Neoadjuvant and Adjuvant Therapy in Intrahepatic Cholangiocarcinoma

Research progress and prospect of postoperative adjuvant therapy for resectable intrahepatic cholangiocarcinoma

Intrahepatic cholangiocarcinoma (ICC) is the second most common primary malignancy of the liver, following hepatocellular carcinoma (HCC). Surgical resection remains the only potentially curative treatment for ICC. However, due to its high malignancy and propensity for postoperative recurrence, the prognosis for ICC is generally poor, and there is currently little standardized approach for adjuvant therapy following curative surgery. This article aims to explore adjuvant treatment strategies for ICC post-curative surgery by reviewing retrospective studies and clinical trials conducted in recent years. The analysis focuses on the effectiveness, challenges, and potential developments in the management of ICC post-surgery, considering the high recurrence rates and the need for improved therapeutic approaches to enhance patient outcomes. Additionally, we discuss the various types of adjuvant treatments that have been explored, including chemotherapy, radiation therapy, and targeted therapies. The goal is to provide a comprehensive overview of the current landscape and highlight promising directions for future research to improve survival and quality of life for ICC patients.

Impact of Lymph Node Dissection for Patients With Clinically Node-Negative Intrahepatic Cholangiocarcinoma: A Multicenter Cohort Study

Background

Lymph node status is a prominent prognostic factor for intrahepatic cholangiocarcinoma (ICC). However, the prognostic value of performing lymph node dissection (LND) in patients with clinical node-negative ICC remains controversial. The aim of this study was to evaluate the clinical value of LND on long-term outcomes in this subgroup of patients.

Methods

We retrospectively analyzed patients who underwent radical liver resection for clinically node-negative ICC from three tertiary hepatobiliary centers. The propensity score matching analysis at 1:1 ratio based on clinicopathological data was conducted between patients with and without LND. Recurrence-free survival (RFS) and overall survival (OS) were compared in the matched cohort.

Results

Among 303 patients who underwent radical liver resection for ICC, 48 patients with clinically positive nodes were excluded, and a total of 159 clinically node-negative ICC patients were finally eligible for the study, with 102 in the LND group and 57 in the non-LND group. After propensity score matching, two well-balanced groups of 51 patients each were analyzed. No significant difference of median RFS (12.0 vs. 10.0 months, P = 0.37) and median OS (22.0 vs. 26.0 months, P = 0.47) was observed between the LND and non-LND group. Also, LND was not identified as one of the independent risks for survival. Among 51 patients who received LND, 11 patients were with positive lymph nodes (lymph node metastasis (LNM) (+)) and presented significantly worse outcomes than those with LND (-). On the other hand, postoperative adjuvant therapy was the independent risk factor for both RFS (hazard ratio (HR): 0.623, 95% confidence interval (CI): 0.393 - 0.987, P = 0.044) and OS (HR: 0.585, 95% CI: 0.359 - 0.952, P = 0.031). Furthermore, postoperative adjuvant therapy was associated with prolonged survivals of non-LND patients (P = 0.02 for RFS and P = 0.03 for OS).

Conclusions

Based on the data, we found that LND did not significantly improve the prognosis of patients with clinically node-negative ICC. Postoperative adjuvant therapy was associated with prolonged survival of ICC patients, especially in non-LND individuals.

Machine learning to predict the early recurrence of intrahepatic cholangiocarcinoma: A systematic review and meta‑analysis

