Differential In Vivo Tumorigenicity of Distinct Subpopulations from a Luminal-Like Breast Cancer Xenograft
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Mendeley | Further Information

{"title"=>"Differential in vivo tumorigenicity of distinct subpopulations from a luminal-like breast cancer xenograft", "type"=>"journal", "authors"=>[{"first_name"=>"Nirma", "last_name"=>"Skrbo", "scopus_author_id"=>"36182549100"}, {"first_name"=>"Geir Olav", "last_name"=>"Hjortland", "scopus_author_id"=>"6603119725"}, {"first_name"=>"Alexandr", "last_name"=>"Kristian", "scopus_author_id"=>"35751198700"}, {"first_name"=>"Ruth", "last_name"=>"Holm", "scopus_author_id"=>"7202326373"}, {"first_name"=>"Silje", "last_name"=>"Nord", "scopus_author_id"=>"55357367600"}, {"first_name"=>"Lina", "last_name"=>"Prasmickaite", "scopus_author_id"=>"6603673299"}, {"first_name"=>"Olav", "last_name"=>"Engebraaten", "scopus_author_id"=>"6701392798"}, {"first_name"=>"Gunhild M.", "last_name"=>"Mælandsmo", "scopus_author_id"=>"7004305861"}, {"first_name"=>"Therese", "last_name"=>"Sørlie", "scopus_author_id"=>"7004332362"}, {"first_name"=>"Kristin", "last_name"=>"Andersen", "scopus_author_id"=>"7402451571"}], "year"=>2014, "source"=>"PLoS ONE", "identifiers"=>{"pmid"=>"25419568", "issn"=>"19326203", "doi"=>"10.1371/journal.pone.0113278", "pui"=>"600596115", "isbn"=>"1932-6203", "scopus"=>"2-s2.0-84912573852", "sgr"=>"84912573852"}, "id"=>"278ce93d-81f3-3108-8a2e-0af4a74f76a8", "abstract"=>"Intratumor heterogeneity caused by genetic, phenotypic or functional differences between cancer cell subpopulations is a considerable clinical challenge. Understanding subpopulation dynamics is therefore central for both optimization of existing therapy and for development of new treatment. The aim of this study was to isolate subpopulations from a primary tumor and by comparing molecular characteristics of these subpopulations, find explanations to their differing tumorigenicity. Cell subpopulations from two patient derived in vivo models of primary breast cancer, ER+ and ER-, were identified. EpCAM+ cells from the ER+ model gave rise to tumors independently of stroma cell support. The tumorigenic fraction was further divided based on SSEA-4 and CD24 expression. Both markers were expressed in ER+ breast cancer biopsies. FAC-sorted cells based on EpCAM, SSEA-4 and CD24 expression were subsequently tested for differences in functionality by in vivo tumorigenicity assay. Three out of four subpopulations of cells were tumorigenic and showed variable ability to recapitulate the marker expression of the original tumor. Whole genome expression analysis of the sorted populations disclosed high similarity in the transcriptional profiles between the tumorigenic populations. Comparing the non-tumorigenic vs the tumorigenic populations, 44 transcripts were, however, significantly differentially expressed. A subset of these, 26 identified and named genes, highly expressed in the non-tumorigenic population, predicted longer overall survival (N = 737, p<0.0001) and distant metastasis free survival (DMFS) (N = 1379, p<0.0001) when performing Kaplan-Meier survival analysis using the GOBO online database. The 26 gene set correlated with longer DMFS in multiple breast cancer subgroups. Copy number profiling revealed no aberrations that could explain the observed differences in tumorigenicity. This study emphasizes the functional variability among cell populations that are otherwise genomically similar, and that the risk of breast cancer recurrence can only be eliminated if the tumorigenic abilities in multiple cancer cell subpopulations are