MRI-based vector radiomics for predicting breast cancer HER2 status and its changes after neoadjuvant therapy.

PURPOSE: To develop a novel MRI-based vector radiomic approach to predict breast cancer (BC) human epidermal growth factor receptor 2 (HER2) status (zero, low, and positive; task 1) and its changes after neoadjuvant therapy (NAT) (positive-to-positive, positive-to-negative, and positive-to-pathologic complete response; task 2). MATERIALS AND METHODS: Both dynamic contrast-enhanced (DCE) MRI data and multi-b-value (MBV) diffusion-weighted imaging (DWI) data were acquired in BC patients at two centers. Vector-radiomic and conventional-radiomic features were extracted from both DCE-MRI and MBV-DWI. After feature selection, the following models were built using the retained features and logistic regression: vector model, conventional model, and combined model that integrates the vector-radiomic and conventional-radiomic features. The models' performances were quantified by the area under the receiver-operating characteristic curve (AUC). RESULTS: The training/external test set (center 1/2) included 483/361 women. For task 1, the vector model (AUCs=0.73∼0.86) was superior to (p<.05) the conventional model (AUCs=0.68∼0.81), and the addition of vector-radiomic features to conventional-radiomic features yielded an incremental predictive value (AUCs=0.80∼0.90, p<.05). For task 2, the combined MBV-DWI model (AUCs=0.85∼0.89) performed better than (p<.05) the conventional MBV-DWI model (AUCs=0.73∼0.82). In addition, for the combined DCE-MRI model and the combined MBV-DWI model, the former (AUCs=0.85∼0.90) outperformed (p<.05) the latter (AUCs=0.80∼0.85) in task 1, whereas the latter (AUCs=0.85∼0.89) outperformed (p<.05) the former (AUCs=0.76∼0.81) in task 2. The above results are true for the training and external test sets. CONCLUSIONS: MRI-based vector radiomics may predict BC HER2 status and its changes after NAT and provide significant incremental prediction over and above conventional radiomics.

Biosynthesis of 10-Hydroxy-2-decenoic Acid through a One-Step Whole-Cell Catalysis.

10-Hydroxy-2-decenoic acid (10-HDA) is an important component of royal jelly, known for its antimicrobial, anti-inflammatory, blood pressure-lowering, and antiradiation effects. Currently, 10-HDA biosynthesis is limited by the substrate selectivity of acyl-coenzyme A dehydrogenase, which restricts the technique to a two-step process. This study aimed to develop an efficient and simplified method for synthesizing 10-HDA. In this study, ACOX from Candida tropicalis 1798, which catalyzes 10-hydroxydecanoyl coenzyme A desaturation for 10-HDA synthesis, was isolated and heterologously coexpressed with FadE, Macs, YdiI, and CYP in Escherichia coli/SK after knocking out FadB, FadJ, and FadR genes. The engineered E. coli/AKS strain achieved a 49.8% conversion of decanoic acid to 10-HDA. CYP expression was improved through ultraviolet mutagenesis and high-throughput screening, increased substrate conversion to 75.6%, and the synthesis of 10-HDA was increased to 0.628 g/L in 10 h. This is the highest conversion rate and product concentration achieved in the shortest time to date. This study provides a simple and efficient method for 10-HDA biosynthesis and offers an effective method for developing strains with high product yields.

A Channel-Dimensional Feature-Reconstructed Deep Learning Model for Predicting Breast Cancer Molecular Subtypes on Overall b-Value Diffusion-Weighted MRI.

