Identification of Biomarkers and Molecular Pathways Implicated in Smoking and COVID-19 Associated Lung Cancer Using Bioinformatics and Machine Learning Approaches

Lung cancer (LC) is a significant global health issue, with smoking as the most common cause. Recent epidemiological studies have suggested that individuals who smoke are more susceptible to COVID-19. In this study, we aimed to investigate the influence of smoking and COVID-19 on LC using bioinformatics and machine learning approaches. We compared the differentially expressed genes (DEGs) between LC, smoking, and COVID-19 datasets and identified 26 down-regulated and 37 up-regulated genes shared between LC and smoking, and 7 down-regulated and 6 up-regulated genes shared between LC and COVID-19. Integration of these datasets resulted in the identification of ten hub genes (SLC22A18, CHAC1, ROBO4, TEK, NOTCH4, CD24, CD34, SOX2, PITX2, and GMDS) from protein-protein interaction network analysis. The WGCNA R package was used to construct correlation network analyses for these shared genes, aiming to investigate the relationships among them. Furthermore, we also examined the correlation of these genes with patient outcomes through survival curve analyses. The gene ontology and pathway analyses were performed to find out the potential therapeutic targets for LC in smoking and COVID-19 patients. Moreover, machine learning algorithms were applied to the TCGA RNAseq data of LC to assess the performance of these common genes and ten hub genes, demonstrating high performances. The identified hub genes and molecular pathways can be utilized for the development of potential therapeutic targets for smoking and COVID-19-associated LC.

Identification of biomarkers, pathways, and therapeutic targets for EGFR-TKI resistance in NSCLC

This study aimed to map the hub genes and potential pathways that might be involved in the molecular pathogenesis of EGFR-TKI resistance in NSCLC. We performed bioinformatics analysis to identify differentially expressed genes, their function, gene interactions, and pathway analysis between EGFR-TKI-sensitive and EGFR-TKI-resistant patient-derived xenotransplantation samples based on Gene Expression Omnibus database. Survival analysis was performed via the GEPIA database (GEO). The relationship between the key gene ITGAM and the therapeutic candidates was retrieved from DGIdb. A total of 1,302 differentially expressed genes were identified based on GEO. The PPI network highlighted 10 potential hub genes. Only ITGAM was linked to poor DSF in NSCLC patients. A total of 10 drugs were predicted to be potential therapeutics for NSCLC with EGFR-TKI resistance. This study indicates the hub genes related to EGFR-TKI resistance in NSCLC through bioinformatics technologies which can improve the understanding of the mechanisms of EGFR-TKI resistance and provide novel insights into therapeutics.

Function and prognostic value of basement membrane -related genes in lung adenocarcinoma

Background: Lung adenocarcinoma (LUAD) has become a common cause of cancer-related death. Many studies have shown that the basement membrane (BM) is associated with the development of cancer. However, BM-related gene expression and its relationship to LUAD prognosis remains unclear. Methods: BM-related genes from previous studies were used. Clinical and mRNA expression information were obtained from TCGA database. Cox, minimum absolute contraction, and selection operator regression were applied to analyze the selected genes affecting LUAD prognosis. A prognostic-risk model was then established. Furthermore, this study applied Kaplan-Meier analysis to assess the outcomes of high- and low-risk groups, then explored their differences in drug sensitivity. The DSigDB database was used to screen for therapeutic small-molecule drugs. Results: Fourteen prognostic models based on BM-related genes were successfully constructed and validated in patients with LUAD. We also found that independence was a prognostic factor in all 14 BM-based models. Functional analysis showed that the enrichment of BM-related genes mainly originated from signaling pathways related to cancer. The BM-based model also suggested that immune cell infiltration is associated with checkpoints. The low-risk patients may benefit from cyclopamine and docetaxel treatments. Conclusion: This study identified a reliable biomarker to predict survival in patients with LUAD and offered new insights into the function of BM-related genes in LUAD.

Identification of Angiogenesis-Related Prognostic Biomarkers Associated With Immune Cell Infiltration in Breast Cancer

Background: This study aimed to explore the prognostic value of angiogenesis-related genes (ARGs) and their association with immune cell infiltration (ICI) in breast cancer (BC).

