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Abstract Background Cancer stem cells (CSCs) are a specific subpopulation of cancer cells with the ability of self‐renewal, infinite proliferation, multidifferentiation and tumorigenicity, and play critical roles in cancer progression and treatment resistance. CSCs are tightly regulated by the tumor microenvironment, such as hypoxia; however, how hypoxia regulates CSCs in non‐small cell lung cancer (NSCLC) remains unclear. Methods The proportion of ALDHhi cells was examined using the Aldefluor assay. Tankyrase inhibitor XAV939 and siRNA were used to inhibit β‐catenin while pcDNA3‐β‐catenin (S33Y) plasmid enhanced the expression of β‐catenin. Western blot was administered for protein detection. The mRNA expression was measured by quantitative real‐time PCR. Results We found that hypoxia led to an increase in the proportion of ALDHhi cells in lung squamous carcinoma (LUSC) H520 cells, while causing a decrease in the ALDHhi cell proportion in lung adenocarcinoma (LUAD) A549 cells. Similarly, β‐catenin expression was upregulated in H520 cells but downregulated in A549 cells upon exposure to hypoxia. Mechanically, the proportion of ALDHhi cells in both cell lines was decreased by β‐catenin inhibitor or siRNA knockdown, whereas increased after β‐catenin overexpression. Furthermore, hypoxia treatment suppressed E‐cadherin expression in H520 cells and enhanced N‐cadherin and β‐catenin expression, while this effect was completely opposite in A549 cells. Conclusion The hypoxia‐EMT‐β‐catenin axis functions as an important regulator for the proportion of CSCs in NSCLC and could potentially be explored as therapeutic targets in the future.

Objective To explore the mechanism and effects of Basonuclin 1(BNC1) on the migration and invasion abilities of lung squamous cell carcinoma. Methods Bioinformatics technology was used to analyze the expression patterns and survival impact of BNC1 in patients with lung squamous cell carcinoma in online databases; Tissue microarrays were stained by immunohistochemistry assay and analyzed for BNC1 protein level. Cell lines for lung squamous cell carcinoma with high and low BNC1 expression were screened in the Cancer Cell Line Encyclopedia (CCLE) database. Wound healing experiment and transwell assay were performed on lung squamous cell carcinoma cell models with knockdown and overexpression of BNC1, and the migration and invasion rates of each cell line were detected; Quantitative reverse transcription PCR(RT-qPCR) was used to validate the migration and invasion of 10 highly related genes derived from literature. Western blotting was used to validate the selected regulatory genes. Results Bioinformatics technology found that BNC1 was highly expressed in lung squamous cell carcinoma tissues and was associated with lower survival rate(P=0.047). The expression of BNC1 in lung squamous cell carcinoma was higher than that in paracancerous tissues (P < 0.05). BNC1 had higher expression in the H226 cells and lower expression in the SK-MES1 cells. BNC1 knockdown inhibited the migration and invasion abilities of lung squamous cell carcinoma cells(P < 0.05), and BNC1 overexpression enhanced the migration and invasion abilities of lung squamous cell carcinoma cells(P < 0.05). Screening of BNC1 downstream regulatory molecules at the mRNA level showed that CDH1 was decreased when BNC1 was overexpressed (P < 0.05), and increased when BNC1 was knocked down (P < 0.05). The results of mRNA level were consistent with the results verified by Western blotting (P < 0.05). Conclusion BNC1 may be a gene predicting poor prognosis for lung squamous cell carcinoma patients, and BNC1 may likely to promote cell migration and invasion of lung squamous cell carcinoma by downregulating CDH1 expression.

Background The purpose of our study was to construct a prognostic model based on ferroptosis-related gene signature to improve the prognosis prediction of lung squamous carcinoma (LUSC).