inhibited.", "link"=>"http://www.mendeley.com/research/differential-vivo-tumorigenicity-distinct-subpopulations-luminallike-breast-cancer-xenograft", "reader_count"=>24, "reader_count_by_academic_status"=>{"Professor > Associate Professor"=>7, "Researcher"=>3, "Student > Ph. D. Student"=>8, "Student > Postgraduate"=>1, "Student > Master"=>2, "Student > Bachelor"=>3}, "reader_count_by_user_role"=>{"Professor > Associate Professor"=>7, "Researcher"=>3, "Student > Ph. D. Student"=>8, "Student > Postgraduate"=>1, "Student > Master"=>2, "Student > Bachelor"=>3}, "reader_count_by_subject_area"=>{"Engineering"=>1, "Biochemistry, Genetics and Molecular Biology"=>1, "Agricultural and Biological Sciences"=>8, "Medicine and Dentistry"=>10, "Psychology"=>1, "Computer Science"=>1, "Immunology and Microbiology"=>2}, "reader_count_by_subdiscipline"=>{"Engineering"=>{"Engineering"=>1}, "Medicine and Dentistry"=>{"Medicine and Dentistry"=>10}, "Psychology"=>{"Psychology"=>1}, "Immunology and Microbiology"=>{"Immunology and Microbiology"=>2}, "Agricultural and Biological Sciences"=>{"Agricultural and Biological Sciences"=>8}, "Computer Science"=>{"Computer Science"=>1}, "Biochemistry, Genetics and Molecular Biology"=>{"Biochemistry, Genetics and Molecular Biology"=>1}}, "reader_count_by_country"=>{"United Kingdom"=>1, "France"=>1, "Germany"=>1}, "group_count"=>0}

Scopus | Further Information

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Figshare

  • {"files"=>["https://ndownloader.figshare.com/files/1805277"], "description"=>"<p>A) Concept figure illustrating the workflow of the <i>in vivo</i> tumorigenicity assays. The FAC-sorted populations are indicated by color in the dot plot. Red indicates SSEA-4<sup>hi</sup>, blue indicate dbl.high, green indicate CD24<sup>hi</sup> and black dots indicate dbl.low cells. B) Growth curves of tumors resulting from injection of FAC-sorted pure populations. 4×10<sup>4</sup> cells from each fraction were injected in the right mammary fat pad of NSG γ null mice. Tumor diameter was measured twice each week. C) Flow cytometry analysis of EpCAM positive cells from the “original” tumor. This is the same tumor as in A, but the fluorochrome intensity is here illustrated by histograms, and unstained control cells are included. Harvested tumors were disaggregated and analyzed by flow cytometry after staining with anti- EpCAM, CD24 and SSEA-4 –antibodies. Dark blue histograms indicate the stained samples; light blue contours indicate the unstained control cells. D) Flow cytometry analysis of EpCAM positive cells from tumors in B. Representative histograms are shown.</p>", "links"=>[], "tags"=>["Whole genome expression analysis", "gobo", "survival", "stroma cell support", "tumorigenic populations", "dmfs", "er", "breast cancer biopsies", "breast cancer subgroups", "vivo tumorigenicity assay", "CD 24 expression", "breast cancer recurrence", "cancer cell subpopulations", "ssea"], "article_id"=>1250381, "categories"=>["Biological Sciences"], "users"=>["Nirma Skrbo", "Geir-Olav Hjortland", "Alexandr Kristian", "Ruth Holm", "Silje Nord", "Lina Prasmickaite", "Olav Engebraaten", "Gunhild M. Mælandsmo", "Therese Sørlie", "Kristin Andersen"], "doi"=>"https://dx.doi.org/10.1371/journal.pone.0113278.g003", "stats"=>{"downloads"=>2, "page_views"=>21, "likes"=>0}, "figshare_url"=>"https://figshare.com/articles/_In_vivo_functional_characterizations_of_four_EpCAM_positive_tumor_cell_subpopulations_defined_by_CD24_and_SSEA_4_from_the_luminal_like_PDX_/1250381", "title"=>"<i>In vivo</i> functional characterizations of four EpCAM positive tumor cell subpopulations, defined by CD24 and SSEA-4, from the luminal-like PDX.", "pos_in_sequence"=>0, "defined_type"=>1, "published_date"=>"2014-11-24 03:06:40"}
