Figure 2 from <i>In Vivo</i> Modeling of Patient Genetic Heterogeneity Identifies New Ways to Target Cholangiocarcinoma
<p><i>In vivo</i> CRISPR-Cas9 screening identifies transforming mutations that interact with mutant Ras. <b>A,</b> Schematic of this study in which high-content sequencing data are collated from patients with ICC and the mutational profile of these tumors rationalized t...
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2025
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| _version_ | 1849927640196055040 |
|---|---|
| author | Nicholas T. Younger (14956251) |
| author2 | Mollie L. Wilson (14956254) Anabel Martinez Lyons (14956257) Edward J. Jarman (9773166) Alison M. Meynert (14956260) Graeme R. Grimes (14160170) Konstantinos Gournopanos (14956263) Scott H. Waddell (14956266) Peter A. Tennant (14956269) David H. Wilson (14956272) Rachel V. Guest (14956275) Stephen J. Wigmore (14915943) Juan Carlos Acosta (14956278) Timothy J. Kendall (14956281) Martin S. Taylor (14956284) Duncan Sproul (13971883) Pleasantine Mill (256953) Luke Boulter (14956287) |
| author2_role | author author author author author author author author author author author author author author author author author |
| author_facet | Nicholas T. Younger (14956251) Mollie L. Wilson (14956254) Anabel Martinez Lyons (14956257) Edward J. Jarman (9773166) Alison M. Meynert (14956260) Graeme R. Grimes (14160170) Konstantinos Gournopanos (14956263) Scott H. Waddell (14956266) Peter A. Tennant (14956269) David H. Wilson (14956272) Rachel V. Guest (14956275) Stephen J. Wigmore (14915943) Juan Carlos Acosta (14956278) Timothy J. Kendall (14956281) Martin S. Taylor (14956284) Duncan Sproul (13971883) Pleasantine Mill (256953) Luke Boulter (14956287) |
| author_role | author |
| dc.creator.none.fl_str_mv | Nicholas T. Younger (14956251) Mollie L. Wilson (14956254) Anabel Martinez Lyons (14956257) Edward J. Jarman (9773166) Alison M. Meynert (14956260) Graeme R. Grimes (14160170) Konstantinos Gournopanos (14956263) Scott H. Waddell (14956266) Peter A. Tennant (14956269) David H. Wilson (14956272) Rachel V. Guest (14956275) Stephen J. Wigmore (14915943) Juan Carlos Acosta (14956278) Timothy J. Kendall (14956281) Martin S. Taylor (14956284) Duncan Sproul (13971883) Pleasantine Mill (256953) Luke Boulter (14956287) |
| dc.date.none.fl_str_mv | 2025-11-24T22:22:14Z |
| dc.identifier.none.fl_str_mv | 10.1158/0008-5472.30698871 |
| dc.relation.none.fl_str_mv | https://figshare.com/articles/figure/Figure_2_from_i_In_Vivo_i_Modeling_of_Patient_Genetic_Heterogeneity_Identifies_New_Ways_to_Target_Cholangiocarcinoma/30698871 |
| dc.rights.none.fl_str_mv | CC BY info:eu-repo/semantics/openAccess |
| dc.subject.none.fl_str_mv | Cancer Cancer Biology Molecular and Cellular Biology Therapeutic Research and Development Methods and Technology Cell Signaling Computational Methods Sequence analysis Drug Targets Gastrointestinal Cancers Liver cancer Gene Technologies Comparative genomics Oncogenes & Tumor Suppressors Kras Preclinical Models Animal models of cancer |
| dc.title.none.fl_str_mv | Figure 2 from <i>In Vivo</i> Modeling of Patient Genetic Heterogeneity Identifies New Ways to Target Cholangiocarcinoma |
| dc.type.none.fl_str_mv | Image Figure info:eu-repo/semantics/publishedVersion image |
| description | <p><i>In vivo</i> CRISPR-Cas9 screening identifies transforming mutations that interact with mutant Ras. <b>A,</b> Schematic of this study in which high-content sequencing data are collated from patients with ICC and the mutational profile of these tumors rationalized to identify novel, high confidence drivers of ICC. These putative drivers are used as input for an <i>in vivo</i> SpCas9/CRISPR screen to identify novel functional processes that drive ICC growth. <b>B,</b> Macroscopic images of the livers following injection with either NRAS<sup>G12V</sup> or KRAS<sup>G12D</sup> alone (left) or in combination with ICC<sup>Lib</sup> (right; dotted line, tumor). Scale bar, 1 cm. <b>C,</b> Quantification of macroscopic tumors per mouse at 10 weeks in mice bearing Nras<sup>G12V</sup> -expressing tumors and 8 weeks in those with Kras<sup>G12D</sup>-driven cancer. Each circle represents a different animal. <b>D,</b> The number of samples containing Indels in a particular gene following whole exome sequencing. Top graph lists those mutations found in both NRAS<sup>G12V</sup> and KRAS<sup>G12D</sup> tumors, and bottom graphs denote those mutations that are found only in KRAS<sup>G12D</sup> - or NRAS<sup>G12V</sup> -expressing tumors. Sample frequency (%) denotes the proportion of tumors containing any given mutation, whereas (count) is absolute number. (<i>N</i> represents anatomically discreet tumors recovered from at least four individual animals, KRAS<sup>G12D</sup><i>N</i> = 14 and NRAS<sup>G12V</sup><i>N</i> = 10.) <b>E,</b> PCA showing how samples group based on their transcriptomic signature and gRNA-induced mutations associated with each tumor type.</p> |
| eu_rights_str_mv | openAccess |