BACKGROUND: Dynamic contrast-enhanced (DCE) MRI commonly outperforms diffusion-weighted (DW) MRI in breast cancer discrimination. However, the side effects of contrast agents limit the use of DCE-MRI, particularly in patients with chronic kidney disease. PURPOSE: To develop a novel deep learning model to fully exploit the potential of overall b-value DW-MRI without the need for a contrast agent in predicting breast cancer molecular subtypes and to evaluate its performance in comparison with DCE-MRI. STUDY TYPE: Prospective. SUBJECTS: 486 female breast cancer patients (training/validation/test: 64%/16%/20%). FIELD STRENGTH/SEQUENCE: 3.0 T/DW-MRI (13 b-values) and DCE-MRI (one precontrast and five postcontrast phases). ASSESSMENT: The breast cancers were divided into four subtypes: luminal A, luminal B, HER2+, and triple negative. A channel-dimensional feature-reconstructed (CDFR) deep neural network (DNN) was proposed to predict these subtypes using pathological diagnosis as the reference standard. Additionally, a non-CDFR DNN (NCDFR-DNN) was built for comparative purposes. A mixture ensemble DNN (ME-DNN) integrating two CDFR-DNNs was constructed to identify subtypes on multiparametric MRI (MP-MRI) combing DW-MRI and DCE-MRI. STATISTICAL TESTS: Model performance was evaluated using accuracy, sensitivity, specificity, and area under the receiver operating characteristic curve (AUC). Model comparisons were performed using the one-way analysis of variance with least significant difference post hoc test and the DeLong test. P < 0.05 was considered significant. RESULTS: The CDFR-DNN (accuracies, 0.79 ~ 0.80; AUCs, 0.93 ~ 0.94) demonstrated significantly improved predictive performance than the NCDFR-DNN (accuracies, 0.76 ~ 0.78; AUCs, 0.92 ~ 0.93) on DW-MRI. Utilizing the CDFR-DNN, DW-MRI attained the predictive performance equal (P = 0.065 ~ 1.000) to DCE-MRI (accuracies, 0.79 ~ 0.80; AUCs, 0.93 ~ 0.95). The predictive performance of the ME-DNN on MP-MRI (accuracies, 0.85 ~ 0.87; AUCs, 0.96 ~ 0.97) was superior to those of both the CDFR-DNN and NCDFR-DNN on either DW-MRI or DCE-MRI. DATA CONCLUSION: The CDFR-DNN enabled overall b-value DW-MRI to achieve the predictive performance comparable to DCE-MRI. MP-MRI outperformed DW-MRI and DCE-MRI in subtype prediction. LEVEL OF EVIDENCE: 2 TECHNICAL EFFICACY STAGE: 1.

Study on the mechanism of warming yang and reducing turbidity decoction in the treatment of diabetic kidney disease based on network pharmacology.

This study aimed to investigate the mechanism of warming yang and reducing turbidity decoction in the treatment of diabetic kidney disease (DKD) by network pharmacology. The active components and corresponding targets of warming yang and reducing turbidity decoction were screened through the Traditional Chinese Medicine Systems Pharmacology database, DKD-related targets were obtained from Genecard and Online Mendelian Inheritance in Man databases, and drug-disease common targets were screened through Venny online website. Then we used STRING and Cytoscape software to analyze and perform protein-protein interaction network, and used CytoNCA plug-in to perform topological analysis to screen out the core target. We used RStudio to performed gene ontology (GO) functional enrichment analysis and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analysis. One hundred one active components in warming yang and reducing turbidity decoction participated in the regulation of the body's response to foreign bodies, lipopolysaccharides, metal ions, ketone bodies, hypoxia and oxidative stress by regulating 186 targets related to DKD, and played a role in the treatment of DKD by interfering with pathways such as interfered with lipids and atherosclerosis, PI3K-Akt, fluid shear stress and atherosclerosis, AGE-RAGE and cell senescence. It was implied that warming yang and reducing turbidity decoction had the features of multi components, multi targets and multi pathways in the treatment of DKD, which might create methods and directions for further verification of the molecular mechanism of warming yang and reducing turbidity decoction.

SST: Spatial and Semantic Transformers for Multi-Label Image Recognition.

