Dataset Information

[Clinical Evaluation of A New Pathological Classification for ?Non-small Cell Lung Cancer Based on Histogenesis of Bronchial Tree].

ABSTRACT: BACKGROUND:Due in part to remarkable advances over the past decade in our understanding of lung cancer, there is a pressing need for a revised classification. The aim of this study was to explore and verify the clinical significance of a new molecular classification of non-small cell lung cancer (NSCLC) on the basis of anatomic site of bronchial tree. METHODS:Double-immunohistochemistry were performed in 105 tumor samples paring with normal lung tissue from non-small cell lung cancer patients by using monoclonal antibody of P63/NapsinA and TTF-1/CK7. By comprehensively analyzing the express profiles of tumors and normal lung tissues, histological characteristics we proposed a brand new pathological classification based on histogenesis for NSCLC and divided them as: bronchiole epithelial cell carcinoma, bronchiole-alveolar cell carcinoma, alveolar cell carcinoma and secretory adenocarcinoma. And to analyze the relationship between this classification and epidermal growth factor receptor (EGFR) mutation and ognosis. RESULTS:Further investigation revealed that our new classification showed strong relevancy with EGFR mutations and effective indicators for prognosis. CONCLUSIONS:The classification system for NSCLC proposed by our research group is convenient for pathological diagnosis and valuable in clinical application.

SUBMITTER: Wang N

PROVIDER: S-EPMC6058656 | biostudies-literature | 2018 Jul

REPOSITORIES: biostudies-literature

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[Clinical Evaluation of A New Pathological Classification for  Non-small Cell Lung Cancer Based on Histogenesis of Bronchial Tree].

Wang Nana N Jiang Nan N Yang Xiaoqing X Fang Lei L Sun Qing Q

Zhongguo fei ai za zhi = Chinese journal of lung cancer 20180701 7

<h4>Background</h4>Due in part to remarkable advances over the past decade in our understanding of lung cancer, there is a pressing need for a revised classification. The aim of this study was to explore and verify the clinical significance of a new molecular classification of non-small cell lung cancer (NSCLC) on the basis of anatomic site of bronchial tree.<h4>Methods</h4>Double-immunohistochemistry were performed in 105 tumor samples paring with normal lung tissue from non-small cell lung can ...[more]

PMID: 30037373

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Project description:To investigate the effect of the bronchial tree on the accuracy of biomechanical-based deformable image registration of human lungs.Three dimensional finite element models have been developed using four dimensional computed tomography image data of ten lung cancer patients. Each model is built of a body, left and right lungs, tumor, and bronchial trees. Triangular shell elements are used for the bronchial trees while tetrahedral elements are used for other components. Hyperelastic material properties based on experimental investigation on human lungs are used for the lung parenchyma. Different material properties are assigned for the bronchial tree using five values for the modulus of elasticity of 0.01, 0.12, 0.5, 10, and 18 MPa. Lungs are modeled to slide inside chest cavities by applying frictionless contact surfaces between each lung and corresponding chest cavity. The accuracy of the models is examined using an average of 40 bronchial bifurcation points identified on inhale and exhale images. Relative accuracy is evaluated by comparing the displacement of all nodes within the lungs as well as the dosimetric difference at the exhale position predicted by the model.There is no significant effect of bronchial tree on the model accuracy based on the bifurcation points analysis. However, on the local level, using an average of 38 000 nodes, there is a maximum difference of 8.5 mm in the deformation of the bronchial trees, as the modulus of elasticity of the bronchial trees increases from 0.01 to 18 MPa; however, more than 96% of nodes are within a 2.5 mm difference in each direction. The average dose difference at the predicted exhale position is less than 35 cGy between the models.The bronchial tree has little effect on the global deformation and the accuracy of deformable image registration of lungs. Hence, the homogenous model is a reasonable assumption. Since there are some local deformation differences between nodes as the material properties of the bronchial tree change that may affect the accuracy of dosimetric results, heterogeneity may be required for a smaller scale modeling of lungs.

Project description:Studies validating the prognostic accuracy of the tumor-node-metastases (TNM) classification in patients with lung cancer treated by neoadjuvant therapy are scarce. Tumor regression, particularly major pathological response (MPR), is an acknowledged prognostic factor in this setting. We aimed to validate a novel combined prognostic score. This retrospective single-center study was conducted on 117 consecutive patients with non-small cell lung cancer resected after neoadjuvant treatment at a Swiss University Cancer Center between 2000 and 2016. All cases were clinicopathologically re-evaluated. We assessed the prognostic performance of a novel prognostic score (PRSC) combining T-category, lymph node status, and MPR, in comparison with the eighth edition of the TNM classification (TNM8), the size adapted TNM8 as proposed by the International Association for the Study of Lung Cancer (IASLC) and MPR alone. The isolated ypT-category and the combined TNM8 stages accurately differentiated overall survival (OS, stage p = 0.004) and disease-free survival (DFS, stage p = 0.018). Tumor regression had a prognostic impact. Optimal cut-offs for MPR emerged as 65% for adenocarcinoma and 10% for non-adenocarcinoma and were statistically significant for survival (OS p = 0.006, DFS p < 0.001). The PRSC differentiated between three prognostic groups (OS and DFS p < 0.001), and was superior compared to the stratification using MPR alone or the TNM8 systems, visualized by lower Akaike (AIC) and Bayesian information criterion (BIC) values. In the multivariate analyses, stage III tumors (HR 4.956, p = 0.003), tumors without MPR (HR 2.432, p = 0.015), and PRSC high-risk tumors (HR 5.692, p < 0.001) had significantly increased risks of occurring death. In conclusion, we support 65% as the optimal cut-off for MPR in adenocarcinomas. TNM8 and MPR were comparable regarding their prognostic significance. The novel prognostic score performed distinctly better regarding OS and DFS.

Dataset Information

[Clinical Evaluation of A New Pathological Classification for ?Non-small Cell Lung Cancer Based on Histogenesis of Bronchial Tree].

Publications

[Clinical Evaluation of A New Pathological Classification for Non-small Cell Lung Cancer Based on Histogenesis of Bronchial Tree].

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[Clinical Evaluation of A New Pathological Classification for  Non-small Cell Lung Cancer Based on Histogenesis of Bronchial Tree].