Whole Transcriptome RNA-Seq Analysis of Breast Cancer Recurrence Risk Using Formalin-Fixed Paraffin-Embedded Tumor Tissue
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{"title"=>"Whole transcriptome RNA-seq analysis of breast cancer recurrence risk using formalin-fixed paraffin-embedded tumor tissue", "type"=>"journal", "authors"=>[{"first_name"=>"Dominick", "last_name"=>"Sinicropi", "scopus_author_id"=>"6603927609"}, {"first_name"=>"Kunbin", "last_name"=>"Qu", "scopus_author_id"=>"55311621700"}, {"first_name"=>"Francois", "last_name"=>"Collin", "scopus_author_id"=>"8269178000"}, {"first_name"=>"Michael", "last_name"=>"Crager", "scopus_author_id"=>"6506912815"}, {"first_name"=>"Mei Lan", "last_name"=>"Liu", "scopus_author_id"=>"56070319300"}, {"first_name"=>"Robert J.", "last_name"=>"Pelham", "scopus_author_id"=>"6701584120"}, {"first_name"=>"Mylan", "last_name"=>"Pho", "scopus_author_id"=>"7801552795"}, {"first_name"=>"Andrewi", "last_name"=>"de Rossi", "scopus_author_id"=>"55311878500"}, {"first_name"=>"Jennie", "last_name"=>"Jeong", "scopus_author_id"=>"16426004500"}, {"first_name"=>"Aaron", "last_name"=>"Scott", "scopus_author_id"=>"7403271725"}, {"first_name"=>"Ranjana", "last_name"=>"Ambannavar", "scopus_author_id"=>"41660979600"}, {"first_name"=>"Christina", "last_name"=>"Zheng", "scopus_author_id"=>"55312028200"}, {"first_name"=>"Raul", "last_name"=>"Mena", "scopus_author_id"=>"16304705700"}, {"first_name"=>"Jose", "last_name"=>"Esteban", "scopus_author_id"=>"57190675267"}, {"first_name"=>"James", "last_name"=>"Stephans", "scopus_author_id"=>"6603499481"}, {"first_name"=>"John", "last_name"=>"Morlan", "scopus_author_id"=>"6507162801"}, {"first_name"=>"Joffre", "last_name"=>"Baker", "scopus_author_id"=>"56327790700"}], "year"=>2012, "source"=>"PLoS ONE", "identifiers"=>{"sgr"=>"84863763618", "doi"=>"10.1371/journal.pone.0040092", "pmid"=>"22808097", "issn"=>"19326203", "scopus"=>"2-s2.0-84863763618", "pui"=>"365232365"}, "id"=>"16de8124-3663-3dac-8a78-9ef907c27eb5", "abstract"=>"RNA biomarkers discovered by RT-PCR-based gene expression profiling of archival formalin-fixed paraffin-embedded (FFPE) tissue form the basis for widely used clinical diagnostic tests; however, RT-PCR is practically constrained in the number of transcripts that can be interrogated. We have developed and optimized RNA-Seq library chemistry as well as bioinformatics and biostatistical methods for whole transcriptome profiling from FFPE tissue. The chemistry accommodates low RNA inputs and sample multiplexing. These methods both enable rediscovery of RNA biomarkers for disease recurrence risk that were previously identified by RT-PCR analysis of a cohort of 136 patients, and also identify a high percentage of recurrence risk markers that were previously discovered using DNA microarrays in a separate cohort of patients, evidence that this RNA-Seq technology has sufficient precision and sensitivity for biomarker discovery. More than two thousand RNAs are strongly associated with breast cancer recurrence risk in the 136 patient cohort (FDR <10%). Many of these are intronic RNAs for which corresponding exons are not also associated with disease recurrence. A number of the RNAs associated with recurrence risk belong to novel RNA networks. It will be important to test the validity of these novel associations in whole transcriptome RNA-Seq screens of other breast cancer cohorts.", "link"=>"http://www.mendeley.com/research/whole-transcriptome-rnaseq-analysis-breast-cancer-recurrence-risk-using-formalinfixed-paraffinembedd-2", "reader_count"=>121, "reader_count_by_academic_status"=>{"Unspecified"=>3, "Professor > Associate Professor"=>4, "Librarian"=>1, "Researcher"=>47, "Student > Doctoral Student"=>3, "Student > Ph. D. Student"=>22, "Student > Postgraduate"=>6, "Student > Master"=>11, "Other"=>11, "Student > Bachelor"=>4, "Lecturer > Senior Lecturer"=>1, "Professor"=>8}, "reader_count_by_user_role"=>{"Unspecified"=>3, "Professor > Associate Professor"=>4, "Librarian"=>1, "Researcher"=>47, "Student > Doctoral Student"=>3, "Student > Ph. D. Student"=>22, "Student > Postgraduate"=>6, "Student > Master"=>11, "Other"=>11, "Student > Bachelor"=>4, "Lecturer > Senior Lecturer"=>1, "Professor"=>8}, "reader_count_by_subject_area"=>{"Engineering"=>1, "Unspecified"=>3, "Biochemistry, Genetics and Molecular Biology"=>20, "Mathematics"=>2, "Medicine and Dentistry"=>16, "Agricultural and Biological Sciences"=>69, "Neuroscience"=>1, "Veterinary Science and Veterinary Medicine"=>1, "Chemistry"=>2, "Computer Science"=>5, "Energy"=>1}, "reader_count_by_subdiscipline"=>{"Engineering"=>{"Engineering"=>1}, "Medicine and Dentistry"=>{"Medicine and Dentistry"=>16}, "Neuroscience"=>{"Neuroscience"=>1}, "Chemistry"=>{"Chemistry"=>2}, "Energy"=>{"Energy"=>1}, "Agricultural and Biological Sciences"=>{"Agricultural and Biological Sciences"=>69}, "Computer Science"=>{"Computer Science"=>5}, "Biochemistry, Genetics and Molecular Biology"=>{"Biochemistry, Genetics and Molecular Biology"=>20}, "Mathematics"=>{"Mathematics"=>2}, "Unspecified"=>{"Unspecified"=>3}, "Veterinary Science and Veterinary Medicine"=>{"Veterinary Science and Veterinary Medicine"=>1}}, "reader_count_by_country"=>{"Sweden"=>1, "Vietnam"=>1, "Hungary"=>1, "United States"=>6, "Denmark"=>1, "Poland"=>1, "South Africa"=>1, "France"=>1, "Australia"=>1, "Germany"=>1, "Spain"=>2}, "group_count"=>6}

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Figshare

  • {"files"=>["https://ndownloader.figshare.com/files/609974"], "description"=>"<p>Among the set of 1307 identified RefSeq RNAs, a subset was selected that contains all RNAs that co-express (at R>0.6) with at least one other RNA in the set of 1307. Cytoscape 2.8 visualization <a href=\"http://www.plosone.org/article/info:doi/10.1371/journal.pone.0040092#pone.0040092-Shannon1\" target=\"_blank\">[31]</a>, <a href=\"http://www.plosone.org/article/info:doi/10.1371/journal.pone.0040092#pone.0040092-Smoot1\" target=\"_blank\">[32]</a>. The degree of node interaction (total number of co-expression interactions) is mapped to node size and color (indicated by scale). Biological annotation of genes that are highly represented in identified networks is indicated by letter labels. <b>A</b>: cell cycle; <b>B</b>: co-expression with ESR1; <b>C</b>: genes mapping to Ch17q23-24; <b>D</b>: genes mapping to Chr821-24; <b>E</b>: genes mapping to Chr9q22; <b>F</b>: olfactory signaling, glucose metabolism, glucuronidation.</p>", "links"=>[], "tags"=>["refseq", "rna", "networks"], "article_id"=>280449, "categories"=>["Cancer", "Biological Sciences", "Genetics"], "users"=>["Dominick Sinicropi", "Kunbin Qu", "Francois Collin", "Michael Crager", "Mei-Lan Liu", "Robert J. Pelham", "Mylan Pho", "Andrew Dei Rossi", "Jennie Jeong", "Aaron Scott", "Ranjana Ambannavar", "Christina Zheng", "Raul Mena", "Jose Esteban", "James Stephans", "John Morlan", "Joffre Baker"], "doi"=>"https://dx.doi.org/10.1371/journal.pone.0040092.g004", "stats"=>{"downloads"=>0, "page_views"=>1, "likes"=>0}, "figshare_url"=>"https://figshare.com/articles/_Multiple_RefSeq_RNA_networks_with_common_biological_themes_/280449", "title"=>"Multiple RefSeq RNA networks with common biological themes.", "pos_in_sequence"=>0, "defined_type"=>1, "published_date"=>"2012-07-13 00:07:29"}
  • {"files"=>["https://ndownloader.figshare.com/files/609815"], "description"=>"<p>Each point represents a patient tumor. The bottom and top of the box are the 25<sup>th</sup> and 75<sup>th</sup> percentiles and the band within the box is the 50<sup>th</sup> percentile (the median) of the points in the group. The ends of the vertical lines represent the lowest datum still within 1.5 interquartile range of the lower quartile, and the highest datum still within 1.5 interquartile range of the upper quartile. Values from RNA-Seq (left panel) and RT-PCR (right panel) are shown: <b>A.</b> BCL2. <b>B.</b> GSTM1. <b>C.</b> AURKA. <b>D.</b> MKI67.