Methods: Transcriptome data of BC were obtained from the TCGA and GEO databases. Differentially expressed ARGs were identified by the limma package. The identification of key genes and construction of the risk score model were performed by univariate and multivariate Cox regression algorithms. The prognostic value of the risk score was assessed by ROC curves and nomogram. GO, KEGG pathway, and GSEA were used to investigate the biological functions of differentially expressed genes (DEGs), and CIBERSORT, ssGSEA, and xCell algorithms were performed to estimate the ICI in high-risk and low-risk groups. The correlations between prognostic biomarkers and differentially distributed immune cells were assessed. Moreover, a ceRNA regulatory network based on prognostic biomarkers was constructed and visualized by Cytoscape software.

Results: A total of 18 differentially expressed ARGs were identified between tumor and adjacent normal tissue samples. TNFSF12, SCG2, COL4A3, and TNNI3 were identified as key prognostic genes by univariate and multivariate Cox regression analyses. The risk score model was further constructed based on the four-gene signature and validated in GSE7390 and GSE88770 datasets. ROC curves and nomogram indicated that the risk score had good accuracy for determining BC patient survival. Biological function analysis showed that DEGs in high- and low-risk groups had a high enrichment in immune-related biological processes and signaling pathways. Moreover, significantly different ICIs were found between high- and low-risk groups, such as memory B cells, CD8⁺ T cells, resting memory CD4⁺ T cells, follicular helper T cells, regulatory T cells, monocytes, M2 macrophages, and neutrophils, and each prognostic biomarker was significantly correlated with one or more immune cell types.

Conclusion: The current study identified novel prognostic ARGs and developed a prognostic model for predicting survival in patients with BC. Furthermore, this study indicated that ICI may act as a bond between angiogenesis and BC. These findings enhance our understanding of angiogenesis in BC and provide novel guidance on developing therapeutic targets for BC patients.

EFNA3 as a predictor of clinical prognosis and immune checkpoint therapy efficacy in patients with lung adenocarcinoma

BACKGROUND

Ephrin receptors (Eph) and their ligands, called ephrins, function in various disease processes. However, the expression level and prognostic value of Eph/ephrins in lung adenocarcinoma (LUAD) are still unclear.

METHODS

The Oncomine and GEPIA databases were used to explore the differential expression of Eph/ephrins in LUAD. Kaplan-Meier plotter was selected to explore the prognostic value of Eph/ephrins. The cBioPortal database was used to analyze the genetic variation of the EFNA3 gene. Immunohistochemistry was used to analyze the expression level and clinical value of ephrin-A3 protein in clinical LUAD tissue. Weighted coexpression network analysis (WGCNA) and gene set enrichment analysis (GSEA) identified the potential regulatory mechanism of EFNA3. CCK-8 assays and colony-forming experiments were used to investigate whether EFNA3 can regulate cell proliferation ability in LUAD. Analysis of lactate, ATP, and glucose uptake levels was used to explore the effect of EFNA3 on glycolysis ability. In addition, we investigated the relationship between EFNA3 and tumor infiltrating immune cells (TIICs). Finally, the potential immunotherapy response prediction value of EFNA3 was also explored.

RESULTS

In this study, we found that EFNA3 expression was significantly correlated with both overall survival (OS) and progression-free survival (PFS) in LUAD patients based on a comprehensive analysis of the Eph/Ephrin family. Next, the expression of the EFNA3 protein was increased in LUAD tissues and was designated an independent prognostic risk factor. Mechanistically, EFNA3 may be involved in nuclear division, synaptic function, and ion channel activity-related pathways. In vitro experiments confirmed the role of EFNA3 in promoting LUAD cells and showed that it could regulate glycolytic capacity. Moreover, EFNA3 was negatively associated with immunity, stromal infiltration, and several TIICs. Finally, EFNA3 was found to be positively related to multiple immunotherapy biomarkers.

