NSAIDs Modulate Clonal Evolution in Barrett's Esophagus
Publication Date
June 13, 2013
Journal
PLOS Genetics
Authors
Rumen L. Kostadinov, Mary K. Kuhner, Xiaohong Li, Carissa A. Sanchez, et al
Volume
9
Issue
6
Pages
e1003553
DOI
https://dx.plos.org/10.1371/journal.pgen.1003553
Publisher URL
http://journals.plos.org/plosgenetics/article?id=10.1371%2Fjournal.pgen.1003553
PubMed
http://www.ncbi.nlm.nih.gov/pubmed/23785299
PubMed Central
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC3681672
Europe PMC
http://europepmc.org/abstract/MED/23785299
Web of Science
000321222600031
Scopus
84879641253
Mendeley
http://www.mendeley.com/research/nsaids-modulate-clonal-evolution-barretts-esophagus
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Mendeley | Further Information

{"title"=>"NSAIDs Modulate Clonal Evolution in Barrett's Esophagus", "type"=>"journal", "authors"=>[{"first_name"=>"Rumen L.", "last_name"=>"Kostadinov", "scopus_author_id"=>"12777159500"}, {"first_name"=>"Mary K.", "last_name"=>"Kuhner", "scopus_author_id"=>"7003270139"}, {"first_name"=>"Xiaohong", "last_name"=>"Li", "scopus_author_id"=>"35074434000"}, {"first_name"=>"Carissa A.", "last_name"=>"Sanchez", "scopus_author_id"=>"57189585798"}, {"first_name"=>"Patricia C.", "last_name"=>"Galipeau", "scopus_author_id"=>"6602909410"}, {"first_name"=>"Thomas G.", "last_name"=>"Paulson", "scopus_author_id"=>"6603773858"}, {"first_name"=>"Cassandra L.", "last_name"=>"Sather", "scopus_author_id"=>"23019872100"}, {"first_name"=>"Amitabh", "last_name"=>"Srivastava", "scopus_author_id"=>"56797226500"}, {"first_name"=>"Robert D.", "last_name"=>"Odze", "scopus_author_id"=>"7005890049"}, {"first_name"=>"Patricia L.", "last_name"=>"Blount", "scopus_author_id"=>"7007040478"}, {"first_name"=>"Thomas L.", "last_name"=>"Vaughan", "scopus_author_id"=>"7103008911"}, {"first_name"=>"Brian J.", "last_name"=>"Reid", "scopus_author_id"=>"7202316393"}, {"first_name"=>"Carlo C.", "last_name"=>"Maley", "scopus_author_id"=>"6602002424"}], "year"=>2013, "source"=>"PLoS Genetics", "identifiers"=>{"issn"=>"15537390", "pui"=>"369235376", "sgr"=>"84879641253", "doi"=>"10.1371/journal.pgen.1003553", "scopus"=>"2-s2.0-84879641253", "isbn"=>"1553-7404 (Electronic)\\r1553-7390 (Linking)", "pmid"=>"23785299"}, "id"=>"53cd29d9-3a15-37fa-8fba-6c784e87c70d", "abstract"=>"Cancer is considered an outcome of decades-long clonal evolution fueled by acquisition of somatic genomic abnormalities (SGAs). Non-steroidal anti-inflammatory drugs (NSAIDs) have been shown to reduce cancer risk, including risk of progression from Barrett's esophagus (BE) to esophageal adenocarcinoma (EA). However, the cancer chemopreventive mechanisms of NSAIDs are not fully understood. We hypothesized that NSAIDs modulate clonal evolution by reducing SGA acquisition rate. We evaluated thirteen individuals with BE. Eleven had not used NSAIDs for 6.2+/-3.5 (mean+/-standard deviation) years and then began using NSAIDs for 5.6+/-2.7 years, whereas two had used NSAIDs for 3.3+/-1.4 years and then discontinued use for 7.9+/-0.7 years. 161 BE biopsies, collected at 5-8 time points over 6.4-19 years, were analyzed using 1Million-SNP arrays to detect SGAs. Even in the earliest biopsies there were many SGAs (284+/-246 in 10/13 and 1442+/-560 in 3/13 individuals) and in most individuals the number of SGAs changed little over time, with both increases and decreases in SGAs detected. The estimated SGA rate was 7.8 per genome per year (95% support interval [SI], 7.1-8.6) off-NSAIDs and 0.6 (95% SI 0.3-1.5) on-NSAIDs. Twelve individuals did not progress to EA. In ten we detected 279+/-86 SGAs affecting 53+/-30 Mb of the genome per biopsy per time point and in two we detected 1,463+/-375 SGAs affecting 180+/-100 Mb. In one individual who progressed to EA we detected a clone having 2,291+/-78 SGAs affecting 588+/-18 Mb of the genome at three time points in the last three of 11.4 years of follow-up. NSAIDs were associated with reduced rate of acquisition of SGAs in eleven of thirteen individuals. Barrett's cells maintained relative equilibrium level of SGAs over time with occasional punctuations by expansion of clones having massive amount of SGAs.", "link"=>"http://www.mendeley.com/research/nsaids-modulate-clonal-evolution-barretts-esophagus", "reader_count"=>59, "reader_count_by_academic_status"=>{"Professor > Associate Professor"=>3, "Researcher"=>16, "Student > Doctoral Student"=>6, "Student > Ph. D. Student"=>15, "Student > Postgraduate"=>4, "Other"=>3, "Student > Master"=>5, "Student > Bachelor"=>3, "Professor"=>4}, "reader_count_by_user_role"=>{"Professor > Associate Professor"=>3, "Researcher"=>16, "Student > Doctoral Student"=>6, "Student > Ph. D. Student"=>15, "Student > Postgraduate"=>4, "Other"=>3, "Student > Master"=>5, "Student > Bachelor"=>3, "Professor"=>4}, "reader_count_by_subject_area"=>{"Engineering"=>1, "Environmental Science"=>1, "Biochemistry, Genetics and Molecular Biology"=>4, "Mathematics"=>1, "Agricultural and Biological Sciences"=>28, "Medicine and Dentistry"=>21, "Social Sciences"=>1, "Computer Science"=>2}, "reader_count_by_subdiscipline"=>{"Engineering"=>{"Engineering"=>1}, "Medicine and Dentistry"=>{"Medicine and Dentistry"=>21}, "Social Sciences"=>{"Social Sciences"=>1}, "Agricultural and Biological Sciences"=>{"Agricultural and Biological Sciences"=>28}, "Computer Science"=>{"Computer Science"=>2}, "Biochemistry, Genetics and Molecular Biology"=>{"Biochemistry, Genetics and Molecular Biology"=>4}, "Mathematics"=>{"Mathematics"=>1}, "Environmental Science"=>{"Environmental Science"=>1}}, "reader_count_by_country"=>{"Sweden"=>1, "United States"=>3, "Italy"=>1, "Spain"=>2}, "group_count"=>4}