Abstract Background Inflammation is known to have an intricate relationship with tumorigenesis and tumor progression while it is also closely related to tumor immune microenvironment. Whereas the role of inflammation‐related genes (IRGs) in lung squamous carcinoma (LUSC) is barely understood. Herein, we recognized IRGs associated with overall survival (OS), built an IRGs signature for risk stratification and explored the impact of IRGs on immune infiltration landscape of LUSC patients. Methods The RNA‐sequencing and clinicopathological data of LUSC patients were downloaded from The Cancer Genome Atlas (TCGA) and the Gene Expression Omnibus (GEO) database, which were defined as training and validation cohorts. Cox regression and least absolute shrinkage and selection operator analyses were performed to build an IRG signature. CIBERSORT, microenvironment cell populations‐counter and tumor immune dysfunction and rejection (TIDE) algorithm were used to perform immune infiltration analysis. Results A two‐IRG signature consisting of KLF6 and SGMS2 was identified according to the training set, which could categorize patients into two different risk groups with distinct OS. Patients in the low‐risk group had more anti‐tumor immune cells infiltrated while patient with high‐risk had lower TIDE score and higher levels of immune checkpoint molecules expressed. The IRG signature was further identified as an independent prognostic factor of OS. Subsequently, a prognostic nomogram including IRG signature, age, and cancer stage was constructed for predicting individualized OS, whose concordance index values were 0.610 (95% CI: 0.568–0.651) in the training set and 0.652 (95% CI: 0.580–0.724) in validation set. Time‐dependent receiver operator characteristic curves revealed that the nomogram had higher prediction accuracy compared with the traditional tumor stage alone. Conclusion The IRG signature was a predictor for patients with LUSC and might serve as a potential indicator of the efficacy of immunotherapy. The nomogram based on the IRG signature showed a relatively good predictive performance in survival.

Abstract Background Immunoglobulin G4 (IgG4)-related disease (IgG4-RD) is a systemic disease that involves the infiltration of IgG4-positive plasma cells in multiple organs. Kimura disease (KD) presents as subcutaneous masses on the head and neck, frequently accompanied by eosinophilia and high immunoglobulin E (IgE) levels. Here, we report a rare case of concurrence of IgG4-RD and KD with manifestations of asthma, pulmonary embolism, and central diabetes insipidus accompanied by lung carcinoma. Case presentation A 65-year-old Chinese male with an eight-year history of KD was admitted to our hospital with complaints of dyspnea and expectoration for one month. Laboratory examination showed a considerable elevation in the serum eosinophil count and total IgE and IgG4 levels. Chest enhanced computed tomography showed filling defects in the right pulmonary artery and a nodule in the left inferior lobe. Pancreatic enhanced magnetic resonance imaging (MRI) and magnetic resonance cholangiopancreatography showed a swollen pancreatic tail and local stricture of the pancreatic duct section of the common bile duct. Enhanced MRI of the pituitary gland showed thickening of the pituitary stalk. Additionally, immunohistochemistry of the specimens collected eight years prior revealed IgG4-positive cells. Following the diagnosis of IgG4-RD with KD, glucocorticoids with immunosuppressants were initiated; there was a prompt improvement in the patient’s condition. One-year post-discharge, the patient underwent wedge-shaped resection of the lung due to enlargement of the pulmonary nodule, and the pathology revealed lung squamous carcinoma. Conclusions This case presents a rare clinical condition in which the concurrence of IgG4-RD and KD causes various rare manifestations including asthma, pulmonary embolism, central diabetes insipidus, and complicated lung carcinoma. This highlights the importance of monitoring for malignancies in IgG4-RD patients during follow-up.

