RNA-seq analysis of lung adenocarcinomas reveals different gene expression profiles between smoking and nonsmoking patients

Expression and Purification of Recombinant ADAMTS8

ADAMTS8 (A Disintegrin-like and Metalloproteinase with Thrombospondin motifs 8) is a secreted zinc-dependent metalloproteinase whose expression is downregulated in a variety of solid tumors. Xenografts expressing high levels of ADAMTS8 have a poor capacity to invade and migrate in nude mice. While this data highlights a beneficial, anti-cancerogenic role of ADAMTS8, the mechanism behind this activity is still not fully elucidated. So far, the only reported substrate for ADAMTS8 is osteopontin (OPN), an extracellular matrix protein widely implicated in multiple steps of cancer progression, albeit, similar to other ADAMTS family members, it is very likely that ADAMTS8 cleaves a variety of substrates. The availability of purified ADAMTS8 may enlighten the biological role of this metalloproteinase.Here we describe methods for expression and purification of recombinant ADAMTS8 in HEK293T cells as well as a convenient assay to test ADAMTS8 proteolytic activity using OPN as a substrate.

Stress, diet, exercise: Common environmental factors and their impact on epigenetic age

Epigenetic aging clocks have gained significant attention as a tool for predicting age-related health conditions in clinical and research settings. They have enabled geroscientists to study the underlying mechanisms of aging and assess the effectiveness of anti-aging therapies, including diet, exercise and environmental exposures. This review explores the effects of modifiable lifestyle factors' on the global DNA methylation landscape, as seen by aging clocks. We also discuss the underlying mechanisms through which these factors contribute to biological aging and provide comments on what these findings mean for people willing to build an evidence-based pro-longevity lifestyle.

A comprehensive assessment of cell type-specific differential expression methods in bulk data

Accounting for cell type compositions has been very successful at analyzing high-throughput data from heterogeneous tissues. Differential gene expression analysis at cell type level is becoming increasingly popular, yielding biomarker discovery in a finer granularity within a particular cell type. Although several computational methods have been developed to identify cell type-specific differentially expressed genes (csDEG) from RNA-seq data, a systematic evaluation is yet to be performed. Here, we thoroughly benchmark six recently published methods: CellDMC, CARseq, TOAST, LRCDE, CeDAR and TCA, together with two classical methods, csSAM and DESeq2, for a comprehensive comparison. We aim to systematically evaluate the performance of popular csDEG detection methods and provide guidance to researchers. In simulation studies, we benchmark available methods under various scenarios of baseline expression levels, sample sizes, cell type compositions, expression level alterations, technical noises and biological dispersions. Real data analyses of three large datasets on inflammatory bowel disease, lung cancer and autism provide evaluation in both the gene level and the pathway level. We find that csDEG calling is strongly affected by effect size, baseline expression level and cell type compositions. Results imply that csDEG discovery is a challenging task itself, with room to improvements on handling low signal-to-noise ratio and low expression genes.

Systematic comparison of ranking aggregation methods for gene lists in experimental results

MOTIVATION

A common experimental output in biomedical science is a list of genes implicated in a given biological process or disease. The gene lists resulting from a group of studies answering the same, or similar, questions can be combined by ranking aggregation methods to find a consensus or a more reliable answer. Evaluating a ranking aggregation method on a specific type of data before using it is required to support the reliability since the property of a dataset can influence the performance of an algorithm. Such evaluation on gene lists is usually based on a simulated database because of the lack of a known truth for real data. However, simulated datasets tend to be too small compared to experimental data and neglect key features, including heterogeneity of quality, relevance and the inclusion of unranked lists.

RESULTS

In this study, a group of existing methods and their variations that are suitable for meta-analysis of gene lists are compared using simulated and real data. Simulated data were used to explore the performance of the aggregation methods as a function of emulating the common scenarios of real genomic data, with various heterogeneity of quality, noise level and a mix of unranked and ranked data using 20 000 possible entities. In addition to the evaluation with simulated data, a comparison using real genomic data on the SARS-CoV-2 virus, cancer (non-small cell lung cancer) and bacteria (macrophage apoptosis) was performed. We summarize the results of our evaluation in a simple flowchart to select a ranking aggregation method, and in an automated implementation using the meta-analysis by information content algorithm to infer heterogeneity of data quality across input datasets.

