Cholangiocarcinoma: anatomical location-dependent clinical, prognostic, and genetic disparities

Exploring the Genomic Landscape of Hepatobiliary Cancers to Establish a Novel Molecular Classification System

Taxonomy of hepatobiliary cancer (HBC) categorizes tumors by location or histopathology (tissue of origin, TO). Tumors originating from different TOs can also be grouped by overlapping genomic alterations (GA) into molecular subtypes (MS). The aim of this study was to create novel HBC MSs. Next-generation sequencing (NGS) data from the AACR-GENIE database were used to examine the genomic landscape of HBCs. Machine learning and gene enrichment analysis identified MSs and their oncogenomic pathways. Descriptive statistics were used to compare subtypes and their associations with clinical and molecular variables. Integrative analyses generated three MSs with different oncogenomic pathways independent of TO (n = 324; p < 0.05). HC-1 "hyper-mutated-proliferative state" MS had rapidly dividing cells susceptible to chemotherapy; HC-2 "adaptive stem cell-cellular senescence" MS had epigenomic alterations to evade immune system and treatment-resistant mechanisms; HC-3 "metabolic-stress pathway" MS had metabolic alterations. The discovery of HBC MSs is the initial step in cancer taxonomy evolution and the incorporation of genomic profiling into the TNM system. The goal is the development of a precision oncology machine learning algorithm to guide treatment planning and improve HBC outcomes. Future studies should validate findings of this study, incorporate clinical outcomes, and compare the MS classification to the AJCC 8th staging system.

The Arising Role of Extracellular Vesicles in Cholangiocarcinoma: A Rundown of the Current Knowledge Regarding Diagnostic and Therapeutic Approaches

Cholangiocarcinomas (CCAs) constitute a heterogeneous group of highly malignant epithelial tumors arising from the biliary tree. This cluster of malignant tumors includes three distinct entities, the intrahepatic, perihilar, and distal CCAs, which are characterized by different epidemiological and molecular backgrounds, as well as prognosis and therapeutic approaches. The higher incidence of CCA over the last decades, the late diagnostic time that contributes to a high mortality and poor prognosis, as well as its chemoresistance, intensified the efforts of the scientific community for the development of novel diagnostic tools and therapeutic approaches. Extracellular vesicles (EVs) comprise highly heterogenic, multi-sized, membrane-enclosed nanostructures that are secreted by a large variety of cells via different routes of biogenesis. Their role in intercellular communication via their cargo that potentially contributes to disease development and progression, as well as their prospect as diagnostic biomarkers and therapeutic tools, has become the focus of interest of several current studies for several diseases, including CCA. The aim of this review is to give a rundown of the current knowledge regarding the emerging role of EVs in cholangiocarcinogenesis and their future perspectives as diagnostic and therapeutic tools.

Endoscopic radiofrequency ablation plus plastic stent placement versus stent placement alone for unresectable extrahepatic biliary cancer: a multicenter randomized controlled trial

BACKGROUND AND AIMS

We sought to compare the efficacy and safety between endoscopic radiofrequency ablation (RFA) and stent placement alone in patients with unresectable extrahepatic biliary cancer (EBC).

METHODS

In this randomized controlled trial, patients with locally advanced or metastatic cholangiocarcinoma (CCA) or ampullary cancer who were unsuitable for surgery were recruited from 3 tertiary centers. Eligible patients were randomly assigned to RFA plus plastic stent placement (RFA group) or plastic stent placement alone (stent placement alone group) in a 1:1 ratio. Both groups underwent 2 scheduled interventions with an interval of approximately 3 months. The primary outcome was overall survival (OS).

RESULTS

Altogether, 174 participants completed the 2 index endoscopic interventions. No significant differences in baseline characteristics were noted between the 2 groups. The median OS was significantly higher in the RFA group (14.3 vs 9.2 months; hazard ratio, .488; 95% confidence interval, .351-.678; P < .001). A survival benefit was also shown in patients with CCA (13.3 vs 9.2 months; hazard ratio, .546; 95% confidence interval, .386-.771; P < .001). However, no significant between-group differences were found in jaundice control or stent patency duration. The postprocedural Karnofsky performance scores were significantly higher in the RFA group until 9 months (all P < .001). Adverse events were comparable between the 2 groups (27.6% vs 19.5%, P = .211), except for acute cholecystitis, which was more frequently observed in the RFA group (9 vs 0, P = .003).

