Dataset Information

The influence of the extent of lymph node metastasis on the prognosis for patients with intrahepatic cholangiocarcinoma.

ABSTRACT:

Purpose

Reports showed that some of intrahepatic cholangiocarcinoma (ICC) patients with lymph node metastasis (LNM) may also gain survival benefit undergone resection. However, the effect of the extent of LNM on prognosis and surgical indication is barely discussed.

Methods

From September 1994 to November 2018, primary ICC patients undergone initial curable surgery were enrolled. Based on the extent of LNM, we divided these patients into 4 groups, including patients with no LNM (group N0), LNM to hepatoduodenal ligament or common hepatic artery (region A, group A), LNM to gastrohepatic lymph nodes for left liver ICC and periduodenal and peripancreatic lymph node for right liver ICC (region B, group B), or LNM beyond these regions (region C, group C). Multivariable Cox regression analysis was performed to identify the prognostic factors for recurrence-free survival (RFS) and overall survival (OS) in all groups.

Results

A total of 133 patients were enrolled. There were 56, 21, 17, and 39 patients in groups N0, A, B, and C, respectively. There was significant difference between groups N0 and C in RFS (P < 0.001) and OS (P = 0.002). When we compared group N0 + A + B with group C, we also found that RFS (P < 0.001) and OS (P = 0.007) were significantly different. In multivariable analysis, the extent of LNM was an independent risk factor for RFS (P < 0.050).

Conclusion

ICC patients with the LNM to regions A and B could still achieve good prognosis with resection. Surgery should be carefully considered when LNM to region C.

SUBMITTER: Wang J

PROVIDER: S-EPMC10172033 | biostudies-literature | 2023 May

REPOSITORIES: biostudies-literature

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Publications

The influence of the extent of lymph node metastasis on the prognosis for patients with intrahepatic cholangiocarcinoma.

Wang Jianping J Shu Man M Peng Hong H Li Shaoqiang S Li Dongming D Shen Jingxian J Kuang Ming M Zhang Ying Y Chen Zebin Z

Annals of surgical treatment and research 20230428 5

<h4>Purpose</h4>Reports showed that some of intrahepatic cholangiocarcinoma (ICC) patients with lymph node metastasis (LNM) may also gain survival benefit undergone resection. However, the effect of the extent of LNM on prognosis and surgical indication is barely discussed.<h4>Methods</h4>From September 1994 to November 2018, primary ICC patients undergone initial curable surgery were enrolled. Based on the extent of LNM, we divided these patients into 4 groups, including patients with no LNM (g ...[more]

PMID: 37179698

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Project description:Background & aimsLymph node metastasis (LNM) is a major determinant of recurrence and prognosis in intrahepatic cholangiocarcinoma (iCCA). LNM disrupts T cell-mediated cytotoxicity, promotes tumor-specific immune tolerance, and facilitates distant metastasis. Despite its importance, extensive research on LMN in iCCA is lacking. This study aimed to systematically explore the heterogeneity of the LNM-associated microenvironment in iCCA by integrating single-cell and multi-omics analyses, identifying metastasis-associated cell subgroups, and validating these findings through multiple cohorts.MethodsWe analyzed single-cell transcriptomics data from primary tumors, cancer-adjacent liver tissues, and tumor-draining lymph nodes of four patients with iCCA who underwent radical surgery. Additionally, we collected 81 tumor and matched lymph node tissue sections from patients with iCCA. We performed single-cell RNA sequencing and multiplex immunohistochemistry, followed by differential gene expression analysis, functional enrichment analysis, single-cell copy number variation assessment, and pseudotime analysis.ResultsOur analysis revealed the complex heterogeneity of the iCCA LNM-associated microenvironment. We found a significant increase in stromal and mature immune cells in the metastatic lymph nodes. T cells constitute the predominant component, with diverse functional subtypes. We identified CD36+ macrophages and SAA1+ tumor cells as key players in the metastatic process. The SAA1-CD36 receptor‒ligand pair may be crucial in forming the LNM-associated microenvironment.ConclusionsWe identified several metastasis-associated cell subgroups. These findings provide new insights into the mechanisms underlying LNM in iCCA and lay the groundwork for the development of novel therapeutic strategies. Our study highlights the importance of single-cell technologies in understanding tumor microenvironment complexity and offers valuable resources for future research.Impact and implicationsThe lack of single-cell transcriptome analysis of intrahepatic cholangiocarcinoma (iCCA) lymph node metastases has prevented us from understanding the underlying mechanisms of disease progression. To fill this knowledge gap, we elucidated the unique ecosystem of iCCA lymph node metastases, which is an important advance in clarifying the impact of the immune environment on the development of this disease. The results of this study identified several LNM-related therapeutic targets, which will not only be helpful to basic researchers, but also provide potential diagnostic and treatment ideas for physicians, thereby helping patients and their caregivers develop more personalized treatment plans. This finding is highly important for improving the prognosis of patients with advanced iCCA in the future.

