Lung cancer staging now and in the future

Integrated Bioinformatics Analysis and Cellular Experimental Validation Identify Lipoprotein Lipase Gene as a Novel Biomarker for Tumorigenesis and Prognosis in Lung Adenocarcinoma

Lung adenocarcinoma (LUAD) is one of the leading causes of death worldwide, and thus, more biomarker and therapeutic targets need to be explored. Herein, we aimed to explore new biomarkers of LUAD by integrating bioinformatics analysis with cell experiments. We firstly identified 266 druggable genes that were significantly differentially expressed between LUAD tissues and adjacent normal lung tissues. Among these genes, SMR analysis with p-value correction suggested that declining lipoprotein lipase (LPL) levels may be causally associated with an elevated risk of LUAD, which was corroborated by co-localization analysis. Analyses of clinical data showed that LPL in lung cancer tissues has considerable diagnostic value for LUAD, and elevated LPL levels were positively associated with improved patient survival outcomes. Cell experiments with an LPL activator proved these findings; the activator inhibited the proliferation and migration of lung cancer cells. Next, we found that LPL promoted the infiltration of immune cells such as DCs, IDCs, and macrophages in LUAD by mononuclear sequencing analysis and TIMER2.0. Meanwhile, patients with low levels of LPL expression demonstrated superior immunotherapeutic responses to anti-PD-1 therapy. We conclude that LPL acts as a diagnostic and prognostic marker for LUAD.

Unsupervised non-small cell lung cancer tumor segmentation using cycled generative adversarial network with similarity-based discriminator

BACKGROUND

Tumor segmentation is crucial for lung disease diagnosis and treatment. Most existing deep learning-based automatic segmentation methods rely on manually annotated data for network training.

PURPOSE

This study aims to develop an unsupervised tumor segmentation network smic-GAN by using a similarity-driven generative adversarial network trained with cycle strategy. The proposed method does not rely on any manual annotations and thus reduce the training data preparation workload.

METHODS

A total of 609 CT scans of lung cancer patients are collected, of which 504 are used for training, 35 for validation, and 70 for testing. Smic-GAN is developed and trained to transform lung CT slices with tumors into synthetic images without tumors. Residual images are obtained by subtracting synthetic images from original CT slices. Thresholding, 3D median filtering, morphological erosion, and dilation operations are implemented to generate binary tumor masks from the residual images. Dice similarity, positive predictive value (PPV), sensitivity (SEN), 95% Hausdorff distance (HD95) and average surface distance (ASD) are used to evaluate the accuracy of tumor contouring.

RESULTS

The smic-GAN method achieved a performance comparable to two supervised methods UNet and Incre-MRRN, and outperformed unsupervised cycle-GAN. The Dice value for smic-GAN is significantly better than cycle-GAN (74.5% ± $ \pm $ 11.2% vs. 69.1%  ± $ \pm $ 16.0%, p < 0.05). The PPV for smic-GAN, UNet, and Incre-MRRN are 83.8% ± $ \pm $ 21.5%,75.1% ± $ \pm $ 19.7%, and 78.2%  ± $ \pm $ 16.6% respectively. The HD95 are 10.3 ± $\pm $ 7.7, 14.5 ± $\pm $ 14.6 and 6.2 ± $\pm $ 4.0 mm, respectively. The ASD are 3.7 ± $\pm $ 2.7, 4.8 ± $\pm $ 3.8, and 2.4 ± $\pm $ 1.8 mm, respectively.

CONCLUSION

The proposed smic-GAN performs comparably to the existing supervised methods UNet and Incre-MRRN. It does not rely on any manual annotations and can reduce the workload of training data preparation. It can also provide a good start for manual annotation in the training of supervised networks.

An innovative electrohydrodynamics-driven SERS platform for molecular stratification and treatment monitoring of lung cancer

The advancement of molecular diagnostics for lung cancer stratification and monitoring is essential for the strategic planning and prompt modification of treatments, aiming to enhance clinical results. To address this need, we suggest a nanocavity structure designed to sensitively analyze the protein signature on small extracellular vesicles (sEVs). This approach facilitates precise, noninvasive staging and treatment monitoring of lung cancer. The nanocavity is created through molecular recognition, involving the interaction of sEVs with nanobox-based core-shell surface-enhanced Raman scattering (SERS) barcodes and asymmetric, mirrorlike gold microelectrodes. By applying an alternating current to the gold microelectrodes, a nanofluidic shear force was generated, promoting the binding of sEVs and the effective assembly of the nanoboxes. This interaction induced a nanocavity between the nanobox and the gold microelectrode, which significantly amplified the electromagnetic field. This amplification enhanced Raman signals from four SERS barcodes simultaneously, allowing the generation of patient-specific molecular sEV signatures. When tested on a cohort of clinical samples (n = 76) using the nanocavity architecture, these patient-specific sEV molecular signatures accurately identified, stratified, and monitored lung cancer patients' treatment, demonstrating its potential for clinical application.

Molecular Stratification and Treatment Monitoring of Lung Cancer Using a Small Extracellular Vesicle-Activated Nanocavity Architecture

Development of molecular diagnostics for lung cancer stratification and monitoring is crucial for the rational planning and timely adjustment of treatments to improve clinical outcomes. In this regard, we propose a nanocavity architecture to sensitively profile the protein signature on small extracellular vesicles (sEVs) to enable accurate, noninvasive staging and treatment monitoring of lung cancer. The nanocavity architecture is formed by molecular recognition through the binding of sEVs with the nanobox-based core-shell surface-enhanced Raman scattering (SERS) barcodes and mirrorlike, asymmetric gold microelectrodes. By imposing an alternating current on the gold microelectrodes, a nanofluidic shear force was stimulated that supported the binding of sEVs and the efficient assembly of the nanoboxes. The binding of sEVs further induced a nanocavity between the nanobox and the gold microelectrode that significantly amplified the electromagnetic field to enable the simultaneous enhancement of Raman signals from four SERS barcodes and generate patient-specific molecular sEV signatures. Importantly, evaluated on a cohort of clinical samples (n = 76) on the nanocavity architecture, the acquired patient-specific sEV molecular signatures achieved accurate identification, stratification, and treatment monitoring of lung cancer patients, highlighting its potential for transition to clinical utility.