  • {"files"=>["https://ndownloader.figshare.com/files/1805284"], "description"=>"<p>Total signal intensity (LogR) and the B allele frequency (BAF) from all four subpopulations are shown (A–D). For illustration of similarities and differences in genomic aberrations, overlay images comparing LogR and BAF from each population to the dbl.high population are shown (E–H). Light blue color indicates copy number pattern observed only in dbl.high population, red color indicates pattern observed only in the cell populations to which dbl.high is compared, and black indicates identical LogR and BAF.</p>", "links"=>[], "tags"=>["Whole genome expression analysis", "gobo", "survival", "stroma cell support", "tumorigenic populations", "dmfs", "er", "breast cancer biopsies", "breast cancer subgroups", "vivo tumorigenicity assay", "CD 24 expression", "breast cancer recurrence", "cancer cell subpopulations", "ssea"], "article_id"=>1250388, "categories"=>["Biological Sciences"], "users"=>["Nirma Skrbo", "Geir-Olav Hjortland", "Alexandr Kristian", "Ruth Holm", "Silje Nord", "Lina Prasmickaite", "Olav Engebraaten", "Gunhild M. Mælandsmo", "Therese Sørlie", "Kristin Andersen"], "doi"=>"https://dx.doi.org/10.1371/journal.pone.0113278.g005", "stats"=>{"downloads"=>1, "page_views"=>14, "likes"=>0}, "figshare_url"=>"https://figshare.com/articles/_SNP_array_data_displayed_as_unsegmented_dotplots_/1250388", "title"=>"SNP array data displayed as unsegmented dotplots.", "pos_in_sequence"=>0, "defined_type"=>1, "published_date"=>"2014-11-24 03:06:40"}
  • {"files"=>["https://ndownloader.figshare.com/files/1805278"], "description"=>"<p>A) Normalized gene expression data from all 15 samples were subjected to t-test comparison of two groups (dbl.high subopoulations vs. the tumorigenic subpopulations) with p≤0.004 and FDR = 0.2. The figure shows a cluster heatmap of the 44 significantly differentially expressed genes. Probes in yellow frames are not included in B, either because they are not annotated, the genes could not be found in GOBO, or they showed lower expression in the dbl.high population. The A_32_P188263 probe maps to the C1QB gene, which is already represented in the 26 gene list. B) Kaplan-Meier analysis using overall survival (OS) and distant metastasis free survival (DMFS) as endpoint and 10-year censoring as displayed in GOBO. C) Total RNA was isolated from FAC-sorted subpopulations and RT-qPCR was performed using primers against CD24. The bars illustrate the fold difference.</p>", "links"=>[], "tags"=>["Whole genome expression analysis", "gobo", "survival", "stroma cell support", "tumorigenic populations", "dmfs", "er", "breast cancer biopsies", "breast cancer subgroups", "vivo tumorigenicity assay", "CD 24 expression", "breast cancer recurrence", "cancer cell subpopulations", "ssea"], "article_id"=>1250382, "categories"=>["Biological Sciences"], "users"=>["Nirma Skrbo", "Geir-Olav Hjortland", "Alexandr Kristian", "Ruth Holm", "Silje Nord", "Lina Prasmickaite", "Olav Engebraaten", "Gunhild M. Mælandsmo", "Therese Sørlie", "Kristin Andersen"], "doi"=>"https://dx.doi.org/10.1371/journal.pone.0113278.g004", "stats"=>{"downloads"=>4, "page_views"=>79, "likes"=>0}, "figshare_url"=>"https://figshare.com/articles/_Whole_genome_expression_analyses_of_sorted_tumor_cell_subpopulations_EpCAM_positive_cells_from_the_luminal_xenografts_were_separated_based_on_expression_of_SSEA_4_and_CD24_using_FACS_/1250382", "title"=>"Whole genome expression analyses of sorted tumor cell subpopulations. EpCAM positive cells from the luminal xenografts were separated based on expression of SSEA-4 and CD24 using FACS.", "pos_in_sequence"=>0, "defined_type"=>1, "published_date"=>"2014-11-24 03:06:40"}
