Gene expression profiling for molecular distinction and characterization of laser captured primary lung cancers

UCHL1 is a potential molecular indicator and therapeutic target for neuroendocrine carcinomas

Neuroendocrine carcinomas, such as neuroendocrine prostate cancer and small-cell lung cancer, commonly have a poor prognosis and limited therapeutic options. We report that ubiquitin carboxy-terminal hydrolase L1 (UCHL1), a deubiquitinating enzyme, is elevated in tissues and plasma from patients with neuroendocrine carcinomas. Loss of UCHL1 decreases tumor growth and inhibits metastasis of these malignancies. UCHL1 maintains neuroendocrine differentiation and promotes cancer progression by regulating nucleoporin, POM121, and p53. UCHL1 binds, deubiquitinates, and stabilizes POM121 to regulate POM121-associated nuclear transport of E2F1 and c-MYC. Treatment with the UCHL1 inhibitor LDN-57444 slows tumor growth and metastasis across neuroendocrine carcinomas. The combination of UCHL1 inhibitors with cisplatin, the standard of care used for neuroendocrine carcinomas, significantly delays tumor growth in pre-clinical settings. Our study reveals mechanisms of UCHL1 function in regulating the progression of neuroendocrine carcinomas and identifies UCHL1 as a therapeutic target and potential molecular indicator for diagnosing and monitoring treatment responses in these malignancies.

ACAA2 is a novel molecular indicator for cancers with neuroendocrine phenotype

BACKGROUND

Neuroendocrine phenotype is commonly associated with therapy resistance and poor prognoses in small-cell neuroendocrine cancers (SCNCs), such as neuroendocrine prostate cancer (NEPC) and small-cell lung cancer (SCLC). Expression levels of current neuroendocrine markers exhibit high case-by-case variability, so multiple markers are used in combination to identify SCNCs. Here, we report that ACAA2 is elevated in SCNCs and is a potential molecular indicator for SCNCs.

METHODS

ACAA2 expressions in tumour xenografts, tissue microarrays (TMAs), and patient tissues from prostate and lung cancers were analysed via immunohistochemistry. ACAA2 mRNA levels in lung and prostate cancer (PC) patients were assessed in published datasets.

RESULTS

ACAA2 protein and mRNA levels were elevated in SCNCs relative to non-SCNCs. Medium/high ACAA2 intensity was observed in 78% of NEPC PDXs samples (N = 27) relative to 33% of adeno-CRPC (N = 86), 2% of localised PC (N = 50), and 0% of benign prostate specimens (N = 101). ACAA2 was also elevated in lung cancer patient tissues with neuroendocrine phenotype. 83% of lung carcinoid tissues (N = 12) and 90% of SCLC tissues (N = 10) exhibited medium/high intensity relative to 40% of lung adenocarcinoma (N = 15).

CONCLUSION

ACAA2 expression is elevated in aggressive SCNCs such as NEPC and SCLC, suggesting it is a potential molecular indicator for SCNCs.

Omics data analysis reveals common molecular basis of small cell lung cancer and COVID-19

The impact of COVID-19 infection on individuals with small cell lung cancer (SCLC) poses a serious threat. Unfortunately, the molecular basis of this severe comorbidity has yet to be elucidated. The present study addresses this gap utilizing publicly available omics data of COVID-19 and SCLC to explore the key molecules and associated pathways involved in the convergence of these diseases. Findings revealed 402 genes, that exhibited differential expression patterns in SCLC patients and also play a pivotal role in COVID-19 pathogenesis. Subsequent functional enrichment analyses identified relevant ontologies and pathways that are significantly associated with these genes, revealing important insights into their potential biological, molecular and cellular functions. The protein-protein interaction network, constructed under four combinatorial topological assessments, highlighted SMAD3, CAV1, PIK3R1, and FN1 as the primary components to this comorbidity. Our results suggest that these components significantly regulate this cross-talk triggering the PI3K-AKT and TGF-β signaling pathways. Lastly, this study made a multi-step computational attempt and identified corylifol A and ginkgetin from natural sources that can potentially inhibit these components. Therefore, the outcomes of this study offer novel perspectives on the common molecular mechanisms underlying SCLC and COVID-19 and present future opportunities for drug development.Communicated by Ramaswamy H. Sarma.

Bioinformatics-based screening of key genes for transformation of tyrosine kinase inhibitor-resistant lung adenocarcinoma to small cell lung cancer

Purpose

Lung adenocarcinoma (LUAD) is a common type of lung cancer. Cancer in a small number of patients with EGFR mutations will transform from LUAD to small cell lung cancer (SCLC) during epidermal growth factor receptor tyrosine kinase inhibitor (EGFR-TKI) therapiesr. The purpose of the present study was to identify the core genes related to the transformation of LUAD into SCLC and to explore the associated molecular mechanisms.

Methods

GSE29016, GSE1037, GSE6044 and GSE40275 mRNA microarray datasets from Gene Expression Omnibus (GEO) were analyzed to obtain differentially expressed genes (DEGs) between LUAD and SCLC tissues, and the results were used for network analysis of protein-protein interactions (PPIs). After identifying the hub gene by STRING and Cytoscape platform, we explored the relationship between hub genes and the occurrence and development of SCLC. Finally, the obtained hub genes were validated in treated LUAD cells.

Results

A total of 41 DEGs were obtained, four hub genes (EZH2, NUSAP1, TTK and UBE2C) were identified, and related prognostic information was obtained. The coexpressed genes of the hub gene set were further screened, and the analysis identified many genes related to the cell cycle. Subsequently, LUAD cell models with TP53 and RB1 inactivation and overexpression of ASCL1 were constructed, and then the expression of hub genes was detected, the results showed that the four hub genes were all elevated in the established cell model.

Conclusion

EZH2, NUSAP1, TTK and UBE2C may affect the transformation of LUAD to SCLC and represent new candidate molecular markers for the occurrence and development of SCLC.

Integrated bioinformatics analyses identifying key transcriptomes correlated with prognosis and immune infiltrations in lung squamous cell carcinoma

Background

Lung Squamous Cell Carcinoma (LUSC) is a major subtype of lung malignancies and is associated with the cause of cancer-mediated mortality worldwide. However, identification of transcriptomic signatures associated with survival-prognosis and immunity of tumor remains lacking.

Method

The GSE2088, GSE6044, GSE19188, GSE21933, GSE33479, GSE33532, and GSE74706 were integrated for identifying differentially expressed genes (DEGs) with combined effect sizes. Also, the TCGA LUSC cohort was used for further analysis. A series of bioinformatics methods were utilized for conducting the whole study.

Results

The 831 genes (such as DSG3, PKP1, DSC3, TPX2, and UBE2C) were found upregulated and the 731 genes (such as ABCA8, SELENBP1, FAM107A, and CACNA2D2) were downregulated in the LUSC. The functional enrichment analysis identifies the upregulated KEGG pathways, including cell cycle, DNA replication, base excision repair, proteasome, mismatch repair, and cellular senescence. Also, the key hub genes (such as EGFR, HRAS, JUN, CDH1, BRCA1, CASP3, RHOA, HDAC1, HIF1A, and CCNA2) were identified along with the eight gene modules that were significantly related to the protein-protein interaction (PPI). The clinical analyses identified that the overexpression group of CDH3, PLAU, PKP3, STIL, CALU, LOXL2, POSTN, DPP3, GALNT2, LOX, and ITPA are substantially associated with a poor survival prognosis and the downregulated group of IL18R1 showed a similar trend. Moreover, our investigation demonstrated that the survival-associated genes were correlated with the stromal and immune scores in LUSC, indicating that the survival-associated genes regulate tumor immunity. The survival-associated genes were genetically altered in 27% of LUSC patients and showed excellent diagnostic efficiency. Finally, the consistent expression level of CDH3, PLAU, PKP3, STIL, CALU, LOXL2, POSTN, DPP3, GALNT2, and ITPA were found in the TCGA LUSC cohort.

Conclusions

The identification of key transcriptomic signatures can be elucidated by the crucial mechanism of LUSC carcinogenesis.

Prognostic biomarkers and immune cell infiltration characteristics in small cell lung cancer

Background

Small cell lung cancer (SCLC) is a highly malignant and aggressive neuroendocrine tumor. With the rise of immunotherapy, it has provided a new direction for SCLC. However, due to the lack of prognostic biomarkers, the median overall survival of SCLC is still to be improved. This study aimed to explore novel biomarkers and tumor-infiltrating immune cell characteristics that may serve as potential diagnostic and prognostic markers in SCLC.

Methods

Gene expression profiles from patients with SCLC were downloaded from the Gene Expression Omnibus (GEO) database, and tumor microenvironment (TME) infiltration profile data were obtained using CIBERSORT. The robust rank aggregation (RRA) method was utilized to integrate three SCLC microarray datasets downloaded from the GEO database and identify robust differentially expressed genes (DEGs) between normal and tumor tissue samples. Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment analyses were performed to explore the functions of the robust DEGs. Subsequently, protein-protein interaction networks and key modules were constructed by Cytoscape, and hub genes were selected from the whole network using the plugin cytoHubba. Survival analysis of hub genes was performed by Kaplan-Meier plotter in 18 patients with extensive-stage SCLC.