Classification of Histological Types and Stages in Non-small Cell Lung Cancer Using Radiomic Features Based on CT Images

Non-invasive diagnostic method based on radiomic features in patients with non-small cell lung cancer (NSCLC) has attracted attention. This study aimed to develop a CT image-based model for both histological typing and clinical staging of patients with NSCLC. A total of 309 NSCLC patients with 537 CT series from The Cancer Imaging Archive (TCIA) database were included in this study. All patients were randomly divided into the training set (247 patients, 425 CT series) and testing set (62 patients, 112 CT series). A total of 107 radiomic features were extracted. Four classifiers including random forest, XGBoost, support vector machine, and logistic regression were used to construct the classification model. The classification model had two output layers: histological type (adenocarcinoma, squamous cell carcinoma, and large cell) and clinical stage (I, II, and III) of NSCLC patients. The area under the receiver operating characteristic curve (AUC), accuracy, sensitivity, specificity, positive predictive value (PPV), and negative predictive value (NPV) with 95% confidence interval (CI) were utilized to evaluate the performance of the model. Seven features were selected for inclusion in the classification model. The random forest model had the best classification ability compared with other classifiers. The AUC of the RF model for histological typing and clinical staging of NSCLC patients in the testing set was 0.700 (95% CI, 0.641-0.759) and 0.881 (95% CI, 0.842-0.920), respectively. The CT image-based radiomic feature model had good classification ability for both histological typing and clinical staging of patients with NSCLC.

Computed Tomography Radiomics to Differentiate Intrahepatic Cholangiocarcinoma and Hepatocellular Carcinoma

AIMS

Intrahepatic cholangiocarcinoma (iCCA) and hepatocellular carcinoma (HCC) differ in prognosis and treatment. We aimed to non-invasively differentiate iCCA and HCC by means of radiomics extracted from contrast-enhanced standard-of-care computed tomography (CT).

MATERIALS AND METHODS

In total, 94 patients (male, n = 68, mean age 63.3 ± 12.4 years) with histologically confirmed iCCA (n = 47) or HCC (n = 47) who underwent contrast-enhanced abdominal CT between August 2014 and November 2021 were retrospectively included. The enhancing tumour border was manually segmented in a clinically feasible way by defining three three-dimensional volumes of interest per tumour. Radiomics features were extracted. Intraclass correlation analysis and Pearson metrics were used to stratify robust and non-redundant features with further feature reduction by LASSO (least absolute shrinkage and selection operator). Independent training and testing datasets were used to build four different machine learning models. Performance metrics and feature importance values were computed to increase the models' interpretability.

RESULTS

The patient population was split into 65 patients for training (iCCA, n = 32) and 29 patients for testing (iCCA, n = 15). A final combined feature set of three radiomics features and the clinical features age and sex revealed a top test model performance of receiver operating characteristic (ROC) area under the curve (AUC) = 0.82 (95% confidence interval =0.66-0.98; train ROC AUC = 0.82) using a logistic regression classifier. The model was well calibrated, and the Youden J Index suggested an optimal cut-off of 0.501 to discriminate between iCCA and HCC with a sensitivity of 0.733 and a specificity of 0.857.

CONCLUSIONS

Radiomics-based imaging biomarkers can potentially help to non-invasively discriminate between iCCA and HCC.

Uniportal VATS for Diagnosis and Staging in Non-Small Cell Lung Cancer (NSCLC)

Uniportal VATS has become an accepted approach in minimally invasive thoracic surgery since its first report for lobectomy in 2011. Since the initial restrictions in indications, it has been used in almost all procedures, from conventional lobectomies to sublobar resections, bronchial and vascular sleeve procedures and even tracheal and carinal resections. In addition to its use for treatment, it provides an excellent approach for suspicious solitary undiagnosed nodules after bronchoscopic or transthoracic image-guided biopsy. Uniportal VATS is also used as a surgical staging method in NSCLC due to its low invasiveness in terms of chest tube duration, hospital stay and postoperative pain. In this article, we review the evidence of uniportal VATS accuracy for NSCLC diagnosis and staging and provide technical details and recommendations for its safe performance for that purpose.

Traditional Treatment Approaches and Role of Immunotherapy in Lung Malignancy and Mesothelioma

There is no denying that many revolutions took place in the fight against cancer during the last decades. However, cancers have always managed to find new ways to challenge humankinds. Variable genomic epidemiology, socio-economic differences and limitations of widespread screening are the major concerns in cancer diagnosis and early treatment. A multidisciplinary approach is essentially to manage a cancer patient efficiently. Thoracic malignancies including lung cancers and pleural mesothelioma are accountable for little more than 11.6% of the global cancer burden [4]. Mesothelioma is one of the rare cancers, but concern is the incidences are increasing globally. However, the good news is first-line chemotherapy with the combination of immune checkpoints inhibitors (ICIs) in non-small cell lung cancer (NSCLC) and mesothelioma has showed promising respond and improved overall survival (OS) in pivotal clinical trials [10]. ICIs are commonly referred as immunotherapy are antigens on the cancer cells, and inhibitors are the antibodies produce by the T cell defence system. By inhibiting immune checkpoints, the cancer cells become visible to be identified as abnormal cells and attack by the body's defence system [17]. The programmed death receptor-1 (PD-1) and programmed death receptor ligand-1 (PD-L1) inhibitors are commonly used immune checkpoint blockers for anti-cancer treatment. PD-1/PD-L1 are proteins produced by immune cells and mimic by cancer cells that are implicated in inhibiting T cell response to regulate our immune system, which results tumour cells escaping the defence mechanism to achieve immune surveillance. Therefore, inhibiting immune checkpoints as well as monoclonal antibodies can lead to effective apoptosis of tumour cells [17]. Mesothelioma is an industrial disease caused by significant asbestos exposure. It is the cancer of the mesothelial tissue which presents in the lining of the mediastinum of pleura, pericardium and peritoneum, most commonly affected sites are pleura of the lung or chest wall lining [9] as route of asbestos exposure is inhalation. Calretinin is a calcium binding protein, typically over exposed in malignant mesotheliomas and the most useful marker even while initial changes take place [5]. On the other hand, Wilm's tumour 1 (WT-1) gene expression on the tumour cells can be related to prognosis as it can elicit immune response, thereby inhibit cell apoptosis. A systematic review and meta-analysis study conducted by Qi et al. has suggested that expression of WT-1 in a solid tumour is fatal however, it gives the tumour cell a feature of immune sensitivity which then acts positively towards the treatment with immunotherapy. Clinical significance of WT-1 oncogene in treatment is still hugely debatable and needs further attention [21]. Recently, Japan has reinstated Nivolumab in patients with chemo-refractory mesothelioma. According to NCCN guidelines, the salvage therapies include Pembrolizumab in PD-L1 positive patients and Nivolumab alone or with Ipilimumab in cancers irrespective of PD-L1 expression [9]. The checkpoint blockers have taken over the biomarker-based research and demonstrated impressive treatment options in immune sensitive and asbestos-related cancers. It can be expected that in near future the immune checkpoint inhibitors will be considered as approved first-line cancer treatment universally.

