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Purpose: We established a CT-derived approach to achieve accurate progression-free survival (PFS) prediction to EGFR tyrosine kinase inhibitors (TKI) therapy in multicenter, stage IV EGFR-mutated non–small cell lung cancer (NSCLC) patients.Experimental Design: A total of 1,032 CT-based phenotypic characteristics were extracted according to the intensity, shape, and texture of NSCLC pretherapy images. On the basis of these CT features extracted from 117 stage IV EGFR-mutant NSCLC patients, a CT-based phenotypic signature was proposed using a Cox regression model with LASSO penalty for the survival risk stratification of EGFR-TKI therapy. The signature was validated using two independent cohorts (101 and 96 patients, respectively). The benefit of EGFR-TKIs in stratified patients was then compared with another stage-IV EGFR-mutant NSCLC cohort only treated with standard chemotherapy (56 patients). Furthermore, an individualized prediction model incorporating the phenotypic signature and clinicopathologic risk characteristics was proposed for PFS prediction, and also validated by multicenter cohorts.Results: The signature consisted of 12 CT features demonstrated good accuracy for discriminating patients with rapid and slow progression to EGFR-TKI therapy in three cohorts (HR: 3.61, 3.77, and 3.67, respectively). Rapid progression patients received EGFR TKIs did not show significant difference with patients underwent chemotherapy for progression-free survival benefit (P = 0.682). Decision curve analysis revealed that the proposed model significantly improved the clinical benefit compared with the clinicopathologic-based characteristics model (P < 0.0001).Conclusions: The proposed CT-based predictive strategy can achieve individualized prediction of PFS probability to EGFR-TKI therapy in NSCLCs, which holds promise of improving the pretherapy personalized management of TKIs. Clin Cancer Res; 24(15); 3583–92. ©2018 AACR.

Supplementary Table S1. Multivariable Cox regression analysis of various clinicopathologic characteristics and the twelve-feature-based signature with progression-free survival; Supplementary Table S2. Detail of treatment of all the patients. Including the administration of TKIs, mean time of TKI therapy and chemotherapy of each department; Supplementary Table S3. Univariate association of twelve features and progression-free survival in the training dataset; Supplementary Table S4. Comparison of clinical variables between the rapid-progression subgroup and slow-progression subgroup in EGFR-TKI cases; Supplementary Figure S1. X-tile plots of the twelve selected key features; Supplementary Figure S2. Turning parameter (λ) selection in the LASSO model; Supplementary Figure S3. Stratified analysis of the signature; Supplementary Figure S4. Time-dependent ROC curves of the risk characteristics; Supplementary Figure S5. Progression probability of three different patient cohorts.

Public access algorithms and source code in this study.

To assess the association between prespecified factors and the malignancy risk of solitary pulmonary nodules (SPNs) to support the development of rapid recommendations for daily use in the Chinese setting.The expert panel for the rapid recommendations voted for 12 candidate factors based on published guidelines, selected publications, and clinical experiences. We then searched Medline, Embase, and Web of Science up to October 17, 2021, for studies investigating the association between these factors and the diagnosis of malignant SPNs in patients with CT-identified SPNs through multivariable regression analysis. The risk of bias was assessed using the Agency for Healthcare Research and Quality (AHRQ) Checklist. We pooled adjusted odds ratios (aOR) between candidate factors and the diagnosis of the malignant SPNs.A total of 32 cross-sectional studies were included. Nine factors were statistically associated with malignant SPNs: age (aOR 1.06, 95% confidence interval [CI]: 1.05-1.07), smoking history (2.83, 1.84-4.36), history of extrathoracic malignancy (5.66, 2.80-11.46), history of malignancy (4.64, 3.37-6.39), family history of malignancy (3.11, 1.66-5.83), nodule diameter (1.23, 1.17-1.31), spiculation (3.41, 2.64-4.41), lobulation (3.85, 2.47-6.01), and mixed ground-glass opacity (mGGO) density of the nodule (5.56, 2.47-12.52). No statistical association was found between family history of lung cancer, emphysema, nodule border, and malignant SPNs.Nine prespecified factors were associated with the concurrent malignancy risk among patients with SPNs. Risk stratification for SPNs is warranted in clinical practice.

