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Background: At present, there is a lack of studies in invasive mucinous adenocarcinoma (IMA) that combine clinicopathological and imaging features to stratify risk and select optimal treatment regimen. We aimed to develop and validate a nomogram for predicting recurrence-free survival (RFS) and identifying adjuvant chemotherapy (ACT) beneficiaries for completely resected stage I primary IMA. Methods: This retrospective study included 750 patients from three hospitals. Patients from two hospitals were divided into training (n=424) and validating cohort (n=185), and patients from the remaining other one hospital constituted external test cohort (n=141) and preoperative computed tomography (CT) image features of each patient were consecutively evaluated. The nomogram was developed by integrating significant prognostic factors of RFS identified in the multivariate analysis. The risk score (RS) based on nomogram was calculated in the entire cohort and the optimal cut-off point for risk stratification was obtained by X-tile software. The Kaplan-Meier method, log-rank test and interaction were used to evaluate the difference in RFS and overall survival (OS) between different risk and treatment groups. Results: Visceral pleural invasion (VPI, P<0.001), lymph-vascular invasion (LVI, P<0.001), tumor size (P<0.001), smoking history (P<0.001), lobulation (P<0.001) were identified as independent prognostic factors for RFS. The concordance index (C-index) of the nomogram was higher than that of tumor-node-metastasis (TNM) staging system (validation cohort: 0.73±0.09 vs. 0.62±0.08, P<0.001; external test cohort: 0.74±0.10 vs. 0.70±0.09, P=0.035). The patients with higher RS were associated with worse RFS [hazard ratios (HRs) ≥4.76] and OS (HRs ≥2.55) in all included cohorts. Chemotherapy benefits in terms of RFS and OS were observed for patients in higher RS group in both stage IB (interaction P=0.012 for RFS and P=0.037 for OS) and stage I IMA (interaction P<0.001 for both RFS and OS). Conclusions: The nomogram based on CT image and clinicopathologic features showed superior performance in predicting RFS for stage I IMA and might identify ACT candidates for personalized patient treatment.
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Objective: Brain radiotherapy often results in impairment of hypothalamic-pituitary (HT-P) function, which in turn causes secretory dysfunction of related hormones. In this paper, the frequency of metastasis in the HT-P area and its high-risk factors in patients with brain metastasis were retrospectively analyzed, and thus provide experimental evidence for protecting HT-P area during whole brain radiotherapy (WBRT). Methods: A retrospective analysis was performed on the data of patients with brain metastasis diagnosed by cranial magnetic resonance imaging (MRI) at the First Hospital of Lanzhou University from 2017 to 2020. The anatomical positions of the hypothalamus and pituitary were delineated, followed by their expansion by 5 mm outwards, respectively, in the three-dimensional direction, and the hypothalamus +5 mm and pituitary +5 mm were obtained as the avoidance area, in which the frequency of brain metastasis was evaluated. Univariate and multivariate logistic regression models were used to analyze the high risk factors of brain metastasis in HT-P area. Results: A total of 3,375 brain metastatic lesions from 411 patients were included in the analysis. The rates of brain metastasis in the hypothalamus +5 mm and pituitary +5 mm in the whole group of cases were 2.9% (12/411) and 1.5% (6/411) respectively; the frequency of lesions was 0.4% (13/3375) and 0.2% (6/3375) respectively. Univariate and multivariate analyses showed that the number of brain metastases (OR = 14.946; 95% CI = 4.071-54.880; p < 0.001), and the occurrence of brain metastasis in the pituitary (OR = 13.331; 95% CI = 1.511-117.620; p = 0.020) were related to brain metastasis in the hypothalamus, and that the only relevant factor for brain metastasis in the pituitary was the occurrence of that in the hypothalamus (OR = 0.069; 95% CI = 0.010-0.461; p = 0.006). There was no correlation between tumor pathological types, the maximum diameter, the total volume of brain metastatic lesions and the risk of brain metastasis in hypothalamus and pituitary. Conclusion: The frequency of brain metastasis in the HT-P area is extremely low. The risk of brain metastases in the hypothalamus is correlated with their number. The larger the number of metastatic lesions, the higher the frequency of brain metastasis. Protection of the HT-P area during WBRT may be unlikely to compromise the tumor recurrence rate for patients with a relatively small number of brain metastases.