Development and Validation of a Comprehensive Model for Predicting Distant Metastasis of Solid Lung Adenocarcinoma: 3D Radiomics, 2D Radiomics and Clinical Features

OBJECTIVE

To develop and validate models for predicting distant metastases in patients with solid lung adenocarcinomas using 3D radiomic features, 2D radiomic features, clinical features, and their combinations.

METHODS

This retrospective study included 253 eligible patients with solid adenocarcinoma of the lung diagnosed at our hospital between August 2018 and August 2021. 3D and 2D regions of interest were segmented from computed tomography-enhanced thin-slice images of the venous phase, and 851 radiomic features were extracted in each region. The Least Absolute Shrinkage and Selection Operator (LASSO) algorithm was used to select radiomic features and calculate radiomic scores, and logistic regression was used to develop the model. Development of a 3D radiomics model (model 1), a 2D radiomics model (model 2), a combined 3D radiomics and 2D radiomics model (model 3), a clinical model (model 4), and a comprehensive model (model 5) for the prediction of distant metastases in patients with solid lung adenocarcinomas. Nomograms were drawn to illustrate model 5, and receiver operating characteristic (ROC) curve, calibration curve, and decision curve analysis (DCA) were used for model evaluation.

RESULTS

The AUC (area under the curve) of model 1, model 2, model 3, model 4, and model 5 in the test set was 0.711, 0.769, 0.775, 0.829, and 0.892, respectively. The Delong test showed that AUC values were statistically different between model 5 and model 1 (p=0.001), and there was no statistical difference in AUC between the other models. Based on a comprehensive review of DCA, ROC curve, and Akaike information criterion (AIC), Model 5 is demonstrated to have better clinical utility, goodness of fit, and parsimony.

CONCLUSION

A comprehensive model based on 3D radiomic features, 2D radiomic features, and clinical features has the potential to predict distant metastasis in patients with solid lung adenocarcinomas.

Potential factors of cytokeratin fragment 21-1 and cancer embryonic antigen for mediastinal lymph node metastasis in lung cancer

Objective: Lung cancer is a common malignant tumor, characterized by being difficult to detect and lacking specific clinical manifestations. This study aimed to find out the risk factors of mediastinal lymph node metastasis and explore the correlation between serum tumor markers and mediastinal lymph node metastasis and lung cancer prognosis.

Methods: A retrospective study of 3,042 lung cancer patients (330 patients with mediastinal lymph node metastasis and 2,712 patients without mediastinal lymph node metastasis) collected from the First Affiliated Hospital of Nanchang University from April 1999 to July 2020. The patients were divided into two groups, namely, mediastinal lymph node metastasis group and non-mediastinal lymph node metastasis group. Student’s t test, non-parametric rank sum test and chi-square test were used to describe whether there is a significant difference between the two groups. We compared the serum biomarkers of the two groups of patients, including exploring serum alkaline phosphatase (ALP), calcium hemoglobin (HB), alpha-fetoprotein (AFP), carcinoembryonic antigen (CEA), CA125, CA-199, CA -153, cytokeratin fragment 19 (CYFRA 21-1), total prostate specific antigen (TPSA), neuron-specific enolase (NSE) levels and the incidence and prognosis of lung cancer mediastinal lymph node metastasis. Binary logistic regression analysis was used to determine its risk factors, and receiver operating curve (ROC) analysis was used to evaluate its diagnostic value for mediastinal lymph node metastasis.

Results: Binary logistic regression analysis showed that carcinoembryonic antigen and CYFRA 21-1 were independent risk factors for mediastinal lymph node metastasis in patients with lung cancer (p < 0.001 and p = 0.002, respectively). The sensitivity and specificity of CEA for the diagnosis of mediastinal lymph node metastasis were 90.2 and 7.6%, respectively; CYFRA 21-1 were 0.6 and 99.0%, respectively.

Conclusion: Serum CEA and CYFRA 21-1 have predictive value in the diagnosis of mediastinal lymph node metastasis in patients with lung cancer.

MicroRNA-1-3p affects lung adenocarcinoma progression through E2F8 and regulating NF-кB pathway

E2F8 can modulate development and progression of various cancers including cervical cancer, breast cancer and hepatocellular carcinoma. But its mechanism in lung adenocarcinoma (LUAD) remains underexplored. In this study, we conducted a series of experiments including qRT-PCR, western blot, CCK-8, scratch healing assay, Transwell, and flow cytometry. Through these assays, we confirmed the notable overexpression of E2F8 in LUAD and its promoting effects on LUAD cell proliferation, migration and invasion. Subsequently, microRNA-1-3p that was negatively associated with E2F8 expression was identified through bioinformatics analysis. qRT-PCR was then carried out for quantification of microRNA-1-3p expression, which displayed low microRNA-1-3p expression in LUAD cells. In addition, dual-luciferase reporter gene assay was utilized for validating the targeted relationship between microRNA-1-3p and E2F8. The results denoted that microRNA-1-3p could bind to the promoter region of E2F8. Finally, the results of rescue experiment revealed that microRNA-1-3p negatively modulated E2F8 level. It regulated NF-κB pathway to repress LUAD cell proliferative, migratory, and invasive properties, lead to cell cycle arrest in G0/G1 phase, and enhance cell apoptosis level. This study unraveled that microRNA-1-3p/E2F8 constrained LUAD malignant progression through NF-κB pathway, which may provide possible targets for LUAD diagnosis and treatment.

Development and Validation of a CT-Based Signature for the Prediction of Distant Metastasis Before Treatment of Non-Small Cell Lung Cancer

RATIONALE AND OBJECTIVES

To develop and validate a radiomics model, a clinical-semantic model and a combined model by using standard methods for the pretreatment prediction of distant metastasis (DM) in patients with non-small-cell lung cancer (NSCLC) and to explore whether the combined model provides added value compared to the individual models.

