Search

Background: There is little information on which pattern should be chosen to perform lymph node dissection for stage I non-small-cell lung cancer. This study aimed to develop a model for predicting lymph node metastasis using pathologic features of patients intraoperatively diagnosed as stage I non-small-cell lung cancer.Methods: We collected pathology data from 284 patients intraoperatively diagnosed as stage I non-small-cell lung cancer who underwent lobectomy with complete lymph node dissection from 2013 through 2014, assessing various factors for an association with metastasis to lymph nodes (age, gender, pathology, tumour location, tumour differentiation, tumour size, pleural invasion, bronchus invasion, multicentric invasion and angiolymphatic invasion). After analysing these variables, we developed a multivariable logistic model to estimate risk of metastasis to lymph nodes.Results: Univariate logistic regression identified tumour size >2.65 cm (p < 0.001), tumour differentiation (p < 0.001), pleural invasion (p = 0.034) and bronchus invasion (p < 0.001) to be risk factors significantly associated with the presence of metastatic lymph nodes. On multivariable analysis, only tumour size >2.65 cm (p < 0.001), tumour differentiation (p = 0.006) and bronchus invasion (p = 0.017) were independent predictors for lymph node metastasis. We developed a model based on these three pathologic factors that determined that the risk of metastasis ranged from 3% to 44% for patients intraoperatively diagnosed as stage I non-small-cell lung cancer. By applying the model, we found that the values ŷ > 0.80, 0.43 < ŷ ≤ 0.80, ŷ ≤ 0.43 plus tumour size >2 cm and ŷ ≤0.43 plus tumour size ≤2 cm yielded positive lymph node metastasis predictive values of 44%, 18%, 14% and 0%, respectively.Conclusions: A non-invasive prediction model including tumour size, tumour differentiation and bronchus invasion may be useful to give thoracic surgeons recommendations on lymph node dissection for patients intraoperatively diagnosed as Stage I non-small cell lung cancer. [ABSTRACT FROM AUTHOR]

Background: Hedyotis diffusa Willd. (HDW) is a common anticancer herbal medicine in China, and its therapeutic effectiveness has been demonstrated in a range of cancer patients. There is no consensus about the therapeutic targets and molecular mechanisms of HDW, which contains many active ingredients., Aim: To clarify the mechanism of HDW for esophageal adenocarcinoma (EAC), we utilized network pharmacology and weighted gene co-expression network analysis methods (WGCNA)., Methods: The gene modules that were linked with the clinical features of EAC were obtained through the WGCNA method. Then, the potential target genes were retrieved through the network pharmacology method in order to determine the targets of the active components. After enrichment analysis, a variety of signaling pathways with significant ratios of target genes were found, including regulation of trans-synaptic signaling, neuroactive ligand-receptor interaction and modulation of chemical synaptic transmission. By means of protein-protein interaction (PPI) network analysis, we have successfully identified the hub genes, which were AR, CNR1, GRIK1, MAPK10, MAPT, PGR and PIK3R1., Result: Our study employed molecular docking simulations to evaluate the binding affinity of the active components with the hub gene. The identified active anticancer constituents in HDW are scopoletol, quercetin, ferulic acid, coumarin, and trans-4-methoxycinnamyl alcohol., Conclusion: Our findings shed light on the molecular underpinnings of HDW in the treatment of EAC and hold great promise for the identification of potential HDW compounds and biomarkers for EAC therapy., (Copyright© Bentham Science Publishers; For any queries, please email at epub@benthamscience.net.)

Objective: To assess the value of (18)F-FDG dual head coincidence imaging in the prediction of the efficacy of radioiodine therapy in patients with cervical lymph node (LN) metastasis of papillary thyroid carcinoma (PTC)., Methods: Thirty-six patients undergoing thyroidectomy and radioiodine ablation of the residual normal thyroid tissue received (18)F-FDG dual head coincidence imaging and then therapeutic (131)I-whole body imaging ((131)I-WBI) in the same week. According to those imaging results, the patients were divided into group I with positive results of both imaging examinations and group II with positive results by (131)I-WBI but negative results by(18)F-FDG dual head coincidence imaging. All the patients were followed up for 6 months., Results: In group I (14 patients), a total of 49 lesions were diagnosed as cervical LN metastases, and the total sensitivity differed significantly between (18)F-FDG dual head coincidence imaging and (131)I- WBI (67.3% vs 89.8%, P=0.027). In both groups, the total sensitivity of (18)F-FDG dual head coincidence imaging and (131)I-WBI showed a significant difference (26.0% vs 94.5%, P<0.001). The target and non-target ratio (T/NT) was identified as one of the factors affecting the radioiodine efficacy (P<0.001). In group II (22 patients), 76 lesions were diagnosed as cervical LN metastases. The effective rates of groups I and II were 35.7% and 81.8%, respectively, showing a significant difference between them (P=0.011)., Conclusion: (131)I-WBI is more sensitive than (18)F-FDG dual head coincidence imaging in detecting cervical LN metastasis in patients with PTC. Patients with cervical LN metastases who have positive results in both (131)I-WBI and (18)F-FDG dual head coincidence imaging tend to have a poorer response to the therapy than the patients with negative results in (18)F-FDG dual head coincidence imaging. The T/NT of the cervical LN metastases in (18)F-FDG dual head coincidence imaging is associated with the efficacy of radioiodine therapy.