Multi-label image recognition has attracted considerable research attention and achieved great success in recent years. Capturing label correlations is an effective manner to advance the performance of multi-label image recognition. Two types of label correlations were principally studied, i.e., the spatial and semantic correlations. However, in the literature, previous methods considered only either of them. In this work, inspired by the great success of Transformer, we propose a plug-and-play module, named the Spatial and Semantic Transformers (SST), to simultaneously capture spatial and semantic correlations in multi-label images. Our proposal is mainly comprised of two independent transformers, aiming to capture the spatial and semantic correlations respectively. Specifically, our Spatial Transformer is designed to model the correlations between features from different spatial positions, while the Semantic Transformer is leveraged to capture the co-existence of labels without manually defined rules. Other than methodological contributions, we also prove that spatial and semantic correlations complement each other and deserve to be leveraged simultaneously in multi-label image recognition. Benefitting from the Transformer's ability to capture long-range correlations, our method remarkably outperforms state-of-the-art methods on four popular multi-label benchmark datasets. In addition, extensive ablation studies and visualizations are provided to validate the essential components of our method.

An innovative random forest-based nonlinear ensemble paradigm of improved feature extraction and deep learning for carbon price forecasting.

Carbon price is the basis of developing a low carbon economy. The accurate carbon price forecast can not only stimulate the actions of enterprises and families, but also encourage the study and development of low carbon technology. However, as the original carbon price series is non-stationary and nonlinear, traditional methods are less robust to predict it. In this study, an innovative nonlinear ensemble paradigm of improved feature extraction and deep learning algorithm is proposed for carbon price forecasting, which includes complete ensemble empirical mode decomposition (CEEMDAN), sample entropy (SE), long short-term memory (LSTM) and random forest (RF). As the core of the proposed model, LSTM enhanced from the recurrent neural network is utilized to establish appropriate prediction models by extracting memory features of the long and short term. Improved feature extraction, as assistant data preprocessing, represents its unique advantage for improving calculating efficiency and accuracy. Removing irrelevant features from original time series through CEEMDAN lets learning easier and it's even better for using SE to recombine similar-complexity modes. Furthermore, compared with simple linear ensemble learning, RF increases the generalization ability for robustness to achieve the final nonlinear output results. Two markets' real data of carbon trading in china are as the experiment cases to test the effectiveness of the above model. The final simulation results indicate that the proposed model performs better than the other four benchmark methods reflected by the smaller statistical errors. Overall, the developed approach provides an effective method for predicting carbon price.

Visible continuum pulses based on enhanced dispersive wave generation for endogenous fluorescence imaging.

In this study, we demonstrate endogenous fluorescence imaging using visible continuum pulses based on 100-fs Ti:sapphire oscillator and a nonlinear photonic crystal fiber. Broadband (500-700 nm) and high-power (150 mW) continuum pulses are generated through enhanced dispersive wave generation by pumping femtosecond pulses at the anomalous dispersion region near zero-dispersion wavelength of high-nonlinear photonic crystal fibers. We also minimize the continuum pulse width by determining the proper fiber length. The visible-wavelength two-photon microscopy produces NADH and tryptophan images of mice tissues simultaneously. Our 500-700 nm continuum pulses support extending nonlinear microscopy to visible wavelength range that is inaccessible to 100-fs Ti:sapphire oscillators and other applications requiring visible laser pulses.

An improved multi-objective optimization model for supporting reservoir operation of China's South-to-North Water Diversion Project.

An improved multi-objective optimization model based on goal programming (GP) for supporting reservoir operation was developed under inflow senarios of multiple runoff guarantee rates (i.e., 25%, 75%, perennial mean, and 95%) and ecological goals with the combination of steady- and pulse-state ecological water demands. Under these four scenarios, discharge flows of Danjingkou Reservoir would be 358.40, 369.67, 268.91 and 98.14×108m3/a, and those at Taocha Canal headwork would be 104.61, 86.62, 95.08 and 64.00×108m3/a, respectively. The generated results for stream flows could successfully meet the predetermined operational goals for the project. Comparatively, under the scenario of 95% runoff guarantee rate, the obtained strategies could not satisfy the ecological water demands. The modeling results indicated that the capacity of water diversion and storage for Danjiangkou Reservoir would be enhanced due to the operation of the South-to-North Water Diversion Project. The results showed the risks associated with possible flooding would be comparatively low under those four runoff guarantee rates. This represents the current priority for flood control in Danjiangkou Reservoir needs to be changed into multiple ones including ecological water supply, water transfer, as well as downstream water security maintenance.