ObjectiveTo investigate the impact that TTN mutation had on the gene heterogeneity expression and prognosis in patients with lung adenocarcinoma.MethodsIn this study, the Cancer Genome Atlas (TCGA) dataset was used to analyze the TTN mutations in lung adenocarcinoma. Lung adenocarcinoma data was collected from the TCGA database, clinical information of patients was analyzed, and bioinformatics statistical methods were applied for mutation analysis and prognosis survival analysis. The results were verified using the GEO dataset.ResultsThe incidence of TTN mutations in lung adenocarcinoma was found to be 73%, and it was related to the prognosis of lung adenocarcinoma. Ten genes were screened with significant contributions to prognosis. A prognosis model was constructed and verified by LASSO COX analysis in the TCGA and GEO datasets based on these ten beneficial factors. The independent prognostic factor H2BC9 for TTN mutation-driven gene heterogeneity expression was screened through multi-factor COX regression analysis.ConclusionOur data showed that the gene heterogeneity expression, which was driven by TTN mutations, prolonged the survival of lung adenocarcinoma patients and provided valuable clues for the prognosis of TTN gene mutations in lung adenocarcinoma.

Lung squamous carcinoma (LUSC) is a malignant tumor of the respiratory system with highly heterogeneous characteristics. Lactate is the main product of aerobic glycolysis during the metabolic reprogramming of tumors. There is growing evidence that lactate metabolic processes have a broad and sophisticated impact on tumor phenotypic plasticity and tumor microenvironment (TME). However, the pattern of lactate metabolism in patients with LUSC and its impact on TME, phenotype, prognosis, and treatment have not been fully elucidated. In this study, we identified two subtypes with different lactate metabolism patterns in LUSC by non-negative matrix factorization and explored their multi-omics features. We observed that lactate metabolism levels in LUSC extensively influenced tumor immune infiltration patterns, adaptation to the hypoxia environment, and energy metabolic reprogramming. Subsequently, we constructed the lactate metabolism-related prognostic index (LMRPI) using Cox stepwise regression analysis. LMRPI showed excellent stability and accuracy, and based on the median value of LMRPI, LUAD were divided into two subgroups. The two subgroups have different patterns of immune infiltration and somatic mutations. Meanwhile, the two subgroups had different responsiveness to immune checkpoint inhibitor (ICI) therapies and different sensitivity to various chemotherapeutic and molecular targeting agents. In conclusion, we defined two subtypes with different lactate metabolism patterns in LUSC and extensively characterized their multi-omics profile. Furthermore, we developed LMRPI that predicts the prognosis of LUSC patients while also predicting their response to various adjuvant therapies, including immunotherapy, to guide their individualized treatment.

Abstract Cr(VI) is broadly applied in industry. Cr(VI) exposure places a big burden on public health, thereby increasing the risk of lung squamous cell carcinoma (LUSC). The mechanisms underlying Cr(VI)‐induced LUSC remain largely elusive. Here, we report that the cancer stem cell (CSC)/tumour‐initiating cell (TIC)‐like subgroup within Cr(VI)‐transformed bronchial epithelial cells (CrT) promotes lung cancer tumourigenesis. Mechanistically, Cr(VI) exposure specifically increases the expression levels of aldehyde dehydrogenase 1A1 (ALDH1A1), a CSC marker, through KLF4‐mediated transcription. ALDH1A1 maintains self‐renewal of CrT/TICs and facilitates the expression and secretion of EGF from CrT/TICs, which subsequently promotes the activation of EGFR signalling in differentiated cancer cells and tumour growth of LUSC. In addition, the ALDH1A1 inhibitor A37 and gemcitabine synergistically suppress LUSC progression. Importantly, high ALDH1A1 expression levels are positively correlated with advanced clinical stages and predict poor survival in LUSC patients. These findings elucidate how ALDH1A1 modulates EGF secretion from TICs to facilitate LUSC tumourigenesis, highlighting new therapeutic strategies for malignant lung cancers.

