Digital Quantification of Gene Expression in Sequential Breast Cancer Biopsies Reveals Activation of an Immune Response
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{"title"=>"Digital Quantification of Gene Expression in Sequential Breast Cancer Biopsies Reveals Activation of an Immune Response", "type"=>"journal", "authors"=>[{"first_name"=>"Rinath M.", "last_name"=>"Jeselsohn", "scopus_author_id"=>"35279706600"}, {"first_name"=>"Lillian", "last_name"=>"Werner", "scopus_author_id"=>"35779446500"}, {"first_name"=>"Meredith M.", "last_name"=>"Regan", "scopus_author_id"=>"7103031293"}, {"first_name"=>"Aquila", "last_name"=>"Fatima", "scopus_author_id"=>"35787119400"}, {"first_name"=>"Lauren", "last_name"=>"Gilmore", "scopus_author_id"=>"37461313100"}, {"first_name"=>"Laura C.", "last_name"=>"Collins", "scopus_author_id"=>"35555297700"}, {"first_name"=>"Andrew H.", "last_name"=>"Beck", "scopus_author_id"=>"35363449100"}, {"first_name"=>"Shannon T.", "last_name"=>"Bailey", "scopus_author_id"=>"9239013100"}, {"first_name"=>"Housheng Hansen", "last_name"=>"He", "scopus_author_id"=>"35995538800"}, {"first_name"=>"Gilles", "last_name"=>"Buchwalter", "scopus_author_id"=>"6508329741"}, {"first_name"=>"Myles", "last_name"=>"Brown", "scopus_author_id"=>"56743782100"}, {"first_name"=>"J. Dirk", "last_name"=>"Iglehart", "scopus_author_id"=>"7101868932"}, {"first_name"=>"Andrea", "last_name"=>"Richardson", "scopus_author_id"=>"7402533820"}, {"first_name"=>"Steven E.", "last_name"=>"Come", "scopus_author_id"=>"7004820090"}], "year"=>2013, "source"=>"PLoS ONE", "identifiers"=>{"sgr"=>"84878550493", "pui"=>"369052304", "doi"=>"10.1371/journal.pone.0064225", "pmid"=>"23741308", "scopus"=>"2-s2.0-84878550493", "issn"=>"19326203", "isbn"=>"1932-6203"}, "id"=>"cb11366a-7658-356e-b3c7-c62af4a64366", "abstract"=>"Advancements in molecular biology have unveiled multiple breast cancer promoting pathways and potential therapeutic targets. Large randomized clinical trials remain the ultimate means of validating therapeutic efficacy, but they require large cohorts of patients and are lengthy and costly. A useful approach is to conduct a window of opportunity study in which patients are exposed to a drug pre-surgically during the interval between the core needle biopsy and the definitive surgery. These are non-therapeutic studies and the end point is not clinical or pathological response but rather evaluation of molecular changes in the tumor specimens that can predict response. However, since the end points of the non-therapeutic studies are biologic, it is critical to first define the biologic changes that occur in the absence of treatment. In this study, we compared the molecular profiles of breast cancer tumors at the time of the diagnostic biopsy versus the definitive surgery in the absence of any intervention using the Nanostring nCounter platform. We found that while the majority of the transcripts did not vary between the two biopsies, there was evidence of activation of immune related genes in response to the first biopsy and further investigations of the immune changes after a biopsy in early breast cancer seem warranted.", "link"=>"http://www.mendeley.com/research/digital-quantification-gene-expression-sequential-breast-cancer-biopsies-reveals-activation-immune-r", "reader_count"=>31, "reader_count_by_academic_status"=>{"Unspecified"=>3, "Professor > Associate Professor"=>2, "Student > Doctoral Student"=>2, "Researcher"=>7, "Student > Ph. D. Student"=>5, "Other"=>5, "Student > Master"=>3, "Student > Bachelor"=>2, "Lecturer > Senior Lecturer"=>1, "Professor"=>1}, "reader_count_by_user_role"=>{"Unspecified"=>3, "Professor > Associate Professor"=>2, "Student > Doctoral Student"=>2, "Researcher"=>7, "Student > Ph. D. Student"=>5, "Other"=>5, "Student > Master"=>3, "Student > Bachelor"=>2, "Lecturer > Senior