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Figshare

  • {"files"=>["http://files.figshare.com/1085554/Figure_6.tif"], "pos_in_sequence"=>0, "stats"=>{"downloads"=>0, "page_views"=>5, "likes"=>0}, "users"=>["Thomas G. Paulson", "Patricia C. Galipeau", "Carissa A. Sanchez", "Rumen L. Kostadinov", "Mary K. Kuhner", "Cassandra L. Sather", "Amitabh Srivastava", "Robert D. Odze", "Patricia L. Blount", "Thomas L. Vaughan", "Brian J. Reid", "Carlo C. Maley", "Xiaohong Li"], "links"=>[], "tags"=>["Genetic causes of cancer", "Cancers and neoplasms", "Early detection", "oncology", "Esophageal cancer", "Gastroenterology and hepatology", "esophagus", "Gastrointestinal tumors", "chemoprevention", "mutation", "genome", "genomics", "Evolutionary modeling", "nsaid", "suggests", "Computational biology", "Predisposing conditions and syndromes", "sga", "population genetics", "Genome evolution", "Cancer detection and diagnosis", "Cancer risk factors"], "title"=>"<p>BEAST analysis suggests that NSAID use reduces the SGA rate (number of SGA events per genome per year).</p>", "figshare_url"=>"http://figshare.com/articles/_BEAST_analysis_suggests_that_NSAID_use_reduces_the_SGA_rate_number_of_SGA_events_per_genome_per_year_/718787", "defined_type"=>1, "doi"=>["http://dx.doi.org/10.1371/journal.pgen.1003553.g006"], "published_date"=>"2013-06-13 02:26:27", "article_id"=>718787, "categories"=>["Biological Sciences", "Medicine"], "description"=>"<p >For all individuals (a&#8211;m), the mean off-NSAID SGA rate was 7.8 (95% support interval [SI]: 7.1&#8211;8.6) and the mean on-NSIAD SGA rate was 0.6 (95% SI: 0.3&#8211;1.5). For individuals a&#8211;k, the mean off-NSAID SGA rate was 8.8 (95% SI: 8.1&#8211;9.5,), whereas the mean on-NSAID SGA rate was 0.2 (95% SI: 0.03&#8211;1.0). For the two individuals l and m that started surveillance on NSAIDs and then went off NSAIDs, there are mixed results. The mean on-NSAID SGA rate for individual l was 3.1 (95% SI: 2.2&#8211;4.7) and the mean off-NSAID SGA rate was 4.4 (95% SI: 3.1&#8211;5.9). However, for individual m the mean on-NSAID SGA rate was 2.5 (95% SI: 2.1&#8211;3.0) and the mean off-NSAID SGA rate was 0.1 (95% SI: 0.01&#8211;0.6). Note that confidence intervals are tighter for the earlier time period for each individual as more inferred ancestry events fell within that time period.</p>"}
  • {"files"=>["http://files.figshare.com/1086011/Figure_1.tif"], "pos_in_sequence"=>0, "stats"=>{"downloads"=>0, "page_views"=>6, "likes"=>0}, "users"=>["Thomas G. Paulson", "Patricia C. Galipeau", "Carissa A. Sanchez", "Rumen L. Kostadinov", "Mary K. Kuhner", "Cassandra L. Sather", "Amitabh Srivastava", "Robert D. Odze", "Patricia L. Blount", "Thomas L. Vaughan", "Brian J. Reid", "Carlo C. Maley", "Xiaohong Li"], "links"=>[], "tags"=>["Genetic causes of cancer", "Predisposing conditions and syndromes", "Gastrointestinal tumors", "mutation", "Early detection", "Evolutionary modeling", "Computational biology", "biopsy", "oncology", "population genetics", "Esophageal cancer", "Genome evolution", "Gastroenterology and hepatology", "Cancer detection and diagnosis", "genomics", "esophagus", "Cancer risk factors", "chemoprevention", "Cancers and neoplasms"], "title"=>"<p>Study design and biopsy sampling.</p>", "figshare_url"=>"http://figshare.com/articles/_Study_design_and_biopsy_sampling_/719111", "defined_type"=>1, "doi"=>["http://dx.doi.org/10.1371/journal.pgen.1003553.g001"], "published_date"=>"2013-06-13 02:31:51", "article_id"=>719111, "categories"=>["Biological Sciences", "Medicine"], "description"=>"<p >Throughout this figure, white indicates time off NSAIDs and gray indicates time on NSAIDs. (Panel A) Thirteen individuals with BE, showing times of endoscopies as black x's, and indicating time on and off NSAIDs. (Panel B) The temporal and spatial location of all biopsies in the study. Red lines show the extent of Barrett's segment from the gastroesophageal junction (GEJ) to the squamocolumnar junction (SCJ). The Y-axis is measured in cm from the GEJ. The X-axis is scaled in years of follow-up, with the total amount of follow-up for each individual indicated below the data for that individual. Small black circles indicate the locations of the biopsies that were assayed in this study.</p>"}