There is still no ideal predictive biomarker for immunotherapy response among patients with non-small cell lung cancer. Costimulatory molecules play a role in anti-tumor immune response. Hence, they can be a potential biomarker for immunotherapy response. The current study comprehensively investigated the expression of costimulatory molecules in lung squamous carcinoma (LUSC) and identified diagnostic biomarkers for immunotherapy response. The costimulatory molecule gene expression profiles of 627 patients were obtained from the The Cancer Genome Atlas, GSE73403, and GSE37745 datasets. Patients were divided into different clusters using the k-means clustering method and were further classified into two discrepant tumor microenvironment (TIME) subclasses (hot and cold tumors) according to the immune score of the ESTIMATE algorithm. A high proportion of activated immune cells, including activated memory CD4 T cells, CD8 T cells, and M1 macrophages. Five CMGs (FAS, TNFRSF14, TNFRSF17, TNFRSF1B, and TNFSF13B) were considered as diagnostic markers using the Least Absolute Shrinkage and Selection Operator and the Support Vector Machine-Recursive Feature Elimination machine learning algorithms. Based on the five CMGs, a diagnostic nomogram for predicting individual tumor immune microenvironment subclasses in the TCGA dataset was developed, and its predictive performance was validated using GSE73403 and GSE37745 datasets. The predictive accuracy of the diagnostic nomogram was satisfactory in all three datasets. Therefore, it can be used to identify patients who may benefit more from immunotherapy.

BackgroundAt present, immunotherapy is a very promising treatment method for lung cancer patients, while the factors affecting response are still controversial. It is crucial to predict the efficacy of lung squamous carcinoma patients who received immunotherapy.MethodsIn our retrospective study, we enrolled lung squamous carcinoma patients who received immunotherapy at Beijing Chest Hospital from January 2017 to November 2021. All patients were grouped into two cohorts randomly, the training cohort (80% of the total) and the test cohort (20% of the total). The training cohort was used to build neural network models to assess the efficacy and outcome of immunotherapy in lung squamous carcinoma based on clinical information. The main outcome was the disease control rate (DCR), and then the secondary outcomes were objective response rate (ORR), progression-free survival (PFS), and overall survival (OS).ResultsA total of 289 patients were included in this study. The DCR model had area under the receiver operating characteristic curve (AUC) value of 0.9526 (95%CI, 0.9088–0.9879) in internal validation and 0.9491 (95%CI, 0.8704–1.0000) in external validation. The ORR model had AUC of 0.8030 (95%CI, 0.7437–0.8545) in internal validation and 0.7040 (95%CI, 0.5457–0.8379) in external validation. The PFS model had AUC of 0.8531 (95%CI, 0.8024–0.8975) in internal validation and 0.7602 (95%CI, 0.6236–0.8733) in external validation. The OS model had AUC of 0.8006 (95%CI, 0.7995–0.8017) in internal validation and 0.7382 (95%CI, 0.7366–0.7398) in external validation.ConclusionsThe neural network models show benefits in the efficacy evaluation of immunotherapy to lung squamous carcinoma patients, especially the DCR and ORR models. In our retrospective study, we found that neoadjuvant and adjuvant immunotherapy may bring greater efficacy benefits to patients.

Abstract Background Clinical options for lung squamous carcinoma (LUSC) are still quite limited. Carcinogenesis is an exceedingly complicated process involving multi-level dysregulations. Therefore, only looking into one layer of genomic dysregulation is far from sufficient. Methods We identified differentially expressed genes with consistent upstream genetic or epigenetic dysregulations in LUSC. Random walk was adopted to identify genes significantly affected by upstream abnormalities. Expression differentiation and survival analysis were conducted for these significant genes, respectively. Prognostic power of selected gene was also tested in 102 male LUSC samples through immunohistochemistry assay. Results Twelve genes were successfully retrieved from biological network, including ERα (ESRS1), EGFR, AR, ATXN1, MAPK3, PRKACA, PRKCA, SMAD4, TP53, TRAF2, UBQLN4 and YWHAG, which were closely related to sex hormone signaling pathway. Survival analysis in public datasets indicated ERα was significantly associated with a poor overall survival (OS) in male LUSC. The result of our immunohistochemistry assay also demonstrated this correlation using R0 resected tumors (n = 102, HR: 2.152, 95% CI: 1.089–4.255, p = 0.024). Although disease-free survival (DFS) difference was non-significant (n = 102, p = 0.12), the tendency of distinction was straight-forward. Cox analysis indicated ERα was the only independent prognostic factor for male patients’ OS after R0 resection (HR = 2.152, p = 0.037). Conclusion ERα was significantly related to a poor prognosis in LUSC, especially for male patients after radical surgery, confirmed by our immunohistochemistry data.