  • {"files"=>["https://ndownloader.figshare.com/files/1805275"], "description"=>"<p>Freshly harvested primary or xenograft tumor material was minced and digested and the whole cell suspension was stained with anti-EpCAM antibody combined with anti-CD24 and anti-SSEA-4. A) Flow analysis of EpCAM positive cells from five randomly chosen primary breast cancer tumors. F indicate tumor number, ER  = estrogen-, PR =  progesterone-, and Her2- receptor status are indicated under the corresponding dot plot. IDC indicates that primary tumor was invasive ductal carcinoma. B) Flow analysis of EpCAM positive cells from three PDX models and two breast cancer cell lines. The dot plots illustrate the distribution of CD24 and SSEA-4 expressing cells. Red dots are antibody stained cells; black dots represent unstained control.</p>", "links"=>[], "tags"=>["Whole genome expression analysis", "gobo", "survival", "stroma cell support", "tumorigenic populations", "dmfs", "er", "breast cancer biopsies", "breast cancer subgroups", "vivo tumorigenicity assay", "CD 24 expression", "breast cancer recurrence", "cancer cell subpopulations", "ssea"], "article_id"=>1250379, "categories"=>["Biological Sciences"], "users"=>["Nirma Skrbo", "Geir-Olav Hjortland", "Alexandr Kristian", "Ruth Holm", "Silje Nord", "Lina Prasmickaite", "Olav Engebraaten", "Gunhild M. Mælandsmo", "Therese Sørlie", "Kristin Andersen"], "doi"=>"https://dx.doi.org/10.1371/journal.pone.0113278.g002", "stats"=>{"downloads"=>5, "page_views"=>345, "likes"=>0}, "figshare_url"=>"https://figshare.com/articles/_Flow_cytometry_analysis_of_EpCAM_positive_cells_from_human_primary_breast_tumors_xenografts_and_breast_cancer_cell_lines_/1250379", "title"=>"Flow cytometry analysis of EpCAM positive cells from human primary breast tumors, xenografts, and breast cancer cell lines.", "pos_in_sequence"=>0, "defined_type"=>1, "published_date"=>"2014-11-24 03:06:40"}
  • {"files"=>["https://ndownloader.figshare.com/files/1805274"], "description"=>"<p>A) Basal-like xenograft cells. B) Luminal-like xenograft cells. A and B displays pseudo-color dot plots (left panels) and histograms (right panels). Freshly harvested xenografts were minced and the whole cell suspensions were washed and stained with monoclonal antibody towards EpCAM, TRA-1-85 (filled blue in histograms), H2-kd (red line in lower histogram) and Hoecst-33342 (intensity measure for DNA content of cells, grey contours in both histograms. Left peak indicate mouse cells, right peak indicate human cells). The population positive for both EpCAM and TRA-1-85, i.e the human tumor cells, are indicated with a circle in the dot plots. C) Flow cytometry analysis of double stained samples (marker of interest and EpCAM/Tra-1-85) of the Luminal-like PDX model. Flow cytometry histograms show the distribution of the markers indicated in the figure. Filled blue histogram represents EpCAM positive tumor cell population, and the EpCAM negative population (mouse stroma cells) is indicated by the red line. Grey contour represent unstained control.