Relationship between DDX46 gene and invasion and metastasis behaviors of TE-1 esophageal squamous cell carcinoma cells / 中国胸心血管外科临床杂志

@#Objective    To investigate the relationship between DDX46 genes and invasion and migration of esophageal squamous cell carcinoma cells. Methods    Human esophageal squamous cell carcinoma cells TE-1 were transfected by fluorescent marker shRNA lentivirus (shDDX46 group), and an empty vector was transfected as a control (shCtrl group). The expression rate of green fluorescent protein under the microscope was used to evaluate the cell transfection efficiency. Real-time fluorescence quantitative polymerase chain reaction (RTFQ-PCR) and Western blotting (WB) detected the knockdown efficiency of the target gene at the mRNA and protein expression levels. Wound healing, invasion assay and migration assay detected the changes of invasion and metastasis ability. Classical pathway analysis was used to explore signaling pathway changes and the possible mechanism of DDX46 in the invasion and metastasis was explored by detecting fibronectin expression. Results    DDX46 gene at mRNA and protein levels was significantly inhibited after lentiviral transfection. Wound healing showed that after 8 h the cell mobility of TE-1 cells decreased significantly (P=0.001). Invasion assay showed that after 24 h the average cell metastasis rate of TE-1 cells was lower in the shDDX46 group than that in the shCtrl group (P<0.001). The cell metastasis rate in the shDDX46 group corresponding to observation points in the transwell assay was lower than that in the shCtrl group (P<0.001) after 24 h culture. The results of the classical pathway analysis showed that the integrin signaling pathway activity was inhibited, further exploration of the mechanism of action found that the expression of fibronectin associated with cell adhesion was decreased. Conclusion    DDX46 gene is related to the invasion and migration ability of esophageal squamous cell carcinoma cells. Knockdown of DDX46 genes may reduce cell adhesion by downregulating the integrin pathway signaling.

The impact of COVID-19 on the diagnosis and treatment of lung cancer / 中国胸心血管外科临床杂志

@#Lung cancer is a complex disease with its own challenges, and is considered to be one of the most common causes of cancer death worldwide. The coronavirus disease 2019 (COVID-19) pandemic, caused by the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), has exacerbated these challenges. The aim of this review is to explore the impact of the COVID-19 pandemic on the screening, diagnosis and treatment of lung cancer. We hope to provide some experience and help for the whole process management of lung cancer patients.

Clinical Study of Artificial Intelligence-assisted Diagnosis System in Predicting the Invasive Subtypes of Early-stage Lung Adenocarcinoma Appearing as Pulmonary Nodules / 中国肺癌杂志