Lecturer"=>1, "Professor"=>1}, "reader_count_by_subject_area"=>{"Unspecified"=>2, "Biochemistry, Genetics and Molecular Biology"=>4, "Mathematics"=>1, "Agricultural and Biological Sciences"=>13, "Medicine and Dentistry"=>9, "Psychology"=>2}, "reader_count_by_subdiscipline"=>{"Medicine and Dentistry"=>{"Medicine and Dentistry"=>9}, "Psychology"=>{"Psychology"=>2}, "Agricultural and Biological Sciences"=>{"Agricultural and Biological Sciences"=>13}, "Biochemistry, Genetics and Molecular Biology"=>{"Biochemistry, Genetics and Molecular Biology"=>4}, "Mathematics"=>{"Mathematics"=>1}, "Unspecified"=>{"Unspecified"=>2}}, "reader_count_by_country"=>{"Netherlands"=>1, "United Kingdom"=>1, "Australia"=>1}, "group_count"=>0}

Scopus | Further Information

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Figshare

  • {"files"=>["https://ndownloader.figshare.com/files/1071740"], "description"=>"<p>Unsupervised clustering heatmap of all samples using the PAM50 genes only. 19 of the 21 paired biopsies co-aggregated in the first level dendrogram.</p>", "links"=>[], "tags"=>["Computational biology", "Molecular genetics", "gene expression", "genetics", "Human genetics", "genetic testing", "Cancer genetics", "Genetic screens", "Genetics of disease", "genomics", "Genome analysis tools", "Genome expression analysis", "Genomic medicine", "Molecular cell biology", "oncology", "Cancers and neoplasms", "Breast tumors", "Invasive ductal carcinoma", "unsupervised", "clustering", "cnb", "ebs", "pam50"], "article_id"=>709741, "categories"=>["Medicine", "Biological Sciences"], "users"=>["Rinath M. Jeselsohn", "Lillian Werner", "Meredith M. Regan", "Aquila Fatima", "Lauren Gilmore", "Laura C. Collins", "Andrew H. Beck", "Shannon T. Bailey", "Housheng Hansen He", "Gilles Buchwalter", "Myles Brown", "J. Dirk Iglehart", "Andrea Richardson", "Steven E. Come"], "doi"=>"https://dx.doi.org/10.1371/journal.pone.0064225.g004", "stats"=>{"downloads"=>2, "page_views"=>125, "likes"=>0}, "figshare_url"=>"https://figshare.com/articles/_Heatmap_of_unsupervised_clustering_of_the_CNB_and_EBS_using_the_PAM50_genes_/709741", "title"=>"Heatmap of unsupervised clustering of the CNB and EBS using the PAM50 genes.", "pos_in_sequence"=>0, "defined_type"=>1, "published_date"=>"2013-05-31 02:42:21"}
  • {"files"=>["https://ndownloader.figshare.com/files/1071739"], "description"=>"<p>Unsupervised clustering heatmap of all samples using the Oncotype Dx genes only. 18 of the 21 paired biopsies co-aggregated in the first level dendrogram. Lower heatmap shows the Nanostring expression levels of the control housekeeping genes.</p>", "links"=>[], "tags"=>["Computational biology", "Molecular genetics", "gene expression", "genetics", "Human genetics", "genetic testing", "Cancer genetics", "Genetic screens", "Genetics of disease", "genomics", "Genome analysis tools", "Genome expression analysis", "Genomic medicine", "Molecular cell biology", "oncology", "Cancers and neoplasms", "Breast tumors", "Invasive ductal carcinoma", "unsupervised", "clustering", "cnb", "ebs", "oncotype", "dx"], "article_id"=>709740, "categories"=>["Medicine", "Biological Sciences"], "users"=>["Rinath M. Jeselsohn", "Lillian Werner", "Meredith M. Regan", "Aquila Fatima", "Lauren Gilmore", "Laura C. Collins", "Andrew H. Beck", "Shannon T. Bailey", "Housheng Hansen He", "Gilles Buchwalter", "Myles Brown", "J. Dirk Iglehart", "Andrea Richardson", "Steven E. Come"], "doi"=>"https://dx.doi.org/10.1371/journal.pone.0064225.g003", "stats"=>{"downloads"=>1, "page_views"=>80, "likes"=>0}, "figshare_url"=>"https://figshare.com/articles/_Heatmap_of_unsupervised_clustering_of_the_CNB_and_EBS_using_the_Oncotype_Dx_genes_/709740", "title"=>"Heatmap of unsupervised clustering of the CNB and EBS using the Oncotype Dx genes.", "pos_in_sequence"=>0, "defined_type"=>1, "published_date"=>"2013-05-31 02:42:20"}