Abstract The development of targeted therapies that inhibit cancer-driving oncogenes has improved outcomes of patients diagnosed with lung adenocarcinoma (LUAD). In contrast, patients diagnosed with lung squamous cell carcinoma (LUSC) suffer worse survival outcomes and lack effective targeted treatment options. Identification of molecular drivers of LUSC to support development of targeted treatments is urgently needed. Addressing this need, the current report introduces the novel cancer gene SLIT- and NTRK-like family member 3 (SLITRK3) and its role in activating the neurotrophic receptor tyrosine kinase 3 (NTRK3) in LUSC cells. Multiple genome-wide data sets from patient samples were produced by us or downloaded from public databases to analyze tumor gene copy number aberrations, mRNA expression and associated survival outcomes. An accompanying mechanistic study employed LUSC cell lines and multiple methods, including in situ immunofluorescence, sphere-formation assay, and fluorescence-activated cell sorting analysis of the CD133-positive cell fraction. Altogether, the results indicate that gene amplification and consequent high expression of SLITRK3 in LUSC is associated with worse outcomes and induces SLITRK3-dependent activation of NTRK3 to promote a cancer stem cell phenotype that is inhibited by existing NTRK-targeted inhibitors. Based on a recent literature search, this is the first report of a mechanistic role for SLITRK3 in cancer.

Cancer immunotherapy is an increasingly successful strategy for treating patients with advanced or conventionally drug-resistant cancers. T cells have been proved to play important roles in anti-tumor and tumor microenvironment shaping, while these roles have not been explained in lung squamous cell carcinoma (LUSC). In this study, we first performed a comprehensive analysis of single-cell RNA sequencing (scRNA-seq) data from the gene expression omnibus (GEO) database to identify 72 T-cell marker genes. Subsequently, we constructed a 5-gene prognostic signature in the training cohort based on the T-cell marker genes from the cancer genome atlas (TCGA) database, which was further validated in the testing cohort and GEO cohort. The areas under the receiver operating characteristic curve at 1-, 3-, and 5-years were 0.614, 0.713 and 0.702 in the training cohort, 0.669, 0.603 and 0.645 in the testing cohort, 0.661, 0.628 and 0.590 in the GEO cohort, respectively. Furthermore, we created a highly reliable nomogram to facilitate clinical application. Gene set enrichment analysis showed that immune-related pathways were mainly enriched in the high-risk group. Tumor immune microenvironment indicated that high-risk group exhibited higher immune score, stromal score, and immune cell infiltration levels. Moreover, genes of the immune checkpoints and human leukocyte antigen family were all overexpressed in high-risk group. Drug sensitivity revealed that low-risk group was sensitive to 8 chemotherapeutic drugs and high-risk group to 4 chemotherapeutic drugs. In short, our study reveals a novel prognostic signature based on T-cell marker genes, which provides a new target and theoretical support for LUSC patients.