MATERIALS AND METHODS

This retrospective study involved 356 patients with NSCLC. According to the image biomarker standardization initiative reference manual, we standardized the image processing and feature extraction using in-house software. Finally, 6692 radiomics features were extracted from each lesion based on contrast-enhanced chest CT images. The least absolute shrinkage selection operator and the recursive feature elimination algorithm were used to select features. The logistic regression classifier was used to build the model. Three models (radiomics model, clinical-semantic model and combined model) were constructed to predict DM in NSCLC. Area under the receiver operating characteristic curves were used to validate the ability of the three models to predict DM. A visual nomogram based on the combined model was developed for DM risk assessment in each patient.

RESULTS

The receiver operating characteristic curve showed predictive performance for DM of the radiomics model (area under the curve [AUC] values for training and validation were 0.76 [95% CI, 0.704 - 0.820] and 0.76 [95% CI, 0.653 - 0.858], respectively). The combined model had AUCs of 0.78 (95% CI, 0.723 - 0.835) and 0.77 (95% CI, 0.673 - 0.870) in the training and validation cohorts, respectively. Both the radiomics model and combined model performed better than the clinical-semantic model (0.70 [95% CI, 0.634 - 0.760] and 0.67 [95% CI, 0.554 - 0.787] in the training and validation cohorts, respectively).

CONCLUSION

The radiomics model and combined model may be useful for the prediction of DM in patients with NSCLC.

Enhanced CT-Based Radiomics to Predict Micropapillary Pattern Within Lung Invasive Adenocarcinoma

Objective

We aimed to investigate whether enhanced CT-based radiomics can predict micropapillary pattern (MPP) of lung invasive adenocarcinoma (IAC) in the pre-op phase and to develop an individual diagnostic predictive model for MPP in IAC.

Methods

170 patients who underwent complete resection for pathologically confirmed lung IAC were included in our study. Of these 121 were used as a training cohort and the other 49 as a test cohort. Clinical features and enhanced CT images were collected and assessed. Quantitative CT analysis was performed based on feature types including first order, shape, gray-level co-occurrence matrix-based, gray-level size zone matrix-based, gray-level run length matrix-based, gray-level dependence matrix-based, neighboring gray tone difference matrix-based features and transform types including Log, wavelet and local binary pattern. Receiver operating characteristic (ROC) and area under the curve (AUC) were used to value the ability to identify the lung IAC with MPP using these characteristics.

Results

Using quantitative CT analysis, one thousand three hundred and seventeen radiomics features were deciphered from R (https://www.r-project.org/). Then these radiomic features were decreased to 14 features after dimension reduction using the least absolute shrinkage and selection operator (LASSO) method in R. After correlation analysis, 5 key features were obtained and used as signatures for predicting MPP within IAC. The individualized prediction model which included age, smoking, family tumor history and radiomics signature had better identification (AUC=0.739) in comparison with the model consisting only of radiomics features (AUC=0.722). DeLong test showed that the difference in AUC between the two models was statistically significant (P<0.01). Compared with the simple radiomics model, the more comprehensive individual prediction model has better prediction performance.

Conclusion

The use of radiomics approach is of great value in the diagnosis of tumors by non-invasive means. The individualized prediction model in the study, when incorporated with age, smoking and radiomics signature, had effective predictive performance of lung IAC with MPP lesions. The combination of imaging features and clinical features can provide additional diagnostic value to identify the micropapillary pattern in IAC and can affect clinical diagnosis and treatment.

The diagnostic and predictive efficacy of 18F-FDG PET/CT metabolic parameters for EGFR mutation status in non-small-cell lung cancer: A meta-analysis

PURPOSE

To investigate the predictive performance of the maximum standardized uptake value (SUV_max) and mean standardized uptake value (SUV_mean) of primary lesions based on 18 F-fluorodeoxyglucose positron emission tomography/computed tomography (¹⁸F-FDG PET/CT) for EGFR mutation status in patients with non-small cell lung cancer (NSCLC).

METHODS

The PubMed/Medline, Embase, Cochrane Library and Web of Science databases were searched as of January 1, 2021. Studies whose reported data could be used to construct contingency tables were included. Study characteristics were extracted, and methodological quality assessment was conducted by two separate reviewers using the Quality Assessment of Diagnostic Accuracy Studies. The pooled sensitivity, specificity and area under the summary receiver operating characteristic curve (AUROC) were calculated. The possible causes of heterogeneity were analysed by meta-regression.

RESULTS

The 18 included studies had a total of 4024 patients. The majority of the studies showed a low to unclear risk of bias and concerns of applicability. For differentiating EGFR-mutant NSCLC from wild-type NSCLC, the pooled sensitivity and specificity were 71 % and 60 % for SUV_max and 64 % and 63 % for SUV_mean, respectively. The summary AUROCs of SUV_max and SUV_mean were 0.69 (95 % CI, 0.65-0.73) and 0.68 (95 % CI, 0.64-0.72), respectively. The meta-regression analysis indicated that blindness to EGFR mutation test results, the number of readers and the number of PET/CT scanners were possible causes of heterogeneity.

CONCLUSIONS

Our meta-analysis implied that SUV_max and SUV_mean of primary lesions from ¹⁸F-FDG PET/CT harboured moderate predictive efficacy for the EGFR mutation status of NSCLC.

Prognostic and clinicopathological value of PD-L2 in lung cancer: A meta-analysis

OBJECTIVE

The prognostic role of programmed death ligand-2 (PD-L2) expression in lung cancer has been widely studied, however, the results are controversial. Accordingly, we investigated the prognostic and clinicopathological value of PD-L2 in patients with lung cancer in this meta-analysis.

METHODS

Relevant studies were systematically searched in the PubMed, Web of Science, EMBASE, ClinicalTrials.gov., Scopus, and Cochrane Library until July 10, 2020. The hazard ratio (HR), odds ratio (OR), and their corresponding 95% confidence intervals (CIs) were calculated.