BACKGROUND@#Lung cancer is the cancer with the highest mortality at home and abroad at present. The detection of lung nodules is a key step to reducing the mortality of lung cancer. Artificial intelligence-assisted diagnosis system presents as the state of the art in the area of nodule detection, differentiation between benign and malignant and diagnosis of invasive subtypes, however, a validation with clinical data is necessary for further application. Therefore, the aim of this study is to evaluate the effectiveness of artificial intelligence-assisted diagnosis system in predicting the invasive subtypes of early‑stage lung adenocarcinoma appearing as pulmonary nodules.@*METHODS@#Clinical data of 223 patients with early-stage lung adenocarcinoma appearing as pulmonary nodules admitted to the Lanzhou University Second Hospital from January 1st, 2016 to December 31th, 2021 were retrospectively analyzed, which were divided into invasive adenocarcinoma group (n=170) and non-invasive adenocarcinoma group (n=53), and the non-invasive adenocarcinoma group was subdivided into minimally invasive adenocarcinoma group (n=31) and preinvasive lesions group (n=22). The malignant probability and imaging characteristics of each group were compared to analyze their predictive ability for the invasive subtypes of early-stage lung adenocarcinoma. The concordance between qualitative diagnostic results of artificial intelligence-assisted diagnosis of the invasive subtypes of early-stage lung adenocarcinoma and postoperative pathology was then analyzed.@*RESULTS@#In different invasive subtypes of early-stage lung adenocarcinoma, the mean CT value of pulmonary nodules (P<0.001), diameter (P<0.001), volume (P<0.001), malignant probability (P<0.001), pleural retraction sign (P<0.001), lobulation (P<0.001), spiculation (P<0.001) were significantly different. At the same time, it was also found that with the increased invasiveness of different invasive subtypes of early-stage lung adenocarcinoma, the proportion of dominant signs of each group gradually increased. On the issue of binary classification, the sensitivity, specificity, and area under the curve (AUC) values of the artificial intelligence-assisted diagnosis system for the qualitative diagnosis of invasive subtypes of early-stage lung adenocarcinoma were 81.76%, 92.45% and 0.871 respectively. On the issue of three classification, the accuracy, recall rate, F1 score, and AUC values of the artificial intelligence-assisted diagnosis system for the qualitative diagnosis of invasive subtypes of early-stage lung adenocarcinoma were 83.86%, 85.03%, 76.46% and 0.879 respectively.@*CONCLUSIONS@#Artificial intelligence-assisted diagnosis system could predict the invasive subtypes of early‑stage lung adenocarcinoma appearing as pulmonary nodules, and has a certain predictive value. With the optimization of algorithms and the improvement of data, it may provide guidance for individualized treatment of patients.

Efficacy of surgical management for esophageal squamous cell carcinoma in pathological stage T1b / 中国胸心血管外科临床杂志

@#Objective    To investigate the prognostic survival status and influence factors for surgical treatment of esophageal squamous cell carcinoma (ESCC) in pathological stage T1b (pT1b). Methods    The patients with ESCC in pT1b undergoing Ivor-Lewis or McKeown esophagectomy in Lanzhou University Second Hospital from 2012 to 2015 were collected, including 78 males (78.3%) and 17 females (21.7%) with an average age of 61.4±7.4 years. Results    The most common postoperative complications were pneumonia (15.8%), anastomotic leakage (12.6%) and arrhythmia (8.4%). Ninety-three (97.9%) patients underwent R0 resection, with an average number of lymph node dissections of 14.4±5.6. The rate of lymph node metastasis was 22.1%, and the incidence of lymph vessel invasion was 13.7%. The median follow-up time was 60.4 months, during which 25 patients died and 27 patients relapsed. The overall survival rate at 3 years was 86.3%, and at 5 years was 72.7%. Multivariate Cox regression analysis showed that lymph node metastasis (P=0.012, HR=2.60, 95%CI 1.23-5.50) and lympovascular invasion (P=0.014, HR=2.73, 95%CI 1.22-6.09) were independent risk factors for overall survival of pT1b ESCC. Conclusion    Esophagectomy via right chest approach combined with two-fields lymphadenectomy is safe and feasible for patients with pT1b ESCC. The progress of pT1b ESCC with lymph node metastasis or lymphovascular invasion is relatively poor.

Study on the application of artificial intelligence system in the detection and differentiation of benign and malignant pulmonary nodules / 中华胸心血管外科杂志

