Predicting human epidermal growth factor receptor 2 status of patients with gastric cancer by computed tomography and clinical features.

Background: There have been no studies on predicting human epidermal growth factor receptor 2 (HER2) status in patients with resectable gastric cancer (GC) in the neoadjuvant and perioperative settings. We aimed to investigate the use of preoperative contrast-enhanced computed tomography (CECT) imaging features combined with clinical characteristics for predicting HER2 expression in GC. Methods: We retrospectively enrolled 301 patients with GC who underwent curative resection and preoperative CECT. HER2 status was confirmed by postoperative immunohistochemical analysis with or without fluorescence in situ hybridization. A prediction model was developed using CECT imaging features and clinical characteristics that were independently associated with HER2 status using multivariate logistic regression analysis. Receiver operating characteristic curves were constructed and the performance of the prediction model was evaluated. The bootstrap method was used for internal validation. Results: Three CECT imaging features and one serum tumor marker were independently associated with HER2 status in GC: enhancement ratio in the arterial phase (odds ratio [OR] = 4.535; 95% confidence interval [CI], 2.220-9.264), intratumoral necrosis (OR = 2.64; 95% CI, 1.180-5.258), tumor margin (OR = 3.773; 95% CI, 1.968-7.235), and cancer antigen 125 (CA125) level (OR = 5.551; 95% CI, 1.361-22.651). A prediction model derived from these variables showed an area under the receiver operating characteristic curve of 0.802 (95% CI, 0.740-0.864) for predicting HER2 status in GC. The established model was stable, and the parameters were accurately estimated. Conclusions: Enhancement ratio in the arterial phase, intratumoral necrosis, tumor margin, and CA125 levels were independently associated with HER2 status in GC. The prediction model derived from these factors may be used preoperatively to estimate HER2 status in GC and guide clinical treatment.

Circulating CD45+EpCAM+ cells as a diagnostic marker for early-stage primary lung cancer.

Lung cancer is a highly prevalent type of cancer, accounting for 11.6% of all cancer incidences. Early detection and treatment can significantly improve the survival rate and quality of life of patients; however, there is no accurate, effective, and easy-to-use test for early lung cancer screening. In this study, flow cytometry was used to detect the presence of CD45+EpCAM+ cells in tumor tissues and peripheral blood mononuclear cells (PBMCs) in patients with lung cancer. Moreover, the proportion of CD45+EpCAM+ cells in PBMCs of patients with lung cancer was found to be significantly higher than that of healthy volunteers. Tumor-related serum markers level was also measured in the peripheral blood of these patients using an electrochemiluminescence assay. The correlation between CD45+EpCAM+ cells, carcinoembryonic antigen (CEA), and lung cancer was investigated using receiver operating characteristic (ROC) curve analysis, which showed the sensitivity and specificity of the CD45+EpCAM+ cell to be 81.58% and 88.89%, respectively. Further analysis yielded an area under the ROC curve (ROC/area under the curve [AUC]) of 0.845 in patients PBMCs with lung cancer, which was slightly higher than that of CEA (0.732). Therefore, the detection of CD45+EpCAM+ cells in PBMCs may be helpful for the early screening and auxiliary diagnosis of lung cancer.