CONCLUSIONS

In conclusion, increased EFNA3 in LUAD patients predicted worse clinical prognosis, promoted LUAD cell proliferation and glycolysis ability, and was related to immunotherapy response.

Identification of key genes associated with lung adenocarcinoma by bioinformatics analysis

Lung adenocarcinoma (LUAD) is the most common histological type of lung cancer, comprising around 40% of all lung cancer. Until now, the pathogenesis of LUAD has not been fully elucidated. In the current study, we comprehensively analyzed the dysregulated genes in lung adenocarcinoma by mining public datasets. Two sets of gene expression datasets were obtained from the Gene Expression Omnibus (GEO) database. The dysregulated genes were identified by using the GEO2R online tool, and analyzed by R packages, Cytoscape software, STRING, and GPEIA online tools. A total of 275 common dysregulated genes were identified in two independent datasets, including 54 common up-regulated and 221 common down-regulated genes in LUAD. Gene Ontology (GO) enrichment analysis showed that these dysregulated genes were significantly enriched in 258 biological processes (BPs), 27 cellular components (CCs), and 21 molecular functions (MFs). Furthermore, protein-protein interaction (PPI) network analysis showed that PECAM1, ENG, KLF4, CDH5, and VWF were key genes. Survival analysis indicated that the low expression of ENG was associated with poor overall survival (OS) of LUAD patients. The low expression of PECAM1 was associated with poor OS and recurrence-free survival of LUAD patients. The cox regression model developed based on age, tumor stage, ENG, PECAM1 could effectively predict 5-year survival of LUAD patients. This study revealed some key genes, BPs, CCs, and MFs involved in LUAD, which would provide new insights into understanding the pathogenesis of LUAD. In addition, ENG and PECAM1 might serve as promising prognostic markers in LUAD.

Prognostic role of lipid phosphate phosphatases in non-smoker, lung adenocarcinoma patients

Sphingosine-1-phosphate (S1P), a bioactive sphingolipid, plays a crucial role in tumorigenesis. It mediates its function through S1P receptors. A few components of the S1P signaling pathway, such as sphingosine kinase 1 (SphK1) and S1P receptor 1 (S1PR1), have been shown to contribute to lung carcinogenesis. In the present study, using web-based computational tools, we assessed the prognostic roles of eight S1P metabolizing enzymes and five S1P receptors in non-small-cell lung cancer (NSCLC) patients. Except for SPHK1, low expression of S1P metabolizing enzymes was correlated with worse overall survival (OS) in NSCLC patients. Moreover, lower expression of lipid phosphate phosphatase-1 and - 3 (PLPP1 and PLPP3) was significantly associated with worse OS in lung adenocarcinoma (LUAD) and non-smoker NSCLC patients. Furthermore, the UALCAN database analysis showed that mRNA and protein expression of PLPP3 and S1PR1 are significantly down regulated in primary tumors due to hypermethylation of their respective promoters. Expression of PLPP3, S1PR1, and S1PR4 was positively correlated with tumor-infiltrating immune cells in NSCLC patients. These results indicate that S1P signaling genes play a critical prognostic role in LUAD patients. Therefore, this gene signature could be used to predict their prognosis more accurately.

Identification and Analysis of Dysfunctional Genes and Pathways in CD8+ T Cells of Non-Small Cell Lung Cancer Based on RNA Sequencing

Lung cancer, the most common of malignant tumors, is typically of the non-small cell (NSCLC) type. T-cell-based immunotherapies are a promising and powerful approach to treating NSCLCs. To characterize the CD8⁺ T cells of non-small cell lung cancer, we re-analyzed the published RNA-Seq gene expression profiles of 36 CD8⁺ T cell isolated from tumor (TIL) samples and 32 adjacent uninvolved lung (NTIL) samples. With an advanced Monte Carlo method of feature selection, we identified the CD8⁺ TIL specific expression patterns. These patterns revealed the key dysfunctional genes and pathways in CD8⁺ TIL and shed light on the molecular mechanisms of immunity and use of immunotherapy.