Results

A total of 312 robust DEGs, including 55 upregulated and 257 downregulated genes, were screened from 129 SCLC tissue samples and 44 normal tissue samples. GO and KEGG enrichment analyses revealed that the robust DEGs were predominantly involved in human T-cell leukemia virus 1 infection, focal adhesion, complement and coagulation cascades, tumor necrosis factor (TNF) signaling pathway, and ECM-receptor interaction, which are closely associated with the development and progression of SCLC. Subsequently, three DEGs modules and six hub genes (ITGA10, DUSP12, PTGS2, FOS, TGFBR2, and ICAM1) were identified through screening with the Cytoscape plugins MCODE and cytoHubba, respectively. Immune cell infiltration analysis by the CIBERSORT algorithm revealed that resting memory CD4+ T cells were the predominant infiltrating immune cells in SCLC. In addition, Kaplan-Meier plotter revealed that the gene prostaglandin-endoperoxide synthase 2 (PTGS2) was a potential prognostic biomarker of SCLC.

Conclusions

Hub genes and tumor-infiltrating immune cells may be the molecular mechanisms underlying the development of SCLC, and this finding could contribute to the formulation of individualized immunotherapy strategies for SCLC.

Chemotherapy- and Immune-Related Gene Panel in Prognosis Prediction and Immune Microenvironment of SCLC

Small-cell lung cancer (SCLC) is a highly proliferative, invasive lung cancer with poor prognosis. Chemotherapy is still the standard first-line treatment for SCLC, but many patients relapse due to chemoresistance. Along with advances in immunology, it is essential to investigate potential indicators of the immune response and the prognosis of SCLC. Using bioinformatics analysis, we identified 313 differentially expressed genes (DEGs) in SCLC and normal lung samples, and we found that four upregulated genes (TOP2A, CDKN2A, BIRC5, and MSH2) were associated with platinum resistance, while immune-related genes (HLA family genes) were downregulated in SCLC. Then, a prognostic prediction model was constructed for SCLC based on those genes. Immune cell infiltration analysis showed that antigen presentation was weak in SCLC, and TOP2A expression was negatively correlated with CD8+ T cells, while HLA-ABC expression was positively correlated with M1 macrophages, memory B cells, and CD8+ T cells. We also found that TOP2A was related to poor prognosis and inversely correlated with HLA-ABC, which was verified with immunohistochemical staining in 151 SCLC specimens. Our study findings indicated that TOP2A may be a potential prognosis indicator and a target to reverse the immunosuppressive tumor microenvironment of SCLC.

Natural compound library screening identifies Sanguinarine chloride for the treatment of SCLC by upregulating CDKN1A

OBJECTIVES

Small cell lung cancer (SCLC) is notorious for aggressive malignancy without effective treatment, and most patients eventually develop tumor progression with a poor prognosis. There is an urgent need for discovering novel antitumor agents or therapeutic strategies for SCLC.

MATERIALS AND METHODS

We performed a screening method based on CCK-8 assay to screen 640 natural compounds for SCLC. The effects of Sanguinarine chloride on SCLC cell proliferation, colony formation, cell cycle, apoptosis, migration and invasion were determined. RNA-seq and bioinformatics analysis was performed to investigate the anti-SCLC mechanism of Sanguinarine chloride. Publicly available datasets and samples were analyzed to investigate the expression level of CDKN1A and its clinical significance. Loss of functional cancer cell models were constructed by shRNA-mediated silencing. Quantitative RT-PCR and Western blot were used to measure gene and protein expression. Immunohistochemistry staining was performed to detect the expression of CDKN1A, Ki67, and Cleaved caspase 3 in xenograft tissues.

RESULTS

We identified Sanguinarine chloride as a potential inhibitor of SCLC, which inhibited cell proliferation, colony formation, cell cycle, cell migration and invasion, and promoted apoptosis of SCLC cells. Sanguinarine chloride played an important role in anti-SCLC by upregulating the expression of CDKN1A. Furthermore, Sanguinarine chloride in combination with panobinostat, or THZ1, or gemcitabine, or (+)-JQ-1 increased the anti-SCLC effect compared with either agent alone treatment.

CONCLUSIONS

Our findings identified Sanguinarine chloride as a potential inhibitor of SCLC by upregulating the expression of CDKN1A. Sanguinarine chloride in combination with chemotherapy compounds exhibited strong synergism anti-SCLC properties, which could be further clinically explored for the treatment of SCLC.

Slug and Vimentin downregulation at the metastatic site is associated with Skip-N2 metastasis of lung adenocarcinoma

OBJECTIVE

Lung cancer displays heterogeneity both in the tumor itself and in its metastatic regions. One interesting behavior of the tumor is known as Skip N2 metastasis, which N2 lymph nodes contain tumor cells while N1 are clean. In this study, mRNA levels of epithelial mesenchymal transition (EMT) related genes in skip N2 and normal N2 involvements of non-small cell lung cancer tissues were investigated to evaluate the possible molecular background that may contribute to the pathogenesis of Skip N2 metastasis.

MATERIALS AND METHODS

Eighty-three surgically resected and paraffin embedded lymph node samples of lung cancer patients were analyzed in this study, which 40 of them were Skip N2. N2 tissues were sampled from 50% tumor containing areas and total RNA was extracted. mRNA levels for 18S, E-cadherin, Vimentin, ZEB1 and SLUG were analyzed via qPCR and E-cadherin and vimentin protein levels via immunohistochemistry (IHC). Bioinformatic analysis were adopted using online datasets to evaluate significantly co-expressed genes with SLUG in lung cancer tissue samples.

RESULTS

Skip-N2 patients who had adenocarcinoma subtype had better survival rates. Comparative analysis of PCR results indicated that Skip N2 tumor tissues had increased E-Cadherin/Vimentin ratio and ZEB1 mRNA expression, and significantly decreased levels of SLUG. E-cadherin IHC staining were higher in Skip N2 and Vimentin were in Non-Skip N2. TP63 had a strong correlation with SLUG expression in the bioinformatics analyses.

CONCLUSION

The results indicate that, at molecular level, Skip N2 pathogenesis has different molecular background and regulation of SLUG expression may orchestrate the process.

Collagen type 1 alpha 1 chain is a novel predictive biomarker of poor progression-free survival and chemoresistance in metastatic lung cancer

Background: Collagen type 1 alpha 1 chain (COL1A1) is an extracellular matrix protein comprising two alpha 1 chains and one alpha 2 chain. Our previous study identified that COL1A1 is the key gene during the development and progression of lung adenocarcinoma by multi-omics analysis. However, the clinical significance of COL1A1 expression in lung cancer samples remains largely unknown. Here, we aimed to evaluate the level of COL1A1 in lung cancer samples and correlate its level with the clinical outcome.

Methods:COL1A1 gene expression in lung cancer samples was analyzed using the Oncomine database (www.oncomine.org). A total of 308 lung cancer samples (208 formalin-fixed paraffin-embedded tissues and 100 blood samples) were assessed for protein expression of COL1A1. Immunohistochemistry staining and enzyme-linked immunosorbent assay were used to detect COL1A1 expression in tissues and serum, respectively.

Results: We identified an elevation of COL1A1 in mRNA level and gene amplification in lung cancer tissues compared with normal lung tissues. High COL1A1 expression was observed in lung cancer tissues and serum (P < 0.05), it was significantly correlated with the peripheral type tumor, the larger diameter of the tumor, the occurrence of lymph node metastases and distant metastases, a higher TNM stage, and smoking (P < 0.05). High COL1A1 expression was associated with poor progression-free survival (PFS) and chemoresistance in lung cancer patients (P < 0.05). Multivariable Cox-regression analysis showed that COL1A1 expression was an independent prognostic factor (P < 0.05). Furthermore, the area under the receiver operating characteristic (AUC) curve was 0.909 for the combined COL1A1 and carcinoembryonic antigen (CEA) measurement.

Conclusion: Our findings revealed that COL1A1 could be used as a novel diagnostic, prognostic, and chemoresistance biomarker of human lung cancer, and these results provide a potential therapeutic strategy for lung cancer patients.

Bioinformatics Analysis of Dysregulated MicroRNA-Messenger RNA Networks in Small Cell Lung Cancer

The present study aimed to identify a key module of differentially expressed miRNAs (DE-miRNAs) together with the corresponding differentially expressed mRNAs (DE-mRNAs) within small cell lung cancer (SCLC). Linear models were applied to ascertain the DE-miRNAs and DE-mRNAs in SCLC versus matched non-carcinoma samples obtained from the RNA expression datasets of GSE19945, GSE74190 and GSE6044. The common DE-miRNAs were identified using the Venn plot. Then, 3 databases were used to retrieve the DE-miRNAs target genes, and the intersection was taken for validating the shared target genes. Besides, Cytoscape was utilized for constructing the miRNAmRNA network for SCLC. Finally, a key module of five DE-miRNAs and four hub genes was determined based on the degree. In addition, the Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) analyses were conducted for exploring those hub genes in terms of their functions along with the involved signal transduction pathways. Altogether 106 shared DE-miRNAs were identified, which were used to predict 63 common target genes. In addition, a key module of five DE-miRNAs (hsa-miR-17-5p, hsa-miR-20a-5p, hsa-miR-20b-5p, hsa-miR-93-5p and hsa-miR- 106b-5p) and four hub genes (SOX4, DPYSL2, TGFBR2 and F3) were extracted from the miRNAmRNA network according to their degree. Finally, the hub genes were subjected to GO as well as KEGG analysis, which revealed that cell cycle G1/S phase transition, the extracellular matrix, and cellular senescence signaling pathways exerted vial parts during SCLC progression. A key module of five DE-miRNAs and four hub genes may be potentially used as clinical biomarkers to predict SCLC.