Objective Malignancy prediction models for pulmonary nodules are most accurate when used within nodules similar to those in which they were developed. This study was to establish models that respectively predict malignancy risk of incidental solid and subsolid pulmonary nodules of different size. Materials and Methods This retrospective study enrolled patients with 5-30 mm pulmonary nodules who had a histopathologic diagnosis of benign or malignant. The median time to lung cancer diagnosis was 25 days. Four training/validation datasets were assembled based on nodule texture and size: subsolid nodules (SSNs) ≤15 mm, SSNs between 15 and 30 mm, solid nodules ≤15 mm and those between 15 and 30 mm. Univariate logistic regression was used to identify potential predictors, and multivariate analysis was used to build four models. Results The study identified 1008 benign and 1813 malignant nodules from a single hospital, and by random selection 1008 malignant nodules were enrolled for further analysis. There was a much higher malignancy rate among SSNs than solid nodules (rate, 75% vs 39%, P

BACKGROUND: Combined small-cell lung cancer (CSCLC) refers to the simultaneous presence of small cell lung cancer (SCLC) and any subtype of the non-small cell lung cancer (NSCLC). This study aimed to explore the prognosis of CSCLC, NSCLC, and pure SCLC patients, and to develop a nomogram to estimate the overall survival (OS) for CSCLC patients. METHODS: Patients diagnosed with NSCLC, CSCLC, and pure SCLC between 2004 and 2015 were identified from the Surveillance Epidemiology and End Results (SEER) database. Survival analyses were performed by using the Kaplan Meier curves and Cox proportional hazards regression. All CSCLC patients were randomly split 7:3 into training and validation sets. A nomogram was developed by integrating all independent predictors for OS. The performance of the nomogram was determined by discrimination, calibration ability, clinical usefulness, and risk stratification ability. RESULTS: A total of 326,695 lung cancer patients, including 871 with CSCLC, 280,391 with NSCLC, and 45,433 with pure SCLC were enrolled. CSCLC was associated with worse survival compared with NSCLC both in the unmatched and matched cohorts. However, compared to pure SCLC, CSCLC was associated with significantly better survival in the unmatched cohorts only, while showed marginally non-significantly better survival after propensity score matching (PSM). For CSCLC, a nomogram was constructed for the 6-month, 1-year, and 3-year OS prediction by combining the independent risk factors, including age, gender, tumor, node, and metastasis stage, surgery, and chemotherapy. The nomogram showed good discrimination and calibration both in the training and validation sets, and better performance than the tumor–node–metastasis staging system. Risk stratification analysis indicated that the nomogram scores efficiently divided CSCLC patients into low-, intermediate-, and high-risk groups (P

Background The prognostic value of TP53 commutation in epidermal growth factor receptor (EGFR) mutant lung cancer is controversial and we therefore conducted this systematic review and meta-analysis. Methods A systematic search was carried out in Pubmed, Web of Science, the Cochrane Library, Medline and Embase up to 19 April 2018. The pooled hazard ratio (HR) of overall survival (OS) and progression-free survival (PFS), the relative risk (RR) of objective response rate (ORR) were calculated. Results Overall, a total of eight studies comprising 2979 patients were included. When generally comparing TP53 mutation group with TP53 wild-type group, we confirmed the prognostic value of poor OS of TP53 in EGFR mutant lung cancers (HR 1.73, 95% CI 1.22–2.44, P = 0.002). In subgroup analysis of OS, the prognostic value was maintained in patients treated with EGFR tyrosine kinase inhibitors (TKIs) but not in those treated with non-targeted therapy (HR 2.29, 95% CI 1.39–3.76, P = 0.001), and was also maintained in patients with advanced-stage lung cancers rather than those of all stages (HR 2.00, 95% CI 1.11–3.61, P = 0.021). For patients treated with EGFR TKIs, TP53 commutation was predictive of a poor PFS (HR 2.18, 95% CI 1.42–3.36, P < 0.001) but the prognostic value on ORR was not observed (RR 1.15, 95% CI 0.92–1.44, P = 0.212). Additional subgroup analysis based on TP53 mutation subtypes was not pooled due to limited data. Conclusion Generally we confirmed the prognostic value of poor OS and PFS of TP53 commutation in EGFR mutant lung cancers, and it should be further investigated and validated regarding the prognostic role of TP53 mutation subtypes.