Randomized double-blind clinical trial of Moluodan () for the treatment of chronic atrophic gastritis with dysplasia.

OBJECTIVE: To assess the efficacy and safety of Moluodan () in treating dysplasia in chronic atrophic gastritis (CAG) patients. METHODS: This was a multi-centered, double-blind, randomized controlled trial. The total of 196 subjects were assigned to receive either Moluodan or folic acid in a 2:1 ratio by blocked randomization. Mucosa marking targeting biopsy (MTB) was used to insure the accuracy and consistency between baseline and after 6-month treatment. Primary outcomes were histological score, response rate of pathological lesions and dysplasia disappearance rate. Secondary endpoints included gastroscopic findings, clinical symptom and patient reported outcome (PRO) instrument. RESULTS: Dysplasia score decreased in Moluodan group (P =0.002), significance was found between groups (P =0.045). Dysplasia disappearance rates were 24.6% and 15.2% in Moluodan and folic acid groups respectively, no significant differences were found (P =0.127). The response rate of atrophy and intestinal metaplasia were 34.6% and 23.0% in Moluodan group, 24.3% and 13.6% in folic acid group. Moluodan could improve erythema (P =0.044), and bile reflux (P =0.059), no significance between groups. Moluodan was better than folic acid in improving epigastric pain, epigastric suffocation, belching and decreased appetite (P <0.05), with symptom disappearance rates of 37% to 83%. CONCLUSIONS: Moluodan improved dysplasia score in histopathology, and erythema and bile reflux score in endoscopy, and superior to folic acid in improving epigastric pain, epigastric suffocation, belching and decreased appetite. [ChiCTR-TRC-00000169].

[Reconstruction of deep wounds in old patients with cutaneous malignant tumor after artificial dermis combined with negative pressure wound therapy].

OBJECTIVE: To evaluate the effects of artificial dermis combined with negative pressure wound therapy on repairing wound aft er resection of cutaneous malignant tumor in elderly. METHODS: The clinical data of 34 hospitalized patients with cutaneous malignant tumor from July, 2009 to February, 2014 were retrospectively analyzed. The patients received local enlarged excision, artificial dermis covered wounds and 12-16 days of negative pressure wound therapy plus a free skin graft transplant on the surface with an artificial dermis. Recovery and complication aft er operation were assessed. RESULTS: All wounds were restored successfully with good appearance. None severe infection happened. CONCLUSION: Artificial dermis combined with negative pressure wound therapy can repair wound efficiently aft er cutaneous malignant tumor resection was performed for old patients.

Expression of c-fos was associated with clinicopathologic characteristics and prognosis in pancreatic cancer.

It has long been regarded that pancreatic cancer (PC) is a life-threatening malignant tumor. Thus, much attention has been paid for factors, especially relative molecules, predictive for prognosis of PC. However, c-fos expression in PC was less investigated. In addition, its association with clinicopathologic variables and prognosis remains unknown. In the present study, expression of c-fos was detected by tissue microarray-based immunohistochemical staining in cancer and adjacent tissues from 333 patients with PC. The staining results were correlated with clinicopathologic parameters and overall survival. Furthermore, prognostic significance of c-fos in subsets of PC was also evaluated. It was shown that low expression of c-fos was more often in cancer than in adjacent tissues of PC (P<0.001). Besides, high cancerous c-fos expression was significantly associated with tumor site and T stage, whereas peri-neural invasion was of a borderline significant relevance. Log-rank test revealed that high expression of c-fos in cancer tissues was a significant marker of poor overall survival, accompanied by some conventional clinicopathologic variables, such as sex, grade, peri-neural invasion, T and N stages. More importantly, cancerous c-fos expression was identified as an independent prognosticator in multivariate analysis. Finally, the prognostic implication of c-fos expression was proven in four subsets of patients with PC. These data suggested that c-fos expression was of relationships with progression and dismal prognosis of PC.