In Silico and In Vitro Analysis of lncRNA XIST Reveals a Panel of Possible Lung Cancer Regulators and a Five-Gene Diagnostic Signature

Simple Summary

Long non-coding RNAs (lncRNA) have been associated with a number of diseases including cancer. A well-studied lncRNA called XIST (X-inactive specific transcript) acts as a major effector of the X-inactivation process. It is expressed on the inactive X chromosome providing a dosage equivalence between males and females. Recently XIST has been implicated in the development of lung cancer. Using a bioinformatics approach, we demonstrate the XIST is over-expressed in female patients compared to males. When XIST gene was silenced in two different cell lines (of male and female origin), a number of genes were differentially expressed; playing a role in signal transduction pathways, energy balance and metabolism, thus providing a better insight of the role of this lncRNA in cancer. Finally, we showed that expression of XIST with another 4 genes provided a strong diagnostic potential to discriminate lung cancer from healthy controls.

Abstract

Long non-coding RNAs (lncRNAs) perform a wide functional repertoire of roles in cell biology, ranging from RNA editing to gene regulation, as well as tumour genesis and tumour progression. The lncRNA X-inactive specific transcript (XIST) is involved in the aetiopathogenesis of non-small cell lung cancer (NSCLC). However, its role at the molecular level is not fully elucidated. The expression of XIST and co-regulated genes TSIX, hnRNPu, Bcl-2, and BRCA1 analyses in lung cancer (LC) and controls were performed in silico. Differentially expressed genes (DEGs) were determined using RNA-seq in H1975 and A549 NSCLC cell lines following siRNA for XIST. XIST exhibited sexual dimorphism, being up-regulated in females compared to males in both control and LC patient cohorts. RNA-seq revealed 944 and 751 DEGs for A549 and H1975 cell lines, respectively. These DEGs are involved in signal transduction, cell communication, energy pathways, and nucleic acid metabolism. XIST expression associated with TSIX, hnRNPu, Bcl-2, and BRCA1 provided a strong collective feature to discriminate between controls and LC, implying a diagnostic potential. There is a much more complex role for XIST in lung cancer. Further studies should concentrate on sex-specific changes and investigate the signalling pathways of the DEGs following silencing of this lncRNA.

Screening and identification of key biomarkers in lung squamous cell carcinoma by bioinformatics analysis

The high mortality rate of lung squamous cell carcinoma (LUSC) is in part due to the lack of early detection of its biomarkers. The identification of key molecules involved in LUSC is therefore required to improve clinical diagnosis and treatment outcomes. The present study used the microarray datasets GSE31552, GSE6044 and GSE12428 from the Gene Expression Omnibus database to identify differentially expressed genes (DEGs). Kyoto Encyclopedia of Genes and Genomes (KEGG) and Gene Ontology (GO) enrichment analyses were conducted to construct the protein-protein interaction network of DEGs and hub genes module using STRING and Cytoscape. The 67 DEGs identified consisted of 42 upregulated genes and 25 downregulated genes. The pathways predicted by KEGG and GO enrichment analyses of DEGs mainly included cell cycle, cell proliferation, glycolysis or gluconeogenesis, and tetrahydrofolate metabolic process. Further analysis of the University of California Santa Cruz and ONCOMINE databases identified 17 hub genes. Overall, the present study demonstrated hub genes that were closely associated with clinical tissue samples of LUSC, and identified TYMS, CCNB2 and RFC4 as potential novel biomarkers of LUSC. The findings of the present study contribute to an improved understanding of the molecular mechanisms of carcinogenesis and progression of LUSC, and assist with the identification of potential diagnostic and therapeutic targets of LUSC.

Cross-disease analysis identified novel common genes for both lung adenocarcinoma and lung squamous cell carcinoma

Lung squamous cell carcinoma (LSCC) exhibits a number of similarities with lung adenocarcinoma (LA) in terms of copy number alterations. However, compared with LA, the range of genetic alterations in LSCC is less understood. In the present study, a large-scale literature-based search of LA-associated genes and LSCC-associated genes was performed to identify the genetic basis in common with these two diseases. For each of the LA-associated genes, a mega-analysis was performed to test its expression variations in LSCC using 11 RNA expression datasets, with significant genes identified using statistical analysis. Subsequently, a functional pathway analysis was performed to identify a possible association between any of the significant genes identified from the mega-analysis and LSCC, followed by a co-expression analysis. A multiple linear regression (MLR) model was employed to investigate the possible influence of sample size, country of origin and study date on gene expression in patients with LSCC. Disease-gene association data analysis identified 1,178 genes involved in LA, 334 in LSCC, with a significant overlap of 187 genes (P<1.02×⁻¹⁶¹). Mega-analysis revealed that three LA-associated genes, such as solute carrier family 2 member 1 (SLC2A1), endothelial PAS domain protein 1 (EPAS1) and cyclin-dependent kinase 4 (CDK4), were significantly associated with LSCC (P<1.60×10⁻⁸), with multiple potential pathways identified by functional pathway analysis, which were further validated by co-expression analysis. The present MLR analysis suggested that the country of origin was a significant factor for the levels of expression of all three genes in patients with LSCC (P<4.0×10⁻³). Collectively, the present results suggested that genes associated with LA should be further investigated for their association with LSCC. In addition, SLC2A1, EPAS1 and CDK4 may be novel risk genes associated with LA and LSCC.

Identification of candidate genes associated with the pathogenesis of small cell lung cancer via integrated bioinformatics analysis

The pathogenesis of small cell lung cancer (SCLC), a highly metastatic malignant tumor, remains unclear. In the present study, important genes and pathways that are involved in the pathogenesis of SCLC were identified. The following four datasets were downloaded from the Gene Expression Omnibus: GSE60052, GSE43346, GSE15240 and GSE6044. The differentially expressed genes (DEGs) between the SCLC samples and the normal samples were analyzed using R software. The limma package was used for every dataset. The RobustRankAggreg package was used to integrate the DEGs from the four datasets. Functional and pathway enrichment analyses were conducted using the Gene Ontology and Kyoto Encyclopedia of Genes and Genomes databases with FunRich software and R software, respectively. In addition, the protein-protein interaction (PPI) network of the DEGs was constructed using the STRING database and Cytoscape software. Hub genes and significant modules were identified using Molecular Complex Detection in Cytoscape software. Finally, the expression values of hub genes were determined using the Oncomine online database. In total, 412 DEGs were identified following the integration of the four datasets, with 146 upregulated genes and 266 downregulated genes. The upregulated DEGs were primarily enriched in the cell cycle, cell division and microtubule binding. The downregulated DEGs were primarily enriched in the complement and coagulation cascades, the cytokine-mediated signaling pathway and protein binding. Eight hub genes and 1 significant module correlated to the cell cycle pathway were identified based on a subset of the PPI network. Finally, five hub genes were identified as highly expressed in SCLC tissue compared with normal tissue. The cell cycle pathway may be the pathway most closely associated with the pathogenesis of SCLC. NDC80, BUB1B, PLK1, CDC20 and MAD2L1 should be the focus of follow-up studies regarding the diagnosis and treatment of SCLC.

Distinct Molecular Mechanisms Analysis of Three Lung Cancer Subtypes Based on Gene Expression Profiles

The purpose was to explore distinct molecular mechanisms of three lung cancer subtypes. GSE6044 microarray data downloaded from Gene Expression Omnibus (GEO) database were applied for identifying the differentially expressed genes (DEGs). Genetic global network was constructed to analyze the network annotation. The DEGs in the genetic global network related to small-cell lung carcinoma (SCLC), lung squamous cell carcinoma (SCC), and lung adenocarcinoma (AC) were screened. Protein-protein international networks of DEGs were constructed. Pathway enrichment analyses of DEGs in three subtypes were performed, followed by construction of interactional network among pathways. There were more DEGs screened in SCLC than in AC and SCC. The genetic global network with 341 genes and 1569 interaction edges was constructed. After annotating these DEGs into a protein interactional network, a total of 695 protein interactions related to these 36 DEGs were obtained. HSP90AA1 was the hub node with the highest degree of 81 in the annotation network. DEGs in SCLC and SCC were mainly enriched in some pathways, including cell cycle, DNA replication, and histidine metabolism; whereas DEGs in AC were enriched in complement and coagulation cascades, and extracellular matrix (ECM)-receptor interaction. Pathway interactional network was constructed with the hub node of a neuroactive ligand receptor interaction. The identified DEGs such as retinoid X receptor alpha (RXRA), cyclin-dependent kinase 2 (CDK2), histone deacetylase 2 (HDAC2), and KIT might be the target genes of lung cancer by participating in different pathways such as ECM-receptor interaction. Complement and coagulation cascades, and ECM-receptor interaction might be the specific pathways for AC; smoking might have a closer relationship with SCC.

Bioinformatics analysis of mRNA and miRNA microarray to identify the key miRNA‑gene pairs in small‑cell lung cancer

Small-cell lung cancer (SCLC) is a type of lung cancer with early metastasis, and high recurrence and mortality rates. The molecular mechanism is still unclear and further research is required. The aim of the present study was to examine the pathogenesis and potential molecular markers of SCLC by comparing the differential expression of mRNA and microRNA (miRNA) between SCLC tissue and normal lung tissue. A transcriptome sequencing dataset (GSE6044) and a non-coding RNA sequence dataset (GSE19945) were downloaded from the Gene Expression Omnibus (GEO) database. In total, 451 differentially expressed genes (DEGs) and 134 differentially expressed miRNAs (DEMs) were identified using the R limma software package and the GEO2R tool of the GEO, respectively. The Gene Ontology function was significantly enriched for 28 terms, and the Kyoto Encyclopedia of Genes and Genomes database had 19 enrichment pathways, mainly related to ‘cell cycle’, ‘DNA replication’ and ‘oocyte meiosis mismatch repair’. The protein-protein interaction network was constructed using Cytoscape software to identify the molecular mechanisms of key signaling pathways and cellular activities in SCLC. The 1,402 miRNA-gene pairs encompassed 602 target genes of the DEMs using miRNAWalk, which is a bioinformatics platform that predicts DEM target genes and miRNA-gene pairs. There were 19 overlapping genes regulated by 32 miRNAs between target genes of the DEMs and DEGs. Bioinformatics analysis may help to better understand the role of DEGs, DEMs and miRNA-gene pairs in cell proliferation and signal transduction. The related hub genes may be used as biomarkers for the diagnosis and prognosis of SCLC, and as potential drug targets.

