Abnormal gene expression and gene fusion in lung adenocarcinoma with high-throughput RNA sequencing

Predicting the Lung Adenocarcinoma and Its Biomarkers by Integrating Gene Expression and DNA Methylation Data

The early symptoms of lung adenocarcinoma patients are inapparent, and the clinical diagnosis of lung adenocarcinoma is primarily through X-ray examination and pathological section examination, whereas the discovery of biomarkers points out another direction for the diagnosis of lung adenocarcinoma with the development of bioinformatics technology. However, it is not accurate and trustworthy to diagnose lung adenocarcinoma due to omics data with high-dimension and low-sample size (HDLSS) features or biomarkers produced by utilizing only single omics data. To address the above problems, the feature selection methods of biological analysis are used to reduce the dimension of gene expression data (GSE19188) and DNA methylation data (GSE139032, GSE49996). In addition, the Cartesian product method is used to expand the sample set and integrate gene expression data and DNA methylation data. The classification is built by using a deep neural network and is evaluated on K-fold cross validation. Moreover, gene ontology analysis and literature retrieving are used to analyze the biological relevance of selected genes, TCGA database is used for survival analysis of these potential genes through Kaplan-Meier estimates to discover the detailed molecular mechanism of lung adenocarcinoma. Survival analysis shows that COL5A2 and SERPINB5 are significant for identifying lung adenocarcinoma and are considered biomarkers of lung adenocarcinoma.

Identification of a Sixteen-gene Prognostic Biomarker for Lung Adenocarcinoma Using a Machine Learning Method

Objectives: Lung adenocarcinoma (LUAD) accounts for a majority of cancer-related deaths worldwide annually. The identification of prognostic biomarkers and prediction of prognosis for LUAD patients is necessary. Materials and Methods: In this study, LUAD RNA-Seq data and clinical data from the Cancer Genome Atlas (TCGA) were divided into TCGA cohort I (n = 338) and II (n = 168). The cohort I was used for model construction, and the cohort II and data from Gene Expression Omnibus (GSE72094 cohort, n = 393; GSE11969 cohort, n = 149) were utilized for validation. First, the survival-related seed genes were selected from the cohort I using the machine learning model (random survival forest, RSF), and then in order to improve prediction accuracy, the forward selection model was utilized to identify the prognosis-related key genes among the seed genes using the clinically-integrated RNA-Seq data. Second, the survival risk score system was constructed by using these key genes in the cohort II, the GSE72094 cohort and the GSE11969 cohort, and the evaluation metrics such as HR, p value and C-index were calculated to validate the proposed method. Third, the developed approach was compared with the previous five prediction models. Finally, bioinformatics analyses (pathway, heatmap, protein-gene interaction network) have been applied to the identified seed genes and key genes. Results and Conclusion: Based on the RSF model and clinically-integrated RNA-Seq data, we identified sixteen key genes that formed the prognostic gene expression signature. These sixteen key genes could achieve a strong power for prognostic prediction of LUAD patients in cohort II (HR = 3.80, p = 1.63e-06, C-index = 0.656), and were further validated in the GSE72094 cohort (HR = 4.12, p = 1.34e-10, C-index = 0.672) and GSE11969 cohort (HR = 3.87, p = 6.81e-07, C-index = 0.670). The experimental results of three independent validation cohorts showed that compared with the traditional Cox model and the use of standalone RNA-Seq data, the machine-learning-based method effectively improved the prediction accuracy of LUAD prognosis, and the derived model was also superior to the other five existing prediction models. KEGG pathway analysis found eleven of the sixteen genes were associated with Nicotine addiction. Thirteen of the sixteen genes were reported for the first time as the LUAD prognosis-related key genes. In conclusion, we developed a sixteen-gene prognostic marker for LUAD, which may provide a powerful prognostic tool for precision oncology.