</p>", "links"=>[], "tags"=>["plots", "normalized", "rnas", "cancer", "stratified", "recurrence"], "article_id"=>280291, "categories"=>["Cancer", "Biological Sciences", "Genetics"], "users"=>["Dominick Sinicropi", "Kunbin Qu", "Francois Collin", "Michael Crager", "Mei-Lan Liu", "Robert J. Pelham", "Mylan Pho", "Andrew Dei Rossi", "Jennie Jeong", "Aaron Scott", "Ranjana Ambannavar", "Christina Zheng", "Raul Mena", "Jose Esteban", "James Stephans", "John Morlan", "Joffre Baker"], "doi"=>"https://dx.doi.org/10.1371/journal.pone.0040092.g003", "stats"=>{"downloads"=>1, "page_views"=>13, "likes"=>0}, "figshare_url"=>"https://figshare.com/articles/_Box_plots_of_normalized_expression_values_of_RNAs_in_breast_cancer_patients_stratified_by_recurrence_status_/280291", "title"=>"Box plots of normalized expression values of RNAs in breast cancer patients, stratified by recurrence status.", "pos_in_sequence"=>0, "defined_type"=>1, "published_date"=>"2012-07-13 00:04:51"}
  • {"files"=>["https://ndownloader.figshare.com/files/609542"], "description"=>"<p>RT-PCR results versus RNA-Seq results. Each point represents a distinct RNA. Genes in the 21-gene breast cancer recurrence risk assay are marked with alphanumeric symbols.</p>", "links"=>[], "tags"=>["recurrence", "ratios", "rna"], "article_id"=>280021, "categories"=>["Cancer", "Biological Sciences", "Genetics"], "users"=>["Dominick Sinicropi", "Kunbin Qu", "Francois Collin", "Michael Crager", "Mei-Lan Liu", "Robert J. Pelham", "Mylan Pho", "Andrew Dei Rossi", "Jennie Jeong", "Aaron Scott", "Ranjana Ambannavar", "Christina Zheng", "Raul Mena", "Jose Esteban", "James Stephans", "John Morlan", "Joffre Baker"], "doi"=>"https://dx.doi.org/10.1371/journal.pone.0040092.g001", "stats"=>{"downloads"=>1, "page_views"=>24, "likes"=>0}, "figshare_url"=>"https://figshare.com/articles/_Scatter_plot_of_recurrence_risk_hazard_ratios_of_RNA_sequences_/280021", "title"=>"Scatter plot of recurrence risk hazard ratios of RNA sequences.", "pos_in_sequence"=>0, "defined_type"=>1, "published_date"=>"2012-07-13 00:00:21"}
  • {"files"=>["https://ndownloader.figshare.com/files/610081"], "description"=>"<p>*Number across entire 136 patient population.</p>", "links"=>[], "tags"=>["median", "rna"], "article_id"=>280556, "categories"=>["Cancer", "Biological Sciences", "Genetics"], "users"=>["Dominick Sinicropi", "Kunbin Qu", "Francois Collin", "Michael Crager", "Mei-Lan Liu", "Robert J. Pelham", "Mylan Pho", "Andrew Dei Rossi", "Jennie Jeong", "Aaron Scott", "Ranjana Ambannavar", "Christina Zheng", "Raul Mena", "Jose Esteban", "James Stephans", "John Morlan", "Joffre Baker"], "doi"=>"https://dx.doi.org/10.1371/journal.pone.0040092.t001", "stats"=>{"downloads"=>3, "page_views"=>6, "likes"=>0}, "figshare_url"=>"https://figshare.com/articles/_Relation_of_median_RNA_count_with_frequency_of_RNA_identification_at_FDR_lt_10_/280556", "title"=>"Relation of median RNA count with frequency of RNA identification at FDR<10%.", "pos_in_sequence"=>0, "defined_type"=>3, "published_date"=>"2012-07-13 00:09:16"}
  • {"files"=>["https://ndownloader.figshare.com/files/609695"], "description"=>"<p>Each point represents a distinct RNA. The magnitude of the effect size is given by the hazard ratio from Cox proportional hazard analysis and statistical significance by P-Value. Genes in the 21-gene breast cancer recurrence risk assay are marked with alphanumeric symbols. <b>A.</b> Analysis of 192 genes measured by RT-PCR. <b>B.</b> Analysis of assembled RefSeq transcripts as measured by whole transcriptome RNA-Seq.</p>", "links"=>[], "tags"=>["rna", "cancer", "recurrence", "136"], "article_id"=>280173, "categories"=>["Cancer", "Biological Sciences", "Genetics"], "users"=>["Dominick Sinicropi", "Kunbin Qu", "Francois Collin", "Michael Crager", "Mei-Lan Liu", "Robert J. Pelham", "Mylan Pho", "Andrew Dei Rossi", "Jennie Jeong", "Aaron Scott", "Ranjana Ambannavar", "Christina Zheng", "Raul Mena", "Jose Esteban", "James Stephans", "John Morlan", "Joffre Baker"], "doi"=>"https://dx.doi.org/10.1371/journal.pone.0040092.g002", "stats"=>{"downloads"=>0, "page_views"=>1, "likes"=>0}, "figshare_url"=>"https://figshare.com/articles/_Relationship_of_increased_RNA_expression_to_risk_of_breast_cancer_recurrence_in_136_breast_cancer_patients_/280173", "title"=>"Relationship of increased RNA expression to risk of breast cancer recurrence in 136 breast cancer patients.", "pos_in_sequence"=>0, "defined_type"=>1, "published_date"=>"2012-07-13 00:02:53"}