Overexpression of eukaryotic translation initiation factor 5A2 (EIF5A2) correlates with cell aggressiveness and poor survival in gastric cancer.

Eukaryotic translation initiation factor 5A2 (EIF5A2) plays an important role in tumor progression and prognosis evaluation. However, little information is available about its potential role in gastric cancer. This study aimed to investigate the function of EIF5A2 in tumor progression and its potential mechanisms. EIF5A2 expression was measured in human gastric cancer cell lines, the immortalized gastric mucosal epithelial cell line (GES-1) and human gastric cancer tissues and knocked down by RNA interference or upregulated by EIF5A2 plasmid transfection. Cell proliferation, migration and invasion were assessed in vitro. The downstream targets of EIF5A2 were examined by western blotting. EIF5A2 and its potential target metastasis-associated protein 1 (MTA1) expression were examined in 160 pairs of human gastric cancer and adjacent non-tumor specimens using immunohistochemistry (IHC) staining, and its correlation with clinicopathological features and survival was investigated. Knockdown of EIF5A2 or MTA1 caused an apparent suppression of HGC27 cell proliferation, migration and invasion. After knockdown of EIF5A2 in HGC27 cells, E-cadherin levels were upregulated and vimentin, cyclin D1, cyclin D3, C-MYC and MTA1 levels were downregulated. Upregulation of EIF5A2 in MKN45 cells resulted in the converse. IHC results showed a positive correlation between EIF5A2 and MTA1 expression in gastric cancers (P<0.001). Both EIF5A2 and MTA1 overexpression were correlated with pT stage (P=0.018 and P=0.042), pN stage (P=0.037 and P=0.020) and lymphovascular invasion (P=0.016 and P=0.044). EIF5A2 or MTA1 overexpression was significantly associated with poor overall survival and disease-free survival (All P<0.05). Multivariate analyses identified EIF5A2 as an independent predictor for both overall survival (P=0.012) and disease-free survival (P=0.008) in gastric cancer patients. Our findings indicate that EIF5A2 upregulation plays an important oncogenic role in gastric cancer. EIF5A2 may represent a new predictor for poor survival and is a potential therapeutic target for gastric cancer.

Nonlinear optical microscopy for immunoimaging: a custom optimized system of high-speed, large-area, multicolor imaging.

BACKGROUND: The nonlinear optical microscopy has become the current state-of-the-art for intravital imaging. Due to its advantages of high resolution, superior tissue penetration, lower photodamage and photobleaching, as well as intrinsic z-sectioning ability, this technology has been widely applied in immunoimaging for a decade. However, in terms of monitoring immune events in native physiological environment, the conventional nonlinear optical microscope system has to be optimized for live animal imaging. Generally speaking, three crucial capabilities are desired, including high-speed, large-area and multicolor imaging. Among numerous high-speed scanning mechanisms used in nonlinear optical imaging, polygon scanning is not only linearly but also dispersion-freely with high stability and tunable rotation speed, which can overcome disadvantages of multifocal scanning, resonant scanner and acousto-optical deflector (AOD). However, low frame rate, lacking large-area or multicolor imaging ability make current polygonbased nonlinear optical microscopes unable to meet the requirements of immune event monitoring. METHODS: We built up a polygon-based nonlinear optical microscope system which was custom optimized for immunoimaging with high-speed, large-are and multicolor imaging abilities. RESULTS: Firstly, we validated the imaging performance of the system by standard methods. Then, to demonstrate the ability to monitor immune events, migration of immunocytes observed by the system based on typical immunological models such as lymph node, footpad and dorsal skinfold chamber are shown. Finally, we take an outlook for the possible advance of related technologies such as sample stabilization and optical clearing for more stable and deeper intravital immunoimaging. CONCLUSIONS: This study will be helpful for optimizing nonlinear optical microscope to obtain more comprehensive and accurate information of immune events.