Inhibiting expression of Cxcl9 promotes angiogenesis in MSCs-HUVECs co-culture

The insufficient vascularization is a major challenge in bone tissue engineering, leading to partial necrosis of the implant. Pre-vascularization is a promising way via in vitro cells co-culture strategies using osteogenic cells and vasculogenic cells, and the cross-talk of cells is essential. In the present study, the effect of rat bone-marrow derived mesenchymal stem cells (BMSCs) on angiogenic capability of human umbilical vein endothelial cells (HUVECs) in growth medium (GM) and osteogenic induction medium (OIM) was investigated. It was demonstrated that cells co-cultured in OIM showed high efficiency in osteogenesis but failed to form capillary-like structure while the results of co-culture in GM were the opposite. By comparing the angiogenic capacity of co-cultures under GM and OIM, chemokine (C-X-C motif) ligand 9 (Cxcl9), secreted by BMSCs in OIM, was identified to be an angiostatic factor to counter-regulate vascular endothelial growth factor (VEGF) and prevent its binding to HUVECs, which abrogated angiogenesis of MSCs-ECs co-culture. Moreover, Cxcl9 was proved to suppress the osteogenic differentiation of BMSCs monoculture. The molecular mechanism of Cxcl9 activation in BMSCs involved mTOR/STAT1 signaling pathway. Therefore, blocking this signaling pathway via rapamycin addition resulted in the inhibition of Cxcl9 and improvement of osteogenic differentiation and angiogenic capacity of co-culture in OIM. These results reveal that Cxcl9 is a negative modulator of angiogenesis and osteogenesis, and its inhibition could promote pre-vascularization of bone tissue engineering.

A transcriptome-based protein network that identifies new therapeutic targets in colorectal cancer

Background

Colon cancer occurrence is increasing worldwide, making it the third most frequent cancer. Although many therapeutic options are available and quite efficient at the early stages, survival is strongly decreased when the disease has spread to other organs. The identification of molecular markers of colon cancer is likely to help understanding its course and, eventually, to uncover novel genes to be targeted by drugs. In this study, we compared gene expression in a set of 95 human colon cancer samples to that in 19 normal colon mucosae, focusing on 401 genes from 5 selected pathways (Apoptosis, Cancer, Cholesterol metabolism and lipoprotein signaling, Drug metabolism, Wnt/beta-catenin). Deregulation of mRNA levels largely matched that of proteins, leading us to build in silico protein networks, starting from mRNA levels, to identify key proteins central to network activity.

Results

Among the analyzed genes, 10.5% (42) had no reported link with colon cancer, including the SFRP1, IGF1 and ADH1B (down), and MYC and IL8 (up), whose encoded proteins were most interacting with other proteins from the same or even distinct networks. Analyzing all pathways globally led us to uncover novel functional links between a priori unrelated or rather remotely connected pathways, such as the Drug metabolism and the Cancer pathways or, even more strikingly, between the Cholesterol metabolism and lipoprotein signaling and the Cancer pathways. In addition, we analyzed the responsiveness of some of the deregulated genes essential to network activities, to chemotherapeutic agents used alone or in presence of Lovastatin, a lipid-lowering drug. Some of these treatments could oppose the deregulations occurring in cancer samples, including those of the CHECK2, CYP51A1, HMGCS1, ITGA2, NME1 or VEGFA genes.

Conclusions

Our network-based approach allowed discovering genes not previously known to play regulatory roles in colon cancer. Our results also showed that selected drug treatments might revert the cancer-specific deregulation of genes playing prominent roles within the networks operating to maintain colon homeostasis. Among those genes, some could constitute novel testable targets to eliminate colon cancer cells, either directly or, potentially, through the use of lipid-lowering drugs such as statins, in association with selected anticancer drugs.

Electronic supplementary material

The online version of this article (10.1186/s12864-017-4139-y) contains supplementary material, which is available to authorized users.

