Differential expression of immune-regulatory proteins C5AR1, CLEC4A and NLRP3 on peripheral blood mononuclear cells in early-stage non-small cell lung cancer patients.

Changes in gene expression profiling of peripheral blood mononuclear cells (PBMC) appear to represent the host's response to the cancer cells via paracrine signaling. We speculated that protein expression on circulating T-lymphocytes represent T-lymphocyte trafficking before infiltration into the tumor microenvironment. The possibility of using protein expression on circulating T-lymphocytes as a biomarker to discriminate early-stage non-small cell lung cancer (NSCLC) was explored. Four independent PBMC gene expression microarray datasets (GSE12771, GSE13255, GSE20189 and GSE3934) were analyzed. We selected C5AR1, CLEC4A and NLRP3 based on their significant protein expression in tumor-infiltrating lymphocytes, but not in normal lymphoid tissue. A validation study using automated flow cytometry was conducted in 141 study participants including 76 treatment-naive early-stage non-small cell lung cancer patients (NSCLC), 12 individuals with non-malignant pulmonary diseases, and 53 healthy individuals. Median ratios of C5AR1, CLEC4A and NLRP3 specific antibody staining to CD3 positive cells in early-stage NSCLC patients compared to healthy controls were 0.014 [0-0.37] vs. 0.01 [0-0.07, p = 0.13], 0.03 [0-0.87] vs. 0.02 [0-0.13, p = 0.10] and 0.19 [0-0.60] vs. 0.09 [0.02-0.31, p < 0.0001], respectively. Median fluorescence intensity (MFI) of CD3+C5AR1+, CD3+CLEC4A+ and CD3+NLRP3+ expression in early-stage NSCLC patients compared to healthy volunteers was 185 [64.2-4801] vs. 107.5 [27-229, p < 0.0001], 91.2 [42.4-2355] vs. 71.25 [46.2-103, p = 0.0005], and 1585 [478-5224] vs. 758.5 [318-1976, p < 0.0001], respectively. NLRP3:CD3 ratio, CD3+C5AR1+, CD3+CLEC4A+ and CD3+NLRP3+ MFI were significantly higher in early-stage NSCLC than healthy volunteers with an area under the ROC curve of 0.69-0.76. The CD3+NLRP3+ MFI provided the most distinguishable expression at 71.5% sensitivity and 70% specificity. Furthermore, CD3+NLRP3+ MFI potentially discriminated between early-stage NSCLC from malignant-mimic inflammation and infection pulmonary disease. Further validation in various pulmonary inflammatory disease might be warranted. Our proof-of-principle findings strengthen the hypothesis that malignancies generate distinctive protein expression fingerprints on circulating T-lymphocytes.

Mononucleotide A-repeats may Play a Regulatory Role in Endothermic Housekeeping Genes.

Background: Coding and non-coding short tandem repeats (STRs) facilitate a great diversity of phenotypic traits. The imbalance of mononucleotide A-repeats around transcription start sites (TSSs) was found in 3 mammals: H. sapiens, M. musculus, and R. norvegicus. Principal Findings: We found that the imbalance pattern originated in some vertebrates. A similar pattern was observed in mammals and birds, but not in amphibians and reptiles. We proposed that the enriched A-repeats upstream of TSSs is a novel hallmark of endotherms or warm-blooded animals. Gene ontology analysis indicates that the primary function of upstream A-repeats involves metabolism, cellular transportation, and sensory perception (smell and chemical stimulus) through housekeeping genes. Conclusions: Upstream A-repeats may play a regulatory role in the metabolic process of endothermic animals.

Co-occurrence CDK4/6 amplification serves as biomarkers of de novo EGFR TKI resistance in sensitizing EGFR mutation non-small cell lung cancer.