AVAILABILITY AND IMPLEMENTATION

The code for simulated data generation and running edited version of algorithms: https://github.com/baillielab/comparison_of_RA_methods. Code to perform an optimal selection of methods based on the results of this review, using the MAIC algorithm to infer the characteristics of an input dataset, can be downloaded here: https://github.com/baillielab/maic. An online service for running MAIC: https://baillielab.net/maic.

SUPPLEMENTARY INFORMATION

Supplementary data are available at Bioinformatics online.

Integrated Analysis of Transcriptomic and Genomic Data Reveals Blood Biomarkers With Diagnostic and Prognostic Potential in Non-small Cell Lung Cancer

Background: Lung cancer is the second most common cancer and the main leading cause of cancer-associated death worldwide. Non-small cell lung cancer (NSCLC) accounts for about 85% of lung cancer diagnoses and more than 50% of all lung cancer cases are diagnosed at an advanced stage; hence have poor prognosis. Therefore, it is important to diagnose NSCLC patients reliably and as early as possible in order to reduce the risk of mortality.

Methods: We identified blood-based gene markers for early NSCLC by performing a multi-omics approach utilizing integrated analysis of global gene expression and copy number alterations of NSCLC patients using array-based techniques. We also validated the diagnostic and the prognostic potential of the gene signature using independent datasets with detailed clinical information.

Results: We identified 12 genes that are significantly expressed in NSCLC patients’ blood, at the earliest stages of the disease, and associated with a poor disease outcome. We then validated 12-gene signature’s diagnostic and prognostic value using independent datasets of gene expression profiling of over 1000 NSCLC patients. Indeed, 12-gene signature predicted disease outcome independently of other clinical factors in multivariate regression analysis (HR = 2.64, 95% CI = 1.72–4.07; p = 1.3 × 10−8). Significantly altered functions, pathways, and gene networks revealed alterations in several key genes and cancer-related pathways that may have importance for NSCLC transformation, including FAM83A, ZNF696, UBE2C, RECK, TIMM50, GEMIN7, and XPO5.

Conclusion: Our findings suggest that integrated genomic and network analyses may provide a reliable approach to identify genes that are associated with NSCLC, and lead to improved diagnosis detecting the disease in early stages in patients’ blood instead of using invasive techniques and also have prognostic potential for discriminating high-risk patients from the low-risk ones.

Molecular Pathology of Lung Cancer

This overview of the molecular pathology of lung cancer includes a review of the most salient molecular alterations of the genome, transcriptome, and the epigenome. The insights provided by the growing use of next-generation sequencing (NGS) in lung cancer will be discussed, and interrelated concepts such as intertumor heterogeneity, intratumor heterogeneity, tumor mutational burden, and the advent of liquid biopsy will be explored. Moreover, this work describes how the evolving field of molecular pathology refines the understanding of different histologic phenotypes of non-small-cell lung cancer (NSCLC) and the underlying biology of small-cell lung cancer. This review will provide an appreciation for how ongoing scientific findings and technologic advances in molecular pathology are crucial for development of biomarkers, therapeutic agents, clinical trials, and ultimately improved patient care.

Gene expression profiles and pathway enrichment analysis to identification of differentially expressed gene and signaling pathways in epithelial ovarian cancer based on high-throughput RNA-seq data