Identification of candidate biomarkers and pathways associated with SCLC by bioinformatics analysis

Small cell lung cancer (SCLC) is one of the highly malignant tumors and a serious threat to human health. The aim of the present study was to explore the underlying molecular mechanisms of SCLC. mRNA microarray datasets GSE6044 and GSE11969 were downloaded from Gene Expression Omnibus database, and the differentially expressed genes (DEGs) between normal lung and SCLC samples were screened using GEO2R tool. Functional and pathway enrichment analyses were performed for common DEGs using the DAVID database, and the protein-protein interaction (PPI) network of common DEGs was constructed by the STRING database and visualized with Cytoscape software. In addition, the hub genes in the network and module analysis of the PPI network were performed using CentiScaPe and plugin Molecular Complex Detection. Finally, the mRNA expression levels of hub genes were validated in the Oncomine database. A total of 150 common DEGs with absolute fold-change >0.5, including 66 significantly downregulated DEGs and 84 upregulated DEGs were obtained. The Gene Ontology term enrichment analysis suggested that common upregulated DEGs were primarily enriched in biological processes (BPs), including ‘cell cycle’, ‘cell cycle phase’, ‘M phase’, ‘cell cycle process’ and ‘DNA metabolic process’. The common downregulated genes were significantly enriched in BPs, including ‘response to wounding’, ‘positive regulation of immune system process’, ‘immune response’, ‘acute inflammatory response’ and ‘inflammatory response’. Kyoto Encyclopedia of Genes and Genomes pathway analysis identified that the common downregulated DEGs were primarily enriched in the ‘complement and coagulation cascades’ signaling pathway; the common upregulated DEGs were mainly enriched in ‘cell cycle’, ‘DNA replication’, ‘oocyte meiosis’ and the ‘mismatch repair’ signaling pathways. From the PPI network, the top 10 hub genes in SCLC were selected, including topoisomerase IIα, proliferating cell nuclear antigen, replication factor C subunit 4, checkpoint kinase 1, thymidylate synthase, minichromosome maintenance protein (MCM) 2, cell division cycle (CDC) 20, cyclin dependent kinase inhibitor 3, MCM3 and CDC6, the mRNA levels of which are upregulated in Oncomine SCLC datasets with the exception of MCM2. Furthermore, the genes in the significant module were enriched in ‘cell cycle’, ‘DNA replication’ and ‘oocyte meiosis’ signaling pathways. Therefore, the present study can shed new light on the understanding of molecular mechanisms of SCLC and may provide molecular targets and diagnostic biomarkers for the treatment and early diagnosis of SCLC.

Integrative transcriptome analysis identifies deregulated microRNA-transcription factor networks in lung adenocarcinoma

Herein, we aimed at identifying global transcriptome microRNA (miRNA) changes and miRNA target genes in lung adenocarcinoma. Samples were selected as training (N = 24) and independent validation (N = 34) sets. Tissues were microdissected to obtain >90% tumor or normal lung cells, subjected to miRNA transcriptome sequencing and TaqMan quantitative PCR validation. We further integrated our data with published miRNA and mRNA expression datasets across 1,491 lung adenocarcinoma and 455 normal lung samples. We identified known and novel, significantly over- and under-expressed (p ≤ 0.01 and FDR≤0.1) miRNAs in lung adenocarcinoma compared to normal lung tissue: let-7a, miR-10a, miR-15b, miR-23b, miR-26a, miR-26b, miR-29a, miR-30e, miR-99a, miR-146b, miR-181b, miR-181c, miR-421, miR-181a, miR-574 and miR-1247. Validated miRNAs included let-7a-2, let-7a-3, miR-15b, miR-21, miR-155 and miR-200b; higher levels of miR-21 expression were associated with lower patient survival (p = 0.042). We identified a regulatory network including miR-15b and miR-155, and transcription factors with prognostic value in lung cancer. Our findings may contribute to the development of treatment strategies in lung adenocarcinoma.

Differentially expressed microRNAs in lung adenocarcinoma invert effects of copy number aberrations of prognostic genes

In many cancers, significantly down- or upregulated genes are found within chromosomal regions with DNA copy number alteration opposite to the expression changes. Generally, this paradox has been overlooked as noise, but can potentially be a consequence of interference of epigenetic regulatory mechanisms, including microRNA-mediated control of mRNA levels.

To explore potential associations between microRNAs and paradoxes in non-small-cell lung cancer (NSCLC) we curated and analyzed lung adenocarcinoma (LUAD) data, comprising gene expressions, copy number aberrations (CNAs) and microRNA expressions. We integrated data from 1,062 tumor samples and 241 normal lung samples, including newly-generated array comparative genomic hybridization (aCGH) data from 63 LUAD samples.

We identified 85 “paradoxical” genes whose differential expression consistently contrasted with aberrations of their copy numbers. Paradoxical status of 70 out of 85 genes was validated on sample-wise basis using The Cancer Genome Atlas (TCGA) LUAD data. Of these, 41 genes are prognostic and form a clinically relevant signature, which we validated on three independent datasets. By meta-analysis of results from 9 LUAD microRNA expression studies we identified 24 consistently-deregulated microRNAs. Using TCGA-LUAD data we showed that deregulation of 19 of these microRNAs explains differential expression of the paradoxical genes.

Our results show that deregulation of paradoxical genes is crucial in LUAD and their expression pattern is maintained epigenetically, defying gene copy number status.

Venetoclax Is Effective in Small-Cell Lung Cancers with High BCL-2 Expression

Purpose: Small-cell lung cancer (SCLC) is an often-fatal neuroendocrine carcinoma usually presenting as extensive disease, carrying a 3% 5-year survival. Despite notable advances in SCLC genomics, new therapies remain elusive, largely due to a lack of druggable targets.Experimental Design: We used a high-throughput drug screen to identify a venetoclax-sensitive SCLC subpopulation and validated the findings with multiple patient-derived xenografts of SCLC.Results: Our drug screen consisting of a very large collection of cell lines demonstrated that venetoclax, an FDA-approved BCL-2 inhibitor, was found to be active in a substantial fraction of SCLC cell lines. Venetoclax induced BIM-dependent apoptosis in vitro and blocked tumor growth and induced tumor regressions in mice bearing high BCL-2-expressing SCLC tumors in vivo BCL-2 expression was a predictive biomarker for sensitivity in SCLC cell lines and was highly expressed in a subset of SCLC cell lines and tumors, suggesting that a substantial fraction of patients with SCLC could benefit from venetoclax. Mechanistically, we uncover a novel role for gene methylation that helped discriminate high BCL-2-expressing SCLCs.Conclusions: Altogether, our findings identify venetoclax as a promising new therapy for high BCL-2-expressing SCLCs. Clin Cancer Res; 24(2); 360-9. ©2017 AACR.

NFIX as a Master Regulator for Lung Cancer Progression

About 40% of lung cancer cases globally are diagnosed at the advanced stage. Lung cancer has a high mortality and overall survival in stage I disease is only 70%. This study was aimed at finding a candidate of transcription regulator that initiates the mechanism for metastasis by integrating computational and functional studies. The genes involved in lung cancer were retrieved using in silico software. 10 kb promoter sequences upstream were scanned for the master regulator. Transient transfection of shRNA NFIXs were conducted against A549 and NCI-H1299 cell lines. qRT-PCR and functional assays for cell proliferation, migration and invasion were carried out to validate the involvement of NFIX in metastasis. Genome-wide gene expression microarray using a HumanHT-12v4.0 Expression BeadChip Kit was performed to identify differentially expressed genes and construct a new regulatory network. The in silico analysis identified NFIX as a master regulator and is strongly associated with 17 genes involved in the migration and invasion pathways including IL6ST, TIMP1 and ITGB1. Silencing of NFIX showed reduced expression of IL6ST, TIMP1 and ITGB1 as well as the cellular proliferation, migration and invasion processes. The data was integrated with the in silico analyses to find the differentially expressed genes. Microarray analysis showed that 18 genes were expressed differentially in both cell lines after statistical analyses integration between t-test, LIMMA and ANOVA with Benjamini-Hochberg adjustment at p-value < 0.05. A transcriptional regulatory network was created using all 18 genes, the existing regulated genes including the new genes PTCH1, NFAT5 and GGCX that were found highly associated with NFIX, the master regulator of metastasis. This study suggests that NFIX is a promising target for therapeutic intervention that is expected to inhibit metastatic recurrence and improve survival rate.

An Expression Signature as an Aid to the Histologic Classification of Non-Small Cell Lung Cancer

PURPOSE

Most non-small cell lung cancers (NSCLC) are now diagnosed from small specimens, and classification using standard pathology methods can be difficult. This is of clinical relevance as many therapy regimens and clinical trials are histology dependent. The purpose of this study was to develop an mRNA expression signature as an adjunct test for routine histopathologic classification of NSCLCs.

EXPERIMENTAL DESIGN

A microarray dataset of resected adenocarcinomas (ADC) and squamous cell carcinomas (SCC) was used as the learning set for an ADC-SCC signature. The Cancer Genome Atlas (TCGA) lung RNAseq dataset was used for validation. Another microarray dataset of ADCs and matched nonmalignant lung was used as the learning set for a tumor versus nonmalignant signature. The classifiers were selected as the most differentially expressed genes and sample classification was determined by a nearest distance approach.