Angiosarcoma of the pericardium: a case report.

BACKGROUND: Primary malignant tumors of the pericardium are rare, and most primary malignant pericardium tumors are mesotheliomas. Primary pericardial angiosarcoma is extremely rare, and it is associated with a poor prognosis. CASE PRESENTATION: We report of a 47-year-old woman who complained of activity-related chest tightness and shortness of breath. Computed tomography, magnetic resonance imaging, and transesophageal echocardiography revealed an enlarged pericardium with hematic and solid components. An exploratory pericardiotomy was performed, and the results of the histological examination were suggestive of spindle cell hemangioendothelioma. She survived for 9 months after surgery without chemotherapy and radiotherapy, and she had a relatively good quality of life. CONCLUSION: Primary pericardial angiosarcoma is difficult to diagnose, and it has a poor prognosis. Pericardiotomy, radiation therapy, and chemotherapy were associated with a prolongation of survival.

Castleman disease variant of POEMS syndrome complicated with multiple cerebral infarction: a rare case report and review of literature.

POEMS syndrome is a rare hematological disorder associated with plasma cell dyscrasia characterized by polyneuropathy, organomegaly, endocrinopathy, monoclonal gammopathy and skin changes. Castleman disease is a lymphoproliferative disorder that can be present in POEMS patients, which can be defined as Castleman disease variant of POEMS syndrome. Herein, we described a 24-year-old male patient diagnosed with this syndrome and also suffered from multiple cerebral infarctions. This patient showed no evidence of monoclonal gammopathy and failed to have electromyography examined. The final diagnosis was established with the help of the axillary lymph node biopsy. As a rare case of POEMS syndrome without evidence fulfilling the major mandatory diagnostic criteria and with cerebrovascular involvement, its characteristics was discussed with a brief literature review in order to facilitate further understanding of the POEMS syndrome.

Prognostic significance of epidermal growth factor-like domain 7 in pancreatic cancer.

BACKGROUND: Recent studies have shown the clinical significance of epidermal growth factor-like domain 7 (EGFL7) in a variety of cancers. However, the relationship between EGFL7 and the prognosis of pancreatic cancer (PC) remains unclear. The present study was undertaken to investigate the role of EGFL7 in the prognosis of PC. METHODS: The expression of EGFL7 in nine PC cell lines was first determined by Western blotting analysis. Tissue microarray-based immunohistochemical staining was performed in paired formalin-fixed paraffin-embedded tumor and non-tumor samples from 83 patients with PC. Finally, correlations between EGFL7 expression and clinicopathological variables as well as overall survival were evaluated. RESULTS: EGFL7 was widely expressed in all PC cell lines tested. EGFL7 expression in tumor tissues was significantly higher than that in non-tumor tissues (P=0.040). In addition, univariate analysis revealed that high EGFL7 expression in tumor tissues was significantly associated with poor overall survival, accompanied by several conventional clinicopathological variables, such as gender, histological grade and lymph node metastasis. In a multivariate Cox regression test, EGFL7 expression was identified as an independent marker for long-term outcome of PC. CONCLUSION: Our data showed that EGFL7 is extensively expressed in PC and that EGFL7 is associated with poor prognosis.

The prognostic value of Cyclin B1 in pancreatic cancer.

Pancreatic cancer (PC), a malignancy with very poor prognosis, presents many molecular alterations, including overexpression of Cyclin B1. However, the prognostic value of the protein in PC remains to be elucidated. In the present study, Cyclin B1 expression was detected immunohistochemically in specimens from 241 patients with PC and was correlated with clinicopathological features and patient survival. It was found that Cyclin B1 expression, located in nucleus and/or cytoplasm, was not statistically associated with clinicopathologic variables. However, overall survival of patients with high Cyclin B1 expression was significantly poorer than that of those with low Cyclin B1 expression (P = 0.010). Moreover, Cyclin B1 was identified as an independent prognostic factor by multivariate Cox regression test (P = 0.003). Finally, its independent implication for prognosis was proven in five subgroups of PC, i.e., males, patients aged ≤ 65 years, G1-2 and N0 tumors as well as those with perineural invasion (all P < 0.05). These data indicate that high expression of Cyclin B1 is a valuable molecular marker of unfavorable prognosis in PC.