  • {"files"=>["http://files.figshare.com/1086012/Figure_2.tif"], "pos_in_sequence"=>0, "stats"=>{"downloads"=>0, "page_views"=>9, "likes"=>0}, "users"=>["Thomas G. Paulson", "Patricia C. Galipeau", "Carissa A. Sanchez", "Rumen L. Kostadinov", "Mary K. Kuhner", "Cassandra L. Sather", "Amitabh Srivastava", "Robert D. Odze", "Patricia L. Blount", "Thomas L. Vaughan", "Brian J. Reid", "Carlo C. Maley", "Xiaohong Li"], "links"=>[], "tags"=>["Genetic causes of cancer", "Predisposing conditions and syndromes", "Gastrointestinal tumors", "mutation", "Early detection", "remains", "Computational biology", "Evolutionary modeling", "oncology", "population genetics", "Esophageal cancer", "Genome evolution", "Gastroenterology and hepatology", "Cancer detection and diagnosis", "genomics", "esophagus", "Cancer risk factors", "chemoprevention", "Cancers and neoplasms"], "title"=>"<p>SGA remains approximately constant over time in most individuals.</p>", "figshare_url"=>"http://figshare.com/articles/_SGA_remains_approximately_constant_over_time_in_most_individuals_/719112", "defined_type"=>1, "doi"=>["http://dx.doi.org/10.1371/journal.pgen.1003553.g002"], "published_date"=>"2013-06-13 02:31:52", "article_id"=>719112, "categories"=>["Biological Sciences", "Medicine"], "description"=>"<p >Black lines indicate 10 individuals with apparent evolutionary stasis and red lines indicate 3 individuals with apparent increase in SGA over time. (Panel A) Mean number of SGA lesions. Solid lines connect the means at each time point for all individuals (a&#8211;m), where the symbols a&#8211;m are plotted at the end of the lines. (Panel B) Mean amount of genome affected by SGA.</p>"}
  • {"files"=>["http://files.figshare.com/1086013/Figure_3.tif"], "pos_in_sequence"=>0, "stats"=>{"downloads"=>0, "page_views"=>8, "likes"=>0}, "users"=>["Thomas G. Paulson", "Patricia C. Galipeau", "Carissa A. Sanchez", "Rumen L. Kostadinov", "Mary K. Kuhner", "Cassandra L. Sather", "Amitabh Srivastava", "Robert D. Odze", "Patricia L. Blount", "Thomas L. Vaughan", "Brian J. Reid", "Carlo C. Maley", "Xiaohong Li"], "links"=>[], "tags"=>["Genetic causes of cancer", "Cancers and neoplasms", "Early detection", "oncology", "Esophageal cancer", "Gastroenterology and hepatology", "esophagus", "Gastrointestinal tumors", "chemoprevention", "lineages", "mutation", "outlier", "off-nsaid", "genomics", "Evolutionary modeling", "phylogenies", "suggests", "Computational biology", "occurred", "within-individual", "Predisposing conditions and syndromes", "sga", "population genetics", "Genome evolution", "Cancer detection and diagnosis", "evolved", "Cancer risk factors"], "title"=>"<p>PAUP analysis of SGA events distribution on lineages of within-individual phylogenies suggests that the greatest number of SGA events occurred on outlier minority of lineages that evolved during off-NSAID periods.</p>", "figshare_url"=>"http://figshare.com/articles/_PAUP_analysis_of_SGA_events_distribution_on_lineages_of_within_individual_phylogenies_suggests_that_the_greatest_number_of_SGA_events_occurred_on_outlier_minority_of_lineages_that_evolved_during_off_NSAID_periods_/719113", "defined_type"=>1, "doi"=>["http://dx.doi.org/10.1371/journal.pgen.1003553.g003"], "published_date"=>"2013-06-13 02:31:53", "article_id"=>719113, "categories"=>["Biological Sciences", "Medicine"], "description"=>"<p >Two violin plots show the distribution of lineage lengths (estimated number of SGA events) that evolved during off-NSAID (white) and on-NSAID (grey) periods within an individual phylogeny (solid line across the violin denotes the median). The volumes of a pair of violin plots are scaled relative to the number of data points the pair contains. Scatter plots show the raw data underlying the violin plots and illustrate the outliers. The majority of individual phylogenies (a, b, d, e, f, g, h, i, j, k) show an off-NSAID lineage containing the maximum number of SGA events.</p>"}
  • {"files"=>["http://files.figshare.com/1086014/Figure_4.tif"], "pos_in_sequence"=>0, "stats"=>{"downloads"=>0, "page_views"=>3, "likes"=>0}, "users"=>["Thomas G. Paulson", "Patricia C. Galipeau", "Carissa A. Sanchez", "Rumen L. Kostadinov", "Mary K. Kuhner", "Cassandra L. Sather", "Amitabh Srivastava", "Robert D. Odze", "Patricia L. Blount", "Thomas L. Vaughan", "Brian J. Reid", "Carlo C. Maley", "Xiaohong Li"], "links"=>[], "tags"=>["Genetic causes of cancer", "individuals", "Predisposing conditions and syndromes", "Cancers and neoplasms", "Early detection", "esophagus", "Computational biology", "Evolutionary modeling", "oncology", "population genetics", "Esophageal cancer", "Genome evolution", "Gastroenterology and hepatology", "Cancer detection and diagnosis", "genomics", "Gastrointestinal tumors", "Cancer risk factors", "chemoprevention", "mutation"], "title"=>"<p>Clonal evolution in individuals b and j.