RESULTS

We developed a 62-gene expression signature that contained many genes used in immunostains for NSCLC typing. It includes 42 genes that distinguish ADC from SCC and 20 genes differentiating nonmalignant lung from lung cancer. Testing of the TCGA and other public datasets resulted in high prediction accuracies (93%-95%). In addition, a prediction score was derived that correlates both with histologic grading and prognosis. We developed a practical version of the Classifier using the HTG EdgeSeq nuclease protection-based technology in combination with next-generation sequencing that can be applied to formalin-fixed paraffin-embedded (FFPE) tissues and small biopsies.

CONCLUSIONS

Our RNA classifier provides an objective, quantitative method to aid in the pathologic diagnosis of lung cancer. Clin Cancer Res; 22(19); 4880-9. ©2016 AACR.

Regulation of TPD52 by antitumor microRNA-218 suppresses cancer cell migration and invasion in lung squamous cell carcinoma

The development of targeted molecular therapies has greatly benefited patients with lung adenocarcinomas. In contrast, these treatments have had little benefit in the management of lung squamous cell carcinoma (lung SCC). Therefore, new treatment options based on current genomic approaches are needed for lung SCC. Aberrant microRNA (miRNA) expression has been shown to promote lung cancer development and aggressiveness. Downregulation of microRNA-218 (miR-218) was frequently observed in our miRNA expression signatures of cancers, and previous studies have shown an antitumor function of miR-218 in several types of cancers. However, the impact of miR-218 on lung SCC is still ambiguous. The present study investigated the antitumor roles of miR-218 in lung SCC to identify the target genes regulated by this miRNA. Ectopic expression of miR-218 greatly inhibited cancer cell migration and invasion in the lung SCC cell lines EBC-1 and SK-MES-1. Through a combination of in silico analysis and gene expression data searching, tumor protein D52 (TPD52) was selected as a putative target of miR-218 regulation. Moreover, direct binding of miR-218 to the 3'-UTR of TPD52 was observed by dual luciferase reporter assay. Overexpression of TPD52 was observed in lung SCC clinical specimens, and knockdown of TPD52 significantly suppressed cancer cell migration and invasion in lung SCC cell lines. Furthermore, the downstream pathways mediated by TPD52 involved critical regulators of genomic stability and mitotic checkpoint genes. Taken together, our data showed that downregulation of miR-218 enhances overexpression of TPD52 in lung SCC cells, promoting cancer cell aggressiveness. Identification of tumor-suppressive miRNA-mediated RNA networks of lung SCC will provide new insights into the potential mechanisms of the molecular pathogenesis of the disease.

Transcriptional Profiling of Newly Generated Dentate Granule Cells Using TU Tagging Reveals Pattern Shifts in Gene Expression during Circuit Integration

Despite representing only a small fraction of hippocampal granule cells, adult-generated newborn granule cells have been implicated in learning and memory (Aimone et al., 2011). Newborn granule cells undergo functional maturation and circuit integration over a period of weeks. However, it is difficult to assess the accompanying gene expression profiles in vivo with high spatial and temporal resolution using traditional methods. Here we used a novel method ["thiouracil (TU) tagging"] to map the profiles of nascent mRNAs in mouse immature newborn granule cells compared with mature granule cells. We targeted a nonmammalian uracil salvage enzyme, uracil phosphoribosyltransferase, to newborn neurons and mature granule cells using retroviral and lentiviral constructs, respectively. Subsequent injection of 4-TU tagged nascent RNAs for analysis by RNA sequencing. Several hundred genes were significantly enhanced in the retroviral dataset compared with the lentiviral dataset. We compared a selection of the enriched genes with steady-state levels of mRNAs using quantitative PCR. Ontology analysis revealed distinct patterns of nascent mRNA expression, with newly generated immature neurons showing enhanced expression for genes involved in synaptic function, and neural differentiation and development, as well as genes not previously associated with granule cell maturation. Surprisingly, the nascent mRNAs enriched in mature cells were related to energy homeostasis and metabolism, presumably indicative of the increased energy demands of synaptic transmission and their complex dendritic architecture. The high spatial and temporal resolution of our modified TU-tagging method provides a foundation for comparison with steady-state RNA analyses by traditional transcriptomic approaches in defining the functional roles of newborn neurons.

Cooperation of the BTB-Zinc finger protein, Abrupt, with cytoskeletal regulators in Drosophila epithelial tumorigenesis

The deregulation of cell polarity or cytoskeletal regulators is a common occurrence in human epithelial cancers. Moreover, there is accumulating evidence in human epithelial cancer that BTB-ZF genes, such as Bcl6 and ZBTB7A, are oncogenic. From our previous studies in the vinegar fly, Drosophila melanogaster, we have identified a cooperative interaction between a mutation in the apico-basal cell polarity regulator Scribble (Scrib) and overexpression of the BTB-ZF protein Abrupt (Ab). Herein, we show that co-expression of ab with actin cytoskeletal regulators, RhoGEF2 or Src64B, in the developing eye-antennal epithelial tissue results in the formation of overgrown amorphous tumours, whereas ab and DRac1 co-expression leads to non-cell autonomous overgrowth. Together with ab, these genes affect the expression of differentiation genes, resulting in tumours locked in a progenitor cell fate. Finally, we show that the expression of two mammalian genes related to ab, Bcl6 and ZBTB7A, which are oncogenes in mammalian epithelial cancers, significantly correlate with the upregulation of cytoskeletal genes or downregulation of apico-basal cell polarity neoplastic tumour suppressor genes in colorectal, lung and other human epithelial cancers. Altogether, this analysis has revealed that upregulation of cytoskeletal regulators cooperate with Abrupt in Drosophila epithelial tumorigenesis, and that high expression of human BTB-ZF genes, Bcl6 and ZBTB7A, shows significant correlations with cytoskeletal and cell polarity gene expression in specific epithelial tumour types. This highlights the need for further investigation of the cooperation between these genes in mammalian systems.

EZH2 inhibition sensitizes BRG1 and EGFR mutant lung tumours to TopoII inhibitors

Non-small-cell lung cancer is the leading cause of cancer-related death worldwide. Chemotherapies such as the topoisomerase II (TopoII) inhibitor etoposide effectively reduce disease in a minority of patients with this cancer; therefore, alternative drug targets, including epigenetic enzymes, are under consideration for therapeutic intervention. A promising potential epigenetic target is the methyltransferase EZH2, which in the context of the polycomb repressive complex 2 (PRC2) is well known to tri-methylate histone H3 at lysine 27 (H3K27me3) and elicit gene silencing. Here we demonstrate that EZH2 inhibition has differential effects on the TopoII inhibitor response of non-small-cell lung cancers in vitro and in vivo. EGFR and BRG1 mutations are genetic biomarkers that predict enhanced sensitivity to TopoII inhibitor in response to EZH2 inhibition. BRG1 loss-of-function mutant tumours respond to EZH2 inhibition with increased S phase, anaphase bridging, apoptosis and TopoII inhibitor sensitivity. Conversely, EGFR and BRG1 wild-type tumours upregulate BRG1 in response to EZH2 inhibition and ultimately become more resistant to TopoII inhibitor. EGFR gain-of-function mutant tumours are also sensitive to dual EZH2 inhibition and TopoII inhibitor, because of genetic antagonism between EGFR and BRG1. These findings suggest an opportunity for precision medicine in the genetically complex disease of non-small-cell lung cancer.

Prioritizing therapeutics for lung cancer: an integrative meta-analysis of cancer gene signatures and chemogenomic data

Repurposing FDA-approved drugs with the aid of gene signatures of disease can accelerate the development of new therapeutics. A major challenge to developing reliable drug predictions is heterogeneity. Different gene signatures of the same disease or drug treatment often show poor overlap across studies, as a consequence of both biological and technical variability, and this can affect the quality and reproducibility of computational drug predictions. Existing algorithms for signature-based drug repurposing use only individual signatures as input. But for many diseases, there are dozens of signatures in the public domain. Methods that exploit all available transcriptional knowledge on a disease should produce improved drug predictions. Here, we adapt an established meta-analysis framework to address the problem of drug repurposing using an ensemble of disease signatures. Our computational pipeline takes as input a collection of disease signatures, and outputs a list of drugs predicted to consistently reverse pathological gene changes. We apply our method to conduct the largest and most systematic repurposing study on lung cancer transcriptomes, using 21 signatures. We show that scaling up transcriptional knowledge significantly increases the reproducibility of top drug hits, from 44% to 78%. We extensively characterize drug hits in silico, demonstrating that they slow growth significantly in nine lung cancer cell lines from the NCI-60 collection, and identify CALM1 and PLA2G4A as promising drug targets for lung cancer. Our meta-analysis pipeline is general, and applicable to any disease context; it can be applied to improve the results of signature-based drug repurposing by leveraging the large number of disease signatures in the public domain.

Computer algorithms that find new uses for known drugs can accelerate the development of new therapies for many diseases, including cancer. One promising strategy is to identify drugs that, at the transcriptional level, reverse the gene expression signature of a disease. A major difficulty with this strategy is variability: different gene expression signatures of the same disease or drug treatment can show poor overlap across studies. Since existing algorithms analyze one signature at a time, this means that the drug candidates they identify may reverse some signatures of a disease but not others. For many diseases, dozens of signatures from different labs are now available in online databases. Combining knowledge across all signatures should lead to better drug predictions. Here, we design a meta-analysis pipeline that takes in a large set of disease signatures and then identifies drugs that consistently reverse deleterious gene changes. We apply our method to find new drug candidates for lung cancer, using 21 signatures. We show that our meta-analysis pipeline increases the reproducibility of top drug hits, and then extensively characterize new lung cancer drug candidates in silico.

