Methylation Markers of Early-Stage Non-Small Cell Lung Cancer
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{"title"=>"Methylation markers of early-stage non-small cell lung cancer", "type"=>"journal", "authors"=>[{"first_name"=>"Kaie", "last_name"=>"Lokk", "scopus_author_id"=>"55270299300"}, {"first_name"=>"Tõnu", "last_name"=>"Vooder", "scopus_author_id"=>"13808183200"}, {"first_name"=>"Raivo", "last_name"=>"Kolde", "scopus_author_id"=>"26534411200"}, {"first_name"=>"Kristjan", "last_name"=>"Välk", "scopus_author_id"=>"37063882100"}, {"first_name"=>"Urmo", "last_name"=>"Võsa", "scopus_author_id"=>"42462595300"}, {"first_name"=>"Retlav", "last_name"=>"Roosipuu", "scopus_author_id"=>"8442831200"}, {"first_name"=>"Lili", "last_name"=>"Milani", "scopus_author_id"=>"56998409700"}, {"first_name"=>"Krista", "last_name"=>"Fischer", "scopus_author_id"=>"7403154309"}, {"first_name"=>"Marina", "last_name"=>"Koltsina", "scopus_author_id"=>"55270299000"}, {"first_name"=>"Egon", "last_name"=>"Urgard", "scopus_author_id"=>"37111500500"}, {"first_name"=>"Tarmo", "last_name"=>"Annilo", "scopus_author_id"=>"6603659613"}, {"first_name"=>"Andres", "last_name"=>"Metspalu", "scopus_author_id"=>"7004697483"}, {"first_name"=>"Neeme", "last_name"=>"Tõnisson", "scopus_author_id"=>"6506585453"}], "year"=>2012, "source"=>"PLoS ONE", "identifiers"=>{"pui"=>"365133264", "sgr"=>"84863085270", "issn"=>"19326203", "pmid"=>"22768131", "scopus"=>"2-s2.0-84863085270", "doi"=>"10.1371/journal.pone.0039813", "isbn"=>"1932-6203 (Electronic) 1932-6203 (Linking)"}, "id"=>"7dbb8d13-c8c5-3a31-ac35-a3aec6e01c85", "abstract"=>"BACKGROUND: Despite of intense research in early cancer detection, there is a lack of biomarkers for the reliable detection of malignant tumors, including non-small cell lung cancer (NSCLC). DNA methylation changes are common and relatively stable in various types of cancers, and may be used as diagnostic or prognostic biomarkers.\\n\\nMETHODS: We performed DNA methylation profiling of samples from 48 patients with stage I NSCLC and 18 matching cancer-free lung samples using microarrays that cover the promoter regions of more than 14,500 genes. We correlated DNA methylation changes with gene expression levels and performed survival analysis.\\n\\nRESULTS: We observed hypermethylation of 496 CpGs in 379 genes and hypomethylation of 373 CpGs in 335 genes in NSCLC. Compared to adenocarcinoma samples, squamous cell carcinoma samples had 263 CpGs in 223 hypermethylated genes and 513 CpGs in 436 hypomethylated genes. 378 of 869 (43.5%) CpG sites discriminating the NSCLC and control samples showed an inverse correlation between CpG site methylation and gene expression levels. As a result of a survival analysis, we found 10 CpGs in 10 genes, in which the methylation level differs in different survival groups.\\n\\nCONCLUSIONS: We have identified a set of genes with altered methylation in NSCLC and found that a minority of them showed an inverse correlation with gene expression levels. We also found a set of genes that associated with the survival of the patients. These newly-identified marker candidates for the molecular screening of NSCLC will need further analysis in order to determine their clinical utility.", "link"=>"http://www.mendeley.com/research/methylation-markers-earlystage-nonsmall-cell-lung-cancer-3", "reader_count"=>30, "reader_count_by_academic_status"=>{"Unspecified"=>1, "Professor > Associate Professor"=>1, "Researcher"=>6, "Student > Doctoral Student"=>3, "Student > Ph. D. Student"=>14, "Student > Postgraduate"=>1, "Student > Master"=>1, "Student > Bachelor"=>2, "Professor"=>1}, "reader_count_by_user_role"=>{"Unspecified"=>1, "Professor > Associate Professor"=>1, "Researcher"=>6, "Student > Doctoral Student"=>3, "Student > Ph. D. Student"=>14, "Student > Postgraduate"=>1, "Student > Master"=>1, "Student > Bachelor"=>2, "Professor"=>1}, "reader_count_by_subject_area"=>{"Unspecified"=>1, "Biochemistry, Genetics and Molecular