</p>", "figshare_url"=>"http://figshare.com/articles/_Clonal_evolution_in_individuals_b_and_j_/719114", "defined_type"=>1, "doi"=>["http://dx.doi.org/10.1371/journal.pgen.1003553.g004"], "published_date"=>"2013-06-13 02:31:54", "article_id"=>719114, "categories"=>["Biological Sciences", "Medicine"], "description"=>"<p >(Panel A) Solid lines connect the mean amount of SGA detected across biopsies at each time point; dots correspond to individual biopsies. In individual b (black line), we observed evolutionary stasis with mean SGA remaining at 119&#177;79 Mb over more than a decade of follow-up. In individual j (red line), a massive burst of SGA was detected in year 8.5; three years later individual j progressed to esophageal adenocarcinoma. Individual b started NSAIDs after year 5, while individual j started NSAIDs only after year 10. (Panels B and C) Circos plots showing genome-wide views of SGA over time. Each ring, labeled with a biopsy number, represents whole-genome SGA data from a different biopsy, with earlier samples toward the center. Thin black line rings separate endoscopies (time points), white background shows time periods off-NSAIDs and gray background shows time periods on-NSAIDs. Within the rings, black segments designate homozygous deletion, red single copy loss, orange copy-neutral LOH, and green copy gain. (Panel B) Circos plot of individual b. Note the appearance of &#8220;new&#8221; whole chromosome LOH at chromosome 6 and 11 in biopsy 5, taken during the off-NSAIDs period, and the detection of a minimally mutated clone in biopsies 9 and 7, taken during the on-NSAIDs period. (Panel C) Circos plot of individual j. A massive burst of SGAs was detected first in biopsy 8, in year 8.5, before the individual began regular NSAID use. Biopsy 2 (second inner ring), taken at the baseline endoscopy 8.5 years prior to the burst, shared a subset of the SGAs seen in the massively altered clone (chromosomes 10, 12, 17 and 18), and thus is likely an early example of its lineage. (Panels D and G) Consensus phylogenetic trees estimated by BEAST reveal long-term co-existence of clones. Branch lengths are scaled according to time, the tips of the phylogeny are biopsies aligned on the x-axis according to their sampling time, and all internal nodes are estimated coalescence times assuming a logistic population growth. Dashed gray line represents the start of NSAID use. (Panels E, F, H, I) Maximum parsimony trees estimated by PAUP reveal the ancestral relationships among biopsies based on shared SGA characters. Differences between the topology of the trees estimated by PAUP and BEAST are typically due to poorly supported short branches and do not affect the analyses of SGA acquisition rates. Branch lengths are scaled according to estimated number of SGAs (Panels E, H) or the amount of genome affected by SGA (Panels F, I). Note that these trees appear very different from those estimated by BEAST as the BEAST branch lengths are scaled by inferred time depth, and the rate of SGA accumulation appears highly variable with time.</p>"}
  • {"files"=>["http://files.figshare.com/1086015/Figure_5.tif"], "pos_in_sequence"=>0, "stats"=>{"downloads"=>0, "page_views"=>4, "likes"=>0}, "users"=>["Thomas G. Paulson", "Patricia C. Galipeau", "Carissa A. Sanchez", "Rumen L. Kostadinov", "Mary K. Kuhner", "Cassandra L. Sather", "Amitabh Srivastava", "Robert D. Odze", "Patricia L. Blount", "Thomas L. Vaughan", "Brian J. Reid", "Carlo C. Maley", "Xiaohong Li"], "links"=>[], "tags"=>["Genetic causes of cancer", "individuals", "Predisposing conditions and syndromes", "Cancers and neoplasms", "Early detection", "esophagus", "Computational biology", "Evolutionary modeling", "oncology", "population genetics", "Esophageal cancer", "Genome evolution", "Gastroenterology and hepatology", "Cancer detection and diagnosis", "genomics", "Gastrointestinal tumors", "Cancer risk factors", "chemoprevention", "mutation"], "title"=>"<p>Clonal evolution in individuals l and f.</p>", "figshare_url"=>"http://figshare.com/articles/_Clonal_evolution_in_individuals_l_and_f_/719115", "defined_type"=>1, "doi"=>["http://dx.doi.org/10.1371/journal.pgen.1003553.g005"], "published_date"=>"2013-06-13 02:31:55", "article_id"=>719115, "categories"=>["Biological Sciences", "Medicine"], "description"=>"<p>(Panel A) Amount of SGA in biopsies (dots) and mean SGA over all biopsies at that time point (lines) for individual l (black) and individual f (red). (Panels B and C) Circos plots showing genome-wide view of SGA over time (see <a href=\"http://www.plosgenetics.org/article/info:doi/10.1371/journal.pgen.1003553#pgen-1003553-g004\" target=\"_blank\">Figure 4</a> legend for details). (Panel B) Individual l. During the off-NSAID period we detected a whole-chromosome gain of chromosome 8 in biopsy 12 (green band) and copy-neutral LOH events on chromosome 1 in biopsies 9 and 11 (orange bands). (Panel C) We detected 1,844±573 of SGAs in individual f, who opted for esophagectomy for high-grade dysplasia after 6.4 years of follow-up and died of another cancer 11.9 years later. (Panels D, E, F) BEAST consensus tree, parsimony tree of SGA number, and parsimony tree of SGA quantity for individual l. (Panels G, H, I) BEAST consensus tree, parsimony tree of SGA number, and parsimony tree of SGA quantity for individual f. In both individuals, BEAST trees reveal long-term co-existence of multiple clones. and maximum parsimony trees reveal an underlying progressive evolution of SGA events irrespective of time. Phylogenetic trees generated as indicated in the legend to <a href=\"http://www.plosgenetics.org/article/info:doi/10.1371/journal.pgen.1003553#pgen-1003553-g004\" target=\"_blank\">Figure 4</a>.</p>"}