BackgroundNon-small cell lung cancer (NSCLC) is a malignant tumor with high mortality. Lung squamous carcinoma (LUSC) and lung adenocarcinoma (LUAD) are the common subtypes of NSCLC. However, how LUSC and LUAD are compatible remains to be elucidated.MethodsWe used a network approach to find highly interconnected genes shared with LUSC and LUAD, and we then built modules to assess the degree of preservation between them. To quantify this result, Z-scores were used to summarize the interrelationships between LUSC and LUAD. Furthermore, we correlated network hub genes with patient survival time to identify risk factors.ResultsOur findings provided a look at the regulatory pattern for LUSC and LUAD. For LUSC, several genes, such as AKR1C1, AKR1C2, and AKR1C3, play key roles in regulating network modules of cell growth pathways. In addition, CCL19, CCR7, CCL21, and LY9 are enriched in LUAD network modules of T lymphocyte-related pathways. LUSC and LUAD have similar expressed gene expression patterns. Their networks share 46 hub genes with connectivity greater than 0.9. These genes are correlated with patient survival time. Among them, the expression level of COL5A2 in LUSC and LUAD is higher than that in normal tissues, which is closely related to the poor prognosis of LUSC and LUAD patients.ConclusionLUSC and LUAD share a network pattern. COL5A2 may be a risk factor in poor prognosis in LUSC and LUAD. The common landscape of LUSC and LUAD will help better define the regulation of NSCLC candidate genes and achieve the goals of precision medicine.

Background: Globally, non-small-cell lung cancer (NSCLC) has a high incidence, and NSCLC patients have poor prognoses. Lung squamous carcinoma (LUSC) is a major pathological type of NSCLC. LncRNAs play important roles in tumor progression and immune system functions. The aim of this study was to construct a predictive model with immune-related lncRNAs and to assess the immune microenvironment in middle- or advanced-stage LUSC patients. Methods: RNA sequencing data and corresponding clinical LUSC data were downloaded from The Cancer Genome Atlas. Immune genes were obtained from the Molecular Signatures Database. Immune-related lncRNAs were identified by Pearson correlation analysis in R. The model was constructed using univariate and multivariate Cox regression analyses. Finally, we validated the prognostic immune-related lncRNA model in a cohort from the Fudan University Shanghai Cancer Center. Results: Our risk model included four immune-related lncRNAs (LINC00944, AL034550.2, AC020907.1 and AC027682.6). Survival analysis revealed that overall and disease-free survival were shorter in the high-risk group than in the low-risk group. Independent prognostic analysis showed that our model could be used as an independent prognostic predictor. The high-risk group was positively associated with CD8+ T cells, B cells, myeloid dendritic cells, macrophages, regulatory T cells (Tregs) and cancer-associated fibroblasts and high expression of PD1 and CTLA4. Additionally, a low-risk score was correlated with lower half maximal inhibitory concentrations (IC50s) of cisplatin, docetaxel, vinorelbine and paclitaxel and a higher IC50 of gemcitabine. Gene set enrichment analysis suggested that these lncRNAs may participate in tumor progression and immune processes. Validation with the clinical cancer cohort demonstrated that higher risk scores were associated with a higher, but not statistically significant, likelihood of recurrence. Conclusion: We established a risk score model including four immune-related lncRNAs. The model accurately predicts the prognosis of middle- or advanced-stage LUSC patients and provides an important reference for individualized treatment.