Despite the development of predictive biomarkers to shape treatment paradigms and outcomes, de novo EGFR TKI resistance advanced non-small cell lung cancer (NSCLC) remains an issue of concern. We explored clinical factors in 332 advanced NSCLC who received EGFR TKI and molecular characteristics through 65 whole exome sequencing of various EGFR TKI responses including; de novo (progression within 3 months), intermediate response (IRs) and long-term response (LTRs) (durability > 2 years). Uncommon EGFR mutation subtypes were significantly variable enriched in de novo resistance. The remaining sensitizing EGFR mutation subtypes (exon 19 del and L858R) accounted for 75% of de novo resistance. Genomic landscape analysis was conducted, focusing in 10 frequent oncogenic signaling pathways with functional contributions; cell cycle, Hippo, Myc, Notch, Nrf2, PI-3-Kinase/Akt, RTK-RAS, TGF-ß, p53 and ß-catenin/Wnt signaling. Cell cycle pathway was the only significant alteration pathway among groups with the FDR p-value of 6 × 10-4. We found only significant q-values of < 0.05 in 7 gene alterations; CDK6, CCNE1, CDK4, CCND3, MET, FGFR4 and HRAS which enrich in de novo resistance [range 36-73%] compared to IRs/LTRs [range 4-22%]. Amplification of CDK4/6 was significant in de novo resistance, contrary to IRs and LTRs (91%, 27.9% and 0%, respectively). The presence of co-occurrence CDK4/6 amplification correlated with poor disease outcome with HR of progression-free survival of 3.63 [95% CI 1.80-7.31, p-value < 0.001]. The presence of CDK4/6 amplification in pretreatment specimen serves as a predictive biomarker for de novo resistance in sensitizing EGFR mutation.

Identification of candidate regulators of mandibular bone loss in FcγRIIB-/- Mice.

Patients with systemic lupus erythematosus (SLE) have increased inflammatory cytokines, leading to periodontitis and alveolar bone loss. However, the mechanisms driving this phenomenon are still unknown. Here, we have identified novel therapeutic targets for and mediators of lupus-mediated bone loss using RNA-sequencing (RNA-seq) in a FcγRIIB-/- mouse model of lupus associated osteopenia. A total of 2,710 upregulated and 3,252 downregulated DEGs were identified. The GO and KEGG annotations revealed that osteoclast differentiation, bone mineralization, ossification, and myeloid cell development were downregulated. WikiPathways indicated that Hedgehog, TNFα NF-κB and Notch signaling pathway were also decreased. We identified downregulated targets, Sufu and Serpina12, that have important roles in bone homeostasis. Sufu and Serpina12 were related to Hedgehog signaling proteins, including Gli1, Gli2, Gli3, Ptch1, and Ptch2. Gene knockdown analysis demonstrated that Sufu, and Serpina12 contributed to osteoclastogenesis and osteoblastogenesis, respectively. Osteoclast and osteoblast marker genes were significantly decreased in Sufu-deficient and Serpina12-deficient cells, respectively. Our results suggest that alterations in Hedgehog signaling play an important role in the pathogenesis of osteopenia in FcγRIIB-/- mice. The novel DEGs and pathways identified in this study provide new insight into the underlying mechanisms of mandibular bone loss during lupus development.

Targeting multiple genes containing long mononucleotide A-T repeats in lung cancer stem cells.

BACKGROUND: Intratumour heterogeneous gene expression among cancer and cancer stem cells (CSCs) can cause failure of current targeted therapies because each drug aims to target the function of a single gene. Long mononucleotide A-T repeats are cis-regulatory transcriptional elements that control many genes, increasing the expression of numerous genes in various cancers, including lung cancer. Therefore, targeting A-T repeats may dysregulate many genes driving cancer development. Here, we tested a peptide nucleic acid (PNA) oligo containing a long A-repeat sequence [A(15)] to disrupt the transcriptional control of the A-T repeat in lung cancer and CSCs. METHODS: First, we separated CSCs from parental lung cancer cell lines. Then, we evaluated the role of A-T repeat gene regulation by counting the number of repeats in differentially regulated genes between CSCs and the parental cells of the CSCs. After testing the dosage and effect of PNA-A15 on normal and cancer cell toxicity and CSC phenotypes, we analysed genome-wide expression to identify dysregulated genes in CSCs. RESULTS: The number of A-T repeats in genes differentially regulated between CSCs and parental cells differed. PNA-A15 was toxic to lung cancer cells and CSCs but not to noncancer cells. Finally, PNA-A15 dysregulated a number of genes in lung CSCs. CONCLUSION: PNA-A15 is a promising novel targeted therapy agent that targets the transcriptional control activity of multiple genes in lung CSCs.

Quantitative STAU2 measurement in lymphocytes for breast cancer risk assessment.