The PFA-AMeX method achieves a good balance between the morphology of tissues and the quality of RNA content in DNA microarray analysis with laser-capture microdissection samples

Recently, large-scale gene expression profiling is often performed using RNA extracted from unfixed frozen or formalin-fixed paraffin embedded (FFPE) samples. However, both types of samples have drawbacks in terms of the morphological preservation and RNA quality. In the present study, we investigated 30 human prostate tissues using the PFA-AMeX method (fixation using paraformaldehyde (PFA) followed by embedding in paraffin by AMeX) with a DNA microarray combined with laser-capture microdissection. Morphologically, in contrast to the case of atypical adenomatous hyperplasia, loss of basal cells in prostate adenocarcinomas was as obvious in PFA-AMeX samples as in FFPE samples. As for quality, the loss of rRNA peaks 18S and 28S on the capillary electropherograms from both FFPE and PFA-AMeX samples showed that the RNA was degraded equally during processing. However, qRT-PCR with 3' and 5' primer sets designed against human beta-actin revealed that, although RNA degradation occurred in both methods, it occurred more mildly in the PFA-AMeX samples. In conclusion, the PFA-AMeX method is good with respect to morphology and RNA quality, which makes it a promising tool for DNA microarrays combined with laser-capture microdissection, and if the appropriate RNA quality criteria are used, the capture of credible GeneChip data is well over 80% efficient, at least in human prostate specimens.

The Robustness of Pathway Analysis in Identifying Potential Drug Targets in Non-Small Cell Lung Carcinoma

The identification of genes responsible for causing cancers from gene expression data has had varied success. Often the genes identified depend on the methods used for detecting expression patterns, or on the ways that the data had been normalized and filtered. The use of gene set enrichment analysis is one way to introduce biological information in order to improve the detection of differentially expressed genes and pathways. In this paper we show that the use of network models while still subject to the problems of normalization is a more robust method for detecting pathways that are differentially overrepresented in lung cancer data. Such differences may provide opportunities for novel therapeutics. In addition, we present evidence that non-small cell lung carcinoma is not a series of homogeneous diseases; rather that there is a heterogeny within the genotype which defies phenotype classification. This diversity helps to explain the lack of progress in developing therapies against non-small cell carcinoma and suggests that drug development may consider multiple pathways as treatment targets.

Lung cancer transcriptomes refined with laser capture microdissection

We evaluated the importance of tumor cell selection for generating gene signatures in non-small cell lung cancer. Tumor and nontumor tissue from macroscopically dissected (Macro) surgical specimens (31 pairs from 32 subjects) was homogenized, extracted, amplified, and hybridized to microarrays. Adjacent scout sections were histologically mapped; sets of approximately 1000 tumor cells and nontumor cells (alveolar or bronchial) were procured by laser capture microdissection (LCM). Within histological strata, LCM and Macro specimens exhibited approximately 67% to 80% nonoverlap in differentially expressed (DE) genes. In a representative subset, LCM uniquely identified 300 DE genes in tumor versus nontumor specimens, largely attributable to cell selection; 382 DE genes were common to Macro, Macro with preamplification, and LCM platforms. RT-qPCR validation in a 33-gene subset was confirmatory (ρ = 0.789 to 0.964, P = 0.0013 to 0.0028). Pathway analysis of LCM data suggested alterations in known cancer pathways (cell growth, death, movement, cycle, and signaling components), among others (eg, immune, inflammatory). A unique nine-gene LCM signature had higher tumor-nontumor discriminatory accuracy (100%) than the corresponding Macro signature (87%). Comparison with Cancer Genome Atlas data sets (based on homogenized Macro tissue) revealed both substantial overlap and important differences from LCM specimen results. Thus, cell selection via LCM enhances expression profiling precision, and confirms both known and under-appreciated lung cancer genes and pathways.

Identification of featured biomarkers in different types of lung cancer with DNA microarray

Lung cancer is a worldwide leading cause of cancer-related death. The aim of this study was to identify target genes and specific biomarkers for identification and treatment of different types of lung cancer with DNA microarray. Gene expression profile GSE6044 and miRNA microarray profile GSE17681 were downloaded from Gene Expression Omnibus database. The differentially expressed genes (DEGs) and miRNAs were screened with multtest package in R language. Then, functional enrichment analysis of identified DEGs was performed. Furthermore, the verified target genes based on screened miRNAs were selected from miRTarBase and miRecords databases. Then miRNA-target gene regulation network was constructed. APOE, CDC6 and ATP2B1were involved in most of the functions obtained for adenocarcinomas, small cell lung cancer and squamous cell carcinomas, respectively. The target DEGs of differentially expressed hsa-miR-29a included FGG in adenocarcinoma, RAN and COL4A1 in small cell lung cancer, GLUL in squamous cell carcinoma. The target DEGs of has-miR-7 were SNCA and SLC7A5 in adenocarcinoma and small cell lung cancer, respectively. ICAM1 and KIT were the target DEGs of hsa-miR-222 in adenocarcinoma and squamous cell carcinoma. The miRNAs and their differentially expressed target genes have the potential to be used in clinic for diagnosis and treatment of different kinds of lung cancer in the future.

Tumor protein D52 (TPD52) and cancer-oncogene understudy or understudied oncogene?

The Tumor protein D52 (TPD52) gene was identified nearly 20 years ago through its overexpression in human cancer, and a substantial body of data now strongly supports TPD52 representing a gene amplification target at chromosome 8q21.13. This review updates progress toward understanding the significance of TPD52 overexpression and targeting, both in tumors known to be characterized by TPD52 overexpression/amplification, and those where TPD52 overexpression/amplification has been recently or variably reported. We highlight recent findings supporting microRNA regulation of TPD52 expression in experimental systems and describe progress toward deciphering TPD52's cellular functions, particularly in cancer cells. Finally, we provide an overview of TPD52's potential as a cancer biomarker and immunotherapeutic target. These combined studies highlight the potential value of genes such as TPD52, which are overexpressed in many cancer types, but have been relatively understudied.

Role of Tertiary Lymphoid Structures (TLS) in Anti-Tumor Immunity: Potential Tumor-Induced Cytokines/Chemokines that Regulate TLS Formation in Epithelial-Derived Cancers

Following the successes of monoclonal antibody immunotherapies (trastuzumab (Herceptin^®) and rituximab (Rituxan^®)) and the first approved cancer vaccine, Provenge^® (sipuleucel-T), investigations into the immune system and how it can be modified by a tumor has become an exciting and promising new field of cancer research. Dozens of clinical trials for new antibodies, cancer and adjuvant vaccines, and autologous T and dendritic cell transfers are ongoing in hopes of identifying ways to re-awaken the immune system and force an anti-tumor response. To date, however, few consistent, reproducible, or clinically-relevant effects have been shown using vaccine or autologous cell transfers due in part to the fact that the immunosuppressive mechanisms of the tumor have not been overcome. Much of the research focus has been on re-activating or priming cytotoxic T cells to recognize tumor, in some cases completely disregarding the potential roles that B cells play in immune surveillance or how a solid tumor should be treated to maximize immunogenicity. Here, we will summarize what is currently known about the induction or evasion of humoral immunity via tumor-induced cytokine/chemokine expression and how formation of tertiary lymphoid structures (TLS) within the tumor microenvironment may be used to enhance immunotherapy response.

Genetic and pharmacologic inhibition of EPHA2 promotes apoptosis in NSCLC

Genome-wide analyses determined previously that the receptor tyrosine kinase (RTK) EPHA2 is commonly overexpressed in non-small cell lung cancers (NSCLCs). EPHA2 overexpression is associated with poor clinical outcomes; therefore, EPHA2 may represent a promising therapeutic target for patients with NSCLC. In support of this hypothesis, here we have shown that targeted disruption of EphA2 in a murine model of aggressive Kras-mutant NSCLC impairs tumor growth. Knockdown of EPHA2 in human NSCLC cell lines reduced cell growth and viability, confirming the epithelial cell autonomous requirements for EPHA2 in NSCLCs. Targeting EPHA2 in NSCLCs decreased S6K1-mediated phosphorylation of cell death agonist BAD and induced apoptosis. Induction of EPHA2 knockdown within established NSCLC tumors in a subcutaneous murine model reduced tumor volume and induced tumor cell death. Furthermore, an ATP-competitive EPHA2 RTK inhibitor, ALW-II-41-27, reduced the number of viable NSCLC cells in a time-dependent and dose-dependent manner in vitro and induced tumor regression in human NSCLC xenografts in vivo. Collectively, these data demonstrate a role for EPHA2 in the maintenance and progression of NSCLCs and provide evidence that ALW-II-41-27 effectively inhibits EPHA2-mediated tumor growth in preclinical models of NSCLC.

Co-expression network analysis identifies Spleen Tyrosine Kinase (SYK) as a candidate oncogenic driver in a subset of small-cell lung cancer

Background

Oncogenic mechanisms in small-cell lung cancer remain poorly understood leaving this tumor with the worst prognosis among all lung cancers. Unlike other cancer types, sequencing genomic approaches have been of limited success in small-cell lung cancer, i.e., no mutated oncogenes with potential driver characteristics have emerged, as it is the case for activating mutations of epidermal growth factor receptor in non-small-cell lung cancer. Differential gene expression analysis has also produced SCLC signatures with limited application, since they are generally not robust across datasets. Nonetheless, additional genomic approaches are warranted, due to the increasing availability of suitable small-cell lung cancer datasets. Gene co-expression network approaches are a recent and promising avenue, since they have been successful in identifying gene modules that drive phenotypic traits in several biological systems, including other cancer types.