Project description:BackgroundThis study aims to introduce the concept of habitat subregions and construct an accurate prediction model by analyzing refined medical images, to predict lymph node metastasis (LNM) in patients with intrahepatic cholangiocarcinoma (ICC) before surgery, and to provide personalized support for clinical decision-making.MethodsClinical, radiological, and pathological data from ICC patients were retrospectively collected. Using information from the arterial and venous phases of multisequence CT images, tumor habitat subregions were delineated through the K-means clustering algorithm. Radiomic features were extracted and screened, and prediction models based on different subregions were constructed and compared with traditional intratumoral models. Finally, a lymph node metastasis prediction model was established by integrating the features of several subregional models, and its performance was evaluated.ResultsA total of 164 ICC patients were included in this study, 103 of whom underwent lymph node dissection. The patients were divided into LNM- and LNM + groups on the basis of lymph node status, and significant differences in white blood cell indicators were found between the two groups. Survival analysis revealed that patients with positive lymph nodes had significantly worse prognoses. Through cluster analysis, the optimal number of habitat subregions was determined to be 5, and prediction models based on different subregions were constructed. A comparison of the performance of each model revealed that the Habitat1 and Habitat5 models had excellent performance. The optimal model obtained by fusing the features of the Habitat1 and Habitat5 models had AUC values of 0.923 and 0.913 in the training set and validation set, respectively, demonstrating good predictive ability. Calibration curves and decision curve analysis further validated the superiority and clinical application value of the model.ConclusionsThis study successfully constructed an accurate prediction model based on habitat subregions that can effectively predict the lymph node metastasis of ICC patients preoperatively. This model is expected to provide personalized decision support to clinicians and help to optimize treatment plans and improve patient outcomes.

Project description:ObjectivesTo develop ultrasound-based radiomics models and a clinical model associated with inflammatory markers for predicting intrahepatic cholangiocarcinoma (ICC) lymph node (LN) metastasis. Both are integrated for enhanced preoperative prediction.MethodsThis study retrospectively enrolled 156 surgically diagnosed ICC patients. A region of interest (ROI) was manually identified on the ultrasound image of the tumor to extract radiomics features. In the training cohort, we performed a Wilcoxon test to screen for differentially expressed features, and then we used 12 machine learning algorithms to develop 107 models within the cross-validation framework and determine the optimal radiomics model through receiver operating characteristic (ROC) curve analysis. Multivariable logistic regression analysis was used to identify independent risk factors to construct a clinical model. The combined model was established by combining ultrasound-based radiomics and clinical parameters. The Delong test and decision curve analysis (DCA) were used to compare the diagnostic efficacy and clinical utility of different models.ResultsA total of 1239 radiomics features were extracted from the ROIs of tumors. Among the 107 prediction models, the model (Stepglm + LASSO) utilizing 10 radiomics features ultimately yielded the highest average area under the receiver operating characteristic curve (AUC) of 0.872, with an AUC of 0.916 in the training cohort and 0.827 in the validation cohort. The combined model, which incorporates the optimal radiomics score, clinical N stage, and platelet-to-lymphocyte ratio (PLR), achieved an AUC of 0.882 in the validation cohort, significantly outperforming the clinical model with an AUC of 0.687 (P = 0.009). According to the DCA analysis, the combined model also showed better clinical benefits.ConclusionsThe combined model incorporating ultrasound-based radiomics features and the PLR marker offers an effective, noninvasive intelligence-assisted tool for preoperative LN metastasis prediction in ICC patients.Clinical trial numberNot applicable.

Dataset Information

The influence of the extent of lymph node metastasis on the prognosis for patients with intrahepatic cholangiocarcinoma.

Purpose

Methods

Results

Conclusion

Publications

The influence of the extent of lymph node metastasis on the prognosis for patients with intrahepatic cholangiocarcinoma.

Similar Datasets

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