[Research advances in epithelial-mesenchymal transition in thyroid carcinoma].

Increasing evidences have demonstrated the roles of epithelial-mesenchymal transition in tumor invasion and metastasis. In the invasive front of papillary thyroid carcinoma, the expressions of adhesion molecules are often lost. In anaplastic thyroid carcinoma, tumor cells showing cancer stem cell characteristics have been identified. Epithelial-mesenchymal transition may thus play a key role in the progression of thyroid cancer. Therefore, it provide new insight for the development of targeted drugs for anaplastic thyroid carcinoma.

N-wasp in pancreatic ductal adenocarcinoma: associations with perineural invasion and poor prognosis.

BACKGROUND: Pancreatic ductal adenocarcinoma (PDAC) has long been acknowledged to have a dismal prognosis. Therefore, prognostic markers, especially molecular ones, are of interest. So far, expression of Neural Wiskott-Aldrich syndrome protein (N-WASP) and its associations with clinicopathologic variables and prognosis for patients with PDAC remain unknown. METHODS: N-WASP expression was detected by immunohistochemical staining in a tissue microarray consisted of tumor and nontumor samples from 86 patients with PDAC. The correlations of N-WASP expression with clinicopathologic features and overall survival were evaluated. In addition, risk factors of perineural invasion (PNI) were identified. RESULTS: High expression of N-WASP was more frequent in tumor than in nontumor tissues of PDAC patients (45.3 vs. 19.8%, p < 0.001). The rank of N-WASP grading was significantly higher in tumor tissues than in nontumor tissues (p = 0.048). Also, high expression of N-WASP in tumor tissues was significantly associated with PNI, and lymph node status had a marginally significant relation to tumoral N-WASP expression. Univariate analyses showed that, in addition to conventional clinicopathologic variables, including sex, histologic grade, PNI and lymph node metastasis, high tumoral N-WASP expression was an independent marker of PNI and served as a significant predictor of poor overall survival. The prognostic implication of N-WASP expression was not proven In the multivariate analysis. CONCLUSIONS: Our data showed highly up-regulated expression of N-WASP in PDAC tissues, its correlations with PNI, and its association with an unfavorable prognosis.

[Value of detecting epidermal growth factor receptor mutations in non-small cell lung cancer tissue by TaqMan-amplification refractory mutation system].

OBJECTIVE: To explore the value of detecting mutations on epidermal growth factor receptor (EGFR) gene in non-small cell lung cancer (NSCLC) tissue by TaqMan-amplification refractory mutation system (TaqMan-ARMS). METHODS: TaqMan-ARMS and DNA sequencing were used to detect the EGFR exon 19 and 21 mutations in tumor tissues and the samples collected from 199 patients at 4 different 3A hospitals in Beijing from January 2008 to March 2011. RESULTS: The rate of mutations in EGFR exon 19 and 21 was 19.1% (38/199), according to their different pathological types. Based upon TaqMan-ARMS, the classification was as followed: adenocarcinoma (35.0% (36/103)), squamous carcinoma (2.2% (2/93)) and adenosquamous carcinoma (0). According to DNA sequencing, they were 19.6% (39/199), 35.9% (37/103), 2.2% (2/93) and 0 respectively. Thus, no statistically significant difference existed between two methods (McNemar Test, P = 1.000, κ = 0.984). The mutation rate of adenocarcinoma was higher than those of squamous and adenosquamous carcinoma. CONCLUSION: The detection of EGFR mutations is highly consistent in the NSCLC tissue by the methods of TaqMan-ARMS and DNA sequencing.