Squamous cell carcinomas (SCC) account for approximately 30% of non-small cell lung cancer. Investigation of the mechanism of invasion and metastasis of lung SCC will be of great help for the development of meaningful targeted therapeutics. This study is intended to understand whether the activation of Hedgehog (Hh) pathway is involved in lung SCC, and whether activated Hh signaling regulates metastasis through epithelial-mesenchymal transition (EMT) in lung SCC.

Surface‐enhanced Raman spectroscopy (SERS) is a surface‐sensitive technique that enhances Raman scattering by molecules adsorbed on nanostructures. The advantages of using SERS include high detection sensibility and fast analysis, thus it is a potentially promising tool for sensing metabolic cancer molecules in trace amounts. To explore this new method of lung cancer detection, we analyzed saliva samples from 61 lung cancer patients and 66 healthy controls. An SERS system and a nano‐modified chip were used in this study. Statistics were analyzed using support vector machine (SVM) and random forest algorithms. The leave‐one‐out algorithm was used based on SVM results to analyze differences in saliva between lung cancer patients and controls. There was a significant difference between the saliva of patients with lung cancer and healthy controls using the Raman spectrum; the intensity of the spectral line in lung cancer patients was weaker than in controls and 12 characteristic peaks were detected. Saliva SERS peaks have been characterized to refer to tissues, body fluids, and biological standard Raman peaks, but it is difficult to identify molecules with current information. The sensitivity and specificity of Raman spectroscopy data and SVM classification results of lung cancer patients and normal saliva samples were both 100%. Using the leave‐one‐out algorithm, the sensitivity was 95.08% and the specificity was 100%. The sensitivity of the random forest method was 96.72% and specificity was 100%. Our results show that SERS has the potential to detect lung cancer.

Background: IBM Watson for Oncology (WFO) provides physicians with evidence‐based treatment options. This study was designed to explore the concordance of the suggested therapeutic regimen for advanced non‐small cell lung (NSCLC) cancer patients between the updated version of WFO and physicians in our department, in order to reflect the differences of cancer treatment between China and the United States.Methods: Retrospective data from 165 patients with advanced NSCLC from September 2014 to March 2018 were entered manually into WFO. WFO recommendations were provided in three categories: recommended, for consideration, and not recommended. Concordance was analyzed by comparing the treatment decisions proposed by WFO with the real treatment. Potential influenced factors were also analyzed.Results: Overall, the treatment recommendations were concordant in 73.3% (121/165) of cases. When two alternative drugs such as icotinib and nedaplatin were included as “for consideration,” the total consistency could be elevated from 73.3% to 90.3%(149/165). The logistic regression analysis showed that gender (P = 0.096), ECOG (P = 0.0.502), smoking (P = 0.455), and pathology (P = 0.633) had no effect on consistency, but stages (P = 0.019), including stage ≤III (77.8%, 21/27) and stage IV (93.5%, 129/138) had significant effects on consistency.Conclusions: In China, most of the treatment recommendations of WFO are consistent with the real world treatment. Factors such as patient preferences, prices, drug approval and medical insurance are also taken into consideration, and they ultimately affect the inconsistency. To be comprehensively and rapidly applied in China, localization needs to be accelerated by WFO.

Purpose: To determine the prognostic factors of epidermal growth factor receptor (EGFR) mutation status in a group of patients with nonsmall cell lung cancer (NSCLC) by analyzing their clinical and radiological features.Materials and methods: Patients with NSCLC who underwent EGFR mutation detection between 2014 and 2017 were included. Clinical features and general imaging features were collected, and radiomic features were extracted from CT data by 3D Slicer software. Prognostic factors of EGFR mutation status were selected by least absolute shrinkage and selection operator (LASSO) logistic regression analysis, and receiver operating characteristic (ROC) curves were drawn for each prediction model of EGFR mutation.Results: A total of 118 patients were enrolled in this study. The smoking index (P = 0.028), pleural retraction (P = 0.041), and three radiomic features were significantly associated with EGFR mutation status. The areas under the ROC curve (AUCs) for prediction models of clinical features, general imaging features, and radiomic features were 0.284, 0.703, and 0.815, respectively, and the AUC for the combined prediction model of the three models was 0.894. Finally, a nomogram was established for individualized EGFR mutation prediction.Conclusions: The combination of radiomic features with clinical features and general imaging features can enable discrimination of EGFR mutation status better than the use of any group of features alone. Our study may help develop a noninvasive biomarker to identify EGFR mutation status by using a combination of the three group features.

Background: Epidermal growth factor receptor (EGFR) mutations occur in about 50% of Asian patients with non‐small cell lung cancer (NSCLC). Patients with advanced NSCLC and EGFR mutations derive clinical benefit from treatment with EGFR‐tyrosine kinase inhibitors (TKIs). This study assessed the efficacy and safety of adjuvant icotinib without chemotherapy in EGFR‐mutated NSCLC patients undergoing resection of stage IB–IIIA.Methods: Our retrospective study enrolled 20 patients treated with icotinib as adjuvant therapy. Survival factors were evaluated by univariate and Cox regression analysis.Results: The median follow‐up time was 30 months (range 24–41). At the data cut‐off, five patients (25%) had recurrence or metastasis and one patient had died of the disease. The two‐year disease‐free survival (DFS) rate was 85%. No recurrence occurred in the high‐risk stage IB subgroup during the follow‐up period. In univariate analysis, the micropapillary pattern had a statistically significant effect on DFS ( P = 0.040). Multivariate logistic regression analysis showed that there was no independent predictor. Drug related adverse events (AEs) occurred in nine patients (45.0%). The most common AEs were skin‐related events and diarrhea, but were relatively mild. No grade 3 AEs or occurrences of intolerable toxicity were observed.Conclusions: Icotinib as adjuvant therapy is effective in patients harboring EGFR mutations after complete resection, with an acceptable AE profile. Further trials with larger sample sizes might confirm the efficiency of adjuvant TKI in selected patients.