The prediction of early recurrent of intrahepatic cholangiocarcinoma (ICC) has been widely investigated; however, the predictive value is currently insufficient. To determine the effectiveness of machine learning (ML) for the diagnosis of early recurrent intrahepatic cholangiocarcinoma (ICC), particularly in comparison with clinical models, the present study aimed to determine which ML model had the best diagnostic performance for inpatients with recurrent ICC. In order to search for studies which could be included, three electronic databases were screened from inception to November 2023. A pairwise meta-analysis was performed to evaluate the diagnostic accuracy of the random effects model. A network meta-analysis was performed to identify the most effective ML-based diagnostic model based on the surface under the cumulative ranking curve score. A total of 5 studies of acceptable quality containing 1,247 patients with ICC were included in the present study. Following pairwise meta-analysis, it was found that the ML-based diagnostic accuracy was greater than that of clinical models (surface under the cumulative ranking curve score closer to 1, with significant differences), which initially proved that the ML-based diagnostic power was more optimal than that of clinical models. According to the network meta-analysis, the nomogram performed the best, indicating that this ML model achieved the best diagnostic accuracy for patients with recurrent ICC. In conclusion, the application of ML-based diagnostic models for patients with recurrent ICC was more optimal than the application of the clinical model. The nomogram model ranked first among the models and is therefore recommended for patients with recurrent ICC.

The benefits of an offline to online cognitive behavioral stress management regarding anxiety, depression, spiritual well-being, and quality of life in postoperative intrahepatic cholangiocarcinoma patients

AIM

Cognitive behavioral stress management (CBSM) has been introduced for the postoperative cancer management, but its application in intrahepatic cholangiocarcinoma (ICC) is rare. This current study constructed an offline to online CBSM (OO-CBSM) program and applying multiple assessing scales, aiming at exploring the benefits of OO-CBSM regarding anxiety, depression, spiritual well-being, and quality of life (QoL) in postoperative ICC patients.

METHODS

The study randomly assigned 68 postoperative ICC patients into OO-CBSM (N = 34) and normal care (NC) (N = 34) groups to undergo 10-week interventions. Hospital anxiety-and-depression scale (HADS), Zung's self-reporting anxiety scale (SAS), and depression scale (SDS), functional-assessment of chronic-illness therapy-spiritual well-being scale (FACIT-Sp), European quality-of-life-5 dimensions (EQ-5D), and quality-of-life questionnaire-core30 (QLQ-C30) were assessed within 6 months (M).

RESULTS

HADS-anxiety scores at M3 (P = 0.049) and M6 (P = 0.009), SAS score at M6 (P = 0.028), HADS-depression score at M3 (P = 0.043), and SDS scores at M3 (P = 0.044) and M6 (P = 0.028), were lower in the OO-CBSM group versus the NC group. Meanwhile, FACIT-Sp scores at M1 (P = 0.042) and M6 (P = 0.003) were higher in the OO-CBSM group over the NC group. Besides, EQ-5D scores at M3 (P = 0.067) and M6 (P = 0.087) disclosed trends to be lower in the OO-CBSM group versus the NC group, but not statistically significant. QLQ-C30-global-health scores at M3 (P = 0.049) and M6 (P = 0.033), and QLQ-C30-function score at M6 (P = 0.046), were higher in OO-CBSM group over NC group; but QLQ-C30-symptom score was not significantly different at any timepoints between them.

CONCLUSION

OO-CBSM attenuates anxiety and depression, and advances spiritual well-being and QoL in postoperative ICC patients, indicating its potency for the ICC postoperative management.

Liver transplantation for intrahepatic cholangiocarcinoma: who, when and how

PURPOSE OF REVIEW

Using transplant oncology principles, selected patients with intrahepatic cholangiocarcinoma (iCCA) may achieve long-term survival after liver transplantation. Strategies for identifying and managing these patients are discussed in this review.

RECENT FINDINGS

Unlike initial reports, several modern series have reported positive outcomes after liver transplantation for iCCA. The main challenges are in identifying the appropriate candidates and graft scarcity. Tumor burden and response to neoadjuvant therapies have been successfully used to identify favorable biology in unresectable cases. New molecular biomarkers will probably predict this response in the future. Also, new technologies and better strategies have been used to increase graft availability for these patients without affecting the liver waitlist.

SUMMARY

Liver transplantation for the management of patients with unresectable iCCA is currently a reality under strict research protocols. Who is a candidate for transplantation, when to use neoadjuvant and locoregional therapies, and how to increase graft availability are the main topics of this review.