</p>", "links"=>[], "tags"=>["Whole genome expression analysis", "gobo", "survival", "stroma cell support", "tumorigenic populations", "dmfs", "er", "breast cancer biopsies", "breast cancer subgroups", "vivo tumorigenicity assay", "CD 24 expression", "breast cancer recurrence", "cancer cell subpopulations", "ssea"], "article_id"=>1250378, "categories"=>["Biological Sciences"], "users"=>["Nirma Skrbo", "Geir-Olav Hjortland", "Alexandr Kristian", "Ruth Holm", "Silje Nord", "Lina Prasmickaite", "Olav Engebraaten", "Gunhild M. Mælandsmo", "Therese Sørlie", "Kristin Andersen"], "doi"=>"https://dx.doi.org/10.1371/journal.pone.0113278.g001", "stats"=>{"downloads"=>0, "page_views"=>26, "likes"=>0}, "figshare_url"=>"https://figshare.com/articles/_Flow_cytometry_analysis_of_total_cell_fractions_of_dissociated_cells_from_PDX_models_/1250378", "title"=>"Flow cytometry analysis of total cell fractions of dissociated cells from PDX models.", "pos_in_sequence"=>0, "defined_type"=>1, "published_date"=>"2014-11-24 03:06:40"}
  • {"files"=>["https://ndownloader.figshare.com/files/1805287"], "description"=>"<p>++++  =  all EpCAM positive cells positive, +++ =  40-90% were positive, ++ =  5–39% were positive, +  =  less than 5% positive cells, 0  =  no cells expressed marker. *  =  was highly positive when xenografts tumor was digested with trypsin.</p><p>Expression of Cell Surface Markers and Aldefluoractivity in EpCAM Positive Cells from Two Breast Cancer Xenografts Models, measured by flow cytometry.</p>", "links"=>[], "tags"=>["Whole genome expression analysis", "gobo", "survival", "stroma cell support", "tumorigenic populations", "dmfs", "er", "breast cancer biopsies", "breast cancer subgroups", "vivo tumorigenicity assay", "CD 24 expression", "breast cancer recurrence", "cancer cell subpopulations", "ssea"], "article_id"=>1250391, "categories"=>["Biological Sciences"], "users"=>["Nirma Skrbo", "Geir-Olav Hjortland", "Alexandr Kristian", "Ruth Holm", "Silje Nord", "Lina Prasmickaite", "Olav Engebraaten", "Gunhild M. Mælandsmo", "Therese Sørlie", "Kristin Andersen"], "doi"=>"https://dx.doi.org/10.1371/journal.pone.0113278.t002", "stats"=>{"downloads"=>8, "page_views"=>17, "likes"=>0}, "figshare_url"=>"https://figshare.com/articles/_Expression_of_Cell_Surface_Markers_and_Aldefluoractivity_in_EpCAM_Positive_Cells_from_Two_Breast_Cancer_Xenografts_Models_measured_by_flow_cytometry_/1250391", "title"=>"Expression of Cell Surface Markers and Aldefluoractivity in EpCAM Positive Cells from Two Breast Cancer Xenografts Models, measured by flow cytometry.", "pos_in_sequence"=>0, "defined_type"=>3, "published_date"=>"2014-11-24 03:06:40"}
  • {"files"=>["https://ndownloader.figshare.com/files/1805288"], "description"=>"<p>The 26 top genes were subjected to gene set analysis on breast cancer patient outcome in the GOBO database <a href=\"http://www.plosone.org/article/info:doi/10.1371/journal.pone.0113278#pone.0113278-Ringner1\" target=\"_blank\">[19]</a>.</p><p>Probes downregulated in dbl.high.</p><p><i>Probes upregulated in dbl.high. The top 26 gene IDs were put in gene set analysis on tumors in the GOBO breast cancer gene expression database.</i></p><p>*Genes annotated by BLAST of probe sequence.</p><p>List of the 44 probes and corresponding genes significantly differentially expressed in the non-tumorigenic population compared to the tumorigenic populations.</p>", "links"=>[], "tags"=>["Whole genome expression analysis", "gobo", "survival", "stroma cell support", "tumorigenic populations", "dmfs", "er", "breast cancer biopsies", "breast cancer subgroups", "vivo tumorigenicity assay", "CD 24 expression", "breast cancer recurrence", "cancer cell subpopulations", "ssea"], "article_id"=>1250392, "categories"=>["Biological Sciences"], "users"=>["Nirma Skrbo", "Geir-Olav Hjortland", "Alexandr Kristian", "Ruth Holm", "Silje Nord", "Lina Prasmickaite", "Olav Engebraaten", "Gunhild M. Mælandsmo", "Therese Sørlie", "Kristin Andersen"], "doi"=>"https://dx.doi.org/10.1371/journal.pone.0113278.t003", "stats"=>{"downloads"=>5, "page_views"=>20, "likes"=>0}, "figshare_url"=>"https://figshare.com/articles/_List_of_the_44_probes_and_corresponding_genes_significantly_differentially_expressed_in_the_non_tumorigenic_population_compared_to_the_tumorigenic_populations_/1250392", "title"=>"List of the 44 probes and corresponding genes significantly differentially expressed in the non-tumorigenic population compared to the tumorigenic populations.", "pos_in_sequence"=>0, "defined_type"=>3, "published_date"=>"2014-11-24 03:06:40"}