RESULTS

Thirteen studies with 3107 participants were included. High PD-L2 expression was associated with poor overall survival (OS) (HR 1.248, 95% CI: 1.071-1.455, p = 0.004) and worse disease-free survival (DFS)/progression-free survival (PFS)/relapse-free survival (RFS) (HR 1.224, 95% CI: 1.058-1.417, p = 0.007) in lung cancer. Furthermore, unfavorable OS was found in lung adenocarcinoma (HR 1.349, 95% CI: 1.051-1.731, p = 0.019), but not in other pathological types (HR 1.192, 95% CI: 0.982-1.447 p = 0.076) with higher PD-L2 expression in our subgroup analysis. Concerning the clinicopathological characteristics, high PD-L2 expression was associated with smoking (OR 0.725, 95% CI: 0.591-0.890, p = 0.002) and PD-L1 (OR 1.607, 95% CI:1.115-2.314, p = 0.011) and vascular invasion (OR 1.500, 95% CI: 1.022-2.203, p = 0.039).

CONCLUSION

PD-L2 overexpression might predict a poor prognosis in lung cancer patients after surgery. PD-L2 expression might be a potential biomarker for PD-1/PD-L1-targeted immunotherapy in lung cancer, which should be investigated in future studies.

Acute pneumothorax due to immunotherapy administration in non-small cell lung cancer

Nowadays we have novel therapies for advanced stage non-small cell lung cancer. Immunotherapy has been introduced in the market for several years and until now its administration is mostly based on the programmed death-ligand 1. First line treatment with immunotherapy can be administered alone if programmed death-ligand 1 expression is ≥ 50%. All therapies for advanced stage disease have advantages and disadvantages, immunotherapy until now has presented mild adverse effects when compared to chemotherapy. However; it is known to induce inflammatory response to different tissues within the body. In our case acute pneumothorax was induced after immunotherapy administration.

Baicalin encapsulating lipid-surfactant conjugate based nanomicelles: Preparation, characterization and anticancer activity

Lung cancer is one of the most common malignant tumors and emerged as one of the leading causes of cancer-related death worldwide. Surgical resection can be a curative treatment for early stage but the most of lung cancer patients are diagnosed at an advanced stage when the pulmonary tumor has been invaded beyond the respiratory system. Therefore, chemotherapy is suitable for curing metastasized tumor. Baicalin (BL) is a flavonoid which has been studied in the treatment of several types of cancer including lung cancer. However, its low solubility in water and non-specificity impede its practical utilization. Hence, we have reported a stearic acid and pluronic F68 conjugated nanomicelles (PF68-SA) system to improve therapeutic efficacy of BL. Solvent evaporation method was used to prepare the BL-loaded PF68-SA nanomicelles (BLNM). The designed BLNM were characterized for the particle size, surface charge, critical micelle concentration, colloidal stability, morphology, and total drug content. BLNM formulation showed improved toxicity of BL against A549 human lung cancer cells in cytotoxicity assay. Further, apoptosis study also depicted BLNM-induced cell death in A549 cells. Therefore, the synthesized fatty acid-modified polymeric nanomicellar system could be useful in overcoming the stability and low therapeutic efficacy issues of hydrophobic anticancer drugs like BL and delivering them to the cancer cells.

Implementation of lung cancer multidisciplinary teams: a review of evidence-practice gaps

Multidisciplinary care (MDC) is considered best practice in lung cancer care. Health care services have made significant investments in MDC through the establishment of multidisciplinary team (MDT) meetings. This investment is likely to be sustained in future. It is imperative that MDT meetings are efficient, effective, and sufficiently nimble to introduce new innovations to enable best practice. In this article, we consider the ‘evidence-practice gaps’ in the implementation of lung cancer MDC. These gaps were derived from the recurrent limitations outlined in existing studies and reviews. We address the contributions that implementation science and quality improvement can make to bridge these gaps by increasing translation and improving the uptake of innovations by teams.

Accuracy of lung cancer staging in the multidisciplinary team setting

Accurate staging of lung cancer is of utmost importance in determining the stage-appropriate treatment and prognosis. Imaging tests which include contrast-enhanced computed tomography (CT) examination of the chest to include the liver and adrenal glands and 18-fluoro-2 deoxyglucose positron emission tomography (PET)/CT scan facilitate the initial tumor node metastasis (TNM) staging of the disease and provide guidance on the optimal biopsy site and biopsy method. The diagnostic and staging approach should be tailored to the individual patient according to risk, benefit, patient preferences, and available expertise. Diagnosis and staging should preferably be accomplished with a single procedure or the least number of invasive procedures if more than one is needed. Ideally, centers managing lung cancer patients should have a multidisciplinary thoracic oncology board prescribing personalized evidence-based management tailored to each individual patient. Multidisciplinary team (MDT) meetings provide a platform for key experts from various disciplines to contribute specific advice on the management of each individual patient. As assessment of mediastinal lymph node involvement is an important component of lung cancer staging, optimal mediastinal staging can be achieved with a variety of techniques that can be discussed and performed by the various specialists in the MDT. Despite a relative paucity of quality evidence that MDT contributes to improvements in lung cancer survival outcomes, this approach has evolved to become the standard of care in many centers around the world. Thoracic MDT has resulted in more focused and timely investigations for histopathologic diagnosis and disease staging which translate into earlier treatment initiation. Moreover, there is increasing evidence that MDT care facilitates and allows access to investigations that lead to improved accuracy of tumor and nodal staging. However, there is still a paucity of evidence on the accuracy of lung cancer staging in the MDT setting.

Between wellness, relapse, and remission: Stages of illness in anorexia nervosa

OBJECTIVE

Psychiatric illnesses, like medical illnesses, can sometimes be considered as progressing through stages. Understanding these stages can lead to a better understanding of pathophysiology, and clarification of prognosis and treatment needs. Opinions from experts in the field of anorexia nervosa (AN) were sought to create a model of stages of illness.

METHOD

The Delphi approach was used to achieve consensus from a panel of 31 individuals from a range of disciplines with expertise in AN. Over three iterative rounds, participants rated agreement with statements about an overall staging framework and definitions of specific stages.

RESULTS

Agreement was reached about a longitudinal progression including Subsyndromal, Full Syndrome, Persistent Illness, and Partial and Full Remission. The panel achieved consensus in defining Subsyndromal AN as characterized by body image disturbance and mild to moderate restrictive eating. Overall, there was consensus that restrictive eating is central to the behavioral features of all stages of AN, and agreement that its absence is essential to any stage of health. There was little consensus about biological markers, other than body mass index, and no consensus about quality of life indices associated with different stages.

DISCUSSION

This panel discussion yielded an expert-informed staging model for AN. This model now needs to be tested for its validity. The lack of consensus in several areas highlighted other research questions to address in order to develop an empirically valid and scientifically useful model of the progression of AN.