BACKGROUND: We aimed to examine the different metastatic patterns and corresponding survival outcomes between all ages of young (aged

BackgroundLow-dose computed tomographic (LDCT) screening has been proven to be powerful in detecting lung cancers in early stage. However, it’s hard to carry out in less-developed regions in lacking of facilities and professionals. The feasibility and efficacy of mobile LDCT scanning combined with remote reading by experienced radiologists from superior hospital for lung cancer screening in deprived areas was explored in this study.MethodsA prospective cohort was conducted in rural areas of western China. Residents over 40 years old were invited for lung cancer screening by mobile LDCT scanning combined with remote image reading or local hospital-based LDCT screening. Rates of positive pulmonary nodules and detected lung cancers in the baseline were compared between the two groups.ResultsAmong 8073 candidates with preliminary response, 7251 eligibilities were assigned to the mobile LDCT with remote reading (n = 4527) and local hospital-based LDCT screening (n = 2724) for lung cancer. Basic characteristics of the subjects were almost similar in the two cohorts except that the mean age of participants in mobile group was relatively older than control (61.18 vs. 59.84 years old, P P vs. 76.1%, 32.9% vs. 29.8%, respectively; both P P = 0.006). Moreover, 80.8% (21/26) of lung cancer patients detected by mobile CT with remote reading were in stage I, remarkedly higher than that of 25.0% in control (1/4, P = 0.020).ConclusionMobile LDCT combined with remote reading is probably a potential mode for lung cancer screening in rural areas.Trial registrationNo. of registration trial was ChiCTR-DDD-15007586 (http://www.chictr.org).

Primary pulmonary lymphoepithelioma-like carcinoma (PPLELC) is a rare subtype of non-small cell lung cancer (NSCLC) for which there is currently no recognized treatment. Recently, favorable immune checkpoint blockade responses have been observed in PPLELC. This study aimed to review the effects of this regimen in patients with advanced PPLELC. PPLELC patients treated with immune checkpoint inhibitors at West China Hospital between January 2008 and December 2019 were retrospectively identified. Demographic parameters and antitumor treatment details were retrieved and reviewed. Among 128 patients diagnosed with PPLELC, 5 who received immune checkpoint inhibitors at advanced stages were included in the analysis. All of these patients were female nonsmokers with a median age of 55.6 (range 53-58) years at diagnosis. Their median PD-L1 expression was 40% (range, 30-80%). Although the patients underwent surgeries, chemotherapy and radiotherapy, all the treatments failed. Immune checkpoint inhibitors were administered palliatively, and three patients responded favorably, with the best overall response being partial remission (PR). Thus, immune checkpoint inhibitors may be a promising treatment for advanced PPLELC, and large clinical trials are warranted to obtain more evidence regarding this regimen.