Epithelial ovarian cancer (EOC) can be considered as a stressful and challenging disease among all women in the world, which has been associated with a poor prognosis and its molecular pathogenesis has remained unclear. In recent years, RNA Sequencing (RNA-seq) has become a functional and amazing technology for profiling gene expression. In the present study, RNA-seq raw data from Sequence Read Archive (SRA) of six tumor and normal ovarian sample was extracted, and then analysis and statistical interpretation was done with Linux and R Packages from the open-source Bioconductor. Gene Ontology (GO) term enrichment and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway analysis were applied for the identification of key genes and pathways involved in EOC. We identified 1091 Differential Expression Genes (DEGs) which have been reported in various studies of ovarian cancer as well as other types of cancer. Among them, 333 genes were up-regulated and 273 genes were down-regulated. In addition, Differentially Expressed Genes (DEGs) including RPL41, ALDH3A2, ERBB2, MIEN1, RBM25, ATF4, UPF2, DDIT3, HOXB8 and IL17D as well as Ribosome and Glycolysis/Gluconeogenesis pathway have had the potentiality to be used as targets for EOC diagnosis and treatment. In this study, unlike that of any other studies on various cancers, ALDH3A2 was most down-regulated gene in most KEGG pathways, and ATF4 was most up-regulated gene in leucine zipper domain binding term. In the other hand, RPL41 as a regulatory of cellular ATF4 level was up-regulated in many term and pathways and augmentation of ATF4 could justify the increase of RPL41 in the EOC. Pivotal pathways and significant genes, which were identified in the present study, can be used for adaptation of different EOC study. However, further molecular biological experiments and computational processes are required to confirm the function of the identified genes associated with EOC.

Post-translational regulation and proteolytic activity of the metalloproteinase ADAMTS8

A disintegrin-like and metalloprotease domain with thrombospondin type 1 motifs (ADAMTS)8 is a secreted protease, which was recently implicated in pathogenesis of pulmonary arterial hypertension (PAH). However, the substrate repertoire of ADAMTS8 and regulation of its activity are incompletely understood. Although considered a proteoglycanase because of high sequence similarity and close phylogenetic relationship to the proteoglycan-degrading proteases ADAMTS1, 4, 5, and 15, as well as tight genetic linkage with ADAMTS15 on human chromosome 11, its aggrecanase activity was reportedly weak. Several post-translational factors are known to regulate ADAMTS proteases such as autolysis, inhibition by endogenous inhibitors, and receptor-mediated endocytosis, but their impacts on ADAMTS8 are unknown. Here, we show that ADAMTS8 undergoes autolysis at six different sites within its spacer domain. We also found that in contrast to ADAMTS4 and 5, ADAMTS8 levels were not regulated through low-density lipoprotein receptor-related protein 1 (LRP1)-mediated endocytosis. Additionally, ADAMTS8 lacked significant activity against the proteoglycans aggrecan, versican, and biglycan. Instead, we found that ADAMTS8 cleaved osteopontin, a phosphoprotein whose expression is upregulated in PAH. Multiple ADAMTS8 cleavage sites were identified using liquid chromatography–tandem mass spectrometry. Osteopontin cleavage by ADAMTS8 was efficiently inhibited by TIMP-3, an endogenous inhibitor of ADAMTS1, 4, and 5, as well as by TIMP-2, which has no previously reported inhibitory activity against other ADAMTS proteases. These differences in post-translational regulation and substrate repertoire differentiate ADAMTS8 from other family members and may help to elucidate its role in PAH.

Involvement of MicroRNA-1-FAM83A Axis Dysfunction in the Growth and Motility of Lung Cancer Cells

Lung cancer is the most prevalent types of cancer and the leading cause of cancer-related deaths worldwide. Among all cancers, lung cancer has the highest incidence, accompanied by a high mortality rate at the advanced stage. Favorable prognostic biomarkers can effectively increase the survival rate in lung cancer. Our results revealed FAM83A (Family with sequence similarity 83, member A) overexpression in lung cancer tissues compared with adjacent normal tissues. Furthermore, high FAM83A expression was closely associated with poor lung cancer survival. Here, through siRNA transfection, we effectively inhibited FAM83A expression in the lung cancer cell lines H1355 and A549. FAM83A knockdown significantly suppressed the proliferation, migration, and invasion ability of these cells. Furthermore, FAM83A knockdown could suppress Epidermal growth factor receptor (EGFR)/Mitogen-activated protein kinase (MAPK)/Choline kinase alpha (CHKA) signaling activation in A549 and H1355. By using a bioinformatics approach, we found that FAM83A overexpression in lung cancer may result from miR-1-3p downregulation. In summary, we identified a novel miR-1-FAM83A axis could partially modulate the EGFR/choline phospholipid metabolism signaling pathway, which suppressed lung cancer growth and motility. Our findings provide new insights for the development of lung cancer therapeutics.

