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A multi-modal data resource for investigating topographic heterogeneity in patient-derived xenograft tumors.


ABSTRACT: Patient-derived xenografts (PDXs) are an essential pre-clinical resource for investigating tumor biology. However, cellular heterogeneity within and across PDX tumors can strongly impact the interpretation of PDX studies. Here, we generated a multi-modal, large-scale dataset to investigate PDX heterogeneity in metastatic colorectal cancer (CRC) across tumor models, spatial scales and genomic, transcriptomic, proteomic and imaging assay modalities. To showcase this dataset, we present analysis to assess sources of PDX variation, including anatomical orientation within the implanted tumor, mouse contribution, and differences between replicate PDX tumors. A unique aspect of our dataset is deep characterization of intra-tumor heterogeneity via immunofluorescence imaging, which enables investigation of variation across multiple spatial scales, from subcellular to whole tumor levels. Our study provides a benchmark data resource to investigate PDX models of metastatic CRC and serves as a template for future, quantitative investigations of spatial heterogeneity within and across PDX tumor models.

SUBMITTER: Rajaram S 

PROVIDER: S-EPMC6823477 | biostudies-literature | 2019 Oct

REPOSITORIES: biostudies-literature

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A multi-modal data resource for investigating topographic heterogeneity in patient-derived xenograft tumors.

Rajaram Satwik S   Roth Maike A MA   Malato Julia J   VandenBerg Scott S   Hann Byron B   Atreya Chloe E CE   Altschuler Steven J SJ   Wu Lani F LF  

Scientific data 20191031 1


Patient-derived xenografts (PDXs) are an essential pre-clinical resource for investigating tumor biology. However, cellular heterogeneity within and across PDX tumors can strongly impact the interpretation of PDX studies. Here, we generated a multi-modal, large-scale dataset to investigate PDX heterogeneity in metastatic colorectal cancer (CRC) across tumor models, spatial scales and genomic, transcriptomic, proteomic and imaging assay modalities. To showcase this dataset, we present analysis to  ...[more]

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