Biology"=>3, "Medicine and Dentistry"=>8, "Agricultural and Biological Sciences"=>15, "Pharmacology, Toxicology and Pharmaceutical Science"=>1, "Chemistry"=>1, "Computer Science"=>1}, "reader_count_by_subdiscipline"=>{"Medicine and Dentistry"=>{"Medicine and Dentistry"=>8}, "Chemistry"=>{"Chemistry"=>1}, "Agricultural and Biological Sciences"=>{"Agricultural and Biological Sciences"=>15}, "Computer Science"=>{"Computer Science"=>1}, "Biochemistry, Genetics and Molecular Biology"=>{"Biochemistry, Genetics and Molecular Biology"=>3}, "Unspecified"=>{"Unspecified"=>1}, "Pharmacology, Toxicology and Pharmaceutical Science"=>{"Pharmacology, Toxicology and Pharmaceutical Science"=>1}}, "reader_count_by_country"=>{"Cuba"=>1, "Netherlands"=>1, "United States"=>2, "Japan"=>1, "Estonia"=>1}, "group_count"=>1}

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Figshare

  • {"files"=>["https://ndownloader.figshare.com/files/615725"], "description"=>"<p>Distance to TSS of hyper- vs hypomethylated CpGs differed by p = 0.0001 (Welch Two Sample t-test).</p>", "links"=>[], "tags"=>["differentially", "methylated", "cpgs", "transcription", "sites", "fdr", "corrected", "methylation", "nsclc", "tumor-free"], "article_id"=>286194, "categories"=>["Cancer", "Cell Biology", "Genetics"], "users"=>["Kaie Lokk", "Tõnu Vooder", "Raivo Kolde", "Kristjan Välk", "Urmo Võsa", "Retlav Roosipuu", "Lili Milani", "Krista Fischer", "Marina Koltsina", "Egon Urgard", "Tarmo Annilo", "Andres Metspalu", "Neeme Tõnisson"], "doi"=>"https://dx.doi.org/10.1371/journal.pone.0039813.t001", "stats"=>{"downloads"=>4, "page_views"=>20, "likes"=>0}, "figshare_url"=>"https://figshare.com/articles/_Distance_of_differentially_methylated_CpGs_to_the_nearby_transcription_start_sites_TSS_FDR_corrected_p_lt_0_05_mean_difference_in_methylation_level_in_NSCLC_vs_tumor_free_lung_at_least_13_6_/286194", "title"=>"Distance of differentially methylated CpGs to the nearby transcription start sites (TSS, FDR corrected p<0.05, mean difference in methylation level in NSCLC vs tumor-free lung at least 13.6%).", "pos_in_sequence"=>0, "defined_type"=>3, "published_date"=>"2012-06-29 01:43:14"}
  • {"files"=>["https://ndownloader.figshare.com/files/615767"], "description"=>"<p>P-values were computed by permuting individuals and recalculating the median gene expression levels 1,000 times. All CpGs and genes represented by both methylation and gene expression arrays were included in permutations.</p>*<p>- Permuted p-value - p-value computed by permuting individuals and recalculating the median gene expression levels 1,000 times.</p>", "links"=>[], "tags"=>["correlations", "differentially", "methylated", "cpg", "sites", "48", "cancer", "samples"], "article_id"=>286243, "categories"=>["Cancer", "Cell Biology", "Genetics"], "users"=>["Kaie Lokk", "Tõnu Vooder", "Raivo Kolde", "Kristjan Välk", "Urmo Võsa", "Retlav Roosipuu", "Lili Milani", "Krista Fischer", "Marina Koltsina", "Egon Urgard", "Tarmo Annilo", "Andres Metspalu", "Neeme Tõnisson"], "doi"=>"https://dx.doi.org/10.1371/journal.pone.0039813.t002", "stats"=>{"downloads"=>0, "page_views"=>0, "likes"=>0}, "figshare_url"=>"https://figshare.com/articles/_Statistically_significant_Pearson_8217_s_correlations_between_differentially_methylated_CpG_sites_and_gene_expression_values_across_48_lung_cancer_samples_and_the_control_samples_with_available_gene_expression_data_/286243", "title"=>"Statistically significant Pearson’s correlations between differentially methylated CpG sites and gene expression values across 48 lung cancer samples and the control samples with available gene expression data.", "pos_in_sequence"=>0, "defined_type"=>3, "published_date"=>"2012-06-29 01:44:03"}