  • {"files"=>["http://files.figshare.com/1086016/Figure_6.tif"], "pos_in_sequence"=>0, "stats"=>{"downloads"=>0, "page_views"=>6, "likes"=>0}, "users"=>["Thomas G. Paulson", "Patricia C. Galipeau", "Carissa A. Sanchez", "Rumen L. Kostadinov", "Mary K. Kuhner", "Cassandra L. Sather", "Amitabh Srivastava", "Robert D. Odze", "Patricia L. Blount", "Thomas L. Vaughan", "Brian J. Reid", "Carlo C. Maley", "Xiaohong Li"], "links"=>[], "tags"=>["Genetic causes of cancer", "Cancers and neoplasms", "Early detection", "oncology", "Esophageal cancer", "Gastroenterology and hepatology", "esophagus", "Gastrointestinal tumors", "chemoprevention", "mutation", "genome", "genomics", "Evolutionary modeling", "nsaid", "suggests", "Computational biology", "Predisposing conditions and syndromes", "sga", "population genetics", "Genome evolution", "Cancer detection and diagnosis", "Cancer risk factors"], "title"=>"<p>BEAST analysis suggests that NSAID use reduces the SGA rate (number of SGA events per genome per year).</p>", "figshare_url"=>"http://figshare.com/articles/_BEAST_analysis_suggests_that_NSAID_use_reduces_the_SGA_rate_number_of_SGA_events_per_genome_per_year_/719116", "defined_type"=>1, "doi"=>["http://dx.doi.org/10.1371/journal.pgen.1003553.g006"], "published_date"=>"2013-06-13 02:31:56", "article_id"=>719116, "categories"=>["Biological Sciences", "Medicine"], "description"=>"<p >For all individuals (a&#8211;m), the mean off-NSAID SGA rate was 7.8 (95% support interval [SI]: 7.1&#8211;8.6) and the mean on-NSIAD SGA rate was 0.6 (95% SI: 0.3&#8211;1.5). For individuals a&#8211;k, the mean off-NSAID SGA rate was 8.8 (95% SI: 8.1&#8211;9.5,), whereas the mean on-NSAID SGA rate was 0.2 (95% SI: 0.03&#8211;1.0). For the two individuals l and m that started surveillance on NSAIDs and then went off NSAIDs, there are mixed results. The mean on-NSAID SGA rate for individual l was 3.1 (95% SI: 2.2&#8211;4.7) and the mean off-NSAID SGA rate was 4.4 (95% SI: 3.1&#8211;5.9). However, for individual m the mean on-NSAID SGA rate was 2.5 (95% SI: 2.1&#8211;3.0) and the mean off-NSAID SGA rate was 0.1 (95% SI: 0.01&#8211;0.6). Note that confidence intervals are tighter for the earlier time period for each individual as more inferred ancestry events fell within that time period.</p>"}
  • {"files"=>["http://files.figshare.com/1086017/Dataset_S1.pdf", "http://files.figshare.com/1086018/Figure_S1.tif", "http://files.figshare.com/1086019/Figure_S2.tif", "http://files.figshare.com/1086020/Figure_S3.tif", "http://files.figshare.com/1086021/Figure_S4.tif", "http://files.figshare.com/1086022/Figure_S5.tif", "http://files.figshare.com/1086023/Figure_S6.pdf", "http://files.figshare.com/1086024/Figure_S7.pdf", "http://files.figshare.com/1086025/Figure_S8.tif", "http://files.figshare.com/1086026/Figure_S9.tif", "http://files.figshare.com/1086027/Figure_S10.tif", "http://files.figshare.com/1086028/Figure_S11.tif", "http://files.figshare.com/1086029/Figure_S12.tif", "http://files.figshare.com/1086030/Figure_S13.tif", "http://files.figshare.com/1086031/Figure_S14.tif", "http://files.figshare.com/1086032/Figure_S15.tif", "http://files.figshare.com/1086033/Table_S1.xlsx", "http://files.figshare.com/1086034/Table_S2.xlsx", "http://files.figshare.com/1086035/Table_S3.xlsx", "http://files.figshare.com/1086036/Table_S4.xlsx", "http://files.figshare.com/1086037/Table_S5.xlsx", "http://files.figshare.com/1086038/Table_S6.xls", "http://files.figshare.com/1086039/Text_S1.doc", "http://files.figshare.com/1086040/Text_S2.doc", "http://files.figshare.com/1086042/Text_S3.doc", "http://files.figshare.com/1086043/Text_S4.doc"], "pos_in_sequence"=>0, "stats"=>{"downloads"=>0, "page_views"=>10, "likes"=>0}, "users"=>["Thomas G. Paulson", "Patricia C. Galipeau", "Carissa A. Sanchez", "Rumen L. Kostadinov", "Mary K. Kuhner", "Cassandra L. Sather", "Amitabh Srivastava", "Robert D. Odze", "Patricia L. Blount", "Thomas L. Vaughan", "Brian J. Reid", "Carlo C. Maley", "Xiaohong Li"], "links"=>[], "tags"=>["Genetic causes of cancer", "Predisposing conditions and syndromes", "mutation", "clonal", "Early detection", "modulate", "esophagus", "Computational biology", "Evolutionary modeling", "oncology", "population genetics", "Esophageal cancer", "Genome evolution", "Gastroenterology and hepatology", "Cancer detection and diagnosis", "genomics", "Gastrointestinal tumors", "Cancer risk factors", "chemoprevention", "Cancers and neoplasms"], "title"=>"<p>NSAIDs Modulate Clonal Evolution in Barrett's Esophagus</p>", "figshare_url"=>"http://figshare.com/articles/_NSAIDs_Modulate_Clonal_Evolution_in_Barrett_s_Esophagus_/719117", "defined_type"=>4, "doi"=>["http://dx.doi.org/10.1371/journal.pgen.1003553.s001", "http://dx.doi.org/10.1371/journal.pgen.1003553.s002", "http://dx.doi.org/10.1371/journal.pgen.1003553.s003", "http://dx.doi.org/10.1371/journal.pgen.1003553.s004", "http://dx.doi.org/10.1371/journal.pgen.1003553.s005", "http://dx.doi.org/10.1371/journal.pgen.1003553.s006", "http://dx.doi.org/10.1371/journal.pgen.1003553.s007", "http://dx.doi.org/10.1371/journal.pgen.1003553.s008", "http://dx.doi.org/10.1371/journal.pgen.1003553.s009", "http://dx.doi.org/10.1371/journal.pgen.1003553.s010", "http://dx.doi.org/10.1371/journal.pgen.1003553.s011", "http://dx.doi.org/10.1371