Background Accurate evaluation of pulmonary nodule malignancy is important for lung cancer management. This current study aimed to develop risk models for small solid and subsolid pulmonary nodules based on clinical and quantitative radiomics features. Methods This study enrolled 5-20 mm pulmonary nodules detected on thoracic high-resolution computed tomography (HRCT), which were all confirmed pathologically. There were 548 solid nodules (242 malignant vs. 306 benign) and 623 subsolid nodules (SSNs 519 malignant vs. 104 benign). Relevant clinical characteristics were recorded. The CT image prior to the initial treatment was chosen for manual segmentation of the targeted nodule using the ITK-SNAP software. Subsequently, the marked image was processed to quantitatively extract 1218 radiomics features using PyRadiomics. We performed five-fold cross-validation to select potential predictors from clinical and radiomics features using the LASSO method and to evaluate the performance of the established models. In total, four types of models were tried: random forest, XGBOOST, SVM, and logistic models. The established models were compared with the Mayo model. Results Lung cancer risk models were developed among four nodule groups: all nodules (410 benign vs. 761 malignant; 1:1.86), nodules ≤10 mm (185 benign vs. 224 malignant; 1:1.21), solid nodules (306 benign vs. 242 malignant; 1.26:1), and SSNs (104 benign vs. 104 malignant; 1:1 matched). Significant clinical and radiomics predictors were selected for each group. The accuracy, area under the ROC curve, sensitivity, and specificity of the best model on validation dataset was 0.86, 0.91, 0.93, 0.73 for all nodules (XGBOOST), 0.82, 0.90, 0.86, 0.76 for nodules ≤10 mm (XGBOOST), 0.80, 0.89, 0.78, 0.82 for solid nodules (XGBOOST) and 0.70, 0.73, 0.73, 0.67 for SSNs (Random Forest). Except for the SSN models, the established clinical-radiomics models were superior to the Mayo model. Conclusions Predictive models based on both clinical and radiomics features can be used to assess the malignancy of small solid and subsolid pulmonary nodules, even for nodules that are 10 mm or smaller.

Background Early and accurate prognosis prediction of the patients was urgently warranted due to the widespread popularity of COVID-19. We performed a meta-analysis aimed at comprehensively summarizing the clinical characteristics and laboratory abnormalities correlated with increased risk of mortality in COVID-19 patients. Methods PubMed, Scopus, Web of Science, and Embase were systematically searched for studies considering the relationship between COVID-19 and mortality up to 4 June 2020. Data were extracted including clinical characteristics and laboratory examination. Results Thirty-one studies involving 9407 COVID-19 patients were included. Dyspnea (OR = 4.52, 95%CI [3.15, 6.48], P < 0.001), chest tightness (OR = 2.50, 95%CI [1.78, 3.52], P9/L, 95%CI [2.34, 4.21], P9/L, 95%CI [-0.46, -0.33], P Conclusions Among the common symptoms of COVID-19 infections, fatigue, expectoration, hemoptysis, dyspnea and chest tightness were independent predictors of death. As for laboratory examinations, significantly increased pretreatment absolute leukocytosis count, LDH, PCT, D-Dimer and ferritin, and decreased pretreatment absolute lymphocyte count were found in non-survivors, which also have an unbeneficial impact on mortality among COVID-19 patients. Motoring these indicators during the hospitalization plays a very important role in predicting the prognosis of patients.

Lung cancer is the leading cause of cancer death and there have been clinical prediction models. This study aimed to evaluate the diagnostic performance of published models and create new models to evaluate the probability of malignant solitary pulmonary nodules (SPNs) in Chinese population. We consecutively enrolled 2061 patients with SPNs from West China Hospital between January 2008 and December 2016, each SPN was pathologically confirmed. First, four published prediction models, Mayo clinic model, Veterans Affairs (VA) model, Brock model and People’s Hospital of Peking University (PEH) model were validated in our patients. Then, utilizing logistic regression, decision tree and random forest (RF), we developed three new models and internally validated them. Area under the receiver operating characteristic curve (AUC) values of four published models were as follows: Mayo 0.705 (95% CI 0.658–0.752, n = 726), VA 0.64 6 (95% CI 0.598–0.695, n = 800), Brock 0.575 (95% CI 0.502–0.648, n = 550) and PEH 0.675 (95% CI 0.627–0.723, n = 726). Logistic regression model, decision tree model and RF model were developed, AUC values of these models were 0.842 (95% CI 0.778–0.906), 0.734 (95% CI 0.647–0.821), 0.851 (95% CI 0.789–0.914), respectively. The four published lung cancer prediction models do not apply to our population, and we have established new models that can be used to predict the probability of malignant SPNs.