PurposeWith the development and application of targeted therapies like tyrosine kinase inhibitors (TKIs) and immune checkpoint inhibitors (ICIs), non-small cell lung cancer (NSCLC) patients have achieved remarkable survival benefits in recent years. However, epidermal growth factor receptor (EGFR) wild-type and low expression of programmed death-ligand 1 (PD-L1) NSCLCs remain unmanageable. Few treatments for these patients exist, and more side effects with combination therapies have been observed. We intended to generate a metabolic gene signature that could successfully identify high-risk patients and reveal its underlying molecular immunology characteristics.MethodsBy identifying the bottom 50% PD-L1 expression level as PD-L1 low expression and removing EGFR mutant samples, a total of 640 lung adenocarcinoma (LUAD) and lung squamous carcinoma (LUSC) tumor samples and 93 adjacent non-tumor samples were finally extracted from The Cancer Genome Atlas (TCGA). We identified differentially expressed metabolic genes (DEMGs) by R package limma and the prognostic genes by Univariate Cox proportional hazards regression analyses. The intersect genes between DEMGs and prognostic genes were put into the least absolute shrinkage and selection operator (LASSO) penalty Cox regression analysis. The metabolic gene signature contained 18 metabolic genes generated and successfully stratified LUAD and LUSC patients into the high-risk and low-risk groups, which was also validated by the Gene Expression Omnibus (GEO) database. Its accuracy was proved by the time-dependent Receiver Operating Characteristic (ROC) curve, Principal Components Analysis (PCA), and nomogram. Furthermore, the Single-sample Gene Set Enrichment Analysis (ssGSEA) and diverse acknowledged methods include XCELL, TIMER, QUANTISEQ, MCPcounter, EPIC, CIBERSORT-ABS, and CIBERSORT revealed its underlying antitumor immunosuppressive status. Besides, its relationship with somatic copy number alterations (SCNAs) and tumor mutational burden (TMB) was also discussed.ResultsIt is noteworthy that metabolism reprogramming is associated with the survival of the double-negative LUAD and LUSC patients. The SCNAs and TMB of critical metabolic genes can inhibit the antitumor immune process, which might be a promising therapeutic target.

ROS1 rearrangements have been identified as driver mutations, accounting for 1–2% of lung adenocarcinoma, but are extremely rare in case of lung squamous cell carcinoma. In this work, we report a lung squamous cell carcinoma in a patient with peripheral lung cancer radiological manifestation, harboring ROS1 rearrangement, with high sensitivity to crizotinib. Our findings suggest that clinicians should pay more attention toward the occurrence of ROS1 rearrangements and the application of crizotinib for lung squamous cell carcinoma treatment.

Abstract Emerging evidences demonstrate that circular RNAs (circRNAs) are abnormally expressed in tumors and could serve as prognostic markers for cancers. However, the expression patterns and clinical implications of circRNAs in non-small cell lung cancer (NSCLC) remain obscure. In this study, we profiled circRNA expressions in 10 pairs of lung adenocarcinoma (LUAD) and squamous cell carcinoma (LUSC) after ribosomal RNA-depletion and RNase R digestion to enrich circRNAs. Combining five circRNA computational programs, we found that LUAD and LUSC not only share common expression patterns, but also exhibit distinct circRNA expression signatures. Moreover, the Receiver Operating Characteristic (ROC) curve analysis indicated that hsa_circ_0077837 and hsa_circ_0001821 could serve as potential biomarkers for both LUAD and LUSC, while hsa_circ_0001073 and hsa_circ_0001495 could be diagnostic/subtyping marker for LUAD and LUSC, respectively. Therefore, our findings highlight the important diagnostic potential of circRNAs in NSCLC.

There are associations between DNA methylation and the expression of long non-coding RNA (lncRNA), also known as lncRNA expression quantitative trait methylations (lnc-eQTMs). Lnc-eQTMs may induce a wide range of carcinogenesis pathways. However, lnc-eQTMs have not been globally identified and studied, and their roles in lung adenocarcinoma (LUAD) and lung squamous carcinoma (LUSC) are largely unknown. In the present study, we identified some differential methylation sites located in genes of long intergenic non-coding RNAs (lincRNAs) and other types of lncRNAs in LUAD and LUSC. An integrated pipeline was established to construct two global cancer-specific regulatory networks of lnc-eQTMs in LUAD and LUSC. The associations between eQTMs showed common and specific features between LUAD and LUSC. Some lnc-eQTMs were also related with survival in LUAD- and LUSC-specific regulatory networks. Lnc-eQTMs were associated with cancer-related functions, such as lung epithelium development and vasculogenesis by functional analysis. Drug repurposing analysis revealed that these lnc-eQTMs may mediate the effects of some anesthesia-related drugs in LUAD and LUSC. In summary, the present study elucidates the roles of lnc-eQTMs in LUAD and LUSC, which could improve our understanding of lung cancer pathogenesis and facilitate treatment.