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Background: Esophageal cancer (EC) is one of the most common malignant tumor types. Surgery is considered the treatment of choice for patients with early- and mid-stage EC. However, because of the traumatic nature of EC surgery and the need for gastrointestinal reconstruction, high rates of postoperative complications such as anastomotic leakage or stenosis, esophageal reflux, and pulmonary infection exist. Its time to explore a novel esophagogastric anastomosis method for McKeown EC surgery to reduce the postoperative complication. Methods: This study recruited a total of 544 patients who underwent McKeown resection for EC between January 2017 and August 2020. The tubular stapler-assisted nested anastomosis was taken as the time node, including 212 patients in the traditional tubular mechanical anastomosis group and 332 patients in the tubular stapler-assisted nested anastomosis group. The 6-month postoperative incidence of anastomotic fistula and anastomotic stenosis was recorded. Anastomosis in McKeown operation for EC and the influence of different anastomosis methods on clinical efficacy were investigated. Results: Compared with traditional mechanical anastomosis, tubular stapler-assisted nested anastomosis had a lower incidence of anastomotic fistula (0% vs. 5.2%), lung infection (3.3% vs. 11.8%), gastroesophageal reflux (6.9% vs. 16.0%), anastomotic stenosis (3.0% vs. 10.4%), neck incision infection (0.9% vs. 7.1%), anastomositis (16.6% vs. 23.6%), and a shorter surgical duration (11.02±1.54 vs. 18.53±3.20 min). Statistical significance was indicated at P<0.05. No significant difference was detected in the incidence of arrhythmia, recurrent laryngeal nerve injury, or chylothorax between the 2 groups. Due to its good effect in McKeown surgery for EC, stapler-assisted nested anastomosis has been widely used in McKeown surgery for EC, and has become a common anastomosis method in our department for McKeown surgery for EC. However, large sample-sized studies and long-term efficacy observation are still needed. Conclusions: The use of tubular stapler-assisted nested anastomosis can significantly reduce the incidence of complications such as anastomotic fistula, anastomotic stricture, gastroesophageal reflux, and pulmonary infection; therefore, it constitutes the preferred technique for cervical anastomosis in McKeown esophagogastrectomy.
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Background: Artificial intelligence (AI) discrimination models using single radioactive variables in recognition algorithms of lung nodules cannot predict lung cancer accurately. Hence, we developed a clinical model that combines AI with blood test variables to predict lung cancer. Methods: Between 2018 and 2021, 584 individuals (358 patients with lung cancer and 226 individuals with lung nodules other than cancer as control) were enrolled prospectively. Machine learning algorithms including lasso regression and random forest (RF) were used to select variables from blood test data, Logistic regression analysis was used to reconfirm the features to build the nomogram model. The predictive performance was assessed by performing the receiver operating characteristic (ROC) curve analysis as well as calibration, clinical decision and impact curves. A cohort of 48 patients was used to independently validate the model. The subgroup application was analyzed by pathological diagnosis. Findings: A total of 584 patients were enrolled (358 lung cancers, 61.30%,226 patients for the control group) to establish the model. The integrated model identified eight potential factors including carcinoembryonic antigen (CEA), AI score, Pro-Gastrin Releasing Peptide (ProGRP), cytokeratin 19 fragment antigen21-1(CYFRA211), squamous cell carcinoma antigen(SCC), indirect bilirubin(IBIL), activated partial thromboplastin time(APTT) and age. The area under the curve (AUC) of the nomogram was 0.907 (95% CI, 0.881-0.929). The decision and clinical impact curves showed good predictive accuracy of the model. An AUC of 0.844 (95% CI, 0.710 - 0.932) was obtained for the external validation group. Conclusion: The nomogram model integrating AI and clinical data can accurately predict lung cancer, especially for the squamous cell carcinoma subtype.