Although mammograms play a key role in early breast cancer detection, the test is not applicable to all women, for example, women under the age of 40. The development of a noninvasive blood test with high sensitivity and accessibility will improve the effectiveness of breast cancer screening programmes. Secretory factors released from cancer cells can induce the expression of certain genes in a large number of white blood cells (WBCs). Therefore, cancer-dependent proteins in WBCs can be used as tumour markers with high sensitivity. Five proteins (LMAN1, AZI2, STAU2, MMP9 and PLOD1) from a systemic analysis of a variety of array data of breast cancer patients were subjected to immunofluorescence staining to evaluate the presence of fixed WBCs on 96-well plates from 363 healthy females and 358 female breast cancer patients. The results revealed that the average fluorescence intensity of anti-STAU2 and the percentage of STAU2-positive T and B lymphocytes in breast cancer patients (110.50 ± 23.38 and 61.87 ± 12.44, respectively) were significantly increased compared with those in healthy females (56.47 ± 32.03 and 33.02 ± 18.10, respectively) (p = 3.56 × 10-71, odds ratio = 24.59, 95% CI = 16.64-36.34). The effect of secreted molecules from breast cancer cells was proven by the increase in STAU2 intensity in PBMCs cocultured with MCF-7 and T47D cells at 48 h (p = 0.0289). The test demonstrated 98.32%, 82.96%, and 48.32% sensitivity and 56.47%, 83.47%, and 98.62% specificity in correlation with the percentage of STAU2-positive cells at 40, 53.34 and 63.38, respectively. We also demonstrated how to use the STAU2 test for the assessment of risk in women under the age of 40. STAU2 is a novel breast cancer marker that can be assessed by quantitative immunofluorescence staining of fixed WBCs that are transportable at room temperature via mail, representing a useful risk assessment tool for women without access to mammograms.

Tumor-induced DNA methylation in the white blood cells of patients with colorectal cancer.

The secretions of cancer cells alter epigenetic regulation in cancer stromal cells. The present study investigated the methylation changes in white blood cells (WBCs) caused by the secretions of colorectal cancer (CRC) cells. Changes in the DNA methylation of peripheral blood mononuclear cells (PBMCs) from normal individuals co-cultured with CRC cells were estimated using a methylation microarray. These changes were then compared against the DNA methylation changes and mRNA levels observed in the WBCs of patients with CRC. Procollagen-lysine, 2-oxoglutarate 5-dioxygenase 1 (PLOD1) and matrix metalloproteinase 9 (MMP9) were selected to assess the DNA methylation of the WBCs from CRC patients using real-time methylation-specific PCR. The majority of the genes analyzed presented high levels of mRNA in the WBCs of the patients with CRC and DNA methylation in the co-cultured PBMCs. Intragenic methylation revealed the strongest association (P=8.52×10-21). For validation, MMP9 and PLOD1 were selected and used to test WBCs from 32 patients with CRC and 57 normal controls. The intragenic MMP9 methylation was commonly found (P<0.0001) with high sensitivity (90.63%) and high specificity (96.49%), and a positive predictive value of 93.33% and a negative predictive value of 93.22%. PLOD1 methylation was revealed to have lower sensitivity (30.00%) but higher specificity (97.92%). In addition to circulating WBCs, MMP9 protein expression was observed in infiltrating WBCs and the metastatic lymph nodes of patients with CRC. In conclusion, CRC cells secrete factors that induce genome wide DNA methylation changes in the WBCs of patients with CRC. These changes, including intragenic MMP9 methylation in WBCs, are promising CRC biomarkers to be tested in future CRC screening studies.

Argonaute 4 as an Effector Protein in RNA-Directed DNA Methylation in Human Cells.

DNA methylation of specific genome locations contributes to the distinct functions of multicellular organisms. DNA methylation can be governed by RNA-dependent DNA methylation (RdDM). RdDM is carried out by endogenous small-RNA-guided epigenomic editing complexes that add a methyl group to a precise DNA location. In plants, the Argonaute 4 (AGO4) protein is one of the main catalytic components involved in RdDM. Although small interfering RNA or short hairpin RNA has been shown to be able to guide DNA methylation in human cells, AGO protein-regulated RdDM in humans has not yet been evaluated. This study aimed to identify a key regulatory AGO protein involved in human RdDM by bioinformatics and to explore its function in RdDM by a combination of AGO4 knockdown, Alu small interfering RNA transfection, AGO4-expressing plasmid transfection, chromatin immunoprecipitation, cell-penetrating peptide-tagged AGO4 combined Alu single-guide RNA transfection, and methylation analyses. We found that first, human AGO4 showed stronger genome-wide association with DNA methylation than AGO1-AGO3. Second, endogenous AGO4 depletion demethylated DNA of known AGO4 bound loci. Finally, exogenous AGO4 de novo methylated the bound DNA sequences. Therefore, we discovered that AGO4 plays a role in human RdDM.