GWAS Follow-up Study Discovers a Novel Genetic Signal on 10q21.2 for Atopic Dermatitis in Chinese Han Population

Atopic dermatitis (AD) is a common inflammatory skin disease with high heritability. Two susceptibility loci have been confirmed in our previous AD genome-wide association study (GWAS). To look for additional genetic factors in Chinese Han ethnicity, we performed a large-scale GWAS follow-up study. Forty-nine top single nucleotide polymorphisms (SNPs) that had never been reported previously were genotyped using Sequenom Massarray system in an independent cohort, which consist of northern Chinese (1634 cases and 1263 controls) and southern Chinese (2985 cases and 9526 controls). Association analyses were performed using PLINK 2 software. Three SNPs in northern and ten SNPs in southern were found exhibiting association evidence with AD (P < 0.05). Finally, SNP rs224108 on 10q21.2 showed high significance for AD in joint analysis of GWAS and replication study (P_meta = 4.55 × 10⁻⁹, OR = 1.21), and was confirmed as an independent genetic marker by Linkage disequilibrium calculation and conditional logistic regression analysis. Bioinformatics analysis strongly suggested that rs224108 may have the potential to alter the target gene expression through non-coding epigenetic regulation effects. Meanwhile, SNP rs11150780 on 17q25.3 was also found suggestive association with AD (P_meta = 7.64 × 10⁻⁷, OR = 1.18). Our findings confirmed a novel susceptibility signal on 10q21.2 for AD in Chinese Han population and advanced the understanding of the genetic contribution to AD.

RNA sequencing uncovers the key long non-coding RNAs and potential molecular mechanism contributing to XAV939-mediated inhibition of non-small cell lung cancer

The present study aimed to reveal the key long non-coding RNAs (lncRNAs) and the potential molecular mechanisms of XAV939 treatment in non-small cell lung cancer (NSCLC). The NSCLC cell line, NCI-H1299, was cultured with 10 µM XAV939 for 12 h, and NCI-H1299 cells without XAV939 treatment were used as controls. Following RNA isolation from the two groups, RNA-sequencing was performed to detect transcript expression levels, and differentially-expressed lncRNAs (DE-lncRNAs) and DE-genes (DEGs) were identified between groups and analyzed for their functions and associated pathways. The potential associations between proteins encoded by DEGs were revealed via a protein-protein interaction (PPI) network. Subsequently, the microRNA (miRNA/miR)-mRNA, lncRNA-miRNA and lncRNA-mRNA interactions were explored, followed by competing endogenous RNA (ceRNA) network construction. A total of 396 DEGs and 224 DE-lncRNAs were identified between the XAV939 and control groups. These lncRNAs were mainly enriched in pathways such as ‘ferroptosis’ [DEG, solute carrier family 7 member 11 (SLC7A11)]. The PPI network consisted of 97 nodes and 112 interactions. Furthermore, a total of 10 noteworthy lncRNAs were revealed in the DE-lncRNA-DEG interaction. Finally, the lncRNA-miRNA-mRNA regulatory association, including MIR503 host gene (MIR503HG)-miR1273c-SRY-box 4 (SOX4), was explored in the current ceRNA network. The downregulation of lncRNA MIR503HG induced by XAV939 may serve an important role in NSCLC suppression via sponging miR-1273c and regulating SOX4 expression. Furthermore, the downregulation of SLC7A11 induced by XAV939 may also inhibit the development of NSCLC via the ferroptosis pathway.

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.

Identification of transcription factors that may reprogram lung adenocarcinoma

BACKGROUND

Lung adenocarcinoma is one of most threatening disease to human health. Although many efforts have been devoted to its genetic study, few researches have been focused on the transcription factors which regulate tumor initiation and progression by affecting multiple downstream gene transcription. It is proved that proper transcription factors may mediate the direct reprogramming of cancer cells, and reverse the tumorigenesis on the epigenetic and transcription levels.

METHODS

In this paper, a computational method is proposed to identify the core transcription factors that can regulate as many as possible lung adenocarcinoma associated genes with as little as possible redundancy. A greedy strategy is applied to find the smallest collection of transcription factors that can cover the differentially expressed genes by its downstream targets. The optimal subset which is mostly enriched in the differentially expressed genes is then selected.

RESULTS

Seven core transcription factors (MCM4, VWF, ECT2, RBMS3, LIMCH1, MYBL2 and FBXL7) are detected, and have been reported to contribute to tumorigenesis of lung adenocarcinoma. The identification of the transcription factors provides a new insight into its oncogenic role in tumor initiation and progression, and benefits the discovery of functional core set that may reverse malignant transformation and reprogram cancer cells.