  • {"files"=>["https://ndownloader.figshare.com/files/1805348", "https://ndownloader.figshare.com/files/1805349", "https://ndownloader.figshare.com/files/1805350"], "description"=>"<div><p>Intratumor heterogeneity caused by genetic, phenotypic or functional differences between cancer cell subpopulations is a considerable clinical challenge. Understanding subpopulation dynamics is therefore central for both optimization of existing therapy and for development of new treatment. The aim of this study was to isolate subpopulations from a primary tumor and by comparing molecular characteristics of these subpopulations, find explanations to their differing tumorigenicity. Cell subpopulations from two patient derived <i>in vivo</i> models of primary breast cancer, ER+ and ER-, were identified. EpCAM+ cells from the ER+ model gave rise to tumors independently of stroma cell support. The tumorigenic fraction was further divided based on SSEA-4 and CD24 expression. Both markers were expressed in ER+ breast cancer biopsies. FAC-sorted cells based on EpCAM, SSEA-4 and CD24 expression were subsequently tested for differences in functionality by <i>in vivo</i> tumorigenicity assay. Three out of four subpopulations of cells were tumorigenic and showed variable ability to recapitulate the marker expression of the original tumor. Whole genome expression analysis of the sorted populations disclosed high similarity in the transcriptional profiles between the tumorigenic populations. Comparing the non-tumorigenic vs the tumorigenic populations, 44 transcripts were, however, significantly differentially expressed. A subset of these, 26 identified and named genes, highly expressed in the non-tumorigenic population, predicted longer overall survival (N = 737, p<0.0001) and distant metastasis free survival (DMFS) (N = 1379, p<0.0001) when performing Kaplan-Meier survival analysis using the GOBO online database. The 26 gene set correlated with longer DMFS in multiple breast cancer subgroups. Copy number profiling revealed no aberrations that could explain the observed differences in tumorigenicity. This study emphasizes the functional variability among cell populations that are otherwise genomically similar, and that the risk of breast cancer recurrence can only be eliminated if the tumorigenic abilities in multiple cancer cell subpopulations are inhibited.</p></div>", "links"=>[], "tags"=>["Whole genome expression analysis", "gobo", "survival", "stroma cell support", "tumorigenic populations", "dmfs", "er", "breast cancer biopsies", "breast cancer subgroups", "vivo tumorigenicity assay", "CD 24 expression", "breast cancer recurrence", "cancer cell subpopulations", "ssea"], "article_id"=>1250437, "categories"=>["Biological Sciences"], "users"=>["Nirma Skrbo", "Geir-Olav Hjortland", "Alexandr Kristian", "Ruth Holm", "Silje Nord", "Lina Prasmickaite", "Olav Engebraaten", "Gunhild M. Mælandsmo", "Therese Sørlie", "Kristin Andersen"], "doi"=>["https://dx.doi.org/10.1371/journal.pone.0113278.s001", "https://dx.doi.org/10.1371/journal.pone.0113278.s002", "https://dx.doi.org/10.1371/journal.pone.0113278.s003"], "stats"=>{"downloads"=>0, "page_views"=>13, "likes"=>0}, "figshare_url"=>"https://figshare.com/articles/Differential_In_Vivo_Tumorigenicity_of_Distinct_Subpopulations_from_a_Luminal_Like_Breast_Cancer_Xenograft/1250437", "title"=>"Differential <i>In Vivo</i> Tumorigenicity of Distinct Subpopulations from a Luminal-Like Breast Cancer Xenograft", "pos_in_sequence"=>0, "defined_type"=>4, "published_date"=>"2014-11-24 03:06:40"}
