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Objectives: Pulmonary carcinosarcoma (PCS) is a rare neoplasm. This study explored the clinicopathological characteristics and survival outcomes of PCS., Methods: The Surveillance, Epidemiology and End Results (SEER) database (1988-2014) was queried for PCS. Overall survival (OS) was evaluated by multivariable Cox regression and nomograms were constructed to predict 3-year OS for PCS. Prognostic performance was evaluated using concordance index and area under the curve analysis. In M0 surgically treated patients, interaction assessments were performed using likelihood ratio tests. Subgroup analysis was performed according to patient age. The clinical features of PCSs were further compared to other non-small-cell lung cancers (NSCLCs)., Results: Multivariable analysis identified age [hazard ratio (HR) 1.03, 95% confidence interval (CI) 1.01-1.04], surgery (HR 0.53, 95% CI 0.36-0.77) and chemotherapy (HR 0.51, 95% CI 0.36-0.73) as significantly associated with OS. The nomogram had a concordance index of 0.747 and an area under the curve of 0.803. The association between age and OS was stronger in those receiving pneumonectomy (P = 0.04 for interactions) compared to those that did not (HR 5.14, 95% CI 1.64-16.07), and was associated with a poorer outcome compared to lobectomy amongst the elderly (age ≥ 70 years). Patients with PCS were more likely to receive surgical treatment and had lower lymphatic metastasis compared to adenocarcinoma, squamous cell carcinoma and large cell carcinoma (all P < 0.05)., Conclusions: PCS had unique clinical features compared to common types of NSCLCs in terms of lymphatic invasion and surgical treatment. Pneumonectomy was associated with poorer survival in elderly patients., (© The Author(s) 2019. Published by Oxford University Press on behalf of the European Association for Cardio-Thoracic Surgery. All rights reserved.)

Lung cancers are broadly classified into small cell lung cancers and non-small cell lung cancers (NSCLC). Lung adenocarcinoma (LUAD) and lung squamous cell carcinoma (LUSC) are two common subtypes of NSCLC, and despite the fact that both occur in lung tissues, these two subtypes show a number of different pathological characteristics. To investigate the differences and seek potential therapy targets, we used bioinformatics methods to analyze RNA-Seq data from different aspects. The previous studies and comparative pathway enrichment analysis on publicly available data showed that expressed or inhibited genes are different in two cancer subtypes through important pathways. Some of these genes could not only affect cell function through expression, but also could regulate other genes' expression by binding to a specific DNA sequence. This kind of genes is called transcription factor (TF) or sequence-specific DNA-binding factor. Transcription factors play important roles in controlling gene expression in carcinoma pathways. Our results revealed transcription factors that may cause differential expression of genes in cellular pathways of LUAD and LUSC, which provide new clues for study and treatment. Once such TF is NFE2l2 which may regulate genes in the Wnt signaling pathway, and the MAPK signaling pathway, thus leading to an increase the cell growth, cell division, and gene transcription. Another TF-XBP1 has high correlation with genes related to cell adhesion molecules and cytokine-cytokine receptor interaction pathways that may further affect the immune system. Moreover, the two TF and high correlated genes also show similar patterns in an independent GEO data set.

Motivation: New developments in high-throughput genomic technologies have enabled the measurement of diverse types of omics biomarkers in a cost-efficient and clinically-feasible manner. Developing computational methods and tools for analysis and translation of such genomic data into clinically-relevant information is an ongoing and active area of investigation. For example, several studies have utilized an unsupervised learning framework to cluster patients by integrating omics data. Despite such recent advances, predicting cancer prognosis using integrated omics biomarkers remains a challenge. There is also a shortage of computational tools for predicting cancer prognosis by using supervised learning methods. The current standard approach is to fit a Cox regression model by concatenating the different types of omics data in a linear manner, while penalty could be added for feature selection. A more powerful approach, however, would be to incorporate data by considering relationships among omics datatypes., Methods: Here we developed two methods: a SKI-Cox method and a wLASSO-Cox method to incorporate the association among different types of omics data. Both methods fit the Cox proportional hazards model and predict a risk score based on mRNA expression profiles. SKI-Cox borrows the information generated by these additional types of omics data to guide variable selection, while wLASSO-Cox incorporates this information as a penalty factor during model fitting., Results: We show that SKI-Cox and wLASSO-Cox models select more true variables than a LASSO-Cox model in simulation studies. We assess the performance of SKI-Cox and wLASSO-Cox using TCGA glioblastoma multiforme and lung adenocarcinoma data. In each case, mRNA expression, methylation, and copy number variation data are integrated to predict the overall survival time of cancer patients. Our methods achieve better performance in predicting patients' survival in glioblastoma and lung adenocarcinoma., (Copyright © 2017. Published by Elsevier Inc.)