Targeting high transcriptional control activity of long mononucleotide A-T repeats in cancer by Argonaute 1.

Epigenetic regulatory changes alter the gene regulation function of DNA repeat elements in cancer and consequently promote malignant phenotypes. Some short tandem repeat sequences, distributed throughout the human genome, can play a role as cis-regulatory elements of the genes. Distributions of tandem long (≥10) and short (<10) A-T repeats in the genome are different depending on gene functions. Long repeats are more commonly found in housekeeping genes and may regulate genes in harmonious fashion. Mononucleotide A-repeats around transcription start sites interact with Argonaute proteins (AGOs) to regulate gene expression. miRNA-bound AGO alterations in cancer have been reported; consequently, these changes would affect genes containing mononucleotide A- and T-repeats. Here, we showed an unprecedented hallmark of gene regulation in cancer. We evaluated the gene expression profiles reported in the Gene Expression Omnibus and found a high density of 13-27 A-T repeats in the up-regulated genes in malignancies derived from the bladder, cervix, head and neck, ovary, vulva, breast, colon, liver, lung, prostate, kidney, thyroid, adrenal gland, bone, blood cells, muscle and brain. Transfection of cell-penetrating protein tag AGO1 containing poly uracils (CPP-AGO1-polyUs) to the lung cancer cell lines altered gene regulation depending on the presence of long A-T repeats. CPP-AGO1-polyUs limited cell proliferation and the ability of a cancer cell to grow into a colony in lung cancer cell lines. In conclusion, long A-T repeats up-regulated many genes in cancer that can be targeted by AGO1 to change the expression of many genes and limited cancer growth.

Nitric oxide promotes cancer cell dedifferentiation by disrupting an Oct4:caveolin-1 complex: A new regulatory mechanism for cancer stem cell formation.

Cancer stem cells (CSCs) are unique populations of cells that can self-renew and generate different cancer cell lineages. Although CSCs are believed to be a promising target for novel therapies, the specific mechanisms by which these putative therapeutics could intervene are less clear. Nitric oxide (NO) is a biological mediator frequently up-regulated in tumors and has been linked to cancer aggressiveness. Here, we search for targets of NO that could explain its activity. We find that it directly affects the stability and function of octamer-binding transcription factor 4 (Oct4), known to drive the stemness of lung cancer cells. We demonstrated that NO promotes the CSC-regulatory activity of Oct4 through a mechanism that involves complex formation between Oct4 and the scaffolding protein caveolin-1 (Cav-1). In the absence of NO, Oct4 forms a molecular complex with Cav-1, which promotes the ubiquitin-mediated proteasomal degradation of Oct4. NO promotes Akt-dependent phosphorylation of Cav-1 at tyrosine 14, disrupting the Cav-1:Oct4 complex. Site-directed mutagenesis and computational modeling studies revealed that the hydroxyl moiety at tyrosine 14 of Cav-1 is crucial for its interaction with Oct4. Both removal of the hydroxyl via mutation to phenylalanine and phosphorylation lead to an increase in binding free energy (ΔGbind) between Oct4 and Cav-1, destabilizing the complex. Together, these results unveiled a novel mechanism of CSC regulation through NO-mediated stabilization of Oct4, a key stem cell transcription factor, and point to new opportunities to design CSC-related therapeutics.

New feature selection for gene expression classification based on degree of class overlap in principal dimensions.

Micro-array data are typically characterized by high dimensional features with a small number of samples. Several problems in identifying genes causing diseases from micro-array data can be transformed into the problem of classifying the features extracted from gene expression in micro-array data. However, too many features can cause low prediction accuracy as well as high computational complexity. Dimensional reduction is a method to eliminate irrelevant features to improve the prediction accuracy. Typically, the eigenvalues or dimensional data variance from principal component analysis are used as criteria to select relevant features. This approach is simple but not efficient since it does not concern the degree of data overlap in each dimension in the feature space. A new method to select relevant features based on degree of dimensional data overlap with proper feature selection was introduced. Furthermore, our study concentrated on small sized data sets which usually occur in reality. The experimental results signified that this new approach can achieve substantially higher prediction accuracy when compared with other methods.