4D-CT Hyper-Elastography Using a Biomechanical Model

Low dose computed tomography (LDCT) is the current gold-standard for lung cancer diagnosis. However, accuracy of diagnosis is limited by the radiologist's ability to discern cancerous from non-cancerous nodules. To assist with diagnoses, a 4D-CT lung elastography method is proposed to distinguish nodules based on tissue stiffness properties. The technique relies on a patient-specific inverse finite element (FE) model of the lung solved using an optimization algorithm. The FE model incorporates hyperelastic material properties for tumor and healthy regions and was deformed according to respiration physiology. The tumor hyperelastic parameters and trans-pulmonary pressure were estimated using an optimization algorithm that maximizes similarity between the actual and simulated tumor and lung image data. The proposed technique was evaluated using an in-silico study where the lung tumor elastic properties were assumed. Following that evaluation, the technique was applied to clinical 4D-CT data of two lung cancer patients. Results from the evaluation study show that the elastography technique recovered known tumor parameters with only 6% error. Tumor hyperelastic properties from the clinical data are also reported. Results from this proof of concept study demonstrate the ability to perform lung elastography with 4D-CT data alone. Advancements in the technique could lead to improved diagnoses and timely treatment of lung cancer.

Upregulation of lncRNA ZFAS1 promotes lung adenocarcinoma progression by sponging miR-1271-5p and upregulating FRS2

Background

Nowadays, the important roles of long non‐coding RNAs (LncRNAs) in lung adenocarcinoma (LAD) is being increasingly recognized. The purpose of this study was to explore the regulatory mechanism of lncRNA ZFAS1 in LAD.

Methods

The expression and function of lncRNA ZFAS1 were assessed by RT‐qPCR, CCK‐8, transwell and dual luciferase reporter assays.

Results

Upregulation of lncRNA ZFAS1 was found in LAD tissues and cells. Knockdown of lncRNA ZFAS1 restrained cell proliferation, migration and invasion in LAD cells. In addition, we determined that lncRNA ZFAS1 could directly bind to miR‐1271‐5p. MiR‐1271‐5p functioned as a tumor suppressor in LAD, and lncRNA ZFAS1 promoted LAD development by downregulating miR‐1271‐5p. Furthermore, FRS2 was a direct target of miR‐1271‐5p. FRS2 promoted progression of LAD by mediating lncRNA ZFAS1/miR‐1271‐5p axis.

Conclusions

LncRNA ZFAS1 promotes cell proliferation, migration and invasion in LAD by downregulating miR‐1271‐5p or upregulating FRS2.

18F-FDG PET/CT and whole-body MRI diagnostic performance in M staging for non-small cell lung cancer: a systematic review and meta-analysis

OBJECTIVES

To evaluate the diagnostic test accuracy of 18F-fluorodeoxyglucose positron emission tomography/computed tomography (18F-FDG PET/CT), whole-body magnetic resonance imaging (WB-MRI), and whole-body diffusion-weighted imaging (WB-DWI) for the detection of metastases in patients with non-small cell lung cancer (NSCLC).

METHODS

MEDLINE, Embase, and Cochrane Library databases were searched up to June 2019. Studies were selected if they reported data that could be used to construct contingency tables to compare 18F-FDG PET/CT, WB-MRI, and WB-DWI. Two authors independently extracted data on study characteristics and assessed methodological quality using the Quality Assessment of Diagnostic Accuracy Studies. Forest plots were generated for sensitivity and specificity of 18F-FDG PET/CT, WB-MRI, and whole-body diffusion-weighted imaging (WB-DWI). Summary receiver operating characteristic plots were created.

RESULTS

The 4 studies meeting inclusion criteria had a total of 564 patients and 559 lesions, 233 of which were metastases. In studies of 18F-FDG PET/CT, the pooled estimates of sensitivity and specificity were 0.83 (95% confidence interval [CI], 0.54-0.95) and 0.93 (95% CI, 0.87-0.96), respectively. For WB-MRI, pooled sensitivity was 0.92 (95% CI, 0.18-1.00) and pooled specificity was 0.93 (95% CI, 0.85-0.95). Pooled sensitivity and specificity for WB-DWI were 0.78 (95% CI, 0.46-0.93) and 0.91 (95% CI, 0.79-0.96), respectively. There was no statistical difference between the diagnostic odds ratio of WB-MRI and WB-DWI compared with that of PET/CT (p = 0.186 for WB-DWI; p = 0.638 for WB-MRI).

CONCLUSION

WB-MRI and DWI are radiation-free alternatives with comparable diagnostic performance to 18F-FDG PET/CT for M staging of NSCLC.

KEY POINTS

• Whole-body MRI with or without diffusion-weighted imaging has a high accuracy for the diagnostic evaluation of metastases in patients with non-small cell lung cancer. • Whole-body MRI may be used as a non-invasive and radiation-free alternative to positron emission tomography with CT with similar diagnostic performance.

Downregulation of miR-499a-5p Predicts a Poor Prognosis of Patients With Non-Small Cell Lung Cancer and Restrains the Tumorigenesis by Targeting Fibroblast Growth Factor 9

The aberrant expression of microRNA is an important regulator in the tumorigenesis of non-small cell lung cancer. In this study, we found that miR-499a-5p was notably downregulated in non-small cell lung cancer tissues and cell lines. Decreased miR-499a-5p expression was associated with larger tumor size and higher TNM stage. Non-small cell lung cancer patients with low expression of miR-499a-5p exhibited a worse overall survival rate compared with those patients with high expression of miR-499a-5p. Ectopic expression of miR-499a-5p significantly suppressed non-small cell lung cancer cell proliferation and colony formation, and hampered cell cycle at G0/G1 phase in vitro. Conversely, knockdown of miR-499a-5p promoted non-small cell lung cancer cell proliferation and colony formation, and induced cell cycle at S phase. Furthermore, in vivo experiments revealed that overexpression of miR-499a-5p inhibited the tumor formation in a nude mouse xenograft model. Mechanistic studies showed that fibroblast growth factor 9 was a direct target gene of miR-499a-5p. miR-499a-5p directly bound to fibroblast growth factor 9 mRNA 3'-UTR, therefore led to the reduction in fibroblast growth factor 9 protein expression. Finally, rescue experiments confirmed that silencing of fibroblast growth factor 9 partially reversed the phenotypes of miR-499a-5p knockdown on non-small cell lung cancer cell proliferation. In conclusion, our study demonstrates that downregulation of miR-499a-5p predicts a worse prognosis of patients with non-small cell lung cancer and restrains the tumorigenesis by targeting fibroblast growth factor 9. These findings may provide valuable clues for the future development of therapeutic strategies against this cancer.