Dasatinib is a tyrosine kinase inhibitor for the treatment of BCR-ABL-positive chronic myeloid leukaemia (CML) or Philadelphia chromosome-positive acute lymphoblastic leukaemia (ALL). Although fluid retention is a common adverse event associated with dasatinib, chylothorax is exceptionally rare. The pathological mechanism, clinical manifestation and management of dasatinib-induced chylothorax are completely unclear. A 71-year-old man treated with dasatinib for CML was admitted for progressive dyspnea. Computed tomography (CT) showed a pleural effusion that was more prominent on the right thoracic cavity. Thoracentesis showed thick milky pleural fluid, which was then confirmed as chylothorax by chylum qualitative tests and triglyceride measurements. Radionuclide lymphoscintigraphy yielded an obstruction at the end segment of the thoracic duct, but no leakage points were found. After excluding common causes, drug-induced chylothorax was presumed. Then, dasatinib was withdrawn, and 1 week later, chylothorax resolved. To further elucidate the relationship between the medication and chylothorax, dasatinib was resumed tentatively for 2 days. As expected, pleural effusion recurred soon. Based on these clinical manifestations, the diagnosis of dasatinib-induced chylothorax was identified. The patient was suggested to stop dasatinib and use an alternative drug as recommended by the haematologist. Pleural effusion is the common adverse reaction of dasatinib, but chylothorax is rare. Only six cases of dasatinib-induced chylothorax have been reported, and our patient is the seventh case. Once a patient with dasatinib treatment develops chylothorax, dasatinib should be considered one of the possible causes. If no other definitive aetiological factor is identified, dasatinib discontinuation might be the optimum scheme.

Purpose: We established a CT-derived approach to achieve accurate progression-free survival (PFS) prediction to EGFR tyrosine kinase inhibitors (TKI) therapy in multicenter, stage IV EGFR-mutated non–small cell lung cancer (NSCLC) patients. Experimental Design: A total of 1,032 CT-based phenotypic characteristics were extracted according to the intensity, shape, and texture of NSCLC pretherapy images. On the basis of these CT features extracted from 117 stage IV EGFR-mutant NSCLC patients, a CT-based phenotypic signature was proposed using a Cox regression model with LASSO penalty for the survival risk stratification of EGFR-TKI therapy. The signature was validated using two independent cohorts (101 and 96 patients, respectively). The benefit of EGFR-TKIs in stratified patients was then compared with another stage-IV EGFR-mutant NSCLC cohort only treated with standard chemotherapy (56 patients). Furthermore, an individualized prediction model incorporating the phenotypic signature and clinicopathologic risk characteristics was proposed for PFS prediction, and also validated by multicenter cohorts. Results: The signature consisted of 12 CT features demonstrated good accuracy for discriminating patients with rapid and slow progression to EGFR-TKI therapy in three cohorts (HR: 3.61, 3.77, and 3.67, respectively). Rapid progression patients received EGFR TKIs did not show significant difference with patients underwent chemotherapy for progression-free survival benefit (P = 0.682). Decision curve analysis revealed that the proposed model significantly improved the clinical benefit compared with the clinicopathologic-based characteristics model (P < 0.0001). Conclusions: The proposed CT-based predictive strategy can achieve individualized prediction of PFS probability to EGFR-TKI therapy in NSCLCs, which holds promise of improving the pretherapy personalized management of TKIs. Clin Cancer Res; 24(15); 3583–92. ©2018 AACR.

OBJECTIVES: To analyze the distant metastasis possibility based on computed tomography (CT) radiomic features in patients with lung cancer. METHODS: This was a retrospective analysis of 348 patients with lung cancer enrolled between 2014 and February 2015. A feature set containing clinical features and 485 radiomic features was extracted from the pretherapy CT images. Feature selection via concave minimization (FSV) was used to select effective features. A support vector machine (SVM) was used to evaluate the predictive ability of each feature. RESULTS: Four radiomic features and three clinical features were obtained by FSV feature selection. Classification accuracy by the proposed SVM with SGD method was 71.02%, and the area under the curve was 72.84% with only the radiomic features extracted from CT. After the addition of clinical features, 89.09% can be achieved. CONCLUSION: The radiomic features of the pretherapy CT images may be used as predictors of distant metastasis. And it also can be used in combination with the patient's gender and tumor T and N phase information to diagnose the possibility of distant metastasis in lung cancer.