Results

We derived an SCLC-specific classifier from weighted gene co-expression network analysis (WGCNA) of a lung cancer dataset. The classifier, termed SCLC-specific hub network (SSHN), robustly separates SCLC from other lung cancer types across multiple datasets and multiple platforms, including RNA-seq and shotgun proteomics. The classifier was also conserved in SCLC cell lines. SSHN is enriched for co-expressed signaling network hubs strongly associated with the SCLC phenotype. Twenty of these hubs are actionable kinases with oncogenic potential, among which spleen tyrosine kinase (SYK) exhibits one of the highest overall statistical associations to SCLC. In patient tissue microarrays and cell lines, SCLC can be separated into SYK-positive and -negative. SYK siRNA decreases proliferation rate and increases cell death of SYK-positive SCLC cell lines, suggesting a role for SYK as an oncogenic driver in a subset of SCLC.

Conclusions

SCLC treatment has thus far been limited to chemotherapy and radiation. Our WGCNA analysis identifies SYK both as a candidate biomarker to stratify SCLC patients and as a potential therapeutic target. In summary, WGCNA represents an alternative strategy to large scale sequencing for the identification of potential oncogenic drivers, based on a systems view of signaling networks. This strategy is especially useful in cancer types where no actionable mutations have emerged.

A drug repositioning approach identifies tricyclic antidepressants as inhibitors of small cell lung cancer and other neuroendocrine tumors

Small cell lung cancer (SCLC) is an aggressive neuroendocrine subtype of lung cancer with high mortality. We used a systematic drug repositioning bioinformatics approach querying a large compendium of gene expression profiles to identify candidate U.S. Food and Drug Administration (FDA)-approved drugs to treat SCLC. We found that tricyclic antidepressants and related molecules potently induce apoptosis in both chemonaïve and chemoresistant SCLC cells in culture, in mouse and human SCLC tumors transplanted into immunocompromised mice, and in endogenous tumors from a mouse model for human SCLC. The candidate drugs activate stress pathways and induce cell death in SCLC cells, at least in part by disrupting autocrine survival signals involving neurotransmitters and their G protein-coupled receptors. The candidate drugs inhibit the growth of other neuroendocrine tumors, including pancreatic neuroendocrine tumors and Merkel cell carcinoma. These experiments identify novel targeted strategies that can be rapidly evaluated in patients with neuroendocrine tumors through the repurposing of approved drugs.

SIGNIFICANCE

Our work shows the power of bioinformatics-based drug approaches to rapidly repurpose FDA-approved drugs and identifies a novel class of molecules to treat patients with SCLC, a cancer for which no effective novel systemic treatments have been identified in several decades. In addition, our experiments highlight the importance of novel autocrine mechanisms in promoting the growth of neuroendocrine tumor cells.

Genetic alterations defining NSCLC subtypes and their therapeutic implications

Lung cancer is the leading cause of cancer death worldwide, accounting for more deaths than breast, prostate and colon cancer combined. While treatment decisions are determined primarily by stage, therapeutically non small cell lung cancer (NSCLC) has traditionally been treated as a single disease. However, recent findings have led to the recognition of histology and molecular subtypes as important determinants in treatment selection. Identifying the genetic differences that define these molecular and histological subtypes has the potential to impact treatment and as such is currently the focus of much research. Microarray and genomic sequencing efforts have provided unparalleled insight into the genomes of lung cancer subtypes, specifically adenocarcinoma (AC) and squamous cell carcinoma (SqCC), revealing subtype specific genomic alterations and molecular subtypes as well as differences in cell signaling pathways. In this review, we discuss the recurrent genomic alterations characteristic of AC and SqCC (including molecular subtypes), their therapeutic implications and emerging clinical practices aimed at tailoring treatments based on a tumor's molecular alterations with the hope of improving patient response and survival.

An exploration of pathways involved in lung carcinoid progression using gene expression profiling

Pulmonary carcinoids comprise a well-differentiated subset of neuroendocrine tumors usually associated with a favorable prognosis, but mechanisms underlying disease progression are poorly understood. In an explorative approach to identify pathways associated with progression, we compared gene expression profiles of tumors from five patients with a favorable and five with a poor disease outcome. Differentially expressed genes were validated using quantitative real-time PCR on 65 carcinoid tumors, in combination with survival analysis. One of the identified pathways was further examined using immunohistochemistry. As compared with other chromosomal locations, a significantly higher number of genes downregulated in carcinoids with a poor prognosis were located at chromosome 11q (P = 0.00017), a region known to be frequently lost in carcinoids. In addition, a number of upregulated genes were found involved in the mitotic spindle checkpoint, the chromosomal passenger complex (CPC), mitotic kinase CDC2 activity and the BRCA-Fanconi anemia pathway. At the individual gene level, BIRC5 (survivin), BUB1, CD44, IL20RA, KLK12 and OTP were independent predictors of patient outcome. For survivin, the number of positive nuclei was also related to poor prognosis within the group of carcinoids. Aurora B kinase and survivin, major components of the CPC, were particularly upregulated in high-grade carcinomas and may therefore comprise therapeutic targets for these tumors. To our knowledge, this is the first expression profiling study focusing specifically on pulmonary carcinoids and progression. We have identified novel pathways underlying malignant progression and validated several genes as being strong prognostic indicators, some of which could serve as putative therapeutic targets.

Prediction of lung cancer histological types by RT-qPCR gene expression in FFPE specimens

Lung cancer histologic diagnosis is clinically relevant because there are histology-specific treatment indications and contraindications. Histologic diagnosis can be challenging owing to tumor characteristics, and it has been shown to have less-than-ideal agreement among pathologists reviewing the same specimens. Microarray profiling studies using frozen specimens have shown that histologies exhibit different gene expression trends; however, frozen specimens are not amenable to routine clinical application. Herein, we developed a gene expression-based predictor of lung cancer histology for FFPE specimens, which are routinely available in clinical settings. Genes predictive of lung cancer histologies were derived from published cohorts that had been profiled by microarrays. Expression of these genes was measured by quantitative RT-PCR (RT-qPCR) in a cohort of patients with FFPE lung cancer. A histology expression predictor (HEP) was developed using RT-qPCR expression data for adenocarcinoma, carcinoid, small cell carcinoma, and squamous cell carcinoma. In cross-validation, the HEP exhibited mean accuracy of 84% and κ = 0.77. In separate independent validation sets, the HEP was compared with pathologist diagnoses on the same tumor block specimens, and the HEP yielded similar accuracy and precision as the pathologists. The HEP also exhibited good performance in specimens with low tumor cellularity. Therefore, RT-qPCR gene expression from FFPE specimens can be effectively used to predict lung cancer histology.

Genome-wide identification of cancer-related polyadenylated and non-polyadenylated RNAs in human breast and lung cell lines

Eukaryotic mRNAs consist of two forms of transcripts: poly(A)+ and poly(A)-, based on the presence or absence of poly(A) tails at the 3' end. Poly(A)+ mRNAs are mainly protein coding mRNAs, whereas the functions of poly(A)- mRNA are largely unknown. Previous studies have shown that a significant proportion of gene transcripts are poly(A)- or bimorphic (containing both poly(A)+ and poly(A)- transcripts). We compared the expression levels of poly(A)- and poly(A)+ RNA mRNAs in normal and cancer cell lines. We also investigated the potential functions of these RNA transcripts using an integrative workflow to explore poly(A)+ and poly(A)- transcriptome sequences between a normal human mammary gland cell line (HMEC) and a breast cancer cell line (MCF-7), as well as between a normal human lung cell line (NHLF) and a lung cancer cell line (A549). The data showed that normal and cancer cell lines differentially express these two forms of mRNA. Gene ontology (GO) annotation analyses hinted at the functions of these two groups of transcripts and grouped the differentially expressed genes according to the form of their transcript. The data showed that cell cycle-, apoptosis-, and cell death-related functions corresponded to most of the differentially expressed genes in these two forms of transcripts, which were also associated with the cancers. Furthermore, translational elongation and translation functions were also found for the poly(A)- protein-coding genes in cancer cell lines. We demonstrate that poly(A)- transcripts play an important role in cancer development.

Understanding cellular mechanisms underlying airway epithelial repair: selecting the most appropriate animal models

Understanding the mechanisms underlying the process of regeneration and repair of airway epithelial structures demands close characterization of the associated cellular and molecular events. The choice of an animal model system to study these processes and the role of lung stem cells is debatable since ideally the chosen animal model should offer a valid comparison with the human lung. Species differences may include the complex three-dimensional lung structures, cellular composition of the lung airway as well as transcriptional control of the molecular events in response to airway epithelium regeneration, and repair following injury. In this paper, we discuss issues related to the study of the lung repair and regeneration including the role of putative stem cells in small- and large-animal models. At the end of this paper, the author discuss the potential for using sheep as a model which can help bridge the gap between small-animal model systems and humans.

Expression of G protein-coupled receptor 19 in human lung cancer cells is triggered by entry into S-phase and supports G(2)-M cell-cycle progression

It has long been known that G protein-coupled receptors (GPCR) are subject to illegitimate expression in tumor cells. Presumably, hijacking the normal physiologic functions of GPCRs contributes to all biologic capabilities acquired during tumorigenesis. Here, we searched for GPCRs that were expressed in lung cancer: the mRNA encoding orphan G protein-coupled receptor 19 (GPR19) was found frequently overexpressed in tissue samples obtained from patients with small cell lung cancer. Several observations indicate that overexpression of Gpr19 confers a specific advantage to lung cancer cells by accelerating transition through the cell-cycle. (i) Knockdown of Gpr19 mRNA by RNA interference reduced cell growth of human lung cancer cell lines. (ii) Cell-cycle progression through G(2)-M-phase was impaired in cells transfected with siRNAs directed against Gpr19 and this was associated with increased protein levels of cyclin B1 and phosphorylated histone H3. (iii) The expression levels of Gpr19 mRNA varied along the cell-cycle with a peak observed in S-phase. (iv) The putative control of Gpr19 expression by E2F transcription factors was verified by chromatin immunoprecipitation: antibodies directed against E2F-1 to -4 allowed for the recovery of the Gpr19 promoter. (v) Removal of E2F binding sites in the Gpr19 promoter diminished the expression of a luciferase reporter. (vi) E2f and Gpr19 expression correlated in lung cancer patient samples. To the best of knowledge, this is the first example of a GPCR showing cell-cycle-specific mRNA expression. Our data also validate GPR19 as a candidate target when overexpressed in lung cancer.