CONCLUSIONS

Compared with stent placement alone, additional RFA may improve OS and quality of life of patients with inoperable primary EBC who do not undergo systemic treatments. (Clinical trial registration number: NCT01844245.).

Survival after surgery among patients with cholangiocarcinoma in Northeast Thailand according to anatomical and morphological classification

BACKGROUND

Cholangiocarcinoma (CCA) has been categorized based on tumor location as intrahepatic (ICCA), perihilar (PCCA) or distal (DCCA), and based on the morphology of the tumor of the bile duct as mass forming (MF), periductal infiltrating (PI) or intraductal (ID). To date, there is limited evidence available regarding the survival of CCA among these different anatomical and morphological classifications. This study aimed to evaluate the survival rate and median survival time after curative surgery among CCA patients according to their anatomical and morphological classifications, and to determine the association between these classifications and survival.

METHODS

This study included CCA patients who underwent curative surgery from the Cholangiocarcinoma Screening and Care Program (CASCAP), Northeast Thailand. The anatomical and morphological classifications were based on pathological findings after surgery. Survival rates of CCA and median survival time since the date of CCA surgery and 95% confidence intervals (CI) were calculated. Multiple cox regression was performed to evaluate factors associated with survival which were quantified by hazard ratios (HR) and their 95% CIs.

RESULTS

Of the 746 CCA patients, 514 had died at the completion of the study which constituted 15,643.6 person-months of data recordings. The incidence rate was 3.3 per 100 patients per month (95% CI: 3.0-3.6), with median survival time of 17.8 months (95% CI: 15.4-20.2), and 5-year survival rate of 24.6% (95% CI: 20.7-28.6). The longest median survival time was 21.8 months (95% CI: 16.3-27.3) while the highest 5-year survival rate of 34.8% (95% CI: 23.8-46.0) occurred in the DCCA group. A combination of anatomical and morphological classifications, PCCA+ID, was associated with the longest median survival time of 40.5 months (95% CI: 17.9-63.0) and the highest 5-year survival rate of 42.6% (95% CI: 25.4-58.9). The ICCA+MF combination was associated with survival (adjusted HR: 1.45; 95% CI: 1.01-2.09; P = 0.013) compared to ICCA+ID patients.

CONCLUSIONS

Among patients receiving surgical treatment, those with PCCA+ID had the highest 5-year survival rate, which was higher than in groups classified by only anatomical characteristics. Additionally, the patients with ICCA+MF tended to have unfavorable surgical outcomes. Showed the highest survival association. Therefore, further investigations into CCA imaging should focus on patients with a combination of anatomical and morphological classifications.

Analysis of metastasis and survival between extrahepatic and intrahepatic cholangiocarcinoma: A large population-based study

To date, extrahepatic cholangiocarcinoma (ECCA) and intrahepatic cholangiocarcinoma (ICCA) have rarely been compared; therefore, we attempted to learn more about the rates of metastasis and survival in both ICCA and ECCA.Data of patients in the SEER database diagnosed with ICCA or ECCA were extracted to analyse the rate of metastasis and survival. Univariate and multivariate logistic regression analyses were performed to identify the risk factors for metastasis. Propensity score matching (PSM) was used to compare survival rates between ECCA and ICCA.Data from a total of 15,751 patients diagnosed with ICCA or ECCA were extracted to analyse the rate of metastasis. Metastasis was more common in ECCA than ICCA (42.62% vs. 31.46%, P < .05), while ICCA in the T1 stage had a lower rate of metastasis (25.35% vs. 30.61%, P < .05). Age, pathology grade, tumour size, lymph node metastasis and T stage were independent risk factors for metastasis in both ECCA and ICCA. There was an inverse correlation between age and metastasis in both ICCA and ECCA. Moreover, PSM demonstrated that patients with ECCA had a better prognosis than patients with ICCA. Patients with ICCA in the T1 stage had better survival than those with ECCA in the T1 stage.Our study was the first to compare the rates of metastasis and survival between ECCA and ICCA. We observed an inverse association between age and metastasis, that patients with ECCA had a better prognosis than patients with ICCA, and that patients with ECCA in the T1 stage had worse survival than patients with ICCA in the T1 stage.