Abstract Background Peripheral monocyte count is an assessable parameter. Recently, evidence suggested an elevated preoperative monocyte counts predicting poor prognosis in malignancies. The aim of this study was to determine the prognostic effect of early postoperative blood monocyte count in patients with lung adenocarcinoma or squamous cell carcinoma following lobectomy. Methods We retrospectively reviewed patients with operated lung adenocarcinoma or squamous cell carcinoma from 2006 to 2011 in Western China Lung Cancer database. Univariate analysis on disease-free survival (DFS) and overall survival (OS) was performed using the Kaplan-Meier and log-rank tests, and multivariate analysis was conducted using the Cox proportional hazards regression model. Results There were 433 patients enrolled in our analysis. High postoperative elevated monocyte was associated with male gender (P

OTUD7B, a multifunctional deubiquitinylase, plays an essential role in inflammation and proliferation signals. However, its function in lung cancer remains largely unknown. The aim of this study was to evaluate the prognostic significance of OTUD7B in patients with lung adenocarcinoma and squamous carcinoma and to characterize its molecular mechanisms in lung cancer progression and metastasis. Two tissue microarrays containing 150 pairs of lung squamous carcinoma and matched adjacent non-cancer tissues, and one tissue microarray containing 75 pairs of lung adenocarcinoma and adjacent non-cancer tissues were included, and immunohistochemical staining was performed to assess the clinical relevance of OTUD7B in non-small cell lung cancer. OTUD7B is highly expressed in both lung squamous carcinoma and adenocarcinoma and correlates with a worse prognosis. MTT proliferation, colony formation, migration and invasion assays and immunoblotting assay in NCI-H358 and A549 cell lines suggested that OTUD7B enhances EGF-induced Akt signal transduction and promotes lung cancer cell proliferation and migration. Immunohistochemical staining of large-scale lung cancer subjects (171 cases) revealed positive correlation of OTUD7B and VEGF expression. ELISA and tube formation assay revealed OTUD7B promotes VEGF production and angiogenesis. NCI-H358 tumor model demonstrated OTUD7B is required for lung tumor progression by facilitating activation of Akt signaling. These findings collectively identified OTUD7B as an independent predictive factor for the prognosis of non-small cell lung cancer and revealed OTUD7B promotes lung cancer cell proliferation and metastasis via Akt/VEGF signal pathway.

Lung squamous cell carcinoma (LUSC) is often diagnosed at the advanced stage with poor prognosis. The mechanisms of its pathogenesis and prognosis require urgent elucidation. This study was performed to screen potential biomarkers related to the occurrence, development and prognosis of LUSC to reveal unknown physiological and pathological processes. Using bioinformatics analysis, the lung squamous cell carcinoma microarray datasets from the Gene Expression Omnibus (GEO) and The Cancer Genome Atlas (TCGA) databases were analyzed to identify differentially expressed genes (DEGs). Furthermore, PPI and WGCNA network analysis were integrated to identify the key genes closely related to the process of LUSC development. In addition, survival analysis was performed to achieve a prognostic model that accomplished good prediction accuracy. Three hundred and thirty–seven up–regulated and 119 down-regulated genes were identified, in which four genes have been found to play vital roles in LUSC development, namely CCNA2, AURKA, AURKB, and FEN1. The prognostic model contained 5 genes, which were all detrimental to prognosis. The AUC of the established prognostic model for predicting the survival of patients at 1, 3, and 5 years was 0.692, 0.722, and 0.651 in the test data, respectively. In conclusion, this study identified several biomarkers of significant interest for additional investigation of the therapies and methods of prognosis of lung squamous cell carcinoma.