Comprehensive epigenetic analysis of the signature genes in lung adenocarcinoma

Aim: This study aimed to explore the epigenetic modifications of signature genes in lung adenocarcinoma. Materials & methods: The data of miRNA expression, mRNA expression and DNA methylation were downloaded from The Cancer Genome Atlas. Differential analysis was performed, followed by correlation analysis of miRNA–mRNA and DNA methylation-mRNA. Results: A total of 14 significant inverse correlations between gene expression and DNA methylation were identified, the expressions of which were selected for further validation via GSE27262, displaying similar pattern with that of the integrated analysis. In addition, qRT-PCR results showed that the expression profiling results of six mRNAs and one miRNA were consistent with the findings of integrated analysis. Five genes showed higher diagnostic value, which was also associated with overall survival of patients. Conclusion: Taken together, the epigenetic alterations of signature genes may hold promise for becoming biomarkers for the early detection of lung adenocarcinoma.

Abnormal expression of mRNA, microRNA alteration and aberrant DNA methylation patterns in rectal adenocarcinoma

Aim

Rectal adenocarcinoma (READ) is a malignancy cancer with the high morbidity and motility worldwide. Our study aimed to explore the potential pathogenesis of READ through integrated analysis of gene expression profiling and DNA methylation data.

Methods

The miRNA, mRNA expression profiling and corresponding DNA methylation data were downloaded from The Cancer Genome Atlas (TCGA) database. Differentially expressed mRNAs/ miRNAs/methylated regions (DEmRNA/DEmiRNAs) were identified in READ. The negatively correlation of DEmiRNA-DEmRNAs and DNA methylation-DEmRNAs were obtained. DEmRNAs expression was validated through quantitative real-time polymerase chain reaction (qRT-PCR) and microarray expression profiling analyses.

Results

1192 dysregulated DEmRNAs, 27 dysregulated DEmiRNAs and 6403 aberrant methylation CpG sites were screened in READ compared to normal controls. 1987 negative interaction pairs among 27 DEmiRNAs and 668 DEmRNAs were predicted. 446 genes with aberrant methylation were annotated. Eventually, 50 DEmRNAs (39 down- and 11 up-regulated DEmRNAs) with hypermethylation, synchronously negatively targeted by DEmiRNAs, were identified through the correlation analysis among 446 genes with aberrant methylation and 668 DEmRNAs. 50 DEmRNAs were significantly enriched in cAMP signaling pathway, circadian entrainment and glutamatergic synapse. The validation results of expression levels of DEmRNAs through qRT-PCR and microarray analyses were compatible with our study.

Conclusion

7 genes of SORCS1, PDZRN4, LONRF2, CNGA3, HAND2, RSPO2 and GNAO1 with hypermethylation and negatively regulation by DEmiRNAs might contribute to the tumorigenesis of READ. Our work might provide valuable foundation for the READ in mechanism elucidation, early diagnosis and therapeutic target identification.

CXCL9: evidence and contradictions for its role in tumor progression

Chemokines are a group of low molecular weight peptides. Their major function is the recruitment of leukocytes to inflammation sites, but they also play a key role in tumor growth, angiogenesis, and metastasis. In the last few years, accumulated experimental evidence supports that monokine induced by interferon (IFN)‐gamma (CXCL9), a member of CXC chemokine family and known to attract CXCR3‐ (CXCR3‐A and CXCR3‐B) T lymphocytes, is involved in the pathogenesis of a variety of physiologic diseases during their initiation and their maintenance. This review for the first time presents the most comprehensive summary for the role of CXCL9 in different types of tumors, and demonstrates its contradictory role of CXCL9 in tumor progression. Altogether, this is a useful resource for researchers investigating therapeutic opportunities for cancer.

The MKK7 p.Glu116Lys Rare Variant Serves as a Predictor for Lung Cancer Risk and Prognosis in Chinese