FAM83A exerts tumor‑suppressive roles in cervical cancer by regulating integrins

Family with sequence similarity 83 member A (FAM83A) has been recently observed to be upregulated in various types of cancer and hypothesized to be serve as an oncogene. The present study aimed to determine the functional roles and the underlying molecular mechanism of FAM83A in cervical cancer. The results demonstrated that although FAM83A expression was increased in cervical cancer compared with normal tissues, the expression levels of FAM83A were decreased in patients with advanced FIGO stage, deep stromal invasion, poor differentiation and/or lymph node metastasis and negatively associated with short survival time of patients with cervical cancer. FAM83A knockdown promoted cell proliferative, migratory and invasive abilities of CaSki and HeLa cells. A mouse xenograft model demonstrated that FAM83A knockdown promoted tumor growth in vivo. Mechanistically, RNA sequencing results revealed that knockdown of FAM83A increased the transcription of genes mainly associated with oncogenesis-associated pathways. In addition, FAM83A knockdown increased the protein levels of α1, α3, α5, β4 and β5 integrins in vitro and in vivo, and the expression of FAM83A was also negatively associated with the levels of these proteins in human cervical cancer tissue samples. In conclusion, the results of the present study suggested that FAM83A may exert a tumor-suppressive role in cervical cancer by suppressing the expression of integrins, which may offer new insight into the biological basis of cervical cancer.

Bioinformatics Analysis to Reveal Potential Differentially Expressed Long Non-Coding RNAs and Genes Associated with Tumour Metastasis in Lung Adenocarcinoma

Background

Due to the onset of metastases, the survival rate of lung adenocarcinoma (LUAD) is still low. In view of this, we performed this study to screen metastasis-associated genes and lncRNAs in LUAD.

Methods

The mRNA and lncRNA expression profiles of 185 metastatic LUAD and 217 non-metastatic LAUD samples were retrieved from the TCGA database and included in this study. The differentially expressed mRNAs (DEmRNAs) and lncRNAs (DElncRNAs) between metastatic samples and non-metastatic samples of LAUD, as well as the cis nearby-targeted DEmRNAs of DElncRNAs and the DElncRNA-DEmRNA co-expression network, were obtained. Quantitative real-time polymerase chain reaction (qRT-PCR) was used to detect the expression levels of selected DEmRNAs. Survival analysis of selected DElncRNAs and DEmRNAs was performed.

Results

In total, 1351 DEmRNAs and 627 DElncRNAs were screened between the LUAD primary tissue samples and metastatic samples. Then, 194 DElncRNA-nearby-targeted DEmRNA pairs and 191 DElncRNA-DEmRNA co-expression pairs were detected. Except for RHCG and KRT81, the expression of the other six DEmRNAs in the qRT-PCR results generally exhibited the same pattern as that in our integrated analysis. The expression of CRHR2, FAM83A-AS1, FAM83A and Z83843.1 was significantly correlated with the overall survival time of patients with metastatic LUAD.

Conclusion

We speculate that two interaction pairs (FAM83A-AS1-FAM83A and Z83843.1-MATR3) and four genes (CRHR2, UGT2B15, CHGB and NEFL) are closely associated with the metastasis of LUAD.

CA-125, CA-153, and CYFRA21-1 as clinical indicators in male lung cancer with ocular metastasis

Despite recent improvements in diagnosis and therapy, lung cancer remains the most common malignant tumor in males, with high morbidity and mortality. As the annual incidence continues to increase worldwide, the prognosis for male patients with lung cancer remains unsatisfactory. Interestingly, smoking is associated with lung cancer and ocular lesions by altering risk factors such as carbohydrate antigen (CA)-125, CA-153 and cytokeratin-19 fragment (CYFRA21-1). A diagnostic standard for serum biomarker levels of ocular metastasis (OM) in males with lung cancer is therefore urgently needed. In this retrospective analysis, we examined the relationship between smoking preference and OM in male patients with lung cancer to identify an independent prognostic factor or establish a quantitative indicated standard for OM using the clinical indexes from 2238 cases of male lung cancer. The combination of CA-125, CA-153 and CYFRA21-1 could help diagnose OM in male lung cancer patients. This finding might lead to more timely diagnosis and effective therapies.