/journal.pgen.1003553.s012", "http://dx.doi.org/10.1371/journal.pgen.1003553.s013", "http://dx.doi.org/10.1371/journal.pgen.1003553.s014", "http://dx.doi.org/10.1371/journal.pgen.1003553.s015", "http://dx.doi.org/10.1371/journal.pgen.1003553.s016", "http://dx.doi.org/10.1371/journal.pgen.1003553.s017", "http://dx.doi.org/10.1371/journal.pgen.1003553.s018", "http://dx.doi.org/10.1371/journal.pgen.1003553.s019", "http://dx.doi.org/10.1371/journal.pgen.1003553.s020", "http://dx.doi.org/10.1371/journal.pgen.1003553.s021", "http://dx.doi.org/10.1371/journal.pgen.1003553.s022", "http://dx.doi.org/10.1371/journal.pgen.1003553.s023", "http://dx.doi.org/10.1371/journal.pgen.1003553.s024", "http://dx.doi.org/10.1371/journal.pgen.1003553.s025", "http://dx.doi.org/10.1371/journal.pgen.1003553.s026"], "published_date"=>"2013-06-13 02:31:57", "article_id"=>719117, "categories"=>["Biological Sciences", "Medicine"], "description"=>"<div><p>Cancer is considered an outcome of decades-long clonal evolution fueled by acquisition of somatic genomic abnormalities (SGAs). Non-steroidal anti-inflammatory drugs (NSAIDs) have been shown to reduce cancer risk, including risk of progression from Barrett's esophagus (BE) to esophageal adenocarcinoma (EA). However, the cancer chemopreventive mechanisms of NSAIDs are not fully understood. We hypothesized that NSAIDs modulate clonal evolution by reducing SGA acquisition rate. We evaluated thirteen individuals with BE. Eleven had not used NSAIDs for 6.2&#177;3.5 (mean&#177;standard deviation) years and then began using NSAIDs for 5.6&#177;2.7 years, whereas two had used NSAIDs for 3.3&#177;1.4 years and then discontinued use for 7.9&#177;0.7 years. 161 BE biopsies, collected at 5&#8211;8 time points over 6.4&#8211;19 years, were analyzed using 1Million-SNP arrays to detect SGAs. Even in the earliest biopsies there were many SGAs (284&#177;246 in 10/13 and 1442&#177;560 in 3/13 individuals) and in most individuals the number of SGAs changed little over time, with both increases and decreases in SGAs detected. The estimated SGA rate was 7.8 per genome per year (95% support interval [SI], 7.1&#8211;8.6) off-NSAIDs and 0.6 (95% SI 0.3&#8211;1.5) on-NSAIDs. Twelve individuals did not progress to EA. In ten we detected 279&#177;86 SGAs affecting 53&#177;30 Mb of the genome per biopsy per time point and in two we detected 1,463&#177;375 SGAs affecting 180&#177;100 Mb. In one individual who progressed to EA we detected a clone having 2,291&#177;78 SGAs affecting 588&#177;18 Mb of the genome at three time points in the last three of 11.4 years of follow-up. NSAIDs were associated with reduced rate of acquisition of SGAs in eleven of thirteen individuals. Barrett's cells maintained relative equilibrium level of SGAs over time with occasional punctuations by expansion of clones having massive amount of SGAs.</p></div>"}
  • {"files"=>["http://files.figshare.com/1085532/Figure_1.tif"], "pos_in_sequence"=>0, "stats"=>{"downloads"=>0, "page_views"=>1, "likes"=>0}, "users"=>["Thomas G. Paulson", "Patricia C. Galipeau", "Carissa A. Sanchez", "Rumen L. Kostadinov", "Mary K. Kuhner", "Cassandra L. Sather", "Amitabh Srivastava", "Robert D. Odze", "Patricia L. Blount", "Thomas L. Vaughan", "Brian J. Reid", "Carlo C. Maley", "Xiaohong Li"], "links"=>[], "tags"=>["Genetic causes of cancer", "Predisposing conditions and syndromes", "Gastrointestinal tumors", "mutation", "Early detection", "Evolutionary modeling", "Computational biology", "biopsy", "oncology", "population genetics", "Esophageal cancer", "Genome evolution", "Gastroenterology and hepatology", "Cancer detection and diagnosis", "genomics", "esophagus", "Cancer risk factors", "chemoprevention", "Cancers and neoplasms"], "title"=>"<p>Study design and biopsy sampling.</p>", "figshare_url"=>"http://figshare.com/articles/_Study_design_and_biopsy_sampling_/718774", "defined_type"=>1, "doi"=>["http://dx.doi.org/10.1371/journal.pgen.1003553.g001"], "published_date"=>"2013-06-13 02:26:14", "article_id"=>718774, "categories"=>["Biological Sciences", "Medicine"], "description"=>"<p >Throughout this figure, white indicates time off NSAIDs and gray indicates time on NSAIDs. (Panel A) Thirteen individuals with BE, showing times of endoscopies as black x's, and indicating time on and off NSAIDs. (Panel B) The temporal and spatial location of all biopsies in the study. Red lines show the extent of Barrett's segment from the gastroesophageal junction (GEJ) to the squamocolumnar junction (SCJ). The Y-axis is measured in cm from the GEJ. The X-axis is scaled in years of follow-up, with the total amount of follow-up for each individual indicated below the data for that individual. Small black circles indicate the locations of the biopsies that were assayed in this study.</p>"}