Accumulated evidence indicates that rare variants exert a vital role on predisposition and progression of human diseases, which provides neoteric insights into disease etiology. In the current study, based on three independently retrospective studies of 5,016 lung cancer patients and 5,181 controls, we analyzed the associations between five rare polymorphisms (i.e., p.Glu116Lys, p.Asn118Ser, p.Arg138Cys, p.Ala195Thr and p.Leu259Phe) in MKK7 and lung cancer risk and prognosis. To decipher the precise mechanisms of MKK7 rare variants on lung cancer, a series of biological experiments was further performed. We found that the MKK7 p.Glu116Lys rare polymorphism was significantly associated with lung cancer risk, progression and prognosis. Compared with Glu/Glu common genotype, the 116Lys rare variants (Lys/Glu/+ Lys/Lys) presented an adverse effect on lung cancer susceptibility (odds ratio [OR] = 3.29, 95% confidence interval [CI] = 2.70-4.01). These rare variants strengthened patients' clinical progression that patients with 116Lys variants had a significantly higher metastasis rate and advanced N, M stages at diagnosis. In addition, the patients with 116Lys variants also contributed to worse cancer prognosis than those carriers with Glu/Glu genotype (hazard ratio [HR] = 1.53, 95% CI = 1.32-1.78). Functional experiments further verified that the MKK7 p.116Lys variants altered the expression of several cancer-related genes and thus affected lung cancer cells proliferation, tumor growth and metastasis in vivo and in vitro. Taken together, our findings proposed that the MKK7 p.Glu116Lys rare polymorphism incurred a pernicious impact on lung cancer risk and prognosis through modulating expressions of a serial of cancer-related genes.

Identification of Commonly Dysregulated Genes in Non-small-cell Lung Cancer by Integrated Analysis of Microarray Data and qRT-PCR Validation

BACKGROUND

Non-small-cell lung cancer (NSCLC), the most common lung cancer, leads to the largest number of cancer-related deaths worldwide. There are many studies to identify the differentially expressed genes (DEGs) between NSCLC and normal control (NC) tissues by means of microarray technology. Because of the inconsistency of the microarray data sets, we performed an integrated analysis to identify DEGs and analyzed their biological function.

METHODS AND RESULTS

We combined 15 microarray data sets and identified 1063 DEGs between NSCLC and NC tissues; in addition, we found that the DEGs were enriched in regulation of cell proliferation process and focal adhesion signaling pathway. The protein-protein interaction network analysis for the top 20 significantly DEGs revealed that CAV1, COL1A1, and ADRB2 were the significant hub proteins. Finally, we employed qRT-PCR to validate the meta-analysis approach by determining the expression of the top 10 most significantly DEGs and found that the expression of these genes were significantly different between tumor and NC tissues, in accordance with the results of meta-analysis.

CONCLUSION

qRT-PCR results indicated that the meta-analysis approach in our study was acceptable. Our data suggested that some of the DEGs, including MMP12, COL11A1, THBS2, FAP, and CAV1, may participate in the pathology of NSCLC and could be applied as potential markers or therapeutic targets for NSCLC.

Identification and validation of gene module associated with lung cancer through coexpression network analysis

Lung cancer, a tumor with heterogeneous biology, is influenced by a complex network of gene interactions. Therefore, elucidating the relationships between genes and lung cancer is critical to attain further knowledge on tumor biology. In this study, we performed weighted gene coexpression network analysis to investigate the roles of gene networks in lung cancer regulation. Gene coexpression relationships were explored in 58 samples with tumorous and matched non-tumorous lungs, and six gene modules were identified on the basis of gene coexpression patterns. The overall expression of one module was significantly higher in the normal group than in the lung cancer group. This finding was validated across six datasets (all p values <0.01). The particular module was highly enriched for genes belonging to the biological Gene Ontology category "response to wounding" (adjusted p value = 4.28 × 10(-10)). A lung cancer-specific hub network (LCHN) consisting of 15 genes was also derived from this module. A support vector machine based on classification model robustly separated lung cancer from adjacent normal tissues in the validation datasets (accuracy ranged from 91.7% to 98.5%) by using the LCHN gene signatures as predictors. Eight genes in the LCHN are associated with lung cancer. Overall, we identified a gene module associated with lung cancer, as well as an LCHN consisting of hub genes that may be candidate biomarkers and therapeutic targets for lung cancer. This integrated analysis of lung cancer transcriptome provides an alternative strategy for identification of potential oncogenic drivers.