  • {"files"=>["https://ndownloader.figshare.com/files/615610"], "description"=>"<p>We performed a survival test on each of the CpG sites. The methylation values are divided into 3 groups: low (0–0.25), medium (0.25–0.75) and high (0.75–1). As a result we found 10 CpG sites whose methylation level differs in different survival groups. The x-axis shows survival in years and the y-axis shows overall survival.</p>", "links"=>[], "tags"=>["curves", "10", "differentially", "methylated", "cpg"], "article_id"=>286084, "categories"=>["Cancer", "Cell Biology", "Genetics"], "users"=>["Kaie Lokk", "Tõnu Vooder", "Raivo Kolde", "Kristjan Välk", "Urmo Võsa", "Retlav Roosipuu", "Lili Milani", "Krista Fischer", "Marina Koltsina", "Egon Urgard", "Tarmo Annilo", "Andres Metspalu", "Neeme Tõnisson"], "doi"=>"https://dx.doi.org/10.1371/journal.pone.0039813.g004", "stats"=>{"downloads"=>0, "page_views"=>0, "likes"=>0}, "figshare_url"=>"https://figshare.com/articles/_Survival_curves_of_10_differentially_methylated_CpG_sites_/286084", "title"=>"Survival curves of 10 differentially methylated CpG sites.", "pos_in_sequence"=>0, "defined_type"=>1, "published_date"=>"2012-06-29 01:41:24"}
  • {"files"=>["https://ndownloader.figshare.com/files/615470"], "description"=>"<p>On the y-axis is shown average log2fold-change determined by Illumina array and qRT-PCR (8 sample pairs). Error bars indicate standard error of the mean (SEM).</p>", "links"=>[], "tags"=>["concordance", "microarray", "qrt-pcr"], "article_id"=>285950, "categories"=>["Cancer", "Cell Biology", "Genetics"], "users"=>["Kaie Lokk", "Tõnu Vooder", "Raivo Kolde", "Kristjan Välk", "Urmo Võsa", "Retlav Roosipuu", "Lili Milani", "Krista Fischer", "Marina Koltsina", "Egon Urgard", "Tarmo Annilo", "Andres Metspalu", "Neeme Tõnisson"], "doi"=>"https://dx.doi.org/10.1371/journal.pone.0039813.g003", "stats"=>{"downloads"=>0, "page_views"=>25, "likes"=>0}, "figshare_url"=>"https://figshare.com/articles/_The_concordance_between_microarray_and_qRT_PCR_measurements_/285950", "title"=>"The concordance between microarray and qRT-PCR measurements.", "pos_in_sequence"=>0, "defined_type"=>1, "published_date"=>"2012-06-29 01:39:10"}
  • {"files"=>["https://ndownloader.figshare.com/files/320573", "https://ndownloader.figshare.com/files/320646", "https://ndownloader.figshare.com/files/320685", "https://ndownloader.figshare.com/files/320771", "https://ndownloader.figshare.com/files/320846", "https://ndownloader.figshare.com/files/320859", "https://ndownloader.figshare.com/files/320886", "https://ndownloader.figshare.com/files/320900", "https://ndownloader.figshare.com/files/320906", "https://ndownloader.figshare.com/files/320927", "https://ndownloader.figshare.com/files/320951"], "description"=>"<div><h3>Background</h3><p>Despite of intense research in early cancer detection, there is a lack of biomarkers for the reliable detection of malignant tumors, including non-small cell lung cancer (NSCLC). DNA methylation changes are common and relatively stable in various types of cancers, and may be used as diagnostic or prognostic biomarkers.</p> <h3>Methods</h3><p>We performed DNA methylation profiling of samples from 48 patients with stage I NSCLC and 18 matching cancer-free lung samples using microarrays that cover the promoter regions of more than 14,500 genes. We correlated DNA methylation changes with gene expression levels and performed survival analysis.</p> <h3>Results</h3><p>We observed hypermethylation of 496 CpGs in 379 genes and hypomethylation of 373 CpGs in 335 genes in NSCLC. Compared to adenocarcinoma samples, squamous cell carcinoma samples had 263 CpGs in 223 hypermethylated genes and 513 CpGs in 436 hypomethylated genes. 378 of 869 (43.5%) CpG sites discriminating the NSCLC and control samples showed an inverse correlation between CpG site methylation and gene expression levels. As a result of a survival analysis, we found 10 CpGs in 10 genes, in which the methylation level differs in different survival groups.</p> <h3>Conclusions</h3><p>We have identified a set of genes with altered methylation in NSCLC and found that a minority of them showed an inverse correlation with gene expression levels. We also found a set of genes that associated with the survival of the patients. These newly-identified marker candidates for the molecular screening of NSCLC will need further analysis in order to determine their clinical utility.