  • {"files"=>["http://files.figshare.com/1085533/Figure_2.tif"], "pos_in_sequence"=>0, "stats"=>{"downloads"=>0, "page_views"=>6, "likes"=>0}, "users"=>["Thomas G. Paulson", "Patricia C. Galipeau", "Carissa A. Sanchez", "Rumen L. Kostadinov", "Mary K. Kuhner", "Cassandra L. Sather", "Amitabh Srivastava", "Robert D. Odze", "Patricia L. Blount", "Thomas L. Vaughan", "Brian J. Reid", "Carlo C. Maley", "Xiaohong Li"], "links"=>[], "tags"=>["Genetic causes of cancer", "Predisposing conditions and syndromes", "Gastrointestinal tumors", "mutation", "Early detection", "remains", "Computational biology", "Evolutionary modeling", "oncology", "population genetics", "Esophageal cancer", "Genome evolution", "Gastroenterology and hepatology", "Cancer detection and diagnosis", "genomics", "esophagus", "Cancer risk factors", "chemoprevention", "Cancers and neoplasms"], "title"=>"<p>SGA remains approximately constant over time in most individuals.</p>", "figshare_url"=>"http://figshare.com/articles/_SGA_remains_approximately_constant_over_time_in_most_individuals_/718775", "defined_type"=>1, "doi"=>["http://dx.doi.org/10.1371/journal.pgen.1003553.g002"], "published_date"=>"2013-06-13 02:26:15", "article_id"=>718775, "categories"=>["Biological Sciences", "Medicine"], "description"=>"<p >Black lines indicate 10 individuals with apparent evolutionary stasis and red lines indicate 3 individuals with apparent increase in SGA over time. (Panel A) Mean number of SGA lesions. Solid lines connect the means at each time point for all individuals (a&#8211;m), where the symbols a&#8211;m are plotted at the end of the lines. (Panel B) Mean amount of genome affected by SGA.</p>"}
  • {"files"=>["http://files.figshare.com/1085534/Figure_3.tif"], "pos_in_sequence"=>0, "stats"=>{"downloads"=>0, "page_views"=>6, "likes"=>0}, "users"=>["Thomas G. Paulson", "Patricia C. Galipeau", "Carissa A. Sanchez", "Rumen L. Kostadinov", "Mary K. Kuhner", "Cassandra L. Sather", "Amitabh Srivastava", "Robert D. Odze", "Patricia L. Blount", "Thomas L. Vaughan", "Brian J. Reid", "Carlo C. Maley", "Xiaohong Li"], "links"=>[], "tags"=>["Genetic causes of cancer", "Cancers and neoplasms", "Early detection", "oncology", "Esophageal cancer", "Gastroenterology and hepatology", "esophagus", "Gastrointestinal tumors", "chemoprevention", "lineages", "mutation", "outlier", "off-nsaid", "genomics", "Evolutionary modeling", "phylogenies", "suggests", "Computational biology", "occurred", "within-individual", "Predisposing conditions and syndromes", "sga", "population genetics", "Genome evolution", "Cancer detection and diagnosis", "evolved", "Cancer risk factors"], "title"=>"<p>PAUP analysis of SGA events distribution on lineages of within-individual phylogenies suggests that the greatest number of SGA events occurred on outlier minority of lineages that evolved during off-NSAID periods.</p>", "figshare_url"=>"http://figshare.com/articles/_PAUP_analysis_of_SGA_events_distribution_on_lineages_of_within_individual_phylogenies_suggests_that_the_greatest_number_of_SGA_events_occurred_on_outlier_minority_of_lineages_that_evolved_during_off_NSAID_periods_/718776", "defined_type"=>1, "doi"=>["http://dx.doi.org/10.1371/journal.pgen.1003553.g003"], "published_date"=>"2013-06-13 02:26:16", "article_id"=>718776, "categories"=>["Biological Sciences", "Medicine"], "description"=>"<p >Two violin plots show the distribution of lineage lengths (estimated number of SGA events) that evolved during off-NSAID (white) and on-NSAID (grey) periods within an individual phylogeny (solid line across the violin denotes the median). The volumes of a pair of violin plots are scaled relative to the number of data points the pair contains. Scatter plots show the raw data underlying the violin plots and illustrate the outliers. The majority of individual phylogenies (a, b, d, e, f, g, h, i, j, k) show an off-NSAID lineage containing the maximum number of SGA events.</p>"}
  • {"files"=>["http://files.figshare.com/1085546/Figure_4.tif"], "pos_in_sequence"=>0, "stats"=>{"downloads"=>0, "page_views"=>6, "likes"=>0}, "users"=>["Thomas G. Paulson", "Patricia C. Galipeau", "Carissa A. Sanchez", "Rumen L. Kostadinov", "Mary K. Kuhner", "Cassandra L. Sather", "Amitabh Srivastava", "Robert D. Odze", "Patricia L. Blount", "Thomas L. Vaughan", "Brian J. Reid", "Carlo C. Maley", "Xiaohong Li"], "links"=>[], "tags"=>["Genetic causes of cancer", "individuals", "Predisposing conditions and syndromes", "Cancers and neoplasms", "Early detection", "esophagus", "Computational biology", "Evolutionary modeling", "oncology", "population genetics", "Esophageal cancer", "Genome evolution", "Gastroenterology and hepatology", "Cancer detection and diagnosis", "genomics", "Gastrointestinal tumors", "Cancer risk factors", "chemoprevention", "mutation"], "title"=>"<p>Clonal evolution in individuals b and j.