  • {"files"=>["https://ndownloader.figshare.com/files/1805286"], "description"=>"<p>Injection in MFP of NSG mice.</p><p>Test of Tumorigenicity of Cell Fractions from two Breast Cancer Xenograft Models.</p>", "links"=>[], "tags"=>["Whole genome expression analysis", "gobo", "survival", "stroma cell support", "tumorigenic populations", "dmfs", "er", "breast cancer biopsies", "breast cancer subgroups", "vivo tumorigenicity assay", "CD 24 expression", "breast cancer recurrence", "cancer cell subpopulations", "ssea"], "article_id"=>1250390, "categories"=>["Biological Sciences"], "users"=>["Nirma Skrbo", "Geir-Olav Hjortland", "Alexandr Kristian", "Ruth Holm", "Silje Nord", "Lina Prasmickaite", "Olav Engebraaten", "Gunhild M. Mælandsmo", "Therese Sørlie", "Kristin Andersen"], "doi"=>"https://dx.doi.org/10.1371/journal.pone.0113278.t001", "stats"=>{"downloads"=>5, "page_views"=>21, "likes"=>0}, "figshare_url"=>"https://figshare.com/articles/_Test_of_Tumorigenicity_of_Cell_Fractions_from_two_Breast_Cancer_Xenograft_Models_/1250390", "title"=>"Test of Tumorigenicity of Cell Fractions from two Breast Cancer Xenograft Models.", "pos_in_sequence"=>0, "defined_type"=>3, "published_date"=>"2014-11-24 03:06:40"}

PMC Usage Stats | Further Information

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  • {"unique-ip"=>"5", "full-text"=>"4", "pdf"=>"1", "scanned-summary"=>"0", "scanned-page-browse"=>"0", "figure"=>"0", "supp-data"=>"0", "cited-by"=>"0", "year"=>"2018", "month"=>"8"}
  • {"unique-ip"=>"7", "full-text"=>"7", "pdf"=>"1", "scanned-summary"=>"0", "scanned-page-browse"=>"0", "figure"=>"0", "supp-data"=>"0", "cited-by"=>"0", "year"=>"2018", "month"=>"10"}
  • {"unique-ip"=>"6", "full-text"=>"10", "pdf"=>"0", "scanned-summary"=>"0", "scanned-page-browse"=>"0", "figure"=>"0", "supp-data"=>"0", "cited-by"=>"0", "year"=>"2018", "month"=>"11"}
  • {"unique-ip"=>"10", "full-text"=>"10", "pdf"=>"1", "scanned-summary"=>"0", "scanned-page-browse"=>"0", "figure"=>"0", "supp-data"=>"0", "cited-by"=>"0", "year"=>"2018", "month"=>"9"}
  • {"unique-ip"=>"8", "full-text"=>"9", "pdf"=>"2", "scanned-summary"=>"0", "scanned-page-browse"=>"0", "figure"=>"7", "supp-data"=>"1", "cited-by"=>"0", "year"=>"2018", "month"=>"12"}
  • {"unique-ip"=>"5", "full-text"=>"5", "pdf"=>"1", "scanned-summary"=>"0", "scanned-page-browse"=>"0", "figure"=>"0", "supp-data"=>"0", "cited-by"=>"0", "year"=>"2019", "month"=>"2"}
  • {"unique-ip"=>"5", "full-text"=>"5", "pdf"=>"0", "scanned-summary"=>"0", "scanned-page-browse"=>"0", "figure"=>"0", "supp-data"=>"2", "cited-by"=>"0", "year"=>"2019", "month"=>"3"}
  • {"unique-ip"=>"8", "full-text"=>"8", "pdf"=>"3", "scanned-summary"=>"0", "scanned-page-browse"=>"0", "figure"=>"5", "supp-data"=>"0", "cited-by"=>"0", "year"=>"2019", "month"=>"4"}
  • {"unique-ip"=>"8", "full-text"=>"6", "pdf"=>"3", "scanned-summary"=>"0", "scanned-page-browse"=>"0", "figure"=>"0", "supp-data"=>"0", "cited-by"=>"0", "year"=>"2019", "month"=>"5"}

Relative Metric

{"start_date"=>"2014-01-01T00:00:00Z", "end_date"=>"2014-12-31T00:00:00Z", "subject_areas"=>[{"subject_area"=>"/Biology and life sciences", "average_usage"=>[291]}, {"subject_area"=>"/Biology and life sciences/Computational biology", "average_usage"=>[341, 529]}]}
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