Effect of tobacco smoking on the epigenetic age of human respiratory organs

BACKGROUND

Smoking leads to the aging of organs. However, no studies have been conducted to quantify the effect of smoking on the aging of respiratory organs and the aging-reversing ability of smoking cessation.

RESULTS

We collected genome-wide methylation datasets of buccal cells, airway cells, esophagus tissue, and lung tissue from non-smokers, smokers, and ex-smokers. We used the "epigenetic clock" method to quantify the epigenetic age acceleration in the four organs. The statistical analyses showed the following: (1) Smoking increased the epigenetic age of airway cells by an average of 4.9 years and lung tissue by 4.3 years. (2) After smoking ceased, the epigenetic age acceleration in airway cells (but not in lung tissue) slowed to a level that non-smokers had. (3) The epigenetic age acceleration in airway cells and lung tissue showed no gender difference.

CONCLUSIONS

Smoking can accelerate the epigenetic age of human respiratory organs, but the effect varies among organs and can be reversed by smoking cessation. Our study provides a powerful incentive to reduce tobacco consumption autonomously.

Survival-related risk score of lung adenocarcinoma identified by weight gene co-expression network analysis

The present study aimed to identify the novel biomarkers and underlying molecular mechanisms of lung adenocarcinoma (LAC) to aid in its diagnosis, prognosis, prediction, disease monitoring and emerging therapies. Data from a total of 498 LAC samples were collected from The Cancer Genome Atlas and divided into two sets by stratified randomization based on pathological Tumor-Node-Metastasis stage. The training set was comprised of 348 samples and the validation set was comprised of 150 samples. A total of 123 samples from the training set for patients who completed follow-up were analyzed by weighted gene co-expression network analysis. A module was identified that contained 113 protein-coding genes that were positively associated with overall survival (OS). A least absolute shrinkage and selection operator (LASSO) Cox regression model was constructed and four survival-associated genes (OPN3, GALNT2, FAM83A and KYNU) were retained. Risk score, calculated by the linear combination of each gene expression multiplied by the LASSO coefficient, could successfully discriminate between patients with LAC exhibiting low and high OS time in both sets. The results from the present study indicate that this risk score may contribute to potential diagnostic and therapeutic strategies for LAC management.

Considering smoking status, coexpression network analysis of non-small cell lung cancer at different cancer stages, exhibits important genes and pathways

Non-small cell lung cancer (NSCLC) is the most common subtype of lung cancer among smokers, nonsmokers, women, and young individuals. Tobacco smoking and different stages of the NSCLC have important roles in cancer evolution and require different treatments. Existence of poorly effective therapeutic options for the NSCLC brings special attention to targeted therapies by considering genetic alterations. In this study, we used RNA-Seq data to compare expression levels of RefSeq genes and to find some genes with similar expression levels. We utilized the "Weighted Gene Co-expression Network Analysis" method for three different datasets to create coexpressed genetic modules having relations with the smoking status and different stages of the NSCLC. Our results indicate seven important genetic modules having important associations with the smoking status and cancer stages. Based on investigated genetic modules and their biological explanation, we then identified 13 newly candidate genes and 7 novel transcription factors in association with the NSCLC, the smoking status, and cancer stages. We then examined those results using other datasets and explained our results biologically to illustrate some important genes in relation with the smoking status and metastatic stage of the NSCLC that can bring some crucial information about cancer evolution. Our genetic findings also can be used as some therapeutic targets for different clinical conditions of the NSCLC.

Overexpression of Family with Sequence Similarity 83, Member A (FAM83A) Predicts Poor Clinical Outcomes in Lung Adenocarcinoma

Background

The aim of this study was to explore the expression levels of family with sequence similarity 83, member A (FAM83A) in lung adenocarcinoma (LUAD) and investigate its clinical prognostic value.