BackgroundPrimary pulmonary lymphoepithelioma-like carcinoma (LELC) is a rare tumor and often misdiagnosed as squamous carcinoma. In the current study, clinical characteristics and outcome of primary pulmonary LELC were systematically compared with pulmonary squamous carcinoma.MethodsForty-two cases of primary pulmonary LELC and 134 squamous carcinomas were enrolled retrospectively. Characteristic and prognosis difference between the two groups was compared, and the independent prognostic factor for pulmonary LELC was identified as well.ResultsIn comparison to squamous carcinoma, pulmonary LELC was more common in women with a younger median age and less smokers. LELC seemed to be smaller in diameter on computed tomography (CT) scans than squamous carcinoma, with scarce spiculation and vascular convergence signs. Epstein-Bar virus-encoded RNA (EBER) by in-situ hybridization was detected in 33 LELC cases, among whom 27 ones were positive in serum EBV-DNA examination. LELC patients presented a much longer median progression-free survival (PFS) than squamous carcinoma. Positive serum EBV-DNA, distant lymph node invasion, advanced clinical stage and receiving radiotherapy were correlated with the shorter PFS in LELC patients. However, only positive serum EBV-DNA was the independent PFS predictor.ConclusionPulmonary LELC looks like distinct from squamous carcinoma. Middle-aged women and nonsmokers are comparatively predominated. CT features of pulmonary LELC are relatively less-malignant. Correspondently, the progression of pulmonary LELC is seemingly favorable than squamous carcinoma and the positive serum EBV-DNA appears to be the predictor of PFS.

Additional file 1: Table S1. Pathological diagnosis, clinical stage and treatment of pulmonary LELC and squamous carcinoma. Table S2. Clinical outcomes of the pulmonary LELC patients and squamous carcinomas. Table S3. Relationship between clinical characteristics and PFS of LELC (Log-rank).

Radiomics is a novel approach for optimizing the analysis massive data from medical images to provide auxiliary guidance in clinical issues. Quantitative feature extraction is one of the critical steps of radiomics. The association between radiomics features and the clinicopathological information of diseases can be identified by several statistics methods. For instance, although significant progress has been made in the field of lung cancer, too many questions remain, especially for the individualized decisions. Radiomics offers a new tool to encode the characteristics of lung cancer which is the leading cause of cancer-related deaths worldwide. Here, we reviewed the workflow and clinical utility of radiomics in lung cancer management, including pulmonary nodules detection, classification, histopathology and genetics evaluation, clinical staging, therapy response, and prognosis prediction. Most of these studies showed positive results, indicating the potential value of radiomics in clinical practice. The implementation of radiomics is both feasible and invaluable, and has aided clinicians in ascertaining the nature of a disease with greater precision. However, it should be noted that radiomics in its current state cannot completely replace the work of therapists or tissue examination. The potential future trends of this modality were also remarked. More efforts are needed to overcome the limitations identified above in order to facilitate the widespread application of radiomics in the reasonably near future.

Background The current study was to investigate the volume doubling time (VDT) of lung adenocarcinomas considering epidermal growth factor receptor (EGFR) mutation status of exon 19 and 21, when compared with EGFR wide type. Methods Eighty-eight patients with pathologically proven adenocarcinomas, which underwent two or more computed tomography (CT) scans spared by 25 or more days, were included. EGFR mutations at exons 19 and 21 were determined using amplification refractory mutation system and all patients were divided into three groups-EGFR wide type group, EGFR mutation in exon 19 and 21 groups. Three-dimensional manual segmentations for all tumors were performed on first and latest follow-up CT scans; subsequently, VDTs were calculated and compared among three groups. Clinicopathoradiologic characters were also collected for subgroup analysis. Results EGFR mutations occurred in 49 (55.7%) patients, 19 in exon 19 and 30 in exon 21, respectively. The median VDT of all patients (33 men, 55 women; median age, 62 years) was 214 days (range, -4,092 to 10,920 days). Highly differentiated adenocarcinomas (median, 408 days) demonstrated longer VDT than those moderately (median, 172 days) or poorly (median, 144 days) differentiated (P=0.04). The VDT distribution was similar among EGFR wide type group (median, 207 days), EGFR mutation in exon 19 group (median, 288 days) and exon 21 group (median, 144 days) (P=0.21). In subgroup analysis, the median VDT of adenocarcinomas with EGFR mutation in exon 19 was longer than that of EGFR wide type for males (P=0.03) or patients without spiculation sign in chest CT (P=0.04). Totally 24 adenocarcinomas presented negative VDTs, most of which tended to be stable. Positive VDT values were used for all median description. Conclusions Overall VDT of lung adenocarcinomas seems not affected by EGFR mutation status. Researches with large population are warranted for further study.