Upstream mononucleotide A-repeats play a cis-regulatory role in mammals through the DICER1 and Ago proteins.

A-repeats are the simplest form of tandem repeats and are found ubiquitously throughout genomes. These mononucleotide repeats have been widely believed to be non-functional 'junk' DNA. However, studies in yeasts suggest that A-repeats play crucial biological functions, and their role in humans remains largely unknown. Here, we showed a non-random pattern of distribution of sense A- and T-repeats within 20 kb around transcription start sites (TSSs) in the human genome. Different distributions of these repeats are observed upstream and downstream of TSSs. Sense A-repeats are enriched upstream, whereas sense T-repeats are enriched downstream of TSSs. This enrichment directly correlates with repeat size. Genes with different functions contain different lengths of repeats. In humans, tissue-specific genes are enriched for short repeats of <10 bp, whereas housekeeping genes are enriched for long repeats of ≥10 bp. We demonstrated that DICER1 and Argonaute proteins are required for the cis-regulatory role of A-repeats. Moreover, in the presence of a synthetic polymer that mimics an A-repeat, protein binding to A-repeats was blocked, resulting in a dramatic change in the expression of genes containing upstream A-repeats. Our findings suggest a length-dependent cis-regulatory function of A-repeats and that Argonaute proteins serve as trans-acting factors, binding to A-repeats.

Candidate cancer-targeting agents identified by expression-profiling arrays.

BACKGROUND: One particularly promising component of personalized medicine in cancer treatment is targeted therapy, which aims to maximize therapeutic efficacy while minimizing toxicity. However, the number of approved targeted agents remains limited. Expression microarray data for different types of cancer are resources to identify genes that were upregulated. The genes are candidate targets for cancer-targeting agents for future anticancer research and targeted treatments. METHODS AND FINDINGS: The gene expression profiles of 48 types of cancer from 2,141 microarrays reported in the Gene Expression Omnibus were analyzed. These data were organized into 78 experimental groups, on which we performed comprehensive analyses using two-tailed Student's t-tests with significance set at P < 0.01 to identify genes that were upregulated compared with normal cells in each cancer type. The resulting list of significantly upregulated genes was cross-referenced with three categories of protein inhibitor targets, categorized by inhibitor type ('Targets of US Food and Drug Administration (FDA)-approved anticancer drugs', 'Targets of FDA-approved nonantineoplastic drugs', or 'Targets of non-FDA-approved chemical agents'). Of the 78 experimental groups studied, 57 (73%) represent cancers that are currently treated with FDA-approved targeted treatment agents. However, the target genes for the indicated therapies are upregulated in only 33 of these groups (57%). Nevertheless, the mRNA expression of the genes targeted by FDA-approved treatment agents is increased in every experimental group, including all of the cancers without FDA-approved targeted treatments. Moreover, many targets of protein inhibitors that have been approved by the FDA as therapies for nonneoplastic diseases, such as 3-hydroxy-3-methylglutaryl-CoA reductase and cyclooxygenase-2 and the targets of many non-FDA-approved chemical agents, such as cyclin-dependent kinase 1 and DNA-dependent protein kinase, are also overexpressed in many types of cancer. CONCLUSION: This research demonstrates a clinical correlation between bioinformatics data and currently approved treatments and suggests novel uses for known protein inhibitors in future antineoplastic research and targeted therapies.

Genes associated with the cis-regulatory functions of intragenic LINE-1 elements.

BACKGROUND: Thousands of intragenic long interspersed element 1 sequences (LINE-1 elements or L1s) reside within genes. These intragenic L1 sequences are conserved and regulate the expression of their host genes. When L1 methylation is decreased, either through chemical induction or in cancer, the intragenic L1 transcription is increased. The resulting L1 mRNAs form RISC complexes with pre-mRNA to degrade the complementary mRNA. In this study, we screened for genes that are involved in intragenic L1 regulation networks. RESULTS: Genes containing L1s were obtained from L1Base (http://l1base.molgen.mpg.de). The expression profiles of 205 genes in 516 gene knockdown experiments were obtained from the Gene Expression Omnibus (GEO) (http://www.ncbi.nlm.nih.gov/geo). The expression levels of the genes with and without L1s were compared using Pearson's chi-squared test. After a permutation based statistical analysis and a multiple hypothesis testing, 73 genes were found to induce significant regulatory changes (upregulation and/or downregulation) in genes with L1s. In detail, 5 genes were found to induce both the upregulation and downregulation of genes with L1s, whereas 27 and 37 genes induced the downregulation and upregulation, respectively, of genes with L1s. These regulations sometimes differed depending on the cell type and the orientation of the intragenic L1s. Moreover, the siRNA-regulating genes containing L1s possess a variety of molecular functions, are responsible for many cellular phenotypes and are associated with a number of diseases. CONCLUSIONS: Cells use intragenic L1s as cis-regulatory elements within gene bodies to modulate gene expression. There may be several mechanisms by which L1s mediate gene expression. Intragenic L1s may be involved in the regulation of several biological processes, including DNA damage and repair, inflammation, immune function, embryogenesis, cell differentiation, cellular response to external stimuli and hormonal responses. Furthermore, in addition to cancer, intragenic L1s may alter gene expression in a variety of diseases and abnormalities.

