; 95% CI, 14.1-26.6; P = 0.024). Node-positive patients with at least one high-risk genetic alteration (TP53 mutation, KRAS mutation, CDKN2A/B deletion) had worse survival compared to wild-type patients (median OS, 12.1 months; 95% CI, 5.7-21.5; P = 0.002), regardless of treatment. Conversely, there was no difference in survival for node-positive patients with IDH1/2 mutations compared to wild-type patients.

CONCLUSIONS

There was no difference in OS for patients with node-positive IHC treated by resection versus HAIC, and both treatments had better survival than SYS alone. The presence of high-risk genetic alterations provides valuable prognostic information that may help guide treatment.