Material/Methods

Bioinformatics mining methods were used to predict the differential expression levels of FAM83A mRNA in LUAD and normal lung tissues based on the TCGA and Oncomine databases. Immunohistochemical staining was performed to demonstrate the FAM83A protein expression levels in 83 cases of LUAD combined with paired normal lung tissues. The correlation between clinicopathologic factors and FAM83A differential expression levels in LUAD was explored by the chi-square test. Kaplan-Meier univariate and Cox multivariate survival analyses were performed to investigate the clinical prognostic value of FAM83A expression in LUAD patients.

Results

Results from TCGA and Oncomine databases revealed that FAM83A mRNA expression level was significantly higher in LUAD than that in normal lung tissues (both P<0.05). Immunohistochemical findings demonstrated that the high positive rate of FAM83A in LUAD was 73.49% (61/83), while that of matched normal lung tissues was only 22.89% (19/83). Moreover, LUAD patients with FAM83A mRNA or high protein levels had dramatically lower OS times than those with FAM83A mRNA or low protein levels (All P<0.05). Lastly, Cox multivariate survival analysis showed that FAM83A differential expression level (low vs. high) was the only independent factor predicting the prognosis of LUAD patients (P=0.001).

Conclusions

FAM83A was overexpressed in LUAD, and FAM83A overexpression could be used as an independent factor of poor prognosis in LUAD patients.

Sequence variant analysis of RNA sequences in severe equine asthma

Background

Severe equine asthma is a chronic inflammatory disease of the lung in horses similar to low-Th2 late-onset asthma in humans. This study aimed to determine the utility of RNA-Seq to call gene sequence variants, and to identify sequence variants of potential relevance to the pathogenesis of asthma.

Methods

RNA-Seq data were generated from endobronchial biopsies collected from six asthmatic and seven non-asthmatic horses before and after challenge (26 samples total). Sequences were aligned to the equine genome with Spliced Transcripts Alignment to Reference software. Read preparation for sequence variant calling was performed with Picard tools and Genome Analysis Toolkit (GATK). Sequence variants were called and filtered using GATK and Ensembl Variant Effect Predictor (VEP) tools, and two RNA-Seq predicted sequence variants were investigated with both PCR and Sanger sequencing. Supplementary analysis of novel sequence variant selection with VEP was based on a score of <0.01 predicted with Sorting Intolerant from Tolerant software, missense nature, location within the protein coding sequence and presence in all asthmatic individuals. For select variants, effect on protein function was assessed with Polymorphism Phenotyping 2 and screening for non-acceptable polymorphism 2 software. Sequences were aligned and 3D protein structures predicted with Geneious software. Difference in allele frequency between the groups was assessed using a Pearson’s Chi-squared test with Yates’ continuity correction, and difference in genotype frequency was calculated using the Fisher’s exact test for count data.

Results

RNA-Seq variant calling and filtering correctly identified substitution variants in PACRG and RTTN. Sanger sequencing confirmed that the PACRG substitution was appropriately identified in all 26 samples while the RTTN substitution was identified correctly in 24 of 26 samples. These variants of uncertain significance had substitutions that were predicted to result in loss of function and to be non-neutral. Amino acid substitutions projected no change of hydrophobicity and isoelectric point in PACRG, and a change in both for RTTN. For PACRG, no difference in allele frequency between the two groups was detected but a higher proportion of asthmatic horses had the altered RTTN allele compared to non-asthmatic animals.

Discussion

RNA-Seq was sensitive and specific for calling gene sequence variants in this disease model. Even moderate coverage (<10–20 counts per million) yielded correct identification in 92% of samples, suggesting RNA-Seq may be suitable to detect sequence variants in low coverage samples. The impact of amino acid alterations in PACRG and RTTN proteins, and possible association of the sequence variants with asthma, is of uncertain significance, but their role in ciliary function may be of future interest.