An omnibus permutation test on ensembles of two-locus analyses can detect pure epistasis and genetic heterogeneity in genome-wide association studies.

This article presents the ability of an omnibus permutation test on ensembles of two-locus analyses (2LOmb) to detect pure epistasis in the presence of genetic heterogeneity. The performance of 2LOmb is evaluated in various simulation scenarios covering two independent causes of complex disease where each cause is governed by a purely epistatic interaction. Different scenarios are set up by varying the number of available single nucleotide polymorphisms (SNPs) in data, number of causative SNPs and ratio of case samples from two affected groups. The simulation results indicate that 2LOmb outperforms multifactor dimensionality reduction (MDR) and random forest (RF) techniques in terms of a low number of output SNPs and a high number of correctly-identified causative SNPs. Moreover, 2LOmb is capable of identifying the number of independent interactions in tractable computational time and can be used in genome-wide association studies. 2LOmb is subsequently applied to a type 1 diabetes mellitus (T1D) data set, which is collected from a UK population by the Wellcome Trust Case Control Consortium (WTCCC). After screening for SNPs that locate within or near genes and exhibit no marginal single-locus effects, the T1D data set is reduced to 95,991 SNPs from 12,146 genes. The 2LOmb search in the reduced T1D data set reveals that 12 SNPs, which can be divided into two independent sets, are associated with the disease. The first SNP set consists of three SNPs from MUC21 (mucin 21, cell surface associated), three SNPs from MUC22 (mucin 22), two SNPs from PSORS1C1 (psoriasis susceptibility 1 candidate 1) and one SNP from TCF19 (transcription factor 19). A four-locus interaction between these four genes is also detected. The second SNP set consists of three SNPs from ATAD1 (ATPase family, AAA domain containing 1). Overall, the findings indicate the detection of pure epistasis in the presence of genetic heterogeneity and provide an alternative explanation for the aetiology of T1D in the UK population.

Small Ancestry Informative Marker panels for complete classification between the original four HapMap populations.

A protocol for the identification of Ancestry Informative Markers (AIMs) from genome-wide Single Nucleotide Polymorphism (SNP) data is proposed. The protocol consists of three main steps: identification of potential positive selection regions via F(ST) extremity measurement, SNP screening via two-stage attribute selection and classification model construction using a Naïve Bayes classifier. The two-stage attribute selection is composed of a newly developed round robin Symmetrical Uncertainty (SU) ranking technique and a wrapper embedded with a Naïve Bayes classifier. The protocol has been applied to the HapMap Phase II data. Two AIM panels, which consist of 10 and 16 SNPs that lead to complete classification between CEU, CHB, JPT and YRI populations, are identified. Moreover, the panels are at least four times smaller than those reported in previous studies. The results suggest that the protocol could be useful in a scenario involving a larger number of populations.

Hypomethylation of intragenic LINE-1 represses transcription in cancer cells through AGO2.