Noninvasive prediction of perineural invasion in intrahepatic cholangiocarcinoma by clinicoradiological features and computed tomography radiomics based on interpretable machine learning: a multicenter cohort study

BACKGROUND

Perineural invasion (PNI) of intrahepatic cholangiocarcinoma (ICC) is a strong independent risk factor for tumour recurrence and long-term patient survival. However, there is a lack of noninvasive tools for accurately predicting the PNI status. The authors develop and validate a combined model incorporating radiomics signature and clinicoradiological features based on machine learning for predicting PNI in ICC, and used the Shapley Additive explanation (SHAP) to visualize the prediction process for clinical application.

METHODS

This retrospective and prospective study included 243 patients with pathologically diagnosed ICC (training, n =136; external validation, n =81; prospective, n =26, respectively) who underwent preoperative contrast-enhanced computed tomography between January 2012 and May 2023 at three institutions (three tertiary referral centres in Guangdong Province, China). The ElasticNet was applied to select radiomics features and construct signature derived from computed tomography images, and univariate and multivariate analyses by logistic regression were used to identify the significant clinical and radiological variables with PNI. A robust combined model incorporating radiomics signature and clinicoradiological features based on machine learning was developed and the SHAP was used to visualize the prediction process. A Kaplan-Meier survival analysis was performed to compare prognostic differences between PNI-positive and PNI-negative groups and was conducted to explore the prognostic information of the combined model.

RESULTS

Among 243 patients (mean age, 61.2 years ± 11.0 (SD); 152 men and 91 women), 108 (44.4%) were diagnosed as PNI-positive. The radiomics signature was constructed by seven radiomics features, with areas under the curves of 0.792, 0.748, and 0.729 in the training, external validation, and prospective cohorts, respectively. Three significant clinicoradiological features were selected and combined with radiomics signature to construct a combined model using machine learning. The eXtreme Gradient Boosting exhibited improved accuracy and robustness (areas under the curves of 0.884, 0.831, and 0.831, respectively). Survival analysis showed the construction combined model could be used to stratify relapse-free survival (hazard ratio, 1.933; 95% CI: 1.093-3.418; P =0.021).

CONCLUSIONS

We developed and validated a robust combined model incorporating radiomics signature and clinicoradiological features based on machine learning to accurately identify the PNI statuses of ICC, and visualize the prediction process through SHAP for clinical application.

Predictive Model of Oxaliplatin-induced Liver Injury Based on Artificial Neural Network and Logistic Regression

Background and Aims

Identifying potential high-risk groups of oxaliplatin-induced liver injury (OILI) is valuable, but tools are lacking. So artificial neural network (ANN) and logistic regression (LR) models will be developed to predict the risk of OILI.

Methods

The medical information of patients treated with oxaliplatin between May and November 2016 at 10 hospitals was collected prospectively. We used the updated Roussel Uclaf causality assessment method (RUCAM) to identify cases of OILI and summarized the patient and medication characteristics. Furthermore, the ANN and LR models for predicting the risk of OILI were developed and evaluated.

Results

The incidence of OILI was 3.65%. The median RUCAM score with interquartile range was 6 (4, 9). The ANN model performed similarly to the LR model in sensitivity, specificity, and accuracy. In discrimination, the area under the curve of the ANN model was larger (0.920>0.833, p=0.019). In calibration, the ANN model was slightly improved. The important predictors of both models overlapped partially, including age, chemotherapy regimens and cycles, single and total dose of OXA, glucocorticoid drugs, and antihistamine drugs.

Conclusions

When the discriminative and calibration ability was given priority, the ANN model outperformed the LR model in predicting the risk of OILI. Other chemotherapy drugs in oxaliplatin-based chemotherapy regimens could have different degrees of impact on OILI. We suspected that OILI may be idiosyncratic, and chemotherapy dose factors may be weakly correlated. Decision making on prophylactic medications needs to be carefully considered, and the actual preventive effect needed to be supported by more evidence.