  • {"files"=>["https://ndownloader.figshare.com/files/1071736"], "description"=>"<p>Color coding- green represents low nanostring expression level and red represents high nanostring expression level. Expression levels are log transformed. A. ER+/HER2 negative breast cancers had high ER expression and low HER2 Nanostring expression, HER2 positive tumors displayed high ERBB2 expression levels and triple negative (TN) cancers had low ER and HER2 expression levels. E = ER, P = PR, H = Her2. B. Ki67 high defined as an IHC score of above 14% and low as ≤14%. Scatter plot showing correlation between the Nanostring Ki67 expression level (Y axis) and IHC Ki67 score (x-axis).</p>", "links"=>[], "tags"=>["Computational biology", "Molecular genetics", "gene expression", "genetics", "Human genetics", "genetic testing", "Cancer genetics", "Genetic screens", "Genetics of disease", "genomics", "Genome analysis tools", "Genome expression analysis", "Genomic medicine", "Molecular cell biology", "oncology", "Cancers and neoplasms", "Breast tumors", "Invasive ductal carcinoma", "cnbs", "nanostring", "ncounter"], "article_id"=>709737, "categories"=>["Medicine", "Biological Sciences"], "users"=>["Rinath M. Jeselsohn", "Lillian Werner", "Meredith M. Regan", "Aquila Fatima", "Lauren Gilmore", "Laura C. Collins", "Andrew H. Beck", "Shannon T. Bailey", "Housheng Hansen He", "Gilles Buchwalter", "Myles Brown", "J. Dirk Iglehart", "Andrea Richardson", "Steven E. Come"], "doi"=>"https://dx.doi.org/10.1371/journal.pone.0064225.g001", "stats"=>{"downloads"=>0, "page_views"=>28, "likes"=>0}, "figshare_url"=>"https://figshare.com/articles/_Correlation_between_CNBs_clinical_data_and_Nanostring_nCounter_expression_values_/709737", "title"=>"Correlation between CNBs clinical data and Nanostring nCounter expression values.", "pos_in_sequence"=>0, "defined_type"=>1, "published_date"=>"2013-05-31 02:42:17"}
  • {"files"=>["https://ndownloader.figshare.com/files/1071746", "https://ndownloader.figshare.com/files/1071747", "https://ndownloader.figshare.com/files/1071749", "https://ndownloader.figshare.com/files/1071750", "https://ndownloader.figshare.com/files/1071751", "https://ndownloader.figshare.com/files/1071752"], "description"=>"<div><p>Advancements in molecular biology have unveiled multiple breast cancer promoting pathways and potential therapeutic targets. Large randomized clinical trials remain the ultimate means of validating therapeutic efficacy, but they require large cohorts of patients and are lengthy and costly. A useful approach is to conduct a window of opportunity study in which patients are exposed to a drug pre-surgically during the interval between the core needle biopsy and the definitive surgery. These are non-therapeutic studies and the end point is not clinical or pathological response but rather evaluation of molecular changes in the tumor specimens that can predict response. However, since the end points of the non-therapeutic studies are biologic, it is critical to first define the biologic changes that occur in the absence of treatment. In this study, we compared the molecular profiles of breast cancer tumors at the time of the diagnostic biopsy versus the definitive surgery in the absence of any intervention using the Nanostring nCounter platform. We found that while the majority of the transcripts did not vary between the two biopsies, there was evidence of activation of immune related genes in response to the first biopsy and further investigations of the immune changes after a biopsy in early breast cancer seem warranted.