</p> </div>", "links"=>[], "tags"=>["methylation", "markers", "early-stage", "non-small", "cancer"], "article_id"=>123270, "categories"=>["Cancer", "Cell Biology", "Genetics"], "users"=>["Kaie Lokk", "Tõnu Vooder", "Raivo Kolde", "Kristjan Välk", "Urmo Võsa", "Retlav Roosipuu", "Lili Milani", "Krista Fischer", "Marina Koltsina", "Egon Urgard", "Tarmo Annilo", "Andres Metspalu", "Neeme Tõnisson"], "doi"=>["https://dx.doi.org/10.1371/journal.pone.0039813.s001", "https://dx.doi.org/10.1371/journal.pone.0039813.s002", "https://dx.doi.org/10.1371/journal.pone.0039813.s003", "https://dx.doi.org/10.1371/journal.pone.0039813.s004", "https://dx.doi.org/10.1371/journal.pone.0039813.s005", "https://dx.doi.org/10.1371/journal.pone.0039813.s006", "https://dx.doi.org/10.1371/journal.pone.0039813.s007", "https://dx.doi.org/10.1371/journal.pone.0039813.s008", "https://dx.doi.org/10.1371/journal.pone.0039813.s009", "https://dx.doi.org/10.1371/journal.pone.0039813.s010", "https://dx.doi.org/10.1371/journal.pone.0039813.s011"], "stats"=>{"downloads"=>48, "page_views"=>16, "likes"=>0}, "figshare_url"=>"https://figshare.com/articles/Methylation_Markers_of_Early_Stage_Non_Small_Cell_Lung_Cancer/123270", "title"=>"Methylation Markers of Early-Stage Non-Small Cell Lung Cancer", "pos_in_sequence"=>0, "defined_type"=>4, "published_date"=>"2012-06-29 00:54:30"}
  • {"files"=>["https://ndownloader.figshare.com/files/615289"], "description"=>"<p>We measured CpGs’ distance from the transcription start site (TSS). a) Distance from TSS of all the CpGs on the methylation array. b) Distance from TSS of hypermethylated CpGs (dotted line) and distance from TSS of hypomethylated CpGs (continuous line). On the x-axis, the distance from TSS is measured in bp-s, and on the y-axis N represents the number of CpGs.</p>", "links"=>[], "tags"=>["genetics and genomics", "oncology", "pathology"], "article_id"=>285774, "categories"=>["Cancer", "Cell Biology", "Genetics"], "users"=>["Kaie Lokk", "Tõnu Vooder", "Raivo Kolde", "Kristjan Välk", "Urmo Võsa", "Retlav Roosipuu", "Lili Milani", "Krista Fischer", "Marina Koltsina", "Egon Urgard", "Tarmo Annilo", "Andres Metspalu", "Neeme Tõnisson"], "doi"=>"https://dx.doi.org/10.1371/journal.pone.0039813.g002", "stats"=>{"downloads"=>0, "page_views"=>0, "likes"=>0}, "figshare_url"=>"https://figshare.com/articles/_CpGs_8217_distance_from_TSS_/285774", "title"=>"CpGs’ distance from TSS.", "pos_in_sequence"=>0, "defined_type"=>1, "published_date"=>"2012-06-29 01:36:14"}
  • {"files"=>["https://ndownloader.figshare.com/files/615138"], "description"=>"<p>DNA methylation levels are shown for the top 100 CpG sites with the highest delta Beta values (FDR corrected) of DNA methylation between cancer tissue and normal lung tissue. Methylation Beta-values are represented as row Z-scores. A heatmap was generated using unsupervised 2D hierarchical cluster analysis. Red indicates high methylation and blue indicates low methylation relative to the row mean.</p>", "links"=>[], "tags"=>["dna", "methylation", "nsclc"], "article_id"=>285615, "categories"=>["Cancer", "Cell Biology", "Genetics"], "users"=>["Kaie Lokk", "Tõnu Vooder", "Raivo Kolde", "Kristjan Välk", "Urmo Võsa", "Retlav Roosipuu", "Lili Milani", "Krista Fischer", "Marina Koltsina", "Egon Urgard", "Tarmo Annilo", "Andres Metspalu", "Neeme Tõnisson"], "doi"=>"https://dx.doi.org/10.1371/journal.pone.0039813.g001", "stats"=>{"downloads"=>2, "page_views"=>0, "likes"=>0}, "figshare_url"=>"https://figshare.com/articles/_Differential_DNA_methylation_between_NSCLC_and_normal_lung_samples_/285615", "title"=>"Differential DNA methylation between NSCLC and normal lung samples.", "pos_in_sequence"=>0, "defined_type"=>1, "published_date"=>"2012-06-29 01:33:35"}

PMC Usage Stats | Further Information

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