Disease onset and aging in the world of circular RNAs

Circular ribonucleic acids (circRNAs) are non-coding RNAs of approximately 100 nucleotides in length with thousands of members in mammalian cells. The presence of circRNAs is believed to be even greater than that of messenger RNAs. Identification of circRNAs occurred approximately 37 years ago with the subsequent demonstration that covalent bonds are necessary for the unique circular structure of these ribonucleic acids. However, present understanding of the complex biological role of circRNAs remains limited and requires further elucidation. CircRNAs may impact aging, multiple disorders, function as biomarkers, and are able to regulate gene expression by acting as effective microRNA (miRNA) sponges. New work suggests that circRNAs are vital for the modulation of cellular senescence and programmed cell death pathways such as apoptosis. These non-coding RNAs can control cell cycle progression, cellular proliferation, and cellular survival impacting disorders linked to aging, cardiovascular disease, and atherosclerosis through pathways that involve cyclin-dependent kinase 2 (CDK2), cyclin-dependent kinase inhibitor 1 (p21), and mammalian forkhead transcription factors. In addition, circRNAs can oversee cellular metabolism and disorders such as diabetes mellitus through the regulation of insulin signaling as well as limit tumor progression through Wnt signaling and β-catenin pathways. Further understanding of the biology of circRNAs offers great promise for the targeting of novel strategies against a wide spectrum of disease entities.

Regeneration in the nervous system with erythropoietin

Globally, greater than 30 million individuals are afflicted with disorders of the nervous system accompanied by tens of thousands of new cases annually with limited, if any, treatment options. Erythropoietin (EPO) offers an exciting and novel therapeutic strategy to address both acute and chronic neurodegenerative disorders. EPO governs a number of critical protective and regenerative mechanisms that can impact apoptotic and autophagic programmed cell death pathways through protein kinase B (Akt), sirtuins, mammalian forkhead transcription factors, and wingless signaling. Translation of the cytoprotective pathways of EPO into clinically effective treatments for some neurodegenerative disorders has been promising, but additional work is necessary. In particular, development of new treatments with erythropoiesis-stimulating agents such as EPO brings several important challenges that involve detrimental vascular outcomes and tumorigenesis. Future work that can effectively and safely harness the complexity of the signaling pathways of EPO will be vital for the fruitful treatment of disorders of the nervous system.

Comparative transcriptome analysis reveals that the extracellular matrix receptor interaction contributes to the venous metastases of hepatocellular carcinoma

Hepatocellular carcinoma (HCC) is the most common type of liver cancer in the world. Portal vein tumor thrombus (PVTT) is one of the most serious complications of HCC and is strongly correlated with a poor prognosis for HCC patients. However, the detailed mechanism of PVTT development remains to be explored. In this study, we present a large-scale transcriptome analysis, by RNA sequencing, of 11 patients diagnosed with HCC with PVTT. The dysregulated genes between HCC and PVTT suggested that the extracellular matrix receptor interaction was correlated with the venous metastases of HCC. Among all of the recurrent alternative splicing events, we identified exon 6 skipping of RPS24, which is likely to be a cancer driver. We also identified five common fusion genes between HCC and its corresponding PVTT samples, including ARID1A-GPATCH3, MDM1-NUP107, PTGES3-RARG, PRLR-TERT, and C9orf3-TMC1. All of these findings broaden our knowledge of PVTT development and may also contribute to the diagnosis and treatment of HCC patients with PVTT.

FoxO proteins in the nervous system

Acute as well as chronic disorders of the nervous system lead to significant morbidity and mortality for millions of individuals globally. Given the ability to govern stem cell proliferation and differentiated cell survival, mammalian forkhead transcription factors of the forkhead box class O (FoxO) are increasingly being identified as potential targets for disorders of the nervous system, such as Alzheimer's disease, Parkinson's disease, Huntington's disease, amyotrophic lateral sclerosis, and auditory neuronal disease. FoxO proteins are present throughout the body, but they are selectively expressed in the nervous system and have diverse biological functions. The forkhead O class transcription factors interface with an array of signal transduction pathways that include protein kinase B (Akt), serum- and glucocorticoid-inducible protein kinase (SgK), IκB kinase (IKK), silent mating type information regulation 2 homolog 1 (S. cerevisiae) (SIRT1), growth factors, and Wnt signaling that can determine the activity and integrity of FoxO proteins. Ultimately, there exists a complex interplay between FoxO proteins and their signal transduction pathways that can significantly impact programmed cell death pathways of apoptosis and autophagy as well as the development of clinical strategies for the treatment of neurodegenerative disorders.