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Fibrilación Atrial , Ablación por Catéter , Fístula , Cardiopatías , Ablación por Radiofrecuencia , Procedimientos Quirúrgicos Robotizados , Humanos , Fibrilación Atrial/cirugía , Procedimientos Quirúrgicos Robotizados/efectos adversos , Fístula/complicaciones , Cardiopatías/cirugía , Ablación por Catéter/efectos adversos , Atrios Cardíacos/cirugíaRESUMEN
Objectives: Localization of pulmonary nodules is challenging. However, traditional localization methods have high radiation doses and a high risk of complications. We developed a noninvasive 3-dimensional printing navigational template for intraoperative localization. It can reduce puncture-related complications and simplify the localization process. This study will verify the feasibility of this method. Methods: Patients with peripheral pulmonary nodules were included in this study. The computed tomography scan sequences were obtained to design a digital template model, which was then imported into a 3-dimensional printer to produce a physical navigational template. Finally, the navigational template is placed into the patient's pleural cavity for intraoperative localization. The precision of the nodule localization and associated complications were evaluated. Results: Twelve patients were finally included in this study. Intraoperative navigational template localization was used in all patients. The success rate of intraoperative nodule localization was 100%, and the median time of localization was 19.5 minutes (range, 16-23.5 minutes). The deviation median of the navigational template was 2.1 mm (range, 1.1-2.7 mm). Among the included patients, no significant complications occurred during intraoperative localization. Conclusions: The 3-dimensional printing template for intraoperative localization is feasible, will cause no trauma to the patient, and has acceptable accuracy for application in nodules localization. This navigational template greatly simplifies the localization process and may potentially break the dependence of percutaneous localization on computed tomography scanning.
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KRAS-driven non-small cell lung cancer (NSCLC) patients have no effective targeted treatment. In this study, we aimed to investigate targeting epidermal growth factor receptor (EGFR) as a therapeutic approach in KRAS-driven lung cancer cells. We show that ablation of EGFR significantly suppressed tumor growth in KRAS-dependent cells and induced significantly higher expression of CX chemokine receptor 7 (CXCR7) and activation of MAPK (ERK1/2). Conversely, rescue of EGFR led to CXCR7 downregulation in EGFR-/- cells. Dual EGFR and CXCR7 inhibition led to substantial reduction of MAPK (pERK) and synergistic inhibition of cell growth. Analysis of two additional EGFR knockout NSCLC cell lines using CRISPR/Cas9 revealed genotype dependency of CXCR7 expression. In addition, treatment of different cells with gefitinib increased CXCR7 expression in EGFRwt but decreased it in EGFRmut cells. CXCR7 protein expression was detected in all NSCLC patient samples, with higher levels in adenocarcinoma as compared to squamous cell lung carcinoma and healthy control cases. In conclusion, EGFR and CXCR7 have a crucial interaction in NSCLC, and dual inhibition may be a potential therapeutic option for NSCLC patients.
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AIM: We investigated the role of GOLPH2 in non-small-cell lung cancer (NSCLC). METHODS: We analyzed the relationship between the expression of GOLPH2 and the clinical pathological characteristics of patients with NSCLC. The function of GOLPH2 in NSCLC cell lines was also explored through overexpression and knockdown studies. RESULTS: The positive expression rate of GOLPH2 protein in NSCLC tissue was higher than that of normal lung tissue. We found that positive GOLPH2 expression was closely associated with unfavorable features of patients with NSCLC. The GOLPH2 expression was an independent predictor of the prognosis of patients with NSCLC. That GOLPH2 can promote the proliferation and invasion of NSCLC cells. CONCLUSION: The GOLPH2 is a novel marker for NSCLC.