</p>", "figshare_url"=>"http://figshare.com/articles/_Clonal_evolution_in_individuals_b_and_j_/718779", "defined_type"=>1, "doi"=>["http://dx.doi.org/10.1371/journal.pgen.1003553.g004"], "published_date"=>"2013-06-13 02:26:19", "article_id"=>718779, "categories"=>["Biological Sciences", "Medicine"], "description"=>"<p >(Panel A) Solid lines connect the mean amount of SGA detected across biopsies at each time point; dots correspond to individual biopsies. In individual b (black line), we observed evolutionary stasis with mean SGA remaining at 119&#177;79 Mb over more than a decade of follow-up. In individual j (red line), a massive burst of SGA was detected in year 8.5; three years later individual j progressed to esophageal adenocarcinoma. Individual b started NSAIDs after year 5, while individual j started NSAIDs only after year 10. (Panels B and C) Circos plots showing genome-wide views of SGA over time. Each ring, labeled with a biopsy number, represents whole-genome SGA data from a different biopsy, with earlier samples toward the center. Thin black line rings separate endoscopies (time points), white background shows time periods off-NSAIDs and gray background shows time periods on-NSAIDs. Within the rings, black segments designate homozygous deletion, red single copy loss, orange copy-neutral LOH, and green copy gain. (Panel B) Circos plot of individual b. Note the appearance of &#8220;new&#8221; whole chromosome LOH at chromosome 6 and 11 in biopsy 5, taken during the off-NSAIDs period, and the detection of a minimally mutated clone in biopsies 9 and 7, taken during the on-NSAIDs period. (Panel C) Circos plot of individual j. A massive burst of SGAs was detected first in biopsy 8, in year 8.5, before the individual began regular NSAID use. Biopsy 2 (second inner ring), taken at the baseline endoscopy 8.5 years prior to the burst, shared a subset of the SGAs seen in the massively altered clone (chromosomes 10, 12, 17 and 18), and thus is likely an early example of its lineage. (Panels D and G) Consensus phylogenetic trees estimated by BEAST reveal long-term co-existence of clones. Branch lengths are scaled according to time, the tips of the phylogeny are biopsies aligned on the x-axis according to their sampling time, and all internal nodes are estimated coalescence times assuming a logistic population growth. Dashed gray line represents the start of NSAID use. (Panels E, F, H, I) Maximum parsimony trees estimated by PAUP reveal the ancestral relationships among biopsies based on shared SGA characters. Differences between the topology of the trees estimated by PAUP and BEAST are typically due to poorly supported short branches and do not affect the analyses of SGA acquisition rates. Branch lengths are scaled according to estimated number of SGAs (Panels E, H) or the amount of genome affected by SGA (Panels F, I). Note that these trees appear very different from those estimated by BEAST as the BEAST branch lengths are scaled by inferred time depth, and the rate of SGA accumulation appears highly variable with time.</p>"}
  • {"files"=>["http://files.figshare.com/1085550/Figure_5.tif"], "pos_in_sequence"=>0, "stats"=>{"downloads"=>0, "page_views"=>6, "likes"=>0}, "users"=>["Thomas G. Paulson", "Patricia C. Galipeau", "Carissa A. Sanchez", "Rumen L. Kostadinov", "Mary K. Kuhner", "Cassandra L. Sather", "Amitabh Srivastava", "Robert D. Odze", "Patricia L. Blount", "Thomas L. Vaughan", "Brian J. Reid", "Carlo C. Maley", "Xiaohong Li"], "links"=>[], "tags"=>["Genetic causes of cancer", "individuals", "Predisposing conditions and syndromes", "Cancers and neoplasms", "Early detection", "esophagus", "Computational biology", "Evolutionary modeling", "oncology", "population genetics", "Esophageal cancer", "Genome evolution", "Gastroenterology and hepatology", "Cancer detection and diagnosis", "genomics", "Gastrointestinal tumors", "Cancer risk factors", "chemoprevention", "mutation"], "title"=>"<p>Clonal evolution in individuals l and f.</p>", "figshare_url"=>"http://figshare.com/articles/_Clonal_evolution_in_individuals_l_and_f_/718783", "defined_type"=>1, "doi"=>["http://dx.doi.org/10.1371/journal.pgen.1003553.g005"], "published_date"=>"2013-06-13 02:26:23", "article_id"=>718783, "categories"=>["Biological Sciences", "Medicine"], "description"=>"<p>(Panel A) Amount of SGA in biopsies (dots) and mean SGA over all biopsies at that time point (lines) for individual l (black) and individual f (red). (Panels B and C) Circos plots showing genome-wide view of SGA over time (see <a href=\"http://www.plosgenetics.org/article/info:doi/10.1371/journal.pgen.1003553#pgen-1003553-g004\" target=\"_blank\">Figure 4</a> legend for details). (Panel B) Individual l. During the off-NSAID period we detected a whole-chromosome gain of chromosome 8 in biopsy 12 (green band) and copy-neutral LOH events on chromosome 1 in biopsies 9 and 11 (orange bands). (Panel C) We detected 1,844±573 of SGAs in individual f, who opted for esophagectomy for high-grade dysplasia after 6.4 years of follow-up and died of another cancer 11.9 years later. (Panels D, E, F) BEAST consensus tree, parsimony tree of SGA number, and parsimony tree of SGA quantity for individual l. (Panels G, H, I) BEAST consensus tree, parsimony tree of SGA number, and parsimony tree of SGA quantity for individual f. In both individuals, BEAST trees reveal long-term co-existence of multiple clones. and maximum parsimony trees reveal an underlying progressive evolution of SGA events irrespective of time. Phylogenetic trees generated as indicated in the legend to <a href=\"http://www.plosgenetics.org/article/info:doi/10.1371/journal.pgen.1003553#pgen-1003553-g004\" target=\"_blank\">Figure 4</a>.</p>"}

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Relative Metric

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