</p></div>", "links"=>[], "tags"=>["Computational biology", "Molecular genetics", "gene expression", "genetics", "Human genetics", "genetic testing", "Cancer genetics", "Genetic screens", "Genetics of disease", "genomics", "Genome analysis tools", "Genome expression analysis", "Genomic medicine", "Molecular cell biology", "oncology", "Cancers and neoplasms", "Breast tumors", "Invasive ductal carcinoma", "quantification", "sequential", "cancer", "biopsies", "reveals", "activation"], "article_id"=>709745, "categories"=>["Medicine", "Biological Sciences"], "users"=>["Rinath M. Jeselsohn", "Lillian Werner", "Meredith M. Regan", "Aquila Fatima", "Lauren Gilmore", "Laura C. Collins", "Andrew H. Beck", "Shannon T. Bailey", "Housheng Hansen He", "Gilles Buchwalter", "Myles Brown", "J. Dirk Iglehart", "Andrea Richardson", "Steven E. Come"], "doi"=>["https://dx.doi.org/10.1371/journal.pone.0064225.s001", "https://dx.doi.org/10.1371/journal.pone.0064225.s002", "https://dx.doi.org/10.1371/journal.pone.0064225.s003", "https://dx.doi.org/10.1371/journal.pone.0064225.s004", "https://dx.doi.org/10.1371/journal.pone.0064225.s005", "https://dx.doi.org/10.1371/journal.pone.0064225.s006"], "stats"=>{"downloads"=>2, "page_views"=>6, "likes"=>0}, "figshare_url"=>"https://figshare.com/articles/_Digital_Quantification_of_Gene_Expression_in_Sequential_Breast_Cancer_Biopsies_Reveals_Activation_of_an_Immune_Response_/709745", "title"=>"Digital Quantification of Gene Expression in Sequential Breast Cancer Biopsies Reveals Activation of an Immune Response", "pos_in_sequence"=>0, "defined_type"=>4, "published_date"=>"2013-05-31 02:42:25"}
  • {"files"=>["https://ndownloader.figshare.com/files/1071744"], "description"=>"<p><b>a</b> and <b>b</b> represent Ki67 staining of CNB and EB respectively and <b>c</b> and <b>d</b> represent CD68 staining in a CNB and EB. Magnification 20×. A. Box plots of the Immunohistochemistry scoring for Ki67 and CD68 in the CNB samples and EBs.</p>", "links"=>[], "tags"=>["Computational biology", "Molecular genetics", "gene expression", "genetics", "Human genetics", "genetic testing", "Cancer genetics", "Genetic screens", "Genetics of disease", "genomics", "Genome analysis tools", "Genome expression analysis", "Genomic medicine", "Molecular cell biology", "oncology", "Cancers and neoplasms", "Breast tumors", "Invasive ductal carcinoma", "cnbs"], "article_id"=>709743, "categories"=>["Medicine", "Biological Sciences"], "users"=>["Rinath M. Jeselsohn", "Lillian Werner", "Meredith M. Regan", "Aquila Fatima", "Lauren Gilmore", "Laura C. Collins", "Andrew H. Beck", "Shannon T. Bailey", "Housheng Hansen He", "Gilles Buchwalter", "Myles Brown", "J. Dirk Iglehart", "Andrea Richardson", "Steven E. Come"], "doi"=>"https://dx.doi.org/10.1371/journal.pone.0064225.g006", "stats"=>{"downloads"=>0, "page_views"=>12, "likes"=>0}, "figshare_url"=>"https://figshare.com/articles/_Immunohistochemistry_analysis_of_CNBs_and_EBs_/709743", "title"=>"Immunohistochemistry analysis of CNBs and EBs.", "pos_in_sequence"=>0, "defined_type"=>1, "published_date"=>"2013-05-31 02:42:23"}
  • {"files"=>["https://ndownloader.figshare.com/files/1071745"], "description"=>"<p>Clinical characteristics of the participating patients.</p>", "links"=>[], "tags"=>["Computational biology", "Molecular genetics", "gene expression", "genetics", "Human genetics", "genetic testing", "Cancer genetics", "Genetic screens", "Genetics of disease", "genomics", "Genome analysis tools", "Genome expression analysis", "Genomic medicine", "Molecular cell biology", "oncology", "Cancers and neoplasms", "Breast tumors", "Invasive ductal carcinoma", "participating"], "article_id"=>709744, "categories"=>["Medicine", "Biological Sciences"], "users"=>["Rinath M. Jeselsohn", "Lillian Werner", "Meredith M. Regan", "Aquila Fatima", "Lauren Gilmore", "Laura C. Collins", "Andrew H. Beck", "Shannon T. Bailey", "Housheng Hansen He", "Gilles Buchwalter", "Myles Brown", "J. Dirk Iglehart", "Andrea Richardson", "Steven E. Come"], "doi"=>"https://dx.doi.org/10.1371/journal.pone.0064225.t001", "stats"=>{"downloads"=>1, "page_views"=>10, "likes"=>0}, "figshare_url"=>"https://figshare.com/articles/_Clinical_characteristics_of_the_participating_patients_/709744", "title"=>"Clinical characteristics of the participating patients.", "pos_in_sequence"=>0, "defined_type"=>3, "published_date"=>"2013-05-31 02:42:24"}