The long noncoding RNA LINC00483 promotes lung adenocarcinoma progression by sponging miR-204-3p

BACKGROUND

The expression of the long noncoding RNA LINC00483 is upregulated in lung adenocarcinoma (LUAD). However, its role in the progression of LUAD and the underlying mechanisms remain elusive.

METHODS

The expressions of LINC00483 and miR-204-3p were determined using quantitative real-time PCR. The correlation between the clinicopathological characteristics of LUAD patients and LINC00483 expression was analyzed using Pearson's χ2 test. A549 and PC-9 cells were transfected with small interfering RNA (siRNA) that specially targeting LINC00483 to assess the impact of its knockdown. Cell proliferation was assessed using the Cell Counting Kit-8 and clone forming assays. Cell migration and cell invasion were evaluated using a transwell assay. The levels of Snail, E-cadherin, N-cadherin and ETS1 proteins were determined via western blotting. The interaction between LINC00483 and miR-204-3p was analyzed using dual-luciferase, fluorescence in situ hybridization and RNA immunoprecipitation.

RESULTS

LINC00483 was upregulated in LUAD tissues and cell lines. Higher LINC00483 levels closely correlated to shorter survival times, advanced TNM stage, larger tumor size and positive lymph node metastasis. Cell proliferation, migration and invasion were suppressed after LINC00483 knockdown. LINC00483 mainly localized in the cytoplasm, where it acted as a sponge of miR-204-3p. ETS1 was validated as a downstream target of miR-204-3p and is thus regulated by LINC00483.

CONCLUSION

This study demonstrated that LINC00483 facilitates the proliferation, migration and invasion of LUAD cells by acting as a sponge for miR-204-3p, which in turn regulates ETS1.

LncRNA SNHG4 promotes the proliferation, migration, invasiveness, and epithelial–mesenchymal transition of lung cancer cells by regulating miR-98-5p

Long noncoding RNA small nucleolar RNA host gene 4 (SNHG4) is usually up-regulated in cancer and regulates the malignant behavior of cancer cells. However, its role in lung cancer remains elusive. In this study, we silenced the expression of SNHG4 in NCI-H1437 and SK-MES-1, two representative non-small-cell lung cancer cell lines, by transfecting them with siRNA (small interfering RNA) that specifically targets SNHG4. We observed significantly inhibited cell proliferation in vitro and reduced tumor growth in vivo after SNHG4 silencing. SNHG4 knockdown also led to cell cycle arrest at the G1 phase, accompanied with down-regulation of cyclin-dependent kinases CDK4 and CDK6. The migration and invasiveness of these two cell lines were remarkably inhibited after SNHG4 silencing. Moreover, our study revealed that the epithelial–mesenchymal transition (EMT) of lung cancer cells was suppressed by SNHG4 silencing, as evidenced by up-regulated E-cadherin and down-regulated SALL4, Twist, and vimentin. In addition, we found that SNHG4 silencing induced up-regulation of miR-98-5p. MiR-98-5p inhibition abrogated the effect of SNHG4 silencing on proliferation and invasion of lung cancer cells. In conclusion, our findings demonstrate that SNHG4 is required by lung cancer cells to maintain malignant phenotype. SNHG4 probably exerts its pro-survival and pro-metastatic effects by sponging anti-tumor miR-98-5p.

Chrysophanol exhibits anti-cancer activities in lung cancer cell through regulating ROS/HIF-1a/VEGF signaling pathway

In the present study, we explored the anti-tumor and anti-angiogenesis effects of chrysophanol, and to investigate the underlying mechanism of the chrysophanol on anti-tumor and anti-angiogenesis in human lung cancer. The viability of cells was measured by CCK-8 assay, cell apoptosis was measured by Annexin-FITC/PI staining assay, and the cell migration and invasion were analyzed by wound-healing assay and transwell assay. ROS generation and mitochondrial membrane potential were analyzed by DCFH-DA probe and mitochondrial staining kit. Angiogenesis was analyzed by tube formation assay. The expression of CD31 was analyzed by immunofluorescence. The levels of proteins were measured by western blot assay. The anti-tumor effects of chrysophanol in vivo were detected by established xenograft mice model. In this study, we found that the cell proliferation, migration, invasion, tube formation, the mitochondrial membrane potential, and the expression of CD31 were inhibited by chrysophanol in a dose-dependent manner, but cell apoptotic ratios and ROS levels were increased by chrysophanol in a dose-dependent manner. Furthermore, the effects of chrysophanol on A549, H738, and HUVEC cell apoptotic rates were reversed by the ROS inhibitor NAC. Besides, the effects of chrysophanol on HUVEC cell tube formation were reversed by the HIF-1α inhibitor KC7F2 and the VEGF inhibitor axitinib in vitro. Moreover, tumor growth was reduced by chrysophanol, and the expression of CD31, CD34, and angiogenin was suppressed by chrysophanol in vivo. Our finding demonstrated that chrysophanol is a highly effective and low-toxic drug for inhibition of tumor growth especially in high vascularized lung cancer.

Is routine baseline brain imaging needed for all newly diagnosed non-small-cell lung cancer patients?

Aim: Dedicated brain imaging is advocated by the National Comprehensive Cancer Network guidelines for newly diagnosed non-small-cell cancer (NSCLC) patients beyond stage I. The current study assessed the performance characteristics of this recommendation. Methods: Through accessing the Surveillance, Epidemiology and End Points (SEER) registry (2010-2015), all patients (regardless of stage) with newly diagnosed NSCLC and complete information about TN stages and presence or absence of brain metastases were extracted. In the current study, the following performance characteristics of the above recommendation were assessed: sensitivity, specificity, positive predictive value (PPV), negative predictive value (NPV), number needed to investigate (NNI) and accuracy. Results: A total of 182,977 NSCLC patients were included. For the overall cohort, PPV (for the recognition of brain metastases) was 13.8% and NNI to detect one case of brain metastasis was 7.2. Likewise, NPV (for the exclusion of brain metastases) was 97%, sensitivity was 92.1%, specificity was 31.1% and overall accuracy was 37.6%. When stratified by histology, patients with adenocarcinoma have PPV of 17.2% and NNI to detect one case with brain metastasis of 5.8. NPV (for the exclusion of brain metastases) was 97%, sensitivity of 91.4%, specificity of 35.4% and overall accuracy of 32.6%. On the other hand, patients with squamous cell carcinoma have PPV of 6.3% and NNI to detect one case with brain metastasis of 15.8. NPV (for the exclusion of brain metastases) was 98.9%, sensitivity of 94.6%, specificity of 26.3% and overall accuracy of 29.7%. Conclusion: In view of the poor specificity, the current study calls for reconsideration of the universal recommendation of dedicated brain imaging (in addition to PET/CT scan) among NSCLC patients beyond stage I.