Identification of mRNAs and lincRNAs associated with lung cancer progression using next-generation RNA sequencing from laser micro-dissected archival FFPE tissue specimens

OBJECTIVES

Adenocarcinoma in situ (AIS) is an intermediate step in the progression of normal lung tissue to invasive adenocarcinoma. However, molecular mechanisms underlying this progression remain to be fully elucidated due to challenges in obtaining fresh clinical samples for downstream analyses. Formalin fixation and paraffin embedding (FFPE) is a tissue preservation system widely used for long-term storage. Until recently, challenges in working with FFPE precluded using new RNA sequencing technologies (RNA-seq), which would help clarify key pathways in cancer progression. Also, isolation techniques including laser-capture micro-dissection provide the ability to select histopathologically distinct tissues, allowing researchers to study transcriptional variations between tightly juxtaposed cell and tissue types.

MATERIALS AND METHODS

Utilizing these technologies and new alignment tools we examined differential expression of long intergenic non-coding RNAs (lincRNAs) and mRNAs across normal, AIS and invasive adenocarcinoma samples from six patients to identify possible markers of lung cancer progression.

RESULTS

RNA extracted and sequenced from these 18 samples generated an average of 198 million reads per sample. After alignment and filtering, uniquely aligned reads represented an average 35% of the total reads. We detected differential expression of a number of lincRNAs and mRNAs when comparing normal to AIS, or AIS to invasive adenocarcinoma. Of these, 5 lincRNAs and 31 mRNAs were consistently up- or down-regulated from normal to AIS and more so to invasive carcinoma. We validated the up-regulation of two mRNAs and one lincRNA by RT-qPCR as proof of principle.

CONCLUSION

Our findings indicate a potential role of not only mRNAs, but also lincRNAs in the progression to invasive adenocarcinoma. We anticipate that these findings will lay the groundwork for future experimental studies of candidate RNAs from FFPE to identify their functional roles in lung cancer.

Systems biology approach to stage-wise characterization of epigenetic genes in lung adenocarcinoma

Background

Epigenetics refers to the reversible functional modifications of the genome that do not correlate to changes in the DNA sequence. The aim of this study is to understand DNA methylation patterns across different stages of lung adenocarcinoma (LUAD).

Results

Our study identified 72, 93 and 170 significant DNA methylated genes in Stages I, II and III respectively. A set of common 34 significant DNA methylated genes located in the promoter section of the true CpG islands were found across stages, and these were: HOX genes, FOXG1, GRIK3, HAND2, PRKCB, etc. Of the total significant DNA methylated genes, 65 correlated with transcription function. The epigenetic analysis identified the following novel genes across all stages: PTGDR, TLX3, and POU4F2. The stage-wise analysis observed the appearance of NEUROG1 gene in Stage I and its re-appearance in Stage III. The analysis showed similar epigenetic pattern across Stage I and Stage III. Pathway analysis revealed important signaling and metabolic pathways of LUAD to correlate with epigenetics. Epigenetic subnetwork analysis identified a set of seven conserved genes across all stages: UBC, KRAS, PIK3CA, PIK3R3, RAF1, BRAF, and RAP1A. A detailed literature analysis elucidated epigenetic genes like FOXG1, HLA-G, and NKX6-2 to be known as prognostic targets.

Conclusion

Integrating epigenetic information for genes with expression data can be useful for comprehending in-depth disease mechanism and for the ultimate goal of better target identification.

Characterization of shear-sensitive genes in the normal rat aorta identifies Hand2 as a major flow-responsive transcription factor

Objective

Shear forces play a key role in the maintenance of vessel wall integrity. Current understanding regarding shear-dependent gene expression is mainly based on in vitro or in vivo observations with experimentally deranged shear, hence reflecting acute molecular events in relation to flow. Our objective was to combine computational fluid dynamic (CFD) simulations with global microarray analysis to study flow-dependent vessel wall biology in the aortic wall under physiological conditions.