Introduction to RNA-Seq and its applications to drug discovery and development

Preclinical Research RNA sequencing (RNA-Seq) is a novel high-throughput technology for comprehensive transcriptome study. It can measure the expression levels of thousands of genes simultaneously and provide insight into functional pathways and regulations in biological processes. In addition, RNA-Seq can provide copious information on alternative splicing, allele-specific expression, unannotated exons, and novel transcripts (gene or noncoding RNAs). This technology has revolutionized the way biologists examine transcriptomes and has been successfully applied in drug discovery and development, being able to identify drug-related genes, microRNAs, and fusion proteins. In this overview, we will review this technology including data analysis, and its recent applications in drug discovery and development.

Transcription factor and microRNA interactions in lung cells: an inhibitory link between NK2 homeobox 1, miR-200c and the developmental and oncogenic factors Nfib and Myb

BACKGROUND

The transcription factor NK2 homeobox 1 (Nkx2-1) plays essential roles in epithelial cell proliferation and differentiation in mouse and human lung development and tumorigenesis. A better understanding of genes and pathways downstream of Nkx2-1 will clarify the multiple roles of this critical lung factor. Nkx2-1 regulates directly or indirectly numerous protein-coding genes; however, there is a paucity of information about Nkx2-1-regulated microRNAs (miRNAs).

METHODS AND RESULTS

By miRNA array analyses of mouse epithelial cell lines in which endogenous Nkx2-1 was knocked-down, we revealed that 29 miRNAs were negatively regulated including miR-200c, and 39 miRNAs were positively regulated by Nkx2-1 including miR-1195. Mouse lungs lacking functional phosphorylated Nkx2-1 showed increased expression of miR-200c and alterations in the expression of other top regulated miRNAs. Moreover, chromatin immunoprecipitation assays showed binding of NKX2-1 protein to regulatory regions of these miRNAs. Promoter reporter assays indicated that 1kb of the miR-200c 5' flanking region was transcriptionally active but did not mediate Nkx2-1- repression of miR-200c expression. 3'UTR reporter assays support a direct regulation of the predicted targets Nfib and Myb by miR-200c.

CONCLUSIONS

These studies suggest that Nkx2-1 controls the expression of specific miRNAs in lung epithelial cells. In particular, we identified a regulatory link between Nkx2-1, the known tumor suppressor miR-200c, and the developmental and oncogenic transcription factors Nfib and Myb, adding new players to the regulatory mechanisms driven by Nkx2-1 in lung epithelial cells that may have implications in lung development and tumorigenesis.

Next-generation technologies for multiomics approaches including interactome sequencing

The development of high-speed analytical techniques such as next-generation sequencing and microarrays allows high-throughput analysis of biological information at a low cost. These techniques contribute to medical and bioscience advancements and provide new avenues for scientific research. Here, we outline a variety of new innovative techniques and discuss their use in omics research (e.g., genomics, transcriptomics, metabolomics, proteomics, and interactomics). We also discuss the possible applications of these methods, including an interactome sequencing technology that we developed, in future medical and life science research.

Programming apoptosis and autophagy with novel approaches for diabetes mellitus

According to the World Health Organization, diabetes mellitus (DM) in the year 2030 will be ranked the seventh leading cause of death in the world. DM impacts all systems of the body with oxidant stress controlling cell fate through endoplasmic reticulum stress, mitochondrial dysfunction, alterations in uncoupling proteins, and the induction of apoptosis and autophagy. Multiple treatment approaches are being entertained for DM with Wnt1 inducible signaling pathway protein 1 (WISP1), mechanistic target of rapamycin (mTOR), and silent mating type information regulation 2 homolog) 1 (S. cerevisiae) (SIRT1) generating significant interest as target pathways that can address maintenance of glucose homeostasis as well as prevention of cellular pathology by controlling insulin resistance, stem cell proliferation, and the programmed cell death pathways of apoptosis and autophagy. WISP1, mTOR, and SIRT1 can rely upon similar pathways such as AMP activated protein kinase as well as govern cellular metabolism through cytokines such as EPO and oral hypoglycemics such as metformin. Yet, these pathways require precise biological control to exclude potentially detrimental clinical outcomes. Further elucidation of the ability to translate the roles of WISP1, mTOR, and SIRT1 into effective clinical avenues offers compelling prospects for new therapies against DM that can benefit hundreds of millions of individuals throughout the globe.