RPS6KB1 is the kinase of ribosomal protein S6 which is 70 kDa and is required for protein translation. Although the abnormal activation of RPS6KB1 has been found in types of diseases, its role and clinical significance in non-small cell lung cancer (NSCLC) has not been fully investigated. In this study, we identified that RPS6KB1 was over-phosphorylated (p-RPS6KB1) in NSCLC and it was an independent unfavorable prognostic marker for NSCLC patients. In spite of the frequent expression of total RPS6KB1 and p-RPS6KB1 in NSCLC specimens by immunohistochemical staining (IHC), only p-RPS6KB1 was associated with the clinicopathologic characteristics of NSCLC subjects. Kaplan-Meier survival analysis revealed that the increased expression of p-RPS6KB1 indicated a poorer 5-year overall survival (OS) for NSCLC patients, while the difference between the positive or negative RPS6KB1 group was not significant. Univariate and multivariate Cox regression analysis was then used to confirm the independent prognostic value of p-RPS6KB1. To illustrate the underlying mechanism of RPS6KB1 phosphorylation in NSCLC, LY2584702 was employed to inhibit the RPS6KB1 phosphorylation specifically both in lung adenocarcinoma cell line A549 and squamous cell carcinoma cell line SK-MES-1. As expected, RPS6KB1 dephosphorylation remarkably suppressed cells proliferation in CCK-8 test, and promoted more cells arresting in G0-G1 phase by cell cycle analysis. Moreover, apoptotic A549 cells with RPS6KB1 dephosphorylation increased dramatically, with an elevating trend in SK-MES-1, indicating a potential involvement of RPS6KB1 phosphorylation in inducing apoptosis. In conclusion, our data suggest that RPS6KB1 is over-activated as p-RPS6KB1 in NSCLC, rather than just the total protein overexpressing. The phosphorylation level of RPS6KB1 might be used as a novel prognostic marker for NSCLC patients.

Overexpression of Raf‐1 has commonly been observed in solid tumors including non‐small cell lung cancer (NSCLC). The objective of this study was to investigate whether overexpression of Raf‐1, phosphorylated‐Raf‐1 (p‐Raf‐1) or both correlates with poor survival rate in NSCLC patients and to explore associations between expression of these proteins and NSCLC cell fate both in vitro and in vivo. Expression of Raf‐1 and p‐Raf‐1 were detected by immunohistochemistry in tumor specimens from 152 NSCLC patients and associations between their expression and the clinicopathological characteristics were assessed. Five‐year median survival rate of patients were analyzed by Kaplan–Meier method, log‐rank test and Cox regression. Cell fate was compared between normal tumor cells and those with Raf‐1 silencing, in both the adenocarcinoma cell line A549 and xenografted mice that were infected with the A549 cell line. The incidence of overexpression of both Raf‐1 and p‐Raf‐1 in NSCLC was much higher than normal control (P

The importance of apoptosis during the process of inhibiting tumorigenesis has been recognized. The role of BH3-only proapoptotic protein Bcl-2-associated death (BAD) in tumor growth remains controversial. The aim of this study was to explore the role of BAD in lung cancer cells. Our study showed that expression of BAD was upregulated in A549 cells by a recombinant lentivirus overexpressing BAD. In vitro, BAD overexpression significantly inhibited A549 cell proliferation and induced apoptosis in cell proliferation and apoptosis assays, respectively. The effect of BAD on A549 cells was studied in tumor xenograft of nude mice and the results showed that the tumor volume in the experimental group was smaller than the control groups. Further, immunohistochemical technique was used to determine the cell proliferation and apoptosis status of the lung tumor xenograft cells. This demonstrated that the in vivo and in vitro results were consistent. Taken together, our results indicate that overexpression of BAD inhibits the growth of A549 cells in vitro and in vivo, through inhibiting cell proliferation and inducing apoptosis. Thus, BAD could be a potential therapeutic target.