Methods and Results

Male Wistar rats were used. Animal-specific wall shear stress (WSS) magnitude and vector direction were estimated using CFD based on aortic geometry and flow information acquired by magnetic resonance imaging. Two distinct flow pattern regions were identified in the normal rat aortic arch; the distal part of the lesser curvature being exposed to low WSS and a non-uniform vector direction, and a region along the greater curvature being subjected to markedly higher levels of WSS and a uniform vector direction. Microarray analysis identified numerous novel mechanosensitive genes, including Trpc4 and Fgf12, and confirmed well-known ones, e.g. Klf2 and Nrf2. Gene ontology analysis revealed an over-representation of genes involved in transcriptional regulation. The most differentially expressed gene, Hand2, is a transcription factor previously shown to be involved in extracellular matrix remodeling. HAND2 protein was endothelial specific and showed higher expression in the regions exposed to low WSS with disturbed flow.

Conclusions

Microarray analysis validated the CFD-defined WSS regions in the rat aortic arch, and identified numerous novel shear-sensitive genes. Defining the functional importance of these genes in relation to atherosusceptibility may provide important insight into the understanding of vascular pathology.

Establishment of a human lung cancer cell line with high metastatic potential to multiple organs: gene expression associated with metastatic potential in human lung cancer

Convenient and reliable multiple organ metastasis model systems might contribute to understanding the mechanism(s) of metastasis of lung cancer, which may lead to overcoming metastasis and improvement in the treatment outcome of lung cancer. We isolated a highly metastatic subline, PC14HM, from the human pulmonary adenocarcinoma cell line, PC14, using an in vivo selection method. The expression of 34,580 genes was compared between PC14HM and parental PC14 by cDNA microarray analysis. Among the differentially expressed genes, expression of four genes in human lung cancer tissues and adjacent normal lung tissues were compared using real-time reverse transcription polymerase chain reaction. Although BALB/c nude mice inoculated with parental PC14 cells had few metastases, almost all mice inoculated with PC14HM cells developed metastases in multiple organs, including the lung, bone and adrenal gland, the same progression seen in human lung cancer. cDNA microarray analysis revealed that 981 genes were differentially (more than 3-fold) expressed between the two cell lines. Functional classification revealed that many of those genes were associated with cell growth, cell communication, development and transcription. Expression of three upregulated genes (HRB-2, HS3ST3A1 and RAB7) was higher in human cancer tissue compared to normal lung tissue, while expression of EDG1, which was downregulated, was lower in the cancer tissue compared to the normal lung. These results suggest that the newly established PC14HM cell line may provide a mouse model of widespread metastasis of lung cancer. This model system may provide insights into the key genetic determinants of widespread metastasis of lung cancer.

Genome-wide host responses against infectious laryngotracheitis virus vaccine infection in chicken embryo lung cells

Background

Infectious laryngotracheitis virus (ILTV; gallid herpesvirus 1) infection causes high mortality and huge economic losses in the poultry industry. To protect chickens against ILTV infection, chicken-embryo origin (CEO) and tissue-culture origin (TCO) vaccines have been used. However, the transmission of vaccine ILTV from vaccinated- to unvaccinated chickens can cause severe respiratory disease. Previously, host cell responses against virulent ILTV infections were determined by microarray analysis. In this study, a microarray analysis was performed to understand host-vaccine ILTV interactions at the host gene transcription level.

Results

The 44 K chicken oligo microarrays were used, and the results were compared to those found in virulent ILTV infection. Total RNAs extracted from vaccine ILTV infected chicken embryo lung cells at 1, 2, 3 and 4 days post infection (dpi), compared to 0 dpi, were subjected to microarray assay using the two color hybridization method. Data analysis using JMP Genomics 5.0 and the Ingenuity Pathway Analysis (IPA) program showed that 213 differentially expressed genes could be grouped into a number of functional categories including tissue development, cellular growth and proliferation, cellular movement, and inflammatory responses. Moreover, 10 possible gene networks were created by the IPA program to show intermolecular connections. Interestingly, of 213 differentially expressed genes, BMP2, C8orf79, F10, and NPY were expressed distinctly in vaccine ILTV infection when compared to virulent ILTV infection.

Conclusions

Comprehensive knowledge of gene expression and biological functionalities of host factors during vaccine ILTV infection can provide insight into host cellular defense mechanisms compared to those of virulent ILTV.