In human cancers, the methylation of long interspersed nuclear element -1 (LINE-1 or L1) retrotransposons is reduced. This occurs within the context of genome wide hypomethylation, and although it is common, its role is poorly understood. L1s are widely distributed both inside and outside of genes, intragenic and intergenic, respectively. Interestingly, the insertion of active full-length L1 sequences into host gene introns disrupts gene expression. Here, we evaluated if intragenic L1 hypomethylation influences their host gene expression in cancer. First, we extracted data from L1base (http://l1base.molgen.mpg.de), a database containing putatively active L1 insertions, and compared intragenic and intergenic L1 characters. We found that intragenic L1 sequences have been conserved across evolutionary time with respect to transcriptional activity and CpG dinucleotide sites for mammalian DNA methylation. Then, we compared regulated mRNA levels of cells from two different experiments available from Gene Expression Omnibus (GEO), a database repository of high throughput gene expression data, (http://www.ncbi.nlm.nih.gov/geo) by chi-square. The odds ratio of down-regulated genes between demethylated normal bronchial epithelium and lung cancer was high (p<1E(-27); OR = 3.14; 95% CI = 2.54-3.88), suggesting cancer genome wide hypomethylation down-regulating gene expression. Comprehensive analysis between L1 locations and gene expression showed that expression of genes containing L1s had a significantly higher likelihood to be repressed in cancer and hypomethylated normal cells. In contrast, many mRNAs derived from genes containing L1s are elevated in Argonaute 2 (AGO2 or EIF2C2)-depleted cells. Hypomethylated L1s increase L1 mRNA levels. Finally, we found that AGO2 targets intronic L1 pre-mRNA complexes and represses cancer genes. These findings represent one of the mechanisms of cancer genome wide hypomethylation altering gene expression. Hypomethylated intragenic L1s are a nuclear siRNA mediated cis-regulatory element that can repress genes. This epigenetic regulation of retrotransposons likely influences many aspects of genomic biology.

Gene hunting of the Genetic Analysis Workshop 16 rheumatoid arthritis data using rough set theory.

We propose to use the rough set theory to identify genes affecting rheumatoid arthritis risk from the data collected by the North American Rheumatoid Arthritis Consortium. For each gene, we employ generalized dynamic reducts in the rough set theory to select a subset of single-nucleotide polymorphisms (SNPs) to represent the genetic information from this gene. We then group the study subjects into different clusters based on their genotype similarity at the selected markers. Statistical association between disease status and cluster membership is then studied to identify genes associated with rheumatoid arthritis. Based on our proposed approach, we are able to identify a number of statistically significant genes associated with rheumatoid arthritis. Aside from genes on chromosome 6, our identified genes include known disease-associated genes such as PTPN22 and TRAF1. In addition, our list contains other biologically plausible genes, such as ADAM15 and AGPAT2. Our findings suggest that ADAM15 and AGPAT2 may contribute to a genetic predisposition through abnormal angiogenesis and adipose tissue.

Two-stage joint selection method to identify candidate markers from genome-wide association studies.

The interaction among multiple genes and environmental factors can affect an individual's susceptibility to disease. Some genes may not show strong marginal associations when they affect disease risk through interactions with other genes. As a result, these genes may not be identified by single-marker methods that are widely used in genome-wide association studies. To explore this possibility in real data, we carried out a two-stage model selection procedure of joint single-nucleotide polymorphism (SNP) analysis to detect genes associated with rheumatoid arthritis (RA) using Genetic Analysis Workshop 16 genome-wide association study data. In the first stage, the genetic markers were screened through an exhaustive two-dimensional search, through which promising SNP and SNP pairs were identified. Then, LASSO was used to choose putative SNPs from the candidates identified in the first stage. We then use the RA data collected by the Wellcome Trust Case Control Consortium to validate the putative genetic factors. Balancing computational load and statistical power, this method detects joint effects that may fail to emerge from single-marker analysis. Based on our proposed approach, we not only replicated the identification of important RA risk genes, but also found novel genes and their epistatic effects on RA. To our knowledge, this is the first two-dimensional scan based analysis for a real genome-wide association study.

A pathway analysis applied to Genetic Analysis Workshop 16 genome-wide rheumatoid arthritis data.

The identification of several hundred genomic regions affecting disease risk has proven the ability of genome-wide association studies have proven their ability to identify genetic contributors to disease. Currently, single-nucleotide polymorphism (SNP) association analysis is the most widely used method of genome-wide association data, but recent research shows that multi-marker tests of association may provide greater power, especially when more than one mutation is present within a gene and the mutations are in low linkage disequilibrium with each other. Here we use a multi-marker association test based on regression to SNPs located within known genes to obtain a gene-level score of association. We then perform pathway analysis using this score as a measure of gene importance. We use two tests of pathway enrichment - a binomial test and a random set method. By utilizing publicly available gene and pathway information, we identify B cell, cytokine and inflammation response, and antigen presentation pathways as being associated with rheumatoid arthritis. These results confirm known biological mechanisms for auto-immunity disorders, of which rheumatoid arthritis is one.