MiR-889 promotes cell growth in human non-small cell lung cancer by regulating KLF9

Currently, non-small cell lung cancer (NSCLC) is still the most common malignancy worldwide. Although miR-889 has been reported to play an important role in various malignancies, the physiological function of miR-889 in NSCLC remains unknown. This paper places emphasis on the influence of miR-889 on the development and progression of non-small cell lung cancer. To detect the expression level of miR-889 in NSCLC tissues and cell lines, quantitative real-time polymerase chain reaction (qRT-PCR) assay and In Situ Hybridization (ISH) were adopted in this study. Cell proliferation and colony forming ability were examined by Cell Counting Kit-8 (CCK-8) and colony formation assays. Furthermore, transwell experiments were conducted to determine the influence of miR-889 on migration. KLF9 expression was evaluated by qRT-PCR and Western blotting. First, miR-889 expression was increased in the cancer tissues of non-small cell lung cancer patients (n = 40) compared with adjacent tissues. Subsequently, knockdown of miR-889 significantly inhibited cell proliferation and migration, while overexpression of miR-889 had the opposite effect. KLF9 may be a potential target of miR-889. In addition, upregulation of miR-889 promotes tumorigenesis in vitro, and KLF9 protein levels are also reduced. The current study suggests that miR-889 may play a potential therapeutic role for NSCLC by targeting KLF9 to control NSCLC proliferation and migration.

Baicalein Inhibits Orthotopic Human Non-Small Cell Lung Cancer Xenografts via Src/Id1 Pathway

Non-small cell lung cancer (NSCLC) is one of the most lethal cancers worldwide. Inhibitor of differentiation 1 (Id1) is the member mostly linked to tumorigenesis in Id family and a potential molecular target in cancer therapy. In the current study, we established an orthotopic lung cancer model by injecting athymic nude mice with A549 cells and evaluated the antitumor effect of baicalein and expression of Id1-related proteins in vivo and in vitro. Micro-CT images showed that tumor volume in baicalein group was significantly reduced. Western blot analysis revealed that baicalein suppressed the expression of Id1 protein, epithelial-to-mesenchymal transition (EMT) related molecules (N-Cadherin, vimentin), and angiogenesis related protein (VEGF-A), accompanied by upregulation of epithelial markers (such as E-cadherin). In addition, phosphorylation of upstream molecular Src was significantly restrained after baicalein treatment. This study firstly demonstrates that baicalein inhibits tumor growth in orthotopic human NSCLC xenografts via targeting Src/Id1 pathway.

Withaferin A inhibits Epithelial to Mesenchymal Transition in Non-Small Cell Lung Cancer Cells

Lung cancer is the leading cause of cancer-related deaths worldwide and in the United States. Despite recent advancements in treatment approaches, metastasis remains a major therapeutic challenge in lung cancer and explains the extremely poor prognosis. Epithelial to mesenchymal transition (EMT), a complex process of cellular reprogramming has become an attractive drug target because it plays a crucial role in the metastasis of non-small cell lung cancer (NSCLC). In the present study, we examined the effects of withaferin A (WFA), a plant-derived steroidal lactone on EMT in human NSCLC cell lines. First, we demonstrated that WFA displayed time- and concentration-dependent cytotoxicity on A549 and H1299 NSCLC cells. Then, cells were exposed to ≤ 0.5 µM WFA for ≤ 4 h to minimize cytotoxicity and determined its effects on EMT, cell adhesion, motility, migration, and invasion. EMT induction was performed by culturing cells in serum-free media containing TGFβ1 (5 ng/mL) and TNFα (25 ng/mL) for 48 h. We observed that pretreatment of cells with WFA inhibited cell adhesion, migration, and invasion of A549 and H1299 cells. Using western blot, immunofluorescence, and qRT-PCR analysis, we demonstrated that WFA suppressed TGFβ1 and TNFα-induced EMT in both cell lines. Mechanistically, WFA suppressed the phosphorylation and nuclear translocation of Smad2/3 and NF-κB in A549 and H1299 cells. Together, our study provides additional evidence demonstrating the inhibitory effects of WFA on EMT induction in NSCLC cells and further demonstrates the therapeutic potential of WFA against the metastasis in NSCLC.

Oncostatin M suppresses metastasis of lung adenocarcinoma by inhibiting SLUG expression through coordination of STATs and PIASs signalings

Oncostatin M (OSM) is linked with multiple biological responses including growth and differentiation. Previous reports showed inhibitory effects of OSM in tumor progression while others showed promoting effects. The dual role of OSM in the development of various cancers is still unclear. We previously described OSM-mediated SLUG suppression, leading to repressed metastasis of lung adenocarcinoma (LAC) cells. However, the underlying mechanism remains elusive. Here, we showed that OSM suppresses SLUG express in LAC cells through a STAT1-dependent transcriptional inhibition. Knockdown of STAT1 reversed the OSM-suppressed SLUG expression and rescued the OSM-mediated inhibition of cell proliferation, migration, and invasion in vitro, as well as pulmonary metastasis in vivo. STAT1 suppressed SLUG transcription through binding to its promoter region in response to OSM. Furthermore, PIAS4, a co-repressor of STAT, and HDAC1 were able to bind to STAT1 on SLUG promoter region, resulting in reduced H3K9 acetylation and suppressed SLUG expression upon OSM treatment. In contrast, PIAS3 bound to activated STAT3, another effector of OSM, in response to OSM and blocked the binding of STAT3 to SLUG promoter region, preventing STAT3-dependent activation of SLUG transcription. Our findings suggested that OSM suppresses SLUG expression and tumor metastasis of LAC through inducing the inhibitory effect of the STAT1-dependent pathway and suppressing the activating effect of STAT3-dependent signaling. These results can serve as a scientific basis for the potential therapeutic intervention of OSM in cancer cells.