Objective:To evaluate the efficacy of artificial intelligence assisted pulmonary nodule diagnosis system in detection pulmonary nodule and predicting the malignant probability of pulmonary nodule.Methods:A retrospectively analyze the clinical data of 199 patients with lung nodules in the Thoracic Surgery Department of Lanzhou University Second Hospital from May 2016 to July 2020. The preoperative chest CT was imported into the artificial intelligence system to record the detected lung nodules, to measure nodal diameter and density classification and malignant probability prediction value of each nodule. The detection rate of pulmonary nodules by artificial intelligence system was calculated, and the sensitivity, specificity, positive likelihood ratio and negative likelihood ratio of artificial intelligence system in the differential diagnosis of benign and malignant pulmonary nodules were calculated and compared with manual film reading. and the sensitivity and specificity in the differential diagnosis of benign and malignant pulmonary nodules under the condition of different size and density of pulmonary nodules.Results:A total of 204 pulmonary nodules were pathologically diagnosed by surgical resection, and the detection rate of pulmonary nodules by artificial intelligence system was 100%. The artificial intelligence system can distinguish benign and malignant pulmonary nodules with a sensitivity of 95.83%(95% CI: 0.8967-0.9883), specificity 25.00%(95% CI: 0.1717-0.3425), and a positive likelihood ratio of 1.27(95% CI: 1.14-1.44), negative likelihood ratio 0.17(95% CI: 0.06-0.46), Manual reading for the differentiation of benign and malignant pulmonary nodules has a sensitivity of 87.36%(95% CI: 0.7850-0.9352), specificity 72.17%(95% CI: 0.6214-0.8079), and a positive likelihood ratio of 3.14(95% CI: 2.26-4.37), the negative likelihood ratio is 0.18(95% CI: 0.10-0.31). 5mm≤diameter of pulmonary nodule<10 mm, sensitivity 100%(95% CI: 0.6637-1.0000), specificity 50.00%(95% CI: 0.01258-0.98740), 10 mm≤diameter of pulmonary nodule <20 mm, sensitivity 94.29%(95% CI: 0.8084-0.9930), specificity 29.83%(95% CI: 0.1843-0.4340), 20 mm≤ diameter of pulmonary nodule ≤30 mm, sensitivity 96.15%(95% CI: 0.8679-0.9953), specificity 18.37%(95% CI: 0.0876-0.9953), sensitivity of subsolid lung nodules: 100%(95% CI: 0.9051-1.0000), specificity 20.00%(95% CI: 0.0051-0.7164), solid lung nodule sensitivity 93.22%(95% CI: 0.8354-0.9812), specificity 25.24%(95% CI: 0.1720-0.3476). Conclusion:The artificial intelligence assistant diagnosis system of pulmonary nodules has a strong performance in the detection of pulmonary nodules, but it can not meet the clinical requirements in the differentiation of benign and malignant pulmonary nodules. At present, the artificial intelligence system can be used as an auxiliary tool for doctors to detect pulmonary nodules and assist in the diagnosis of benign and malignant pulmonary nodules.

A retrospective study of the effect of postoperative adjuvant therapy on patients with locally advanced pT3N0M0 esophageal squamous cell carcinoma / 中国肿瘤临床

Objective:To evaluate the effect of postoperative adjuvant therapy on patients with locally advanced pathologic T3N0M0 (pT3N0M0)esophageal squamous cell carcinoma(ESCC).Methods:In this retrospective study,we evaluated patients who underwent esophagectomy at Lanzhou University Second Hospital.Patients were divided into 4 groups:surgery-alone(S),surgery+radiotherapy group(S+RT),surgery+chemotherapy(S+CT),and surgery+chemoradiotherapy(S+CRT)groups.Both the clinicopathologic informa-tion and the long-term follow-up results were analyzed.Results:From January 2010 to April 2014,a total of 177 patients with a medi-an age of 61 years(range 43-78),were enrolled into the study.Among them,79 received surgery alone;the remaining 98 patients re-ceived adjuvant therapy,of whom 28 patients received adjuvant radiotherapy,38 received adjuvant chemotherapy,and 32 received ad-juvant chemoradiotherapy.Overall survival and disease-free survival were better in Group S+Adjuvant than in Group S(P=0.012,P=0.007,respectively).Comparisons among the four groups showed that the overall survival was higher in Group S+CRT than in Group S (P=0.031).Group S+RT was associated with better overall survival and disease-free survival than Group S(P=0.038,P=0.011,respec-tively).Conclusions:Patients with pT3N0M0 ESCC could benefit from adjuvant radiotherapy and chemoradiotherapy,as radiotherapy could help achieve better locoregional control.