  • {"files"=>["https://ndownloader.figshare.com/files/317801", "https://ndownloader.figshare.com/files/317846", "https://ndownloader.figshare.com/files/317913", "https://ndownloader.figshare.com/files/317962", "https://ndownloader.figshare.com/files/318008", "https://ndownloader.figshare.com/files/318044", "https://ndownloader.figshare.com/files/318073", "https://ndownloader.figshare.com/files/318105", "https://ndownloader.figshare.com/files/318117", "https://ndownloader.figshare.com/files/318150", "https://ndownloader.figshare.com/files/318191", "https://ndownloader.figshare.com/files/318214"], "description"=>"<div><p>RNA biomarkers discovered by RT-PCR-based gene expression profiling of archival formalin-fixed paraffin-embedded (FFPE) tissue form the basis for widely used clinical diagnostic tests; however, RT-PCR is practically constrained in the number of transcripts that can be interrogated. We have developed and optimized RNA-Seq library chemistry as well as bioinformatics and biostatistical methods for whole transcriptome profiling from FFPE tissue. The chemistry accommodates low RNA inputs and sample multiplexing. These methods both enable rediscovery of RNA biomarkers for disease recurrence risk that were previously identified by RT-PCR analysis of a cohort of 136 patients, and also identify a high percentage of recurrence risk markers that were previously discovered using DNA microarrays in a separate cohort of patients, evidence that this RNA-Seq technology has sufficient precision and sensitivity for biomarker discovery. More than two thousand RNAs are strongly associated with breast cancer recurrence risk in the 136 patient cohort (FDR <10%). Many of these are intronic RNAs for which corresponding exons are not also associated with disease recurrence. A number of the RNAs associated with recurrence risk belong to novel RNA networks. It will be important to test the validity of these novel associations in whole transcriptome RNA-Seq screens of other breast cancer cohorts.</p> </div>", "links"=>[], "tags"=>["transcriptome", "rna-seq", "cancer", "recurrence", "formalin-fixed", "paraffin-embedded"], "article_id"=>122733, "categories"=>["Cancer", "Biological Sciences", "Genetics"], "users"=>["Dominick Sinicropi", "Kunbin Qu", "Francois Collin", "Michael Crager", "Mei-Lan Liu", "Robert J. Pelham", "Mylan Pho", "Andrew Dei Rossi", "Jennie Jeong", "Aaron Scott", "Ranjana Ambannavar", "Christina Zheng", "Raul Mena", "Jose Esteban", "James Stephans", "John Morlan", "Joffre Baker"], "doi"=>["https://dx.doi.org/10.1371/journal.pone.0040092.s001", "https://dx.doi.org/10.1371/journal.pone.0040092.s002", "https://dx.doi.org/10.1371/journal.pone.0040092.s003", "https://dx.doi.org/10.1371/journal.pone.0040092.s004", "https://dx.doi.org/10.1371/journal.pone.0040092.s005", "https://dx.doi.org/10.1371/journal.pone.0040092.s006", "https://dx.doi.org/10.1371/journal.pone.0040092.s007", "https://dx.doi.org/10.1371/journal.pone.0040092.s008", "https://dx.doi.org/10.1371/journal.pone.0040092.s009", "https://dx.doi.org/10.1371/journal.pone.0040092.s010", "https://dx.doi.org/10.1371/journal.pone.0040092.s011", "https://dx.doi.org/10.1371/journal.pone.0040092.s012"], "stats"=>{"downloads"=>22, "page_views"=>11, "likes"=>0}, "figshare_url"=>"https://figshare.com/articles/Whole_Transcriptome_RNA_Seq_Analysis_of_Breast_Cancer_Recurrence_Risk_Using_Formalin_Fixed_Paraffin_Embedded_Tumor_Tissue/122733", "title"=>"Whole Transcriptome RNA-Seq Analysis of Breast Cancer Recurrence Risk Using Formalin-Fixed Paraffin-Embedded Tumor Tissue", "pos_in_sequence"=>0, "defined_type"=>4, "published_date"=>"2012-07-13 00:45:33"}

PMC Usage Stats | Further Information

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Relative Metric

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