Impact of Staging Concordance and Downstaging After Neoadjuvant Therapy on Survival Following Resection of Intrahepatic Cholangiocarcinoma: A Bayesian Analysis

INTRODUCTION

Concordance between clinical and pathological staging, as well as the overall survival (OS) benefit associated with neoadjuvant therapy (NAT) remain ill-defined. We sought to determine the impact of staging accuracy and NAT downstaging on OS among patients with intrahepatic cholangiocarcinoma (ICC).

METHODS

Patients treated for ICC between 2010 and 2018 were identified using the National Cancer Database. A Bayesian approach was applied to estimate NAT downstaging. OS was assessed relative to staging concordant/overstaged disease treated with upfront surgery, understaged disease treated with upfront surgery, no downstaging, and downstaging after NAT.

RESULTS

Among 3384 patients, 2904 (85.8%) underwent upfront surgery, whereas 480 (14.2%) received NAT and 85/480 (18.4%) were downstaged. Patients with cT3 (odds ratio [OR] 2.12, 95% confidence interval [CI] 1.34-3.34), cN1 (OR 2.47, 95% CI 1.71-3.58) disease, and patients treated at high-volume facilities (OR 1.63, 95% CI 1.13-2.36) were more likely to receive NAT (all p < 0.05). Median OS was 40.1 months (95% CI 38.6-43.4). Patients with cT1-2N1 (NAT: 31.5 months vs. upfront surgery: 22.4 months; p = 0.04) and cT3-4N1 (NAT: 27.8 months vs. upfront surgery: 14.4 months; p = 0.01) disease benefited most from NAT. NAT downstaging decreased the risk of death among patients with cT3-4N1 disease (hazard ratio [HR] 0.35, 95% CI 0.15-0.82). In contrast, understaged patients with cT1-2N0/X (HR 2.15, 95% CI 1.83-2.53) and cT3-4N0/X (HR 1.71, 95% CI 1.06-2.74) disease treated with upfront surgery had increased risk of death.

CONCLUSIONS

Patients with N1 ICC treated with NAT demonstrated improved OS compared with upfront surgery. Downstaging secondary to NAT conferred survival benefits among patients with cT3-4N1 versus upfront surgery. NAT should be considered in ICC patients with advanced T disease and/or nodal metastases.

Development and external validation of a prognosis model to predict outcomes after curative resection of early-stage intrahepatic cholangiocarcinoma

Background

Early-stage intrahepatic cholangiocarcinoma (ESICC) with curative resection and lymph node-negative still has the risk of poor prognosis, and there lacks prognosis-assessing tools for these patients. The objective of this study was to develop a prognosis model to predict outcomes and identify risk stratification for ESICC after resection.

Methods

Totally 263 patients with ESICC after hepatectomy from January 2012 to January 2022 were analyzed. Clinicopathological factors were selected using multivariable Cox regression analysis and a prognosis model was developed. The performance of the model was evaluated by concordance index (C-index), calibration plots, decision curves analysis (DCA), and net reclassification index (NRI). Kaplan-Meier curves were analyzed for risk stratification of overall survival (OS) and recurrence-free survival (RFS) based on the prognosis model.

Results

The clinicopathological features that were independently associated with OS of ESICC included carbohydrate antigen19-9, carcinoembryonic antigen, tumor size, tumor differentiation, and T stage. The prognosis model based on these prognostic factors demonstrated excellent discriminatory performance in both derivation cohort (C-index, 0.71) and external validation cohort (C-index, 0.78), which outperformed the TNM staging system (C-index, 0.59) and individual prognostic factors (all C-index &lt; 0.7). Calibration plots, DCA and NRI also showed superior predictive performance. According to the risk for survival, the model stratified patients into low risk (median OS, 66.6 months; median RFS, 24.3 months) and high risk (median OS, 24.0 months; median RFS, 6.4 months) (P &lt; 0.001).