A Bayesian latent variable approach to aggregation of partial and top-ranked lists in genomic studies

In genomic research, it is becoming increasingly popular to perform meta-analysis, the practice of combining results from multiple studies that target a common essential biological problem. Rank aggregation, a robust meta-analytic approach, consolidates such studies at the rank level. There exists extensive research on this topic, and various methods have been developed in the past. However, these methods have two major limitations when they are applied in the genomic context. First, they are mainly designed to work with full lists, whereas partial and/or top-ranked lists prevail in genomic studies. Second, the component studies are often clustered, and the existing methods fail to utilize such information. To address the above concerns, a Bayesian latent variable approach, called BiG, is proposed to formally deal with partial and top-ranked lists and incorporate the effect of clustering. Various reasonable prior specifications for variance parameters in hierarchical models are carefully studied and compared. Simulation results demonstrate the superior performance of BiG compared with other popular rank aggregation methods under various practical settings. A non-small-cell lung cancer data example is analyzed for illustration.

Meta-analysis of mRNA expression profiles to identify differentially expressed genes in lung adenocarcinoma tissue from smokers and non-smokers

Compared to other types of lung cancer, lung adenocarcinoma patients with a history of smoking have a poor prognosis during the treatment of lung cancer. How lung adenocarcinoma-related genes are differentially expressed between smoker and non-smoker patients has yet to be fully elucidated. We performed a meta-analysis of four publicly available microarray datasets related to lung adenocarcinoma tissue in patients with a history of smoking using R statistical software. The top 50 differentially expressed genes (DEGs) in smoking vs. non‑smoking patients are shown using heat maps. Additionally, we conducted KEGG and GO analyses. In addition, we performed a PPI network analysis for 8 genes that were selected during a previous analysis. We identified a total of 2,932 DEGs (1,806 upregulated, 1,126 downregulated) and five genes (CDC45, CDC20, ANAPC7, CDC6, ESPL1) that may link lung adenocarcinoma to smoking history. Our study may provide new insights into the complex mechanisms of lung adenocarcinoma in smoking patients, and our novel gene expression signatures will be useful for future clinical studies.

Environmental perturbations lead to extensive directional shifts in RNA processing

Environmental perturbations have large effects on both organismal and cellular traits, including gene expression, but the extent to which the environment affects RNA processing remains largely uncharacterized. Recent studies have identified a large number of genetic variants associated with variation in RNA processing that also have an important role in complex traits; yet we do not know in which contexts the different underlying isoforms are used. Here, we comprehensively characterized changes in RNA processing events across 89 environments in five human cell types and identified 15,300 event shifts (FDR = 15%) comprised of eight event types in over 4,000 genes. Many of these changes occur consistently in the same direction across conditions, indicative of global regulation by trans factors. Accordingly, we demonstrate that environmental modulation of splicing factor binding predicts shifts in intron retention, and that binding of transcription factors predicts shifts in alternative first exon (AFE) usage in response to specific treatments. We validated the mechanism hypothesized for AFE in two independent datasets. Using ATAC-seq, we found altered binding of 64 factors in response to selenium at sites of AFE shift, including ELF2 and other factors in the ETS family. We also performed AFE QTL mapping in 373 individuals and found an enrichment for SNPs predicted to disrupt binding of the ELF2 factor. Together, these results demonstrate that RNA processing is dramatically changed in response to environmental perturbations through specific mechanisms regulated by trans factors.

[Omics technologies in diagnostics of lung adenocarcinoma]

To date lung adenocarcinoma (LAC) is the most common type of lung cancer. Numerous studies on LAC biology resulted in identification of crucial mutations in protooncogenes and activating neoplastic transformation pathways. Therapeutic approaches that significantly increase the survival rate of patients with LAC of different etiology have been developed and introduced into clinical practice. However, the main problem in the treatment of LAC is early diagnosis, taking into account both factors and mechanisms responsible in tumor initiation and progression. Identification of a wide biomarker repertoire with high specificity and reliability of detection appears to be a solution to this problem. In this context, proteins with differential expression in normal and pathological condition, suitable for detection in biological fluids are the most promising biomarkers. In this review we have analyzed literature data on studies aimed at search of LAC biomarkers. The major attention has been paid to protein biomarkers as the most promising and convenient subject of clinical diagnosis. The review also summarizes existing knowledge on posttranslational modifications, splice variants, isoforms, as well as model systems and transcriptome changes in LAC.