Epigenetic regulation plays an important role in tumor metastasis. KDM1A is a histone demethylase specific for H3K4me2/me1 demethylation, and has been found to be overexpressed in many cancers, including non-small cell lung cancer (NSCLC). However, the role of KDM1A in lung cancer remains unclear. Here, we show that KDM1A promotes cancer metastasis in NSCLC cells by repressing TIMP3 (tissue inhibitor of metalloproteinase 3) expression. Consistently with this, overexpression of TIMP3 inhibited MMP2 expression and JNK phosphorylation, both of which are known to be important for cell invasion and migration. Importantly, knockdown of TIMP3 in KDM1A-deficient cells rescued the metastatic capability of NSCLC cells. These findings were also confirmed by pharmacological inhibition assays. We further demonstrate that KDM1A removes H3K4me2 at the promoter of TIMP3, thus repressing the transcription of TIMP3. Finally, high expression of KDM1A and low expression of TIMP3 significantly correlate with a poor prognosis in NSCLC patients. This study establishes a mechanism by which KDM1A promotes cancer metastasis in NSCLC cells, and we suggest that KDM1A may be a potential therapeutic target for NSCLC treatment., Competing Interests: The authors declare no potential conflicts of interest.

LKB1 regulates both cell growth and energy metabolism. It remains unclear how LKB1 inactivation coordinates tumor progression with metabolic adaptation in non-small cell lung cancer (NSCLC). Here in Kras(G12D);Lkb1(lox/lox) (KL) mouse model, we reveal differential reactive oxygen species (ROS) levels in lung adenocarcinoma (ADC) and squamous cell carcinoma (SCC). ROS can modulate ADC-to-SCC transdifferentiation (AST). Further, pentose phosphate pathway deregulation and impaired fatty acid oxidation collectively contribute to the redox imbalance and functionally affect AST. Similar tumor and redox heterogeneity also exist in human NSCLC with LKB1 inactivation. In preclinical trials toward metabolic stress, certain KL ADC can develop drug resistance through squamous transdifferentiation. This study uncovers critical redox control of tumor plasticity that may affect therapeutic response in NSCLC., (Copyright © 2015 Elsevier Inc. All rights reserved.)

Whether the Hippo pathway contributes to cell lineage transition under pathological conditions, especially tumorigenesis, remains largely unknown. Here we show that YAP, the major effector of the Hippo pathway, displays a distinct activation pattern in lung adenocarcinoma (ADC) and squamous cell carcinoma (SCC); YAP is initially activated by LKB1 loss in lung ADC, which upregulates ZEB2 expression and represses DNp63 transcription in a default manner. During transdifferentiation, YAP is inactivated, which in turn relieves ZEB2-mediated default repression of DNp63 and triggers squamous differentiation reprogramming. Disruption of the YAP barrier for phenotypic transition significantly accelerates squamous transdifferentiation, whereas constitutive YAP activation conversely inhibits this transition. More importantly, ectopic DNp63 expression rescues the inhibitory effect of YAP on squamous transdifferentiation. These findings have established YAP as an essential barrier for lung cancer cell fate conversion and provided a mechanism for regulating cancer plasticity, which might hold important implication for YAP-targeted therapies.

Metastasis is the major cause for high mortality of lung cancer with the underlying mechanisms poorly understood. The scaffolding protein neural precursor cell expressed, developmentally down-regulated 9 (NEDD9) has been identified as a pro-metastasis gene in several types of cancers including melanoma and breast cancer. However, the exact role and related mechanism of NEDD9 in regulating lung cancer metastasis still remain largely unknown. Here, we demonstrate that NEDD9 knockdown significantly inhibits migration, invasion and metastasis of lung cancer cells in vitro and in vivo. The pro-metastasis role of Nedd9 in lung cancer is further supported by studies in mice models of spontaneous cancer metastasis. Moreover, we find that NEDD9 promotes lung cancer cell migration and invasion through the induction of epithelial-mesenchymal transition (EMT) potentially via focal adhesion kinase activation. More importantly, NEDD9 expression inversely correlates with E-cadherin expression in human lung cancer specimens, consistent with the findings from in vitro studies. Taken together, this study highlights that NEDD9 is an important mediator promotes lung cancer metastasis via EMT., (© 2013 UICC.)