Conclusions

Our prognosis model can robustly predict the outcomes of ESICC after curative resection and provide precise evaluation on prognosis risk, facilitating clinicians to develop individualized postoperative treatment options.

Newest Therapies for Cholangiocarcinoma: An Updated Overview of Approved Treatments with Transplant Oncology Vision

Simple Summary

Cholangiocarcinoma is a relatively rare but deadly disease with traditionally limited treatment options. The disease can be categorized by anatomic location within the biliary tree, with different associated risk factors and molecular profiles. Recent years have seen a burgeoning of targeted therapies that have enhanced survival in subsets of patients with certain mutations. We herein discuss these more recent advances as well as providing an overview of more well-known treatment modalities, with the goal of providing an accessible source for practicing clinicians.

Abstract

A minority of cholangiocarcinoma (CCA) can be cured by surgical intervention (i.e., liver resection (LR) and liver transplantation (LT)). When modern criteria for LT are met, this intervention along with neoadjuvant treatments may achieve unprecedented survival in selected patients. Liver resection is associated with a median overall survival (OS) of 40 months, this number drastically decreases for unresectable advanced cholangiocarcinoma (CCA), which is treated with systemic therapy. The first-line chemotherapy regimen of gemcitabine and cisplatin is associated with a median overall survival of only 11.7 months. Since the Food and Drug Administration (FDA)’s approval of the isocitrate dehydrogenase (IDH) 1 inhibitor ivosidenib in August 2021, there has been increasing interest in targeted therapy for CCA patients harboring mutations in fibroblast growth factor receptor (FGFR) 2, neurotrophic receptor tyrosine kinase (NTRK), B-raf kinase (BRAF), and HER2. At the same time, immunotherapy with immune checkpoint inhibitors isalso being used in relapsed CCA. This review looks into the most recently completed and ongoing studies of targeted therapy as monotherapy or in combination with chemo- and/or immunotherapy. Whether it is resection, liver transplant, radiotherapy, chemotherapy, immunotherapy, targeted therapy, or any combination of these treatment modalities, great strides are being made to improve outcomes for this challenging disease.

Identification of macrophage correlated biomarkers to predict the prognosis in patients with intrahepatic cholangiocarcinoma

Background

It has been shown that tumor-associated immune cells, particularly macrophages, play a fundamental role in the development and treatment response of intrahepatic cholangiocarcinoma (ICC). However, little is known about macrophages at the single cellular level of ICC patients.

Methods

ScRNA-seq from Zhang et al. was used in the present study to identify the genes differentially expressed in ICCs. Furthermore, transcriptomic data from TCGA datasets, IHC and flowcytometry from our cohort were used to confirm the findings. Kaplan-Meier and TIDE scores were also used for prognostic analysis and ICB responses.

Results

A significant number of macrophages were found in ICCs as compared to adjacent tissues. We then extracted, processed, and classified the macrophages from the ICCs and adjacent tissues into 12 clusters. Significantly, the macrophages from the ICC exhibited an immunosuppressed state in terms of both signature gene expression and functional enrichment. Furthermore, our results indicate that, of the 10 selective tumor-promoting genes of macrophages, only MMP19 and SIRPα can predict ICB responses in ICCs. Although a higher expression of MMP19 and SIRPα predict a poor prognosis for ICCs without immunotherapy after surgery, patients with high SIRPα expression were more sensitive to immunotherapy, whereas those with high MMP19 expression were not sensitive to immunotherapy. To define the mechanisms, we found that SIRPα^hi ICCs exhibited an increased enrichment KEGG pathway of leukocyte transendothelial migration and neutrophil extracellular trap formation. The increased immune cell infiltration will increase sensitivity to immunotherapy.

Conclusion

Collectively, macrophages are critical to the immune status of ICCs, and MMP19 and SIRPα can predict prognosis and ICB responses for ICCs.