  • {"files"=>["https://ndownloader.figshare.com/files/1071742"], "description"=>"<p>A. Individual patient plots (n = 21) for NanoString expression level at the time of the CNB and EB for Ki67, CD68, and VEGFA. P-values are from Wilcoxon signed rank tests. B. Bar graph represents the Nanostring expression value differences between the CNB and EBs for all the genes that had a statistically significant change (by Wilcoxon signed rank tests). <b>*</b> denotes genes with immune related functions.</p>", "links"=>[], "tags"=>["Computational biology", "Molecular genetics", "gene expression", "genetics", "Human genetics", "genetic testing", "Cancer genetics", "Genetic screens", "Genetics of disease", "genomics", "Genome analysis tools", "Genome expression analysis", "Genomic medicine", "Molecular cell biology", "oncology", "Cancers and neoplasms", "Breast tumors", "Invasive ductal carcinoma", "genes", "cnbs"], "article_id"=>709742, "categories"=>["Medicine", "Biological Sciences"], "users"=>["Rinath M. Jeselsohn", "Lillian Werner", "Meredith M. Regan", "Aquila Fatima", "Lauren Gilmore", "Laura C. Collins", "Andrew H. Beck", "Shannon T. Bailey", "Housheng Hansen He", "Gilles Buchwalter", "Myles Brown", "J. Dirk Iglehart", "Andrea Richardson", "Steven E. Come"], "doi"=>"https://dx.doi.org/10.1371/journal.pone.0064225.g005", "stats"=>{"downloads"=>4, "page_views"=>16, "likes"=>0}, "figshare_url"=>"https://figshare.com/articles/_Changes_in_the_expression_levels_of_immune_related_genes_between_CNBs_and_EBs_/709742", "title"=>"Changes in the expression levels of immune related genes between CNBs and EBs.", "pos_in_sequence"=>0, "defined_type"=>1, "published_date"=>"2013-05-31 02:42:22"}
  • {"files"=>["https://ndownloader.figshare.com/files/1071738"], "description"=>"<p>Heatmap of unsupervised clustering of all the samples and all the transcripts. All of the CNB and EB pairs co-aggregated at the first level dendrogram.</p>", "links"=>[], "tags"=>["Computational biology", "Molecular genetics", "gene expression", "genetics", "Human genetics", "genetic testing", "Cancer genetics", "Genetic screens", "Genetics of disease", "genomics", "Genome analysis tools", "Genome expression analysis", "Genomic medicine", "Molecular cell biology", "oncology", "Cancers and neoplasms", "Breast tumors", "Invasive ductal carcinoma", "unsupervised", "clustering", "cnb", "eb"], "article_id"=>709739, "categories"=>["Medicine", "Biological Sciences"], "users"=>["Rinath M. Jeselsohn", "Lillian Werner", "Meredith M. Regan", "Aquila Fatima", "Lauren Gilmore", "Laura C. Collins", "Andrew H. Beck", "Shannon T. Bailey", "Housheng Hansen He", "Gilles Buchwalter", "Myles Brown", "J. Dirk Iglehart", "Andrea Richardson", "Steven E. Come"], "doi"=>"https://dx.doi.org/10.1371/journal.pone.0064225.g002", "stats"=>{"downloads"=>2, "page_views"=>12, "likes"=>0}, "figshare_url"=>"https://figshare.com/articles/_Heatmap_of_unsupervised_clustering_of_both_the_CNB_and_EB_samples_/709739", "title"=>"Heatmap of unsupervised clustering of both the CNB and EB samples.", "pos_in_sequence"=>0, "defined_type"=>1, "published_date"=>"2013-05-31 02:42:19"}

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Relative Metric

{"start_date"=>"2013-01-01T00:00:00Z", "end_date"=>"2013-12-31T00:00:00Z", "subject_areas"=>[{"subject_area"=>"/Biology and life sciences", "average_usage"=>[269, 466, 588, 697, 800, 896, 988, 1076, 1165, 1254, 1340, 1417]}, {"subject_area"=>"/Biology and life sciences/Genetics", "average_usage"=>[284, 491, 620, 738, 843, 945, 1043, 1137, 1225, 1315, 1400, 1479, 1555]}, {"subject_area"=>"/Engineering and technology", "average_usage"=>[254, 440, 558, 675, 785, 883, 972, 1061, 1154, 1248, 1336, 1414, 1489]}]}
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