Impaired response of the bronchial epithelium to inflammation characterizes severe equine asthma

BACKGROUND

Severe equine asthma is a naturally occurring lung inflammatory disease of mature animals characterized by neutrophilic inflammation, bronchoconstriction, mucus hypersecretion and airway remodeling. Exacerbations are triggered by inhalation of dust and microbial components. Affected animals eventually are unable of aerobic performance. In this study transcriptomic differences between asthmatic and non-asthmatic animals in the response of the bronchial epithelium to an inhaled challenge were determined.

RESULTS

Paired endobronchial biopsies were obtained pre- and post-challenge from asthmatic and non-asthmatic animals. The transcriptome, determined by RNA-seq and analyzed with edgeR, contained 111 genes differentially expressed (DE) after challenge between horses with and without asthma, and 81 of these were upregulated. Genes involved in neutrophil migration and activation were in central location in interaction networks, and related gene ontology terms were significantly overrepresented. Relative abundance of specific gene products as determined by immunohistochemistry was correlated with differential gene expression. Gene sets involved in neutrophil chemotaxis, immune and inflammatory response, secretion, blood coagulation and apoptosis were overrepresented among up-regulated genes, while the rhythmic process gene set was overrepresented among down-regulated genes. MMP1, IL8, TLR4 and MMP9 appeared to be the most important proteins in connecting the STRING protein network of DE genes.

CONCLUSIONS

Several differentially expressed genes and networks in horses with asthma also contribute to human asthma, highlighting similarities between severe human adult and equine asthma. Neutrophil activation by the bronchial epithelium is suggested as the trigger of the inflammatory cascade in equine asthma, followed by epithelial injury and impaired repair and differentiation. Circadian rhythm dysregulation and the sonic Hedgehog pathway were identified as potential novel contributory factors in equine asthma.

A comparative study of rank aggregation methods for partial and top ranked lists in genomic applications

Rank aggregation (RA), the process of combining multiple ranked lists into a single ranking, has played an important role in integrating information from individual genomic studies that address the same biological question. In previous research, attention has been focused on aggregating full lists. However, partial and/or top ranked lists are prevalent because of the great heterogeneity of genomic studies and limited resources for follow-up investigation. To be able to handle such lists, some ad hoc adjustments have been suggested in the past, but how RA methods perform on them (after the adjustments) has never been fully evaluated. In this article, a systematic framework is proposed to define different situations that may occur based on the nature of individually ranked lists. A comprehensive simulation study is conducted to examine the performance characteristics of a collection of existing RA methods that are suitable for genomic applications under various settings simulated to mimic practical situations. A non-small cell lung cancer data example is provided for further comparison. Based on our numerical results, general guidelines about which methods perform the best/worst, and under what conditions, are provided. Also, we discuss key factors that substantially affect the performance of the different methods.

FAM83 family oncogenes are broadly involved in human cancers: an integrative multi-omics approach

The development of novel targeted therapies for cancer treatment requires identification of reliable targets. FAM83 (‘family with sequence similarity 83’) family members A, B, and D were shown recently to have oncogenic potential. However, the overall oncogenic abilities of FAM83 family genes remain largely unknown. Here, we used a systematic and integrative genomics approach to investigate oncogenic properties of the entire FAM83 family members. We assessed transcriptional expression patterns of eight FAM83 family genes (FAM83A‐H) across tumor types, the relationship between their expression and changes in DNA copy number, and the association with patient survival. By comparing the gene expression levels of FAM83 family members in cancers from 17 different tumor types with those in their corresponding normal tissues, we identified consistent upregulation of FAM83D and FAM83H across the majority of tumor types, which is largely driven by increased DNA copy number. Importantly, we found also that a higher expression level of a signature of FAM83 family members was associated with poor prognosis in a number of human cancers. In breast cancer, we found that alterations in FAM83 family genes correlated significantly with TP53 mutation, whereas significant, but inverse correlation was observed with PIK3CA and CDH1 (E‐cadherin) mutations. We also identified that expression levels of 55 proteins were significantly associated with alterations in FAM83 family genes including a decrease in GATA3, ESR1, and PGR proteins in tumors with alterations in FAM83. Our results provide strong evidence for a critical role of FAM83 family genes in tumor development, with possible relevance for therapeutic target development.