Machine-learning radiomics to predict early recurrence in perihilar cholangiocarcinoma after curative resection

BACKGROUND AND AIMS

Up to 40%-65% of patients with perihilar cholangiocarcinoma (PHC) rapidly progress to early recurrence (ER) even after curative resection. Quantification of ER risk is difficult and a reliable prognostic prediction tool is absent. We developed and validated a multilevel model, integrating clinicopathology, molecular pathology and radiology, especially radiomics coupled with machine-learning algorithms, to predict the ER of patients after curative resection in PHC.

METHODS

In total, 274 patients who underwent contrast-enhanced CT (CECT) and curative resection at 2 institutions were retrospectively identified and randomly divided into training (n = 167), internal validation (n = 70) and external validation (n = 37) sets. A machine-learning analysis of 18,120 radiomic features based on multiphase CECT and 48 clinico-radiologic characteristics was performed for the multilevel model.

RESULTS

Comprehensively, 7 independent factors (tumour differentiation, lymph node metastasis, pre-operative CA19-9 level, enhancement pattern, A-Shrink score, V-Shrink score and P-Shrink score) were built to the multilevel model and quantified the risk of ER. We benchmarked the gain in discrimination with the area under the curve (AUC) of 0.883, superior to the rival clinical and radiomic models (AUCs 0.792-0.805). The accuracy (ACC) of the multilevel model was 0.826, which was significantly higher than those of the conventional staging systems (AJCC 8th (0.641), MSKCC (0.617) and Gazzaniga (0.581)).

CONCLUSION

The radiomics-based multilevel model demonstrated superior performance to rival models and conventional staging systems, and could serve as a visual prognostic tool to plan surveillance of ER and guide post-operative individualized management in PHC.

Systemic treatment options for advanced biliary tract carcinoma

Advanced biliary tract cancers (BTC) include a diverse collection of rare and heterogenous tumors with poor prognosis. The combination of gemcitabine and cisplatin is the established first-line therapy for advanced BTC. There are no accepted standard treatments in the second line setting, though there are several ongoing clinical trials that implement chemotherapy as a therapeutic strategy. The understanding of the molecular landscape of BTC has offered hope of targeted therapies to the identified actionable genomic aberrations, such as FGFR2 gene fusions, mutations of IDH1/2, HER2, BRAC1/2 and BRAF. Pembigatinib has become the first approved targeted therapy for BTC with FGFR2 fusion or other rearrangements. Recent immunotherapy has opened new therapy avenues in BTC with pembrolizumab approved for either microsatellite instability high (MSI-H) or DNA mismatch repair deficient (dMMR) advanced solid tumors, including BTC. The combination of immunotherapy with other modalities is currently being evaluated in different clinical trials, since single agent immunotherapy appears to provide modest benefits in advanced BTC. In this review, we summarize the current status of treatment options, including systemic chemotherapy, targeted therapy, immunotherapy, and various combinations in advanced BTC.

Differentiation combined hepatocellular and cholangiocarcinoma from intrahepatic cholangiocarcinoma based on radiomics machine learning

BACKGROUND

Combined hepatocellular and cholangiocarcinoma (CHC) and intrahepatic cholangiocarcinoma (ICC) are hard to identify in clinical practice preoperatively. This study looked to develop and confirm a radiomics-based model for preoperative differentiation CHC from ICC.

METHODS

The model was developed in 86 patients with ICC and 46 CHC, confirmed in 37 ICC and 20 CHC, and data were collected from January 2014 to December 2018. The radiomics scores (Radscores) were built from radiomics features of contrast-enhanced computed tomography in 12 regions of interest (ROI). The Radscore and clinical-radiologic factors were integrated into the combined model using multivariable logistic regression. The best-combined model constructed the radiomics-based nomogram, and the performance was assessed concerning its calibration, discrimination, and clinical usefulness.

RESULTS

The radiomics features extracted from tumor ROI in the arterial phase (AP) with preprocessing were selected to build Radscore and yielded an area under the curve (AUC) of 0.800 and 0.789 in training and validation cohorts, respectively. The radiomics-based model contained Radscore and 4 clinical-radiologic factors showed the best performance (training cohort, AUC =0.942; validation cohort, AUC =0.942) and good calibration (training cohort, AUC =0.935; validation cohort, AUC =0.931).

CONCLUSIONS

The proposed radiomics-based model may be used conveniently to the preoperatively differentiate CHC from ICC.