Objective: The purpose of this study was to establish a comprehensive evaluation system to assess the risk factors of lung cancer for the general population. Methods: With the method of evidence-based medicine, risk factors of lung cancer were identified and their risk assignments were calculated to design the Self-evaluation Scoring Questionnaire for High-risk Individuals of Lung Cancer. Studies including more than 10 000 subjects were carried the out to confirm the questionnaire's value. Results: The questionnaire consisted of 15 risk factors and their risk assignments, such as sex, age, smoking, female passive smoking, previous illness histories, exposure to harmful gases, mental depression and genetic susceptibility. In the population application, data from 30 lung cancer patients revealed its desired reliability and validity. The next pre-investigation, including 94 patients and 252 controls, confirmed its differentiating power, and encouraged a much larger-scale survey with 2161 subjects to determine the threshold (T) to identify high-risk individuals, the threshold was 116 points. According to this criterion, 1537 high-risk volunteers and 6556 controls were recruited to participate in a 3-year follow-up study from 2007 to 2009. There were 31 cases of lung cancer detected in the high-risk group, with a detection rate of 2.02%, significantly higher than that of the controls (5/6556, 0.08%), indicating an excellent predictive value of the questionnaire. Conclusions: The Self-evaluation Scoring Questionnaire for High-risk Individuals of Lung Cancer was a good means for evaluating the risks of lung cancer.

The mammalian Janus kinase (JAK) family plays a critical role in cytokine/growth factor signalling pathways and is associated with human cancers. In this study, we explored the role of JAK1 in the non-small cell lung cancer (NSCLC) cell line A549 and its molecular crosstalk with the phosphatidyl inositol-3-kinase (PI3K)/mammalian target of the rapamycin (mTOR) pathway. One hundred and two NSCLC and 50 normal lung specimens were collected after surgical resection. JAK1 expression and phosphorylation were determined via immunohistochemical staining (IHC) assay. A stable knockdown of JAK1 was performed in A549 cells by RNA interference. Stable cell proliferation, cell cycle, apoptosis, and invasion were characterised in vitro. Tumourigenicity was analysed in vivo. The NSCLC xenograft protein expression of PI3K/mTOR pathway molecules was determined by Western blot assay. JAK1 expression was higher in NSCLC tissues than in normal lung tissues (P

Background Ribosomal protein S6 (rpS6), a component of the 40S ribosomal subunit, is involved in multiple cellular bioactivities. However, its clinicopathological significance in non-small cell lung cancer (NSCLC) is poorly understood. Methods Expressions of total rpS6 (t-rpS6) and phosphorylated rpS6 (Ser235/236, p-rpS6) were detected immunohistochemically in 316 NSCLC tissues and 82 adjacent controls, followed by statistical evaluation of the relationship between proteins expressions and patients’ survivals to identify their prognostic values. Cytological experiments with overexpressing or silencing rpS6 by lentivirus in human bronchial epithelial (HBE) and NSCLC cell lines were performed to explore potential mechanisms by which rpS6 affects the clinical development of NSCLC. Additionally, specific RNA interference for Akt1, Akt2, Akt3, Akt inhibitor and subsequent cellular bioactivity tests were employed as well to investigate the upstream regulation of rpS6. Results Positive rates of t-rpS6 and p-rpS6 were both significantly increased in NSCLC tissues, compared with controls (82.91 vs 62.20 % for t-rpS6; 52.22 vs 21.95 % for p-rpS6; both P

Demographic characteristics of NSCLC patients and controls (Chi-square test). Table S2. Relationship between clinical characteristics and t-rpS6, p-rpS6 expressions in 316 NSCLC patients. (DOC 76Â kb)