| id | Manara_8b023457956b4da37779c92ef9ce8cb9 |
| identifier_str_mv | 10.1158/0008-5472.30698871 |
| network_acronym_str | Manara |
| network_name_str | ManaraRepo |
| oai_identifier_str | oai:figshare.com:article/30698871 |
| publishDate | 2025 |
| repository.mail.fl_str_mv | |
| repository.name.fl_str_mv | |
| repository_id_str | |
| rights_invalid_str_mv | CC BY |
| spelling | Figure 2 from <i>In Vivo</i> Modeling of Patient Genetic Heterogeneity Identifies New Ways to Target CholangiocarcinomaNicholas T. Younger (14956251)Mollie L. Wilson (14956254)Anabel Martinez Lyons (14956257)Edward J. Jarman (9773166)Alison M. Meynert (14956260)Graeme R. Grimes (14160170)Konstantinos Gournopanos (14956263)Scott H. Waddell (14956266)Peter A. Tennant (14956269)David H. Wilson (14956272)Rachel V. Guest (14956275)Stephen J. Wigmore (14915943)Juan Carlos Acosta (14956278)Timothy J. Kendall (14956281)Martin S. Taylor (14956284)Duncan Sproul (13971883)Pleasantine Mill (256953)Luke Boulter (14956287)CancerCancer BiologyMolecular and Cellular BiologyTherapeutic Research and DevelopmentMethods and TechnologyCell SignalingComputational MethodsSequence analysisDrug TargetsGastrointestinal CancersLiver cancerGene TechnologiesComparative genomicsOncogenes & Tumor SuppressorsKrasPreclinical ModelsAnimal models of cancer<p><i>In vivo</i> CRISPR-Cas9 screening identifies transforming mutations that interact with mutant Ras. <b>A,</b> Schematic of this study in which high-content sequencing data are collated from patients with ICC and the mutational profile of these tumors rationalized to identify novel, high confidence drivers of ICC. These putative drivers are used as input for an <i>in vivo</i> SpCas9/CRISPR screen to identify novel functional processes that drive ICC growth. <b>B,</b> Macroscopic images of the livers following injection with either NRAS<sup>G12V</sup> or KRAS<sup>G12D</sup> alone (left) or in combination with ICC<sup>Lib</sup> (right; dotted line, tumor). Scale bar, 1 cm. <b>C,</b> Quantification of macroscopic tumors per mouse at 10 weeks in mice bearing Nras<sup>G12V</sup> -expressing tumors and 8 weeks in those with Kras<sup>G12D</sup>-driven cancer. Each circle represents a different animal. <b>D,</b> The number of samples containing Indels in a particular gene following whole exome sequencing. Top graph lists those mutations found in both NRAS<sup>G12V</sup> and KRAS<sup>G12D</sup> tumors, and bottom graphs denote those mutations that are found only in KRAS<sup>G12D</sup> - or NRAS<sup>G12V</sup> -expressing tumors. Sample frequency (%) denotes the proportion of tumors containing any given mutation, whereas (count) is absolute number. (<i>N</i> represents anatomically discreet tumors recovered from at least four individual animals, KRAS<sup>G12D</sup><i>N</i> = 14 and NRAS<sup>G12V</sup><i>N</i> = 10.) <b>E,</b> PCA showing how samples group based on their transcriptomic signature and gRNA-induced mutations associated with each tumor type.</p>2025-11-24T22:22:14ZImageFigureinfo:eu-repo/semantics/publishedVersionimage10.1158/0008-5472.30698871https://figshare.com/articles/figure/Figure_2_from_i_In_Vivo_i_Modeling_of_Patient_Genetic_Heterogeneity_Identifies_New_Ways_to_Target_Cholangiocarcinoma/30698871CC BYinfo:eu-repo/semantics/openAccessoai:figshare.com:article/306988712025-11-24T22:22:14Z |
| spellingShingle | Figure 2 from <i>In Vivo</i> Modeling of Patient Genetic Heterogeneity Identifies New Ways to Target Cholangiocarcinoma Nicholas T. Younger (14956251) Cancer Cancer Biology Molecular and Cellular Biology Therapeutic Research and Development Methods and Technology Cell Signaling Computational Methods Sequence analysis Drug Targets Gastrointestinal Cancers Liver cancer Gene Technologies Comparative genomics Oncogenes & Tumor Suppressors Kras Preclinical Models Animal models of cancer |
| status_str | publishedVersion |
| title | Figure 2 from <i>In Vivo</i> Modeling of Patient Genetic Heterogeneity Identifies New Ways to Target Cholangiocarcinoma |
| title_full | Figure 2 from <i>In Vivo</i> Modeling of Patient Genetic Heterogeneity Identifies New Ways to Target Cholangiocarcinoma |
| title_fullStr | Figure 2 from <i>In Vivo</i> Modeling of Patient Genetic Heterogeneity Identifies New Ways to Target Cholangiocarcinoma |
| title_full_unstemmed | Figure 2 from <i>In Vivo</i> Modeling of Patient Genetic Heterogeneity Identifies New Ways to Target Cholangiocarcinoma |
| title_short | Figure 2 from <i>In Vivo</i> Modeling of Patient Genetic Heterogeneity Identifies New Ways to Target Cholangiocarcinoma |
| title_sort | Figure 2 from <i>In Vivo</i> Modeling of Patient Genetic Heterogeneity Identifies New Ways to Target Cholangiocarcinoma |
| topic | Cancer Cancer Biology Molecular and Cellular Biology Therapeutic Research and Development Methods and Technology Cell Signaling Computational Methods Sequence analysis Drug Targets Gastrointestinal Cancers Liver cancer Gene Technologies Comparative genomics Oncogenes & Tumor Suppressors Kras Preclinical Models Animal models of cancer |