The role of pseudokinases in cancer

Kinases play a critical role in regulating many cellular functions including development, differentiation and proliferation. To date, over 518 proteins with kinase activity, comprising ~2-3% of total cellular proteins, have been identified from within the human kinome. Interestingly, approximately 10% of kinases are categorised as pseudokinases since they lack one or more conserved catalytic residues within their kinase domain and were originally thought to have no enzymatic activity. Recently, there has been strong evidence to suggest that some pseudokinsases can not only function as scaffold proteins, but may also possess kinase activity leading to modulation of cell signalling pathways. Altered activity of these pseudokinases can result in impaired cellular function, particularly in malignancies. In this review we are discussing recent evidence that apart from a scaffolding role, pseudokinases also orchestrate cellular processes as active kinases per se in signalling pathways of malignant cells.

Molecular and cellular biology of neuroendocrine lung tumors: evidence for separate biological entities

Pulmonary neuroendocrine tumors (NETs) are traditionally described as comprising a spectrum of neoplasms, ranging from low grade typical carcinoids (TCs) via the intermediate grade atypical carcinoids (ACs) to the highly malignant small cell lung cancers (SCLCs) and large cell neuroendocrine carcinomas (LCNECs). Recent data, however, suggests that two categories can be distinguished on basis of molecular and clinical data, i.e. the high grade neuroendocrine (NE) carcinomas and the carcinoid tumors. Bronchial carcinoids and SCLCs may originate from the same pulmonary NE precursor cells, but a precursor lesion has only been observed in association with carcinoids, termed diffuse idiopathic pulmonary neuroendocrine cell hyperplasia. The occurrence of mixed tumors exclusively comprising high grade NE carcinomas also supports a different carcinogenesis for these two groups. Histopathologically, high grade NE lung tumors are characterized by high mitotic and proliferative indices, while carcinoids are defined by maximally 10 mitoses per 2mm(2) (10 high-power fields) and rarely have Ki67-proliferative indices over 10%. High grade NE carcinomas are chemosensitive tumors, although they usually relapse. Surgery is often not an option due to extensive disease at presentation and early metastasis, especially in SCLC. Conversely, carcinoids are often insensitive to chemo- and radiation therapy, but cure can usually be achieved by surgery. A meta-analysis of comparative genomic hybridization studies performed for this review, as well as gene expression profiling data indicates separate clustering of carcinoids and carcinomas. Chromosomal aberrations are much more frequent in carcinomas, except for deletion of 11q, which is involved in the whole spectrum of NE lung tumors. Deletions of chromosome 3p are rare in carcinoids but are a hallmark of the high grade pulmonary NE carcinomas. On the contrary, mutations of the multiple endocrine neoplasia type 1 (MEN1) gene are restricted to carcinoid tumors. Many of the differences between carcinoids and high grade lung NETs can be ascribed to tobacco consumption, which is strongly linked to the occurrence of high grade NE carcinomas. Smoking causes p53 mutations, very frequently present in SCLCs and LCNECs, but rarely in carcinoids. It further results in other early genetic events in SCLCs and LCNECs, such as 3p and 17p deletions. Smoking induces downregulation of E-cadherin and associated epithelial to mesenchymal transition. Also, high grade lung NETs display higher frequencies of aberrations of the Rb pathway, and of the intrinsic and extrinsic apoptotic routes. Carcinoid biology on the other hand is not depending on cigarette smoke intake but rather characterized by aberrations of other specific genetic events, probably including Menin or its targets and interaction partners. This results in a gradual evolution, most likely from proliferating pulmonary NE cells via hyperplasia and tumorlets towards classical carcinoid tumors. We conclude that carcinoids and high grade NE lung carcinomas are separate biological entities and do not comprise one spectrum of pulmonary NETs. This implies the need to reconsider both diagnostic as well as therapeutic approaches for these different groups of malignancies.

Anterior gradient 2 overexpression in lung adenocarcinoma

The histologic subtyping of the 2 major histotypes of nonsmall-cell lung cancer, that is, adenocarcinoma (AdC) and squamous cell carcinoma (SCC), is crucial to therapeutic decision making, but making this distinction can be a challenge. Querying the Oncomine database pinpointed anterior gradient 2 (AGR2) as being upregulated in lung AdC. On applying both quantitative real-time polymerase chain reaction and immunohistochemistry, this study tested the reliability of AGR2 status as a histotype-specific marker of lung AdC. AGR2 immunohistochemistry expression was semiquantitatively assessed in 120 cases of lung cancer (60 AdCs, 60 SCCs); 35 additional tissue samples from non-neoplastic lungs were considered as normal controls. To further support our findings, the expression of AGR2 mRNA was tested by quantitative real-time polymerase chain reaction in 30 of the considered cases (10 AdCs, 10 SCCs, and 10 normal lungs). AGR2 was consistently expressed in normal bronchial/bronchiolar columnar cells. Cases of AdC always expressed the protein (staining moderately in 30% and strongly in 70%), whereas none of the SCC cases strongly expressed AGR2 (staining was negative in 55%, weak in 33%, and moderate in 12%). AGR2 mRNA was significantly overexpressed in AdCs by comparison with SCCs (P=0.003) or normal lung tissue (P=0.002). AGR2 is upregulated in lung AdC (by comparison with either SCC or normal bronchial/bronchiolar columnar cells). AGR2 protein expression may support the histologic subtyping of nonsmall-cell lung cancer and be of clinical value in differentiating lung AdC from SCC.

Metagenes associated with survival in non-small cell lung cancer

NSCLC (non-small cell lung cancer) comprises about 80% of all lung cancer cases worldwide. Surgery is most effective treatment for patients with early-stage disease. However, 30%-55% of these patients develop recurrence within 5 years. Therefore, markers that can be used to accurately classify early-stage NSCLC patients into different prognostic groups may be helpful in selecting patients who should receive specific therapies.A previously published dataset was used to evaluate gene expression profiles of different NSCLC subtypes. A moderated two-sample t-test was used to identify differentially expressed genes between all tumor samples and cancer-free control tissue, between SCC samples and AC/BC samples and between stage I tumor samples and all other tumor samples. Gene expression microarray measurements were validated using qRT-PCR.Bayesian regression analysis and Kaplan-Meier survival analysis were performed to determine metagenes associated with survival. We identified 599 genes which were down-regulated and 402 genes which were up-regulated in NSCLC compared to the normal lung tissue and 112 genes which were up-regulated and 101 genes which were down-regulated in AC/BC compared to the SCC. Further, for stage Ib patients the metagenes potentially associated with survival were identified.Genes that expressed differently between normal lung tissue and cancer showed enrichment in gene ontology terms which were associated with mitosis and proliferation. Bayesian regression and Kaplan-Meier analysis showed that gene-expression patterns and metagene profiles can be applied to predict the probability of different survival outcomes in NSCLC patients.

Involvement of aryl hydrocarbon receptor signaling in the development of small cell lung cancer induced by HPV E6/E7 oncoproteins

Background

Lung cancers consist of four major types that and for clinical-pathological reasons are often divided into two broad categories: small cell lung cancer (SCLC) and non-small cell lung cancer (NSCLC). All major histological types of lung cancer are associated with smoking, although the association is stronger for SCLC and squamous cell carcinoma than adenocarcinoma. To date, epidemiological studies have identified several environmental, genetic, hormonal and viral factors associated with lung cancer risk. It has been estimated that 15-25% of human cancers may have a viral etiology. The human papillomavirus (HPV) is a proven cause of most human cervical cancers, and might have a role in other malignancies including vulva, skin, oesophagus, head and neck cancer. HPV has also been speculated to have a role in the pathogenesis of lung cancer. To validate the hypothesis of HPV involvement in small cell lung cancer pathogenesis we performed a gene expression profile of transgenic mouse model of SCLC induced by HPV-16 E6/E7 oncoproteins.

Methods

Gene expression profile of SCLC has been performed using Agilent whole mouse genome (4 × 44k) representing ~ 41000 genes and mouse transcripts. Samples were obtained from two HPV16-E6/E7 transgenic mouse models and from littermate's normal lung. Data analyses were performed using GeneSpring 10 and the functional classification of deregulated genes was performed using Ingenuity Pathway Analysis (Ingenuity^® Systems, http://www.ingenuity.com).

Results

Analysis of deregulated genes induced by the expression of E6/E7 oncoproteins supports the hypothesis of a linkage between HPV infection and SCLC development. As a matter of fact, comparison of deregulated genes in our system and those in human SCLC showed that many of them are located in the Aryl Hydrocarbon Receptor Signal transduction pathway.

Conclusions

In this study, the global gene expression of transgenic mouse model of SCLC induced by HPV-16 E6/E7 oncoproteins led us to identification of several genes involved in SCLC tumor development. Furthermore, our study reveled that the Aryl Hydrocarbon Receptor Signaling is the primarily affected pathway by the E6/E7 oncoproteins expression and that this pathway is also deregulated in human SCLC. Our results provide the basis for the development of new therapeutic approaches against human SCLC.